Effects of Mobile Instant Messaging on Collaborative Learning Processes and Outcomes: The Case of South Korea

ERIC Educational Resources Information Center

Kim, Hyewon; Lee, MiYoung; Kim, Minjeong

2014-01-01

The purpose of this paper was to investigate the effects of mobile instant messaging on collaborative learning processes and outcomes. The collaborative processes were measured in terms of different types of interactions. We measured the outcomes of the collaborations through both the students' taskwork and their teamwork. The collaborative…

Comparing Learning Gains: Audio Versus Text-based Instructor Communication in a Blended Online Learning Environment

NASA Astrophysics Data System (ADS)

Shimizu, Dominique

Though blended course audio feedback has been associated with several measures of course satisfaction at the postsecondary and graduate levels compared to text feedback, it may take longer to prepare and positive results are largely unverified in K-12 literature. The purpose of this quantitative study was to investigate the time investment and learning impact of audio communications with 228 secondary students in a blended online learning biology unit at a central Florida public high school. A short, individualized audio message regarding the student's progress was given to each student in the audio group; similar text-based messages were given to each student in the text-based group on the same schedule; a control got no feedback. A pretest and posttest were employed to measure learning gains in the three groups. To compare the learning gains in two types of feedback with each other and to no feedback, a controlled, randomized, experimental design was implemented. In addition, the creation and posting of audio and text feedback communications were timed in order to assess whether audio feedback took longer to produce than text only feedback. While audio feedback communications did take longer to create and post, there was no difference between learning gains as measured by posttest scores when student received audio, text-based, or no feedback. Future studies using a similar randomized, controlled experimental design are recommended to verify these results and test whether the trend holds in a broader range of subjects, over different time frames, and using a variety of assessment types to measure student learning.

A Study of a "Model of School Learning." Monograph Number 4.

ERIC Educational Resources Information Center

Carroll, John B.; Spearritt, Donald

A booklet of a programmed-instruction type was developed to obtain the measures needed to test Carroll's model of school learning, including ability, aptitude, quality of instruction, opportunity for learning, perserverance, and time criterion. Simple rules in an artificial foreign language were taught by means of the booklet to sixth-grade…

Machine learning based analytics of micro-MRI trabecular bone microarchitecture and texture in type 1 Gaucher disease.

PubMed

Sharma, Gulshan B; Robertson, Douglas D; Laney, Dawn A; Gambello, Michael J; Terk, Michael

2016-06-14

Type 1 Gaucher disease (GD) is an autosomal recessive lysosomal storage disease, affecting bone metabolism, structure and strength. Current bone assessment methods are not ideal. Semi-quantitative MRI scoring is unreliable, not standardized, and only evaluates bone marrow. DXA BMD is also used but is a limited predictor of bone fragility/fracture risk. Our purpose was to measure trabecular bone microarchitecture, as a biomarker of bone disease severity, in type 1 GD individuals with different GD genotypes and to apply machine learning based analytics to discriminate between GD patients and healthy individuals. Micro-MR imaging of the distal radius was performed on 20 type 1 GD patients and 10 healthy controls (HC). Fifteen stereological and textural measures (STM) were calculated from the MR images. General linear models demonstrated significant differences between GD and HC, and GD genotypes. Stereological measures, main contributors to the first two principal components (PCs), explained ~50% of data variation and were significantly different between males and females. Subsequent PCs textural measures were significantly different between GD patients and HC individuals. Textural measures also significantly differed between GD genotypes, and distinguished between GD patients with normal and pathologic DXA scores. PCA and SVM predictive analyses discriminated between GD and HC with maximum accuracy of 73% and area under ROC curve of 0.79. Trabecular STM differences can be quantified between GD patients and HC, and GD sub-types using micro-MRI and machine learning based analytics. Work is underway to expand this approach to evaluate GD disease burden and treatment efficacy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Classification

NASA Astrophysics Data System (ADS)

Oza, Nikunj

2012-03-01

A supervised learning task involves constructing a mapping from input data (normally described by several features) to the appropriate outputs. A set of training examples— examples with known output values—is used by a learning algorithm to generate a model. This model is intended to approximate the mapping between the inputs and outputs. This model can be used to generate predicted outputs for inputs that have not been seen before. Within supervised learning, one type of task is a classification learning task, in which each output is one or more classes to which the input belongs. For example, we may have data consisting of observations of sunspots. In a classification learning task, our goal may be to learn to classify sunspots into one of several types. Each example may correspond to one candidate sunspot with various measurements or just an image. A learning algorithm would use the supplied examples to generate a model that approximates the mapping between each supplied set of measurements and the type of sunspot. This model can then be used to classify previously unseen sunspots based on the candidate’s measurements. The generalization performance of a learned model (how closely the target outputs and the model’s predicted outputs agree for patterns that have not been presented to the learning algorithm) would provide an indication of how well the model has learned the desired mapping. More formally, a classification learning algorithm L takes a training set T as its input. The training set consists of |T| examples or instances. It is assumed that there is a probability distribution D from which all training examples are drawn independently—that is, all the training examples are independently and identically distributed (i.i.d.). The ith training example is of the form (x_i, y_i), where x_i is a vector of values of several features and y_i represents the class to be predicted.* In the sunspot classification example given above, each training example would represent one sunspot’s classification (y_i) and the corresponding set of measurements (x_i). The output of a supervised learning algorithm is a model h that approximates the unknown mapping from the inputs to the outputs. In our example, h would map from the sunspot measurements to the type of sunspot. We may have a test set S—a set of examples not used in training that we use to test how well the model h predicts the outputs on new examples. Just as with the examples in T, the examples in S are assumed to be independent and identically distributed (i.i.d.) draws from the distribution D. We measure the error of h on the test set as the proportion of test cases that h misclassifies: 1/|S| Sigma(x,y union S)[I(h(x)!= y)] where I(v) is the indicator function—it returns 1 if v is true and 0 otherwise. In our sunspot classification example, we would identify additional examples of sunspots that were not used in generating the model, and use these to determine how accurate the model is—the fraction of the test samples that the model classifies correctly. An example of a classification model is the decision tree shown in Figure 23.1. We will discuss the decision tree learning algorithm in more detail later—for now, we assume that, given a training set with examples of sunspots, this decision tree is derived. This can be used to classify previously unseen examples of sunpots. For example, if a new sunspot’s inputs indicate that its "Group Length" is in the range 10-15, then the decision tree would classify the sunspot as being of type “E,” whereas if the "Group Length" is "NULL," the "Magnetic Type" is "bipolar," and the "Penumbra" is "rudimentary," then it would be classified as type "C." In this chapter, we will add to the above description of classification problems. We will discuss decision trees and several other classification models. In particular, we will discuss the learning algorithms that generate these classification models, how to use them to classify new examples, and the strengths and weaknesses of these models. We will end with pointers to further reading on classification methods applied to astronomy data.

Does the Room Matter? Active Learning in Traditional and Enhanced Lecture Spaces

PubMed Central

Stoltzfus, Jon R.; Libarkin, Julie

2016-01-01

SCALE-UP–type classrooms, originating with the Student-Centered Active Learning Environment with Upside-down Pedagogies project, are designed to facilitate active learning by maximizing opportunities for interactions between students and embedding technology in the classroom. Positive impacts when active learning replaces lecture are well documented, both in traditional lecture halls and SCALE-UP–type classrooms. However, few studies have carefully analyzed student outcomes when comparable active learning–based instruction takes place in a traditional lecture hall and a SCALE-UP–type classroom. Using a quasi-experimental design, we compared student perceptions and performance between sections of a nonmajors biology course, one taught in a traditional lecture hall and one taught in a SCALE-UP–type classroom. Instruction in both sections followed a flipped model that relied heavily on cooperative learning and was as identical as possible given the infrastructure differences between classrooms. Results showed that students in both sections thought that SCALE-UP infrastructure would enhance performance. However, measures of actual student performance showed no difference between the two sections. We conclude that, while SCALE-UP–type classrooms may facilitate implementation of active learning, it is the active learning and not the SCALE-UP infrastructure that enhances student performance. As a consequence, we suggest that institutions can modify existing classrooms to enhance student engagement without incorporating expensive technology. PMID:27909018

Working Memory Deficits in ADHD: The Contribution of Age, Learning/Language Difficulties, and Task Parameters

ERIC Educational Resources Information Center

Sowerby, Paula; Seal, Simon; Tripp, Gail

2011-01-01

Objective: To further define the nature of working memory (WM) impairments in children with combined-type ADHD. Method: A total of 40 Children with ADHD and an age and gender-matched control group (n = 40) completed two measures of visuo-spatial WM and two measures of verbal WM. The effects of age and learning/language difficulties on performance…

Predictive modeling of structured electronic health records for adverse drug event detection.

PubMed

Zhao, Jing; Henriksson, Aron; Asker, Lars; Boström, Henrik

2015-01-01

The digitization of healthcare data, resulting from the increasingly widespread adoption of electronic health records, has greatly facilitated its analysis by computational methods and thereby enabled large-scale secondary use thereof. This can be exploited to support public health activities such as pharmacovigilance, wherein the safety of drugs is monitored to inform regulatory decisions about sustained use. To that end, electronic health records have emerged as a potentially valuable data source, providing access to longitudinal observations of patient treatment and drug use. A nascent line of research concerns predictive modeling of healthcare data for the automatic detection of adverse drug events, which presents its own set of challenges: it is not yet clear how to represent the heterogeneous data types in a manner conducive to learning high-performing machine learning models. Datasets from an electronic health record database are used for learning predictive models with the purpose of detecting adverse drug events. The use and representation of two data types, as well as their combination, are studied: clinical codes, describing prescribed drugs and assigned diagnoses, and measurements. Feature selection is conducted on the various types of data to reduce dimensionality and sparsity, while allowing for an in-depth feature analysis of the usefulness of each data type and representation. Within each data type, combining multiple representations yields better predictive performance compared to using any single representation. The use of clinical codes for adverse drug event detection significantly outperforms the use of measurements; however, there is no significant difference over datasets between using only clinical codes and their combination with measurements. For certain adverse drug events, the combination does, however, outperform using only clinical codes. Feature selection leads to increased predictive performance for both data types, in isolation and combined. We have demonstrated how machine learning can be applied to electronic health records for the purpose of detecting adverse drug events and proposed solutions to some of the challenges this presents, including how to represent the various data types. Overall, clinical codes are more useful than measurements and, in specific cases, it is beneficial to combine the two.

Predictive modeling of structured electronic health records for adverse drug event detection

PubMed Central

2015-01-01

Background The digitization of healthcare data, resulting from the increasingly widespread adoption of electronic health records, has greatly facilitated its analysis by computational methods and thereby enabled large-scale secondary use thereof. This can be exploited to support public health activities such as pharmacovigilance, wherein the safety of drugs is monitored to inform regulatory decisions about sustained use. To that end, electronic health records have emerged as a potentially valuable data source, providing access to longitudinal observations of patient treatment and drug use. A nascent line of research concerns predictive modeling of healthcare data for the automatic detection of adverse drug events, which presents its own set of challenges: it is not yet clear how to represent the heterogeneous data types in a manner conducive to learning high-performing machine learning models. Methods Datasets from an electronic health record database are used for learning predictive models with the purpose of detecting adverse drug events. The use and representation of two data types, as well as their combination, are studied: clinical codes, describing prescribed drugs and assigned diagnoses, and measurements. Feature selection is conducted on the various types of data to reduce dimensionality and sparsity, while allowing for an in-depth feature analysis of the usefulness of each data type and representation. Results Within each data type, combining multiple representations yields better predictive performance compared to using any single representation. The use of clinical codes for adverse drug event detection significantly outperforms the use of measurements; however, there is no significant difference over datasets between using only clinical codes and their combination with measurements. For certain adverse drug events, the combination does, however, outperform using only clinical codes. Feature selection leads to increased predictive performance for both data types, in isolation and combined. Conclusions We have demonstrated how machine learning can be applied to electronic health records for the purpose of detecting adverse drug events and proposed solutions to some of the challenges this presents, including how to represent the various data types. Overall, clinical codes are more useful than measurements and, in specific cases, it is beneficial to combine the two. PMID:26606038

A comparison of in-class learner engagement across lecture, problem-based learning, and team learning using the STROBE classroom observation tool.

PubMed

Kelly, P Adam; Haidet, Paul; Schneider, Virginia; Searle, Nancy; Seidel, Charles L; Richards, Boyd F

2005-01-01

Having recently introduced team learning into the preclinical medical curriculum, evidence of the relative impact of this instructional method on in-class learner engagement was sought. To compare patterns of engagement behaviors among learners in class sessions across 3 distinct instructional methods: lecture, problem-based learning (PBL), and team learning. Trained observers used the STROBE classroom observation tool to measure learner engagement in 7 lecture, 4 PBL, and 3 team learning classrooms over a 12-month period. Proportions of different types of engagement behaviors were compared using chi-square. In PBL and team learning, the amount of learner-to-learner engagement was similar and much greater than in lecture, where most engagement was of the learner-to-instructor and self-engagement types. Also, learner-to-instructor engagement appeared greater in team learning than in PBL. Observed engagement behaviors confirm the potential of team learning to foster engagement similar to PBL, but with greater faculty input.

The Effects of Cognitive Style on the Learning Preferences of Graduate School Students

DTIC Science & Technology

1993-09-01

Pre-Test Relationships Between Cognitive Style Types and Preferences for Learning MTDs ......... 91 vi Figure Page 15. Post-Test Relationships Between...Abstract This research establishes significant relationships between an individual’s cognitive style, measured by the Myers-Briggs Type Indicator (MBTI...the data provide an opportunity to determine if there are any relationships between them. Also, due to the pre-tests and post-tests, there is

A Tool for Measuring Active Learning in the Classroom

PubMed Central

Devlin, John W.; Kirwin, Jennifer L.; Qualters, Donna M.

2007-01-01

Objectives To develop a valid and reliable active-learning inventory tool for use in large classrooms and compare faculty perceptions of active-learning using the Active-Learning Inventory Tool. Methods The Active-Learning Inventory Tool was developed using published literature and validated by national experts in educational research. Reliability was established by trained faculty members who used the Active-Learning Inventory Tool to observe 9 pharmacy lectures. Instructors were then interviewed to elicit perceptions regarding active learning and asked to share their perceptions. Results Per lecture, 13 (range: 4-34) episodes of active learning encompassing 3 (range: 2-5) different types of active learning occurred over 2.2 minutes (0.6-16) per episode. Both interobserver (≥87%) and observer-instructor agreement (≥68%) were high for these outcomes. Conclusions The Active-Learning Inventory Tool is a valid and reliable tool to measure active learning in the classroom. Future studies are needed to determine the impact of the Active-Learning Inventory Tool on teaching and its usefulness in other disciplines. PMID:17998982

An Examination of a State-Level Mathematics Test: What Type of Learning Does the Mathematics Test Actually Measure?

ERIC Educational Resources Information Center

Wilkins, Jesse L. M.; Jones, Brett D.

2009-01-01

Most U.S. states have developed sophisticated assessment programs to evaluate student achievement and hold schools, teachers, and students accountable for learning important content. The No Child Left Behind Act of 2001 (NCLB, 2002) has placed further pressure on educators and administrators to ensure that all students are learning. Yet, some…

A Latent Profile Analysis of University Students' Self-Regulated Learning Strategies

ERIC Educational Resources Information Center

Ning, Hoi Kwan; Downing, Kevin

2015-01-01

Based on self-reported cognitive, metacognitive, and behavioural strategy measures obtained from 828 final-year students from a university in Hong Kong, latent profile analysis (LPA) identified four distinct types of students with differential self-regulated learning strategy orientations: "competent self-regulated learners",…

The use of errorless learning strategies for patients with Alzheimer's disease: a literature review.

PubMed

Li, Ruijie; Liu, Karen P Y

2012-12-01

The aim of this article was to review the evidence of errorless learning on learning outcomes in patients with early-stage Alzheimer's disease. A computer-aided literature search from 1999 to 2011 was carried out using MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO and PsycArticles. Keywords included 'errorless learning or practice' and 'Alzheimer's disease'. Four studies that fulfilled the inclusion criteria were selected and reviewed. Two of the studies were clinical controlled trials: one was a single-group pretest-post-test trial and the other was a multiple single-participant study. Demographic variables, design, treatment and outcome measures were summarized. Recall trials were used as the primary outcome measure. Results indicate that the use of errorless learning promotes better retention of specific types of information. Errorless learning is effective in memory rehabilitation of older adults with Alzheimer's disease. However, it would require more studies with unified outcome measures to allow for the formulation of standardized clinical protocol and recommendations.

The Extrapolation of Elementary Sequences

NASA Technical Reports Server (NTRS)

Laird, Philip; Saul, Ronald

1992-01-01

We study sequence extrapolation as a stream-learning problem. Input examples are a stream of data elements of the same type (integers, strings, etc.), and the problem is to construct a hypothesis that both explains the observed sequence of examples and extrapolates the rest of the stream. A primary objective -- and one that distinguishes this work from previous extrapolation algorithms -- is that the same algorithm be able to extrapolate sequences over a variety of different types, including integers, strings, and trees. We define a generous family of constructive data types, and define as our learning bias a stream language called elementary stream descriptions. We then give an algorithm that extrapolates elementary descriptions over constructive datatypes and prove that it learns correctly. For freely-generated types, we prove a polynomial time bound on descriptions of bounded complexity. An especially interesting feature of this work is the ability to provide quantitative measures of confidence in competing hypotheses, using a Bayesian model of prediction.

Student Achievement in Computer Programming: Lecture vs Computer-Aided Instruction

ERIC Educational Resources Information Center

Tsai, San-Yun W.; Pohl, Norval F.

1978-01-01

This paper discusses a study of the differences in student learning achievement, as measured by four different types of common performance evaluation techniques, in a college-level computer programming course under three teaching/learning environments: lecture, computer-aided instruction, and lecture supplemented with computer-aided instruction.…

Operational Test and Evaluation Handbook for Aircrew Training Devices. Volume II. Operational Effectiveness Evaluation

DTIC Science & Technology

1982-02-01

should also convey an understanding of the differ- ences in learning behavior between initial learning activity and later skill maintenance and...refinement might then be, ATTACK MANEUVERS * Pop-up attack # Loft/ LADO type attack * Level/laydown attack Figure 5-4 showe diagrammatically the...sensitive to differ- ences in performance. Severai criteria should be used to guide the selection/development of performance measures, i.e., measure validity

Instructional Coach Weighs 3 Types of Data to Get Triple-Strength Feedback

ERIC Educational Resources Information Center

Boehle, Monica

2014-01-01

This article describes three types of data that can impact how instructional coaches face the challenges in measuring the impact of their work with teachers on student learning. Descriptions of the three types of data--"shifts in teacher reflective tendencies," "the use of student performance as an indicator of success," and…

The Role of Personality Temperament and Student Learning in Principles of Economics: Further Evidence.

ERIC Educational Resources Information Center

Ziegert, Andrea L.

2000-01-01

Explores the relationship between student personality types and measures of student performance in principles of microeconomics using the Keirsey Sorter, a 70-question Myers-Briggs Type Indicator (MBTI); results from the Test of Understanding of College Economics (TUCE); and course grades. Suggests that personality types do affect student…

The distressed (Type D) personality factor of social inhibition, but not negative affectivity, enhances eyeblink conditioning.

PubMed

Allen, M T; Handy, J D; Blankenship, M R; Servatius, R J

2018-06-01

Recent work has focused on a learning diathesis model in which specific personality factors such as behavioral inhibition (BI) may influence associative learning and in turn increase risk for the development of anxiety disorders. We have found in a series of studies that individuals self-reporting high levels of BI exhibit enhanced acquisition of conditioned eyeblinks. In the study reported here, hypotheses were extended to include distressed (Type D) personality which has been found to be related to BI. Type D personality is measured with the DS-14 scale which includes two subscales measuring negative affectivity (NA) and social inhibition (SI). We hypothesized that SI, which is similar to BI, would result in enhanced acquisition while the effect of NA is unclear. Eighty nine participants completed personality inventories including the Adult Measure of Behavioral Inhibition (AMBI) and DS-14. All participants received 60 acquisition trials with a 500 ms, 1000 Hz, tone CS and a co-terminating 50 ms, 5 psi corneal airpuff US. Participants received either 100% CS-US paired trials or a schedule of partial reinforcement where 50% US alone trials were intermixed into CS-US training. Acquisition of CRs did not differ between the two training protocols. Whereas BI was significantly related to Type D, SI, and NA, only BI and SI individuals exhibited enhanced acquisition of conditioned eyeblinks as compared to non-inhibited individuals. Personality factors now including social inhibition can be used to identify individuals who express enhanced associative learning which lends further support to a learning diathesis model of anxiety disorders. Copyright © 2018 Elsevier B.V. All rights reserved.

Absence of an association between insulin-dependent diabetes mellitus and developmental learning difficulties.

PubMed

Crawford, S G; Kaplan, B J; Field, L L

1995-01-01

For several years, investigators have been examining the relationship between learning difficulties and a variety of immunological disorders. Two recent studies by Hansen and colleagues reported a negative association between Type 1 diabetes and reading disabilities (dyslexia): subjects with Type 1 diabetes had a lower prevalence of dyslexia than their nondiabetic relatives. In order to control for the impact of environmental variables on learning, we investigated the relationship between Type 1 diabetes and learning problems in 27 sibling pairs, ranging in age from 6 to 20 years. One child in each pair had Type 1 diabetes, and the other child was the unaffected sibling closest in age. Children were assessed for cognitive skills, academic achievement in reading, mathematics, and written language, as well as for speech articulation and motor coordination. Other variables that were examined included handedness, behavioural variables, medical history, and pregnancy and birth complications. We found no significant differences between the 27 children with Type 1 diabetes and their unaffected siblings on any of the cognitive, academic achievement, or speech articulation measures. There were also no significant differences on handedness, behavioural variables, or health history.

Does the Room Matter? Active Learning in Traditional and Enhanced Lecture Spaces.

PubMed

Stoltzfus, Jon R; Libarkin, Julie

2016-01-01

SCALE-UP-type classrooms, originating with the Student-Centered Active Learning Environment with Upside-down Pedagogies project, are designed to facilitate active learning by maximizing opportunities for interactions between students and embedding technology in the classroom. Positive impacts when active learning replaces lecture are well documented, both in traditional lecture halls and SCALE-UP-type classrooms. However, few studies have carefully analyzed student outcomes when comparable active learning-based instruction takes place in a traditional lecture hall and a SCALE-UP-type classroom. Using a quasi-experimental design, we compared student perceptions and performance between sections of a nonmajors biology course, one taught in a traditional lecture hall and one taught in a SCALE-UP-type classroom. Instruction in both sections followed a flipped model that relied heavily on cooperative learning and was as identical as possible given the infrastructure differences between classrooms. Results showed that students in both sections thought that SCALE-UP infrastructure would enhance performance. However, measures of actual student performance showed no difference between the two sections. We conclude that, while SCALE-UP-type classrooms may facilitate implementation of active learning, it is the active learning and not the SCALE-UP infrastructure that enhances student performance. As a consequence, we suggest that institutions can modify existing classrooms to enhance student engagement without incorporating expensive technology. © 2016 J. R. Stoltzfus and J. Libarkin. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Psychometric Characteristics of the EEAA (Scale of Affective Strategies in the Learning Process)

ERIC Educational Resources Information Center

Villardón-Gallego, Lourdes; Yániz, Concepción

2014-01-01

Introduction: Affective strategies for coping with affective states linked to the learning process may be oriented toward controlling emotions or toward controlling motivation. Both types affect performance, directly and indirectly. The objective of this research was to design an instrument for measuring the affective strategies used by university…

Reformulating Testing to Measure Thinking and Learning. Technical Report No. 6898.

ERIC Educational Resources Information Center

Collins, Allan

This paper discusses systemic problems with testing and outlines two scenarios for reformulating testing based on intelligent tutoring systems. Five desiderata are provided to underpin the type of testing proposed: (1) tests should emphasize learning and thinking; (2) tests should require generation as well as selection; (3) tests should be…

More Efficient Learning on Web Courseware Systems?

ERIC Educational Resources Information Center

Zufic, Janko; Kalpic, Damir

2007-01-01

The article describes a research conducted on students at the University in Pula, by which was attempted to establish whether there is a relationship between exam success and a type of online teaching material from which a student learns. Students were subjected to psychological testing that measured factors of intelligence: verbal, non-verbal and…

The role of different types of instrumentality in motivation, study strategies, and performance: know why you learn, so you'll know what you learn!

PubMed

Simons, Joke; Dewitte, Siegfried; Lens, Willy

2004-09-01

Two theories in the field of motivation and achievement, namely the future time perspective theory and goal theory, result in conflicting recommendations for enhancing students' motivation, because of their differential emphasis on the task at hand and on the future consequences of a task. We will present a framework consisting of four types of instrumentality that combines both perspectives. The implications of those different types for goal orientation, motivation, cognitive strategies, study habits and performance are investigated. Participants were a group of 184 first-year nurse students with ages ranging from 18 to 45 years. Questionnaires were administered that measured instrumentality, goal orientation, motivation, deep and surface level learning strategies, study habits, and a manipulation check. At the end of the year, exam scores were collected. The results showed that different types of instrumentality are related differently to the motivational, cognitive and achievement measures. Being internally regulated and perceiving the utility of the courses resulted both in a more adaptive goal orientation and higher intrinsic motivation, which led to the use of more adaptive cognitive strategies and to better study habits, which ultimately enhanced performance. Linking performance to extrinsic rewards and not seeing the utility of the course for the future yielded the opposite pattern. Type of instrumentality has indeed a differential influence on motivational, cognitive, and behavioural variables.

Examining the Relationships of Different Cognitive Load Types Related to User Interface in Web-Based Instruction

ERIC Educational Resources Information Center

Cheon, Jongpil; Grant, Michael

2012-01-01

This study proposes a new instrument to measure cognitive load types related to user interface and demonstrates theoretical assumptions about different load types. In reconsidering established cognitive load theory, the inadequacies of the theory are criticized in terms of the adaption of learning efficiency score and distinction of cognitive load…

Prepared stimuli enhance aversive learning without weakening the impact of verbal instructions

PubMed Central

2018-01-01

Fear-relevant stimuli such as snakes and spiders are thought to capture attention due to evolutionary significance. Classical conditioning experiments indicate that these stimuli accelerate learning, while instructed extinction experiments suggest they may be less responsive to instructions. We manipulated stimulus type during instructed aversive reversal learning and used quantitative modeling to simultaneously test both hypotheses. Skin conductance reversed immediately upon instruction in both groups. However, fear-relevant stimuli enhanced dynamic learning, as measured by higher learning rates in participants conditioned with images of snakes and spiders. Results are consistent with findings that dissociable neural pathways underlie feedback-driven and instructed aversive learning. PMID:29339561

Realizing a Deflection-type D.C. Bridge-based Thermometer under Project-based Learning Approach

NASA Astrophysics Data System (ADS)

Warsahemas, T.; Ramadhiansyah; Ulum, A. I. N.; Yuliza, E.; Khairurrijal

2016-08-01

In addition to conventional learning, project-based learning (PBL) helps students developing skills and becoming more engaged in learning as they have a chance to solve real life problems of actual projects. As the name suggests, PBL is a model that organizes learning around projects. In this paper, the project that will be completed by a group of three students is about making a water temperature measuring instrument using a simple deflection-type d.c. bridge circuit. The project was done in the period of January to April 2015 when they was taking the Measurement and Data Processing Techniques, which is a compulsory course in the fourth semester of undergraduate program in Department of Physics at Institut Teknologi Bandung. With the help of a lecturer and a tutor as facilitators, they have followed this series of steps: 1. Start with a driving question, a problem to be solved, 2. Exploring the driving question by participating in authentic, situated inquiry, 3. Engaging collaborative activities with lecturer and tutor to find solutions to the driving question, 4. Scaffolding with learning technologies that help students participating in activities normally beyond their ability, and 5. Creating a set of tangible products that address the driving question. With this series of steps, the students have become easier to understand the lectures that have been given and the instrument has been realized to measure the temperature of water properly. When realizing the project under the PBL method, we learned other materials beside that have been taught in the course. Due to this project, we have had more skills like designing and soldering as well as problem-solving, teamwork, critical thinking, synthesis and analysis.

Attentional effects on rule extraction and consolidation from speech.

PubMed

López-Barroso, Diana; Cucurell, David; Rodríguez-Fornells, Antoni; de Diego-Balaguer, Ruth

2016-07-01

Incidental learning plays a crucial role in the initial phases of language acquisition. However the knowledge derived from implicit learning, which is based on prediction-based mechanisms, may become explicit. The role that attention plays in the formation of implicit and explicit knowledge of the learned material is unclear. In the present study, we investigated the role that attention plays in the acquisition of non-adjacent rule learning from speech. In addition, we also tested whether the amount of attention during learning changes the representation of the learned material after a 24h delay containing sleep. For that, we developed an experiment run on two consecutive days consisting on the exposure to an artificial language that contained non-adjacent dependencies (rules) between words whereas different conditions were established to manipulate the amount of attention given to the rules (target and non-target conditions). Furthermore, we used both indirect and direct measures of learning that are more sensitive to implicit and explicit knowledge, respectively. Whereas the indirect measures indicated that learning of the rules occurred regardless of attention, more explicit judgments after learning showed differences in the type of learning reached under the two attention conditions. 24 hours later, indirect measures showed no further improvements during additional language exposure and explicit judgments indicated that only the information more robustly learned in the previous day, was consolidated. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Attentional effects on rule extraction and consolidation from speech

PubMed Central

López-Barroso, Diana; Cucurell, David; Rodríguez-Fornells, Antoni; de Diego-Balaguer, Ruth

2016-01-01

Incidental learning plays a crucial role in the initial phases of language acquisition. However the knowledge derived from implicit learning, which is based on prediction-based mechanisms, may become explicit. The role that attention plays in the formation of implicit and explicit knowledge of the learned material is unclear. In the present study, we investigated the role that attention plays in the acquisition of non-adjacent rule learning from speech. In addition, we also tested whether the amount of attention during learning changes the representation of the learned material after a 24 h delay containing sleep. For that, we developed an experiment run on two consecutive days consisting on the exposure to an artificial language that contained non-adjacent dependencies (rules) between words whereas different conditions were established to manipulate the amount of attention given to the rules (target and non-target conditions). Furthermore, we used both indirect and direct measures of learning that are more sensitive to implicit and explicit knowledge, respectively. Whereas the indirect measures indicated that learning of the rules occurred regardless of attention, more explicit judgments after learning showed differences in the type of learning reached under the two attention conditions. 24 hours later, indirect measures showed no further improvements during additional language exposure and explicit judgments indicated that only the information more robustly learned in the previous day, was consolidated. PMID:27031495

Disentangling perceptual from motor implicit sequence learning with a serial color-matching task.

PubMed

Gheysen, Freja; Gevers, Wim; De Schutter, Erik; Van Waelvelde, Hilde; Fias, Wim

2009-08-01

This paper contributes to the domain of implicit sequence learning by presenting a new version of the serial reaction time (SRT) task that allows unambiguously separating perceptual from motor learning. Participants matched the colors of three small squares with the color of a subsequently presented large target square. An identical sequential structure was tied to the colors of the target square (perceptual version, Experiment 1) or to the manual responses (motor version, Experiment 2). Short blocks of sequenced and randomized trials alternated and hence provided a continuous monitoring of the learning process. Reaction time measurements demonstrated clear evidence of independently learning perceptual and motor serial information, though revealed different time courses between both learning processes. No explicit awareness of the serial structure was needed for either of the two types of learning to occur. The paradigm introduced in this paper evidenced that perceptual learning can occur with SRT measurements and opens important perspectives for future imaging studies to answer the ongoing question, which brain areas are involved in the implicit learning of modality specific (motor vs. perceptual) or general serial order.

Distance Education in a Cost Accounting Course: Instruction, Interaction, and Multiple Measures of Learning Outcomes

ERIC Educational Resources Information Center

Chen, Clement C.; Jones, Keith T.; Moreland, Keith

2010-01-01

Students in online and traditional classroom sections of an intermediate-level cost accounting course responded to a survey about their experiences in the course. Specifically, several items related to the instruction and learning outcomes were addressed. Additionally, student examination performance in the two types of sections was compared. The…

Deep Learning Questions Can Help Selection of High Ability Candidates for Universities

ERIC Educational Resources Information Center

Mellanby, Jane; Cortina-Borja, Mario; Stein, John

2009-01-01

Selection of students for places at universities mainly depends on GCSE grades and predictions of A-level grades, both of which tend to favour applicants from independent schools. We have therefore developed a new type of test that would measure candidates' "deep learning" approach since this assesses the motivation and creative thinking…

The Instructional Factors That Lead to Cheating in a Korean Cyber University Context

ERIC Educational Resources Information Center

Costley, Jamie

2017-01-01

Purpose: This paper looks at a particular type of cheating that occurs in an online university setting. That is, when students who have a connection from outside the online learning environment conspire to cheat together. It measures the correlations between student variables and cheating, instructional variables and cheating and learning outcomes…

Ascending Bloom's Pyramid: Fostering Student Creativity and Innovation in Academic Library Spaces

ERIC Educational Resources Information Center

Bieraugel, Mark; Neill, Stern

2017-01-01

Our research examined the degree to which behaviors and learning associated with creativity and innovation were supported in five academic library spaces and three other spaces at a mid-sized university. Based on survey data from 226 students, we apply a number of statistical techniques to measure student perceptions of the types of learning and…

Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach

PubMed Central

Yamamoto, Yoichiro; Saito, Akira; Tateishi, Ayako; Shimojo, Hisashi; Kanno, Hiroyuki; Tsuchiya, Shinichi; Ito, Ken-ichi; Cosatto, Eric; Graf, Hans Peter; Moraleda, Rodrigo R.; Eils, Roland; Grabe, Niels

2017-01-01

Machine learning systems have recently received increased attention for their broad applications in several fields. In this study, we show for the first time that histological types of breast tumors can be classified using subtle morphological differences of microenvironmental myoepithelial cell nuclei without any direct information about neoplastic tumor cells. We quantitatively measured 11661 nuclei on the four histological types: normal cases, usual ductal hyperplasia and low/high grade ductal carcinoma in situ (DCIS). Using a machine learning system, we succeeded in classifying the four histological types with 90.9% accuracy. Electron microscopy observations suggested that the activity of typical myoepithelial cells in DCIS was lowered. Through these observations as well as meta-analytic database analyses, we developed a paracrine cross-talk-based biological mechanism of DCIS progressing to invasive cancer. Our observations support novel approaches in clinical computational diagnostics as well as in therapy development against progression. PMID:28440283

Learning Strategies in Matching to Sample: If-then and Configural Learning by Pigeons

PubMed Central

Katz, Jeffrey S.; Bodily, Kent D.; Wright, Anthony A.

2008-01-01

Pigeons learned a matching-to-sample task with a split training-set design in which half of the stimulus displays were untrained and tested following acquisition. Transfer to the untrained displays along with no novel-stimulus transfer indicated that these pigeons learned the task (partially) via if-then rules. Comparisons to other performance measures indicated that they also partially learned the task via configural learning (learning the gestalt of the whole stimulus display). Differences in the FR-sample requirement (1 vs. 20) had no systematic effect on the type of learning or level of learning obtained. Differences from a previous study (Wright, 1997) are discussed, including the effect of displaying the stimuli vertically (traditional display orientation) or horizontally from the floor. PMID:18079071

Handwriting generates variable visual output to facilitate symbol learning.

PubMed

Li, Julia X; James, Karin H

2016-03-01

Recent research has demonstrated that handwriting practice facilitates letter categorization in young children. The present experiments investigated why handwriting practice facilitates visual categorization by comparing 2 hypotheses: that handwriting exerts its facilitative effect because of the visual-motor production of forms, resulting in a direct link between motor and perceptual systems, or because handwriting produces variable visual instances of a named category in the environment that then changes neural systems. We addressed these issues by measuring performance of 5-year-old children on a categorization task involving novel, Greek symbols across 6 different types of learning conditions: 3 involving visual-motor practice (copying typed symbols independently, tracing typed symbols, tracing handwritten symbols) and 3 involving visual-auditory practice (seeing and saying typed symbols of a single typed font, of variable typed fonts, and of handwritten examples). We could therefore compare visual-motor production with visual perception both of variable and similar forms. Comparisons across the 6 conditions (N = 72) demonstrated that all conditions that involved studying highly variable instances of a symbol facilitated symbol categorization relative to conditions where similar instances of a symbol were learned, regardless of visual-motor production. Therefore, learning perceptually variable instances of a category enhanced performance, suggesting that handwriting facilitates symbol understanding by virtue of its environmental output: supporting the notion of developmental change though brain-body-environment interactions. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Handwriting generates variable visual input to facilitate symbol learning

PubMed Central

Li, Julia X.; James, Karin H.

2015-01-01

Recent research has demonstrated that handwriting practice facilitates letter categorization in young children. The present experiments investigated why handwriting practice facilitates visual categorization by comparing two hypotheses: That handwriting exerts its facilitative effect because of the visual-motor production of forms, resulting in a direct link between motor and perceptual systems, or because handwriting produces variable visual instances of a named category in the environment that then changes neural systems. We addressed these issues by measuring performance of 5 year-old children on a categorization task involving novel, Greek symbols across 6 different types of learning conditions: three involving visual-motor practice (copying typed symbols independently, tracing typed symbols, tracing handwritten symbols) and three involving visual-auditory practice (seeing and saying typed symbols of a single typed font, of variable typed fonts, and of handwritten examples). We could therefore compare visual-motor production with visual perception both of variable and similar forms. Comparisons across the six conditions (N=72) demonstrated that all conditions that involved studying highly variable instances of a symbol facilitated symbol categorization relative to conditions where similar instances of a symbol were learned, regardless of visual-motor production. Therefore, learning perceptually variable instances of a category enhanced performance, suggesting that handwriting facilitates symbol understanding by virtue of its environmental output: supporting the notion of developmental change though brain-body-environment interactions. PMID:26726913

Exogenous and endogenous attention during perceptual learning differentially affect post-training target thresholds

PubMed Central

Mukai, Ikuko; Bahadur, Kandy; Kesavabhotla, Kartik; Ungerleider, Leslie G.

2012-01-01

There is conflicting evidence in the literature regarding the role played by attention in perceptual learning. To further examine this issue, we independently manipulated exogenous and endogenous attention and measured the rate of perceptual learning of oriented Gabor patches presented in different quadrants of the visual field. In this way, we could track learning at attended, divided-attended, and unattended locations. We also measured contrast thresholds of the Gabor patches before and after training. Our results showed that, for both exogenous and endogenous attention, accuracy in performing the orientation discrimination improved to a greater extent at attended than at unattended locations. Importantly, however, only exogenous attention resulted in improved contrast thresholds. These findings suggest that both exogenous and endogenous attention facilitate perceptual learning, but that these two types of attention may be mediated by different neural mechanisms. PMID:21282340

A mediation analysis of achievement motives, goals, learning strategies, and academic achievement.

PubMed

Diseth, Age; Kobbeltvedt, Therese

2010-12-01

Previous research is inconclusive regarding antecedents and consequences of achievement goals, and there is a need for more research in order to examine the joint effects of different types of motives and learning strategies as predictors of academic achievement. To investigate the relationship between achievement motives, achievement goals, learning strategies (deep, surface, and strategic), and academic achievement in a hierarchical model. Participants were 229 undergraduate students (mean age: 21.2 years) of psychology and economics at the University of Bergen, Norway. Variables were measured by means of items from the Achievement Motives Scale (AMS), the Approaches and Study Skills Inventory for Students, and an achievement goal scale. Correlation analysis showed that academic achievement (examination grade) was positively correlated with performance-approach goal, mastery goal, and strategic learning strategies, and negatively correlated with performance-avoidance goal and surface learning strategy. A path analysis (structural equation model) showed that achievement goals were mediators between achievement motives and learning strategies, and that strategic learning strategies mediated the relationship between achievement goals and academic achievement. This study integrated previous findings from several studies and provided new evidence on the direct and indirect effects of different types of motives and learning strategies as predictors of academic achievement.

Learning to Fail in Aphasia: An Investigation of Error Learning in Naming

PubMed Central

Middleton, Erica L.; Schwartz, Myrna F.

2013-01-01

Purpose To determine if the naming impairment in aphasia is influenced by error learning and if error learning is related to type of retrieval strategy. Method Nine participants with aphasia and ten neurologically-intact controls named familiar proper noun concepts. When experiencing tip-of-the-tongue naming failure (TOT) in an initial TOT-elicitation phase, participants were instructed to adopt phonological or semantic self-cued retrieval strategies. In the error learning manipulation, items evoking TOT states during TOT-elicitation were randomly assigned to a short or long time condition where participants were encouraged to continue to try to retrieve the name for either 20 seconds (short interval) or 60 seconds (long). The incidence of TOT on the same items was measured on a post test after 48-hours. Error learning was defined as a higher rate of recurrent TOTs (TOT at both TOT-elicitation and post test) for items assigned to the long (versus short) time condition. Results In the phonological condition, participants with aphasia showed error learning whereas controls showed a pattern opposite to error learning. There was no evidence for error learning in the semantic condition for either group. Conclusion Error learning is operative in aphasia, but dependent on the type of strategy employed during naming failure. PMID:23816662

Effects of Sound, Vocabulary, and Grammar Learning Aptitude on Adult Second Language Speech Attainment in Foreign Language Classrooms

ERIC Educational Resources Information Center

Saito, Kazuya

2017-01-01

This study examines the relationship between different types of language learning aptitude (measured via the LLAMA test) and adult second language (L2) learners' attainment in speech production in English-as-a-foreign-language (EFL) classrooms. Picture descriptions elicited from 50 Japanese EFL learners from varied proficiency levels were analyzed…

Relationships of the Leadership Attitudes and Beliefs Scale with Student Types, Study Habits, Life-Long Learning, and GPA

ERIC Educational Resources Information Center

Wielkiewicz, Richard M.; Prom, Christina L.; Loos, Steven

2005-01-01

The Leadership Attitudes and Beliefs Scale (LABS-III; Wielkiewicz, 2000) was validated against a measure with a more traditional, position-based definition of leadership. Disagreement with Hierarchical Thinking was associated with a higher GPA. A Life-Long Learning scale was strongly associated with GPA, Systemic Thinking, and social activism.…

Low-rank structure learning via nonconvex heuristic recovery.

PubMed

Deng, Yue; Dai, Qionghai; Liu, Risheng; Zhang, Zengke; Hu, Sanqing

2013-03-01

In this paper, we propose a nonconvex framework to learn the essential low-rank structure from corrupted data. Different from traditional approaches, which directly utilizes convex norms to measure the sparseness, our method introduces more reasonable nonconvex measurements to enhance the sparsity in both the intrinsic low-rank structure and the sparse corruptions. We will, respectively, introduce how to combine the widely used ℓp norm (0 < p < 1) and log-sum term into the framework of low-rank structure learning. Although the proposed optimization is no longer convex, it still can be effectively solved by a majorization-minimization (MM)-type algorithm, with which the nonconvex objective function is iteratively replaced by its convex surrogate and the nonconvex problem finally falls into the general framework of reweighed approaches. We prove that the MM-type algorithm can converge to a stationary point after successive iterations. The proposed model is applied to solve two typical problems: robust principal component analysis and low-rank representation. Experimental results on low-rank structure learning demonstrate that our nonconvex heuristic methods, especially the log-sum heuristic recovery algorithm, generally perform much better than the convex-norm-based method (0 < p < 1) for both data with higher rank and with denser corruptions.

Measuring The Impact Of Motivation On Achievement And Course Completion Rates In MarineNet Distance Education

DTIC Science & Technology

2016-09-01

the Marine Corps. This research applies the learning theory of human motivation to archival MarineNet data to determine if motivation factors impact...motivations. Each type of motivation has a different effect on human learning and course outcomes. To test this theory, archival data from the MarineNet...demonstrate the similarities and dissimilarities that exist between civilian and Marine Corps DE programs as well as the gap in knowledge on human learning

Linking Individual Learning Styles to Approach-Avoidance Motivational Traits and Computational Aspects of Reinforcement Learning

PubMed Central

Carl Aberg, Kristoffer; Doell, Kimberly C.; Schwartz, Sophie

2016-01-01

Learning how to gain rewards (approach learning) and avoid punishments (avoidance learning) is fundamental for everyday life. While individual differences in approach and avoidance learning styles have been related to genetics and aging, the contribution of personality factors, such as traits, remains undetermined. Moreover, little is known about the computational mechanisms mediating differences in learning styles. Here, we used a probabilistic selection task with positive and negative feedbacks, in combination with computational modelling, to show that individuals displaying better approach (vs. avoidance) learning scored higher on measures of approach (vs. avoidance) trait motivation, but, paradoxically, also displayed reduced learning speed following positive (vs. negative) outcomes. These data suggest that learning different types of information depend on associated reward values and internal motivational drives, possibly determined by personality traits. PMID:27851807

The effects of shared information on semantic calculations in the gene ontology.

PubMed

Bible, Paul W; Sun, Hong-Wei; Morasso, Maria I; Loganantharaj, Rasiah; Wei, Lai

2017-01-01

The structured vocabulary that describes gene function, the gene ontology (GO), serves as a powerful tool in biological research. One application of GO in computational biology calculates semantic similarity between two concepts to make inferences about the functional similarity of genes. A class of term similarity algorithms explicitly calculates the shared information (SI) between concepts then substitutes this calculation into traditional term similarity measures such as Resnik, Lin, and Jiang-Conrath. Alternative SI approaches, when combined with ontology choice and term similarity type, lead to many gene-to-gene similarity measures. No thorough investigation has been made into the behavior, complexity, and performance of semantic methods derived from distinct SI approaches. We apply bootstrapping to compare the generalized performance of 57 gene-to-gene semantic measures across six benchmarks. Considering the number of measures, we additionally evaluate whether these methods can be leveraged through ensemble machine learning to improve prediction performance. Results showed that the choice of ontology type most strongly influenced performance across all evaluations. Combining measures into an ensemble classifier reduces cross-validation error beyond any individual measure for protein interaction prediction. This improvement resulted from information gained through the combination of ontology types as ensemble methods within each GO type offered no improvement. These results demonstrate that multiple SI measures can be leveraged for machine learning tasks such as automated gene function prediction by incorporating methods from across the ontologies. To facilitate future research in this area, we developed the GO Graph Tool Kit (GGTK), an open source C++ library with Python interface (github.com/paulbible/ggtk).

Web-Based Evaluation System to Measure Learning Effectiveness in Kampo Medicine

PubMed Central

Usuku, Koichiro; Segawa, Makoto; Wang, Yue; Ogashiwa, Kahori; Fujita, Yusuke; Ogihara, Hiroyuki; Tazuma, Susumu

2016-01-01

Measuring the learning effectiveness of Kampo Medicine (KM) education is challenging. The aim of this study was to develop a web-based test to measure the learning effectiveness of KM education among medical students (MSs). We used an open-source Moodle platform to test 30 multiple-choice questions classified into 8-type fields (eight basic concepts of KM) including “qi-blood-fluid” and “five-element” theories, on 117 fourth-year MSs. The mean (±standard deviation [SD]) score on the web-based test was 30.2 ± 11.9 (/100). The correct answer rate ranged from 17% to 36%. A pattern-based portfolio enabled these rates to be individualized in terms of KM proficiency. MSs with scores higher (n = 19) or lower (n = 14) than mean ± 1SD were defined as high or low achievers, respectively. Cluster analysis using the correct answer rates for the 8-type field questions revealed clear divisions between high and low achievers. Interestingly, each high achiever had a different proficiency pattern. In contrast, three major clusters were evident among low achievers, all of whom responded with a low percentage of or no correct answers. In addition, a combination of three questions accurately classified high and low achievers. These findings suggest that our web-based test allows individual quantitative assessment of the learning effectiveness of KM education among MSs. PMID:27738440

Web-Based Evaluation System to Measure Learning Effectiveness in Kampo Medicine.

PubMed

Iizuka, Norio; Usuku, Koichiro; Nakae, Hajime; Segawa, Makoto; Wang, Yue; Ogashiwa, Kahori; Fujita, Yusuke; Ogihara, Hiroyuki; Tazuma, Susumu; Hamamoto, Yoshihiko

2016-01-01

Measuring the learning effectiveness of Kampo Medicine (KM) education is challenging. The aim of this study was to develop a web-based test to measure the learning effectiveness of KM education among medical students (MSs). We used an open-source Moodle platform to test 30 multiple-choice questions classified into 8-type fields (eight basic concepts of KM) including "qi-blood-fluid" and "five-element" theories, on 117 fourth-year MSs. The mean (±standard deviation [SD]) score on the web-based test was 30.2 ± 11.9 (/100). The correct answer rate ranged from 17% to 36%. A pattern-based portfolio enabled these rates to be individualized in terms of KM proficiency. MSs with scores higher ( n = 19) or lower ( n = 14) than mean ± 1SD were defined as high or low achievers, respectively. Cluster analysis using the correct answer rates for the 8-type field questions revealed clear divisions between high and low achievers. Interestingly, each high achiever had a different proficiency pattern. In contrast, three major clusters were evident among low achievers, all of whom responded with a low percentage of or no correct answers. In addition, a combination of three questions accurately classified high and low achievers. These findings suggest that our web-based test allows individual quantitative assessment of the learning effectiveness of KM education among MSs.

Online incidental statistical learning of audiovisual word sequences in adults: a registered report.

PubMed

Kuppuraj, Sengottuvel; Duta, Mihaela; Thompson, Paul; Bishop, Dorothy

2018-02-01

Statistical learning has been proposed as a key mechanism in language learning. Our main goal was to examine whether adults are capable of simultaneously extracting statistical dependencies in a task where stimuli include a range of structures amenable to statistical learning within a single paradigm. We devised an online statistical learning task using real word auditory-picture sequences that vary in two dimensions: (i) predictability and (ii) adjacency of dependent elements. This task was followed by an offline recall task to probe learning of each sequence type. We registered three hypotheses with specific predictions. First, adults would extract regular patterns from continuous stream (effect of grammaticality). Second, within grammatical conditions, they would show differential speeding up for each condition as a factor of statistical complexity of the condition and exposure. Third, our novel approach to measure online statistical learning would be reliable in showing individual differences in statistical learning ability. Further, we explored the relation between statistical learning and a measure of verbal short-term memory (STM). Forty-two participants were tested and retested after an interval of at least 3 days on our novel statistical learning task. We analysed the reaction time data using a novel regression discontinuity approach. Consistent with prediction, participants showed a grammaticality effect, agreeing with the predicted order of difficulty for learning different statistical structures. Furthermore, a learning index from the task showed acceptable test-retest reliability ( r  = 0.67). However, STM did not correlate with statistical learning. We discuss the findings noting the benefits of online measures in tracking the learning process.

Online incidental statistical learning of audiovisual word sequences in adults: a registered report

PubMed Central

Duta, Mihaela; Thompson, Paul

2018-01-01

Statistical learning has been proposed as a key mechanism in language learning. Our main goal was to examine whether adults are capable of simultaneously extracting statistical dependencies in a task where stimuli include a range of structures amenable to statistical learning within a single paradigm. We devised an online statistical learning task using real word auditory–picture sequences that vary in two dimensions: (i) predictability and (ii) adjacency of dependent elements. This task was followed by an offline recall task to probe learning of each sequence type. We registered three hypotheses with specific predictions. First, adults would extract regular patterns from continuous stream (effect of grammaticality). Second, within grammatical conditions, they would show differential speeding up for each condition as a factor of statistical complexity of the condition and exposure. Third, our novel approach to measure online statistical learning would be reliable in showing individual differences in statistical learning ability. Further, we explored the relation between statistical learning and a measure of verbal short-term memory (STM). Forty-two participants were tested and retested after an interval of at least 3 days on our novel statistical learning task. We analysed the reaction time data using a novel regression discontinuity approach. Consistent with prediction, participants showed a grammaticality effect, agreeing with the predicted order of difficulty for learning different statistical structures. Furthermore, a learning index from the task showed acceptable test–retest reliability (r = 0.67). However, STM did not correlate with statistical learning. We discuss the findings noting the benefits of online measures in tracking the learning process. PMID:29515876

Extracting laboratory test information from biomedical text

PubMed Central

Kang, Yanna Shen; Kayaalp, Mehmet

2013-01-01

Background: No previous study reported the efficacy of current natural language processing (NLP) methods for extracting laboratory test information from narrative documents. This study investigates the pathology informatics question of how accurately such information can be extracted from text with the current tools and techniques, especially machine learning and symbolic NLP methods. The study data came from a text corpus maintained by the U.S. Food and Drug Administration, containing a rich set of information on laboratory tests and test devices. Methods: The authors developed a symbolic information extraction (SIE) system to extract device and test specific information about four types of laboratory test entities: Specimens, analytes, units of measures and detection limits. They compared the performance of SIE and three prominent machine learning based NLP systems, LingPipe, GATE and BANNER, each implementing a distinct supervised machine learning method, hidden Markov models, support vector machines and conditional random fields, respectively. Results: Machine learning systems recognized laboratory test entities with moderately high recall, but low precision rates. Their recall rates were relatively higher when the number of distinct entity values (e.g., the spectrum of specimens) was very limited or when lexical morphology of the entity was distinctive (as in units of measures), yet SIE outperformed them with statistically significant margins on extracting specimen, analyte and detection limit information in both precision and F-measure. Its high recall performance was statistically significant on analyte information extraction. Conclusions: Despite its shortcomings against machine learning methods, a well-tailored symbolic system may better discern relevancy among a pile of information of the same type and may outperform a machine learning system by tapping into lexically non-local contextual information such as the document structure. PMID:24083058

Types of Homeschool Environments and Need Support for Children's Achievement Motivation

ERIC Educational Resources Information Center

Bell, Debra A.; Kaplan, Avi; Thurman, S. Kenneth

2016-01-01

Working within a self-determination theory (SDT) framework, this study used cluster analysis to examine the naturally occurring types of homeschool-learning environments parents (N = 457) have created. Measures of support for student autonomy, mastery goal structure, and use of conditional regard were adapted for a homeschool context and used as…

Electrical test prediction using hybrid metrology and machine learning

NASA Astrophysics Data System (ADS)

Breton, Mary; Chao, Robin; Muthinti, Gangadhara Raja; de la Peña, Abraham A.; Simon, Jacques; Cepler, Aron J.; Sendelbach, Matthew; Gaudiello, John; Emans, Susan; Shifrin, Michael; Etzioni, Yoav; Urenski, Ronen; Lee, Wei Ti

2017-03-01

Electrical test measurement in the back-end of line (BEOL) is crucial for wafer and die sorting as well as comparing intended process splits. Any in-line, nondestructive technique in the process flow to accurately predict these measurements can significantly improve mean-time-to-detect (MTTD) of defects and improve cycle times for yield and process learning. Measuring after BEOL metallization is commonly done for process control and learning, particularly with scatterometry (also called OCD (Optical Critical Dimension)), which can solve for multiple profile parameters such as metal line height or sidewall angle and does so within patterned regions. This gives scatterometry an advantage over inline microscopy-based techniques, which provide top-down information, since such techniques can be insensitive to sidewall variations hidden under the metal fill of the trench. But when faced with correlation to electrical test measurements that are specific to the BEOL processing, both techniques face the additional challenge of sampling. Microscopy-based techniques are sampling-limited by their small probe size, while scatterometry is traditionally limited (for microprocessors) to scribe targets that mimic device ground rules but are not necessarily designed to be electrically testable. A solution to this sampling challenge lies in a fast reference-based machine learning capability that allows for OCD measurement directly of the electrically-testable structures, even when they are not OCD-compatible. By incorporating such direct OCD measurements, correlation to, and therefore prediction of, resistance of BEOL electrical test structures is significantly improved. Improvements in prediction capability for multiple types of in-die electrically-testable device structures is demonstrated. To further improve the quality of the prediction of the electrical resistance measurements, hybrid metrology using the OCD measurements as well as X-ray metrology (XRF) is used. Hybrid metrology is the practice of combining information from multiple sources in order to enable or improve the measurement of one or more critical parameters. Here, the XRF measurements are used to detect subtle changes in barrier layer composition and thickness that can have second-order effects on the electrical resistance of the test structures. By accounting for such effects with the aid of the X-ray-based measurements, further improvement in the OCD correlation to electrical test measurements is achieved. Using both types of solution incorporation of fast reference-based machine learning on nonOCD-compatible test structures, and hybrid metrology combining OCD with XRF technology improvement in BEOL cycle time learning could be accomplished through improved prediction capability.

Teacher Evaluation: Alternate Measures of Student Growth. Q&A with Brian Gill. REL Mid-Atlantic Webinar

ERIC Educational Resources Information Center

Regional Educational Laboratory Mid-Atlantic, 2013

2013-01-01

This webinar described the findings of our literature review on alternative measures of student growth that are used in teacher evaluation. The review focused on two types of alternative growth measures: statistical growth/value-added models and teacher-developed student learning objectives. This Q&A addressed the questions participants had…

Assessing and Measuring Statistics Cognition in Higher Education Online Environments: Emerging Research and Opportunities

ERIC Educational Resources Information Center

Chase, Justin P.; Yan, Zheng

2017-01-01

The ability to effective learn, process, and retain new information is critical to the success of any student. Since mathematics are becoming increasingly more important in our educational systems, it is imperative that we devise an efficient system to measure these types of information recall. "Assessing and Measuring Statistics Cognition in…

Online neural monitoring of statistical learning

PubMed Central

Batterink, Laura J.; Paller, Ken A.

2017-01-01

The extraction of patterns in the environment plays a critical role in many types of human learning, from motor skills to language acquisition. This process is known as statistical learning. Here we propose that statistical learning has two dissociable components: (1) perceptual binding of individual stimulus units into integrated composites and (2) storing those integrated representations for later use. Statistical learning is typically assessed using post-learning tasks, such that the two components are conflated. Our goal was to characterize the online perceptual component of statistical learning. Participants were exposed to a structured stream of repeating trisyllabic nonsense words and a random syllable stream. Online learning was indexed by an EEG-based measure that quantified neural entrainment at the frequency of the repeating words relative to that of individual syllables. Statistical learning was subsequently assessed using conventional measures in an explicit rating task and a reaction-time task. In the structured stream, neural entrainment to trisyllabic words was higher than in the random stream, increased as a function of exposure to track the progression of learning, and predicted performance on the RT task. These results demonstrate that monitoring this critical component of learning via rhythmic EEG entrainment reveals a gradual acquisition of knowledge whereby novel stimulus sequences are transformed into familiar composites. This online perceptual transformation is a critical component of learning. PMID:28324696

Measuring the Jungian personality types of Hispanic high school students.

PubMed

Mittag, K C

1999-09-01

Measures of normal variations in personality, called psychological type, are frequently used in education (e.g., to identify learning styles) and counseling (e.g., in career counseling). However, the most frequently-used measure of types, developed by Myers and Briggs, has been criticized on various psychometric grounds. The present study investigated the psychometric properties of an alternative measure, the Personal Preferences Self-Description Questionnaire (PPSDQ), which employs normative rather than ipsative (forced-choice) items. Because previous studies of the measure have primarily used older and highly literate participants, the present study was conducted with 328 Hispanic high school students to determine whether the sound psychometric quality of PPSDQ scores was compromised by vocabulary or language issues. The results of reliability and factor analyses were generally favorable as regards PPSDQ score integrity.

A cerebellar learning model of vestibulo-ocular reflex adaptation in wild-type and mutant mice.

PubMed

Clopath, Claudia; Badura, Aleksandra; De Zeeuw, Chris I; Brunel, Nicolas

2014-05-21

Mechanisms of cerebellar motor learning are still poorly understood. The standard Marr-Albus-Ito theory posits that learning involves plasticity at the parallel fiber to Purkinje cell synapses under control of the climbing fiber input, which provides an error signal as in classical supervised learning paradigms. However, a growing body of evidence challenges this theory, in that additional sites of plasticity appear to contribute to motor adaptation. Here, we consider phase-reversal training of the vestibulo-ocular reflex (VOR), a simple form of motor learning for which a large body of experimental data is available in wild-type and mutant mice, in which the excitability of granule cells or inhibition of Purkinje cells was affected in a cell-specific fashion. We present novel electrophysiological recordings of Purkinje cell activity measured in naive wild-type mice subjected to this VOR adaptation task. We then introduce a minimal model that consists of learning at the parallel fibers to Purkinje cells with the help of the climbing fibers. Although the minimal model reproduces the behavior of the wild-type animals and is analytically tractable, it fails at reproducing the behavior of mutant mice and the electrophysiology data. Therefore, we build a detailed model involving plasticity at the parallel fibers to Purkinje cells' synapse guided by climbing fibers, feedforward inhibition of Purkinje cells, and plasticity at the mossy fiber to vestibular nuclei neuron synapse. The detailed model reproduces both the behavioral and electrophysiological data of both the wild-type and mutant mice and allows for experimentally testable predictions. Copyright © 2014 the authors 0270-6474/14/347203-13$15.00/0.

Competition between multiple words for a referent in cross-situational word learning

PubMed Central

Benitez, Viridiana L.; Yurovsky, Daniel; Smith, Linda B.

2016-01-01

Three experiments investigated competition between word-object pairings in a cross-situational word-learning paradigm. Adults were presented with One-Word pairings, where a single word labeled a single object, and Two-Word pairings, where two words labeled a single object. In addition to measuring learning of these two pairing types, we measured competition between words that refer to the same object. When the word-object co-occurrences were presented intermixed in training (Experiment 1), we found evidence for direct competition between words that label the same referent. Separating the two words for an object in time eliminated any evidence for this competition (Experiment 2). Experiment 3 demonstrated that adding a linguistic cue to the second label for a referent led to different competition effects between adults who self-reported different language learning histories, suggesting both distinctiveness and language learning history affect competition. Finally, in all experiments, competition effects were unrelated to participants’ explicit judgments of learning, suggesting that competition reflects the operating characteristics of implicit learning processes. Together, these results demonstrate that the role of competition between overlapping associations in statistical word-referent learning depends on time, the distinctiveness of word-object pairings, and language learning history. PMID:27087742

Engine classification using vibrations measured by Laser Doppler Vibrometer on different surfaces

NASA Astrophysics Data System (ADS)

Wei, J.; Liu, Chi-Him; Zhu, Zhigang; Vongsy, Karmon; Mendoza-Schrock, Olga

2015-05-01

In our previous studies, vehicle surfaces' vibrations caused by operating engines measured by Laser Doppler Vibrometer (LDV) have been effectively exploited in order to classify vehicles of different types, e.g., vans, 2-door sedans, 4-door sedans, trucks, and buses, as well as different types of engines, such as Inline-four engines, V-6 engines, 1-axle diesel engines, and 2-axle diesel engines. The results are achieved by employing methods based on an array of machine learning classifiers such as AdaBoost, random forests, neural network, and support vector machines. To achieve effective classification performance, we seek to find a more reliable approach to pick authentic vibrations of vehicle engines from a trustworthy surface. Compared with vibrations directly taken from the uncooperative vehicle surfaces that are rigidly connected to the engines, these vibrations are much weaker in magnitudes. In this work we conducted a systematic study on different types of objects. We tested different types of engines ranging from electric shavers, electric fans, and coffee machines among different surfaces such as a white board, cement wall, and steel case to investigate the characteristics of the LDV signals of these surfaces, in both the time and spectral domains. Preliminary results in engine classification using several machine learning algorithms point to the right direction on the choice of type of object surfaces to be planted for LDV measurements.

