Active learning on the ward: outcomes from a comparative trial with traditional methods.

PubMed

Melo Prado, Hegla; Hannois Falbo, Gilliatt; Rodrigues Falbo, Ana; Natal Figueirôa, José

2011-03-01

Academic activity during internship is essentially practical and ward rounds are traditionally considered the cornerstone of clinical education. However, the efficacy and effectiveness of ward rounds for learning purposes have been under-investigated and it is necessary to assess alternative educational paradigms for this activity. This study aimed to compare the educational effectiveness of ward rounds conducted with two different learning methodologies. Student subjects were first tested on 30 true/false questions to assess their initial degree of knowledge on pneumonia and diarrhoea. Afterwards, they attended ward rounds conducted using an active and a traditional learning methodology. The participants were submitted to a second test 48hours later in order to assess knowledge acquisition and were asked to answer two questions about self-directed learning and their opinions on the two learning methodologies used. Seventy-two medical students taking part in a paediatric clinic rotation were enrolled. The active methodology proved to be more effective than the traditional methodology for the three outcomes considered: knowledge acquisition (33 students [45.8%] versus 21 students [29.2%]; p=0.03); self-directed learning (38 students [52.8%] versus 11 students [15.3%]; p<0.001), and student opinion on the methods (61 students [84.7%] versus 38 students [52.8%]; p<0.001). The active methodology produced better results than the traditional methodology in a ward-based context. This study seems to be valuable in terms of the new evidence it demonstrates on learning methodologies in the context of the ward round. © Blackwell Publishing Ltd 2011.

The Key Factors of an Active Learning Method in a Microprocessors Course

ERIC Educational Resources Information Center

Carpeno, A.; Arriaga, J.; Corredor, J.; Hernandez, J.

2011-01-01

The creation of the European Higher Education Area (EHEA) is promoting a change toward a new model of education focused on the student. It is impelling methodological innovation processes in many European universities, leading more teachers to apply methods based on active and cooperative learning in their classrooms. However, the successful…

Student Reciprocal Peer Teaching as a Method for Active Learning: An Experience in an Electrotechnical Laboratory

ERIC Educational Resources Information Center

Muñoz-García, Miguel A.; Moreda, Guillermo P.; Hernández-Sánchez, Natalia; Valiño, Vanesa

2013-01-01

Active learning is one of the most efficient mechanisms for learning, according to the psychology of learning. When students act as teachers for other students, the communication is more fluent and knowledge is transferred easier than in a traditional classroom. This teaching method is referred to in the literature as reciprocal peer teaching. In…

Active learning in capstone design courses.

PubMed

Goldberg, Jay R

2012-01-01

There is a growing trend to encourage students to take a more active role in their own education. Many schools are moving away from the sage on the stage to the guide on the side model where the instructor is a facilitator of learning. In this model, the emphasis is more on learning and less on teaching, and it requires instructors to incorporate more active and student-centered learning methods into their courses. These methods include collaborative, cooperative, problem-based, and project-based learning.

Accelerated Learning: Madness with a Method.

ERIC Educational Resources Information Center

Zemke, Ron

1995-01-01

Accelerated learning methods have evolved into a variety of holistic techniques that involve participants in the learning process and overcome negative attitudes about learning. These components are part of the mix: the brain, learning environment, music, imaginative activities, suggestion, positive mental state, the arts, multiple intelligences,…

Tracking Active Learning in the Medical School Curriculum: A Learning-Centered Approach.

PubMed

McCoy, Lise; Pettit, Robin K; Kellar, Charlyn; Morgan, Christine

2018-01-01

Medical education is moving toward active learning during large group lecture sessions. This study investigated the saturation and breadth of active learning techniques implemented in first year medical school large group sessions. Data collection involved retrospective curriculum review and semistructured interviews with 20 faculty. The authors piloted a taxonomy of active learning techniques and mapped learning techniques to attributes of learning-centered instruction. Faculty implemented 25 different active learning techniques over the course of 9 first year courses. Of 646 hours of large group instruction, 476 (74%) involved at least 1 active learning component. The frequency and variety of active learning components integrated throughout the year 1 curriculum reflect faculty familiarity with active learning methods and their support of an active learning culture. This project has sparked reflection on teaching practices and facilitated an evolution from teacher-centered to learning-centered instruction.

Manifold Regularized Experimental Design for Active Learning.

PubMed

Zhang, Lining; Shum, Hubert P H; Shao, Ling

2016-12-02

Various machine learning and data mining tasks in classification require abundant data samples to be labeled for training. Conventional active learning methods aim at labeling the most informative samples for alleviating the labor of the user. Many previous studies in active learning select one sample after another in a greedy manner. However, this is not very effective because the classification models has to be retrained for each newly labeled sample. Moreover, many popular active learning approaches utilize the most uncertain samples by leveraging the classification hyperplane of the classifier, which is not appropriate since the classification hyperplane is inaccurate when the training data are small-sized. The problem of insufficient training data in real-world systems limits the potential applications of these approaches. This paper presents a novel method of active learning called manifold regularized experimental design (MRED), which can label multiple informative samples at one time for training. In addition, MRED gives an explicit geometric explanation for the selected samples to be labeled by the user. Different from existing active learning methods, our method avoids the intrinsic problems caused by insufficiently labeled samples in real-world applications. Various experiments on synthetic datasets, the Yale face database and the Corel image database have been carried out to show how MRED outperforms existing methods.

Resource Letter ALIP-1: Active-Learning Instruction in Physics

NASA Astrophysics Data System (ADS)

Meltzer, David E.; Thornton, Ronald K.

2012-06-01

This Resource Letter provides a guide to the literature on research-based active-learning instruction in physics. These are instructional methods that are based on, assessed by, and validated through research on the teaching and learning of physics. They involve students in their own learning more deeply and more intensely than does traditional instruction, particularly during class time. The instructional methods and supporting body of research reviewed here offer potential for significantly improved learning in comparison to traditional lecture-based methods of college and university physics instruction. We begin with an introduction to the history of active learning in physics in the United States, and then discuss some methods for and outcomes of assessing pedagogical effectiveness. We enumerate and describe common characteristics of successful active-learning instructional strategies in physics. We then discuss a range of methods for introducing active-learning instruction in physics and provide references to those methods for which there is published documentation of student learning gains.

A Bridge to Active Learning: A Summer Bridge Program Helps Students Maximize Their Active-Learning Experiences and the Active-Learning Experiences of Others

PubMed Central

Cooper, Katelyn M.; Ashley, Michael; Brownell, Sara E.

2017-01-01

National calls to improve student academic success in college have sparked the development of bridge programs designed to help students transition from high school to college. We designed a 2-week Summer Bridge program that taught introductory biology content in an active-learning way. Through a set of exploratory interviews, we unexpectedly identified that Bridge students had developed sophisticated views of active learning, even though this was not an explicit goal of the program. We conducted an additional set of semistructured interviews that focused on active learning and compared the interviews of Bridge students with those from non-Bridge students who had been eligible for but did not participate in the program. We used the constant comparative method to identify themes from the interviews. We found that Bridge students perceived that, because they knew how to approach active learning and viewed it as important, they benefited more from active learning in introductory biology than non-Bridge students. Specifically, Bridge students seemed to be more aware of their own learning gains from participating in active learning. Compared with the majority of non-Bridge students, the majority of Bridge students described using a greater variety of strategies to maximize their experiences in active learning. Finally, in contrast to non-Bridge students, Bridge students indicated that they take an equitable approach to group work. These findings suggest that we may be able to prime students to maximize their own and other’s experiences in active learning. PMID:28232588

The guided autobiography method: a learning experience.

PubMed

Thornton, James E

2008-01-01

This article discusses the proposition that learning is an unexplored feature of the guided autobiography method and its developmental exchange. Learning, conceptualized and explored as the embedded and embodied processes, is essential in narrative activities of the guided autobiography method leading to psychosocial development and growth in dynamic, temporary social groups. The article is organized in four sections and summary. The first section provides a brief overview of the guided autobiography method describing the interplay of learning and experiencing in temporary social groups. The second section offers a limited review on learning and experiencing as processes that are essential for development, growth, and change. The third section reviews the small group activities and the emergence of the "developmental exchange" in the guided autobiography method. Two theoretical constructs provide a conceptual foundation for the developmental exchange: a counterpart theory of aging as development and collaborative-situated group learning theory. The summary recaps the main ideas and issues that shape the guided autobiography method as learning and social experience using the theme, "Where to go from here."

Inter-Labeler and Intra-Labeler Variability of Condition Severity Classification Models Using Active and Passive Learning Methods

PubMed Central

Nissim, Nir; Shahar, Yuval; Boland, Mary Regina; Tatonetti, Nicholas P; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert

2018-01-01

Background and Objectives Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE framework for classifying the severity of clinical conditions, and shown its significant reduction of labeling efforts. The use of any of three AL methods (one well known [SVM-Margin], and two that we introduced [Exploitation and Combination_XA]) significantly reduced (by 48% to 64%) condition labeling efforts, compared to standard passive (random instance-selection) SVM learning. Furthermore, our new AL methods achieved maximal accuracy using 12% fewer labeled cases than the SVM-Margin AL method. However, because labelers have varying levels of expertise, a major issue associated with learning methods, and AL methods in particular, is how to best to use the labeling provided by a committee of labelers. First, we wanted to know, based on the labelers’ learning curves, whether using AL methods (versus standard passive learning methods) has an effect on the Intra-labeler variability (within the learning curve of each labeler) and inter-labeler variability (among the learning curves of different labelers). Then, we wanted to examine the effect of learning (either passively or actively) from the labels created by the majority consensus of a group of labelers. Methods We used our CAESAR-ALE framework for classifying the severity of clinical conditions, the three AL methods and the passive learning method, as mentioned above, to induce the classifications models. We used a dataset of 516 clinical conditions and their severity labeling, represented by features aggregated from the medical records of 1.9 million patients treated at Columbia University Medical Center. We analyzed the variance of the classification performance within (intra-labeler), and especially among (inter-labeler) the classification models that were induced by

Inter-labeler and intra-labeler variability of condition severity classification models using active and passive learning methods.

PubMed

Nissim, Nir; Shahar, Yuval; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert

2017-09-01

Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE framework for classifying the severity of clinical conditions, and shown its significant reduction of labeling efforts. The use of any of three AL methods (one well known [SVM-Margin], and two that we introduced [Exploitation and Combination_XA]) significantly reduced (by 48% to 64%) condition labeling efforts, compared to standard passive (random instance-selection) SVM learning. Furthermore, our new AL methods achieved maximal accuracy using 12% fewer labeled cases than the SVM-Margin AL method. However, because labelers have varying levels of expertise, a major issue associated with learning methods, and AL methods in particular, is how to best to use the labeling provided by a committee of labelers. First, we wanted to know, based on the labelers' learning curves, whether using AL methods (versus standard passive learning methods) has an effect on the Intra-labeler variability (within the learning curve of each labeler) and inter-labeler variability (among the learning curves of different labelers). Then, we wanted to examine the effect of learning (either passively or actively) from the labels created by the majority consensus of a group of labelers. We used our CAESAR-ALE framework for classifying the severity of clinical conditions, the three AL methods and the passive learning method, as mentioned above, to induce the classifications models. We used a dataset of 516 clinical conditions and their severity labeling, represented by features aggregated from the medical records of 1.9 million patients treated at Columbia University Medical Center. We analyzed the variance of the classification performance within (intra-labeler), and especially among (inter-labeler) the classification models that were induced by using the labels provided by seven

Group-Based Active Learning of Classification Models.

PubMed

Luo, Zhipeng; Hauskrecht, Milos

2017-05-01

Learning of classification models from real-world data often requires additional human expert effort to annotate the data. However, this process can be rather costly and finding ways of reducing the human annotation effort is critical for this task. The objective of this paper is to develop and study new ways of providing human feedback for efficient learning of classification models by labeling groups of examples. Briefly, unlike traditional active learning methods that seek feedback on individual examples, we develop a new group-based active learning framework that solicits label information on groups of multiple examples. In order to describe groups in a user-friendly way, conjunctive patterns are used to compactly represent groups. Our empirical study on 12 UCI data sets demonstrates the advantages and superiority of our approach over both classic instance-based active learning work, as well as existing group-based active-learning methods.

3-Dimensional and Interactive Istanbul University Virtual Laboratory Based on Active Learning Methods

ERIC Educational Resources Information Center

Ince, Elif; Kirbaslar, Fatma Gulay; Yolcu, Ergun; Aslan, Ayse Esra; Kayacan, Zeynep Cigdem; Alkan Olsson, Johanna; Akbasli, Ayse Ceylan; Aytekin, Mesut; Bauer, Thomas; Charalambis, Dimitris; Gunes, Zeliha Ozsoy; Kandemir, Ceyhan; Sari, Umit; Turkoglu, Suleyman; Yaman, Yavuz; Yolcu, Ozgu

2014-01-01

The purpose of this study is to develop a 3-dimensional interactive multi-user and multi-admin IUVIRLAB featuring active learning methods and techniques for university students and to introduce the Virtual Laboratory of Istanbul University and to show effects of IUVIRLAB on students' attitudes on communication skills and IUVIRLAB. Although there…

Graduate Faculty Perceptions of Experiential Learning Activities in Multicultural Classrooms

ERIC Educational Resources Information Center

Su, Yu-Han

2012-01-01

Current graduate programs employ many effective teaching methods. One of these methods, using experiential learning activities (Lee & Caffarella, 1994) in class, includes the subcomponents of cooperative learning, self-directed learning, and active learning. While these methods are commonly used, not much scholarly literature has examined the…

Using Active Learning to Teach Concepts and Methods in Quantitative Biology.

PubMed

Waldrop, Lindsay D; Adolph, Stephen C; Diniz Behn, Cecilia G; Braley, Emily; Drew, Joshua A; Full, Robert J; Gross, Louis J; Jungck, John A; Kohler, Brynja; Prairie, Jennifer C; Shtylla, Blerta; Miller, Laura A

2015-11-01

This article provides a summary of the ideas discussed at the 2015 Annual Meeting of the Society for Integrative and Comparative Biology society-wide symposium on Leading Students and Faculty to Quantitative Biology through Active Learning. It also includes a brief review of the recent advancements in incorporating active learning approaches into quantitative biology classrooms. We begin with an overview of recent literature that shows that active learning can improve students' outcomes in Science, Technology, Engineering and Math Education disciplines. We then discuss how this approach can be particularly useful when teaching topics in quantitative biology. Next, we describe some of the recent initiatives to develop hands-on activities in quantitative biology at both the graduate and the undergraduate levels. Throughout the article we provide resources for educators who wish to integrate active learning and technology into their classrooms. © The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Modelling Typical Online Language Learning Activity

ERIC Educational Resources Information Center

Montoro, Carlos; Hampel, Regine; Stickler, Ursula

2014-01-01

This article presents the methods and results of a four-year-long research project focusing on the language learning activity of individual learners using online tasks conducted at the University of Guanajuato (Mexico) in 2009-2013. An activity-theoretical model (Blin, 2010; Engeström, 1987) of the typical language learning activity was used to…

Research on Mobile Learning Activities Applying Tablets

ERIC Educational Resources Information Center

Kurilovas, Eugenijus; Juskeviciene, Anita; Bireniene, Virginija

2015-01-01

The paper aims to present current research on mobile learning activities in Lithuania while implementing flagship EU-funded CCL project on application of tablet computers in education. In the paper, the quality of modern mobile learning activities based on learning personalisation, problem solving, collaboration, and flipped class methods is…

A Bridge to Active Learning: A Summer Bridge Program Helps Students Maximize Their Active-Learning Experiences and the Active-Learning Experiences of Others.

PubMed

Cooper, Katelyn M; Ashley, Michael; Brownell, Sara E

2017-01-01

National calls to improve student academic success in college have sparked the development of bridge programs designed to help students transition from high school to college. We designed a 2-week Summer Bridge program that taught introductory biology content in an active-learning way. Through a set of exploratory interviews, we unexpectedly identified that Bridge students had developed sophisticated views of active learning, even though this was not an explicit goal of the program. We conducted an additional set of semistructured interviews that focused on active learning and compared the interviews of Bridge students with those from non-Bridge students who had been eligible for but did not participate in the program. We used the constant comparative method to identify themes from the interviews. We found that Bridge students perceived that, because they knew how to approach active learning and viewed it as important, they benefited more from active learning in introductory biology than non-Bridge students. Specifically, Bridge students seemed to be more aware of their own learning gains from participating in active learning. Compared with the majority of non-Bridge students, the majority of Bridge students described using a greater variety of strategies to maximize their experiences in active learning. Finally, in contrast to non-Bridge students, Bridge students indicated that they take an equitable approach to group work. These findings suggest that we may be able to prime students to maximize their own and other's experiences in active learning. © 2017 K. M. Cooper et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

A Novel Teaching Tool Combined With Active-Learning to Teach Antimicrobial Spectrum Activity.

