Evaluating Online Resources in Terms of Learning Environment and Student Attitudes in Middle-Grade Mathematics Classes

ERIC Educational Resources Information Center

Earle, James E.; Fraser, Barry J.

2017-01-01

The main objective of this research was to use learning environment and attitude scales in evaluating online resource materials for supporting a traditional mathematics curriculum. The sample consisted of 914 middle-school students in 49 classes. A second research focus was the validation of the chosen learning environment questionnaire, the…

Incremental concept learning with few training examples and hierarchical classification

NASA Astrophysics Data System (ADS)

Bouma, Henri; Eendebak, Pieter T.; Schutte, Klamer; Azzopardi, George; Burghouts, Gertjan J.

2015-10-01

Object recognition and localization are important to automatically interpret video and allow better querying on its content. We propose a method for object localization that learns incrementally and addresses four key aspects. Firstly, we show that for certain applications, recognition is feasible with only a few training samples. Secondly, we show that novel objects can be added incrementally without retraining existing objects, which is important for fast interaction. Thirdly, we show that an unbalanced number of positive training samples leads to biased classifier scores that can be corrected by modifying weights. Fourthly, we show that the detector performance can deteriorate due to hard-negative mining for similar or closely related classes (e.g., for Barbie and dress, because the doll is wearing a dress). This can be solved by our hierarchical classification. We introduce a new dataset, which we call TOSO, and use it to demonstrate the effectiveness of the proposed method for the localization and recognition of multiple objects in images.

An Assessment of Service-Learning in 34 US Schools of Pharmacy Follow Up on the 2001 Professional Affairs Committee Report

PubMed Central

Schlesselman, Lauren; Borrego, Matthew; Mehta, Bella; Drobitch, Robert K.; Smith, Thomas

2015-01-01

Objective. To determine if the service-learning components used at a convenience sample of schools and colleges of pharmacy meet the intent of the 2001 AACP Professional Affairs Committee (PAC) report. Methods. An online questionnaire was used to survey faculty members or staff involved with service-learning education at their school of pharmacy. Questions addressed aspects of service-learning including types of activities used, duration of student involvement with community partners, and association of learning objectives with service-learning activities. Results. The majority (85.3%) of respondents reported their institution used service-learning. Activities reported as part of service-learning ranged from working at health fairs to involvement with pharmacy school recruitment. More than half (64.3%) of service-learning activities involved long-term interactions with one community partner, and 74.1% of respondents indicated there was always an opportunity for student reflection on the service-learning activity. Conclusion. There is increasing though inconsistent application of PAC guidelines regarding service-learning. PMID:26688584

Visual object tracking by correlation filters and online learning

NASA Astrophysics Data System (ADS)

Zhang, Xin; Xia, Gui-Song; Lu, Qikai; Shen, Weiming; Zhang, Liangpei

2018-06-01

Due to the complexity of background scenarios and the variation of target appearance, it is difficult to achieve high accuracy and fast speed for object tracking. Currently, correlation filters based trackers (CFTs) show promising performance in object tracking. The CFTs estimate the target's position by correlation filters with different kinds of features. However, most of CFTs can hardly re-detect the target in the case of long-term tracking drifts. In this paper, a feature integration object tracker named correlation filters and online learning (CFOL) is proposed. CFOL estimates the target's position and its corresponding correlation score using the same discriminative correlation filter with multi-features. To reduce tracking drifts, a new sampling and updating strategy for online learning is proposed. Experiments conducted on 51 image sequences demonstrate that the proposed algorithm is superior to the state-of-the-art approaches.

Incrementally learning objects by touch: online discriminative and generative models for tactile-based recognition.

PubMed

Soh, Harold; Demiris, Yiannis

2014-01-01

Human beings not only possess the remarkable ability to distinguish objects through tactile feedback but are further able to improve upon recognition competence through experience. In this work, we explore tactile-based object recognition with learners capable of incremental learning. Using the sparse online infinite Echo-State Gaussian process (OIESGP), we propose and compare two novel discriminative and generative tactile learners that produce probability distributions over objects during object grasping/palpation. To enable iterative improvement, our online methods incorporate training samples as they become available. We also describe incremental unsupervised learning mechanisms, based on novelty scores and extreme value theory, when teacher labels are not available. We present experimental results for both supervised and unsupervised learning tasks using the iCub humanoid, with tactile sensors on its five-fingered anthropomorphic hand, and 10 different object classes. Our classifiers perform comparably to state-of-the-art methods (C4.5 and SVM classifiers) and findings indicate that tactile signals are highly relevant for making accurate object classifications. We also show that accurate "early" classifications are possible using only 20-30 percent of the grasp sequence. For unsupervised learning, our methods generate high quality clusterings relative to the widely-used sequential k-means and self-organising map (SOM), and we present analyses into the differences between the approaches.

Learning style and concept acquisition of community college students in introductory biology

NASA Astrophysics Data System (ADS)

Bobick, Sandra Burin

This study investigated the influence of learning style on concept acquisition within a sample of community college students in a general biology course. There are two subproblems within the larger problem: (1) the influence of demographic variables (age, gender, number of college credits, prior exposure to scientific information) on learning style, and (2) the correlations between prior scientific knowledge, learning style and student understanding of the concept of the gene. The sample included all students enrolled in an introductory general biology course during two consecutive semesters at an urban community college. Initial data was gathered during the first week of the semester, at which time students filled in a short questionnaire (age, gender, number of college credits, prior exposure to science information either through reading/visual sources or a prior biology course). Subjects were then given the Inventory of Learning Processes-Revised (ILP-R) which measures general preferences in five learning styles; Deep Learning; Elaborative Learning, Agentic Learning, Methodical Learning and Literal Memorization. Subjects were then given the Gene Conceptual Knowledge pretest: a 15 question objective section and an essay section. Subjects were exposed to specific concepts during lecture and laboratory exercises. At the last lab, students were given the Genetics Conceptual Knowledge Posttest. Pretest/posttest gains were correlated with demographic variables and learning styles were analyzed for significant correlations. Learning styles, as the independent variable in a simultaneous multiple regression, were significant predictors of results on the gene assessment tests, including pretest, posttest and gain. Of the learning styles, Deep Learning accounted for the greatest positive predictive value of pretest essay and pretest objective results. Literal Memorization was a significant negative predictor for posttest essay, essay gain and objective gain. Simultaneous multiple regression indicated that demographic variables were significant positive predictors for Methodical, Deep and Elaborative Learning Styles. Stepwise multiple regression resulted in number of credits, Read Science and gender (female) as significant predictors of learning styles. The findings of this study emphasize the importance of learning styles in conceptual understanding of the gene and the correlation of nonformal exposure to science information with learning style and conceptual understanding.

Tracking of multiple targets using online learning for reference model adaptation.

PubMed

Pernkopf, Franz

2008-12-01

Recently, much work has been done in multiple object tracking on the one hand and on reference model adaptation for a single-object tracker on the other side. In this paper, we do both tracking of multiple objects (faces of people) in a meeting scenario and online learning to incrementally update the models of the tracked objects to account for appearance changes during tracking. Additionally, we automatically initialize and terminate tracking of individual objects based on low-level features, i.e., face color, face size, and object movement. Many methods unlike our approach assume that the target region has been initialized by hand in the first frame. For tracking, a particle filter is incorporated to propagate sample distributions over time. We discuss the close relationship between our implemented tracker based on particle filters and genetic algorithms. Numerous experiments on meeting data demonstrate the capabilities of our tracking approach. Additionally, we provide an empirical verification of the reference model learning during tracking of indoor and outdoor scenes which supports a more robust tracking. Therefore, we report the average of the standard deviation of the trajectories over numerous tracking runs depending on the learning rate.

Secondary Social Studies: Alaska Curriculum Guide. Second Edition.

ERIC Educational Resources Information Center

Alaska State Dept. of Education, Juneau. Office of Curriculum Services.

A secondary social studies model curriculum guide for Alaska is presented. The body of the guide lists topics/concepts, learning outcomes/objectives, and sample learning activities in a 3 column format. The first column, topics/concepts, describes the content area, defining the subject broadly and listing subconcepts or associated vocabulary. The…

Pharmacists' Perceptions of Facilitators and Barriers to Lifelong Learning

PubMed Central

Bruskiewitz, Ruth H.; DeMuth, James E.

2007-01-01

Objectives To reevaluate facilitators of and barriers to pharmacists' participation in lifelong learning previously examined in a 1990 study. Methods A survey instrument was mailed to 274 pharmacists who volunteered to participate based on a prior random sample survey. Data based on perceptions of facilitators and barriers to lifelong learning, as well as self-perception as a lifelong learner, were analyzed and compared to a similar 1990 survey. Results The response rate for the survey was 88%. The top 3 facilitators and barriers to lifelong learning from the 2003 and the 1990 samples were: (1) personal desire to learn; (2) requirement to maintain professional licensure; and (3) enjoyment/relaxation provided by learning as change of pace from the “routine.” The top 3 barriers were: (1) job constraints; (2) scheduling (location, distance, time) of group learning activities; and (3) family constraints (eg, spouse, children, personal). Respondents' broad self-perception as lifelong learners continued to be highly positive overall, but remained less positive relative to more specific lifelong learning skills such as the ability to identify learning objectives as well as to evaluate learning outcomes. Conclusions Little has changed in the last decade relative to how pharmacists view themselves as lifelong learners, as well as what they perceive as facilitators and barriers to lifelong learning. To address factors identified as facilitators and barriers, continuing education (CE) providers should focus on pharmacists' time constraints, whether due to employment, family responsibilities, or time invested in the educational activity itself, and pharmacists' internal motivations to learn (personal desire, enjoyment), as well as external forces such as mandatory CE for relicensure. PMID:17786254

Learning, Attention/Hyperactivity, and Conduct Problems as Sequelae of Excessive Daytime Sleepiness in a General Population Study of Young Children

PubMed Central

Calhoun, Susan L.; Fernandez-Mendoza, Julio; Vgontzas, Alexandros N.; Mayes, Susan D.; Tsaoussoglou, Marina; Rodriguez-Muñoz, Alfredo; Bixler, Edward O.

2012-01-01

Study Objectives: Although excessive daytime sleepiness (EDS) is a common problem in children, with estimates of 15%; few studies have investigated the sequelae of EDS in young children. We investigated the association of EDS with objective neurocognitive measures and parent reported learning, attention/hyperactivity, and conduct problems in a large general population sample of children. Design: Cross-sectional. Setting: Population based. Participants: 508 children from The Penn State Child Cohort. Interventions: N/A. Measurements and Results: Children underwent a 9-h polysomnogram, comprehensive neurocognitive testing, and parent rating scales. Children were divided into 2 groups: those with and without parent-reported EDS. Structural equation modeling was used to examine whether processing speed and working memory performance would mediate the relationship between EDS and learning, attention/hyperactivity, and conduct problems. Logistic regression models suggest that parent-reported learning, attention/hyperactivity, and conduct problems, as well as objective measurement of processing speed and working memory are significant sequelae of EDS, even when controlling for AHI and objective markers of sleep. Path analysis demonstrates that processing speed and working memory performance are strong mediators of the association of EDS with learning and attention/hyperactivity problems, while to a slightly lesser degree are mediators from EDS to conduct problems. Conclusions: This study suggests that in a large general population sample of young children, parent-reported EDS is associated with neurobehavioral (learning, attention/hyperactivity, conduct) problems and poorer performance in processing speed and working memory. Impairment due to EDS in daytime cognitive and behavioral functioning can have a significant impact on children's development. Citation: Calhoun SL; Fernandez-Mendoza J; Vgontzas AN; Mayes SD; Tsaoussoglou M; Rodriguez-Muñoz A; Bixler EO. Learning, attention/hyperactivity, and conduct problems as sequelae of excessive daytime sleepiness in a general population study of young children. SLEEP 2012;35(5):627-632. PMID:22547888

Instructional Objectives for Junior College Courses in Economics: Principles of Macroeconomics and Principles of Microeconomics.

ERIC Educational Resources Information Center

Thompson, Fred A.

These sets of behavioral objectives for junior college economics courses were written to serve as a guide to instruction, a student guide to learning, and a basis for evaluation. The objectives are offered as samples that may be used where they correspond to the skills, abilities, and attitudes other instructors want their students to acquire.…

Using Blended Learning for Enhancing EFL Prospective Teachers' Pedagogical Knowledge and Performance

ERIC Educational Resources Information Center

Badawi, Mohamed Farrag

2009-01-01

The basic objective of the present study is to investigate the effectiveness of using blended learning model in developing EFL prospective teachers' pedagogical knowledge and performance. The study sample included 38 EFL Saudi prospective teachers (fourth-year students) at the Faculty of Education & Arts, University of Tabuk, KSA. To collect…

Longitudinal Models of Reading Achievement of Students with Learning Disabilities and without Disabilities

ERIC Educational Resources Information Center

Sullivan, Amanda L.; Kohli, Nidhi; Farnsworth, Elyse M.; Sadeh, Shanna; Jones, Leila

2017-01-01

Objective: Accurate estimation of developmental trajectories can inform instruction and intervention. We compared the fit of linear, quadratic, and piecewise mixed-effects models of reading development among students with learning disabilities relative to their typically developing peers. Method: We drew an analytic sample of 1,990 students from…

How Does Early Feedback in an Online Programming Course Change Problem Solving?

ERIC Educational Resources Information Center

Ebrahimi, Alireza

2012-01-01

How does early feedback change the programming problem solving in an online environment and help students choose correct approaches? This study was conducted in a sample of students learning programming in an online course entitled Introduction to C++ and OOP (Object Oriented Programming) using the ANGEL learning management system platform. My…

Using the Technique of Journal Writing to Learn Emergency Psychiatry

ERIC Educational Resources Information Center

Bhuvaneswar, Chaya; Stern, Theodore; Beresin, Eugene

2009-01-01

Objective: The authors discuss journal writing in learning emergency psychiatry. Methods: The journal of a psychiatry intern rotating through an emergency department is used as sample material for analysis that could take place in supervision or a resident support group. A range of articles are reviewed that illuminate the relevance of journal…

Learning Efficiency of Two ICT-Based Instructional Strategies in Greek Sheep Farmers

ERIC Educational Resources Information Center

Bellos, Georgios; Mikropoulos, Tassos A.; Deligeorgis, Stylianos; Kominakis, Antonis

2016-01-01

Purpose: The objective of the present study was to compare the learning efficiency of two information and communications technology (ICT)-based instructional strategies (multimedia presentation (MP) and concept mapping) in a sample (n = 187) of Greek sheep farmers operating mainly in Western Greece. Design/methodology/approach: In total, 15…

Landscape-scale carbon sampling strategy-lessons learned. Chapter 17

Treesearch

John B. Bradford; Peter Weishampel; Marie-Louise Smith; Randall Kolka; David Y. Hollinger; Richard A. Birdsey; Scott Ollinger; Michael Ryan

2008-01-01

Previous chapters examined individual processes relevant to forest carbon cycling, and characterized measurement approaches for understanding those processes at landscape scales. In this final chapter, we address our overall approach to understanding forest carbon dynamics over large areas. Our objective is to identify any lessons that we learned in the course of...

Applying active learning to supervised word sense disambiguation in MEDLINE

PubMed Central

Chen, Yukun; Cao, Hongxin; Mei, Qiaozhu; Zheng, Kai; Xu, Hua

2013-01-01

Objectives This study was to assess whether active learning strategies can be integrated with supervised word sense disambiguation (WSD) methods, thus reducing the number of annotated samples, while keeping or improving the quality of disambiguation models. Methods We developed support vector machine (SVM) classifiers to disambiguate 197 ambiguous terms and abbreviations in the MSH WSD collection. Three different uncertainty sampling-based active learning algorithms were implemented with the SVM classifiers and were compared with a passive learner (PL) based on random sampling. For each ambiguous term and each learning algorithm, a learning curve that plots the accuracy computed from the test set as a function of the number of annotated samples used in the model was generated. The area under the learning curve (ALC) was used as the primary metric for evaluation. Results Our experiments demonstrated that active learners (ALs) significantly outperformed the PL, showing better performance for 177 out of 197 (89.8%) WSD tasks. Further analysis showed that to achieve an average accuracy of 90%, the PL needed 38 annotated samples, while the ALs needed only 24, a 37% reduction in annotation effort. Moreover, we analyzed cases where active learning algorithms did not achieve superior performance and identified three causes: (1) poor models in the early learning stage; (2) easy WSD cases; and (3) difficult WSD cases, which provide useful insight for future improvements. Conclusions This study demonstrated that integrating active learning strategies with supervised WSD methods could effectively reduce annotation cost and improve the disambiguation models. PMID:23364851

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.

Age Matters: Student Experiences with Audio Learning Guides in University-Based Continuing Education

ERIC Educational Resources Information Center

Mercer, Lorraine; Pianosi, Birgit

2012-01-01

The primary objective of this research was to explore the experiences of undergraduate distance education students using sample audio versions (provided on compact disc) of the learning guides for their courses. The results of this study indicated that students responded positively to the opportunity to have word-for-word audio versions of their…

Trainee Teachers' Conceptions of Teaching and Learning, Classroom Layout and Exam Design

ERIC Educational Resources Information Center

Betoret, Fernando Domenech; Artiga, Amparo Gomez

2004-01-01

The objective of this study centres on identifying and classifying the conceptions of teaching and learning held by future secondary school teachers, and on analysing the relationship between these conceptions and the way classroom space is organized and exams are designed. The test instruments used were applied to a sample of 138 graduates, who…

Difficulties in Academic Writing: From the Perspective of King Saud University Postgraduate Students

ERIC Educational Resources Information Center

Al Fadda, Hind

2012-01-01

The purpose of this study was to determine what difficulties King Saud University students encounter when learning to write academic English and to differentiate between students' learning needs and objectives. The sample consisted of 50 postgraduate students enrolled in King Saud University during the academic year 2009-2010. Analysis of the data…

Relationship between Learning Problems and Attention Deficit in Childhood

ERIC Educational Resources Information Center

Ponde, Milena Pereira; Cruz-Freire, Antonio Carlos; Silveira, Andre Almeida

2012-01-01

Objective: To assess the impact of attention deficit on learning problems in a sample of schoolchildren in the city of Salvador, Bahia, Brazil. Method: All students enrolled in selected elementary schools were included in this study, making a total of 774 children. Each child was assessed by his or her teacher using a standardized scale. "The…

Identification and Comparison of Academic Self Regulatory Learning Strategy Use of Students Enrolled in Traditional and Accelerated Baccalaureate Degree Nursing Programs

ERIC Educational Resources Information Center

Mullen, Patricia A.

2009-01-01

Objective: To explore and compare the use of metacognitive, cognitive, and environmental resource management self regulatory learning (SRL) strategies used by a national sample of students enrolled in traditional and accelerated baccalaureate nursing programs. Background: Learner focused reforms in nursing education require students to assume more…

Academic Performance in ADHD when Controlled for Comorbid Learning Disorders, Family Income, and Parental Education in Brazil

ERIC Educational Resources Information Center

Carmine Pastura, Giuseppe Mario; Mattos, Paulo; Campos Araujo, Alexandra Prufer de Queiroz

2009-01-01

Objective: Scholastic achievement in a nonclinical sample of ADHD children and adolescents was evaluated taking into consideration variables such as comorbid learning disorders, family income, and parental education which may also be associated with poor academic performance. Method: After screening for ADHD in 396 students, the authors compared…

Biologically Inspired Model for Visual Cognition Achieving Unsupervised Episodic and Semantic Feature Learning.

PubMed

Qiao, Hong; Li, Yinlin; Li, Fengfu; Xi, Xuanyang; Wu, Wei

2016-10-01

Recently, many biologically inspired visual computational models have been proposed. The design of these models follows the related biological mechanisms and structures, and these models provide new solutions for visual recognition tasks. In this paper, based on the recent biological evidence, we propose a framework to mimic the active and dynamic learning and recognition process of the primate visual cortex. From principle point of view, the main contributions are that the framework can achieve unsupervised learning of episodic features (including key components and their spatial relations) and semantic features (semantic descriptions of the key components), which support higher level cognition of an object. From performance point of view, the advantages of the framework are as follows: 1) learning episodic features without supervision-for a class of objects without a prior knowledge, the key components, their spatial relations and cover regions can be learned automatically through a deep neural network (DNN); 2) learning semantic features based on episodic features-within the cover regions of the key components, the semantic geometrical values of these components can be computed based on contour detection; 3) forming the general knowledge of a class of objects-the general knowledge of a class of objects can be formed, mainly including the key components, their spatial relations and average semantic values, which is a concise description of the class; and 4) achieving higher level cognition and dynamic updating-for a test image, the model can achieve classification and subclass semantic descriptions. And the test samples with high confidence are selected to dynamically update the whole model. Experiments are conducted on face images, and a good performance is achieved in each layer of the DNN and the semantic description learning process. Furthermore, the model can be generalized to recognition tasks of other objects with learning ability.

Student nurses' learning on community-based education in Ethiopia.

PubMed

Salmon, Karen; Keneni, Gutema

2004-07-01

At Jimma University educational goals are to apply the concept of community-oriented education through community-based education (CBE) of health students. This study examined the experiences of student nurses on CBE. The aims of the study were to identify factors that students considered had helped or hindered their learning on CBE and to ascertain if the stated learning objectives were met. A quantitative, descriptive, survey design was adopted, using a single, anonymous questionnaire. Some qualitative data were gained using open questions. A convenience sample of 95 students participated in the research. Participants represented 90% of all students who had completed their CBE placements. Participation, mentors' willingness to answer questions and the relevance of the placement were factors that facilitated learning. Factors reported by students that hindered learning were difficulties of self-expression in a group, mentors emphasising mistakes and weakness and the short time-frame due to ongoing lectures during placement. Students said learning objectives most met were socio-demographic assessment, identifying health problems and action planning. Objectives reported to be least met were identifying environmental health problems, planning preventive health interventions and implementing health interventions. These include the need to develop students' group skills, prepare mentors to facilitate learning, organise CBE in spiral phases, avoid concurrent lectures and improve study facilities.

Intelligent Detection of Structure from Remote Sensing Images Based on Deep Learning Method

NASA Astrophysics Data System (ADS)

Xin, L.

2018-04-01

Utilizing high-resolution remote sensing images for earth observation has become the common method of land use monitoring. It requires great human participation when dealing with traditional image interpretation, which is inefficient and difficult to guarantee the accuracy. At present, the artificial intelligent method such as deep learning has a large number of advantages in the aspect of image recognition. By means of a large amount of remote sensing image samples and deep neural network models, we can rapidly decipher the objects of interest such as buildings, etc. Whether in terms of efficiency or accuracy, deep learning method is more preponderant. This paper explains the research of deep learning method by a great mount of remote sensing image samples and verifies the feasibility of building extraction via experiments.

Learning Progress in Evolution Theory: Climbing a Ladder or Roaming a Landscape?

ERIC Educational Resources Information Center

Zabel, Jorg; Gropengiesser, Harald

2011-01-01

The objective of this naturalistic study was to explore, model and visualise the learning progress of 13-year-old students in the domain of evolution theory. Data were collected under actual classroom conditions and with a sample size of 107 learners, which followed a teaching unit on Darwin's theory of natural selection. Before and after the…

Comparison of sampling strategies for object-based classification of urban vegetation from Very High Resolution satellite images

NASA Astrophysics Data System (ADS)

Rougier, Simon; Puissant, Anne; Stumpf, André; Lachiche, Nicolas

2016-09-01

Vegetation monitoring is becoming a major issue in the urban environment due to the services they procure and necessitates an accurate and up to date mapping. Very High Resolution satellite images enable a detailed mapping of the urban tree and herbaceous vegetation. Several supervised classifications with statistical learning techniques have provided good results for the detection of urban vegetation but necessitate a large amount of training data. In this context, this study proposes to investigate the performances of different sampling strategies in order to reduce the number of examples needed. Two windows based active learning algorithms from state-of-art are compared to a classical stratified random sampling and a third combining active learning and stratified strategies is proposed. The efficiency of these strategies is evaluated on two medium size French cities, Strasbourg and Rennes, associated to different datasets. Results demonstrate that classical stratified random sampling can in some cases be just as effective as active learning methods and that it should be used more frequently to evaluate new active learning methods. Moreover, the active learning strategies proposed in this work enables to reduce the computational runtime by selecting multiple windows at each iteration without increasing the number of windows needed.

Multi-objects recognition for distributed intelligent sensor networks

NASA Astrophysics Data System (ADS)

He, Haibo; Chen, Sheng; Cao, Yuan; Desai, Sachi; Hohil, Myron E.

2008-04-01

This paper proposes an innovative approach for multi-objects recognition for homeland security and defense based intelligent sensor networks. Unlike the conventional way of information analysis, data mining in such networks is typically characterized with high information ambiguity/uncertainty, data redundancy, high dimensionality and real-time constrains. Furthermore, since a typical military based network normally includes multiple mobile sensor platforms, ground forces, fortified tanks, combat flights, and other resources, it is critical to develop intelligent data mining approaches to fuse different information resources to understand dynamic environments, to support decision making processes, and finally to achieve the goals. This paper aims to address these issues with a focus on multi-objects recognition. Instead of classifying a single object as in the traditional image classification problems, the proposed method can automatically learn multiple objectives simultaneously. Image segmentation techniques are used to identify the interesting regions in the field, which correspond to multiple objects such as soldiers or tanks. Since different objects will come with different feature sizes, we propose a feature scaling method to represent each object in the same number of dimensions. This is achieved by linear/nonlinear scaling and sampling techniques. Finally, support vector machine (SVM) based learning algorithms are developed to learn and build the associations for different objects, and such knowledge will be adaptively accumulated for objects recognition in the testing stage. We test the effectiveness of proposed method in different simulated military environments.

Detecting and preventing error propagation via competitive learning.

PubMed

Silva, Thiago Christiano; Zhao, Liang

2013-05-01

Semisupervised learning is a machine learning approach which is able to employ both labeled and unlabeled samples in the training process. It is an important mechanism for autonomous systems due to the ability of exploiting the already acquired information and for exploring the new knowledge in the learning space at the same time. In these cases, the reliability of the labels is a crucial factor, because mislabeled samples may propagate wrong labels to a portion of or even the entire data set. This paper has the objective of addressing the error propagation problem originated by these mislabeled samples by presenting a mechanism embedded in a network-based (graph-based) semisupervised learning method. Such a procedure is based on a combined random-preferential walk of particles in a network constructed from the input data set. The particles of the same class cooperate among them, while the particles of different classes compete with each other to propagate class labels to the whole network. Computer simulations conducted on synthetic and real-world data sets reveal the effectiveness of the model. Copyright © 2012 Elsevier Ltd. All rights reserved.

Marginal Space Deep Learning: Efficient Architecture for Volumetric Image Parsing.

PubMed

Ghesu, Florin C; Krubasik, Edward; Georgescu, Bogdan; Singh, Vivek; Yefeng Zheng; Hornegger, Joachim; Comaniciu, Dorin

2016-05-01

Robust and fast solutions for anatomical object detection and segmentation support the entire clinical workflow from diagnosis, patient stratification, therapy planning, intervention and follow-up. Current state-of-the-art techniques for parsing volumetric medical image data are typically based on machine learning methods that exploit large annotated image databases. Two main challenges need to be addressed, these are the efficiency in scanning high-dimensional parametric spaces and the need for representative image features which require significant efforts of manual engineering. We propose a pipeline for object detection and segmentation in the context of volumetric image parsing, solving a two-step learning problem: anatomical pose estimation and boundary delineation. For this task we introduce Marginal Space Deep Learning (MSDL), a novel framework exploiting both the strengths of efficient object parametrization in hierarchical marginal spaces and the automated feature design of Deep Learning (DL) network architectures. In the 3D context, the application of deep learning systems is limited by the very high complexity of the parametrization. More specifically 9 parameters are necessary to describe a restricted affine transformation in 3D, resulting in a prohibitive amount of billions of scanning hypotheses. The mechanism of marginal space learning provides excellent run-time performance by learning classifiers in clustered, high-probability regions in spaces of gradually increasing dimensionality. To further increase computational efficiency and robustness, in our system we learn sparse adaptive data sampling patterns that automatically capture the structure of the input. Given the object localization, we propose a DL-based active shape model to estimate the non-rigid object boundary. Experimental results are presented on the aortic valve in ultrasound using an extensive dataset of 2891 volumes from 869 patients, showing significant improvements of up to 45.2% over the state-of-the-art. To our knowledge, this is the first successful demonstration of the DL potential to detection and segmentation in full 3D data with parametrized representations.

Perception of medical undergraduate students about interactive lectures in an outcome-based integrated curriculum: A cross-sectional study

PubMed Central

Asad, Mohammad Rehan; Amir, Khwaja; Tadvi, Naser Ashraf; Afzal, Kamran; Sami, Waqas; Irfan, Abdul

2017-01-01

OBJECTIVE: The objective of this study is to explore the student's perspectives toward the interactive lectures as a teaching and learning method in an integrated curriculum. MATERIALS AND METHODS: This cross-sectional study was conducted among 1st, 2nd and 3rd year male medical students (n = 121). A self-administered questionnaire based on the Visual, Auditory, Reader, Kinesthetic learning styles, learning theories, and role of feedback in teaching and learning on five-point Likert rating scale was used. The questionnaire was constructed after extensive literature review. RESULTS: There was an 80% response rate in this study. The total number of undergraduate medical students responded in the study were n = 97, 34 students of 1st year, n = 30 students of 2nd year and n = 33 student were in 3rd year, the mean scores of the student responses were calculated using Independent samples Kruskal–Wallis. There was no significant difference in the responses of the students of different years except for the question “The Interactive lectures facilitate effective use of learning resources.” Which showed significant difference in the responses of the 3 years students by Independent samples Kruskal–Wallis test. No significant association was found between the year of study and items of the questionnaire except for the same item, “ The Interactive lectures facilitates effective use of learning resources” by Spearman rank correlation test. CONCLUSION: The students perceive interactive lecture as an effective tool for facilitating visual and auditory learning modes, and for achieving curricular strategies. The student find the feedback given during the interactive lectures is effective in modifying learning attitude and enhancing motivation toward learning. PMID:29296601

Learning to explore the structure of kinematic objects in a virtual environment

PubMed Central

Buckmann, Marcus; Gaschler, Robert; Höfer, Sebastian; Loeben, Dennis; Frensch, Peter A.; Brock, Oliver

2015-01-01

The current study tested the quantity and quality of human exploration learning in a virtual environment. Given the everyday experience of humans with physical object exploration, we document substantial practice gains in the time, force, and number of actions needed to classify the structure of virtual chains, marking the joints as revolute, prismatic, or rigid. In line with current work on skill acquisition, participants could generalize the new and efficient psychomotor patterns of object exploration to novel objects. On the one hand, practice gains in exploration performance could be captured by a negative exponential practice function. On the other hand, they could be linked to strategies and strategy change. After quantifying how much was learned in object exploration and identifying the time course of practice-related gains in exploration efficiency (speed), we identified what was learned. First, we identified strategy components that were associated with efficient (fast) exploration performance: sequential processing, simultaneous use of both hands, low use of pulling rather than pushing, and low use of force. Only the latter was beneficial irrespective of the characteristics of the other strategy components. Second, we therefore characterized efficient exploration behavior by strategies that simultaneously take into account the abovementioned strategy components. We observed that participants maintained a high level of flexibility, sampling from a pool of exploration strategies trading the level of psycho-motoric challenges with exploration speed. We discuss the findings pursuing the aim of advancing intelligent object exploration by combining analytic (object exploration in humans) and synthetic work (object exploration in robots) in the same virtual environment. PMID:25904878

Semi-Supervised Marginal Fisher Analysis for Hyperspectral Image Classification

NASA Astrophysics Data System (ADS)

Huang, H.; Liu, J.; Pan, Y.

2012-07-01

The problem of learning with both labeled and unlabeled examples arises frequently in Hyperspectral image (HSI) classification. While marginal Fisher analysis is a supervised method, which cannot be directly applied for Semi-supervised classification. In this paper, we proposed a novel method, called semi-supervised marginal Fisher analysis (SSMFA), to process HSI of natural scenes, which uses a combination of semi-supervised learning and manifold learning. In SSMFA, a new difference-based optimization objective function with unlabeled samples has been designed. SSMFA preserves the manifold structure of labeled and unlabeled samples in addition to separating labeled samples in different classes from each other. The semi-supervised method has an analytic form of the globally optimal solution, and it can be computed based on eigen decomposition. Classification experiments with a challenging HSI task demonstrate that this method outperforms current state-of-the-art HSI-classification methods.

Sample heterogeneity in unipolar depression as assessed by functional connectivity analyses is dominated by general disease effects.

PubMed

Feder, Stephan; Sundermann, Benedikt; Wersching, Heike; Teuber, Anja; Kugel, Harald; Teismann, Henning; Heindel, Walter; Berger, Klaus; Pfleiderer, Bettina

2017-11-01

Combinations of resting-state fMRI and machine-learning techniques are increasingly employed to develop diagnostic models for mental disorders. However, little is known about the neurobiological heterogeneity of depression and diagnostic machine learning has mainly been tested in homogeneous samples. Our main objective was to explore the inherent structure of a diverse unipolar depression sample. The secondary objective was to assess, if such information can improve diagnostic classification. We analyzed data from 360 patients with unipolar depression and 360 non-depressed population controls, who were subdivided into two independent subsets. Cluster analyses (unsupervised learning) of functional connectivity were used to generate hypotheses about potential patient subgroups from the first subset. The relationship of clusters with demographical and clinical measures was assessed. Subsequently, diagnostic classifiers (supervised learning), which incorporated information about these putative depression subgroups, were trained. Exploratory cluster analyses revealed two weakly separable subgroups of depressed patients. These subgroups differed in the average duration of depression and in the proportion of patients with concurrently severe depression and anxiety symptoms. The diagnostic classification models performed at chance level. It remains unresolved, if subgroups represent distinct biological subtypes, variability of continuous clinical variables or in part an overfitting of sparsely structured data. Functional connectivity in unipolar depression is associated with general disease effects. Cluster analyses provide hypotheses about potential depression subtypes. Diagnostic models did not benefit from this additional information regarding heterogeneity. Copyright © 2017 Elsevier B.V. All rights reserved.

Active Prior Tactile Knowledge Transfer for Learning Tactual Properties of New Objects

PubMed Central

Feng, Di

2018-01-01

Reusing the tactile knowledge of some previously-explored objects (prior objects) helps us to easily recognize the tactual properties of new objects. In this paper, we enable a robotic arm equipped with multi-modal artificial skin, like humans, to actively transfer the prior tactile exploratory action experiences when it learns the detailed physical properties of new objects. These experiences, or prior tactile knowledge, are built by the feature observations that the robot perceives from multiple sensory modalities, when it applies the pressing, sliding, and static contact movements on objects with different action parameters. We call our method Active Prior Tactile Knowledge Transfer (APTKT), and systematically evaluated its performance by several experiments. Results show that the robot improved the discrimination accuracy by around 10% when it used only one training sample with the feature observations of prior objects. By further incorporating the predictions from the observation models of prior objects as auxiliary features, our method improved the discrimination accuracy by over 20%. The results also show that the proposed method is robust against transferring irrelevant prior tactile knowledge (negative knowledge transfer). PMID:29466300

The Effect of Teaching Methods and Learning Styles on Capabilities of Writing Essays on Elementary School's Students in East Jakarta

ERIC Educational Resources Information Center

Wuryani; Yufiarti

2017-01-01

The objective of this research was to discover the effect of teaching methods and learning styles on the student's ability to write essays. This study was conducted in elementary school in East Jakarta. The population of this studies was 3rd-grade elementary school students who study in East Jakarta. Samples were taken with stratified cluster…

Objective detection of apoptosis in rat renal tissue sections using light microscopy and free image analysis software with subsequent machine learning: Detection of apoptosis in renal tissue.

PubMed

Macedo, Nayana Damiani; Buzin, Aline Rodrigues; de Araujo, Isabela Bastos Binotti Abreu; Nogueira, Breno Valentim; de Andrade, Tadeu Uggere; Endringer, Denise Coutinho; Lenz, Dominik

2017-02-01

The current study proposes an automated machine learning approach for the quantification of cells in cell death pathways according to DNA fragmentation. A total of 17 images of kidney histological slide samples from male Wistar rats were used. The slides were photographed using an Axio Zeiss Vert.A1 microscope with a 40x objective lens coupled with an Axio Cam MRC Zeiss camera and Zen 2012 software. The images were analyzed using CellProfiler (version 2.1.1) and CellProfiler Analyst open-source software. Out of the 10,378 objects, 4970 (47,9%) were identified as TUNEL positive, and 5408 (52,1%) were identified as TUNEL negative. On average, the sensitivity and specificity values of the machine learning approach were 0.80 and 0.77, respectively. Image cytometry provides a quantitative analytical alternative to the more traditional qualitative methods more commonly used in studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

ASSOCIATIVE CONCEPT LEARNING IN ANIMALS

PubMed Central

Zentall, Thomas R.; Wasserman, Edward A.; Urcuioli, Peter J.

2014-01-01

Nonhuman animals show evidence for three types of concept learning: perceptual or similarity-based in which objects/stimuli are categorized based on physical similarity; relational in which one object/stimulus is categorized relative to another (e.g., same/different); and associative in which arbitrary stimuli become interchangeable with one another by virtue of a common association with another stimulus, outcome, or response. In this article, we focus on various methods for establishing associative concepts in nonhuman animals and evaluate data documenting the development of associative classes of stimuli. We also examine the nature of the common within-class representation of samples that have been associated with the same reinforced comparison response (i.e., many-to-one matching) by describing manipulations for distinguishing possible representations. Associative concepts provide one foundation for human language such that spoken and written words and the objects they represent become members of a class of interchangeable stimuli. The mechanisms of associative concept learning and the behavioral flexibility it allows, however, are also evident in the adaptive behaviors of animals lacking language. PMID:24170540

Comparison of four machine learning methods for object-oriented change detection in high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Bai, Ting; Sun, Kaimin; Deng, Shiquan; Chen, Yan

2018-03-01

High resolution image change detection is one of the key technologies of remote sensing application, which is of great significance for resource survey, environmental monitoring, fine agriculture, military mapping and battlefield environment detection. In this paper, for high-resolution satellite imagery, Random Forest (RF), Support Vector Machine (SVM), Deep belief network (DBN), and Adaboost models were established to verify the possibility of different machine learning applications in change detection. In order to compare detection accuracy of four machine learning Method, we applied these four machine learning methods for two high-resolution images. The results shows that SVM has higher overall accuracy at small samples compared to RF, Adaboost, and DBN for binary and from-to change detection. With the increase in the number of samples, RF has higher overall accuracy compared to Adaboost, SVM and DBN.

The Write Stuff: Teaching the Introductory Public Relations Writing Course.

ERIC Educational Resources Information Center

King, Cynthia M.

2001-01-01

Outlines an introductory public relations writing course. Presents course topics and objectives, and assignments designed to meet them. Provides a sample grading rubric and evaluates major public relations writing textbooks. Discusses learning and assessment strategies. (SR)

A longitudinal interprofessional simulation curriculum for critical care teams: Exploring successes and challenges.

PubMed

Leclair, Laurie W; Dawson, Mary; Howe, Alison; Hale, Sue; Zelman, Eric; Clouser, Ryan; Garrison, Garth; Allen, Gilman

2018-05-01

Interprofessional care teams are the backbone of intensive care units (ICUs) where severity of illness is high and care requires varied skills and experience. Despite this care model, longitudinal educational programmes for such workplace teams rarely include all professions. In this article, we report findings on the initial assessment and evaluation of an ongoing, longitudinal simulation-based curriculum for interprofessional workplace critical care teams. The study had two independent components, quantitative learner assessment and qualitative curricular evaluation. To assess curriculum effectiveness at meeting learning objectives, participant-reported key learning points identified using a self-assessment tool administered immediately following curricular participation were mapped to session learning objectives. To evaluate the curriculum, we conducted a qualitative study using a phenomenology approach involving purposeful sampling of nine curricular participants undergoing recorded semi-structured interviews. Verbatim transcripts were reviewed by two independent readers to derive themes further subdivided into successes and barriers. Learner self-assessment demonstrated that the majority of learners, across all professions, achieved at least one intended learning objective with senior learners more likely to report team-based objectives and junior learners more likely to report knowledge/practice objectives. Successes identified by curricular evaluation included authentic critical care curricular content, safe learning environment, and team comradery from shared experience. Barriers included unfamiliarity with the simulation environment and clinical coverage for curricular participation. This study suggests that a sustainable interprofessional curriculum for workplace ICU critical care teams can achieve the desired educational impact and effectively deliver authentic simulated work experiences if barriers to educational engagement and participation can be overcome.

Using transfer learning to detect galaxy mergers

NASA Astrophysics Data System (ADS)

Ackermann, Sandro; Schawinksi, Kevin; Zhang, Ce; Weigel, Anna K.; Turp, M. Dennis

2018-05-01

We investigate the use of deep convolutional neural networks (deep CNNs) for automatic visual detection of galaxy mergers. Moreover, we investigate the use of transfer learning in conjunction with CNNs, by retraining networks first trained on pictures of everyday objects. We test the hypothesis that transfer learning is useful for improving classification performance for small training sets. This would make transfer learning useful for finding rare objects in astronomical imaging datasets. We find that these deep learning methods perform significantly better than current state-of-the-art merger detection methods based on nonparametric systems like CAS and GM20. Our method is end-to-end and robust to image noise and distortions; it can be applied directly without image preprocessing. We also find that transfer learning can act as a regulariser in some cases, leading to better overall classification accuracy (p = 0.02). Transfer learning on our full training set leads to a lowered error rate from 0.0381 down to 0.0321, a relative improvement of 15%. Finally, we perform a basic sanity-check by creating a merger sample with our method, and comparing with an already existing, manually created merger catalogue in terms of colour-mass distribution and stellar mass function.

Hoarding behaviors in children with learning disabilities.

PubMed

Testa, Renée; Pantelis, Christos; Fontenelle, Leonardo F

2011-05-01

Our objective was to describe the prevalence, comorbidity, and neuropsychological profiles of children with hoarding and learning disabilities. From 61 children with learning disabilities, 16.4% exhibited hoarding as a major clinical issue. Although children with learning disabilities and hoarding displayed greater rates of obsessive-compulsive disorder (30%) as compared to those with learning disabilities without hoarding (5.9%), the majority of patients belonging to the former group did not display obsessive-compulsive disorder diagnosis. When learning disability patients with hoarding were compared to age-, sex-, and IQ-matched learning disability subjects without hoarding, hoarders exhibited a slower learning curve on word list-learning task. In conclusion, salient hoarding behaviors were found to be relatively common in a sample of children with learning disabilities and not necessarily associated with obsessive-compulsive disorder, supporting its nosological independence. It is unclear whether underlying cognitive features may play a major role in the development of hoarding behaviors in children with learning disabilities.

Predictors of Long-Term Change in Adult Cognitive Performance: Systematic Review and Data from the Northern Finland Birth Cohort 1966.

PubMed

Rannikko, Irina; Jääskeläinen, Erika; Miettunen, Jouko; Ahmed, Anthony O; Veijola, Juha; Remes, Anne M; Murray, Graham K; Husa, Anja P; Järvelin, Marjo-Riitta; Isohanni, Matti; Haapea, Marianne

2016-01-01

Several social life events and challenges have an impact on cognitive development. Our goal was to analyze the predictors of change in cognitive performance in early midlife in a general population sample. Additionally, systematic literature review was performed. The study sample was drawn from the Northern Finland Birth Cohort 1966 at the ages of 34 and 43 years. Primary school performance, sociodemographic factors and body mass index (BMI) were used to predict change in cognitive performance measured by the California Verbal Learning Test, Visual Object Learning Test, and Abstraction Inhibition and Working Memory task. Analyses were weighted by gender and education, and p-values were corrected for multiple comparisons using Benjamini-Hochberg procedure (B-H). Male gender predicted decrease in episodic memory. Poor school marks of practical subjects, having no children, and increase in BMI were associated with decrease in episodic memory, though non-significantly after B-H. Better school marks, and higher occupational class were associated with preserved performance in visual object learning. Higher vocational education predicted preserved performance in visual object learning test, though non-significantly after B-H. Likewise, having children predicted decreased performance in executive functioning but non-significantly after B-H. Adolescent cognitive ability, change in BMI and several sociodemographic factors appear to predict cognitive changes in early midlife. The key advantage of present study is the exploration of possible predictors of change in cognitive performance among general population in the early midlife, a developmental period that has been earlier overlooked.

Service-learning in nursing education: its impact on leadership and social justice.

PubMed

Groh, Carla J; Stallwood, Lynda G; Daniels, John J

2011-01-01

Although studies suggest that service-learning is positive for students, findings reported are primarily qualitative. A convenience sample of 306 senior-level nursing students completed the Service-Learning Self-Evaluation Tool (SLSET) pre- and post-service-learning experience over a six-year span. The constructs measured were leadership skills and social justice. Paired t-tests were calculated. Statistically significant differences were noted between pre- and post-service-learning experience, with students rating themselves higher on leadership and social justice items after the experience. Cronbach's alpha for leadership and social justice were greater than 0.80. Service-learning as an educational methodology that combines community service with academic learning objectives is a viable strategy for facilitating leadership skills and increased awareness of social justice issues in nursing students.

Learning-based stochastic object models for characterizing anatomical variations

NASA Astrophysics Data System (ADS)

Dolly, Steven R.; Lou, Yang; Anastasio, Mark A.; Li, Hua

2018-03-01

It is widely known that the optimization of imaging systems based on objective, task-based measures of image quality via computer-simulation requires the use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in human anatomy within a specified ensemble of patients remains a challenging task. Previously reported numerical anatomic models lack the ability to accurately model inter-patient and inter-organ variations in human anatomy among a broad patient population, mainly because they are established on image data corresponding to a few of patients and individual anatomic organs. This may introduce phantom-specific bias into computer-simulation studies, where the study result is heavily dependent on which phantom is used. In certain applications, however, databases of high-quality volumetric images and organ contours are available that can facilitate this SOM development. In this work, a novel and tractable methodology for learning a SOM and generating numerical phantoms from a set of volumetric training images is developed. The proposed methodology learns geometric attribute distributions (GAD) of human anatomic organs from a broad patient population, which characterize both centroid relationships between neighboring organs and anatomic shape similarity of individual organs among patients. By randomly sampling the learned centroid and shape GADs with the constraints of the respective principal attribute variations learned from the training data, an ensemble of stochastic objects can be created. The randomness in organ shape and position reflects the learned variability of human anatomy. To demonstrate the methodology, a SOM of an adult male pelvis is computed and examples of corresponding numerical phantoms are created.

Advertising Appeal.

ERIC Educational Resources Information Center

Miller, Sandra K.

The individualized learning package for secondary consumer education deals with consumer buying as influenced by advertising. The teacher's section of the package contains a statement of purpose and instructional objectives. Equipment and materials (specific textbooks, audiovisual aids, and sources for sample post-test advertisements) needed for…

Standardization of computer-assisted semen analysis using an e-learning application.

PubMed

Ehlers, J; Behr, M; Bollwein, H; Beyerbach, M; Waberski, D

2011-08-01

Computer-assisted semen analysis (CASA) is primarily used to obtain accurate and objective kinetic sperm measurements. Additionally, AI centers use computer-assessed sperm concentration in the sample as a basis for calculating the number of insemination doses available from a given ejaculate. The reliability of data is often limited and results can vary even when the same CASA systems with identical settings are used. The objective of the present study was to develop a computer-based training module for standardized measurements with a CASA system and to evaluate its training effect on the quality of the assessment of sperm motility and concentration. A digital versatile disc (DVD) has been produced showing the standardization of sample preparation and analysis with the CASA system SpermVision™ version 3.0 (Minitube, Verona, WI, USA) in words, pictures, and videos, as well as the most probable sources of error. Eight test persons educated in spermatology, but with different levels of experience with the CASA system, prepared and assessed 10 aliquots from one prediluted bull ejaculate using the same CASA system and laboratory equipment before and after electronic learning (e-learning). After using the e-learning application, the coefficient of variation was reduced on average for the sperm concentration from 26.1% to 11.3% (P ≤ 0.01), and for motility from 5.8% to 3.1% (P ≤ 0.05). For five test persons, the difference in the coefficient of variation before and after use of the e-learning application was significant (P ≤ 0.05). Individual deviations of means from the group mean before e-learning were reduced compared with individual deviations from the group mean after e-learning. According to a survey, the e-learning application was highly accepted by users. In conclusion, e-learning presents an effective, efficient, and accepted tool for improvement of the precision of CASA measurements. This study provides a model for the standardization of other laboratory procedures using e-learning. Copyright © 2011 Elsevier Inc. All rights reserved.

Accommodation Decision Making for Postsecondary Students With Learning Disabilities: Individually Tailored or One Size Fits All?

PubMed

Weis, Robert; Dean, Emily L; Osborne, Karen J

2016-09-01

Clinicians uniformly recommend accommodations for college students with learning disabilities; however, we know very little about which accommodations they select and the validity of their recommendations. We examined the assessment documentation of a large sample of community college students receiving academic accommodations for learning disabilities to determine (a) which accommodations their clinicians recommended and (b) whether clinicians' recommendations were supported by objective data gathered during the assessment process. In addition to test and instructional accommodations, many clinicians recommended that students with learning disabilities should have different educational expectations, standards, and methods of evaluation (i.e., grading) than their nondisabled classmates. Many of their recommendations for accommodations were not supported by objective evidence from students' history, diagnosis, test data, and current functioning. Furthermore, clinicians often recommended accommodations that were not specific to the student's diagnosis or area of disability. Our findings highlight the need for individually selected accommodations matched to students' needs and academic contexts. © Hammill Institute on Disabilities 2014.

Neural principles of memory and a neural theory of analogical insight

NASA Astrophysics Data System (ADS)

Lawson, David I.; Lawson, Anton E.

1993-12-01

Grossberg's principles of neural modeling are reviewed and extended to provide a neural level theory to explain how analogies greatly increase the rate of learning and can, in fact, make learning and retention possible. In terms of memory, the key point is that the mind is able to recognize and recall when it is able to match sensory input from new objects, events, or situations with past memory records of similar objects, events, or situations. When a match occurs, an adaptive resonance is set up in which the synaptic strengths of neurons are increased; thus a long term record of the new input is formed in memory. Systems of neurons called outstars and instars are presumably the underlying units that enable this to occur. Analogies can greatly facilitate learning and retention because they activate the outstars (i.e., the cells that are sampling the to-be-learned pattern) and cause the neural activity to grow exponentially by forming feedback loops. This increased activity insures the boost in synaptic strengths of neurons, thus causing storage and retention in long-term memory (i.e., learning).

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.)

Aviation and the Community - Measuring the Impact on the Local Economy

ERIC Educational Resources Information Center

Journal of Aerospace Education, 1975

1975-01-01

Gives a sample of a research questionnaire which might be used in a unit which seeks to determine the impact of airports on communities and can serve as learning objectives for a unit on the importance of the airport. (BR)

Low-Rank Discriminant Embedding for Multiview Learning.