Healthy older adults demonstrate generalized postural motor learning in response to variable amplitude oscillations of the support surface

PubMed Central

Van Ooteghem, Karen; Frank, James S.; Allard, Fran; Horak, Fay B

2011-01-01

Postural motor learning for dynamic balance tasks has been demonstrated in healthy older adults (Van Ooteghem et al. 2009). The purpose of this study was to investigate the type of knowledge (general or specific) obtained with balance training in this age group and to examine whether embedding perturbation regularities within a balance task masks specific learning. Two groups of older adults maintained balance on a constant frequency-variable amplitude oscillating platform. One group was trained using an embedded sequence (ES) protocol which contained the same 15-s sequence of variable amplitude oscillations in the middle of each trial. A second group was trained using a looped sequence (LS) protocol which contained a 15-s sequence repeated three times to form each trial. All trials were 45-s. Participants were not informed of any repetition. To examine learning, participants performed a retention test following a 24-h delay. LS participants also completed a transfer task. Specificity of learning was examined by comparing performance for repeated versus random sequences (ES) and training versus transfer sequences (LS). Performance was measured by deriving spatial and temporal measures of whole body centre of mass (COM), and trunk orientation. Both groups improved performance with practice as characterized by reduced COM displacement, improved COM-platform phase relationships, and decreased angular trunk motion. Improvements were also characterized by general rather than specific postural motor learning. These findings are similar to young adults (Van Ooteghem et al. 2008) and indicate that age does not influence the type of learning which occurs for balance control. PMID:20544184

The "Intentionality Measurement Instrument" [or "IMI"]: A Comprehensive Psychometric Instrument Based upon the Dual Quadrant Scalar Model of Intentionality That Is Designed to Measure Intent, Motive Type, and Disposition

ERIC Educational Resources Information Center

Osler, James Edward, II

2016-01-01

The overall aim of this paper is to provide an epistemological rational for the measurement of intentionality. The purpose of this narrative is to identify "Intentionality" as an arena of action in the dispositional learning domain can be measured using an "Intentionality Measurement Instrument" [also referred by the acronym…

Machine learning algorithms to classify spinal muscular atrophy subtypes.

PubMed

Srivastava, Tuhin; Darras, Basil T; Wu, Jim S; Rutkove, Seward B

2012-07-24

The development of better biomarkers for disease assessment remains an ongoing effort across the spectrum of neurologic illnesses. One approach for refining biomarkers is based on the concept of machine learning, in which individual, unrelated biomarkers are simultaneously evaluated. In this cross-sectional study, we assess the possibility of using machine learning, incorporating both quantitative muscle ultrasound (QMU) and electrical impedance myography (EIM) data, for classification of muscles affected by spinal muscular atrophy (SMA). Twenty-one normal subjects, 15 subjects with SMA type 2, and 10 subjects with SMA type 3 underwent EIM and QMU measurements of unilateral biceps, wrist extensors, quadriceps, and tibialis anterior. EIM and QMU parameters were then applied in combination using a support vector machine (SVM), a type of machine learning, in an attempt to accurately categorize 165 individual muscles. For all 3 classification problems, normal vs SMA, normal vs SMA 3, and SMA 2 vs SMA 3, use of SVM provided the greatest accuracy in discrimination, surpassing both EIM and QMU individually. For example, the accuracy, as measured by the receiver operating characteristic area under the curve (ROC-AUC) for the SVM discriminating SMA 2 muscles from SMA 3 muscles was 0.928; in comparison, the ROC-AUCs for EIM and QMU parameters alone were only 0.877 (p < 0.05) and 0.627 (p < 0.05), respectively. Combining EIM and QMU data categorizes individual SMA-affected muscles with very high accuracy. Further investigation of this approach for classifying and for following the progression of neuromuscular illness is warranted.

The CBAL Reading Assessment: An Approach for Balancing Measurement and Learning Goals. Research Report. ETS RR-11-21

ERIC Educational Resources Information Center

Sheehan, Kathleen M.; O'Reilly, Tenaha

2011-01-01

"No Child Left Behind" has highlighted the need for new types of assessments that not only provide high-quality evidence about what students know and can do, but also help to move learning forward. This paper describes a linked set of formative and summative reading assessments designed to address the tradeoffs inherent in these two…

Comparing the neural basis of monetary reward and cognitive feedback during information-integration category learning.

PubMed

Daniel, Reka; Pollmann, Stefan

2010-01-06

The dopaminergic system is known to play a central role in reward-based learning (Schultz, 2006), yet it was also observed to be involved when only cognitive feedback is given (Aron et al., 2004). Within the domain of information-integration category learning, in which information from several stimulus dimensions has to be integrated predecisionally (Ashby and Maddox, 2005), the importance of contingent feedback is well established (Maddox et al., 2003). We examined the common neural correlates of reward anticipation and prediction error in this task. Sixteen subjects performed two parallel information-integration tasks within a single event-related functional magnetic resonance imaging session but received a monetary reward only for one of them. Similar functional areas including basal ganglia structures were activated in both task versions. In contrast, a single structure, the nucleus accumbens, showed higher activation during monetary reward anticipation compared with the anticipation of cognitive feedback in information-integration learning. Additionally, this activation was predicted by measures of intrinsic motivation in the cognitive feedback task and by measures of extrinsic motivation in the rewarded task. Our results indicate that, although all other structures implicated in category learning are not significantly affected by altering the type of reward, the nucleus accumbens responds to the positive incentive properties of an expected reward depending on the specific type of the reward.

Moving virtuality into reality: A comparison study of the effectiveness of traditional and alternative assessments of learning in a multisensory, fully immersive physics program

NASA Astrophysics Data System (ADS)

Gamor, Keysha Ingram

This paper contains a research study that investigated the relative efficacy of using both a traditional paper-and-pencil assessment instrument and an alternative, virtual reality (VR) assessment instrument to assist educators and/or instructional designers in measuring learning in a virtual reality learning environment. To this end, this research study investigated assessment in VR, with the goal of analyzing aspects of student learning in VR that are feasible to access or capture by traditional assessments and alternative assessments. The researcher also examined what additional types of learning alternative assessments may offer. More specifically, this study compared the effectiveness of a traditional method with an alternative (performance-based) method of assessment that was used to examine the ability of the tools to accurately evidence the levels of students' understanding and learning. The domain area was electrostatics, a complex, abstract multidimensional concept, with which students often experience difficulty. Outcomes of the study suggest that, in the evaluation of learning in an immersive VR learning environment, assessments would most accurately manifest student learning if the assessment measure matched the learning environment itself. In this study, learning and assessing in the VR environment yielded higher final test scores than learning in VR and testing with traditional paper-and-pencil. Being able to transfer knowledge from a VR environment to other situations is critical in demonstrating the overall level of understanding of a concept. For this reason, the researcher recommends a combination of testing measures to enhance understanding of complex, abstract concepts.

Classification of Strawberry Fruit Shape by Machine Learning

NASA Astrophysics Data System (ADS)

Ishikawa, T.; Hayashi, A.; Nagamatsu, S.; Kyutoku, Y.; Dan, I.; Wada, T.; Oku, K.; Saeki, Y.; Uto, T.; Tanabata, T.; Isobe, S.; Kochi, N.

2018-05-01

Shape is one of the most important traits of agricultural products due to its relationships with the quality, quantity, and value of the products. For strawberries, the nine types of fruit shape were defined and classified by humans based on the sampler patterns of the nine types. In this study, we tested the classification of strawberry shapes by machine learning in order to increase the accuracy of the classification, and we introduce the concept of computerization into this field. Four types of descriptors were extracted from the digital images of strawberries: (1) the Measured Values (MVs) including the length of the contour line, the area, the fruit length and width, and the fruit width/length ratio; (2) the Ellipse Similarity Index (ESI); (3) Elliptic Fourier Descriptors (EFDs), and (4) Chain Code Subtraction (CCS). We used these descriptors for the classification test along with the random forest approach, and eight of the nine shape types were classified with combinations of MVs + CCS + EFDs. CCS is a descriptor that adds human knowledge to the chain codes, and it showed higher robustness in classification than the other descriptors. Our results suggest machine learning's high ability to classify fruit shapes accurately. We will attempt to increase the classification accuracy and apply the machine learning methods to other plant species.

Brain Type or Sex Differences? A structural equation model of the relation between brain type, sex, and motivation to learn science

NASA Astrophysics Data System (ADS)

Zeyer, Albert; Bölsterli, Katrin; Brovelli, Dorothee; Odermatt, Freia

2012-03-01

Sex is considered to be one of the most significant factors influencing attitudes towards science. However, the so-called brain type approach from cognitive science suggests that the difference in motivation to learn science does not primarily differentiate the girls from the boys, but rather the so-called systemisers from the empathizers. The present study investigates this hypothesis by using structural equation modelling on a sex-stratified sample of 500 male and female students of secondary II level. The results show, that the motivation to learn science is directly influenced by the systemizing quotient SQ, but not by sex. The impact of sex on the motivation to learn science, measured by five key concepts, only works indirectly, namely through the influence of sex on the SQ. The empathizing quotient (EQ) has no impact on the motivation to learn science. The SQ explains between 13 and 23 percent of the variation of the five key constructs. In female students, the impact of the SQ is very similar for all key concepts. In male students, it is highest for self-efficacy and lowest for assessment anxiety. The motivation to learn science is significantly larger for male students in all involved SMQ key concepts, but the difference is small. The interpretation of these findings and conclusions for science teaching and further research are discussed.

Monitoring Hitting Load in Tennis Using Inertial Sensors and Machine Learning.

PubMed

Whiteside, David; Cant, Olivia; Connolly, Molly; Reid, Machar

2017-10-01

Quantifying external workload is fundamental to training prescription in sport. In tennis, global positioning data are imprecise and fail to capture hitting loads. The current gold standard (manual notation) is time intensive and often not possible given players' heavy travel schedules. To develop an automated stroke-classification system to help quantify hitting load in tennis. Nineteen athletes wore an inertial measurement unit (IMU) on their wrist during 66 video-recorded training sessions. Video footage was manually notated such that known shot type (serve, rally forehand, slice forehand, forehand volley, rally backhand, slice backhand, backhand volley, smash, or false positive) was associated with the corresponding IMU data for 28,582 shots. Six types of machine-learning models were then constructed to classify true shot type from the IMU signals. Across 10-fold cross-validation, a cubic-kernel support vector machine classified binned shots (overhead, forehand, or backhand) with an accuracy of 97.4%. A second cubic-kernel support vector machine achieved 93.2% accuracy when classifying all 9 shot types. With a view to monitoring external load, the combination of miniature inertial sensors and machine learning offers a practical and automated method of quantifying shot counts and discriminating shot types in elite tennis players.

Realization of Deflection-type Bridge instruments to determine soil moisture using Research-Based Learning

NASA Astrophysics Data System (ADS)

Yuliza, E.; Munir, M. M.; Abdullah, M.; Khairurrijal

2016-08-01

It is clear that the quality of education is directly related to the quality of teachers and the teaching methods. One of the teaching methods that can improve the quality of education is research-based learning (RBL) method. In this method, students act as the center of learning while teachers become the guides that provide direction and advice. RBL is a learning method that combines cooperative learning, problem solving, authentic learning, contextual case study and inquiry approach discovery. The main goal of this method is to construct a student that can think critically, analyze and evaluate problems, and find a new science from these problems (learning by doing). In this paper, RBL is used to improve the understanding about measurement using deflection-type Bridge that is implemented in the determination of ground water changes. In general, there are three stages that have been done. Firstly the exposure stage, then the experience stage and lastly the capstone stage. The exposure stage aims to increase the knowledge and the comprehension of student about the topic through understanding the basics concepts, reviewing the literature and others. The understanding gained in the exposure stage is being used for application and analysis at the experience stage. While the final stage is the publication of research results both verbally and in writing. Based on the steps that have been conducted, it can be showed that deflection-type Bridge can be utilized in soil moisture meter.

The Relationship between Emotional and Esteem Social Support Messages and Health.

PubMed

Robinson, James D; Turner, Jeanine W; Tian, Yan; Neustadtl, Alan; Mun, Seong Ki; Levine, Betty

2017-11-28

The purpose of this investigation is to determine the relative contribution of five types of social support to improved patient health. This analysis suggests that emotional and esteem social support messages are associated with improved patient health as measured by a decrease in average blood glucose levels among diabetic patients. In addition, when two system feature variables, two system use variables, two measures of learning, one measure of self-efficacy, and one measure of affect toward their HCP were added to the baseline model, a third significant factor emerged. Perceptions about learning about diabetes from reading the digital messages sent by their HCP also predicted improved patient health. Cognitive-Emotional Theory of Esteem Support Messages suggests a combination of esteem social support and emotional social support messages enhanced our ability to predict improved patient health by change in patient hemoglobin A1c (HbA1c) scores. While a nonrandomized prospective study, this investigation provides support for the notion that provider-patient interaction is related to improved patient health and that both emotional and esteem social support messages play a role in that process. Finally, the study suggests some types of social support are and other types are not associated with improved patient health; this is consistent with the optimal matching hypothesis.

Perceptions of Teaching Methods for Preclinical Oral Surgery: A Comparison with Learning Styles

PubMed Central

Omar, Esam

2017-01-01

Purpose: Dental extraction is a routine part of clinical dental practice. For this reason, understanding the way how students’ extraction knowledge and skills development are important. Problem Statement and Objectives: To date, there is no accredited statement about the most effective method for the teaching of exodontia to dental students. Students have different abilities and preferences regarding how they learn and process information. This is defined as learning style. In this study, the effectiveness of active learning in the teaching of preclinical oral surgery was examined. The personality type of the groups involved in this study was determined, and the possible effect of personality type on learning style was investigated. Method: This study was undertaken over five years from 2011 to 2015. The sample consisted of 115 students and eight staff members. Questionnaires were submitted by 68 students and all eight staff members involved. Three measures were used in the study: The Index of Learning Styles (Felder and Soloman, 1991), the Myers-Briggs Type Indicator (MBTI), and the styles of learning typology (Grasha and Hruska-Riechmann). Results and Discussion: Findings indicated that demonstration and minimal clinical exposure give students personal validation. Frequent feedback on their work is strongly indicated to build the cognitive, psychomotor, and interpersonal skills needed from preclinical oral surgery courses. Conclusion: Small group cooperative active learning in the form of demonstration and minimal clinical exposure that gives frequent feedback and students’ personal validation on their work is strongly indicated to build the skills needed for preclinical oral surgery courses. PMID:28357004

The structure of stereotyped calls reflects kinship and social affiliation in resident killer whales (Orcinus orca).

PubMed

Deecke, Volker B; Barrett-Lennard, Lance G; Spong, Paul; Ford, John K B

2010-05-01

A few species of mammals produce group-specific vocalisations that are passed on by learning, but the function of learned vocal variation remains poorly understood. Resident killer whales live in stable matrilineal groups with repertoires of seven to 17 stereotyped call types. Some types are shared among matrilines, but their structure typically shows matriline-specific differences. Our objective was to analyse calls of nine killer whale matrilines in British Columbia to test whether call similarity primarily reflects social or genetic relationships. Recordings were made in 1985-1995 in the presence of focal matrilines that were either alone or with groups with non-overlapping repertoires. We used neural network discrimination performance to measure the similarity of call types produced by different matrilines and determined matriline association rates from 757 encounters with one or more focal matrilines. Relatedness was measured by comparing variation at 11 microsatellite loci for the oldest female in each group. Call similarity was positively correlated with association rates for two of the three call types analysed. Similarity of the N4 call type was also correlated with matriarch relatedness. No relationship between relatedness and association frequency was detected. These results show that call structure reflects relatedness and social affiliation, but not because related groups spend more time together. Instead, call structure appears to play a role in kin recognition and shapes the association behaviour of killer whale groups. Our results therefore support the hypothesis that increasing social complexity plays a role in the evolution of learned vocalisations in some mammalian species.

The structure of stereotyped calls reflects kinship and social affiliation in resident killer whales ( Orcinus orca)

NASA Astrophysics Data System (ADS)

Deecke, Volker B.; Barrett-Lennard, Lance G.; Spong, Paul; Ford, John K. B.

2010-05-01

A few species of mammals produce group-specific vocalisations that are passed on by learning, but the function of learned vocal variation remains poorly understood. Resident killer whales live in stable matrilineal groups with repertoires of seven to 17 stereotyped call types. Some types are shared among matrilines, but their structure typically shows matriline-specific differences. Our objective was to analyse calls of nine killer whale matrilines in British Columbia to test whether call similarity primarily reflects social or genetic relationships. Recordings were made in 1985-1995 in the presence of focal matrilines that were either alone or with groups with non-overlapping repertoires. We used neural network discrimination performance to measure the similarity of call types produced by different matrilines and determined matriline association rates from 757 encounters with one or more focal matrilines. Relatedness was measured by comparing variation at 11 microsatellite loci for the oldest female in each group. Call similarity was positively correlated with association rates for two of the three call types analysed. Similarity of the N4 call type was also correlated with matriarch relatedness. No relationship between relatedness and association frequency was detected. These results show that call structure reflects relatedness and social affiliation, but not because related groups spend more time together. Instead, call structure appears to play a role in kin recognition and shapes the association behaviour of killer whale groups. Our results therefore support the hypothesis that increasing social complexity plays a role in the evolution of learned vocalisations in some mammalian species.

On the tip of the tongue: learning typing and pointing with an intra-oral computer interface.

PubMed

Caltenco, Héctor A; Breidegard, Björn; Struijk, Lotte N S Andreasen

2014-07-01

To evaluate typing and pointing performance and improvement over time of four able-bodied participants using an intra-oral tongue-computer interface for computer control. A physically disabled individual may lack the ability to efficiently control standard computer input devices. There have been several efforts to produce and evaluate interfaces that provide individuals with physical disabilities the possibility to control personal computers. Training with the intra-oral tongue-computer interface was performed by playing games over 18 sessions. Skill improvement was measured through typing and pointing exercises at the end of each training session. Typing throughput improved from averages of 2.36 to 5.43 correct words per minute. Pointing throughput improved from averages of 0.47 to 0.85 bits/s. Target tracking performance, measured as relative time on target, improved from averages of 36% to 47%. Path following throughput improved from averages of 0.31 to 0.83 bits/s and decreased to 0.53 bits/s with more difficult tasks. Learning curves support the notion that the tongue can rapidly learn novel motor tasks. Typing and pointing performance of the tongue-computer interface is comparable to performances of other proficient assistive devices, which makes the tongue a feasible input organ for computer control. Intra-oral computer interfaces could provide individuals with severe upper-limb mobility impairments the opportunity to control computers and automatic equipment. Typing and pointing performance of the tongue-computer interface is comparable to performances of other proficient assistive devices, but does not cause fatigue easily and might be invisible to other people, which is highly prioritized by assistive device users. Combination of visual and auditory feedback is vital for a good performance of an intra-oral computer interface and helps to reduce involuntary or erroneous activations.

Diminished Neural Adaptation during Implicit Learning in Autism

PubMed Central

Schipul, Sarah E.; Just, Marcel Adam

2015-01-01

Neuroimaging studies have shown evidence of disrupted neural adaptation during learning in individuals with autism spectrum disorder (ASD) in several types of tasks, potentially stemming from frontal-posterior cortical underconnectivity (Schipul et al., 2012). The aim of the current study was to examine neural adaptations in an implicit learning task that entails participation of frontal and posterior regions. Sixteen high-functioning adults with ASD and sixteen neurotypical control participants were trained on and performed an implicit dot pattern prototype learning task in a functional magnetic resonance imaging (fMRI) session. During the preliminary exposure to the type of implicit prototype learning task later to be used in the scanner, the ASD participants took longer than the neurotypical group to learn the task, demonstrating altered implicit learning in ASD. After equating task structure learning, the two groups’ brain activation differed during their learning of a new prototype in the subsequent scanning session. The main findings indicated that neural adaptations in a distributed task network were reduced in the ASD group, relative to the neurotypical group, and were related to ASD symptom severity. Functional connectivity was reduced and did not change as much during learning for the ASD group, and was related to ASD symptom severity. These findings suggest that individuals with ASD show altered neural adaptations during learning, as seen in both activation and functional connectivity measures. This finding suggests why many real-world implicit learning situations may pose special challenges for ASD. PMID:26484826

[Effects of nano-selenium on the capability of learning memory and the activity of Se-protein of mice].

PubMed

Qin, Fenju; Ye, Yaxin; Yao, Xuemei

2008-07-01

To investigate the effects of Nano-Selenium on learning memory capability and activity of two kinds of Se-protein in brain and liver of mice, Na, SeO3 as the controls. The mice were administred two kinds of origin (doses of 1 microgSe/d, 2 microgSe/d, 4 microgSe/d) Se by intra-gastric injection respectively. The learning memory ability of the mice was measured by Y-type maze test. Activities of glutathione peroxidase (GSH-Px) and iodothyronine deiodinase (ID) in brain and liver were also measured. In comparison with the control groups of Na2 Se03, learning memory abilities were improved and activities of ID and GSH-Px (P < 0.01 or P < 0.05) of brain and liver were increased in Nano-Se treatment groups. Nano-Se could improve learning memory ability of mice, and enhance ID and GSH-Px activities of brain and liver in mice.

Documenting Student Learning in Music Performance: A Framework

ERIC Educational Resources Information Center

Wesolowski, Brian

2014-01-01

A fundamental aim of the Race to the Top agenda is to assess the effectiveness of teachers based on value-added growth measurement models of student achievement. However, in nontested grades and subject areas, such as music, alternative assessment types are being considered, including district-, school-, or teacher-developed measures. This article…

Gaseous Detonation-Driven Fracture of Tubes

DTIC Science & Technology

2004-03-01

understanding, in addition to leading to safer piping system design in nuclear power plants, can also assist accident investigators in learning what type...load, there are derived expressions in the literature from which one can learn about some essential features of mode I dynamic fracture. For a...along a 0.2-mm deep longitudinal groove. Pressure histories were measured by pressure transducers mounted inside the tube, axial and circumferen- tial

Measuring preschool learning engagement in the laboratory.

PubMed

Halliday, Simone E; Calkins, Susan D; Leerkes, Esther M

2018-03-01

Learning engagement is a critical factor for academic achievement and successful school transitioning. However, current methods of assessing learning engagement in young children are limited to teacher report or classroom observation, which may limit the types of research questions one could assess about this construct. The current study investigated the validity of a novel assessment designed to measure behavioral learning engagement among young children in a standardized laboratory setting and examined how learning engagement in the laboratory relates to future classroom adjustment. Preschool-aged children (N = 278) participated in a learning-based Tangrams task and Story sequencing task and were observed based on seven behavioral indicators of engagement. Confirmatory factor analysis supported the construct validity for a behavioral engagement factor composed of six of the original behavioral indicators: attention to instructions, on-task behavior, enthusiasm/energy, persistence, monitoring progress/strategy use, and negative affect. Concurrent validity for this behavioral engagement factor was established through its associations with parent-reported mastery motivation and pre-academic skills in math and literacy measured in the laboratory, and predictive validity was demonstrated through its associations with teacher-reported classroom learning behaviors and performance in math and reading in kindergarten. These associations were found when behavioral engagement was observed during both the nonverbal task and the verbal story sequencing tasks and persisted even after controlling for child minority status, gender, and maternal education. Learning engagement in preschool appears to be successfully measurable in a laboratory setting. This finding has implications for future research on the mechanisms that support successful academic development. Copyright © 2017 Elsevier Inc. All rights reserved.

Online neural monitoring of statistical learning.

PubMed

Batterink, Laura J; Paller, Ken A

2017-05-01

The extraction of patterns in the environment plays a critical role in many types of human learning, from motor skills to language acquisition. This process is known as statistical learning. Here we propose that statistical learning has two dissociable components: (1) perceptual binding of individual stimulus units into integrated composites and (2) storing those integrated representations for later use. Statistical learning is typically assessed using post-learning tasks, such that the two components are conflated. Our goal was to characterize the online perceptual component of statistical learning. Participants were exposed to a structured stream of repeating trisyllabic nonsense words and a random syllable stream. Online learning was indexed by an EEG-based measure that quantified neural entrainment at the frequency of the repeating words relative to that of individual syllables. Statistical learning was subsequently assessed using conventional measures in an explicit rating task and a reaction-time task. In the structured stream, neural entrainment to trisyllabic words was higher than in the random stream, increased as a function of exposure to track the progression of learning, and predicted performance on the reaction time (RT) task. These results demonstrate that monitoring this critical component of learning via rhythmic EEG entrainment reveals a gradual acquisition of knowledge whereby novel stimulus sequences are transformed into familiar composites. This online perceptual transformation is a critical component of learning. Copyright © 2017 Elsevier Ltd. All rights reserved.

Genetic deletion of CB1 receptors improves non-associative learning.

PubMed

Degroot, Aldemar; Salhoff, Craig; Davis, Richard J; Nomikos, George G

2005-07-01

Habituation (a form of non-associative learning) was measured by assessing locomotion in novel activity monitors in CB1 receptor knockout mice and juxtaposed to habituation measured in muscarinic M2, M4, and double M2/M4 receptor knockout mice. M2 and M2/M4, but not M4, receptor knockout mice appeared to have an impaired ability to habituate, whereas CB1 receptor knockout mice showed enhanced habituation compared to wild-type animals. We conclude that CB1 receptor gene invalidation improves habituation tentatively through an increase in cholinergic neurotransmission.

Identification of Type 2 Diabetes Risk Factors Using Phenotypes Consisting of Anthropometry and Triglycerides based on Machine Learning.

PubMed

Lee, Bum Ju; Kim, Jong Yeol

2016-01-01

The hypertriglyceridemic waist (HW) phenotype is strongly associated with type 2 diabetes; however, to date, no study has assessed the predictive power of phenotypes based on individual anthropometric measurements and triglyceride (TG) levels. The aims of the present study were to assess the association between the HW phenotype and type 2 diabetes in Korean adults and to evaluate the predictive power of various phenotypes consisting of combinations of individual anthropometric measurements and TG levels. Between November 2006 and August 2013, 11,937 subjects participated in this retrospective cross-sectional study. We measured fasting plasma glucose and TG levels and performed anthropometric measurements. We employed binary logistic regression (LR) to examine statistically significant differences between normal subjects and those with type 2 diabetes using HW and individual anthropometric measurements. For more reliable prediction results, two machine learning algorithms, naive Bayes (NB) and LR, were used to evaluate the predictive power of various phenotypes. All prediction experiments were performed using a tenfold cross validation method. Among all of the variables, the presence of HW was most strongly associated with type 2 diabetes (p < 0.001, adjusted odds ratio (OR) = 2.07 [95% CI, 1.72-2.49] in men; p < 0.001, adjusted OR = 2.09 [1.79-2.45] in women). When comparing waist circumference (WC) and TG levels as components of the HW phenotype, the association between WC and type 2 diabetes was greater than the association between TG and type 2 diabetes. The phenotypes tended to have higher predictive power in women than in men. Among the phenotypes, the best predictors of type 2 diabetes were waist-to-hip ratio + TG in men (AUC by NB = 0.653, AUC by LR = 0.661) and rib-to-hip ratio + TG in women (AUC by NB = 0.73, AUC by LR = 0.735). Although the presence of HW demonstrated the strongest association with type 2 diabetes, the predictive power of the combined measurements of the actual WC and TG values may not be the best manner of predicting type 2 diabetes. Our findings may provide clinical information concerning the development of clinical decision support systems for the initial screening of type 2 diabetes.

Developing and feasibility testing of data collection methods for an economic evaluation of a supported selfmanagement programme for adults with a learning disability and type 2 diabetes.

PubMed

O'Dwyer, John L; Russell, Amy M; Bryant, Louise D; Walwyn, Rebecca E A; Wright-Hughes, Alexandra M; Graham, Elizabeth H; Wright, Judy M; Meer, Shaista; Birtwistle, Jacqueline; Farrin, Amanda J; House, Allan O; Hulme, Claire T

2018-01-01

The challenges of conducting research with hard to reach vulnerable groups are particularly pertinent for people with learning disabilities. Data collection methods for previous cost and cost-effectiveness analyses of health and social care interventions targeting people with learning disabilities have relied on health care/health insurance records or data collection forms completed by the service provider rather than by people with learning disabilities themselves. This paper reports on the development and testing of data collection methods for an economic evaluation within a randomised controlled trial (RCT) for a supported self-management programme for people with mild/moderate learning disabilities and type 2 diabetes. A case finding study was conducted to identify types of health and social care use and data collection methods employed in previous studies with this population. Based on this evidence, resource use questionnaires for completion by GP staff and interviewer-administered participant questionnaires (covering a wider cost perspective and health-related quality of life) were tested within a feasibility RCT. Interviewer-administered questionnaires included the EQ-5D-3L (the NICE recommended measure for use in economic evaluation). Participants were adults > 18 years with a mild or moderate learning disability and type 2 diabetes, with mental capacity to give consent to research participation. Data collection for questionnaires completed by GP staff requesting data for the last 12 months proved time intensive and difficult. Whilst 82.3% (121/147) of questionnaires were returned, up to 17% of service use items were recorded as unknown. Subsequently, a shorter recall period (4 months) led to a higher return rate but with a higher rate of missing data. Missing data for interviewer-administered participant questionnaires was > 8% but the interviewers reported difficulty with participant recall. Almost 60% (48/80) of participants had difficulty completing the EQ-5D-3L. Further investigation as to how service use can be recorded is recommended. Concerns about the reliability of identifying service use data directly from participants with a learning disability due to challenges in completion, specifically around recall, remain. The degree of difficulty to complete EQ-5D-3L indicates concerns regarding the appropriateness of using this measure in its current form in research with this population. Current Controlled Trials ISRCTN41897033 (registered 21 January 2013).

Longitudinal measures of cognition in the Ts65Dn mouse: refining windows and defining modalities for therapeutic intervention in Down syndrome

PubMed Central

Olmos-Serrano, J. Luis; Tyler, William A.; Cabral, Howard J.; Haydar, Tarik F.

2016-01-01

Mouse models have provided insights into adult changes in learning and memory in Down syndrome, but an in-depth assessment of how these abnormalities develop over time has never been conducted. To address this shortcoming, we conducted a longitudinal behavioral study from birth until late adulthood in the Ts65Dn mouse model to measure the emergence and continuity of learning and memory deficits in individuals with a broad array of tests. Our results demonstrate for the first time that the pace at which neonatal and perinatal milestones are acquired is correlated with later cognitive performance as an adult. In addition, we find that lifelong behavioral indexing stratifies mice within each genotype. Our expanded assessment reveals that diminished cognitive flexibility, as measured by reversal learning, is the most robust learning and memory impairment in both young and old Ts65Dn mice. Moreover, we find that reversal learning degrades with age and is therefore a useful biomarker for studying age-related decline in cognitive ability. Altogether, our results indicate that preclinical studies aiming to restore cognitive function in Ts65Dn should target both neonatal milestones and reversal learning in adulthood. Here we provide the quantitative framework for this type of approach. PMID:26854932

Aging does not affect generalized postural motor learning in response to variable amplitude oscillations of the support surface.

PubMed

Van Ooteghem, Karen; Frank, James S; Allard, Fran; Horak, Fay B

2010-08-01

Postural motor learning for dynamic balance tasks has been demonstrated in healthy older adults (Van Ooteghem et al. in Exp Brain Res 199(2):185-193, 2009). The purpose of this study was to investigate the type of knowledge (general or specific) obtained with balance training in this age group and to examine whether embedding perturbation regularities within a balance task masks specific learning. Two groups of older adults maintained balance on a translating platform that oscillated with variable amplitude and constant frequency. One group was trained using an embedded-sequence (ES) protocol which contained the same 15-s sequence of variable amplitude oscillations in the middle of each trial. A second group was trained using a looped-sequence (LS) protocol which contained a 15-s sequence repeated three times to form each trial. All trials were 45 s. Participants were not informed of any repetition. To examine learning, participants performed a retention test following a 24-h delay. LS participants also completed a transfer task. Specificity of learning was examined by comparing performance for repeated versus random sequences (ES) and training versus transfer sequences (LS). Performance was measured by deriving spatial and temporal measures of whole body center of mass (COM) and trunk orientation. Both groups improved performance with practice as characterized by reduced COM displacement, improved COM-platform phase relationships, and decreased angular trunk motion. Furthermore, improvements reflected general rather than specific postural motor learning regardless of training protocol (ES or LS). This finding is similar to young adults (Van Ooteghem et al. in Exp Brain Res 187(4):603-611, 2008) and indicates that age does not influence the type of learning which occurs for balance control.

Predicting explorative motor learning using decision-making and motor noise.

PubMed

Chen, Xiuli; Mohr, Kieran; Galea, Joseph M

2017-04-01

A fundamental problem faced by humans is learning to select motor actions based on noisy sensory information and incomplete knowledge of the world. Recently, a number of authors have asked whether this type of motor learning problem might be very similar to a range of higher-level decision-making problems. If so, participant behaviour on a high-level decision-making task could be predictive of their performance during a motor learning task. To investigate this question, we studied performance during an explorative motor learning task and a decision-making task which had a similar underlying structure with the exception that it was not subject to motor (execution) noise. We also collected an independent measurement of each participant's level of motor noise. Our analysis showed that explorative motor learning and decision-making could be modelled as the (approximately) optimal solution to a Partially Observable Markov Decision Process bounded by noisy neural information processing. The model was able to predict participant performance in motor learning by using parameters estimated from the decision-making task and the separate motor noise measurement. This suggests that explorative motor learning can be formalised as a sequential decision-making process that is adjusted for motor noise, and raises interesting questions regarding the neural origin of explorative motor learning.

Predicting explorative motor learning using decision-making and motor noise

PubMed Central

Galea, Joseph M.

2017-01-01

A fundamental problem faced by humans is learning to select motor actions based on noisy sensory information and incomplete knowledge of the world. Recently, a number of authors have asked whether this type of motor learning problem might be very similar to a range of higher-level decision-making problems. If so, participant behaviour on a high-level decision-making task could be predictive of their performance during a motor learning task. To investigate this question, we studied performance during an explorative motor learning task and a decision-making task which had a similar underlying structure with the exception that it was not subject to motor (execution) noise. We also collected an independent measurement of each participant’s level of motor noise. Our analysis showed that explorative motor learning and decision-making could be modelled as the (approximately) optimal solution to a Partially Observable Markov Decision Process bounded by noisy neural information processing. The model was able to predict participant performance in motor learning by using parameters estimated from the decision-making task and the separate motor noise measurement. This suggests that explorative motor learning can be formalised as a sequential decision-making process that is adjusted for motor noise, and raises interesting questions regarding the neural origin of explorative motor learning. PMID:28437451

Developing an instrument to measure emotional behaviour abilities of meaningful learning through the Delphi technique.

PubMed

Cadorin, Lucia; Bagnasco, Annamaria; Tolotti, Angela; Pagnucci, Nicola; Sasso, Loredana

2017-09-01

To identify items for a new instrument that measures emotional behaviour abilities of meaningful learning, according to Fink's Taxonomy. Meaningful learning is an active process that promotes a wider and deeper understanding of concepts. It is the result of an interaction between new and previous knowledge and produces a long-term change of knowledge and skills. To measure meaningful learning capability, it is very important in the education of health professionals to identify problems or special learning needs. For this reason, it is necessary to create valid instruments. A Delphi Study technique was implemented in four phases by means of e-mail. The study was conducted from April-September 2015. An expert panel consisting of ten researchers with experience in Fink's Taxonomy was established to identify the items of the instrument. Data were analysed for conceptual description and item characteristics and attributes were rated. Expert consensus was sought in each of these phases. An 87·5% consensus cut-off was established. After four rounds, consensus was obtained for validation of the content of the instrument 'Assessment of Meaningful learning Behavioural and Emotional Abilities'. This instrument consists of 56 items evaluated on a 6-point Likert-type scale. Foundational Knowledge, Application, Integration, Human Dimension, Caring and Learning How to Learn were the six major categories explored. This content validated tool can help educators (teachers, trainers and tutors) to identify and improve the strategies to support students' learning capability, which could increase their awareness of and/or responsibility in the learning process. © 2017 John Wiley & Sons Ltd.

How Differences among Data Collectors Are Reflected in the Reliability and Validity of Data Collected by Likert-Type Scales?

ERIC Educational Resources Information Center

Köksal, Mustafa Serdar; Ertekin, Pelin; Çolakoglu, Özgür Murat

2014-01-01

The purpose of this study is to investigate association of data collectors' differences with the differences in reliability and validity of scores regarding affective variables (motivation toward science learning and science attitude) that are measured by Likert-type scales. Four researchers trained in data collection and seven science teachers…

Teaching graphic symbol combinations to children with limited speech during shared story reading.

PubMed

Tönsing, Kerstin M; Dada, Shakila; Alant, Erna

2014-12-01

The aim of this study was to determine the effect of an intervention strategy on the production of graphic symbol combinations in children with limited speech. Four children between the ages of 6;5 and 10;8 (years;months) with limited speech participated in the study. A single-subject, multiple probe design across three different types of semantic relations was used. Generalization to untrained exemplars was also monitored. Results were mixed across the four participants: two participants learned to combine symbols across different types of relations, maintained these skills post intervention, and generalized their skills to untrained combinations; and two participants showed less consistent evidence of learning. The effects, as measured during structured probes, were strong for one participant, moderate for another, and inconclusive for the two others. Responses during shared story reading suggested that the measurement probes might have underestimated participants' ability to combine symbols.

Validity of Cognitive Load Measures in Simulation-Based Training: A Systematic Review.

PubMed

Naismith, Laura M; Cavalcanti, Rodrigo B

2015-11-01

Cognitive load theory (CLT) provides a rich framework to inform instructional design. Despite the applicability of CLT to simulation-based medical training, findings from multimedia learning have not been consistently replicated in this context. This lack of transferability may be related to issues in measuring cognitive load (CL) during simulation. The authors conducted a review of CLT studies across simulation training contexts to assess the validity evidence for different CL measures. PRISMA standards were followed. For 48 studies selected from a search of MEDLINE, EMBASE, PsycInfo, CINAHL, and ERIC databases, information was extracted about study aims, methods, validity evidence of measures, and findings. Studies were categorized on the basis of findings and prevalence of validity evidence collected, and statistical comparisons between measurement types and research domains were pursued. CL during simulation training has been measured in diverse populations including medical trainees, pilots, and university students. Most studies (71%; 34) used self-report measures; others included secondary task performance, physiological indices, and observer ratings. Correlations between CL and learning varied from positive to negative. Overall validity evidence for CL measures was low (mean score 1.55/5). Studies reporting greater validity evidence were more likely to report that high CL impaired learning. The authors found evidence that inconsistent correlations between CL and learning may be related to issues of validity in CL measures. Further research would benefit from rigorous documentation of validity and from triangulating measures of CL. This can better inform CLT instructional design for simulation-based medical training.

The Effect of Hearing Loss on Novel Word Learning in Infant- and Adult-Directed Speech.

PubMed

Robertson, V Susie; von Hapsburg, Deborah; Hay, Jessica S

Relatively little is known about how young children with hearing impairment (HI) learn novel words in infant- and adult-directed speech (ADS). Infant-directed speech (IDS) supports word learning in typically developing infants relative to ADS. This study examined how children with normal hearing (NH) and children with HI learn novel words in IDS and ADS. It was predicted that IDS would support novel word learning in both groups of children. In addition, children with HI were expected to be less proficient word learners as compared with their NH peers. A looking-while-listening paradigm was used to measure novel word learning in 16 children with sensorineural HI (age range 23.2 to 42.1 months) who wore either bilateral hearing aids (n = 10) or bilateral cochlear implants (n = 6) and 16 children with NH (age range 23.1 to 42.1 months) who were matched for gender, chronological age, and maternal education level. Two measures of word learning were assessed (accuracy and reaction time). Each child participated in two experiments approximately 1 week apart, one in IDS and one in ADS. Both groups successfully learned the novel words in both speech type conditions, as evidenced by children looking at the correct picture significantly above chance. As a group, children with NH outperformed children with HI in the novel word learning task; however, there were no significant differences between performance on IDS versus ADS. More fine-grained time course analyses revealed that children with HI, and particularly children who use hearing aids, had more difficulty learning novel words in ADS, compared with children with NH. The pattern of results observed in the children with HI suggests that they may need extended support from clinicians and caregivers, through the use of IDS, during novel word learning. Future research should continue to focus on understanding the factors (e.g., device type and use, age of intervention, audibility, acoustic characteristics of input, etc.) that may influence word learning in children with HI in both IDS and ADS.

Refining Markov state models for conformational dynamics using ensemble-averaged data and time-series trajectories

NASA Astrophysics Data System (ADS)

Matsunaga, Y.; Sugita, Y.

2018-06-01

A data-driven modeling scheme is proposed for conformational dynamics of biomolecules based on molecular dynamics (MD) simulations and experimental measurements. In this scheme, an initial Markov State Model (MSM) is constructed from MD simulation trajectories, and then, the MSM parameters are refined using experimental measurements through machine learning techniques. The second step can reduce the bias of MD simulation results due to inaccurate force-field parameters. Either time-series trajectories or ensemble-averaged data are available as a training data set in the scheme. Using a coarse-grained model of a dye-labeled polyproline-20, we compare the performance of machine learning estimations from the two types of training data sets. Machine learning from time-series data could provide the equilibrium populations of conformational states as well as their transition probabilities. It estimates hidden conformational states in more robust ways compared to that from ensemble-averaged data although there are limitations in estimating the transition probabilities between minor states. We discuss how to use the machine learning scheme for various experimental measurements including single-molecule time-series trajectories.

Dependent Measure and Time Constraints Modulate the Competition between Conflicting Feature-Based and Rule-Based Generalization Processes

ERIC Educational Resources Information Center

Cobos, Pedro L.; Gutiérrez-Cobo, María J.; Morís, Joaquín; Luque, David

2017-01-01

In our study, we tested the hypothesis that feature-based and rule-based generalization involve different types of processes that may affect each other producing different results depending on time constraints and on how generalization is measured. For this purpose, participants in our experiments learned cue-outcome relationships that followed…

Teaching Assessment of Classroom Learning: Using Scenarios To Teach Basic Tests and Measurement Concepts.

ERIC Educational Resources Information Center

Cochran, H. Keith

This paper contains two scenario-type assignments for students in a university tests and measurements class as well as a collection of materials developed by actual students in response to these assignments. An opening explanation argues that education students, often nearing the end of their program when they take the tests and measurement…

A Study of the Relationships among Learning Styles, Participation Types, and Performance in Programming Language Learning Supported by Online Forums

ERIC Educational Resources Information Center

Shaw, Ruey-Shiang

2012-01-01

This study is focused on the relationships among learning styles, participation types, and learning performance for programming language learning supported by an online forum. Kolb's learning style inventory was used in this study to determine a learner's learning type: "Diverger", "Assimilator", "Converger", and "Accommodator". Social Learning…

Distinguishing Service Learning from Other Types of Experiential Learning

ERIC Educational Resources Information Center

Lim, Sook; Bloomquist, Catherine

2015-01-01

This discussion paper examines the lack of clarity surrounding the term "service learning" in the library and information science (LIS) literature, which frequently conflates service learning with other types of experiential learning. We suggest that the lack of distinction between service learning and other types of experiential…

The many facets of motor learning and their relevance for Parkinson's disease.

PubMed

Marinelli, Lucio; Quartarone, Angelo; Hallett, Mark; Frazzitta, Giuseppe; Ghilardi, Maria Felice

2017-07-01

The final goal of motor learning, a complex process that includes both implicit and explicit (or declarative) components, is the optimization and automatization of motor skills. Motor learning involves different neural networks and neurotransmitters systems depending on the type of task and on the stage of learning. After the first phase of acquisition, a motor skill goes through consolidation (i.e., becoming resistant to interference) and retention, processes in which sleep and long-term potentiation seem to play important roles. The studies of motor learning in Parkinson's disease have yielded controversial results that likely stem from the use of different experimental paradigms. When a task's characteristics, instructions, context, learning phase and type of measures are taken into consideration, it is apparent that, in general, only learning that relies on attentional resources and cognitive strategies is affected by PD, in agreement with the finding of a fronto-striatal deficit in this disease. Levodopa administration does not seem to reverse the learning deficits in PD, while deep brain stimulation of either globus pallidus or subthalamic nucleus appears to be beneficial. Finally and most importantly, patients with PD often show a decrease in retention of newly learned skill, a problem that is present even in the early stages of the disease. A thorough dissection and understanding of the processes involved in motor learning is warranted to provide solid bases for effective medical, surgical and rehabilitative approaches in PD. Copyright © 2017 International Federation of Clinical Neurophysiology. All rights reserved.

Knowledge Management: An Introduction.

ERIC Educational Resources Information Center

Mac Morrow, Noreen

2001-01-01

Discusses issues related to knowledge management and organizational knowledge. Highlights include types of knowledge; the knowledge economy; intellectual capital; knowledge and learning organizations; knowledge management strategies and processes; organizational culture; the role of technology; measuring knowledge; and the role of the information…

A cross-sectional study of paramedics' readiness for interprofessional learning and cooperation: results from five universities.

PubMed

Williams, Brett; Boyle, Malcolm; Brightwell, Richard; McCall, Michael; McMullen, Paula; Munro, Graham; O'Meara, Peter; Webb, Vanessa

2013-11-01

Healthcare systems are evolving to feature the promotion of interprofessional practice more prominently. The development of successful and functional interprofessional practice is best achieved through interprofessional learning. Given that most paramedic programmes take an isolative uni-professional educational approach to their healthcare undergraduate courses, serious questions must be raised as to whether students are being adequately prepared for the interprofessional healthcare workplace. The objective of this study was to assess the attitudes of paramedic students towards interprofessional learning across five Australian universities. Using a convenience sample of paramedic student attitudes towards interprofessional learning and cooperation were measured using two standardised self-reporting instruments: Readiness for Interprofessional Learning Scale (RIPLS) and Interdisciplinary Education Perception Scale (IEPS). Students' readiness for interprofessional learning did not appear to be significantly influenced by their gender nor the type of paramedic degree they were undertaking. As students progressed through their degrees their appreciation for collaborative teamwork and their understanding of paramedic identity grew, however this appeared to negatively affect their willingness to engage in interprofessional learning with other healthcare students. The tertiary institute attended also appeared to influence students' preparedness and attitudes to shared learning. This study has found no compelling evidence that students' readiness for interprofessional learning is significantly affected by either their gender or the type of degree undertaken. By contrast it was seen that the tertiary institutions involved in this study produced students at different levels of preparedness for IPL and cooperation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Assessing Student Behaviors and Motivation for Actively Learning Biology

NASA Astrophysics Data System (ADS)

Moore, Michael Edward

Vision and Change states that one of the major changes in the way we design biology courses should be a switch in approach from teacher-centered learning to student-centered learning and identifies active learning as a recommended methods. Studies show performance benefits for students taking courses that use active learning. What is unknown is why active learning is such an effective instructional tool and the limits of this instructional method’s ability to influence performance. This dissertation builds a case in three steps for why active learning is an effective instructional tool. In step one, I assessed the influence of different types of active learning (clickers, group activities, and whole class discussions) on student engagement behavior in one semester of two different introductory biology courses and found that active learning positively influenced student engagement behavior significantly more than lecture. For step two, I examined over four semesters whether student engagement behavior was a predictor of performance and found participation (engagement behavior) in the online (video watching) and in-class course activities (clicker participation) that I measure were significant predictors of performance. In the third, I assessed whether certain active learning satisfied the psychological needs that lead to students’ intrinsic motivation to participate in those activities when compared over two semesters and across two different institutions of higher learning. Findings from this last step show us that student’s perceptions of autonomy, competency, and relatedness in doing various types of active learning are significantly higher than lecture and consistent across two institutions of higher learning. Lastly, I tie everything together, discuss implications of the research, and address future directions for research on biology student motivation and behavior.

Selection and Use of Online Learning Resources by First-Year Medical Students: Cross-Sectional Study

PubMed Central

Elliott, Kristine

2017-01-01

Background Medical students have access to a wide range of learning resources, many of which have been specifically developed for or identified and recommended to them by curriculum developers or teaching staff. There is an expectation that students will access and use these resources to support their self-directed learning. However, medical educators lack detailed and reliable data about which of these resources students use to support their learning and how this use relates to key learning events or activities. Objective The purpose of this study was to comprehensively document first-year medical student selection and use of online learning resources to support their bioscience learning within a case-based curriculum and assess these data in relation to our expectations of student learning resource requirements and use. Methods Study data were drawn from 2 sources: a survey of student learning resource selection and use (2013 cohort; n=326) and access logs from the medical school learning platform (2012 cohort; n=337). The paper-based survey, which was distributed to all first-year students, was designed to assess the frequency and types of online learning resources accessed by students and included items about their perceptions of the usefulness, quality, and reliability of various resource types and sources. Of 237 surveys returned, 118 complete responses were analyzed (36.2% response rate). Usage logs from the learning platform for an entire semester were processed to provide estimates of first-year student resource use on an individual and cohort-wide basis according to method of access, resource type, and learning event. Results According to the survey data, students accessed learning resources via the learning platform several times per week on average, slightly more often than they did for resources from other online sources. Google and Wikipedia were the most frequently used nonuniversity sites, while scholarly information sites (eg, online journals and scholarly databases) were accessed relatively infrequently. Students were more likely to select learning resources based on the recommendation of peers than of teaching staff. The overwhelming majority of the approximately 70,000 resources accessed by students via the learning platform were lecture notes, with each accessed an average of 167 times. By comparison, recommended journal articles and (online) textbook chapters were accessed only 49 and 31 times, respectively. The number and type of learning resources accessed by students through the learning platform was highly variable, with a cluster analysis revealing that a quarter of students accessed very few resources in this way. Conclusions Medical students have easy access to a wide range of quality learning resources, and while some make good use of the learning resources recommended to them, many ignore most and access the remaining ones infrequently. Learning analytics can provide useful measures of student resource access through university learning platforms but fails to account for resources accessed via external online sources or sharing of resources using social media. PMID:28970187

Identifying residential neighbourhood types from settlement points in a machine learning approach.

PubMed

Jochem, Warren C; Bird, Tomas J; Tatem, Andrew J

2018-05-01

Remote sensing techniques are now commonly applied to map and monitor urban land uses to measure growth and to assist with development and planning. Recent work in this area has highlighted the use of textures and other spatial features that can be measured in very high spatial resolution imagery. Far less attention has been given to using geospatial vector data (i.e. points, lines, polygons) to map land uses. This paper presents an approach to distinguish residential settlement types (regular vs. irregular) using an existing database of settlement points locating structures. Nine data features describing the density, distance, angles, and spacing of the settlement points are calculated at multiple spatial scales. These data are analysed alone and with five common remote sensing measures on elevation, slope, vegetation, and nighttime lights in a supervised machine learning approach to classify land use areas. The method was tested in seven provinces of Afghanistan (Balkh, Helmand, Herat, Kabul, Kandahar, Kunduz, Nangarhar). Overall accuracy ranged from 78% in Kandahar to 90% in Nangarhar. This research demonstrates the potential to accurately map land uses from even the simplest representation of structures.

How does beneficiary knowledge of the Medicare program vary by type of insurance?

PubMed

McCormack, Lauren A; Uhrig, Jennifer D

2003-08-01

Prior research found that Medicare beneficiaries' knowledge of the Medicare program varied by the type of supplemental insurance they had. However, none of these studies used both multivariate methods and nationally representative data to examine the issue. OBJECTIVES To measure beneficiary knowledge of the Medicare program and to evaluate how knowledge varies by type of supplemental insurance. A mail survey with telephone follow-up to a nationally representative random sample of Medicare beneficiaries, which had a 76% response rate. The purpose of the study was to evaluate the effects of providing the Medicare & You handbook on beneficiary knowledge, information needs, and health plan decision making. A total of 3738 Medicare beneficiaries who completed the survey. A psychometrically validated 22-item index that reflects Medicare-related knowledge in seven different content areas. RESULTS Overall, beneficiaries with a Medicare HMO or non-employer-sponsored supplemental insurance were more knowledgeable about Medicare than those who had Medicare only. In general, beneficiaries tended to be more knowledgeable about issues related to the type of insurance they had (fee-for-service or managed care) than other types of insurance. Higher levels of knowledge about one's own type of insurance may suggest that beneficiaries learn by experience or they learn more about that type of insurance before enrollment. Further research is needed to better understand how and when beneficiaries learn about insurance and what educational strategies are more effective at increasing knowledge.

Longitudinal measures of cognition in the Ts65Dn mouse: Refining windows and defining modalities for therapeutic intervention in Down syndrome.

PubMed

Olmos-Serrano, J Luis; Tyler, William A; Cabral, Howard J; Haydar, Tarik F

2016-05-01

Mouse models have provided insights into adult changes in learning and memory in Down syndrome, but an in-depth assessment of how these abnormalities develop over time has never been conducted. To address this shortcoming, we conducted a longitudinal behavioral study from birth until late adulthood in the Ts65Dn mouse model to measure the emergence and continuity of learning and memory deficits in individuals with a broad array of tests. Our results demonstrate for the first time that the pace at which neonatal and perinatal milestones are acquired is correlated with later cognitive performance as an adult. In addition, we find that life-long behavioral indexing stratifies mice within each genotype. Our expanded assessment reveals that diminished cognitive flexibility, as measured by reversal learning, is the most robust learning and memory impairment in both young and old Ts65Dn mice. Moreover, we find that reversal learning degrades with age and is therefore a useful biomarker for studying age-related decline in cognitive ability. Altogether, our results indicate that preclinical studies aiming to restore cognitive function in Ts65Dn should target both neonatal milestones and reversal learning in adulthood. Here we provide the quantitative framework for this type of approach. Copyright © 2016 Elsevier Inc. All rights reserved.

[Long-term effect of a cognitive intervention on learning and participation in a significant leisure activity in early dementia of Alzheimer type: a case study].

PubMed

Provencher, Véronique; Bier, Nathalie; Audet, Thérèse; Gagnon, Lise

2009-06-01

Decreased ability to accomplish significant leisure activities often occurs in early stages of dementia of Alzheimer type (DAT). As a long term effect, it may eventually affect the quality of life of the patient as well as that of the caregiver's. In a previous study, a woman with early DAT (77 years old, MMSE: 24/30) improved her participation in 2 leisure activities (listening to music and praying in a group) following the learning of a few tasks (e.g. using a radio cassette, remembering the significance of an pre-programmed ring) as a result of a cognitive intervention. The present study presents the long term effect of this intervention on the retention of the learned tasks and on spontaneous participation in both leisure activities of her daily living. Measures of tasks' learning and spontaneous participation in activities have been obtained through direct observation (ex: ability to use the tasks learned without assistance) and telephone conversations with the caregiver. The measures were taken 9 to 15 months post-intervention. Nine months after the end of the intervention, the participant could no longer use the radio cassette, but was able to remember the significance of the pre-programmed ring. Similarly, she stopped listening to music, but still attended her prayer group. The intervention appears to maintain participation in a leisure activity for several months in a patient with early DAT, in spite of expected functional decline. This functional impact can be achieved through retention of specific learned tasks as well as by strong external cues (daily pre-programmed ring), and can increase the quality of life for patients with DAT.

Development and Validation of Two Instruments Measuring Intrinsic, Extraneous, and Germane Cognitive Load.

PubMed

Klepsch, Melina; Schmitz, Florian; Seufert, Tina

2017-01-01

Cognitive Load Theory is one of the most powerful research frameworks in educational research. Beside theoretical discussions about the conceptual parts of cognitive load, the main challenge within this framework is that there is still no measurement instrument for the different aspects of cognitive load, namely intrinsic, extraneous, and germane cognitive load. Hence, the goal of this paper is to develop a differentiated measurement of cognitive load. In Study 1 ( N = 97), we developed and analyzed two strategies to measure cognitive load in a differentiated way: (1) Informed rating: We trained learners in differentiating the concepts of cognitive load, so that they could rate them in an informed way. They were asked then to rate 24 different learning situations or learning materials related to either high or low intrinsic, extraneous, or germane load. (2) Naïve rating: For this type of rating of cognitive load we developed a questionnaire with two to three items for each type of load. With this questionnaire, the same learning situations had to be rated. In the second study ( N = between 65 and 95 for each task), we improved the instrument for the naïve rating. For each study, we analyzed whether the instruments are reliable and valid, for Study 1, we also checked for comparability of the two measurement strategies. In Study 2, we conducted a simultaneous scenario based factor analysis. The informed rating seems to be a promising strategy to assess the different aspects of cognitive load, but it seems not economic and feasible for larger studies and a standardized training would be necessary. The improved version of the naïve rating turned out to be a useful, feasible, and reliable instrument. Ongoing studies analyze the conceptual validity of this measurement with up to now promising results.

The learning environment and resident burnout: a national study.

PubMed

van Vendeloo, Stefan N; Prins, David J; Verheyen, Cees C P M; Prins, Jelle T; van den Heijkant, Fleur; van der Heijden, Frank M M A; Brand, Paul L P

2018-04-01

Concerns exist about the negative impact of burnout on the professional and personal lives of residents. It is suggested that the origins of burnout among residents are rooted in the learning environment. We aimed to evaluate the association between the learning environment and burnout in a national sample of Dutch residents. We conducted a cross-sectional online survey among all Dutch residents in September 2015. We measured the learning environment using the three domain scores on content, organization, and atmosphere from the Scan of Postgraduate Educational Environment Domains (SPEED) and burnout using the Dutch version of the Maslach Burnout Inventory (UBOS-C). Of 1,231 responding residents (33 specialties), 185 (15.0%) met criteria for burnout. After adjusting for demographic (age, gender and marital status) and work-related factors (year of training, type of teaching hospital and type of specialty), we found a consistent inverse association between SPEED scores and the risk of burnout (aOR 0.54, 95% CI 0.46 to 0.62, p < 0.001). We found a strong and consistent inverse association between the perceived quality of the learning environment and burnout among residents. This suggests that the learning environment is of key importance in preventing resident burnout.

Effectiveness of Student's Note-Taking Activities and Characteristics of Their Learning Performance in Two Types of Online Learning

ERIC Educational Resources Information Center

Nakayama, Minoru; Mutsuura, Kouichi; Yamamoto, Hiroh

2017-01-01

Aspects of learning behavior during two types of university courses, a blended learning course and a fully online course, were examined using note-taking activity. The contribution of students' characteristics and styles of learning to note-taking activity and learning performance were analyzed, and the relationships between the two types of…

The relationships between trait anxiety, place recognition memory, and learning strategy.

PubMed

Hawley, Wayne R; Grissom, Elin M; Dohanich, Gary P

2011-01-20

Rodents learn to navigate mazes using various strategies that are governed by specific regions of the brain. The type of strategy used when learning to navigate a spatial environment is moderated by a number of factors including emotional states. Heightened anxiety states, induced by exposure to stressors or administration of anxiogenic agents, have been found to bias male rats toward the use of a striatum-based stimulus-response strategy rather than a hippocampus-based place strategy. However, no study has yet examined the relationship between natural anxiety levels, or trait anxiety, and the type of learning strategy used by rats on a dual-solution task. In the current experiment, levels of inherent anxiety were measured in an open field and compared to performance on two separate cognitive tasks, a Y-maze task that assessed place recognition memory, and a visible platform water maze task that assessed learning strategy. Results indicated that place recognition memory on the Y-maze correlated with the use of place learning strategy on the water maze. Furthermore, lower levels of trait anxiety correlated positively with better place recognition memory and with the preferred use of place learning strategy. Therefore, competency in place memory and bias in place strategy are linked to the levels of inherent anxiety in male rats. Copyright © 2010 Elsevier B.V. All rights reserved.

Do Science Teachers Distinguish Between Their own Learning and the Learning of Their Students?

NASA Astrophysics Data System (ADS)

Brauer, Heike; Wilde, Matthias

2018-02-01

Learning beliefs influence learning and teaching. For this reason, teachers and teacher educators need to be aware of them. To support students' knowledge construction, teachers must develop appropriate learning and teaching beliefs. Teachers appear to have difficulties when analysing students' learning. This seems to be due to the inability to differentiate the beliefs about their students' learning from those about their own learning. Both types of beliefs seem to be intertwined. This study focuses on whether pre-service teachers' beliefs about their own learning are identical to those about their students' learning. Using a sample of pre-service teachers, we measured general beliefs about "constructivist" and "transmissive" learning and science-specific beliefs about "connectivity" and "taking pre-concepts into account". We also analysed the development of these four beliefs during teacher professionalisation by comparing beginning and advanced pre-service teachers. Our results show that although pre-service teachers make the distinction between their own learning and the learning of their students for the general tenets of constructivist and transmissive learning, there is no significant difference for science-specific beliefs. The beliefs pre-service teachers hold about their students' science learning remain closely tied to their own.

Social intuition as a form of implicit learning: Sequences of body movements are learned less explicitly than letter sequences

PubMed Central

Norman, Elisabeth; Price, Mark C.

2012-01-01

In the current paper, we first evaluate the suitability of traditional serial reaction time (SRT) and artificial grammar learning (AGL) experiments for measuring implicit learning of social signals. We then report the results of a novel sequence learning task which combines aspects of the SRT and AGL paradigms to meet our suggested criteria for how implicit learning experiments can be adapted to increase their relevance to situations of social intuition. The sequences followed standard finite-state grammars. Sequence learning and consciousness of acquired knowledge were compared between 2 groups of 24 participants viewing either sequences of individually presented letters or sequences of body-posture pictures, which were described as series of yoga movements. Participants in both conditions showed above-chance classification accuracy, indicating that sequence learning had occurred in both stimulus conditions. This shows that sequence learning can still be found when learning procedures reflect the characteristics of social intuition. Rule awareness was measured using trial-by-trial evaluation of decision strategy (Dienes & Scott, 2005; Scott & Dienes, 2008). For letters, sequence classification was best on trials where participants reported responding on the basis of explicit rules or memory, indicating some explicit learning in this condition. For body-posture, classification was not above chance on these types of trial, but instead showed a trend to be best on those trials where participants reported that their responses were based on intuition, familiarity, or random choice, suggesting that learning was more implicit. Results therefore indicate that the use of traditional stimuli in research on sequence learning might underestimate the extent to which learning is implicit in domains such as social learning, contributing to ongoing debate about levels of conscious awareness in implicit learning. PMID:22679467

A mouse model of fragile X syndrome exhibits heightened arousal and/or emotion following errors or reversal of contingencies.