PubMed

MacDougall, Conan

2017-03-25

Objective. To design instructional methods that would promote long-term retention of knowledge of antimicrobial pharmacology, particularly the spectrum of activity for antimicrobial agents, in pharmacy students. Design. An active-learning approach was used to teach selected sessions in a required antimicrobial pharmacology course. Students were expected to review key concepts from the course reader prior to the in-class sessions. During class, brief concept reviews were followed by active-learning exercises, including a novel schematic method for learning antimicrobial spectrum of activity ("flower diagrams"). Assessment. At the beginning of the next quarter (approximately 10 weeks after the in-class sessions), 360 students (three yearly cohorts) completed a low-stakes multiple-choice examination on the concepts in antimicrobial spectrum of activity. When data for students was pooled across years, the mean number of correct items was 75.3% for the items that tested content delivered with the active-learning method vs 70.4% for items that tested content delivered via traditional lecture (mean difference 4.9%). Instructor ratings on student evaluations of the active-learning approach were high (mean scores 4.5-4.8 on a 5-point scale) and student comments were positive about the active-learning approach and flower diagrams. Conclusion. An active-learning approach led to modestly higher scores in a test of long-term retention of pharmacology knowledge and was well-received by students.

A Novel Teaching Tool Combined With Active-Learning to Teach Antimicrobial Spectrum Activity

PubMed Central

2017-01-01

Objective. To design instructional methods that would promote long-term retention of knowledge of antimicrobial pharmacology, particularly the spectrum of activity for antimicrobial agents, in pharmacy students. Design. An active-learning approach was used to teach selected sessions in a required antimicrobial pharmacology course. Students were expected to review key concepts from the course reader prior to the in-class sessions. During class, brief concept reviews were followed by active-learning exercises, including a novel schematic method for learning antimicrobial spectrum of activity (“flower diagrams”). Assessment. At the beginning of the next quarter (approximately 10 weeks after the in-class sessions), 360 students (three yearly cohorts) completed a low-stakes multiple-choice examination on the concepts in antimicrobial spectrum of activity. When data for students was pooled across years, the mean number of correct items was 75.3% for the items that tested content delivered with the active-learning method vs 70.4% for items that tested content delivered via traditional lecture (mean difference 4.9%). Instructor ratings on student evaluations of the active-learning approach were high (mean scores 4.5-4.8 on a 5-point scale) and student comments were positive about the active-learning approach and flower diagrams. Conclusion. An active-learning approach led to modestly higher scores in a test of long-term retention of pharmacology knowledge and was well-received by students. PMID:28381885

The Guided Autobiography Method: A Learning Experience

ERIC Educational Resources Information Center

Thornton, James E.

2008-01-01

This article discusses the proposition that learning is an unexplored feature of the guided autobiography method and its developmental exchange. Learning, conceptualized and explored as the embedded and embodied processes, is essential in narrative activities of the guided autobiography method leading to psychosocial development and growth in…

Influence on Learning of a Collaborative Learning Method Comprising the Jigsaw Method and Problem-based Learning (PBL).

PubMed

Takeda, Kayoko; Takahashi, Kiyoshi; Masukawa, Hiroyuki; Shimamori, Yoshimitsu

2017-01-01

Recently, the practice of active learning has spread, increasingly recognized as an essential component of academic studies. Classes incorporating small group discussion (SGD) are conducted at many universities. At present, assessments of the effectiveness of SGD have mostly involved evaluation by questionnaires conducted by teachers, by peer assessment, and by self-evaluation of students. However, qualitative data, such as open-ended descriptions by students, have not been widely evaluated. As a result, we have been unable to analyze the processes and methods involved in how students acquire knowledge in SGD. In recent years, due to advances in information and communication technology (ICT), text mining has enabled the analysis of qualitative data. We therefore investigated whether the introduction of a learning system comprising the jigsaw method and problem-based learning (PBL) would improve student attitudes toward learning; we did this by text mining analysis of the content of student reports. We found that by applying the jigsaw method before PBL, we were able to improve student attitudes toward learning and increase the depth of their understanding of the area of study as a result of working with others. The use of text mining to analyze qualitative data also allowed us to understand the processes and methods by which students acquired knowledge in SGD and also changes in students' understanding and performance based on improvements to the class. This finding suggests that the use of text mining to analyze qualitative data could enable teachers to evaluate the effectiveness of various methods employed to improve learning.

Feasibility of Active Machine Learning for Multiclass Compound Classification.

PubMed

Lang, Tobias; Flachsenberg, Florian; von Luxburg, Ulrike; Rarey, Matthias

2016-01-25

A common task in the hit-to-lead process is classifying sets of compounds into multiple, usually structural classes, which build the groundwork for subsequent SAR studies. Machine learning techniques can be used to automate this process by learning classification models from training compounds of each class. Gathering class information for compounds can be cost-intensive as the required data needs to be provided by human experts or experiments. This paper studies whether active machine learning can be used to reduce the required number of training compounds. Active learning is a machine learning method which processes class label data in an iterative fashion. It has gained much attention in a broad range of application areas. In this paper, an active learning method for multiclass compound classification is proposed. This method selects informative training compounds so as to optimally support the learning progress. The combination with human feedback leads to a semiautomated interactive multiclass classification procedure. This method was investigated empirically on 15 compound classification tasks containing 86-2870 compounds in 3-38 classes. The empirical results show that active learning can solve these classification tasks using 10-80% of the data which would be necessary for standard learning techniques.

An Evaluation of Active Learning Causal Discovery Methods for Reverse-Engineering Local Causal Pathways of Gene Regulation

PubMed Central

Ma, Sisi; Kemmeren, Patrick; Aliferis, Constantin F.; Statnikov, Alexander

2016-01-01

Reverse-engineering of causal pathways that implicate diseases and vital cellular functions is a fundamental problem in biomedicine. Discovery of the local causal pathway of a target variable (that consists of its direct causes and direct effects) is essential for effective intervention and can facilitate accurate diagnosis and prognosis. Recent research has provided several active learning methods that can leverage passively observed high-throughput data to draft causal pathways and then refine the inferred relations with a limited number of experiments. The current study provides a comprehensive evaluation of the performance of active learning methods for local causal pathway discovery in real biological data. Specifically, 54 active learning methods/variants from 3 families of algorithms were applied for local causal pathways reconstruction of gene regulation for 5 transcription factors in S. cerevisiae. Four aspects of the methods’ performance were assessed, including adjacency discovery quality, edge orientation accuracy, complete pathway discovery quality, and experimental cost. The results of this study show that some methods provide significant performance benefits over others and therefore should be routinely used for local causal pathway discovery tasks. This study also demonstrates the feasibility of local causal pathway reconstruction in real biological systems with significant quality and low experimental cost. PMID:26939894

Creating Stimulating Learning and Thinking Using New Models of Activity-Based Learning and Metacognitive-Based Activities

ERIC Educational Resources Information Center

Pang, Katherine

2010-01-01

The purpose of this paper is to present a novel way to stimulate learning, creativity, and thinking based on a new understanding of activity-based learning (ABL) and two methods for developing metacognitive-based activities for the classroom. ABL, in this model, is based on the premise that teachers are distillers and facilitators of information…

Semantic-gap-oriented active learning for multilabel image annotation.

PubMed

Tang, Jinhui; Zha, Zheng-Jun; Tao, Dacheng; Chua, Tat-Seng

2012-04-01

User interaction is an effective way to handle the semantic gap problem in image annotation. To minimize user effort in the interactions, many active learning methods were proposed. These methods treat the semantic concepts individually or correlatively. However, they still neglect the key motivation of user feedback: to tackle the semantic gap. The size of the semantic gap of each concept is an important factor that affects the performance of user feedback. User should pay more efforts to the concepts with large semantic gaps, and vice versa. In this paper, we propose a semantic-gap-oriented active learning method, which incorporates the semantic gap measure into the information-minimization-based sample selection strategy. The basic learning model used in the active learning framework is an extended multilabel version of the sparse-graph-based semisupervised learning method that incorporates the semantic correlation. Extensive experiments conducted on two benchmark image data sets demonstrated the importance of bringing the semantic gap measure into the active learning process.

Use of Web Technology and Active Learning Strategies in a Quality Assessment Methods Course.

ERIC Educational Resources Information Center

Poirier, Therese I.; O'Neil, Christine K.

2000-01-01

The authors describe and evaluate quality assessment methods in a health care course that utilized web technology and various active learning strategies. The course was judged successful by student performance, evaluations and student assessments. The instructors were pleased with the outcomes achieved and the educational pedagogy used for this…

Diverse expected gradient active learning for relative attributes.

PubMed

You, Xinge; Wang, Ruxin; Tao, Dacheng

2014-07-01

The use of relative attributes for semantic understanding of images and videos is a promising way to improve communication between humans and machines. However, it is extremely labor- and time-consuming to define multiple attributes for each instance in large amount of data. One option is to incorporate active learning, so that the informative samples can be actively discovered and then labeled. However, most existing active-learning methods select samples one at a time (serial mode), and may therefore lose efficiency when learning multiple attributes. In this paper, we propose a batch-mode active-learning method, called diverse expected gradient active learning. This method integrates an informativeness analysis and a diversity analysis to form a diverse batch of queries. Specifically, the informativeness analysis employs the expected pairwise gradient length as a measure of informativeness, while the diversity analysis forces a constraint on the proposed diverse gradient angle. Since simultaneous optimization of these two parts is intractable, we utilize a two-step procedure to obtain the diverse batch of queries. A heuristic method is also introduced to suppress imbalanced multiclass distributions. Empirical evaluations of three different databases demonstrate the effectiveness and efficiency of the proposed approach.

Diverse Expected Gradient Active Learning for Relative Attributes.

PubMed

You, Xinge; Wang, Ruxin; Tao, Dacheng

2014-06-02

The use of relative attributes for semantic understanding of images and videos is a promising way to improve communication between humans and machines. However, it is extremely labor- and time-consuming to define multiple attributes for each instance in large amount of data. One option is to incorporate active learning, so that the informative samples can be actively discovered and then labeled. However, most existing active-learning methods select samples one at a time (serial mode), and may therefore lose efficiency when learning multiple attributes. In this paper, we propose a batch-mode active-learning method, called Diverse Expected Gradient Active Learning (DEGAL). This method integrates an informativeness analysis and a diversity analysis to form a diverse batch of queries. Specifically, the informativeness analysis employs the expected pairwise gradient length as a measure of informativeness, while the diversity analysis forces a constraint on the proposed diverse gradient angle. Since simultaneous optimization of these two parts is intractable, we utilize a two-step procedure to obtain the diverse batch of queries. A heuristic method is also introduced to suppress imbalanced multi-class distributions. Empirical evaluations of three different databases demonstrate the effectiveness and efficiency of the proposed approach.

Implementing Collaborative Learning Methods in the Political Science Classroom

ERIC Educational Resources Information Center

Wolfe, Angela

2012-01-01

Collaborative learning is one, among other, active learning methods, widely acclaimed in higher education. Consequently, instructors in fields that lack pedagogical training often implement new learning methods such as collaborative learning on the basis of trial and error. Moreover, even though the benefits in academic circles are broadly touted,…

A Scale Development for Teacher Competencies on Cooperative Learning Method

ERIC Educational Resources Information Center

Kocabas, Ayfer; Erbil, Deniz Gokce

2017-01-01

Cooperative learning method is a learning method studied both in Turkey and in the world for long years as an active learning method. Although cooperative learning method takes place in training programs, it cannot be implemented completely in the direction of its principles. The results of the researches point out that teachers have problems with…

Comparison of Feature Learning Methods for Human Activity Recognition Using Wearable Sensors

PubMed Central

Li, Frédéric; Nisar, Muhammad Adeel; Köping, Lukas; Grzegorzek, Marcin

2018-01-01

Getting a good feature representation of data is paramount for Human Activity Recognition (HAR) using wearable sensors. An increasing number of feature learning approaches—in particular deep-learning based—have been proposed to extract an effective feature representation by analyzing large amounts of data. However, getting an objective interpretation of their performances faces two problems: the lack of a baseline evaluation setup, which makes a strict comparison between them impossible, and the insufficiency of implementation details, which can hinder their use. In this paper, we attempt to address both issues: we firstly propose an evaluation framework allowing a rigorous comparison of features extracted by different methods, and use it to carry out extensive experiments with state-of-the-art feature learning approaches. We then provide all the codes and implementation details to make both the reproduction of the results reported in this paper and the re-use of our framework easier for other researchers. Our studies carried out on the OPPORTUNITY and UniMiB-SHAR datasets highlight the effectiveness of hybrid deep-learning architectures involving convolutional and Long-Short-Term-Memory (LSTM) to obtain features characterising both short- and long-term time dependencies in the data. PMID:29495310

Comparison of Feature Learning Methods for Human Activity Recognition Using Wearable Sensors.

PubMed

Li, Frédéric; Shirahama, Kimiaki; Nisar, Muhammad Adeel; Köping, Lukas; Grzegorzek, Marcin

2018-02-24

Getting a good feature representation of data is paramount for Human Activity Recognition (HAR) using wearable sensors. An increasing number of feature learning approaches-in particular deep-learning based-have been proposed to extract an effective feature representation by analyzing large amounts of data. However, getting an objective interpretation of their performances faces two problems: the lack of a baseline evaluation setup, which makes a strict comparison between them impossible, and the insufficiency of implementation details, which can hinder their use. In this paper, we attempt to address both issues: we firstly propose an evaluation framework allowing a rigorous comparison of features extracted by different methods, and use it to carry out extensive experiments with state-of-the-art feature learning approaches. We then provide all the codes and implementation details to make both the reproduction of the results reported in this paper and the re-use of our framework easier for other researchers. Our studies carried out on the OPPORTUNITY and UniMiB-SHAR datasets highlight the effectiveness of hybrid deep-learning architectures involving convolutional and Long-Short-Term-Memory (LSTM) to obtain features characterising both short- and long-term time dependencies in the data.

Active-Learning Processes Used in US Pharmacy Education

PubMed Central

Brown, Stacy D.; Clavier, Cheri W.; Wyatt, Jarrett

2011-01-01

Objective To document the type and extent of active-learning techniques used in US colleges and schools of pharmacy as well as factors associated with use of these techniques. Methods A survey instrument was developed to assess whether and to what extent active learning was used by faculty members of US colleges and schools of pharmacy. This survey instrument was distributed via the American Association of Colleges of Pharmacy (AACP) mailing list. Results Ninety-five percent (114) of all US colleges and schools of pharmacy were represented with at least 1 survey among the 1179 responses received. Eighty-seven percent of respondents used active-learning techniques in their classroom activities. The heavier the teaching workload the more active-learning strategies were used. Other factors correlated with higher use of active-learning strategies included younger faculty member age (inverse relationship), lower faculty member rank (inverse relationship), and departments that focused on practice, clinical and social, behavioral, and/or administrative sciences. Conclusions Active learning has been embraced by pharmacy educators and is used to some extent by the majority of US colleges and schools of pharmacy. Future research should focus on how active-learning methods can be used most effectively within pharmacy education, how it can gain even broader acceptance throughout the academy, and how the effect of active learning on programmatic outcomes can be better documented. PMID:21769144

Active Learning with Irrelevant Examples

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri; Mazzoni, Dominic

2009-01-01

An improved active learning method has been devised for training data classifiers. One example of a data classifier is the algorithm used by the United States Postal Service since the 1960s to recognize scans of handwritten digits for processing zip codes. Active learning algorithms enable rapid training with minimal investment of time on the part of human experts to provide training examples consisting of correctly classified (labeled) input data. They function by identifying which examples would be most profitable for a human expert to label. The goal is to maximize classifier accuracy while minimizing the number of examples the expert must label. Although there are several well-established methods for active learning, they may not operate well when irrelevant examples are present in the data set. That is, they may select an item for labeling that the expert simply cannot assign to any of the valid classes. In the context of classifying handwritten digits, the irrelevant items may include stray marks, smudges, and mis-scans. Querying the expert about these items results in wasted time or erroneous labels, if the expert is forced to assign the item to one of the valid classes. In contrast, the new algorithm provides a specific mechanism for avoiding querying the irrelevant items. This algorithm has two components: an active learner (which could be a conventional active learning algorithm) and a relevance classifier. The combination of these components yields a method, denoted Relevance Bias, that enables the active learner to avoid querying irrelevant data so as to increase its learning rate and efficiency when irrelevant items are present. The algorithm collects irrelevant data in a set of rejected examples, then trains the relevance classifier to distinguish between labeled (relevant) training examples and the rejected ones. The active learner combines its ranking of the items with the probability that they are relevant to yield a final decision about which item

A ranking method for the concurrent learning of compounds with various activity profiles.

PubMed

Dörr, Alexander; Rosenbaum, Lars; Zell, Andreas

2015-01-01

In this study, we present a SVM-based ranking algorithm for the concurrent learning of compounds with different activity profiles and their varying prioritization. To this end, a specific labeling of each compound was elaborated in order to infer virtual screening models against multiple targets. We compared the method with several state-of-the-art SVM classification techniques that are capable of inferring multi-target screening models on three chemical data sets (cytochrome P450s, dehydrogenases, and a trypsin-like protease data set) containing three different biological targets each. The experiments show that ranking-based algorithms show an increased performance for single- and multi-target virtual screening. Moreover, compounds that do not completely fulfill the desired activity profile are still ranked higher than decoys or compounds with an entirely undesired profile, compared to other multi-target SVM methods. SVM-based ranking methods constitute a valuable approach for virtual screening in multi-target drug design. The utilization of such methods is most helpful when dealing with compounds with various activity profiles and the finding of many ligands with an already perfectly matching activity profile is not to be expected.