PubMed

Li, Jingjing; Wu, Yue; Zhao, Jidong; Lu, Ke

2017-11-01

This paper focuses on the specific problem of multiview learning where samples have the same feature set but different probability distributions, e.g., different viewpoints or different modalities. Since samples lying in different distributions cannot be compared directly, this paper aims to learn a latent subspace shared by multiple views assuming that the input views are generated from this latent subspace. Previous approaches usually learn the common subspace by either maximizing the empirical likelihood, or preserving the geometric structure. However, considering the complementarity between the two objectives, this paper proposes a novel approach, named low-rank discriminant embedding (LRDE), for multiview learning by taking full advantage of both sides. By further considering the duality between data points and features of multiview scene, i.e., data points can be grouped based on their distribution on features, while features can be grouped based on their distribution on the data points, LRDE not only deploys low-rank constraints on both sample level and feature level to dig out the shared factors across different views, but also preserves geometric information in both the ambient sample space and the embedding feature space by designing a novel graph structure under the framework of graph embedding. Finally, LRDE jointly optimizes low-rank representation and graph embedding in a unified framework. Comprehensive experiments in both multiview manner and pairwise manner demonstrate that LRDE performs much better than previous approaches proposed in recent literatures.

Deep Hashing for Scalable Image Search.

PubMed

Lu, Jiwen; Liong, Venice Erin; Zhou, Jie

2017-05-01

In this paper, we propose a new deep hashing (DH) approach to learn compact binary codes for scalable image search. Unlike most existing binary codes learning methods, which usually seek a single linear projection to map each sample into a binary feature vector, we develop a deep neural network to seek multiple hierarchical non-linear transformations to learn these binary codes, so that the non-linear relationship of samples can be well exploited. Our model is learned under three constraints at the top layer of the developed deep network: 1) the loss between the compact real-valued code and the learned binary vector is minimized, 2) the binary codes distribute evenly on each bit, and 3) different bits are as independent as possible. To further improve the discriminative power of the learned binary codes, we extend DH into supervised DH (SDH) and multi-label SDH by including a discriminative term into the objective function of DH, which simultaneously maximizes the inter-class variations and minimizes the intra-class variations of the learned binary codes with the single-label and multi-label settings, respectively. Extensive experimental results on eight widely used image search data sets show that our proposed methods achieve very competitive results with the state-of-the-arts.

Framing From Experience: Cognitive Processes and Predictions of Risky Choice.

PubMed

Gonzalez, Cleotilde; Mehlhorn, Katja

2016-07-01

A framing bias shows risk aversion in problems framed as "gains" and risk seeking in problems framed as "losses," even when these are objectively equivalent and probabilities and outcomes values are explicitly provided. We test this framing bias in situations where decision makers rely on their own experience, sampling the problem's options (safe and risky) and seeing the outcomes before making a choice. In Experiment 1, we replicate the framing bias in description-based decisions and find risk indifference in gains and losses in experience-based decisions. Predictions of an Instance-Based Learning model suggest that objective probabilities as well as the number of samples taken are factors that contribute to the lack of framing effect. We test these two factors in Experiment 2 and find no framing effect when a few samples are taken but when large samples are taken, the framing effect appears regardless of the objective probability values. Implications of behavioral results and cognitive modeling are discussed. Copyright © 2015 Cognitive Science Society, Inc.

Identification of Interesting Objects in Large Spectral Surveys Using Highly Parallelized Machine Learning

NASA Astrophysics Data System (ADS)

Škoda, Petr; Palička, Andrej; Koza, Jakub; Shakurova, Ksenia

2017-06-01

The current archives of LAMOST multi-object spectrograph contain millions of fully reduced spectra, from which the automatic pipelines have produced catalogues of many parameters of individual objects, including their approximate spectral classification. This is, however, mostly based on the global shape of the whole spectrum and on integral properties of spectra in given bandpasses, namely presence and equivalent width of prominent spectral lines, while for identification of some interesting object types (e.g. Be stars or quasars) the detailed shape of only a few lines is crucial. Here the machine learning is bringing a new methodology capable of improving the reliability of classification of such objects even in boundary cases. We present results of Spark-based semi-supervised machine learning of LAMOST spectra attempting to automatically identify the single and double-peak emission of Hα line typical for Be and B[e] stars. The labelled sample was obtained from archive of 2m Perek telescope at Ondřejov observatory. A simple physical model of spectrograph resolution was used in domain adaptation to LAMOST training domain. The resulting list of candidates contains dozens of Be stars (some are likely yet unknown), but also a bunch of interesting objects resembling spectra of quasars and even blazars, as well as many instrumental artefacts. The verification of a nature of interesting candidates benefited considerably from cross-matching and visualisation in the Virtual Observatory environment.

Mere exposure alters category learning of novel objects.

PubMed

Folstein, Jonathan R; Gauthier, Isabel; Palmeri, Thomas J

2010-01-01

We investigated how mere exposure to complex objects with correlated or uncorrelated object features affects later category learning of new objects not seen during exposure. Correlations among pre-exposed object dimensions influenced later category learning. Unlike other published studies, the collection of pre-exposed objects provided no information regarding the categories to be learned, ruling out unsupervised or incidental category learning during pre-exposure. Instead, results are interpreted with respect to statistical learning mechanisms, providing one of the first demonstrations of how statistical learning can influence visual object learning.

Mere Exposure Alters Category Learning of Novel Objects

PubMed Central

Folstein, Jonathan R.; Gauthier, Isabel; Palmeri, Thomas J.

2010-01-01

We investigated how mere exposure to complex objects with correlated or uncorrelated object features affects later category learning of new objects not seen during exposure. Correlations among pre-exposed object dimensions influenced later category learning. Unlike other published studies, the collection of pre-exposed objects provided no information regarding the categories to be learned, ruling out unsupervised or incidental category learning during pre-exposure. Instead, results are interpreted with respect to statistical learning mechanisms, providing one of the first demonstrations of how statistical learning can influence visual object learning. PMID:21833209

Investigating Verbal and Visual Auditory Learning After Conformal Radiation Therapy for Childhood Ependymoma

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

Di Pinto, Marcos; Conklin, Heather M.; Li Chenghong

Purpose: The primary objective of this study was to determine whether children with localized ependymoma experience a decline in verbal or visual-auditory learning after conformal radiation therapy (CRT). The secondary objective was to investigate the impact of age and select clinical factors on learning before and after treatment. Methods and Materials: Learning in a sample of 71 patients with localized ependymoma was assessed with the California Verbal Learning Test (CVLT-C) and the Visual-Auditory Learning Test (VAL). Learning measures were administered before CRT, at 6 months, and then yearly for a total of 5 years. Results: There was no significant declinemore » on measures of verbal or visual-auditory learning after CRT; however, younger age, more surgeries, and cerebrospinal fluid shunting did predict lower scores at baseline. There were significant longitudinal effects (improved learning scores after treatment) among older children on the CVLT-C and children that did not receive pre-CRT chemotherapy on the VAL. Conclusion: There was no evidence of global decline in learning after CRT in children with localized ependymoma. Several important implications from the findings include the following: (1) identification of and differentiation among variables with transient vs. long-term effects on learning, (2) demonstration that children treated with chemotherapy before CRT had greater risk of adverse visual-auditory learning performance, and (3) establishment of baseline and serial assessment as critical in ascertaining necessary sensitivity and specificity for the detection of modest effects.« less

The Effective of Using 5 Simple Steps (QSCCS) Learning Activities on Facebook to Promote Self-Learning in the 21st Century in Technology Printing and Advertising Course for Undergraduate Students in Education Technology and Communications

ERIC Educational Resources Information Center

Sittiwong, Tipparat; Wongnam, Thanet

2015-01-01

The objectives of this study were to: 1) study the result of implementing QSCCS with Facebook; 2) study students' opinions concerning the implementation of QSCCS with Facebook. The samples were 38 Technology and Communications undergraduates who attended Printing and Advertising Technology course in academic year of 2013. The information was…

Communication Modality Sampling for a Toddler with Angelman Syndrome

ERIC Educational Resources Information Center

Martin, Jolene Hyppa; Reichle, Joe; Dimian, Adele; Chen, Mo

2013-01-01

Purpose: Vocal, gestural, and graphic communication modes were implemented concurrently with a toddler with Angelman syndrome to identify the most efficiently learned communication mode to emphasize in an initial augmentative communication system. Method: Symbols representing preferred objects were introduced in vocal, gestural, and graphic…

Apollo Lunar Sample Integration into Google Moon: A New Approach to Digitization

NASA Technical Reports Server (NTRS)

Dawson, Melissa D.; Todd, nancy S.; Lofgren, Gary E.

2011-01-01

The Google Moon Apollo Lunar Sample Data Integration project is part of a larger, LASER-funded 4-year lunar rock photo restoration project by NASA s Acquisition and Curation Office [1]. The objective of this project is to enhance the Apollo mission data already available on Google Moon with information about the lunar samples collected during the Apollo missions. To this end, we have combined rock sample data from various sources, including Curation databases, mission documentation and lunar sample catalogs, with newly available digital photography of rock samples to create a user-friendly, interactive tool for learning about the Apollo Moon samples

Object Classification With Joint Projection and Low-Rank Dictionary Learning.

PubMed

Foroughi, Homa; Ray, Nilanjan; Hong Zhang

2018-02-01

For an object classification system, the most critical obstacles toward real-world applications are often caused by large intra-class variability, arising from different lightings, occlusion, and corruption, in limited sample sets. Most methods in the literature would fail when the training samples are heavily occluded, corrupted or have significant illumination or viewpoint variations. Besides, most of the existing methods and especially deep learning-based methods, need large training sets to achieve a satisfactory recognition performance. Although using the pre-trained network on a generic large-scale data set and fine-tune it to the small-sized target data set is a widely used technique, this would not help when the content of base and target data sets are very different. To address these issues simultaneously, we propose a joint projection and low-rank dictionary learning method using dual graph constraints. Specifically, a structured class-specific dictionary is learned in the low-dimensional space, and the discrimination is further improved by imposing a graph constraint on the coding coefficients, that maximizes the intra-class compactness and inter-class separability. We enforce structural incoherence and low-rank constraints on sub-dictionaries to reduce the redundancy among them, and also make them robust to variations and outliers. To preserve the intrinsic structure of data, we introduce a supervised neighborhood graph into the framework to make the proposed method robust to small-sized and high-dimensional data sets. Experimental results on several benchmark data sets verify the superior performance of our method for object classification of small-sized data sets, which include a considerable amount of different kinds of variation, and may have high-dimensional feature vectors.

Interoperability Gap Challenges for Learning Object Repositories & Learning Management Systems

ERIC Educational Resources Information Center

Mason, Robert T.

2011-01-01

An interoperability gap exists between Learning Management Systems (LMSs) and Learning Object Repositories (LORs). Learning Objects (LOs) and the associated Learning Object Metadata (LOM) that is stored within LORs adhere to a variety of LOM standards. A common LOM standard found in LORs is the Sharable Content Object Reference Model (SCORM)…

Self-Taught Low-Rank Coding for Visual Learning.

PubMed

Li, Sheng; Li, Kang; Fu, Yun

2018-03-01

The lack of labeled data presents a common challenge in many computer vision and machine learning tasks. Semisupervised learning and transfer learning methods have been developed to tackle this challenge by utilizing auxiliary samples from the same domain or from a different domain, respectively. Self-taught learning, which is a special type of transfer learning, has fewer restrictions on the choice of auxiliary data. It has shown promising performance in visual learning. However, existing self-taught learning methods usually ignore the structure information in data. In this paper, we focus on building a self-taught coding framework, which can effectively utilize the rich low-level pattern information abstracted from the auxiliary domain, in order to characterize the high-level structural information in the target domain. By leveraging a high quality dictionary learned across auxiliary and target domains, the proposed approach learns expressive codings for the samples in the target domain. Since many types of visual data have been proven to contain subspace structures, a low-rank constraint is introduced into the coding objective to better characterize the structure of the given target set. The proposed representation learning framework is called self-taught low-rank (S-Low) coding, which can be formulated as a nonconvex rank-minimization and dictionary learning problem. We devise an efficient majorization-minimization augmented Lagrange multiplier algorithm to solve it. Based on the proposed S-Low coding mechanism, both unsupervised and supervised visual learning algorithms are derived. Extensive experiments on five benchmark data sets demonstrate the effectiveness of our approach.

EMR Behavioral Curriculum and Student Record.

ERIC Educational Resources Information Center

Hartnett, John J.

Intended for use as a curriculum guide, a source for objectives for the individualized educational plan, and an evaluation instrument to measure handicapped students' learning, the guide lists sequences of developmental tasks. Tasks are outlined for primary, intermediate, and secondary levels in the following areas (sample subskills in…

Designing Science Learning in the First Years of Schooling. An intervention study with sequenced learning material on the topic of `floating and sinking'

NASA Astrophysics Data System (ADS)

Leuchter, Miriam; Saalbach, Henrik; Hardy, Ilonca

2014-07-01

Research on learning and instruction of science has shown that learning environments applied in preschool and primary school rarely makes use of structured learning materials in problem-based environments although these are decisive quality features for promoting conceptual change and scientific reasoning within early science learning. We thus developed and implemented a science learning environment for children in the first years of schooling which contains structured learning materials with the goal of supporting conceptual change concerning the understanding of the floating and sinking of objects and fostering students' scientific reasoning skills. In the present implementation study, we aim to provide a best-practice example of early science learning. The study was conducted with a sample of 15 classes of the first years of schooling and a total of 244 children. Tests were constructed to measure children's conceptual understanding before and after the implementation. Our results reveal a decrease in children's misconceptions from pretest to posttest. After the curriculum, the children were able to produce significantly more correct predictions about the sinking or floating of objects than before the curriculum and also relative to a control group. Moreover, due to the intervention, the explanations given for their predictions implied a more elaborated concept of material kinds. All in all, a well-structured curriculum promoting comparison and scientific reasoning by means of inquiry learning was shown to support children's conceptual change.

Intelligent Discovery for Learning Objects Using Semantic Web Technologies

ERIC Educational Resources Information Center

Hsu, I-Ching

2012-01-01

The concept of learning objects has been applied in the e-learning field to promote the accessibility, reusability, and interoperability of learning content. Learning Object Metadata (LOM) was developed to achieve these goals by describing learning objects in order to provide meaningful metadata. Unfortunately, the conventional LOM lacks the…

Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle

PubMed Central

Cerezo, Rebeca; Esteban, María; Sánchez-Santillán, Miguel; Núñez, José C.

2017-01-01

Introduction: Research about student performance has traditionally considered academic procrastination as a behavior that has negative effects on academic achievement. Although there is much evidence for this in class-based environments, there is a lack of research on Computer-Based Learning Environments (CBLEs). Therefore, the purpose of this study is to evaluate student behavior in a blended learning program and specifically procrastination behavior in relation to performance through Data Mining techniques. Materials and Methods: A sample of 140 undergraduate students participated in a blended learning experience implemented in a Moodle (Modular Object Oriented Developmental Learning Environment) Management System. Relevant interaction variables were selected for the study, taking into account student achievement and analyzing data by means of association rules, a mining technique. The association rules were arrived at and filtered through two selection criteria: 1, rules must have an accuracy over 0.8 and 2, they must be present in both sub-samples. Results: The findings of our study highlight the influence of time management in online learning environments, particularly on academic achievement, as there is an association between procrastination variables and student performance. Conclusion: Negative impact of procrastination in learning outcomes has been observed again but in virtual learning environments where practical implications, prevention of, and intervention in, are different from class-based learning. These aspects are discussed to help resolve student difficulties at various ages. PMID:28883801

Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle.

PubMed

Cerezo, Rebeca; Esteban, María; Sánchez-Santillán, Miguel; Núñez, José C

2017-01-01

Introduction: Research about student performance has traditionally considered academic procrastination as a behavior that has negative effects on academic achievement. Although there is much evidence for this in class-based environments, there is a lack of research on Computer-Based Learning Environments (CBLEs) . Therefore, the purpose of this study is to evaluate student behavior in a blended learning program and specifically procrastination behavior in relation to performance through Data Mining techniques. Materials and Methods: A sample of 140 undergraduate students participated in a blended learning experience implemented in a Moodle (Modular Object Oriented Developmental Learning Environment) Management System. Relevant interaction variables were selected for the study, taking into account student achievement and analyzing data by means of association rules, a mining technique. The association rules were arrived at and filtered through two selection criteria: 1, rules must have an accuracy over 0.8 and 2, they must be present in both sub-samples. Results: The findings of our study highlight the influence of time management in online learning environments, particularly on academic achievement, as there is an association between procrastination variables and student performance. Conclusion: Negative impact of procrastination in learning outcomes has been observed again but in virtual learning environments where practical implications, prevention of, and intervention in, are different from class-based learning. These aspects are discussed to help resolve student difficulties at various ages.

Using computer-assisted learning to engage diverse learning styles in understanding business management principles.

PubMed

Frost, Mary E; Derby, Dustin C; Haan, Andrea G

2013-01-01

Objective : Changes in small business and insurance present challenges for newly graduated chiropractors. Technology that reaches identified, diverse learning styles may assist the chiropractic student in business classes to meet course outcomes better. Thus, the purpose of our study is to determine if the use of technology-based instructional aids enhance students' mastery of course learning outcomes. Methods : Using convenience sampling, 86 students completed a survey assessing course learning outcomes, learning style, and the helpfulness of lecture and computer-assisted learning related to content mastery. Quantitative analyses occurred. Results : Although respondents reported not finding the computer-assisted learning as helpful as the lecture, significant relationships were found between pre- and post-assisted learning measures of the learning outcomes 1 and 2 for the visual and kinesthetic groups. Surprisingly, however, all learning style groups exhibited significant pre- and post-assisted learning appraisal relationships with learning outcomes 3 and 4. Conclusion : While evidence exists within the current study of a relationship between students' learning of the course content corollary to the use of technologic instructional aids, the exact nature of the relationship remains unclear.

Using computer-assisted learning to engage diverse learning styles in understanding business management principles.

PubMed

Frost, Mary E; Derby, Dustin C; Haan, Andrea G

2013-06-27

Objective : Changes in small business and insurance present challenges for newly graduated chiropractors. Technology that reaches identified, diverse learning styles may assist the chiropractic student in business classes to meet course outcomes better. Thus, the purpose of our study is to determine if the use of technology-based instructional aids enhance students' mastery of course learning outcomes. Methods : Using convenience sampling, 86 students completed a survey assessing course learning outcomes, learning style, and the helpfulness of lecture and computer-assisted learning related to content mastery. Quantitative analyses occurred. Results : Although respondents reported not finding the computer-assisted learning as helpful as the lecture, significant relationships were found between pre- and post-assisted learning measures of the learning outcomes 1 and 2 for the visual and kinesthetic groups. Surprisingly, however, all learning style groups exhibited significant pre- and post-assisted learning appraisal relationships with learning outcomes 3 and 4. Conclusion : While evidence exists within the current study of a relationship between students' learning of the course content corollary to the use of technologic instructional aids, the exact nature of the relationship remains unclear.

Special Classes for Gifted Students? Absolutely!

ERIC Educational Resources Information Center

Burton-Szabo, Sally

1996-01-01

This article makes a case for special classes for gifted students and answers objections to special classes raised by the middle school movement and the cooperative learning movement. A sample "Celebration of Me" unit taught to gifted seventh graders which involved poetry, literature, personal development, art, music, and physical fitness is…

Assessing Learning, Quality and Engagement in Learning Objects: The Learning Object Evaluation Scale for Students (LOES-S)

ERIC Educational Resources Information Center

Kay, Robin H.; Knaack, Liesel

2009-01-01

Learning objects are interactive web-based tools that support the learning of specific concepts by enhancing, amplifying, and/or guiding the cognitive processes of learners. Research on the impact, effectiveness, and usefulness of learning objects is limited, partially because comprehensive, theoretically based, reliable, and valid evaluation…

Liberating Learning Object Design from the Learning Style of Student Instructional Designers

ERIC Educational Resources Information Center

Akpinar, Yavuz

2007-01-01

Learning objects are a new form of learning resource, and the design of these digital environments has many facets. To investigate senior instructional design students' use of reflection tools in designing learning objects, a series of studies was conducted using the Reflective Action Instructional Design and Learning Object Review Instrument…

Learning Objects and Gerontology

ERIC Educational Resources Information Center

Weinreich, Donna M.; Tompkins, Catherine J.

2006-01-01

Virtual AGE (vAGE) is an asynchronous educational environment that utilizes learning objects focused on gerontology and a learning anytime/anywhere philosophy. This paper discusses the benefits of asynchronous instruction and the process of creating learning objects. Learning objects are "small, reusable chunks of instructional media" Wiley…

The effect of learning models and emotional intelligence toward students learning outcomes on reaction rate

NASA Astrophysics Data System (ADS)

Sutiani, Ani; Silitonga, Mei Y.

2017-08-01

This research focused on the effect of learning models and emotional intelligence in students' chemistry learning outcomes on reaction rate teaching topic. In order to achieve the objectives of the research, with 2x2 factorial research design was used. There were two factors tested, namely: the learning models (factor A), and emotional intelligence (factor B) factors. Then, two learning models were used; problem-based learning/PBL (A1), and project-based learning/PjBL (A2). While, the emotional intelligence was divided into higher and lower types. The number of population was six classes containing 243 grade X students of SMAN 10 Medan, Indonesia. There were 15 students of each class were chosen as the sample of the research by applying purposive sampling technique. The data were analyzed by applying two-ways analysis of variance (2X2) at the level of significant α = 0.05. Based on hypothesis testing, there was the interaction between learning models and emotional intelligence in students' chemistry learning outcomes. Then, the finding of the research showed that students' learning outcomes in reaction rate taught by using PBL with higher emotional intelligence is higher than those who were taught by using PjBL. There was no significant effect between students with lower emotional intelligence taught by using both PBL and PjBL in reaction rate topic. Based on the finding, the students with lower emotional intelligence were quite hard to get in touch with other students in group discussion.

Scripting Scenarios for the Human Patient Simulator

NASA Technical Reports Server (NTRS)

Bacal, Kira; Miller, Robert; Doerr, Harold

2004-01-01

The Human Patient Simulator (HPS) is particularly useful in providing scenario-based learning which can be tailored to fit specific scenarios and which can be modified in realtime to enhance the teaching environment. Scripting these scenarios so as to maximize learning requires certain skills, in order to ensure that a change in student performance, understanding, critical thinking, and/or communication skills results. Methods: A "good" scenario can be defined in terms of applicability, learning opportunities, student interest, and clearly associated metrics. Obstacles to such a scenario include a lack of understanding of the applicable environment by the scenario author(s), a desire (common among novices) to cover too many topics, failure to define learning objectives, mutually exclusive or confusing learning objectives, unskilled instructors, poor preparation , disorganized approach, or an inappropriate teaching philosophy (such as "trial by fire" or education through humiliation). Results: Descriptions of several successful teaching programs, used in the military, civilian, and NASA medical environments , will be provided, along with sample scenarios. Discussion: Simulator-based lessons have proven to be a time- and cost-efficient manner by which to educate medical personnel. Particularly when training for medical care in austere environments (pre-hospital, aeromedical transport, International Space Station, military operations), the HPS can enhance the learning experience.

Analogical reasoning in amazons.

PubMed

Obozova, Tanya; Smirnova, Anna; Zorina, Zoya; Wasserman, Edward

2015-11-01

Two juvenile orange-winged amazons (Amazona amazonica) were initially trained to match visual stimuli by color, shape, and number of items, but not by size. After learning these three identity matching-to-sample tasks, the parrots transferred discriminative responding to new stimuli from the same categories that had been used in training (other colors, shapes, and numbers of items) as well as to stimuli from a different category (stimuli varying in size). In the critical testing phase, both parrots exhibited reliable relational matching-to-sample (RMTS) behavior, suggesting that they perceived and compared the relationship between objects in the sample stimulus pair to the relationship between objects in the comparison stimulus pairs, even though no physical matches were possible between items in the sample and comparison pairs. The parrots spontaneously exhibited this higher-order relational responding without having ever before been trained on RMTS tasks, therefore joining apes and crows in displaying this abstract cognitive behavior.

A Weighted Deep Representation Learning Model for Imbalanced Fault Diagnosis in Cyber-Physical Systems.

PubMed

Wu, Zhenyu; Guo, Yang; Lin, Wenfang; Yu, Shuyang; Ji, Yang

2018-04-05

Predictive maintenance plays an important role in modern Cyber-Physical Systems (CPSs) and data-driven methods have been a worthwhile direction for Prognostics Health Management (PHM). However, two main challenges have significant influences on the traditional fault diagnostic models: one is that extracting hand-crafted features from multi-dimensional sensors with internal dependencies depends too much on expertise knowledge; the other is that imbalance pervasively exists among faulty and normal samples. As deep learning models have proved to be good methods for automatic feature extraction, the objective of this paper is to study an optimized deep learning model for imbalanced fault diagnosis for CPSs. Thus, this paper proposes a weighted Long Recurrent Convolutional LSTM model with sampling policy (wLRCL-D) to deal with these challenges. The model consists of 2-layer CNNs, 2-layer inner LSTMs and 2-Layer outer LSTMs, with under-sampling policy and weighted cost-sensitive loss function. Experiments are conducted on PHM 2015 challenge datasets, and the results show that wLRCL-D outperforms other baseline methods.

A Weighted Deep Representation Learning Model for Imbalanced Fault Diagnosis in Cyber-Physical Systems

PubMed Central

Guo, Yang; Lin, Wenfang; Yu, Shuyang; Ji, Yang

2018-01-01

Predictive maintenance plays an important role in modern Cyber-Physical Systems (CPSs) and data-driven methods have been a worthwhile direction for Prognostics Health Management (PHM). However, two main challenges have significant influences on the traditional fault diagnostic models: one is that extracting hand-crafted features from multi-dimensional sensors with internal dependencies depends too much on expertise knowledge; the other is that imbalance pervasively exists among faulty and normal samples. As deep learning models have proved to be good methods for automatic feature extraction, the objective of this paper is to study an optimized deep learning model for imbalanced fault diagnosis for CPSs. Thus, this paper proposes a weighted Long Recurrent Convolutional LSTM model with sampling policy (wLRCL-D) to deal with these challenges. The model consists of 2-layer CNNs, 2-layer inner LSTMs and 2-Layer outer LSTMs, with under-sampling policy and weighted cost-sensitive loss function. Experiments are conducted on PHM 2015 challenge datasets, and the results show that wLRCL-D outperforms other baseline methods. PMID:29621131

An Investigation on the Correlation of Learner Styles and Learning Objects Characteristics in a Proposed Learning Objects Management Model (LOMM)

ERIC Educational Resources Information Center

Wanapu, Supachanun; Fung, Chun Che; Kerdprasop, Nittaya; Chamnongsri, Nisachol; Niwattanakul, Suphakit

2016-01-01

The issues of accessibility, management, storage and organization of Learning Objects (LOs) in education systems are a high priority of the Thai Government. Incorporating personalized learning or learning styles in a learning object management system to improve the accessibility of LOs has been addressed continuously in the Thai education system.…

The development of the learning video for the flipped classroom model on student of open university on human skeletal system and muscles

NASA Astrophysics Data System (ADS)

Andrini, V. S.

2018-05-01

The objectives of the research are to develop the learning video for the flipped classroom model for Open University’s student and to know the effectiveness of the video. The development of the video used Research and Development ADDIE design (Analyses, Design, Development, Implementation, Evaluation). The sampling used purposive sampling was 28 students in Open University of Nganjuk. The techniques of data collection were the observation data to know the problems of the students, and learning facilities, the test (pre-test and post-test) to know a knowledge aspect, a questionnaire to know advisability of video learning, a structured interview to confirm their answer. The result of the expert of matter and media showed that the average product score was 3.75 of 4 or very good, the small-scale test showed that the average score was 3.60 of 4 and the large-scale test showed that the average score was 3.80 of 4, it had a very good category. The t-test with paired sample test showed that sig. (2-tailed) < 0.05. The N-gain score of pre and post test was 0.55, it had the medium category. It can be concluded that the development of the learning video for flipped classroom was effective to be implemented.

Effectiveness Of Horizontal Peer-Assisted Learning In Physical Examination Performance.

PubMed

Shah, Inamullah; Mahboob, Usman; Shah, Sajida

2017-01-01

All students cannot be individually trained in physical examination skills due to faculty and time limitations. Peer-assisted learning (PAL) can solve this dilemma if it is used in undergraduate curriculum. Empirical effectiveness of horizontal peer-assisted learning model has not been reported previously. The objective of this study was to compare horizontal peer-assisted learning (PAL) with expert-assisted learning (EAL) in teaching of physical examination skills. This is a randomized controlled study (Solomon four group design) carried out at a medical school. A total of 120 undergraduate year 5 students were randomized into two groups to undergo training in four areas of physical examination. Stratified random sampling technique was used. Group 1 was trained by EAL while Group 2 by PAL. Half students from both groups were given a pre-test to assess the testing effect. Both groups were given a post-test in the form of an OSCE. Independent samples t-test and paired sample t-test were used as tests of significance. Group 2 scored significantly higher than Group 1. There was significant difference (p=.000) in mean post-test scores of Group-1 (69.98±5.6) and Group-2 (85.27±5.6). Difference in mean scores was not significant (p=.977) between students who had taken the pre-test and those who had not. This study has implications in curriculum development as it provides quantitative evidence indicating that horizontal PAL as a learning strategy can actually replace, rather than augment, expert-assisted learning in teaching clinical skills to undergraduate students.

Pharmacists' perceptions of facilitators and barriers to lifelong learning.

PubMed

Hanson, Alan L; Bruskiewitz, Ruth H; Demuth, James E

2007-08-15

To reevaluate facilitators of and barriers to pharmacists' participation in lifelong learning previously examined in a 1990 study. A survey instrument was mailed to 274 pharmacists who volunteered to participate based on a prior random sample survey. Data based on perceptions of facilitators and barriers to lifelong learning, as well as self-perception as a lifelong learner, were analyzed and compared to a similar 1990 survey. The response rate for the survey was 88%. The top 3 facilitators and barriers to lifelong learning from the 2003 and the 1990 samples were: (1) personal desire to learn; (2) requirement to maintain professional licensure; and (3) enjoyment/relaxation provided by learning as change of pace from the "routine." The top 3 barriers were: (1) job constraints; (2) scheduling (location, distance, time) of group learning activities; and (3) family constraints (eg, spouse, children, personal). Respondents' broad self-perception as lifelong learners continued to be highly positive overall, but remained less positive relative to more specific lifelong learning skills such as the ability to identify learning objectives as well as to evaluate learning outcomes. Little has changed in the last decade relative to how pharmacists view themselves as lifelong learners, as well as what they perceive as facilitators and barriers to lifelong learning. To address factors identified as facilitators and barriers, continuing education (CE) providers should focus on pharmacists' time constraints, whether due to employment, family responsibilities, or time invested in the educational activity itself, and pharmacists' internal motivations to learn (personal desire, enjoyment), as well as external forces such as mandatory CE for relicensure.

Virtual Workshop Environment (VWE): A Taxonomy and Service Oriented Architecture (SOA) Framework for Modularized Virtual Learning Environments (VLE)--Applying the Learning Object Concept to the VLE

ERIC Educational Resources Information Center

Paulsson, Fredrik; Naeve, Ambjorn

2006-01-01

Based on existing Learning Object taxonomies, this article suggests an alternative Learning Object taxonomy, combined with a general Service Oriented Architecture (SOA) framework, aiming to transfer the modularized concept of Learning Objects to modularized Virtual Learning Environments. The taxonomy and SOA-framework exposes a need for a clearer…

Medical Students' Knowledge about Alcohol and Drug Problems: Results of the Medical Council of Canada Examination

ERIC Educational Resources Information Center

Kahan, Meldon; Midmer, Deana; Wilson, Lynn; Borsoi, Diane

2006-01-01

Purpose: To determine knowledge of a national sample of medical students about substance withdrawal, screening and early intervention, medical and psychiatric complications of addiction, and treatment options. Methods: Based on learning objectives developed by medical faculty, twenty-two questions on addictions were included in the 1998 Canadian…

English Education and Aging.

ERIC Educational Resources Information Center

Gillis, Candida

1983-01-01

Suggests that English teachers are in an excellent position to help students learn about the aged and aging because they know literature that treats the joys and pains of later life and they understand how language shapes and reflects cultural attitudes. Proposes objectives and presents samples of activities to be used in an aging unit. (MM)

Genetics and Cinema: Personal Misconceptions That Constitute Obstacles to Learning

ERIC Educational Resources Information Center

Muela, Francisco Javier; Abril, Ana María

2014-01-01

The primary objective of this paper is to find out whether the genetic concepts conveyed by cinema could encourage students' personal misconceptions in this area. To that end, two sources of conceptions were compared: the students' personal concepts (from a consolidated bibliography and from an experimental sample) and the concepts conveyed by…

Cognitive Processes Underlying Women's Risk Judgments: Associations with Sexual Victimization History and Rape Myth Acceptance

ERIC Educational Resources Information Center

Yeater, Elizabeth A.; Treat, Teresa A.; Viken, Richard J.; McFall, Richard M.

2010-01-01

Objective: This study evaluated the effects of sexual victimization history, rape myth acceptance, implicit attention, and recent learning on the cognitive processes underlying undergraduate women's explicit risk judgments. Method: Participants were 194 undergraduate women between 18 and 24 years of age. The sample was ethnically diverse and…

A deep learning framework to discern and count microscopic nematode eggs.

PubMed

Akintayo, Adedotun; Tylka, Gregory L; Singh, Asheesh K; Ganapathysubramanian, Baskar; Singh, Arti; Sarkar, Soumik

2018-06-14

In order to identify and control the menace of destructive pests via microscopic image-based identification state-of-the art deep learning architecture is demonstrated on the parasitic worm, the soybean cyst nematode (SCN), Heterodera glycines. Soybean yield loss is negatively correlated with the density of SCN eggs that are present in the soil. While there has been progress in automating extraction of egg-filled cysts and eggs from soil samples counting SCN eggs obtained from soil samples using computer vision techniques has proven to be an extremely difficult challenge. Here we show that a deep learning architecture developed for rare object identification in clutter-filled images can identify and count the SCN eggs. The architecture is trained with expert-labeled data to effectively build a machine learning model for quantifying SCN eggs via microscopic image analysis. We show dramatic improvements in the quantification time of eggs while maintaining human-level accuracy and avoiding inter-rater and intra-rater variabilities. The nematode eggs are correctly identified even in complex, debris-filled images that are often difficult for experts to identify quickly. Our results illustrate the remarkable promise of applying deep learning approaches to phenotyping for pest assessment and management.

Imaging complex objects using learning tomography

NASA Astrophysics Data System (ADS)

Lim, JooWon; Goy, Alexandre; Shoreh, Morteza Hasani; Unser, Michael; Psaltis, Demetri

2018-02-01

Optical diffraction tomography (ODT) can be described using the scattering process through an inhomogeneous media. An inherent nonlinearity exists relating the scattering medium and the scattered field due to multiple scattering. Multiple scattering is often assumed to be negligible in weakly scattering media. This assumption becomes invalid as the sample gets more complex resulting in distorted image reconstructions. This issue becomes very critical when we image a complex sample. Multiple scattering can be simulated using the beam propagation method (BPM) as the forward model of ODT combined with an iterative reconstruction scheme. The iterative error reduction scheme and the multi-layer structure of BPM are similar to neural networks. Therefore we refer to our imaging method as learning tomography (LT). To fairly assess the performance of LT in imaging complex samples, we compared LT with the conventional iterative linear scheme using Mie theory which provides the ground truth. We also demonstrate the capacity of LT to image complex samples using experimental data of a biological cell.

Siamese convolutional networks for tracking the spine motion

NASA Astrophysics Data System (ADS)

Liu, Yuan; Sui, Xiubao; Sun, Yicheng; Liu, Chengwei; Hu, Yong

2017-09-01

Deep learning models have demonstrated great success in various computer vision tasks such as image classification and object tracking. However, tracking the lumbar spine by digitalized video fluoroscopic imaging (DVFI), which can quantitatively analyze the motion mode of spine to diagnose lumbar instability, has not yet been well developed due to the lack of steady and robust tracking method. In this paper, we propose a novel visual tracking algorithm of the lumbar vertebra motion based on a Siamese convolutional neural network (CNN) model. We train a full-convolutional neural network offline to learn generic image features. The network is trained to learn a similarity function that compares the labeled target in the first frame with the candidate patches in the current frame. The similarity function returns a high score if the two images depict the same object. Once learned, the similarity function is used to track a previously unseen object without any adapting online. In the current frame, our tracker is performed by evaluating the candidate rotated patches sampled around the previous frame target position and presents a rotated bounding box to locate the predicted target precisely. Results indicate that the proposed tracking method can detect the lumbar vertebra steadily and robustly. Especially for images with low contrast and cluttered background, the presented tracker can still achieve good tracking performance. Further, the proposed algorithm operates at high speed for real time tracking.

Understanding Learner Acceptance of Learning Objects: The Roles of Learning Object Characteristics and Individual Differences

ERIC Educational Resources Information Center

Lau, Siong-Hoe; Woods, Peter C.

2009-01-01

Many organisations and institutions have integrated learning objects into their e-learning systems to make the instructional resources more efficient. Like any other information systems, this trend has made user acceptance of learning objects an increasingly critical issue as a high level of learner satisfaction and acceptance reflects that the…

Learned filters for object detection in multi-object visual tracking

NASA Astrophysics Data System (ADS)

Stamatescu, Victor; Wong, Sebastien; McDonnell, Mark D.; Kearney, David

2016-05-01

We investigate the application of learned convolutional filters in multi-object visual tracking. The filters were learned in both a supervised and unsupervised manner from image data using artificial neural networks. This work follows recent results in the field of machine learning that demonstrate the use learned filters for enhanced object detection and classification. Here we employ a track-before-detect approach to multi-object tracking, where tracking guides the detection process. The object detection provides a probabilistic input image calculated by selecting from features obtained using banks of generative or discriminative learned filters. We present a systematic evaluation of these convolutional filters using a real-world data set that examines their performance as generic object detectors.

Spatiotemporal information during unsupervised learning enhances viewpoint invariant object recognition

PubMed Central

Tian, Moqian; Grill-Spector, Kalanit

2015-01-01

Recognizing objects is difficult because it requires both linking views of an object that can be different and distinguishing objects with similar appearance. Interestingly, people can learn to recognize objects across views in an unsupervised way, without feedback, just from the natural viewing statistics. However, there is intense debate regarding what information during unsupervised learning is used to link among object views. Specifically, researchers argue whether temporal proximity, motion, or spatiotemporal continuity among object views during unsupervised learning is beneficial. Here, we untangled the role of each of these factors in unsupervised learning of novel three-dimensional (3-D) objects. We found that after unsupervised training with 24 object views spanning a 180° view space, participants showed significant improvement in their ability to recognize 3-D objects across rotation. Surprisingly, there was no advantage to unsupervised learning with spatiotemporal continuity or motion information than training with temporal proximity. However, we discovered that when participants were trained with just a third of the views spanning the same view space, unsupervised learning via spatiotemporal continuity yielded significantly better recognition performance on novel views than learning via temporal proximity. These results suggest that while it is possible to obtain view-invariant recognition just from observing many views of an object presented in temporal proximity, spatiotemporal information enhances performance by producing representations with broader view tuning than learning via temporal association. Our findings have important implications for theories of object recognition and for the development of computational algorithms that learn from examples. PMID:26024454

Virtual learning object and environment: a concept analysis.

PubMed

Salvador, Pétala Tuani Candido de Oliveira; Bezerril, Manacés Dos Santos; Mariz, Camila Maria Santos; Fernandes, Maria Isabel Domingues; Martins, José Carlos Amado; Santos, Viviane Euzébia Pereira

2017-01-01

To analyze the concept of virtual learning object and environment according to Rodgers' evolutionary perspective. Descriptive study with a mixed approach, based on the stages proposed by Rodgers in his concept analysis method. Data collection occurred in August 2015 with the search of dissertations and theses in the Bank of Theses of the Coordination for the Improvement of Higher Education Personnel. Quantitative data were analyzed based on simple descriptive statistics and the concepts through lexicographic analysis with support of the IRAMUTEQ software. The sample was made up of 161 studies. The concept of "virtual learning environment" was presented in 99 (61.5%) studies, whereas the concept of "virtual learning object" was presented in only 15 (9.3%) studies. A virtual learning environment includes several and different types of virtual learning objects in a common pedagogical context. Analisar o conceito de objeto e de ambiente virtual de aprendizagem na perspectiva evolucionária de Rodgers. Estudo descritivo, de abordagem mista, realizado a partir das etapas propostas por Rodgers em seu modelo de análise conceitual. A coleta de dados ocorreu em agosto de 2015 com a busca de dissertações e teses no Banco de Teses e Dissertações da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior. Os dados quantitativos foram analisados a partir de estatística descritiva simples e os conceitos pela análise lexicográfica com suporte do IRAMUTEQ. A amostra é constituída de 161 estudos. O conceito de "ambiente virtual de aprendizagem" foi apresentado em 99 (61,5%) estudos, enquanto o de "objeto virtual de aprendizagem" em apenas 15 (9,3%). Concluiu-se que um ambiente virtual de aprendizagem reúne vários e diferentes tipos de objetos virtuais de aprendizagem em um contexto pedagógico comum.

Stable orthogonal local discriminant embedding for linear dimensionality reduction.

PubMed

Gao, Quanxue; Ma, Jingjie; Zhang, Hailin; Gao, Xinbo; Liu, Yamin

2013-07-01

Manifold learning is widely used in machine learning and pattern recognition. However, manifold learning only considers the similarity of samples belonging to the same class and ignores the within-class variation of data, which will impair the generalization and stableness of the algorithms. For this purpose, we construct an adjacency graph to model the intraclass variation that characterizes the most important properties, such as diversity of patterns, and then incorporate the diversity into the discriminant objective function for linear dimensionality reduction. Finally, we introduce the orthogonal constraint for the basis vectors and propose an orthogonal algorithm called stable orthogonal local discriminate embedding. Experimental results on several standard image databases demonstrate the effectiveness of the proposed dimensionality reduction approach.

Active learning for clinical text classification: is it better than random sampling?

PubMed Central

Figueroa, Rosa L; Ngo, Long H; Goryachev, Sergey; Wiechmann, Eduardo P

2012-01-01

Objective This study explores active learning algorithms as a way to reduce the requirements for large training sets in medical text classification tasks. Design Three existing active learning algorithms (distance-based (DIST), diversity-based (DIV), and a combination of both (CMB)) were used to classify text from five datasets. The performance of these algorithms was compared to that of passive learning on the five datasets. We then conducted a novel investigation of the interaction between dataset characteristics and the performance results. Measurements Classification accuracy and area under receiver operating characteristics (ROC) curves for each algorithm at different sample sizes were generated. The performance of active learning algorithms was compared with that of passive learning using a weighted mean of paired differences. To determine why the performance varies on different datasets, we measured the diversity and uncertainty of each dataset using relative entropy and correlated the results with the performance differences. Results The DIST and CMB algorithms performed better than passive learning. With a statistical significance level set at 0.05, DIST outperformed passive learning in all five datasets, while CMB was found to be better than passive learning in four datasets. We found strong correlations between the dataset diversity and the DIV performance, as well as the dataset uncertainty and the performance of the DIST algorithm. Conclusion For medical text classification, appropriate active learning algorithms can yield performance comparable to that of passive learning with considerably smaller training sets. In particular, our results suggest that DIV performs better on data with higher diversity and DIST on data with lower uncertainty. PMID:22707743

The influence of personality on neural mechanisms of observational fear and reward learning

PubMed Central

Hooker, Christine I.; Verosky, Sara C.; Miyakawa, Asako; Knight, Robert T.; D’Esposito, Mark

2012-01-01

Fear and reward learning can occur through direct experience or observation. Both channels can enhance survival or create maladaptive behavior. We used fMRI to isolate neural mechanisms of observational fear and reward learning and investigate whether neural response varied according to individual differences in neuroticism and extraversion. Participants learned object-emotion associations by observing a woman respond with fearful (or neutral) and happy (or neutral) facial expressions to novel objects. The amygdala-hippocampal complex was active when learning the object-fear association, and the hippocampus was active when learning the object-happy association. After learning, objects were presented alone; amygdala activity was greater for the fear (vs. neutral) and happy (vs. neutral) associated object. Importantly, greater amygdala-hippocampal activity during fear (vs. neutral) learning predicted better recognition of learned objects on a subsequent memory test. Furthermore, personality modulated neural mechanisms of learning. Neuroticism positively correlated with neural activity in the amygdala and hippocampus during fear (vs. neutral) learning. Low extraversion/high introversion was related to faster behavioral predictions of the fearful and neutral expressions during fear learning. In addition, low extraversion/high introversion was related to greater amygdala activity during happy (vs. neutral) learning, happy (vs. neutral) object recognition, and faster reaction times for predicting happy and neutral expressions during reward learning. These findings suggest that neuroticism is associated with an increased sensitivity in the neural mechanism for fear learning which leads to enhanced encoding of fear associations, and that low extraversion/high introversion is related to enhanced conditionability for both fear and reward learning. PMID:18573512

View-invariant object category learning, recognition, and search: how spatial and object attention are coordinated using surface-based attentional shrouds.

PubMed

Fazl, Arash; Grossberg, Stephen; Mingolla, Ennio

2009-02-01

How does the brain learn to recognize an object from multiple viewpoints while scanning a scene with eye movements? How does the brain avoid the problem of erroneously classifying parts of different objects together? How are attention and eye movements intelligently coordinated to facilitate object learning? A neural model provides a unified mechanistic explanation of how spatial and object attention work together to search a scene and learn what is in it. The ARTSCAN model predicts how an object's surface representation generates a form-fitting distribution of spatial attention, or "attentional shroud". All surface representations dynamically compete for spatial attention to form a shroud. The winning shroud persists during active scanning of the object. The shroud maintains sustained activity of an emerging view-invariant category representation while multiple view-specific category representations are learned and are linked through associative learning to the view-invariant object category. The shroud also helps to restrict scanning eye movements to salient features on the attended object. Object attention plays a role in controlling and stabilizing the learning of view-specific object categories. Spatial attention hereby coordinates the deployment of object attention during object category learning. Shroud collapse releases a reset signal that inhibits the active view-invariant category in the What cortical processing stream. Then a new shroud, corresponding to a different object, forms in the Where cortical processing stream, and search using attention shifts and eye movements continues to learn new objects throughout a scene. The model mechanistically clarifies basic properties of attention shifts (engage, move, disengage) and inhibition of return. It simulates human reaction time data about object-based spatial attention shifts, and learns with 98.1% accuracy and a compression of 430 on a letter database whose letters vary in size, position, and orientation. The model provides a powerful framework for unifying many data about spatial and object attention, and their interactions during perception, cognition, and action.

Student generated learning objectives: extent of congruence with faculty set objectives and factors influencing their generation.

PubMed

Abdul Ghaffar Al-Shaibani, Tarik A; Sachs-Robertson, Annette; Al Shazali, Hafiz O; Sequeira, Reginald P; Hamdy, Hosam; Al-Roomi, Khaldoon

2003-07-01

A problem-based learning strategy is used for curriculum planning and implementation at the Arabian Gulf University, Bahrain. Problems are constructed in a way that faculty-set objectives are expected to be identified by students during tutorials. Students in small groups, along with a tutor functioning as a facilitator, identify learning issues and define their learning objectives. We compared objectives identified by student groups with faculty-set objectives to determine extent of congruence, and identified factors that influenced students' ability at identifying faculty-set objectives. Male and female students were segregated and randomly grouped. A faculty tutor was allocated for each group. This study was based on 13 problems given to entry-level medical students. Pooled objectives of these problems were classified into four categories: structural, functional, clinical and psychosocial. Univariate analysis of variance was used for comparison, and a p > 0.05 was considered significant. The mean of overall objectives generated by the students was 54.2%, for each problem. Students identified psychosocial learning objectives more readily than structural ones. Female students identified more psychosocial objectives, whereas male students identified more of structural objectives. Tutor characteristics such as medical/non-medical background, and the years of teaching were correlated with categories of learning issues identified. Students identify part of the faculty-set learning objectives during tutorials with a faculty tutor acting as a facilitator. Students' gender influences types of learning issues identified. Content expertise of tutors does not influence identification of learning needs by students.

Constructed-response matching to sample and spelling instruction.

PubMed Central

Dube, W V; McDonald, S J; McIlvane, W J; Mackay, H A

1991-01-01

The development of interactive programmed instruction using a microcomputer as a teaching machine is described. The program applied a constructed-response matching-to-sample procedure to computer-assisted spelling instruction and review. On each trial, subjects were presented with a sample stimulus and a choice pool consisting of 10 individual letters. In initial training, sample stimuli were arrays of letters, and subjects were taught to construct identical arrays by touching the matching letters in the choice pool. After generalized constructed-response identity matching was established, pictures (line drawings) of common objects were presented as samples. At first, correct spelling was prompted by also presenting the printed name to be "copied" via identity matching; then the prompts were faded out. The program was implemented with 2 mentally retarded individuals. Assessment trials determined appropriate words for training. Correct spelling was established via the prompt-fading procedure; training trials were interspersed among baseline trials that reviewed and maintained spelling of previously learned words. As new words were learned, they were added to a cumulative baseline to generate an individualized review and practice battery for each subject. PMID:1890049

Dynamic Learning Objects to Teach Java Programming Language

ERIC Educational Resources Information Center

Narasimhamurthy, Uma; Al Shawkani, Khuloud

2010-01-01

This article describes a model for teaching Java Programming Language through Dynamic Learning Objects. The design of the learning objects was based on effective learning design principles to help students learn the complex topic of Java Programming. Visualization was also used to facilitate the learning of the concepts. (Contains 1 figure and 2…

A Framework for the Flexible Content Packaging of Learning Objects and Learning Designs

ERIC Educational Resources Information Center

Lukasiak, Jason; Agostinho, Shirley; Burnett, Ian; Drury, Gerrard; Goodes, Jason; Bennett, Sue; Lockyer, Lori; Harper, Barry

2004-01-01

This paper presents a platform-independent method for packaging learning objects and learning designs. The method, entitled a Smart Learning Design Framework, is based on the MPEG-21 standard, and uses IEEE Learning Object Metadata (LOM) to provide bibliographic, technical, and pedagogical descriptors for the retrieval and description of learning…

Object Oriented Learning Objects

ERIC Educational Resources Information Center

Morris, Ed

2005-01-01

We apply the object oriented software engineering (OOSE) design methodology for software objects (SOs) to learning objects (LOs). OOSE extends and refines design principles for authoring dynamic reusable LOs. Our learning object class (LOC) is a template from which individualised LOs can be dynamically created for, or by, students. The properties…

Creating Usage Context-Based Object Similarities to Boost Recommender Systems in Technology Enhanced Learning

ERIC Educational Resources Information Center

Niemann, Katja; Wolpers, Martin

2015-01-01

In this paper, we introduce a new way of detecting semantic similarities between learning objects by analysing their usage in web portals. Our approach relies on the usage-based relations between the objects themselves rather then on the content of the learning objects or on the relations between users and learning objects. We then take this new…

[Competence Based Catalogue of Learning Objectives for Rehabilitation, Physical Medicine, Naturopathic Treatment - Revised Version - Joint Recommendations of the German Society of Rehabilitation Science and the German Society of Physical Medicine and Rehabilitation].