PubMed

Moon, J; Ota, K T; Driscoll, L L; Levitsky, D A; Strupp, B J

2008-07-01

This study was designed to further assess cognitive and affective functioning in a mouse model of Fragile X syndrome (FXS), the Fmr1(tm1Cgr) or Fmr1 "knockout" (KO) mouse. Male KO mice and wild-type littermate controls were tested on learning set and reversal learning tasks. The KO mice were not impaired in associative learning, transfer of learning, or reversal learning, based on measures of learning rate. Analyses of videotapes of the reversal learning task revealed that both groups of mice exhibited higher levels of activity and wall-climbing during the initial sessions of the task than during the final sessions, a pattern also seen for trials following an error relative to those following a correct response. Notably, the increase in both behavioral measures seen early in the task was significantly more pronounced for the KO mice than for controls, as was the error-induced increase in activity level. This pattern of effects suggests that the KO mice reacted more strongly than controls to the reversal of contingencies and pronounced drop in reinforcement rate, and to errors in general. This pattern of effects is consistent with the heightened emotional reactivity frequently described for humans with FXS. (c) 2008 Wiley Periodicals, Inc.

A Nationwide Learning-Style Assessment of Undergraduate Athletic Training Students in CAAHEP-Accredited Athletic Training Programs

PubMed Central

Stradley, Stephanie L.; Buckley, Bernadette D.; Kaminski, Thomas W.; Horodyski, MaryBeth; Fleming, David; Janelle, Christopher M.

2002-01-01

Objective: To identify the learning styles and preferred environmental characteristics of undergraduate athletic training students in Commission on Accreditation of Allied Health Education Programs (CAAHEP)-accredited athletic training education programs and to determine if learning-style differences existed among geographic regions of the country. Design and Setting: Fifty CAAHEP-accredited athletic training programs were randomly selected in proportion to the number of programs in each geographic region. Ten students from each school were selected to complete the Kolb Learning Style Inventory (LSI) and the Productivity Environmental Preference Survey (PEPS). Subjects: A total of 193 undergraduate athletic training students (84 men, 109 women) with a mean age of 22.3 ± 2.8 years completed the PEPS, while 188 students completed the LSI. Measurements: We used chi-square analyses to determine if differences existed in learning-style type and if these differences were based on geographic location. We calculated analysis of variance to determine if there were any geographic differences in the mean overall combination scores of the LSI. Descriptive statistics were used to evaluate the PEPS. Results: The overall return rate was 38%. The chi-square analyses revealed no significant difference in learning-style type for athletic training students, regardless of the geographic region. The LSI yielded a relatively even distribution of learning styles: 29.3% of the students were accommodators, 19.7% were divergers, 21.8% were convergers, and 29.3% were assimilators. The overall mean combination scores were 4.9 (abstract-concrete) and 4.9 (active-reflective), and analysis of variance indicated no significant difference in the mean combination scores among the geographic regions. The PEPS revealed that undergraduate athletic training students demonstrated a strong preference for learning in the afternoon. Conclusions: Undergraduate athletic training students demonstrated great diversity in learning style. Educators must strongly consider this diversity and incorporate teaching methods that will benefit all types of learners. PMID:12937535

Relearning of Activities of Daily Living: A Comparison of the Effectiveness of Three Learning Methods in Patients with Dementia of the Alzheimer Type.

PubMed

Bourgeois, J; Laye, M; Lemaire, J; Leone, E; Deudon, A; Darmon, N; Giaume, C; Lafont, V; Brinck-Jensen, S; Dechamps, A; König, A; Robert, P

2016-01-01

This study examined the effectiveness of three different learning methods: trial and error learning (TE), errorless learning (EL) and learning by modeling with spaced retrieval (MR) on the relearning process of IADL in mild-to-moderately severe Alzheimer's Dementia (AD) patients (n=52), using a 6-weeks randomized controlled trial design. The participants had to relearn three IADLs. Repeated-measure analyses during pre-intervention, post-intervention and 1-month delayed sessions were performed. All three learning methods were found to have similar efficiency. However, the intervention produced greater improvements in the actual performance of the IADL tasks than on their explicit knowledge. This study confirms that the relearning of IADL is possible with AD patients through individualized interventions, and that the improvements can be maintained even after the intervention.

Effects of three types of lecture notes on medical student achievement.

PubMed

Russell, I J; Caris, T N; Harris, G D; Hendricson, W D

1983-08-01

Two parallel studies were conducted with junior medical students to determine what influence the forms of lecture notes would have on learning. The three types of notes given to the students were: a comprehensive manuscript of the lecture containing text, tables, and figures; a partial handout which included some illustrations but required substantial annotation by the students; and a skeleton outline containing no data from the lecture. The students' knowledge about the subject was measured before the lecture, immediately after the lecture, two to four weeks later, and approximately three months later. The students' responses to questionnaires indicated a strong preference for very detained handouts as essential to preparation for examinations. By contract, the students' performances on tests generally were better for those who had received the partial or skeleton handout formats. This was particularly true for information presented during the last quarter of each lecture, when learning efficiency of the skeleton handout group increased while the other two handout groups exhibited learning fatigue. It was concluded that learning by medical students was improved when they recorded notes in class.

The impact of secondary-task type on the sensitivity of reaction-time based measurement of cognitive load for novices learning surgical skills using simulation.

PubMed

Rojas, David; Haji, Faizal; Shewaga, Rob; Kapralos, Bill; Dubrowski, Adam

2014-01-01

Interest in the measurement of cognitive load (CL) in simulation-based education has grown in recent years. In this paper we present two pilot experiments comparing the sensitivity of two reaction time based secondary task measures of CL. The results suggest that simple reaction time measures are sensitive enough to detect changes in CL experienced by novice learners in the initial stages of simulation-based surgical skills training.

Half Lives for ``Irradiated'' Nonscience Majors

NASA Astrophysics Data System (ADS)

Geise, Kathleen; Hallam, Peter; Rattray, Rebecca; Stencel, Robert; Wolfe, Tristan

2014-03-01

We launched new hands-on radiation labs to supplement lecture material for undergraduate, non-science majors at the University of Denver to reinforce learning objectives during winter quarter 2014 and in order to help educate the public about nuclear energy decisions. Our learning objectives included: 1. differentiate between particle radiation and electro-magnetic radiation, 2. understand that particle radiation comes in alpha, beta and gamma types, 3. atomic and nuclear structure, 4. decay and half-life, 5. understand safe vs. unsafe doses and issues surrounding nuclear waste disposal. We used prelab surveys, prelab assessments, laboratory write-ups and quizzes to measure success with the learning objectives.

Measuring Changes in Interest in Science and Technology at the College Level in Response to Two Instructional Interventions

NASA Astrophysics Data System (ADS)

Romine, William L.; Sadler, Troy D.

2016-06-01

Improving interest in science, technology, engineering, and mathematics (STEM) is crucial to widening participation and success in STEM studies at the college level. To understand how classroom and extracurricular interventions affect interest, it is necessary to have appropriate measurement tools. We describe the adaptation and revalidation of a previously existing multidimensional instrument to the end of measuring interest in environmental science and technology in college nonscience majors. We demonstrate the revised instrument's ability to detect change in this group over an 8-week time period. While collection of demographic information was not part of the study design, participating students were similar in that they hailed from three environmental science nonmajor classes sharing a common syllabus and instructional delivery method. Change in interest was measured in response to two types of scientific literature-based learning approaches: a scientific practice approach and a traditional, quiz-driven approach. We found that both approaches led to moderate gains in interest in learning environmental science and careers in environmental science across an 8-week time period. Interest in using technology for learning increased among students using the scientific practice approach; in contrast, the same measure decreased among students using the reading/quiz approach. This result invites the possibility that interest in using technology as a learning tool may relate to technological literacy, which must be taught explicitly in the context of authentic inquiry experiences.

A process-based approach to characterizing the effect of acute alprazolam challenge on visual paired associate learning and memory in healthy older adults.

PubMed

Pietrzak, Robert H; Scott, James Cobb; Harel, Brian T; Lim, Yen Ying; Snyder, Peter J; Maruff, Paul

2012-11-01

Alprazolam is a benzodiazepine that, when administered acutely, results in impairments in several aspects of cognition, including attention, learning, and memory. However, the profile (i.e., component processes) that underlie alprazolam-related decrements in visual paired associate learning has not been fully explored. In this double-blind, placebo-controlled, randomized cross-over study of healthy older adults, we used a novel, "process-based" computerized measure of visual paired associate learning to examine the effect of a single, acute 1-mg dose of alprazolam on component processes of visual paired associate learning and memory. Acute alprazolam challenge was associated with a large magnitude reduction in visual paired associate learning and memory performance (d = 1.05). Process-based analyses revealed significant increases in distractor, exploratory, between-search, and within-search error types. Analyses of percentages of each error type suggested that, relative to placebo, alprazolam challenge resulted in a decrease in the percentage of exploratory errors and an increase in the percentage of distractor errors, both of which reflect memory processes. Results of this study suggest that acute alprazolam challenge decreases visual paired associate learning and memory performance by reducing the strength of the association between pattern and location, which may reflect a general breakdown in memory consolidation, with less evidence of reductions in executive processes (e.g., working memory) that facilitate visual paired associate learning and memory. Copyright © 2012 John Wiley & Sons, Ltd.

Learning Object Repositories

ERIC Educational Resources Information Center

Lehman, Rosemary

2007-01-01

This chapter looks at the development and nature of learning objects, meta-tagging standards and taxonomies, learning object repositories, learning object repository characteristics, and types of learning object repositories, with type examples. (Contains 1 table.)

Factors Influencing Learning Environments in an Integrated Experiential Program

NASA Astrophysics Data System (ADS)

Koci, Peter

The research conducted for this dissertation examined the learning environment of a specific high school program that delivered the explicit curriculum through an integrated experiential manner, which utilized field and outdoor experiences. The program ran over one semester (five months) and it integrated the grade 10 British Columbian curriculum in five subjects. A mixed methods approach was employed to identify the students' perceptions and provide richer descriptions of their experiences related to their unique learning environment. Quantitative instruments were used to assess changes in students' perspectives of their learning environment, as well as other supporting factors including students' mindfulness, and behaviours towards the environment. Qualitative data collection included observations, open-ended questions, and impromptu interviews with the teacher. The qualitative data describe the factors and processes that influenced the learning environment and give a richer, deeper interpretation which complements the quantitative findings. The research results showed positive scores on all the quantitative measures conducted, and the qualitative data provided further insight into descriptions of learning environment constructs that the students perceived as most important. A major finding was that the group cohesion measure was perceived by students as the most important attribute of their preferred learning environment. A flow chart was developed to help the researcher conceptualize how the learning environment, learning process, and outcomes relate to one another in the studied program. This research attempts to explain through the consideration of this case study: how learning environments can influence behavioural change and how an interconnectedness among several factors in the learning process is influenced by the type of learning environment facilitated. Considerably more research is needed in this area to understand fully the complexity learning environments and how they influence learning and behaviour. Keywords: learning environments; integrated experiential programs; environmental education.

Designing a Semantic Bliki System to Support Different Types of Knowledge and Adaptive Learning

ERIC Educational Resources Information Center

Huang, Shiu-Li; Yang, Chia-Wei

2009-01-01

Though blogs and wikis have been used to support knowledge management and e-learning, existing blogs and wikis cannot support different types of knowledge and adaptive learning. A case in point, types of knowledge vary greatly in category and viewpoints. Additionally, adaptive learning is crucial to improving one's learning performance. This study…

Measuring learning gain: Comparing anatomy drawing screencasts and paper-based resources.

PubMed

Pickering, James D

2017-07-01

The use of technology-enhanced learning (TEL) resources is now a common tool across a variety of healthcare programs. Despite this popular approach to curriculum delivery there remains a paucity in empirical evidence that quantifies the change in learning gain. The aim of the study was to measure the changes in learning gain observed with anatomy drawing screencasts in comparison to a traditional paper-based resource. Learning gain is a widely used term to describe the tangible changes in learning outcomes that have been achieved after a specific intervention. In regard to this study, a cohort of Year 2 medical students voluntarily participated and were randomly assigned to either a screencast or textbook group to compare changes in learning gain across resource type. Using a pre-test/post-test protocol, and a range of statistical analyses, the learning gain was calculated at three test points: immediate post-test, 1-week post-test and 4-week post-test. Results at all test points revealed a significant increase in learning gain and large effect sizes for the screencast group compared to the textbook group. Possible reasons behind the difference in learning gain are explored by comparing the instructional design of both resources. Strengths and weaknesses of the study design are also considered. This work adds to the growing area of research that supports the effective design of TEL resources which are complimentary to the cognitive theory of multimedia learning to achieve both an effective and efficient learning resource for anatomical education. Anat Sci Educ 10: 307-316. © 2016 American Association of Anatomists. © 2016 American Association of Anatomists.

Measuring Effectiveness in Conflict Environments

DTIC Science & Technology

2009-09-01

87 14. SUBJECT TERMS Type Keywords Here 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY CLASSIFICATION OF THIS... penetration and disruption.”53 Measuring casualties would obviously correspond with these kinds of objectives but do not provide the kind of information...39. 103 U.S. House of Representative Committee on Armed Services, “Agency Stovepipes vs . Strategic Agility: Lessons We Need to Learn from Provincial

E-Learning Personalization Using Triple-Factor Approach in Standard-Based Education

NASA Astrophysics Data System (ADS)

Laksitowening, K. A.; Santoso, H. B.; Hasibuan, Z. A.

2017-01-01

E-Learning can be a tool in monitoring learning process and progress towards the targeted competency. Process and progress on every learner can be different one to another, since every learner may have different learning type. Learning type itself can be identified by taking into account learning style, motivation, and knowledge ability. This study explores personalization for learning type based on Triple-Factor Approach. Considering that factors in Triple-Factor Approach are dynamic, the personalization system needs to accommodate the changes that may occurs. Originated from the issue, this study proposed personalization that guides learner progression dynamically towards stages of their learning process. The personalization is implemented in the form of interventions that trigger learner to access learning contents and discussion forums more often as well as improve their level of knowledge ability based on their state of learning type.

Seven Types of Ambiguity in Evaluating the Impact of Humanities Provision in Undergraduate Medicine Curricula.

PubMed

Bleakley, Alan

2015-12-01

Inclusion of the humanities in undergraduate medicine curricula remains controversial. Skeptics have placed the burden of proof of effectiveness upon the shoulders of advocates, but this may lead to pursuing measurement of the immeasurable, deflecting attention away from the more pressing task of defining what we mean by the humanities in medicine. While humanities input can offer a fundamental critical counterweight to a potentially reductive biomedical science education, a new wave of thinking suggests that the kinds of arts and humanities currently used in medical education are neither radical nor critical enough to have a deep effect on students' learning and may need to be reformulated. The humanities can certainly educate for tolerance of ambiguity as a basis to learning democratic habits for contemporary team-based clinical work. William Empson's 'seven types of ambiguity' model for analyzing poetry is transposed to medical education to: (a) formulate seven values proffered by the humanities for improving medical education; (b) offer seven ways of measuring impact of medical humanities provision, thereby reducing ambiguity; and (c) --as a counterweight to (b) - celebrate seven types of ambiguity in contemporary medical humanities that critically reconsider issues of proof of impact.

The role of domain-general cognitive resources in children's construction of a vitalist theory of biology.

PubMed

Bascandziev, Igor; Tardiff, Nathan; Zaitchik, Deborah; Carey, Susan

2018-08-01

Some episodes of learning are easier than others. Preschoolers can learn certain facts, such as "my grandmother gave me this purse," only after one or two exposures (easy to learn; fast mapping), but they require several years to learn that plants are alive or that the sun is not alive (hard to learn). One difference between the two kinds of knowledge acquisition is that hard cases often require conceptual construction, such as the construction of the biological concept alive, whereas easy cases merely involve forming new beliefs formulated over concepts the child already has (belief revision, a form of knowledge enrichment). We asked whether different domain-general cognitive resources support these two types of knowledge acquisition (conceptual construction and knowledge enrichment that supports fast mapping) by testing 82 6-year-olds in a pre-training/training/post-training study. We measured children's improvement in an episode involving theory construction (the beginning steps of acquisition of the framework theory of vitalist biology, which requires conceptual change) and in an episode involving knowledge enrichment alone (acquisition of little known facts about animals, such as the location of crickets' ears and the color of octopus blood). In addition, we measured children's executive functions and receptive vocabulary to directly compare the resources drawn upon in the two episodes of learning. We replicated and extended previous findings highlighting the differences between conceptual construction and knowledge enrichment, and we found that Executive Functions predict improvement on the Vitalism battery but not on the Fun Facts battery and that Receptive Vocabulary predicts improvement the Fun Facts battery but not on the Vitalism battery. This double dissociation provides new evidence for the distinction between the two types of knowledge acquisition, and bears on the nature of the learning mechanisms involved in each. Copyright © 2018 Elsevier Inc. All rights reserved.

Virtual Visualisation Laboratory for Science and Mathematics Content (Vlab-SMC) with Special Reference to Teaching and Learning of Chemistry

NASA Astrophysics Data System (ADS)

Badioze Zaman, Halimah; Bakar, Norashiken; Ahmad, Azlina; Sulaiman, Riza; Arshad, Haslina; Mohd. Yatim, Nor Faezah

Research on the teaching of science and mathematics in schools and universities have shown that available teaching models are not effective in instilling the understanding of scientific and mathematics concepts, and the right scientific and mathematics skills required for learners to become good future scientists (mathematicians included). The extensive development of new technologies has a marked influence on education, by facilitating the design of new learning and teaching materials, that can improve the attitude of learners towards Science and Mathematics and the plausibility of advanced interactive, personalised learning process. The usefulness of the computer in Science and Mathematics education; as an interactive communication medium that permits access to all types of information (texts, images, different types of data such as sound, graphics and perhaps haptics like smell and touch); as an instrument for problem solving through simulations of scientific and mathematics phenomenon and experiments; as well as measuring and monitoring scientific laboratory experiments. This paper will highlight on the design and development of the virtual Visualisation Laboratory for Science & Mathematics Content (VLab-SMC) based on the Cognitivist- Constructivist-Contextual development life cycle model as well as the Instructional Design (ID) model, in order to achieve its objectives in teaching and learning. However, this paper with only highlight one of the virtual labs within VLab-SMC that is, the Virtual Lab for teaching Chemistry (VLab- Chem). The development life cycle involves the educational media to be used, measurement of content, and the authoring and programming involved; whilst the ID model involves the application of the cognitivist, constructivist and contextual theories in the modeling of the modules of VLab-SMC generally and Vlab-Chem specifically, using concepts such as 'learning by doing', contextual learning, experimental simulations 3D and real-time animations to create a virtual laboratory based on a real laboratory. Initial preliminary study shows positive indicators of VLab-Chem for the teaching and learning of Chemistry on the topic of 'Salts and Acids'.

Applications of machine learning in cancer prediction and prognosis.

PubMed

Cruz, Joseph A; Wishart, David S

2007-02-11

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on "older" technologies such artificial neural networks (ANNs) instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15-25%) improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression.

A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries.

PubMed

Jiang, Min; Chen, Yukun; Liu, Mei; Rosenbloom, S Trent; Mani, Subramani; Denny, Joshua C; Xu, Hua

2011-01-01

The authors' goal was to develop and evaluate machine-learning-based approaches to extracting clinical entities-including medical problems, tests, and treatments, as well as their asserted status-from hospital discharge summaries written using natural language. This project was part of the 2010 Center of Informatics for Integrating Biology and the Bedside/Veterans Affairs (VA) natural-language-processing challenge. The authors implemented a machine-learning-based named entity recognition system for clinical text and systematically evaluated the contributions of different types of features and ML algorithms, using a training corpus of 349 annotated notes. Based on the results from training data, the authors developed a novel hybrid clinical entity extraction system, which integrated heuristic rule-based modules with the ML-base named entity recognition module. The authors applied the hybrid system to the concept extraction and assertion classification tasks in the challenge and evaluated its performance using a test data set with 477 annotated notes. Standard measures including precision, recall, and F-measure were calculated using the evaluation script provided by the Center of Informatics for Integrating Biology and the Bedside/VA challenge organizers. The overall performance for all three types of clinical entities and all six types of assertions across 477 annotated notes were considered as the primary metric in the challenge. Systematic evaluation on the training set showed that Conditional Random Fields outperformed Support Vector Machines, and semantic information from existing natural-language-processing systems largely improved performance, although contributions from different types of features varied. The authors' hybrid entity extraction system achieved a maximum overall F-score of 0.8391 for concept extraction (ranked second) and 0.9313 for assertion classification (ranked fourth, but not statistically different than the first three systems) on the test data set in the challenge.

Selection and Use of Online Learning Resources by First-Year Medical Students: Cross-Sectional Study.

PubMed

Judd, Terry; Elliott, Kristine

2017-10-02

Medical students have access to a wide range of learning resources, many of which have been specifically developed for or identified and recommended to them by curriculum developers or teaching staff. There is an expectation that students will access and use these resources to support their self-directed learning. However, medical educators lack detailed and reliable data about which of these resources students use to support their learning and how this use relates to key learning events or activities. The purpose of this study was to comprehensively document first-year medical student selection and use of online learning resources to support their bioscience learning within a case-based curriculum and assess these data in relation to our expectations of student learning resource requirements and use. Study data were drawn from 2 sources: a survey of student learning resource selection and use (2013 cohort; n=326) and access logs from the medical school learning platform (2012 cohort; n=337). The paper-based survey, which was distributed to all first-year students, was designed to assess the frequency and types of online learning resources accessed by students and included items about their perceptions of the usefulness, quality, and reliability of various resource types and sources. Of 237 surveys returned, 118 complete responses were analyzed (36.2% response rate). Usage logs from the learning platform for an entire semester were processed to provide estimates of first-year student resource use on an individual and cohort-wide basis according to method of access, resource type, and learning event. According to the survey data, students accessed learning resources via the learning platform several times per week on average, slightly more often than they did for resources from other online sources. Google and Wikipedia were the most frequently used nonuniversity sites, while scholarly information sites (eg, online journals and scholarly databases) were accessed relatively infrequently. Students were more likely to select learning resources based on the recommendation of peers than of teaching staff. The overwhelming majority of the approximately 70,000 resources accessed by students via the learning platform were lecture notes, with each accessed an average of 167 times. By comparison, recommended journal articles and (online) textbook chapters were accessed only 49 and 31 times, respectively. The number and type of learning resources accessed by students through the learning platform was highly variable, with a cluster analysis revealing that a quarter of students accessed very few resources in this way. Medical students have easy access to a wide range of quality learning resources, and while some make good use of the learning resources recommended to them, many ignore most and access the remaining ones infrequently. Learning analytics can provide useful measures of student resource access through university learning platforms but fails to account for resources accessed via external online sources or sharing of resources using social media. ©Terry Judd, Kristine Elliott. Originally published in JMIR Medical Education (http://mededu.jmir.org), 02.10.2017.

Measuring cognitive load during procedural skills training with colonoscopy as an exemplar.

PubMed

Sewell, Justin L; Boscardin, Christy K; Young, John Q; Ten Cate, Olle; O'Sullivan, Patricia S

2016-06-01

Few studies have investigated cognitive factors affecting learning of procedural skills in medical education. Cognitive load theory, which focuses on working memory, is highly relevant, but methods for measuring cognitive load during procedural training are not well understood. Using colonoscopy as an exemplar, we used cognitive load theory to develop a self-report instrument to measure three types of cognitive load (intrinsic, extraneous and germane load) and to provide evidence for instrument validity. We developed the instrument (the Cognitive Load Inventory for Colonoscopy [CLIC]) using a multi-step process. It included 19 items measuring three types of cognitive load, three global rating items and demographics. We then conducted a cross-sectional survey that was administered electronically to 1061 gastroenterology trainees in the USA. Participants completed the CLIC following a colonoscopy. The two study phases (exploratory and confirmatory) each lasted for 10 weeks during the 2014-2015 academic year. Exploratory factor analysis determined the most parsimonious factor structure; confirmatory factor analysis assessed model fit. Composite measures of intrinsic, extraneous and germane load were compared across years of training and with global rating items. A total of 477 (45.0%) invitees participated (116 in the exploratory study and 361 in the confirmatory study) in 154 (95.1%) training programmes. Demographics were similar to national data from the USA. The most parsimonious factor structure included three factors reflecting the three types of cognitive load. Confirmatory factor analysis verified that a three-factor model was the best fit. Intrinsic, extraneous and germane load items had high internal consistency (Cronbach's alpha 0.90, 0.87 and 0.96, respectively) and correlated as expected with year in training and global assessment of cognitive load. The CLIC measures three types of cognitive load during colonoscopy training. Evidence of validity is provided. Although CLIC items relate to colonoscopy, the development process we detail can be used to adapt the instrument for use in other learning settings in medical education. © 2016 John Wiley & Sons Ltd.

2013 CAEL Forum & News: Competency-Based Education

ERIC Educational Resources Information Center

Council for Adult and Experiential Learning, 2013

2013-01-01

In 2012, CAEL released the report "Competency-Based Degree Programs in the U.S.: Postsecondary Credentials for Measurable Student Learning and Performance," which examined the current state of competency-based postsecondary education in the U.S., profiling the various types of competency-based, or competency-focused, models that…

Multiple Goal Orientations and Foreign Language Anxiety

ERIC Educational Resources Information Center

Koul, Ravinder; Roy, Laura; Kaewkuekool, Sittichai; Ploisawaschai, Suthee

2009-01-01

This investigation examines Thai college students' motivational goals for learning the English language. Thai student volunteers (N = 1387) from two types of educational institutions participated in this survey study which combined measures of goal orientations based on two different goal constructs and motivation models. Results of two-step…

A Way to Measure Success in the Rehabilitation of Drug Addicts

ERIC Educational Resources Information Center

Chinlund, Stephen J.

1974-01-01

Persons concerned about drug addiction and who seek to help addicts must learn to distinguish between types of addicts. Three cases are reviewed. Those offering help to addicts in need should look beyond simple abstinence to the development of the total person. (Author/PC)

Instructional methods and cognitive and learning styles in web-based learning: report of two randomised trials.

PubMed

Cook, David A; Gelula, Mark H; Dupras, Denise M; Schwartz, Alan

2007-09-01

Adapting web-based (WB) instruction to learners' individual differences may enhance learning. Objectives This study aimed to investigate aptitude-treatment interactions between learning and cognitive styles and WB instructional methods. We carried out a factorial, randomised, controlled, crossover, post-test-only trial involving 89 internal medicine residents, family practice residents and medical students at 2 US medical schools. Parallel versions of a WB course in complementary medicine used either active or reflective questions and different end-of-module review activities ('create and study a summary table' or 'study an instructor-created table'). Participants were matched or mismatched to question type based on active or reflective learning style. Participants used each review activity for 1 course module (crossover design). Outcome measurements included the Index of Learning Styles, the Cognitive Styles Analysis test, knowledge post-test, course rating and preference. Post-test scores were similar for matched (mean +/- standard error of the mean 77.4 +/- 1.7) and mismatched (76.9 +/- 1.7) learners (95% confidence interval [CI] for difference - 4.3 to 5.2l, P = 0.84), as were course ratings (P = 0.16). Post-test scores did not differ between active-type questions (77.1 +/- 2.1) and reflective-type questions (77.2 +/- 1.4; P = 0.97). Post-test scores correlated with course ratings (r = 0.45). There was no difference in post-test subscores for modules completed using the 'construct table' format (78.1 +/- 1.4) or the 'table provided' format (76.1 +/- 1.4; CI - 1.1 to 5.0, P = 0.21), and wholist and analytic styles had no interaction (P = 0.75) or main effect (P = 0.18). There was no association between activity preference and wholist or analytic scores (P = 0.37). Cognitive and learning styles had no apparent influence on learning outcomes. There were no differences in outcome between these instructional methods.

Science curiosity in learning environments: developing an attitudinal scale for research in schools, homes, museums, and the community

NASA Astrophysics Data System (ADS)

Weible, Jennifer L.; Toomey Zimmerman, Heather

2016-05-01

Although curiosity is considered an integral aspect of science learning, researchers have debated how to define, measure, and support its development in individuals. Prior measures of curiosity include questionnaire type scales (primarily for adults) and behavioral measures. To address the need to measure scientific curiosity, the Science Curiosity in Learning Environments (SCILE) scale was created and validated as a 12-item scale to measure scientific curiosity in youth. The scale was developed through (a) adapting the language of the Curiosity and Exploration Inventory-II [Kashdan, T. B., Gallagher, M. W., Silvia, P. J., Winterstein, B. P., Breen, W. E., Terhar, D., & Steger, M. F. (2009). The curiosity and exploration inventory-II: Development, factor structure, and psychometrics. Journal of Research in Personality, 43(6), 987-998] for youth and (b) crafting new items based on scientific practices drawn from U.S. science standards documents. We administered a preliminary set of 30 items to 663 youth ages 8-18 in the U.S.A. Exploratory and confirmatory factor analysis resulted in a three-factor model: stretching, embracing, and science practices. The findings indicate that the SCILE scale is a valid measure of youth's scientific curiosity for boys and girls as well as elementary, middle school, and high school learners.

Supporting Scientific Experimentation and Reasoning in Young Elementary School Students

NASA Astrophysics Data System (ADS)

Varma, Keisha

2014-06-01

Researchers from multiple perspectives have shown that young students can engage in the scientific reasoning involved in science experimentation. However, there is little research on how well these young students learn in inquiry-based learning environments that focus on using scientific experimentation strategies to learn new scientific information. This work investigates young children's science concept learning via inquiry-based instruction on the thermodynamics system in a developmentally appropriate, technology-supported learning environment. First- and third-grade students participate in three sets of guided experimentation activities that involve using handheld computers to measure change in temperature given different types of insulation materials. Findings from pre- and post-comparisons show that students at both grade levels are able to learn about the thermodynamics system through engaging in the guided experiment activities. The instruction groups outperformed the control groups on multiple measures of thermodynamics knowledge, and the older children outperform the younger children. Knowledge gains are discussed in the context of mental models of the thermodynamics system that include the individual concepts mentioned above and the relationships between them. This work suggests that young students can benefit from science instruction centered on experimentation activities. It shows the benefits of presenting complex scientific information authentic contexts and the importance of providing the necessary scaffolding for meaningful scientific inquiry and experimentation.

Assessing STEM content learning: using the Arctic's changing climate to develop 21st century learner

NASA Astrophysics Data System (ADS)

Henderson, G. R.; Durkin, S.; Moran, A.

2016-12-01

In recent years the U.S. federal government has called for an increased focus on science, technology, engineering, and mathematics (STEM) in the educational system to ensure that there will be sufficient technical expertise to meet the needs of business and industry. As a direct result of this STEM emphasis, the number of outreach activities aimed at actively engaging these students in STEM learning has surged. Such activities, frequently in the form of summer camps led by university faculty, have targeted primary and secondary school students with the goal of growing student interest in STEM majors and STEM careers. This study assesses short-term content learning using a climate module that highlights rapidly changing Arctic climate conditions to illustrate concepts of radiative energy balance and climate feedback. Hands-on measurement of short and longwave radiation using simple instrumentation is used to demonstrate concepts that are then related back to the "big picture" Arctic issue. Pre and post module questionnaires were used to assess content learning, as this learning type has been identified as the basis for STEM literacy and the vehicle by which 21st century learning skills are usually developed. In this instance, students applied subject knowledge they gained by taking radiation measurements to better understand the real-world problem of climate change.

Some simple guides to finding useful information in exploration geochemical data

USGS Publications Warehouse

Singer, D.A.; Kouda, R.

2001-01-01

Most regional geochemistry data reflect processes that can produce superfluous bits of noise and, perhaps, information about the mineralization process of interest. There are two end-member approaches to finding patterns in geochemical data-unsupervised learning and supervised learning. In unsupervised learning, data are processed and the geochemist is given the task of interpreting and identifying possible sources of any patterns. In supervised learning, data from known subgroups such as rock type, mineralized and nonmineralized, and types of mineralization are used to train the system which then is given unknown samples to classify into these subgroups. To locate patterns of interest, it is helpful to transform the data and to remove unwanted masking patterns. With trace elements use of a logarithmic transformation is recommended. In many situations, missing censored data can be estimated using multiple regression of other uncensored variables on the variable with censored values. In unsupervised learning, transformed values can be standardized, or normalized, to a Z-score by subtracting the subset's mean and dividing by its standard deviation. Subsets include any source of differences that might be related to processes unrelated to the target sought such as different laboratories, regional alteration, analytical procedures, or rock types. Normalization removes effects of different means and measurement scales as well as facilitates comparison of spatial patterns of elements. These adjustments remove effects of different subgroups and hopefully leave on the map the simple and uncluttered pattern(s) related to the mineralization only. Supervised learning methods, such as discriminant analysis and neural networks, offer the promise of consistent and, in certain situations, unbiased estimates of where mineralization might exist. These methods critically rely on being trained with data that encompasses all populations fairly and that can possibly fall into only the identified populations. ?? 2001 International Association for Mathematical Geology.

Usability study of the EduMod eLearning Program for contouring nodal stations of the head and neck.

PubMed

Deraniyagala, Rohan; Amdur, Robert J; Boyer, Arthur L; Kaylor, Scott

2015-01-01

A major strategy for improving radiation oncology education and competence evaluation is to develop eLearning programs that reproduce the real work environment. A valuable measure of the quality of an eLearning program is "usability," which is a multidimensional endpoint defined from the end user's perspective. The gold standard for measuring usability is the Software Usability Measurement Inventory (SUMI). The purpose of this study is to use the SUMI to measure usability of an eLearning course that uses innovative software to teach and test contouring of nodal stations of the head and neck. This is a prospective institutional review board-approved study in which all participants gave written informed consent. The study population was radiation oncology residents from 8 different programs across the United States. The subjects had to pass all sections of the same 2 eLearning modules and then complete the SUMI usability evaluation instrument. We reached the accrual goal of 25 participants. Usability results for the EduMod eLearning course, "Nodal Stations of the Head and Neck," were compared with a large database of scores of other major software programs. Results were evaluated in 5 domains: Affect, Helpfulness, Control, Learnability, and Global Usability. In all 5 domains, usability scores for the study modules were higher than the database mean and statistically superior in 4 domains. This is the first study to evaluate usability of an eLearning program related to radiation oncology. Usability of 2 representative modules related to contouring nodal stations of the head and neck was highly favorable, with scores that were superior to the industry standard in multiple domains. These results support the continued development of this type of eLearning program for teaching and testing radiation oncology technical skills. Copyright © 2015 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

Unstable Memories Create a High-Level Representation that Enables Learning Transfer.

PubMed

Mosha, Neechi; Robertson, Edwin M

2016-01-11

A memory is unstable, making it susceptible to interference and disruption, after its acquisition [1-4]. The function or possible benefit of a memory being unstable at its acquisition is not well understood. Potentially, instability may be critical for the communication between recently acquired memories, which would allow learning in one task to be transferred to the other subsequent task [1, 5]. Learning may be transferred between any memories that are unstable, even between different types of memory. Here, we test the link between a memory being unstable and the transfer of learning to a different type of memory task. We measured how learning in one task transferred to and thus improved learning in a subsequent task. There was transfer from a motor skill to a word list task and, vice versa, from a word list to a motor skill task. What was transferred was a high-level relationship between elements, rather than knowledge of the individual elements themselves. Memory instability was correlated with subsequent transfer, suggesting that transfer was related to the instability of the memory. Using different methods, we stabilized the initial memory, preventing it from being susceptible to interference, and found that these methods consistently prevented transfer to the subsequent memory task. This suggests that the transfer of learning across diverse tasks is due to a high-level representation that can only be formed when a memory is unstable. Our work has identified an important function of memory instability. Copyright © 2016 Elsevier Ltd. All rights reserved.

Communications Training in Pharmacy Education, 1995-2010

PubMed Central

Vaudan, Cristina; Sporrong, Sofia Kälvemark

2013-01-01

The role of the pharmacist as a “communicator” of information and advice between patients, other healthcare practitioners, and the community is recognized as a vital component of the responsibilities of a practicing pharmacist. Pharmacy education is changing to reflect this, although the difficulty is in designing a curriculum that is capable of equipping students with the necessary knowledge and skills, using activities that are effective in promoting communication competency. The objective of this review was to identify published, peer-reviewed articles concerning communication training in pharmacy education programs, and describe which communication skills the structured learning activities aimed to improve and how these learning activities were assessed. A systematic literature search was conducted and the articles found were analyzed and divided into categories based on specific communication skills taught and type of learning activity used. Oral interpersonal communication skills targeted at patients were the most common skill-type described, followed by clinical writing skills. Common teaching methods included simulated and standardized patient interactions and pharmacy practice experience courses. Most educational interventions were assessed by subjective measures. Many interventions were described as fragments, in isolation of other learning activities that took place in a course, which impedes complete analysis of study results. To succeed in communication training, integration between different learning activities and progression within pharmacy educations are important. PMID:23519011

Classification of breast tumour using electrical impedance and machine learning techniques.

PubMed

Al Amin, Abdullah; Parvin, Shahnaj; Kadir, M A; Tahmid, Tasmia; Alam, S Kaisar; Siddique-e Rabbani, K

2014-06-01

When a breast lump is detected through palpation, mammography or ultrasonography, the final test for characterization of the tumour, whether it is malignant or benign, is biopsy. This is invasive and carries hazards associated with any surgical procedures. The present work was undertaken to study the feasibility for such characterization using non-invasive electrical impedance measurements and machine learning techniques. Because of changes in cell morphology of malignant and benign tumours, changes are expected in impedance at a fixed frequency, and versus frequency of measurement. Tetrapolar impedance measurement (TPIM) using four electrodes at the corners of a square region of sides 4 cm was used for zone localization. Data of impedance in two orthogonal directions, measured at 5 and 200 kHz from 19 subjects, and their respective slopes with frequency were subjected to machine learning procedures through the use of feature plots. These patients had single or multiple tumours of various types in one or both breasts, and four of them had malignant tumours, as diagnosed by core biopsy. Although size and depth of the tumours are expected to affect the measurements, this preliminary work ignored these effects. Selecting 12 features from the above measurements, feature plots were drawn for the 19 patients, which displayed considerable overlap between malignant and benign cases. However, based on observed qualitative trend of the measured values, when all the feature values were divided by respective ages, the two types of tumours separated out reasonably well. Using K-NN classification method the results obtained are, positive prediction value: 60%, negative prediction value: 93%, sensitivity: 75%, specificity: 87% and efficacy: 84%, which are very good for such a test on a small sample size. Study on a larger sample is expected to give confidence in this technique, and further improvement of the technique may have the ability to replace biopsy.

Impaired verbal learning in forensic inpatients with Schizophrenia Spectrum Disorder.

PubMed

Corbett, Lasha; Karyadi, Kenny A; Kinney, Dominique; Nitch, Stephen R; Bayan, Stacey Marie; Williams, Mark

2018-01-01

The present study aimed to: (a) examine verbal learning performances among forensic inpatients diagnosed with Schizophrenia Spectrum Disorder (SSD); and (b) compare verbal learning performances among forensic SSD inpatients, SSD outpatients, and a small control sample. Participants included forensic SSD inpatients (n = 71), SSD outpatients (n = 305; see Stone et al.), and a control sample from the California Verbal Learning Test-II (CVLT-II) manual (n = 78; see Delis, Kramer, Kaplan, & Ober). Five verbal learning outcomes were measured using the CVLT-II. The average forensic SSD inpatients performed 1 to 1.5 standard deviations below the mean across the five verbal learning outcomes, many of whom (26.8% to 36.6%) performed in the impaired range across the five outcomes. Forensic SSD inpatients performed significantly lower than the SSD outpatients on three verbal learning outcomes and significantly lower than healthy controls on all five verbal learning outcomes. Results indicated forensically committed SSD inpatients have diminished verbal learning performances. Study findings could help define normative verbal learning performances in different types of SSD patients, may guide the development of compensatory strategies for verbal learning deficits, and could subsequently lead to more successful clinical outcomes in this population.

Mathematical learning models that depend on prior knowledge and instructional strategies

NASA Astrophysics Data System (ADS)

Pritchard, David E.; Lee, Young-Jin; Bao, Lei

2008-06-01

We present mathematical learning models—predictions of student’s knowledge vs amount of instruction—that are based on assumptions motivated by various theories of learning: tabula rasa, constructivist, and tutoring. These models predict the improvement (on the post-test) as a function of the pretest score due to intervening instruction and also depend on the type of instruction. We introduce a connectedness model whose connectedness parameter measures the degree to which the rate of learning is proportional to prior knowledge. Over a wide range of pretest scores on standard tests of introductory physics concepts, it fits high-quality data nearly within error. We suggest that data from MIT have low connectedness (indicating memory-based learning) because the test used the same context and representation as the instruction and that more connected data from the University of Minnesota resulted from instruction in a different representation from the test.

Modeling Geomagnetic Variations using a Machine Learning Framework

NASA Astrophysics Data System (ADS)

Cheung, C. M. M.; Handmer, C.; Kosar, B.; Gerules, G.; Poduval, B.; Mackintosh, G.; Munoz-Jaramillo, A.; Bobra, M.; Hernandez, T.; McGranaghan, R. M.

2017-12-01

We present a framework for data-driven modeling of Heliophysics time series data. The Solar Terrestrial Interaction Neural net Generator (STING) is an open source python module built on top of state-of-the-art statistical learning frameworks (traditional machine learning methods as well as deep learning). To showcase the capability of STING, we deploy it for the problem of predicting the temporal variation of geomagnetic fields. The data used includes solar wind measurements from the OMNI database and geomagnetic field data taken by magnetometers at US Geological Survey observatories. We examine the predictive capability of different machine learning techniques (recurrent neural networks, support vector machines) for a range of forecasting times (minutes to 12 hours). STING is designed to be extensible to other types of data. We show how STING can be used on large sets of data from different sensors/observatories and adapted to tackle other problems in Heliophysics.

Comparing physical activity and sedentary time among overweight and nonoverweight preschoolers enrolled in early learning programs: a cross-sectional study.

PubMed

Tucker, Patricia; Maltby, Alana M; Burke, Shauna M; Vanderloo, Leigh M; Irwin, Jennifer D

2016-09-01

Establishing appropriate physical activity and sedentary behaviours during early childhood is important to ensure children accrue the many associated health benefits. While physical activity levels have been reported as low within early learning programs, little research has explored the physical activity and sedentary time of Canadian preschoolers classified as overweight within these facilities. The purpose of this study was to compare objectively measured physical activity and sedentary time among preschoolers classified as overweight and nonoverweight in early learning programs. Direct assessment of physical activity and sedentary time of 216 preschool-aged children was collected via Actical accelerometers during early learning hours, while body mass index percentile was calculated based on preschoolers' objectively measured height and weight. Results of three 3-way ANOVAs suggest that rates of moderate to vigorous physical activity, total physical activity, and sedentary time (p > 0.05) did not significantly differ based on weight status, sex, and type of early learning facility. This study is one of few that has examined differences in overweight and nonoverweight preschoolers' sedentary time, and adds to the limited research exploring physical activity levels among overweight and nonoverweight preschoolers during early learning hours. Given the high rates of sedentary time reported, programming within early learning facilities is necessary to support preschoolers, regardless of weight status, to achieve increased physical activity levels and decreased sedentary time.

Expanding the boundaries of evaluative learning research: How intersecting regularities shape our likes and dislikes.

PubMed

Hughes, Sean; De Houwer, Jan; Perugini, Marco

2016-06-01

Over the last 30 years, researchers have identified several types of procedures through which novel preferences may be formed and existing ones altered. For instance, regularities in the presence of a single stimulus (as in the case of mere exposure) or 2 or more stimuli (as in the case of evaluative conditioning) have been shown to influence liking. We propose that intersections between regularities represent a previously unrecognized class of procedures for changing liking. Across 4 related studies, we found strong support for the hypothesis that when environmental regularities intersect with one another (i.e., share elements or have elements that share relations with other elements), the evaluative properties of the elements of those regularities can change. These changes in liking were observed across a range of stimuli and procedures and were evident when self-report measures, implicit measures, and behavioral choice measures of liking were employed. Functional and mental explanations of this phenomenon are offered followed by a discussion of how this new type of evaluative learning effect can accelerate theoretical, methodological, and empirical development in attitude research. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A Theoretical Framework for Studying Educational Media: A Pilot Study.

ERIC Educational Resources Information Center

Wager, Walter

1980-01-01

Three types of stimulus materials (text, film, and live demonstration) were used to teach graduate students cardiopulmonary resuscitation; and verbal learning and a motor skill task were measured to determine the effectiveness of the different media. No significant differences were found among the three modes of instruction. (Author/JEG)

Volunteers in Wikipedia: Why the Community Matters

ERIC Educational Resources Information Center

Baytiyeh, Hoda; Pfaffman, Jay

2010-01-01

Wikipedia is a reliable encyclopedia with over seven million articles in several languages all contributed and maintained by volunteers. To learn more about what drives people to devote their time and expertise to building and maintaining this remarkable resource, surveys with Likert-scaled items measuring different types of motivations were…

The Learning of Complex Speech Act Behaviour.

ERIC Educational Resources Information Center

Olshtain, Elite; Cohen, Andrew

1990-01-01

Pre- and posttraining measurement of adult English-as-a-Second-Language learners' (N=18) apology speech act behavior found no clear-cut quantitative improvement after training, although there was an obvious qualitative approximation of native-like speech act behavior in terms of types of intensification and downgrading, choice of strategy, and…

Useful Pedagogies or Financial Hardships? Interactive Response Technology (Clickers) in the Large College Classroom

ERIC Educational Resources Information Center

Boatright-Horowitz, Su L.

2009-01-01

Interactive response systems "clickers" can provide multiple benefits to the students and faculty who use them, including immediate performance feedback and greater student engagement in learning. My own exploration of this technology has yielded five pedagogically different types of polling questions, specifically measurement of student…

Applications of Machine Learning in Cancer Prediction and Prognosis

PubMed Central

Cruz, Joseph A.; Wishart, David S.

2006-01-01

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on “older” technologies such artificial neural networks (ANNs) instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15–25%) improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression. PMID:19458758

An exploration of the relationship between academic and experiential learning approaches in vocational education.

PubMed

de Jong, Jan A Stavenga; Wierstra, Ronny F A; Hermanussen, José

2006-03-01

Research on individual learning approaches (or learning styles) is split in two traditions, one of which is biased towards academic learning, and the other towards learning from direct experience. In the reported study, the two traditions are linked by investigating the relationships between school-based (academic) and work-based (experiential) learning approaches of students in vocational education programs. Participants were 899 students of a Dutch school for secondary vocational education; 758 provided data on school-based learning, and 407 provided data on work-based learning, resulting in an overlap of 266 students from whom data were obtained on learning in both settings. Learning approaches in school and work settings were measured with questionnaires. Using factor analysis and cluster analysis, items and students were grouped, both with respect to school- and work-based learning. The study identified two academic learning dimensions (constructive learning and reproductive learning), and three experiential learning dimensions (analysis, initiative, and immersion). Construction and analysis were correlated positively, and reproduction and initiative negatively. Cluster analysis resulted in the identification of three school-based learning orientations and three work-based learning orientations. The relation between the two types of learning orientations, expressed in Cramér's V, appeared to be weak. It is concluded that learning approaches are relatively context specific, which implies that neither theoretical tradition can claim general applicability.

SVMs for Vibration-Based Terrain Classification

NASA Astrophysics Data System (ADS)

Weiss, Christian; Stark, Matthias; Zell, Andreas

When an outdoor mobile robot traverses different types of ground surfaces, different types of vibrations are induced in the body of the robot. These vibrations can be used to learn a discrimination between different surfaces and to classify the current terrain. Recently, we presented a method that uses Support Vector Machines for classification, and we showed results on data collected with a hand-pulled cart. In this paper, we show that our approach also works well on an outdoor robot. Furthermore, we more closely investigate in which direction the vibration should be measured. Finally, we present a simple but effective method to improve the classification by combining measurements taken in multiple directions.

The Association between Learning and Learning Style in Instructional Marketing Games

ERIC Educational Resources Information Center

Garber, Lawrence L., Jr.; Hyatt, Eva M.; Boya, Unal O.; Ausherman, Babs

2012-01-01

To understand how learners of respective types respond to marketing games, a joint space generated by canonical correlation analysis is used to recreate Kolb's learning style-type plot and locate business students as points within it according to their learning style types. Two hundred twenty-three undergraduate students played The Marketing Game!…

Predictive information processing is a fundamental learning mechanism present in early development: evidence from infants.

PubMed

Trainor, Laurel J

2012-02-01

Evidence is presented that predictive coding is fundamental to brain function and present in early infancy. Indeed, mismatch responses to unexpected auditory stimuli are among the earliest robust cortical event-related potential responses, and have been measured in young infants in response to many types of deviation, including in pitch, timing, and melodic pattern. Furthermore, mismatch responses change quickly with specific experience, suggesting that predictive coding reflects a powerful, early-developing learning mechanism. Copyright © 2011 Elsevier B.V. All rights reserved.

The Relationship of Stated Learning Preferences, Personality Type, and Career Background to Academic and Leadership Performance at the United States Air Command and Staff College

DTIC Science & Technology

1999-12-11

Kolb envisioned experiential 26 Table 2 Subscales on the NASSP Learning Styles Profile Cognitive Styles Perceptual Responses Analytic Skill...Research Type Theory and Learning Preferences Jung and the Theory of Psychological Types Isabel Briggs Myers’ Contribution to Jung’s Work The Myers...Implications Recommendations for Further Study Summary of Specific Conclusions Discussion Grounded Curriculum Learning Preferences Type Theory Student

A similarity based learning framework for interim analysis of outcome prediction of acupuncture for neck pain.

PubMed

Zhang, Gang; Liang, Zhaohui; Yin, Jian; Fu, Wenbin; Li, Guo-Zheng

2013-01-01

Chronic neck pain is a common morbid disorder in modern society. Acupuncture has been administered for treating chronic pain as an alternative therapy for a long time, with its effectiveness supported by the latest clinical evidence. However, the potential effective difference in different syndrome types is questioned due to the limits of sample size and statistical methods. We applied machine learning methods in an attempt to solve this problem. Through a multi-objective sorting of subjective measurements, outstanding samples are selected to form the base of our kernel-oriented model. With calculation of similarities between the concerned sample and base samples, we are able to make full use of information contained in the known samples, which is especially effective in the case of a small sample set. To tackle the parameters selection problem in similarity learning, we propose an ensemble version of slightly different parameter setting to obtain stronger learning. The experimental result on a real data set shows that compared to some previous well-known methods, the proposed algorithm is capable of discovering the underlying difference among different syndrome types and is feasible for predicting the effective tendency in clinical trials of large samples.

How Many U.S. High School Students Have a Foreign Language Reading "Disability"? Reading Without Meaning and the Simple View.

PubMed

Sparks, Richard L; Luebbers, Julie

Conventional wisdom suggests that students classified as learning disabled will exhibit difficulties with foreign language (FL) learning, but evidence has not supported a relationship between FL learning problems and learning disabilities. The simple view of reading model posits that reading comprehension is the product of word decoding and language comprehension and that there are good readers and 3 types of poor readers-dyslexic, hyperlexic, and garden variety-who exhibit different profiles of strengths and/or deficits in word decoding and language comprehension. In this study, a random sample of U.S. high school students completing first-, second-, and third-year Spanish courses were administered standardized measures of Spanish word decoding and reading comprehension, compared with monolingual Spanish readers from first to eleventh grades, and classified into reader types according to the simple view of reading. The majority of students fit the hyperlexic profile, and no participants fit the good reader profile until they were compared with first- and second-grade monolingual Spanish readers. Findings call into question the practice of diagnosing an FL "disability" before a student engages in FL study.

An iterative learning strategy for the auto-tuning of the feedforward and feedback controller in type-1 diabetes.

PubMed

Fravolini, M L; Fabietti, P G

2014-01-01

This paper proposes a scheme for the control of the blood glucose in subjects with type-1 diabetes mellitus based on the subcutaneous (s.c.) glucose measurement and s.c. insulin administration. The tuning of the controller is based on an iterative learning strategy that exploits the repetitiveness of the daily feeding habit of a patient. The control consists of a mixed feedback and feedforward contribution whose parameters are tuned through an iterative learning process that is based on the day-by-day automated analysis of the glucose response to the infusion of exogenous insulin. The scheme does not require any a priori information on the patient insulin/glucose response, on the meal times and on the amount of ingested carbohydrates (CHOs). Thanks to the learning mechanism the scheme is able to improve its performance over time. A specific logic is also introduced for the detection and prevention of possible hypoglycaemia events. The effectiveness of the methodology has been validated using long-term simulation studies applied to a set of nine in silico patients considering realistic uncertainties on the meal times and on the quantities of ingested CHOs.

Consolidation of novel word learning in native English-speaking adults.

PubMed

Kurdziel, Laura B F; Spencer, Rebecca M C

2016-01-01

Sleep has been shown to improve the retention of newly learned words. However, most methodologies have used artificial or foreign language stimuli, with learning limited to word/novel word or word/image pairs. Such stimuli differ from many word-learning scenarios in which definition strings are learned with novel words. Thus, we examined sleep's benefit on learning new words within a native language by using very low-frequency words. Participants learned 45 low-frequency English words and, at subsequent recall, attempted to recall the words when given the corresponding definitions. Participants either learned in the morning with recall in the evening (wake group), or learned in the evening with recall the following morning (sleep group). Performance change across the delay was significantly better in the sleep than the wake group. Additionally, the Levenshtein distance, a measure of correctness of the typed word compared with the target word, became significantly worse following wake, whereas sleep protected correctness of recall. Polysomnographic data from a subsample of participants suggested that rapid eye movement (REM) sleep may be particularly important for this benefit. These results lend further support for sleep's function on semantic learning even for word/definition pairs within a native language.

Semantic and visual memory codes in learning disabled readers.

PubMed

Swanson, H L

1984-02-01

Two experiments investigated whether learning disabled readers' impaired recall is due to multiple coding deficiencies. In Experiment 1, learning disabled and skilled readers viewed nonsense pictures without names or with either relevant or irrelevant names with respect to the distinctive characteristics of the picture. Both types of names improved recall of nondisabled readers, while learning disabled readers exhibited better recall for unnamed pictures. No significant difference in recall was found between name training (relevant, irrelevant) conditions within reading groups. In Experiment 2, both reading groups participated in recall training for complex visual forms labeled with unrelated words, hierarchically related words, or without labels. A subsequent reproduction transfer task showed a facilitation in performance in skilled readers due to labeling, with learning disabled readers exhibiting better reproduction for unnamed pictures. Measures of output organization (clustering) indicated that recall is related to the development of superordinate categories. The results suggest that learning disabled children's reading difficulties are due to an inability to activate a semantic representation that interconnects visual and verbal codes.

Traditional Instruction of Differential Equations and Conceptual Learning

ERIC Educational Resources Information Center

Arslan, Selahattin

2010-01-01

Procedural and conceptual learning are two types of learning, related to two types of knowledge, which are often referred to in mathematics education. Procedural learning involves only memorizing operations with no understanding of underlying meanings. Conceptual learning involves understanding and interpreting concepts and the relations between…

Study on Practical Application of Turboprop Engine Condition Monitoring and Fault Diagnostic System Using Fuzzy-Neuro Algorithms

NASA Astrophysics Data System (ADS)

Kong, Changduk; Lim, Semyeong; Kim, Keunwoo

2013-03-01

The Neural Networks is mostly used to engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measuring performance data, and proposes a fault diagnostic system using the base performance model and artificial intelligent methods such as Fuzzy and Neural Networks. Each real engine performance model, which is named as the base performance model that can simulate a new engine performance, is inversely made using its performance test data. Therefore the condition monitoring of each engine can be more precisely carried out through comparison with measuring performance data. The proposed diagnostic system identifies firstly the faulted components using Fuzzy Logic, and then quantifies faults of the identified components using Neural Networks leaned by fault learning data base obtained from the developed base performance model. In leaning the measuring performance data of the faulted components, the FFBP (Feed Forward Back Propagation) is used. In order to user's friendly purpose, the proposed diagnostic program is coded by the GUI type using MATLAB.

Intercorrelates of Postsecondary Students' Learning Styles and Personality Traits.

ERIC Educational Resources Information Center

Rothschild, Jacqueline; Piland, William E.

1994-01-01

Describes a study investigating the learning styles and personality types of community college and private university students. Identifies three broad types of learners (cooperative, independent, and competitive), suggesting significant correlations between experimenting personality types and learning style preferences. Discusses the role of…

The relationship of document and quantitative literacy with learning styles and selected personal variables for aerospace technology students at Indiana State University

NASA Astrophysics Data System (ADS)

Martin, Royce Ann

The purpose of this study was to determine the extent that student scores on a researcher-constructed quantitative and document literacy test, the Aviation Documents Delineator (ADD), were associated with (a) learning styles (imaginative, analytic, common sense, dynamic, and undetermined), as identified by the Learning Type Measure, (b) program curriculum (aerospace administration, professional pilot, both aerospace administration and professional pilot, other, or undeclared), (c) overall cumulative grade point average at Indiana State University, and (d) year in school (freshman, sophomore, junior, or senior). The Aviation Documents Delineator (ADD) was a three-part, 35 question survey that required students to interpret graphs, tables, and maps. Tasks assessed in the ADD included (a) locating, interpreting, and describing specific data displayed in the document, (b) determining data for a specified point on the table through interpolation, (c) comparing data for a string of variables representing one aspect of aircraft performance to another string of variables representing a different aspect of aircraft performance, (d) interpreting the documents to make decisions regarding emergency situations, and (e) performing single and/or sequential mathematical operations on a specified set of data. The Learning Type Measure (LTM) was a 15 item self-report survey developed by Bernice McCarthy (1995) to profile an individual's processing and perception tendencies in order to reveal different individual approaches to learning. The sample used in this study included 143 students enrolled in Aerospace Technology Department courses at Indiana State University in the fall of 1996. The ADD and the LTM were administered to each subject. Data collected in this investigation were analyzed using a stepwise multiple regression analysis technique. Results of the study revealed that the variables, year in school and GPA, were significant predictors of the criterion variables, document, quantitative, and total literacy, when utilizing the ADD. The variables learning style and program of study were found not to be significant predictors of literacy scores on the ADD instrument.

Interleaved Practice in Multi-Dimensional Learning Tasks: Which Dimension Should We Interleave?

ERIC Educational Resources Information Center

Rau, Martina A.; Aleven, Vincent; Rummel, Nikol

2013-01-01

Research shows that multiple representations can enhance student learning. Many curricula use multiple representations across multiple task types. The temporal sequence of representations and task types is likely to impact student learning. Research on contextual interference shows that interleaving learning tasks leads to better learning results…

A framework to develop a clinical learning culture in health facilities: ideas from the literature.

PubMed

Henderson, A; Briggs, J; Schoonbeek, S; Paterson, K

2011-06-01

Internationally, there is an increase in demand to educate nurses within the clinical practice environment. Clinical practice settings that encourage teaching and learning during episodes of care delivery can be powerful in educating both the existing nursing workforce and nursing students. This paper presents a framework, informed by the literature, that identifies the key factors that are needed to encourage the interactions fundamental to learning in clinical practice. Learning occurs when nurses demonstrate good practice, share their knowledge through conversations and discussions, and also provide feedback to learners, such as students and novices. These types of interactions occur when positive leadership practices encourage trust and openness between staff; when the management team provides sessions for staff to learn how to interact with learners, and also when partnerships provide support and guidance around learning in the workplace. APPLICATION OF CONCEPTS: This framework presents how the concepts of leadership, management and partnership interact to create and sustain learning environments. The feedback from proposed measurement tools can provide valuable information about the positive and negative aspects of these concepts in the clinical learning environment. Analysis of the subscales can assist in identifying appropriate recommended strategies outlined in the framework to guide nurses in improving the recognized deficits in the relationship between the concepts. Leadership, management and partnerships are pivotal for the creation and maintenance of positive learning environments. Diagnostic measurement tools can provide specific information about weaknesses across these areas. This knowledge can guide future initiatives. © 2011 The Authors. International Nursing Review © 2011 International Council of Nurses.

Using Multiple Ways to Investigate Cognitive Load Theory in the Context of Physics Instruction

NASA Astrophysics Data System (ADS)

Zu, Tianlong

Cognitive load theory (CLT) (Sweller 1988, 1998, 2010) provides us a guiding framework for designing instructional materials. CLT differentiates three subtypes of cognitive load: intrinsic, extraneous, and germane cognitive load. The three cognitive loads are theorized based on the number of simultaneously processed elements in working memory. Intrinsic cognitive load depends upon the number of interacting elements in the instructional material that are related to the learning objective. Extraneous cognitive load is the mental resources allocated to processing unnecessary information which does not contribute to learning as caused by non- optimal instructional procedure. It is determined by the number of interacting elements which are not related to learning goal. Both intrinsic and extraneous load vary according to prior knowledge of learners. Germane cognitive load is indirectly related to interacting elements. It represents the cognitive resources deployed for processing intrinsic load, chunking information and constructing and automating schema. Germane cognitive load is related to level of motivation of the learner. Given this triarchic model of cognitive load and their different roles in learning activities, different learning outcomes can be expected depending upon the characteristics of the educational materials, learner characteristics, and instructional setting. In three experiments, we investigated cognitive load theory following different approaches. Given the triarchic nature of cognitive load construct, it is critical to find non- intrusive ways to measure cognitive load. In study one, we replicated and extended a previous landmark study to investigate the use of eye movements related metrics to measure the three kinds of cognitive load independently. We also collected working memory capacity of students using a cognitive operation-span task. Two of the three types of cognitive load (intrinsic and extraneous) were directly manipulated, and the third type of cognitive load (germane) was indirectly ascertained. We found that different eye-movement based parameters were most sensitive to different types of cognitive load. These results indicate that it is possible to monitor the three kinds of cognitive load separately using eye movement parameters. We also compared the up-to-date cognitive load theory model with an alternative model using a multi-level model analysis and we found that Sweller's (2010) up-to-date model is supported by our data. In educational settings, active learning based methodologies such as peer instruction have been shown to be effective in facilitating students' conceptual understanding. In study two, we discussed the effect of peer interaction on conceptual test performance of students from a cognitive load perspective. Based on the literature, a self-reported cognitive load survey was developed to measure each type of cognitive load. We found that a certain level of prior knowledge is necessary for peer interaction to work and that peer interaction is effective mainly through significantly decreasing the intrinsic load experienced by students, even though it may increase the extraneous load. In study three, we compared the effect of guided instruction in the form of worked examples using narrated-animated video solutions and semi-guided instruction using visual cues on students' performance, shift of visual attention during transfer, and extraneous cognitive load during learning. We found that multimedia video solutions can be more effective in promoting transfer performance of learners than visual cues. We also found evidence that guided instruction in the form of multimedia video solutions can decrease extraneous cognitive load of students during learning, more so than semi-guided instruction using visual cues.