Impact of a novel teaching method based on feedback, activity, individuality and relevance on students’ learning

PubMed Central

Brooks, William S.; Laskar, Simone N.; Benjamin, Miles W.; Chan, Philip

2016-01-01

Objectives This study examines the perceived impact of a novel clinical teaching method based on FAIR principles (feedback, activity, individuality and relevance) on students’ learning on clinical placement. Methods This was a qualitative research study. Participants were third year and final year medical students attached to one UK vascular firm over a four-year period (N=108). Students were asked to write a reflective essay on how FAIRness approach differs from previous clinical placement, and its advantages and disadvantages. Essays were thematically analysed and globally rated (positive, negative or neutral) by two independent researchers. Results Over 90% of essays reported positive experiences of feedback, activity, individuality and relevance model.  The model provided multifaceted feedback; active participation; longitudinal improvement; relevance to stage of learning and future goals; structured teaching; professional development; safe learning environment; consultant involvement in teaching. Students perceived preparation for tutorials to be time intensive for tutors/students; a lack of teaching on medical sciences and direct observation of performance; more than once weekly sessions would be beneficial; some issues with peer and public feedback, relevance to upcoming exam and large group sizes. Students described negative experiences of “standard” clinical teaching. Conclusions Progressive teaching programmes based on the FAIRness principles, feedback, activity, individuality and relevance, could be used as a model to improve current undergraduate clinical teaching. PMID:26995588

Attitudes of Face-to-Face and E-Learning Instructors toward "Active Learning"

ERIC Educational Resources Information Center

Pundak, David; Herscovitz, Orit; Shacham, Miri

2010-01-01

Instruction in higher education has developed significantly over the past two decades, influenced by two trends: promotion of active learning methods and integration of web technology in e-Learning. Many studies found that active teaching improves students' success, involvement and thinking skills. Nevertheless, internationally, most instructors…

STEM learning activity among home-educating families

NASA Astrophysics Data System (ADS)

Bachman, Jennifer

2011-12-01

Science, technology, engineering, and mathematics (STEM) learning was studied among families in a group of home-educators in the Pacific Northwest. Ethnographic methods recorded learning activity (video, audio, fieldnotes, and artifacts) which was analyzed using a unique combination of Cultural-Historical Activity Theory (CHAT) and Mediated Action (MA), enabling analysis of activity at multiple levels. Findings indicate that STEM learning activity is family-led, guided by parents' values and goals for learning, and negotiated with children to account for learner interests and differences, and available resources. Families' STEM education practice is dynamic, evolves, and influenced by larger societal STEM learning activity. Parents actively seek support and resources for STEM learning within their home-school community, working individually and collectively to share their funds of knowledge. Home-schoolers also access a wide variety of free-choice learning resources: web-based materials, museums, libraries, and community education opportunities (e.g. afterschool, weekend and summer programs, science clubs and classes, etc.). A lesson-heuristic, grounded in Mediated Action, represents and analyzes home STEM learning activity in terms of tensions between parental goals, roles, and lesson structure. One tension observed was between 'academic' goals or school-like activity and 'lifelong' goals or everyday learning activity. Theoretical and experiential learning was found in both activity, though parents with academic goals tended to focus more on theoretical learning and those with lifelong learning goals tended to be more experiential. Examples of the National Research Council's science learning strands (NRC, 2009) were observed in the STEM practices of all these families. Findings contribute to the small but growing body of empirical CHAT research in science education, specifically to the empirical base of family STEM learning practices at home. It also fills a

Aligning Professional Skills and Active Learning Methods: An Application for Information and Communications Technology Engineering

ERIC Educational Resources Information Center

Llorens, Ariadna; Berbegal-Mirabent, Jasmina; Llinàs-Audet, Xavier

2017-01-01

Engineering education is facing new challenges to effectively provide the appropriate skills to future engineering professionals according to market demands. This study proposes a model based on active learning methods, which is expected to facilitate the acquisition of the professional skills most highly valued in the information and…

Captivate: Building Blocks for Implementing Active Learning

ERIC Educational Resources Information Center

Kitchens, Brent; Means, Tawnya; Tan, Yinliang

2018-01-01

In this study, the authors propose a set of key elements that impact the success of an active learning implementation: content delivery, active learning methods, physical environment, technology enhancement, incentive alignment, and educator investment. Through a range of metrics the authors present preliminary evidence that students in courses…

Machine learning methods in chemoinformatics

PubMed Central

Mitchell, John B O

2014-01-01

Machine learning algorithms are generally developed in computer science or adjacent disciplines and find their way into chemical modeling by a process of diffusion. Though particular machine learning methods are popular in chemoinformatics and quantitative structure–activity relationships (QSAR), many others exist in the technical literature. This discussion is methods-based and focused on some algorithms that chemoinformatics researchers frequently use. It makes no claim to be exhaustive. We concentrate on methods for supervised learning, predicting the unknown property values of a test set of instances, usually molecules, based on the known values for a training set. Particularly relevant approaches include Artificial Neural Networks, Random Forest, Support Vector Machine, k-Nearest Neighbors and naïve Bayes classifiers. WIREs Comput Mol Sci 2014, 4:468–481. How to cite this article: WIREs Comput Mol Sci 2014, 4:468–481. doi:10.1002/wcms.1183 PMID:25285160

A Tool for Measuring Active Learning in the Classroom

PubMed Central

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

2007-01-01

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

Student Reciprocal Peer Teaching as a Method for Active Learning: An Experience in an Electrotechnical Laboratory

NASA Astrophysics Data System (ADS)

Muñoz-García, Miguel A.; Moreda, Guillermo P.; Hernández-Sánchez, Natalia; Valiño, Vanesa

2013-10-01

Active learning is one of the most efficient mechanisms for learning, according to the psychology of learning. When students act as teachers for other students, the communication is more fluent and knowledge is transferred easier than in a traditional classroom. This teaching method is referred to in the literature as reciprocal peer teaching. In this study, the method is applied to laboratory sessions of a higher education institution course, and the students who act as teachers are referred to as "laboratory monitors." A particular way to select the monitors and its impact in the final marks is proposed. A total of 181 students participated in the experiment, experiences with laboratory monitors are discussed, and methods for motivating and training laboratory monitors and regular students are proposed. The types of laboratory sessions that can be led by classmates are discussed. This work is related to the changes in teaching methods in the Spanish higher education system, prompted by the Bologna Process for the construction of the European Higher Education Area

Assessing Student Behaviors and Motivation for Actively Learning Biology

ERIC Educational Resources Information Center

Moore, Michael Edward

2017-01-01

Vision and Change states that one of the major changes in the way we design biology courses should be a switch in approach from teacher-centered learning to student-centered learning and identifies active learning as a recommended methods. Studies show performance benefits for students taking courses that use active learning. What is unknown is…

Generalized query-based active learning to identify differentially methylated regions in DNA.

PubMed

Haque, Md Muksitul; Holder, Lawrence B; Skinner, Michael K; Cook, Diane J

2013-01-01

Active learning is a supervised learning technique that reduces the number of examples required for building a successful classifier, because it can choose the data it learns from. This technique holds promise for many biological domains in which classified examples are expensive and time-consuming to obtain. Most traditional active learning methods ask very specific queries to the Oracle (e.g., a human expert) to label an unlabeled example. The example may consist of numerous features, many of which are irrelevant. Removing such features will create a shorter query with only relevant features, and it will be easier for the Oracle to answer. We propose a generalized query-based active learning (GQAL) approach that constructs generalized queries based on multiple instances. By constructing appropriately generalized queries, we can achieve higher accuracy compared to traditional active learning methods. We apply our active learning method to find differentially DNA methylated regions (DMRs). DMRs are DNA locations in the genome that are known to be involved in tissue differentiation, epigenetic regulation, and disease. We also apply our method on 13 other data sets and show that our method is better than another popular active learning technique.

[Which learning methods are expected for ultrasound training? Blended learning on trial].

PubMed

Röhrig, S; Hempel, D; Stenger, T; Armbruster, W; Seibel, A; Walcher, F; Breitkreutz, R

2014-10-01

Current teaching methods in graduate and postgraduate training often include frontal presentations. Especially in ultrasound education not only knowledge but also sensomotory and visual skills need to be taught. This requires new learning methods. This study examined which types of teaching methods are preferred by participants in ultrasound training courses before, during and after the course by analyzing a blended learning concept. It also investigated how much time trainees are willing to spend on such activities. A survey was conducted at the end of a certified ultrasound training course. Participants were asked to complete a questionnaire based on a visual analogue scale (VAS) in which three categories were defined: category (1) vote for acceptance with a two thirds majority (VAS 67-100%), category (2) simple acceptance (50-67%) and category (3) rejection (< 50%). A total of 176 trainees participated in this survey. Participants preferred an e-learning program with interactive elements, short presentations (less than 20 min), incorporating interaction with the audience, hands-on sessions in small groups, an alternation between presentations and hands-on-sessions, live demonstrations and quizzes. For post-course learning, interactive and media-assisted approaches were preferred, such as e-learning, films of the presentations and the possibility to stay in contact with instructors in order to discuss the results. Participants also voted for maintaining a logbook for documentation of results. The results of this study indicate the need for interactive learning concepts and blended learning activities. Directors of ultrasound courses may consider these aspects and are encouraged to develop sustainable learning pathways.

A Qualitative Research on Active Learning Practices in Pre-School Education

ERIC Educational Resources Information Center

Pekdogan, Serpil; Kanak, Mehmet

2016-01-01

In educational environments prepared based on the active learning method, children learn with interest and pleasure, doing and experiencing, and directly through their own experiences. Considering the contributions of the active learning method and the educational environments designed based on it to children's development, it can be said that…

Animal-Centered Learning Activities in Pharmacy Education

PubMed Central

Lust, Elaine

2006-01-01

Objectives To assess the contribution of animal-centered activities to students achieving learning outcomes in a veterinary therapeutics course. Design Qualitative methods were used to assess the outcome of using “hands-on” animal interactions as tools of engagement in the course. Reflective commentary on animal-centered activities was collected and analyzed. Assessment Animal-centered learning activities are effective tools for engaging students and facilitating their understanding and application of veterinary therapeutic knowledge, skills, and attitudes. Analysis of qualitative data revealed themes of professional caring and caring behaviors as a direct result of animal-centered activities. Elements of empathy, caring, compassion, and self-awareness were strong undercurrents in student's comments. Conclusions Animal-centered learning activities provide an innovative learning environment for the application of veterinary pharmacy knowledge, skills, and attitudes directly to animal patients. The use of animals in the course is a successful active-learning technique to engage pharmacy students and assist them in developing caring attitudes and behaviors beneficial to future health care providers. PMID:17149415

Successful Application of Active Learning Techniques to Introductory Microbiology.

ERIC Educational Resources Information Center

Hoffman, Elizabeth A.

2001-01-01

Points out the low student achievement in microbiology courses and presents an active learning method applied in an introductory microbiology course which features daily quizzes, cooperative learning activities, and group projects. (Contains 30 references.) (YDS)

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

Impact of a novel teaching method based on feedback, activity, individuality and relevance on students' learning.

PubMed

Edafe, Ovie; Brooks, William S; Laskar, Simone N; Benjamin, Miles W; Chan, Philip

2016-03-20

This study examines the perceived impact of a novel clinical teaching method based on FAIR principles (feedback, activity, individuality and relevance) on students' learning on clinical placement. This was a qualitative research study. Participants were third year and final year medical students attached to one UK vascular firm over a four-year period (N=108). Students were asked to write a reflective essay on how FAIRness approach differs from previous clinical placement, and its advantages and disadvantages. Essays were thematically analysed and globally rated (positive, negative or neutral) by two independent researchers. Over 90% of essays reported positive experiences of feedback, activity, individuality and relevance model. The model provided multifaceted feedback; active participation; longitudinal improvement; relevance to stage of learning and future goals; structured teaching; professional development; safe learning environment; consultant involvement in teaching. Students perceived preparation for tutorials to be time intensive for tutors/students; a lack of teaching on medical sciences and direct observation of performance; more than once weekly sessions would be beneficial; some issues with peer and public feedback, relevance to upcoming exam and large group sizes. Students described negative experiences of "standard" clinical teaching. Progressive teaching programmes based on the FAIRness principles, feedback, activity, individuality and relevance, could be used as a model to improve current undergraduate clinical teaching.

Active Learning in the Physics Classroom

NASA Astrophysics Data System (ADS)

Naron, Carol

Many students enter physics classes filled with misconceptions about physics concepts. Students tend to retain these misconceptions into their adult lives, even after physics instruction. Constructivist researchers have found that students gain understanding through their experiences. Researchers have also found that active learning practices increase conceptual understanding of introductory physics students. This project study sought to examine whether incorporating active learning practices in an advanced placement physics classroom increased conceptual understanding as measured by the force concept inventory (FCI). Physics students at the study site were given the FCI as both a pre- and posttest. Test data were analyzed using two different methods---a repeated-measures t test and the Hake gain method. The results of this research project showed that test score gains were statistically significant, as measured by the t test. The Hake gain results indicated a low (22.5%) gain for the class. The resulting project was a curriculum plan for teaching the mechanics portion of Advanced Placement (AP) physics B as well as several active learning classroom practices supported by the research. This project will allow AP physics teachers an opportunity to improve their curricular practices. Locally, the results of this project study showed that research participants gained understanding of physics concepts. Social change may occur as teachers implement active learning strategies, thus creating improved student understanding of physics concepts.

Active learning in the presence of unlabelable examples

NASA Technical Reports Server (NTRS)

Mazzoni, Dominic; Wagstaff, Kiri

2004-01-01

We propose a new active learning framework where the expert labeler is allowed to decline to label any example. This may be necessary because the true label is unknown or because the example belongs to a class that is not part of the real training problem. We show that within this framework, popular active learning algorithms (such as Simple) may perform worse than random selection because they make so many queries to the unlabelable class. We present a method by which any active learning algorithm can be modified to avoid unlabelable examples by training a second classifier to distinguish between the labelable and unlabelable classes. We also demonstrate the effectiveness of the method on two benchmark data sets and a real-world problem.

Active Learning and Cooperative Learning in the Organic Chemistry Lecture Class

NASA Astrophysics Data System (ADS)

Paulson, Donald R.

1999-08-01

Faculty in the physical sciences are one of the academic groups least receptive to the use of active learning strategies and cooperative learning in their classrooms. This is particularly so in traditional lecture classes. It is the objective of this paper to show how effective these techniques can be in improving student performance in classes. The use of active learning strategies and cooperative learning groups in my organic chemistry lecture classes has increased the overall pass rate in my classes by an astounding 20-30% over the traditional lecture mode. This has been accomplished without any reduction in "standards". The actual methods employed are presented as well as a discussion of how I came to radically change the way I teach my classes.

Active-learning processes used in US pharmacy education.

PubMed

Stewart, David W; Brown, Stacy D; Clavier, Cheri W; Wyatt, Jarrett

2011-05-10

To document the type and extent of active-learning techniques used in US colleges and schools of pharmacy as well as factors associated with use of these techniques. A survey instrument was developed to assess whether and to what extent active learning was used by faculty members of US colleges and schools of pharmacy. This survey instrument was distributed via the American Association of Colleges of Pharmacy (AACP) mailing list. Ninety-five percent (114) of all US colleges and schools of pharmacy were represented with at least 1 survey among the 1179 responses received. Eighty-seven percent of respondents used active-learning techniques in their classroom activities. The heavier the teaching workload the more active-learning strategies were used. Other factors correlated with higher use of active-learning strategies included younger faculty member age (inverse relationship), lower faculty member rank (inverse relationship), and departments that focused on practice, clinical and social, behavioral, and/or administrative sciences. Active learning has been embraced by pharmacy educators and is used to some extent by the majority of US colleges and schools of pharmacy. Future research should focus on how active-learning methods can be used most effectively within pharmacy education, how it can gain even broader acceptance throughout the academy, and how the effect of active learning on programmatic outcomes can be better documented.

Active Learning Promoting Student Teachers' Professional Competences in Finland and Turkey

ERIC Educational Resources Information Center

Niemi, Hannele; Nevgi, Anne; Aksit, Fisun

2016-01-01

This study investigates student teachers' active learning experiences in teacher education (TE) in Finnish and Turkish contexts and attempts to determine how active learning methods' impact student teachers' professional competences. Student teachers (N = 728) assessed their active learning experiences and the professional competences they…

Status of the Usage of Active Learning and Teaching Method and Techniques by Social Studies Teachers

ERIC Educational Resources Information Center

Akman, Özkan

2016-01-01

The purpose of this study was to determine the active learning and teaching methods and techniques which are employed by the social studies teachers working in state schools of Turkey. This usage status was assessed using different variables. This was a case study, wherein the research was limited to 241 social studies teachers. These teachers…

Active Learning Strategies for Phenotypic Profiling of High-Content Screens.