PubMed

Mau, Wilfried; Liebl, Max Emanuel; Deck, Ruth; Lange, Uwe; Smolenski, Ulrich Christian; Walter, Susanne; Gutenbrunner, Christoph

2017-12-01

Since the first publication of learning objectives for the interdisciplinary subject "Rehabilitation, Physical Medicine, Naturopathic Treatment" in undergraduate medical education in 2004 a revision is reasonable due to heterogenous teaching programmes in the faculties and the introduction of the National Competence Based Catalogue of Learning Objectives in Medicine as well as the "Masterplan Medical Education 2020". Therefore the German Society of Rehabilitation Science and the German Society of Physical Medicine and Rehabilitation started a structured consensus process using the DELPHI-method to reduce the learning objectives and arrange them more clearly. Objectives of particular significance are emphasised. All learning objectives are assigned to the cognitive and methodological level 1 or to the action level 2. The learning objectives refer to the less detailed National Competence Based Catalogue of Learning Objectives in Medicine. The revised learning objectives will contribute to further progress in competence based and more homogenous medical teaching in core objectives of Rehabilitation, Physical Medicine, and Naturopathic Treatment in the faculties. © Georg Thieme Verlag KG Stuttgart · New York.

Hybrid Multiagent System for Automatic Object Learning Classification

NASA Astrophysics Data System (ADS)

Gil, Ana; de La Prieta, Fernando; López, Vivian F.

The rapid evolution within the context of e-learning is closely linked to international efforts on the standardization of learning object metadata, which provides learners in a web-based educational system with ubiquitous access to multiple distributed repositories. This article presents a hybrid agent-based architecture that enables the recovery of learning objects tagged in Learning Object Metadata (LOM) and provides individualized help with selecting learning materials to make the most suitable choice among many alternatives.

Assessing the reading comprehension of adults with learning disabilities.

PubMed

Jones, F W; Long, K; Finlay, W M L

2006-06-01

This study's aim was to begin the process of measuring the reading comprehension of adults with mild and borderline learning disabilities, in order to generate information to help clinicians and other professionals to make written material for adults with learning disabilities more comprehensible. The Test for the Reception of Grammar (TROG), with items presented visually rather than orally, and the Reading Comprehension sub-test of the Wechsler Objective Reading Dimensions (WORD) battery were given to 24 service-users of a metropolitan community learning disability team who had an estimated IQ in the range 50-79. These tests were demonstrated to have satisfactory split-half reliability and convergent validity with this population, supporting both their use in this study and in clinical work. Data are presented concerning the distribution across the sample of reading-ages and the comprehension of written grammatical constructions. These data should be useful to those who are preparing written material for adults with learning disabilities.

Interviewing Neuroscientists for an Undergraduate Honors Project

PubMed Central

Montiel, Catalina; Meitzen, John

2017-01-01

Honors projects that supplement standard coursework are a widely used practice in undergraduate curricula. These projects can take many forms, ranging from laboratory research projects to performing service learning to literature analyses. Here we discuss an honors project focused on interviewing neuroscientists to learn about individual scientific practice and career paths, and synthesizing the resulting information into a personal reflection essay. We detail step-by-step instructions for performing this type of project, including how to develop interview questions, a sample project timeline, deliverables, learning objectives and outcomes, and address potential pitfalls. We provide sample interview questions, an interview solicitation email, and in the supplemental materials an example student reflection essay, assessment rubrics, and the transcription of a student-conducted interview of Drs. John Godwin and Santosh Mishra of North Carolina State University. This type of project is a promising method to enable student-researcher communication, and potentially useful to a broad spectrum of both honors and non-honors neuroscience coursework. PMID:29371847

Interviewing Neuroscientists for an Undergraduate Honors Project.

PubMed

Montiel, Catalina; Meitzen, John

2017-01-01

Honors projects that supplement standard coursework are a widely used practice in undergraduate curricula. These projects can take many forms, ranging from laboratory research projects to performing service learning to literature analyses. Here we discuss an honors project focused on interviewing neuroscientists to learn about individual scientific practice and career paths, and synthesizing the resulting information into a personal reflection essay. We detail step-by-step instructions for performing this type of project, including how to develop interview questions, a sample project timeline, deliverables, learning objectives and outcomes, and address potential pitfalls. We provide sample interview questions, an interview solicitation email, and in the supplemental materials an example student reflection essay, assessment rubrics, and the transcription of a student-conducted interview of Drs. John Godwin and Santosh Mishra of North Carolina State University. This type of project is a promising method to enable student-researcher communication, and potentially useful to a broad spectrum of both honors and non-honors neuroscience coursework.

Extended Relation Metadata for SCORM-Based Learning Content Management Systems

ERIC Educational Resources Information Center

Lu, Eric Jui-Lin; Horng, Gwoboa; Yu, Chia-Ssu; Chou, Ling-Ying

2010-01-01

To increase the interoperability and reusability of learning objects, Advanced Distributed Learning Initiative developed a model called Content Aggregation Model (CAM) to describe learning objects and express relationships between learning objects. However, the suggested relations defined in the CAM can only describe structure-oriented…

Visual Attention to Movement and Color in Children with Cortical Visual Impairment

ERIC Educational Resources Information Center

Cohen-Maitre, Stacey Ann; Haerich, Paul

2005-01-01

This study investigated the ability of color and motion to elicit and maintain visual attention in a sample of children with cortical visual impairment (CVI). It found that colorful and moving objects may be used to engage children with CVI, increase their motivation to use their residual vision, and promote visual learning.

New Teen Drivers and Their Parents: What They Know and What They Expect

ERIC Educational Resources Information Center

Sherman, Keith; Lapidus, Garry; Gelven, Erica; Banco, Leonard

2004-01-01

Objectives: To assess teens' and parents' knowledge of teen driver safety and to compare teens' and parents' expectations about learning to drive and acquiring a driver's license. Methods: A convenience sample of 613 Connecticut teens enrolled in commercial driving schools and one of their parents completed self-administered surveys. Results:…

Teachers' Perception Regarding Facial Expressions as an Effective Teaching Tool

ERIC Educational Resources Information Center

Butt, Muhammad Naeem; Iqbal, Mohammad

2011-01-01

The major objective of the study was to explore teachers' perceptions about the importance of facial expression in the teaching-learning process. All the teachers of government secondary schools constituted the population of the study. A sample of 40 teachers, both male and female, in rural and urban areas of district Peshawar, were selected…

Lessons learned from research and surveillance directed at highly pathogenic influenza A viruses in wild birds inhabiting North America

USDA-ARS?s Scientific Manuscript database

Following detections of highly pathogenic (HP) influenza A viruses (IAVs) in wild birds inhabiting East Asia after the turn of the millennium, the intensity of sampling of wild birds for IAVs increased throughout much of North America and the objectives for many research and surveillance efforts wer...

The Role of Emotional Intelligence in Mediating the Relationship between Emerging Adulthood and Academic Achievement

ERIC Educational Resources Information Center

Noor, Farukh; Hanafi, Zahyah

2017-01-01

Purpose: Academic achievement of students can be fostered and improved if they learn to apply emotional intelligence in their emerging adulthood. The core objective of this research is to test the relationship between emerging adulthood and academic achievement by taking emotional intelligence as a mediator. Methodology: The sample comprises 90…

Building Academic Quality in Distance Higher Education. A Monograph in Higher Education Evaluation and Policy.

ERIC Educational Resources Information Center

Chacon-Duque, Fabio J.

The factors that determine course completion and achievement in college distance education were investigated using a sample of 25 courses offered through the Independent Learning Program at the Pennsylvania State University. The main objective was to develop a multivariate model to explain and predict outcomes of distance education. Additional…

Vocabulary Teaching in Foreign Language via Audiovisual Method Technique of Listening and Following Writing Scripts

ERIC Educational Resources Information Center

Bozavli, Ebubekir

2017-01-01

The objective is hereby study is to compare the effects of conventional and audiovisual methods on learning efficiency and success of retention with regard to vocabulary teaching in foreign language. Research sample consists of 21 undergraduate and 7 graduate students studying at Department of French Language Teaching, Kazim Karabekir Faculty of…

Teacher Opinions on Ministry of National Education 2002, 2006, and 2013 Preschool Education Curricula in Turkey

ERIC Educational Resources Information Center

Durmusoglu, Mine Canan

2017-01-01

This study was aimed to make a historical review by collecting and comparing teachers' opinions on target-behaviors/learning-objectives outcomes, content, plans, activities, practices and assessment of the Ministry of National Education (MoNE), Turkey 2002, 2006, and 2013 preschool education curricula (PEC) in six categories. The sample group of…

SRA Economics Materials in Grades One and Two. Evaluation Reports.

ERIC Educational Resources Information Center

Shaver, James P.; Larkins, A. Guy

A class of first graders and a class of second graders in four Salt Lake City schools comprised the experimental sample in a study whose objectives were (1) to develop a test for assessing learning with "Our Working World" materials, published by Science Research Associate (SRA), and (2) to determine if students using the materials made…

Electromagnetic Spectrum. 7th and 8th Grade Agriculture Science Curriculum. Teacher Materials.

ERIC Educational Resources Information Center

Southern Illinois Univ., Carbondale. Dept. of Agricultural Education and Mechanization.

This curriculum guide, the second in a set of six, contains teacher and student materials for a unit on the electromagnetic spectrum prepared as part of a seventh- and eighth-grade agricultural science curriculum that is integrated with science instruction. The guide contains the state goals and sample learning objectives for each goal for…

Curriculum Development for Professional Leaders in Extension Education.

ERIC Educational Resources Information Center

Findlay, Edward Weldon

The study is based on the premise that if one is able to identify the areas of behavior in which professionals require competence, one can link this behavior to a related structure of concepts which may serve as logical teaching and learning objectives in the development of training programs. A sample of 211 extension agents (in agriculture, home…

Ensemble based adaptive over-sampling method for imbalanced data learning in computer aided detection of microaneurysm.

PubMed

Ren, Fulong; Cao, Peng; Li, Wei; Zhao, Dazhe; Zaiane, Osmar

2017-01-01

Diabetic retinopathy (DR) is a progressive disease, and its detection at an early stage is crucial for saving a patient's vision. An automated screening system for DR can help in reduce the chances of complete blindness due to DR along with lowering the work load on ophthalmologists. Among the earliest signs of DR are microaneurysms (MAs). However, current schemes for MA detection appear to report many false positives because detection algorithms have high sensitivity. Inevitably some non-MAs structures are labeled as MAs in the initial MAs identification step. This is a typical "class imbalance problem". Class imbalanced data has detrimental effects on the performance of conventional classifiers. In this work, we propose an ensemble based adaptive over-sampling algorithm for overcoming the class imbalance problem in the false positive reduction, and we use Boosting, Bagging, Random subspace as the ensemble framework to improve microaneurysm detection. The ensemble based over-sampling methods we proposed combine the strength of adaptive over-sampling and ensemble. The objective of the amalgamation of ensemble and adaptive over-sampling is to reduce the induction biases introduced from imbalanced data and to enhance the generalization classification performance of extreme learning machines (ELM). Experimental results show that our ASOBoost method has higher area under the ROC curve (AUC) and G-mean values than many existing class imbalance learning methods. Copyright © 2016 Elsevier Ltd. All rights reserved.

Age-related impairments in active learning and strategic visual exploration.

PubMed

Brandstatt, Kelly L; Voss, Joel L

2014-01-01

Old age could impair memory by disrupting learning strategies used by younger individuals. We tested this possibility by manipulating the ability to use visual-exploration strategies during learning. Subjects controlled visual exploration during active learning, thus permitting the use of strategies, whereas strategies were limited during passive learning via predetermined exploration patterns. Performance on tests of object recognition and object-location recall was matched for younger and older subjects for objects studied passively, when learning strategies were restricted. Active learning improved object recognition similarly for younger and older subjects. However, active learning improved object-location recall for younger subjects, but not older subjects. Exploration patterns were used to identify a learning strategy involving repeat viewing. Older subjects used this strategy less frequently and it provided less memory benefit compared to younger subjects. In previous experiments, we linked hippocampal-prefrontal co-activation to improvements in object-location recall from active learning and to the exploration strategy. Collectively, these findings suggest that age-related memory problems result partly from impaired strategies during learning, potentially due to reduced hippocampal-prefrontal co-engagement.

Perceptual Learning and Attention: Reduction of Object Attention Limitations with Practice

PubMed Central

Dosher, Barbara Anne; Han, Songmei; Lu, Zhong-Lin

2012-01-01

Perceptual learning has widely been claimed to be attention driven; attention assists in choosing the relevant sensory information and attention may be necessary in many cases for learning. In this paper, we focus on the interaction of perceptual learning and attention – that perceptual learning can reduce or eliminate the limitations of attention, or, correspondingly, that perceptual learning depends on the attention condition. Object attention is a robust limit on performance. Two attributes of a single attended object may be reported without loss, while the same two attributes of different objects can exhibit a substantial dual-report deficit due to the sharing of attention between objects. The current experiments document that this fundamental dual-object report deficit can be reduced, or eliminated, through perceptual learning that is partially specific to retinal location. This suggests that alternative routes established by practice may reduce the competition between objects for processing resources. PMID:19796653

Learning while Babbling: Prelinguistic Object-Directed Vocalizations Indicate a Readiness to Learn

ERIC Educational Resources Information Center

Goldstein, Michael H.; Schwade, Jennifer; Briesch, Jacquelyn; Syal, Supriya

2010-01-01

Two studies illustrate the functional significance of a new category of prelinguistic vocalizing--object-directed vocalizations (ODVs)--and show that these sounds are connected to learning about words and objects. Experiment 1 tested 12-month-old infants' perceptual learning of objects that elicited ODVs. Fourteen infants' vocalizations were…

Assessment of the core learning objectives curriculum for the urology clerkship.

PubMed

Rapp, David E; Gong, Edward M; Reynolds, W Stuart; Lucioni, Alvaro; Zagaja, Gregory P

2007-11-01

The traditional approach to the surgical clerkship has limitations, including variability of clinical exposure. To optimize student education we developed and introduced the core learning objectives curriculum, which is designed to allow students freedom to direct their learning and focus on core concepts. We performed a prospective, randomized, controlled study to compare the efficacy of core learning objectives vs traditional curricula through objective and subjective measures. Medical students were randomly assigned to the core learning objectives or traditional curricula during the 2-week urology clerkship. Faculty was blinded to student assignment. Upon rotation completion all students were given a 20-question multiple choice examination covering basic urology concepts. In addition, students completed a questionnaire addressing subjective clerkship satisfaction, comprising 15 questions. Between June 2005 and January 2007, 10 core learning objectives students and 10 traditional students completed the urology clerkship. The average +/- SEM multiple choice examination score was 12.1 +/- 0.87 and 9.8 +/- 0.59 for students assigned to the core learning objectives and traditional curricula, respectively (p <0.05). Subjective scores were higher in the core learning objectives cohort, although this result did not attain statistical significance (124.9 +/- 3.72 vs 114.3 +/- 4.96, p = 0.1). Core learning objectives students reported higher satisfaction in all 15 assessed subjective end points. Our experience suggests that the core learning objectives model may be an effective educational tool to help students achieve a broad and directed exposure to the core urological concepts.

A Data Mining Approach to Improve Re-Accessibility and Delivery of Learning Knowledge Objects

ERIC Educational Resources Information Center

Sabitha, Sai; Mehrotra, Deepti; Bansal, Abhay

2014-01-01

Today Learning Management Systems (LMS) have become an integral part of learning mechanism of both learning institutes and industry. A Learning Object (LO) can be one of the atomic components of LMS. A large amount of research is conducted into identifying benchmarks for creating Learning Objects. Some of the major concerns associated with LO are…

Learned Non-Rigid Object Motion is a View-Invariant Cue to Recognizing Novel Objects

PubMed Central

Chuang, Lewis L.; Vuong, Quoc C.; Bülthoff, Heinrich H.

2012-01-01

There is evidence that observers use learned object motion to recognize objects. For instance, studies have shown that reversing the learned direction in which a rigid object rotated in depth impaired recognition accuracy. This motion reversal can be achieved by playing animation sequences of moving objects in reverse frame order. In the current study, we used this sequence-reversal manipulation to investigate whether observers encode the motion of dynamic objects in visual memory, and whether such dynamic representations are encoded in a way that is dependent on the viewing conditions. Participants first learned dynamic novel objects, presented as animation sequences. Following learning, they were then tested on their ability to recognize these learned objects when their animation sequence was shown in the same sequence order as during learning or in the reverse sequence order. In Experiment 1, we found that non-rigid motion contributed to recognition performance; that is, sequence-reversal decreased sensitivity across different tasks. In subsequent experiments, we tested the recognition of non-rigidly deforming (Experiment 2) and rigidly rotating (Experiment 3) objects across novel viewpoints. Recognition performance was affected by viewpoint changes for both experiments. Learned non-rigid motion continued to contribute to recognition performance and this benefit was the same across all viewpoint changes. By comparison, learned rigid motion did not contribute to recognition performance. These results suggest that non-rigid motion provides a source of information for recognizing dynamic objects, which is not affected by changes to viewpoint. PMID:22661939

Practical coaching by mentors: student midwives' perceptions.

PubMed

Finnerty, Gina; Collington, Val

2013-11-01

The objective of this paper was to explore some of the specific strategies used by midwife mentors to mediate practice learning from the perspective of a sample of student midwives. Audio-diaries were completed by student midwives over ten days in practice and were transcribed using discourse analysis. A sub-sample from 19 students' learning diaries from a national midwifery education study conducted by Pope et al. (2003) has been selected as the diaries informed a separate study. The sample of student midwives were studying on degree and diploma programmes at five case study sites in England. Students described how their mentors apparently successfully tailored their teaching to the students' needs. However, there was perceived disparity in techniques used by individual mentors to pass on their practice know-how. The findings demonstrate the pivotal role of the mentor for 'scaffolding' learning and also using 'fading' techniques within a cognitive apprenticeship model. Mentors need assistance to adapt their mentoring styles and to use a wider range of instruction strategies for student midwives. This has practical implications for mentor preparation programmes and mentorship models. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

Teacher Trainees as Learning Object Designers: Problems and Issues in Learning Object Development Process

ERIC Educational Resources Information Center

Guler, Cetin; Altun, Arif

2010-01-01

Learning objects (LOs) can be defined as resources that are reusable, digital with the aim of fulfilling learning objectives (or expectations). Educators, both at the individual and institutional levels, are cautioned about the fact that LOs are to be processed through a proper development process. Who should be involved in the LO development…

Patterns of Learning Object Reuse in the Connexions Repository

ERIC Educational Resources Information Center

Duncan, S. M.

2009-01-01

Since the term "learning object" was first published, there has been either an explicit or implicit expectation of reuse. There has also been a lot of speculation about why learning objects are, or are not, reused. This study quantitatively examined the actual amount and type of learning object use, to include reuse, modification, and translation,…

Writing objectives and evaluating learning in the affective domain.

PubMed

Maier-Lorentz, M M

1999-01-01

Staff educators recognize the importance of affective competency for effective nursing practice. Inservice programs must include affective learning with objectives stated in measurable terms. Staff educators often express frustration in developing affective objectives and evaluating the learning outcome because attitudes and feelings are usually inferred from observations. This article presents affective learning objectives for a gerontological nursing inservice program and a rating scale that measures attitudes to evaluate the learning outcome.

Learning to learn causal models.

PubMed

Kemp, Charles; Goodman, Noah D; Tenenbaum, Joshua B

2010-09-01

Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical Bayesian framework that helps to explain how learning about several causal systems can accelerate learning about systems that are subsequently encountered. Given experience with a set of objects, our framework learns a causal model for each object and a causal schema that captures commonalities among these causal models. The schema organizes the objects into categories and specifies the causal powers and characteristic features of these categories and the characteristic causal interactions between categories. A schema of this kind allows causal models for subsequent objects to be rapidly learned, and we explore this accelerated learning in four experiments. Our results confirm that humans learn rapidly about the causal powers of novel objects, and we show that our framework accounts better for our data than alternative models of causal learning. Copyright © 2010 Cognitive Science Society, Inc.

Remembering Math: The Design of Digital Learning Objects to Spark Professional Learning

ERIC Educational Resources Information Center

Halverson, Richard; Wolfenstein, Moses; Williams, Caroline C.; Rockman, Charles

2009-01-01

This article describes how the design of digital learning objects can spark professional learning. The challenge was to build learning objects that would help experienced special education teachers, who had been teaching in math classes, to demonstrate their proficiency in middle and secondary school mathematics on the PRAXIS examination. While…

Collaborative Production of Learning Objects on French Literary Works Using the LOC Software

ERIC Educational Resources Information Center

Penman, Christine

2015-01-01

This case study situates the collaborative design of learning objects (interactive online learning material) using the LOC (Learning Object Creator) software in the context of language activities external to the core learning activities of language students at a UK university. It describes the creative and pedagogical processes leading to the…

Learning Objects and Virtual Learning Environments Technical Evaluation Criteria

ERIC Educational Resources Information Center

Kurilovas, Eugenijus; Dagiene, Valentina

2009-01-01

The main scientific problems investigated in this article deal with technical evaluation of quality attributes of the main components of e-Learning systems (referred here as DLEs--Digital Libraries of Educational Resources and Services), i.e., Learning Objects (LOs) and Virtual Learning Environments (VLEs). The main research object of the work is…

A Case Study: Developing Learning Objects with an Explicit Learning Design

ERIC Educational Resources Information Center

Watson, Julie

2010-01-01

In learning object design an emphasis on visual attractiveness and high technological impact has seemed to persist while content frequently reflects a lack of clear pedagogical basis for the application of learning objects for online learning. Most apparent is the absence of supportive scaffolding for the student user; interactivity built on an…

Implementation of formal learning objectives during a physical medicine and rehabilitation sports medicine rotation.

PubMed

Smith, Jay; Laskowski, Edward R; Newcomer-Aney, Karen L; Thompson, Jeffrey M; Schaefer, Michael P; Morfe, Erasmus G

2005-04-01

To develop and implement formal learning objectives during a physical medicine and rehabilitation sports medicine rotation and characterize resident experiences with the objectives over a 16-mo period. Prospective, including learning objective development, implementation, and postrotation survey. A total of 69 learning objectives were developed by physical medicine and rehabilitation staff physician consensus, including 39 core objectives. Eighteen residents completed 4-wk sports medicine rotations from January 2003 through April 2004. Residents completed an average of 31 total objectives (45%; range, 3-52), of which 24 (62%; range, 3-35) were core. Residents completed the highest percentage of knee (60%), shoulder (57%), and ankle-foot (57%) objectives and reported that objectives related to these areas were most effective to facilitate learning. In general, residents reported that objective content was good and that the objectives delineated important concepts to learn during the rotation. Seventeen of 18 residents indicated that the objectives should be permanently implemented into the sports rotation and that similar objectives should be developed for other rotations. Based on our experience and the recommendations of residents, the average resident should be able to complete approximately 30 objectives during a typical 4-wk rotation. Successful implementation of specific, consensus-derived learning objectives is possible within the context of a busy clinical practice. Our initial physician staff and resident experience with the objectives suggests that this model may be useful as a supplementary educational tool in physical medicine and rehabilitation residency programs.

Meanings of care in health promotion.

PubMed

Falcón, Gladys Carmela Santos; Erdmann, Alacoque Lorenzini; Backes, Dirce Stein

2008-01-01

The objective of the study is to understand the meaning built by students and professors on health promotion in the teaching and learning process of health care in Nursing. It is a qualitative study using ground theory as a methodological reference. Data was collected through interviews, with three samples groups, 13 students and four professors, by classroom observation, and through meetings with nursing professors. The central subject resulting from this analysis was: constructing teaching and learning in order, disorder and self organization for a new way of caring promoting health. The teaching/learning process directed at health promotion develops in a stage of crisis, going from a state of order to a state of disorder that is uncertain and contradictory regarding what society understands about health.

An Investigation into Digital Media: Characteristics of Learning Objects Which K-12 Teachers Determine Meet Their Instructional Needs

ERIC Educational Resources Information Center

Guthrie, Patricia Ann

2010-01-01

In recent years, learning objects have emerged as an instructional tool for teachers. Digital libraries and collections provide teachers with free or fee-base access to a variety of learning objects from photos and famous speeches to Flash animations and interactive Java Applets. Learning objects offer opportunities for students to interact with…

Inquiry-Based Learning Using Everyday Objects: Hands-On Instructional Strategies That Promote Active Learning in Grades 3-8.

ERIC Educational Resources Information Center

Alvarado, Amy Edmonds; Herr, Patricia R.

This book explores the concept of using everyday objects as a process initiated both by students and teachers, encouraging growth in student observation, inquisitiveness, and reflection in learning. After "Introduction: Welcome to Inquiry-Based Learning using Everyday Objects (Object-Based Inquiry), there are nine chapters in two parts. Part 1,…

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

The Analysis of the Relationship between Primary Learning Styles and Learning Objects in an Online Environment

ERIC Educational Resources Information Center

Özdemir, Muzaffer

2016-01-01

This study investigates the relationships between the primary learning styles of students and different learning objects presented simultaneously in an online learning environment in the context of the usage levels of these objects. A total of 103 sophomores from a Turkish State University participated in the study. Felder-Solomon Index of…

Building Interoperable Learning Objects Using Reduced Learning Object Metadata

ERIC Educational Resources Information Center

Saleh, Mostafa S.

2005-01-01

The new e-learning generation depends on Semantic Web technology to produce learning objects. As the production of these components is very costly, they should be produced and registered once, and reused and adapted in the same context or in other contexts as often as possible. To produce those components, developers should use learning standards…

Teaching Dental Students to Understand the Temporomandibular Joint Using MRI: Comparison of Conventional and Digital Learning Methods.

PubMed

Arús, Nádia A; da Silva, Átila M; Duarte, Rogério; da Silveira, Priscila F; Vizzotto, Mariana B; da Silveira, Heraldo L D; da Silveira, Heloisa E D

2017-06-01

The aims of this study were to evaluate and compare the performance of dental students in interpreting the temporomandibular joint (TMJ) with magnetic resonance imaging (MRI) scans using two learning methods (conventional and digital interactive learning) and to examine the usability of the digital learning object (DLO). The DLO consisted of tutorials about MRI and anatomic and functional aspects of the TMJ. In 2014, dental students in their final year of study who were enrolled in the elective "MRI Interpretation of the TMJ" course comprised the study sample. After exclusions for nonattendance and other reasons, 29 of the initial 37 students participated in the study, for a participation rate of 78%. The participants were divided into two groups: a digital interactive learning group (n=14) and a conventional learning group (n=15). Both methods were assessed by an objective test applied before and after training and classes. Aspects such as support and training requirements, complexity, and consistency of the DLO were also evaluated using the System Usability Scale (SUS). A significant between-group difference in the posttest results was found, with the conventional learning group scoring better than the DLO group, indicated by mean scores of 9.20 and 8.11, respectively, out of 10. However, when the pretest and posttest results were compared, both groups showed significantly improved performance. The SUS score was 89, which represented a high acceptance of the DLO by the users. The students who used the conventional method of learning showed superior performance in interpreting the TMJ using MRI compared to the group that used digital interactive learning.

Implementing Infrastructures for Managing Learning Objects

ERIC Educational Resources Information Center

Klemke, Roland; Ternier, Stefaan; Kalz, Marco; Specht, Marcus

2010-01-01

Making learning objects available is critical to reuse learning resources. Making content transparently available and providing added value to different stakeholders is among the goals of the European Commission's eContentplus programme. This paper analyses standards and protocols relevant for making learning objects accessible in distributed data…

Credit assignment between body and object probed by an object transportation task.

PubMed

Kong, Gaiqing; Zhou, Zhihao; Wang, Qining; Kording, Konrad; Wei, Kunlin

2017-10-17

It has been proposed that learning from movement errors involves a credit assignment problem: did I misestimate properties of the object or those of my body? For example, an overestimate of arm strength and an underestimate of the weight of a coffee cup can both lead to coffee spills. Though previous studies have found signs of simultaneous learning of the object and of the body during object manipulation, there is little behavioral evidence about their quantitative relation. Here we employed a novel weight-transportation task, in which participants lift the first cup filled with liquid while assessing their learning from errors. Specifically, we examined their transfer of learning when switching to a contralateral hand, the second identical cup, or switching both hands and cups. By comparing these transfer behaviors, we found that 25% of the learning was attributed to the object (simply because of the use of the same cup) and 58% of the learning was attributed to the body (simply because of the use of the same hand). The nervous system thus seems to partition the learning of object manipulation between the object and the body.

Machine-learning-based real-bogus system for the HSC-SSP moving object detection pipeline

NASA Astrophysics Data System (ADS)

Lin, Hsing-Wen; Chen, Ying-Tung; Wang, Jen-Hung; Wang, Shiang-Yu; Yoshida, Fumi; Ip, Wing-Huen; Miyazaki, Satoshi; Terai, Tsuyoshi

2018-01-01

Machine-learning techniques are widely applied in many modern optical sky surveys, e.g., Pan-STARRS1, PTF/iPTF, and the Subaru/Hyper Suprime-Cam survey, to reduce human intervention in data verification. In this study, we have established a machine-learning-based real-bogus system to reject false detections in the Subaru/Hyper-Suprime-Cam Strategic Survey Program (HSC-SSP) source catalog. Therefore, the HSC-SSP moving object detection pipeline can operate more effectively due to the reduction of false positives. To train the real-bogus system, we use stationary sources as the real training set and "flagged" data as the bogus set. The training set contains 47 features, most of which are photometric measurements and shape moments generated from the HSC image reduction pipeline (hscPipe). Our system can reach a true positive rate (tpr) ˜96% with a false positive rate (fpr) ˜1% or tpr ˜99% at fpr ˜5%. Therefore, we conclude that stationary sources are decent real training samples, and using photometry measurements and shape moments can reject false positives effectively.

Difference among Levels of Inquiry: Process Skills Improvement at Senior High School in Indonesia

ERIC Educational Resources Information Center

Hardianti, Tuti; Kuswanto, Heru

2017-01-01

The objective of the research concerned here was to discover the difference in effectiveness among Levels 2, 3, and 4 of inquiry learning in improving students' process skills. The research was a quasi-experimental study using the pretest-posttest non-equivalent control group research design. Three sample groups were selected by means of cluster…

Have Astronauts Visited Neptune? Student Ideas about How Scientists Study the Solar System

ERIC Educational Resources Information Center

Palma, Christopher; Plummer, Julia; Rubin, KeriAnn; Flarend, Alice; Ong, Yann Shiou; McDonald, Scott; Ghent, Chrysta; Gleason, Timothy; Furman, Tanya

2017-01-01

The nature of students' ideas about the scientific practices used by astronomers when studying objects in our Solar System is of widespread interest to discipline-based astronomy education researchers. A sample of middle-school, high-school, and college students (N = 42) in the U.S. were interviewed about how astronomers were able to learn about…

Electrical Energy. 7th and 8th Grade Agriculture Science Curriculum. Teacher Materials.

ERIC Educational Resources Information Center

Southern Illinois Univ., Carbondale. Dept. of Agricultural Education and Mechanization.

This curriculum guide, the fifth in a set of six, contains teacher and student materials for a unit on electrical energy prepared as part of a seventh- and eighth-grade agricultural science curriculum that is integrated with science instruction. The guide contains the state goals and sample learning objectives for each goal for students in grades…

Effects of Training Method and Gender on Learning 2D/3D Geometry

ERIC Educational Resources Information Center

Khairulanuar, Samsudin; Nazre, Abd Rashid; Jamilah, H.; Sairabanu, Omar Khan; Norasikin, Fabil

2010-01-01

This article reports the findings of an experimental study involving 36 primary school students (16 girls, 20 boys, Mean age = 9.5 years, age range: 8-10 years) in geometrical understanding of 2D and 3D objects. Students were assigned into two experimental groups and one control group based on a stratified random sampling procedure. The first…

Identifying the Financial Literacy Skills Necessary to Run a Small New Zealand Business

ERIC Educational Resources Information Center

Samkin, Grant; Pitu, Elizabeth; Low, Mary

2014-01-01

The objectives of this paper are to identify the financial skills small business owners believe necessary to be successful in business, and to establish whether there is a role for secondary school accounting in contributing to the learning of these skills. A combination of a social network website and snowball sampling technique was used to…

Learning from Non-Reported Data: Interpreting Missing Body Mass Index Values in Young Children

ERIC Educational Resources Information Center

Arbour-Nicitopoulos, Kelly P.; Faulkner, Guy E.; Leatherdale, Scott T.

2010-01-01

The objective of this study was to examine the pattern of relations between missing weight and height (BMI) data and a range of demographic, physical activity, sedentary behavior, and academic measures in a young sample of elementary school children. A secondary analysis of a large cross-sectional study, PLAY-On, was conducted using self-reported…

Linking Course-Embedded Assessment Measures and Performance on the Educational Testing Service Major Field Test in Business

ERIC Educational Resources Information Center

Barboza, Gustavo A.; Pesek, James

2012-01-01

Assessment of the business curriculum and its learning goals and objectives has become a major field of interest for business schools. The exploratory results of the authors' model using a sample of 173 students show robust support for the hypothesis that high marks in course-embedded assessment on business-specific analytical skills positively…

Predictable Locations Aid Early Object Name Learning

PubMed Central

Benitez, Viridiana L.; Smith, Linda B.

2012-01-01

Expectancy-based localized attention has been shown to promote the formation and retrieval of multisensory memories in adults. Three experiments show that these processes also characterize attention and learning in 16- to 18- month old infants and, moreover, that these processes may play a critical role in supporting early object name learning. The three experiments show that infants learn names for objects when those objects have predictable rather than varied locations, that infants who anticipate the location of named objects better learn those object names, and that infants integrate experiences that are separated in time but share a common location. Taken together, these results suggest that localized attention, cued attention, and spatial indexing are an inter-related set of processes in young children that aid in the early building of coherent object representations. The relevance of the experimental results and spatial attention for everyday word learning are discussed. PMID:22989872

Preceptors’ Self-Assessment of Their Ability to Perform the Learning Objectives of an Experiential Program

PubMed Central

2012-01-01

Objective. To evaluate preceptors’ perception of their ability to perform the Structured Practical Experiences in Pharmacy (SPEP) learning objectives through a self-assessment activity. Methods. A self-assessment instrument consisting of 28 learning objectives associated with clinic, community, and hospital pharmacy practice experiences were developed. Preceptors rated their performance ability for each of the learning objectives using a 3-point Likert scale. Results. Of the 116 preceptors, 89 (77%) completed the self-assessment survey instrument. The overall preceptor responses to the items on performance of the 28 SPEP learning objectives ranged from good to excellent. Years of experience, practice experience setting, and involvement as a SPEP or SPEP and PharmD preceptor had no influence on their self-reported capabilities. Conclusion. Most preceptors rated their ability to perform the learning objectives for the structured practical experiences in pharmacy as high. Competency areas requiring further preceptor development were identified. PMID:23193333

Participative Knowledge Production of Learning Objects for E-Books.

ERIC Educational Resources Information Center

Dodero, Juan Manuel; Aedo, Ignacio; Diaz, Paloma

2002-01-01

Defines a learning object as any digital resource that can be reused to support learning and thus considers electronic books as learning objects. Highlights include knowledge management; participative knowledge production, i.e. authoring electronic books by a distributed group of authors; participative knowledge production architecture; and…

Personalized Learning Objects Recommendation Based on the Semantic-Aware Discovery and the Learner Preference Pattern

ERIC Educational Resources Information Center

Wang, Tzone I; Tsai, Kun Hua; Lee, Ming Che; Chiu, Ti Kai

2007-01-01

With vigorous development of the Internet, especially the web page interaction technology, distant E-learning has become more and more realistic and popular. Digital courses may consist of many learning units or learning objects and, currently, many learning objects are created according to SCORM standard. It can be seen that, in the near future,…

Learning Object Retrieval and Aggregation Based on Learning Styles

ERIC Educational Resources Information Center

Ramirez-Arellano, Aldo; Bory-Reyes, Juan; Hernández-Simón, Luis Manuel

2017-01-01

The main goal of this article is to develop a Management System for Merging Learning Objects (msMLO), which offers an approach that retrieves learning objects (LOs) based on students' learning styles and term-based queries, which produces a new outcome with a better score. The msMLO faces the task of retrieving LOs via two steps: The first step…

The effects of concept and vee mappings under three learning modes on Jamaican eighth graders' knowledge of nutrition and plant reproduction

NASA Astrophysics Data System (ADS)

Ugwu, Okechukwu; Soyibo, Kola

2004-01-01

The first objective of this study was to investigate if the experimental students' post-test knowledge of nutrition and plant reproduction would be improved more significantly than that of their control group counterparts based on their treatment, attitudes to science, self-esteem, gender and socio-economic background. Treatment involved teaching the experimental students under three learning modes--pure cooperative, cooperative-competitive and individualistic whole class interpersonal competitive condition--using concept and vee mappings and the lecture method. The control groups received the same treatment but were not exposed to concept and vee mappings. This study's second objective was to determine which of the three learning modes would produce the highest post-test mean gain in the subjects' knowledge of the two biology concepts. The study's sample comprised 932 eighth graders (12-13-year-olds) in 14 co-educational comprehensive high schools randomly selected from two Jamaican parishes. An integrated science performance test, an attitudes to science questionnaire and a self-esteem questionnaire were used to collect data. The results indicated that the experimental students (a) under the three learning modes, (b) with high, moderate, and low attitudes to science, and (c) with high, moderate, and low self-esteem, performed significantly better than their control group counterparts. The individualist whole class learning mode engendered the highest mean gain on the experimental students' knowledge, while the cooperative-competitive learning mode generated the highest mean gain for the control group students.

Learning Objects--Instructional Metadata and Sequencing.

ERIC Educational Resources Information Center

Redeker, Giselher

The main focus of current discussions within the standardization process of learning technology is on economical opportunities and technical aspects of learning objects. There has been little discussion about the instructional or didactical issues. The purpose of this paper is to conceptualize a taxonomy of learning objects for the facilitation of…

The International Learning Object Metadata Survey

ERIC Educational Resources Information Center

Friesen, Norm

2004-01-01

A wide range of projects and organizations is currently making digital learning resources (learning objects) available to instructors, students, and designers via systematic, standards-based infrastructures. One standard that is central to many of these efforts and infrastructures is known as Learning Object Metadata (IEEE 1484.12.1-2002, or LOM).…

Learning the 3-D structure of objects from 2-D views depends on shape, not format

PubMed Central

Tian, Moqian; Yamins, Daniel; Grill-Spector, Kalanit

2016-01-01

Humans can learn to recognize new objects just from observing example views. However, it is unknown what structural information enables this learning. To address this question, we manipulated the amount of structural information given to subjects during unsupervised learning by varying the format of the trained views. We then tested how format affected participants' ability to discriminate similar objects across views that were rotated 90° apart. We found that, after training, participants' performance increased and generalized to new views in the same format. Surprisingly, the improvement was similar across line drawings, shape from shading, and shape from shading + stereo even though the latter two formats provide richer depth information compared to line drawings. In contrast, participants' improvement was significantly lower when training used silhouettes, suggesting that silhouettes do not have enough information to generate a robust 3-D structure. To test whether the learned object representations were format-specific or format-invariant, we examined if learning novel objects from example views transfers across formats. We found that learning objects from example line drawings transferred to shape from shading and vice versa. These results have important implications for theories of object recognition because they suggest that (a) learning the 3-D structure of objects does not require rich structural cues during training as long as shape information of internal and external features is provided and (b) learning generates shape-based object representations independent of the training format. PMID:27153196

Effect of tDCS on task relevant and irrelevant perceptual learning of complex objects.

PubMed

Van Meel, Chayenne; Daniels, Nicky; de Beeck, Hans Op; Baeck, Annelies

2016-01-01

During perceptual learning the visual representations in the brain are altered, but these changes' causal role has not yet been fully characterized. We used transcranial direct current stimulation (tDCS) to investigate the role of higher visual regions in lateral occipital cortex (LO) in perceptual learning with complex objects. We also investigated whether object learning is dependent on the relevance of the objects for the learning task. Participants were trained in two tasks: object recognition using a backward masking paradigm and an orientation judgment task. During both tasks, an object with a red line on top of it were presented in each trial. The crucial difference between both tasks was the relevance of the object: the object was relevant for the object recognition task, but not for the orientation judgment task. During training, half of the participants received anodal tDCS stimulation targeted at the lateral occipital cortex (LO). Afterwards, participants were tested on how well they recognized the trained objects, the irrelevant objects presented during the orientation judgment task and a set of completely new objects. Participants stimulated with tDCS during training showed larger improvements of performance compared to participants in the sham condition. No learning effect was found for the objects presented during the orientation judgment task. To conclude, this study suggests a causal role of LO in relevant object learning, but given the rather low spatial resolution of tDCS, more research on the specificity of this effect is needed. Further, mere exposure is not sufficient to train object recognition in our paradigm.

Exploring emerging learning needs: a UK-wide consultation on environmental sustainability learning objectives for medical education.

PubMed

Walpole, Sarah C; Mortimer, Frances; Inman, Alice; Braithwaite, Isobel; Thompson, Trevor

2015-12-24

This study aimed to engage wide-ranging stakeholders and develop consensus learning objectives for undergraduate and postgraduate medical education. A UK-wide consultation garnered opinions of healthcare students, healthcare educators and other key stakeholders about environmental sustainability in medical education. The policy Delphi approach informed this study. Draft learning objectives were revised iteratively during three rounds of consultation: online questionnaire or telephone interview, face-to-face seminar and email consultation. Twelve draft learning objectives were developed based on review of relevant literature. In round one, 64 participants' median ratings of the learning objectives were 3.5 for relevance and 3.0 for feasibility on a Likert scale of one to four. Revisions were proposed, e.g. to highlight relevance to public health and professionalism. Thirty three participants attended round two. Conflicting opinions were explored. Added content areas included health benefits of sustainable behaviours. To enhance usability, restructuring provided three overarching learning objectives, each with subsidiary points. All participants from rounds one and two were contacted in round three, and no further edits were required. This is the first attempt to define consensus learning objectives for medical students about environmental sustainability. Allowing a wide range of stakeholders to comment on multiple iterations of the document stimulated their engagement with the issues raised and ownership of the resulting learning objectives.

[Digital learning object for diagnostic reasoning in nursing applied to the integumentary system].

PubMed

da Costa, Cecília Passos Vaz; Luz, Maria Helena Barros Araújo

2015-12-01

To describe the creation of a digital learning object for diagnostic reasoning in nursing applied to the integumentary system at a public university of Piaui. A methodological study applied to technological production based on the pedagogical framework of problem-based learning. The methodology for creating the learning object observed the stages of analysis, design, development, implementation and evaluation recommended for contextualized instructional design. The revised taxonomy of Bloom was used to list the educational goals. The four modules of the developed learning object were inserted into the educational platform Moodle. The theoretical assumptions allowed the design of an important online resource that promotes effective learning in the scope of nursing education. This study should add value to nursing teaching practices through the use of digital learning objects for teaching diagnostic reasoning applied to skin and skin appendages.

Developing Learning Objectives for Accounting Ethics Using Bloom's Taxonomy

ERIC Educational Resources Information Center

Kidwell, Linda A.; Fisher, Dann G.; Braun, Robert L.; Swanson, Diane L.

2013-01-01

The purpose of our article is to offer a set of core knowledge learning objectives for accounting ethics education. Using Bloom's taxonomy of educational objectives, we develop learning objectives in six content areas: codes of ethical conduct, corporate governance, the accounting profession, moral development, classical ethics theories, and…

Design, Development, and Validation of Learning Objects

ERIC Educational Resources Information Center

Nugent, Gwen; Soh, Leen-Kiat; Samal, Ashok

2006-01-01

A learning object is a small, stand-alone, mediated content resource that can be reused in multiple instructional contexts. In this article, we describe our approach to design, develop, and validate Shareable Content Object Reference Model (SCORM) compliant learning objects for undergraduate computer science education. We discuss the advantages of…

How learning might strengthen existing visual object representations in human object-selective cortex.

PubMed

Brants, Marijke; Bulthé, Jessica; Daniels, Nicky; Wagemans, Johan; Op de Beeck, Hans P

2016-02-15

Visual object perception is an important function in primates which can be fine-tuned by experience, even in adults. Which factors determine the regions and the neurons that are modified by learning is still unclear. Recently, it was proposed that the exact cortical focus and distribution of learning effects might depend upon the pre-learning mapping of relevant functional properties and how this mapping determines the informativeness of neural units for the stimuli and the task to be learned. From this hypothesis we would expect that visual experience would strengthen the pre-learning distributed functional map of the relevant distinctive object properties. Here we present a first test of this prediction in twelve human subjects who were trained in object categorization and differentiation, preceded and followed by a functional magnetic resonance imaging session. Specifically, training increased the distributed multi-voxel pattern information for trained object distinctions in object-selective cortex, resulting in a generalization from pre-training multi-voxel activity patterns to after-training activity patterns. Simulations show that the increased selectivity combined with the inter-session generalization is consistent with a training-induced strengthening of a pre-existing selectivity map. No training-related neural changes were detected in other regions. In sum, training to categorize or individuate objects strengthened pre-existing representations in human object-selective cortex, providing a first indication that the neuroanatomical distribution of learning effects depends upon the pre-learning mapping of visual object properties. Copyright © 2015 Elsevier Inc. All rights reserved.

Mapping seabed sediments: Comparison of manual, geostatistical, object-based image analysis and machine learning approaches

NASA Astrophysics Data System (ADS)

Diesing, Markus; Green, Sophie L.; Stephens, David; Lark, R. Murray; Stewart, Heather A.; Dove, Dayton

2014-08-01

Marine spatial planning and conservation need underpinning with sufficiently detailed and accurate seabed substrate and habitat maps. Although multibeam echosounders enable us to map the seabed with high resolution and spatial accuracy, there is still a lack of fit-for-purpose seabed maps. This is due to the high costs involved in carrying out systematic seabed mapping programmes and the fact that the development of validated, repeatable, quantitative and objective methods of swath acoustic data interpretation is still in its infancy. We compared a wide spectrum of approaches including manual interpretation, geostatistics, object-based image analysis and machine-learning to gain further insights into the accuracy and comparability of acoustic data interpretation approaches based on multibeam echosounder data (bathymetry, backscatter and derivatives) and seabed samples with the aim to derive seabed substrate maps. Sample data were split into a training and validation data set to allow us to carry out an accuracy assessment. Overall thematic classification accuracy ranged from 67% to 76% and Cohen's kappa varied between 0.34 and 0.52. However, these differences were not statistically significant at the 5% level. Misclassifications were mainly associated with uncommon classes, which were rarely sampled. Map outputs were between 68% and 87% identical. To improve classification accuracy in seabed mapping, we suggest that more studies on the effects of factors affecting the classification performance as well as comparative studies testing the performance of different approaches need to be carried out with a view to developing guidelines for selecting an appropriate method for a given dataset. In the meantime, classification accuracy might be improved by combining different techniques to hybrid approaches and multi-method ensembles.

Spontaneous revisitation during visual exploration as a link among strategic behavior, learning, and the hippocampus.

PubMed

Voss, Joel L; Warren, David E; Gonsalves, Brian D; Federmeier, Kara D; Tranel, Dan; Cohen, Neal J

2011-08-02

Effective exploratory behaviors involve continuous updating of sensory sampling to optimize the efficacy of information gathering. Despite some work on this issue in animals, little information exists regarding the cognitive or neural mechanisms for this sort of behavioral optimization in humans. Here we examined a visual exploration phenomenon that occurred when human subjects studying an array of objects spontaneously looked "backward" in their scanning paths to view recently seen objects again. This "spontaneous revisitation" of recently viewed objects was associated with enhanced hippocampal activity and superior subsequent memory performance in healthy participants, but occurred only rarely in amnesic patients with severe damage to the hippocampus. These findings demonstrate the necessity of the hippocampus not just in the aspects of long-term memory with which it has been associated previously, but also in the short-term adaptive control of behavior. Functional neuroimaging showed hippocampal engagement occurring in conjunction with frontocerebellar circuits, thereby revealing some of the larger brain circuitry essential for the strategic deployment of information-seeking behaviors that optimize learning.

Word Learning in Children with Autism Spectrum Disorders

PubMed Central

Luyster, Rhiannon; Lord, Catherine

2010-01-01

Autism Spectrum Disorders (ASD) have been gaining attention, partly as an example of unusual developmental trajectories related to early neurobiological differences. The present investigation addressed the process of learning new words in order to explore mechanisms of language delay and impairment. The sample included 21 typically developing toddlers matched on expressive vocabulary with 21 young children with ASD. Two tasks were administered to teach children a new word and were supplemented by cognitive and diagnostic measures. In most analyses, there were no group differences in performance. Children with ASD did not consistently make mapping errors, even in word learning situations which required the use of social information. These findings indicate that some children with ASD, in developmentally appropriate tasks, are able to use information from social interactions to guide word-object mappings. This result has important implications for our understanding of how children with ASD learn language. PMID:19899931

Component Pin Recognition Using Algorithms Based on Machine Learning

NASA Astrophysics Data System (ADS)

Xiao, Yang; Hu, Hong; Liu, Ze; Xu, Jiangchang

2018-04-01

The purpose of machine vision for a plug-in machine is to improve the machine’s stability and accuracy, and recognition of the component pin is an important part of the vision. This paper focuses on component pin recognition using three different techniques. The first technique involves traditional image processing using the core algorithm for binary large object (BLOB) analysis. The second technique uses the histogram of oriented gradients (HOG), to experimentally compare the effect of the support vector machine (SVM) and the adaptive boosting machine (AdaBoost) learning meta-algorithm classifiers. The third technique is the use of an in-depth learning method known as convolution neural network (CNN), which involves identifying the pin by comparing a sample to its training. The main purpose of the research presented in this paper is to increase the knowledge of learning methods used in the plug-in machine industry in order to achieve better results.

Unintended Learning in Primary School Practical Science Lessons from Polanyi's Perspective of Intellectual Passion

NASA Astrophysics Data System (ADS)

Park, Jisun; Song, Jinwoong; Abrahams, Ian

2016-03-01

This study explored, from the perspective of intellectual passion developed by Michael Polanyi, the unintended learning that occurred in primary practical science lessons. We use the term `unintended' learning to distinguish it from `intended' learning that appears in teachers' learning objectives. Data were collected using video and audio recordings of a sample of twenty-four whole class practical science lessons, taught by five teachers, in Korean primary schools with 10- to 12-year-old students. In addition, video and audio recordings were made for each small group of students working together in order to capture their activities and intra-group discourse. Pre-lesson interviews with the teachers were undertaken and audio-recorded to ascertain their intended learning objectives. Selected key vignettes, including unintended learning, were analysed from the perspective of intellectual passion developed by Polanyi. What we found in this study is that unintended learning could occur when students got interested in something in the first place and could maintain their interest. In addition, students could get conceptual knowledge when they tried to connect their experience to their related prior knowledge. It was also found that the processes of intended learning and of unintended learning were different. Intended learning was characterized by having been planned by the teacher who then sought to generate students' interest in it. In contrast, unintended learning originated from students' spontaneous interest and curiosity as a result of unplanned opportunities. Whilst teachers' persuasive passion comes first in the process of intended learning, students' heuristic passion comes first in the process of unintended learning. Based on these findings, we argue that teachers need to be more aware that unintended learning, on the part of individual students, can occur during their lesson and to be able to better use this opportunity so that this unintended learning can be shared by the whole class. Furthermore, we argue that teachers' deliberate action and a more interactive classroom culture are necessary in order to allow students to develop, in addition to heuristic passion, persuasive passion towards their unintended learning.