Development and Validation of Two Instruments Measuring Intrinsic, Extraneous, and Germane Cognitive Load

PubMed Central

Klepsch, Melina; Schmitz, Florian; Seufert, Tina

2017-01-01

Cognitive Load Theory is one of the most powerful research frameworks in educational research. Beside theoretical discussions about the conceptual parts of cognitive load, the main challenge within this framework is that there is still no measurement instrument for the different aspects of cognitive load, namely intrinsic, extraneous, and germane cognitive load. Hence, the goal of this paper is to develop a differentiated measurement of cognitive load. In Study 1 (N = 97), we developed and analyzed two strategies to measure cognitive load in a differentiated way: (1) Informed rating: We trained learners in differentiating the concepts of cognitive load, so that they could rate them in an informed way. They were asked then to rate 24 different learning situations or learning materials related to either high or low intrinsic, extraneous, or germane load. (2) Naïve rating: For this type of rating of cognitive load we developed a questionnaire with two to three items for each type of load. With this questionnaire, the same learning situations had to be rated. In the second study (N = between 65 and 95 for each task), we improved the instrument for the naïve rating. For each study, we analyzed whether the instruments are reliable and valid, for Study 1, we also checked for comparability of the two measurement strategies. In Study 2, we conducted a simultaneous scenario based factor analysis. The informed rating seems to be a promising strategy to assess the different aspects of cognitive load, but it seems not economic and feasible for larger studies and a standardized training would be necessary. The improved version of the naïve rating turned out to be a useful, feasible, and reliable instrument. Ongoing studies analyze the conceptual validity of this measurement with up to now promising results. PMID:29201011

Multiple intelligences and alternative teaching strategies: The effects on student academic achievement, conceptual understanding, and attitude

NASA Astrophysics Data System (ADS)

Baragona, Michelle

The purpose of this study was to investigate the interactions between multiple intelligence strengths and alternative teaching methods on student academic achievement, conceptual understanding and attitudes. The design was a quasi-experimental study, in which students enrolled in Principles of Anatomy and Physiology, a developmental biology course, received lecture only, problem-based learning with lecture, or peer teaching with lecture. These students completed the Multiple Intelligence Inventory to determine their intelligence strengths, the Students' Motivation Toward Science Learning questionnaire to determine student attitudes towards learning in science, multiple choice tests to determine academic achievement, and open-ended questions to determine conceptual understanding. Effects of intelligence types and teaching methods on academic achievement and conceptual understanding were determined statistically by repeated measures ANOVAs. No significance occurred in academic achievement scores due to lab group or due to teaching method used; however, significant interactions between group and teaching method did occur in students with strengths in logical-mathematical, interpersonal, kinesthetic, and intrapersonal intelligences. Post-hoc analysis using Tukey HSD tests revealed students with strengths in logical-mathematical intelligence and enrolled in Group Three scored significantly higher when taught by problem-based learning (PBL) as compared to peer teaching (PT). No significance occurred in conceptual understanding scores due to lab group or due to teaching method used; however, significant interactions between group and teaching method did occur in students with strengths in musical, kinesthetic, intrapersonal, and spatial intelligences. Post-hoc analysis using Tukey HSD tests revealed students with strengths in logical-mathematical intelligence and enrolled in Group Three scored significantly higher when taught by lecture as compared to PBL. Students with strengths in intrapersonal intelligence and enrolled in Group One scored significantly lower when taught by lecture as compared to PBL. Results of a repeated measures ANOVA for student attitudes showed significant increases in positive student attitudes toward science learning for all three types of teaching method between pretest and posttest; but there were no significant differences in posttest attitude scores by type of teaching method.

Development and preliminary testing of a self-rating instrument to measure self-directed learning ability of nursing students.

PubMed

Cheng, Su-Fen; Kuo, Chien-Lin; Lin, Kuan-Chia; Lee-Hsieh, Jane

2010-09-01

With the growing trend of preparing students for lifelong learning, the theory of self-directed learning (SDL) has been increasingly applied in the context of higher education. In order to foster lifelong learning, abilities among nursing students, faculties need to have an appropriate instrument to measure the SDL abilities of nursing students. The objectives of this study were to develop an instrument to measure the SDL abilities of nursing students and to test the validity and reliability of this instrument. This study was conducted in 4 phases. In Phase 1, based on a review of the literature, the researchers developed an instrument to measure SDL. In Phase 2, two rounds of the Delphi study were conducted, to determine the content validity of the instrument. In Phase 3, a convenience sample of 1072 nursing students from two representative schools across three different types of nursing programs were recruited to test the construct validity of the Self-Directed Learning Instrument (SDLI). Finally, in Phase 4, the internal consistency and reliability of the instrument were tested. The resulting SDLI consists of 20 items across the following four domains: learning motivation, planning and implementing, self-monitoring, and interpersonal, communication. The final model in confirmatory factor analysis revealed that this 20-item SDLI indicated a good fit of the model. The value of Cronbach's alpha for the total scale was .916 and for the four domains were .801, .861, .785, and .765, respectively. The SDLI is a valid and reliable instrument for identifying student SDL abilities. It is available to students in nursing and similar medical programs to evaluate their own SDL. This scale may also enable nursing faculty to assess students' SDL status, design better lesson plans and curricula, and, implement appropriate teaching strategies for nursing students in order to foster the growth of lifelong learning abilities. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Learning Actions, Objects and Types of Interaction: A Methodological Analysis of Expansive Learning among Pre-Service Teachers

ERIC Educational Resources Information Center

Rantavuori, Juhana; Engeström, Yrjö; Lipponen, Lasse

2016-01-01

The paper analyzes a collaborative learning process among Finnish pre-service teachers planning their own learning in a self-regulated way. The study builds on cultural-historical activity theory and the theory of expansive learning, integrating for the first time an analysis of learning actions and an analysis of types of interaction. We examine…

Classification and authentication of unknown water samples using machine learning algorithms.

PubMed

Kundu, Palash K; Panchariya, P C; Kundu, Madhusree

2011-07-01

This paper proposes the development of water sample classification and authentication, in real life which is based on machine learning algorithms. The proposed techniques used experimental measurements from a pulse voltametry method which is based on an electronic tongue (E-tongue) instrumentation system with silver and platinum electrodes. E-tongue include arrays of solid state ion sensors, transducers even of different types, data collectors and data analysis tools, all oriented to the classification of liquid samples and authentication of unknown liquid samples. The time series signal and the corresponding raw data represent the measurement from a multi-sensor system. The E-tongue system, implemented in a laboratory environment for 6 numbers of different ISI (Bureau of Indian standard) certified water samples (Aquafina, Bisleri, Kingfisher, Oasis, Dolphin, and McDowell) was the data source for developing two types of machine learning algorithms like classification and regression. A water data set consisting of 6 numbers of sample classes containing 4402 numbers of features were considered. A PCA (principal component analysis) based classification and authentication tool was developed in this study as the machine learning component of the E-tongue system. A proposed partial least squares (PLS) based classifier, which was dedicated as well; to authenticate a specific category of water sample evolved out as an integral part of the E-tongue instrumentation system. The developed PCA and PLS based E-tongue system emancipated an overall encouraging authentication percentage accuracy with their excellent performances for the aforesaid categories of water samples. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

The Relationship of Personality Differences, Evaluation Scores and Perceptions of the Clinical Learning Environment

ERIC Educational Resources Information Center

Bynum, K. Megan

2017-01-01

This study examined the relationship between personality differences between preceptor and athletic training student to evaluation scores. The personality differences of seven preceptors and their paired ATS were measured using the Myers-Briggs Type Indicator test. From the quantitative findings, we cannot conclude at this time a relationship…

Fidelity of Simulation and Transfer of Training: A Review of the Problem.

ERIC Educational Resources Information Center

Gerathewohl, Siegfried J.

The document is concerned with the several kinds of flight simulators available today which are valuable tools for research, training, and proficiency measurement. They range from simple trainer type devices useful for learning specific tasks, to very sophisticated ground based facilities and aircraft used for crew training under simulated…

Two Types of Learning in a Business Simulation.

ERIC Educational Resources Information Center

Livingston, Samuel A.

Fourteen high school students, chosen at random from a group of 28, spent 5 hours participating in a business simulation, after which all 28 students took tests designed to measure their knowledge of business facts and concepts and their ability to evaluate business decisions. The simulation group outperformed the control group on both tests, but…

Which Group Teaching Styles Best Promote Information Gain for Adults with Mental Disorders?

ERIC Educational Resources Information Center

Emer, Denise; McLarney, Amber; Goodwin, Melinda; Keller, Peggy

2002-01-01

Group psychoeducation formats were evaluated to determine which promoted the greatest learning and retention of therapeutically relevant information in adult clients with mental disorders. Study 1 compared lecture and interactive formats; Study 2 compared two types of interactive formats. Both studies also measured client satisfaction with the…

Assessing Students' Deep Conceptual Understanding in Physical Sciences: An Example on Sinking and Floating

ERIC Educational Resources Information Center

Shen, Ji; Liu, Ou Lydia; Chang, Hsin-Yi

2017-01-01

This paper presents a transformative modeling framework that guides the development of assessment to measure students' deep understanding in physical sciences. The framework emphasizes 3 types of connections that students need to make when learning physical sciences: (1) linking physical states, processes, and explanatory models, (2) integrating…

The Nature of Adolescent Learner Interaction in a Virtual High School Setting

ERIC Educational Resources Information Center

Borup, J.; Graham, C.R.; Davies, R.S.

2013-01-01

This study used survey data to measure the effect of learners' reported interactions with content, peers, and instructors on several course outcomes in two virtual high school courses that emphasized interactive learning. Surveys found that the large majority of students viewed all investigated types of interaction as educational and motivational.…

Using Machine Learning To Predict Which Light Curves Will Yield Stellar Rotation Periods

NASA Astrophysics Data System (ADS)

Agüeros, Marcel; Teachey, Alexander

2018-01-01

Using time-domain photometry to reliably measure a solar-type star's rotation period requires that its light curve have a number of favorable characteristics. The probability of recovering a period will be a non-linear function of these light curve features, which are either astrophysical in nature or set by the observations. We employ standard machine learning algorithms (artificial neural networks and random forests) to predict whether a given light curve will produce a robust rotation period measurement from its Lomb-Scargle periodogram. The algorithms are trained and validated using salient statistics extracted from both simulated light curves and their corresponding periodograms, and we apply these classifiers to the most recent Intermediate Palomar Transient Factory (iPTF) data release. With this pipeline, we anticipate measuring rotation periods for a significant fraction of the ∼4x108 stars in the iPTF footprint.

Prescribing Some Criminological Theory: An Examination of the Illicit Use of Prescription Stimulants Among College Students.

PubMed

Maahs, Jeffrey R; Weidner, Robert R; Smith, Ryan

2016-02-01

Recent evidence indicates that the illicit use of prescription stimulants such as Adderall and Ritalin is common across college campuses and in professions (e.g., trucking) where staying awake and focused is valued. Existing research has established use patterns and explored respondents' reasons for using these stimulants. Less is known, however, about whether or how well mainstream criminological theory explains this type of illegal activity. This article reports results from a survey (N = 484) of college students from a Midwestern university, examining whether measures of strain, self-control, and social learning predict the illicit use of prescription stimulants. Measures from social learning and social control theories were significant predictors of illicit use of prescription stimulants, whereas the measure of academic strain was not; the strongest predictor of illicit use of prescription stimulants was general deviance. Implications of these findings are discussed. © The Author(s) 2014.

Support Vector Machines for Differential Prediction

PubMed Central

Kuusisto, Finn; Santos Costa, Vitor; Nassif, Houssam; Burnside, Elizabeth; Page, David; Shavlik, Jude

2015-01-01

Machine learning is continually being applied to a growing set of fields, including the social sciences, business, and medicine. Some fields present problems that are not easily addressed using standard machine learning approaches and, in particular, there is growing interest in differential prediction. In this type of task we are interested in producing a classifier that specifically characterizes a subgroup of interest by maximizing the difference in predictive performance for some outcome between subgroups in a population. We discuss adapting maximum margin classifiers for differential prediction. We first introduce multiple approaches that do not affect the key properties of maximum margin classifiers, but which also do not directly attempt to optimize a standard measure of differential prediction. We next propose a model that directly optimizes a standard measure in this field, the uplift measure. We evaluate our models on real data from two medical applications and show excellent results. PMID:26158123

Support Vector Machines for Differential Prediction.

PubMed

Kuusisto, Finn; Santos Costa, Vitor; Nassif, Houssam; Burnside, Elizabeth; Page, David; Shavlik, Jude

Machine learning is continually being applied to a growing set of fields, including the social sciences, business, and medicine. Some fields present problems that are not easily addressed using standard machine learning approaches and, in particular, there is growing interest in differential prediction . In this type of task we are interested in producing a classifier that specifically characterizes a subgroup of interest by maximizing the difference in predictive performance for some outcome between subgroups in a population. We discuss adapting maximum margin classifiers for differential prediction. We first introduce multiple approaches that do not affect the key properties of maximum margin classifiers, but which also do not directly attempt to optimize a standard measure of differential prediction. We next propose a model that directly optimizes a standard measure in this field, the uplift measure. We evaluate our models on real data from two medical applications and show excellent results.

Assessing a learning process with functional ANOVA estimators of EEG power spectral densities.

PubMed

Gutiérrez, David; Ramírez-Moreno, Mauricio A

2016-04-01

We propose to assess the process of learning a task using electroencephalographic (EEG) measurements. In particular, we quantify changes in brain activity associated to the progression of the learning experience through the functional analysis-of-variances (FANOVA) estimators of the EEG power spectral density (PSD). Such functional estimators provide a sense of the effect of training in the EEG dynamics. For that purpose, we implemented an experiment to monitor the process of learning to type using the Colemak keyboard layout during a twelve-lessons training. Hence, our aim is to identify statistically significant changes in PSD of various EEG rhythms at different stages and difficulty levels of the learning process. Those changes are taken into account only when a probabilistic measure of the cognitive state ensures the high engagement of the volunteer to the training. Based on this, a series of statistical tests are performed in order to determine the personalized frequencies and sensors at which changes in PSD occur, then the FANOVA estimates are computed and analyzed. Our experimental results showed a significant decrease in the power of [Formula: see text] and [Formula: see text] rhythms for ten volunteers during the learning process, and such decrease happens regardless of the difficulty of the lesson. These results are in agreement with previous reports of changes in PSD being associated to feature binding and memory encoding.

The time course of spoken word learning and recognition: studies with artificial lexicons.

PubMed

Magnuson, James S; Tanenhaus, Michael K; Aslin, Richard N; Dahan, Delphine

2003-06-01

The time course of spoken word recognition depends largely on the frequencies of a word and its competitors, or neighbors (similar-sounding words). However, variability in natural lexicons makes systematic analysis of frequency and neighbor similarity difficult. Artificial lexicons were used to achieve precise control over word frequency and phonological similarity. Eye tracking provided time course measures of lexical activation and competition (during spoken instructions to perform visually guided tasks) both during and after word learning, as a function of word frequency, neighbor type, and neighbor frequency. Apparent shifts from holistic to incremental competitor effects were observed in adults and neural network simulations, suggesting such shifts reflect general properties of learning rather than changes in the nature of lexical representations.

Hispanic College Students' Learning Styles, Personality Types, and Gender Differences: A Collective Case Study of Ten Hispanic College Students Exposed to the Myers Briggs Type Indicator

ERIC Educational Resources Information Center

Harris, Rachelle D.

2014-01-01

The research body regarding learning styles has been abundant; however, research related to Separate and Connected learning styles has not been as copious. The purpose of this qualitative study was to explore the association between learning styles, personality types, and gender differences for Hispanic college students between the ages of 18-24…

A Usability Study of Users’ Perceptions Toward a Multimedia Computer-Assisted Learning Tool for Neuroanatomy

PubMed Central

Gould, Douglas J.; Terrell, Mark A.; Fleming, Jo

2015-01-01

This usability study evaluated users’ perceptions of a multimedia prototype for a new e-learning tool: Anatomy of the Central Nervous System: A Multimedia Course. Usability testing is a collection of formative evaluation methods that inform the developmental design of e-learning tools to maximize user acceptance, satisfaction, and adoption. Sixty-two study participants piloted the prototype and completed a usability questionnaire designed to measure two usability properties: program need and program applicability. Statistical analyses were used to test the hypothesis that the multimedia prototype was well designed and highly usable, it was perceived as: 1) highly needed across a spectrum of educational contexts, 2) highly applicable in supporting the pedagogical processes of teaching and learning neuroanatomy, and 3) was highly usable by all types of users. Three independent variables represented user differences: level of expertise (faculty vs. student), age, and gender. Analysis of the results supports the research hypotheses that the prototype was designed well for different types of users in various educational contexts and for supporting the pedagogy of neuroanatomy. In addition, the results suggest that the multimedia program will be most useful as a neuroanatomy review tool for health-professions students preparing for licensing or board exams. This study demonstrates the importance of integrating quality properties of usability with principles of human learning during the instructional design process for multimedia products. PMID:19177405

Type of High School Predicts Academic Performance at University Better than Individual Differences

PubMed Central

2016-01-01

Psychological correlates of academic performance have always been of high relevance to psychological research. The relation between psychometric intelligence and academic performance is one of the most consistent and well-established findings in psychology. It is hypothesized that intelligence puts a limit on what an individual can learn or achieve. Moreover, a growing body of literature indicates a relationship between personality traits and academic performance. This relationship helps us to better understand how an individual will learn or achieve their goals. The aim of this study is to further investigate the relationship between psychological correlates of academic performance by exploring the potentially moderating role of prior education. The participants in this study differed in the type of high school they attended. They went either to gymnasium, a general education type of high school that prepares students specifically for university studies, or to vocational school, which prepares students both for the labour market and for further studies. In this study, we used archival data of psychological testing during career guidance in the final year of high school, and information about the university graduation of those who received guidance. The psychological measures included intelligence, personality and general knowledge. The results show that gymnasium students had greater chances of performing well at university, and that this relationship exceeds the contribution of intelligence and personality traits to university graduation. Moreover, psychological measures did not interact with type of high school, which indicates that students from different school types do not profit from certain individual characteristics. PMID:27695073

Type of High School Predicts Academic Performance at University Better than Individual Differences.

PubMed

Banai, Benjamin; Perin, Višnja

2016-01-01

Psychological correlates of academic performance have always been of high relevance to psychological research. The relation between psychometric intelligence and academic performance is one of the most consistent and well-established findings in psychology. It is hypothesized that intelligence puts a limit on what an individual can learn or achieve. Moreover, a growing body of literature indicates a relationship between personality traits and academic performance. This relationship helps us to better understand how an individual will learn or achieve their goals. The aim of this study is to further investigate the relationship between psychological correlates of academic performance by exploring the potentially moderating role of prior education. The participants in this study differed in the type of high school they attended. They went either to gymnasium, a general education type of high school that prepares students specifically for university studies, or to vocational school, which prepares students both for the labour market and for further studies. In this study, we used archival data of psychological testing during career guidance in the final year of high school, and information about the university graduation of those who received guidance. The psychological measures included intelligence, personality and general knowledge. The results show that gymnasium students had greater chances of performing well at university, and that this relationship exceeds the contribution of intelligence and personality traits to university graduation. Moreover, psychological measures did not interact with type of high school, which indicates that students from different school types do not profit from certain individual characteristics.

K-12 Teachers' Perceptions of and Their Satisfaction with Interaction Type in Blended Learning Environments

ERIC Educational Resources Information Center

Kuo, Yu-Chun; Belland, Brian R.; Schroder, Kerstin E. E.; Walker, Andrew E.

2014-01-01

Blended learning is an effective approach to instruction that combines features of face-to-face learning and computer-mediated learning. This study investigated the relationship between student perceptions of three types of interaction and blended learning course satisfaction. The participants included K-12 teachers enrolled in a graduate-level…

Errors analysis of problem solving using the Newman stage after applying cooperative learning of TTW type

NASA Astrophysics Data System (ADS)

Rr Chusnul, C.; Mardiyana, S., Dewi Retno

2017-12-01

Problem solving is the basis of mathematics learning. Problem solving teaches us to clarify an issue coherently in order to avoid misunderstanding information. Sometimes there may be mistakes in problem solving due to misunderstanding the issue, choosing a wrong concept or misapplied concept. The problem-solving test was carried out after students were given treatment on learning by using cooperative learning of TTW type. The purpose of this study was to elucidate student problem regarding to problem solving errors after learning by using cooperative learning of TTW type. Newman stages were used to identify problem solving errors in this study. The new research used a descriptive method to find out problem solving errors in students. The subject in this study were students of Vocational Senior High School (SMK) in 10th grade. Test and interview was conducted for data collection. Thus, the results of this study suggested problem solving errors in students after learning by using cooperative learning of TTW type for Newman stages.

Evaluation of artificial neural network algorithms for predicting METs and activity type from accelerometer data: validation on an independent sample.

PubMed

Freedson, Patty S; Lyden, Kate; Kozey-Keadle, Sarah; Staudenmayer, John

2011-12-01

Previous work from our laboratory provided a "proof of concept" for use of artificial neural networks (nnets) to estimate metabolic equivalents (METs) and identify activity type from accelerometer data (Staudenmayer J, Pober D, Crouter S, Bassett D, Freedson P, J Appl Physiol 107: 1330-1307, 2009). The purpose of this study was to develop new nnets based on a larger, more diverse, training data set and apply these nnet prediction models to an independent sample to evaluate the robustness and flexibility of this machine-learning modeling technique. The nnet training data set (University of Massachusetts) included 277 participants who each completed 11 activities. The independent validation sample (n = 65) (University of Tennessee) completed one of three activity routines. Criterion measures were 1) measured METs assessed using open-circuit indirect calorimetry; and 2) observed activity to identify activity type. The nnet input variables included five accelerometer count distribution features and the lag-1 autocorrelation. The bias and root mean square errors for the nnet MET trained on University of Massachusetts and applied to University of Tennessee were +0.32 and 1.90 METs, respectively. Seventy-seven percent of the activities were correctly classified as sedentary/light, moderate, or vigorous intensity. For activity type, household and locomotion activities were correctly classified by the nnet activity type 98.1 and 89.5% of the time, respectively, and sport was correctly classified 23.7% of the time. Use of this machine-learning technique operates reasonably well when applied to an independent sample. We propose the creation of an open-access activity dictionary, including accelerometer data from a broad array of activities, leading to further improvements in prediction accuracy for METs, activity intensity, and activity type.

Investigating Flipped Learning: Student Self-Regulated Learning, Perceptions, and Achievement in an Introductory Biology Course

NASA Astrophysics Data System (ADS)

Sletten, Sarah Rae

2017-06-01

In flipped classrooms, lectures, which are normally delivered in-class, are assigned as homework in the form of videos, and assignments that were traditionally assigned as homework, are done as learning activities in class. It was hypothesized that the effectiveness of the flipped model hinges on a student's desire and ability to adopt a self-directed learning style. The purpose of this study was twofold; it aimed at examining the relationship between two variables—students' perceptions of the flipped model and their self-regulated learning (SRL) behaviors—and the impact that these variables have on achievement in a flipped class. For the study, 76 participants from a flipped introductory biology course were asked about their SRL strategy use and perceptions of the flipped model. SRL strategy use was measured using a modified version of the Motivated Strategies for Learning Questionnaire (MSLQ; Wolters et al. 2005), while the flipped perceptions survey was newly derived. Student letter grades were collected as a measure of achievement. Through regression analysis, it was found that students' perceptions of the flipped model positively predict students' use of several types of SRL strategies. However, the data did not indicate a relationship between student perceptions and achievement, neither directly nor indirectly, through SRL strategy use. Results suggest that flipped classrooms demonstrate their successes in the active learning sessions through constructivist teaching methods. Video lectures hold an important role in flipped classes, however, students may need to practice SRL skills to become more self-directed and effectively learn from them.

Environmental Monitoring Networks Optimization Using Advanced Active Learning Algorithms

NASA Astrophysics Data System (ADS)

Kanevski, Mikhail; Volpi, Michele; Copa, Loris

2010-05-01

The problem of environmental monitoring networks optimization (MNO) belongs to one of the basic and fundamental tasks in spatio-temporal data collection, analysis, and modeling. There are several approaches to this problem, which can be considered as a design or redesign of monitoring network by applying some optimization criteria. The most developed and widespread methods are based on geostatistics (family of kriging models, conditional stochastic simulations). In geostatistics the variance is mainly used as an optimization criterion which has some advantages and drawbacks. In the present research we study an application of advanced techniques following from the statistical learning theory (SLT) - support vector machines (SVM) and the optimization of monitoring networks when dealing with a classification problem (data are discrete values/classes: hydrogeological units, soil types, pollution decision levels, etc.) is considered. SVM is a universal nonlinear modeling tool for classification problems in high dimensional spaces. The SVM solution is maximizing the decision boundary between classes and has a good generalization property for noisy data. The sparse solution of SVM is based on support vectors - data which contribute to the solution with nonzero weights. Fundamentally the MNO for classification problems can be considered as a task of selecting new measurement points which increase the quality of spatial classification and reduce the testing error (error on new independent measurements). In SLT this is a typical problem of active learning - a selection of the new unlabelled points which efficiently reduce the testing error. A classical approach (margin sampling) to active learning is to sample the points closest to the classification boundary. This solution is suboptimal when points (or generally the dataset) are redundant for the same class. In the present research we propose and study two new advanced methods of active learning adapted to the solution of MNO problem: 1) hierarchical top-down clustering in an input space in order to remove redundancy when data are clustered, and 2) a general method (independent on classifier) which gives posterior probabilities that can be used to define the classifier confidence and corresponding proposals for new measurement points. The basic ideas and procedures are explained by applying simulated data sets. The real case study deals with the analysis and mapping of soil types, which is a multi-class classification problem. Maps of soil types are important for the analysis and 3D modeling of heavy metals migration in soil and prediction risk mapping. The results obtained demonstrate the high quality of SVM mapping and efficiency of monitoring network optimization by using active learning approaches. The research was partly supported by SNSF projects No. 200021-126505 and 200020-121835.

Morningness-eveningness preferences, learning approach and academic achievement of undergraduate medical students.

PubMed

Akram, Nimra; Khan, Naheed; Ameen, Mehreen; Mahmood, Shahmeera; Shamim, Komal; Amin, Marium; Rana, Qurrat Ul Ain

2018-05-15

Several studies have focused on determining the effect of chronotype and learning approach on academic achievement separately indicating that morning types have an academic advantage over the evening types and so have the deep learners over the surface learners. But, surprisingly none have assessed the possible relationship between chronotype and learning approach. So, the current study aimed to evaluate this association and their individual influence on academic performance as indicated by the Cumulative Grade Point Average (CGPA) as well as the effect of their interaction on academic performance. The study included 345 undergraduate medical students who responded to reduced Morningness-Eveningness Questionnaire and Biggs Revised Two-Factor Study Process Questionnaire. Morning types indulged in deep learning while evening types in surface learning. Morning and evening types did not differ on academic performance but deep learners had better academic outcomes than their counterparts. The interaction between chronotype and learning approach was significant on determining academic achievement. Our findings gave the impression that chronotype could have an impact on academic performance not directly but indirectly through learning approaches.

Effectiveness of an e-Learning Platform for Image Interpretation Education of Medical Staff and Students.

PubMed

Ogura, Akio; Hayashi, Norio; Negishi, Tohru; Watanabe, Haruyuki

2018-05-09

Medical staff must be able to perform accurate initial interpretations of radiography to prevent diagnostic errors. Education in medical image interpretation is an ongoing need that is addressed by text-based and e-learning platforms. The effectiveness of these methods has been previously reported. Here, we describe the effectiveness of an e-learning platform used for medical image interpretation education. Ten third-year medical students without previous experience in chest radiography interpretation were provided with e-learning instructions. Accuracy of diagnosis using chest radiography was provided before and after e-learning education. We measured detection accuracy for two image groups: nodular shadow and ground-glass shadow. We also distributed the e-learning system to the two groups and analyzed the effectiveness of education for both types of image shadow. The mean correct answer rate after the 2-week e-learning period increased from 34.5 to 72.7%. Diagnosis of the ground glass shadow improved significantly more than that of the mass shadow. Education using the e-leaning platform is effective for interpretation of chest radiography results. E-learning is particularly effective for the interpretation of chest radiography images containing ground glass shadow.

Participatory Equity and Student Outcomes in Living-Learning Programs of Differing Thematic Types

ERIC Educational Resources Information Center

Soldner, Matthew Edward

2011-01-01

This study evaluated participatory equity in varying thematic types of living-learning programs and, for a subset of student group x program type combinations found to be below equity, used latent mean modeling to determine whether statistically significant mean differences existed between the outcome scores of living-learning participants and…

Correlation of Students' Brain Types to Their Conceptions of Learning Science and Approaches to Learning Science

ERIC Educational Resources Information Center

Park, Jiyeon; Jeon, Dongryul

2015-01-01

The systemizing and empathizing brain type represent two contrasted students' characteristics. The present study investigated differences in the conceptions and approaches to learning science between the systemizing and empathizing brain type students. The instruments are questionnaires on the systematizing and empathizing, questionnaires on the…

Improving Open Access through Prior Learning Assessment

ERIC Educational Resources Information Center

Yin, Shuangxu; Kawachi, Paul

2013-01-01

This paper explores and presents new data on how to improve open access in distance education through using prior learning assessments. Broadly there are three types of prior learning assessment (PLAR): Type-1 for prospective students to be allowed to register for a course; Type-2 for current students to avoid duplicating work-load to gain…

Practice-based learning can improve osteoporosis care.

PubMed

Hess, Brian J; Johnston, Mary M; Iobst, William F; Lipner, Rebecca S

2013-10-01

To examine physician engagement in practice-based learning using a self-evaluation module to assess and improve their care of individuals with or at risk of osteoporosis. Retrospective cohort study. Internal medicine and subspecialty clinics. Eight hundred fifty U.S. physicians with time-limited certification in general internal medicine or a subspecialty. Performance rates on 23 process measures and seven practice system domain scores were obtained from the American Board of Internal Medicine (ABIM) Osteoporosis Practice Improvement Module (PIM), an Internet-based self-assessment module that physicians use to improve performance on one targeted measure. Physicians remeasured performance on their targeted measures by conducting another medical chart review. Variability in performance on measures was found, with observed differences between general internists, geriatricians, and rheumatologists. Some practice system elements were modestly associated with measure performance; the largest association was between providing patient-centered self-care support and documentation of calcium intake and vitamin D estimation and counseling (correlation coefficients from 0.20 to 0.28, Ps < .002). For all practice types, the most commonly selected measure targeted for improvement was documentation of vitamin D level (38% of physicians). On average, physicians reported significant and large increases in performance on measures targeted for improvement. Gaps exist in the quality of osteoporosis care, and physicians can apply practice-based learning using the ABIM PIM to take action to improve the quality of care. © 2013, Copyright the Authors Journal compilation © 2013, The American Geriatrics Society.

Sea Slugs, Subliminal Pictures, and Vegetative State Patients: Boundaries of Consciousness in Classical Conditioning

PubMed Central

Bekinschtein, Tristan A.; Peeters, Moos; Shalom, Diego; Sigman, Mariano

2011-01-01

Classical (trace) conditioning is a specific variant of associative learning in which a neutral stimulus leads to the subsequent prediction of an emotionally charged or noxious stimulus after a temporal gap. When conditioning is concurrent with a distraction task, only participants who can report the relationship (the contingency) between stimuli explicitly show associative learning. This suggests that consciousness is a prerequisite for trace conditioning. We review and question three main controversies concerning this view. Firstly, virtually all animals, even invertebrate sea slugs, show this type of learning; secondly, unconsciously perceived stimuli may elicit trace conditioning; and thirdly, some vegetative state patients show trace learning. We discuss and analyze these seemingly contradictory arguments to find the theoretical boundaries of consciousness in classical conditioning. We conclude that trace conditioning remains one of the best measures to test conscious processing in the absence of explicit reports. PMID:22164148

Overcoming complexities: Damage detection using dictionary learning framework

NASA Astrophysics Data System (ADS)

Alguri, K. Supreet; Melville, Joseph; Deemer, Chris; Harley, Joel B.

2018-04-01

For in situ damage detection, guided wave structural health monitoring systems have been widely researched due to their ability to evaluate large areas and their ability detect many types of damage. These systems often evaluate structural health by recording initial baseline measurements from a pristine (i.e., undamaged) test structure and then comparing later measurements with that baseline. Yet, it is not always feasible to have a pristine baseline. As an alternative, substituting the baseline with data from a surrogate (nearly identical and pristine) structure is a logical option. While effective in some circumstance, surrogate data is often still a poor substitute for pristine baseline measurements due to minor differences between the structures. To overcome this challenge, we present a dictionary learning framework to adapt surrogate baseline data to better represent an undamaged test structure. We compare the performance of our framework with two other surrogate-based damage detection strategies: (1) using raw surrogate data for comparison and (2) using sparse wavenumber analysis, a precursor to our framework for improving the surrogate data. We apply our framework to guided wave data from two 108 mm by 108 mm aluminum plates. With 20 measurements, we show that our dictionary learning framework achieves a 98% accuracy, raw surrogate data achieves a 92% accuracy, and sparse wavenumber analysis achieves a 57% accuracy.

Integrating Collaborative Learning Groups in the Large Enrollment Lecture

NASA Astrophysics Data System (ADS)

Adams, J. P.; Brissenden, G.; Lindell Adrian, R.; Slater, T. F.

1998-12-01

Recent reforms for undergraduate education propose that students should work in teams to solve problems that simulate problems that research scientists address. In the context of an innovative large-enrollment course at Montana State University, faculty have developed a series of 15 in-class, collaborative learning group activities that provide students with realistic scenarios to investigate. Focusing on a team approach, the four principle types of activities employed are historical, conceptual, process, and open-ended activities. Examples of these activities include classifying stellar spectra, characterizing galaxies, parallax measurements, estimating stellar radii, and correlating star colors with absolute magnitudes. Summative evaluation results from a combination of attitude surveys, astronomy concept examinations, and focus group interviews strongly suggest that, overall, students are learning more astronomy, believe that the group activities are valuable, enjoy the less-lecture course format, and have significantly higher attendance rates. In addition, class observations of 48 self-formed, collaborative learning groups reveal that female students are more engaged in single-gender learning groups than in mixed gender groups.

Emergent literacy in print and electronic contexts: The influence of book type, narration source, and attention.

PubMed

O'Toole, Kathryn J; Kannass, Kathleen N

2018-09-01

Young children learn from traditional print books, but there has been no direct comparison of their learning from print books and tablet e-books while controlling for narration source. The current project used a between-subjects design and examined how 4-year-olds (N = 100) learned words and story content from a print book read aloud by a live adult, a print book narrated by an audio device, an e-book read aloud by a live adult, and an e-book narrated by an audio device. Attention to the book and prior experience with tablet e-books were also measured and included in analyses. When controlling for vocabulary, the overall pattern of results revealed that children learned more words from the e-book and from the audio narrator, but story comprehension did not differ as a function of condition. Attention predicted learning, but only in some print book contexts, and significant effects of prior experience did not emerge. Copyright © 2018 Elsevier Inc. All rights reserved.

Identifying Green Infrastructure from Social Media and Crowdsourcing- An Image Based Machine-Learning Approach.

NASA Astrophysics Data System (ADS)

Rai, A.; Minsker, B. S.

2016-12-01

In this work we introduce a novel dataset GRID: GReen Infrastructure Detection Dataset and a framework for identifying urban green storm water infrastructure (GI) designs (wetlands/ponds, urban trees, and rain gardens/bioswales) from social media and satellite aerial images using computer vision and machine learning methods. Along with the hydrologic benefits of GI, such as reducing runoff volumes and urban heat islands, GI also provides important socio-economic benefits such as stress recovery and community cohesion. However, GI is installed by many different parties and cities typically do not know where GI is located, making study of its impacts or siting new GI difficult. We use object recognition learning methods (template matching, sliding window approach, and Random Hough Forest method) and supervised machine learning algorithms (e.g., support vector machines) as initial screening approaches to detect potential GI sites, which can then be investigated in more detail using on-site surveys. Training data were collected from GPS locations of Flickr and Instagram image postings and Amazon Mechanical Turk identification of each GI type. Sliding window method outperformed other methods and achieved an average F measure, which is combined metric for precision and recall performance measure of 0.78.

The Effects of Rhythmicity and Amplitude on Transfer of Motor Learning

PubMed Central

Ben-Tov, Mor; Levy-Tzedek, Shelly; Karniel, Amir

2012-01-01

We perform rhythmic and discrete arm movements on a daily basis, yet the motor control literature is not conclusive regarding the mechanisms controlling these movements; does a single mechanism generate both movement types, or are they controlled by separate mechanisms? A recent study reported partial asymmetric transfer of learning from discrete movements to rhythmic movements. Other studies have shown transfer of learning between large-amplitude to small-amplitude movements. The goal of this study is to explore which aspect is important for learning to be transferred from one type of movement to another: rhythmicity, amplitude or both. We propose two hypotheses: (1) Rhythmic and discrete movements are generated by different mechanisms; therefore we expect to see a partial or no transfer of learning between the two types of movements; (2) Within each movement type (rhythmic/discrete), there will be asymmetric transition of learning from larger movements to smaller ones. We used a learning-transfer paradigm, in which 70 participants performed flexion/extension movements with their forearm, and switched between types of movement, which differed in amplitude and/or rhythmicity. We found partial transfer of learning between discrete and rhythmic movements, and an asymmetric transfer of learning from larger movements to smaller movements (within the same type of movement). Our findings suggest that there are two different mechanisms underlying the generation of rhythmic and discrete arm movements, and that practicing on larger movements helps perform smaller movements; the latter finding might have implications for rehabilitation. PMID:23056549

The effects of rhythmicity and amplitude on transfer of motor learning.

PubMed

Ben-Tov, Mor; Levy-Tzedek, Shelly; Karniel, Amir

2012-01-01

We perform rhythmic and discrete arm movements on a daily basis, yet the motor control literature is not conclusive regarding the mechanisms controlling these movements; does a single mechanism generate both movement types, or are they controlled by separate mechanisms? A recent study reported partial asymmetric transfer of learning from discrete movements to rhythmic movements. Other studies have shown transfer of learning between large-amplitude to small-amplitude movements. The goal of this study is to explore which aspect is important for learning to be transferred from one type of movement to another: rhythmicity, amplitude or both. We propose two hypotheses: (1) Rhythmic and discrete movements are generated by different mechanisms; therefore we expect to see a partial or no transfer of learning between the two types of movements; (2) Within each movement type (rhythmic/discrete), there will be asymmetric transition of learning from larger movements to smaller ones. We used a learning-transfer paradigm, in which 70 participants performed flexion/extension movements with their forearm, and switched between types of movement, which differed in amplitude and/or rhythmicity. We found partial transfer of learning between discrete and rhythmic movements, and an asymmetric transfer of learning from larger movements to smaller movements (within the same type of movement). Our findings suggest that there are two different mechanisms underlying the generation of rhythmic and discrete arm movements, and that practicing on larger movements helps perform smaller movements; the latter finding might have implications for rehabilitation.

An Incremental Type-2 Meta-Cognitive Extreme Learning Machine.

PubMed

Pratama, Mahardhika; Zhang, Guangquan; Er, Meng Joo; Anavatti, Sreenatha

2017-02-01

Existing extreme learning algorithm have not taken into account four issues: 1) complexity; 2) uncertainty; 3) concept drift; and 4) high dimensionality. A novel incremental type-2 meta-cognitive extreme learning machine (ELM) called evolving type-2 ELM (eT2ELM) is proposed to cope with the four issues in this paper. The eT2ELM presents three main pillars of human meta-cognition: 1) what-to-learn; 2) how-to-learn; and 3) when-to-learn. The what-to-learn component selects important training samples for model updates by virtue of the online certainty-based active learning method, which renders eT2ELM as a semi-supervised classifier. The how-to-learn element develops a synergy between extreme learning theory and the evolving concept, whereby the hidden nodes can be generated and pruned automatically from data streams with no tuning of hidden nodes. The when-to-learn constituent makes use of the standard sample reserved strategy. A generalized interval type-2 fuzzy neural network is also put forward as a cognitive component, in which a hidden node is built upon the interval type-2 multivariate Gaussian function while exploiting a subset of Chebyshev series in the output node. The efficacy of the proposed eT2ELM is numerically validated in 12 data streams containing various concept drifts. The numerical results are confirmed by thorough statistical tests, where the eT2ELM demonstrates the most encouraging numerical results in delivering reliable prediction, while sustaining low complexity.

Motivation Matters? The Relationship among Different Types of Learning Motivation, Engagement Behaviors and Learning Outcomes of Undergraduate Students in Taiwan

ERIC Educational Resources Information Center

Hsieh, Tzu-Ling

2014-01-01

The purpose of this study is to understand predictors of different learning outcomes among various student background characteristics, types of learning motivation and engagement behaviors. 178 junior students were surveyed at a 4-year research university in Taiwan. The scales of motivation, engagement and perceived learning outcomes were adapted…

Testing the effectiveness of problem-based learning with learning-disabled students in biology

NASA Astrophysics Data System (ADS)

Guerrera, Claudia Patrizia

The purpose of the present study was to investigate the effects of problem-based learning (PBL) with learning-disabled (LD) students. Twenty-four students (12 dyads) classified as LD and attending a school for the learning-disabled participated in the study. Students engaged in either a computer-based environment involving BioWorld, a hospital simulation designed to teach biology students problem-solving skills, or a paper-and-pencil version based on the computer program. A hybrid model of learning was adopted whereby students were provided with direct instruction on the digestive system prior to participating in a problem-solving activity. Students worked in dyads and solved three problems involving the digestive system in either a computerized or a paper-and-pencil condition. The experimenter acted as a coach to assist students throughout the problem-solving process. A follow-up study was conducted, one month later, to measure the long-term learning gains. Quantitative and qualitative methods were used to analyze three types of data: process data, outcome data, and follow-up data. Results from the process data showed that all students engaged in effective collaboration and became more systematic in their problem solving over time. Findings from the outcome and follow-up data showed that students in both treatment conditions, made both learning and motivational gains and that these benefits were still evident one month later. Overall, results demonstrated that the computer facilitated students' problem solving and scientific reasoning skills. Some differences were noted in students' collaboration and the amount of assistance required from the coach in both conditions. Thus, PBL is an effective learning approach with LD students in science, regardless of the type of learning environment. These results have implications for teaching science to LD students, as well as for future designs of educational software for this population.

Medical student changes in self-regulated learning during the transition to the clinical environment.

PubMed

Cho, Kenneth K; Marjadi, Brahm; Langendyk, Vicki; Hu, Wendy

2017-03-21

Self-regulated learning (SRL), which is learners' ability to proactively select and use different strategies to reach learning goals, is associated with academic and clinical success and life-long learning. SRL does not develop automatically in the clinical environment and its development during the preclinical to clinical learning transition has not been quantitatively studied. Our study aims to fill this gap by measuring SRL in medical students during the transitional period and examining its contributing factors. Medical students were invited to complete a questionnaire at the commencement of their first clinical year (T0), and 10 weeks later (T1). The questionnaire included the Motivated Strategies for Learning Questionnaire (MSLQ) and asked about previous clinical experience. Information about the student's background, demographic characteristics and first clinical rotation were also gathered. Of 118 students invited to participate, complete paired responses were obtained from 72 medical students (response rate 61%). At T1, extrinsic goal orientation increased and was associated with gender (males were more likely to increase extrinsic goal orientation) and type of first attachment (critical care and community based attachments, compared to hospital ward based attachments). Metacognitive self-regulation decreased at T1 and was negatively associated with previous clinical experience. Measurable changes in self-regulated learning occur during the transition from preclinical learning to clinical immersion, particularly in the domains of extrinsic goal orientation and metacognitive self-regulation. Self-determination theory offers possible explanations for this finding which have practical implications and point the way to future research. In addition, interventions to promote metacognition before the clinical immersion may assist in preserving SRL during the transition and thus promote life-long learning skills in preparation for real-world practice.

Special Issue: Faculty Members' Scholarly Learning across Institutional Types

ERIC Educational Resources Information Center

Baker, Vickie L.; Terosky, Aimee LaPointe; Martinez, Edna

2017-01-01

Scholarly learning has been and continues to be largely understudied and misunderstood; oftentimes scholarly learning is only studied in the context of research universities (Neumann, 2009a), thereby failing to acknowledge the ways in which faculty scholarly learning is enacted and supported across institutional types. In this monograph, the…

The Scientific Status of Learning Styles Theories

ERIC Educational Resources Information Center

Willingham, Daniel T.; Hughes, Elizabeth M.; Dobolyi, David G.

2015-01-01

Theories of learning styles suggest that individuals think and learn best in different ways. These are not differences of ability but rather preferences for processing certain types of information or for processing information in certain types of way. If accurate, learning styles theories could have important implications for instruction because…

Peer Interaction in Three Collaborative Learning Environments

ERIC Educational Resources Information Center

Staarman, Judith Kleine; Krol, Karen; Meijden, Henny van der

2005-01-01

The aim of the study was to gain insight into the occurrence of different types of peer interaction and particularly the types of interaction beneficial for learning in different collaborative learning environments. Based on theoretical notions related to collaborative learning and peer interaction, a coding scheme was developed to analyze the…

Control of a simulated arm using a novel combination of Cerebellar learning mechanisms

NASA Technical Reports Server (NTRS)

Assad, C.; Hartmann, M.; Paulin, M. G.

2001-01-01

We present a model of cerebellar cortex that combines two types of learning: feedforward predicitve association based on local Hebbian-type learning between granule cell ascending branch and parallel fiber inputs, and reinforcement learning with feedback error correction based on climbing fiber activity.

Effects of Instructions and Stimulus Representation on Children's Selective Learning.

ERIC Educational Resources Information Center

Gottfried, Adele E.

Developmental selective learning processes of elementary school age children were investigated using two types of incidental learning methodologies. The purposes of this study were to: (1) compare the effects of the two types of incidental learning paradigms, and (2) determine the influence of different kinds of stimulus relationships on…

Washback to Learning Outcomes: A Comparative Study of IELTS Preparation and University Pre-Sessional Language Courses

ERIC Educational Resources Information Center

Green, Anthony

2007-01-01

This study investigated whether dedicated test preparation classes gave learners an advantage in improving their writing test scores. Score gains following instruction on a measure of academic writing skills--the International English Language Testing System (IELTS) academic writing test--were compared across language courses of three types; all…

Facebook Enhanced College Courses and the Impact of Personality on Sense of Classroom Community

ERIC Educational Resources Information Center

Barczyk, Casimir C.; Duncan, Doris G.

2017-01-01

The impact of personality type on students' sense of classroom connectedness was examined in a study of university-level business courses that used Facebook to enhance classroom learning. The study was conducted using an independent measures static group comparison research design. Nearly 600 students registered in six different business courses…

Rational Number Learning in the Early Years: What is Possible?

ERIC Educational Resources Information Center

Hunting, Robert P.

This report describes an investigation of how young children respond to two types of tasks: (1) finding one-half of a continuous and a discrete material; and (2) attempting to share continuous and discrete material equally between two dolls. Continuous material, such as string, paper, or liquid, is quantified by adults using measurement units. A…

Formative Assessment and Increased Student Involvement Increase Grades in an Upper Secondary School Biology Course

ERIC Educational Resources Information Center

Granbom, Martin

2016-01-01

This study shows that formative methods and increased student participation has a positive influence on learning measured as grades. The study was conducted during the course Biology A in a Swedish Upper Secondary School. The students constructed grade criteria and defined working methods and type of examination within a given topic, Gene…

The Effects of Idealized and Grounded Materials on Learning, Transfer, and Interest: An Organizing Framework for Categorizing External Knowledge Representations

ERIC Educational Resources Information Center

Belenky, Daniel M.; Schalk, Lennart

2014-01-01

Research in both cognitive and educational psychology has explored the effect of different types of external knowledge representations (e.g., manipulatives, graphical/pictorial representations, texts) on a variety of important outcome measures. We place this large and multifaceted research literature into an organizing framework, classifying three…

Measuring the attitudes and awareness of environmental education camp users

Treesearch

Roger E. McCay; David A. Gansner; John J. Padalino

1978-01-01

Questionnaires for evaluating what people expect from environmental camps and what they learn while there have been developed and applied at the Pocono Environmental Education Center, Dingman's Ferry, Penna. Nine questionnaires for various ages and types of users are presented. The results can be used by camp administrators and educators to evaluate their own...

The Hows and Whys of Studying: The Relationship of Goals to Strategies.

ERIC Educational Resources Information Center

Nolen, Susan Bobbitt

A correlational study of 62 8th grade, 60 11th grade, and 58 college students investigated developmental differences in learning goals, study strategy beliefs and their inter-relationship for science classes. Questionnaires measured levels of task orientation, ego orientation, and work avoidance, as well as belief in the utility of two types of…

2010 CEOS Field Reflectance Intercomparisons Lessons Learned

NASA Technical Reports Server (NTRS)

Thome, Kurtis; Fox, Nigel

2011-01-01

This paper summarizes lessons learned from the 2009 and 2010 joint field campaigns to Tuz Golu, Turkey. Emphasis is placed on the 2010 campaign related to understanding the equipment and measurement protocols, processing schemes, and traceability to SI quantities. Participants in both 2009 and 2010 used an array of measurement approaches to determine surface reflectance. One lesson learned is that even with all of the differences in collection between groups, the differences in reflectance are currently dominated by instrumental artifacts including knowledge of the white reference. Processing methodology plays a limited role once the bi-directional reflectance of the white reference is used rather than a hemispheric-directional value. The lack of a basic set of measurement protocols, or best practices, limits a group s ability to ensure SI traceability and the development of proper error budgets. Finally, rigorous attention to sampling methodology and its impact on instrument behavior is needed. The results of the 2009 and 2010 joint campaigns clearly demonstrate both the need and utility of such campaigns and such comparisons must continue in the future to ensure a coherent set of data that can span multiple sensor types and multiple decades.

Undergraduates Achieve Learning Gains in Plant Genetics through Peer Teaching of Secondary Students

PubMed Central

Chrispeels, H. E.; Klosterman, M. L.; Martin, J. B.; Lundy, S. R.; Watkins, J. M.; Gibson, C. L.

2014-01-01

This study tests the hypothesis that undergraduates who peer teach genetics will have greater understanding of genetic and molecular biology concepts as a result of their teaching experiences. Undergraduates enrolled in a non–majors biology course participated in a service-learning program in which they led middle school (MS) or high school (HS) students through a case study curriculum to discover the cause of a green tomato variant. The curriculum explored plant reproduction and genetic principles, highlighting variation in heirloom tomato fruits to reinforce the concept of the genetic basis of phenotypic variation. HS students were taught additional activities related to mole­cular biology techniques not included in the MS curriculum. We measured undergraduates’ learning outcomes using pre/postteaching content assessments and the course final exam. Undergraduates showed significant gains in understanding of topics related to the curriculum they taught, compared with other course content, on both types of assessments. Undergraduates who taught HS students scored higher on questions specific to the HS curriculum compared with undergraduates who taught MS students, despite identical lecture content, on both types of assessments. These results indicate the positive effect of service-learning peer-teaching experiences on undergraduates’ content knowledge, even for non–science major students. PMID:25452487

Learning styles of preclinical students in a medical college in western Nepal.

PubMed

Shankar, P R; Dubey, A K; Binu, V S; Subish, P; Deshpande, V Y

2006-01-01

Information on the learning styles of medical students are lacking in medical colleges in Nepal. Learning styles may be associated with student understanding and may predict success in examination. The present study was carried out to obtain information on learning styles and preferences for teaching of fourth semester medical students and note the association, if any, between respondents' personal characteristics and preferences for learning styles and types of teaching. The correlation between preferences for learning styles and types of teaching and performance in the second year university examination was also explored. The study was carried out during October 2003 at the Manipal College of Medical Sciences, Pokhara, Nepal using the Approaches and Study Skills Inventory (ASSIST) instrument. Information on the respondents' personal characteristics was collected. Respondents had to indicate their degree of agreement with a set of statements using a modified Likert-type scale. The statements were grouped into three main learning styles and two types of teaching. The median scores among different subgroups of respondents were compared using appropriate non-parametric tests (p<0.05). Ninety-two students (92%) participated; fifty-six were male. Thirty-one respondents were Nepalese, 48 were Indians. Majority were educated in English medium schools. The median scores for deep and surface learning styles were 64 and 49 respectively (maximum score=80). The scores for strategic learning was 75.5 (maximum score=100). There was no clear preference for any particular type of teaching. Indian students used more surface apathetic learning strategies compared to others. There was a negative correlation between surface learning and marks obtained in the final examination. The students mainly used deep and strategic learning styles. Differences in preference for learning styles and types of teaching were noted according the respondents' personal characteristics. This was a preliminary study and further studies are required.

The effect of design modifications to the typographical layout of the New York State elementary science learning standards on user preference and process time

NASA Astrophysics Data System (ADS)

Arnold, Jeffery E.

The purpose of this study was to determine the effect of four different design layouts of the New York State elementary science learning standards on user processing time and preference. Three newly developed layouts contained the same information as the standards core curriculum. In this study, the layout of the core guide is referred to as Book. The layouts of the new documents are referred to as Chart, Map, and Tabloid based on the format used to convey content hierarchy information. Most notably, all the new layouts feature larger page sizes, color, page tabs, and an icon based navigation system (IBNS). A convenience sample of 48 New York State educators representing three educator types (16 pre-service teachers, 16 in-service teachers, and 16 administrators) participated in the study. After completing timed tasks accurately, participants scored each layout based on preference. Educator type and layout were the independent variables, and process time and user preference were the dependent variables. A two-factor experimental design with Educator Type as the between variable and with repeated measures on Layout, the within variable, showed a significant difference in process time for Educator Type and Layout. The main effect for Educator Type (F(2, 45) = 8.03, p <.001) was significant with an observed power of .94, and an effect size of .26. The pair-wise comparisons for process time showed that pre-service teachers (p = .02) and administrators (p =.009) completed the assigned tasks more quickly when compared to in-service teachers. The main effect for Layout (F(3, 135) = 4.47, p =.01) was also significant with an observed power of .80, and an effect size of .09. Pair-wise comparisons showed that the newly developed Chart (p = .019) and Map (p = .032) layouts reduced overall process time when compared to the existing state learning standards (Book). The Layout X Educator type interaction was not significant. The same two-factor experimental design on preference, showed the main effect for Layout (F(3, 135) = 28.43, p =.001) was significant. The observed power was 1.0, with an effect size of .39. Pair-wise comparisons for preference scores showed that the Chart (p = .001), Map (p = .001), and Tabloid (p = .001) were preferred over the Book layout. The Layout Type X Educator Type interaction and the main effect for Educator Type were not significant. This study provides evidence that the newly developed design layouts improve usability (as measured by process time and preference scores) of the New York State elementary science learning standard documents. Features in the new layout design, such as the IBNS, may provide a foundation for a visual language and aid users in navigating standard documents across grade level and subject areas. Implications for the next generation of standard documents are presented.

Ensemble learning for spatial interpolation of soil potassium content based on environmental information.

PubMed

Liu, Wei; Du, Peijun; Wang, Dongchen

2015-01-01

One important method to obtain the continuous surfaces of soil properties from point samples is spatial interpolation. In this paper, we propose a method that combines ensemble learning with ancillary environmental information for improved interpolation of soil properties (hereafter, EL-SP). First, we calculated the trend value for soil potassium contents at the Qinghai Lake region in China based on measured values. Then, based on soil types, geology types, land use types, and slope data, the remaining residual was simulated with the ensemble learning model. Next, the EL-SP method was applied to interpolate soil potassium contents at the study site. To evaluate the utility of the EL-SP method, we compared its performance with other interpolation methods including universal kriging, inverse distance weighting, ordinary kriging, and ordinary kriging combined geographic information. Results show that EL-SP had a lower mean absolute error and root mean square error than the data produced by the other models tested in this paper. Notably, the EL-SP maps can describe more locally detailed information and more accurate spatial patterns for soil potassium content than the other methods because of the combined use of different types of environmental information; these maps are capable of showing abrupt boundary information for soil potassium content. Furthermore, the EL-SP method not only reduces prediction errors, but it also compliments other environmental information, which makes the spatial interpolation of soil potassium content more reasonable and useful.

A study of the effects of constructivist-based vs. traditional direct instruction on 8th grade science comprehension

NASA Astrophysics Data System (ADS)

Berube, Clair Thompson

2001-07-01

Studies conducted nationwide over the past several decades point consistently to the evidence that American school children lag behind several other countries in science scores. Problems arise from this dilemma, including the question of the ability of our youngsters to compete nationally and globally in the sciences as adults. Current research in this area of scores currently studies mostly mathematics. The few studies conducted concerning science mainly highlight students in other countries and neglects minorities and females regarding outcomes. By contrast, this study investigated the effects of teacher types (also defined as teaching styles or classroom orientation) on student outcomes on two measures; the standardized Standards of Learning 8th grade science test for the state of Virginia, and the Higher-Order Skills test (Berube, 2001), which was a researcher-constricted comprehension measurement. Minority and gender interactions were analyzed as well. Teacher type was designated by using the Constructivist Learning Environment Survey (Taylor & Fraser, 1991). Participants included students from five large urban middle schools and thirteen middle school science teachers. Scores from the two measures were used to determine differences in student outcomes as they pertained to teacher type, gender and ethnicity. Analysis indicated that students who were taught by teachers with more traditional and mixed teaching styles performed better on the Higher-Order Skills comprehension measurement, while teachers with constructivist teaching styles actually had the lowest scoring students. Also, the interaction of ethnicity and teacher type was significant, indicating that Higher-Order Skills scores were influenced by that interaction, with Caucasians scoring the highest when taught by teachers with mixed teaching styles. Such findings could profit school administrators considering the interaction of student achievement and teaching styles on high-stakes testing environments. Suggestions are made for future studies concerning females and minorities in these same environments.

Diverse Family Types and Out-of-School Learning Time of Young School-Age Children

ERIC Educational Resources Information Center

Ono, Hiromi; Sanders, James

2010-01-01

Sources of differentials in out-of-school learning time between children in first marriage biological parent families and children in six nontraditional family types are identified. Analyses of time diaries reveal that children in four of the six nontraditional family types spend fewer minutes learning than do children in first marriage biological…

Using Cooperative Learning to Teach via Text Types

ERIC Educational Resources Information Center

Jacobs, George M.; Yong, Seah-Tay Hui

2004-01-01

This article offers ideas as to how students can collaborate as they learn about and utilize a variety of text types (also known as rhetorical modes). The article begins with explanations of the teaching of text types and cooperative learning. The longest section of the article consists of examples of ways that students can use cooperative…

How Do B-Learning and Learning Patterns Influence Learning Outcomes?

PubMed Central

Sáiz Manzanares, María Consuelo; Marticorena Sánchez, Raúl; García Osorio, César Ignacio; Díez-Pastor, José F.

2017-01-01

Learning Management System (LMS) platforms provide a wealth of information on the learning patterns of students. Learning Analytics (LA) techniques permit the analysis of the logs or records of the activities of both students and teachers on the on-line platform. The learning patterns differ depending on the type of Blended Learning (B-Learning). In this study, we analyse: (1) whether significant differences exist between the learning outcomes of students and their learning patterns on the platform, depending on the type of B-Learning [Replacement blend (RB) vs. Supplemental blend (SB)]; (2) whether a relation exists between the metacognitive and the motivational strategies (MS) of students, their learning outcomes and their learning patterns on the platform. The 87,065 log records of 129 students (69 in RB and 60 in SB) in the Moodle 3.1 platform were analyzed. The results revealed different learning patterns between students depending on the type of B-Learning (RB vs. SB). We have found that the degree of blend, RB vs. SB, seems to condition student behavior on the platform. Learning patterns in RB environments can predict student learning outcomes. Additionally, in RB environments there is a relationship between the learning patterns and the metacognitive and (MS) of the students. PMID:28559866

How Do B-Learning and Learning Patterns Influence Learning Outcomes?

PubMed

Sáiz Manzanares, María Consuelo; Marticorena Sánchez, Raúl; García Osorio, César Ignacio; Díez-Pastor, José F

2017-01-01

Learning Management System (LMS) platforms provide a wealth of information on the learning patterns of students. Learning Analytics (LA) techniques permit the analysis of the logs or records of the activities of both students and teachers on the on-line platform. The learning patterns differ depending on the type of Blended Learning (B-Learning). In this study, we analyse: (1) whether significant differences exist between the learning outcomes of students and their learning patterns on the platform, depending on the type of B-Learning [Replacement blend (RB) vs. Supplemental blend (SB)]; (2) whether a relation exists between the metacognitive and the motivational strategies (MS) of students, their learning outcomes and their learning patterns on the platform. The 87,065 log records of 129 students (69 in RB and 60 in SB) in the Moodle 3.1 platform were analyzed. The results revealed different learning patterns between students depending on the type of B-Learning (RB vs. SB). We have found that the degree of blend, RB vs. SB, seems to condition student behavior on the platform. Learning patterns in RB environments can predict student learning outcomes. Additionally, in RB environments there is a relationship between the learning patterns and the metacognitive and (MS) of the students.

A machine learning approach to improve contactless heart rate monitoring using a webcam.

PubMed

Monkaresi, Hamed; Calvo, Rafael A; Yan, Hong

2014-07-01

Unobtrusive, contactless recordings of physiological signals are very important for many health and human-computer interaction applications. Most current systems require sensors which intrusively touch the user's skin. Recent advances in contact-free physiological signals open the door to many new types of applications. This technology promises to measure heart rate (HR) and respiration using video only. The effectiveness of this technology, its limitations, and ways of overcoming them deserves particular attention. In this paper, we evaluate this technique for measuring HR in a controlled situation, in a naturalistic computer interaction session, and in an exercise situation. For comparison, HR was measured simultaneously using an electrocardiography device during all sessions. The results replicated the published results in controlled situations, but show that they cannot yet be considered as a valid measure of HR in naturalistic human-computer interaction. We propose a machine learning approach to improve the accuracy of HR detection in naturalistic measurements. The results demonstrate that the root mean squared error is reduced from 43.76 to 3.64 beats/min using the proposed method.