PubMed

Smith, Kevin; Horvath, Peter

2014-06-01

High-content screening is a powerful method to discover new drugs and carry out basic biological research. Increasingly, high-content screens have come to rely on supervised machine learning (SML) to perform automatic phenotypic classification as an essential step of the analysis. However, this comes at a cost, namely, the labeled examples required to train the predictive model. Classification performance increases with the number of labeled examples, and because labeling examples demands time from an expert, the training process represents a significant time investment. Active learning strategies attempt to overcome this bottleneck by presenting the most relevant examples to the annotator, thereby achieving high accuracy while minimizing the cost of obtaining labeled data. In this article, we investigate the impact of active learning on single-cell-based phenotype recognition, using data from three large-scale RNA interference high-content screens representing diverse phenotypic profiling problems. We consider several combinations of active learning strategies and popular SML methods. Our results show that active learning significantly reduces the time cost and can be used to reveal the same phenotypic targets identified using SML. We also identify combinations of active learning strategies and SML methods which perform better than others on the phenotypic profiling problems we studied. © 2014 Society for Laboratory Automation and Screening.

An active role for machine learning in drug development

PubMed Central

Murphy, Robert F.

2014-01-01

Due to the complexity of biological systems, cutting-edge machine-learning methods will be critical for future drug development. In particular, machine-vision methods to extract detailed information from imaging assays and active-learning methods to guide experimentation will be required to overcome the dimensionality problem in drug development. PMID:21587249

Active Learning Strategies and Assessment in World Geography Classes

ERIC Educational Resources Information Center

Klein, Phil

2003-01-01

Active learning strategies include a variety of methods, such as inquiry and discovery, in which students are actively engaged in the learning process. This article describes several strategies that can be used in secondary-or college-level world geography courses. The goal of these activities is to foster development of a spatial perspective in…

Research-based active-learning instruction in physics

NASA Astrophysics Data System (ADS)

Meltzer, David E.; Thornton, Ronald K.

2013-04-01

The development of research-based active-learning instructional methods in physics has significantly altered the landscape of U.S. physics education during the past 20 years. Based on a recent review [D.E. Meltzer and R.K. Thornton, Am. J. Phys. 80, 478 (2012)], we define these methods as those (1) explicitly based on research in the learning and teaching of physics, (2) that incorporate classroom and/or laboratory activities that require students to express their thinking through speaking, writing, or other actions that go beyond listening and the copying of notes, or execution of prescribed procedures, and (3) that have been tested repeatedly in actual classroom settings and have yielded objective evidence of improved student learning. We describe some key features common to methods in current use. These features focus on (a) recognizing and addressing students' physics ideas, and (b) guiding students to solve problems in realistic physical settings, in novel and diverse contexts, and to justify or explain the reasoning they have used.

Finite Element Learning Modules as Active Learning Tools

ERIC Educational Resources Information Center

Brown, Ashland O.; Jensen, Daniel; Rencis, Joseph; Wood, Kristin; Wood, John; White, Christina; Raaberg, Kristen Kaufman; Coffman, Josh

2012-01-01

The purpose of active learning is to solicit participation by students beyond the passive mode of traditional classroom lectures. Reading, writing, participating in discussions, hands-on activities, engaging in active problem solving, and collaborative learning can all be involved. The skills acquired during active learning tend to go above and…

Faculty motivations to use active learning among pharmacy educators.

PubMed

Rockich-Winston, Nicole; Train, Brian C; Rudolph, Michael J; Gillette, Chris

2018-03-01

Faculty motivations to use active learning have been limited to surveys evaluating faculty perceptions within active learning studies. Our objective in this study was to evaluate the relationship between faculty intrinsic motivation, extrinsic motivation, and demographic variables and the extent of active learning use in the classroom. An online survey was administered to individual faculty members at 137 colleges and schools of pharmacy across the United States. The survey assessed intrinsic and extrinsic motivations, active learning strategies, classroom time dedicated to active learning, and faculty development resources. Bivariate associations and multivariable stepwise linear regression were used to analyze the results. In total, 979 faculty members completed the questionnaire (23.6% response rate). All motivation variables were significantly correlated with percent active learning use (p < 0.001). Intrinsic motivation demonstrated the highest correlation (r = 0.447) followed by current extrinsic motivations (r = 0.245) and ideal extrinsic motivations (r = 0.291). Variables associated with higher intrinsic motivation included the number of resources used (r = 0.233, p < 0.001) and the number of active learning methods used in the last year (r = 0.259, p < 0.001). Years of teaching experience was negatively associated with intrinsic motivation (r = -0.177, p < 0.001). Regression analyses confirmed the importance of intrinsic and extrinsic motivations in predicting active learning use. Our results suggest that faculty members who are intrinsically motivated to use active learning are more likely to dedicate additional class time to active learning. Furthermore, intrinsic motivation may be positively associated with encouraging faculty members to attend active learning workshops and supporting faculty to use various active learning strategies in the classroom. Copyright © 2017 Elsevier Inc. All rights reserved.

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

Active learning for noisy oracle via density power divergence.

PubMed

Sogawa, Yasuhiro; Ueno, Tsuyoshi; Kawahara, Yoshinobu; Washio, Takashi

2013-10-01

The accuracy of active learning is critically influenced by the existence of noisy labels given by a noisy oracle. In this paper, we propose a novel pool-based active learning framework through robust measures based on density power divergence. By minimizing density power divergence, such as β-divergence and γ-divergence, one can estimate the model accurately even under the existence of noisy labels within data. Accordingly, we develop query selecting measures for pool-based active learning using these divergences. In addition, we propose an evaluation scheme for these measures based on asymptotic statistical analyses, which enables us to perform active learning by evaluating an estimation error directly. Experiments with benchmark datasets and real-world image datasets show that our active learning scheme performs better than several baseline methods. Copyright © 2013 Elsevier Ltd. All rights reserved.

Understanding Fatty Acid Metabolism through an Active Learning Approach

ERIC Educational Resources Information Center

Fardilha, M.; Schrader, M.; da Cruz e Silva, O. A. B.; da Cruz e Silva, E. F.

2010-01-01

A multi-method active learning approach (MALA) was implemented in the Medical Biochemistry teaching unit of the Biomedical Sciences degree at the University of Aveiro, using problem-based learning as the main learning approach. In this type of learning strategy, students are involved beyond the mere exercise of being taught by listening. Less…

Comparing the Effectiveness of Traditional and Active Learning Methods in Business Statistics: Convergence to the Mean

ERIC Educational Resources Information Center

Weltman, David; Whiteside, Mary

2010-01-01

This research shows that active learning is not universally effective and, in fact, may inhibit learning for certain types of students. The results of this study show that as increased levels of active learning are utilized, student test scores decrease for those with a high grade point average. In contrast, test scores increase as active learning…

Assessing Student Behaviors and Motivation for Actively Learning Biology

NASA Astrophysics Data System (ADS)

Moore, Michael Edward

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

Active-learning strategies: the use of a game to reinforce learning in nursing education. A case study.

PubMed

Boctor, Lisa

2013-03-01

The majority of nursing students are kinesthetic learners, preferring a hands-on, active approach to education. Research shows that active-learning strategies can increase student learning and satisfaction. This study looks at the use of one active-learning strategy, a Jeopardy-style game, 'Nursopardy', to reinforce Fundamentals of Nursing material, aiding in students' preparation for a standardized final exam. The game was created keeping students varied learning styles and the NCLEX blueprint in mind. The blueprint was used to create 5 categories, with 26 total questions. Student survey results, using a five-point Likert scale showed that they did find this learning method enjoyable and beneficial to learning. More research is recommended regarding learning outcomes, when using active-learning strategies, such as games. Copyright © 2012 Elsevier Ltd. All rights reserved.

Semi-Supervised Active Learning for Sound Classification in Hybrid Learning Environments.

PubMed

Han, Wenjing; Coutinho, Eduardo; Ruan, Huabin; Li, Haifeng; Schuller, Björn; Yu, Xiaojie; Zhu, Xuan

2016-01-01

Coping with scarcity of labeled data is a common problem in sound classification tasks. Approaches for classifying sounds are commonly based on supervised learning algorithms, which require labeled data which is often scarce and leads to models that do not generalize well. In this paper, we make an efficient combination of confidence-based Active Learning and Self-Training with the aim of minimizing the need for human annotation for sound classification model training. The proposed method pre-processes the instances that are ready for labeling by calculating their classifier confidence scores, and then delivers the candidates with lower scores to human annotators, and those with high scores are automatically labeled by the machine. We demonstrate the feasibility and efficacy of this method in two practical scenarios: pool-based and stream-based processing. Extensive experimental results indicate that our approach requires significantly less labeled instances to reach the same performance in both scenarios compared to Passive Learning, Active Learning and Self-Training. A reduction of 52.2% in human labeled instances is achieved in both of the pool-based and stream-based scenarios on a sound classification task considering 16,930 sound instances.

Semi-Supervised Active Learning for Sound Classification in Hybrid Learning Environments

PubMed Central

Han, Wenjing; Coutinho, Eduardo; Li, Haifeng; Schuller, Björn; Yu, Xiaojie; Zhu, Xuan

2016-01-01

Coping with scarcity of labeled data is a common problem in sound classification tasks. Approaches for classifying sounds are commonly based on supervised learning algorithms, which require labeled data which is often scarce and leads to models that do not generalize well. In this paper, we make an efficient combination of confidence-based Active Learning and Self-Training with the aim of minimizing the need for human annotation for sound classification model training. The proposed method pre-processes the instances that are ready for labeling by calculating their classifier confidence scores, and then delivers the candidates with lower scores to human annotators, and those with high scores are automatically labeled by the machine. We demonstrate the feasibility and efficacy of this method in two practical scenarios: pool-based and stream-based processing. Extensive experimental results indicate that our approach requires significantly less labeled instances to reach the same performance in both scenarios compared to Passive Learning, Active Learning and Self-Training. A reduction of 52.2% in human labeled instances is achieved in both of the pool-based and stream-based scenarios on a sound classification task considering 16,930 sound instances. PMID:27627768

A Natural Teaching Method Based on Learning Theory.

ERIC Educational Resources Information Center

Smilkstein, Rita

1991-01-01

The natural teaching method is active and student-centered, based on schema and constructivist theories, and informed by research in neuroplasticity. A schema is a mental picture or understanding of something we have learned. Humans can have knowledge only to the degree to which they have constructed schemas from learning experiences and practice.…

Active Learning Using Hint Information.

PubMed

Li, Chun-Liang; Ferng, Chun-Sung; Lin, Hsuan-Tien

2015-08-01

The abundance of real-world data and limited labeling budget calls for active learning, an important learning paradigm for reducing human labeling efforts. Many recently developed active learning algorithms consider both uncertainty and representativeness when making querying decisions. However, exploiting representativeness with uncertainty concurrently usually requires tackling sophisticated and challenging learning tasks, such as clustering. In this letter, we propose a new active learning framework, called hinted sampling, which takes both uncertainty and representativeness into account in a simpler way. We design a novel active learning algorithm within the hinted sampling framework with an extended support vector machine. Experimental results validate that the novel active learning algorithm can result in a better and more stable performance than that achieved by state-of-the-art algorithms. We also show that the hinted sampling framework allows improving another active learning algorithm designed from the transductive support vector machine.

Active learning: a step towards automating medical concept extraction.

PubMed

Kholghi, Mahnoosh; Sitbon, Laurianne; Zuccon, Guido; Nguyen, Anthony

2016-03-01

This paper presents an automatic, active learning-based system for the extraction of medical concepts from clinical free-text reports. Specifically, (1) the contribution of active learning in reducing the annotation effort and (2) the robustness of incremental active learning framework across different selection criteria and data sets are determined. The comparative performance of an active learning framework and a fully supervised approach were investigated to study how active learning reduces the annotation effort while achieving the same effectiveness as a supervised approach. Conditional random fields as the supervised method, and least confidence and information density as 2 selection criteria for active learning framework were used. The effect of incremental learning vs standard learning on the robustness of the models within the active learning framework with different selection criteria was also investigated. The following 2 clinical data sets were used for evaluation: the Informatics for Integrating Biology and the Bedside/Veteran Affairs (i2b2/VA) 2010 natural language processing challenge and the Shared Annotated Resources/Conference and Labs of the Evaluation Forum (ShARe/CLEF) 2013 eHealth Evaluation Lab. The annotation effort saved by active learning to achieve the same effectiveness as supervised learning is up to 77%, 57%, and 46% of the total number of sequences, tokens, and concepts, respectively. Compared with the random sampling baseline, the saving is at least doubled. Incremental active learning is a promising approach for building effective and robust medical concept extraction models while significantly reducing the burden of manual annotation. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

[Flipped classroom as a strategy to enhance active learning].

PubMed

Wakabayashi, Noriyuki

2015-03-01

This paper reviews the introduction of a flipped class for fourth grade dentistry students, and analyzes the characteristics of the learning method. In fiscal 2013 and 2014, a series of ten three-hour units for removable partial prosthodontics were completed with the flipped class method; a lecture video of approximately 60 minutes was made by the teacher (author) and uploaded to the university's e-learning website one week before each class. Students were instructed to prepare for the class by watching the streaming video on their PC, tablet, or smartphone. In the flipped class, students were not given a lecture, but were asked to solve short questions displayed on screen, to make a short presentation about a part of the video lecture, and to discuss a critical question related to the main subject of the day. An additional team-based learning (TBL) session with individual and group answers was implemented. The average individual scores were considerably higher in the last two years, when the flipped method was implemented, than in the three previous years when conventional lectures were used. The following learning concepts were discussed: the role of the flipped method as an active learning strategy, the efficacy of lecture videos and short questions, students' participation in the class discussion, present-day value of the method, cooperation with TBL, the significance of active learning in relation with the students' learning ability, and the potential increase in the preparation time and workload for students.

Implementing active-learning strategies to improve physics learning in Latin America

NASA Astrophysics Data System (ADS)

Alarcon, Hugo; Zavala, G.; Fernandez, R.; Benegas, J.

2006-12-01

It is evident that the most effective active-learning strategies to improve physics learning at the college level have been developed in the United States. Recently, some universities in Latin America have begun adopting such methods as a part of institutional projects, or motivated by national projects led by education authorities. In this work we will present two cases, a large-scale implementation of Tutorials in Introductory Physics (1) in Mexico supported by the institution as a part of a change in its educational model, and a medium-scale implementation of this method in Chile supported by the national government. In both experiences, the professors involved in the educational experience have previously participated in a training workshop that prepared them for implementing this strategy in the classroom. The training workshop, described elsewhere (2), was designed also under active learning premises, so teachers completed the proposed activities in the same way as their students will do. We will present the first results of these two projects. References: (1) McDermott, L. C., Shaffer, P. S., & PER (1998). "Tutorials in Introductory Physics", Prentice Hall, translated as "Tutoriales para Física Introductoria" (2001) Prentice Hall, Buenos Aires.. (2) Zavala, G., Alarcón, H. and Benegas, J. (2005). "Innovative training of in-service teachers for active learning: A short teacher development course based on Physics Education Research", accepted for publication, J. of Sc. Teach. Ed. This work has been partially supported by Tecnológico de Monterrey through the Chair in Physics Education Research and by MECE Educación Superior Program (Chile).

MLS student active learning within a "cloud" technology program.

PubMed

Tille, Patricia M; Hall, Heather

2011-01-01

In November 2009, the MLS program in a large public university serving a geographically large, sparsely populated state instituted an initiative for the integration of technology enhanced teaching and learning within the curriculum. This paper is intended to provide an introduction to the system requirements and sample instructional exercises used to create an active learning technology-based classroom. Discussion includes the following: 1.) define active learning and the essential components, 2.) summarize teaching methods, technology and exercises utilized within a "cloud" technology program, 3.) describe a "cloud" enhanced classroom and programming 4.) identify active learning tools and exercises that can be implemented into laboratory science programs, and 5.) describe the evaluation and assessment of curriculum changes and student outcomes. The integration of technology in the MLS program is a continual process and is intended to provide student-driven active learning experiences.

[Introduction of active learning and student readership in teaching by the pharmaceutical faculty].

PubMed

Sekiguchi, Masaki; Yamato, Ippei; Kato, Tetsuta; Torigoe, Kojyun

2005-07-01

We have introduced improvements and new approaches into our teaching methods by exploiting 4 active learning methods for pharmacy students of first year. The 4 teaching methods for each lesson or take home assignment are follows: 1) problem-based learning (clinical case) including a student presentation of the clinical case, 2) schematic drawings of the human organs, one drawing done in 15-20 min during the week following a lecture and a second drawing done with reference to a professional textbook, 3) learning of professional themes in take home assignments, and 4) short test in order to confirm the understanding of technical terms by using paper or computer. These improvements and new methods provide active approaches for pharmacy students (as opposed to passive memorization of words and image study). In combination, they have proven to be useful as a learning method to acquire expert knowledge and to convert from passive learning approach to active learning approach of pharmacy students in the classroom.