Learning Objects as Tools for Teaching Information Literacy Online: A Survey of Librarian Usage

ERIC Educational Resources Information Center

Mestre, Lori S.; Baures, Lisa; Niedbala, Mona; Bishop, Corinne; Cantrell, Sarah; Perez, Alice; Silfen, Kate

2011-01-01

Based on information gathered from two discussion sessions moderated by members of the Education and Behavioral Sciences Section's Online Learning Research Committee a survey was conducted to identify how librarians use course/learning management systems and learning objects to deliver instruction. Objectives of the study were to identify the…

Learning from Objects: A Future for 21st Century Urban Arts Education

ERIC Educational Resources Information Center

Lasky, Dorothea

2009-01-01

In this technological age, where mind and body are increasingly disconnected in the classroom, object-based learning--along with strong museum-school partnerships--provide many benefits for student learning. In this article, the author first outlines some of the special mind-body connections that object-based learning in museums affords learners…

Learning Grasp Context Distinctions that Generalize

NASA Technical Reports Server (NTRS)

Platt, Robert; Grupen, Roderic A.; Fagg, Andrew H.

2006-01-01

Control-based approaches to grasp synthesis create grasping behavior by sequencing and combining control primitives. In the absence of any other structure, these approaches must evaluate a large number of feasible control sequences as a function of object shape, object pose, and task. This work explores a new approach to grasp synthesis that limits consideration to variations on a generalized localize-reach-grasp control policy. A new learning algorithm, known as schema structured learning, is used to learn which instantiations of the generalized policy are most likely to lead to a successful grasp in different problem contexts. Two experiments are described where Dexter, a bimanual upper torso, learns to select an appropriate grasp strategy as a function of object eccentricity and orientation. In addition, it is shown that grasp skills learned in this way can generalize to new objects. Results are presented showing that after learning how to grasp a small, representative set of objects, the robot's performance quantitatively improves for similar objects that it has not experienced before.

Transforming clinical imaging and 3D data for virtual reality learning objects: HTML5 and mobile devices implementation.

PubMed

Trelease, Robert B; Nieder, Gary L

2013-01-01

Web deployable anatomical simulations or "virtual reality learning objects" can easily be produced with QuickTime VR software, but their use for online and mobile learning is being limited by the declining support for web browser plug-ins for personal computers and unavailability on popular mobile devices like Apple iPad and Android tablets. This article describes complementary methods for creating comparable, multiplatform VR learning objects in the new HTML5 standard format, circumventing platform-specific limitations imposed by the QuickTime VR multimedia file format. Multiple types or "dimensions" of anatomical information can be embedded in such learning objects, supporting different kinds of online learning applications, including interactive atlases, examination questions, and complex, multi-structure presentations. Such HTML5 VR learning objects are usable on new mobile devices that do not support QuickTime VR, as well as on personal computers. Furthermore, HTML5 VR learning objects can be embedded in "ebook" document files, supporting the development of new types of electronic textbooks on mobile devices that are increasingly popular and self-adopted for mobile learning. © 2012 American Association of Anatomists.

The company objects keep: Linking referents together during cross-situational word learning.

PubMed

Zettersten, Martin; Wojcik, Erica; Benitez, Viridiana L; Saffran, Jenny

2018-04-01

Learning the meanings of words involves not only linking individual words to referents but also building a network of connections among entities in the world, concepts, and words. Previous studies reveal that infants and adults track the statistical co-occurrence of labels and objects across multiple ambiguous training instances to learn words. However, it is less clear whether, given distributional or attentional cues, learners also encode associations amongst the novel objects. We investigated the consequences of two types of cues that highlighted object-object links in a cross-situational word learning task: distributional structure - how frequently the referents of novel words occurred together - and visual context - whether the referents were seen on matching backgrounds. Across three experiments, we found that in addition to learning novel words, adults formed connections between frequently co-occurring objects. These findings indicate that learners exploit statistical regularities to form multiple types of associations during word learning.

Consistently Sampled Correlation Filters with Space Anisotropic Regularization for Visual Tracking

PubMed Central

Shi, Guokai; Xu, Tingfa; Luo, Jiqiang; Li, Yuankun

2017-01-01

Most existing correlation filter-based tracking algorithms, which use fixed patches and cyclic shifts as training and detection measures, assume that the training samples are reliable and ignore the inconsistencies between training samples and detection samples. We propose to construct and study a consistently sampled correlation filter with space anisotropic regularization (CSSAR) to solve these two problems simultaneously. Our approach constructs a spatiotemporally consistent sample strategy to alleviate the redundancies in training samples caused by the cyclical shifts, eliminate the inconsistencies between training samples and detection samples, and introduce space anisotropic regularization to constrain the correlation filter for alleviating drift caused by occlusion. Moreover, an optimization strategy based on the Gauss-Seidel method was developed for obtaining robust and efficient online learning. Both qualitative and quantitative evaluations demonstrate that our tracker outperforms state-of-the-art trackers in object tracking benchmarks (OTBs). PMID:29231876

Running Improves Pattern Separation during Novel Object Recognition.

PubMed

Bolz, Leoni; Heigele, Stefanie; Bischofberger, Josef

2015-10-09

Running increases adult neurogenesis and improves pattern separation in various memory tasks including context fear conditioning or touch-screen based spatial learning. However, it is unknown whether pattern separation is improved in spontaneous behavior, not emotionally biased by positive or negative reinforcement. Here we investigated the effect of voluntary running on pattern separation during novel object recognition in mice using relatively similar or substantially different objects.We show that running increases hippocampal neurogenesis but does not affect object recognition memory with 1.5 h delay after sample phase. By contrast, at 24 h delay, running significantly improves recognition memory for similar objects, whereas highly different objects can be distinguished by both, running and sedentary mice. These data show that physical exercise improves pattern separation, independent of negative or positive reinforcement. In sedentary mice there is a pronounced temporal gradient for remembering object details. In running mice, however, increased neurogenesis improves hippocampal coding and temporally preserves distinction of novel objects from familiar ones.

Authoring of Learning Objects in Context

ERIC Educational Resources Information Center

Specht, Marcus; Kravcik, Milos

2006-01-01

Learning objects and content interchange standards provide new possibilities for e-learning. Nevertheless the content often lacks context data to find appropriate use for adaptive learning on demand and personalized learning experiences. In the Remotely Accessible Field Trips (RAFT) project mobile authoring of learning content in context has shown…

Systematic evaluation of deep learning based detection frameworks for aerial imagery

NASA Astrophysics Data System (ADS)

Sommer, Lars; Steinmann, Lucas; Schumann, Arne; Beyerer, Jürgen

2018-04-01

Object detection in aerial imagery is crucial for many applications in the civil and military domain. In recent years, deep learning based object detection frameworks significantly outperformed conventional approaches based on hand-crafted features on several datasets. However, these detection frameworks are generally designed and optimized for common benchmark datasets, which considerably differ from aerial imagery especially in object sizes. As already demonstrated for Faster R-CNN, several adaptations are necessary to account for these differences. In this work, we adapt several state-of-the-art detection frameworks including Faster R-CNN, R-FCN, and Single Shot MultiBox Detector (SSD) to aerial imagery. We discuss adaptations that mainly improve the detection accuracy of all frameworks in detail. As the output of deeper convolutional layers comprise more semantic information, these layers are generally used in detection frameworks as feature map to locate and classify objects. However, the resolution of these feature maps is insufficient for handling small object instances, which results in an inaccurate localization or incorrect classification of small objects. Furthermore, state-of-the-art detection frameworks perform bounding box regression to predict the exact object location. Therefore, so called anchor or default boxes are used as reference. We demonstrate how an appropriate choice of anchor box sizes can considerably improve detection performance. Furthermore, we evaluate the impact of the performed adaptations on two publicly available datasets to account for various ground sampling distances or differing backgrounds. The presented adaptations can be used as guideline for further datasets or detection frameworks.

Perception of medical undergraduate students about interactive lectures in an outcome-based integrated curriculum: A cross-sectional study.

PubMed

Asad, Mohammad Rehan; Amir, Khwaja; Tadvi, Naser Ashraf; Afzal, Kamran; Sami, Waqas; Irfan, Abdul

2017-01-01

The objective of this study is to explore the student's perspectives toward the interactive lectures as a teaching and learning method in an integrated curriculum. This cross-sectional study was conducted among 1 st , 2 nd and 3 rd year male medical students ( n = 121). A self-administered questionnaire based on the Visual, Auditory, Reader, Kinesthetic learning styles, learning theories, and role of feedback in teaching and learning on five-point Likert rating scale was used. The questionnaire was constructed after extensive literature review. There was an 80% response rate in this study. The total number of undergraduate medical students responded in the study were n = 97, 34 students of 1 st year, n = 30 students of 2 nd year and n = 33 student were in 3 rd year, the mean scores of the student responses were calculated using Independent samples Kruskal-Wallis. There was no significant difference in the responses of the students of different years except for the question "The Interactive lectures facilitate effective use of learning resources." Which showed significant difference in the responses of the 3 years students by Independent samples Kruskal-Wallis test. No significant association was found between the year of study and items of the questionnaire except for the same item, " The Interactive lectures facilitates effective use of learning resources" by Spearman rank correlation test. The students perceive interactive lecture as an effective tool for facilitating visual and auditory learning modes, and for achieving curricular strategies. The student find the feedback given during the interactive lectures is effective in modifying learning attitude and enhancing motivation toward learning.

An Evaluation of the Impact of an Agricultural Science Outreach Program on the Attitudes of Rural Students

ERIC Educational Resources Information Center

Lewis, Jessica; Oliver, Richard; Oliver, Mary

2017-01-01

A "citizen science" outreach program was aimed at high school students in Western Australia with a focus on agricultural sciences. The program had two main objectives: the collection of samples and the mapping of the distribution of the leaf disease powdery mildew of barley across the state; and support for the teaching and learning of…

Solar Energy. 7th and 8th Grade Agriculture Science Curriculum. Teacher Materials.

ERIC Educational Resources Information Center

Southern Illinois Univ., Carbondale. Dept. of Agricultural Education and Mechanization.

This curriculum guide, the third in a set of six, contains teacher and student materials for a unit on solar energy prepared as part of a seventh- and eighth-grade agricultural science curriculum that is integrated with science instruction. The guide contains the state goals and sample learning objectives for each goal for students in grades 8-10…

"What the Hell Is Revise?": A Qualitative Study of Student Approaches to Coursework in Developmental English at One Urban-Serving Community College

ERIC Educational Resources Information Center

Perun, Stefan Austin

2015-01-01

Objective: To learn how interactions among the content, professor, and students shaped passing and failing developmental English at one urban-serving community college (USCC). Method: I observed three sections of developmental English at USCC throughout a semester and conducted semi-structured interviews with all three professors and a sample of…

Contamination Knowledge Strategy for the Mars 2020 Sample-Collecting Rover

NASA Technical Reports Server (NTRS)

Farley, K. A.; Williford, K.; Beaty, D W.; McSween, H. Y.; Czaja, A. D.; Goreva, Y. S.; Hausrath, E.; Herd, C. D. K.; Humayun, M.; McCubbin, F. M.;

Learned Helplessness and Sexual Risk Taking in Adolescent and Young Adult African American Females.

PubMed

Pittiglio, Laura

2017-08-01

Research involving adolescent and young African American (AA) females has demonstrated that they face uncontrollable obstacles which can interfere with the negotiation of safer sexual behaviors. If these obstacles are perceived as uncontrollable, then these females may be at risk for the development of Learned Helplessness (LH). As the LH model predicts, if these obstacles are believed not to be in their control, it may lead to deficits in motivational or cognitive decision-making, deficits that could certainly influence their sexual risk taking behaviors. Therefore, the primary objective for this pilot study was to trial the Learned Helplessness Scale (LHS) to examine the perceptions of LH in this population. A convenience sample of 50 adolescent and young AA females between the ages of 16 and 21 were recruited from two clinics in Southeast Michigan. Scores on the LHS ranged from 20 to 57, with a mean score of 39.1 (standard deviation = 10.49). The higher range of scores in the sample demonstrates a continuum of LH among the participants in the study.

How does the brain rapidly learn and reorganize view-invariant and position-invariant object representations in the inferotemporal cortex?

PubMed

Cao, Yongqiang; Grossberg, Stephen; Markowitz, Jeffrey

2011-12-01

All primates depend for their survival on being able to rapidly learn about and recognize objects. Objects may be visually detected at multiple positions, sizes, and viewpoints. How does the brain rapidly learn and recognize objects while scanning a scene with eye movements, without causing a combinatorial explosion in the number of cells that are needed? How does the brain avoid the problem of erroneously classifying parts of different objects together at the same or different positions in a visual scene? In monkeys and humans, a key area for such invariant object category learning and recognition is the inferotemporal cortex (IT). A neural model is proposed to explain how spatial and object attention coordinate the ability of IT to learn invariant category representations of objects that are seen at multiple positions, sizes, and viewpoints. The model clarifies how interactions within a hierarchy of processing stages in the visual brain accomplish this. These stages include the retina, lateral geniculate nucleus, and cortical areas V1, V2, V4, and IT in the brain's What cortical stream, as they interact with spatial attention processes within the parietal cortex of the Where cortical stream. The model builds upon the ARTSCAN model, which proposed how view-invariant object representations are generated. The positional ARTSCAN (pARTSCAN) model proposes how the following additional processes in the What cortical processing stream also enable position-invariant object representations to be learned: IT cells with persistent activity, and a combination of normalizing object category competition and a view-to-object learning law which together ensure that unambiguous views have a larger effect on object recognition than ambiguous views. The model explains how such invariant learning can be fooled when monkeys, or other primates, are presented with an object that is swapped with another object during eye movements to foveate the original object. The swapping procedure is predicted to prevent the reset of spatial attention, which would otherwise keep the representations of multiple objects from being combined by learning. Li and DiCarlo (2008) have presented neurophysiological data from monkeys showing how unsupervised natural experience in a target swapping experiment can rapidly alter object representations in IT. The model quantitatively simulates the swapping data by showing how the swapping procedure fools the spatial attention mechanism. More generally, the model provides a unifying framework, and testable predictions in both monkeys and humans, for understanding object learning data using neurophysiological methods in monkeys, and spatial attention, episodic learning, and memory retrieval data using functional imaging methods in humans. Copyright © 2011 Elsevier Ltd. All rights reserved.

View-Invariant Object Category Learning, Recognition, and Search: How Spatial and Object Attention are Coordinated Using Surface-Based Attentional Shrouds

ERIC Educational Resources Information Center

Fazl, Arash; Grossberg, Stephen; Mingolla, Ennio

2009-01-01

How does the brain learn to recognize an object from multiple viewpoints while scanning a scene with eye movements? How does the brain avoid the problem of erroneously classifying parts of different objects together? How are attention and eye movements intelligently coordinated to facilitate object learning? A neural model provides a unified…

How Object, Situation and Personality Shape Human Attitude in Learning: An Activity Perspective and a Multilevel Modeling Approach

ERIC Educational Resources Information Center

Sun, Jun

2009-01-01

Based on Activity Theory, this article examines attitude formation in human learning as shaped by the experiences of individual learners with various learning objects in particular learning contexts. It hypothesizes that a learner's object-related perceptions, personality traits and situational perceptions may have different relationships with the…

Building Communities for the Exchange of Learning Objects: Theoretical Foundations and Requirements

ERIC Educational Resources Information Center

Koper, Rob; Pannekeet, Kees; Hendriks, Maaike; Hummel, Hans

2004-01-01

In order to reduce overall costs of developing high-quality digital courses (including both the content, and the learning and teaching activities), the exchange of learning objects has been recognized as a promising solution. This article makes an inventory of the issues involved in the exchange of learning objects within a community. It explores…

The Item-Specific Deficit Approach to evaluating verbal memory dysfunction: rationale, psychometrics, and application.

PubMed

Wright, Matthew J; Woo, Ellen; Schmitter-Edgecombe, Maureen; Hinkin, Charles H; Miller, Eric N; Gooding, Amanda L

2009-10-01

In the current study, we introduce the Item-Specific Deficit Approach (ISDA), a novel method for characterizing memory process deficits in list-learning data. To meet this objective, we applied the ISDA to California Verbal Learning Test (CVLT) data collected from a sample of 132 participants (53 healthy participants and 79 neurologically compromised participants). Overall, the ISDA indices measuring encoding, consolidation, and retrieval deficits demonstrated advantages over some traditional indices and indicated acceptable reliability and validity. Currently, the ISDA is intended for experimental use, although further research may support its utility for characterizing memory impairments in clinical assessments.

The Implementation of Medical Informatics in the National Competence Based Catalogue of Learning Objectives for Undergraduate Medical Education (NKLM).

PubMed

Behrends, Marianne; Steffens, Sandra; Marschollek, Michael

2017-01-01

The National Competence Based Catalogue of Learning Objectives for Undergraduate Medical Education (NKLM) describes medical skills and attitudes without being ordered by subjects or organs. Thus, the NKLM enables systematic curriculum mapping and supports curricular transparency. In this paper we describe where learning objectives related to Medical Informatics (MI) in Hannover coincide with other subjects and where they are taught exclusively in MI. An instance of the web-based MERLIN-database was used for the mapping process. In total 52 learning objectives overlapping with 38 other subjects could be allocated to MI. No overlap exists for six learning objectives describing explicitly topics of information technology or data management for scientific research. Most of the overlap was found for learning objectives relating to documentation and aspects of data privacy. The identification of numerous shared learning objectives with other subjects does not mean that other subjects teach the same content as MI. Identifying common learning objectives rather opens up the possibility for teaching cooperations which could lead to an important exchange and hopefully an improvement in medical education. Mapping of a whole medical curriculum offers the opportunity to identify common ground between MI and other medical subjects. Furthermore, in regard to MI, the interaction with other medical subjects can strengthen its role in medical education.

Verbal learning in marijuana users seeking treatment: a comparison between depressed and non-depressed samples

PubMed Central

Roebke, Patrick V.; Vadhan, Nehal P.; Brooks, Daniel J.; Levin, Frances R.

2014-01-01

Background: Both individuals with marijuana use and depressive disorders exhibit verbal learning and memory decrements. Objectives: This study investigated the interaction between marijuana dependence and depression on learning and memory performance. Methods: The California Verbal Learning Test – Second Edition (CVLT-II) was administered to depressed (n=71) and non-depressed (n=131) near-daily marijuana users. The severity of depressive symptoms was measured by the self-rated Beck Depression Inventory (BDI-II) and the clinician-rated Hamilton Depression Rating Scale (HAM-D). Multivariate analyses of covariance statistics (MANCOVA) were employed to analyze group differences in cognitive performance. Pearson’s correlation coefficients were calculated to examine the relative associations between marijuana use, depression and CVLT-II performance. Findings from each group were compared to published normative data. Results: Although both groups exhibited decreased CVLT-II performance relative to the test’s normative sample (p<0.05), marijuana-dependent subjects with a depressive disorder did not perform differently than marijuana-dependent subjects without a depressive disorder (p>0.05). Further, poorer CVLT-II performance was modestly associated with increased self-reported daily amount of marijuana use (corrected p<0.002), but was not significantly associated with increased scores on measures of depressive symptoms (corrected p>0.002). Conclusion: These findings suggest an inverse association between marijuana use and verbal learning function, but not between depression and verbal learning function in regular marijuana users. PMID:24918839

Teaching from Objects and Stories: Learning about the Bering Sea Eskimo People. Smithsonian in Your Classroom.

ERIC Educational Resources Information Center

Smigielski, Alan

The three lesson plans in this issue feature the Eskimos of the Bering Sea and their culture. The lesson plans are: (1) "Learning about a Culture from Its Objects"; (2) "Learning about a Culture from a Story"; and (3) "Everyday Objects." Each lesson cites student objectives; lists materials needed; gives subjects…

Summary and Synthesis: How to Present a Research Proposal.

PubMed

Setia, Maninder Singh; Panda, Saumya

2017-01-01

This concluding module attempts to synthesize the key learning points discussed during the course of the previous ten sets of modules on methodology and biostatistics. The objective of this module is to discuss how to present a model research proposal, based on whatever was discussed in the preceding modules. The lynchpin of a research proposal is the protocol, and the key component of a protocol is the study design. However, one must not neglect the other areas, be it the project summary through which one catches the eyes of the reviewer of the proposal, or the background and the literature review, or the aims and objectives of the study. Two critical areas in the "methods" section that cannot be emphasized more are the sampling strategy and a formal estimation of sample size. Without a legitimate sample size, none of the conclusions based on the statistical analysis would be valid. Finally, the ethical parameters of the study should be well understood by the researchers, and that should get reflected in the proposal.

Summary and Synthesis: How to Present a Research Proposal

PubMed Central

Setia, Maninder Singh; Panda, Saumya

2017-01-01

This concluding module attempts to synthesize the key learning points discussed during the course of the previous ten sets of modules on methodology and biostatistics. The objective of this module is to discuss how to present a model research proposal, based on whatever was discussed in the preceding modules. The lynchpin of a research proposal is the protocol, and the key component of a protocol is the study design. However, one must not neglect the other areas, be it the project summary through which one catches the eyes of the reviewer of the proposal, or the background and the literature review, or the aims and objectives of the study. Two critical areas in the “methods” section that cannot be emphasized more are the sampling strategy and a formal estimation of sample size. Without a legitimate sample size, none of the conclusions based on the statistical analysis would be valid. Finally, the ethical parameters of the study should be well understood by the researchers, and that should get reflected in the proposal. PMID:28979004

MODeLeR: A Virtual Constructivist Learning Environment and Methodology for Object-Oriented Design

ERIC Educational Resources Information Center

Coffey, John W.; Koonce, Robert

2008-01-01

This article contains a description of the organization and method of use of an active learning environment named MODeLeR, (Multimedia Object Design Learning Resource), a tool designed to facilitate the learning of concepts pertaining to object modeling with the Unified Modeling Language (UML). MODeLeR was created to provide an authentic,…

Design Guide for Earth System Science Education: Common Student Learning Objectives and Special Pedagogical Approaches

NASA Astrophysics Data System (ADS)

Baker, D.

2006-12-01

As part of the NASA-supported undergraduate Earth System Science Education (ESSE) program, fifty-seven institutions have developed and implemented a wide range of Earth system science (ESS) courses, pedagogies, and evaluation tools. The Teaching, Learning, and Evaluation section of USRA's online ESSE Design Guide showcases these ESS learning environments. This Design Guide section also provides resources for faculty who wish to develop ESS courses. It addresses important course design issues including prior student knowledge and interests, student learning objectives, learning resources, pedagogical approaches, and assessments tied to student learning objectives. The ESSE Design Guide provides links to over 130 ESS course syllabi at introductory, senior, and graduate levels. ESS courses over the past 15 years exhibit common student learning objectives and unique pedagogical approaches. From analysis of ESS course syllabi, seven common student learning objectives emerged: 1) demonstrate systems thinking, 2) develop an ESS knowledge base, 3) apply ESS to the human dimension, 4) expand and apply analytical skills, 5) improve critical thinking skills, 6) build professional/career skills, and 7) acquire an enjoyment and appreciation for science. To meet these objectives, ESSE often requires different ways of teaching than in traditional scientific disciplines. This presentation will highlight some especially successful pedagogical approaches for creating positive and engaging ESS learning environments.

Abstract numerical discrimination learning in rats.

PubMed

Taniuchi, Tohru; Sugihara, Junko; Wakashima, Mariko; Kamijo, Makiko

2016-06-01

In this study, we examined rats' discrimination learning of the numerical ordering positions of objects. In Experiments 1 and 2, five out of seven rats successfully learned to respond to the third of six identical objects in a row and showed reliable transfer of this discrimination to novel stimuli after being trained with three different training stimuli. In Experiment 3, the three rats from Experiment 2 continued to be trained to respond to the third object in an object array, which included an odd object that needed to be excluded when identifying the target third object. All three rats acquired this selective-counting task of specific stimuli, and two rats showed reliable transfer of this selective-counting performance to test sets of novel stimuli. In Experiment 4, the three rats from Experiment 3 quickly learned to respond to the third stimulus in object rows consisting of either six identical or six different objects. These results offer strong evidence for abstract numerical discrimination learning in rats.

Impact of feature saliency on visual category learning.

PubMed

Hammer, Rubi

2015-01-01

People have to sort numerous objects into a large number of meaningful categories while operating in varying contexts. This requires identifying the visual features that best predict the 'essence' of objects (e.g., edibility), rather than categorizing objects based on the most salient features in a given context. To gain this capacity, visual category learning (VCL) relies on multiple cognitive processes. These may include unsupervised statistical learning, that requires observing multiple objects for learning the statistics of their features. Other learning processes enable incorporating different sources of supervisory information, alongside the visual features of the categorized objects, from which the categorical relations between few objects can be deduced. These deductions enable inferring that objects from the same category may differ from one another in some high-saliency feature dimensions, whereas lower-saliency feature dimensions can best differentiate objects from distinct categories. Here I illustrate how feature saliency affects VCL, by also discussing kinds of supervisory information enabling reflective categorization. Arguably, principles debated here are often being ignored in categorization studies.

Impact of feature saliency on visual category learning

PubMed Central

Hammer, Rubi

2015-01-01

People have to sort numerous objects into a large number of meaningful categories while operating in varying contexts. This requires identifying the visual features that best predict the ‘essence’ of objects (e.g., edibility), rather than categorizing objects based on the most salient features in a given context. To gain this capacity, visual category learning (VCL) relies on multiple cognitive processes. These may include unsupervised statistical learning, that requires observing multiple objects for learning the statistics of their features. Other learning processes enable incorporating different sources of supervisory information, alongside the visual features of the categorized objects, from which the categorical relations between few objects can be deduced. These deductions enable inferring that objects from the same category may differ from one another in some high-saliency feature dimensions, whereas lower-saliency feature dimensions can best differentiate objects from distinct categories. Here I illustrate how feature saliency affects VCL, by also discussing kinds of supervisory information enabling reflective categorization. Arguably, principles debated here are often being ignored in categorization studies. PMID:25954220

A Benchmark Dataset and Saliency-guided Stacked Autoencoders for Video-based Salient Object Detection.

PubMed

Li, Jia; Xia, Changqun; Chen, Xiaowu

2017-10-12

Image-based salient object detection (SOD) has been extensively studied in past decades. However, video-based SOD is much less explored due to the lack of large-scale video datasets within which salient objects are unambiguously defined and annotated. Toward this end, this paper proposes a video-based SOD dataset that consists of 200 videos. In constructing the dataset, we manually annotate all objects and regions over 7,650 uniformly sampled keyframes and collect the eye-tracking data of 23 subjects who free-view all videos. From the user data, we find that salient objects in a video can be defined as objects that consistently pop-out throughout the video, and objects with such attributes can be unambiguously annotated by combining manually annotated object/region masks with eye-tracking data of multiple subjects. To the best of our knowledge, it is currently the largest dataset for videobased salient object detection. Based on this dataset, this paper proposes an unsupervised baseline approach for video-based SOD by using saliencyguided stacked autoencoders. In the proposed approach, multiple spatiotemporal saliency cues are first extracted at the pixel, superpixel and object levels. With these saliency cues, stacked autoencoders are constructed in an unsupervised manner that automatically infers a saliency score for each pixel by progressively encoding the high-dimensional saliency cues gathered from the pixel and its spatiotemporal neighbors. In experiments, the proposed unsupervised approach is compared with 31 state-of-the-art models on the proposed dataset and outperforms 30 of them, including 19 imagebased classic (unsupervised or non-deep learning) models, six image-based deep learning models, and five video-based unsupervised models. Moreover, benchmarking results show that the proposed dataset is very challenging and has the potential to boost the development of video-based SOD.

Exploiting Attribute Correlations: A Novel Trace Lasso-Based Weakly Supervised Dictionary Learning Method.

PubMed

Wu, Lin; Wang, Yang; Pan, Shirui

2017-12-01

It is now well established that sparse representation models are working effectively for many visual recognition tasks, and have pushed forward the success of dictionary learning therein. Recent studies over dictionary learning focus on learning discriminative atoms instead of purely reconstructive ones. However, the existence of intraclass diversities (i.e., data objects within the same category but exhibit large visual dissimilarities), and interclass similarities (i.e., data objects from distinct classes but share much visual similarities), makes it challenging to learn effective recognition models. To this end, a large number of labeled data objects are required to learn models which can effectively characterize these subtle differences. However, labeled data objects are always limited to access, committing it difficult to learn a monolithic dictionary that can be discriminative enough. To address the above limitations, in this paper, we propose a weakly-supervised dictionary learning method to automatically learn a discriminative dictionary by fully exploiting visual attribute correlations rather than label priors. In particular, the intrinsic attribute correlations are deployed as a critical cue to guide the process of object categorization, and then a set of subdictionaries are jointly learned with respect to each category. The resulting dictionary is highly discriminative and leads to intraclass diversity aware sparse representations. Extensive experiments on image classification and object recognition are conducted to show the effectiveness of our approach.

Learning Object Names at Different Hierarchical Levels Using Cross-Situational Statistics.

PubMed

Chen, Chi-Hsin; Zhang, Yayun; Yu, Chen

2018-05-01

Objects in the world usually have names at different hierarchical levels (e.g., beagle, dog, animal). This research investigates adults' ability to use cross-situational statistics to simultaneously learn object labels at individual and category levels. The results revealed that adults were able to use co-occurrence information to learn hierarchical labels in contexts where the labels for individual objects and labels for categories were presented in completely separated blocks, in interleaved blocks, or mixed in the same trial. Temporal presentation schedules significantly affected the learning of individual object labels, but not the learning of category labels. Learners' subsequent generalization of category labels indicated sensitivity to the structure of statistical input. Copyright © 2017 Cognitive Science Society, Inc.

An Object Oriented Approach to Improve the Precision of Learning Object Retrieval in a Self Learning Environment

ERIC Educational Resources Information Center

Raghuveer, V. R.; Tripathy, B. K.

2012-01-01

With the advancements in the WWW and ICT, the e-learning domain has developed very fast. Even many educational institutions these days have shifted their focus towards the e-learning and mobile learning environments. However, from the quality of learning point of view, which is measured in terms of "active learning" taking place, the…

The Development of the Virtual Learning Media of the Sacred Object Artwork

ERIC Educational Resources Information Center

Nuanmeesri, Sumitra; Jamornmongkolpilai, Saran

2018-01-01

This research aimed to develop the virtual learning media of the sacred object artwork by applying the concept of the virtual technology in order to publicize knowledge on the cultural wisdom of the sacred object artwork. It was done by designing and developing the virtual learning media of the sacred object artwork for the virtual presentation.…

Proposal of a Framework for Internet Based Licensing of Learning Objects

ERIC Educational Resources Information Center

Santos, Osvaldo A.; Ramos, Fernando M. S.

2004-01-01

This paper presents a proposal of a framework whose main objective is to manage the delivery and rendering of learning objects in a digital rights controlled environment. The framework is based on a digital licensing scheme that requires each learning object to have the proper license in order to be rendered by a trusted player. A conceptual model…

Challenges in Developing XML-Based Learning Repositories

NASA Astrophysics Data System (ADS)

Auksztol, Jerzy; Przechlewski, Tomasz

There is no doubt that modular design has many advantages, including the most important ones: reusability and cost-effectiveness. In an e-leaming community parlance the modules are determined as Learning Objects (LOs) [11]. An increasing amount of learning objects have been created and published online, several standards has been established and multiple repositories developed for them. For example Cisco Systems, Inc., "recognizes a need to move from creating and delivering large inflexible training courses, to database-driven objects that can be reused, searched, and modified independent of their delivery media" [6]. The learning object paradigm of education resources authoring is promoted mainly to reduce the cost of the content development and to increase its quality. A frequently used metaphor of Learning Objects paradigm compares them to Lego Logs or objects in Object-Oriented program design [25]. However a metaphor is only an abstract idea, which should be turned to something more concrete to be usable. The problem is that many papers on LOs end up solely in metaphors. In our opinion Lego or OO metaphors are gross oversimplificatation of the problem as there is much easier to develop Lego set or design objects in OO program than develop truly interoperable, context-free learning content1.

The Delphi Technique in Identifying Learning Objectives for the Development of Science, Technology and Society Modules for Palestinian Ninth Grade Science Curriculum

NASA Astrophysics Data System (ADS)

Abualrob, Marwan M. A.; Gnanamalar Sarojini Daniel, Esther

2013-10-01

This article outlines how learning objectives based upon science, technology and society (STS) elements for Palestinian ninth grade science textbooks were identified, which was part of a bigger study to establish an STS foundation in the ninth grade science curriculum in Palestine. First, an initial list of STS elements was determined. Second, using this list, ninth grade science textbooks and curriculum document contents were analyzed. Third, based on this content analysis, a possible list of 71 learning objectives for the integration of STS elements was prepared. This list of learning objectives was refined by using a two-round Delphi technique. The Delphi study was used to rate and to determine the consensus regarding which items (i.e. learning objectives for STS in the ninth grade science textbooks in Palestine) are to be accepted for inclusion. The results revealed that of the initial 71 objectives in round one, 59 objectives within round two had a mean score of 5.683 or higher, which indicated that the learning objectives could be included in the development of STS modules for ninth grade science in Palestine.

Fast Compressive Tracking.

PubMed

Zhang, Kaihua; Zhang, Lei; Yang, Ming-Hsuan

2014-10-01

It is a challenging task to develop effective and efficient appearance models for robust object tracking due to factors such as pose variation, illumination change, occlusion, and motion blur. Existing online tracking algorithms often update models with samples from observations in recent frames. Despite much success has been demonstrated, numerous issues remain to be addressed. First, while these adaptive appearance models are data-dependent, there does not exist sufficient amount of data for online algorithms to learn at the outset. Second, online tracking algorithms often encounter the drift problems. As a result of self-taught learning, misaligned samples are likely to be added and degrade the appearance models. In this paper, we propose a simple yet effective and efficient tracking algorithm with an appearance model based on features extracted from a multiscale image feature space with data-independent basis. The proposed appearance model employs non-adaptive random projections that preserve the structure of the image feature space of objects. A very sparse measurement matrix is constructed to efficiently extract the features for the appearance model. We compress sample images of the foreground target and the background using the same sparse measurement matrix. The tracking task is formulated as a binary classification via a naive Bayes classifier with online update in the compressed domain. A coarse-to-fine search strategy is adopted to further reduce the computational complexity in the detection procedure. The proposed compressive tracking algorithm runs in real-time and performs favorably against state-of-the-art methods on challenging sequences in terms of efficiency, accuracy and robustness.

Student Team Achievement Divisions: Its Effect on Electrical Motor Installation Knowledge Competence

NASA Astrophysics Data System (ADS)

Hanafi, Ahmad; Basuki, Ismet

2018-04-01

Student team achievement division (STAD) was an active learning strategy with the small group inside of the classroom members. The students would work in small heterogeneous groups (of five to six members) and help one another to comprehend the material given. To achieve the objectives of the study, this research aims to know the effect of STAD on competence of electrical motor installation. The objective of the student competence was knowledge competence. The data was collected from 30 students. the participants were the students of second class at electrical installation techniques, SMKN 1 Pungging Indonesia. The design of empirical test in this research was one shot case study. The result of knowledge test would be compared by criteria for minimum competence, which was 75. Knowledge competence was analyzed with one sample t test technique. From the analysis got average 84.93, which meant average of student competence had reached criteria for minimum competence. From that analyze, It could be concluded that STAD was effective on electrical motor installation knowledge competence. STAD could grow student motivation to learn better than other models. But, in the application of cooperative learning teacher should prepare carefully before the learning process to avoid problems that could arise during group learning such as students who were less active in the groups. The problem could be resolved by away the teachers took around to check each group. It was felt could minimize the problems.

Performance of thigh-mounted triaxial accelerometer algorithms in objective quantification of sedentary behaviour and physical activity in older adults

PubMed Central

Verschueren, Sabine M. P.; Degens, Hans; Morse, Christopher I.; Onambélé, Gladys L.

2017-01-01

Accurate monitoring of sedentary behaviour and physical activity is key to investigate their exact role in healthy ageing. To date, accelerometers using cut-off point models are most preferred for this, however, machine learning seems a highly promising future alternative. Hence, the current study compared between cut-off point and machine learning algorithms, for optimal quantification of sedentary behaviour and physical activity intensities in the elderly. Thus, in a heterogeneous sample of forty participants (aged ≥60 years, 50% female) energy expenditure during laboratory-based activities (ranging from sedentary behaviour through to moderate-to-vigorous physical activity) was estimated by indirect calorimetry, whilst wearing triaxial thigh-mounted accelerometers. Three cut-off point algorithms and a Random Forest machine learning model were developed and cross-validated using the collected data. Detailed analyses were performed to check algorithm robustness, and examine and benchmark both overall and participant-specific balanced accuracies. This revealed that the four models can at least be used to confidently monitor sedentary behaviour and moderate-to-vigorous physical activity. Nevertheless, the machine learning algorithm outperformed the cut-off point models by being robust for all individual’s physiological and non-physiological characteristics and showing more performance of an acceptable level over the whole range of physical activity intensities. Therefore, we propose that Random Forest machine learning may be optimal for objective assessment of sedentary behaviour and physical activity in older adults using thigh-mounted triaxial accelerometry. PMID:29155839

Performance of thigh-mounted triaxial accelerometer algorithms in objective quantification of sedentary behaviour and physical activity in older adults.

PubMed

Wullems, Jorgen A; Verschueren, Sabine M P; Degens, Hans; Morse, Christopher I; Onambélé, Gladys L

2017-01-01

Accurate monitoring of sedentary behaviour and physical activity is key to investigate their exact role in healthy ageing. To date, accelerometers using cut-off point models are most preferred for this, however, machine learning seems a highly promising future alternative. Hence, the current study compared between cut-off point and machine learning algorithms, for optimal quantification of sedentary behaviour and physical activity intensities in the elderly. Thus, in a heterogeneous sample of forty participants (aged ≥60 years, 50% female) energy expenditure during laboratory-based activities (ranging from sedentary behaviour through to moderate-to-vigorous physical activity) was estimated by indirect calorimetry, whilst wearing triaxial thigh-mounted accelerometers. Three cut-off point algorithms and a Random Forest machine learning model were developed and cross-validated using the collected data. Detailed analyses were performed to check algorithm robustness, and examine and benchmark both overall and participant-specific balanced accuracies. This revealed that the four models can at least be used to confidently monitor sedentary behaviour and moderate-to-vigorous physical activity. Nevertheless, the machine learning algorithm outperformed the cut-off point models by being robust for all individual's physiological and non-physiological characteristics and showing more performance of an acceptable level over the whole range of physical activity intensities. Therefore, we propose that Random Forest machine learning may be optimal for objective assessment of sedentary behaviour and physical activity in older adults using thigh-mounted triaxial accelerometry.

Asteroids in the High Cadence Transient Survey

NASA Astrophysics Data System (ADS)

Peña, J.; Fuentes, C.; Förster, F.; Maureira, J. C.; San Martín, J.; Littín, J.; Huijse, P.; Cabrera-Vives, G.; Estévez, P. A.; Galbany, L.; González-Gaitán, S.; Martínez, J.; de Jaeger, Th.; Hamuy, M.

2018-03-01

We report on the serendipitous observations of solar system objects imaged during the High cadence Transient Survey 2014 observation campaign. Data from this high-cadence wide-field survey was originally analyzed for finding variable static sources using machine learning to select the most-likely candidates. In this work, we search for moving transients consistent with solar system objects and derive their orbital parameters. We use a simple, custom motion detection algorithm to link trajectories and assume Keplerian motion to derive the asteroid’s orbital parameters. We use known asteroids from the Minor Planet Center database to assess the detection efficiency of the survey and our search algorithm. Trajectories have an average of nine detections spread over two days, and our fit yields typical errors of {σ }a∼ 0.07 {au}, σ e ∼ 0.07 and σ i ∼ 0.°5 in semimajor axis, eccentricity, and inclination, respectively, for known asteroids in our sample. We extract 7700 orbits from our trajectories, identifying 19 near-Earth objects, 6687 asteroids, 14 Centaurs, and 15 trans-Neptunian objects. This highlights the complementarity of supernova wide-field surveys for solar system research and the significance of machine learning to clean data of false detections. It is a good example of the data-driven science that Large Synoptic Survey Telescope will deliver.

Design of Learning Objects for Concept Learning: Effects of Multimedia Learning Principles and an Instructional Approach

ERIC Educational Resources Information Center

Chiu, Thomas K. F.; Churchill, Daniel

2016-01-01

Literature suggests using multimedia learning principles in the design of instructional material. However, these principles may not be sufficient for the design of learning objects for concept learning in mathematics. This paper reports on an experimental study that investigated the effects of an instructional approach, which includes two teaching…

[Effect of object consistency in a spatial contextual cueing paradigm].

PubMed

Takeda, Yuji

2008-04-01

Previous studies demonstrated that attention can be quickly guided to a target location in a visual search task when the spatial configurations of search items and/or the object identities were repeated in the previous trials. This phenomenon is termed contextual cueing. Recently, it was reported that spatial configuration learning and object identity learning occurred independently, when novel contours were used as search items. The present study examined whether this learning occurred independently even when the search items were meaningful. The results showed that the contextual cueing effect was observed even if the relationships between the spatial locations and object identities were jumbled (Experiment 1). However, it disappeared when the search items were changed into geometric patterns (Experiment 2). These results suggest that the spatial configuration can be learned independent of the object identities; however, the use of the learned configuration is restricted by the learning situations.

Mobile Authoring of Open Educational Resources as Reusable Learning Objects

ERIC Educational Resources Information Center

Kinshuk; Jesse, Ryan

2013-01-01

E-learning technologies have allowed authoring and playback of standardized reusable learning objects (RLO) for several years. Effective mobile learning requires similar functionality at both design time and runtime. Mobile devices can play RLO using applications like SMILE, mobile access to a learning management system (LMS), or other systems…

An Intelligent Semantic E-Learning Framework Using Context-Aware Semantic Web Technologies

ERIC Educational Resources Information Center

Huang, Weihong; Webster, David; Wood, Dawn; Ishaya, Tanko

2006-01-01

Recent developments of e-learning specifications such as Learning Object Metadata (LOM), Sharable Content Object Reference Model (SCORM), Learning Design and other pedagogy research in semantic e-learning have shown a trend of applying innovative computational techniques, especially Semantic Web technologies, to promote existing content-focused…

Grading for Understanding--Standards-Based Grading

ERIC Educational Resources Information Center

Zimmerman, Todd

2017-01-01

Standards-based grading (SBG), sometimes called learning objectives-based assessment (LOBA), is an assessment model that relies on students demonstrating mastery of learning objectives (sometimes referred to as standards). The goal of this grading system is to focus students on mastering learning objectives rather than on accumulating points. I…

Reduction in training time of a deep learning model in detection of lesions in CT

NASA Astrophysics Data System (ADS)

Makkinejad, Nazanin; Tajbakhsh, Nima; Zarshenas, Amin; Khokhar, Ashfaq; Suzuki, Kenji

2018-02-01

Deep learning (DL) emerged as a powerful tool for object detection and classification in medical images. Building a well-performing DL model, however, requires a huge number of images for training, and it takes days to train a DL model even on a cutting edge high-performance computing platform. This study is aimed at developing a method for selecting a "small" number of representative samples from a large collection of training samples to train a DL model for the could be used to detect polyps in CT colonography (CTC), without compromising the classification performance. Our proposed method for representative sample selection (RSS) consists of a K-means clustering algorithm. For the performance evaluation, we applied the proposed method to select samples for the training of a massive training artificial neural network based DL model, to be used for the classification of polyps and non-polyps in CTC. Our results show that the proposed method reduce the training time by a factor of 15, while maintaining the classification performance equivalent to the model trained using the full training set. We compare the performance using area under the receiveroperating- characteristic curve (AUC).

Learning Specific Content in Technology Education: Learning Study as a Collaborative Method in Swedish Preschool Class Using Hands-On Material

ERIC Educational Resources Information Center

Kilbrink, Nina; Bjurulf, Veronica; Blomberg, Ingela; Heidkamp, Anja; Hollsten, Ann-Christin

2014-01-01

This article describes the process of a learning study conducted in technology education in a Swedish preschool class. The learning study method used in this study is a collaborative method, where researchers and teachers work together as a team concerning teaching and learning about a specific learning object. The object of learning in this study…

Hierarchical combinatorial deep learning architecture for pancreas segmentation of medical computed tomography cancer images.

PubMed

Fu, Min; Wu, Wenming; Hong, Xiafei; Liu, Qiuhua; Jiang, Jialin; Ou, Yaobin; Zhao, Yupei; Gong, Xinqi

2018-04-24

Efficient computational recognition and segmentation of target organ from medical images are foundational in diagnosis and treatment, especially about pancreas cancer. In practice, the diversity in appearance of pancreas and organs in abdomen, makes detailed texture information of objects important in segmentation algorithm. According to our observations, however, the structures of previous networks, such as the Richer Feature Convolutional Network (RCF), are too coarse to segment the object (pancreas) accurately, especially the edge. In this paper, we extend the RCF, proposed to the field of edge detection, for the challenging pancreas segmentation, and put forward a novel pancreas segmentation network. By employing multi-layer up-sampling structure replacing the simple up-sampling operation in all stages, the proposed network fully considers the multi-scale detailed contexture information of object (pancreas) to perform per-pixel segmentation. Additionally, using the CT scans, we supply and train our network, thus get an effective pipeline. Working with our pipeline with multi-layer up-sampling model, we achieve better performance than RCF in the task of single object (pancreas) segmentation. Besides, combining with multi scale input, we achieve the 76.36% DSC (Dice Similarity Coefficient) value in testing data. The results of our experiments show that our advanced model works better than previous networks in our dataset. On the other words, it has better ability in catching detailed contexture information. Therefore, our new single object segmentation model has practical meaning in computational automatic diagnosis.

Tracking-Learning-Detection.

PubMed

Kalal, Zdenek; Mikolajczyk, Krystian; Matas, Jiri

2012-07-01

This paper investigates long-term tracking of unknown objects in a video stream. The object is defined by its location and extent in a single frame. In every frame that follows, the task is to determine the object's location and extent or indicate that the object is not present. We propose a novel tracking framework (TLD) that explicitly decomposes the long-term tracking task into tracking, learning, and detection. The tracker follows the object from frame to frame. The detector localizes all appearances that have been observed so far and corrects the tracker if necessary. The learning estimates the detector's errors and updates it to avoid these errors in the future. We study how to identify the detector's errors and learn from them. We develop a novel learning method (P-N learning) which estimates the errors by a pair of "experts": (1) P-expert estimates missed detections, and (2) N-expert estimates false alarms. The learning process is modeled as a discrete dynamical system and the conditions under which the learning guarantees improvement are found. We describe our real-time implementation of the TLD framework and the P-N learning. We carry out an extensive quantitative evaluation which shows a significant improvement over state-of-the-art approaches.

Active machine learning for rapid landslide inventory mapping with VHR satellite images (Invited)

NASA Astrophysics Data System (ADS)

Stumpf, A.; Lachiche, N.; Malet, J.; Kerle, N.; Puissant, A.

2013-12-01

VHR satellite images have become a primary source for landslide inventory mapping after major triggering events such as earthquakes and heavy rainfalls. Visual image interpretation is still the prevailing standard method for operational purposes but is time-consuming and not well suited to fully exploit the increasingly better supply of remote sensing data. Recent studies have addressed the development of more automated image analysis workflows for landslide inventory mapping. In particular object-oriented approaches that account for spatial and textural image information have been demonstrated to be more adequate than pixel-based classification but manually elaborated rule-based classifiers are difficult to adapt under changing scene characteristics. Machine learning algorithm allow learning classification rules for complex image patterns from labelled examples and can be adapted straightforwardly with available training data. In order to reduce the amount of costly training data active learning (AL) has evolved as a key concept to guide the sampling for many applications. The underlying idea of AL is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and data structure to iteratively select the most valuable samples that should be labelled by the user. With relatively few queries and labelled samples, an AL strategy yields higher accuracies than an equivalent classifier trained with many randomly selected samples. This study addressed the development of an AL method for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. Our approach [1] is based on the Random Forest algorithm and considers the classifier uncertainty as well as the variance of potential sampling regions to guide the user towards the most valuable sampling areas. The algorithm explicitly searches for compact regions and thereby avoids a spatially disperse sampling pattern inherent to most other AL methods. The accuracy, the sampling time and the computational runtime of the algorithm were evaluated on multiple satellite images capturing recent large scale landslide events. Sampling between 1-4% of the study areas the accuracies between 74% and 80% were achieved, whereas standard sampling schemes yielded only accuracies between 28% and 50% with equal sampling costs. Compared to commonly used point-wise AL algorithm the proposed approach significantly reduces the number of iterations and hence the computational runtime. Since the user can focus on relatively few compact areas (rather than on hundreds of distributed points) the overall labeling time is reduced by more than 50% compared to point-wise queries. An experimental evaluation of multiple expert mappings demonstrated strong relationships between the uncertainties of the experts and the machine learning model. It revealed that the achieved accuracies are within the range of the inter-expert disagreement and that it will be indispensable to consider ground truth uncertainties to truly achieve further enhancements in the future. The proposed method is generally applicable to a wide range of optical satellite images and landslide types. [1] A. Stumpf, N. Lachiche, J.-P. Malet, N. Kerle, and A. Puissant, Active learning in the spatial domain for remote sensing image classification, IEEE Transactions on Geosciece and Remote Sensing. 2013, DOI 10.1109/TGRS.2013.2262052.

Automotive Mechanics. Student Learning Guides.

ERIC Educational Resources Information Center

Ridge Vocational-Technical Center, Winter Haven, FL.

These 33 learning guides are self-instructional packets for 33 tasks identified as essential for performance on an entry-level job in automotive mechanics. Each guide is based on a terminal performance objective (task) and 1-9 enabling objectives. For each enabliing objective, some or all of these materials may be presented: learning steps…

Learning and Forgetting New Names and Objects in MCI and AD

ERIC Educational Resources Information Center

Gronholm-Nyman, Petra; Rinne, Juha O.; Laine, Matti

2010-01-01

We studied how subjects with mild cognitive impairment (MCI), early Alzheimer's disease (AD) and age-matched controls learned and maintained the names of unfamiliar objects that were trained with or without semantic support (object definitions). Naming performance, phonological cueing, incidental learning of the definitions and recognition of the…

Information Retrieval in Virtual Universities

ERIC Educational Resources Information Center

Puustjärvi, Juha; Pöyry, Päivi

2006-01-01

Information retrieval in the context of virtual universities deals with the representation, organization, and access to learning objects. The representation and organization of learning objects should provide the learner with an easy access to the learning objects. In this article, we give an overview of the ONES system, and analyze the relevance…

Learning Objects for Educational Applications via PDA Technology

ERIC Educational Resources Information Center

Churchill, Daniel

2008-01-01

This article discusses an ongoing study into issues relevant to the design of learning objects for educational applications via portable digital assistant (PDA) technology. The specific areas of inquiry in this study are: the kinds of learning objects that are effective for PDA delivery; contexts for their effective educational applications; and…

Mechanical Drafting. Student Learning Guides.