Perceptions of problem-based learning (PBL) group effectiveness in a socially-culturally diverse medical student population.

PubMed

Singaram, V S; Dolmans, D H J M; Lachman, N; van der Vleuten, C P M

2008-07-01

A key aspect of the success of a PBL curriculum is the effective implementation of its small group tutorials. Diversity among students participating in tutorials may affect the effectiveness of the tutorials and may require different implementation strategies. To determine how students from diverse backgrounds perceive the effectiveness of the processes and content of the PBL tutorials. This study also aims to explore the relationship between students' perceptions of their PBL tutorials and their gender, age, language, prior educational training, and secondary schooling. Data were survey results from 244 first-year student-respondents at the Nelson Mandela School of Medicine at the University of KwaZulu-Natal in South Africa. Exploratory factor analysis was conducted to verify scale constructs in the questionnaire. Relationships between independent and dependent variables were investigated in an analysis of variance. The average scores for the items measured varied between 3.3 and 3.8 (scale value 1 indicated negative regard and 5 indicated positive regard). Among process measures, approximately two-thirds of students felt that learning in a group was neither frustrating nor stressful and that they enjoyed learning how to work with students from different social and cultural backgrounds. Among content measures, 80% of the students felt that they learned to work successfully with students from different social and cultural groups and 77% felt that they benefited from the input of other group members. Mean ratings on these measures did not vary with students' gender, age, first language, prior educational training, and the types of schools they had previously attended. Medical students of the University of KwaZulu-Natal, regardless of their backgrounds, generally have positive perceptions of small group learning. These findings support previous studies in highlighting the role that small group tutorials can play in overcoming cultural barriers and promoting unity and collaborative learning within diverse student groups.

Examining the Role of Manipulatives and Metacognition on Engagement, Learning, and Transfer

ERIC Educational Resources Information Center

Belenky, Daniel M.; Nokes, Timothy J.

2009-01-01

How does the type of learning material impact what is learned? The current research investigates the nature of students' learning of math concepts when using manipulatives (Uttal, Scudder, & DeLoache, 1997). We examined how the type of manipulative (concrete, abstract, none) and problem-solving prompt (metacognitive or problem-focused) affect…

Multi-Resource Learning.

ERIC Educational Resources Information Center

Cuda, Rebecca A.

2001-01-01

Describes a multi-resource learning environment in which students can engage in their own learning with the teacher taking more of a facilitative role. This type of learning can occur as part of a unit of study and must be supplemented with more traditional types of instruction to ensure that the necessary content is given by the teacher. (SAH)

Learning about the Types of Plastic Wastes: Effectiveness of Inquiry Learning Strategies

ERIC Educational Resources Information Center

So, Wing-Mui Winnie; Cheng, Nga-Yee Irene; Chow, Cheuk-Fai; Zhan, Ying

2016-01-01

This study aims to examine the impacts of the inquiry learning strategies employed in a "Plastic Education Project" on primary students' knowledge, beliefs and intended behaviour in Hong Kong. Student questionnaires and a test on plastic types were adopted for data collection. Results reveal that the inquiry learning strategies…

Non-Declarative Sequence Learning does not Show Savings in Relearning

PubMed Central

Keisler, Aysha; Willingham, Daniel T.

2007-01-01

Researchers have utilized the savings in relearning paradigm in a variety of settings since Ebbinghaus developed the tool over a century ago. In spite of its widespread use, we do not yet understand what type(s) of memory are measurable by savings. Specifically, can savings measure both declarative and non-declarative memories? The lack of conscious recollection of the encoded material in some studies indicates that non-declarative memories may show savings effects, but as all studies to date have used declarative tasks, we cannot be certain. Here, we administer a non-declarative task and then measure savings in relearning the material declaratively. Our results show that while material outside of awareness may show savings effects, non-declarative sequence memory does not. These data highlight the important distinction between memory without awareness and non-declarative memory. PMID:17343944

Non-declarative sequence learning does not show savings in relearning.

PubMed

Keisler, Aysha; Willingham, Daniel T

2007-04-01

Researchers have utilized the savings in relearning paradigm in a variety of settings since Ebbinghaus developed the tool over a century ago. In spite of its widespread use, we do not yet understand what type(s) of memory are measurable by savings. Specifically, can savings measure both declarative and non-declarative memories? The lack of conscious recollection of the encoded material in some studies indicates that non-declarative memories may show savings effects, but as all studies to date have used declarative tasks, we cannot be certain. Here, we administer a non-declarative task and then measure savings in relearning the material declaratively. Our results show that while material outside of awareness may show savings effects, non-declarative sequence memory does not. These data highlight the important distinction between memory without awareness and non-declarative memory.

Neural network based glucose - insulin metabolism models for children with Type 1 diabetes.

PubMed

Mougiakakou, Stavroula G; Prountzou, Aikaterini; Iliopoulou, Dimitra; Nikita, Konstantina S; Vazeou, Andriani; Bartsocas, Christos S

2006-01-01

In this paper two models for the simulation of glucose-insulin metabolism of children with Type 1 diabetes are presented. The models are based on the combined use of Compartmental Models (CMs) and artificial Neural Networks (NNs). Data from children with Type 1 diabetes, stored in a database, have been used as input to the models. The data are taken from four children with Type 1 diabetes and contain information about glucose levels taken from continuous glucose monitoring system, insulin intake and food intake, along with corresponding time. The influences of taken insulin on plasma insulin concentration, as well as the effect of food intake on glucose input into the blood from the gut, are estimated from the CMs. The outputs of CMs, along with previous glucose measurements, are fed to a NN, which provides short-term prediction of glucose values. For comparative reasons two different NN architectures have been tested: a Feed-Forward NN (FFNN) trained with the back-propagation algorithm with adaptive learning rate and momentum, and a Recurrent NN (RNN), trained with the Real Time Recurrent Learning (RTRL) algorithm. The results indicate that the best prediction performance can be achieved by the use of RNN.

Model driven mobile care for patients with type 1 diabetes.

PubMed

Skrøvseth, Stein Olav; Arsand, Eirik; Godtliebsen, Fred; Joakimsen, Ragnar M

2012-01-01

We gathered a data set from 30 patients with type 1 diabetes by giving the patients a mobile phone application, where they recorded blood glucose measurements, insulin injections, meals, and physical activity. Using these data as a learning data set, we describe a new approach of building a mobile feedback system for these patients based on periodicities, pattern recognition, and scale-space trends. Most patients have important patterns for periodicities and trends, though better resolution of input variables is needed to provide useful feedback using pattern recognition.

Study on Fault Diagnostics of a Turboprop Engine Using Inverse Performance Model and Artificial Intelligent Methods

NASA Astrophysics Data System (ADS)

Kong, Changduk; Lim, Semyeong

2011-12-01

Recently, the health monitoring system of major gas path components of gas turbine uses mostly the model based method like the Gas Path Analysis (GPA). This method is to find quantity changes of component performance characteristic parameters such as isentropic efficiency and mass flow parameter by comparing between measured engine performance parameters such as temperatures, pressures, rotational speeds, fuel consumption, etc. and clean engine performance parameters without any engine faults which are calculated by the base engine performance model. Currently, the expert engine diagnostic systems using the artificial intelligent methods such as Neural Networks (NNs), Fuzzy Logic and Genetic Algorithms (GAs) have been studied to improve the model based method. Among them the NNs are mostly used to the engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base if there are large amount of learning data. In addition, it has a very complex structure for finding effectively single type faults or multiple type faults of gas path components. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measured performance data, and proposes a fault diagnostic system using the base engine performance model and the artificial intelligent methods such as Fuzzy logic and Neural Network. The proposed diagnostic system isolates firstly the faulted components using Fuzzy Logic, then quantifies faults of the identified components using the NN leaned by fault learning data base, which are obtained from the developed base performance model. In leaning the NN, the Feed Forward Back Propagation (FFBP) method is used. Finally, it is verified through several test examples that the component faults implanted arbitrarily in the engine are well isolated and quantified by the proposed diagnostic system.

Multi-Source Learning for Joint Analysis of Incomplete Multi-Modality Neuroimaging Data

PubMed Central

Yuan, Lei; Wang, Yalin; Thompson, Paul M.; Narayan, Vaibhav A.; Ye, Jieping

2013-01-01

Incomplete data present serious problems when integrating largescale brain imaging data sets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiative (ADNI), for example, over half of the subjects lack cerebrospinal fluid (CSF) measurements; an independent half of the subjects do not have fluorodeoxyglucose positron emission tomography (FDG-PET) scans; many lack proteomics measurements. Traditionally, subjects with missing measures are discarded, resulting in a severe loss of available information. We address this problem by proposing two novel learning methods where all the samples (with at least one available data source) can be used. In the first method, we divide our samples according to the availability of data sources, and we learn shared sets of features with state-of-the-art sparse learning methods. Our second method learns a base classifier for each data source independently, based on which we represent each source using a single column of prediction scores; we then estimate the missing prediction scores, which, combined with the existing prediction scores, are used to build a multi-source fusion model. To illustrate the proposed approaches, we classify patients from the ADNI study into groups with Alzheimer’s disease (AD), mild cognitive impairment (MCI) and normal controls, based on the multi-modality data. At baseline, ADNI’s 780 participants (172 AD, 397 MCI, 211 Normal), have at least one of four data types: magnetic resonance imaging (MRI), FDG-PET, CSF and proteomics. These data are used to test our algorithms. Comprehensive experiments show that our proposed methods yield stable and promising results. PMID:24014189

Feedback error learning control of magnetic satellites using type-2 fuzzy neural networks with elliptic membership functions.

PubMed

Khanesar, Mojtaba Ahmadieh; Kayacan, Erdal; Reyhanoglu, Mahmut; Kaynak, Okyay

2015-04-01

A novel type-2 fuzzy membership function (MF) in the form of an ellipse has recently been proposed in literature, the parameters of which that represent uncertainties are de-coupled from its parameters that determine the center and the support. This property has enabled the proposers to make an analytical comparison of the noise rejection capabilities of type-1 fuzzy logic systems with its type-2 counterparts. In this paper, a sliding mode control theory-based learning algorithm is proposed for an interval type-2 fuzzy logic system which benefits from elliptic type-2 fuzzy MFs. The learning is based on the feedback error learning method and not only the stability of the learning is proved but also the stability of the overall system is shown by adding an additional component to the control scheme to ensure robustness. In order to test the efficiency and efficacy of the proposed learning and the control algorithm, the trajectory tracking problem of a magnetic rigid spacecraft is studied. The simulations results show that the proposed control algorithm gives better performance results in terms of a smaller steady state error and a faster transient response as compared to conventional control algorithms.

Effects of ecstasy/polydrug use on memory for associative information.

PubMed

Gallagher, Denis T; Fisk, John E; Montgomery, Catharine; Judge, Jeannie; Robinson, Sarita J; Taylor, Paul J

2012-08-01

Associative learning underpins behaviours that are fundamental to the everyday functioning of the individual. Evidence pointing to learning deficits in recreational drug users merits further examination. A word pair learning task was administered to examine associative learning processes in ecstasy/polydrug users. After assignment to either single or divided attention conditions, 44 ecstasy/polydrug users and 48 non-users were presented with 80 word pairs at encoding. Following this, four types of stimuli were presented at the recognition phase: the words as originally paired (old pairs), previously presented words in different pairings (conjunction pairs), old words paired with new words, and pairs of new words (not presented previously). The task was to identify which of the stimuli were intact old pairs. Ecstasy/ploydrug users produced significantly more false-positive responses overall compared to non-users. Increased long-term frequency of ecstasy use was positively associated with the propensity to produce false-positive responses. It was also associated with a more liberal signal detection theory decision criterion value. Measures of long term and recent cannabis use were also associated with these same word pair learning outcome measures. Conjunction word pairs, irrespective of drug use, generated the highest level of false-positive responses and significantly more false-positive responses were made in the divided attention condition compared to the single attention condition. Overall, the results suggest that long-term ecstasy exposure may induce a deficit in associative learning and this may be in part a consequence of users adopting a more liberal decision criterion value.

Questioning short-term memory and its measurement: Why digit span measures long-term associative learning.

PubMed

Jones, Gary; Macken, Bill

2015-11-01

Traditional accounts of verbal short-term memory explain differences in performance for different types of verbal material by reference to inherent characteristics of the verbal items making up memory sequences. The role of previous experience with sequences of different types is ostensibly controlled for either by deliberate exclusion or by presenting multiple trials constructed from different random permutations. We cast doubt on this general approach in a detailed analysis of the basis for the robust finding that short-term memory for digit sequences is superior to that for other sequences of verbal material. Specifically, we show across four experiments that this advantage is not due to inherent characteristics of digits as verbal items, nor are individual digits within sequences better remembered than other types of individual verbal items. Rather, the advantage for digit sequences stems from the increased frequency, compared to other verbal material, with which digits appear in random sequences in natural language, and furthermore, relatively frequent digit sequences support better short-term serial recall than less frequent ones. We also provide corpus-based computational support for the argument that performance in a short-term memory setting is a function of basic associative learning processes operating on the linguistic experience of the rememberer. The experimental and computational results raise questions not only about the role played by measurement of digit span in cognition generally, but also about the way in which long-term memory processes impact on short-term memory functioning. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Measuring meaningful learning in the undergraduate chemistry laboratory

NASA Astrophysics Data System (ADS)

Galloway, Kelli R.

The undergraduate chemistry laboratory has been an essential component in chemistry education for over a century. The literature includes reports on investigations of singular aspects laboratory learning and attempts to measure the efficacy of reformed laboratory curriculum as well as faculty goals for laboratory learning which found common goals among instructors for students to learn laboratory skills, techniques, experimental design, and to develop critical thinking skills. These findings are important for improving teaching and learning in the undergraduate chemistry laboratory, but research is needed to connect the faculty goals to student perceptions. This study was designed to explore students' ideas about learning in the undergraduate chemistry laboratory. Novak's Theory of Meaningful Learning was used as a guide for the data collection and analysis choices for this research. Novak's theory states that in order for meaningful learning to occur the cognitive, affective, and psychomotor domains must be integrated. The psychomotor domain is inherent in the chemistry laboratory, but the extent to which the cognitive and affective domains are integrated is unknown. For meaningful learning to occur in the laboratory, students must actively integrate both the cognitive domain and the affective domains into the "doing" of their laboratory work. The Meaningful Learning in the Laboratory Instrument (MLLI) was designed to measure students' cognitive and affective expectations and experiences within the context of conducting experiments in the undergraduate chemistry laboratory. Evidence for the validity and reliability of the data generated by the MLLI were collected from multiple quantitative studies: a one semester study at one university, a one semester study at 15 colleges and universities across the United States, and a longitudinal study where the MLLI was administered 6 times during two years of general and organic chemistry laboratory courses. Results from these studies revealed students' narrow cognitive expectations for learning that go largely unmet by their experiences and diverse affective expectations and experiences. Concurrently, a qualitative study was carried out to describe and characterize students' cognitive and affective experiences in the undergraduate chemistry laboratory. Students were video recorded while performing one of their regular laboratory experiments and then interviewed about their experiences. The students' descriptions of their learning experiences were characterized by their overreliance on following the experimental procedure correctly rather than developing process-oriented problem solving skills. Future research could use the MLLI to intentionally compare different types of laboratory curricula or environments.

The learning type makes the difference - the interrelation of Kolb's learning styles and psychological status of preclinical medical students at the University of Erlangen.

PubMed

Burger, Pascal H; Scholz, Michael

2014-01-01

Theories on learning styles and types have been integral to discussions on the basics of teaching for nearly 40 years. The learning style typology of Kolb divides learners into four groups (Diverger, Assimilator, Converger and Accomodator), which differ both in terms of their learning behaviour as well as personality and preferences. We studied the sense of coherence and burnout symptoms in medical students of the preclinical semesters (1(st) to 4(th) semester) at the Friedrich-Alexander University of Erlangen within the context of the observed learning styles. A total of 530 students were interviewed in winter semester 2012/13 using standardized psychometric questionnaires. Our students showed a significant correlation between the respective learning styles and expression of a sense of coherence, as well as cognitive and emotional burnout symptoms. The learning styles of the students differed significantly within these same parameters. We also demonstrated that learning styles and types not only influence study performance, but that there are also relationships to sense of coherence and psychological ailments. A more forward-looking integration of the theory of learning types in the medical education curriculum could positively influence both the performance and psychological well-being of the students.

The learning type makes the difference – the interrelation of Kolb's learning styles and psychological status of preclinical medical students at the University of Erlangen

PubMed Central

Burger, Pascal H.; Scholz, Michael

2014-01-01

Theories on learning styles and types have been integral to discussions on the basics of teaching for nearly 40 years. The learning style typology of Kolb divides learners into four groups (Diverger, Assimilator, Converger and Accomodator), which differ both in terms of their learning behaviour as well as personality and preferences. We studied the sense of coherence and burnout symptoms in medical students of the preclinical semesters (1st to 4th semester) at the Friedrich-Alexander University of Erlangen within the context of the observed learning styles. A total of 530 students were interviewed in winter semester 2012/13 using standardized psychometric questionnaires. Our students showed a significant correlation between the respective learning styles and expression of a sense of coherence, as well as cognitive and emotional burnout symptoms. The learning styles of the students differed significantly within these same parameters. We also demonstrated that learning styles and types not only influence study performance, but that there are also relationships to sense of coherence and psychological ailments. A more forward-looking integration of the theory of learning types in the medical education curriculum could positively influence both the performance and psychological well-being of the students. PMID:25489342

Influence of learning styles on the practical performance after the four-step basic life support training approach – An observational cohort study

PubMed Central

Henke, Alexandra; Stieger, Lina; Beckers, Stefan; Biermann, Henning; Rossaint, Rolf; Sopka, Saša

2017-01-01

Background Learning and training basic life support (BLS)—especially external chest compressions (ECC) within the BLS-algorithm—are essential resuscitation training for laypersons as well as for health care professionals. The objective of this study was to evaluate the influence of learning styles on the performance of BLS and to identify whether all types of learners are sufficiently addressed by Peyton’s four-step approach for BLS training. Methods A study group of first-year medical students (n = 334) without previous medical knowledge was categorized according to learning styles using the German Lernstilinventar questionnaire based on Kolb’s Learning Styles Inventory. Students’ BLS performances were assessed before and after a four-step BLS training approach lasting 4 hours. Standardized BLS training was provided by an educational staff consisting of European Resuscitation Council-certified advanced life support providers and instructors. Pre- and post-intervention BLS performance was evaluated using a single-rescuer-scenario and standardized questionnaires (6-point-Likert-scales: 1 = completely agree, 6 = completely disagree). The recorded points of measurement were the time to start, depth, and frequency of ECC. Results The study population was categorized according to learning styles: diverging (5%, n = 16), assimilating (36%, n = 121), converging (41%, n = 138), and accommodating (18%, n = 59). Independent of learning styles, both male and female participants showed significant improvement in cardiopulmonary resuscitation (CPR) performance. Based on the Kolb learning styles, no significant differences between the four groups were observed in compression depth, frequency, time to start CPR, or the checklist-based assessment within the baseline assessment. A significant sex effect on the difference between pre- and post-interventional assessment points was observed for mean compression depth and mean compression frequency. Conclusions The findings of this work show that the four-step-approach for BLS training addresses all types of learners independent of their learning styles and does not lead to significant differences in the performance of CPR. PMID:28542636

Influence of learning styles on the practical performance after the four-step basic life support training approach - An observational cohort study.

PubMed

Schröder, Hanna; Henke, Alexandra; Stieger, Lina; Beckers, Stefan; Biermann, Henning; Rossaint, Rolf; Sopka, Saša

2017-01-01

Learning and training basic life support (BLS)-especially external chest compressions (ECC) within the BLS-algorithm-are essential resuscitation training for laypersons as well as for health care professionals. The objective of this study was to evaluate the influence of learning styles on the performance of BLS and to identify whether all types of learners are sufficiently addressed by Peyton's four-step approach for BLS training. A study group of first-year medical students (n = 334) without previous medical knowledge was categorized according to learning styles using the German Lernstilinventar questionnaire based on Kolb's Learning Styles Inventory. Students' BLS performances were assessed before and after a four-step BLS training approach lasting 4 hours. Standardized BLS training was provided by an educational staff consisting of European Resuscitation Council-certified advanced life support providers and instructors. Pre- and post-intervention BLS performance was evaluated using a single-rescuer-scenario and standardized questionnaires (6-point-Likert-scales: 1 = completely agree, 6 = completely disagree). The recorded points of measurement were the time to start, depth, and frequency of ECC. The study population was categorized according to learning styles: diverging (5%, n = 16), assimilating (36%, n = 121), converging (41%, n = 138), and accommodating (18%, n = 59). Independent of learning styles, both male and female participants showed significant improvement in cardiopulmonary resuscitation (CPR) performance. Based on the Kolb learning styles, no significant differences between the four groups were observed in compression depth, frequency, time to start CPR, or the checklist-based assessment within the baseline assessment. A significant sex effect on the difference between pre- and post-interventional assessment points was observed for mean compression depth and mean compression frequency. The findings of this work show that the four-step-approach for BLS training addresses all types of learners independent of their learning styles and does not lead to significant differences in the performance of CPR.

(How) do we learn from errors? A prospective study of the link between the ward's learning practices and medication administration errors.

PubMed

Drach-Zahavy, A; Somech, A; Admi, H; Peterfreund, I; Peker, H; Priente, O

2014-03-01

Attention in the ward should shift from preventing medication administration errors to managing them. Nevertheless, little is known in regard with the practices nursing wards apply to learn from medication administration errors as a means of limiting them. To test the effectiveness of four types of learning practices, namely, non-integrated, integrated, supervisory and patchy learning practices in limiting medication administration errors. Data were collected from a convenient sample of 4 hospitals in Israel by multiple methods (observations and self-report questionnaires) at two time points. The sample included 76 wards (360 nurses). Medication administration error was defined as any deviation from prescribed medication processes and measured by a validated structured observation sheet. Wards' use of medication administration technologies, location of the medication station, and workload were observed; learning practices and demographics were measured by validated questionnaires. Results of the mixed linear model analysis indicated that the use of technology and quiet location of the medication cabinet were significantly associated with reduced medication administration errors (estimate=.03, p<.05 and estimate=-.17, p<.01 correspondingly), while workload was significantly linked to inflated medication administration errors (estimate=.04, p<.05). Of the learning practices, supervisory learning was the only practice significantly linked to reduced medication administration errors (estimate=-.04, p<.05). Integrated and patchy learning were significantly linked to higher levels of medication administration errors (estimate=-.03, p<.05 and estimate=-.04, p<.01 correspondingly). Non-integrated learning was not associated with it (p>.05). How wards manage errors might have implications for medication administration errors beyond the effects of typical individual, organizational and technology risk factors. Head nurse can facilitate learning from errors by "management by walking around" and monitoring nurses' medication administration behaviors. Copyright © 2013 Elsevier Ltd. All rights reserved.

Understanding and Managing Learning Disabilities in Adults. Professional Practices in Adult Education and Human Resource Development Series.

ERIC Educational Resources Information Center

Jordan, Dale R.

This book reviews learning disabilities (LD) in adults and makes suggestions for helping adults cope with these disabilities. Each chapter covers a type of learning disability or related syndrome or explains characteristics of the brain. Chapter 1 explains several types of specific learning disabilities that make classroom performance difficult…

The Experience of Contrasting Learning Styles, Learning Preferences, and Personality Types in the Community College English Classroom

ERIC Educational Resources Information Center

Lawrence, William K.

2014-01-01

This study focuses on the classroom experiences of students who identify themselves as learning best as reflective-observers (Assimilators) in contrast to those who learn best as active- experimenters (Accommodators), with additional consideration for their self-identified personality type (introvert vs. extrovert) as well as one of the VARK…

Integrating Research on Misconceptions, Reasoning Patterns and Three Types of Learning Cycles.

ERIC Educational Resources Information Center

Lawson, Anton E.

This paper describes how the learning cycle leads students to become more skilled reasoners. The three phases of the learning cycle are described and examples and goals of each are provided. Information is also offered on the three types of learning cycles: the descriptive; the empirical-inductive; and the hypothetical-deductive. Each is described…

Comparing University Students and Community College Students Learning Styles and Myers-Briggs Type Indicator (MBTI) Preferences.

ERIC Educational Resources Information Center

Herbster, Douglas L.; And Others

This document reports on a study to determine if there is a pattern between specific learning styles and Myers-Briggs Type Indicator preferences. The learning style inventory used for the study, "The Teaching and Learning Styles Survey for Adolescents (TLC)," is based on Jungian style preferences--thinker, feeler, sensor, and…

The impact of constructivist teaching strategies on the acquisition of higher order cognition and learning

NASA Astrophysics Data System (ADS)

Merrill, Alison Saricks

The purpose of this quasi-experimental quantitative mixed design study was to compare the effectiveness of brain-based teaching strategies versus a traditional lecture format in the acquisition of higher order cognition as determined by test scores. A second purpose was to elicit student feedback about the two teaching approaches. The design was a 2 x 2 x 2 factorial design study with repeated measures on the last factor. The independent variables were type of student, teaching method, and a within group change over time. Dependent variables were a between group comparison of pre-test, post-test gain scores and a within and between group comparison of course examination scores. A convenience sample of students enrolled in medical-surgical nursing was used. One group (n=36) was made up of traditional students and the other group (n=36) consisted of second-degree students. Four learning units were included in this study. Pre- and post-tests were given on the first two units. Course examinations scores from all four units were compared. In one cohort two of the units were taught via lecture format and two using constructivist activities. These methods were reversed for the other cohort. The conceptual basis for this study derives from neuroscience and cognitive psychology. Learning is defined as the growth of new dendrites. Cognitive psychologists view learning as a constructive activity in which new knowledge is built on an internal foundation of existing knowledge. Constructivist teaching strategies are designed to stimulate the brain's natural learning ability. There was a statistically significant difference based on type of teaching strategy (t = -2.078, df = 270, p = .039, d = .25)) with higher mean scores on the examinations covering brain-based learning units. There was no statistical significance based on type of student. Qualitative data collection was conducted in an on-line forum at the end of the semester. Students had overall positive responses about the constructivist activities. Major themes were described. Constructivist strategies help bridge the gap between neurological and cognitive sciences and classroom teaching and learning. A variety of implications for nursing educators are outlined as well as directions for future research.

Higher iridescent-to-pigment optical effect in flowers facilitates learning, memory and generalization in foraging bumblebees.

PubMed

de Premorel, Géraud; Giurfa, Martin; Andraud, Christine; Gomez, Doris

2017-10-25

Iridescence-change of colour with changes in the angle of view or of illumination-is widespread in the living world, but its functions remain poorly understood. The presence of iridescence has been suggested in flowers where diffraction gratings generate iridescent colours. Such colours have been suggested to serve plant-pollinator communication. Here we tested whether a higher iridescence relative to corolla pigmentation would facilitate discrimination, learning and retention of iridescent visual targets. We conditioned bumblebees ( Bombus terrestris ) to discriminate iridescent from non-iridescent artificial flowers and we varied iridescence detectability by varying target iridescent relative to pigment optical effect. We show that bees rewarded on targets with higher iridescent relative to pigment effect required fewer choices to complete learning, showed faster generalization to novel targets exhibiting the same iridescence-to-pigment level and had better long-term memory retention. Along with optical measurements, behavioural results thus demonstrate that bees can learn iridescence-related cues as bona fide signals for flower reward. They also suggest that floral advertising may be shaped by competition between iridescence and corolla pigmentation, a fact that has important evolutionary implications for pollinators. Optical measurements narrow down the type of cues that bees may have used for learning. Beyond pollinator-plant communication, our experiments help understanding how receivers influence the evolution of iridescence signals generated by gratings. © 2017 The Author(s).

Reinforcement learning for partially observable dynamic processes: adaptive dynamic programming using measured output data.

PubMed

Lewis, F L; Vamvoudakis, Kyriakos G

2011-02-01

Approximate dynamic programming (ADP) is a class of reinforcement learning methods that have shown their importance in a variety of applications, including feedback control of dynamical systems. ADP generally requires full information about the system internal states, which is usually not available in practical situations. In this paper, we show how to implement ADP methods using only measured input/output data from the system. Linear dynamical systems with deterministic behavior are considered herein, which are systems of great interest in the control system community. In control system theory, these types of methods are referred to as output feedback (OPFB). The stochastic equivalent of the systems dealt with in this paper is a class of partially observable Markov decision processes. We develop both policy iteration and value iteration algorithms that converge to an optimal controller that requires only OPFB. It is shown that, similar to Q -learning, the new methods have the important advantage that knowledge of the system dynamics is not needed for the implementation of these learning algorithms or for the OPFB control. Only the order of the system, as well as an upper bound on its "observability index," must be known. The learned OPFB controller is in the form of a polynomial autoregressive moving-average controller that has equivalent performance with the optimal state variable feedback gain.

The Function of Annotations in the Comprehension of Scientific Texts: Cognitive Load Effects and the Impact of Verbal Ability

ERIC Educational Resources Information Center

Wallen, Erik; Plass, Jan L.; Brunken, Roland

2005-01-01

Students participated in a study (n = 98) investigating the effectiveness of three types of annotations on three learning outcome measures. The annotations were designed to support the cognitive processes in the comprehension of scientific texts, with a function to aid either the process of selecting relevant information, organizing the…

Investigating Student Perceptions of the Chemistry Laboratory and Their Approaches to Learning in the Laboratory

NASA Astrophysics Data System (ADS)

Berger, Spencer Granett

This dissertation explores student perceptions of the instructional chemistry laboratory and the approaches students take when learning in the laboratory environment. To measure student perceptions of the chemistry laboratory, a survey instrument was developed. 413 students responded to the survey during the Fall 2011 semester. Students' perception of the usefulness of the laboratory in helping them learn chemistry in high school was related to several factors regarding their experiences in high school chemistry. Students' perception of the usefulness of the laboratory in helping them learn chemistry in college was also measured. Reasons students provided for the usefulness of the laboratory were categorized. To characterize approaches to learning in the laboratory, students were interviewed midway through semester (N=18). The interviews were used to create a framework describing learning approaches that students use in the laboratory environment. Students were categorized into three levels: students who view the laboratory as a requirement, students who believe that the laboratory augments their understanding, and students who view the laboratory as an important part of science. These categories describe the types of strategies students used when conducting experiments. To further explore the relationship between students' perception of the laboratory and their approaches to learning, two case studies are described. These case studies involve interviews in the beginning and end of the semester. In the interviews, students reflect on what they have learned in the laboratory and describe their perceptions of the laboratory environment. In order to encourage students to adopt higher-level approaches to learning in the laboratory, a metacognitive intervention was created. The intervention involved supplementary questions that students would answer while completing laboratory experiments. The questions were designed to encourage students to think critically about the laboratory procedures. In order to test the effects of the intervention, an experimental group (N=87) completed these supplementary questions during two laboratory experiments while a control group (N=84) performed the same experiments without these additional questions. The effects of the intervention on laboratory exam performance were measured. Students in the experimental group had a higher average on the laboratory exam than students in the control group.

Language Learning Strategies Employed by Chinese English-Major Pre-Service Teachers in Relation to Gender and Personality Types

ERIC Educational Resources Information Center

Zhou, Chaoying; Intaraprasert, Channarong

2015-01-01

This study was intended to investigate the use of language learning strategy employed by English-major pre-service teachers in Midwest China in relation to their gender and personality types. The modified Strategy Inventory for Language Learning (SILL) and adopted personality type inventory were used to collect the data. ANOVA and Chi-square tests…

Phonological and Semantic Cues to Learning from Word-Types

PubMed Central

Richtsmeier, Peter

2017-01-01

Word-types represent the primary form of data for many models of phonological learning, and they often predict performance in psycholinguistic tasks. Word-types are often tacitly defined as phonologically unique words. Yet, an explicit test of this definition is lacking, and natural language patterning suggests that word meaning could also act as a cue to word-type status. This possibility was tested in a statistical phonotactic learning experiment in which phonological and semantic properties of word-types varied. During familiarization, the learning targets—word-medial consonant sequences—were instantiated either by four related word-types or by just one word-type (the experimental frequency factor). The expectation was that more word-types would lead participants to generalize the target sequences. Regarding semantic cues, related word-types were either associated with different referents or all with a single referent. Regarding phonological cues, related word-types differed from each other by one, two, or more phonemes. At test, participants rated novel wordforms for their similarity to the familiarization words. When participants heard four related word-types, they gave higher ratings to test words with the same consonant sequences, irrespective of the phonological and semantic manipulations. The results support the existing phonological definition of word-types. PMID:29187914

Supporting cognitive engagement in a learning-by-doing learning environment: Case studies of participant engagement and social configurations in Kitchen Science Investigators

NASA Astrophysics Data System (ADS)

Gardner, Christina M.

Learning-by-doing learning environments support a wealth of physical engagement in activities. However, there is also a lot of variability in what participants learn in each enactment of these types of environments. Therefore, it is not always clear how participants are learning in these environments. In order to design technologies to support learning in these environments, we must have a greater understanding of how participants engage in learning activities, their goals for their engagement, and the types of help they need to cognitively engage in learning activities. To gain a greater understanding of participant engagement and factors and circumstances that promote and inhibit engagement, this dissertation explores and answers several questions: What are the types of interactions and experiences that promote and /or inhibit learning and engagement in learning-by-doing learning environments? What are the types of configurations that afford or inhibit these interactions and experiences in learning-by-doing learning environments? I explore answers to these questions through the context of two enactments of Kitchen Science Investigators (KSI), a learning-by-doing learning environment where middle-school aged children learn science through cooking from customizing recipes to their own taste and texture preferences. In small groups, they investigate effects of ingredients through the design of cooking and science experiments, through which they experience and learn about chemical, biological, and physical science phenomena and concepts (Clegg, Gardner, Williams, & Kolodner, 2006). The research reported in this dissertation sheds light on the different ways participant engagement promotes and/or inhibits cognitive engagement in by learning-by-doing learning environments through two case studies. It also provides detailed descriptions of the circumstances (social, material, and physical configurations) that promote and/or inhibit participant engagement in these learning environments through cross-case analyses of these cases. Finally, it offers suggestions about structuring activities, selecting materials and resources, and designing facilitation and software-realized scaffolding in the design of these types of learning environments. These design implications focus on affording participant engagement in science content and practices learning. Overall, the case studies, cross-case analyses, and empirically-based design implications begin to bridge the gap between theory and practice in the design and implementation of these learning environments. This is demonstrated by providing detailed and explanatory examples and factors that affect how participants take up the affordances of the learning opportunities designed into these learning environments.

Does learning style influence academic performance in different forms of assessment?

PubMed

Wilkinson, Tracey; Boohan, Mairead; Stevenson, Michael

2014-03-01

Educational research on learning styles has been conducted for some time, initially within the field of psychology. Recent research has widened to include more diverse disciplines, with greater emphasis on application. Although there are numerous instruments available to measure several different dimensions of learning style, it is generally accepted that styles differ, although the qualities of more than one style may be inherent in any one learner. But do these learning styles have a direct effect on student performance in examinations, specifically in different forms of assessment? For this study, hypotheses were formulated suggesting that academic performance is influenced by learning style. Using the Honey and Mumford Learning Style Questionnaire, learning styles of a cohort of first year medical and dental students at Queen's University Belfast were assessed. Pearson correlation was performed between the score for each of the four learning styles and the student examination results in a variety of subject areas (including anatomy) and in different types of assessments - single best answer, short answer questions and Objective Structured Clinical Examinations. In most of the analyses, there was no correlation between learning style and result and in the few cases where the correlations were statistically significant, they generally appeared to be weak. It seems therefore from this study that although the learning styles of students vary, they have little effect on academic performance, including in specific forms of assessment. © 2013 Anatomical Society.

Word Learning Deficits in Children With Dyslexia

PubMed Central

Hogan, Tiffany; Green, Samuel; Gray, Shelley; Cabbage, Kathryn; Cowan, Nelson

2017-01-01

Purpose The purpose of this study is to investigate word learning in children with dyslexia to ascertain their strengths and weaknesses during the configuration stage of word learning. Method Children with typical development (N = 116) and dyslexia (N = 68) participated in computer-based word learning games that assessed word learning in 4 sets of games that manipulated phonological or visuospatial demands. All children were monolingual English-speaking 2nd graders without oral language impairment. The word learning games measured children's ability to link novel names with novel objects, to make decisions about the accuracy of those names and objects, to recognize the semantic features of the objects, and to produce the names of the novel words. Accuracy data were analyzed using analyses of covariance with nonverbal intelligence scores as a covariate. Results Word learning deficits were evident for children with dyslexia across every type of manipulation and on 3 of 5 tasks, but not for every combination of task/manipulation. Deficits were more common when task demands taxed phonology. Visuospatial manipulations led to both disadvantages and advantages for children with dyslexia. Conclusion Children with dyslexia evidence spoken word learning deficits, but their performance is highly dependent on manipulations and task demand, suggesting a processing trade-off between visuospatial and phonological demands. PMID:28388708

Learning Achieved in Structured Online Debates: Levels of Learning and Types of Postings

ERIC Educational Resources Information Center

Jin, Li; Jeong, Allan

2013-01-01

The purpose of this study was to examine the learning process exhibited in restrained online debates in terms of to what extent each of Bloom's six levels of cognitive learning were exhibited among four types of message (argument, critique, evidence, and explanation). Thirty-three graduate students enrolled in an online entry-level course in…

Learning Factors Transfer Analysis: Using Learning Curve Analysis to Automatically Generate Domain Models

ERIC Educational Resources Information Center

Pavlik, Philip I. Jr.; Cen, Hao; Koedinger, Kenneth R.

2009-01-01

This paper describes a novel method to create a quantitative model of an educational content domain of related practice item-types using learning curves. By using a pairwise test to search for the relationships between learning curves for these item-types, we show how the test results in a set of pairwise transfer relationships that can be…

An Exploratory Analysis of Personality, Attitudes, and Study Skills on the Learning Curve within a Team-based Learning Environment

PubMed Central

Henry, Teague; Campbell, Ashley

2015-01-01

Objective. To examine factors that determine the interindividual variability of learning within a team-based learning environment. Methods. Students in a pharmacokinetics course were given 4 interim, low-stakes cumulative assessments throughout the semester and a cumulative final examination. Students’ Myers-Briggs personality type was assessed, as well as their study skills, motivations, and attitudes towards team-learning. A latent curve model (LCM) was applied and various covariates were assessed to improve the regression model. Results. A quadratic LCM was applied for the first 4 assessments to predict final examination performance. None of the covariates examined significantly impacted the regression model fit except metacognitive self-regulation, which explained some of the variability in the rate of learning. There were some correlations between personality type and attitudes towards team learning, with introverts having a lower opinion of team-learning than extroverts. Conclusion. The LCM could readily describe the learning curve. Extroverted and introverted personality types had the same learning performance even though preference for team-learning was lower in introverts. Other personality traits, study skills, or practice did not significantly contribute to the learning variability in this course. PMID:25861101

An exploratory analysis of personality, attitudes, and study skills on the learning curve within a team-based learning environment.

PubMed

Persky, Adam M; Henry, Teague; Campbell, Ashley

2015-03-25

To examine factors that determine the interindividual variability of learning within a team-based learning environment. Students in a pharmacokinetics course were given 4 interim, low-stakes cumulative assessments throughout the semester and a cumulative final examination. Students' Myers-Briggs personality type was assessed, as well as their study skills, motivations, and attitudes towards team-learning. A latent curve model (LCM) was applied and various covariates were assessed to improve the regression model. A quadratic LCM was applied for the first 4 assessments to predict final examination performance. None of the covariates examined significantly impacted the regression model fit except metacognitive self-regulation, which explained some of the variability in the rate of learning. There were some correlations between personality type and attitudes towards team learning, with introverts having a lower opinion of team-learning than extroverts. The LCM could readily describe the learning curve. Extroverted and introverted personality types had the same learning performance even though preference for team-learning was lower in introverts. Other personality traits, study skills, or practice did not significantly contribute to the learning variability in this course.

Performance on large-scale science tests: Item attributes that may impact achievement scores

NASA Astrophysics Data System (ADS)

Gordon, Janet Victoria

Significant differences in achievement among ethnic groups persist on the eighth-grade science Washington Assessment of Student Learning (WASL). The WASL measures academic performance in science using both scenario and stand-alone question types. Previous research suggests that presenting target items connected to an authentic context, like scenario question types, can increase science achievement scores especially in underrepresented groups and thus help to close the achievement gap. The purpose of this study was to identify significant differences in performance between gender and ethnic subgroups by question type on the 2005 eighth-grade science WASL. MANOVA and ANOVA were used to examine relationships between gender and ethnic subgroups as independent variables with achievement scores on scenario and stand-alone question types as dependent variables. MANOVA revealed no significant effects for gender, suggesting that the 2005 eighth-grade science WASL was gender neutral. However, there were significant effects for ethnicity. ANOVA revealed significant effects for ethnicity and ethnicity by gender interaction in both question types. Effect sizes were negligible for the ethnicity by gender interaction. Large effect sizes between ethnicities on scenario question types became moderate to small effect sizes on stand-alone question types. This indicates the score advantage the higher performing subgroups had over the lower performing subgroups was not as large on stand-alone question types compared to scenario question types. A further comparison examined performance on multiple-choice items only within both question types. Similar achievement patterns between ethnicities emerged; however, achievement patterns between genders changed in boys' favor. Scenario question types appeared to register differences between ethnic groups to a greater degree than stand-alone question types. These differences may be attributable to individual differences in cognition, characteristics of test items themselves and/or opportunities to learn. Suggestions for future research are made.

Learning of Temporal and Spatial Movement Aspects: A Comparison of Four Types of Haptic Control and Concurrent Visual Feedback.

PubMed

Rauter, Georg; Sigrist, Roland; Riener, Robert; Wolf, Peter

2015-01-01

In literature, the effectiveness of haptics for motor learning is controversially discussed. Haptics is believed to be effective for motor learning in general; however, different types of haptic control enhance different movement aspects. Thus, in dependence on the movement aspects of interest, one type of haptic control may be effective whereas another one is not. Therefore, in the current work, it was investigated if and how different types of haptic controllers affect learning of spatial and temporal movement aspects. In particular, haptic controllers that enforce active participation of the participants were expected to improve spatial aspects. Only haptic controllers that provide feedback about the task's velocity profile were expected to improve temporal aspects. In a study on learning a complex trunk-arm rowing task, the effect of training with four different types of haptic control was investigated: position control, path control, adaptive path control, and reactive path control. A fifth group (control) trained with visual concurrent augmented feedback. As hypothesized, the position controller was most effective for learning of temporal movement aspects, while the path controller was most effective in teaching spatial movement aspects of the rowing task. Visual feedback was also effective for learning temporal and spatial movement aspects.

Attribute-driven transfer learning for detecting novel buried threats with ground-penetrating radar

NASA Astrophysics Data System (ADS)

Colwell, Kenneth A.; Collins, Leslie M.

2016-05-01

Ground-penetrating radar (GPR) technology is an effective method of detecting buried explosive threats. The system uses a binary classifier to distinguish "targets", or buried threats, from "nontargets" arising from system prescreener false alarms; this classifier is trained on a dataset of previously-observed buried threat types. However, the threat environment is not static, and new threat types that appear must be effectively detected even if they are not highly similar to every previously-observed type. Gathering a new dataset that includes a new threat type is expensive and time-consuming; minimizing the amount of new data required to effectively detect the new type is therefore valuable. This research aims to reduce the number of training examples needed to effectively detect new types using transfer learning, which leverages previous learning tasks to accelerate and improve new ones. Further, new types have attribute data, such as composition, components, construction, and size, which can be observed without GPR and typically are not explicitly included in the learning process. Since attribute tags for buried threats determine many aspects of their GPR representation, a new threat type's attributes can be highly relevant to the transfer-learning process. In this work, attribute data is used to drive transfer learning, both by using attributes to select relevant dataset examples for classifier fusion, and by extending a relevance vector machine (RVM) model to perform intelligent attribute clustering and selection. Classification performance results for both the attribute-only case and the low-data case are presented, using a dataset containing a variety of threat types.

Matching student personality types and learning preferences to teaching methodologies.

PubMed

Jessee, Stephen A; O'Neill, Paula N; Dosch, Robert O

2006-06-01

The purpose of this study was to identify teaching styles that complement the learning preferences of undergraduate dental students while enhancing the quality of patient care. A formidable challenge to reform in dental education has been overcoming the resistance by faculty and administration to recommended changes. The organizational structure of dental institutions, with their independent departments, makes obtaining consensus on educational issues difficult. For beneficial change to occur, clear evidence of the benefits to all within the organization must be presented. The objectives of the study were to 1) identify the most common personality types among first- and second-year undergraduate dental students at the University of Texas Dental Branch at Houston using the Myers-Briggs Type Indicator (MBTI); 2) identify the learning preferences of these personality types; and 3) determine a more effective approach to teaching clinical dentistry based upon student personality types and learning preferences. Four common personality types were identified among respondents: ISTJ, ESFJ, ESTJ, and ISFJ, with a predisposition for Sensing (S) (desire for facts, use of senses) over Intuition (N) (look for possibilities, relationships) and Judging (J) (prefers decisiveness, closure) over Perceiving (P) (desire flexibility, spontaneity). The most common occurring personality type, ISTJ, represents an Introverted, Sensing, Thinking, Judging individual. Specific clinical curricular techniques that would appeal to these common personality types are identified, and an explanation of their benefit is provided. Results of this study demonstrate the importance of faculty understanding and acknowledging different student personality types and related learning preferences as a way to initiate improvement of undergraduate dental education, promote student motivation, and allow for an expression of learning style preference.

Assessment of noise levels of the equipments used in the dental teaching institution, Bangalore.

PubMed

Kadanakuppe, Sushi; Bhat, Padma K; Jyothi, C; Ramegowda, C

2011-01-01

In dental practical classes, the acoustic environment is characterized by high noise levels in relation to other teaching areas, due to the exaggerated noise produced by some of these devices and use of dental equipment by many users at the same time. To measure, analyze and compare noise levels of equipments among dental learning areas under different working conditions and also to measure and compare noise levels between used and brand new handpieces under different working conditions. Noise levels were measured and analyzed in different dental learning areas that included clinical, pre-clinical areas and laboratories selected as representatives of a variety of learning-teaching activities. The noise levels were determined using a precision noise level meter (CENTER® 325 IEC 651 TYPE II) with a microphone. The mean of the maxima was determined. The data were collected, tabulated, and statistically analyzed using t tests. The noise levels measured varied between 64 and 97 dB(A).The differences in sound levels when the equipment was merely turned on and during cutting operations and also between used and brand new equipments were recorded. The laboratory engines had the highest noise levels, whereas the noise levels in high-speed turbine handpieces and the low-speed contra angle handpieces were decreased. The noise levels detected in this study are considered to be close to the limit of risk of hearing loss.

The Optimum Font Size and Type for Students Aged 9-12 Reading Arabic Characters on Screen: A Case Study

NASA Astrophysics Data System (ADS)

Abubaker, A. A.; Lu, J.

2012-05-01

More and more, interest in the way data is displayed on screen has increased, especially with the increase in the number of people using e-text for learning purposes. So, this requires more focus on factors that affect screen legibility. Text display factors, such as font size, line length and font type, have an impact on reading online. Two font types [Arabic Traditional and Simplified Arabic] in four different sizes [10, 14, 16 and 18] are measured using Arabic text. On-line processes were measured using reading-aloud technique. Accuracy of reading was also measured by the average of errors that students made when reading the text, while reading speed was tested by the time it took students to read the text. However, results indicated that Arabic text in font size 10 is not readable to students aged 10 to 12. On the other hand, font sizes sixteen and eighteen are more readable than any smaller-sized font, the averages of error size 18 improve in all font types, while age has a significant impact on reading speed. Simplified Arabic font is reported as readable to students aged 10-12, especially in sizes 14 and 18.

Preferences for learning different types of genome sequencing results among young breast cancer patients: Role of psychological and clinical factors.

PubMed

Kaphingst, Kimberly A; Ivanovich, Jennifer; Lyons, Sarah; Biesecker, Barbara; Dresser, Rebecca; Elrick, Ashley; Matsen, Cindy; Goodman, Melody

2018-01-29

The growing importance of genome sequencing means that patients will increasingly face decisions regarding what results they would like to learn. The present study examined psychological and clinical factors that might affect these preferences. 1,080 women diagnosed with breast cancer at age 40 or younger completed an online survey. We assessed their interest in learning various types of genome sequencing results: risk of preventable disease or unpreventable disease, cancer treatment response, uncertain meaning, risk to relatives' health, and ancestry/physical traits. Multivariable logistic regression was used to examine whether being "very" interested in each result type was associated with clinical factors: BRCA1/2 mutation status, prior genetic testing, family history of breast cancer, and psychological factors: cancer recurrence worry, genetic risk worry, future orientation, health information orientation, and genome sequencing knowledge. The proportion of respondents who were very interested in learning each type of result ranged from 16% to 77%. In all multivariable models, those who were very interested in learning a result type had significantly higher knowledge about sequencing benefits, greater genetic risks worry, and stronger health information orientation compared to those with less interest (p-values < .05). Our findings indicate that high interest in return of various types of genome sequencing results was more closely related to psychological factors. Shared decision-making approaches that increase knowledge about genome sequencing and incorporate patient preferences for health information and learning about genetic risks may help support patients' informed choices about learning different types of sequencing results. © Society of Behavioral Medicine 2018.

An Integrated Framework for Human-Robot Collaborative Manipulation.

PubMed

Sheng, Weihua; Thobbi, Anand; Gu, Ye

2015-10-01

This paper presents an integrated learning framework that enables humanoid robots to perform human-robot collaborative manipulation tasks. Specifically, a table-lifting task performed jointly by a human and a humanoid robot is chosen for validation purpose. The proposed framework is split into two phases: 1) phase I-learning to grasp the table and 2) phase II-learning to perform the manipulation task. An imitation learning approach is proposed for phase I. In phase II, the behavior of the robot is controlled by a combination of two types of controllers: 1) reactive and 2) proactive. The reactive controller lets the robot take a reactive control action to make the table horizontal. The proactive controller lets the robot take proactive actions based on human motion prediction. A measure of confidence of the prediction is also generated by the motion predictor. This confidence measure determines the leader/follower behavior of the robot. Hence, the robot can autonomously switch between the behaviors during the task. Finally, the performance of the human-robot team carrying out the collaborative manipulation task is experimentally evaluated on a platform consisting of a Nao humanoid robot and a Vicon motion capture system. Results show that the proposed framework can enable the robot to carry out the collaborative manipulation task successfully.

Integration of multimodal RNA-seq data for prediction of kidney cancer survival

PubMed Central

Schwartzi, Matt; Parkl, Martin; Phanl, John H.; Wang., May D.

2016-01-01

Kidney cancer is of prominent concern in modern medicine. Predicting patient survival is critical to patient awareness and developing a proper treatment regimens. Previous prediction models built upon molecular feature analysis are limited to just gene expression data. In this study we investigate the difference in predicting five year survival between unimodal and multimodal analysis of RNA-seq data from gene, exon, junction, and isoform modalities. Our preliminary findings report higher predictive accuracy-as measured by area under the ROC curve (AUC)-for multimodal learning when compared to unimodal learning with both support vector machine (SVM) and k-nearest neighbor (KNN) methods. The results of this study justify further research on the use of multimodal RNA-seq data to predict survival for other cancer types using a larger sample size and additional machine learning methods. PMID:27532026

Measuring Explicit Word Learning of Preschool Children: A Development Study.

PubMed

Kelley, Elizabeth Spencer

2017-08-15

The purpose of this article is to present preliminary results related to the development of a new measure of explicit word learning. The measure incorporated elements of explicit vocabulary instruction and dynamic assessment and was designed to be sensitive to differences in word learning skill and to be feasible for use in clinical settings. The explicit word learning measure included brief teaching trials and repeated fine-grained measurement of semantic knowledge and production of 3 novel words (2 verbs and 1 adjective). Preschool children (N = 23) completed the measure of explicit word learning; standardized, norm-referenced measures of expressive and receptive vocabulary; and an incidental word learning task. The measure of explicit word learning provided meaningful information about word learning. Performance on the explicit measure was related to existing vocabulary knowledge and incidental word learning. Findings from this development study indicate that further examination of the measure of explicit word learning is warranted. The measure may have the potential to identify children who are poor word learners. https://doi.org/10.23641/asha.5170738.

Exploration of factors that affect the comparative effectiveness of physical and virtual manipulatives in an undergraduate laboratory

NASA Astrophysics Data System (ADS)

Chini, Jacquelyn J.; Madsen, Adrian; Gire, Elizabeth; Rebello, N. Sanjay; Puntambekar, Sadhana

2012-06-01

Recent research results have failed to support the conventionally held belief that students learn physics best from hands-on experiences with physical equipment. Rather, studies have found that students who perform similar experiments with computer simulations perform as well or better on measures of conceptual understanding than their peers who used physical equipment. In this study, we explored how university-level nonscience majors’ understanding of the physics concepts related to pulleys was supported by experimentation with real pulleys and a computer simulation of pulleys. We report that when students use one type of manipulative (physical or virtual), the comparison is influenced both by the concept studied and the timing of the post-test. Students performed similarly on questions related to force and mechanical advantage regardless of the type of equipment used. On the other hand, students who used the computer simulation performed better on questions related to work immediately after completing the activities; however, the two groups performed similarly on the work questions on a test given one week later. Additionally, both sequences of experimentation (physical-virtual and virtual-physical) equally supported students’ understanding of all of the concepts. These results suggest that both the concept learned and the stability of learning gains should continue to be explored to improve educators’ ability to select the best learning experience for a given topic.

Rapid Training of Information Extraction with Local and Global Data Views

DTIC Science & Technology

2012-05-01

relation type extension system based on active learning a relation type extension system based on semi-supervised learning, and a crossdomain...bootstrapping system for domain adaptive named entity extraction. The active learning procedure adopts features extracted at the sentence level as the local

Modeled changes of cerebellar activity in mutant mice are predictive of their learning impairments

NASA Astrophysics Data System (ADS)

Badura, Aleksandra; Clopath, Claudia; Schonewille, Martijn; de Zeeuw, Chris I.

2016-11-01

Translating neuronal activity to measurable behavioral changes has been a long-standing goal of systems neuroscience. Recently, we have developed a model of phase-reversal learning of the vestibulo-ocular reflex, a well-established, cerebellar-dependent task. The model, comprising both the cerebellar cortex and vestibular nuclei, reproduces behavioral data and accounts for the changes in neural activity during learning in wild type mice. Here, we used our model to predict Purkinje cell spiking as well as behavior before and after learning of five different lines of mutant mice with distinct cell-specific alterations of the cerebellar cortical circuitry. We tested these predictions by obtaining electrophysiological data depicting changes in neuronal spiking. We show that our data is largely consistent with the model predictions for simple spike modulation of Purkinje cells and concomitant behavioral learning in four of the mutants. In addition, our model accurately predicts a shift in simple spike activity in a mutant mouse with a brainstem specific mutation. This combination of electrophysiological and computational techniques opens a possibility of predicting behavioral impairments from neural activity.

Modeled changes of cerebellar activity in mutant mice are predictive of their learning impairments

PubMed Central

Badura, Aleksandra; Clopath, Claudia; Schonewille, Martijn; De Zeeuw, Chris I.

2016-01-01

Translating neuronal activity to measurable behavioral changes has been a long-standing goal of systems neuroscience. Recently, we have developed a model of phase-reversal learning of the vestibulo-ocular reflex, a well-established, cerebellar-dependent task. The model, comprising both the cerebellar cortex and vestibular nuclei, reproduces behavioral data and accounts for the changes in neural activity during learning in wild type mice. Here, we used our model to predict Purkinje cell spiking as well as behavior before and after learning of five different lines of mutant mice with distinct cell-specific alterations of the cerebellar cortical circuitry. We tested these predictions by obtaining electrophysiological data depicting changes in neuronal spiking. We show that our data is largely consistent with the model predictions for simple spike modulation of Purkinje cells and concomitant behavioral learning in four of the mutants. In addition, our model accurately predicts a shift in simple spike activity in a mutant mouse with a brainstem specific mutation. This combination of electrophysiological and computational techniques opens a possibility of predicting behavioral impairments from neural activity. PMID:27805050

The Impact of Control Belief and Learning Disorientation on Cognitive Load: The Mediating Effect of Academic Emotions in Two Types of Hypermedia Learning Environments

ERIC Educational Resources Information Center

Sunawan; Xiong, Junmei

2017-01-01

The present study tested the influence of control belief, learning disorientation, and academic emotions on cognitive load in two types of concept-map structures within hypermedia learning environment. Four hundred and eighty-five students were randomly assigned to two groups: 245 students in the hierarchical group and 240 students in the…

Pushing the Limits of Imagination: Mental Practice for Learning Sequences

ERIC Educational Resources Information Center

Wohldmann, Erica L.; Healy, Alice F.; Bourne, Lyle E., Jr.

2007-01-01

In 2 experiments, the efficacy of motor imagery for learning to type number sequences was examined. Adults practiced typing 4-digit numbers. Then, during subsequent training, they either typed in the same or a different location, imagined typing, merely looked at each number, or performed an irrelevant task. Repetition priming (faster responses…

Sentiment analysis: a comparison of deep learning neural network algorithm with SVM and naϊve Bayes for Indonesian text

NASA Astrophysics Data System (ADS)

Calvin Frans Mariel, Wahyu; Mariyah, Siti; Pramana, Setia

2018-03-01

Deep learning is a new era of machine learning techniques that essentially imitate the structure and function of the human brain. It is a development of deeper Artificial Neural Network (ANN) that uses more than one hidden layer. Deep Learning Neural Network has a great ability on recognizing patterns from various data types such as picture, audio, text, and many more. In this paper, the authors tries to measure that algorithm’s ability by applying it into the text classification. The classification task herein is done by considering the content of sentiment in a text which is also called as sentiment analysis. By using several combinations of text preprocessing and feature extraction techniques, we aim to compare the precise modelling results of Deep Learning Neural Network with the other two commonly used algorithms, the Naϊve Bayes and Support Vector Machine (SVM). This algorithm comparison uses Indonesian text data with balanced and unbalanced sentiment composition. Based on the experimental simulation, Deep Learning Neural Network clearly outperforms the Naϊve Bayes and SVM and offers a better F-1 Score while for the best feature extraction technique which improves that modelling result is Bigram.

Active Sampling State Dynamically Enhances Olfactory Bulb Odor Representation.

PubMed

Jordan, Rebecca; Fukunaga, Izumi; Kollo, Mihaly; Schaefer, Andreas T

2018-06-27

The olfactory bulb (OB) is the first site of synaptic odor information processing, yet a wealth of contextual and learned information has been described in its activity. To investigate the mechanistic basis of contextual modulation, we use whole-cell recordings to measure odor responses across rapid learning episodes in identified mitral/tufted cells (MTCs). Across these learning episodes, diverse response changes occur already during the first sniff cycle. Motivated mice develop active sniffing strategies across learning that robustly correspond to the odor response changes, resulting in enhanced odor representation. Evoking fast sniffing in different behavioral states demonstrates that response changes during active sampling exceed those predicted from feedforward input alone. Finally, response changes are highly correlated in tufted cells, but not mitral cells, indicating there are cell-type-specific effects on odor representation during active sampling. Altogether, we show that active sampling is strongly associated with enhanced OB responsiveness on rapid timescales. Copyright © 2018 The Francis Crick Institute. Published by Elsevier Inc. All rights reserved.

Technology-Based Assessments for 21st Century Skills: Theoretical and Practical Implications from Modern Research. Current Perspectives on Cognition, Learning and Instruction

ERIC Educational Resources Information Center

Mayrath, Michael C., Ed.; Clarke-Midura, Jody, Ed.; Robinson, Daniel H., Ed.; Schraw, Gregory, Ed.

2012-01-01

Creative problem solving, collaboration, and technology fluency are core skills requisite of any nation's workforce that strives to be competitive in the 21st Century. Teaching these types of skills is an economic imperative, and assessment is a fundamental component of any pedagogical program. Yet, measurement of these skills is complex due to…

Immediate Evaluation of Training Events at the Economic Development Institute of the World Bank Measuring Reaction, Self-Efficacy and Learning in a Worldwide Context.

ERIC Educational Resources Information Center

Le Rouzie, Violaine; Cusick, Mary

The Economic Development Institute of the World Bank (EDI) conducts extensive training events for a variety of audiences throughout the world. Over the years, EDI has used several types of instruments to evaluate these events. Drawing lessons from these experiences, this paper presents a "hierarchy" of training evaluation designs. These…

Concurrent Medical Conditions and Health Care Use and Needs among Children with Learning and Behavioral Developmental Disabilities, National Health Interview Survey, 2006-2010

ERIC Educational Resources Information Center

Schieve, Laura A.; Gonzalez, Vanessa; Boulet, Sheree L.; Visser, Susanna N.; Rice, Catherine E.; Braun, Kim Van Naarden; Boyle, Coleen A.

2012-01-01

Studies document various associated health risks for children with developmental disabilities (DDs). Further study is needed by disability type. Using the 2006-2010 National Health Interview Surveys, we assessed the prevalence of numerous medical conditions (e.g. asthma, frequent diarrhea/colitis, seizures), health care use measures (e.g. seeing a…

Overview of Pavement Management.

DTIC Science & Technology

1987-01-01

what types of construction and maintenance have worked or failed in the past and can be used as a learning tool . Historical and current data can also be...basis. - Instant records. S- Reasonably good repeatability of results. Disadvantages are: - Need for frequent calibration. - Numerous operating...variations. 2.4 Performance There are other rating methods and numerous methods of 3 measuring road roughness, the use of which help to evaluate

Multidimensional outcome considerations in assessing the efficacy of medical educational programs.

PubMed

Blumberg, Phyllis

2003-01-01

To be accredited, schools must evaluate the effectiveness of their programs. Educators are looking for specific indicators beyond the traditional measures. Data from multiple methods, including indicators of student performance and of the institutional environment, can be used to determine if educational program goals are met. This article outlines specific ways to consider three types of efficacy outcomes that are consistent with accreditation guidelines: educational, clinical career, and environmental outcomes. Specific measurable outcomes for each of these categories are derived from higher education literature: for example, learning approaches and information acquisition for education; professional behaviors and interpersonal dimensions for clinical career, and scholarship of teaching and teaching itself as a shared and valued activity for environmental outcomes. These outcomes address student assessment and program evaluation. Data from problem-based learning programs illustrate these outcomes. Educators can determine if educational program innovations have met their goals by collecting efficacy outcome data.