Using Active Learning for Speeding up Calibration in Simulation Models

PubMed Central

Cevik, Mucahit; Ali Ergun, Mehmet; Stout, Natasha K.; Trentham-Dietz, Amy; Craven, Mark; Alagoz, Oguzhan

2015-01-01

Background Most cancer simulation models include unobservable parameters that determine the disease onset and tumor growth. These parameters play an important role in matching key outcomes such as cancer incidence and mortality and their values are typically estimated via lengthy calibration procedure, which involves evaluating large number of combinations of parameter values via simulation. The objective of this study is to demonstrate how machine learning approaches can be used to accelerate the calibration process by reducing the number of parameter combinations that are actually evaluated. Methods Active learning is a popular machine learning method that enables a learning algorithm such as artificial neural networks to interactively choose which parameter combinations to evaluate. We develop an active learning algorithm to expedite the calibration process. Our algorithm determines the parameter combinations that are more likely to produce desired outputs, therefore reduces the number of simulation runs performed during calibration. We demonstrate our method using previously developed University of Wisconsin Breast Cancer Simulation Model (UWBCS). Results In a recent study, calibration of the UWBCS required the evaluation of 378,000 input parameter combinations to build a race-specific model and only 69 of these combinations produced results that closely matched observed data. By using the active learning algorithm in conjunction with standard calibration methods, we identify all 69 parameter combinations by evaluating only 5620 of the 378,000 combinations. Conclusion Machine learning methods hold potential in guiding model developers in the selection of more promising parameter combinations and hence speeding up the calibration process. Applying our machine learning algorithm to one model shows that evaluating only 1.49% of all parameter combinations would be sufficient for the calibration. PMID:26471190

Cross-domain active learning for video concept detection

NASA Astrophysics Data System (ADS)

Li, Huan; Li, Chao; Shi, Yuan; Xiong, Zhang; Hauptmann, Alexander G.

2011-08-01

As video data from a variety of different domains (e.g., news, documentaries, entertainment) have distinctive data distributions, cross-domain video concept detection becomes an important task, in which one can reuse the labeled data of one domain to benefit the learning task in another domain with insufficient labeled data. In this paper, we approach this problem by proposing a cross-domain active learning method which iteratively queries labels of the most informative samples in the target domain. Traditional active learning assumes that the training (source domain) and test data (target domain) are from the same distribution. However, it may fail when the two domains have different distributions because querying informative samples according to a base learner that initially learned from source domain may no longer be helpful for the target domain. In our paper, we use the Gaussian random field model as the base learner which has the advantage of exploring the distributions in both domains, and adopt uncertainty sampling as the query strategy. Additionally, we present an instance weighting trick to accelerate the adaptability of the base learner, and develop an efficient model updating method which can significantly speed up the active learning process. Experimental results on TRECVID collections highlight the effectiveness.

Applying active learning to supervised word sense disambiguation in MEDLINE.

PubMed

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

2013-01-01

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. 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. 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. This study demonstrated that integrating active learning strategies with supervised WSD methods could effectively reduce annotation cost and improve the disambiguation models.

[Supporting an Academic Society with the Active Learning Tool Clica].

PubMed

Arai, Kensuke; Mitsubori, Masahiro

2018-01-01

　Within school classrooms, Active Learning has been receiving unprecedented attention. Indeed, Active Learning's popularity does not stop in the classroom. As more and more people argue that the Japanese government needs to renew guidelines for education, Active Learning has surfaced as a method capable of providing the necessary knowledge and training for people in all areas of society, helping them reach their full potential. It has become accepted that Active Learning is more effective over the passive listening of lectures, where there is little to no interaction. Active Learning emphasizes that learners explain their thoughts, ask questions, and express their opinions, resulting in a better retention rate of the subject at hand. In this review, I introduce an Active Learning support tool developed at Digital Knowledge, "Clica". This tool is currently being used at many educational institutions. I will also introduce an online questionnaire that Digital Knowledge provided at the 10th Annual Meeting of the Japanese Society for Pharmaceutical Palliative Care and Sciences.

Analysis of a Constellation Lab Cooperative Learning Activity

NASA Astrophysics Data System (ADS)

Gauthier, A. J.

2001-12-01

A cooperative learning activity was designed for use in the undergraduate laboratory course Introduction to Astronomical Observation. This group exercise enhances the student's learning of constellations and will hopefully increase retention of the material throughout the semester. It also serves as an "ice-breaker" during the first week of lab, promoting student involvement and vested interest in the course. To gain some insight into the student mind, a survey was conducted to evaluate the usefulness and overall opinion of this method. The students who completed the survey had previously been enrolled in a pre-requisite astronomy course that also required a constellation lab. In this previous course they "learned" the constellations from an instructor and a flashlight beam, studied them on their own, and then promptly took a quiz. Both methods are analyzed from an instructional designer's point of view and suggestions for future activities are presented. The preliminary results and accompanying activity will be discussed in poster and hand-out medium.

Cooperative Learning as a Democratic Learning Method

ERIC Educational Resources Information Center

Erbil, Deniz Gökçe; Kocabas, Ayfer

2018-01-01

In this study, the effects of applying the cooperative learning method on the students' attitude toward democracy in an elementary 3rd-grade life studies course was examined. Over the course of 8 weeks, the cooperative learning method was applied with an experimental group, and traditional methods of teaching life studies in 2009, which was still…

Moments of movement: active learning and practice development.

PubMed

Dewing, Jan

2010-01-01

As our understanding of practice development becomes more sophisticated, we enhance our understanding of how the facilitation of learning in and from practice, can be more effectively achieved. This paper outlines an approach for enabling and maximizing learning within practice development known as 'Active Learning'. It considers how, given establishing a learning culture is a prerequisite for the sustainability of PD within organisations, practice developers can do more to maximize learning for practitioners and other stakeholders. Active Learning requires that more attention be given by organisations committed to PD, at a corporate and strategic level for how learning strategies are developed in the workplace. Specifically, a move away from a heavy reliance on training may be required. Practice development facilitators also need to review: how they organise and offer learning, so that learning strategies are consistent with the vision, aims and processes of PD; have skills in the planning, delivery and evaluation of learning as part of their role and influence others who provide more traditional methods of training and education.

Interactive lecture demonstrations, active learning, and the ALOP project

NASA Astrophysics Data System (ADS)

Lakshminarayanan, Vasudevan

2011-05-01

There is considerable evidence from the physics education literature that traditional approaches are ineffective in teaching physics concepts. A better teaching method is to use the active learning environment, which can be created using interactive lecture demonstrations. Based on the active learning methodology and within the framework of the UNESCO mandate in physics education and introductory physics, the ALOP project (active learning in optics and photonics) was started in 2003, to provide a focus on an experimental area that is adaptable and relevant to research and educational conditions in many developing countries. This project is discussed in this paper.

Active Learning in an Introductory Meteorology Class

NASA Astrophysics Data System (ADS)

Marchese, P. J.; Bluestone, C.

2007-12-01

Active learning modules were introduced to the primarily minority population in the introductory meteorology class at Queensborough Community College (QCC). These activities were developed at QCC and other 4 year colleges and designed to reinforce basic meteorological concepts. The modules consisted of either Interactive Lecture Demonstrations (ILD) or discovery-based activities. During the ILD the instructor would describe an experiment that would be demonstrated in class. Students would predict what the outcome would be and compare their expected results to the actual outcome of the experiment. In the discovery-based activities students would learn about physical concepts by performing basic experiments. These activities differed from the traditional lab in that it avoided "cookbook" procedures and emphasized having the students learn about the concept using the scientific method. As a result of these activities student scores measuring conceptual understanding, as well as factual knowledge, increased as compared to student scores in a more affluent community college. Students also had higher self- efficacy scores. Lower scoring students demonstrated the greatest benefit, while the better students had little (or no) changes.

Active learning of cortical connectivity from two-photon imaging data.

PubMed

Bertrán, Martín A; Martínez, Natalia L; Wang, Ye; Dunson, David; Sapiro, Guillermo; Ringach, Dario

2018-01-01

Understanding how groups of neurons interact within a network is a fundamental question in system neuroscience. Instead of passively observing the ongoing activity of a network, we can typically perturb its activity, either by external sensory stimulation or directly via techniques such as two-photon optogenetics. A natural question is how to use such perturbations to identify the connectivity of the network efficiently. Here we introduce a method to infer sparse connectivity graphs from in-vivo, two-photon imaging of population activity in response to external stimuli. A novel aspect of the work is the introduction of a recommended distribution, incrementally learned from the data, to optimally refine the inferred network. Unlike existing system identification techniques, this "active learning" method automatically focuses its attention on key undiscovered areas of the network, instead of targeting global uncertainty indicators like parameter variance. We show how active learning leads to faster inference while, at the same time, provides confidence intervals for the network parameters. We present simulations on artificial small-world networks to validate the methods and apply the method to real data. Analysis of frequency of motifs recovered show that cortical networks are consistent with a small-world topology model.

Using Active Learning for Speeding up Calibration in Simulation Models.

PubMed

Cevik, Mucahit; Ergun, Mehmet Ali; Stout, Natasha K; Trentham-Dietz, Amy; Craven, Mark; Alagoz, Oguzhan

2016-07-01

Most cancer simulation models include unobservable parameters that determine disease onset and tumor growth. These parameters play an important role in matching key outcomes such as cancer incidence and mortality, and their values are typically estimated via a lengthy calibration procedure, which involves evaluating a large number of combinations of parameter values via simulation. The objective of this study is to demonstrate how machine learning approaches can be used to accelerate the calibration process by reducing the number of parameter combinations that are actually evaluated. Active learning is a popular machine learning method that enables a learning algorithm such as artificial neural networks to interactively choose which parameter combinations to evaluate. We developed an active learning algorithm to expedite the calibration process. Our algorithm determines the parameter combinations that are more likely to produce desired outputs and therefore reduces the number of simulation runs performed during calibration. We demonstrate our method using the previously developed University of Wisconsin breast cancer simulation model (UWBCS). In a recent study, calibration of the UWBCS required the evaluation of 378 000 input parameter combinations to build a race-specific model, and only 69 of these combinations produced results that closely matched observed data. By using the active learning algorithm in conjunction with standard calibration methods, we identify all 69 parameter combinations by evaluating only 5620 of the 378 000 combinations. Machine learning methods hold potential in guiding model developers in the selection of more promising parameter combinations and hence speeding up the calibration process. Applying our machine learning algorithm to one model shows that evaluating only 1.49% of all parameter combinations would be sufficient for the calibration. © The Author(s) 2015.

Using Oceanography to Support Active Learning

NASA Astrophysics Data System (ADS)

Byfield, V.

2012-04-01

Teachers are always on the lookout for material to give their brightest students, in order to keep them occupied, stimulated and challenged, while the teacher gets on with helping the rest. They are also looking for material that can inspire and enthuse those who think that school is 'just boring!' Oceanography, well presented, has the capacity to do both. As a relatively young science, oceanography is not a core curriculum subject (possibly an advantage), but it draws on the traditional sciences of biology, chemistry, physic and geology, and can provide wonderful examples for teaching concepts in school sciences. It can also give good reasons for learning science, maths and technology. Exciting expeditions (research cruises) to far-flung places; opportunities to explore new worlds, a different angle on topical debates such as climate change, pollution, or conservation can bring a new life to old subjects. Access to 'real' data from satellites or Argo floats can be used to develop analytical and problem solving skills. The challenge is to make all this available in a form that can easily be used by teachers and students to enhance the learning experience. We learn by doing. Active teaching methods require students to develop their own concepts of what they are learning. This stimulates new neural connections in the brain - the physical manifestation of learning. There is a large body of evidence to show that active learning is much better remembered and understood. Active learning develops thinking skills through analysis, problem solving, and evaluation. It helps learners to use their knowledge in realistic and useful ways, and see its importance and relevance. Most importantly, properly used, active learning is fun. This paper presents experiences from a number of education outreach projects that have involved the National Oceanography Centre in Southampton, UK. All contain some element of active learning - from quizzes and puzzles to analysis of real data from

Rethinking Active Learning in the Context of Japanese Higher Education

ERIC Educational Resources Information Center

Ito, Hiroshi

2017-01-01

This paper reconsiders active learning (AL) in the context of Japanese higher education. AL encourages students to actively engage with learning, enhancing their generic and employability skills. In Japan, AL has become increasingly popular but lacks a clear definition. AL proponents suggest that it is the use of instructional methods that…

Active Learning of Classification Models with Likert-Scale Feedback.

PubMed

Xue, Yanbing; Hauskrecht, Milos

2017-01-01

Annotation of classification data by humans can be a time-consuming and tedious process. Finding ways of reducing the annotation effort is critical for building the classification models in practice and for applying them to a variety of classification tasks. In this paper, we develop a new active learning framework that combines two strategies to reduce the annotation effort. First, it relies on label uncertainty information obtained from the human in terms of the Likert-scale feedback. Second, it uses active learning to annotate examples with the greatest expected change. We propose a Bayesian approach to calculate the expectation and an incremental SVM solver to reduce the time complexity of the solvers. We show the combination of our active learning strategy and the Likert-scale feedback can learn classification models more rapidly and with a smaller number of labeled instances than methods that rely on either Likert-scale labels or active learning alone.

Active Learning of Classification Models with Likert-Scale Feedback

PubMed Central

Xue, Yanbing; Hauskrecht, Milos

2017-01-01

Annotation of classification data by humans can be a time-consuming and tedious process. Finding ways of reducing the annotation effort is critical for building the classification models in practice and for applying them to a variety of classification tasks. In this paper, we develop a new active learning framework that combines two strategies to reduce the annotation effort. First, it relies on label uncertainty information obtained from the human in terms of the Likert-scale feedback. Second, it uses active learning to annotate examples with the greatest expected change. We propose a Bayesian approach to calculate the expectation and an incremental SVM solver to reduce the time complexity of the solvers. We show the combination of our active learning strategy and the Likert-scale feedback can learn classification models more rapidly and with a smaller number of labeled instances than methods that rely on either Likert-scale labels or active learning alone. PMID:28979827

Active learning for ontological event extraction incorporating named entity recognition and unknown word handling.

PubMed

Han, Xu; Kim, Jung-jae; Kwoh, Chee Keong

2016-01-01

Biomedical text mining may target various kinds of valuable information embedded in the literature, but a critical obstacle to the extension of the mining targets is the cost of manual construction of labeled data, which are required for state-of-the-art supervised learning systems. Active learning is to choose the most informative documents for the supervised learning in order to reduce the amount of required manual annotations. Previous works of active learning, however, focused on the tasks of entity recognition and protein-protein interactions, but not on event extraction tasks for multiple event types. They also did not consider the evidence of event participants, which might be a clue for the presence of events in unlabeled documents. Moreover, the confidence scores of events produced by event extraction systems are not reliable for ranking documents in terms of informativity for supervised learning. We here propose a novel committee-based active learning method that supports multi-event extraction tasks and employs a new statistical method for informativity estimation instead of using the confidence scores from event extraction systems. Our method is based on a committee of two systems as follows: We first employ an event extraction system to filter potential false negatives among unlabeled documents, from which the system does not extract any event. We then develop a statistical method to rank the potential false negatives of unlabeled documents 1) by using a language model that measures the probabilities of the expression of multiple events in documents and 2) by using a named entity recognition system that locates the named entities that can be event arguments (e.g. proteins). The proposed method further deals with unknown words in test data by using word similarity measures. We also apply our active learning method for the task of named entity recognition. We evaluate the proposed method against the BioNLP Shared Tasks datasets, and show that our method

The Effectiveness of WhatsApp Mobile Learning Activities Guided by Activity Theory on Students' Knowledge Management

ERIC Educational Resources Information Center

Barhoumi, Chokri

2015-01-01

This research paper explores the effectiveness of using mobile technologies to support a blended learning course titled Scientific Research Methods in Information Science. Specifically, it discusses the effects of WhatsApp mobile learning activities guided by activity theory on students' knowledge Management (KM). During the 2014 academic year,…

Workshop on active learning: two examples

NASA Astrophysics Data System (ADS)

Ben Lakhdar, Zohra; Lahmar, Souad; Lakshminarayanan, Vasudevan

2014-07-01

Optics is an enabling science that has far ranging importance in many diverse fields. However, many students do not find it to be of great interest. A solution to this problem is to train teachers in active learning methodologies so that the subject matter can be presented to generate student interest. We describe a workshop to present an example of an active learning process in Optics developed for training of teachers in developing countries (a UNESCO project) and will focus on 2 two different activities: 1. Interference and diffraction is considered by students as being very hard to understand and is taught in most developing countries as purely theoretical with almost no experiments. Simple experiments to enhance the conceptual understanding of these wave phenomena will be presented and 2. Image formation by the eye. Here we will discuss myopia, hyperopia and astigmatism as well as accommodation. In this module we will discuss image. The objective of the workshop will be to provide an experience of the use of the active learning method in optics including the use of experiments, mind's on and hands-on exercises, group and class discussions

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

PubMed

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

2007-09-01

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

Active Learning with Statistical Models.