ERIC Educational Resources Information Center

Ridge Vocational-Technical Center, Winter Haven, FL.

These four learning guides are self-instructional packets for four tasks identified as essential for performance on an entry-level job in mechanical drafting. Each guide is based on a terminal performance objective (task) and 2-4 enabling objectives. For each enabling objective, some or all of these materials may be presented: learning steps…

Livestock. Student Learning Guides.

ERIC Educational Resources Information Center

Ridge Vocational-Technical Center, Winter Haven, FL.

These 25 learning guides are self-instructional packets for 25 tasks identified as essential for performance on an entry-level job in livestock production. Each guide is based on a terminal performance objective (task) and 1-4 enabling objectives. For each enabling objective, some or all of these materials may be presented: learning steps (outline…

FILILAB: Creation and Use of a Learning Object Repository for EFL

ERIC Educational Resources Information Center

Litzler, Mary Frances; Garcia Laborda, Jesus; Halbach, Ana

2012-01-01

Background: Students at the Universidad de Alcala need batteries of learning objects and exercises. Although student textbooks tend to include a wide range of additional exercises, students in advanced linguistics and language courses require learning objects to obtain additional practice. Online repositories offer excellent opportunities for…

Learning Objects Update: Review and Critical Approach to Content Aggregation

ERIC Educational Resources Information Center

Balatsoukas, Panos; Morris, Anne; O'Brien, Ann

2008-01-01

The structure and composite nature of a learning object is still open to interpretation. Although several theoretical studies advocate integrated approaches to the structure and aggregation level of learning objects, in practice, many content specifications, such as SCORM, IMS Content Packaging, and course authoring tools, do not explicitly state…

Statistical Learning Is Constrained to Less Abstract Patterns in Complex Sensory Input (but not the Least)

PubMed Central

Emberson, Lauren L.; Rubinstein, Dani

2016-01-01

The influence of statistical information on behavior (either through learning or adaptation) is quickly becoming foundational to many domains of cognitive psychology and cognitive neuroscience, from language comprehension to visual development. We investigate a central problem impacting these diverse fields: when encountering input with rich statistical information, are there any constraints on learning? This paper examines learning outcomes when adult learners are given statistical information across multiple levels of abstraction simultaneously: from abstract, semantic categories of everyday objects to individual viewpoints on these objects. After revealing statistical learning of abstract, semantic categories with scrambled individual exemplars (Exp. 1), participants viewed pictures where the categories as well as the individual objects predicted picture order (e.g., bird1—dog1, bird2—dog2). Our findings suggest that participants preferentially encode the relationships between the individual objects, even in the presence of statistical regularities linking semantic categories (Exps. 2 and 3). In a final experiment we investigate whether learners are biased towards learning object-level regularities or simply construct the most detailed model given the data (and therefore best able to predict the specifics of the upcoming stimulus) by investigating whether participants preferentially learn from the statistical regularities linking individual snapshots of objects or the relationship between the objects themselves (e.g., bird_picture1— dog_picture1, bird_picture2—dog_picture2). We find that participants fail to learn the relationships between individual snapshots, suggesting a bias towards object-level statistical regularities as opposed to merely constructing the most complete model of the input. This work moves beyond the previous existence proofs that statistical learning is possible at both very high and very low levels of abstraction (categories vs. individual objects) and suggests that, at least with the current categories and type of learner, there are biases to pick up on statistical regularities between individual objects even when robust statistical information is present at other levels of abstraction. These findings speak directly to emerging theories about how systems supporting statistical learning and prediction operate in our structure-rich environments. Moreover, the theoretical implications of the current work across multiple domains of study is already clear: statistical learning cannot be assumed to be unconstrained even if statistical learning has previously been established at a given level of abstraction when that information is presented in isolation. PMID:27139779

Effects of interactive instructional techniques in a web-based peripheral nervous system component for human anatomy.

PubMed

Allen, Edwin B; Walls, Richard T; Reilly, Frank D

2008-02-01

This study investigated the effects of interactive instructional techniques in a web-based peripheral nervous system (PNS) component of a first year medical school human anatomy course. Existing data from 9 years of instruction involving 856 students were used to determine (1) the effect of web-based interactive instructional techniques on written exam item performance and (2) differences between student opinions of the benefit level of five different types of interactive learning objects used. The interactive learning objects included Patient Case studies, review Games, Simulated Interactive Patients (SIP), Flashcards, and unit Quizzes. Exam item analysis scores were found to be significantly higher (p < 0.05) for students receiving the instructional treatment incorporating the web-based interactive learning objects than for students not receiving this treatment. Questionnaires using a five-point Likert scale were analysed to determine student opinion ratings of the interactive learning objects. Students reported favorably on the benefit level of all learning objects. Students rated the benefit level of the Simulated Interactive Patients (SIP) highest, and this rating was significantly higher (p < 0.05) than all other learning objects. This study suggests that web-based interactive instructional techniques improve student exam performance. Students indicated a strong acceptance of Simulated Interactive Patient learning objects.

Near or far: The effect of spatial distance and vocabulary knowledge on word learning.

PubMed

Axelsson, Emma L; Perry, Lynn K; Scott, Emilly J; Horst, Jessica S

2016-01-01

The current study investigated the role of spatial distance in word learning. Two-year-old children saw three novel objects named while the objects were either in close proximity to each other or spatially separated. Children were then tested on their retention for the name-object associations. Keeping the objects spatially separated from each other during naming was associated with increased retention for children with larger vocabularies. Children with a lower vocabulary size demonstrated better retention if they saw objects in close proximity to each other during naming. This demonstrates that keeping a clear view of objects during naming improves word learning for children who have already learned many words, but keeping objects within close proximal range is better for children at earlier stages of vocabulary acquisition. The effect of distance is therefore not equal across varying vocabulary sizes. The influences of visual crowding, cognitive load, and vocabulary size on word learning are discussed. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Bloom's taxonomy of cognitive learning objectives.

PubMed

Adams, Nancy E

2015-07-01

Information professionals who train or instruct others can use Bloom's taxonomy to write learning objectives that describe the skills and abilities that they desire their learners to master and demonstrate. Bloom's taxonomy differentiates between cognitive skill levels and calls attention to learning objectives that require higher levels of cognitive skills and, therefore, lead to deeper learning and transfer of knowledge and skills to a greater variety of tasks and contexts.

The Subject-Object Approach as a Direction of the Learning Theory in the Context of Modern Linguistic Education Paradigms

ERIC Educational Resources Information Center

Salkhanova, Zhanat H.; Lee, Valentine S.; Tumanova, Ainakul B.; Zhusanbaeva, Aida T.

2016-01-01

The research object is the activity-based learning theory. The purpose of the study is to prove the assumption that the subject-object approach as a direction of the learning theory is the most effective one in the context of development of modern paradigms of linguistic education. The authors believe that the main content of the learning activity…

Use of individualized learning plans among fourth-year sub-interns in pediatrics and internal medicine.

PubMed

Shepard, Michelle E; Sastre, Elizabeth A; Davidson, Mario A; Fleming, Amy E

2012-01-01

Individualized Learning Plans (ILPs) are an effective tool for promoting self-directed learning among residents. However, no literature details ILP use among medical students. Fifty fourth-year sub-interns in pediatrics and internal medicine created ILPs, including a self-assessment of strengths and weaknesses based on ACGME core competencies and the setting of learning objectives. During weekly follow-up meetings with faculty mentors and peers, students discussed challenges and revised goals. Upon completion of the rotation, students completed a survey of Likert-scale questions addressing satisfaction with and perceived utility of ILP components. Students most often self-identified strengths in the areas of Professionalism and Interpersonal and Communication Skills and weaknesses in Patient Care and Systems-Based Practice. Eighty-two percent set at least one learning objective in an identified area of weakness. Students expressed high confidence in their abilities to create achievable learning objectives and to generate strategies to meet those objectives. Students agreed that discussions during group meetings were meaningful, and they identified the setting learning objectives and weekly meetings as the most important elements of the exercise. Fourth-year sub-interns reported that ILPs helped them to accomplish rotation goals, with the setting of learning objectives and weekly discussions being the most useful elements.

An Adaptive Navigation Support System for Conducting Context-Aware Ubiquitous Learning in Museums

ERIC Educational Resources Information Center

Chiou, Chuang-Kai; Tseng, Judy C. R.; Hwang, Gwo-Jen; Heller, Shelly

2010-01-01

In context-aware ubiquitous learning, students are guided to learn in the real world with personalized supports from the learning system. As the learning resources are realistic objects in the real world, certain physical constraints, such as the limitation of stream of people who visit the same learning object, the time for moving from one object…

Ontologies for Effective Use of Context in E-Learning Settings

ERIC Educational Resources Information Center

Jovanovic, Jelena; Gasevic, Dragan; Knight, Colin; Richards, Griff

2007-01-01

This paper presents an ontology-based framework aimed at explicit representation of context-specific metadata derived from the actual usage of learning objects and learning designs. The core part of the proposed framework is a learning object context ontology, that leverages a range of other kinds of learning ontologies (e.g., user modeling…

Throw out Learning Objectives! In Support of a New Taxonomy

ERIC Educational Resources Information Center

Gander, Sharon L.

2006-01-01

In the right hands, learning objectives are great tools for clarifying thinking, breaking down learning into component parts, creating a logical order to learning, and demonstrating that a learning intervention is successful. Mostly, however, they have become cliches. With the industry's tendency to use them as pro forma media bites, they tend to…

Learning from Online Modules in Diverse Instructional Contexts

ERIC Educational Resources Information Center

Nugent, Gwen; Kohmetscher, Amy; Namuth-Covert, Deana; Guretzky, John; Murphy, Patrick; Lee, DoKyoung

2016-01-01

Learning objects originally developed for use in online learning environments can also be used to enhance face-to-face instruction. This study examined the learning impacts of online learning objects packaged into modules and used in different contexts for undergraduate education offered on campus at three institutions. A multi-case study approach…

Mechanisms of object recognition: what we have learned from pigeons

PubMed Central

Soto, Fabian A.; Wasserman, Edward A.

2014-01-01

Behavioral studies of object recognition in pigeons have been conducted for 50 years, yielding a large body of data. Recent work has been directed toward synthesizing this evidence and understanding the visual, associative, and cognitive mechanisms that are involved. The outcome is that pigeons are likely to be the non-primate species for which the computational mechanisms of object recognition are best understood. Here, we review this research and suggest that a core set of mechanisms for object recognition might be present in all vertebrates, including pigeons and people, making pigeons an excellent candidate model to study the neural mechanisms of object recognition. Behavioral and computational evidence suggests that error-driven learning participates in object category learning by pigeons and people, and recent neuroscientific research suggests that the basal ganglia, which are homologous in these species, may implement error-driven learning of stimulus-response associations. Furthermore, learning of abstract category representations can be observed in pigeons and other vertebrates. Finally, there is evidence that feedforward visual processing, a central mechanism in models of object recognition in the primate ventral stream, plays a role in object recognition by pigeons. We also highlight differences between pigeons and people in object recognition abilities, and propose candidate adaptive specializations which may explain them, such as holistic face processing and rule-based category learning in primates. From a modern comparative perspective, such specializations are to be expected regardless of the model species under study. The fact that we have a good idea of which aspects of object recognition differ in people and pigeons should be seen as an advantage over other animal models. From this perspective, we suggest that there is much to learn about human object recognition from studying the “simple” brains of pigeons. PMID:25352784

Intraperirhinal cortex administration of the synthetic cannabinoid, HU210, disrupts object recognition memory in rats.

PubMed

Sticht, Martin A; Jacklin, Derek L; Mechoulam, Raphael; Parker, Linda A; Winters, Boyer D

2015-03-25

Cannabinoids disrupt learning and memory in human and nonhuman participants. Object recognition memory, which is particularly susceptible to the impairing effects of cannabinoids, relies critically on the perirhinal cortex (PRh); however, to date, the effects of cannabinoids within PRh have not been assessed. In the present study, we evaluated the effects of localized administration of the synthetic cannabinoid, HU210 (0.01, 1.0 μg/hemisphere), into PRh on spontaneous object recognition in Long-Evans rats. Animals received intra-PRh infusions of HU210 before the sample phase, and object recognition memory was assessed at various delays in a subsequent retention test. We found that presample intra-PRh HU210 dose dependently (1.0 μg but not 0.01 μg) interfered with spontaneous object recognition performance, exerting an apparently more pronounced effect when memory demands were increased. These novel findings show that cannabinoid agonists in PRh disrupt object recognition memory. Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.

Efficiency of printed materials in worksite health promotion.

PubMed

Kishchuk, N; Anbar, F; O'Loughlin, J; Masson, P; Sacks-Silver, G

1991-01-01

Printed health promotion materials are widely believed to be an efficient means of achieving basic health promotion objectives, such as increasing knowledge of risk factors. This study examined the efficiency of cardiovascular health promotion leaflets in reaching employees in a heterogeneous sample of worksites. Two types of distribution were used: copies of the leaflets were either made available centrally or distributed to each individual employee. Interviews were conducted with 272 employees in six worksites. Respondents were asked whether they recognized, had read, and had learned something from the leaflets. Only one-quarter of respondents recognized the leaflets and only 14% stated that they had learned something. The efficiency of the leaflets was therefore much lower than expected. Z-tests for proportions showed that recognition, reading, and learning were significantly greater among those employees who had been given individual copies of the material. Among those who had been given individual copies, 45% reported recognizing the leaflet, 36% reading it, and 23% learning something from it. Among those who had only central access, the respective scores were 11%, 7% and 6%. These results suggest that the potential cost-effectiveness of printed materials such as leaflets and brochures should be weighed against alternative forms of intervention, given specific program objectives and characteristics of the target population. They also suggest that the cost and effort required in organizing the distribution of individual copies may be recouped in greater penetration.

Rapid effects of dorsal hippocampal G-protein coupled estrogen receptor on learning in female mice.

PubMed

Lymer, Jennifer; Robinson, Alana; Winters, Boyer D; Choleris, Elena

2017-03-01

Through rapid mechanisms of action, estrogens affect learning and memory processes. It has been shown that 17β-estradiol and an Estrogen Receptor (ER) α agonist enhances performance in social recognition, object recognition, and object placement tasks when administered systemically or infused in the dorsal hippocampus. In contrast, systemic and dorsal hippocampal ERβ activation only promote spatial learning. In addition, 17β-estradiol, the ERα and the G-protein coupled estrogen receptor (GPER) agonists increase dendritic spine density in the CA1 hippocampus. Recently, we have shown that selective systemic activation of the GPER also rapidly facilitated social recognition, object recognition, and object placement learning in female mice. Whether activation the GPER specifically in the dorsal hippocampus can also rapidly improve learning and memory prior to acquisition is unknown. Here, we investigated the rapid effects of infusion of the GPER agonist, G-1 (dose: 50nM, 100nM, 200nM), in the dorsal hippocampus on social recognition, object recognition, and object placement learning tasks in home cage. These paradigms were completed within 40min, which is within the range of rapid estrogenic effects. Dorsal hippocampal administration of G-1 improved social (doses: 50nM, 200nM G-1) and object (dose: 200nM G-1) recognition with no effect on object placement. Additionally, when spatial cues were minimized by testing in a Y-apparatus, G-1 administration promoted social (doses: 100nM, 200nM G-1) and object (doses: 50nM, 100nM, 200nM G-1) recognition. Therefore, like ERα, the GPER in the hippocampus appears to be sufficient for the rapid facilitation of social and object recognition in female mice, but not for the rapid facilitation of object placement learning. Thus, the GPER in the dorsal hippocampus is involved in estrogenic mediation of learning and memory and these effects likely occur through rapid signalling mechanisms. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Scaling up spike-and-slab models for unsupervised feature learning.

PubMed

Goodfellow, Ian J; Courville, Aaron; Bengio, Yoshua

2013-08-01

We describe the use of two spike-and-slab models for modeling real-valued data, with an emphasis on their applications to object recognition. The first model, which we call spike-and-slab sparse coding (S3C), is a preexisting model for which we introduce a faster approximate inference algorithm. We introduce a deep variant of S3C, which we call the partially directed deep Boltzmann machine (PD-DBM) and extend our S3C inference algorithm for use on this model. We describe learning procedures for each. We demonstrate that our inference procedure for S3C enables scaling the model to unprecedented large problem sizes, and demonstrate that using S3C as a feature extractor results in very good object recognition performance, particularly when the number of labeled examples is low. We show that the PD-DBM generates better samples than its shallow counterpart, and that unlike DBMs or DBNs, the PD-DBM may be trained successfully without greedy layerwise training.

Ego-Motion and Tracking for Continuous Object Learning: A Brief Survey

DTIC Science & Technology

2017-09-01

ARL-TR-8167• SEP 2017 US Army Research Laboratory Ego-motion and Tracking for ContinuousObject Learning: A Brief Survey by Jason Owens and Philip...SEP 2017 US Army Research Laboratory Ego-motion and Tracking for ContinuousObject Learning: A Brief Survey by Jason Owens and Philip OsteenVehicle...

Parts Marketing. A Student Learning Guide.

ERIC Educational Resources Information Center

Ridge Vocational-Technical Center, Winter Haven, FL.

This learning guide is a self-instructional packet for one task identified as essential for performance on an entry-level job in parts marketing. The guide is based on a terminal performance objective (task) and two enabling objectives. For each enabling objective, some or all of these materials may be presented: learning steps (outline of student…

Transformative Sustainability Learning: Cultivating a Tree-Planting Ethos in Western Kenya

ERIC Educational Resources Information Center

Bull, Marijoan

2013-01-01

Given the fundamental objective of ESD--perspective change--it is increasingly being aligned with the theoretical foundation of Mezirow's Transformative Learning. In 2008, Sipos et al. built upon this connection by proposing a matrix of learning objectives to assess ESD in formal settings. These objectives, grouped under the title of…

Semantic Overlays in Educational Content Networks--The hylOs Approach

ERIC Educational Resources Information Center

Engelhardt, Michael; Hildebrand, Arne; Lange, Dagmar; Schmidt, Thomas C.

2006-01-01

Purpose: The paper aims to introduce an educational content management system, Hypermedia Learning Objects System (hylOs), which is fully compliant to the IEEE LOM eLearning object metadata standard. Enabled through an advanced authoring toolset, hylOs allows the definition of instructional overlays of a given eLearning object mesh.…

Small Schools Student Learning Objectives, K-3: Reading, Language Arts, Mathematics, Science, Social Studies.

ERIC Educational Resources Information Center

Hartl, David, Ed.; And Others

Developed by primary teachers and elementary principals from small districts in Snohomish and Island counties in Washington, this handbook contains sequenced student learning objectives for grades K-3 in the curriculum areas of reading, language arts, mathematics, science, and social studies. Each student learning objective is correlated to the…

Welding. Student Learning Guides.

ERIC Educational Resources Information Center

Ridge Vocational-Technical Center, Winter Haven, FL.

These 23 learning guides are self-instructional packets for 23 tasks identified as essential for performance on an entry-level job in welding. Each guide is based on a terminal performance objective (task) and 1-4 enabling objectives. For each enabling objective, some or all of these materials may be presented: learning steps (outline of student…

An Assistant for Loading Learning Object Metadata: An Ontology Based Approach

ERIC Educational Resources Information Center

Casali, Ana; Deco, Claudia; Romano, Agustín; Tomé, Guillermo

2013-01-01

In the last years, the development of different Repositories of Learning Objects has been increased. Users can retrieve these resources for reuse and personalization through searches in web repositories. The importance of high quality metadata is key for a successful retrieval. Learning Objects are described with metadata usually in the standard…

History, Context, and Policies of a Learning Object Repository

ERIC Educational Resources Information Center

Simpson, Steven Marshall

2016-01-01

Learning object repositories, a form of digital libraries, are robust systems that provide educators new ways to search for educational resources, collaborate with peers, and provide instruction to students in unique and varied ways. This study examines a learning object repository created by a large suburban school district to increase teaching…

The Effects of Using Learning Objects in Two Different Settings

ERIC Educational Resources Information Center

Cakiroglu, Unal; Baki, Adnan; Akkan, Yasar

2012-01-01

The study compared the effects of Learning Objects (LOs) within different applications; in classroom and in extracurricular activities. So in this study, firstly a Learning Object Repository (LOR) has been designed in parallel with 9th grade school mathematics curriculum. One of the two treatment groups was named as "classroom group" (n…

Plumbing and Pipefitting. Student Learning Guides.

ERIC Educational Resources Information Center

Ridge Vocational-Technical Center, Winter Haven, FL.

These 32 learning guides are self-instructional packets for 32 tasks identified as essential for performance on an entry-level job in plumbing and pipefitting. Each guide is based on a terminal performance objective (task) and 1-4 enabling objectives. For each enabling objective, some or all of these materials may be presented: learning steps…

Clothing Production. Student Learning Guides.

ERIC Educational Resources Information Center

Ridge Vocational-Technical Center, Winter Haven, FL.

These 59 learning guides are self-instructional packets for 59 tasks identified as essential for performance on an entry-level job in clothing production. Each guide is based on a terminal performance objective (task) and 2-5 enabling objectives. For each enabling objective, some or all of these materials may be presented: learning steps (outline…

The Sloan-C Pillars and Boundary Objects As a Framework for Evaluating Blended Learning

ERIC Educational Resources Information Center

Laumakis, Mark; Graham, Charles; Dziuban, Chuck

2009-01-01

The authors contend that blended learning represents a boundary object; a construct that brings together constituencies from a variety of backgrounds with each of these cohorts defining the object somewhat differently. The Sloan-C Pillars (learning effectiveness, access, cost effectiveness, student satisfaction, and faculty satisfaction) provide…

Distribution majorization of corner points by reinforcement learning for moving object detection

NASA Astrophysics Data System (ADS)

Wu, Hao; Yu, Hao; Zhou, Dongxiang; Cheng, Yongqiang

2018-04-01

Corner points play an important role in moving object detection, especially in the case of free-moving camera. Corner points provide more accurate information than other pixels and reduce the computation which is unnecessary. Previous works only use intensity information to locate the corner points, however, the information that former and the last frames provided also can be used. We utilize the information to focus on more valuable area and ignore the invaluable area. The proposed algorithm is based on reinforcement learning, which regards the detection of corner points as a Markov process. In the Markov model, the video to be detected is regarded as environment, the selections of blocks for one corner point are regarded as actions and the performance of detection is regarded as state. Corner points are assigned to be the blocks which are seperated from original whole image. Experimentally, we select a conventional method which uses marching and Random Sample Consensus algorithm to obtain objects as the main framework and utilize our algorithm to improve the result. The comparison between the conventional method and the same one with our algorithm show that our algorithm reduce 70% of the false detection.

Human Factors Engineering. Student Supplement,

DTIC Science & Technology

1981-08-01

a job TASK TAXONOMY A classification scheme for the different levels of activities in a system, i.e., job - task - sub-task, etc. TASK-AN~ALYSIS...with the classification of learning objectives by learning category so as to identify learningPhas III guidelines necessary for optimum learning to...correct. .4... .the sequencing of all dependent tasks. .1.. .the classification of learning objectives by learning category and the Identification of

Learning to recognize objects on the fly: a neurally based dynamic field approach.

PubMed

Faubel, Christian; Schöner, Gregor

2008-05-01

Autonomous robots interacting with human users need to build and continuously update scene representations. This entails the problem of rapidly learning to recognize new objects under user guidance. Based on analogies with human visual working memory, we propose a dynamical field architecture, in which localized peaks of activation represent objects over a small number of simple feature dimensions. Learning consists of laying down memory traces of such peaks. We implement the dynamical field model on a service robot and demonstrate how it learns 30 objects from a very small number of views (about 5 per object are sufficient). We also illustrate how properties of feature binding emerge from this framework.

Designing Web-based telemedicine training for military health care providers.

PubMed

Bangert, D; Doktor, R; Johnson, E

2001-01-01

The purpose of the study was to ascertain those learning objectives that will initiate increased use of telemedicine by military health care providers. Telemedicine is increasingly moving to the center of the health care industry's service offerings. As this migration occurs, health professionals will require training for proper and effective change management. The United States Department of Defense (DoD) is embracing the use of telemedicine and wishes to use Web-based training as a tool for effective change management to increase use. This article summarizes the findings of an educational needs assessment of military health care providers for the creation of the DoD Web-based telemedicine training curriculum. Forty-eight health care professionals were interviewed and surveyed to capture their opinions on what learning objectives a telemedicine training curriculum should include. Twenty learning objectives were found to be needed in a telemedicine training program. These 20 learning objectives were grouped into four learning clusters that formed the structure for the training program. In order of importance, the learning clusters were clinical, technical, organizational, and introduction to telemedicine. From these clusters, five Web-based modules were created, with two addressing clinical learning needs and one for each of the other learning objective clusters.

Visual statistical learning is not reliably modulated by selective attention to isolated events

PubMed Central

Musz, Elizabeth; Weber, Matthew J.; Thompson-Schill, Sharon L.

2014-01-01

Recent studies of visual statistical learning (VSL) indicate that the visual system can automatically extract temporal and spatial relationships between objects. We report several attempts to replicate and extend earlier work (Turk-Browne et al., 2005) in which observers performed a cover task on one of two interleaved stimulus sets, resulting in learning of temporal relationships that occur in the attended stream, but not those present in the unattended stream. Across four experiments, we exposed observers to a similar or identical familiarization protocol, directing attention to one of two interleaved stimulus sets; afterward, we assessed VSL efficacy for both sets using either implicit response-time measures or explicit familiarity judgments. In line with prior work, we observe learning for the attended stimulus set. However, unlike previous reports, we also observe learning for the unattended stimulus set. When instructed to selectively attend to only one of the stimulus sets and ignore the other set, observers could extract temporal regularities for both sets. Our efforts to experimentally decrease this effect by changing the cover task (Experiment 1) or the complexity of the statistical regularities (Experiment 3) were unsuccessful. A fourth experiment using a different assessment of learning likewise failed to show an attentional effect. Simulations drawing random samples our first three experiments (n=64) confirm that the distribution of attentional effects in our sample closely approximates the null. We offer several potential explanations for our failure to replicate earlier findings, and discuss how our results suggest limiting conditions on the relevance of attention to VSL. PMID:25172196

Associative vocabulary learning: development and testing of two paradigms for the (re-) acquisition of action- and object-related words.

PubMed

Freundlieb, Nils; Ridder, Volker; Dobel, Christian; Enriquez-Geppert, Stefanie; Baumgaertner, Annette; Zwitserlood, Pienie; Gerloff, Christian; Hummel, Friedhelm C; Liuzzi, Gianpiero

2012-01-01

Despite a growing number of studies, the neurophysiology of adult vocabulary acquisition is still poorly understood. One reason is that paradigms that can easily be combined with neuroscientfic methods are rare. Here, we tested the efficiency of two paradigms for vocabulary (re-) acquisition, and compared the learning of novel words for actions and objects. Cortical networks involved in adult native-language word processing are widespread, with differences postulated between words for objects and actions. Words and what they stand for are supposed to be grounded in perceptual and sensorimotor brain circuits depending on their meaning. If there are specific brain representations for different word categories, we hypothesized behavioural differences in the learning of action-related and object-related words. Paradigm A, with the learning of novel words for body-related actions spread out over a number of days, revealed fast learning of these new action words, and stable retention up to 4 weeks after training. The single-session Paradigm B employed objects and actions. Performance during acquisition did not differ between action-related and object-related words (time*word category: p = 0.01), but the translation rate was clearly better for object-related (79%) than for action-related words (53%, p = 0.002). Both paradigms yielded robust associative learning of novel action-related words, as previously demonstrated for object-related words. Translation success differed for action- and object-related words, which may indicate different neural mechanisms. The paradigms tested here are well suited to investigate such differences with neuroscientific means. Given the stable retention and minimal requirements for conscious effort, these learning paradigms are promising for vocabulary re-learning in brain-lesioned people. In combination with neuroimaging, neuro-stimulation or pharmacological intervention, they may well advance the understanding of language learning to optimize therapeutic strategies.

Point-of-care mobile digital microscopy and deep learning for the detection of soil-transmitted helminths and Schistosoma haematobium

PubMed Central

Holmström, Oscar; Linder, Nina; Ngasala, Billy; Mårtensson, Andreas; Linder, Ewert; Lundin, Mikael; Moilanen, Hannu; Suutala, Antti; Diwan, Vinod; Lundin, Johan

2017-01-01

ABSTRACT Background: Microscopy remains the gold standard in the diagnosis of neglected tropical diseases. As resource limited, rural areas often lack laboratory equipment and trained personnel, new diagnostic techniques are needed. Low-cost, point-of-care imaging devices show potential in the diagnosis of these diseases. Novel, digital image analysis algorithms can be utilized to automate sample analysis. Objective: Evaluation of the imaging performance of a miniature digital microscopy scanner for the diagnosis of soil-transmitted helminths and Schistosoma haematobium, and training of a deep learning-based image analysis algorithm for automated detection of soil-transmitted helminths in the captured images. Methods: A total of 13 iodine-stained stool samples containing Ascaris lumbricoides, Trichuris trichiura and hookworm eggs and 4 urine samples containing Schistosoma haematobium were digitized using a reference whole slide-scanner and the mobile microscopy scanner. Parasites in the images were identified by visual examination and by analysis with a deep learning-based image analysis algorithm in the stool samples. Results were compared between the digital and visual analysis of the images showing helminth eggs. Results: Parasite identification by visual analysis of digital slides captured with the mobile microscope was feasible for all analyzed parasites. Although the spatial resolution of the reference slide-scanner is higher, the resolution of the mobile microscope is sufficient for reliable identification and classification of all parasites studied. Digital image analysis of stool sample images captured with the mobile microscope showed high sensitivity for detection of all helminths studied (range of sensitivity = 83.3–100%) in the test set (n = 217) of manually labeled helminth eggs. Conclusions: In this proof-of-concept study, the imaging performance of a mobile, digital microscope was sufficient for visual detection of soil-transmitted helminths and Schistosoma haematobium. Furthermore, we show that deep learning-based image analysis can be utilized for the automated detection and classification of helminths in the captured images. PMID:28838305

Object Familiarity Facilitates Foreign Word Learning in Preschoolers

ERIC Educational Resources Information Center

Sera, Maria D.; Cole, Caitlin A.; Oromendia, Mercedes; Koenig, Melissa A.

2014-01-01

Studying how children learn words in a foreign language can shed light on how language learning changes with development. In one experiment, we examined whether three-, four-, and five-year-olds could learn and remember words for familiar and unfamiliar objects in their native English and a foreign language. All age groups could learn and remember…

Technically Speaking: Transforming Language Learning through Virtual Learning Environments (MOOs).

ERIC Educational Resources Information Center

von der Emde, Silke; Schneider, Jeffrey; Kotter, Markus

2001-01-01

Draws on experiences from a 7-week exchange between students learning German at an American college and advanced students of English at a German university. Maps out the benefits to using a MOO (multiple user domains object-oriented) for language learning: a student-centered learning environment structured by such objectives as peer teaching,…

Semi-Supervised Tripled Dictionary Learning for Standard-dose PET Image Prediction using Low-dose PET and Multimodal MRI

PubMed Central

Wang, Yan; Ma, Guangkai; An, Le; Shi, Feng; Zhang, Pei; Lalush, David S.; Wu, Xi; Pu, Yifei; Zhou, Jiliu; Shen, Dinggang

2017-01-01

Objective To obtain high-quality positron emission tomography (PET) image with low-dose tracer injection, this study attempts to predict the standard-dose PET (S-PET) image from both its low-dose PET (L-PET) counterpart and corresponding magnetic resonance imaging (MRI). Methods It was achieved by patch-based sparse representation (SR), using the training samples with a complete set of MRI, L-PET and S-PET modalities for dictionary construction. However, the number of training samples with complete modalities is often limited. In practice, many samples generally have incomplete modalities (i.e., with one or two missing modalities) that thus cannot be used in the prediction process. In light of this, we develop a semi-supervised tripled dictionary learning (SSTDL) method for S-PET image prediction, which can utilize not only the samples with complete modalities (called complete samples) but also the samples with incomplete modalities (called incomplete samples), to take advantage of the large number of available training samples and thus further improve the prediction performance. Results Validation was done on a real human brain dataset consisting of 18 subjects, and the results show that our method is superior to the SR and other baseline methods. Conclusion This work proposed a new S-PET prediction method, which can significantly improve the PET image quality with low-dose injection. Significance The proposed method is favorable in clinical application since it can decrease the potential radiation risk for patients. PMID:27187939

An explanatory model of academic achievement based on aptitudes, goal orientations, self-concept and learning strategies.

PubMed

Miñano Pérez, Pablo; Castejón Costa, Juan-Luis; Gilar Corbí, Raquel

2012-03-01

As a result of studies examining factors involved in the learning process, various structural models have been developed to explain the direct and indirect effects that occur between the variables in these models. The objective was to evaluate a structural model of cognitive and motivational variables predicting academic achievement, including general intelligence, academic self-concept, goal orientations, effort and learning strategies. The sample comprised of 341 Spanish students in the first year of compulsory secondary education. Different tests and questionnaires were used to evaluate each variable, and Structural Equation Modelling (SEM) was applied to contrast the relationships of the initial model. The model proposed had a satisfactory fit, and all the hypothesised relationships were significant. General intelligence was the variable most able to explain academic achievement. Also important was the direct influence of academic self-concept on achievement, goal orientations and effort, as well as the mediating ability of effort and learning strategies between academic goals and final achievement.

Learning transitive verbs from single-word verbs in the input by young children acquiring English.

PubMed

Ninio, Anat

2016-09-01

The environmental context of verbs addressed by adults to young children is claimed to be uninformative regarding the verbs' meaning, yielding the Syntactic Bootstrapping Hypothesis that, for verb learning, full sentences are needed to demonstrate the semantic arguments of verbs. However, reanalysis of Gleitman's (1990) original data regarding input to a blind child revealed the context of single-word parental verbs to be more transparent than that of sentences. We tested the hypothesis that English-speaking children learn their early verbs from parents' single-word utterances. Distribution of single-word transitive verbs produced by a large sample of young children was strongly predicted by the relative token frequency of verbs in parental single-word utterances, but multiword sentences had no predictive value. Analysis of the interactive context showed that objects of verbs are retrievable by pragmatic inference, as is the meaning of the verbs. Single-word input appears optimal for learning an initial vocabulary of verbs.

The use of single-date MODIS imagery for estimating large-scale urban impervious surface fraction with spectral mixture analysis and machine learning techniques

NASA Astrophysics Data System (ADS)

Deng, Chengbin; Wu, Changshan

2013-12-01

Urban impervious surface information is essential for urban and environmental applications at the regional/national scales. As a popular image processing technique, spectral mixture analysis (SMA) has rarely been applied to coarse-resolution imagery due to the difficulty of deriving endmember spectra using traditional endmember selection methods, particularly within heterogeneous urban environments. To address this problem, we derived endmember signatures through a least squares solution (LSS) technique with known abundances of sample pixels, and integrated these endmember signatures into SMA for mapping large-scale impervious surface fraction. In addition, with the same sample set, we carried out objective comparative analyses among SMA (i.e. fully constrained and unconstrained SMA) and machine learning (i.e. Cubist regression tree and Random Forests) techniques. Analysis of results suggests three major conclusions. First, with the extrapolated endmember spectra from stratified random training samples, the SMA approaches performed relatively well, as indicated by small MAE values. Second, Random Forests yields more reliable results than Cubist regression tree, and its accuracy is improved with increased sample sizes. Finally, comparative analyses suggest a tentative guide for selecting an optimal approach for large-scale fractional imperviousness estimation: unconstrained SMA might be a favorable option with a small number of samples, while Random Forests might be preferred if a large number of samples are available.

From brain synapses to systems for learning and memory: Object recognition, spatial navigation, timed conditioning, and movement control.

PubMed

Grossberg, Stephen

2015-09-24

This article provides an overview of neural models of synaptic learning and memory whose expression in adaptive behavior depends critically on the circuits and systems in which the synapses are embedded. It reviews Adaptive Resonance Theory, or ART, models that use excitatory matching and match-based learning to achieve fast category learning and whose learned memories are dynamically stabilized by top-down expectations, attentional focusing, and memory search. ART clarifies mechanistic relationships between consciousness, learning, expectation, attention, resonance, and synchrony. ART models are embedded in ARTSCAN architectures that unify processes of invariant object category learning, recognition, spatial and object attention, predictive remapping, and eye movement search, and that clarify how conscious object vision and recognition may fail during perceptual crowding and parietal neglect. The generality of learned categories depends upon a vigilance process that is regulated by acetylcholine via the nucleus basalis. Vigilance can get stuck at too high or too low values, thereby causing learning problems in autism and medial temporal amnesia. Similar synaptic learning laws support qualitatively different behaviors: Invariant object category learning in the inferotemporal cortex; learning of grid cells and place cells in the entorhinal and hippocampal cortices during spatial navigation; and learning of time cells in the entorhinal-hippocampal system during adaptively timed conditioning, including trace conditioning. Spatial and temporal processes through the medial and lateral entorhinal-hippocampal system seem to be carried out with homologous circuit designs. Variations of a shared laminar neocortical circuit design have modeled 3D vision, speech perception, and cognitive working memory and learning. A complementary kind of inhibitory matching and mismatch learning controls movement. This article is part of a Special Issue entitled SI: Brain and Memory. Copyright © 2014 Elsevier B.V. All rights reserved.

Information and Communication Technology for French and English Speaking Postsecondary Students with Disabilities: What Are Their Needs and How Well Are These Being Met?

ERIC Educational Resources Information Center

Fichten, Catherine S.; Nguyen, Mai N.; Asuncion, Jennison V.; Barile, Maria; Budd, Jillian; Amsel, Rhonda; Libman, Eva

2010-01-01

This study evaluates how well information and communication technology (ICT) related needs of students with various disabilities are met at school, at home, and in e-learning contexts. Results are based on the POSITIVES Scale, a 26 item objective measure of how well the ICT related needs of these students are met. The sample consists of 131…

Common Learning Objectives for Undergraduate Control Systems Laboratories

ERIC Educational Resources Information Center

Reck, Rebecca M.

2017-01-01

Course objectives, like research objectives and product requirements, help provide clarity and direction for faculty and students. Unfortunately, course and laboratory objectives are not always clearly stated. Without a clear set of objectives, it can be hard to design a learning experience and determine whether students are achieving the intended…

The role of picture of process (pp) on senior high school students’ collision concept learning activities and multirepresentation ability

NASA Astrophysics Data System (ADS)

Sutarto; Indrawati; Wicaksono, I.

2018-04-01

The objectives of the study are to describe the effect of PP collision concepts to high school students’ learning activities and multirepresentation abilities. This study was a quasi experimental with non- equivalent post-test only control group design. The population of this study were students who will learn the concept of collision in three state Senior High Schools in Indonesia, with a sample of each school 70 students, 35 students as an experimental group and 35 students as a control group. Technique of data collection were observation and test. The data were analized by descriptive and inferensial statistic. Student learning activities were: group discussions, describing vectors of collision events, and formulating problem-related issues of impact. Multirepresentation capabilities were student ability on image representation, verbal, mathematics, and graph. The results showed that the learning activities in the three aspects for the three high school average categorized good. The impact of using PP on students’ ability on image and graph representation were a significant impact, but for verbal and mathematical skills there are differences but not significant.

E-learning and the future of dental education: opinions of administrators and information technology specialists.

PubMed

Hillenburg, K L; Cederberg, R A; Gray, S A; Hurst, C L; Johnson, G K; Potter, B J

2006-08-01

The digital revolution and growth of the Internet have led to many innovations in the area of electronic learning (e-learning). To survive and prosper, educators must be prepared to respond creatively to these changes. Administrators and information technology specialists at six dental schools and their parent institutions were interviewed regarding their opinions of the impact that e-learning will have on the future of dental education. Interview questions encompassed vision, rate of change, challenges, role of faculty, resources, enrolment, collaboration, responsibility for course design and content, mission and fate of the institution. The objective of this qualitative study was to sample the opinions of educational administrators and information technology specialists from selected US universities regarding the impact of e-learning on dental education to detect trends in their attitudes. Responses to the survey indicated disagreement between administrators and informational technology specialists regarding the rate of change, generation of resources, impact on enrolment, responsibility for course design and content, mission and fate of the university. General agreement was noted with regard to vision, challenges, role of faculty and need for collaboration.

Learning in the zone: toward workforce development of evidence-based public policy communication.

PubMed

Meyerson, Beth E; Haderxhanaj, Laura T; Comer, Karen; Zimet, Gregory D

2018-06-05

Evidence-based policy communication (EBPC) is an important, emerging focus in public health research. However, we have yet to understand public health workforce ability to develop and/or use it. The study objective was to characterize capacity to develop and use EBPC and identify cooperative learning and development opportunities using the case of Human papillomavirus (HPV). Vygotsky's Zone of Proximal Development (ZPD) informed guided interviews with 27 advocates in Indiana from government, industry, research, state associations and individuals. Participants focused on HPV, cancer, women's health, school health and minority health. Capacity to develop and use EBPC was reported to develop through cooperative learning opportunities on the job or in advocacy focused coalitions. Coalition learning appeared to translate across health topics. Notably, policy experience did not assure understanding or use of EBPC. The ZPD framework can inform workforce EBPC interventions by focusing on actual development, potential development and factors for learning and development in the ZPD. Future studies should further clarify and evaluate emerging indicators in additional public health policy areas with a larger sample.

Discriminative Bayesian Dictionary Learning for Classification.

PubMed

Akhtar, Naveed; Shafait, Faisal; Mian, Ajmal

2016-12-01

We propose a Bayesian approach to learn discriminative dictionaries for sparse representation of data. The proposed approach infers probability distributions over the atoms of a discriminative dictionary using a finite approximation of Beta Process. It also computes sets of Bernoulli distributions that associate class labels to the learned dictionary atoms. This association signifies the selection probabilities of the dictionary atoms in the expansion of class-specific data. Furthermore, the non-parametric character of the proposed approach allows it to infer the correct size of the dictionary. We exploit the aforementioned Bernoulli distributions in separately learning a linear classifier. The classifier uses the same hierarchical Bayesian model as the dictionary, which we present along the analytical inference solution for Gibbs sampling. For classification, a test instance is first sparsely encoded over the learned dictionary and the codes are fed to the classifier. We performed experiments for face and action recognition; and object and scene-category classification using five public datasets and compared the results with state-of-the-art discriminative sparse representation approaches. Experiments show that the proposed Bayesian approach consistently outperforms the existing approaches.

A framework for analyzing interdisciplinary tasks: implications for student learning and curricular design.

PubMed

Gouvea, Julia Svoboda; Sawtelle, Vashti; Geller, Benjamin D; Turpen, Chandra

2013-06-01

The national conversation around undergraduate science instruction is calling for increased interdisciplinarity. As these calls increase, there is a need to consider the learning objectives of interdisciplinary science courses and how to design curricula to support those objectives. We present a framework that can help support interdisciplinary design research. We developed this framework in an introductory physics for life sciences majors (IPLS) course for which we designed a series of interdisciplinary tasks that bridge physics and biology. We illustrate how this framework can be used to describe the variation in the nature and degree of interdisciplinary interaction in tasks, to aid in redesigning tasks to better align with interdisciplinary learning objectives, and finally, to articulate design conjectures that posit how different characteristics of these tasks might support or impede interdisciplinary learning objectives. This framework will be useful for both curriculum designers and education researchers seeking to understand, in more concrete terms, what interdisciplinary learning means and how integrated science curricula can be designed to support interdisciplinary learning objectives.

The construction of learning objects on communicable diseases for community health agents.

PubMed

Pacheco, Kátia Cilene Ferreira; Azambuja, Marcelo Schenk de; Bonamigo, Andrea Wander

2018-06-07

To describe the creation of a learning object about communicable diseases and their identification, monitoring, and prevention for community health agents. The qualitative, exploratory, case study conducted in the North District Management Zone - Baltazar of the Universidade Federal de Ciências da Saúde de Porto Alegre, from October to January 2015 2016. The study had 58 participants and consisted of the stages field research, Bardin's content analysis, and design of the learning object. The profile of the professionals working in the location was established. These agents identified the most commonly found diseases and stressed their needs in relation to a technological resource. The identified needs were considered to define the content and structure the learning object. The learning object is an alternative method for sharing knowledge on communicable diseases. The tool allows the combination of technology with teaching, which makes the learning process and the work of the community health agents more rewarding and productive.

A Framework for Analyzing Interdisciplinary Tasks: Implications for Student Learning and Curricular Design

PubMed Central

Gouvea, Julia Svoboda; Sawtelle, Vashti; Geller, Benjamin D.; Turpen, Chandra

2013-01-01

The national conversation around undergraduate science instruction is calling for increased interdisciplinarity. As these calls increase, there is a need to consider the learning objectives of interdisciplinary science courses and how to design curricula to support those objectives. We present a framework that can help support interdisciplinary design research. We developed this framework in an introductory physics for life sciences majors (IPLS) course for which we designed a series of interdisciplinary tasks that bridge physics and biology. We illustrate how this framework can be used to describe the variation in the nature and degree of interdisciplinary interaction in tasks, to aid in redesigning tasks to better align with interdisciplinary learning objectives, and finally, to articulate design conjectures that posit how different characteristics of these tasks might support or impede interdisciplinary learning objectives. This framework will be useful for both curriculum designers and education researchers seeking to understand, in more concrete terms, what interdisciplinary learning means and how integrated science curricula can be designed to support interdisciplinary learning objectives. PMID:23737627

The evaluation of student-centredness of teaching and learning: a new mixed-methods approach

PubMed Central

Lemos, Ana R.; Sandars, John E.; Alves, Palmira

2014-01-01

Objectives The aim of the study was to develop and consider the usefulness of a new mixed-methods approach to evaluate the student-centredness of teaching and learning on undergraduate medical courses. An essential paradigm for the evaluation was the coherence between how teachers conceptualise their practice (espoused theories) and their actual practice (theories-in-use). Methods The context was a module within an integrated basic sciences course in an undergraduate medical degree programme. The programme had an explicit intention of providing a student-centred curriculum. A content analysis framework based on Weimer’s dimensions of student-centred teaching was used to analyze data collected from individual interviews with seven teachers to identify espoused theories and 34h of classroom observations and one student focus group to identify theories-in-use. The interviewees were identified by purposeful sampling. The findings from the three methods were triangulated to evaluate the student-centredness of teaching and learning on the course. Results Different, but complementary, perspectives of the student-centredness of teaching and learning were identified by each method. The triangulation of the findings revealed coherence between the teachers’ espoused theories and theories-in-use. Conclusions A mixed-methods approach that combined classroom observations with interviews from a purposeful sample of teachers and students offered a useful evaluation of the extent of student-centredness of teaching and learning of this basic science course. Our case study suggests that this new approach is applicable to other courses in medical education. PMID:25341225

OLIVER: an online library of images for veterinary education and research.

PubMed

McGreevy, Paul; Shaw, Tim; Burn, Daniel; Miller, Nick

2007-01-01

As part of a strategic move by the University of Sydney toward increased flexibility in learning, the Faculty of Veterinary Science undertook a number of developments involving Web-based teaching and assessment. OLIVER underpins them by providing a rich, durable repository for learning objects. To integrate Web-based learning, case studies, and didactic presentations for veterinary and animal science students, we established an online library of images and other learning objects for use by academics in the Faculties of Veterinary Science and Agriculture. The objectives of OLIVER were to maximize the use of the faculty's teaching resources by providing a stable archiving facility for graphic images and other multimedia learning objects that allows flexible and precise searching, integrating indexing standards, thesauri, pull-down lists of preferred terms, and linking of objects within cases. OLIVER offers a portable and expandable Web-based shell that facilitates ongoing storage of learning objects in a range of media. Learning objects can be downloaded in common, standardized formats so that they can be easily imported for use in a range of applications, including Microsoft PowerPoint, WebCT, and Microsoft Word. OLIVER now contains more than 9,000 images relating to many facets of veterinary science; these are annotated and supported by search engines that allow rapid access to both images and relevant information. The Web site is easily updated and adapted as required.

Object based implicit contextual learning: a study of eye movements.

PubMed

van Asselen, Marieke; Sampaio, Joana; Pina, Ana; Castelo-Branco, Miguel

2011-02-01

Implicit contextual cueing refers to a top-down mechanism in which visual search is facilitated by learned contextual features. In the current study we aimed to investigate the mechanism underlying implicit contextual learning using object information as a contextual cue. Therefore, we measured eye movements during an object-based contextual cueing task. We demonstrated that visual search is facilitated by repeated object information and that this reduction in response times is associated with shorter fixation durations. This indicates that by memorizing associations between objects in our environment we can recognize objects faster, thereby facilitating visual search.

Prediction errors to emotional expressions: the roles of the amygdala in social referencing.

PubMed

Meffert, Harma; Brislin, Sarah J; White, Stuart F; Blair, James R

2015-04-01

Social referencing paradigms in humans and observational learning paradigms in animals suggest that emotional expressions are important for communicating valence. It has been proposed that these expressions initiate stimulus-reinforcement learning. Relatively little is known about the role of emotional expressions in reinforcement learning, particularly in the context of social referencing. In this study, we examined object valence learning in the context of a social referencing paradigm. Participants viewed objects and faces that turned toward the objects and displayed a fearful, happy or neutral reaction to them, while judging the gender of these faces. Notably, amygdala activation was larger when the expressions following an object were less expected. Moreover, when asked, participants were both more likely to want to approach, and showed stronger amygdala responses to, objects associated with happy relative to objects associated with fearful expressions. This suggests that the amygdala plays two roles in social referencing: (i) initiating learning regarding the valence of an object as a function of prediction errors to expressions displayed toward this object and (ii) orchestrating an emotional response to the object when value judgments are being made regarding this object. Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

Managing and learning with multiple models: Objectives and optimization algorithms

USGS Publications Warehouse

Probert, William J. M.; Hauser, C.E.; McDonald-Madden, E.; Runge, M.C.; Baxter, P.W.J.; Possingham, H.P.

2011-01-01

The quality of environmental decisions should be gauged according to managers' objectives. Management objectives generally seek to maximize quantifiable measures of system benefit, for instance population growth rate. Reaching these goals often requires a certain degree of learning about the system. Learning can occur by using management action in combination with a monitoring system. Furthermore, actions can be chosen strategically to obtain specific kinds of information. Formal decision making tools can choose actions to favor such learning in two ways: implicitly via the optimization algorithm that is used when there is a management objective (for instance, when using adaptive management), or explicitly by quantifying knowledge and using it as the fundamental project objective, an approach new to conservation.This paper outlines three conservation project objectives - a pure management objective, a pure learning objective, and an objective that is a weighted mixture of these two. We use eight optimization algorithms to choose actions that meet project objectives and illustrate them in a simulated conservation project. The algorithms provide a taxonomy of decision making tools in conservation management when there is uncertainty surrounding competing models of system function. The algorithms build upon each other such that their differences are highlighted and practitioners may see where their decision making tools can be improved. ?? 2010 Elsevier Ltd.