Integrating Skills and Wills Instruction in Self-Regulated Science Text Reading for Secondary Students

NASA Astrophysics Data System (ADS)

Michalsky, Tova

2013-07-01

This study investigated the effectiveness of cognitive-metacognitive versus motivational components of the IMPROVE self-regulatory model, used while reading scientific texts, for 10th graders' scientific literacy and self-regulated learning (SRL). Three treatment groups (N = 198) received one type of self-addressable questions while reading scientific texts: cognitive-metacognitive (CogMet), motivational (Mot), or combined (CogMetMot). Control group received no self-addressed questions (noSRL). One measure assessed scientific literacy, and two measures assessed SRL: (a) as an aptitude-pre/post questionnaires assessing self-perceived SRL, and (b) as an event-audiotaping participants' thinking-aloud SRL behaviors in real-time learning experiences and data coding illustrating SRL changes. Findings indicated that treatment groups significantly outperformed the non-treatment group. No differences emerged between CogMet and Mot, whereas fully combined SRL support (CogMetMot) was most effective. Theoretical and practical implications of this preliminary study are discussed.

Computational Analysis of Behavior.

PubMed

Egnor, S E Roian; Branson, Kristin

2016-07-08

In this review, we discuss the emerging field of computational behavioral analysis-the use of modern methods from computer science and engineering to quantitatively measure animal behavior. We discuss aspects of experiment design important to both obtaining biologically relevant behavioral data and enabling the use of machine vision and learning techniques for automation. These two goals are often in conflict. Restraining or restricting the environment of the animal can simplify automatic behavior quantification, but it can also degrade the quality or alter important aspects of behavior. To enable biologists to design experiments to obtain better behavioral measurements, and computer scientists to pinpoint fruitful directions for algorithm improvement, we review known effects of artificial manipulation of the animal on behavior. We also review machine vision and learning techniques for tracking, feature extraction, automated behavior classification, and automated behavior discovery, the assumptions they make, and the types of data they work best with.

Utility of behavioral versus cognitive measures in differentiating between subtypes of frontotemporal lobar degeneration and Alzheimer's disease.

PubMed

Heidler-Gary, Jennifer; Gottesman, Rebecca; Newhart, Melissa; Chang, Shannon; Ken, Lynda; Hillis, Argye E

2007-01-01

We hypothesized that a modified version of the Frontal Behavioral Inventory (FBI-mod), along with a few cognitive tests, would be clinically useful in distinguishing between clinically defined Alzheimer's disease (AD) and subtypes of frontotemporal lobar degeneration (FTLD): frontotemporal dementia (dysexecutive type), progressive nonfluent aphasia, and semantic dementia. We studied 80 patients who were diagnosed with AD (n = 30) or FTLD (n = 50), on the basis of a comprehensive neuropsychological battery, imaging, neurological examination, and history. We found significant between-group differences on the FBI-mod, two subtests of the Rey Auditory Verbal Learning Test (verbal learning and delayed recall), and the Trail Making Test Part B (one measure of 'executive functioning'). AD was characterized by relatively severe impairment in verbal learning, delayed recall, and executive functioning, with relatively normal scores on the FBI-mod. Frontotemporal dementia was characterized by relatively severe impairment on the FBI-mod and executive functioning in the absence of severe impairment in verbal learning and recall. Progressive nonfluent aphasia was characterized by severe impairment in executive functioning with relatively normal scores on verbal learning and recall and FBI-mod. Finally, semantic dementia was characterized by relatively severe deficits in delayed recall, but relatively normal performance on new learning, executive functioning, and on FBI-mod. Discriminant function analysis confirmed that the FBI-mod, in conjunction with the Rey Auditory Verbal Learning Test, and the Trail Making Test Part B categorized the majority of patients as subtypes of FTLD or AD in the same way as a full neuropsychological battery, neurological examination, complete history, and imaging. These tests may be useful for efficient clinical diagnosis, although progressive nonfluent aphasia and semantic dementia are likely to be best distinguished by language tests not included in standard neuropsychological test batteries.

P09.62 Towards individualized survival prediction in glioblastoma patients using machine learning methods

PubMed Central

Vera, L.; Pérez-Beteta, J.; Molina, D.; Borrás, J. M.; Benavides, M.; Barcia, J. A.; Velásquez, C.; Albillo, D.; Lara, P.; Pérez-García, V. M.

2017-01-01

Abstract Introduction: Machine learning methods are integrated in clinical research studies due to their strong capability to discover parameters having a high information content and their predictive combined potential. Several studies have been developed using glioblastoma patient’s imaging data. Many of them have focused on including large numbers of variables, mostly two-dimensional textural features and/or genomic data, regardless of their meaning or potential clinical relevance. Materials and methods: 193 glioblastoma patients were included in the study. Preoperative 3D magnetic resonance images were collected and semi-automatically segmented using an in-house software. After segmentation, a database of 90 parameters including geometrical and textural image-based measures together with patients’ clinical data (including age, survival, type of treatment, etc.) was constructed. The criterion for including variables in the study was that they had either shown individual impact on survival in single or multivariate analyses or have a precise clinical or geometrical meaning. These variables were used to perform several machine learning experiments. In a first set of computational cross-validation experiments based on regression trees, those attributes showing the highest information measures were extracted. In the second phase, more sophisticated learning methods were employed in order to validate the potential of the previous variables predicting survival. Concretely support vector machines, neural networks and sparse grid methods were used. Results: Variables showing high information measure in the first phase provided the best prediction results in the second phase. Specifically, patient age, Stupp regimen and a geometrical measure related with the irregularity of contrast-enhancing areas were the variables showing the highest information measure in the first stage. For the second phase, the combinations of patient age and Stupp regimen together with one tumor geometrical measure and one tumor heterogeneity feature reached the best quality prediction. Conclusions: Advanced machine learning methods identified the parameters with the highest information measure and survival predictive potential. The uninformed machine learning methods identified a novel feature measure with direct impact on survival. Used in combination with other previously known variables multi-indexes can be defined that can help in tumor characterization and prognosis prediction. Recent advances on the definition of those multi-indexes will be reported in the conference. Funding: James S. Mc. Donnell Foundation (USA) 21st Century Science Initiative in Mathematical and Complex Systems Approaches for Brain Cancer [Collaborative award 220020450 and planning grant 220020420], MINECO/FEDER [MTM2015-71200-R], JCCM [PEII-2014-031-P].

The effects of types of reflective scaffolding and language proficiency on the acquisition of physics knowledge in a game-based learning environment

NASA Astrophysics Data System (ADS)

Huang, Tsu-Ting

With the capability of creating a situated and engaging learning environment, video games have been considered as a powerful tool to enhance students' learning outcomes and interest in learning. Yet, little empirical evidence exists to support the effectiveness of video games in learning. Particularly, little attention has been given to the design of specific game elements. Focusing on middle school students, the goal of this study was to investigate the effects of two types of representations of reflective scaffolds (verbal and visual) on students' learning outcomes, game performance, and level of engagement in a video game for physics learning. In addition, the role of students' level of English proficiency was examined to understand whether the effects of reflective scaffolds were influenced by students' language proficiency. Two studies were conducted. Study 1 playtested the game with target players and led to game modification for its use in Study 2, which focused on the effects of different types of reflective scaffolds and level of English proficiency. The results of Study 2 showed that students who received both verbal and visual reflective scaffolds completed the most levels compared to the other groups in the given time. No significant effect of type of reflective scaffolds were found on learning outcomes despite the fact that the pattern of the learning outcomes across conditions was close to prediction. Participants' engagement in gameplay was high regardless of the type of scaffolds they received, their interest in learning physics, and their prior knowledge of physics. The results of video analysis also showed that the game used in this study was able to engage students not only in gameplay but also in learning physics. Finally, English proficiency functioned as a significant factor moderating the effects of scaffolds, learning outcomes and game performance. Students with limited English proficiency benefited more from visual reflective scaffolds than verbal ones.

Risk factors for mental disorders develop early in German students of dentistry.

PubMed

Scholz, M; Neumann, C; Ropohl, A; Paulsen, F; Burger, P H M

2016-11-01

We investigated mental risk factors such as symptoms of burnout and sense of coherence in students of dental medicine at the University of Erlangen in the context of a learning type survey. Our aim was to assess the presence of analogies to the results we had previously determined for students of human medicine. We surveyed a total of 163 dentistry students during the first 2.5 years, up to the first state examination. To ensure comparability, the data were collected from all students at the beginning of each semester. Standardized, validated questionnaires on burnout symptoms (Burnout Screening Scales; BOSS-II), sense of coherence (Sense of Coherence Scale; SOC-L9) and learning type according to Kolb were used in the survey. A total of about 90% of the students provided responses to the voluntary survey. The extent and manifest dynamics of the stress levels observed can be characterized as dramatic. Having started out at cognitive and emotional stress levels typical of the normal populace, a massive deterioration of these parameters was observed in the students by the time they were facing their first state examination in the 5th semester. At the same time, their sense of coherence also suffered a pronounced drop-off. No significant learning type-correlated differences were determined in a mean comparison of the measured parameters. Based on the results obtained, we see a need for preventive course offerings to students of dentistry to reduce the prevalence of mental disorders in this group. We discern additional potential for enhancement of mental health with courses more specifically geared to the different learning styles among the students. Copyright © 2016 Elsevier GmbH. All rights reserved.

A National Study Assessing the Teaching and Learning of Introductory Astronomy; Part I: The Effect of Interactive Instruction

NASA Astrophysics Data System (ADS)

Prather, E. E.; Rudolph, A. L.; Brissenden, G.; Schlingman, W. M.

2011-09-01

We present the results of a national study on the teaching and learning of astronomy taught in general education, non-science major, introductory astronomy courses (Astro 101). Nearly 4000 students enrolled in 69 sections of Astro 101 taught at 31 institutions completed (pre- and post- instruction) the Light and Spectroscopy Concept Inventory (LSCI) from Fall 2006 to Fall 2007. The classes varied in size from very small (N < 10) to large (N˜180) and were from all types of institutions, including both 2-year and 4-year colleges and universities. To study how the instruction in different classrooms affected student learning, we developed and administered an Interactivity Assessment Instrument (IAI). This short survey, completed by instructors, allowed us to estimate the fraction of classroom time spent on learner- centered, active-engagement instruction such as Peer Instruction and collaborative tutorials. Pre-instruction LSCI scores were clustered around ˜25% (24 ± 2%), independent of class size and institution type; however, the gains measured varied from about (-)0.07-0.50. The distribution of gain scores indicates that differences were due to instruction in the classroom, not the type of class or institution. Interactivity Assessment Scores (IAS's) ranged from 0%-50%, showing that our IAI was able to distinguish between classes with higher and lower levels of interactivity. A comparison of class-averaged gain score to IAS showed that higher interactivity classes (IAS > 25%) were the only instructional environments capable of reaching the highest gains ( > 0.30). However, the range of gains seen for both groups of classes was quite wide, suggesting that the use of interactive learning strategies is not sufficient by itself to achieve high student gain.

Teaching the Fundamentals of Energy Efficiency

NASA Astrophysics Data System (ADS)

Meier, Alan

2010-02-01

A course on energy efficiency is a surprisingly valuable complement to a student's education in physics and many other disciplines. The Univ. of California, Davis, offers a 1-quarter course on ``understanding the other side of the meter.'' Lectures begin by giving students a demand-side perspective on how, where, and why energy is used. Students measure energy use of appliances in their homes and then report results. This gives students a practical sense of the difference between energy and power and learn how appliances transform energy into useful services. Lectures introduce the types of direct conservation measures--reducing demand, reducing fixed consumptions, and increasing efficiency. Practical examples draw upon simple concepts in heat transfer, thermodynamics, and mechanics. Graphical techniques, strengthened through problem sets, explain the interdependence of conservation measures. Lectures then examine indirect energy savings from measures and consider questions like ``where can one achieve the greatest fuel savings in a car by removing one gram of mass?'' Finally, students learn about conservation measures that circumvent physical limits by adopting new processes. By the end of the course, students have a gained a new perspective on energy consumption and the opportunities to reduce it. )

The external-internal loop of interference: Two types of attention and their influence on the learning abilities of mice

PubMed Central

Sauce, Bruno; Wass, Christopher; Smith, Andrew; Kwan, Stephanie; Matzel, Louis D.

2016-01-01

Attention is a component of the working memory system, and as such, is responsible for protecting task-relevant information from interference. Cognitive performance (particularly outside of the laboratory) is often plagued by interference, and the source of this interference, either external or internal, might influence the expression of individual differences in attentional ability. By definition, external attention (also described as “selective attention”) protects working memory against sensorial distractors of all kinds, while internal attention (also called “inhibition”) protects working memory against emotional impulses, irrelevant information from memory, and automatically-generated responses. At present, it is unclear if these two types of attention are expressed independently in non-human animals, and how they might differentially impact performance on other cognitive processes, such as learning. By using a diverse battery of four attention tests (with varying levels of internal and external sources of interference), here we aimed both to explore this issue, and to obtain a robust and general (less task-specific) measure of attention in mice. Exploratory factor analyses revealed two factors (external and internal attention) that in total, accounted for 73% of the variance in attentional performance. Confirmatory factor analyses found an excellent fit with the data of the model of attention that assumed an external and internal distinction (with a resulting correlation of 0.43). In contrast, a model of attention that assumed one source of variance (i.e., “general attention”) exhibited a poor fit with the data. Regarding the relationship between attention and learning, higher resistance against external sources of interference promoted better new learning, but tended to impair performance when cognitive flexibility was required, such as during the reversal of a previously instantiated response. The present results suggest that there can be (at least) two types of attention that contribute to the common variance in attentional performance in mice, and that external and internal attentions might have opposing influences on the rate at which animals learn. PMID:25452087

Analysis of difficulties in mathematics learning on students with guardian personality type in problem-solving HOTS geometry test

NASA Astrophysics Data System (ADS)

Karimah, R. K. N.; Kusmayadi, T. A.; Pramudya, I.

2018-04-01

Learning in the current 2013 curriculum is based on contextual issues based on questions that can encourage students to think broadly. HOTS is a real-life based assessment of everyday life, but in practice, the students are having trouble completing the HOTS issue. Learning difficulty is also influenced by personality type Based on the fact that the real difference one can see from a person is behavior. Kersey classifies the personality into 4 types, namely Idealist, Rational, Artisan, and Guardian. The researcher focuses on the type of guardian personality that is the type of personality that does not like the picture. This study aims to describe the difficulty of learning mathematics in students with a type of guardian personality in the completion of Geometry materials especially in solving HOTS. This research type is descriptive qualitative research. Instruments used in this study were the researchers themselves, personality class test sheets, learning difficulty test sheets in the form of HOTS Geometry test, and interview guides. The results showed that students with guardian personality it was found that a total of 3.37 % difficulties of number fact skill, 4.49 % difficulties of arithmetics skill, 37.08 % difficulties of information skill, 31.46% difficulties of language skill, 23.60 % difficulties of visual-spatial skill.

Learning a novel phonological contrast depends on interactions between individual differences and training paradigm design

PubMed Central

Perrachione, Tyler K.; Lee, Jiyeon; Ha, Louisa Y. Y.; Wong, Patrick C. M.

2011-01-01

Studies evaluating phonological contrast learning typically investigate either the predictiveness of specific pretraining aptitude measures or the efficacy of different instructional paradigms. However, little research considers how these factors interact—whether different students learn better from different types of instruction—and what the psychological basis for any interaction might be. The present study demonstrates that successfully learning a foreign-language phonological contrast for pitch depends on an interaction between individual differences in perceptual abilities and the design of the training paradigm. Training from stimuli with high acoustic-phonetic variability is generally thought to improve learning; however, we found high-variability training enhanced learning only for individuals with strong perceptual abilities. Learners with weaker perceptual abilities were actually impaired by high-variability training relative to a low-variability condition. A second experiment assessing variations on the high-variability training design determined that the property of this learning environment most detrimental to perceptually weak learners is the amount of trial-by-trial variability. Learners’ perceptual limitations can thus override the benefits of high-variability training where trial-by-trial variability in other irrelevant acoustic-phonetic features obfuscates access to the target feature. These results demonstrate the importance of considering individual differences in pretraining aptitudes when evaluating the efficacy of any speech training paradigm. PMID:21786912

Effects of competitive learning tools on medical students: A case study.

PubMed

Corell, Alfredo; Regueras, Luisa M; Verdú, Elena; Verdú, María J; de Castro, Juan P

2018-01-01

Competitive learning techniques are being successfully used in courses of different disciplines. However, there is still a significant gap in analyzing their effects in medical students competing individually. The authors conducted this study to assess the effectiveness of the use of a competitive learning tool on the academic achievement and satisfaction of medical students. The authors collected data from a Human Immunology course in medical students (n = 285) and conducted a nonrandomized (quasi-experimental) control group pretest-posttest design. They used the Mann-Whitney U-test to measure the strength of the association between two variables and to compare the two student groups. The improvement and academic outcomes of the experimental group students were significantly higher than those of the control group students. The students using the competitive learning tool had better academic performance, and they were satisfied with this type of learning. The study, however, had some limitations. The authors did not make a random assignment to the control and experimental groups and the groups were not completely homogenous. The use of competitive learning techniques motivates medical students, improves their academic outcomes and may foster the cooperation among students and provide a pleasant classroom environment. The authors are planning further studies with a more complete evaluation of cognitive learning styles or incorporating chronometry as well as team-competition.

The importance of relational coordination and reciprocal learning for chronic illness care within primary care teams.

PubMed

Noël, Polly Hitchcock; Lanham, Holly J; Palmer, Ray F; Leykum, Luci K; Parchman, Michael L

2013-01-01

Recent research from a complexity theory perspective suggests that implementation of complex models of care, such as the Chronic Care Model (CCM), requires strong relationships and learning capacities among primary care teams. Our primary aim was to assess the extent to which practice member perceptions of relational coordination and reciprocal learning were associated with the presence of CCM elements in community-based primary care practices. We used baseline measures from a cluster randomized controlled trial testing a practice facilitation intervention to implement the CCM and improve risk factor control for patients with Type 2 diabetes in small primary care practices. Practice members (i.e., physicians, nonphysician providers, and staff) completed baseline assessments, which included the Relational Coordination Scale, Reciprocal Learning Scale, and the Assessment of Chronic Illness Care (ACIC) survey, along with items assessing individual and clinic characteristics. To assess the association between Relational Coordination, Reciprocal Learning, and ACIC, we used a series of hierarchical linear regression models accounting for clustering of individual practice members within clinics and controlling for individual- and practice-level characteristics and tested for mediation effects. A total of 283 practice members from 39 clinics completed baseline measures. Relational Coordination scores were significantly and positively associated with ACIC scores (Model 1). When Reciprocal Learning was added, Relational Coordination remained a significant yet notably attenuated predictor of ACIC (Model 2). The mediation effect was significant (z = 9.3, p < .01); 24% of the association between Relational Coordination and ACIC scores was explained by Reciprocal Learning. Of the individual- and practice-level covariates included in Model 3, only the presence of an electronic medical record was significant; Relational Coordination and Reciprocal Learning remained significant independent predictors of ACIC. Efforts to implement complex models of care should incorporate strategies to strengthen relational coordination and reciprocal learning among team members.

The Importance of Relational Coordination and Reciprocal Learning for Chronic Illness Care within Primary Care Teams

PubMed Central

Noël, Polly Hitchcock; Lanham, Holly J.; Palmer, Ray F.; Leykum, Luci K.; Parchman, Michael L.

2012-01-01

Background Recent research from a complexity theory perspective suggests that implementation of complex models of care, such as the Chronic Care Model (CCM), requires strong relationships and learning capacities among primary care teams. Purposes Our primary aim was to assess the extent to which practice member perceptions of relational coordination and reciprocal learning were associated with the presence of CCM elements in community-based primary care practices. Methodology/Approach We used baseline measures from a cluster randomized controlled trial testing a practice facilitation intervention to implement the CCM and improve risk factor control for patients with type 2 diabetes in small primary care practices. Practice members (i.e., physicians, non-physician providers, and staff) completed baseline assessments, which included the Relational Coordination Scale, Reciprocal Learning Scale, and the Assessment of Chronic Illness Care (ACIC) survey, along with items assessing individual and clinic characteristics. To assess the association between Relational Coordination, Reciprocal Learning, and ACIC, we used a series of hierarchical linear regression models accounting for clustering of individual practice members within clinics and controlling for individual- and practice-level characteristics, and tested for mediation effects. Findings 283 practice members from 39 clinics completed baseline measures. Relational Coordination scores were significantly and positively associated with ACIC scores (Model 1). When Reciprocal Learning was added, Relational Coordination remained a significant yet notably attenuated predictor of ACIC (Model 2). The mediation effect was significant (z = 9.3, p<.01); 24% of the association between Relational Coordination and ACIC scores was explained by Reciprocal Learning. Of the individual and practice level covariates included in Model 3, only the presence of an electronic medical record was significant; Relational Coordination and Reciprocal Learning remained significant independent predictors of ACIC. Practice Implications Efforts to implement complex models of care should incorporate strategies to strengthen relational coordination and reciprocal learning among team members. PMID:22310483

Developing an online chemistry laboratory for non-chemistry majors

NASA Astrophysics Data System (ADS)

Poole, Jacqueline H.

Distance education, also known as online learning, is student-centered/self-directed educational opportunities. This style of learning is expanding in scope and is increasingly being accepted throughout the academic curriculum as a result of its flexibility for the student as well as the cost-effectiveness for the institution. Nevertheless, the introduction of online science courses including chemistry and physics have lagged behind due to the challenge of re-creation of the hands-on laboratory learning experience. This dissertation looks at the effectiveness of the design of a series of chemistry laboratory experiments for possible online delivery that provide students with simulated hands-on experiences. One class of college Chemistry 101 students conducted chemistry experiments inside and outside of the physical laboratory using instructions on Blackboard and Late Nite Labs(TM). Learning outcomes measured by (a) pretests, (b) written laboratory reports, (c) posttest assessments, (d) student reactions as determined by a questionnaire, and (e) a focus group interview were utilized to compare both types of laboratory experiences. The research findings indicated learning outcomes achieved by students outside of the traditional physical laboratory were statistically greater than the equivalent face-to-face instruction in the traditional laboratory. Evidence from student reactions comparing both types of laboratory formats (online and traditional face-to-face) indicated student preference for the online laboratory format. The results are an initial contribution to the design of a complete sequence of experiments that can be performed independently by online students outside of the traditional face-to-face laboratory that will satisfy the laboratory requirement for the two-semester college Chemistry 101 laboratory course.

Relationships Between the Way Students Are Assessed in Science Classrooms and Science Achievement Across Canada

NASA Astrophysics Data System (ADS)

Chu, Man-Wai; Fung, Karen

2018-04-01

Canadian students experience many different assessments throughout their schooling (O'Connor 2011). There are many benefits to using a variety of assessment types, item formats, and science-based performance tasks in the classroom to measure the many dimensions of science education. Although using a variety of assessments is beneficial, it is unclear exactly what types, format, and tasks are used in Canadian science classrooms. Additionally, since assessments are often administered to help improve student learning, this study identified assessments that may improve student learning as measured using achievement scores on a standardized test. Secondary analyses of the students' and teachers' responses to the questionnaire items asked in the Pan-Canadian Assessment Program were performed. The results of the hierarchical linear modeling analyses indicated that both students and teachers identified teacher-developed classroom tests or quizzes as the most common types of assessments used. Although this ranking was similar across the country, statistically significant differences in terms of the assessments that are used in science classrooms among the provinces were also identified. The investigation of which assessment best predicted student achievement scores indicated that minds-on science performance-based tasks significantly explained 4.21% of the variance in student scores. However, mixed results were observed between the student and teacher responses towards tasks that required students to choose their own investigation and design their own experience or investigation. Additionally, teachers that indicated that they conducted more demonstrations of an experiment or investigation resulted in students with lower scores.

WE-A-BRE-01: Debate: To Measure or Not to Measure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moran, J; Miften, M; Mihailidis, D

2014-06-15

Recent studies have highlighted some of the limitations of patient-specific pre-treatment IMRT QA measurements with respect to assessing plan deliverability. Pre-treatment QA measurements are frequently performed with detectors in phantoms that do not involve any patient heterogeneities or with an EPID without a phantom. Other techniques have been developed where measurement results are used to recalculate the patient-specific dose volume histograms. Measurements continue to play a fundamental role in understanding the initial and continued performance of treatment planning and delivery systems. Less attention has been focused on the role of computational techniques in a QA program such as calculation withmore » independent dose calculation algorithms or recalculation of the delivery with machine log files or EPID measurements. This session will explore the role of pre-treatment measurements compared to other methods such as computational and transit dosimetry techniques. Efficiency and practicality of the two approaches will also be presented and debated. The speakers will present a history of IMRT quality assurance and debate each other regarding which types of techniques are needed today and for future quality assurance. Examples will be shared of situations where overall quality needed to be assessed with calculation techniques in addition to measurements. Elements where measurements continue to be crucial such as for a thorough end-to-end test involving measurement will be discussed. Operational details that can reduce the gamma tool effectiveness and accuracy for patient-specific pre-treatment IMRT/VMAT QA will be described. Finally, a vision for the future of IMRT and VMAT plan QA will be discussed from a safety perspective. Learning Objectives: Understand the advantages and limitations of measurement and calculation approaches for pre-treatment measurements for IMRT and VMAT planning Learn about the elements of a balanced quality assurance program involving modulated techniques Learn how to use tools and techniques such as an end-to-end test to enhance your IMRT and VMAT QA program.« less

Health-Related Intensity Profiles of Physical Education Classes at Different Phases of the Teaching/Learning Process

ERIC Educational Resources Information Center

Bronikowski, Michal; Bronikowska, Malgorzata; Kantanista, Adam; Ciekot, Monika; Laudanska-Krzeminska, Ida; Szwed, Szymon

2009-01-01

Study aim: To assess the intensities of three types of physical education (PE) classes corresponding to the phases of the teaching/learning process: Type 1--acquiring and developing skills, Type 2--selecting and applying skills, tactics and compositional principles and Type 3--evaluating and improving performance skills. Material and methods: A…

Analysis of space radiation data of semiconductor memories

NASA Technical Reports Server (NTRS)

Stassinopoulos, E. G.; Brucker, G. J.; Stauffer, C. A.

1996-01-01

This article presents an analysis of radiation effects for several select device types and technologies aboard the Combined Release and Radiation Effects Satellite (CRRES) satellite. These space-flight measurements covered a period of about 14 months of mission lifetime. Single Event Upset (SEU) data of the investigated devices from the Microelectronics Package (MEP) were processed and analyzed. Valid upset measurements were determined by correcting for invalid readings, hard failures, missing data tapes (thus voids in data), and periods over which devices were disabled from interrogation. The basic resolution time of the measurement system was confirmed to be 2 s. Lessons learned, important findings, and recommendations are presented.

Learning of state-space models with highly informative observations: A tempered sequential Monte Carlo solution

NASA Astrophysics Data System (ADS)

Svensson, Andreas; Schön, Thomas B.; Lindsten, Fredrik

2018-05-01

Probabilistic (or Bayesian) modeling and learning offers interesting possibilities for systematic representation of uncertainty using probability theory. However, probabilistic learning often leads to computationally challenging problems. Some problems of this type that were previously intractable can now be solved on standard personal computers thanks to recent advances in Monte Carlo methods. In particular, for learning of unknown parameters in nonlinear state-space models, methods based on the particle filter (a Monte Carlo method) have proven very useful. A notoriously challenging problem, however, still occurs when the observations in the state-space model are highly informative, i.e. when there is very little or no measurement noise present, relative to the amount of process noise. The particle filter will then struggle in estimating one of the basic components for probabilistic learning, namely the likelihood p (data | parameters). To this end we suggest an algorithm which initially assumes that there is substantial amount of artificial measurement noise present. The variance of this noise is sequentially decreased in an adaptive fashion such that we, in the end, recover the original problem or possibly a very close approximation of it. The main component in our algorithm is a sequential Monte Carlo (SMC) sampler, which gives our proposed method a clear resemblance to the SMC2 method. Another natural link is also made to the ideas underlying the approximate Bayesian computation (ABC). We illustrate it with numerical examples, and in particular show promising results for a challenging Wiener-Hammerstein benchmark problem.

Cognitive Profile of Neurofibromatosis Type 1: Rethinking Nonverbal Learning Disabilities

ERIC Educational Resources Information Center

Cutting, Laurie E.; Clements, Amy M.; Lightman, Andrea D.; Yerby-Hammack, Pamula D.; Denckla, Martha Bridge

2004-01-01

The cognitive profiles of children with Neurofibromatosis Type 1 (NF-1) have many similarities to those observed in learning disabilities in the general school population, as well as some distinct features. Approximately 30-65 percent of children with NF-1 have learning disabilities; most commonly, they have language and reading disabilities,…

Types of Language Learning Strategies Used by Tertiary English Majors

ERIC Educational Resources Information Center

Chuin, Tan Khye; Kaur, Sarjit

2015-01-01

This study investigated the types of language learning strategies used by 73 English majors from the School of Humanities in Universiti Sains Malaysia. Using questionnaires adopted from Oxford's (1990) Strategy Inventory of Language Learning (SILL) and focus group interviews, the study also examined the English major students' perceptions of using…

The Learning Organization and the Level of Consciousness

ERIC Educational Resources Information Center

Chiva, Ricardo

2017-01-01

Purpose: The purpose of this paper is to analyze learning organization by comparing with other types of organizations. This typology is based on the levels of consciousness and relates each type of organization with a level of learning and an organizational structure. Design/methodology/approach: This is a conceptual paper based on the concept of…

Elementary School Students' Strategic Learning: Does Task-Type Matter?

ERIC Educational Resources Information Center

Malmberg, Jonna; Järvelä, Sanna; Kirschner, Paul A.

2014-01-01

This study investigated what types of learning patterns and strategies elementary school students use to carry out ill- and well-structured tasks. Specifically, it was investigated which and when learning patterns actually emerge with respect to students' task solutions. The present study uses computer log file traces to investigate how…

Examining Culturally Structured Learning Environments with Different Types of Music-Linked Movement Opportunity

ERIC Educational Resources Information Center

Cole, Juanita M.; Boykin, A. Wade

2008-01-01

This study describes two experiments that extended earlier work on the Afrocultural theme Movement Expression. The impact of various learning conditions characterized by different types of music-linked movement on story recall performance was examined. African American children were randomly assigned to a learning condition, presented a story, and…

Predicting Learners Styles Based on Fuzzy Model

ERIC Educational Resources Information Center

Alian, Marwah; Shaout, Adnan

2017-01-01

Learners style is grouped into four types mainly; Visual, auditory, kinesthetic and Read/Write. Each type of learners learns primarily through one of the main receiving senses, visual, listening, or by doing. Learner style has an effect on the learning process and learner's achievement. It is better to select suitable learning tool for the learner…

Search strategy selection in the Morris water maze indicates allocentric map formation during learning that underpins spatial memory formation.

PubMed

Rogers, Jake; Churilov, Leonid; Hannan, Anthony J; Renoir, Thibault

2017-03-01

Using a Matlab classification algorithm, we demonstrate that a highly salient distal cue array is required for significantly increased likelihoods of spatial search strategy selection during Morris water maze spatial learning. We hypothesized that increased spatial search strategy selection during spatial learning would be the key measure demonstrating the formation of an allocentric map to the escape location. Spatial memory, as indicated by quadrant preference for the area of the pool formally containing the hidden platform, was assessed as the main measure that this allocentric map had formed during spatial learning. Our C57BL/6J wild-type (WT) mice exhibit quadrant preference in the highly salient cue paradigm but not the low, corresponding with a 120% increase in the odds of a spatial search strategy selection during learning. In contrast, quadrant preference remains absent in serotonin 1A receptor (5-HT 1A R) knockout (KO) mice, who exhibit impaired search strategy selection during spatial learning. Additionally, we also aimed to assess the impact of the quality of the distal cue array on the spatial learning curves of both latency to platform and path length using mixed-effect regression models and found no significant associations or interactions. In contrast, we demonstrated that the spatial learning curve for search strategy selection was absent during training in the low saliency paradigm. Therefore, we propose that allocentric search strategy selection during spatial learning is the learning parameter in mice that robustly indicates the formation of a cognitive map for the escape goal location. These results also suggest that both latency to platform and path length spatial learning curves do not discriminate between allocentric and egocentric spatial learning and do not reliably predict spatial memory formation. We also show that spatial memory, as indicated by the absolute time in the quadrant formerly containing the hidden platform alone (without reference to the other areas of the pool), was not sensitive to cue saliency or impaired in 5-HT 1A R KO mice. Importantly, in the absence of a search strategy analysis, this suggests that to establish that the Morris water maze has worked (i.e. control mice have formed an allocentric map to the escape goal location), a measure of quadrant preference needs to be reported to establish spatial memory formation. This has implications for studies that claim hippocampal functioning is impaired using latency to platform or path length differences within the existing Morris water maze literature. Copyright © 2016 Elsevier Inc. All rights reserved.

Grounded Learning Experience: Helping Students Learn Physics through Visuo-Haptic Priming and Instruction

NASA Astrophysics Data System (ADS)

Huang, Shih-Chieh Douglas

In this dissertation, I investigate the effects of a grounded learning experience on college students' mental models of physics systems. The grounded learning experience consisted of a priming stage and an instruction stage, and within each stage, one of two different types of visuo-haptic representation was applied: visuo-gestural simulation (visual modality and gestures) and visuo-haptic simulation (visual modality, gestures, and somatosensory information). A pilot study involving N = 23 college students examined how using different types of visuo-haptic representation in instruction affected people's mental model construction for physics systems. Participants' abilities to construct mental models were operationalized through their pretest-to-posttest gain scores for a basic physics system and their performance on a transfer task involving an advanced physics system. Findings from this pilot study revealed that, while both simulations significantly improved participants' mental modal construction for physics systems, visuo-haptic simulation was significantly better than visuo-gestural simulation. In addition, clinical interviews suggested that participants' mental model construction for physics systems benefited from receiving visuo-haptic simulation in a tutorial prior to the instruction stage. A dissertation study involving N = 96 college students examined how types of visuo-haptic representation in different applications support participants' mental model construction for physics systems. Participant's abilities to construct mental models were again operationalized through their pretest-to-posttest gain scores for a basic physics system and their performance on a transfer task involving an advanced physics system. Participants' physics misconceptions were also measured before and after the grounded learning experience. Findings from this dissertation study not only revealed that visuo-haptic simulation was significantly more effective in promoting mental model construction and remedying participants' physics misconceptions than visuo-gestural simulation, they also revealed that visuo-haptic simulation was more effective during the priming stage than during the instruction stage. Interestingly, the effects of visuo-haptic simulation in priming and visuo-haptic simulation in instruction on participants' pretest-to-posttest gain scores for a basic physics system appeared additive. These results suggested that visuo-haptic simulation is effective in physics learning, especially when it is used during the priming stage.

AGSuite: Software to conduct feature analysis of artificial grammar learning performance.

PubMed

Cook, Matthew T; Chubala, Chrissy M; Jamieson, Randall K

2017-10-01

To simplify the problem of studying how people learn natural language, researchers use the artificial grammar learning (AGL) task. In this task, participants study letter strings constructed according to the rules of an artificial grammar and subsequently attempt to discriminate grammatical from ungrammatical test strings. Although the data from these experiments are usually analyzed by comparing the mean discrimination performance between experimental conditions, this practice discards information about the individual items and participants that could otherwise help uncover the particular features of strings associated with grammaticality judgments. However, feature analysis is tedious to compute, often complicated, and ill-defined in the literature. Moreover, the data violate the assumption of independence underlying standard linear regression models, leading to Type I error inflation. To solve these problems, we present AGSuite, a free Shiny application for researchers studying AGL. The suite's intuitive Web-based user interface allows researchers to generate strings from a database of published grammars, compute feature measures (e.g., Levenshtein distance) for each letter string, and conduct a feature analysis on the strings using linear mixed effects (LME) analyses. The LME analysis solves the inflation of Type I errors that afflicts more common methods of repeated measures regression analysis. Finally, the software can generate a number of graphical representations of the data to support an accurate interpretation of results. We hope the ease and availability of these tools will encourage researchers to take full advantage of item-level variance in their datasets in the study of AGL. We moreover discuss the broader applicability of the tools for researchers looking to conduct feature analysis in any field.

Intact attentional processing but abnormal responding in M1 muscarinic receptor-deficient mice using an automated touchscreen method

PubMed Central

Bartko, Susan J.; Romberg, Carola; White, Benjamin; Wess, Jürgen; Bussey, Timothy J.; Saksida, Lisa M.

2014-01-01

Cholinergic receptors have been implicated in schizophrenia, Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease. However, to better target therapeutically the appropriate receptor subsystems, we need to understand more about the functions of those subsystems. In the current series of experiments, we assessed the functional role of M1 receptors in cognition by testing M1 receptor-deficient mice (M1R−/−) on the five-choice serial reaction time test of attentional and response functions, carried out using a computer-automated touchscreen test system. In addition, we tested these mice on several tasks featuring learning, memory and perceptual challenges. An advantage of the touchscreen method is that each test in the battery is carried out in the same task setting, using the same types of stimuli, responses and feedback, thus providing a high level of control and task comparability. The surprising finding, given the predominance of the M1 receptor in cortex, was the complete lack of effect of M1 deletion on measures of attentional function per se. Moreover, M1R−/− mice performed relatively normally on tests of learning, memory and perception, although they were impaired in object recognition memory with, but not without an interposed delay interval. They did, however, show clear abnormalities on a variety of response measures: M1R−/− mice displayed fewer omissions, more premature responses, and increased perseverative responding compared to wild-types. These data suggest that M1R−/− mice display abnormal responding in the face of relatively preserved attention, learning and perception. PMID:21903112

Influence of learning style on instructional multimedia effects on graduate student cognitive and psychomotor performance.

PubMed

Smith, A Russell; Cavanaugh, Catherine; Jones, Joyce; Venn, John; Wilson, William

2006-01-01

Learning outcomes may improve in graduate healthcare students when attention is given to individual learning styles. Interactive multimedia is one tool shown to increase success in meeting the needs of diverse learners. The purpose of this study was to examine the effect of learning style and type of instruction on physical therapy students' cognitive and psychomotor performance. Participants were obtained by a sample of convenience with students recruited from two physical therapy programs. Twenty-seven students volunteered to participate from Program 1. Twenty-three students volunteered to participate from Program 2. Gregorc learning styles were identified through completion of the Gregorc Style Delineator. Students were randomly assigned to one of two instructional strategies: 1) instructional CD or 2) live demonstration. Differences in cognitive or psychomotor performance following instructional multimedia based on learning style were not demonstrated in this study. Written examination scores improved with both instructional strategies demonstrating no differences between the strategies. Practical examination ankle scores were significantly higher in participants receiving CD instruction than in participants receiving live presentation. Learning style did not significantly affect this improvement. Program 2 performed significantly better on written knee and practical knee and ankle examinations. Learning style had no significant effect on student performance following instruction in clinical skills via interactive multimedia. Future research may include additional measurement instruments assessing other models of learning styles and possible interaction of learning style and instructional strategy on students over longer periods of time, such as a semester or an entire curriculum.

Pre-registration nursing student's quality of practice learning: Clinical learning environment inventory (actual) questionnaire.

PubMed

Shivers, Eleanor; Hasson, Felicity; Slater, Paul

2017-08-01

Clinical learning is a vital component of nurse education and assessing student's experiences can provide useful insights for development. Whilst most research in this area has focused on the acute setting little attention has been given to all pre-registration nurses' experience across the clinical placements arenas. To examine of pre-registration nursing students (first, second and third year) assessment of their actual experiences of their most recent clinical learning clinical learning experience. A cross sectional survey involving a descriptive online anonymous questionnaire based on the clinical learning environment inventory tool. One higher education institution in the United Kingdom. Nursing students (n=147) enrolled in an undergraduate nursing degree. This questionnaire included demographic questions and the Clinical Learning Environment Inventory (CLEI) a 42 item tool measuring student's satisfaction with clinical placement. SPPS version 22 was employed to analyse data with descriptive and inferential statistics. Overall students were satisfied with their clinical learning experience across all placement areas. This was linked to the 6 constructs of the clinical learning environment inventory; personalization, innovation, individualization, task orientation, involvement, satisfaction. Significant differences in student experience were noted between age groups and student year but there was no difference noted between placement type, age and gender. Nursing students had a positive perception of their clinical learning experience, although there remains room for improvement. Enabling a greater understanding of students' perspective on the quality of clinical education is important for nursing education and future research. Copyright © 2017. Published by Elsevier Ltd.

Dissociation of visual associative and motor learning in Drosophila at the flight simulator.

PubMed

Wang, Shunpeng; Li, Yan; Feng, Chunhua; Guo, Aike

2003-08-29

Ever since operant conditioning was studied experimentally, the relationship between associative learning and possible motor learning has become controversial. Although motor learning and its underlying neural substrates have been extensively studied in mammals, it is still poorly understood in invertebrates. The visual discriminative avoidance paradigm of Drosophila at the flight simulator has been widely used to study the flies' visual associative learning and related functions, but it has not been used to study the motor learning process. In this study, newly-designed data analysis was employed to examine the flies' solitary behavioural variable that was recorded at the flight simulator-yaw torque. Analysis was conducted to explore torque distributions of both wild-type and mutant flies in conditioning, with the following results: (1) Wild-type Canton-S flies had motor learning performance in conditioning, which was proved by modifications of the animal's behavioural mode in conditioning. (2) Repetition of training improved the motor learning performance of wild-type Canton-S flies. (3) Although mutant dunce(1) flies were defective in visual associative learning, they showed essentially normal motor learning performance in terms of yaw torque distribution in conditioning. Finally, we tentatively proposed that both visual associative learning and motor learning were involved in the visual operant conditioning of Drosophila at the flight simulator, that the two learning forms could be dissociated and they might have different neural bases.

Learning a cost function for microscope image segmentation.

PubMed

Nilufar, Sharmin; Perkins, Theodore J

2014-01-01

Quantitative analysis of microscopy images is increasingly important in clinical researchers' efforts to unravel the cellular and molecular determinants of disease, and for pathological analysis of tissue samples. Yet, manual segmentation and measurement of cells or other features in images remains the norm in many fields. We report on a new system that aims for robust and accurate semi-automated analysis of microscope images. A user interactively outlines one or more examples of a target object in a training image. We then learn a cost function for detecting more objects of the same type, either in the same or different images. The cost function is incorporated into an active contour model, which can efficiently determine optimal boundaries by dynamic programming. We validate our approach and compare it to some standard alternatives on three different types of microscopic images: light microscopy of blood cells, light microscopy of muscle tissue sections, and electron microscopy cross-sections of axons and their myelin sheaths.

Potentiation of latent inhibition by haloperidol and clozapine is attenuated in Dopamine D2 receptor (Drd-2)-deficient mice: Do antipsychotics influence learning to ignore irrelevant stimuli via both Drd-2 and non-Drd-2 mechanisms?

PubMed Central

O’Callaghan, Matthew J; Bay-Richter, Cecilie; O’Tuathaigh, Colm MP; Heery, David M; Waddington, John L; Moran, Paula M

2014-01-01

Whether the dopamine Drd-2 receptor is necessary for the behavioural action of antipsychotic drugs is an important question, as Drd-2 antagonism is responsible for their debilitating motor side effects. Using Drd-2 null mice (Drd2 -/-) it has previously been shown that Drd-2 is not necessary for antipsychotic drugs to reverse D-amphetamine disruption of latent inhibition (LI), a behavioural measure of learning to ignore irrelevant stimuli. Weiner’s ‘two-headed’ model indicates that antipsychotics not only reverse LI disruption, ‘disrupted LI’, but also potentiate LI when low/absent in controls, ‘persistent’ LI. We investigated whether antipsychotic drugs haloperidol or clozapine potentiated LI in wild-type controls or Drd2 -/-. Both drugs potentiated LI in wild-type but not in Drd2-/- mice, suggesting moderation of this effect of antipsychotics in the absence of Drd-2. Haloperidol potentiated LI similarly in both Drd1-/- and wild-type mice, indicating no such moderation in Drd1-/-. These data suggest that antipsychotic drugs can have either Drd-2 or non-Drd-2 effects on learning to ignore irrelevant stimuli, depending on how the abnormality is produced. Identification of the non-Drd-2 mechanism may help to identify novel non-Drd2 based therapeutic strategies for psychosis. PMID:25122042

Look/Learn

ERIC Educational Resources Information Center

Nicoll, William

1976-01-01

The textbook characteristics of type size, type style, and layout, and the important psychological role these play in learning are discussed in terms of their application to the design of a typewriting text. (Editor/HD)

Impact of Indoor Physical Environment on Learning Efficiency in Different Types of Tasks: A 3 × 4 × 3 Full Factorial Design Analysis.

PubMed

Xiong, Lilin; Huang, Xiao; Li, Jie; Mao, Peng; Wang, Xiang; Wang, Rubing; Tang, Meng

2018-06-13

Indoor physical environments appear to influence learning efficiency nowadays. For improvement in learning efficiency, environmental scenarios need to be designed when occupants engage in different learning tasks. However, how learning efficiency is affected by indoor physical environment based on task types are still not well understood. The present study aims to explore the impacts of three physical environmental factors (i.e., temperature, noise, and illuminance) on learning efficiency according to different types of tasks, including perception, memory, problem-solving, and attention-oriented tasks. A 3 × 4 × 3 full factorial design experiment was employed in a university classroom with 10 subjects recruited. Environmental scenarios were generated based on different levels of temperature (17 °C, 22 °C, and 27 °C), noise (40 dB(A), 50 dB(A), 60 dB(A), and 70 dB(A)) and illuminance (60 lx, 300 lx, and 2200 lx). Accuracy rate (AC), reaction time (RT), and the final performance indicator (PI) were used to quantify learning efficiency. The results showed ambient temperature, noise, and illuminance exerted significant main effect on learning efficiency based on four task types. Significant concurrent effects of the three factors on final learning efficiency was found in all tasks except problem-solving-oriented task. The optimal environmental scenarios for top learning efficiency were further identified under different environmental interactions. The highest learning efficiency came in thermoneutral, relatively quiet, and bright conditions in perception-oriented task. Subjects performed best under warm, relatively quiet, and moderately light exposure when recalling images in the memory-oriented task. Learning efficiency peaked to maxima in thermoneutral, fairly quiet, and moderately light environment in problem-solving process while in cool, fairly quiet and bright environment with regard to attention-oriented task. The study provides guidance for building users to conduct effective environmental intervention with simultaneous controls of ambient temperature, noise, and illuminance. It contributes to creating the most suitable indoor physical environment for improving occupants learning efficiency according to different task types. The findings could further supplement the present indoor environment-related standards or norms with providing empirical reference on environmental interactions.

Mathematics authentic assessment on statistics learning: the case for student mini projects

NASA Astrophysics Data System (ADS)

Fauziah, D.; Mardiyana; Saputro, D. R. S.

2018-03-01

Mathematics authentic assessment is a form of meaningful measurement of student learning outcomes for the sphere of attitude, skill and knowledge in mathematics. The construction of attitude, skill and knowledge achieved through the fulfilment of tasks which involve active and creative role of the students. One type of authentic assessment is student mini projects, started from planning, data collecting, organizing, processing, analysing and presenting the data. The purpose of this research is to learn the process of using authentic assessments on statistics learning which is conducted by teachers and to discuss specifically the use of mini projects to improving students’ learning in the school of Surakarta. This research is an action research, where the data collected through the results of the assessments rubric of student mini projects. The result of data analysis shows that the average score of rubric of student mini projects result is 82 with 96% classical completeness. This study shows that the application of authentic assessment can improve students’ mathematics learning outcomes. Findings showed that teachers and students participate actively during teaching and learning process, both inside and outside of the school. Student mini projects also provide opportunities to interact with other people in the real context while collecting information and giving presentation to the community. Additionally, students are able to exceed more on the process of statistics learning using authentic assessment.

Broad-based visual benefits from training with an integrated perceptual-learning video game.

PubMed

Deveau, Jenni; Lovcik, Gary; Seitz, Aaron R

2014-06-01

Perception is the window through which we understand all information about our environment, and therefore deficits in perception due to disease, injury, stroke or aging can have significant negative impacts on individuals' lives. Research in the field of perceptual learning has demonstrated that vision can be improved in both normally seeing and visually impaired individuals, however, a limitation of most perceptual learning approaches is their emphasis on isolating particular mechanisms. In the current study, we adopted an integrative approach where the goal is not to achieve highly specific learning but instead to achieve general improvements to vision. We combined multiple perceptual learning approaches that have individually contributed to increasing the speed, magnitude and generality of learning into a perceptual-learning based video-game. Our results demonstrate broad-based benefits of vision in a healthy adult population. Transfer from the game includes; improvements in acuity (measured with self-paced standard eye-charts), improvement along the full contrast sensitivity function, and improvements in peripheral acuity and contrast thresholds. The use of this type of this custom video game framework built up from psychophysical approaches takes advantage of the benefits found from video game training while maintaining a tight link to psychophysical designs that enable understanding of mechanisms of perceptual learning and has great potential both as a scientific tool and as therapy to help improve vision. Copyright © 2014 Elsevier B.V. All rights reserved.

Learning Bayesian Networks from Correlated Data

NASA Astrophysics Data System (ADS)

Bae, Harold; Monti, Stefano; Montano, Monty; Steinberg, Martin H.; Perls, Thomas T.; Sebastiani, Paola

2016-05-01

Bayesian networks are probabilistic models that represent complex distributions in a modular way and have become very popular in many fields. There are many methods to build Bayesian networks from a random sample of independent and identically distributed observations. However, many observational studies are designed using some form of clustered sampling that introduces correlations between observations within the same cluster and ignoring this correlation typically inflates the rate of false positive associations. We describe a novel parameterization of Bayesian networks that uses random effects to model the correlation within sample units and can be used for structure and parameter learning from correlated data without inflating the Type I error rate. We compare different learning metrics using simulations and illustrate the method in two real examples: an analysis of genetic and non-genetic factors associated with human longevity from a family-based study, and an example of risk factors for complications of sickle cell anemia from a longitudinal study with repeated measures.

A New Approach to Active Learning in the Planetarium

NASA Astrophysics Data System (ADS)

Hodge, T. M.; Saderholm, J. C.

2012-08-01

In a recent survey, Small & Plummer (2010) found that the goals of planetarium professionals are aligned with inquiry-based, active learning. However, most planetarium shows are designed as passive entertainment, with education as a secondary goal. In addition, there are very few research-based studies on the types of activities which promote greater learning within the planetarium environment, particularly at the post-secondary level. We report the results of the pilot test of a novel use of the planetarium to provide a simulated night sky, which students use to make longitudinal observations and measurements of planetary positions. In spite of several pragmatic limitations, the planetarium environment is well suited to student construction of both geocentric and heliocentric models of the solar system from direct observation. The curriculum we are developing addresses common misconceptions about the nature of science, in particular the use of modeling in the development of scientific knowledge.

Execution and pauses in writing narratives: processing time, cognitive effort and typing skill.

PubMed

Alves, Rui Alexandre; Castro, São Luís; Olive, Thierry

2008-12-01

At the behavioural level, the activity of a writer can be described as periods of typing separated by pauses. Although some studies have been concerned with the functions of pauses, few have investigated motor execution periods. Precise estimates of the distribution of writing processes, and their cognitive demands, across periods of typing and pauses are lacking. Furthermore, it is uncertain how typing skill affects these aspects of writing. We addressed these issues, selecting writers of low and high typing skill who performed dictation and composition tasks. The occurrences of writing processes were assessed through directed verbalization, and their cognitive demands were measured through interference in reaction times (IRT). Before writing a narrative, 34 undergraduates learned to categorize examples of introspective thoughts as different types of activities related to writing (planning, translating, or revising). Then, while writing, they responded to random auditory probes, and reported their ongoing activity according to the learned categories. Convergent with previous findings, translating was most often reported, and revising and planning had fewer occurrences. Translating was mostly activated during motor execution, whereas revising and planning were mainly activated during pauses. However, none of the writing processes can be characterized as being typical of pauses, since translating was activated to a similar extent as the other two processes. Regarding cognitive demands, revising is likely to be the most demanding process in narrative writing. Typing skill had an impact on IRTs of motor execution. The demands of execution were greater in the low than in the high typing skill group, but these greater demands did not affect the strategy of writing processes activation. Nevertheless, low typing skill had a detrimental impact on text quality.

Can Role-Play with Virtual Humans Teach Interpersonal Skills?

DTIC Science & Technology

2012-12-01

the participants in the control group completed unrelated coursework. One day later, all of the participants completed the posttest . The...the data from the three types of items on the pretest and posttest . Three participants failed to follow instructions during the experimental...measure learning. For example, two items were answered correctly on the pretest and posttest by all of the participants; the items were too easy. Such

Examining the Role of Orthographic Coding Ability in Elementary Students with Previously Identified Reading Disability, Speech or Language Impairment, or Comorbid Language and Learning Disabilities

ERIC Educational Resources Information Center

Haugh, Erin Kathleen

2017-01-01

The purpose of this study was to examine the role orthographic coding might play in distinguishing between membership in groups of language-based disability types. The sample consisted of 36 second and third-grade subjects who were administered the PAL-II Receptive Coding and Word Choice Accuracy subtest as a measure of orthographic coding…

Noise levels in the learning-teaching activities in a dental medicine school

NASA Astrophysics Data System (ADS)

Matos, Andreia; Carvalho, Antonio P. O.; Fernandes, Joao C. S.

2002-11-01

The noise levels made by different clinical handpieces and laboratory engines are considered to be the main descriptors of acoustical comfort in learning spaces in a dental medicine school. Sound levels were measured in five types of classrooms and teaching laboratories at the University of Porto Dental Medicine School. Handpiece noise measurements were made while instruments were running free and during operations with cutting tools (tooth, metal, and acrylic). Noise levels were determined using a precision sound level meter, which was positioned at ear level and also at one-meter distance from the operator. Some of the handpieces were brand new and the others had a few years of use. The sound levels encountered were between 60 and 99 dB(A) and were compared with the noise limits in A-weighted sound pressure level for mechanical equipments installed in educational buildings included in the Portuguese Noise Code and in other European countries codes. The daily personal noise exposure levels (LEP,d) of the students and professors were calculated to be between 85 and 90 dB(A) and were compared with the European legal limits. Some noise limits for this type of environment are proposed and suggestions for the improvement of the acoustical environment are given.

From dioramas to the dinner table: An ethnographic case study of the role of science museums in family life

NASA Astrophysics Data System (ADS)

Ellenbogen, Kirsten M.

What we know about learning in museums tends to come from studies of single museum visits evaluating success according to the museum's agenda, neglecting the impressive cooperative learning strategies and resources that families bring to their museum experiences. This is a report of an ethnographic case study of four families that visit science museums frequently. The study used ethnographic research and discourse analysis as combined methodological approaches, and was grounded in a sociocultural perspective that frames science as a socially and culturally constituted activity. Over eighteen months, data were collected during observations of the families in science museums, at home, and at other leisure sites. The study generated two types of findings. First, macroanalysis based on established frameworks for understanding learning in museums revealed differences in the orientation and extent of the museum visits. Additionally, a hierarchical framework for measuring science learning in museums proved insensitive. These findings underscore limitations of some of the traditional frameworks for understanding family learning in science museums. Second, microanalysis of interactions around science objects at home and in museums revealed that parents provided children with opportunities to understand the "middle ground" of science. Analysis also revealed that families adapted the science content of the museum to renegotiate family identities. Interestingly, the types of discourse most valued in science education were least important for establishing family identity. These frequent museumgoers eliminated the distance between them and science objects by transforming their meanings to establish family identity. This study demonstrates that the families' mediating strategies shape not just an understanding of science, but also a family identity that is constructed in and through interactions with science. The results of this study provide a foundation for examining how families use museums over time and the network of learning resources that support family life. This study suggests possible ways for museum professionals to reconsider the design of learning activities, museum environments, and a shift in focus from the learning institution of the science museum to the learning institution of the family.

Transformational Learning: Reflections of an Adult Learning Story

ERIC Educational Resources Information Center

Foote, Laura S.

2015-01-01

Transformational learning, narrative learning, and spiritual learning frame adult experiences in new and exciting ways. These types of learning can involve a simple transformation of belief or opinion or a radical transformation involving one's total perspective; learning may occur abruptly or incrementally. Education should liberate students from…

The Effect of Type of Podcasts and Learning Styles on Language Proficiency and Confidence

ERIC Educational Resources Information Center

Kelly, Wei Qiang; Klein, James D.

2016-01-01

This study examined the effect of type of podcasts and learning styles on speaking, listening, and confidence when college used podcasts for learning Chinese. It focused on college students enrolled in a beginning-level Chinese course at a large university in the southeastern United States. Findings indicated that listening to grammar podcasts…

Lessons Learned from My Students: The Impact of SEM Teaching and Learning on Affective Development

ERIC Educational Resources Information Center

Hebert, Thomas P.

2010-01-01

Through reflection on his years as an enrichment teacher in Schoolwide Enrichment Model (SEM) programs, the author describes significant ways the social and emotional development of his students was shaped by their involvement in enriched teaching and learning. Through portraits of his students engaged in Type II and Type III enrichment, the…

Investigation into Motivation Types and Influences on Motivation: The Case of Chinese Non-English Majors

ERIC Educational Resources Information Center

Zhao, Lei

2012-01-01

Motivation is one of the most important factors affecting students' performance of English learning, which is widely concerned by foreign language teachers and researchers for a long time. However, how to promote students' motivation in learning English by knowing their English learning motivation types at the initial stages and the factors that…

Type 2 Diabetes Risk Test

MedlinePlus

... Risk? Home Prevention Diagnosing Diabetes and Learning About Prediabetes Type 2 Diabetes Risk Test Lower Your Risk ... Diabetes Risk Test Diagnosing Diabetes and Learning About Prediabetes Lower Your Risk donate en -- A Future Without ...

Causal Model Progressions as a Foundation for Intelligent Learning Environments.

DTIC Science & Technology

1987-11-01

Foundation for Intelligent Learning Environments 3Barbara Y. White and John R. Frederiksen ~DTIC Novemr1987 ELECTE November1987 JUNO 9 88 Approved I )’I...Learning Environments 12. PERSONAL AUTHOR(S? Barbara Y. White and John R. Frederiksen 13a. TYPE OF REPORT 13b TIME COVERED 14. DATE OF REPORT (Year...architecture of a new type of learning environment that incorporates features of microworlds and of intelligent tutorng systems. The environment is based on

MULTI-SOURCE FEATURE LEARNING FOR JOINT ANALYSIS OF INCOMPLETE MULTIPLE HETEROGENEOUS NEUROIMAGING DATA

PubMed Central

Yuan, Lei; Wang, Yalin; Thompson, Paul M.; Narayan, Vaibhav A.; Ye, Jieping

2012-01-01

Analysis of incomplete data is a big challenge when integrating large-scale brain imaging datasets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiative (ADNI), for example, over half of the subjects lack cerebrospinal fluid (CSF) measurements; an independent half of the subjects do not have fluorodeoxyglucose positron emission tomography (FDG-PET) scans; many lack proteomics measurements. Traditionally, subjects with missing measures are discarded, resulting in a severe loss of available information. In this paper, we address this problem by proposing an incomplete Multi-Source Feature (iMSF) learning method where all the samples (with at least one available data source) can be used. To illustrate the proposed approach, we classify patients from the ADNI study into groups with Alzheimer’s disease (AD), mild cognitive impairment (MCI) and normal controls, based on the multi-modality data. At baseline, ADNI’s 780 participants (172 AD, 397 MCI, 211 NC), have at least one of four data types: magnetic resonance imaging (MRI), FDG-PET, CSF and proteomics. These data are used to test our algorithm. Depending on the problem being solved, we divide our samples according to the availability of data sources, and we learn shared sets of features with state-of-the-art sparse learning methods. To build a practical and robust system, we construct a classifier ensemble by combining our method with four other methods for missing value estimation. Comprehensive experiments with various parameters show that our proposed iMSF method and the ensemble model yield stable and promising results. PMID:22498655

Does it really matter whether students' contributions are spoken versus typed in an intelligent tutoring system with natural language?

PubMed

D'Mello, Sidney K; Dowell, Nia; Graesser, Arthur

2011-03-01

There is the question of whether learning differs when students speak versus type their responses when interacting with intelligent tutoring systems with natural language dialogues. Theoretical bases exist for three contrasting hypotheses. The speech facilitation hypothesis predicts that spoken input will increase learning, whereas the text facilitation hypothesis predicts typed input will be superior. The modality equivalence hypothesis claims that learning gains will be equivalent. Previous experiments that tested these hypotheses were confounded by automated speech recognition systems with substantial error rates that were detected by learners. We addressed this concern in two experiments via a Wizard of Oz procedure, where a human intercepted the learner's speech and transcribed the utterances before submitting them to the tutor. The overall pattern of the results supported the following conclusions: (1) learning gains associated with spoken and typed input were on par and quantitatively higher than a no-intervention control, (2) participants' evaluations of the session were not influenced by modality, and (3) there were no modality effects associated with differences in prior knowledge and typing proficiency. Although the results generally support the modality equivalence hypothesis, highly motivated learners reported lower cognitive load and demonstrated increased learning when typing compared with speaking. We discuss the implications of our findings for intelligent tutoring systems that can support typed and spoken input.

Deep Learning-Based Noise Reduction Approach to Improve Speech Intelligibility for Cochlear Implant Recipients.