DTIC Science & Technology

1995-01-01

Active Learning with Statistical Models ASC-9217041, NSF CDA-9309300 6. AUTHOR(S) David A. Cohn, Zoubin Ghahramani, and Michael I. Jordan 7. PERFORMING...TERMS 15. NUMBER OF PAGES Al, MIT, Artificial Intelligence, active learning , queries, locally weighted 6 regression, LOESS, mixtures of gaussians...COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES A.I. Memo No. 1522 January 9. 1995 C.B.C.L. Paper No. 110 Active Learning with

Teachers as Co-Designers of Technology-Rich Learning Activities for Early Literacy

ERIC Educational Resources Information Center

Cviko, Amina; McKenney, Susan; Voogt, Joke

2015-01-01

Although kindergarten teachers often struggle with implementing technology, they are rarely involved in co-designing technology-rich learning activities. This study involved teachers in the co-design of technology-rich learning activities and sought to explore implementation and pupil learning outcomes. A case-study method was used to investigate:…

Promoting Technology-Assisted Active Learning in Computer Science Education

ERIC Educational Resources Information Center

Gao, Jinzhu; Hargis, Jace

2010-01-01

This paper describes specific active learning strategies for teaching computer science, integrating both instructional technologies and non-technology-based strategies shown to be effective in the literature. The theoretical learning components addressed include an intentional method to help students build metacognitive abilities, as well as…

Understanding Insurance. A Guide for Industrial Cooperative Training Programs. Learning Activity Package No. 15.

ERIC Educational Resources Information Center

Duenk, Lester G.; Tuel, Charles

This learning activity package (LAP) on the insurance industry and the methods used to give protection to the insured is designed for student self-study. Following a list of learning objectives, the LAP contains a pretest (answer key provided at the back). Six learning activities follow. The learning activities cover the following material: terms…

Frank Gilbreth and health care delivery method study driven learning.

PubMed

Towill, Denis R

2009-01-01

The purpose of this article is to look at method study, as devised by the Gilbreths at the beginning of the twentieth century, which found early application in hospital quality assurance and surgical "best practice". It has since become a core activity in all modern methods, as applied to healthcare delivery improvement programmes. The article traces the origin of what is now currently and variously called "business process re-engineering", "business process improvement" and "lean healthcare" etc., by different management gurus back to the century-old pioneering work of Frank Gilbreth. The outcome is a consistent framework involving "width", "length" and "depth" dimensions within which healthcare delivery systems can be analysed, designed and successfully implemented to achieve better and more consistent performance. Healthcare method (saving time plus saving motion) study is best practised as co-joint action learning activity "owned" by all "players" involved in the re-engineering process. However, although process mapping is a key step forward, in itself it is no guarantee of effective re-engineering. It is not even the beginning of the end of the change challenge, although it should be the end of the beginning. What is needed is innovative exploitation of method study within a healthcare organisational learning culture accelerated via the Gilbreth Knowledge Flywheel. It is shown that effective healthcare delivery pipeline improvement is anchored into a team approach involving all "players" in the system especially physicians. A comprehensive process study, constructive dialogue, proper and highly professional re-engineering plus managed implementation are essential components. Experience suggests "learning" is thereby achieved via "natural groups" actively involved in healthcare processes. The article provides a proven method for exploiting Gilbreths' outputs and their many successors in enabling more productive evidence-based healthcare delivery as summarised

Active Learning Using Arbitrary Binary Valued Queries

DTIC Science & Technology

1990-10-01

active learning in the sense that the learner has complete choice in the information received. Specifically, we allow the learner to ask arbitrary yes...no questions. We consider both active learning under a fixed distribution and distribution-free active learning . In the case of active learning , the...a concept class is actively learnable iff it is finite, so that active learning is in fact less powerful than the usual passive learning model. We

Methods of learning in statistical education: Design and analysis of a randomized trial

NASA Astrophysics Data System (ADS)

Boyd, Felicity Turner

Background. Recent psychological and technological advances suggest that active learning may enhance understanding and retention of statistical principles. A randomized trial was designed to evaluate the addition of innovative instructional methods within didactic biostatistics courses for public health professionals. Aims. The primary objectives were to evaluate and compare the addition of two active learning methods (cooperative and internet) on students' performance; assess their impact on performance after adjusting for differences in students' learning style; and examine the influence of learning style on trial participation. Methods. Consenting students enrolled in a graduate introductory biostatistics course were randomized to cooperative learning, internet learning, or control after completing a pretest survey. The cooperative learning group participated in eight small group active learning sessions on key statistical concepts, while the internet learning group accessed interactive mini-applications on the same concepts. Controls received no intervention. Students completed evaluations after each session and a post-test survey. Study outcome was performance quantified by examination scores. Intervention effects were analyzed by generalized linear models using intent-to-treat analysis and marginal structural models accounting for reported participation. Results. Of 376 enrolled students, 265 (70%) consented to randomization; 69, 100, and 96 students were randomized to the cooperative, internet, and control groups, respectively. Intent-to-treat analysis showed no differences between study groups; however, 51% of students in the intervention groups had dropped out after the second session. After accounting for reported participation, expected examination scores were 2.6 points higher (of 100 points) after completing one cooperative learning session (95% CI: 0.3, 4.9) and 2.4 points higher after one internet learning session (95% CI: 0.0, 4.7), versus

A Bayesian Active Learning Experimental Design for Inferring Signaling Networks.

PubMed

Ness, Robert O; Sachs, Karen; Mallick, Parag; Vitek, Olga

2018-06-21

Machine learning methods for learning network structure are applied to quantitative proteomics experiments and reverse-engineer intracellular signal transduction networks. They provide insight into the rewiring of signaling within the context of a disease or a phenotype. To learn the causal patterns of influence between proteins in the network, the methods require experiments that include targeted interventions that fix the activity of specific proteins. However, the interventions are costly and add experimental complexity. We describe an active learning strategy for selecting optimal interventions. Our approach takes as inputs pathway databases and historic data sets, expresses them in form of prior probability distributions on network structures, and selects interventions that maximize their expected contribution to structure learning. Evaluations on simulated and real data show that the strategy reduces the detection error of validated edges as compared with an unguided choice of interventions and avoids redundant interventions, thereby increasing the effectiveness of the experiment.

Active Learning with Irrelevant Examples

NASA Technical Reports Server (NTRS)

Mazzoni, Dominic; Wagstaff, Kiri L.; Burl, Michael

2006-01-01

Active learning algorithms attempt to accelerate the learning process by requesting labels for the most informative items first. In real-world problems, however, there may exist unlabeled items that are irrelevant to the user's classification goals. Queries about these points slow down learning because they provide no information about the problem of interest. We have observed that when irrelevant items are present, active learning can perform worse than random selection, requiring more time (queries) to achieve the same level of accuracy. Therefore, we propose a novel approach, Relevance Bias, in which the active learner combines its default selection heuristic with the output of a simultaneously trained relevance classifier to favor items that are likely to be both informative and relevant. In our experiments on a real-world problem and two benchmark datasets, the Relevance Bias approach significantly improved the learning rate of three different active learning approaches.

Ensemble Methods for Classification of Physical Activities from Wrist Accelerometry.

PubMed

Chowdhury, Alok Kumar; Tjondronegoro, Dian; Chandran, Vinod; Trost, Stewart G

2017-09-01

To investigate whether the use of ensemble learning algorithms improve physical activity recognition accuracy compared to the single classifier algorithms, and to compare the classification accuracy achieved by three conventional ensemble machine learning methods (bagging, boosting, random forest) and a custom ensemble model comprising four algorithms commonly used for activity recognition (binary decision tree, k nearest neighbor, support vector machine, and neural network). The study used three independent data sets that included wrist-worn accelerometer data. For each data set, a four-step classification framework consisting of data preprocessing, feature extraction, normalization and feature selection, and classifier training and testing was implemented. For the custom ensemble, decisions from the single classifiers were aggregated using three decision fusion methods: weighted majority vote, naïve Bayes combination, and behavior knowledge space combination. Classifiers were cross-validated using leave-one subject out cross-validation and compared on the basis of average F1 scores. In all three data sets, ensemble learning methods consistently outperformed the individual classifiers. Among the conventional ensemble methods, random forest models provided consistently high activity recognition; however, the custom ensemble model using weighted majority voting demonstrated the highest classification accuracy in two of the three data sets. Combining multiple individual classifiers using conventional or custom ensemble learning methods can improve activity recognition accuracy from wrist-worn accelerometer data.

Involving postgraduate's students in undergraduate small group teaching promotes active learning in both

PubMed Central

Kalra, Ruchi; Modi, Jyoti Nath; Vyas, Rashmi

2015-01-01

Background: Lecture is a common traditional method for teaching, but it may not stimulate higher order thinking and students may also be hesitant to express and interact. The postgraduate (PG) students are less involved with undergraduate (UG) teaching. Team based small group active learning method can contribute to better learning experience. Aim: To-promote active learning skills among the UG students using small group teaching methods involving PG students as facilitators to impart hands-on supervised training in teaching and managerial skills. Methodology: After Institutional approval under faculty supervision 92 UGs and 8 PGs participated in 6 small group sessions utilizing the jigsaw technique. Feedback was collected from both. Observations: Undergraduate Feedback (Percentage of Students Agreed): Learning in small groups was a good experience as it helped in better understanding of the subject (72%), students explored multiple reading resources (79%), they were actively involved in self-learning (88%), students reported initial apprehension of performance (71%), identified their learning gaps (86%), team enhanced their learning process (71%), informal learning in place of lecture was a welcome change (86%), it improved their communication skills (82%), small group learning can be useful for future self-learning (75%). Postgraduate Feedback: Majority performed facilitation for first time, perceived their performance as good (75%), it was helpful in self-learning (100%), felt confident of managing students in small groups (100%), as facilitator they improved their teaching skills, found it more useful and better identified own learning gaps (87.5%). Conclusions: Learning in small groups adopting team based approach involving both UGs and PGs promoted active learning in both and enhanced the teaching skills of the PGs. PMID:26380201

Active Learning Framework for Non-Intrusive Load Monitoring: Preprint

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

Jin, Xin

2016-05-16

Non-Intrusive Load Monitoring (NILM) is a set of techniques that estimate the electricity usage of individual appliances from power measurements taken at a limited number of locations in a building. One of the key challenges in NILM is having too much data without class labels yet being unable to label the data manually for cost or time constraints. This paper presents an active learning framework that helps existing NILM techniques to overcome this challenge. Active learning is an advanced machine learning method that interactively queries a user for the class label information. Unlike most existing NILM systems that heuristically requestmore » user inputs, the proposed method only needs minimally sufficient information from a user to build a compact and yet highly representative load signature library. Initial results indicate the proposed method can reduce the user inputs by up to 90% while still achieving similar disaggregation performance compared to a heuristic method. Thus, the proposed method can substantially reduce the burden on the user, improve the performance of a NILM system with limited user inputs, and overcome the key market barriers to the wide adoption of NILM technologies.« less

Active-learning versus teacher-centered instruction for learning acids and bases

NASA Astrophysics Data System (ADS)

Acar Sesen, Burcin; Tarhan, Leman

2011-07-01

Background and purpose: Active-learning as a student-centered learning process has begun to take more interest in constructing scientific knowledge. For this reason, this study aimed to investigate the effectiveness of active-learning implementation on high-school students' understanding of 'acids and bases'. Sample The sample of this study was 45 high-school students (average age 17 years) from two different classes, which were randomly assigned to the experimental (n = 21) and control groups (n = 25), in a high school in Turkey. Design and methods A pre-test consisting of 25 items was applied to both experimental and control groups before the treatment in order to identify student prerequisite knowledge about their proficiency for learning 'acids and bases'. A one-way analysis of variance (ANOVA) was conducted to compare the pre-test scores for groups and no significant difference was found between experimental (ME = 40.14) and control groups (MC = 41.92) in terms of mean scores (F 1,43 = 2.66, p > 0.05). The experimental group was taught using an active-learning curriculum developed by the authors and the control group was taught using traditional course content based on teacher-centered instruction. After the implementation, 'Acids and Bases Achievement Test' scores were collected for both groups. Results ANOVA results showed that students' 'Acids and Bases Achievement Test' post-test scores differed significantly in terms of groups (F 1,43 = 102.53; p < 0.05). Additionally, in this study 54 misconceptions, 14 of them not reported in the literature before, were observed in the following terms: 'acid and base theories'; 'metal and non-metal oxides'; 'acid and base strengths'; 'neutralization'; 'pH and pOH'; 'hydrolysis'; 'acid-base equilibrium'; 'buffers'; 'indicators'; and 'titration'. Based on the achievement test and individual interview results, it was found that high-school students in the experimental group had fewer misconceptions and understood the

Comparative analysis of machine learning methods in ligand-based virtual screening of large compound libraries.

PubMed

Ma, Xiao H; Jia, Jia; Zhu, Feng; Xue, Ying; Li, Ze R; Chen, Yu Z

2009-05-01

Machine learning methods have been explored as ligand-based virtual screening tools for facilitating drug lead discovery. These methods predict compounds of specific pharmacodynamic, pharmacokinetic or toxicological properties based on their structure-derived structural and physicochemical properties. Increasing attention has been directed at these methods because of their capability in predicting compounds of diverse structures and complex structure-activity relationships without requiring the knowledge of target 3D structure. This article reviews current progresses in using machine learning methods for virtual screening of pharmacodynamically active compounds from large compound libraries, and analyzes and compares the reported performances of machine learning tools with those of structure-based and other ligand-based (such as pharmacophore and clustering) virtual screening methods. The feasibility to improve the performance of machine learning methods in screening large libraries is discussed.

Combining traditional anatomy lectures with e-learning activities: how do students perceive their learning experience?

PubMed Central

Wieser, Heike; Waldboth, Simone; Mischo-Kelling, Maria

2016-01-01

Objectives The purpose of this study was to investigate how students perceived their learning experience when combining traditional anatomy lectures with preparatory e-learning activities that consisted of fill-in-the-blank assignments, videos, and multiple-choice quizzes. Methods A qualitative study was conducted to explore changes in study behaviour and perception of learning. Three group interviews with students were conducted and thematically analysed. Results Data was categorized into four themes: 1. Approaching the course material, 2. Understanding the material, 3. Consolidating the material, and 4. Perceived learning outcome.  Students appreciated the clear structure of the course, and reported that online activities encouraged them towards a first engagement with the material. They felt that they were more active during in-class sessions, described self-study before the end-of-term exam as easier, and believed that contents would remain in their memories for a longer time. Conclusions By adjusting already existing resources, lectures can be combined fairly easily and cost-effectively with preparatory e-learning activities. The creation of online components promote well-structured courses, can help minimize ‘student passivity’ as a characteristic element of lectures, and can support students in distributing their studies throughout the term, thus suggesting enhanced learning. Further research work should be designed to confirm the afore-mentioned findings through objective measurements of student learning outcomes. PMID:26897012

Enhancing learning in geosciences and water engineering via lab activities

NASA Astrophysics Data System (ADS)

Valyrakis, Manousos; Cheng, Ming

2016-04-01

This study focuses on the utilisation of lab based activities to enhance the learning experience of engineering students studying Water Engineering and Geosciences. In particular, the use of modern highly visual and tangible presentation techniques within an appropriate laboratory based space are used to introduce undergraduate students to advanced engineering concepts. A specific lab activity, namely "Flood-City", is presented as a case study to enhance the active engagement rate, improve the learning experience of the students and better achieve the intended learning objectives of the course within a broad context of the engineering and geosciences curriculum. Such activities, have been used over the last few years from the Water Engineering group @ Glasgow, with success for outreach purposes (e.g. Glasgow Science Festival and demos at the Glasgow Science Centre and Kelvingrove museum). The activity involves a specific setup of the demonstration flume in a sand-box configuration, with elements and activities designed so as to gamely the overall learning activity. Social media platforms can also be used effectively to the same goals, particularly in cases were the students already engage in these online media. To assess the effectiveness of this activity a purpose designed questionnaire is offered to the students. Specifically, the questionnaire covers several aspects that may affect student learning, performance and satisfaction, such as students' motivation, factors to effective learning (also assessed by follow-up quizzes), and methods of communication and assessment. The results, analysed to assess the effectiveness of the learning activity as the students perceive it, offer a promising potential for the use of such activities in outreach and learning.

Implementation of K-Means Clustering Method for Electronic Learning Model

NASA Astrophysics Data System (ADS)

Latipa Sari, Herlina; Suranti Mrs., Dewi; Natalia Zulita, Leni

2017-12-01

Teaching and Learning process at SMK Negeri 2 Bengkulu Tengah has applied e-learning system for teachers and students. The e-learning was based on the classification of normative, productive, and adaptive subjects. SMK Negeri 2 Bengkulu Tengah consisted of 394 students and 60 teachers with 16 subjects. The record of e-learning database was used in this research to observe students’ activity pattern in attending class. K-Means algorithm in this research was used to classify students’ learning activities using e-learning, so that it was obtained cluster of students’ activity and improvement of student’s ability. Implementation of K-Means Clustering method for electronic learning model at SMK Negeri 2 Bengkulu Tengah was conducted by observing 10 students’ activities, namely participation of students in the classroom, submit assignment, view assignment, add discussion, view discussion, add comment, download course materials, view article, view test, and submit test. In the e-learning model, the testing was conducted toward 10 students that yielded 2 clusters of membership data (C1 and C2). Cluster 1: with membership percentage of 70% and it consisted of 6 members, namely 1112438 Anggi Julian, 1112439 Anis Maulita, 1112441 Ardi Febriansyah, 1112452 Berlian Sinurat, 1112460 Dewi Anugrah Anwar and 1112467 Eka Tri Oktavia Sari. Cluster 2:with membership percentage of 30% and it consisted of 4 members, namely 1112463 Dosita Afriyani, 1112471 Erda Novita, 1112474 Eskardi and 1112477 Fachrur Rozi.