Relationships among Blood Pressure, Triglycerides and Verbal Learning in African Americans

PubMed Central

Sims, Regina C.; Madhere, Serge; Gordon, Shalanda; Clark, Elijah; Abayomi, Kobi A.; Callender, Clive O.; Campbell, Alfonso L.

2013-01-01

Background Individuals at greater risk for cardiovascular disease (CVD) display poorer cognitive functioning across various cognitive domains. This finding is particularly prevalent among older adults; however, few studies examine these relationships among younger adults or among African Americans. Purpose The objective was to examine the relationships among 2 cardiovascular risk factors, elevated blood pressure and elevated triglycerides, and verbal learning in a community-based sample of African Americans. Methods Measurements of blood pressure and triglycerides were obtained in 121 African-American adults and compared to performance on 3 domains of the California Verbal Learning Test-II (CVLT-II). Results Blood pressure was not related to CVLT-II performance. Triglyceride levels were inversely related to CVLT-II performance. Higher triglyceride levels were associated with poorer immediate, short delay and long delay recall. Conclusions Consistent with studies involving older participants, the current investigation shows that in a nonelderly sample of African Americans, triglyceride levels may be related to cognitive functioning. Because early detection and intervention of vascular-related cognitive impairment may have a salutary effect, future studies should include younger adults to highlight the impact of cardiovascular risk on cognition. PMID:18942281

Interservice Procedures for Instructional Systems Development. Phase 3. Develop

DTIC Science & Technology

1975-08-01

Occur at wide intervals to be learned *Reads about the actions to *Occur at the end, but before be learned tests or on-the-job performance *Watches a...the particular sub-category. Use the learning objective action statement, conditions, standards, and the test item to help select which guidelines to...objective. EXAMPLE If you have a CLASSIFYING objective like "identifying poisonous plants,’ when you get to guideline 16. "To test learning, require the

Tracking Multiple Statistics: Simultaneous Learning of Object Names and Categories in English and Mandarin Speakers

ERIC Educational Resources Information Center

Chen, Chi-hsin; Gershkoff-Stowe, Lisa; Wu, Chih-Yi; Cheung, Hintat; Yu, Chen

2017-01-01

Two experiments were conducted to examine adult learners' ability to extract multiple statistics in simultaneously presented visual and auditory input. Experiment 1 used a cross-situational learning paradigm to test whether English speakers were able to use co-occurrences to learn word-to-object mappings and concurrently form object categories…

Teaching and Assessing Ethics as a Learning Objective: One School's Journey

ERIC Educational Resources Information Center

Templin, Carl R.; Christensen, David

2009-01-01

This paper reports the results of a ten-year effort to establish ethics as a learning objective for all business students, to assess the effectiveness in achieving that learning objective and to incorporate ethical conduct as a part of the school's organizational culture. First, it addresses the importance of ethics instruction for all business…

The Open Learning Object Model to Promote Open Educational Resources

ERIC Educational Resources Information Center

Fulantelli, Giovanni; Gentile, Manuel; Taibi, Davide; Allegra, Mario

2008-01-01

In this paper we present the results of research work, that forms part of the activities of the EU-funded project SLOOP: Sharing Learning Objects in an Open Perspective, aimed at encouraging the definition, development and management of Open Educational Resources based on the Learning Object paradigm (Wiley, 2000). We present a model of Open…

Differences in How Monolingual and Bilingual Children Learn Second Labels for Familiar Objects

ERIC Educational Resources Information Center

Rowe, Lindsey; Jacobson, Rebecca; Saylor, Megan M.

2015-01-01

Monolingual children sometimes resist learning second labels for familiar objects. One explanation is that they are guided by word learning constraints that lead to the assumption that objects have only one name. It is less clear whether bilingual children observe this constraint. In the current study, we test the hypothesis that bilingual…

Small Schools Student Learning Objectives, 9-12: Mathematics, Reading, Reading in the Content Areas, Language Arts.

ERIC Educational Resources Information Center

Nelson, JoAnne, Ed.; Hartl, David, Ed.

Designed by Washington curriculum specialists and secondary teachers to assist teachers in small schools with the improvement of curriculum and instruction and to aid smaller districts lacking curriculum personnel to comply with Washington's Student Learning Objectives Law, this handbook contains learning objectives in the areas of language arts,…

Searching for and Positioning of Contextualized Learning Objects

ERIC Educational Resources Information Center

Baldiris, Silvia; Graf, Sabine; Fabregat, Ramon; Mendez, Nestor Dario Duque

2012-01-01

Learning object economies are marketplaces for the sharing and reuse of learning objects (LO). There are many motivations for stimulating the development of the LO economy. The main reason is the possibility of providing the right content, at the right time, to the right learner according to adequate quality standards in the context of a lifelong…

A Selection System and Catalog for Instructional Media and Devices.

ERIC Educational Resources Information Center

Boucher, Brian G.; And Others

A system is presented which facilitates the selection of training media and devices based on the requirements of specific learning objectives. The system consists of the use of a set of descriptive parameters which are common to both learning objectives and media. The system allows the essential intent of learning objectives to be analyzed in…

Real-world visual statistics and infants' first-learned object names

PubMed Central

Clerkin, Elizabeth M.; Hart, Elizabeth; Rehg, James M.; Yu, Chen

2017-01-01

We offer a new solution to the unsolved problem of how infants break into word learning based on the visual statistics of everyday infant-perspective scenes. Images from head camera video captured by 8 1/2 to 10 1/2 month-old infants at 147 at-home mealtime events were analysed for the objects in view. The images were found to be highly cluttered with many different objects in view. However, the frequency distribution of object categories was extremely right skewed such that a very small set of objects was pervasively present—a fact that may substantially reduce the problem of referential ambiguity. The statistical structure of objects in these infant egocentric scenes differs markedly from that in the training sets used in computational models and in experiments on statistical word-referent learning. Therefore, the results also indicate a need to re-examine current explanations of how infants break into word learning. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’. PMID:27872373

Tracking Multiple Statistics: Simultaneous Learning of Object Names and Categories in English and Mandarin Speakers.

PubMed

Chen, Chi-Hsin; Gershkoff-Stowe, Lisa; Wu, Chih-Yi; Cheung, Hintat; Yu, Chen

2017-08-01

Two experiments were conducted to examine adult learners' ability to extract multiple statistics in simultaneously presented visual and auditory input. Experiment 1 used a cross-situational learning paradigm to test whether English speakers were able to use co-occurrences to learn word-to-object mappings and concurrently form object categories based on the commonalities across training stimuli. Experiment 2 replicated the first experiment and further examined whether speakers of Mandarin, a language in which final syllables of object names are more predictive of category membership than English, were able to learn words and form object categories when trained with the same type of structures. The results indicate that both groups of learners successfully extracted multiple levels of co-occurrence and used them to learn words and object categories simultaneously. However, marked individual differences in performance were also found, suggesting possible interference and competition in processing the two concurrent streams of regularities. Copyright © 2016 Cognitive Science Society, Inc.

Implicit and Explicit Contributions to Object Recognition: Evidence from Rapid Perceptual Learning

PubMed Central

Hassler, Uwe; Friese, Uwe; Gruber, Thomas

2012-01-01

The present study investigated implicit and explicit recognition processes of rapidly perceptually learned objects by means of steady-state visual evoked potentials (SSVEP). Participants were initially exposed to object pictures within an incidental learning task (living/non-living categorization). Subsequently, degraded versions of some of these learned pictures were presented together with degraded versions of unlearned pictures and participants had to judge, whether they recognized an object or not. During this test phase, stimuli were presented at 15 Hz eliciting an SSVEP at the same frequency. Source localizations of SSVEP effects revealed for implicit and explicit processes overlapping activations in orbito-frontal and temporal regions. Correlates of explicit object recognition were additionally found in the superior parietal lobe. These findings are discussed to reflect facilitation of object-specific processing areas within the temporal lobe by an orbito-frontal top-down signal as proposed by bi-directional accounts of object recognition. PMID:23056558

Development and Assessment of an E-learning Course on Pediatric Cardiology Basics

PubMed Central

2017-01-01

Background Early detection of congenital heart disease is a worldwide problem. This is more critical in developing countries, where shortage of professional specialists and structural health care problems are a constant. E-learning has the potential to improve capacity, by overcoming distance barriers and by its ability to adapt to the reduced time of health professionals. Objective The study aimed to develop an e-learning pediatric cardiology basics course and evaluate its pedagogical impact and user satisfaction. Methods The sample consisted of 62 health professionals, including doctors, nurses, and medical students, from 20 hospitals linked via a telemedicine network in Northeast Brazil. The course was developed using Moodle (Modular Object Oriented Dynamic Learning Environment; Moodle Pty Ltd, Perth, Australia) and contents adapted from a book on this topic. Pedagogical impact evaluation used a pre and posttest approach. User satisfaction was evaluated using Wang’s questionnaire. Results Pedagogical impact results revealed differences in knowledge assessment before and after the course (Z=−4.788; P<.001). Questionnaire results indicated high satisfaction values (Mean=87%; SD=12%; minimum=67%; maximum=100%). Course adherence was high (79%); however, the withdrawal exhibited a value of 39%, with the highest rate in the early chapters. Knowledge gain revealed significant differences according to the profession (X22=8.6; P=.01) and specialty (X22=8.4; P=.04). Time dedication to the course was significantly different between specialties (X22=8.2; P=.04). Conclusions The main contributions of this study are the creation of an asynchronous e-learning course on Moodle and the evaluation of its impact, confirming that e-learning is a viable tool to improve training in neonatal congenital heart diseases. PMID:28490416

Assessing Integration of Clinical and Public Health Skills in Preventive Medicine Residencies: Using Competency Mapping

PubMed Central

Sarigiannis, Amy N.; Boulton, Matthew L.

2012-01-01

Objectives. We evaluated the utility of a competency mapping process for assessing the integration of clinical and public health skills in a newly developed Community Health Center (CHC) rotation at the University of Michigan School of Public Health Preventive Medicine residency. Methods. Learning objectives for the CHC rotation were derived from the Accreditation Council for Graduate Medical Education core clinical preventive medicine competencies. CHC learning objectives were mapped to clinical preventive medicine competencies specific to the specialty of public health and general preventive medicine. Objectives were also mapped to The Council on Linkages Between Academia and Public Health Practice’s tier 2 Core Competencies for Public Health Professionals. Results. CHC learning objectives mapped to all 4 (100%) of the public health and general preventive medicine clinical preventive medicine competencies. CHC population-level learning objectives mapped to 32 (94%) of 34 competencies for public health professionals. Conclusions. Utilizing competency mapping to assess clinical–public health integration in a new CHC rotation proved to be feasible and useful. Clinical preventive medicine learning objectives for a CHC rotation can also address public health competencies. PMID:22690972

Plan of Work 2010: Towards True Student-Centered Learning

ERIC Educational Resources Information Center

European Students' Union (NJ1), 2010

2010-01-01

The European Students' Union's (ESU's) vision regarding the Student Centered Learning concept stems from the fundamental belief that the learning process should have at its core learning objectives as they are prioritized by each individual students, also that each (potential) student should be empowered to define those objectives and progress…

Form over Substance: Learning Objectives in the Business Core

ERIC Educational Resources Information Center

Stokes, Leonard; Rosetti, Joseph L.; King, Michelle

2010-01-01

While members of the business faculty community have been advocating active learning in the classroom, it appears that textbooks encourage learning from a passive perspective. A review of learning objectives from 16 textbooks used in Financial Accounting, Managerial Accounting, Finance, and Marketing demonstrates a focus on basically the same set…

Holistic Approach to Learning and Teaching Introductory Object-Oriented Programming

ERIC Educational Resources Information Center

Thota, Neena; Whitfield, Richard

2010-01-01

This article describes a holistic approach to designing an introductory, object-oriented programming course. The design is grounded in constructivism and pedagogy of phenomenography. We use constructive alignment as the framework to align assessments, learning, and teaching with planned learning outcomes. We plan learning and teaching activities,…

Web-Based Learning Design Tool

ERIC Educational Resources Information Center

Bruno, F. B.; Silva, T. L. K.; Silva, R. P.; Teixeira, F. G.

2012-01-01

Purpose: The purpose of this paper is to propose a web-based tool that enables the development and provision of learning designs and its reuse and re-contextualization as generative learning objects, aimed at developing educational materials. Design/methodology/approach: The use of learning objects can facilitate the process of production and…

Learning Activities for the Young Handicapped Child.

ERIC Educational Resources Information Center

Bailey, Don; And Others

Presented is a collection of learning activities for the young handicapped child covering 295 individual learning objectives in six areas of development: gross motor skills, fine motor skills, social skills, self help skills, cognitive skills, and language skills. Provided for each learning activity are the teaching objective, teaching procedures,…

The Usefulness of Learning Objects in Industry Oriented Learning Environments

ERIC Educational Resources Information Center

Fernando, Shantha; Sol, Henk; Dahanayake, Ajantha

2012-01-01

A model is presented to evaluate the usefulness of learning objects for industry oriented learning environments that emphasise training university graduates for job opportunities in a competitive industry oriented economy. Knowledge workers of the industry seek continuous professional development to keep their skills and knowledge up to date. Many…

Layered Learning Design: Towards an Integration of Learning Design and Learning Object Perspectives

ERIC Educational Resources Information Center

Boyle, Tom

2010-01-01

The use of ICT to enhance teaching and learning depends on effective design, which operates at many levels of granularity from the small to the very large. This reflects the range of educational problems from course design down to the design of activities focused on specific learning objectives. For maximum impact these layers of design need to be…

A Rule-Based System for Hybrid Search and Delivery of Learning Objects to Learners

ERIC Educational Resources Information Center

Biletskiy, Yevgen; Baghi, Hamidreza; Steele, Jarrett; Vovk, Ruslan

2012-01-01

Purpose: Presently, searching the internet for learning material relevant to ones own interest continues to be a time-consuming task. Systems that can suggest learning material (learning objects) to a learner would reduce time spent searching for material, and enable the learner to spend more time for actual learning. The purpose of this paper is…

Learning How (and How Not) to Weld: Vocational Learning in Technical Vocational Education

ERIC Educational Resources Information Center

Asplund, Stig-Börje; Kilbrink, Nina

2018-01-01

This article focuses on vocational learning in technical vocational education in upper-secondary school, with a special focus on the object of learning to weld. A concrete teaching situation where the learning object to weld is the focus of the interaction between a vocational teacher and an upper-secondary student was documented by a video camera…

Behavioral Objectives and Student Learning Contracts in the Teaching of Economics

ERIC Educational Resources Information Center

Journal of Economic Education, 1972

1972-01-01

The use of stated behavioral objectives and student learning contracts, planned and prepared by student and teacher, as teaching methods are discussed and an example of a learning contract is presented. (JB)

Learning object correspondences with the observed transport shape measure.

PubMed

Pitiot, Alain; Delingette, Hervé; Toga, Arthur W; Thompson, Paul M

2003-07-01

We propose a learning method which introduces explicit knowledge to the object correspondence problem. Our approach uses an a priori learning set to compute a dense correspondence field between two objects, where the characteristics of the field bear close resemblance to those in the learning set. We introduce a new local shape measure we call the "observed transport measure", whose properties make it particularly amenable to the matching problem. From the values of our measure obtained at every point of the objects to be matched, we compute a distance matrix which embeds the correspondence problem in a highly expressive and redundant construct and facilitates its manipulation. We present two learning strategies that rely on the distance matrix and discuss their applications to the matching of a variety of 1-D, 2-D and 3-D objects, including the corpus callosum and ventricular surfaces.

Infant sensitivity to speaker and language in learning a second label.

PubMed

Bhagwat, Jui; Casasola, Marianella

2014-02-01

Two experiments examined when monolingual, English-learning 19-month-old infants learn a second object label. Two experimenters sat together. One labeled a novel object with one novel label, whereas the other labeled the same object with a different label in either the same or a different language. Infants were tested on their comprehension of each label immediately following its presentation. Infants mapped the first label at above chance levels, but they did so with the second label only when requested by the speaker who provided it (Experiment 1) or when the second experimenter labeled the object in a different language (Experiment 2). These results show that 19-month-olds learn second object labels but do not readily generalize them across speakers of the same language. The results highlight how speaker and language spoken guide infants' acceptance of second labels, supporting sociopragmatic views of word learning. Copyright © 2013 Elsevier Inc. All rights reserved.

The Development of Invariant Object Recognition Requires Visual Experience with Temporally Smooth Objects

ERIC Educational Resources Information Center

Wood, Justin N.; Wood, Samantha M. W.

2018-01-01

How do newborns learn to recognize objects? According to temporal learning models in computational neuroscience, the brain constructs object representations by extracting smoothly changing features from the environment. To date, however, it is unknown whether newborns depend on smoothly changing features to build invariant object representations.…

Teachers' Concepts of Spatial Scale: An international comparison

NASA Astrophysics Data System (ADS)

Jones, M. Gail; Paechter, Manuela; Yen, Chiung-Fen; Gardner, Grant; Taylor, Amy; Tretter, Thomas

2013-09-01

Metric scale is an important concept taught as part of science curricula across different countries. This study explored metric and relative (body-length) scale concepts of inservice (N = 92) and preservice (N = 134) teachers from Austria, and Taiwan, and their concepts were compared with those of teachers from the USA. Participants completed three assessments: the Scale Anchoring Objects (SAO), Scale of Objects Questionnaire (SOQ), and a subsample of participants were interviewed with the Learning Scale Interview. A Rasch analysis was conducted with the SAO and SOQ and results showed that the Rasch model held for these assessments, indicating that there is an underlying common dimension to understanding scale. Further analyses showed that accuracy of knowledge of scale measured by the SAO and SOQ was not related to professional experience. There were significant differences in teachers' accuracy of scale concepts by nationality. This was true for both metric and body-length SAO assessments. Post hoc comparisons showed that the Austrian and Taiwanese participants were significantly more accurate than the US sample on the SAO and SOQ. The Austrian participants scored significantly higher than the US and the Taiwanese participants. The results of the interviews showed that the Taiwanese experienced teacher participants were more likely to report learning size and scale through in-school experiences than the Austrian or the US participants. US teachers reported learning size and scale most often through participating in hobbies and sports, Taiwanese teachers reported learning scale through sports and reading, and Austrian teachers most often noted that they learned about scale through travel.

A Neural-Dynamic Architecture for Concurrent Estimation of Object Pose and Identity

PubMed Central

Lomp, Oliver; Faubel, Christian; Schöner, Gregor

2017-01-01

Handling objects or interacting with a human user about objects on a shared tabletop requires that objects be identified after learning from a small number of views and that object pose be estimated. We present a neurally inspired architecture that learns object instances by storing features extracted from a single view of each object. Input features are color and edge histograms from a localized area that is updated during processing. The system finds the best-matching view for the object in a novel input image while concurrently estimating the object’s pose, aligning the learned view with current input. The system is based on neural dynamics, computationally operating in real time, and can handle dynamic scenes directly off live video input. In a scenario with 30 everyday objects, the system achieves recognition rates of 87.2% from a single training view for each object, while also estimating pose quite precisely. We further demonstrate that the system can track moving objects, and that it can segment the visual array, selecting and recognizing one object while suppressing input from another known object in the immediate vicinity. Evaluation on the COIL-100 dataset, in which objects are depicted from different viewing angles, revealed recognition rates of 91.1% on the first 30 objects, each learned from four training views. PMID:28503145

Use of SMART Learning Objectives to Introduce Continuing Professional Development Into the Pharmacy Curriculum

PubMed Central

Khandoobhai, Anand; Leadon, Kim

2012-01-01

Objective. To determine whether a 2-year continuing professional development (CPD) training program improved first-year (P1) and second-year (P2) pharmacy students’ ability to write SMART (specific, measurable, achievable, relevant, and timed) learning objectives. Design. First-year students completed live or online CPD training, including creating portfolios and writing SMART objectives prior to their summer introductory pharmacy practice experience (IPPE). In year 2, P1 and P2 students were included. SMART learning objectives were graded and analyzed. Assessment. On several objectives, the 2011 P1 students (n = 130) scored higher than did the P2 cohort (n = 105). In 2011, P2 students outscored their own performance in 2010. In 2011, P1 students who had been trained in online modules performed the same as did live-session trainees with respect to SMART objectives. Conclusion. With focused online or live training, students are capable of incorporating principles of CPD by writing SMART learning objectives. PMID:22611277

Towards an Object-Oriented Model for the Design and Development of Learning Objects

ERIC Educational Resources Information Center

Chrysostomou, Chrysostomos; Papadopoulos, George

2008-01-01

This work introduces the concept of an Object-Oriented Learning Object (OOLO) that is developed in a manner similar to the one that software objects are developed through Object-Oriented Software Engineering (OO SWE) techniques. In order to make the application of the OOLO feasible and efficient, an OOLO model needs to be developed based on…

Knowledge Transfer in Health Care Through Digitally Collecting Learning Experiences - Results of Witra Care.

PubMed

Behrends, Marianne; Kupka, Thomas; Schmeer, Regina; Meyenburg-Altwarg, Iris; Marschollek, Michael

2016-01-01

The goal of the project Witra Care was to investigate how far the use of mobile technology is suitable to collect experience-based knowledge of nurses. Nine new employees and seven experienced nurses received for six weeks a mobile phone or a tablet pc with a mobile application that allowed them to collect learning object as pictures, videos, audio files or notes. In Witra Care the nurses created 303 learning objects. They have found the collecting of learning experiences was helpful for their learning processes. The learning objects demonstrate various aspects of daily routines in nursing. The results of Witra Care show that the documentation of learning experiences with mobile devices helps to gather information about the practical knowledge in the daily work of nurses, identifies individual learning needs of the employees and supports them in their personal learning processes.

The effects of short-term and long-term learning on the responses of lateral intraparietal neurons to visually presented objects

PubMed Central

Sigurdardottir, Heida M.; Sheinberg, David L.

2015-01-01

The lateral intraparietal area (LIP) of the dorsal visual stream is thought to play an important role in visually directed orienting, or the guidance of where to look and pay attention. LIP can also respond selectively to differently shaped objects. We sought to understand how and to what extent short-term and long-term experience with visual orienting can determine the nature of responses of LIP neurons to objects of different shapes. We taught monkeys to arbitrarily associate centrally presented objects of various shapes with orienting either toward or away from a preferred peripheral spatial location of a neuron. For some objects the training lasted for less than a single day, while for other objects the training lasted for several months. We found that neural responses to visual objects are affected both by such short-term and long-term experience, but that the length of the learning period determines exactly how this neural plasticity manifests itself. Short-term learning over the course of a single training session affects neural responses to objects, but these effects are only seen relatively late after visual onset; at this time, the neural responses to newly learned objects start to resemble those of familiar over-learned objects that share their meaning or arbitrary association. Long-term learning, on the other hand, affects the earliest and apparently bottom-up responses to visual objects. These responses tend to be greater for objects that have repeatedly been associated with looking toward, rather than away from, LIP neurons’ preferred spatial locations. Responses to objects can nonetheless be distinct even though the objects have both been similarly acted on in the past and will lead to the same orienting behavior in the future. Our results therefore also indicate that a complete experience-driven override of LIP object responses is difficult or impossible. PMID:25633647

Cortical Dynamics of Contextually Cued Attentive Visual Learning and Search: Spatial and Object Evidence Accumulation

ERIC Educational Resources Information Center

Huang, Tsung-Ren; Grossberg, Stephen

2010-01-01

How do humans use target-predictive contextual information to facilitate visual search? How are consistently paired scenic objects and positions learned and used to more efficiently guide search in familiar scenes? For example, humans can learn that a certain combination of objects may define a context for a kitchen and trigger a more efficient…

Word Learning and Attention Allocation Based on Word Class and Category Knowledge

ERIC Educational Resources Information Center

Hupp, Julie M.

2015-01-01

Attention allocation in word learning may vary developmentally based on the novelty of the object. It has been suggested that children differentially learn verbs based on the novelty of the agent, but adults do not because they automatically infer the object's category and thus treat it like a familiar object. The current research examined…

The Effects of Discipline on the Application of Learning Object Metadata in UK Higher Education: The Case of the Jorum Repository

ERIC Educational Resources Information Center

Balatsoukas, Panos; O'Brien, Ann; Morris, Anne

2011-01-01

Introduction: This paper reports on the findings of a study investigating the potential effects of discipline (sciences and engineering versus humanities and social sciences) on the application of the Institute of Electrical and Electronic Engineers learning object metadata elements for the description of learning objects in the Jorum learning…

An Analysis on Usage Preferences of Learning Objects and Learning Object Repositories among Pre-Service Teachers

ERIC Educational Resources Information Center

Yeni, Sabiha; Ozdener, Nesrin

2014-01-01

The purpose of the study is to investigate how pre-service teachers benefit from learning objects repositories while preparing course content. Qualitative and quantitative data collection methods were used in a mixed methods approach. This study was carried out with 74 teachers from the Faculty of Education. In the first phase of the study,…

Cognitive Task Analysis of Experts in Designing Multimedia Learning Object Guideline (M-LOG)

ERIC Educational Resources Information Center

Razak, Rafiza Abdul; Palanisamy, Punithavathy

2013-01-01

The purpose of this study was to design and develop a set of guidelines for multimedia learning objects to inform instructional designers (IDs) about the procedures involved in the process of content analysis. This study was motivated by the absence of standardized procedures in the beginning phase of the multimedia learning object design which is…

Research on Daily Objects Detection Based on Deep Neural Network

NASA Astrophysics Data System (ADS)

Ding, Sheng; Zhao, Kun

2018-03-01

With the rapid development of deep learning, great breakthroughs have been made in the field of object detection. In this article, the deep learning algorithm is applied to the detection of daily objects, and some progress has been made in this direction. Compared with traditional object detection methods, the daily objects detection method based on deep learning is faster and more accurate. The main research work of this article: 1. collect a small data set of daily objects; 2. in the TensorFlow framework to build different models of object detection, and use this data set training model; 3. the training process and effect of the model are improved by fine-tuning the model parameters.

Representing and Learning Complex Object Interactions

PubMed Central

Zhou, Yilun; Konidaris, George

2017-01-01

We present a framework for representing scenarios with complex object interactions, in which a robot cannot directly interact with the object it wishes to control, but must instead do so via intermediate objects. For example, a robot learning to drive a car can only indirectly change its pose, by rotating the steering wheel. We formalize such complex interactions as chains of Markov decision processes and show how they can be learned and used for control. We describe two systems in which a robot uses learning from demonstration to achieve indirect control: playing a computer game, and using a hot water dispenser to heat a cup of water. PMID:28593181

Cognitive domains in the dog: independence of working memory from object learning, selective attention, and motor learning.

PubMed

Zanghi, Brian M; Araujo, Joseph; Milgram, Norton W

2015-05-01

Cognition in dogs, like in humans, is not a unitary process. Some functions, such as simple discrimination learning, are relatively insensitive to age; others, such as visuospatial learning can provide behavioral biomarkers of age. The present experiment sought to further establish the relationship between various cognitive domains, namely visuospatial memory, object discrimination learning (ODL), and selective attention (SA). In addition, we also set up a task to assess motor learning (ML). Thirty-six beagles (9-16 years) performed a variable delay non-matching to position (vDNMP) task using two objects with 20- and 90-s delay and were divided into three groups based on a combined score (HMP = 88-93 % accuracy [N = 12]; MMP = 79-86 % accuracy [N = 12]; LMP = 61-78 % accuracy [N = 12]). Variable object oddity task was used to measure ODL (correct or incorrect object) and SA (0-3 incorrect distractor objects with same [SA-same] or different [SA-diff] correct object as ODL). ML involved reaching various distances (0-15 cm). Age did not differ between memory groups (mean 11.6 years). ODL (ANOVA P = 0.43), or SA-same and SA-different (ANOVA P = 0.96), performance did not differ between the three vDNMP groups, although mean errors during ODL was numerically higher for LMP dogs. Errors increased (P < 0.001) for all dogs with increasing number of distractor objects during both SA tasks. vDNMP groups remained different (ANOVA P < 0.001) when re-tested with vDNMP task 42 days later. Maximum ML distance did not differ between vDNMP groups (ANOVA P = 0.96). Impaired short-term memory performance in aged dogs does not appear to predict performance of cognitive domains associated with object learning, SA, or maximum ML distance.

Development of learning objectives for neurology in a veterinary curriculum: part I: undergraduates.

PubMed

Lin, Yu-Wei; Volk, Holger A; Penderis, Jacques; Tipold, Andrea; Ehlers, Jan P

2015-01-13

With an increasing caseload of veterinary neurology patients in first opinion practice, there is a requirement to establish relevant learning objectives for veterinary neurology encompassing knowledge, skills and attitudes for veterinary undergraduate students in Europe. With help of experts in veterinary neurology from the European College of Veterinary Neurology (ECVN) and the European Society of Veterinary Neurology (ESVN) a survey of veterinary neurologic learning objectives using a modified Delphi method was conducted. The first phase comprised the development of a draft job description and learning objectives by a working group established by the ECVN. In the second phase, a quantitative questionnaire (multiple choice, Likert scale and free text) covering 140 learning objectives and subdivided into 8 categories was sent to 341 ESVN and ECVN members and a return rate of 62% (n = 213/341) was achieved. Of these 140 learning objectives ECVN Diplomates and ESVN members considered 42 (30%) objectives as not necessary for standard clinical veterinary neurology training, 94 (67%) were graded to be learned at a beginner level and 4 (3%) at an advanced level. The following objectives were interpreted as the most important day one skills: interpret laboratory tests, perform a neurological examination and establish a neuroanatomical localization. In this survey the three most important diseases of the central nervous system included epilepsy, intervertebral disc disease and inflammatory diseases. The three most important diseases of the peripheral nervous system included polyradiculoneuritis, myasthenia gravis and toxic neuropathies. The results of this study should help to reform the veterinary curriculum regarding neurology and may reduce the phenomenon of "Neurophobia".

Effectiveness of brain-based learning and animated cartoons for enhancing healthy habits among school children in Khon Kaen, Thailand.

PubMed

Banchonhattakit, Pannee; Duangsong, Rujira; Muangsom, Niramon; Kamsong, Theppamon; Phangwan, Krittiya

2015-03-01

The objective of this study was to investigate the effectiveness of brain-based learning (BBL) and animated cartoons on video compact discs (VCDs) in enhancing the healthy habits of school children. A representative sample of 1085 school children in the first through the third grades at 16 schools was selected by multistage random sampling. Knowledge of healthy habits and self-reported adoption of practices were assessed by a questionnaire. BBL and VCD, either combined or as single-intervention techniques, led to improved knowledge and practice of healthy behavior, whereas conventional teaching did not. As a single-intervention technique, BBL on its own led to a greater improvement in healthy practices than VCD, but the addition of BBL to VCD made no difference, and there was no difference between BBL and VCD in terms of improvements in knowledge. In conclusion, both BBL and VCD are effective, but VCD requires fewer resources. Recommendations are made for further research. © 2012 APJPH.

Free energy computations by minimization of Kullback-Leibler divergence: An efficient adaptive biasing potential method for sparse representations

NASA Astrophysics Data System (ADS)

Bilionis, I.; Koutsourelakis, P. S.

2012-05-01

The present paper proposes an adaptive biasing potential technique for the computation of free energy landscapes. It is motivated by statistical learning arguments and unifies the tasks of biasing the molecular dynamics to escape free energy wells and estimating the free energy function, under the same objective of minimizing the Kullback-Leibler divergence between appropriately selected densities. It offers rigorous convergence diagnostics even though history dependent, non-Markovian dynamics are employed. It makes use of a greedy optimization scheme in order to obtain sparse representations of the free energy function which can be particularly useful in multidimensional cases. It employs embarrassingly parallelizable sampling schemes that are based on adaptive Sequential Monte Carlo and can be readily coupled with legacy molecular dynamics simulators. The sequential nature of the learning and sampling scheme enables the efficient calculation of free energy functions parametrized by the temperature. The characteristics and capabilities of the proposed method are demonstrated in three numerical examples.

Instructional Learning Objects in the Digital Classroom: Effectively Measuring Impact on Student Success

ERIC Educational Resources Information Center

Contrino, Jacline L.

2016-01-01

Demonstrating library impact on student success is critical for all academic libraries today. This article discusses how the library of a large online university serving non-traditional students evaluated how customized point-of-need learning objects (LOs) embedded in the learning management system impacted student learning. Using a comprehensive…

The Challenge of Content Creation to Facilitate Personalized E-Learning Experiences

ERIC Educational Resources Information Center

Turker, Ali; Gorgun, Ilhami; Conlan, Owen

2006-01-01

The runtime creation of pedagogically coherent learning content for an individual learner's needs and preferences is a considerable challenge. By selecting and combining appropriate learning assets into a new learning object such needs and preferences may be accounted for. However, to assure coherence, these objects should be consumed within…

Learning by Creating and Exchanging Objects: The SCY Experience

ERIC Educational Resources Information Center

De Jong, Ton; Van Joolingen, Wouter R.; Giemza, Adam; Girault, Isabelle; Hoppe, Ulrich; Kindermann, Jorg; Kluge, Anders; Lazonder, Ard W.; Vold, Vibeke; Weinberger, Armin; Weinbrenner, Stefan; Wichmann, Astrid; Anjewierden, Anjo; Bodin, Marjolaine; Bollen, Lars; D'Ham, Cedric; Dolonen, Jan; Engler, Jan; Geraedts, Caspar; Grosskreutz, Henrik; Hovardas, Tasos; Julien, Rachel; Lechner, Judith; Ludvigsen, Sten; Matteman, Yuri; Meistadt, Oyvind; Naess, Bjorge; Ney, Muriel; Pedaste, Margus; Perritano, Anthony; Rinket, Marieke; Von Schlanbusch, Henrik; Sarapuu, Tago; Schulz, Florian; Sikken, Jakob; Slotta, Jim; Toussaint, Jeremy; Verkade, Alex; Wajeman, Claire; Wasson, Barbara; Zacharia, Zacharias C.; Van Der Zanden, Martine

2010-01-01

Science Created by You (SCY) is a project on learning in science and technology domains. SCY uses a pedagogical approach that centres around products, called "emerging learning objects" (ELOs) that are created by students. Students work individually and collaboratively in SCY-Lab (the general SCY learning environment) on "missions" that are guided…

Providing Author-Defined State Data Storage to Learning Objects

ERIC Educational Resources Information Center

Kassahun, Ayalew; Beulens, Adrie; Hartog, Rob

2006-01-01

Two major trends in eLearning are the shift from presentational towards activating learning objects and the shift from proprietary towards SCORM conformant delivery systems. In a large program on the design, development and use of digital learning material for food and biotechnology in higher education, a large amount of experience has been gained…

The Role of Professional Objects in Technology-Enhanced Learning Environments in Higher Education

ERIC Educational Resources Information Center

Zitter, Ilya; de Bruijn, Elly; Simons, Robert-Jan; ten Cate, Olle

2012-01-01

We study project-based, technology-enhanced learning environments in higher education, which should produce, by means of specific mechanisms, learning outcomes in terms of transferable knowledge and learning-, thinking-, collaboration- and regulation-skills. Our focus is on the role of objects from professional practice serving as boundary objects…

Greater loss of object than spatial mnemonic discrimination in aged adults.

PubMed

Reagh, Zachariah M; Ho, Huy D; Leal, Stephanie L; Noche, Jessica A; Chun, Amanda; Murray, Elizabeth A; Yassa, Michael A

2016-04-01

Previous studies across species have established that the aging process adversely affects certain memory-related brain regions earlier than others. Behavioral tasks targeted at the function of vulnerable regions can provide noninvasive methods for assessing the integrity of particular components of memory throughout the lifespan. The present study modified a previous task designed to separately but concurrently test detailed memory for object identity and spatial location. Memory for objects or items is thought to rely on perirhinal and lateral entorhinal cortices, among the first targets of Alzheimer's related neurodegeneration. In line with prior work, we split an aged adult sample into "impaired" and "unimpaired" groups on the basis of a standardized word-learning task. The "impaired" group showed widespread difficulty with memory discrimination, whereas the "unimpaired" group showed difficulty with object, but not spatial memory discrimination. These findings support the hypothesized greater age-related impacts on memory for objects or items in older adults, perhaps even with healthy aging. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Learning of Rule Ensembles for Multiple Attribute Ranking Problems

NASA Astrophysics Data System (ADS)

Dembczyński, Krzysztof; Kotłowski, Wojciech; Słowiński, Roman; Szeląg, Marcin

In this paper, we consider the multiple attribute ranking problem from a Machine Learning perspective. We propose two approaches to statistical learning of an ensemble of decision rules from decision examples provided by the Decision Maker in terms of pairwise comparisons of some objects. The first approach consists in learning a preference function defining a binary preference relation for a pair of objects. The result of application of this function on all pairs of objects to be ranked is then exploited using the Net Flow Score procedure, giving a linear ranking of objects. The second approach consists in learning a utility function for single objects. The utility function also gives a linear ranking of objects. In both approaches, the learning is based on the boosting technique. The presented approaches to Preference Learning share good properties of the decision rule preference model and have good performance in the massive-data learning problems. As Preference Learning and Multiple Attribute Decision Aiding share many concepts and methodological issues, in the introduction, we review some aspects bridging these two fields. To illustrate the two approaches proposed in this paper, we solve with them a toy example concerning the ranking of a set of cars evaluated by multiple attributes. Then, we perform a large data experiment on real data sets. The first data set concerns credit rating. Since recent research in the field of Preference Learning is motivated by the increasing role of modeling preferences in recommender systems and information retrieval, we chose two other massive data sets from this area - one comes from movie recommender system MovieLens, and the other concerns ranking of text documents from 20 Newsgroups data set.

Social pediatrics: weaving horizontal and vertical threads through pediatric residency.

PubMed

van den Heuvel, Meta; Martimianakis, Maria Athina Tina; Levy, Rebecca; Atkinson, Adelle; Ford-Jones, Elizabeth; Shouldice, Michelle

2017-01-13

Social pediatrics teaches pediatric residents how to understand disease within their patients' social, environmental and political contexts. It's an essential component of pediatric residency training; however there is very little literature that addresses how such a broad-ranging topic can be taught effectively. The aim of this study was to determine and characterize social pediatric education in our pediatric residency training in order to identify strengths and gaps. A social pediatrics curriculum map was developed, attending to 3 different dimensions: (1) the intended curriculum as prescribed by the Objectives of Training for Pediatrics of the Royal College of Physicians and Surgeons of Canada (RCPSC), (2) the formal curriculum defined by rotation-specific learning objectives, and (3) the informal/hidden curriculum as reflected in resident and teacher experiences and perceptions. Forty-one social pediatric learning objectives were extracted from the RCPSC Objectives of Training for Pediatrics, most were listed in the Medical Expert (51%) and Health Advocate competencies (24%). Almost all RCPSC social pediatric learning objectives were identified in more than one rotation and/or seminar. Adolescent Medicine (29.2%), Pediatric Ambulatory Medicine (26.2%) and Developmental Pediatrics (25%) listed the highest proportion of social pediatric learning objectives. Four (10%) RCPSC social pediatric objectives were not explicitly named within learning objectives of the formal curriculum. The informal curriculum revealed that both teachers and residents viewed social pediatrics as integral to all clinical encounters. Perceived barriers to teaching and learning of social pediatrics included time constraints, particularly in a tertiary care environment, and the value of social pediatrics relative to medical expert knowledge. Despite the lack of an explicit thematic presentation of social pediatric learning objectives by the Royal College and residency training program, social pediatric topics are integrated, taught and learned throughout the entire curriculum. Special attention needs to be given to the hidden curriculum and system barriers that may impede social pediatric education.

Embodied attention and word learning by toddlers

PubMed Central

Yu, Chen; Smith, Linda B.

2013-01-01

Many theories of early word learning begin with the uncertainty inherent to learning a word from its co-occurrence with a visual scene. However, the relevant visual scene for infant word learning is neither from the adult theorist’s view nor the mature partner’s view, but is rather from the learner’s personal view. Here we show that when 18-month old infants interacted with objects in play with their parents, they created moments in which a single object was visually dominant. If parents named the object during these moments of bottom-up selectivity, later forced-choice tests showed that infants learned the name, but did not when naming occurred during a less visually selective moment. The momentary visual input for parents and toddlers was captured via head cameras placed low on each participant’s forehead as parents played with and named objects for their infant. Frame-by-frame analyses of the head camera images at and around naming moments were conducted to determine the visual properties at input that were associated with learning. The analyses indicated that learning occurred when bottom-up visual information was clean and uncluttered. The sensory-motor behaviors of infants and parents were also analyzed to determine how their actions on the objects may have created these optimal visual moments for learning. The results are discussed with respect to early word learning, embodied attention, and the social role of parents in early word learning. PMID:22878116

A way toward analyzing high-content bioimage data by means of semantic annotation and visual data mining

NASA Astrophysics Data System (ADS)

Herold, Julia; Abouna, Sylvie; Zhou, Luxian; Pelengaris, Stella; Epstein, David B. A.; Khan, Michael; Nattkemper, Tim W.

2009-02-01

In the last years, bioimaging has turned from qualitative measurements towards a high-throughput and highcontent modality, providing multiple variables for each biological sample analyzed. We present a system which combines machine learning based semantic image annotation and visual data mining to analyze such new multivariate bioimage data. Machine learning is employed for automatic semantic annotation of regions of interest. The annotation is the prerequisite for a biological object-oriented exploration of the feature space derived from the image variables. With the aid of visual data mining, the obtained data can be explored simultaneously in the image as well as in the feature domain. Especially when little is known of the underlying data, for example in the case of exploring the effects of a drug treatment, visual data mining can greatly aid the process of data evaluation. We demonstrate how our system is used for image evaluation to obtain information relevant to diabetes study and screening of new anti-diabetes treatments. Cells of the Islet of Langerhans and whole pancreas in pancreas tissue samples are annotated and object specific molecular features are extracted from aligned multichannel fluorescence images. These are interactively evaluated for cell type classification in order to determine the cell number and mass. Only few parameters need to be specified which makes it usable also for non computer experts and allows for high-throughput analysis.

Concept mapping learning strategy to enhance students' mathematical connection ability

NASA Astrophysics Data System (ADS)

Hafiz, M.; Kadir, Fatra, Maifalinda

2017-05-01

The concept mapping learning strategy in teaching and learning mathematics has been investigated by numerous researchers. However, there are still less researchers who have scrutinized about the roles of map concept which is connected to the mathematical connection ability. Being well understood on map concept, it may help students to have ability to correlate one concept to other concept in order that the student can solve mathematical problems faced. The objective of this research was to describe the student's mathematical connection ability and to analyze the effect of using concept mapping learning strategy to the students' mathematical connection ability. This research was conducted at senior high school in Jakarta. The method used a quasi-experimental with randomized control group design with the total number was 72 students as the sample. Data obtained through using test in the post-test after giving the treatment. The results of the research are: 1) Students' mathematical connection ability has reached the good enough level category; 2) Students' mathematical connection ability who had taught with concept mapping learning strategy is higher than who had taught with conventional learning strategy. Based on the results above, it can be concluded that concept mapping learning strategycould enhance the students' mathematical connection ability, especially in trigonometry.

Who Reaps the Benefits of Social Change? Exploration and Its Socioecological Boundaries.

PubMed

Lechner, Clemens M; Obschonka, Martin; Silbereisen, Rainer K

2017-04-01

We investigated the interplay between the personality trait exploration and objective socioecological conditions in shaping individual differences in the experience of two individual-level benefits of current social change: new lifestyle options, which arise from the societal trend toward individualization, and new learning opportunities, which accrue from the societal trend toward lifelong learning. We hypothesized that people with higher trait exploration experience a greater increase in lifestyle options and learning opportunities--but more so in social ecologies in which individualization and lifelong learning are stronger, thus offering greater latitude for exploring the benefits of these trends. We employed structural equation modeling in two parallel adult samples from Germany (N = 2,448) and Poland (N = 2,571), using regional divorce rates as a proxy for individualization and Internet domain registration rates as a proxy for lifelong learning. Higher exploration was related to a greater perceived increase in lifestyle options and in learning opportunities over the past 5 years. These associations were stronger in regions in which the trends toward individualization and lifelong learning, respectively, were more prominent. Individuals higher in exploration are better equipped to reap the benefits of current social change--but the effects of exploration are bounded by the conditions in the social ecology. © 2015 Wiley Periodicals, Inc.

Interidentity amnesia for neutral, episodic information in dissociative identity disorder.

PubMed

Huntjens, Rafaële J C; Postma, Albert; Peters, Madelon L; Woertman, Liesbeth; van der Hart, Onno

2003-05-01

Interidentity amnesia is considered a hallmark of dissociative identity disorder (DID) in clinical practice. In this study, objective methods of testing episodic memory transfer between identities were used. Tests of both recall (interference paradigm) and recognition were used. A sample of 31 DID patients was included. Additionally, 50 control subjects participated, half functioning as normal controls and the other half simulating interidentity amnesia. Twenty-one patients subjectively reported complete one-way amnesia for the learning episode. However, objectively, neither recall nor recognition scores of patients were different from those of normal controls. It is suggested that clinical models of amnesia in DID may be specified to exclude episodic memory impairments for emotionally neutral material.

Learning Experience as Transaction: A Framework for Instructional Design

ERIC Educational Resources Information Center

Parrish, Patrick E.; Wilson, Brent G.; Dunlap, Joanna C.

2011-01-01

This article presents a framework for understanding learning experience as an object for instructional design--as an object for design as well as research and understanding. Compared to traditional behavioral objectives or discrete cognitive skills, the object of experience is more holistic, requiring simultaneous attention to cognition, behavior,…

Category learning increases discriminability of relevant object dimensions in visual cortex.

PubMed

Folstein, Jonathan R; Palmeri, Thomas J; Gauthier, Isabel

2013-04-01

Learning to categorize objects can transform how they are perceived, causing relevant perceptual dimensions predictive of object category to become enhanced. For example, an expert mycologist might become attuned to species-specific patterns of spacing between mushroom gills but learn to ignore cap textures attributable to varying environmental conditions. These selective changes in perception can persist beyond the act of categorizing objects and influence our ability to discriminate between them. Using functional magnetic resonance imaging adaptation, we demonstrate that such category-specific perceptual enhancements are associated with changes in the neural discriminability of object representations in visual cortex. Regions within the anterior fusiform gyrus became more sensitive to small variations in shape that were relevant during prior category learning. In addition, extrastriate occipital areas showed heightened sensitivity to small variations in shape that spanned the category boundary. Visual representations in cortex, just like our perception, are sensitive to an object's history of categorization.

Mutual interference between statistical summary perception and statistical learning.

PubMed

Zhao, Jiaying; Ngo, Nhi; McKendrick, Ryan; Turk-Browne, Nicholas B

2011-09-01

The visual system is an efficient statistician, extracting statistical summaries over sets of objects (statistical summary perception) and statistical regularities among individual objects (statistical learning). Although these two kinds of statistical processing have been studied extensively in isolation, their relationship is not yet understood. We first examined how statistical summary perception influences statistical learning by manipulating the task that participants performed over sets of objects containing statistical regularities (Experiment 1). Participants who performed a summary task showed no statistical learning of the regularities, whereas those who performed control tasks showed robust learning. We then examined how statistical learning influences statistical summary perception by manipulating whether the sets being summarized contained regularities (Experiment 2) and whether such regularities had already been learned (Experiment 3). The accuracy of summary judgments improved when regularities were removed and when learning had occurred in advance. In sum, calculating summary statistics impeded statistical learning, and extracting statistical regularities impeded statistical summary perception. This mutual interference suggests that statistical summary perception and statistical learning are fundamentally related.

A fast learning method for large scale and multi-class samples of SVM

NASA Astrophysics Data System (ADS)

Fan, Yu; Guo, Huiming

2017-06-01

A multi-class classification SVM(Support Vector Machine) fast learning method based on binary tree is presented to solve its low learning efficiency when SVM processing large scale multi-class samples. This paper adopts bottom-up method to set up binary tree hierarchy structure, according to achieved hierarchy structure, sub-classifier learns from corresponding samples of each node. During the learning, several class clusters are generated after the first clustering of the training samples. Firstly, central points are extracted from those class clusters which just have one type of samples. For those which have two types of samples, cluster numbers of their positive and negative samples are set respectively according to their mixture degree, secondary clustering undertaken afterwards, after which, central points are extracted from achieved sub-class clusters. By learning from the reduced samples formed by the integration of extracted central points above, sub-classifiers are obtained. Simulation experiment shows that, this fast learning method, which is based on multi-level clustering, can guarantee higher classification accuracy, greatly reduce sample numbers and effectively improve learning efficiency.

How category learning affects object representations: Not all morphspaces stretch alike

PubMed Central

Folstein, Jonathan R.; Gauthier, Isabel; Palmeri, Thomas J.

2012-01-01

How does learning to categorize objects affect how we visually perceive them? Behavioral, neurophysiological, and neuroimaging studies have tested the degree to which category learning influences object representations, with conflicting results. Some studies find that objects become more visually discriminable along dimensions relevant to previously learned categories, while others find no such effect. One critical factor we explore here lies in the structure of the morphspaces used in different studies. Studies finding no increase in discriminability often use “blended” morphspaces, with morphparents lying at corners of the space. By contrast, studies finding increases in discriminability use “factorial” morphspaces, defined by separate morphlines forming axes of the space. Using the same four morphparents, we created both factorial and blended morphspaces matched in pairwise discriminability. Category learning caused a selective increase in discriminability along the relevant dimension of the factorial space, but not in the blended space, and led to the creation of functional dimensions in the factorial space, but not in the blended space. These findings demonstrate that not all morphspaces stretch alike: Only some morphspaces support enhanced discriminability to relevant object dimensions following category learning. Our results have important implications for interpreting neuroimaging studies reporting little or no effect of category learning on object representations in the visual system: Those studies may have been limited by their use of blended morphspaces. PMID:22746950

Perceptual Learning of Object Shape

PubMed Central

Golcu, Doruk; Gilbert, Charles D.

2009-01-01

Recognition of objects is accomplished through the use of cues that depend on internal representations of familiar shapes. We used a paradigm of perceptual learning during visual search to explore what features human observers use to identify objects. Human subjects were trained to search for a target object embedded in an array of distractors, until their performance improved from near-chance levels to over 80% of trials in an object specific manner. We determined the role of specific object components in the recognition of the object as a whole by measuring the transfer of learning from the trained object to other objects sharing components with it. Depending on the geometric relationship of the trained object with untrained objects, transfer to untrained objects was observed. Novel objects that shared a component with the trained object were identified at much higher levels than those that did not, and this could be used as an indicator of which features of the object were important for recognition. Training on an object also transferred to the components of the object when these components were embedded in an array of distractors of similar complexity. These results suggest that objects are not represented in a holistic manner during learning, but that their individual components are encoded. Transfer between objects was not complete, and occurred for more than one component, regardless of how well they distinguish the object from distractors. This suggests that a joint involvement of multiple components was necessary for full performance. PMID:19864574

Case-Based Learning in Athletic Training

ERIC Educational Resources Information Center

Berry, David C.

2013-01-01

The National Athletic Trainers' Association (NATA) Executive Committee for Education has emphasized the need for proper recognition and management of orthopaedic and general medical conditions through their support of numerous learning objectives and the clinical integrated proficiencies. These learning objectives and integrated clinical…

Real-world visual statistics and infants' first-learned object names.