PubMed

Lai, Ying-Hui; Tsao, Yu; Lu, Xugang; Chen, Fei; Su, Yu-Ting; Chen, Kuang-Chao; Chen, Yu-Hsuan; Chen, Li-Ching; Po-Hung Li, Lieber; Lee, Chin-Hui

2018-01-20

We investigate the clinical effectiveness of a novel deep learning-based noise reduction (NR) approach under noisy conditions with challenging noise types at low signal to noise ratio (SNR) levels for Mandarin-speaking cochlear implant (CI) recipients. The deep learning-based NR approach used in this study consists of two modules: noise classifier (NC) and deep denoising autoencoder (DDAE), thus termed (NC + DDAE). In a series of comprehensive experiments, we conduct qualitative and quantitative analyses on the NC module and the overall NC + DDAE approach. Moreover, we evaluate the speech recognition performance of the NC + DDAE NR and classical single-microphone NR approaches for Mandarin-speaking CI recipients under different noisy conditions. The testing set contains Mandarin sentences corrupted by two types of maskers, two-talker babble noise, and a construction jackhammer noise, at 0 and 5 dB SNR levels. Two conventional NR techniques and the proposed deep learning-based approach are used to process the noisy utterances. We qualitatively compare the NR approaches by the amplitude envelope and spectrogram plots of the processed utterances. Quantitative objective measures include (1) normalized covariance measure to test the intelligibility of the utterances processed by each of the NR approaches; and (2) speech recognition tests conducted by nine Mandarin-speaking CI recipients. These nine CI recipients use their own clinical speech processors during testing. The experimental results of objective evaluation and listening test indicate that under challenging listening conditions, the proposed NC + DDAE NR approach yields higher intelligibility scores than the two compared classical NR techniques, under both matched and mismatched training-testing conditions. When compared to the two well-known conventional NR techniques under challenging listening condition, the proposed NC + DDAE NR approach has superior noise suppression capabilities and gives less distortion for the key speech envelope information, thus, improving speech recognition more effectively for Mandarin CI recipients. The results suggest that the proposed deep learning-based NR approach can potentially be integrated into existing CI signal processors to overcome the degradation of speech perception caused by noise.

Sleep effects on slow-brain-potential reflections of associative learning.

PubMed

Verleger, Rolf; Ludwig, Janna; Kolev, Vasil; Yordanova, Juliana; Wagner, Ullrich

2011-03-01

Previous research has indicated that information acquired before sleep gets consolidated during sleep. This process of consolidation might be reflected after sleep in changed extent and topography of cortical activation during retrieval of information. Here, we designed an experiment to measure those changes by means of slow event-related EEG potentials (SPs). Retrieval of newly learnt verbal or spatial associations was tested both immediately after learning and two days later. In the night directly following immediate recall, participants either slept or stayed awake. In line with previous studies, SPs measured during retrieval from memory had parietal or left-frontal foci depending on whether the retrieved associations were spatial or verbal. However, contrary to our expectations, sleep-related consolidation did not further accentuate these content-specific topographic profiles. Rather, sleep modified SPs independently of the spatial or verbal type of learned association: SPs were reduced more after sleep than after waking specifically for those stimulus configurations that had been presented in the same combination at retrieval before sleep. The association-independent stimulus-specific effect might generally form a major component of sleep-related effects on memory. Copyright © 2010 Elsevier B.V. All rights reserved.

Investigation of irradiated 1H-Benzo[b]pyrrole by ESR, thermal methods and learning algorithm

NASA Astrophysics Data System (ADS)

Algul, Gulay; Ceylan, Yusuf; Usta, Keziban; Yumurtaci Aydogmus, Hacer; Usta, Ayhan; Asik, Biray

2016-05-01

1H-Benzo[b]pyrrole samples were irradiated in the air with gamma source at 0.969 kGy per hour at room temperature for 24, 48 and 72 h. After irradiation, electron spin resonance, thermogravimetry analysis (TGA) and differential thermal analysis (DTA) measurements were immediately carried out on the irradiated and unirradiated samples. The ESR measurements were performed between 320 and 400 K. ESR spectra were recorded from the samples irradiated for 48 and 72 h. The obtained spectra were observed to be dependent on temperature. Two radical-type centres were detected on the sample. Detected radiation-induced radicals were attributed to R-+•NH and R=•CC2H2. The g-values and hyperfine constants were calculated by means of the experimental spectra. It was also determined from TGA spectrum that both the unirradiated and irradiated samples were decomposed at one step with the rising temperature. Moreover, a theoretical study was presented. Success of the machine learning methods was tested. It was found that bagging techniques, which are widely used in the machine learning literature, could optimise prediction accuracy noticeably.

Measuring the impact of informal science education in zoos on environmental knowledge, attitudes and behaviors

NASA Astrophysics Data System (ADS)

Wilson, Christopher David

Despite the emphasis in modern zoos and aquaria on conservation and environmental education, we know very little about what people learn in these settings, and even less about how they learn it. Research on informal learning in settings such as zoos has suffered from a lack of theory, with few connections being made to theories of learning in formal settings, or to theories regarding the nature of the educational goals. This dissertation consists of three parts: the development and analysis of a test instrument designed to measure constructs of environmental learning in zoos; the application of the test instrument along with qualitative data collection in an evaluation designed to measure the effectiveness of a zoo's education programs; and the analysis of individually matched pre- and post-test data to examine how environmental learning takes place, with respect to the constructivist view of learning, as well as theories of environmental learning and the barriers to pro-environmental behavior. The test instrument consisted of 40 items split into four scales: environmental knowledge, attitudes toward the environment, support for conservation, and environmentally responsible behavior. A model-driven approach was used to develop the instrument, which was analyzed using Item Response Theory and the Rasch dichotomous measurement model. After removal of two items with extremely high difficulty, the instrument was found to be unidimensional and sufficiently reliable. The results of the IRT analyses are interpreted with respect to a modern validity framework. The evaluation portion of this study applied this test instrument to measuring the impact of zoo education programs on 750 fourth through seventh grade students. Qualitative data was collected from program observations and teacher surveys, and a comparison was also made between programs that took place at the zoo, and those that took place in the school classroom, thereby asking questions regarding the role of setting in environmental education. It was found that students in both program types significantly increased their environmental knowledge as a result of the program, but only students in the school-based programs significantly improved their attitudes towards the environment. Analyzing by grade, seventh grade students scored significantly lower on all aspects of the test than the younger students, suggesting a detrimental effect of novel settings on learning in adolescents. Teacher survey data suggests that teachers place great importance on how the education program would fit in with their school-based curriculum, but did little to integrate the program into their classroom teaching. Observations of the programs revealed some logistical issues, and some concerns regarding the zoo instructors' use of curriculum materials. Analyzing the test data from a constructivist perspective revealed that students with high incoming environmental attitudes had significant increases in environmental knowledge. That is, students with positive attitudes towards the environment are predisposed to engage in learning about the environment. Some gender-specific findings are also discussed.

Eliciting explanations: Constraints on when self-explanation aids learning.

PubMed

Rittle-Johnson, Bethany; Loehr, Abbey M

2017-10-01

Generating explanations for oneself in an attempt to make sense of new information (i.e., self-explanation) is often a powerful learning technique. Despite its general effectiveness, in a growing number of studies, prompting for self-explanation improved some aspects of learning, but reduced learning of other aspects. Drawing on this recent research, as well as on research comparing self-explanation under different conditions, we propose four constraints on the effectiveness of self-explanation. First, self-explanation promotes attention to particular types of information, so it is better suited to promote particular learning outcomes in particular types of domains, such as transfer in domains guided by general principles or heuristics. Second, self-explaining a variety of types of information can improve learning, but explaining one's own solution methods or choices may reduce learning under certain conditions. Third, explanation prompts focus effort on particular aspects of the to-be-learned material, potentially drawing effort away from other important information. Explanation prompts must be carefully designed to align with target learning outcomes. Fourth, prompted self-explanation often promotes learning better than unguided studying, but alternative instructional techniques may be more effective under some conditions. Attention to these constraints should optimize the effectiveness of self-explanation as an instructional technique in future research and practice.

Training-induced elevations in extracellular lactate in hippocampus and striatum: Dissociations by cognitive strategy and type of reward.

PubMed

Newman, Lori A; Scavuzzo, Claire J; Gold, Paul E; Korol, Donna L

2017-01-01

Recent evidence suggests that astrocytes convert glucose to lactate, which is released from the astrocytes and supports learning and memory. This report takes a multiple memory perspective to test the role of astrocytes in cognition using real-time lactate measurements during learning and memory. Extracellular lactate levels in the hippocampus or striatum were determined with lactate biosensors while rats were learning place (hippocampus-sensitive) or response (striatum-sensitive) versions of T-mazes. In the first experiment, rats were trained on the place and response tasks to locate a food reward. Extracellular lactate levels in the hippocampus increased beyond those of feeding controls during place training but not during response training. However, striatal lactate levels did not increase beyond those of controls when rats were trained on either the place or the response version of the maze. Because food ingestion itself increased blood glucose and brain lactate levels, the contribution of feeding may have confounded the brain lactate measures. Therefore, we conducted a second similar experiment using water as the reward. A very different pattern of lactate responses to training emerged when water was used as the task reward. First, provision of water itself did not result in large increases in either brain or blood lactate levels. Moreover, extracellular lactate levels increased in the striatum during response but not place learning, whereas extracellular lactate levels in the hippocampus did not differ across tasks. The findings from the two experiments suggest that the relative engagement of the hippocampus and striatum dissociates not only by task but also by reward type. The divergent lactate responses of the hippocampus and striatum in place and response tasks under different reward conditions may reflect ethological constraints tied to foraging for food and water. Copyright © 2016 Elsevier Inc. All rights reserved.

Protein Dynamics Associated with Failed and Rescued Learning in the Ts65Dn Mouse Model of Down Syndrome

PubMed Central

Ahmed, Md. Mahiuddin; Dhanasekaran, A. Ranjitha; Block, Aaron; Tong, Suhong; Costa, Alberto C. S.; Stasko, Melissa; Gardiner, Katheleen J.

2015-01-01

Down syndrome (DS) is caused by an extra copy of human chromosome 21 (Hsa21). Although it is the most common genetic cause of intellectual disability (ID), there are, as yet, no effective pharmacotherapies. The Ts65Dn mouse model of DS is trisomic for orthologs of ∼55% of Hsa21 classical protein coding genes. These mice display many features relevant to those seen in DS, including deficits in learning and memory (L/M) tasks requiring a functional hippocampus. Recently, the N-methyl-D-aspartate (NMDA) receptor antagonist, memantine, was shown to rescue performance of the Ts65Dn in several L/M tasks. These studies, however, have not been accompanied by molecular analyses. In previous work, we described changes in protein expression induced in hippocampus and cortex in control mice after exposure to context fear conditioning (CFC), with and without memantine treatment. Here, we extend this analysis to Ts65Dn mice, measuring levels of 85 proteins/protein modifications, including components of MAP kinase and MTOR pathways, and subunits of NMDA receptors, in cortex and hippocampus of Ts65Dn mice after failed learning in CFC and after learning was rescued by memantine. We show that, compared with wild type littermate controls, (i) of the dynamic responses seen in control mice in normal learning, >40% also occur in Ts65Dn in failed learning or are compensated by baseline abnormalities, and thus are considered necessary but not sufficient for successful learning, and (ii) treatment with memantine does not in general normalize the initial protein levels but instead induces direct and indirect responses in approximately half the proteins measured and results in normalization of the endpoint protein levels. Together, these datasets provide a first view of the complexities associated with pharmacological rescue of learning in the Ts65Dn. Extending such studies to additional drugs and mouse models of DS will aid in identifying pharmacotherapies for effective clinical trials. PMID:25793384

Machine learning-based patient specific prompt-gamma dose monitoring in proton therapy

NASA Astrophysics Data System (ADS)

Gueth, P.; Dauvergne, D.; Freud, N.; Létang, J. M.; Ray, C.; Testa, E.; Sarrut, D.

2013-07-01

Online dose monitoring in proton therapy is currently being investigated with prompt-gamma (PG) devices. PG emission was shown to be correlated with dose deposition. This relationship is mostly unknown under real conditions. We propose a machine learning approach based on simulations to create optimized treatment-specific classifiers that detect discrepancies between planned and delivered dose. Simulations were performed with the Monte-Carlo platform Gate/Geant4 for a spot-scanning proton therapy treatment and a PG camera prototype currently under investigation. The method first builds a learning set of perturbed situations corresponding to a range of patient translation. This set is then used to train a combined classifier using distal falloff and registered correlation measures. Classifier performances were evaluated using receiver operating characteristic curves and maximum associated specificity and sensitivity. A leave-one-out study showed that it is possible to detect discrepancies of 5 mm with specificity and sensitivity of 85% whereas using only distal falloff decreases the sensitivity down to 77% on the same data set. The proposed method could help to evaluate performance and to optimize the design of PG monitoring devices. It is generic: other learning sets of deviations, other measures and other types of classifiers could be studied to potentially reach better performance. At the moment, the main limitation lies in the computation time needed to perform the simulations.

Performance of Children With Developmental Dyslexia on Two Skill Learning Tasks-Serial Reaction Time and Tower of Hanoi Puzzle: A Test of the Specific Procedural Learning Difficulties Theory.

PubMed

Vakil, Eli; Lowe, Michal; Goldfus, Carol

2015-01-01

Among the various theories proposed to explain developmental dyslexia (DD), the theory of specific procedural learning difficulties has gained certain support and is the framework for the current research. This theory claims that an inability to achieve skill automaticity explains the difficulties experienced by individuals with DD. Previous research on automaticity and DD has exhibited methodological issues such as a failure to test a range of skills. The current study broadens previous findings by delineating various reading skills correlated with several aspects of skill acquisition. Furthermore, the study utilizes two nonverbal tasks that reflect distinct types of skills: Serial Reaction Time (SRT) and the Tower of Hanoi Puzzle (TOHP). A total of 53 children aged 11 to 13 participated in the study, of whom 23 were children with DD and 30 were controls. Participants completed a test battery that consisted of reading tests, the SRT, and the TOHP. Results show no differences in learning rate between individuals with or without DD, although individuals with DD performed both tasks at a slower rate. Correlations were identified between a number of reading measures and measures of skill acquisition, expressed primarily in individuals with DD. Implications are examined in the discussion. © Hammill Institute on Disabilities 2013.

Measuring Cognitive Load in Embodied Learning Settings.

PubMed

Skulmowski, Alexander; Rey, Günter Daniel

2017-01-01

In recent years, research on embodied cognition has inspired a number of studies on multimedia learning and instructional psychology. However, in contrast to traditional research on education and multimedia learning, studies on embodied learning (i.e., focusing on bodily action and perception in the context of education) in some cases pose new problems for the measurement of cognitive load. This review provides an overview over recent studies on embodied learning in which cognitive load was measured using surveys, behavioral data, or physiological measures. The different methods are assessed in terms of their success in finding differences of cognitive load in embodied learning scenarios. At the same time, we highlight the most important challenges for researchers aiming to include these measures into their study designs. The main issues we identified are: (1) Subjective measures must be appropriately phrased to be useful for embodied learning; (2) recent findings indicate potentials as well as problematic aspects of dual-task measures; (3) the use of physiological measures offers great potential, but may require mobile equipment in the context of embodied scenarios; (4) meta-cognitive measures can be useful extensions of cognitive load measurement for embodied learning.

Meta-Analysis of Fluid Intelligence Tests of Children from the Chinese Mainland with Learning Difficulties

PubMed Central

Tong, Fang; Fu, Tong

2013-01-01

Objective To evaluate the differences in fluid intelligence tests between normal children and children with learning difficulties in China. Method PubMed, MD Consult, and other Chinese Journal Database were searched from their establishment to November 2012. After finding comparative studies of Raven measurements of normal children and children with learning difficulties, full Intelligent Quotation (FIQ) values and the original values of the sub-measurement were extracted. The corresponding effect model was selected based on the results of heterogeneity and parallel sub-group analysis was performed. Results Twelve documents were included in the meta-analysis, and the studies were all performed in mainland of China. Among these, two studies were performed at child health clinics, the other ten sites were schools and control children were schoolmates or classmates. FIQ was evaluated using a random effects model. WMD was −13.18 (95% CI: −16.50–−9.85). Children with learning difficulties showed significantly lower FIQ scores than controls (P<0.00001); Type of learning difficulty and gender differences were evaluated using a fixed-effects model (I2 = 0%). The sites and purposes of the studies evaluated here were taken into account, but the reasons of heterogeneity could not be eliminated; The sum IQ of all the subgroups showed considerable heterogeneity (I2 = 76.5%). The sub-measurement score of document A showed moderate heterogeneity among all documents, and AB, B, and E showed considerable heterogeneity, which was used in a random effect model. Individuals with learning difficulties showed heterogeneity as well. There was a moderate delay in the first three items (−0.5 to −0.9), and a much more pronounced delay in the latter three items (−1.4 to −1.6). Conclusion In the Chinese mainland, the level of fluid intelligence of children with learning difficulties was lower than that of normal children. Delayed development in sub-items of C, D, and E was more obvious. PMID:24236016

The Multimedia-Based Learning System Improved Cognitive Skills and Motivation of Disabled Children with a Very High Rate

ERIC Educational Resources Information Center

Saad, Sawsan; Dandashi, Amal; Aljaam, Jihad M.; Saleh, Moataz

2015-01-01

A multimedia-based learning system to teach children with intellectual disabilities (ID) the basic living and science concepts is proposed. The tutorials' development is pedagogically based on Mayer's Cognitive Theory of Multimedia Learning combined with Skinner's Operant Conditioning Model. Two types of tutorials are proposed. In the first type;…

What the Right Data Can Do: Find Sources that Can Help Tailor Learning to Each Educator's Needs

ERIC Educational Resources Information Center

Holcomb, Edie

2013-01-01

Learning Forward's Data standard advocates using data from a variety of sources and types--including student, educator, and system data--to plan, assess, and evaluate professional learning. This presents several challenges, beginning with the emphasis on a variety of sources and types. The pressures of No Child Left Behind have focused American…

Social cultural and situative perspective of studying emotions in teaching and learning: characteristics, challenges and opportunities

NASA Astrophysics Data System (ADS)

Tan, Seng-Chee

2013-09-01

In this forum, I take a learning sciences perspective to examine the paper by Bellocchi, Ritchie, Tobin, Sandhu and Sandhu ( Cultural Studies of Science Education, doi: 10.1007/s11422-013-9526-3 , 2013) titled "Examining emotional climate of preservice science teacher education." I characterize their approach as a social cultural and situative perspective of studying emotions in teaching and learning. Such an approach overcomes the limitations of examining emotions as individual psychological constructs, but it also incurs other methodological challenges. I suggest an alternative approach of examining the individual's emotions, as well as their aggregates as a group measure. This approach allows us to study variations in emotional outcomes at an individual level or at a group level. I also suggest examining interplay of emotions with other aspects of learning outcomes, for example, cognitive learning outcomes. Finally, I suggest studying development of meta-emotional knowledge among teachers as another fertile area of research that could benefit the teachers in their classroom practices.

An investigation of the role of some person and situation variables in multiple cue probability learning.

PubMed

Bayindir, Mustafa; Bolger, Fergus; Say, Bilge

2016-07-19

Making decisions using judgements of multiple non-deterministic indicators is an important task, both in everyday and professional life. Learning of such decision making has often been studied as the mapping of stimuli (cues) to an environmental variable (criterion); however, little attention has been paid to the effects of situation-by-person interactions on this learning. Accordingly, we manipulated cue and feedback presentation mode (graphic or numeric) and task difficulty, and measured individual differences in working memory capacity (WMC). We predicted that graphic presentation, fewer cues, and elevated WMC would facilitate learning, and that person and task characteristics would interact such that presentation mode compatible with the decision maker's cognitive capability (enhanced visual or verbal WMC) would assist learning, particularly for more difficult tasks. We found our predicted main effects, but no significant interactions, except that those with greater WMC benefited to a larger extent with graphic than with numeric presentation, regardless of which type of working memory was enhanced or number of cues. Our findings suggest that the conclusions of past research based predominantly on tasks using numeric presentation need to be reevaluated and cast light on how working memory helps us learn multiple cue-criterion relationships, with implications for dual-process theories of cognition.

The effects of team-based learning techniques on nursing students' perception of the psycho-social climate of the classroom.

PubMed

Koohestani, Hamid Reza; Baghcheghi, Nayereh

2016-01-01

Background: Team-based learning is a structured type of cooperative learning that is becoming increasingly more popular in nursing education. This study compares levels of nursing students' perception of the psychosocial climate of the classroom between conventional lecture group and team-based learning group. Methods: In a quasi-experimental study with pretest-posttest design 38 nursing students of second year participated. One half of the 16 sessions of cardiovascular disease nursing course sessions was taught by lectures and the second half with team-based learning. The modified college and university classroom environment inventory (CUCEI) was used to measure the perception of classroom environment. This was completed after the final lecture and TBL sessions. Results: Results revealed a significant difference in the mean scores of psycho-social climate for the TBL method (Mean (SD): 179.8(8.27)) versus the mean score for the lecture method (Mean (SD): 154.213.44)). Also, the results showed significant differences between the two groups in the innovation (p<0.001), student cohesiveness (p=0.01), cooperation (p<0.001) and equity (p= 0.03) sub-scales scores (p<0.05). Conclusion: This study provides evidence that team-based learning does have a positive effect on nursing students' perceptions of their psycho-social climate of the classroom.

Does Augmented Reality Affect High School Students' Learning Outcomes in Chemistry?

NASA Astrophysics Data System (ADS)

Renner, Jonathan Christopher

Some teens may prefer using a self-directed, constructivist, and technologic approach to learning rather than traditional classroom instruction. If it can be demonstrated, educators may adjust their teaching methodology. The guiding research question for this study focused on how augmented reality affects high school students' learning outcomes in chemistry, as measured by a pretest and posttest methodology when ensuring that the individual outcomes were not the result of group collaboration. This study employed a quantitative, quasi-experimental study design that used a comparison and experimental group. Inferential statistical analysis was employed. The study was conducted at a high school in southwest Colorado. Eighty-nine respondents returned completed and signed consent forms, and 78 participants completed the study. Results demonstrated that augmented reality instruction caused posttest scores to significantly increase, as compared to pretest scores, but it was not as effective as traditional classroom instruction. Scores did improve under both types of instruction; therefore, more research is needed in this area. The present study was the first quantitative experiment controlling for individual learning to validate augmented reality using mobile handheld digital devices that affected individual students' learning outcomes without group collaboration. This topic was important to the field of education as it may help educators understand how students learn and it may also change the way students are taught.

The Effect of Learning Type and Avatar Similarity on Learning Outcomes in Educational Video Games

ERIC Educational Resources Information Center

Lewis, Melissa L.

2009-01-01

Two theories guide two very different ideas about learning. Social cognitive theory (Bandura, 1977, 1989) places the greater emphasis on observational learning, or learning by watching a model produce a behavior before doing it oneself. Other researchers purport that experiential learning, or learning by doing, results in stronger learning (Kolb,…

The Development of a Comprehensive and Coherent Theory of Learning

ERIC Educational Resources Information Center

Illeris, Knud

2015-01-01

This article is an account of how the author developed a comprehensive understanding of human learning over a period of almost 50 years. The learning theory includes the structure of learning, different types of learning, barriers of learning as well as how individual dispositions, age, the learning environment and general social and societal…

Course Management Systems and Blended Learning: An Innovative Learning Approach

ERIC Educational Resources Information Center

Chou, Amy Y.; Chou, David C.

2011-01-01

This article utilizes Rogers' innovation-decision process model (2003) and Beckman and Berry's innovation process model (2007) to create an innovative learning map that illustrates three learning methods (i.e., face-to-face learning, online learning, and blended learning) in two types of innovation (i.e., incremental innovation and radical…

Vocabulary learning in primary school children: working memory and long-term memory components.

PubMed

Morra, Sergio; Camba, Roberta

2009-10-01

The goal of this study was to investigate which working memory and long-term memory components predict vocabulary learning. We used a nonword learning paradigm in which 8- to 10-year-olds learned picture-nonword pairs. The nonwords varied in length (two vs. four syllables) and phonology (native sounding vs. including one Russian phoneme). Short, phonologically native nonwords were learned best, whereas learning long nonwords leveled off after a few presentation cycles. Linear structural equation analyses showed an influence of three constructs-phonological sensitivity, vocabulary knowledge, and central attentional resources (M capacity)-on nonword learning, but the extent of their contributions depended on specific characteristics of the nonwords to be learned. Phonological sensitivity predicted learning of all nonword types except short native nonwords, vocabulary predicted learning of only short native nonwords, and M capacity predicted learning of short nonwords but not long nonwords. The discussion considers three learning processes-effortful activation of phonological representations, lexical mediation, and passive associative learning-that use different cognitive resources and could be involved in learning different nonword types.

The Application of Cognitive Diagnostic Approaches via Neural Network Analysis of Serious Educational Games

NASA Astrophysics Data System (ADS)

Lamb, Richard L.

Serious Educational Games (SEGs) have been a topic of increased popularity within the educational realm since the early millennia. SEGs are generalized form of Serious Games to mean games for purposes other than entertainment but, that also specifically include training, educational purpose and pedagogy within their design. This rise in popularity (for SEGs) has occurred at a time when school systems have increased the type, number, and presentations of student achievement tests for decision-making purposes. These tests often task the form of end of course (year) tests and periodic benchmark testing. As the use of these tests, has increased policymakers have suggested their use as a measure for teacher accountability. The change in testing resulted from a push by school districts and policy makers at various component levels for a data-driven decision-making (D3M) approach. With the data-driven decision making approaches by school districts, there has been an increased focus on the measurement and assessment of student content knowledge with little focus on the contributing factors and cognitive attributes within learning that cross multiple-content areas. One-way to increase the focus on these aspects of learning (factors and attributes) that are additional to content learning is through assessments based in cognitive diagnostics. Cognitive diagnostics are a family of methodological approaches in which tasks tie to specific cognitive attributes for analytical purposes. This study explores data derived from computer data logging (n=158,000) in an observational design, using traditional statistical techniques such as clustering (exploratory and confirmatory), item response theory and through data mining techniques such as artificial neural network analysis. From these analyses, a model of student learning emerges illustrating student thinking and learning while engaged in SEG Design. This study seeks to use cognitive diagnostic type approaches to measure student learning while designing science task based SEGs. In addition, the study suggests that it may be possible to use SEGs to provide a means to administer cognitive diagnostic based assessments in real time. Results of this study suggest the confirmation of four families (factors) of traits illustrating a simple factor loading structure. Item response theory (IRT) results illustrate a 2-parameter logistic model (2PLM) fit allowing for parameterization using the IRT-True Score Method (chi2=1.70, df=1, p=0.19). Finally, fit statistics for the artificial neural network suggest the developed model adequately fits the current data set and provides a means to explore cognitive attributes and their effect on task outcomes. This study has developed a justification for combining and developing two distinct areas of research related to student learning. The first is the use of cognitive diagnostic approaches to assess student learning as it relates to the cognitive attributes used during science processing. The second area is an examination and modeling of the relationship between attributes as propagated in an artificial neural network. Results of the study provide for an ANN model of student cognition while designing science based SEGs (r 2=0.73, RMSE= 0.21) at a convergence of 1000 training iterations. The literature presented in this dissertation work integrates work from multiple field areas. Fields represented in this work range from science education, educational psychology, measurement, and computational psychology.

Effectiveness of motor sequential learning according to practice schedules in healthy adults; distributed practice versus massed practice

PubMed Central

Kwon, Yong Hyun; Kwon, Jung Won; Lee, Myoung Hee

2015-01-01

[Purpose] The purpose of the current study was to compare the effectiveness of motor sequential learning according to two different types of practice schedules, distributed practice schedule (two 12-hour inter-trial intervals) and massed practice schedule (two 10-minute inter-trial intervals) using a serial reaction time (SRT) task. [Subjects and Methods] Thirty healthy subjects were recruited and then randomly and evenly assigned to either the distributed practice group or the massed practice group. All subjects performed three consecutive sessions of the SRT task following one of the two different types of practice schedules. Distributed practice was scheduled for two 12-hour inter-session intervals including sleeping time, whereas massed practice was administered for two 10-minute inter-session intervals. Response time (RT) and response accuracy (RA) were measured in at pre-test, mid-test, and post-test. [Results] For RT, univariate analysis demonstrated significant main effects in the within-group comparison of the three tests as well as the interaction effect of two groups × three tests, whereas the between-group comparison showed no significant effect. The results for RA showed no significant differences in neither the between-group comparison nor the interaction effect of two groups × three tests, whereas the within-group comparison of the three tests showed a significant main effect. [Conclusion] Distributed practice led to enhancement of motor skill acquisition at the first inter-session interval as well as at the second inter-interval the following day, compared to massed practice. Consequentially, the results of this study suggest that a distributed practice schedule can enhance the effectiveness of motor sequential learning in 1-day learning as well as for two days learning formats compared to massed practice. PMID:25931727

Individual differences in personality in laying hens are related to learning a colour cue association.

PubMed

de Haas, Elske N; Lee, Caroline; Hernandez, Carlos E; Naguib, Marc; Rodenburg, T Bas

2017-01-01

Personality can influence how animals perceive and learn cues. The behaviour and physiological responses animals show during stressful events is indicative of their personality. Acute induced stress prior to a cognitive test are known to affect the judgement of a stimulus, but personality of an individual could also affect learning of a specific cognitive paradigm. Here, we assessed if adult laying hens' behaviour and physiological responses, as indicators of their personality, were related to their cognitive performance. We assessed their behavioural responses to a tonic immobility test, an open field test, and a manual restraint test, and measured plasma corticosterone levels after manual restraint. After that, hens (n=20) were trained in a pre-set training schedule to associate a colour-cue with a reward. In a two-choice go-go test, hens needed to choose between a baited or non-baited food container displayed randomly on the left or right side of an arena. Success in learning was related to personality, with better performance of hens which showed a reactive personality type by a long latency to walk, struggle or vocalize during the tests. Only eight out of 20 hens reached the training criteria. The non-learners showed a strong side preference during all training days. Side preferences were strong in hens with high levels of plasma corticosterone and with a long duration of tonic immobility, indicating that fearful, stress-sensitive hens are more prone to develop side biases. Our results show that learning can be hindered by side biases, and fearful animals with a more proactive personality type are more sensitive to develop such biases. Copyright © 2016 Elsevier B.V. All rights reserved.

Neural Measures Reveal Implicit Learning during Language Processing.

PubMed

Batterink, Laura J; Cheng, Larry Y; Paller, Ken A

2016-10-01

Language input is highly variable; phonological, lexical, and syntactic features vary systematically across different speakers, geographic regions, and social contexts. Previous evidence shows that language users are sensitive to these contextual changes and that they can rapidly adapt to local regularities. For example, listeners quickly adjust to accented speech, facilitating comprehension. It has been proposed that this type of adaptation is a form of implicit learning. This study examined a similar type of adaptation, syntactic adaptation, to address two issues: (1) whether language comprehenders are sensitive to a subtle probabilistic contingency between an extraneous feature (font color) and syntactic structure and (2) whether this sensitivity should be attributed to implicit learning. Participants read a large set of sentences, 40% of which were garden-path sentences containing temporary syntactic ambiguities. Critically, but unbeknownst to participants, font color probabilistically predicted the presence of a garden-path structure, with 75% of garden-path sentences (and 25% of normative sentences) appearing in a given font color. ERPs were recorded during sentence processing. Almost all participants indicated no conscious awareness of the relationship between font color and sentence structure. Nonetheless, after sufficient time to learn this relationship, ERPs time-locked to the point of syntactic ambiguity resolution in garden-path sentences differed significantly as a function of font color. End-of-sentence grammaticality judgments were also influenced by font color, suggesting that a match between font color and sentence structure increased processing fluency. Overall, these findings indicate that participants can implicitly detect subtle co-occurrences between physical features of sentences and abstract, syntactic properties, supporting the notion that implicit learning mechanisms are generally operative during online language processing.

Learning a novel phonological contrast depends on interactions between individual differences and training paradigm design.

PubMed

Perrachione, Tyler K; Lee, Jiyeon; Ha, Louisa Y Y; Wong, Patrick C M

2011-07-01

Studies evaluating phonological contrast learning typically investigate either the predictiveness of specific pretraining aptitude measures or the efficacy of different instructional paradigms. However, little research considers how these factors interact--whether different students learn better from different types of instruction--and what the psychological basis for any interaction might be. The present study demonstrates that successfully learning a foreign-language phonological contrast for pitch depends on an interaction between individual differences in perceptual abilities and the design of the training paradigm. Training from stimuli with high acoustic-phonetic variability is generally thought to improve learning; however, we found high-variability training enhanced learning only for individuals with strong perceptual abilities. Learners with weaker perceptual abilities were actually impaired by high-variability training relative to a low-variability condition. A second experiment assessing variations on the high-variability training design determined that the property of this learning environment most detrimental to perceptually weak learners is the amount of trial-by-trial variability. Learners' perceptual limitations can thus override the benefits of high-variability training where trial-by-trial variability in other irrelevant acoustic-phonetic features obfuscates access to the target feature. These results demonstrate the importance of considering individual differences in pretraining aptitudes when evaluating the efficacy of any speech training paradigm. © 2011 Acoustical Society of America

Touchscreen assays of learning, response inhibition, and motivation in the marmoset (Callithrix jacchus).

PubMed

Kangas, Brian D; Bergman, Jack; Coyle, Joseph T

2016-05-01

Recent developments in precision gene editing have led to the emergence of the marmoset as an experimental subject of considerable interest and translational value. A better understanding of behavioral phenotypes of the common marmoset will inform the extent to which forthcoming transgenic mutants are cognitively intact. Therefore, additional information regarding their learning, inhibitory control, and motivational abilities is needed. The present studies used touchscreen-based repeated acquisition and discrimination reversal tasks to examine basic dimensions of learning and response inhibition. Marmosets were trained daily to respond to one of the two simultaneously presented novel stimuli. Subjects learned to discriminate the two stimuli (acquisition) and, subsequently, with the contingencies switched (reversal). In addition, progressive ratio performance was used to measure the effort expended to obtain a highly palatable reinforcer varying in magnitude and, thereby, provide an index of relative motivational value. Results indicate that rates of both acquisition and reversal of novel discriminations increased across successive sessions, but that rate of reversal learning remained slower than acquisition learning, i.e., more trials were needed for mastery. A positive correlation was observed between progressive ratio break point and reinforcement magnitude. These results closely replicate previous findings with squirrel monkeys, thus providing evidence of similarity in learning processes across nonhuman primate species. Moreover, these data provide key information about the normative phenotype of wild-type marmosets using three relevant behavioral endpoints.

Effects of competitive learning tools on medical students: A case study

PubMed Central

2018-01-01

Objective Competitive learning techniques are being successfully used in courses of different disciplines. However, there is still a significant gap in analyzing their effects in medical students competing individually. The authors conducted this study to assess the effectiveness of the use of a competitive learning tool on the academic achievement and satisfaction of medical students. Methods The authors collected data from a Human Immunology course in medical students (n = 285) and conducted a nonrandomized (quasi-experimental) control group pretest-posttest design. They used the Mann-Whitney U-test to measure the strength of the association between two variables and to compare the two student groups. Results The improvement and academic outcomes of the experimental group students were significantly higher than those of the control group students. The students using the competitive learning tool had better academic performance, and they were satisfied with this type of learning. The study, however, had some limitations. The authors did not make a random assignment to the control and experimental groups and the groups were not completely homogenous. Conclusion The use of competitive learning techniques motivates medical students, improves their academic outcomes and may foster the cooperation among students and provide a pleasant classroom environment. The authors are planning further studies with a more complete evaluation of cognitive learning styles or incorporating chronometry as well as team-competition. PMID:29518123

Learn it now, sing it later? Field and laboratory studies on song repertoire acquisition and song use in nightingales.

PubMed

Kiefer, S; Scharff, C; Hultsch, H; Kipper, S

2014-11-01

In many bird species, song changes with age. The mechanisms that account for such changes are only partially understood. Common nightingales Luscinia megarhynchos change the size and composition of their repertoire between their first and second breeding season. To inquire into mechanisms involved in such changes, we compared the singing of 1-year-old and older free-living nightingales. Older males have more song types in common than have 1-year olds. Certain song types frequently sung by older birds did not (or only rarely) occur in the repertoire of yearlings ('mature' song types). We conducted learning experiments with hand-reared nightingales to address reasons for the lack of mature song types. The acquisition success of mature songs was as good as that of control songs (commonly sung by both age groups). However, the analysis of song type use revealed that all yearlings sang common song types more often than mature types. This indicates that the absence of certain song types in the repertoires of free-living yearlings cannot be accounted for by learning and/or motor constraints during song learning. Moreover, our results suggest that in communication networks, animals may restrict the actual use of their signal repertoire to a certain subset depending on the context.

Comparing brain activity patterns during spontaneous exploratory and cue-instructed learning using single photon-emission computed tomography (SPECT) imaging of regional cerebral blood flow in freely behaving rats.

PubMed

Mannewitz, A; Bock, J; Kreitz, S; Hess, A; Goldschmidt, J; Scheich, H; Braun, Katharina

2018-05-01

Learning can be categorized into cue-instructed and spontaneous learning types; however, so far, there is no detailed comparative analysis of specific brain pathways involved in these learning types. The aim of this study was to compare brain activity patterns during these learning tasks using the in vivo imaging technique of single photon-emission computed tomography (SPECT) of regional cerebral blood flow (rCBF). During spontaneous exploratory learning, higher levels of rCBF compared to cue-instructed learning were observed in motor control regions, including specific subregions of the motor cortex and the striatum, as well as in regions of sensory pathways including olfactory, somatosensory, and visual modalities. In addition, elevated activity was found in limbic areas, including specific subregions of the hippocampal formation, the amygdala, and the insula. The main difference between the two learning paradigms analyzed in this study was the higher rCBF observed in prefrontal cortical regions during cue-instructed learning when compared to spontaneous learning. Higher rCBF during cue-instructed learning was also observed in the anterior insular cortex and in limbic areas, including the ectorhinal and entorhinal cortexes, subregions of the hippocampus, subnuclei of the amygdala, and the septum. Many of the rCBF changes showed hemispheric lateralization. Taken together, our study is the first to compare partly lateralized brain activity patterns during two different types of learning.

The State of Wiki Usage in U.S. K-12 Schools: Leveraging Web 2.0 Data Warehouses to Assess Quality and Equity in Online Learning Environments

ERIC Educational Resources Information Center

Reich, Justin; Murnane, Richard; Willett, John

2012-01-01

To document wiki usage in U.S. K-12 settings, this study examined a representative sample drawn from a population of nearly 180,000 wikis. The authors measured the opportunities wikis provide for students to develop 21st-century skills such as expert thinking, complex communication, and new media literacy. The authors found four types of wiki…

Habitat Restoration on Mobile Bay

NASA Astrophysics Data System (ADS)

Murphy, B.

2017-12-01

Alabama has some of the most biodiversity found anywhere in our nation, however we are rapidly losing many of these species to habitat loss. Our marine science class realized our shoreline on our campus on Mobile Bay was disappearing and wanted to help. We collaborated with local scientists from Dauphin Island Sea Lab under the direction of Dr. Just Cebrian and our instructor, Dr. Megan McCall, to create a project to help restore the habitat. We had to first collect beach profile surveys and learn how to measure elevations. Next we installed plants that we measured and collected growth data. Our project went through a series of prototypes and corrective measures based on the type of wave energy we discovered on our shores. Finally we landed on a type of wave attenuator of crab traps filled with rock and staked into the sand. This coming year we will begin collecting data on any changes to the beach profile as well as fish counts to evaluate the effectiveness of our installation.

Estimates of the atmospheric parameters of M-type stars: a machine-learning perspective

NASA Astrophysics Data System (ADS)

Sarro, L. M.; Ordieres-Meré, J.; Bello-García, A.; González-Marcos, A.; Solano, E.

2018-05-01

Estimating the atmospheric parameters of M-type stars has been a difficult task due to the lack of simple diagnostics in the stellar spectra. We aim at uncovering good sets of predictive features of stellar atmospheric parameters (Teff, log (g), [M/H]) in spectra of M-type stars. We define two types of potential features (equivalent widths and integrated flux ratios) able to explain the atmospheric physical parameters. We search the space of feature sets using a genetic algorithm that evaluates solutions by their prediction performance in the framework of the BT-Settl library of stellar spectra. Thereafter, we construct eight regression models using different machine-learning techniques and compare their performances with those obtained using the classical χ2 approach and independent component analysis (ICA) coefficients. Finally, we validate the various alternatives using two sets of real spectra from the NASA Infrared Telescope Facility (IRTF) and Dwarf Archives collections. We find that the cross-validation errors are poor measures of the performance of regression models in the context of physical parameter prediction in M-type stars. For R ˜ 2000 spectra with signal-to-noise ratios typical of the IRTF and Dwarf Archives, feature selection with genetic algorithms or alternative techniques produces only marginal advantages with respect to representation spaces that are unconstrained in wavelength (full spectrum or ICA). We make available the atmospheric parameters for the two collections of observed spectra as online material.

Contextualised Media for Learning

ERIC Educational Resources Information Center

de Jong, Tim; Specht, Marcus; Koper, Rob

2008-01-01

In this paper, we analyse how contextualised media can be used to support learning. Additionally, the advantages of contextualised learning and the types of learning that are fit to be supported are discussed. Our focus throughout the paper will be on lifelong learning, and the integration of formal and informal learning therein. However, we…

Learning Organisations--Reengineering Schools for Life Long Learning.

ERIC Educational Resources Information Center

O'Sullivan, Fergus

1997-01-01

Examines some key ideas behind the learning organization and explains why the concept is so powerful in contemporary contexts. Identifies various types of learning organizations, and suggests an analytical technique for relating styles of organizational learning to the environmental context. The key to becoming a learning organization is…

Classification of AB O 3 perovskite solids: a machine learning study

DOE PAGES

Pilania, G.; Balachandran, P. V.; Gubernatis, J. E.; ...

2015-07-23

Here we explored the use of machine learning methods for classifying whether a particularABO 3chemistry forms a perovskite or non-perovskite structured solid. Starting with three sets of feature pairs (the tolerance and octahedral factors, theAandBionic radii relative to the radius of O, and the bond valence distances between theAandBions from the O atoms), we used machine learning to create a hyper-dimensional partial dependency structure plot using all three feature pairs or any two of them. Doing so increased the accuracy of our predictions by 2–3 percentage points over using any one pair. We also included the Mendeleev numbers of theAandBatomsmore » to this set of feature pairs. Moreover, doing this and using the capabilities of our machine learning algorithm, the gradient tree boosting classifier, enabled us to generate a new type of structure plot that has the simplicity of one based on using just the Mendeleev numbers, but with the added advantages of having a higher accuracy and providing a measure of likelihood of the predicted structure.« less

Two Anatomically and Computationally Distinct Learning Signals Predict Changes to Stimulus-Outcome Associations in Hippocampus.

PubMed

Boorman, Erie D; Rajendran, Vani G; O'Reilly, Jill X; Behrens, Tim E

2016-03-16

Complex cognitive processes require sophisticated local processing but also interactions between distant brain regions. It is therefore critical to be able to study distant interactions between local computations and the neural representations they act on. Here we report two anatomically and computationally distinct learning signals in lateral orbitofrontal cortex (lOFC) and the dopaminergic ventral midbrain (VM) that predict trial-by-trial changes to a basic internal model in hippocampus. To measure local computations during learning and their interaction with neural representations, we coupled computational fMRI with trial-by-trial fMRI suppression. We find that suppression in a medial temporal lobe network changes trial-by-trial in proportion to stimulus-outcome associations. During interleaved choice trials, we identify learning signals that relate to outcome type in lOFC and to reward value in VM. These intervening choice feedback signals predicted the subsequent change to hippocampal suppression, suggesting a convergence of signals that update the flexible representation of stimulus-outcome associations. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Multisource Data Classification Using A Hybrid Semi-supervised Learning Scheme

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vatsavai, Raju; Bhaduri, Budhendra L; Shekhar, Shashi

2009-01-01

In many practical situations thematic classes can not be discriminated by spectral measurements alone. Often one needs additional features such as population density, road density, wetlands, elevation, soil types, etc. which are discrete attributes. On the other hand remote sensing image features are continuous attributes. Finding a suitable statistical model and estimation of parameters is a challenging task in multisource (e.g., discrete and continuous attributes) data classification. In this paper we present a semi-supervised learning method by assuming that the samples were generated by a mixture model, where each component could be either a continuous or discrete distribution. Overall classificationmore » accuracy of the proposed method is improved by 12% in our initial experiments.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Racah, Evan; Ko, Seyoon; Sadowski, Peter

Experiments in particle physics produce enormous quantities of data that must be analyzed and interpreted by teams of physicists. This analysis is often exploratory, where scientists are unable to enumerate the possible types of signal prior to performing the experiment. Thus, tools for summarizing, clustering, visualizing and classifying high-dimensional data are essential. Here in this work, we show that meaningful physical content can be revealed by transforming the raw data into a learned high-level representation using deep neural networks, with measurements taken at the Daya Bay Neutrino Experiment as a case study. We further show how convolutional deep neural networksmore » can provide an effective classification filter with greater than 97% accuracy across different classes of physics events, significantly better than other machine learning approaches.« less

Measuring Cognitive Load in Embodied Learning Settings

PubMed Central

Skulmowski, Alexander; Rey, Günter Daniel

2017-01-01

In recent years, research on embodied cognition has inspired a number of studies on multimedia learning and instructional psychology. However, in contrast to traditional research on education and multimedia learning, studies on embodied learning (i.e., focusing on bodily action and perception in the context of education) in some cases pose new problems for the measurement of cognitive load. This review provides an overview over recent studies on embodied learning in which cognitive load was measured using surveys, behavioral data, or physiological measures. The different methods are assessed in terms of their success in finding differences of cognitive load in embodied learning scenarios. At the same time, we highlight the most important challenges for researchers aiming to include these measures into their study designs. The main issues we identified are: (1) Subjective measures must be appropriately phrased to be useful for embodied learning; (2) recent findings indicate potentials as well as problematic aspects of dual-task measures; (3) the use of physiological measures offers great potential, but may require mobile equipment in the context of embodied scenarios; (4) meta-cognitive measures can be useful extensions of cognitive load measurement for embodied learning. PMID:28824473

Comparing Curriculum Types: 'Powerful Knowledge' and '21st Century Learning'

ERIC Educational Resources Information Center

McPhail, Graham; Rata, Elizabeth

2016-01-01

This paper theorises a curriculum model containing four features. We use these features as criteria to analyse and evaluate two distinctive curriculum design types: '21st Century Learning' and 'Powerful Knowledge'. The four features are: (i) the underpinning theory of knowledge in each curriculum design type; (ii) the knowledge structures used to…

Using Different Types of Dictionaries for Improving EFL Reading Comprehension and Vocabulary Learning

ERIC Educational Resources Information Center

Alharbi, Majed A.

2016-01-01

This study investigated the effects of monolingual book dictionaries, popup dictionaries, and type-in dictionaries on improving reading comprehension and vocabulary learning in an EFL program. An experimental design involving four groups and a post-test was chosen for the experiment: (1) pop-up dictionary (experimental group 1); (2) type-in…

Measuring students' self-regulated learning in professional education: bridging the gap between event and aptitude measurements.

PubMed

Endedijk, Maaike D; Brekelmans, Mieke; Sleegers, Peter; Vermunt, Jan D

Self-regulated learning has benefits for students' academic performance in school, but also for expertise development during their professional career. This study examined the validity of an instrument to measure student teachers' regulation of their learning to teach across multiple and different kinds of learning events in the context of a postgraduate professional teacher education programme. Based on an analysis of the literature, we developed a log with structured questions that could be used as a multiple-event instrument to determine the quality of student teachers' regulation of learning by combining data from multiple learning experiences. The findings showed that this structured version of the instrument measured student teachers' regulation of their learning in a valid and reliable way. Furthermore, with the aid of the Structured Learning Report individual differences in student teachers' regulation of learning could be discerned. Together the findings indicate that a multiple-event instrument can be used to measure regulation of learning in multiple contexts for various learning experiences at the same time, without the necessity of relying on students' ability to rate themselves across all these different experiences. In this way, this instrument can make an important contribution to bridging the gap between two dominant approaches to measure SRL, the traditional aptitude and event measurement approach.

Effects of WOE Presentation Types Used in Pre-Training on the Cognitive Load and Comprehension of Content in Animation-Based Learning Environments

ERIC Educational Resources Information Center

Jung, Jung,; Kim, Dongsik; Na, Chungsoo

2016-01-01

This study investigated the effectiveness of various types of worked-out examples used in pre-training to optimize the cognitive load and enhance learners' comprehension of the content in an animation-based learning environment. An animation-based learning environment was developed specifically for this study. The participants were divided into…

Linking Science Fiction and Physics Courses

ERIC Educational Resources Information Center

McBride, Krista K.

2016-01-01

Generally, cohorts or learning communities enrich higher learning in students. Learning communities consist of conventionally separate groups of students that meet together with common academic purposes and goals. Types of learning communities include paired courses with concurrent student enrollment, living-learning communities, and faculty…

Integrating different data types by regularized unsupervised multiple kernel learning with application to cancer subtype discovery.

PubMed

Speicher, Nora K; Pfeifer, Nico

2015-06-15

Despite ongoing cancer research, available therapies are still limited in quantity and effectiveness, and making treatment decisions for individual patients remains a hard problem. Established subtypes, which help guide these decisions, are mainly based on individual data types. However, the analysis of multidimensional patient data involving the measurements of various molecular features could reveal intrinsic characteristics of the tumor. Large-scale projects accumulate this kind of data for various cancer types, but we still lack the computational methods to reliably integrate this information in a meaningful manner. Therefore, we apply and extend current multiple kernel learning for dimensionality reduction approaches. On the one hand, we add a regularization term to avoid overfitting during the optimization procedure, and on the other hand, we show that one can even use several kernels per data type and thereby alleviate the user from having to choose the best kernel functions and kernel parameters for each data type beforehand. We have identified biologically meaningful subgroups for five different cancer types. Survival analysis has revealed significant differences between the survival times of the identified subtypes, with P values comparable or even better than state-of-the-art methods. Moreover, our resulting subtypes reflect combined patterns from the different data sources, and we demonstrate that input kernel matrices with only little information have less impact on the integrated kernel matrix. Our subtypes show different responses to specific therapies, which could eventually assist in treatment decision making. An executable is available upon request. © The Author 2015. Published by Oxford University Press.

Best practices for measuring students' attitudes toward learning science.

PubMed

Lovelace, Matthew; Brickman, Peggy

2013-01-01

Science educators often characterize the degree to which tests measure different facets of college students' learning, such as knowing, applying, and problem solving. A casual survey of scholarship of teaching and learning research studies reveals that many educators also measure how students' attitudes influence their learning. Students' science attitudes refer to their positive or negative feelings and predispositions to learn science. Science educators use attitude measures, in conjunction with learning measures, to inform the conclusions they draw about the efficacy of their instructional interventions. The measurement of students' attitudes poses similar but distinct challenges as compared with measurement of learning, such as determining validity and reliability of instruments and selecting appropriate methods for conducting statistical analyses. In this review, we will describe techniques commonly used to quantify students' attitudes toward science. We will also discuss best practices for the analysis and interpretation of attitude data.

Best Practices for Measuring Students’ Attitudes toward Learning Science

PubMed Central

Lovelace, Matthew; Brickman, Peggy

2013-01-01

Science educators often characterize the degree to which tests measure different facets of college students’ learning, such as knowing, applying, and problem solving. A casual survey of scholarship of teaching and learning research studies reveals that many educators also measure how students’ attitudes influence their learning. Students’ science attitudes refer to their positive or negative feelings and predispositions to learn science. Science educators use attitude measures, in conjunction with learning measures, to inform the conclusions they draw about the efficacy of their instructional interventions. The measurement of students’ attitudes poses similar but distinct challenges as compared with measurement of learning, such as determining validity and reliability of instruments and selecting appropriate methods for conducting statistical analyses. In this review, we will describe techniques commonly used to quantify students’ attitudes toward science. We will also discuss best practices for the analysis and interpretation of attitude data. PMID:24297288

Measurement Learning Trajectories: A Tool for Professional Development

ERIC Educational Resources Information Center

McCool, Jenni K.

2009-01-01

This study investigated the ways in which a teacher developed conceptions of measurement teaching and learning as she collaborated with a researcher to learn and implement a measurement learning trajectory with two of her students. Teachers need tools that effectively address the content area of measurement and can be used to improve their…

Investigating Agricultural Instructors' Attitudes toward E-Learning in Iran

ERIC Educational Resources Information Center

Mohammadi, Davoud; Hosseini, Seyed Mahmoud; Fami, Hossein Shabanali

2011-01-01

With the rapid changes in all types of learning and teaching environments, there is a need to implement electronic learning (e-learning) to train students with new technologies. However the trend of using e-learning as learning and/or teaching tool is now rapidly expanding into education. Although e-learning environments are popular, there is…

Learning during Processing: Word Learning Doesn't Wait for Word Recognition to Finish

ERIC Educational Resources Information Center

Apfelbaum, Keith S.; McMurray, Bob

2017-01-01

Previous research on associative learning has uncovered detailed aspects of the process, including what types of things are learned, how they are learned, and where in the brain such learning occurs. However, perceptual processes, such as stimulus recognition and identification, take time to unfold. Previous studies of learning have not addressed…

Discriminative structural approaches for enzyme active-site prediction.

PubMed

Kato, Tsuyoshi; Nagano, Nozomi

2011-02-15

Predicting enzyme active-sites in proteins is an important issue not only for protein sciences but also for a variety of practical applications such as drug design. Because enzyme reaction mechanisms are based on the local structures of enzyme active-sites, various template-based methods that compare local structures in proteins have been developed to date. In comparing such local sites, a simple measurement, RMSD, has been used so far. This paper introduces new machine learning algorithms that refine the similarity/deviation for comparison of local structures. The similarity/deviation is applied to two types of applications, single template analysis and multiple template analysis. In the single template analysis, a single template is used as a query to search proteins for active sites, whereas a protein structure is examined as a query to discover the possible active-sites using a set of templates in the multiple template analysis. This paper experimentally illustrates that the machine learning algorithms effectively improve the similarity/deviation measurements for both the analyses.

Training to Enhance Design Team Performance: A Cure for Tunnel Vision

NASA Technical Reports Server (NTRS)

Parker, James W.; Parker, Nelson C. (Technical Monitor)

2001-01-01

Design Team performance is a function of the quality and degree of academic training and the cumulative, learned experience of the individual members of the team. Teamwork, leadership, and communications certainly are factors that affect the measure of the performance of the team, but they are not addressed here. This paper focuses on accelerating the learned experience of team members and describes an organizational approach that can significantly increase the effective experience level for any engineering design team. The performance measure of the whole team can be increased by increasing the engineering disciplines' cross awareness of each other and by familiarizing them with their affect at the system level. Discipline engineers know their own discipline well, but typically are not intimately familiar with their technical interaction with and dependencies on all the other disciplines of engineering. These dependencies are design integration functions and are worked out well by the discipline engineers as long as they are involved in the design of types of systems that they have experience with.

"I Reassessed Who I Am"

ERIC Educational Resources Information Center

O'Meara, Casey

2017-01-01

This instrumental case study describes students' experiences in an academic cluster gateway course through social justice service-learning as civic learning pedagogy. The case under study recognized institutional factors supporting participatory off-campus community learning, and social justice service-learning as a type of civic learning pedagogy.

Fostering Effective Early Learning (FEEL) through a professional development programme for early childhood educators to improve professional practice and child outcomes in the year before formal schooling: study protocol for a cluster randomised controlled trial.

PubMed

Melhuish, Edward; Howard, Steven J; Siraj, Iram; Neilsen-Hewett, Cathrine; Kingston, Denise; de Rosnay, Marc; Duursma, Elisabeth; Luu, Betty

2016-12-19

A substantial research base documents the benefits of attendance at high-quality early childhood education and care (ECEC) for positive behavioural and learning outcomes. Research has also found that the quality of many young children's experiences and opportunities in ECEC depends on the skills, dispositions and understandings of the early childhood adult educators. Increasingly, research has shown that the quality of children's interactions with educators and their peers, more than any other programme feature, influence what children learn and how they feel about learning. Hence, we sought to investigate the extent to which evidence-based professional development (PD) - focussed on promoting sustained shared thinking through quality interactions - could improve the quality of ECEC and, as a consequence, child outcomes. The Fostering Effective Early Learning (FEEL) study is a cluster randomised controlled trial for evaluating the benefits of a professional development (PD) programme for early childhood educators, compared with no extra PD. Ninety long-day care and preschool centres in New South Wales, Australia, will be selected to ensure representation across National Quality Standards (NQS) ratings, location, centre type and socioeconomic areas. Participating centres will be randomly allocated to one of two groups, stratified by centre type and NQS rating: (1) an intervention group (45 centres) receiving a PD intervention or (2) a control group (45 centres) that continues engaging in typical classroom practice. Randomisation to these groups will occur after the collection of baseline environmental quality ratings. Primary outcomes, at the child level, will be two measures of language development: verbal comprehension and expressive vocabulary. Secondary outcomes at the child level will be measures of early numeracy, social development and self-regulation. Secondary outcomes at the ECEC room level will be measures of environmental quality derived from full-day observations. In all cases, data collectors will be blinded to group allocation. This is the first randomised controlled trial of a new approach to PD, which is focussed on activities previously found to be influential in children's early language, numeracy, social and self-regulatory development. Results should inform practitioners, policy-makers and families of the value of specific professional development for early childhood educators. Australian New Zealand Clinical Trials Registry (ACTRN) identifier ACTRN12616000536460 . Registered on 27 April 2016. This trial was retrospectively registered, given the first participant (centre) had been enrolled at the time of registration.

Measuring the Effect of an Online Learning Community on Engineering Cooperative Education Students' Perceived and Measured Learning

ERIC Educational Resources Information Center

Todd, Anita M.

2013-01-01

This quasi-experimental, static-group comparison study of two non-equivalent groups examined how Work-Integrated Learning (WIL) community participation of at-work, cooperative education students affected student perceived performance, perceived learning, and measured learning with student grade point average (GPA) and work term as covariates. The…

The Nature and Nurture of Military Genius: Developing Senior Strategic Leaders for the Postmodern Military

DTIC Science & Technology

2010-06-01

the ability to think and solve problems. Short of a theory regarding how people learn , a theory that describes how people think and solve problems...not what to think . In terms of learning theory, this type of instruction falls under Saltz’s second type of learning : learning for problem solving...Jeff Geraghty is a student at the School of Advanced Air and Space Studies. He has served in the Air Force as an F-15E pilot, staff officer, and an

Creation of learning kits

NASA Technical Reports Server (NTRS)

Stow, D. A.; Estes, J. E.; Mertz, F. C.

1981-01-01

A learning kit is an essential part of any remote sensing workshop, course, or in-house training program to provide the "hands-on" experience of working with remotely sensed imagery. This is the objective of laboratory and field exercises as well as the reason behind the production of imagery/map kits. The way in which these learning kits (containing conventional remotely sensed and collateral data products) are put together is described and some concerns that influence the creation of learning kits are discussed. These include budgetary constraints, number of imagery types, and number of collateral data types.

Drowning Digitally? How Disequilibrium Shapes Practice in a Blended Learning Charter School

ERIC Educational Resources Information Center

Bingham, Andrea J.

2016-01-01

Background/Context: Blended learning--a learning model in which online learning is combined with faceto- face instruction to provide a more personalized learning experience for students--has shown enormous growth in recent years. Though many policymakers and educators are optimistic about the potential of blended learning to provide the type of…

A Study of Multimedia Annotation of Web-Based Materials

ERIC Educational Resources Information Center

Hwang, Wu-Yuin; Wang, Chin-Yu; Sharples, Mike

2007-01-01

Web-based learning has become an important way to enhance learning and teaching, offering many learning opportunities. A limitation of current Web-based learning is the restricted ability of students to personalize and annotate the learning materials. Providing personalized tools and analyzing some types of learning behavior, such as students'…

Reversal of Long-Term Potentiation-Like Plasticity Processes after Motor Learning Disrupts Skill Retention

PubMed Central

Cantarero, Gabriela; Lloyd, Ashley

2013-01-01

Plasticity of synaptic connections in the primary motor cortex (M1) is thought to play an essential role in learning and memory. Human and animal studies have shown that motor learning results in long-term potentiation (LTP)-like plasticity processes, namely potentiation of M1 and a temporary occlusion of additional LTP-like plasticity. Moreover, biochemical processes essential for LTP are also crucial for certain types of motor learning and memory. Thus, it has been speculated that the occlusion of LTP-like plasticity after learning, indicative of how much LTP was used to learn, is essential for retention. Here we provide supporting evidence of it in humans. Induction of LTP-like plasticity can be abolished using a depotentiation protocol (DePo) consisting of brief continuous theta burst stimulation. We used transcranial magnetic stimulation to assess whether application of DePo over M1 after motor learning affected (1) occlusion of LTP-like plasticity and (2) retention of motor skill learning. We found that the magnitude of motor memory retention is proportional to the magnitude of occlusion of LTP-like plasticity. Moreover, DePo stimulation over M1, but not over a control site, reversed the occlusion of LTP-like plasticity induced by motor learning and disrupted skill retention relative to control subjects. Altogether, these results provide evidence of a link between occlusion of LTP-like plasticity and retention and that this measure could be used as a biomarker to predict retention. Importantly, attempts to reverse the occlusion of LTP-like plasticity after motor learning comes with the cost of reducing retention of motor learning. PMID:23904621

Developmental and individual differences in pure numerical estimation.

PubMed

Booth, Julie L; Siegler, Robert S

2006-01-01

The authors examined developmental and individual differences in pure numerical estimation, the type of estimation that depends solely on knowledge of numbers. Children between kindergarten and 4th grade were asked to solve 4 types of numerical estimation problems: computational, numerosity, measurement, and number line. In Experiment 1, kindergartners and 1st, 2nd, and 3rd graders were presented problems involving the numbers 0-100; in Experiment 2, 2nd and 4th graders were presented problems involving the numbers 0-1,000. Parallel developmental trends, involving increasing reliance on linear representations of numbers and decreasing reliance on logarithmic ones, emerged across different types of estimation. Consistent individual differences across tasks were also apparent, and all types of estimation skill were positively related to math achievement test scores. Implications for understanding of mathematics learning in general are discussed. Copyright 2006 APA, all rights reserved.

Potential communicative acts in children with autism spectrum disorders.

PubMed

Braddock, Barbara A; Pickett, Colleen; Ezzelgot, Jamie; Sheth, Shivani; Korte-Stroff, Emily; Loncke, Filip; Bock, Lynn

2015-01-01

To describe potential communicative acts in a sample of 17 children with autism spectrum disorders who produced few to no intelligible words (mean age = 32.82 months). Parents reported on children's potential communicative acts for 10 different communicative functions. A potential communicative act was defined as any behavior produced by an individual that may be interpreted by others to serve a communicative purpose. Significant associations were found between higher number of gesture types and increased scores on language comprehension, language expression, and non-verbal thinking measures. Relative to other types of potential communicative acts, parents reported that children used higher proportions of body movement. Number of body movement types was not related to child ability, while number of gesture types was related to receptive and expressive language. Findings underscore the link between language and gesture, and offer support for an ecological systems perspective of language learning.