Perceptions of the use of intelligent information access systems in university level active learning activities among teachers of biomedical subjects.

PubMed

Aparicio, Fernando; Morales-Botello, María Luz; Rubio, Margarita; Hernando, Asunción; Muñoz, Rafael; López-Fernández, Hugo; Glez-Peña, Daniel; Fdez-Riverola, Florentino; de la Villa, Manuel; Maña, Manuel; Gachet, Diego; Buenaga, Manuel de

2018-04-01

Student participation and the use of active methodologies in classroom learning are being increasingly emphasized. The use of intelligent systems can be of great help when designing and developing these types of activities. Recently, emerging disciplines such as 'educational data mining' and 'learning analytics and knowledge' have provided clear examples of the importance of the use of artificial intelligence techniques in education. The main objective of this study was to gather expert opinions regarding the benefits of using complementary methods that are supported by intelligent systems, specifically, by intelligent information access systems, when processing texts written in natural language and the benefits of using these methods as companion tools to the learning activities that are employed by biomedical and health sciences teachers. Eleven teachers of degree courses who belonged to the Faculties of Biomedical Sciences (BS) and Health Sciences (HS) of a Spanish university in Madrid were individually interviewed. These interviews were conducted using a mixed methods questionnaire that included 66 predefined close-ended and open-ended questions. In our study, three intelligent information access systems (i.e., BioAnnote, CLEiM and MedCMap) were successfully used to evaluate the teacher's perceptions regarding the utility of these systems and their different methods in learning activities. All teachers reported using active learning methods in the classroom, most of which were computer programs that were used for initially designing and later executing learning activities. All teachers used case-based learning methods in the classroom, with a specific emphasis on case reports written in Spanish and/or English. In general, few or none of the teachers were familiar with the technical terms related to the technologies used for these activities such as "intelligent systems" or "concept/mental maps". However, they clearly realized the potential applicability of such

Exploring Representativeness and Informativeness for Active Learning.

PubMed

Du, Bo; Wang, Zengmao; Zhang, Lefei; Zhang, Liangpei; Liu, Wei; Shen, Jialie; Tao, Dacheng

2017-01-01

How can we find a general way to choose the most suitable samples for training a classifier? Even with very limited prior information? Active learning, which can be regarded as an iterative optimization procedure, plays a key role to construct a refined training set to improve the classification performance in a variety of applications, such as text analysis, image recognition, social network modeling, etc. Although combining representativeness and informativeness of samples has been proven promising for active sampling, state-of-the-art methods perform well under certain data structures. Then can we find a way to fuse the two active sampling criteria without any assumption on data? This paper proposes a general active learning framework that effectively fuses the two criteria. Inspired by a two-sample discrepancy problem, triple measures are elaborately designed to guarantee that the query samples not only possess the representativeness of the unlabeled data but also reveal the diversity of the labeled data. Any appropriate similarity measure can be employed to construct the triple measures. Meanwhile, an uncertain measure is leveraged to generate the informativeness criterion, which can be carried out in different ways. Rooted in this framework, a practical active learning algorithm is proposed, which exploits a radial basis function together with the estimated probabilities to construct the triple measures and a modified best-versus-second-best strategy to construct the uncertain measure, respectively. Experimental results on benchmark datasets demonstrate that our algorithm consistently achieves superior performance over the state-of-the-art active learning algorithms.

Competency and an active learning program in undergraduate nursing education.

PubMed

Shin, Hyunsook; Sok, Sohyune; Hyun, Kyung Sun; Kim, Mi Ja

2015-03-01

To evaluate the effect of an active learning program on competency of senior students. Active learning strategies have been used to help students achieve desired nursing competency, but their effectiveness has not been systematically examined. A descriptive, cross-sectional comparative design was used. Two cohort group comparisons using t-test were made: one in an active learning group and the other in a traditional learning group. A total of 147 senior nursing students near graduation participated in this study: 73 in 2010 and 74 in 2013. The active learning program incorporated high-fidelity simulation, situation-based case studies, standardized patients, audio-video playback, reflective activities and technology such as a SmartPad-based program. The overall scores of the nursing competency in the active group were significantly higher than those in the traditional group. Of five overall subdomains, the scores of the special and general clinical performance competency, critical thinking and human understanding were significantly higher in the active group than in the traditional group. Importance-performance analysis showed that all five subdomains of the active group clustered in the high importance and high performance quadrant, indicating significantly better achievements. In contrast, the students in the traditional group showed scattered patterns in three quadrants, excluding the low importance and low performance quadrants. This pattern indicates that the traditional learning method did not yield the high performance in most important areas. The findings of this study suggest that an active learning strategy is useful for helping undergraduate students to gain competency. © 2014 John Wiley & Sons Ltd.

Workjobs: Activity-Centered Learning for Early Childhood Education.

ERIC Educational Resources Information Center

Lorton, Mary Baratta

Based on the idea that through active involvement with the materials the child would draw out the generalizations within the material, a teacher's method of activity-centered learning for early childhood education is presented. The first section of the book deals with the development of language through workjobs, emphasizing perception, matching,…

Incorporating active learning in psychiatry education.

PubMed

Kumar, Sonia; McLean, Loyola; Nash, Louise; Trigwell, Keith

2017-06-01

We aim to summarise the active learning literature in higher education and consider its relevance for postgraduate psychiatry trainees, to inform the development of a new Formal Education Course (FEC): the Master of Medicine (Psychiatry) at the University of Sydney. We undertook a literature search on 'active learning', 'flipped classroom', 'problem-based learning' and 'psychiatry education'. The effectiveness of active learning pedagogy in higher education is well supported by evidence; however, there have been few psychiatry-specific studies. A new 'flipped classroom' format was developed for the Master of Medicine (Psychiatry). Postgraduate psychiatry training is an active learning environment; the pedagogical approach to FECs requires further evaluation.

Active Learning in a Math for Liberal Arts Classroom

ERIC Educational Resources Information Center

Lenz, Laurie

2015-01-01

Inquiry-based learning is a topic of growing interest in the mathematical community. Much of the focus has been on using these methods in calculus and higher-level classes. This article describes the design and implementation of a set of inquiry-based learning activities in a Math for Liberal Arts course at a small, private, Catholic college.…

Development of active learning modules in pharmacology for small group teaching.

PubMed

Tripathi, Raakhi K; Sarkate, Pankaj V; Jalgaonkar, Sharmila V; Rege, Nirmala N

2015-01-01

Current teaching in pharmacology in undergraduate medical curriculum in India is primarily drug centered and stresses imparting factual knowledge rather than on pharmacotherapeutic skills. These skills would be better developed through active learning by the students. Hence modules that will encourage active learning were developed and compared with traditional methods within the Seth GS Medical College, Mumbai. After Institutional Review Board approval, 90 second year undergraduate medical students who consented were randomized into six sub-groups, each with 15 students. Pre-test was administered. The three sub-groups were taught a topic using active learning modules (active learning groups), which included problems on case scenarios, critical appraisal of prescriptions and drug identification. The remaining three sub-groups were taught the same topic in a conventional tutorial mode (tutorial learning groups). There was crossover for the second topic. Performance was assessed using post-test. Questionnaires with Likert-scaled items were used to assess feedback on teaching technique, student interaction and group dynamics. The active and tutorial learning groups differed significantly in their post-test scores (11.3 ± 1.9 and 15.9 ± 2.7, respectively, P < 0.05). In students' feedback, 69/90 students had perceived the active learning session as interactive (vs. 37/90 students in tutorial group) and enhanced their understanding vs. 56/90 in tutorial group), aroused intellectual curiosity (47/90 students of active learning group vs. 30/90 in tutorial group) and provoked self-learning (41/90 active learning group vs. 14/90 in tutorial group). Sixty-four students in the active learning group felt that questioning each other helped in understanding the topic, which was the experience of 25/90 students in tutorial group. Nevertheless, students (55/90) preferred tutorial mode of learning to help them score better in their examinations. In this study, students preferred

Instructional Utility and Learning Efficacy of Common Active Learning Strategies

ERIC Educational Resources Information Center

McConell, David A.; Chapman, LeeAnna; Czaijka, C. Douglas; Jones, Jason P.; Ryker, Katherine D.; Wiggen, Jennifer

2017-01-01

The adoption of active learning instructional practices in college science, technology, engineering, and mathematics (STEM) courses has been shown to result in improvements in student learning, contribute to increased retention rates, and reduce the achievement gap among different student populations. Descriptions of active learning strategies…

An Activity-Based Learning Approach for Key Geographical Information Systems (GIS) Concepts

ERIC Educational Resources Information Center

Srivastava, Sanjeev Kumar; Tait, Cynthia

2012-01-01

This study presents the effect of active learning methods of concepts in geographical information systems where students participated in a series of interlocked learning experiences. These activities spanned several teaching weeks and involved the creation of a hand drawn map that was scanned and geo-referenced with locations' coordinates derived…

Teachers' Everyday Professional Development: Mapping Informal Learning Activities, Antecedents, and Learning Outcomes

ERIC Educational Resources Information Center

Kyndt, Eva; Gijbels, David; Grosemans, Ilke; Donche, Vincent

2016-01-01

Although a lot is known about teacher development by means of formal learning activities, research on teachers' everyday learning is limited. In the current systematic review, we analyzed 74 studies focusing on teachers' informal learning to identify teachers' learning activities, antecedents for informal learning, and learning outcomes. In…

Connecting Family Learning and Active Citizenship

ERIC Educational Resources Information Center

Flanagan, Mary

2009-01-01

In Ireland family learning and active citizenship has not been linked together until 2006. It was while the Clare Family Learning Project was involved in a family learning EU learning network project, that a suggestion to create a new partnership project linking both areas was made and FACE IT! was born (Families and Active Citizenship…

Create a good learning environment and motivate active learning enthusiasm

NASA Astrophysics Data System (ADS)

Bi, Weihong; Fu, Guangwei; Fu, Xinghu; Zhang, Baojun; Liu, Qiang; Jin, Wa

2017-08-01

In view of the current poor learning initiative of undergraduates, the idea of creating a good learning environment and motivating active learning enthusiasm is proposed. In practice, the professional tutor is allocated and professional introduction course is opened for college freshman. It can promote communication between the professional teachers and students as early as possible, and guide students to know and devote the professional knowledge by the preconceived form. Practice results show that these solutions can improve the students interest in learning initiative, so that the active learning and self-learning has become a habit in the classroom.

Active Learning Strategies for the Mathematics Classroom

ERIC Educational Resources Information Center

Kerrigan, John

2018-01-01

Active learning involves students engaging with course content beyond lecture: through writing, applets, simulations, games, and more (Prince, 2004). As mathematics is often viewed as a subject area that is taught using more traditional methods (Goldsmith & Mark, 1999), there are actually many simple ways to make undergraduate mathematics…

Navigating the Active Learning Swamp: Creating an Inviting Environment for Learning.

ERIC Educational Resources Information Center

Johnson, Marie C.; Malinowski, Jon C.

2001-01-01

Reports on a survey of faculty members (n=29) asking them to define active learning, to rate how effectively different teaching techniques contribute to active learning, and to list the three teaching techniques they use most frequently. Concludes that active learning requires establishing an environment rather than employing a specific teaching…

Development of Speaking Skills through Activity Based Learning at the Elementary Level

ERIC Educational Resources Information Center

Ul-Haq, Zahoor; Khurram, Bushra Ahmed; Bangash, Arshad Khan

2017-01-01

Purpose: This paper discusses an effective instructional method called "activity based learning" that can be used to develop the speaking skills of students in the elementary school level. The present study was conducted to determine the effect of activity based learning on the development of the speaking skills of low and high achievers…

Integrated Method of Teaching in Web Quest Activity and Its Impact on Undergraduate Students’ Cognition and Learning Behaviors: A Future Trend in Medical Education

PubMed Central

Jahromi, Zohreh Badiyepeymaie; Mosalanejad, Leili

2015-01-01

Introduction: Web Quest is one of the new ways of teaching and learning that is based on research, and includes the principles of learning and cognitive activities, such as collaborative learning, social and cognitive learning, and active learning, and increases motivation. The aim of this study is to evaluate the Web Quest influence on students’ learning behaviors. Materials and Methods: In this quasi-experimental study, which was performed on undergraduates taking a psychiatric course at Jahrom University of Medical Sciences, simple sampling was used to select the cases to be studied; the students entered the study through census and were trained according toWeb Quest methodology. The procedure was to present the course as a case study and team work. Each topic included discussing concepts and then patient’s treatment and the communicative principles for two weeks. Active participation of the students in response to the scenario and introduced problem was equal to preparing scientific videos about the disease and collecting the latest medical treatment for the disease from the Internet. Three questionnaires, including the self-directed learning Questionnaire, teamwork evaluation Questionnaire (value of team), and Buffard self-regulated Questionnaire, were the data gathering tools. Results: The results showed that the average of self-regulated learning and self-directed learning (SDL) increased after the educational intervention. However, the increase was not significant. On the other hand, problem solving (P=0.001) and the value of teamwork (P=0.002), apart from increasing the average, had significant statistical values. Conclusions: In view of Web Quest’s positive impacts on students’ learning behaviors, problem solving and teamwork, the effective use of active learning and teaching practices and use of technology in medical education are recommended. PMID:25946931

Learning style and teaching method preferences of Saudi students of physical therapy

PubMed Central

Al Maghraby, Mohamed A.; Alshami, Ali M.

2013-01-01

Context: To the researchers’ knowledge, there are no published studies that have investigated the learning styles and preferred teaching methods of physical therapy students in Saudi Arabia. Aim: The study was conducted to determine the learning styles and preferred teaching methods of Saudi physical therapy students. Settings and Design: A cross-sectional study design. Materials and Methods: Fifty-three Saudis studying physical therapy (21 males and 32 females) participated in the study. The principal researcher gave an introductory lecture to explain the different learning styles and common teaching methods. Upon completion of the lecture, questionnaires were distributed, and were collected on completion. Statistical Analysis Used: Percentages were calculated for the learning styles and teaching methods. Pearson’s correlations were performed to investigate the relationship between them. Results: More than 45 (85%) of the students rated hands-on training as the most preferred teaching method. Approximately 30 (57%) students rated the following teaching methods as the most preferred methods: “Advanced organizers,” “demonstrations,” and “multimedia activities.” Although 31 (59%) students rated the concrete-sequential learning style the most preferred, these students demonstrated mixed styles on the other style dimensions: Abstract-sequential, abstract-random, and concrete-random. Conclusions: The predominant concrete-sequential learning style is consistent with the most preferred teaching method (hands-on training). The high percentage of physical therapy students whose responses were indicative of mixed learning styles suggests that they can accommodate multiple teaching methods. It is recommended that educators consider the diverse learning styles of the students and utilize a variety of teaching methods in order to promote an optimal learning environment for the students. PMID:24672278

Measuring the learning effectiveness of Web-based teacher professional development in the hypothesis based learning method of teaching science

NASA Astrophysics Data System (ADS)

Wilson, Penne L.

2007-12-01

interviews; Part II is a series of embedded, explanatory case studies which present an in-depth examination of three of the participants of this study to better understand the factors that influenced their learning of the HbL method of teaching science. Findings of this study indicate that teachers did learn the HbL method of teaching science through the online HbL workshop, the only place instruction in the HbL method was available. The structure of the online workshop which first introduced an element of the HbL process to teachers, next asked them to conduct a personal activity, and then to use a similar activity in their classrooms with students, and to reflect on the outcome of the activity, was successful in teaching the HbL method. Teachers expressed satisfaction with the structure of the online workshop and with the HbL method which they believed made learning science fun and which encouraged students to become more creative and critical thinkers, and also increased their knowledge of science concepts. The main motivation for learning HbL and the primary factor that led to teachers' satisfaction was the students' positive reaction to the HbL method. The teachers were encouraged because the students loved to do science after being introduced to HbL. Also identified in this study was the need by a participant for the inclusion of video models of teachers using the HbL method within the HbL online workshop. This suggestion demonstrated the need to incorporate more learning styles in the activities included in the HbL workshop in order to appeal to a wider audience of online learners.

"Bringing Life to Learning": A Study of Active Learning in Hospitality Education

ERIC Educational Resources Information Center

Chau, Salott; Cheung, Catherine

2017-01-01

Active learning connects students to the real life situations they will encounter in their future jobs. In hospitality education, active learning implements various lively, fun activities to introduce practical scenarios students may experience in their hospitality careers. This study identifies 18 essential active-learning items of hospitality…

Learning Science, Learning about Science, Doing Science: Different Goals Demand Different Learning Methods

ERIC Educational Resources Information Center

Hodson, Derek

2014-01-01

This opinion piece paper urges teachers and teacher educators to draw careful distinctions among four basic learning goals: learning science, learning about science, doing science and learning to address socio-scientific issues. In elaboration, the author urges that careful attention is paid to the selection of teaching/learning methods that…

Computer game-based and traditional learning method: a comparison regarding students' knowledge retention.