PubMed

Clerkin, Elizabeth M; Hart, Elizabeth; Rehg, James M; Yu, Chen; Smith, Linda B

2017-01-05

We offer a new solution to the unsolved problem of how infants break into word learning based on the visual statistics of everyday infant-perspective scenes. Images from head camera video captured by 8 1/2 to 10 1/2 month-old infants at 147 at-home mealtime events were analysed for the objects in view. The images were found to be highly cluttered with many different objects in view. However, the frequency distribution of object categories was extremely right skewed such that a very small set of objects was pervasively present-a fact that may substantially reduce the problem of referential ambiguity. The statistical structure of objects in these infant egocentric scenes differs markedly from that in the training sets used in computational models and in experiments on statistical word-referent learning. Therefore, the results also indicate a need to re-examine current explanations of how infants break into word learning.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).

Maintenance and Exchange of Learning Objects in a Web Services Based e-Learning System

ERIC Educational Resources Information Center

Vossen, Gottfried; Westerkamp, Peter

2004-01-01

"Web services" enable partners to exploit applications via the Internet. Individual services can be composed to build new and more complex ones with additional and more comprehensive functionality. In this paper, we apply the Web service paradigm to electronic learning, and show how to exchange and maintain learning objects is a…

An Ontological Representation of Learning Objects and Learning Designs as Codified Knowledge

ERIC Educational Resources Information Center

Sanchez-Alonso, Salvador; Frosch-Wilke, Dirk

2005-01-01

Purpose: The aim of this paper is discussing about the similarities between the life cycle of knowledge management and the processes in which learning objects are created, evaluated and used. Design/methodology/approach: The paper describes LO and learning designs and depicts their integration into the knowledge life cycle (KLC) of the KMCI,…

Knowledge Enriched Learning by Converging Knowledge Object & Learning Object

ERIC Educational Resources Information Center

Sabitha, Sai; Mehrotra, Deepti; Bansal, Abhay

2015-01-01

The most important dimension of learning is the content, and a Learning Management System (LMS) suffices this to a certain extent. The present day LMS are designed to primarily address issues like ease of use, search, content and performance. Many surveys had been conducted to identify the essential features required for the improvement of LMS,…

Analyzing the Quality of Students Interaction in a Distance Learning Object-Oriented Programming Discipline

ERIC Educational Resources Information Center

Carvalho, Elizabeth Simão

2015-01-01

Teaching object-oriented programming to students in an in-classroom environment demands well-thought didactic and pedagogical strategies in order to guarantee a good level of apprenticeship. To teach it on a completely distance learning environment (e-learning) imposes possibly other strategies, besides those that the e-learning model of Open…

An Evaluation of Learning Objects in Singapore Primary Education: A Case Study Approach

ERIC Educational Resources Information Center

Grace, Tay Pei Lyn; Suan, Ng Peck; Wanzhen, Liaw

2008-01-01

Purpose: The purpose of this paper is to evaluate the usability and interface design of e-learning portal developed for primary schools in Singapore. Design/methodology/approach: Using Singapore-based learning EDvantage (LEAD) portal as a case study, this paper reviews and analyses the usability and usefulness of embedded learning objects (LOs)…

A Workflow for Learning Objects Lifecycle and Reuse: Towards Evaluating Cost Effective Reuse

ERIC Educational Resources Information Center

Sampson, Demetrios G.; Zervas, Panagiotis

2011-01-01

Over the last decade Learning Objects (LOs) have gained a lot of attention as a common format for developing and sharing digital educational content in the field of technology-enhanced learning. The main advantage of LOs is considered to be their potential for component-based reuse in different learning settings supporting different learning…

A Methodology for Developing Learning Objects for Web Course Delivery

ERIC Educational Resources Information Center

Stauffer, Karen; Lin, Fuhua; Koole, Marguerite

2008-01-01

This article presents a methodology for developing learning objects for web-based courses using the IMS Learning Design (IMS LD) specification. We first investigated the IMS LD specification, determining how to use it with online courses and the student delivery model, and then applied this to a Unit of Learning (UOL) for online computer science…

Developing a Learning Object Metadata Application Profile Based on LOM Suitable for the Australian Higher Education Context

ERIC Educational Resources Information Center

Agostinho, Shirley; Bennett, Sue; Lockyer, Lori; Harper, Barry

2004-01-01

This paper reports recent work in developing of structures and processes that support university teachers and instructional designers incorporating learning objects into higher education focused learning designs. The aim of the project is to develop a framework to guide the design and implementation of high quality learning experiences. This…

Memory for Object Locations: Priority Effect and Sex Differences in Associative Spatial Learning

ERIC Educational Resources Information Center

Cinan, Sevtap; Atalay, Deniz; Sisman, Simge; Basbug, Gokce; Dervent-Ozbek, Sevinc; Teoman, Dalga D.; Karagoz, Ayca; Karadeniz, A. Yezdan; Beykurt, Sinem; Suleyman, Hediye; Memis, H. Ozge; Yurtsever, Ozgur D.

2007-01-01

This paper reports two experiments conducted to examine priority effects and sex differences in object location memory. A new task of paired position-learning was designed, based on the A-B A-C paradigm, which was used in paired word learning. There were three different paired position-learning conditions: (1) positions of several different…

Learning Objects and Learning Content Management Systems in Engineering Education: Implications of New Trends

ERIC Educational Resources Information Center

Sjoer, Ellen; Dopper, Sofia

2006-01-01

Learning objects and learning content management systems are considered to be "the next wave in engineering education". The results of experiments with these new trends in ICT in engineering education are described in this paper. The prospects were examined and the concepts of reusability of content for teachers and for personalized…

Optimal Contrast: Competition between Two Referents Improves Word Learning

ERIC Educational Resources Information Center

Zosh, Jennifer M.; Brinster, Meredith; Halberda, Justin

2013-01-01

Does making an inference lead to better learning than being instructed directly? Two experiments evaluated preschoolers' ability to learn new words, comparing their memory for words learned via inference or instruction. On Inference trials, one familiar and one novel object was presented and children were asked to "Point at the [object name (i.e.,…

eLearning: a review of Internet-based continuing medical education.

PubMed

Wutoh, Rita; Boren, Suzanne Austin; Balas, E Andrew

2004-01-01

The objective was to review the effect of Internet-based continuing medical education (CME) interventions on physician performance and health care outcomes. Data sources included searches of MEDLINE (1966 to January 2004), CINAHL (1982 to December 2003), ACP Journal Club (1991 to July/August 2003), and the Cochrane Database of Systematic Reviews (third quarter, 2003). Studies were included in the analyses if they were randomized controlled trials of Internet-based education in which participants were practicing health care professionals or health professionals in training. CME interventions were categorized according to the nature of the intervention, sample size, and other information about educational content and format. Sixteen studies met the eligibility criteria. Six studies generated positive changes in participant knowledge over traditional formats; only three studies showed a positive change in practices. The remainder of the studies showed no difference in knowledge levels between Internet-based interventions and traditional formats for CME. The results demonstrate that Internet-based CME programs are just as effective in imparting knowledge as traditional formats of CME. Little is known as to whether these positive changes in knowledge are translated into changes in practice. Subjective reports of change in physician behavior should be confirmed through chart review or other objective measures. Additional studies need to be performed to assess how long these new learned behaviors could be sustained. eLearning will continue to evolve as new innovations and more interactive modes are incorporated into learning.

Learning viewpoint invariant perceptual representations from cluttered images.

PubMed

Spratling, Michael W

2005-05-01

In order to perform object recognition, it is necessary to form perceptual representations that are sufficiently specific to distinguish between objects, but that are also sufficiently flexible to generalize across changes in location, rotation, and scale. A standard method for learning perceptual representations that are invariant to viewpoint is to form temporal associations across image sequences showing object transformations. However, this method requires that individual stimuli be presented in isolation and is therefore unlikely to succeed in real-world applications where multiple objects can co-occur in the visual input. This paper proposes a simple modification to the learning method that can overcome this limitation and results in more robust learning of invariant representations.

Sampling Assumptions Affect Use of Indirect Negative Evidence in Language Learning.

PubMed

Hsu, Anne; Griffiths, Thomas L

2016-01-01

A classic debate in cognitive science revolves around understanding how children learn complex linguistic patterns, such as restrictions on verb alternations and contractions, without negative evidence. Recently, probabilistic models of language learning have been applied to this problem, framing it as a statistical inference from a random sample of sentences. These probabilistic models predict that learners should be sensitive to the way in which sentences are sampled. There are two main types of sampling assumptions that can operate in language learning: strong and weak sampling. Strong sampling, as assumed by probabilistic models, assumes the learning input is drawn from a distribution of grammatical samples from the underlying language and aims to learn this distribution. Thus, under strong sampling, the absence of a sentence construction from the input provides evidence that it has low or zero probability of grammaticality. Weak sampling does not make assumptions about the distribution from which the input is drawn, and thus the absence of a construction from the input as not used as evidence of its ungrammaticality. We demonstrate in a series of artificial language learning experiments that adults can produce behavior consistent with both sets of sampling assumptions, depending on how the learning problem is presented. These results suggest that people use information about the way in which linguistic input is sampled to guide their learning.

Sampling Assumptions Affect Use of Indirect Negative Evidence in Language Learning

PubMed Central

2016-01-01

A classic debate in cognitive science revolves around understanding how children learn complex linguistic patterns, such as restrictions on verb alternations and contractions, without negative evidence. Recently, probabilistic models of language learning have been applied to this problem, framing it as a statistical inference from a random sample of sentences. These probabilistic models predict that learners should be sensitive to the way in which sentences are sampled. There are two main types of sampling assumptions that can operate in language learning: strong and weak sampling. Strong sampling, as assumed by probabilistic models, assumes the learning input is drawn from a distribution of grammatical samples from the underlying language and aims to learn this distribution. Thus, under strong sampling, the absence of a sentence construction from the input provides evidence that it has low or zero probability of grammaticality. Weak sampling does not make assumptions about the distribution from which the input is drawn, and thus the absence of a construction from the input as not used as evidence of its ungrammaticality. We demonstrate in a series of artificial language learning experiments that adults can produce behavior consistent with both sets of sampling assumptions, depending on how the learning problem is presented. These results suggest that people use information about the way in which linguistic input is sampled to guide their learning. PMID:27310576

Communication in Health Professions: A European consensus on inter- and multi-professional learning objectives in German.

PubMed

Bachmann, Cadja; Kiessling, Claudia; Härtl, Anja; Haak, Rainer

2016-01-01

Communication is object of increasing attention in the health professions. Teaching communication competencies should already begin in undergraduate education or pre-registration training. The aim of this project was to translate the Health Professions Core Communication Curriculum (HPCCC), an English catalogue of learning objectives, into German to make its content widely accessible in the German-speaking countries. This catalogue lists 61 educational objectives and was agreed on by 121 international communication experts. A European reference framework for inter- and multi-professional curriculum development for communication in the health professions in German-speaking countries should be provided. The German version of the HPCCC was drafted by six academics and went through multiple revisions until consensus was reached. The learning objectives were paired with appropriate teaching and assessment tools drawn from the database of the teaching Committee of the European Association for Communication Health Care (tEACH). The HPCCC learning objectives are now available in German and can be applied for curriculum planning and development in the different German-speaking health professions, the educational objectives can also be used for inter-professional purposes. Examples for teaching methods and assessment tools are given for using and implementing the objectives. The German version of the HPCCC with learning objectives for communication in health professions can contribute significantly to inter- and multi-professional curriculum development in the health care professions in the German-speaking countries. Examples for teaching methods and assessment tools from the materials compiled by tEACH supplement the curricular content and provide suggestions for practical implementation of the learning objectives in teaching and assessment. The relevance of the German HPCCC to the processes of curriculum development for the various health professions and inter-professional approaches should be the subject of further evaluation.

Statistical Mechanics of Node-perturbation Learning with Noisy Baseline

NASA Astrophysics Data System (ADS)

Hara, Kazuyuki; Katahira, Kentaro; Okada, Masato

2017-02-01

Node-perturbation learning is a type of statistical gradient descent algorithm that can be applied to problems where the objective function is not explicitly formulated, including reinforcement learning. It estimates the gradient of an objective function by using the change in the object function in response to the perturbation. The value of the objective function for an unperturbed output is called a baseline. Cho et al. proposed node-perturbation learning with a noisy baseline. In this paper, we report on building the statistical mechanics of Cho's model and on deriving coupled differential equations of order parameters that depict learning dynamics. We also show how to derive the generalization error by solving the differential equations of order parameters. On the basis of the results, we show that Cho's results are also apply in general cases and show some general performances of Cho's model.

Type of Maternal Object Motion during Synchronous Naming Predicts Preverbal Infants' Learning of Word-Object Relations

ERIC Educational Resources Information Center

Matatyaho, Dalit J.; Gogate, Lakshmi J.

2008-01-01

Mothers' use of specific types of object motion in synchrony with object naming was examined, along with infants' joint attention to the mother and object, as a predictor of word learning. During a semistructured 3-min play episode, mothers (N = 24) taught the names of 2 toy objects to their preverbal 6- to 8-month-old infants. The episodes were…

Large-scale weakly supervised object localization via latent category learning.

PubMed

Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

2015-04-01

Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.

Learning from picture books: Infants' use of naming information.

PubMed

Khu, Melanie; Graham, Susan A; Ganea, Patricia A

2014-01-01

The present study investigated whether naming would facilitate infants' transfer of information from picture books to the real world. Eighteen- and 21-month-olds learned a novel label for a novel object depicted in a picture book. Infants then saw a second picture book in which an adult demonstrated how to elicit the object's non-obvious property. Accompanying narration described the pictures using the object's newly learnt label. Infants were subsequently tested with the real-world object depicted in the book, as well as a different-color exemplar. Infants' performance on the test trials was compared with that of infants in a no label condition. When presented with the exact object depicted in the picture book, 21-month-olds were significantly more likely to attempt to elicit the object's non-obvious property than were 18-month-olds. Learning the object's label before learning about the object's hidden property did not improve 18-month-olds' performance. At 21-months, the number of infants in the label condition who attempted to elicit the real-world object's non-obvious property was greater than would be predicted by chance, but the number of infants in the no label condition was not. Neither age group nor label condition predicted test performance for the different-color exemplar. The findings are discussed in relation to infants' learning and transfer from picture books.

The effects of short-term and long-term learning on the responses of lateral intraparietal neurons to visually presented objects.

PubMed

Sigurdardottir, Heida M; Sheinberg, David L

2015-07-01

The lateral intraparietal area (LIP) is thought to play an important role in the guidance of where to look and pay attention. LIP can also respond selectively to differently shaped objects. We sought to understand to what extent short-term and long-term experience with visual orienting determines the responses of LIP to objects of different shapes. We taught monkeys to arbitrarily associate centrally presented objects of various shapes with orienting either toward or away from a preferred spatial location of a neuron. The training could last for less than a single day or for several months. We found that neural responses to objects are affected by such experience, but that the length of the learning period determines how this neural plasticity manifests. Short-term learning affects neural responses to objects, but these effects are only seen relatively late after visual onset; at this time, the responses to newly learned objects resemble those of familiar objects that share their meaning or arbitrary association. Long-term learning affects the earliest bottom-up responses to visual objects. These responses tend to be greater for objects that have been associated with looking toward, rather than away from, LIP neurons' preferred spatial locations. Responses to objects can nonetheless be distinct, although they have been similarly acted on in the past and will lead to the same orienting behavior in the future. Our results therefore indicate that a complete experience-driven override of LIP object responses may be difficult or impossible. We relate these results to behavioral work on visual attention.

SortNet: learning to rank by a neural preference function.

PubMed

Rigutini, Leonardo; Papini, Tiziano; Maggini, Marco; Scarselli, Franco

2011-09-01

Relevance ranking consists in sorting a set of objects with respect to a given criterion. However, in personalized retrieval systems, the relevance criteria may usually vary among different users and may not be predefined. In this case, ranking algorithms that adapt their behavior from users' feedbacks must be devised. Two main approaches are proposed in the literature for learning to rank: the use of a scoring function, learned by examples, that evaluates a feature-based representation of each object yielding an absolute relevance score, a pairwise approach, where a preference function is learned to determine the object that has to be ranked first in a given pair. In this paper, we present a preference learning method for learning to rank. A neural network, the comparative neural network (CmpNN), is trained from examples to approximate the comparison function for a pair of objects. The CmpNN adopts a particular architecture designed to implement the symmetries naturally present in a preference function. The learned preference function can be embedded as the comparator into a classical sorting algorithm to provide a global ranking of a set of objects. To improve the ranking performances, an active-learning procedure is devised, that aims at selecting the most informative patterns in the training set. The proposed algorithm is evaluated on the LETOR dataset showing promising performances in comparison with other state-of-the-art algorithms.

Active Learning to Overcome Sample Selection Bias: Application to Photometric Variable Star Classification

NASA Astrophysics Data System (ADS)

Richards, Joseph W.; Starr, Dan L.; Brink, Henrik; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; James, J. Berian; Long, James P.; Rice, John

2012-01-01

Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.

Naming and Categorization in Young Children: IV: Listener Behavior Training and Transfer of Function

PubMed Central

Horne, Pauline J; Hughes, J. Carl; Lowe, C. Fergus

2006-01-01

Following pretraining with everyday objects, 14 children aged from 1 to 4 years were trained, for each of three pairs of different arbitrary wooden shapes (Set 1), to select one stimulus in response to the spoken word /zog/, and the other to /vek/. When given a test for the corresponding tacts (“zog” and “vek”), 10 children passed, showing that they had learned common names for the stimuli, and 4 failed. All children were trained to clap to one stimulus of Pair 1 and wave to the other. All those who named showed either transfer of the novel functions to the remaining two pairs of stimuli in Test 1, or novel function comprehension for all three pairs in Test 2, or both. Three of these children next participated in, and passed, category match-to-sample tests. In contrast, all 4 children who had learned only listener behavior failed both the category transfer and category match-to-sample tests. When 3 of them were next trained to name the stimuli, they passed the category transfer and (for the 2 subjects tested) category match-to-sample tests. Three children were next trained on the common listener relations with another set of arbitrary stimuli (Set 2); all succeeded on the tact and category tests with the Set 2 stimuli. Taken together with the findings from the other studies in the series, the present experiment shows that (a) common listener training also establishes the corresponding names in some but not all children, and (b) only children who learn common names categorize; all those who learn only listener behavior fail. This is good evidence in support of the naming account of categorization. PMID:16673828

Attribute conjunctions and the part configuration advantage in object category learning.

PubMed

Saiki, J; Hummel, J E

1996-07-01

Five experiments demonstrated that in object category learning people are particularly sensitive to conjunctions of part shapes and relative locations. Participants learned categories defined by a part's shape and color (part-color conjunctions) or by a part's shape and its location relative to another part (part-location conjunctions). The statistical properties of the categories were identical across these conditions, as were the salience of color and relative location. Participants were better at classifying objects defined by part-location conjunctions than objects defined by part-color conjunctions. Subsequent experiments revealed that this effect was not due to the specific color manipulation or the role of location per se. These results suggest that the shape bias in object categorization is at least partly due to sensitivity to part-location conjunctions and suggest a new processing constraint on category learning.

Development and Implementation of a Learning Object Repository for French Teaching and Learning: Issues and Promises

ERIC Educational Resources Information Center

Caws, Catherine

2008-01-01

This paper discusses issues surrounding the development of a learning object repository (FLORE) for teaching and learning French at the postsecondary level. An evaluation based on qualitative and quantitative data was set up in order to better assess how second-language (L2) students in French perceived the integration of this new repository into…

Perseverative Interference with Object-in-Place Scene Learning in Rhesus Monkeys with Bilateral Ablation of Ventrolateral Prefrontal Cortex

ERIC Educational Resources Information Center

Baxter, Mark G.; Browning, Philip G. F.; Mitchell, Anna S.

2008-01-01

Surgical disconnection of the frontal cortex and inferotemporal cortex severely impairs many aspects of visual learning and memory, including learning of new object-in-place scene memory problems, a monkey model of episodic memory. As part of a study of specialization within prefrontal cortex in visual learning and memory, we tested monkeys with…

Lexical Stress and Phonetic Processing in Word Learning in 20- to 24-Month-Old English-Learning Children

ERIC Educational Resources Information Center

Floccia, Caroline; Nazzi, Thierry; Austin, Keith; Arreckx, Frederique; Goslin, Jeremy

2011-01-01

To investigate the interaction between segmental and supra-segmental stress-related information in early word learning, two experiments were conducted with 20- to 24-month-old English-learning children. In an adaptation of the object categorization study designed by Nazzi and Gopnik (2001), children were presented with pairs of novel objects whose…

Everyday objects of learning about health and healing and implications for science education

NASA Astrophysics Data System (ADS)

Gitari, Wanja

2006-02-01

The role of science education in rural development is of great interest to science educators. In this study I investigated how residents of rural Kirumi, Kenya, approach health and healing, through discussions and semistructured and in-depth interviews with 150 residents, 3 local herbalists, and 2 medical researchers over a period of 6 months. I constructed objects of learning by looking for similarities and differences within interpretive themes. Objects of learning found comprise four types of personal learning tools, three types of relational learning tools, three genres of moral obligation, and five genres of knowledge guarding. Findings show that rural people use (among other learning tools) inner sensing to engage thought processes that lead to health and healing knowledge. The sociocultural context is also an important component in learning. Inner sensing and residents' sociocultural context are not presently emphasized in Kenyan science teaching. I discuss the potential use of rural objects of learning in school science, with specific reference to a health topic in the Kenyan science curriculum. In addition, the findings add to the literature in the Science, Technology, Society, and Environment (STSE) approach to science education, and cross-cultural and global science education.

Online Feature Transformation Learning for Cross-Domain Object Category Recognition.

PubMed

Zhang, Xuesong; Zhuang, Yan; Wang, Wei; Pedrycz, Witold

2017-06-09

In this paper, we introduce a new research problem termed online feature transformation learning in the context of multiclass object category recognition. The learning of a feature transformation is viewed as learning a global similarity metric function in an online manner. We first consider the problem of online learning a feature transformation matrix expressed in the original feature space and propose an online passive aggressive feature transformation algorithm. Then these original features are mapped to kernel space and an online single kernel feature transformation (OSKFT) algorithm is developed to learn a nonlinear feature transformation. Based on the OSKFT and the existing Hedge algorithm, a novel online multiple kernel feature transformation algorithm is also proposed, which can further improve the performance of online feature transformation learning in large-scale application. The classifier is trained with k nearest neighbor algorithm together with the learned similarity metric function. Finally, we experimentally examined the effect of setting different parameter values in the proposed algorithms and evaluate the model performance on several multiclass object recognition data sets. The experimental results demonstrate the validity and good performance of our methods on cross-domain and multiclass object recognition application.

Cooperative inference: Features, objects, and collections.

PubMed

Searcy, Sophia Ray; Shafto, Patrick

2016-10-01

Cooperation plays a central role in theories of development, learning, cultural evolution, and education. We argue that existing models of learning from cooperative informants have fundamental limitations that prevent them from explaining how cooperation benefits learning. First, existing models are shown to be computationally intractable, suggesting that they cannot apply to realistic learning problems. Second, existing models assume a priori agreement about which concepts are favored in learning, which leads to a conundrum: Learning fails without precise agreement on bias yet there is no single rational choice. We introduce cooperative inference, a novel framework for cooperation in concept learning, which resolves these limitations. Cooperative inference generalizes the notion of cooperation used in previous models from omission of labeled objects to the omission values of features, labels for objects, and labels for collections of objects. The result is an approach that is computationally tractable, does not require a priori agreement about biases, applies to both Boolean and first-order concepts, and begins to approximate the richness of real-world concept learning problems. We conclude by discussing relations to and implications for existing theories of cognition, cognitive development, and cultural evolution. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Carpentry. Student Learning Guide.

ERIC Educational Resources Information Center

Palm Beach County Board of Public Instruction, West Palm Beach, FL.

This student learning guide contains 17 modules for completing a course in carpentry. It is designed especially for use in secondary schools in Palm Beach County, Florida. Each module covers one task, and consists of a purpose, performance objective, enabling objectives, learning activities keyed to resources, information sheets, student…

Virtual Museum Learning

ERIC Educational Resources Information Center

Prosser, Dominic; Eddisford, Susan

2004-01-01

This paper examines children's and adults' attitudes to virtual representations of museum objects. Drawing on empirical research data gained from two web-based digital learning environments. The paper explores the characteristics of on-line learning activities that move children from a sense of wonder into meaningful engagement with objects and…

Masonry. Student Learning Guide.

ERIC Educational Resources Information Center

Palm Beach County Board of Public Instruction, West Palm Beach, FL.

This student learning guide contains nine modules for completing a course in masonry. It is designed especially for use in secondary schools in Palm Beach County, Florida. Each module covers one task, and consists of a purpose, performance objective, enabling objectives, learning activities keyed to resources, information sheets, student…

Redesign and Evaluation of a Patient Assessment Course

PubMed Central

Sobieraj, Diana M.; McCaffrey, Desmond; Lee, Jennifer J.

2009-01-01

Objectives To redesign a patient assessment course using a structured instructional design process and evaluate student learning. Design Course coordinators collaborated with an instructional design and development expert to incorporate new pedagogical approaches (eg, Web-based self-tests), create new learning activities (eg, peer collaboration on worksheets, SOAP note writing), and develop grading rubrics. Assessment Formative and summative surveys were administered for student self-assessment and course evaluation. Seventy-six students (78%) completed the summative survey. The mean course grade was 91.8% ± 3.6%, with more than 75% of students reporting achievement of primary course learning objectives. All of the additional learning activities helped students meet the learning objectives with the exception of the written drug information response. Conclusion The use of a structured instructional design process to redesign a patient assessment course was successful in creating a curriculum that succeeded in teaching students the specified learning objectives. Other colleges and schools are encouraged to collaborate with an instructional design and development expert to improve the pharmacy curriculum. PMID:19960090

Object recognition based on Google's reverse image search and image similarity

NASA Astrophysics Data System (ADS)

Horváth, András.

2015-12-01

Image classification is one of the most challenging tasks in computer vision and a general multiclass classifier could solve many different tasks in image processing. Classification is usually done by shallow learning for predefined objects, which is a difficult task and very different from human vision, which is based on continuous learning of object classes and one requires years to learn a large taxonomy of objects which are not disjunct nor independent. In this paper I present a system based on Google image similarity algorithm and Google image database, which can classify a large set of different objects in a human like manner, identifying related classes and taxonomies.

Attention to Maternal Multimodal Naming by 6- to 8-Month-Old Infants and Learning of Word-Object Relations

ERIC Educational Resources Information Center

Gogate, Lakshmi J.; Bolzani, Laura H.; Betancourt, Eugene A.

2006-01-01

We examined whether mothers' use of temporal synchrony between spoken words and moving objects, and infants' attention to object naming, predict infants' learning of word-object relations. Following 5 min of free play, 24 mothers taught their 6- to 8-month-olds the names of 2 toy objects, "Gow" and "Chi," during a 3-min play…

Writing-to-Learn

PubMed Central

Balachandran, Shreedevi; Venkatesaperumal, Ramesh; Clara, Jothi; Shukri, Raghda K.

2014-01-01

Objectives: The objectives of this study were to assess the attitude of Omani nursing students towards writing-to-learn (WTL) and its relationship to demographic variables, self-efficacy and the writing process Methods: A cross-sectional design was used to evaluate attitudes towards WTL by Sultan Qaboos University nursing students. A convenience sample of 106 students was used and data collected between October 2009 and March 2010. A modified version of the WTL attitude scale developed by Dobie and Poirrier was used to collect the data. Descriptive and inferential statistics were used for analysis. Results: Senior and junior students had more positive attitudes to WTL than mid-level students who tended to have negative attitudes towards writing. Although 52.8% students had negative attitudes towards the writing process, the median was higher for attitudes to the writing process compared to the median for self-efficacy. There was a positive correlation between self-efficacy and writing process scores. Conclusion: Overall, students had negative attitudes towards WTL. Attitudes are learnt or formed through previous experiences. The incorporation of WTL strategies into teaching can transform students’ negative attitudes towards writing into positive ones. PMID:24516740

Objects of Desire.

ERIC Educational Resources Information Center

Zielinski, Dave

2000-01-01

Describes learning objects, also known as granules, chunks, or information nuggets, and likens them to help screens. Discusses concerns about how they can go wrong: (1) faulty pretest questions; (2) missing links in the learning object chain; (3) poor frames of reference; and (4) lack of customization. (JOW)

Curriculum development for a national cardiotocography education program: a Delphi survey to obtain consensus on learning objectives.

PubMed

Thellesen, Line; Hedegaard, Morten; Bergholt, Thomas; Colov, Nina P; Hoegh, Stinne; Sorensen, Jette L

2015-08-01

To define learning objectives for a national cardiotocography (CTG) education program based on expert consensus. A three-round Delphi survey. One midwife and one obstetrician from each maternity unit in Denmark were appointed based on CTG teaching experience and clinical obstetric experience. Following national and international guidelines, the research group determined six topics as important when using CTG: fetal physiology, equipment, indication, interpretation, clinical management, and communication/responsibility. In the first Delphi round, participants listed one to five learning objectives within the predefined topics. Responses were analyzed by a directed approach to content analysis. Phrasing was modified in accordance with Bloom's taxonomy. In the second and third Delphi rounds, participants rated each objective on a five-point relevance scale. Consensus was predefined as objectives with a mean rating value of ≥ 3. A prioritized list of CTG learning objectives. A total of 42 midwives and obstetricians from 21 maternity units were invited to participate, of whom 26 completed all three Delphi rounds, representing 18 maternity units. The final prioritized list included 40 objectives. The highest ranked objectives emphasized CTG interpretation and clinical management. The lowest ranked objectives emphasized fetal physiology. Mean ratings of relevance ranged from 3.15 to 5.00. National consensus on CTG learning objectives was achieved using the Delphi methodology. This was an initial step in developing a valid CTG education program. A prioritized list of objectives will clarify which topics to emphasize in a CTG education program. © 2015 Nordic Federation of Societies of Obstetrics and Gynecology.

Optimized Graph Learning Using Partial Tags and Multiple Features for Image and Video Annotation.

PubMed

Song, Jingkuan; Gao, Lianli; Nie, Feiping; Shen, Heng Tao; Yan, Yan; Sebe, Nicu

2016-11-01

In multimedia annotation, due to the time constraints and the tediousness of manual tagging, it is quite common to utilize both tagged and untagged data to improve the performance of supervised learning when only limited tagged training data are available. This is often done by adding a geometry-based regularization term in the objective function of a supervised learning model. In this case, a similarity graph is indispensable to exploit the geometrical relationships among the training data points, and the graph construction scheme essentially determines the performance of these graph-based learning algorithms. However, most of the existing works construct the graph empirically and are usually based on a single feature without using the label information. In this paper, we propose a semi-supervised annotation approach by learning an optimized graph (OGL) from multi-cues (i.e., partial tags and multiple features), which can more accurately embed the relationships among the data points. Since OGL is a transductive method and cannot deal with novel data points, we further extend our model to address the out-of-sample issue. Extensive experiments on image and video annotation show the consistent superiority of OGL over the state-of-the-art methods.

Discovery learning model with geogebra assisted for improvement mathematical visual thinking ability

NASA Astrophysics Data System (ADS)

Juandi, D.; Priatna, N.

2018-05-01

The main goal of this study is to improve the mathematical visual thinking ability of high school student through implementation the Discovery Learning Model with Geogebra Assisted. This objective can be achieved through study used quasi-experimental method, with non-random pretest-posttest control design. The sample subject of this research consist of 62 senior school student grade XI in one of school in Bandung district. The required data will be collected through documentation, observation, written tests, interviews, daily journals, and student worksheets. The results of this study are: 1) Improvement students Mathematical Visual Thinking Ability who obtain learning with applied the Discovery Learning Model with Geogebra assisted is significantly higher than students who obtain conventional learning; 2) There is a difference in the improvement of students’ Mathematical Visual Thinking ability between groups based on prior knowledge mathematical abilities (high, medium, and low) who obtained the treatment. 3) The Mathematical Visual Thinking Ability improvement of the high group is significantly higher than in the medium and low groups. 4) The quality of improvement ability of high and low prior knowledge is moderate category, in while the quality of improvement ability in the high category achieved by student with medium prior knowledge.

Learning and serial effects on verbal memory in mild cognitive impairment.

PubMed

Campos-Magdaleno, María; Díaz-Bóveda, Rosalía; Juncos-Rabadán, Onésimo; Facal, David; Pereiro, Arturo X

2016-01-01

The objective of this study was to examine different patterns of learning and episodic memory in 3 mild cognitive impairment (MCI) groups and a control group by administering the California Verbal Learning Test (CVLT) and using serial position effect as a principal variable. The study sample included 3 groups of patients with MCI (n = 90) divided into single-domain amnestic, multiple-domain amnestic, and multiple-domain nonamnestic MCI and a group of healthy controls (n = 60). We compared the performance of each group on several CVLT measures used in previous research, and we included a new measure that provides specific information about the serial effect. Data showed a similar pattern of learning and memory impairment in both amnestic MCI groups (i.e., no differences between the multiple-domain and single-domain subtypes); the recency effect was significantly higher in both amnestic MCI groups than in all other groups, and the primacy effect was only lower in the multiple-domain amnestic MCI subtype. Verbal learning and memory profiles of patients with amnestic MCI were very similar, independent of the presence of deficits in cognitive domains other than episodic memory. Results are discussed in light of the unitary-store model of memory.

Effects of dorsal hippocampus catecholamine depletion on paired-associates learning and place learning in rats.

PubMed

Roschlau, Corinna; Hauber, Wolfgang

2017-04-14

Growing evidence suggests that the catecholamine (CA) neurotransmitters dopamine and noradrenaline support hippocampus-mediated learning and memory. However, little is known to date about which forms of hippocampus-mediated spatial learning are modulated by CA signaling in the hippocampus. Therefore, in the current study we examined the effects of 6-hydroxydopamine-induced CA depletion in the dorsal hippocampus on two prominent forms of hippocampus-based spatial learning, that is learning of object-location associations (paired-associates learning) as well as learning and choosing actions based on a representation of the context (place learning). Results show that rats with CA depletion of the dorsal hippocampus were able to learn object-location associations in an automated touch screen paired-associates learning (PAL) task. One possibility to explain this negative result is that object-location learning as tested in the touchscreen PAL task seems to require relatively little hippocampal processing. Results further show that in rats with CA depletion of the dorsal hippocampus the use of a response strategy was facilitated in a T-maze spatial learning task. We suspect that impaired hippocampus CA signaling may attenuate hippocampus-based place learning and favor dorsolateral striatum-based response learning. Copyright © 2017 Elsevier B.V. All rights reserved.

A model of blended learning in a preclinical course in prosthetic dentistry.

PubMed

Reissmann, Daniel R; Sierwald, Ira; Berger, Florian; Heydecke, Guido

2015-02-01

The aim of this study was to evaluate the use of blending learning that added online tools to traditional learning methods in a preclinical course in prosthetic dentistry at one dental school in Germany. The e-learning modules were comprised of three main components: fundamental principles, additional information, and learning objective tests. Video recordings of practical demonstrations were prepared and cut into sequences meant to achieve single learning goals. The films were accompanied by background information and, after digital processing, were made available online. Additionally, learning objective tests and learning contents were integrated. Evaluations of 71 of 89 students (response rate: 80%) in the course with the integrated e-learning content were available for the study. Compared with evaluation results of the previous years, a substantial and statistically significant increase in satisfaction with learning content (from 30% and 34% to 86%, p<0.001) and learning effect (from 65% and 63% to 83%, p<0.05) was observed. Satisfaction ratings stayed on a high level in three subsequent courses with the modules. Qualitative evaluation revealed mostly positive responses, with not a single negative comment regarding the blended learning concept. The results showed that the e-learning tool was appreciated by the students and suggest that learning objective tests can be successfully implemented in blended learning.

Debunking the Buzz Words Or Can Hermeneutic Analysis Be Used To Evaluate Pedagogically Based Learning Objects Designed from Constructivist Epistemological Ontologies Defined in XML Metadata?

ERIC Educational Resources Information Center

Stuckey, Bronwyn; Hensman, Jim; Hofmann, Tobias; Dewey, Barbara; Brown, Helen; Cameron, Sonja

Arguably the biggest "buzz word" of the current year has been "learning or knowledge object". To understand the learning object and why it should be such a highly desirable commodity, it is necessary to unpack not only this concept but more importantly revisit some contributing concepts and constructs (more buzz words) that support the building of…

Learning to distinguish similar objects

NASA Astrophysics Data System (ADS)

Seibert, Michael; Waxman, Allen M.; Gove, Alan N.

1995-04-01

This paper describes how the similarities and differences among similar objects can be discovered during learning to facilitate recognition. The application domain is single views of flying model aircraft captured in silhouette by a CCD camera. The approach was motivated by human psychovisual and monkey neurophysiological data. The implementation uses neural net processing mechanisms to build a hierarchy that relates similar objects to superordinate classes, while simultaneously discovering the salient differences between objects within a class. Learning and recognition experiments both with and without the class similarity and difference learning show the effectiveness of the approach on this visual data. To test the approach, the hierarchical approach was compared to a non-hierarchical approach, and was found to improve the average percentage of correctly classified views from 77% to 84%.

Welding. Student Learning Guide.

ERIC Educational Resources Information Center

Palm Beach County Board of Public Instruction, West Palm Beach, FL.

This student learning guide contains 30 modules for completing a course in welding. It is designed especially for use in secondary schools in Palm Beach County, Florida. Each module covers one task, and consists of a purpose, performance objective, enabling objectives, learning activities keyed to resources, information sheets, student self-check…

A computational exploration of complementary learning mechanisms in the primate ventral visual pathway.

PubMed

Spoerer, Courtney J; Eguchi, Akihiro; Stringer, Simon M

2016-02-01

In order to develop transformation invariant representations of objects, the visual system must make use of constraints placed upon object transformation by the environment. For example, objects transform continuously from one point to another in both space and time. These two constraints have been exploited separately in order to develop translation and view invariance in a hierarchical multilayer model of the primate ventral visual pathway in the form of continuous transformation learning and temporal trace learning. We show for the first time that these two learning rules can work cooperatively in the model. Using these two learning rules together can support the development of invariance in cells and help maintain object selectivity when stimuli are presented over a large number of locations or when trained separately over a large number of viewing angles. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Automatic target recognition and detection in infrared imagery under cluttered background

NASA Astrophysics Data System (ADS)

Gundogdu, Erhan; Koç, Aykut; Alatan, A. Aydın.

2017-10-01

Visual object classification has long been studied in visible spectrum by utilizing conventional cameras. Since the labeled images has recently increased in number, it is possible to train deep Convolutional Neural Networks (CNN) with significant amount of parameters. As the infrared (IR) sensor technology has been improved during the last two decades, labeled images extracted from IR sensors have been started to be used for object detection and recognition tasks. We address the problem of infrared object recognition and detection by exploiting 15K images from the real-field with long-wave and mid-wave IR sensors. For feature learning, a stacked denoising autoencoder is trained in this IR dataset. To recognize the objects, the trained stacked denoising autoencoder is fine-tuned according to the binary classification loss of the target object. Once the training is completed, the test samples are propagated over the network, and the probability of the test sample belonging to a class is computed. Moreover, the trained classifier is utilized in a detect-by-classification method, where the classification is performed in a set of candidate object boxes and the maximum confidence score in a particular location is accepted as the score of the detected object. To decrease the computational complexity, the detection step at every frame is avoided by running an efficient correlation filter based tracker. The detection part is performed when the tracker confidence is below a pre-defined threshold. The experiments conducted on the real field images demonstrate that the proposed detection and tracking framework presents satisfactory results for detecting tanks under cluttered background.

A Theory of How Columns in the Neocortex Enable Learning the Structure of the World

PubMed Central

Hawkins, Jeff; Ahmad, Subutai; Cui, Yuwei

2017-01-01

Neocortical regions are organized into columns and layers. Connections between layers run mostly perpendicular to the surface suggesting a columnar functional organization. Some layers have long-range excitatory lateral connections suggesting interactions between columns. Similar patterns of connectivity exist in all regions but their exact role remain a mystery. In this paper, we propose a network model composed of columns and layers that performs robust object learning and recognition. Each column integrates its changing input over time to learn complete predictive models of observed objects. Excitatory lateral connections across columns allow the network to more rapidly infer objects based on the partial knowledge of adjacent columns. Because columns integrate input over time and space, the network learns models of complex objects that extend well beyond the receptive field of individual cells. Our network model introduces a new feature to cortical columns. We propose that a representation of location relative to the object being sensed is calculated within the sub-granular layers of each column. The location signal is provided as an input to the network, where it is combined with sensory data. Our model contains two layers and one or more columns. Simulations show that using Hebbian-like learning rules small single-column networks can learn to recognize hundreds of objects, with each object containing tens of features. Multi-column networks recognize objects with significantly fewer movements of the sensory receptors. Given the ubiquity of columnar and laminar connectivity patterns throughout the neocortex, we propose that columns and regions have more powerful recognition and modeling capabilities than previously assumed. PMID:29118696

"Notice of Violation of IEEE Publication Principles" Multiobjective Reinforcement Learning: A Comprehensive Overview.

PubMed

Liu, Chunming; Xu, Xin; Hu, Dewen

2013-04-29

Reinforcement learning is a powerful mechanism for enabling agents to learn in an unknown environment, and most reinforcement learning algorithms aim to maximize some numerical value, which represents only one long-term objective. However, multiple long-term objectives are exhibited in many real-world decision and control problems; therefore, recently, there has been growing interest in solving multiobjective reinforcement learning (MORL) problems with multiple conflicting objectives. The aim of this paper is to present a comprehensive overview of MORL. In this paper, the basic architecture, research topics, and naive solutions of MORL are introduced at first. Then, several representative MORL approaches and some important directions of recent research are reviewed. The relationships between MORL and other related research are also discussed, which include multiobjective optimization, hierarchical reinforcement learning, and multi-agent reinforcement learning. Finally, research challenges and open problems of MORL techniques are highlighted.

Object Permanence and Relational Words: A Lexical Training Study.

ERIC Educational Resources Information Center

Tomasello, Michael; Farrar, Michael Jeffrey

1986-01-01

Describes a lexical training program developed to teach object, visible movement, and invisible movement words to children at stage 5 (N=7) and stage 6 (N=16) object permanence development. Stage 6 children learned all three types of words equally well, while stage 5 children learned object and visible movement but not invisible movement words.…

Seven Steps You Can Take to Improve Your Objectives. Third Edition.

ERIC Educational Resources Information Center

Alvir, Claire Gelinas

This document gives examples of seven steps a classroom teacher can take to improve both instructional and learning objectives. This improvement is to be measured by increased student learning. The seven steps are as follows: a) write a simple behavioral objective, b) edit, c) revise objective to make it learner centered, d) clarify, e) evaluate…

It's all connected: Pathways in visual object recognition and early noun learning.

PubMed

Smith, Linda B

2013-11-01

A developmental pathway may be defined as the route, or chain of events, through which a new structure or function forms. For many human behaviors, including object name learning and visual object recognition, these pathways are often complex and multicausal and include unexpected dependencies. This article presents three principles of development that suggest the value of a developmental psychology that explicitly seeks to trace these pathways and uses empirical evidence on developmental dependencies among motor development, action on objects, visual object recognition, and object name learning in 12- to 24-month-old infants to make the case. The article concludes with a consideration of the theoretical implications of this approach. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Grounding statistical learning in context: The effects of learning and retrieval contexts on cross-situational word learning.

PubMed

Chen, Chi-Hsin; Yu, Chen

2017-06-01

Natural language environments usually provide structured contexts for learning. This study examined the effects of semantically themed contexts-in both learning and retrieval phases-on statistical word learning. Results from 2 experiments consistently showed that participants had higher performance in semantically themed learning contexts. In contrast, themed retrieval contexts did not affect performance. Our work suggests that word learners are sensitive to statistical regularities not just at the level of individual word-object co-occurrences but also at another level containing a whole network of associations among objects and their properties.

Nursing students' attitudes to biomedical science lectures.

PubMed

Al-Modhefer, A K; Roe, S

To explore what first-year nursing students believe to be the preferred characteristics of common foundation programme biomedical science lecturers, and to investigate whether students prefer active or passive learning. Survey and interview methodologies were used to explore the attitudes of a cohort of first-year nursing students at Queen's University Belfast. Questionnaires were distributed among 300 students. Individuals were asked to select five of a list of 14 criteria that they believed characterised the qualities of an effective lecturer. Informal interviews were carried out with five participants who were randomly selected from the sample to investigate which teaching methods were most beneficial in assisting their learning. Nursing students favoured didactic teaching and found interactivity in lectures intimidating. Students preferred to learn biomedical science passively and depended heavily on their instructors. In response to the survey, the authors propose a set of recommendations to enhance the learning process in large classes. This guidance includes giving clear objectives and requirements to students, encouraging active participation, and sustaining student interest through the use of improved teaching aids and innovative techniques.

[Kolb's learning styles in medical students].

PubMed

Borracci, Raúl A; Arribalzaga, Eduardo B

2015-01-01

The objective of this work was to study the relationship of Kolb's learning styles in academic success or failure in medical students. A prospective cohort study in 116 medical students of a private Argentine university was performed between March 2005 and March 2011. The follow-up included two cut-offs; during 2005-2006 the students' learning styles were determined and five years later, when individuals had to end their career, they were grouped into graduated, delayed or dropped status. At the end of the period, 50% of the students ended successfully, 24.1% abandoned and 25.9% was delayed. Learning styles were assimilator in 60.3% of cases, divergent in 14.7%, accommodator in 6.9%, convergent in 6.0% and undefined in 12.1%. In conclusion, the follow-up during the career demonstrated that convergent or undefined styles had a tendency to abandon the career, while delayed students had a more theoretical and reflexive style than successful individuals. The results observed in convergent students differed from other reports. This difference would be explained by a particular characteristic of the sample or by the teaching and evaluation profile of the university.

Evidence-based practice guidelines for instructing individuals with neurogenic memory impairments: what have we learned in the past 20 years?

PubMed

Ehlhardt, Laurie A; Sohlberg, McKay Moore; Kennedy, Mary; Coelho, Carl; Ylvisaker, Mark; Turkstra, Lyn; Yorkston, Kathryn

2008-06-01

This article examines the instructional research literature pertinent to teaching procedures or information to individuals with acquired memory impairments due to brain injury or related conditions. The purpose is to evaluate the available evidence in order to generate practice guidelines for clinicians working in the field of cognitive rehabilitation. A systematic review of the instructional literature from 1986 to 2006 revealed 51 studies meeting search criteria. Studies were analysed and coded within the following four key domains: Population Sample, Intervention, Study Design, and Treatment Outcomes. Coding included 17 characteristics of the population sample; seven intervention parameters; five study design features; and five treatment outcome parameters. Interventions that were evaluated included systematic instructional techniques such as method of vanishing cues and errorless learning. The majority of the studies reported positive outcomes in favour of systematic instruction. However, issues related to the design and execution of effective instruction lack clarity and require further study. The interaction between the target learning objective and the individual learner profile is not well understood. The evidence review concludes with clinical recommendations based on the instructional literature and a call to clinicians to incorporate these methods into their practice to maximise patient outcomes.

Validation to Portuguese of the Scale of Student Satisfaction and Self-Confidence in Learning1

PubMed Central

Almeida, Rodrigo Guimarães dos Santos; Mazzo, Alessandra; Martins, José Carlos Amado; Baptista, Rui Carlos Negrão; Girão, Fernanda Berchelli; Mendes, Isabel Amélia Costa

2015-01-01

Objective: translate and validate to Portuguese the Scale of Student Satisfaction and Self-Confidence in Learning. Material and Methods: methodological translation and validation study of a research tool. After following all steps of the translation process, for the validation process, the event III Workshop Brazil - Portugal: Care Delivery to Critical Patients was created, promoted by one Brazilian and another Portuguese teaching institution. Results: 103 nurses participated. As to the validity and reliability of the scale, the correlation pattern between the variables, the sampling adequacy test (Kaiser-Meyer-Olkin) and the sphericity test (Bartlett) showed good results. In the exploratory factorial analysis (Varimax), item 9 behaved better in factor 1 (Satisfaction) than in factor 2 (Self-confidence in learning). The internal consistency (Cronbach's alpha) showed coefficients of 0.86 in factor 1 with six items and 0.77 for factor 2 with 07 items. Conclusion: in Portuguese this tool was called: Escala de Satisfação de Estudantes e Autoconfiança na Aprendizagem. The results found good psychometric properties and a good potential use. The sampling size and specificity are limitations of this study, but future studies will contribute to consolidate the validity of the scale and strengthen its potential use. PMID:26625990

The two-week pediatric surgery rotation: is it time wasted?

PubMed

Dutta, S; Wales, P W; Fecteau, A

2004-05-01

With increasing medical school emphasis on generalist training and decreasing enrollment in surgical residency, the authors assessed the adequacy of a 2-week pediatric surgery rotation on meeting the learning and competency objectives outlined in The Canadian Association of Pediatric Surgeons' Self-Directed Evaluation Tool. A prospective survey was conducted of 39 clinical clerks. An anonymous self-assessment scale measuring competency objectives (medical and psychosocial) was administered pre-and postrotation. Also, exposure to pediatric surgical conditions from a list of "essential" and "nonessential" learning objectives was measured. Statistical analysis was performed using paired t test with significance at.05 level. Response rate was 77% and 54% for the competency and learning objectives, respectively. Students reported improvement in medical (P <.00001; 95% CI, 1.30, 1.90) and psychosocial (P =.00036; 95% CI 0.64, 1.28) competency objectives after the rotation. Almost all "essential" learning objectives were met. Overall, students reported an increased awareness of the breadth of pediatric surgical practice (P <.0001; 95% CI 2.06, 3.18). A 2-week rotation in pediatric surgery appears adequate in fulfilling most competency and learning objectives, but discussion is needed about how to best assess student competency, which topics are considered essential, and the long-term effect on recruitment to the profession.

Different Modes of Digital Learning Object Use in School Settings: Do We Design for Individual or Collaborative Learning?

ERIC Educational Resources Information Center

Akpinar, Yavuz

2014-01-01

The aim of the studies reported in this paper is to gain classroom based empirical evidence on the learning effectiveness of learning objects used in two types of study settings: Collaborative and individual. A total of 127 seventh and ninth grade students participated in the experiments. They were assigned into one of the study modes and worked…

Incorporating Learning Objects in a Curriculum Re-Design to Meet Needs of Students with Specific Learning Disabilities in Illinois Agricultural Education Programs

ERIC Educational Resources Information Center

Pense, Seburn L.; Calvin, Jennifer; Watson, Dennis G.; Wakefield, Dexter B.