Students' Strategies of Measuring Time Using Traditional "Gasing" Game in Third Grade of Primary School

ERIC Educational Resources Information Center

Jaelani, Anton; Putri, Ratu Ilma Indra; Hartono, Yusuf

2013-01-01

Understanding of measuring time has difficulty for children because it is intangible. Standard units often used directly by teacher for learning time measurement. Many researches involved games in designing learning material to facilitate fun and meaningful learning for children. For this reason, learning of time measurement that connects with…

ß-Adrenoceptor Activation Enhances L-Type Calcium Channel Currents in Anterior Piriform Cortex Pyramidal Cells of Neonatal Mice: Implication for Odor Learning

ERIC Educational Resources Information Center

Ghosh, Abhinaba; Mukherjee, Bandhan; Chen, Xihua; Yuan, Qi

2017-01-01

Early odor preference learning occurs in one-week-old rodents when a novel odor is paired with a tactile stimulation mimicking maternal care. ß-Adrenoceptors and L-type calcium channels (LTCCs) in the anterior piriform cortex (aPC) are critically involved in this learning. However, whether ß-adrenoceptors interact directly with LTCCs in aPC…

The write way to spell: printing vs. typing effects on orthographic learning

PubMed Central

Ouellette, Gene; Tims, Talisa

2014-01-01

Prior research has shown superior orthographic learning resulting from spelling practice relative to repeated reading. One mechanism proposed to underlie this advantage of spelling in establishing detailed orthographic representations in memory is the motoric component of the manual movements evoked in printing or writing. This study investigated this contention directly by testing the effects of typing vs. printing on the orthographic learning achieved through spelling practice, and further evaluated whether practice modality interacts with pre-existing individual characteristics. Forty students in grade 2 (mean age 7 years 5 months) were introduced to 10 novel non-words. Some of the students practiced spelling the items by printing, while the others practiced spelling them on a keyboard. Participants were tested for recognition and spelling of these items 1 and 7 days later. Results revealed high rates of orthographic learning with no main effects of practice modality, testing time, or post-test modality. Hierarchical regression analyses revealed an interaction between typing proficiency and practice modality, such that pre-existing keyboarding skills constrained or facilitated learning within the typing-practice group. A similar interaction was not found between printing skills and learning within the printing group. Results are discussed with reference to both prominent reading theory and educational applications. PMID:24592247

Type and Use of Innovative Learning Environments in Australasian Schools. ILETC Survey 1

ERIC Educational Resources Information Center

Imms, Wesley; Mahat, Marian; Byers, Terry; Murphy, Dan

2017-01-01

This report provides results of a survey disseminated to over 6000 school principals in Australia and New Zealand (NZ). Participants were invited to provide their perceptions of (1) the types of learning spaces in their schools; (2) the types of teaching approaches observed in those spaces; (3) the degree to which teachers in those spaces utilised…

Considering Personality Type in Adult Learning: Using the Myers-Briggs Type Indicator in Instructor Preparation at PricewaterhouseCoopers

ERIC Educational Resources Information Center

Daisley, Richard J.

2011-01-01

This article explores the feasibility of using the Myers-Briggs Type Indicator (MBTI) as a framework for instructor development in a professional services training environment. It explores the consistency of MBTI with common adult learning theory, addresses questions on MBTI's reliability and validity, and explores the applicability of MBTI to the…

Towards Understanding How to Leverage Sense-Making, Induction and Refinement, and Fluency to Improve Robust Learning

ERIC Educational Resources Information Center

Doroudi, Shayan; Holstein, Kenneth; Aleven, Vincent; Brunskill, Emma

2015-01-01

The field of EDM has focused more on modeling student knowledge than on investigating what sequences of different activity types achieve good learning outcomes. In this paper we consider three activity types, targeting sense-making, induction and refinement, and fluency building. We investigate what mix of the three types might be most effective…

Drosophila Courtship Conditioning As a Measure of Learning and Memory.

PubMed

Koemans, Tom S; Oppitz, Cornelia; Donders, Rogier A T; van Bokhoven, Hans; Schenck, Annette; Keleman, Krystyna; Kramer, Jamie M

2017-06-05

Many insights into the molecular mechanisms underlying learning and memory have been elucidated through the use of simple behavioral assays in model organisms such as the fruit fly, Drosophila melanogaster. Drosophila is useful for understanding the basic neurobiology underlying cognitive deficits resulting from mutations in genes associated with human cognitive disorders, such as intellectual disability (ID) and autism. This work describes a methodology for testing learning and memory using a classic paradigm in Drosophila known as courtship conditioning. Male flies court females using a distinct pattern of easily recognizable behaviors. Premated females are not receptive to mating and will reject the male's copulation attempts. In response to this rejection, male flies reduce their courtship behavior. This learned reduction in courtship behavior is measured over time, serving as an indicator of learning and memory. The basic numerical output of this assay is the courtship index (CI), which is defined as the percentage of time that a male spends courting during a 10 min interval. The learning index (LI) is the relative reduction of CI in flies that have been exposed to a premated female compared to naïve flies with no previous social encounters. For the statistical comparison of LIs between genotypes, a randomization test with bootstrapping is used. To illustrate how the assay can be used to address the role of a gene relating to learning and memory, the pan-neuronal knockdown of Dihydroxyacetone phosphate acyltransferase (Dhap-at) was characterized here. The human ortholog of Dhap-at, glyceronephosphate O-acyltransferase (GNPT), is involved in rhizomelic chondrodysplasia punctata type 2, an autosomal-recessive syndrome characterized by severe ID. Using the courtship conditioning assay, it was determined that Dhap-at is required for long-term memory, but not for short-term memory. This result serves as a basis for further investigation of the underlying molecular mechanisms.

Modeling Novelty Habituation During Exploratory Activity in Drosophila

PubMed Central

Soibam, Benjamin; Shah, Shishir; Gunaratne, Gemunu H.; Roman, Gregg W.

2013-01-01

Habituation is a common form of non-associative learning in which the organism gradually decreases its response to repeated stimuli. The decrease in exploratory activity of many animal species during exposure to a novel open field arena is a widely studied habituation paradigm. However, a theoretical framework to quantify how the novelty of the arena is learned during habituation is currently missing. Drosophila melanogaster display a high mean absolute activity and a high probability for directional persistence when first introduced to a novel arena. Both measures decrease during habituation to the arena. Here, we propose a phenomenological model of habituation for Drosophila exploration based on two principles: Drosophila form a spatial representation of the arena edge as a set of connected local patches, and repeated exposure to these patches is essential for the habituation of the novelty. The level of exposure depends on the number of visitations and is quantified by a variable referred to as “coverage.” This model was tested by comparing predictions against the experimentally measured behavior of wild type Drosophila. The novelty habituation of wild type Canton-S depends on coverage and is specifically independent of the arena radius. Our model describes the time dependent locomotor activity, ΔD, of Canton-S using an experimentally established stochastic process Pn(ΔD) which depends on the coverage. The quantitative measures of exploration and habituation were further applied to three mutant genotypes. Consistent with a requirement for vision in novelty habituation, blind no receptor potential A7 mutants display a failure in the decay of probability for directional persistence and mean absolute activity. The rutabaga2080 habituation mutant also shows defects in these measures. The kurtz1 non-visual arrestin mutant demonstrates a rapid decay in these measures, implying reduced motivation. The model and the habituation measures offer a powerful framework for understanding mechanisms associated with open field habituation. PMID:23597866

Empowering Adaptive Lectures through Activation of Intelligent and Web 2.0 Technologies

ERIC Educational Resources Information Center

El-Ghareeb, Haitham; Riad, A.

2011-01-01

Different Learning Paradigms can be presented by different educators as a result of utilizing several types of Information and Communication Technologies in the Learning Process. The three abstract Learning Delivery Models are: "Traditional", "Distance", and "Hybrid Learning". Hybrid Learning attempts to maintain the…

Measuring learning potential in people with schizophrenia: A comparison of two tasks.

PubMed

Rempfer, Melisa V; McDowd, Joan M; Brown, Catana E

2017-12-01

Learning potential measures utilize dynamic assessment methods to capture performance changes following training on a cognitive task. Learning potential has been explored in schizophrenia research as a predictor of functional outcome and there have been calls for psychometric development in this area. Because the majority of learning potential studies have utilized the Wisconsin Card Sorting Test (WCST), we extended this work using a novel measure, the Rey Osterrieth Complex Figure Test (ROCFT). This study had the following aims: 1) to examine relationships among different learning potential indices for two dynamic assessment tasks, 2) to examine the association between WCST and ROCFT learning potential measures, and 3) to address concurrent validity with a performance-based measure of functioning (Test of Grocery Shopping Skills; TOGSS). Eighty-one adults with schizophrenia or schizoaffective disorder completed WCST and ROCFT learning measures and the TOGSS. Results indicated the various learning potential computational indices are intercorrelated and, similar to other studies, we found support for regression residuals and post-test scores as optimal indices. Further, we found modest relationships between the two learning potential measures and the TOGSS. These findings suggest learning potential includes both general and task-specific constructs but future research is needed to further explore this question. Copyright © 2017 Elsevier B.V. All rights reserved.

The external-internal loop of interference: two types of attention and their influence on the learning abilities of mice.

PubMed

Sauce, Bruno; Wass, Christopher; Smith, Andrew; Kwan, Stephanie; Matzel, Louis D

2014-12-01

Attention is a component of the working memory system, and is responsible for protecting task-relevant information from interference. Cognitive performance (particularly outside of the laboratory) is often plagued by interference, and the source of this interference, either external or internal, might influence the expression of individual differences in attentional ability. By definition, external attention (also described as "selective attention") protects working memory against sensorial distractors of all kinds, while internal attention (also called "inhibition") protects working memory against emotional impulses, irrelevant information from memory, and automatically-generated responses. At present, it is unclear if these two types of attention are expressed independently in non-human animals, and how they might differentially impact performance on other cognitive processes, such as learning. By using a diverse battery of four attention tests (with varying levels of internal and external sources of interference), here we aimed both to explore this issue, and to obtain a robust and general (less task-specific) measure of attention in mice. Exploratory factor analyses revealed two factors (external and internal attention) that in total, accounted for 73% of the variance in attentional performance. Confirmatory factor analyses found an excellent fit with the data of the model of attention that assumed an external and internal distinction (with a resulting correlation of 0.43). In contrast, a model of attention that assumed one source of variance (i.e., "general attention") exhibited a poor fit with the data. Regarding the relationship between attention and learning, higher resistance against external sources of interference promoted better new learning, but tended to impair performance when cognitive flexibility was required, such as during the reversal of a previously instantiated response. The present results suggest that there can be (at least) two types of attention that contribute to the common variance in attentional performance in mice, and that external and internal attentions might have opposing influences on the rate at which animals learn. Copyright © 2014 Elsevier Inc. All rights reserved.

Reinforcement learning signals in the human striatum distinguish learners from nonlearners during reward-based decision making.

PubMed

Schönberg, Tom; Daw, Nathaniel D; Joel, Daphna; O'Doherty, John P

2007-11-21

The computational framework of reinforcement learning has been used to forward our understanding of the neural mechanisms underlying reward learning and decision-making behavior. It is known that humans vary widely in their performance in decision-making tasks. Here, we used a simple four-armed bandit task in which subjects are almost evenly split into two groups on the basis of their performance: those who do learn to favor choice of the optimal action and those who do not. Using models of reinforcement learning we sought to determine the neural basis of these intrinsic differences in performance by scanning both groups with functional magnetic resonance imaging. We scanned 29 subjects while they performed the reward-based decision-making task. Our results suggest that these two groups differ markedly in the degree to which reinforcement learning signals in the striatum are engaged during task performance. While the learners showed robust prediction error signals in both the ventral and dorsal striatum during learning, the nonlearner group showed a marked absence of such signals. Moreover, the magnitude of prediction error signals in a region of dorsal striatum correlated significantly with a measure of behavioral performance across all subjects. These findings support a crucial role of prediction error signals, likely originating from dopaminergic midbrain neurons, in enabling learning of action selection preferences on the basis of obtained rewards. Thus, spontaneously observed individual differences in decision making performance demonstrate the suggested dependence of this type of learning on the functional integrity of the dopaminergic striatal system in humans.

Moderation of Stimulus Material on the Prediction of IQ with Infants' Performance in the Visual Expectation Paradigm: Do Greebles Make the Task More Challenging?

ERIC Educational Resources Information Center

Teubert, Manuel; Lohaus, Arnold; Fassbender, Ina; Vöhringer, Isabel A.; Suhrke, Janina; Poloczek, Sonja; Freitag, Claudia; Lamm, Bettina; Teiser, Johanna; Keller, Heidi; Knopf, Monika; Schwarzer, Gudrun

2015-01-01

The objective of this study was to examine the role of the stimulus material for the prediction of later IQ by early learning measures in the Visual Expectation Paradigm (VExP). The VExP was assessed at 9?months using two types of stimuli, Greebles and human faces. Greebles were assumed to be associated with a higher load on working memory in…

Effect of Subliminal Lexical Priming on the Subjective Perception of Images: A Machine Learning Approach.

PubMed

Mohan, Dhanya Menoth; Kumar, Parmod; Mahmood, Faisal; Wong, Kian Foong; Agrawal, Abhishek; Elgendi, Mohamed; Shukla, Rohit; Ang, Natania; Ching, April; Dauwels, Justin; Chan, Alice H D

2016-01-01

The purpose of the study is to examine the effect of subliminal priming in terms of the perception of images influenced by words with positive, negative, and neutral emotional content, through electroencephalograms (EEGs). Participants were instructed to rate how much they like the stimuli images, on a 7-point Likert scale, after being subliminally exposed to masked lexical prime words that exhibit positive, negative, and neutral connotations with respect to the images. Simultaneously, the EEGs were recorded. Statistical tests such as repeated measures ANOVAs and two-tailed paired-samples t-tests were performed to measure significant differences in the likability ratings among the three prime affect types; the results showed a strong shift in the likeness judgment for the images in the positively primed condition compared to the other two. The acquired EEGs were examined to assess the difference in brain activity associated with the three different conditions. The consistent results obtained confirmed the overall priming effect on participants' explicit ratings. In addition, machine learning algorithms such as support vector machines (SVMs), and AdaBoost classifiers were applied to infer the prime affect type from the ERPs. The highest classification rates of 95.0% and 70.0% obtained respectively for average-trial binary classifier and average-trial multi-class further emphasize that the ERPs encode information about the different kinds of primes.

Effect of Subliminal Lexical Priming on the Subjective Perception of Images: A Machine Learning Approach

PubMed Central

Mahmood, Faisal; Wong, Kian Foong; Agrawal, Abhishek; Elgendi, Mohamed; Shukla, Rohit; Ang, Natania; Ching, April; Dauwels, Justin; Chan, Alice H. D.

2016-01-01

The purpose of the study is to examine the effect of subliminal priming in terms of the perception of images influenced by words with positive, negative, and neutral emotional content, through electroencephalograms (EEGs). Participants were instructed to rate how much they like the stimuli images, on a 7-point Likert scale, after being subliminally exposed to masked lexical prime words that exhibit positive, negative, and neutral connotations with respect to the images. Simultaneously, the EEGs were recorded. Statistical tests such as repeated measures ANOVAs and two-tailed paired-samples t-tests were performed to measure significant differences in the likability ratings among the three prime affect types; the results showed a strong shift in the likeness judgment for the images in the positively primed condition compared to the other two. The acquired EEGs were examined to assess the difference in brain activity associated with the three different conditions. The consistent results obtained confirmed the overall priming effect on participants’ explicit ratings. In addition, machine learning algorithms such as support vector machines (SVMs), and AdaBoost classifiers were applied to infer the prime affect type from the ERPs. The highest classification rates of 95.0% and 70.0% obtained respectively for average-trial binary classifier and average-trial multi-class further emphasize that the ERPs encode information about the different kinds of primes. PMID:26866807

Measuring Learning through Cross Sectional Testing

ERIC Educational Resources Information Center

Lovett, Steve; Johnson, Jennie

2012-01-01

The measurement of student learning is becoming increasingly important in U.S. higher education. One way to measure learning is through longitudinal testing, but this becomes especially difficult when applied to cumulative learning within programs in situations of low persistence. In particular, many Hispanic Serving Institutions (HSIs) find…

Challenges in Modeling and Measuring Learning Trajectories

ERIC Educational Resources Information Center

Confrey, Jere; Jones, R. Seth; Gianopulos, Garron

2015-01-01

Briggs and Peck make a compelling case for creating new, more intuitive measures of learning, based on creating vertical scales using learning trajectories (LT) in place of "domain sampling." We believe that the importance of creating measurement scales that coordinate recognizable landmarks in learning trajectories with interval scales…

Mobile Assisted Language Learning Experiences

ERIC Educational Resources Information Center

Kim, Daesang; Ruecker, Daniel; Kim, Dong-Joong

2017-01-01

The purpose of this study was to investigate the benefits of learning with mobile technology for TESOL students and to explore their perceptions of learning with this type of technology. The study provided valuable insights on how students perceive and adapt to learning with mobile technology for effective learning experiences for both students…

Examining Informal Learning in Commercial Airline Pilots' Communities of Practice

ERIC Educational Resources Information Center

Corns, Kevin M.

2014-01-01

A pragmatic sequential mixed methods research methodology was used to examine commercial airline pilots' (N =156) types and frequencies of informal learning activities, perceptions of workplace informal learning, and opinions on how organizations should support workplace informal learning outside of the formal learning environment. This study…

Second Language Experience Facilitates Statistical Learning of Novel Linguistic Materials

ERIC Educational Resources Information Center

Potter, Christine E.; Wang, Tianlin; Saffran, Jenny R.

2017-01-01

Recent research has begun to explore individual differences in statistical learning, and how those differences may be related to other cognitive abilities, particularly their effects on language learning. In this research, we explored a different type of relationship between language learning and statistical learning: the possibility that learning…

Factors that Influence Informal Learning in the Workplace

ERIC Educational Resources Information Center

Berg, Shelley A.; Chyung, Seung Youn

2008-01-01

Purpose: The purpose of this research is to investigate factors that influence informal learning in the workplace and the types of informal learning activities people engage in at work. More specifically, the research examined: the relationship between informal learning engagement and the presence of learning organization characteristics; and…

Effects of Different Types of Virtual Reality Display on Presence and Learning in a Safety Training Scenario.

PubMed

Buttussi, Fabio; Chittaro, Luca

2018-02-01

The increasing availability of head-mounted displays (HMDs) for home use motivates the study of the possible effects that adopting this new hardware might have on users. Moreover, while the impact of display type has been studied for different kinds of tasks, it has been scarcely explored in procedural training. Our study considered three different types of displays used by participants for training in aviation safety procedures with a serious game. The three displays were respectively representative of: (i) desktop VR (a standard desktop monitor), (ii) many setups for immersive VR used in the literature (an HMD with narrow field of view and a 3-DOF tracker), and (iii) new setups for immersive home VR (an HMD with wide field of view and 6-DOF tracker). We assessed effects on knowledge gain, and different self-reported measures (self-efficacy, engagement, presence). Unlike previous studies of display type that measured effects only immediately after the VR experience, we considered also a longer time span (2 weeks). Results indicated that the display type played a significant role in engagement and presence. The training benefits (increased knowledge and self-efficacy) were instead obtained, and maintained at two weeks, regardless of the display used. The paper discusses the implications of these results.

Neuroimaging Evidence for 2 Types of Plasticity in Association with Visual Perceptual Learning.

PubMed

Shibata, Kazuhisa; Sasaki, Yuka; Kawato, Mitsuo; Watanabe, Takeo

2016-09-01

Visual perceptual learning (VPL) is long-term performance improvement as a result of perceptual experience. It is unclear whether VPL is associated with refinement in representations of the trained feature (feature-based plasticity), improvement in processing of the trained task (task-based plasticity), or both. Here, we provide empirical evidence that VPL of motion detection is associated with both types of plasticity which occur predominantly in different brain areas. Before and after training on a motion detection task, subjects' neural responses to the trained motion stimuli were measured using functional magnetic resonance imaging. In V3A, significant response changes after training were observed specifically to the trained motion stimulus but independently of whether subjects performed the trained task. This suggests that the response changes in V3A represent feature-based plasticity in VPL of motion detection. In V1 and the intraparietal sulcus, significant response changes were found only when subjects performed the trained task on the trained motion stimulus. This suggests that the response changes in these areas reflect task-based plasticity. These results collectively suggest that VPL of motion detection is associated with the 2 types of plasticity, which occur in different areas and therefore have separate mechanisms at least to some degree. © The Author 2016. Published by Oxford University Press.

The Effects of Gender and Type of Inquiry Curriculum on Sixth Grade Students' Science Process Skills and Epistemological Beliefs in Science

NASA Astrophysics Data System (ADS)

Zaleta, Kristy L.

The purpose of this study was to investigate the impact of gender and type of inquiry curriculum (open or structured) on science process skills and epistemological beliefs in science of sixth grade students. The current study took place in an urban northeastern middle school. The researcher utilized a sample of convenience comprised of 303 sixth grade students taught by four science teachers on separate teams. The study employed mixed methods with a quasi-experimental design, pretest-posttest comparison group with 17 intact classrooms of students. Students' science process skills and epistemological beliefs in science (source, certainty, development, and justification) were measured before and after the intervention, which exposed different groups of students to different types of inquiry (structured or open). Differences between comparison and treatment groups and between male and female students were analyzed after the intervention, on science process skills, using a two-way analysis of covariance (ANCOVA), and, on epistemological beliefs in science, using a two-way multivariate analysis of covariance (MANCOVA). Responses from two focus groups of open inquiry students were cycle coded and examined for themes and patterns. Quantitative measurements indicated that girls scored significantly higher on science process skills than boys, regardless of type of inquiry instruction. Neither gender nor type of inquiry instruction predicted students' epistemological beliefs in science after accounting for students' pretest scores. The dimension Development accounted for 10.6% of the variance in students' science process skills. Qualitative results indicated that students with sophisticated epistemological beliefs expressed engagement with the open-inquiry curriculum. Students in both the sophisticated and naive beliefs groups identified challenges with the curriculum and improvement in learning as major themes. The types of challenges identified differed between the groups: sophisticated beliefs group students focused on their insecurity of not knowing how to complete the activities correctly, and naive beliefs group students focused on the amount of work and how long it took them to complete it. The description of the improvement in learning was at a basic level for the naive beliefs group and at a more complex level for the sophisticated beliefs group. Implications for researchers and educators are discussed.

An Exposition of Current Mobile Learning Design Guidelines and Frameworks

ERIC Educational Resources Information Center

Teall, Ed; Wang, Minjuan; Callaghan, Vic; Ng, Jason W. P.

2014-01-01

As mobile devices with wireless access become more readily available, learning delivered via mobile devices of all types must be designed to ensure successful learning. This paper first examines three questions related to the design of mobile learning: 1) what mobile learning (m-learning) guidelines can be identified in the current literature, 2)…

Effects of Providing a Rationale for Learning a Lesson on Students' Motivation and Learning in Online Learning Environments

ERIC Educational Resources Information Center

Shin, Tae Seob

2010-01-01

This study examined whether providing a rationale for learning a particular lesson influences students' motivation and learning in online learning environments. A mixed-method design was used to investigate the effects of two types of rationales (former student vs. instructor rationales) presented in an online introductory educational psychology…

The Use of a Reflective Learning Journal in an Introductory Statistics Course

ERIC Educational Resources Information Center

Denton, Ashley Waggoner

2018-01-01

Reflective learning entails a thoughtful learning process through which one not only learns a particular piece of knowledge or skill, but better understands "how" one learned it--knowledge that can then be transferred well beyond the scope of the specific learning experience. This type of thinking empowers learners by making them more…

"I know your name, but not your number"--Patients with verbal short-term memory deficits are impaired in learning sequences of digits.

PubMed

Bormann, Tobias; Seyboth, Margret; Umarova, Roza; Weiller, Cornelius

2015-06-01

Studies on verbal learning in patients with impaired verbal short-term memory (vSTM) have revealed dissociations among types of verbal information. Patients with impaired vSTM are able to learn lists of known words but fail to acquire new word forms. This suggests that vSTM is involved in new word learning. The present study assessed both new word learning and the learning of digit sequences in two patients with impaired vSTM. In two experiments, participants were required to learn people's names, ages and professions, or their four digit 'phone numbers'. The STM patients were impaired on learning unknown family names and phone numbers, but managed to acquire other verbal information. In contrast, a patient with a severe verbal episodic memory impairment was impaired across information types. These results indicate verbal STM involvement in the learning of digit sequences. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Cost-Effectiveness Analysis of Blended Versus Face-to-Face Delivery of Evidence-Based Medicine to Medical Students.

PubMed

Maloney, Stephen; Nicklen, Peter; Rivers, George; Foo, Jonathan; Ooi, Ying Ying; Reeves, Scott; Walsh, Kieran; Ilic, Dragan

2015-07-21

Blended learning describes a combination of teaching methods, often utilizing digital technologies. Research suggests that learner outcomes can be improved through some blended learning formats. However, the cost-effectiveness of delivering blended learning is unclear. This study aimed to determine the cost-effectiveness of a face-to-face learning and blended learning approach for evidence-based medicine training within a medical program. The economic evaluation was conducted as part of a randomized controlled trial (RCT) comparing the evidence-based medicine (EBM) competency of medical students who participated in two different modes of education delivery. In the traditional face-to-face method, students received ten 2-hour classes. In the blended learning approach, students received the same total face-to-face hours but with different activities and additional online and mobile learning. Online activities utilized YouTube and a library guide indexing electronic databases, guides, and books. Mobile learning involved self-directed interactions with patients in their regular clinical placements. The attribution and differentiation of costs between the interventions within the RCT was measured in conjunction with measured outcomes of effectiveness. An incremental cost-effectiveness ratio was calculated comparing the ongoing operation costs of each method with the level of EBM proficiency achieved. Present value analysis was used to calculate the break-even point considering the transition cost and the difference in ongoing operation cost. The incremental cost-effectiveness ratio indicated that it costs 24% less to educate a student to the same level of EBM competency via the blended learning approach used in the study, when excluding transition costs. The sunk cost of approximately AUD $40,000 to transition to the blended model exceeds any savings from using the approach within the first year of its implementation; however, a break-even point is achieved within its third iteration and relative savings in the subsequent years. The sensitivity analysis indicates that approaches with higher transition costs, or staffing requirements over that of a traditional method, are likely to result in negative value propositions. Under the study conditions, a blended learning approach was more cost-effective to operate and resulted in improved value for the institution after the third year iteration, when compared to the traditional face-to-face model. The wider applicability of the findings are dependent on the type of blended learning utilized, staffing expertise, and educational context.

Active learning for ontological event extraction incorporating named entity recognition and unknown word handling.

PubMed

Han, Xu; Kim, Jung-jae; Kwoh, Chee Keong

2016-01-01

Biomedical text mining may target various kinds of valuable information embedded in the literature, but a critical obstacle to the extension of the mining targets is the cost of manual construction of labeled data, which are required for state-of-the-art supervised learning systems. Active learning is to choose the most informative documents for the supervised learning in order to reduce the amount of required manual annotations. Previous works of active learning, however, focused on the tasks of entity recognition and protein-protein interactions, but not on event extraction tasks for multiple event types. They also did not consider the evidence of event participants, which might be a clue for the presence of events in unlabeled documents. Moreover, the confidence scores of events produced by event extraction systems are not reliable for ranking documents in terms of informativity for supervised learning. We here propose a novel committee-based active learning method that supports multi-event extraction tasks and employs a new statistical method for informativity estimation instead of using the confidence scores from event extraction systems. Our method is based on a committee of two systems as follows: We first employ an event extraction system to filter potential false negatives among unlabeled documents, from which the system does not extract any event. We then develop a statistical method to rank the potential false negatives of unlabeled documents 1) by using a language model that measures the probabilities of the expression of multiple events in documents and 2) by using a named entity recognition system that locates the named entities that can be event arguments (e.g. proteins). The proposed method further deals with unknown words in test data by using word similarity measures. We also apply our active learning method for the task of named entity recognition. We evaluate the proposed method against the BioNLP Shared Tasks datasets, and show that our method can achieve better performance than such previous methods as entropy and Gibbs error based methods and a conventional committee-based method. We also show that the incorporation of named entity recognition into the active learning for event extraction and the unknown word handling further improve the active learning method. In addition, the adaptation of the active learning method into named entity recognition tasks also improves the document selection for manual annotation of named entities.

Arterial spin labeling reveals relationships between resting cerebral perfusion and motor learning in Parkinson's disease.

PubMed

Barzgari, Amy; Sojkova, Jitka; Maritza Dowling, N; Pozorski, Vincent; Okonkwo, Ozioma C; Starks, Erika J; Oh, Jennifer; Thiesen, Frances; Wey, Alexandra; Nicholas, Christopher R; Johnson, Sterling; Gallagher, Catherine L

2018-05-09

Parkinson's disease (PD) is an age-related neurodegenerative disease that produces changes in movement, cognition, sleep, and autonomic function. Motor learning involves acquisition of new motor skills through practice, and is affected by PD. The purpose of the present study was to evaluate regional differences in resting cerebral blood flow (rCBF), measured using arterial spin labeling (ASL) MRI, during a finger-typing task of motor skill acquisition in PD patients compared to age- and gender-matched controls. Voxel-wise multiple linear regression models were used to examine the relationship between rCBF and several task variables, including initial speed, proficiency gain, and accuracy. In these models, a task-by-disease group interaction term was included to investigate where the relationship between rCBF and task performance was influenced by PD. At baseline, perfusion was lower in PD subjects than controls in the right occipital cortex. The task-by-disease group interaction for initial speed was significantly related to rCBF (p < 0.05, corrected) in several brain regions involved in motor learning, including the occipital, parietal, and temporal cortices, cerebellum, anterior cingulate, and the superior and middle frontal gyri. In these regions, PD patients showed higher rCBF, and controls lower rCBF, with improved performance. Within the control group, proficiency gain over 12 typing trials was related to greater rCBF in cerebellar, occipital, and temporal cortices. These results suggest that higher rCBF within networks involved in motor learning enable PD patients to compensate for disease-related deficits.

Undergraduates achieve learning gains in plant genetics through peer teaching of secondary students.

PubMed

Chrispeels, H E; Klosterman, M L; Martin, J B; Lundy, S R; Watkins, J M; Gibson, C L; Muday, G K

2014-01-01

This study tests the hypothesis that undergraduates who peer teach genetics will have greater understanding of genetic and molecular biology concepts as a result of their teaching experiences. Undergraduates enrolled in a non-majors biology course participated in a service-learning program in which they led middle school (MS) or high school (HS) students through a case study curriculum to discover the cause of a green tomato variant. The curriculum explored plant reproduction and genetic principles, highlighting variation in heirloom tomato fruits to reinforce the concept of the genetic basis of phenotypic variation. HS students were taught additional activities related to mole-cular biology techniques not included in the MS curriculum. We measured undergraduates' learning outcomes using pre/postteaching content assessments and the course final exam. Undergraduates showed significant gains in understanding of topics related to the curriculum they taught, compared with other course content, on both types of assessments. Undergraduates who taught HS students scored higher on questions specific to the HS curriculum compared with undergraduates who taught MS students, despite identical lecture content, on both types of assessments. These results indicate the positive effect of service-learning peer-teaching experiences on undergraduates' content knowledge, even for non-science major students. © 2014 H. E. Chrispeels et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Deep Learning for Classification of Colorectal Polyps on Whole-slide Images.

PubMed

Korbar, Bruno; Olofson, Andrea M; Miraflor, Allen P; Nicka, Catherine M; Suriawinata, Matthew A; Torresani, Lorenzo; Suriawinata, Arief A; Hassanpour, Saeed

2017-01-01

Histopathological characterization of colorectal polyps is critical for determining the risk of colorectal cancer and future rates of surveillance for patients. However, this characterization is a challenging task and suffers from significant inter- and intra-observer variability. We built an automatic image analysis method that can accurately classify different types of colorectal polyps on whole-slide images to help pathologists with this characterization and diagnosis. Our method is based on deep-learning techniques, which rely on numerous levels of abstraction for data representation and have shown state-of-the-art results for various image analysis tasks. Our method covers five common types of polyps (i.e., hyperplastic, sessile serrated, traditional serrated, tubular, and tubulovillous/villous) that are included in the US Multisociety Task Force guidelines for colorectal cancer risk assessment and surveillance. We developed multiple deep-learning approaches by leveraging a dataset of 2074 crop images, which were annotated by multiple domain expert pathologists as reference standards. We evaluated our method on an independent test set of 239 whole-slide images and measured standard machine-learning evaluation metrics of accuracy, precision, recall, and F1 score and their 95% confidence intervals. Our evaluation shows that our method with residual network architecture achieves the best performance for classification of colorectal polyps on whole-slide images (overall accuracy: 93.0%, 95% confidence interval: 89.0%-95.9%). Our method can reduce the cognitive burden on pathologists and improve their efficacy in histopathological characterization of colorectal polyps and in subsequent risk assessment and follow-up recommendations.

Deep Learning for Classification of Colorectal Polyps on Whole-slide Images

PubMed Central

Korbar, Bruno; Olofson, Andrea M.; Miraflor, Allen P.; Nicka, Catherine M.; Suriawinata, Matthew A.; Torresani, Lorenzo; Suriawinata, Arief A.; Hassanpour, Saeed

2017-01-01

Context: Histopathological characterization of colorectal polyps is critical for determining the risk of colorectal cancer and future rates of surveillance for patients. However, this characterization is a challenging task and suffers from significant inter- and intra-observer variability. Aims: We built an automatic image analysis method that can accurately classify different types of colorectal polyps on whole-slide images to help pathologists with this characterization and diagnosis. Setting and Design: Our method is based on deep-learning techniques, which rely on numerous levels of abstraction for data representation and have shown state-of-the-art results for various image analysis tasks. Subjects and Methods: Our method covers five common types of polyps (i.e., hyperplastic, sessile serrated, traditional serrated, tubular, and tubulovillous/villous) that are included in the US Multisociety Task Force guidelines for colorectal cancer risk assessment and surveillance. We developed multiple deep-learning approaches by leveraging a dataset of 2074 crop images, which were annotated by multiple domain expert pathologists as reference standards. Statistical Analysis: We evaluated our method on an independent test set of 239 whole-slide images and measured standard machine-learning evaluation metrics of accuracy, precision, recall, and F1 score and their 95% confidence intervals. Results: Our evaluation shows that our method with residual network architecture achieves the best performance for classification of colorectal polyps on whole-slide images (overall accuracy: 93.0%, 95% confidence interval: 89.0%–95.9%). Conclusions: Our method can reduce the cognitive burden on pathologists and improve their efficacy in histopathological characterization of colorectal polyps and in subsequent risk assessment and follow-up recommendations. PMID:28828201

Discrete Regularization for Calibration of Geologic Facies Against Dynamic Flow Data

NASA Astrophysics Data System (ADS)

Khaninezhad, Mohammad-Reza; Golmohammadi, Azarang; Jafarpour, Behnam

2018-04-01

Subsurface flow model calibration involves many more unknowns than measurements, leading to ill-posed problems with nonunique solutions. To alleviate nonuniqueness, the problem is regularized by constraining the solution space using prior knowledge. In certain sedimentary environments, such as fluvial systems, the contrast in hydraulic properties of different facies types tends to dominate the flow and transport behavior, making the effect of within facies heterogeneity less significant. Hence, flow model calibration in those formations reduces to delineating the spatial structure and connectivity of different lithofacies types and their boundaries. A major difficulty in calibrating such models is honoring the discrete, or piecewise constant, nature of facies distribution. The problem becomes more challenging when complex spatial connectivity patterns with higher-order statistics are involved. This paper introduces a novel formulation for calibration of complex geologic facies by imposing appropriate constraints to recover plausible solutions that honor the spatial connectivity and discreteness of facies models. To incorporate prior connectivity patterns, plausible geologic features are learned from available training models. This is achieved by learning spatial patterns from training data, e.g., k-SVD sparse learning or the traditional Principal Component Analysis. Discrete regularization is introduced as a penalty functions to impose solution discreteness while minimizing the mismatch between observed and predicted data. An efficient gradient-based alternating directions algorithm is combined with variable splitting to minimize the resulting regularized nonlinear least squares objective function. Numerical results show that imposing learned facies connectivity and discreteness as regularization functions leads to geologically consistent solutions that improve facies calibration quality.

Real-time probabilistic covariance tracking with efficient model update.

PubMed

Wu, Yi; Cheng, Jian; Wang, Jinqiao; Lu, Hanqing; Wang, Jun; Ling, Haibin; Blasch, Erik; Bai, Li

2012-05-01

The recently proposed covariance region descriptor has been proven robust and versatile for a modest computational cost. The covariance matrix enables efficient fusion of different types of features, where the spatial and statistical properties, as well as their correlation, are characterized. The similarity between two covariance descriptors is measured on Riemannian manifolds. Based on the same metric but with a probabilistic framework, we propose a novel tracking approach on Riemannian manifolds with a novel incremental covariance tensor learning (ICTL). To address the appearance variations, ICTL incrementally learns a low-dimensional covariance tensor representation and efficiently adapts online to appearance changes of the target with only O(1) computational complexity, resulting in a real-time performance. The covariance-based representation and the ICTL are then combined with the particle filter framework to allow better handling of background clutter, as well as the temporary occlusions. We test the proposed probabilistic ICTL tracker on numerous benchmark sequences involving different types of challenges including occlusions and variations in illumination, scale, and pose. The proposed approach demonstrates excellent real-time performance, both qualitatively and quantitatively, in comparison with several previously proposed trackers.

Student laboratory presentations as a learning tool in anatomy education.

PubMed

Chollet, Madeleine B; Teaford, Mark F; Garofalo, Evan M; DeLeon, Valerie B

2009-01-01

Previous studies have shown that anatomy students who complete oral laboratory presentations believe they understand the material better and retain it longer than they otherwise would if they only took examinations on the material; however, we have found no studies that empirically test such outcomes. The purpose of this study was to assess the effectiveness of oral presentations through comparisons with other methods of assessment, most notably, examination performance. Specifically, we tested whether students (n = 256) performed better on examination questions on topics covered by their oral presentations than on other topics. Each student completed two graded, 12-minute laboratory presentations on two different assigned topics during the course and took three examinations, each of which covered a third of the course material. Examination questions were characterized by type (memorization, pathway, analytical, spatial). A two-way repeated measures analysis of variance revealed that students performed better on topics covered by their presentations than on topics not covered by their presentations (P < 0.005), regardless of presentation grade (P > 0.05) and question type (P > 0.05). These results demonstrate empirically that oral presentations are an effective learning tool.

Social Cues Alter Implicit Motor Learning in a Serial Reaction Time Task.

PubMed

Geiger, Alexander; Cleeremans, Axel; Bente, Gary; Vogeley, Kai

2018-01-01

Learning is a central ability for human development. Many skills we learn, such as language, are learned through observation or imitation in social contexts. Likewise, many skills are learned implicitly, that is, without an explicit intent to learn and without full awareness of the acquired knowledge. Here, we asked whether performance in a motor learning task is modulated by social vs. object cues of varying validity. To address this question, we asked participants to carry out a serial reaction time (SRT) task in which, on each trial, people have to respond as fast and as accurately as possible to the appearance of a stimulus at one of four possible locations. Unbeknownst to participants, the sequence of successive locations was sequentially structured, so that knowledge of the sequence facilitates anticipation of the next stimulus and hence faster motor responses. Crucially, each trial also contained a cue pointing to the next stimulus location. Participants could thus learn based on the cue, or on learning about the sequence of successive locations, or on a combination of both. Results show an interaction between cue type and cue validity for the motor responses: social cues (vs. object cues) led to faster responses in the low validity (LV) condition only. Concerning the extent to which learning was implicit, results show that in the cued blocks only, the highly valid social cue led to implicit learning. In the uncued blocks, participants showed no implicit learning in the highly valid social cue condition, but did in all other combinations of stimulus type and cueing validity. In conclusion, our results suggest that implicit learning is context-dependent and can be influenced by the cue type, e.g., social and object cues.

Blended learning with Moodle in medical statistics: an assessment of knowledge, attitudes and practices relating to e-learning.

PubMed

Luo, Li; Cheng, Xiaohua; Wang, Shiyuan; Zhang, Junxue; Zhu, Wenbo; Yang, Jiaying; Liu, Pei

2017-09-19

Blended learning that combines a modular object-oriented dynamic learning environment (Moodle) with face-to-face teaching was applied to a medical statistics course to improve learning outcomes and evaluate the impact factors of students' knowledge, attitudes and practices (KAP) relating to e-learning. The same real-name questionnaire was administered before and after the intervention. The summed scores of every part (knowledge, attitude and practice) were calculated using the entropy method. A mixed linear model was fitted using the SAS PROC MIXED procedure to analyse the impact factors of KAP. Educational reform, self-perceived character, registered permanent residence and hours spent online per day were significant impact factors of e-learning knowledge. Introversion and middle type respondents' average scores were higher than those of extroversion type respondents. Regarding e-learning attitudes, educational reform, community number, Internet age and hours spent online per day had a significant impact. Specifically, participants whose Internet age was no greater than 6 years scored 7.00 points lower than those whose Internet age was greater than 10 years. Regarding e-learning behaviour, educational reform and parents' literacy had a significant impact, as the average score increased 10.05 points (P < 0.0001). This educational reform that combined Moodle with a traditional class achieved good results in terms of students' e-learning KAP. Additionally, this type of blended course can be implemented in many other curriculums.

An Integrated Scale for Measuring an Organizational Learning System

ERIC Educational Resources Information Center

Jyothibabu, C.; Farooq, Ayesha; Pradhan, Bibhuti Bhusan

2010-01-01

Purpose: The purpose of this paper is to develop an integrated measurement scale for an organizational learning system by capturing the learning enablers, learning results and performance outcome in an organization. Design/methodology/approach: A new measurement scale was developed by integrating and modifying two existing scales, identified…

Learning Disabilities

ERIC Educational Resources Information Center

Myklebust, Helmer R.

1976-01-01

Minimal cerebral dysfunctions are noted as primary cause for learning disability in children. Although children have normal capacities for learning, it is stated that their cognitive processes have been altered and special instructional techniques and procedures are needed. The various types of learning disabilities are discussed. (EB)

Brain Type or Sex Differences? A Structural Equation Model of the Relation between Brain Type, Sex, and Motivation to Learn Science

ERIC Educational Resources Information Center

Zeyer, Albert; Bolsterli, Katrin; Brovelli, Dorothee; Odermatt, Freia

2012-01-01

Sex is considered to be one of the most significant factors influencing attitudes towards science. However, the so-called brain type approach from cognitive science suggests that the difference in motivation to learn science does not primarily differentiate the girls from the boys, but rather the so-called systemisers from the empathizers. The…

Colour learning when foraging for nectar and pollen: bees learn two colours at once.

PubMed

Muth, Felicity; Papaj, Daniel R; Leonard, Anne S

2015-09-01

Bees are model organisms for the study of learning and memory, yet nearly all such research to date has used a single reward, nectar. Many bees collect both nectar (carbohydrates) and pollen (protein) on a single foraging bout, sometimes from different plant species. We tested whether individual bumblebees could learn colour associations with nectar and pollen rewards simultaneously in a foraging scenario where one floral type offered only nectar and the other only pollen. We found that bees readily learned multiple reward-colour associations, and when presented with novel floral targets generalized to colours similar to those trained for each reward type. These results expand the ecological significance of work on bee learning and raise new questions regarding the cognitive ecology of pollination. © 2015 The Author(s).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sebok, A.; Nystad, E.

This paper describes a study investigating questions of learning effectiveness in different VR technology types. Four VR display technology types were compared in terms of their ability to support procedural learning. The VR systems included two desktop displays (mono-scopic and stereoscopic view), a large screen stereoscopic display, and a mono-scopic head-mounted display. Twenty-four participants completed procedural training scenarios on these different display types. Training effectiveness was assessed in terms of objective task performance. Following the training session, participants performed the procedure they had just learned using the same VR display type they used for training. Time to complete the proceduremore » and errors were recorded. Retention and transfer of training were evaluated in a talk-through session 24 hours after the training. In addition, subjective questionnaire data were gathered to investigate perceived workload, Sense of Presence, simulator sickness, perceived usability, and ease of navigation. While no difference was found for the short-term learning, the study results indicate that retention and transfer of training were better supported by the large screen stereoscopic condition. (authors)« less

Graph Kernels for Molecular Similarity.

PubMed

Rupp, Matthias; Schneider, Gisbert

2010-04-12

Molecular similarity measures are important for many cheminformatics applications like ligand-based virtual screening and quantitative structure-property relationships. Graph kernels are formal similarity measures defined directly on graphs, such as the (annotated) molecular structure graph. Graph kernels are positive semi-definite functions, i.e., they correspond to inner products. This property makes them suitable for use with kernel-based machine learning algorithms such as support vector machines and Gaussian processes. We review the major types of kernels between graphs (based on random walks, subgraphs, and optimal assignments, respectively), and discuss their advantages, limitations, and successful applications in cheminformatics. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Engagement with physics across diverse festival audiences

NASA Astrophysics Data System (ADS)

Roche, Joseph; Stanley, Jessica; Davis, Nicola

2016-07-01

Science shows provide a method of introducing large public audiences to physics concepts in a nonformal learning environment. While these shows have the potential to provide novel means of educational engagement, it is often difficult to measure that engagement. We present a method of producing an interactive physics show that seeks to provide effective and measurable audience engagement. We share our results from piloting this method at a leading music and arts festival as well as a science festival. This method also facilitated the collection of opinions and feedback directly from the audience which helps explore the benefits and limitations of this type of nonformal engagement in physics education.

Measuring coercive control: what can we learn from national population surveys?

PubMed

Myhill, Andy

2015-03-01

Numerous academic studies point to gender symmetry in the prevalence of intimate partner violence (IPV). Many of these studies report findings from surveys with small and/or unrepresentative samples that have insufficient questions to differentiate adequately between different types of abuse. Data from a large, nationally representative survey suggest that, while the prevalence of situational violence is fairly symmetrical, coercive controlling abuse is highly gendered, with women overwhelmingly the victims. The authors conclude that more comprehensive measures are required in national surveys that consider a wider range of controlling behaviors as well as the meaning and impact of abuse. © The Author(s) 2015.

Fostering science literacy, environmental stewardship, and collaboration: Assessing a garden-based approach to teaching life science

NASA Astrophysics Data System (ADS)

Fisher-Maltese, Carley B.

Recently, schools nationwide have expressed a renewed interest in school gardens (California School Garden Network, 2010), viewing them as innovative educational tools. Most of the scant studies on these settings investigate the health/nutritional impacts, environmental attitudes, or emotional dispositions of students. However, few studies examine the science learning potential of a school garden from an informal learning perspective. Those studies that do examine learning emphasize individual learning of traditional school content (math, science, etc.) (Blaire, 2009; Dirks & Orvis, 2005; Klemmer, Waliczek & Zajicek, 2005a & b; Smith & Mostenbocker, 2005). My study sought to demonstrate the value of school garden learning through a focus on measures of learning typically associated with traditional learning environments, as well as informal learning environments. Grounded in situated, experiential, and contextual model of learning theories, the purpose of this case study was to examine the impacts of a school garden program at a K-3 elementary school. Results from pre/post tests, pre/post surveys, interviews, recorded student conversations, and student work reveal a number of affordances, including science learning, cross-curricular lessons in an authentic setting, a sense of school community, and positive shifts in attitude toward nature and working collaboratively with other students. I also analyzed this garden-based unit as a type curriculum reform in one school in an effort to explore issues of implementing effective practices in schools. Facilitators and barriers to implementing a garden-based science curriculum at a K-3 elementary school are discussed. Participants reported a number of implementation processes necessary for success: leadership, vision, and material, human, and social resources. However, in spite of facilitators, teachers reported barriers to implementing the garden-based curriculum, specifically lack of time and content knowledge.

E-Learning in Croatian Higher Education: An Analysis of Students' Perceptions

NASA Astrophysics Data System (ADS)

Dukić, Darko; Andrijanić, Goran

2010-06-01

Over the last years, e-learning has taken an important role in Croatian higher education as a result of strategies defined and measures undertaken. Nonetheless, in comparison to the developed countries, the achievements in e-learning implementation are still unsatisfactory. Therefore, the efforts to advance e-learning within Croatian higher education need to be intensified. It is further necessary to undertake ongoing activities in order to solve possible problems in e-learning system functioning, which requires the development of adequate evaluation instruments and methods. One of the key steps in this process would be examining and analyzing users' attitudes. This paper presents a study of Croatian students' perceptions with regard to certain aspects of e-learning usage. Given the character of this research, adequate statistical methods were required for the data processing. The results of the analysis indicate that, for the most part, Croatian students have positive perceptions of e-learning, particularly as support to time-honored forms of teaching. However, they are not prepared to completely give up the traditional classroom. Using factor analysis, we identified four underlying factors of a collection of variables related to students' perceptions of e-learning. Furthermore, a certain number of statistically significant differences in student attitudes have been confirmed, in terms of gender and year of study. In our study we used discriminant analysis to determine discriminant functions that distinguished defined groups of students. With this research we managed to a certain degree to alleviate the current data insufficiency in the area of e-learning evaluation among Croatian students. Since this type of learning is gaining in importance within higher education, such analyses have to be conducted continuously.

Scaffolding scientific discussion using socially relevant representations in networked multimedia

NASA Astrophysics Data System (ADS)

Hoadley, Christopher M.

1999-11-01

How do students make use of social cues when learning on the computer? This work examines how students in a middle-school science course learned through on-line peer discussion. Cognitive accounts of collaboration stress interacting with ideas, while socially situated accounts stress the interpersonal context. The design of electronic environments allows investigation into the interrelation of cognitive and social dimensions. I use on-line peer discussion to investigate how socially relevant representations in interfaces can aid learning. First, I identify some of the variables that affect individual participation in on-line discussion, including interface features. Individual participation is predicted by student attitudes towards learning from peers. Second, I describe the range of group outcomes for these on-line discussions. There is a large effect of discussion group on learning outcomes which is not reducible to group composition or gross measures of group process. Third, I characterize how students (individually) construct understanding from these group discussions. Learning in the on-line discussions is shown to be a result of sustained interaction over time, not merely encountering or expressing ideas. Experimental manipulations in the types of social cues available to students suggest that many students do use socially relevant representations to support their understanding of multiple viewpoints and science reasoning. Personalizing scientific disputes can afford reflection on the nature of scientific discovery and advance. While there are many individual differences in how social representations are used by students in learning, overall learning benefits for certain social representations can be shown. This work has profound implications for design of collaborative instructional methods, equitable access to science learning, design of instructional technology, and understanding of learning and cognition in social settings.

Parameters and Measures in Assessment of Motor Learning in Neurorehabilitation; A Systematic Review of the Literature

PubMed Central

Shishov, Nataliya; Melzer, Itshak; Bar-Haim, Simona

2017-01-01

Upper limb function, essential for daily life, is often impaired in individuals after stroke and cerebral palsy (CP). For an improved upper limb function, learning should occur, and therefore training with motor learning principles is included in many rehabilitation interventions. Despite accurate measurement being an important aspect for examination and optimization of treatment outcomes, there are no standard algorithms for outcome measures selection. Moreover, the ability of the chosen measures to identify learning is not well established. We aimed to review and categorize the parameters and measures utilized for identification of motor learning in stroke and CP populations. PubMed, Pedro, and Web of Science databases were systematically searched between January 2000 and March 2016 for studies assessing a form of motor learning following upper extremity training using motor control measures. Thirty-two studies in persons after stroke and 10 studies in CP of any methodological quality were included. Identified outcome measures were sorted into two categories, “parameters,” defined as identifying a form of learning, and “measures,” as tools measuring the parameter. Review's results were organized as a narrative synthesis focusing on the outcome measures. The included studies were heterogeneous in their study designs, parameters and measures. Parameters included adaptation (n = 6), anticipatory control (n = 2), after-effects (n = 3), de-adaptation (n = 4), performance (n = 24), acquisition (n = 8), retention (n = 8), and transfer (n = 14). Despite motor learning theory's emphasis on long-lasting changes and generalization, the majority of studies did not assess the retention and transfer parameters. Underlying measures included kinematic analyses in terms of speed, geometry or both (n = 39), dynamic metrics, measures of accuracy, consistency, and coordination. There is no exclusivity of measures to a specific parameter. Many factors affect task performance and the ability to measure it—necessitating the use of several metrics to examine different features of movement and learning. Motor learning measures' applicability to clinical setting can benefit from a treatment-focused approach, currently lacking. The complexity of motor learning results in various metrics, utilized to assess its occurrence, making it difficult to synthesize findings across studies. Further research is desirable for development of an outcome measures selection algorithm, while considering the quality of such measurements. PMID:28286474

The effects of team-based learning techniques on nursing students’ perception of the psycho-social climate of the classroom

PubMed Central

Koohestani, Hamid Reza; Baghcheghi, Nayereh

2016-01-01

Background: Team-based learning is a structured type of cooperative learning that is becoming increasingly more popular in nursing education. This study compares levels of nursing students’ perception of the psychosocial climate of the classroom between conventional lecture group and team-based learning group. Methods: In a quasi-experimental study with pretest-posttest design 38 nursing students of second year participated. One half of the 16 sessions of cardiovascular disease nursing course sessions was taught by lectures and the second half with team-based learning. The modified college and university classroom environment inventory (CUCEI) was used to measure the perception of classroom environment. This was completed after the final lecture and TBL sessions. Results: Results revealed a significant difference in the mean scores of psycho-social climate for the TBL method (Mean (SD): 179.8(8.27)) versus the mean score for the lecture method (Mean (SD): 154.213.44)). Also, the results showed significant differences between the two groups in the innovation (p<0.001), student cohesiveness (p=0.01), cooperation (p<0.001) and equity (p= 0.03) sub-scales scores (p<0.05). Conclusion: This study provides evidence that team-based learning does have a positive effect on nursing students’ perceptions of their psycho-social climate of the classroom. PMID:28210602

Shared or Integrated: Which Type of Integration is More Effective Improves Students’ Creativity?

NASA Astrophysics Data System (ADS)

Mariyam, M.; Kaniawati, I.; Sriyati, S.

2017-09-01

Integrated science learning has various types of integration. This study aims to apply shared and integrated type of integration with project based learning (PjBL) model to improve students’ creativity on waste recycling theme. The research method used is a quasi experiment with the matching-only pre test-post test design. The samples of this study are 108 students consisting of 36 students (experiment class 1st), 35 students (experiment class 2nd) and 37 students (control class 3rd) at one of Junior High School in Tanggamus, Lampung. The results show that there is difference of creativity improvement in the class applied by PjBL model with shared type of integration, integrated type of integration and without any integration in waste recycling theme. Class applied by PjBL model with shared type of integration has the higher creativity improvement than the PjBL model with integrated type of integration and without any integration. Integrated science learning using shared type only combines 2 lessons, hence an intact concept is resulted. So, PjBL model with shared type of integration more effective improves students’ creativity than integrated type.

Reflections on using a postgraduate educational environment measure.

PubMed

Joiner, Adam B; Dearman, Samuel P

2016-10-01

The aim was to use an educational environment measure to learn more about our postgraduate psychiatry education program, in order to gain further insights into areas for development. The educational environment includes such things as atmosphere and facilities. A secondary aim was to explore if different types of trainees experienced any aspects of the educational environment differently. The education environment measure used was able to reveal areas of the educational environment which trainees did not feel were adequate, as well as differences between how different trainees perceive some aspects of the educational environment. This allowed us to understand where improvements which we had not previously considered should be made to the educational environment. © The Royal Australian and New Zealand College of Psychiatrists 2016.

Impact of Self-Explanation and Analogical Comparison Support on Learning Processes, Motivation, Metacognition, and Transfer

NASA Astrophysics Data System (ADS)

Richey, J. Elizabeth

Research examining analogical comparison and self-explanation has produced a robust set of findings about learning and transfer supported by each instructional technique. However, it is unclear how the types of knowledge generated through each technique differ, which has important implications for cognitive theory as well as instructional practice. I conducted a pair of experiments to directly compare the effects of instructional prompts supporting self-explanation, analogical comparison, and the study of instructional explanations across a number of fine-grained learning process, motivation, metacognition, and transfer measures. Experiment 1 explored these questions using sequence extrapolation problems, and results showed no differences between self-explanation and analogical comparison support conditions on any measure. Experiment 2 explored the same questions in a science domain. I evaluated condition effects on transfer outcomes; self-reported self-explanation, analogical comparison, and metacognitive processes; and achievement goals. I also examined relations between transfer and self-reported processes and goals. Receiving materials with analogical comparison support and reporting greater levels of analogical comparison were both associated with worse transfer performance, while reporting greater levels of self-explanation was associated with better performance. Learners' self-reports of self-explanation and analogical comparison were not related to condition assignment, suggesting that the questionnaires did not measure the same processes promoted by the intervention, or that individual differences in processing are robust even when learners are instructed to engage in self-explanation or analogical comparison.

Visual-spatial learning impairments are associated with hippocampal PSD-95 protein dysregulation in a mouse model of fragile X syndrome.

PubMed

Gandhi, Réno M; Kogan, Cary S; Messier, Claude; Macleod, Lindsey S

2014-03-05

Fragile X syndrome is the most common cause of inherited intellectual disability and is caused by the lack of fragile X mental retardation protein (FMRP) expression. In-vitro findings in mice and post-mortem autopsies in humans are characterized by dendritic spine abnormalities in the absence of Fmrp/FMRP. Biochemical and electrophysiological studies have identified postsynaptic density protein (PSD)-95 as having an established role in dendritic morphology as well as a molecular target of Fmrp. How Fmrp affects the expression of PSD-95 following behavioral learning is unknown. In the current study, wild type controls and Fmr1 knockout mice were trained in a subset of the Hebb-Williams (H-W) mazes. Dorsal hippocampal PSD-95 protein levels relative to a stable cytoskeleton protein (β-tubulin) were measured. We report a significant upregulation of PSD-95 protein levels in wild type mice, whereas training-related protein increases were blunted in Fmr1 knockout mice. In addition, there was a significant negative correlation between mean total errors on the mazes and PSD-95 protein levels. The coefficient of determination indicated that the mean total errors on the H-W mazes accounted for 35% of the variance in PSD-95 protein levels. These novel findings suggest that reduced PSD-95-associated postsynaptic plasticity may contribute to the learning and memory deficits observed in human fragile X syndrome patients.

Overcoming misconceptions of graph interpretation of kinematics motion using calculator based rangers

NASA Astrophysics Data System (ADS)

Olson, John R.

This is a quasi-experimental study of 261 first year high school students that analyzes gains made through the use of calculator based rangers attached to calculators. The study has qualitative components but is based on quantitative tests. Biechner's TUG-K test was used for the pretest, posttest, and post-posttest. The population was divided into one group that predicted the results before using the CBRs and another that did not predict first but completed the same activities. The data for the groups was further disaggregated into learning style groups (based on Kolb's Learning Styles Inventory), type of class (advanced vs. general physics), and gender. Four instructors used the labs developed by the author for this study and created significant differences between the groups by instructor based on interviews, participant observation and one way ANOVA. No significant differences were found between learning styles based on MANOVA. No significant differences were found between predict and nonpredict groups for the one way ANOVAs or MANOVA, however, some differences do exist as measured by a survey and participant observation. Significant differences do exist between gender and type of class (advanced/general) based on one way ANOVA and MANOVA. The males outscored the females on all tests and the advanced physics scored higher than the general physics on all tests. The advanced physics scoring higher was expected but the difference between genders was not.

Model-Free Machine Learning in Biomedicine: Feasibility Study in Type 1 Diabetes

PubMed Central

Daskalaki, Elena; Diem, Peter; Mougiakakou, Stavroula G.

2016-01-01

Although reinforcement learning (RL) is suitable for highly uncertain systems, the applicability of this class of algorithms to medical treatment may be limited by the patient variability which dictates individualised tuning for their usually multiple algorithmic parameters. This study explores the feasibility of RL in the framework of artificial pancreas development for type 1 diabetes (T1D). In this approach, an Actor-Critic (AC) learning algorithm is designed and developed for the optimisation of insulin infusion for personalised glucose regulation. AC optimises the daily basal insulin rate and insulin:carbohydrate ratio for each patient, on the basis of his/her measured glucose profile. Automatic, personalised tuning of AC is based on the estimation of information transfer (IT) from insulin to glucose signals. Insulin-to-glucose IT is linked to patient-specific characteristics related to total daily insulin needs and insulin sensitivity (SI). The AC algorithm is evaluated using an FDA-accepted T1D simulator on a large patient database under a complex meal protocol, meal uncertainty and diurnal SI variation. The results showed that 95.66% of time was spent in normoglycaemia in the presence of meal uncertainty and 93.02% when meal uncertainty and SI variation were simultaneously considered. The time spent in hypoglycaemia was 0.27% in both cases. The novel tuning method reduced the risk of severe hypoglycaemia, especially in patients with low SI. PMID:27441367

An Efficacious Measurement of Learning Initiatives: E-Learning Systems, Learning-Organization Culture, Knowledge Creation, and Innovativeness

ERIC Educational Resources Information Center

Grundhoefer, Raymie

2013-01-01

The purpose of this research is twofold: (a) develop a validated measure for learning initiatives based on knowledge-creation theory and (b) conduct a quantitative study to investigate the relationships between electronic learning systems, learning-organization culture, efficacious knowledge creation (EKC), and innovativeness. Although Cheng-Chang…

Do we face a fourth paradigm shift in medicine--algorithms in education?

PubMed

Eitel, F; Kanz, K G; Hortig, E; Tesche, A

2000-08-01

Medicine has evolved toward rationalization since the Enlightenment, favouring quantitative measures. Now, a paradigm shift toward control through formalization can be observed in health care whose structures and processes are subjected to increasing standardization. However, educational reforms and curricula do not yet adequately respond to this shift. The aim of this article is to describe innovative approaches in medical education for adapting to these changes. The study design is a descriptive case report relying on a literature review and on a reform project's evaluation. Concept mapping is used to graphically represent relationships among concepts, i.e. defined terms from educational literature. Definitions of 'concept map', 'guideline' and 'algorithm' are presented. A prototypical algorithm for organizational decision making in the project's instructional design is shown. Evaluation results of intrinsic learning motivation are demonstrated: intrinsic learning motivation depends upon students' perception of their competence exhibiting path coefficients varying from 0.42 to 0.51. Perception of competence varies with the type of learning environment. An innovative educational format, called 'evidence-based learning (EBL)' is deduced from these findings and described here. Effects of formalization consist of structuring decision making about implementation of different learning environments or about minimizing variance in teaching or learning. Unintended effects of formalization such as implementation problems and bureaucracy are discussed. Formalized tools for designing medical education are available. Specific instructional designs influence students' learning motivation. Concept maps are suitable for controlling educational quality, thus enabling the paradigm shift in medical education.