2012-01-01

A quasi-experimental pilot study of curriculum re-design using Learning Objects (LO) to instruct agricultural education students with Specific Learning Disabilities (SLD) was conducted in five high schools in the federally designated economically distressed area, the Illinois Delta Region. Six LOs were developed based on a unit of instruction in…

LABRADOR: a learning autonomous behavior-based robot for adaptive detection and object retrieval

NASA Astrophysics Data System (ADS)

Yamauchi, Brian; Moseley, Mark; Brookshire, Jonathan

2013-01-01

As part of the TARDEC-funded CANINE (Cooperative Autonomous Navigation in a Networked Environment) Program, iRobot developed LABRADOR (Learning Autonomous Behavior-based Robot for Adaptive Detection and Object Retrieval). LABRADOR was based on the rugged, man-portable, iRobot PackBot unmanned ground vehicle (UGV) equipped with an explosives ordnance disposal (EOD) manipulator arm and a custom gripper. For LABRADOR, we developed a vision-based object learning and recognition system that combined a TLD (track-learn-detect) filter based on object shape features with a color-histogram-based object detector. Our vision system was able to learn in real-time to recognize objects presented to the robot. We also implemented a waypoint navigation system based on fused GPS, IMU (inertial measurement unit), and odometry data. We used this navigation capability to implement autonomous behaviors capable of searching a specified area using a variety of robust coverage strategies - including outward spiral, random bounce, random waypoint, and perimeter following behaviors. While the full system was not integrated in time to compete in the CANINE competition event, we developed useful perception, navigation, and behavior capabilities that may be applied to future autonomous robot systems.

Changing to Concept-Based Curricula: The Process for Nurse Educators

PubMed Central

Baron, Kristy A.

2017-01-01

Background: The complexity of health care today requires nursing graduates to use effective thinking skills. Many nursing programs are revising curricula to include concept-based learning that encourages problem-solving, effective thinking, and the ability to transfer knowledge to a variety of situations—requiring nurse educators to modify their teaching styles and methods to promote student-centered learning. Changing from teacher-centered learning to student-centered learning requires a major shift in thinking and application. Objective: The focus of this qualitative study was to understand the process of changing to concept-based curricula for nurse educators who previously taught in traditional curriculum designs. Methods: The sample included eight educators from two institutions in one Western state using a grounded theory design. Results: The themes that emerged from participants’ experiences consisted of the overarching concept, support for change, and central concept, finding meaning in the change. Finding meaning is supported by three main themes: preparing for the change, teaching in a concept-based curriculum, and understanding the teaching-learning process. Conclusion: Changing to a concept-based curriculum required a major shift in thinking and application. Through support, educators discovered meaning to make the change by constructing authentic learning opportunities that mirrored practice, refining the change process, and reinforcing benefits of teaching. PMID:29399236

Fast and Accurate Learning When Making Discrete Numerical Estimates.

PubMed

Sanborn, Adam N; Beierholm, Ulrik R

2016-04-01

Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates.

Individual differences in the benefits of feedback for learning.

PubMed

Kelley, Christopher M; McLaughlin, Anne Collins

2012-02-01

Research on learning from feedback has produced ambiguous guidelines for feedback design--some have advocated minimal feedback, whereas others have recommended more extensive feedback that highly supported performance. The objective of the current study was to investigate how individual differences in cognitive resources may predict feedback requirements and resolve previous conflicted findings. Cognitive resources were controlled for by comparing samples from populations with known differences, older and younger adults.To control for task demands, a simple rule-based learning task was created in which participants learned to identify fake Windows pop-ups. Pop-ups were divided into two categories--those that required fluid ability to identify and those that could be identified using crystallized intelligence. In general, results showed participants given higher feedback learned more. However, when analyzed by type of task demand, younger adults performed comparably with both levels of feedback for both cues whereas older adults benefited from increased feedbackfor fluid ability cues but from decreased feedback for crystallized ability cues. One explanation for the current findings is feedback requirements are connected to the cognitive abilities of the learner-those with higher abilities for the type of demands imposed by the task are likely to benefit from reduced feedback. We suggest the following considerations for feedback design: Incorporate learner characteristics and task demands when designing learning support via feedback.

Fast and Accurate Learning When Making Discrete Numerical Estimates

PubMed Central

Sanborn, Adam N.; Beierholm, Ulrik R.

2016-01-01

Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates. PMID:27070155

Applying Active Learning to Assertion Classification of Concepts in Clinical Text

PubMed Central

Chen, Yukun; Mani, Subramani; Xu, Hua

2012-01-01

Supervised machine learning methods for clinical natural language processing (NLP) research require a large number of annotated samples, which are very expensive to build because of the involvement of physicians. Active learning, an approach that actively samples from a large pool, provides an alternative solution. Its major goal in classification is to reduce the annotation effort while maintaining the quality of the predictive model. However, few studies have investigated its uses in clinical NLP. This paper reports an application of active learning to a clinical text classification task: to determine the assertion status of clinical concepts. The annotated corpus for the assertion classification task in the 2010 i2b2/VA Clinical NLP Challenge was used in this study. We implemented several existing and newly developed active learning algorithms and assessed their uses. The outcome is reported in the global ALC score, based on the Area under the average Learning Curve of the AUC (Area Under the Curve) score. Results showed that when the same number of annotated samples was used, active learning strategies could generate better classification models (best ALC – 0.7715) than the passive learning method (random sampling) (ALC – 0.7411). Moreover, to achieve the same classification performance, active learning strategies required fewer samples than the random sampling method. For example, to achieve an AUC of 0.79, the random sampling method used 32 samples, while our best active learning algorithm required only 12 samples, a reduction of 62.5% in manual annotation effort. PMID:22127105

A reduction in hippocampal GABAA receptor alpha5 subunits disrupts the memory for location of objects in mice.

PubMed

Prut, L; Prenosil, G; Willadt, S; Vogt, K; Fritschy, J-M; Crestani, F

2010-07-01

The memory for location of objects, which binds information about objects to discrete positions or spatial contexts of occurrence, is a form of episodic memory particularly sensitive to hippocampal damage. Its early decline is symptomatic for elderly dementia. Substances that selectively reduce alpha5-GABA(A) receptor function are currently developed as potential cognition enhancers for Alzheimer's syndrome and other dementia, consistent with genetic studies implicating these receptors that are highly expressed in hippocampus in learning performance. Here we explored the consequences of reduced GABA(A)alpha5-subunit contents, as occurring in alpha5(H105R) knock-in mice, on the memory for location of objects. This required the behavioral characterization of alpha5(H105R) and wild-type animals in various tasks examining learning and memory retrieval strategies for objects, locations, contexts and their combinations. In mutants, decreased amounts of alpha5-subunits and retained long-term potentiation in hippocampus were confirmed. They exhibited hyperactivity with conserved circadian rhythm in familiar actimeters, and normal exploration and emotional reactivity in novel places, allocentric spatial guidance, and motor pattern learning acquisition, inhibition and flexibility in T- and eight-arm mazes. Processing of object, position and context memories and object-guided response learning were spared. Genotype difference in object-in-place memory retrieval and in encoding and response learning strategies for object-location combinations manifested as a bias favoring object-based recognition and guidance strategies over spatial processing of objects in the mutants. These findings identify in alpha5(H105R) mice a behavioral-cognitive phenotype affecting basal locomotion and the memory for location of objects indicative of hippocampal dysfunction resulting from moderately decreased alpha5-subunit contents.

World Culture Areas: Africa [And] U.S.S.R. Grade 6.

ERIC Educational Resources Information Center

Nevens, Margaret; And Others

Two social studies units for sixth grade provide information and learning activities about Africa and Russia. Both units contain lists of concepts to be learned, skills, objectives, learning activities, common misconceptions, vocabulary, maps, objective and essay tests, and bibliographies. The unit on Africa helps students understand the wide…

Commercial Foods and Culinary Arts. Student Learning Guide.

ERIC Educational Resources Information Center

Palm Beach County Board of Public Instruction, West Palm Beach, FL.

This student learning guide contains one module for completing a course in commercial foods and culinary arts. It is designed especially for use in secondary schools in Palm Beach County, Florida. The module covers one task, and consists of a purpose, performance objective, enabling objectives, learning activities keyed to resources, information…

Quantifying the Reuse of Learning Objects

ERIC Educational Resources Information Center

Elliott, Kristine; Sweeney, Kevin

2008-01-01

This paper reports the findings of one case study from a larger project, which aims to quantify the claimed efficiencies of reusing learning objects to develop e-learning resources. The case study describes how an online inquiry project "Diabetes: A waste of energy" was developed by searching for, evaluating, modifying and then…

Diesel Equipment Department. Student Learning Guide.

ERIC Educational Resources Information Center

Palm Beach County Board of Public Instruction, West Palm Beach, FL.

Eleven student learning guides are provided for the duty entitled "completing core curriculum" of the diesel equipment program. Each learning guide concerns one of the tasks that comprise the duty. Introductory materials for each guide include the purpose and performance and enabling objectives. For each enabling objective, these materials are…

Learning Objects, Repositories, Sharing and Reusability

ERIC Educational Resources Information Center

Koppi, Tony; Bogle, Lisa; Bogle, Mike

2005-01-01

The online Learning Resource Catalogue (LRC) Project has been part of an international consortium for several years and currently includes 25 institutions worldwide. The LRC Project has evolved for several pragmatic reasons into an academic network whereby members can identify and share reusable learning objects as well as collaborate in a number…

Machine Shop. Student Learning Guide.

ERIC Educational Resources Information Center

Palm Beach County Board of Public Instruction, West Palm Beach, FL.

This student learning guide contains eight modules for completing a course in machine shop. It is designed especially for use in Palm Beach County, Florida. Each module covers one task, and consists of a purpose, performance objective, enabling objectives, learning activities and resources, information sheets, student self-check with answer key,…

A complete system for head tracking using motion-based particle filter and randomly perturbed active contour

NASA Astrophysics Data System (ADS)

Bouaynaya, N.; Schonfeld, Dan

2005-03-01

Many real world applications in computer and multimedia such as augmented reality and environmental imaging require an elastic accurate contour around a tracked object. In the first part of the paper we introduce a novel tracking algorithm that combines a motion estimation technique with the Bayesian Importance Sampling framework. We use Adaptive Block Matching (ABM) as the motion estimation technique. We construct the proposal density from the estimated motion vector. The resulting algorithm requires a small number of particles for efficient tracking. The tracking is adaptive to different categories of motion even with a poor a priori knowledge of the system dynamics. Particulary off-line learning is not needed. A parametric representation of the object is used for tracking purposes. In the second part of the paper, we refine the tracking output from a parametric sample to an elastic contour around the object. We use a 1D active contour model based on a dynamic programming scheme to refine the output of the tracker. To improve the convergence of the active contour, we perform the optimization over a set of randomly perturbed initial conditions. Our experiments are applied to head tracking. We report promising tracking results in complex environments.

Active learning for semi-supervised clustering based on locally linear propagation reconstruction.

PubMed

Chang, Chin-Chun; Lin, Po-Yi

2015-03-01

The success of semi-supervised clustering relies on the effectiveness of side information. To get effective side information, a new active learner learning pairwise constraints known as must-link and cannot-link constraints is proposed in this paper. Three novel techniques are developed for learning effective pairwise constraints. The first technique is used to identify samples less important to cluster structures. This technique makes use of a kernel version of locally linear embedding for manifold learning. Samples neither important to locally linear propagation reconstructions of other samples nor on flat patches in the learned manifold are regarded as unimportant samples. The second is a novel criterion for query selection. This criterion considers not only the importance of a sample to expanding the space coverage of the learned samples but also the expected number of queries needed to learn the sample. To facilitate semi-supervised clustering, the third technique yields inferred must-links for passing information about flat patches in the learned manifold to semi-supervised clustering algorithms. Experimental results have shown that the learned pairwise constraints can capture the underlying cluster structures and proven the feasibility of the proposed approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Surgical education and training in an outer metropolitan hospital: a qualitative study of surgical trainers and trainees.

PubMed

Nestel, Debra; Harlim, Jennifer; Bryant, Melanie; Rampersad, Rajay; Hunter-Smith, David; Spychal, Bob

2017-08-01

The landscape of surgical training is changing. The anticipated increase in the numbers of surgical trainees and the shift to competency-based surgical training places pressures on an already stretched health service. With these pressures in mind, we explored trainers' and trainees' experiences of surgical training in a less traditional rotation, an outer metropolitan hospital. We considered practice-based learning theories to make meaning of surgical training in this setting, in particular Actor-network theory. We adopted a qualitative approach and purposively sampled surgical trainers and trainees to participate in individual interviews and focus groups respectively. Transcripts were made and thematically analysed. Institutional human research ethics approval was obtained. Four surgical trainers and fourteen trainees participated. Almost without exception, participants' report training needs to be well met. Emergent inter-related themes were: learning as social activity; learning and programmatic factors; learning and physical infrastructure; and, learning and organizational structure. This outer metropolitan hospital is suited to the provision of surgical training with the current rotational system for trainees. The setting offers experiences that enable consolidation of learning providing a rich and varied overall surgical training program. Although relational elements of learning were paramount they occurred within a complex environment. Actor-network theory was used to give meaning to emergent themes acknowledging that actors (both people and objects) and their interactions combine to influence training quality, shifting the focus of responsibility for learning away from individuals to the complex interactions in which they work and learn.

The Convergence of Intelligences

NASA Astrophysics Data System (ADS)

Diederich, Joachim

Minsky (1985) argued an extraterrestrial intelligence may be similar to ours despite very different origins. ``Problem- solving'' offers evolutionary advantages and individuals who are part of a technical civilisation should have this capacity. On earth, the principles of problem-solving are the same for humans, some primates and machines based on Artificial Intelligence (AI) techniques. Intelligent systems use ``goals'' and ``sub-goals'' for problem-solving, with memories and representations of ``objects'' and ``sub-objects'' as well as knowledge of relations such as ``cause'' or ``difference.'' Some of these objects are generic and cannot easily be divided into parts. We must, therefore, assume that these objects and relations are universal, and a general property of intelligence. Minsky's arguments from 1985 are extended here. The last decade has seen the development of a general learning theory (``computational learning theory'' (CLT) or ``statistical learning theory'') which equally applies to humans, animals and machines. It is argued that basic learning laws will also apply to an evolved alien intelligence, and this includes limitations of what can be learned efficiently. An example from CLT is that the general learning problem for neural networks is intractable, i.e. it cannot be solved efficiently for all instances (it is ``NP-complete''). It is the objective of this paper to show that evolved intelligences will be constrained by general learning laws and will use task-decomposition for problem-solving. Since learning and problem-solving are core features of intelligence, it can be said that intelligences converge despite very different origins.

Speckle-learning-based object recognition through scattering media.

PubMed

Ando, Takamasa; Horisaki, Ryoichi; Tanida, Jun

2015-12-28

We experimentally demonstrated object recognition through scattering media based on direct machine learning of a number of speckle intensity images. In the experiments, speckle intensity images of amplitude or phase objects on a spatial light modulator between scattering plates were captured by a camera. We used the support vector machine for binary classification of the captured speckle intensity images of face and non-face data. The experimental results showed that speckles are sufficient for machine learning.

Multi-sensory learning and learning to read.

PubMed

Blomert, Leo; Froyen, Dries

2010-09-01

The basis of literacy acquisition in alphabetic orthographies is the learning of the associations between the letters and the corresponding speech sounds. In spite of this primacy in learning to read, there is only scarce knowledge on how this audiovisual integration process works and which mechanisms are involved. Recent electrophysiological studies of letter-speech sound processing have revealed that normally developing readers take years to automate these associations and dyslexic readers hardly exhibit automation of these associations. It is argued that the reason for this effortful learning may reside in the nature of the audiovisual process that is recruited for the integration of in principle arbitrarily linked elements. It is shown that letter-speech sound integration does not resemble the processes involved in the integration of natural audiovisual objects such as audiovisual speech. The automatic symmetrical recruitment of the assumedly uni-sensory visual and auditory cortices in audiovisual speech integration does not occur for letter and speech sound integration. It is also argued that letter-speech sound integration only partly resembles the integration of arbitrarily linked unfamiliar audiovisual objects. Letter-sound integration and artificial audiovisual objects share the necessity of a narrow time window for integration to occur. However, they differ from these artificial objects, because they constitute an integration of partly familiar elements which acquire meaning through the learning of an orthography. Although letter-speech sound pairs share similarities with audiovisual speech processing as well as with unfamiliar, arbitrary objects, it seems that letter-speech sound pairs develop into unique audiovisual objects that furthermore have to be processed in a unique way in order to enable fluent reading and thus very likely recruit other neurobiological learning mechanisms than the ones involved in learning natural or arbitrary unfamiliar audiovisual associations. Copyright 2010 Elsevier B.V. All rights reserved.

Learning from other people’s fear: amygdala-based social reference learning in social anxiety disorder

PubMed Central

Blair, K. S.; Otero, M.; Teng, C.; Geraci, M.; Lewis, E.; Hollon, N.; Blair, R. J. R.; Ernst, Monique; Grillon, C.; Pine, D. S.

2016-01-01

Background Social anxiety disorder involves fear of social objects or situations. Social referencing may play an important role in the acquisition of this fear and could be a key determinant in future biomarkers and treatment pathways. However, the neural underpinnings mediating such learning in social anxiety are unknown. Using event-related functional magnetic resonance imaging, we examined social reference learning in social anxiety disorder. Specifically, would patients with the disorder show increased amygdala activity during social reference learning, and further, following social reference learning, show particularly increased response to objects associated with other people’s negative reactions? Method A total of 32 unmedicated patients with social anxiety disorder and 22 age-, intelligence quotient- and gender-matched healthy individuals responded to objects that had become associated with others’ fearful, angry, happy or neutral reactions. Results During the social reference learning phase, a significant group × social context interaction revealed that, relative to the comparison group, the social anxiety group showed a significantly greater response in the amygdala, as well as rostral, dorsomedial and lateral frontal and parietal cortices during the social, relative to non-social, referencing trials. In addition, during the object test phase, relative to the comparison group, the social anxiety group showed increased bilateral amygdala activation to objects associated with others’ fearful reactions, and a trend towards decreased amygdala activation to objects associated with others’ happy and neutral reactions. Conclusions These results suggest perturbed observational learning in social anxiety disorder. In addition, they further implicate the amygdala and dorsomedial prefrontal cortex in the disorder, and underscore their importance in future biomarker developments. PMID:27476529

Qualitative differences in memory for vista and environmental spaces are caused by opaque borders, not movement or successive presentation.

PubMed

Meilinger, Tobias; Strickrodt, Marianne; Bülthoff, Heinrich H

2016-10-01

Two classes of space define our everyday experience within our surrounding environment: vista spaces, such as rooms or streets which can be perceived from one vantage point, and environmental spaces, for example, buildings and towns which are grasped from multiple views acquired during locomotion. However, theories of spatial representations often treat both spaces as equal. The present experiments show that this assumption cannot be upheld. Participants learned exactly the same layout of objects either within a single room or spread across multiple corridors. By utilizing a pointing and a placement task we tested the acquired configurational memory. In Experiment 1 retrieving memory of the object layout acquired in environmental space was affected by the distance of the traveled path and the order in which the objects were learned. In contrast, memory retrieval of objects learned in vista space was not bound to distance and relied on different ordering schemes (e.g., along the layout structure). Furthermore, spatial memory of both spaces differed with respect to the employed reference frame orientation. Environmental space memory was organized along the learning experience rather than layout intrinsic structure. In Experiment 2 participants memorized the object layout presented within the vista space room of Experiment 1 while the learning procedure emulated environmental space learning (movement, successive object presentation). Neither factor rendered similar results as found in environmental space learning. This shows that memory differences between vista and environmental space originated mainly from the spatial compartmentalization which was unique to environmental space learning. Our results suggest that transferring conclusions from findings obtained in vista space to environmental spaces and vice versa should be made with caution. Copyright © 2016 Elsevier B.V. All rights reserved.

Online faculty development for creating E-learning materials.

PubMed

Niebuhr, Virginia; Niebuhr, Bruce; Trumble, Julie; Urbani, Mary Jo

2014-01-01

Faculty who want to develop e-learning materials face pedagogical challenges of transforming instruction for the online environment, especially as many have never experienced online learning themselves. They face technical challenges of learning new software and time challenges of not all being able to be in the same place at the same time to learn these new skills. The objective of the Any Day Any Place Teaching (ADAPT) faculty development program was to create an online experience in which faculty could learn to produce e-learning materials. The ADAPT curriculum included units on instructional design, copyright principles and peer review, all for the online environment, and units on specific software tools. Participants experienced asynchronous and synchronous methods, including a learning management system, PC-based videoconferencing, online discussions, desktop sharing, an online toolbox and optional face-to-face labs. Project outcomes were e-learning materials developed and participants' evaluations of the experience. Likert scale responses for five instructional units (quantitative) were analyzed for distance from neutral using one-sample t-tests. Interview data (qualitative) were analyzed with assurance of data trustworthiness and thematic analysis techniques. Participants were 27 interprofessional faculty. They evaluated the program instruction as easy to access, engaging and logically presented. They reported increased confidence in new skills and increased awareness of copyright issues, yet continued to have time management challenges and remained uncomfortable about peer review. They produced 22 new instructional materials. Online faculty development methods are helpful for faculty learning to create e-learning materials. Recommendations are made to increase the success of such a faculty development program.

Confidence-Based Data Association and Discriminative Deep Appearance Learning for Robust Online Multi-Object Tracking.

PubMed

Bae, Seung-Hwan; Yoon, Kuk-Jin

2018-03-01

Online multi-object tracking aims at estimating the tracks of multiple objects instantly with each incoming frame and the information provided up to the moment. It still remains a difficult problem in complex scenes, because of the large ambiguity in associating multiple objects in consecutive frames and the low discriminability between objects appearances. In this paper, we propose a robust online multi-object tracking method that can handle these difficulties effectively. We first define the tracklet confidence using the detectability and continuity of a tracklet, and decompose a multi-object tracking problem into small subproblems based on the tracklet confidence. We then solve the online multi-object tracking problem by associating tracklets and detections in different ways according to their confidence values. Based on this strategy, tracklets sequentially grow with online-provided detections, and fragmented tracklets are linked up with others without any iterative and expensive association steps. For more reliable association between tracklets and detections, we also propose a deep appearance learning method to learn a discriminative appearance model from large training datasets, since the conventional appearance learning methods do not provide rich representation that can distinguish multiple objects with large appearance variations. In addition, we combine online transfer learning for improving appearance discriminability by adapting the pre-trained deep model during online tracking. Experiments with challenging public datasets show distinct performance improvement over other state-of-the-arts batch and online tracking methods, and prove the effect and usefulness of the proposed methods for online multi-object tracking.

A comparison of machine learning methods for classification using simulation with multiple real data examples from mental health studies.

PubMed

Khondoker, Mizanur; Dobson, Richard; Skirrow, Caroline; Simmons, Andrew; Stahl, Daniel

2016-10-01

Recent literature on the comparison of machine learning methods has raised questions about the neutrality, unbiasedness and utility of many comparative studies. Reporting of results on favourable datasets and sampling error in the estimated performance measures based on single samples are thought to be the major sources of bias in such comparisons. Better performance in one or a few instances does not necessarily imply so on an average or on a population level and simulation studies may be a better alternative for objectively comparing the performances of machine learning algorithms. We compare the classification performance of a number of important and widely used machine learning algorithms, namely the Random Forests (RF), Support Vector Machines (SVM), Linear Discriminant Analysis (LDA) and k-Nearest Neighbour (kNN). Using massively parallel processing on high-performance supercomputers, we compare the generalisation errors at various combinations of levels of several factors: number of features, training sample size, biological variation, experimental variation, effect size, replication and correlation between features. For smaller number of correlated features, number of features not exceeding approximately half the sample size, LDA was found to be the method of choice in terms of average generalisation errors as well as stability (precision) of error estimates. SVM (with RBF kernel) outperforms LDA as well as RF and kNN by a clear margin as the feature set gets larger provided the sample size is not too small (at least 20). The performance of kNN also improves as the number of features grows and outplays that of LDA and RF unless the data variability is too high and/or effect sizes are too small. RF was found to outperform only kNN in some instances where the data are more variable and have smaller effect sizes, in which cases it also provide more stable error estimates than kNN and LDA. Applications to a number of real datasets supported the findings from the simulation study. © The Author(s) 2013.

Biometric identification

NASA Astrophysics Data System (ADS)

Syryamkim, V. I.; Kuznetsov, D. N.; Kuznetsova, A. S.

2018-05-01

Image recognition is an information process implemented by some information converter (intelligent information channel, recognition system) having input and output. The input of the system is fed with information about the characteristics of the objects being presented. The output of the system displays information about which classes (generalized images) the recognized objects are assigned to. When creating and operating an automated system for pattern recognition, a number of problems are solved, while for different authors the formulations of these tasks, and the set itself, do not coincide, since it depends to a certain extent on the specific mathematical model on which this or that recognition system is based. This is the task of formalizing the domain, forming a training sample, learning the recognition system, reducing the dimensionality of space.

Terrestrial-passage theory: failing a test.

PubMed

Reed, Charles F; Krupinski, Elizabeth A

2009-01-01

Terrestrial-passage theory proposes that the 'moon' and 'sky' illusions occur because observers learn to expect an elevation-dependent transformation of visual angle. The transformation accompanies daily movement through ordinary environments of fixed-altitude objects. Celestial objects display the same visual angle at all elevations, and hence are necessarily non-conforming with the ordinary transformation. On hypothesis, observers should target angular sizes to appear greater at elevation than at horizon. However, in a sample of forty-eight observers there was no significant difference between the perceived angular size of a constellation of stars at horizon and that predicted for a specific elevation. Occurrence of the illusion was not restricted to those observers who expected angular expansion. These findings fail to support the terrestrial-passage theory of the illusion.

National Geological and Geophysical Data Preservation Program: Successes and Lessons Learned

NASA Astrophysics Data System (ADS)

Adrian, B. M.

2014-12-01

The United States Geological Survey (USGS) is widely recognized in the earth science community as possessing extensive collections of geologic and geophysical materials gathered by its research personnel. Since the USGS was established in 1879, hundreds of thousands of samples have been gathered in collections that range from localized, geographically-based assemblages to ones that are national or international in scope. These materials include, but are not limited to, rock and mineral specimens; fossils; drill cores and cuttings; geochemical standards; and soil, sediment, and geochemical samples. The USGS National Geological and Geophysical Data Preservation Program (NGGDPP) was established with the passage of the Energy Policy Act of 2005. Since its implementation, the USGS NGGDPP has taken an active role in providing opportunities to inventory, archive and preserve geologic and geophysical samples, and to make these samples and ancillary data discoverable on the Internet. Preserving endangered geoscience collections is more cost effective than recollecting this information. Preserving these collections, however, is only one part of the process - there also needs to be a means to facilitate open discovery and access to the physical objects and the ancillary digital records. The NGGDPP has celebrated successes such as the development of the USGS Geologic Collections Management System (GCMS), a master catalog and collections management plan, and the implementation and advancement of the National Digital Catalog, a digital inventory and catalog of geological and geophysical data and collections held by the USGS and State geological surveys. Over this period of time there has been many lessons learned. With the successes and lessons learned, NGGDPP is poised to take on challenges the future may bring.

Using machine-learning to optimize phase contrast in a low-cost cellphone microscope

PubMed Central

Wartmann, Rolf; Schadwinkel, Harald; Heintzmann, Rainer

2018-01-01

Cellphones equipped with high-quality cameras and powerful CPUs as well as GPUs are widespread. This opens new prospects to use such existing computational and imaging resources to perform medical diagnosis in developing countries at a very low cost. Many relevant samples, like biological cells or waterborn parasites, are almost fully transparent. As they do not exhibit absorption, but alter the light’s phase only, they are almost invisible in brightfield microscopy. Expensive equipment and procedures for microscopic contrasting or sample staining often are not available. Dedicated illumination approaches, tailored to the sample under investigation help to boost the contrast. This is achieved by a programmable illumination source, which also allows to measure the phase gradient using the differential phase contrast (DPC) [1, 2] or even the quantitative phase using the derived qDPC approach [3]. By applying machine-learning techniques, such as a convolutional neural network (CNN), it is possible to learn a relationship between samples to be examined and its optimal light source shapes, in order to increase e.g. phase contrast, from a given dataset to enable real-time applications. For the experimental setup, we developed a 3D-printed smartphone microscope for less than 100 $ using off-the-shelf components only such as a low-cost video projector. The fully automated system assures true Koehler illumination with an LCD as the condenser aperture and a reversed smartphone lens as the microscope objective. We show that the effect of a varied light source shape, using the pre-trained CNN, does not only improve the phase contrast, but also the impression of an improvement in optical resolution without adding any special optics, as demonstrated by measurements. PMID:29494620

Application of Multi-Objective Human Learning Optimization Method to Solve AC/DC Multi-Objective Optimal Power Flow Problem

NASA Astrophysics Data System (ADS)

Cao, Jia; Yan, Zheng; He, Guangyu

2016-06-01

This paper introduces an efficient algorithm, multi-objective human learning optimization method (MOHLO), to solve AC/DC multi-objective optimal power flow problem (MOPF). Firstly, the model of AC/DC MOPF including wind farms is constructed, where includes three objective functions, operating cost, power loss, and pollutant emission. Combining the non-dominated sorting technique and the crowding distance index, the MOHLO method can be derived, which involves individual learning operator, social learning operator, random exploration learning operator and adaptive strategies. Both the proposed MOHLO method and non-dominated sorting genetic algorithm II (NSGAII) are tested on an improved IEEE 30-bus AC/DC hybrid system. Simulation results show that MOHLO method has excellent search efficiency and the powerful ability of searching optimal. Above all, MOHLO method can obtain more complete pareto front than that by NSGAII method. However, how to choose the optimal solution from pareto front depends mainly on the decision makers who stand from the economic point of view or from the energy saving and emission reduction point of view.

Commognitive analysis of undergraduate mathematics students' first encounter with the subgroup test

NASA Astrophysics Data System (ADS)

Ioannou, Marios

2018-06-01

This study analyses learning aspects of undergraduate mathematics students' first encounter with the subgroup test, using the commognitive theoretical framework. It focuses on students' difficulties as these are related to the object-level and metalevel mathematical learning in group theory, and, when possible, highlights any commognitive conflicts. In the data analysis, one can identify three types of difficulties, relevant to object-level learning: namely regarding the frequently observed confusion between groups and sets, the object-level rules of visual mediators, and the object-level rules of contextual notions, such as permutations, exponentials, sets and matrices. In addition, data analysis suggests two types of difficulties, relevant to metalevel learning. The first refers to the actual proof that the three conditions of subgroup test hold, and the second is related to syntactic inaccuracies, incomplete argumentation and problematic use of visual mediators. Finally, this study suggests that there are clear links between object-level and metalevel learning, mainly due to the fact that objectification of the various relevant mathematical notions influences the endorsement of the governing metarules.

Drought Management Activities of the National Drought Mitigation Center (NDMC): Contributions Toward a Global Drought Early Warning System (GDEWS)

NASA Astrophysics Data System (ADS)

Stumpf, A.; Lachiche, N.; Malet, J.; Kerle, N.; Puissant, A.

2011-12-01

VHR satellite images have become a primary source for landslide inventory mapping after major triggering events such as earthquakes and heavy rainfalls. Visual image interpretation is still the prevailing standard method for operational purposes but is time-consuming and not well suited to fully exploit the increasingly better supply of remote sensing data. Recent studies have addressed the development of more automated image analysis workflows for landslide inventory mapping. In particular object-oriented approaches that account for spatial and textural image information have been demonstrated to be more adequate than pixel-based classification but manually elaborated rule-based classifiers are difficult to adapt under changing scene characteristics. Machine learning algorithm allow learning classification rules for complex image patterns from labelled examples and can be adapted straightforwardly with available training data. In order to reduce the amount of costly training data active learning (AL) has evolved as a key concept to guide the sampling for many applications. The underlying idea of AL is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and data structure to iteratively select the most valuable samples that should be labelled by the user. With relatively few queries and labelled samples, an AL strategy yields higher accuracies than an equivalent classifier trained with many randomly selected samples. This study addressed the development of an AL method for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. Our approach [1] is based on the Random Forest algorithm and considers the classifier uncertainty as well as the variance of potential sampling regions to guide the user towards the most valuable sampling areas. The algorithm explicitly searches for compact regions and thereby avoids a spatially disperse sampling pattern inherent to most other AL methods. The accuracy, the sampling time and the computational runtime of the algorithm were evaluated on multiple satellite images capturing recent large scale landslide events. Sampling between 1-4% of the study areas the accuracies between 74% and 80% were achieved, whereas standard sampling schemes yielded only accuracies between 28% and 50% with equal sampling costs. Compared to commonly used point-wise AL algorithm the proposed approach significantly reduces the number of iterations and hence the computational runtime. Since the user can focus on relatively few compact areas (rather than on hundreds of distributed points) the overall labeling time is reduced by more than 50% compared to point-wise queries. An experimental evaluation of multiple expert mappings demonstrated strong relationships between the uncertainties of the experts and the machine learning model. It revealed that the achieved accuracies are within the range of the inter-expert disagreement and that it will be indispensable to consider ground truth uncertainties to truly achieve further enhancements in the future. The proposed method is generally applicable to a wide range of optical satellite images and landslide types. [1] A. Stumpf, N. Lachiche, J.-P. Malet, N. Kerle, and A. Puissant, Active learning in the spatial domain for remote sensing image classification, IEEE Transactions on Geosciece and Remote Sensing. 2013, DOI 10.1109/TGRS.2013.2262052.

A Study on the Difficulties of Learning Phase Transition in Object-Oriented Analysis and Design from the Viewpoint of Semantic Distance

ERIC Educational Resources Information Center

Shin, Shin-Shing

2015-01-01

Students in object-oriented analysis and design (OOAD) courses typically encounter difficulties transitioning from object-oriented analysis (OOA) to logical design (OOLD). This study conducted an empirical experiment to examine these learning difficulties by evaluating differences between OOA-to-OOLD and OOLD-to-object-oriented-physical-design…

The Interactive Effects of the Availability of Objectives and/or Rules on Computer-Based Learning: A Replication.

ERIC Educational Resources Information Center

Merrill, Paul F.; And Others

To replicate and extend the results of a previous study, this project investigated the effects of behavioral objectives and/or rules on computer-based learning task performance. The 133 subjects were randomly assigned to an example-only, objective-example, rule example, or objective-rule example group. The availability of rules and/or objectives…

Reweighted mass center based object-oriented sparse subspace clustering for hyperspectral images

NASA Astrophysics Data System (ADS)

Zhai, Han; Zhang, Hongyan; Zhang, Liangpei; Li, Pingxiang

2016-10-01

Considering the inevitable obstacles faced by the pixel-based clustering methods, such as salt-and-pepper noise, high computational complexity, and the lack of spatial information, a reweighted mass center based object-oriented sparse subspace clustering (RMC-OOSSC) algorithm for hyperspectral images (HSIs) is proposed. First, the mean-shift segmentation method is utilized to oversegment the HSI to obtain meaningful objects. Second, a distance reweighted mass center learning model is presented to extract the representative and discriminative features for each object. Third, assuming that all the objects are sampled from a union of subspaces, it is natural to apply the SSC algorithm to the HSI. Faced with the high correlation among the hyperspectral objects, a weighting scheme is adopted to ensure that the highly correlated objects are preferred in the procedure of sparse representation, to reduce the representation errors. Two widely used hyperspectral datasets were utilized to test the performance of the proposed RMC-OOSSC algorithm, obtaining high clustering accuracies (overall accuracy) of 71.98% and 89.57%, respectively. The experimental results show that the proposed method clearly improves the clustering performance with respect to the other state-of-the-art clustering methods, and it significantly reduces the computational time.

Expectancy violations promote learning in young children

PubMed Central

Stahl, Aimee E.; Feigenson, Lisa

2018-01-01

Children, including infants, have expectations about the world around them, and produce reliable responses when these expectations are violated. However, little is known about how such expectancy violations affect subsequent cognition. Here we tested the hypothesis that violations of expectation enhance children’s learning. In four experiments we compared 3- to 6-year-old children’s ability to learn novel words in situations that defied versus accorded with their core knowledge of object behavior. In Experiments 1 and 2 we taught children novel words following one of two types of events. One event violated expectations about the spatiotemporal or featural properties of objects (e.g., an object appeared to magically change locations). The other event was almost identical, but did not violate expectations (e.g., an object was visibly moved from one location to another). In both experiments we found that children robustly learned when taught after the surprising event, but not following the expected event. In Experiment 3 we ruled out two alternative explanations for our results. Finally, in Experiment 4, we asked whether surprise affects children’s learning in a targeted or a diffuse way. We found that surprise only enhanced children’s learning about the entity that had behaved surprisingly, and not about unrelated objects. Together, these experiments show that core knowledge – and violations of expectations generated by core knowledge – shapes new learning. PMID:28254617

eNOSHA, a Free, Open and Flexible Learning Object Repository--An Iterative Development Process for Global User-Friendliness

ERIC Educational Resources Information Center

Mozelius, Peter; Hettiarachchi, Enosha

2012-01-01

This paper describes the iterative development process of a Learning Object Repository (LOR), named eNOSHA. Discussions on a project for a LOR started at the e-Learning Centre (eLC) at The University of Colombo, School of Computing (UCSC) in 2007. The eLC has during the last decade been developing learning content for a nationwide e-learning…

Prefrontal Cortex Networks Shift from External to Internal Modes during Learning.

PubMed

Brincat, Scott L; Miller, Earl K

2016-09-14

As we learn about items in our environment, their neural representations become increasingly enriched with our acquired knowledge. But there is little understanding of how network dynamics and neural processing related to external information changes as it becomes laden with "internal" memories. We sampled spiking and local field potential activity simultaneously from multiple sites in the lateral prefrontal cortex (PFC) and the hippocampus (HPC)-regions critical for sensory associations-of monkeys performing an object paired-associate learning task. We found that in the PFC, evoked potentials to, and neural information about, external sensory stimulation decreased while induced beta-band (∼11-27 Hz) oscillatory power and synchrony associated with "top-down" or internal processing increased. By contrast, the HPC showed little evidence of learning-related changes in either spiking activity or network dynamics. The results suggest that during associative learning, PFC networks shift their resources from external to internal processing. As we learn about items in our environment, their representations in our brain become increasingly enriched with our acquired "top-down" knowledge. We found that in the prefrontal cortex, but not the hippocampus, processing of external sensory inputs decreased while internal network dynamics related to top-down processing increased. The results suggest that during learning, prefrontal cortex networks shift their resources from external (sensory) to internal (memory) processing. Copyright © 2016 the authors 0270-6474/16/369739-16$15.00/0.

How organizational learning is associated with patient rights: a qualitative content analysis

PubMed Central

Heidari, Shahin; Nayeri, Nahid Dehghan; Ravari, Ali; Sabzevari, Sakineh

2016-01-01

Background Nowadays, patient rights, particularly receiving favorable health care based on modern knowledge, informed consent, and privacy, are important issues in health care delivery systems. Organizational learning is considered an important factor influencing health care quality and patient rights. However, there is little evidence regarding this issue. Objective The present study was conducted to explore the role of organizational learning in patient rights from clinical nurses’ viewpoint. Design This qualitative study was conducted through conventional content analysis. In total, 18 nurses who met the inclusion criteria participated in this study through purposive sampling with maximum variation. Data were gathered through 20 in-depth, semi-structured interviews, which continued until data saturation was achieved. Data collection also included constant and simultaneous comparative analyses. Results Data analysis led to four major themes: conservation of patient safety, providing favorable care, being the patient's advocate, and informing the patients. All the participants believed that organizational learning could play a vital role in respecting patient rights and interests. Conclusions Participants believed that their efforts to conduct organizational learning, tried to improve respecting the patient rights via conservation of patient safety, trying to improve quality of care, being an advocate, and informing the patient. It would be appreciable if nursing managers honored the commitment of the nurses for learning, highlight their role as defenders of patient rights, and encourage them to initiate organizational learning. PMID:27465289

Prefrontal Cortex Networks Shift from External to Internal Modes during Learning

PubMed Central

Brincat, Scott L.

2016-01-01

As we learn about items in our environment, their neural representations become increasingly enriched with our acquired knowledge. But there is little understanding of how network dynamics and neural processing related to external information changes as it becomes laden with “internal” memories. We sampled spiking and local field potential activity simultaneously from multiple sites in the lateral prefrontal cortex (PFC) and the hippocampus (HPC)—regions critical for sensory associations—of monkeys performing an object paired-associate learning task. We found that in the PFC, evoked potentials to, and neural information about, external sensory stimulation decreased while induced beta-band (∼11–27 Hz) oscillatory power and synchrony associated with “top-down” or internal processing increased. By contrast, the HPC showed little evidence of learning-related changes in either spiking activity or network dynamics. The results suggest that during associative learning, PFC networks shift their resources from external to internal processing. SIGNIFICANCE STATEMENT As we learn about items in our environment, their representations in our brain become increasingly enriched with our acquired “top-down” knowledge. We found that in the prefrontal cortex, but not the hippocampus, processing of external sensory inputs decreased while internal network dynamics related to top-down processing increased. The results suggest that during learning, prefrontal cortex networks shift their resources from external (sensory) to internal (memory) processing. PMID:27629722

Data Mining for Efficient and Accurate Large Scale Retrieval of Geophysical Parameters

NASA Astrophysics Data System (ADS)

Obradovic, Z.; Vucetic, S.; Peng, K.; Han, B.

2004-12-01

Our effort is devoted to developing data mining technology for improving efficiency and accuracy of the geophysical parameter retrievals by learning a mapping from observation attributes to the corresponding parameters within the framework of classification and regression. We will describe a method for efficient learning of neural network-based classification and regression models from high-volume data streams. The proposed procedure automatically learns a series of neural networks of different complexities on smaller data stream chunks and then properly combines them into an ensemble predictor through averaging. Based on the idea of progressive sampling the proposed approach starts with a very simple network trained on a very small chunk and then gradually increases the model complexity and the chunk size until the learning performance no longer improves. Our empirical study on aerosol retrievals from data obtained with the MISR instrument mounted at Terra satellite suggests that the proposed method is successful in learning complex concepts from large data streams with near-optimal computational effort. We will also report on a method that complements deterministic retrievals by constructing accurate predictive algorithms and applying them on appropriately selected subsets of observed data. The method is based on developing more accurate predictors aimed to catch global and local properties synthesized in a region. The procedure starts by learning the global properties of data sampled over the entire space, and continues by constructing specialized models on selected localized regions. The global and local models are integrated through an automated procedure that determines the optimal trade-off between the two components with the objective of minimizing the overall mean square errors over a specific region. Our experimental results on MISR data showed that the combined model can increase the retrieval accuracy significantly. The preliminary results on various large heterogeneous spatial-temporal datasets provide evidence that the benefits of the proposed methodology for efficient and accurate learning exist beyond the area of retrieval of geophysical parameters.

Performance evaluation of Al-Zahra academic medical center based on Iran balanced scorecard model.

PubMed

Raeisi, Ahmad Reza; Yarmohammadian, Mohammad Hossein; Bakhsh, Roghayeh Mohammadi; Gangi, Hamid

2012-01-01

Growth and development in any country's national health system, without an efficient evaluation system, lacks the basic concepts and tools necessary for fulfilling the system's goals. The balanced scorecard (BSC) is a technique widely used to measure the performance of an organization. The basic core of the BSC is guided by the organization's vision and strategies, which are the bases for the formation of four perspectives of BSC. The goal of this research is the performance evaluation of Al-Zahra Academic Medical Center in Isfahan University of Medical Sciences, based on Iran BSC model. This is a combination (quantitative-qualitative) research which was done at Al-Zahra Academic Medical Center in Isfahan University of Medical Sciences in 2011. The research populations were hospital managers at different levels. Sampling method was purposive sampling in which the key informed personnel participated in determining the performance indicators of hospital as the BSC team members in focused discussion groups. After determining the conceptual elements in focused discussion groups, the performance objectives (targets) and indicators of hospital were determined and sorted in perspectives by the group discussion participants. Following that, the performance indicators were calculated by the experts according to the predetermined objectives; then, the score of each indicator and the mean score of each perspective were calculated. Research findings included development of the organizational mission, vision, values, objectives, and strategies. The strategies agreed upon by the participants in the focus discussion group included five strategies, which were customer satisfaction, continuous quality improvement, development of human resources, supporting innovation, expansion of services and improving the productivity. Research participants also agreed upon four perspectives for the Al-Zahra hospital BSC. In the patients and community perspective (customer), two objectives and three indicators were agreed upon, with a mean score of 75.9%. In the internal process perspective, 4 objectives and 14 indicators were agreed upon, with a mean score of 79.37%. In the learning and growth perspective, four objectives and eight indicators were agreed upon, with a mean score of 81.11%. Finally, in the financial perspective, two objectives and five indicators were agreed upon, with a mean score of 67.15%. One way to create demand for hospital services is performance evaluation by paying close attention to all BSC perspectives, especially the non-financial perspectives such as customers and internal processes perspectives. In this study, the BSC showed the differences in performance level of the organization in different perspectives, which would assist the hospital managers improve their performance indicators. The learning and growth perspective obtained the highest score, and the financial perspective obtained the least score. Since the learning and growth perspective acts as a base for all other perspectives and they depend on it, hospitals must continuously improve the service processes and the quality of services by educating staff and updating their policies and procedures. This can increase customer satisfaction and productivity and finally improve the BSC in financial perspective.

Developing a University Course for Online Delivery Based on Learning Objects: From Ideals to Compromises

ERIC Educational Resources Information Center

Wilhelm, Pierre; Wilde, Russ

2005-01-01

A course instructor and his assistant at Athabasca University investigated whether the process of transferring interoperable learning objects from online repositories facilitated course production, both pedagogically and economically. They examined the efficiency of the objects-assembly method from several perspectives while developing an online…

Children Monitor Individuals' Expertise for Word Learning

ERIC Educational Resources Information Center

Sobel, David M.; Corriveau, Kathleen H.

2010-01-01

Two experiments examined preschoolers' ability to learn novel words using others' expertise about objects' nonobvious properties. In Experiment 1, 4-year-olds (n = 24) endorsed individuals' labels for objects based on their differing causal knowledge about those objects. Experiment 2 examined the robustness of this inference and its development.…

Educators Prescriptive Handbook: A Developmental Sequence of Learning Skills.

ERIC Educational Resources Information Center

Santa Ana Unified School District, CA.

The handbook lists 141 developmental objectives with instructions for remediation to aid children with learning problems in the areas of sensory motor development, auditory perception, language, visual perception, and academic achievement. Objectives are listed in chart format with each objective associated with one or more skill examples,…

Teaching Measurement to Children: Grades K-6. Revised Edition.

ERIC Educational Resources Information Center

Borelli, Michael L.; Morelli, Sandra Z.

Objectives are listed describing the progression which students follow in learning to measure. These objectives follow a sequence that corresponds closely with the intellectual sequence found in students' learning. Grade-level recommendation charts follow the objectives. Topics dealt with are length, distance, area, volume, capacity, mass, and…

Learning Object Names at Different Hierarchical Levels Using Cross-Situational Statistics

ERIC Educational Resources Information Center

Chen, Chi-hsin; Zhang, Yayun; Yu, Chen

2018-01-01

Objects in the world usually have names at different hierarchical levels (e.g., "beagle," "dog," "animal"). This research investigates adults' ability to use cross-situational statistics to simultaneously learn object labels at individual and category levels. The results revealed that adults were able to use…

Bounds on the sample complexity for private learning and private data release

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

Kasiviswanathan, Shiva; Beime, Amos; Nissim, Kobbi

2009-01-01

Learning is a task that generalizes many of the analyses that are applied to collections of data, and in particular, collections of sensitive individual information. Hence, it is natural to ask what can be learned while preserving individual privacy. [Kasiviswanathan, Lee, Nissim, Raskhodnikova, and Smith; FOCS 2008] initiated such a discussion. They formalized the notion of private learning, as a combination of PAC learning and differential privacy, and investigated what concept classes can be learned privately. Somewhat surprisingly, they showed that, ignoring time complexity, every PAC learning task could be performed privately with polynomially many samples, and in many naturalmore » cases this could even be done in polynomial time. While these results seem to equate non-private and private learning, there is still a significant gap: the sample complexity of (non-private) PAC learning is crisply characterized in terms of the VC-dimension of the concept class, whereas this relationship is lost in the constructions of private learners, which exhibit, generally, a higher sample complexity. Looking into this gap, we examine several private learning tasks and give tight bounds on their sample complexity. In particular, we show strong separations between sample complexities of proper and improper private learners (such separation does not exist for non-private learners), and between sample complexities of efficient and inefficient proper private learners. Our results show that VC-dimension is not the right measure for characterizing the sample complexity of proper private learning. We also examine the task of private data release (as initiated by [Blum, Ligett, and Roth; STOC 2008]), and give new lower bounds on the sample complexity. Our results show that the logarithmic dependence on size of the instance space is essential for private data release.« less

Quality Assurance for Digital Learning Object Repositories: Issues for the Metadata Creation Process

ERIC Educational Resources Information Center

Currier, Sarah; Barton, Jane; O'Beirne, Ronan; Ryan, Ben

2004-01-01

Metadata enables users to find the resources they require, therefore it is an important component of any digital learning object repository. Much work has already been done within the learning technology community to assure metadata quality, focused on the development of metadata standards, specifications and vocabularies and their implementation…

The Use of a Well-Designed Instructional Guideline in Online MBA Teaching

ERIC Educational Resources Information Center

Duesing, Robert J.; Ling, Juan; Yang, Jiaqin

2016-01-01

This study investigated the positive impact of a teaching practice on student learning outcomes in an online MBA program. An instructional project guideline was developed to help online students enhance their achieving required learning objectives corresponding to five categories of Bloom's Taxonomy. The course learning objectives are based on…

Model Based Usability Heuristics for Constructivist E-Learning

ERIC Educational Resources Information Center

Katre, Dinesh S.

2007-01-01

Many e-learning applications and games have been studied to identify the common interaction models of constructivist learning, namely: 1. Move the object to appropriate location; 2. Place objects in appropriate order and location(s); 3. Click to identify; 4. Change the variable factors to observe the effects; and 5. System personification and…

Predictable Locations Aid Early Object Name Learning

ERIC Educational Resources Information Center

Benitez, Viridiana L.; Smith, Linda B.

2012-01-01

Expectancy-based localized attention has been shown to promote the formation and retrieval of multisensory memories in adults. Three experiments show that these processes also characterize attention and learning in 16- to 18-month old infants and, moreover, that these processes may play a critical role in supporting early object name learning. The…

An Online Authoring Tool for Creating Activity-Based Learning Objects

ERIC Educational Resources Information Center

Ahn, Jeong Yong; Mun, Gil Seong; Han, Kyung Soo; Choi, Sook Hee

2017-01-01

As higher education increasingly relies on e-learning, the need for tools that will allow teachers themselves to develop effective e-learning objects as simply and quickly as possible has also been increasingly recognized. This article discusses the design and development of a novel tool, Enook (Evolutionary note book), for creating activity-based…

A Bootstrapping Model of Frequency and Context Effects in Word Learning

ERIC Educational Resources Information Center

Kachergis, George; Yu, Chen; Shiffrin, Richard M.

2017-01-01

Prior research has shown that people can learn many nouns (i.e., word--object mappings) from a short series of ambiguous situations containing multiple words and objects. For successful cross-situational learning, people must approximately track which words and referents co-occur most frequently. This study investigates the effects of allowing…