PubMed

Rondon, Silmara; Sassi, Fernanda Chiarion; Furquim de Andrade, Claudia Regina

2013-02-25

Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students' prior knowledge (i.e. before undergoing the learning method), short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method) were assessed with a multiple choice questionnaire. Students' performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students' short and long-term knowledge retention.

The impact of rigorous mathematical thinking as learning method toward geometry understanding

NASA Astrophysics Data System (ADS)

Nugraheni, Z.; Budiyono, B.; Slamet, I.

2018-05-01

To reach higher order thinking skill, needed to be mastered the conceptual understanding. RMT is a unique realization of the cognitive conceptual construction approach based on Mediated Learning Experience (MLE) theory by Feurstein and Vygotsky’s sociocultural theory. This was quasi experimental research which was comparing the experimental class that was given Rigorous Mathematical Thinking (RMT) as learning method and control class that was given Direct Learning (DL) as the conventional learning activity. This study examined whether there was different effect of two learning method toward conceptual understanding of Junior High School students. The data was analyzed by using Independent t-test and obtained a significant difference of mean value between experimental and control class on geometry conceptual understanding. Further, by semi-structure interview known that students taught by RMT had deeper conceptual understanding than students who were taught by conventional way. By these result known that Rigorous Mathematical Thinking (RMT) as learning method have positive impact toward Geometry conceptual understanding.

Utility of Self-Made Crossword Puzzles as an Active Learning Method to Study Biochemistry in Undergraduate Education

ERIC Educational Resources Information Center

Coticone, Sulekha Rao

2013-01-01

To incorporate an active learning component in a one-semester biochemistry course, students were asked to create crossword puzzles using key concepts. Student observations on the use of self-made crossword puzzles as an active-learning instructional tool were collected using a 5-point Likert survey at the end of the semester. A majority of the…

Computer game-based and traditional learning method: a comparison regarding students’ knowledge retention

PubMed Central

2013-01-01

Background Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Methods Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students’ prior knowledge (i.e. before undergoing the learning method), short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method) were assessed with a multiple choice questionnaire. Students’ performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Results Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. Conclusions The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students’ short and long-term knowledge retention. PMID:23442203

Developing Interactive E-Learning Activities

ERIC Educational Resources Information Center

Watkins, Ryan

2005-01-01

Although e-learning can offer interactive and engaging learning experiences, the creative ideas that are necessary to create such environments are not always easy to come up with when designing, developing, or teaching e-learning courses. E-learning activities use online technologies such as chat rooms, discussion boards, or email to facilitate…

Reinforcement Learning with Orthonormal Basis Adaptation Based on Activity-Oriented Index Allocation

NASA Astrophysics Data System (ADS)

Satoh, Hideki

An orthonormal basis adaptation method for function approximation was developed and applied to reinforcement learning with multi-dimensional continuous state space. First, a basis used for linear function approximation of a control function is set to an orthonormal basis. Next, basis elements with small activities are replaced with other candidate elements as learning progresses. As this replacement is repeated, the number of basis elements with large activities increases. Example chaos control problems for multiple logistic maps were solved, demonstrating that the method for adapting an orthonormal basis can modify a basis while holding the orthonormality in accordance with changes in the environment to improve the performance of reinforcement learning and to eliminate the adverse effects of redundant noisy states.

Reducing Student Resistance to Active Learning: Strategies for Instructors

ERIC Educational Resources Information Center

Finelli, Cynthia J.; Nguyen, Kevin; DeMonbrun, Matthew; Borrego, Maura; Prince, Michael; Husman, Jennifer; Henderson, Charles; Shekhar, Prateek; Waters, Cynthia K.

2018-01-01

In spite of considerable evidence of the effectiveness of active learning and other contemporary teaching methods, barriers to adoption of those methods, such as possible student resistance, continue to exist. This study addresses student resistance by analyzing data from 1,051 students who completed our Student Response to Instructional Practices…

Using active learning strategies to investigate student learning and attitudes in a large enrollment, introductory geology course

NASA Astrophysics Data System (ADS)

Berry, Stacy Jane

There has been an increased emphasis for college instruction to incorporate more active and collaborative involvement of students in the learning process. These views have been asserted by The Association of American Colleges (AAC), the National Science Foundation (NSF), and The National Research Counsel (NRC), which are advocating for the modification of traditional instructional techniques to allow students the opportunity to be more cooperative (Task Group on General Education, 1988). This has guided educators and facilitators into shifting teaching paradigms from a teacher centered to a more student-centered curriculum. The present study investigated achievement outcomes and attitudes of learners in a large enrollment (n ~ 200), introductory geology course using a student centered learning cycle format of instruction versus another similar section that used a traditional lecture format. Although the course is a recruiting class for majors, over 95% of the students that enroll are non-majors. Measurements of academic evaluation were through four unit exams, classroom communication systems, weekly web-based homework, in-class activities, and a thematic collaborative poster/paper project and presentation. The qualitative methods to investigate the effectiveness of the teaching design included: direct observation, self-reporting about learning, and open-ended interviews. By disaggregating emerging data, we tried to concentrate on patterns and causal relationships between achievement performance and attitudes regarding learning geology. Statistical analyses revealed positive relationships between student engagement in supplemental activities and achievement mean scores within and between the two sections. Completing weekly online homework had the most robust relationship with overall achievement performance. Contrary to expectations, a thematic group project only led to modest gains in achievement performance, although the social and professional gains could be

Is Peer Interaction Necessary for Optimal Active Learning?

ERIC Educational Resources Information Center

Linton, Debra L.; Farmer, Jan Keith; Peterson, Ernie

2014-01-01

Meta-analyses of active-learning research consistently show that active-learning techniques result in greater student performance than traditional lecture-based courses. However, some individual studies show no effect of active-learning interventions. This may be due to inexperienced implementation of active learning. To minimize the effect of…

Student Perceptions of Active Learning

ERIC Educational Resources Information Center

Lumpkin, Angela; Achen, Rebecca M.; Dodd, Regan K.

2015-01-01

A paradigm shift from lecture-based courses to interactive classes punctuated with engaging, student-centered learning activities has begun to characterize the work of some teachers in higher education. Convinced through the literature of the values of using active learning strategies, we assessed through an action research project in five college…

Active-Learning versus Teacher-Centered Instruction for Learning Acids and Bases

ERIC Educational Resources Information Center

Sesen, Burcin Acar; Tarhan, Leman

2011-01-01

Background and purpose: Active-learning as a student-centered learning process has begun to take more interest in constructing scientific knowledge. For this reason, this study aimed to investigate the effectiveness of active-learning implementation on high-school students' understanding of "acids and bases". Sample: The sample of this…

Active learning of cortical connectivity from two-photon imaging data

PubMed Central

Wang, Ye; Dunson, David; Sapiro, Guillermo; Ringach, Dario

2018-01-01

Understanding how groups of neurons interact within a network is a fundamental question in system neuroscience. Instead of passively observing the ongoing activity of a network, we can typically perturb its activity, either by external sensory stimulation or directly via techniques such as two-photon optogenetics. A natural question is how to use such perturbations to identify the connectivity of the network efficiently. Here we introduce a method to infer sparse connectivity graphs from in-vivo, two-photon imaging of population activity in response to external stimuli. A novel aspect of the work is the introduction of a recommended distribution, incrementally learned from the data, to optimally refine the inferred network. Unlike existing system identification techniques, this “active learning” method automatically focuses its attention on key undiscovered areas of the network, instead of targeting global uncertainty indicators like parameter variance. We show how active learning leads to faster inference while, at the same time, provides confidence intervals for the network parameters. We present simulations on artificial small-world networks to validate the methods and apply the method to real data. Analysis of frequency of motifs recovered show that cortical networks are consistent with a small-world topology model. PMID:29718955

Learning Science, Learning about Science, Doing Science: Different goals demand different learning methods

NASA Astrophysics Data System (ADS)

Hodson, Derek

2014-10-01

This opinion piece paper urges teachers and teacher educators to draw careful distinctions among four basic learning goals: learning science, learning about science, doing science and learning to address socio-scientific issues. In elaboration, the author urges that careful attention is paid to the selection of teaching/learning methods that recognize key differences in learning goals and criticizes the common assertion that 'current wisdom advocates that students best learn science through an inquiry-oriented teaching approach' on the grounds that conflating the distinction between learning by inquiry and engaging in scientific inquiry is unhelpful in selecting appropriate teaching/learning approaches.

Linking Mission to Learning Activities for Assurance of Learning

ERIC Educational Resources Information Center

Yeung, Shirley Mo-ching

2011-01-01

Can accreditation-related requirements and mission statements measure learning outcomes? This study focuses on triangulating accreditation-related requirements with mission statements and learning activities to learning outcomes. This topic has not been comprehensively explored in the past. After looking into the requirements of AACSB, ISO, and…

Simultaneous anatomical sketching as learning by doing method of teaching human anatomy

PubMed Central

Noorafshan, Ali; Hoseini, Leila; Amini, Mitra; Dehghani, Mohammad-Reza; Kojuri, Javad; Bazrafkan, Leila

2014-01-01

Objective: Learning by lecture is a passive experience. Many innovative techniques have been presented to stimulate students to assume a more active attitude toward learning. In this study, simultaneous sketch drawing, as an interactive learning technique was applied to teach anatomy to the medical students. Materials and Methods: We reconstructed a fun interactive model of teaching anatomy as simultaneous anatomic sketching. To test the model's instruction effectiveness, we conducted a quasi- experimental study and then the students were asked to write their learning experiences in their portfolio, also their view was evaluated by a questionnaire. Results: The results of portfolio evaluation revealed that students believed that this method leads to deep learning and understanding anatomical subjects better. Evaluation of the students’ views on this teaching approach was showed that, more than 80% of the students were agreed or completely agreed with this statement that leaning anatomy concepts are easier and the class is less boring with this method. More than 60% of the students were agreed or completely agreed to sketch anatomical figures with professor simultaneously. They also found the sketching make anatomy more attractive and it reduced the time for learning anatomy. These number of students were agree or completely agree that the method help them learning anatomical concept in anatomy laboratory. More than 80% of the students found the simultaneous sketching is a good method for learning anatomy overall. Conclusion: Sketch drawing, as an interactive learning technique, is an attractive for students to learn anatomy. PMID:25013843

Active Learning in Engineering Education: a (re)introduction

NASA Astrophysics Data System (ADS)

Lima, Rui M.; Andersson, Pernille Hammar; Saalman, Elisabeth

2017-01-01

The informal network 'Active Learning in Engineering Education' (ALE) has been promoting Active Learning since 2001. ALE creates opportunity for practitioners and researchers of engineering education to collaboratively learn how to foster learning of engineering students. The activities in ALE are centred on the vision that learners construct their knowledge based on meaningful activities and knowledge. In 2014, the steering committee of the ALE network reinforced the need to discuss the meaning of Active Learning and that was the base for this proposal for a special issue. More than 40 submissions were reviewed by the European Journal of Engineering Education community and this theme issue ended up with eight contributions, which are different both in their research and Active Learning approaches. These different Active Learning approaches are aligned with the different approaches that can be increasingly found in indexed journals.

Enhancing students' learning in problem based learning: validation of a self-assessment scale for active learning and critical thinking.

PubMed

Khoiriyah, Umatul; Roberts, Chris; Jorm, Christine; Van der Vleuten, C P M

2015-08-26

Problem based learning (PBL) is a powerful learning activity but fidelity to intended models may slip and student engagement wane, negatively impacting learning processes, and outcomes. One potential solution to solve this degradation is by encouraging self-assessment in the PBL tutorial. Self-assessment is a central component of the self-regulation of student learning behaviours. There are few measures to investigate self-assessment relevant to PBL processes. We developed a Self-assessment Scale on Active Learning and Critical Thinking (SSACT) to address this gap. We wished to demonstrated evidence of its validity in the context of PBL by exploring its internal structure. We used a mixed methods approach to scale development. We developed scale items from a qualitative investigation, literature review, and consideration of previous existing tools used for study of the PBL process. Expert review panels evaluated its content; a process of validation subsequently reduced the pool of items. We used structural equation modelling to undertake a confirmatory factor analysis (CFA) of the SSACT and coefficient alpha. The 14 item SSACT consisted of two domains "active learning" and "critical thinking." The factorial validity of SSACT was evidenced by all items loading significantly on their expected factors, a good model fit for the data, and good stability across two independent samples. Each subscale had good internal reliability (>0.8) and strongly correlated with each other. The SSACT has sufficient evidence of its validity to support its use in the PBL process to encourage students to self-assess. The implementation of the SSACT may assist students to improve the quality of their learning in achieving PBL goals such as critical thinking and self-directed learning.

Active Learning in the Middle Grades

ERIC Educational Resources Information Center

Edwards, Susan

2015-01-01

What is active learning and what does it look like in the classroom? If students are participating in active learning, they are playing a more engaged role in the learning process and are not overly reliant on the teacher (Bransford, Brown, & Cocking, 2003; Petress, 2008). The purpose of this article is to propose a framework to describe and…

Autonomous Motion Learning for Intra-Vehicular Activity Space Robot

NASA Astrophysics Data System (ADS)

Watanabe, Yutaka; Yairi, Takehisa; Machida, Kazuo

Space robots will be needed in the future space missions. So far, many types of space robots have been developed, but in particular, Intra-Vehicular Activity (IVA) space robots that support human activities should be developed to reduce human-risks in space. In this paper, we study the motion learning method of an IVA space robot with the multi-link mechanism. The advantage point is that this space robot moves using reaction force of the multi-link mechanism and contact forces from the wall as space walking of an astronaut, not to use a propulsion. The control approach is determined based on a reinforcement learning with the actor-critic algorithm. We demonstrate to clear effectiveness of this approach using a 5-link space robot model by simulation. First, we simulate that a space robot learn the motion control including contact phase in two dimensional case. Next, we simulate that a space robot learn the motion control changing base attitude in three dimensional case.

Active Learning Not Associated with Student Learning in a Random Sample of College Biology Courses

PubMed Central

Andrews, T. M.; Leonard, M. J.; Colgrove, C. A.; Kalinowski, S. T.

2011-01-01

Previous research has suggested that adding active learning to traditional college science lectures substantially improves student learning. However, this research predominantly studied courses taught by science education researchers, who are likely to have exceptional teaching expertise. The present study investigated introductory biology courses randomly selected from a list of prominent colleges and universities to include instructors representing a broader population. We examined the relationship between active learning and student learning in the subject area of natural selection. We found no association between student learning gains and the use of active-learning instruction. Although active learning has the potential to substantially improve student learning, this research suggests that active learning, as used by typical college biology instructors, is not associated with greater learning gains. We contend that most instructors lack the rich and nuanced understanding of teaching and learning that science education researchers have developed. Therefore, active learning as designed and implemented by typical college biology instructors may superficially resemble active learning used by education researchers, but lacks the constructivist elements necessary for improving learning. PMID:22135373

Simultaneous anatomical sketching as learning by doing method of teaching human anatomy.

PubMed

Noorafshan, Ali; Hoseini, Leila; Amini, Mitra; Dehghani, Mohammad-Reza; Kojuri, Javad; Bazrafkan, Leila

2014-01-01

Learning by lecture is a passive experience. Many innovative techniques have been presented to stimulate students to assume a more active attitude toward learning. In this study, simultaneous sketch drawing, as an interactive learning technique was applied to teach anatomy to the medical students. We reconstructed a fun interactive model of teaching anatomy as simultaneous anatomic sketching. To test the model's instruction effectiveness, we conducted a quasi- experimental study and then the students were asked to write their learning experiences in their portfolio, also their view was evaluated by a questionnaire. The results of portfolio evaluation revealed that students believed that this method leads to deep learning and understanding anatomical subjects better. Evaluation of the students' views on this teaching approach was showed that, more than 80% of the students were agreed or completely agreed with this statement that leaning anatomy concepts are easier and the class is less boring with this method. More than 60% of the students were agreed or completely agreed to sketch anatomical figures with professor simultaneously. They also found the sketching make anatomy more attractive and it reduced the time for learning anatomy. These number of students were agree or completely agree that the method help them learning anatomical concept in anatomy laboratory. More than 80% of the students found the simultaneous sketching is a good method for learning anatomy overall. Sketch drawing, as an interactive learning technique, is an attractive for students to learn anatomy.

In Defense of Active Learning

ERIC Educational Resources Information Center

Pica, Rae

2008-01-01

Effective early childhood teachers use what they know about and have observed in young children to design programs to meet children's developmental needs. Play and active learning are key tools to address those needs and facilitate children's early education. In this article, the author discusses the benefits of active learning in the education of…

Like a Chameleon: A Beginning Teacher's Journey to Implement Active Learning

ERIC Educational Resources Information Center

Edwards, Susan

2017-01-01

The purpose of this study was to follow the learning trajectory of a beginning teacher attempting to implement active learning instructional methods in a middle grades classroom. The study utilized a qualitative case study methodological approach with the researcher in the role of participant observer. Three research questions were explored: the…

Information Activities and Appropriation in Teacher Trainees' Digital, Group-Based Learning

ERIC Educational Resources Information Center

Hanell, Fredrik

2016-01-01

Introduction: This paper reports results from an ethnographic study of teacher trainees' information activities in digital, group-based learning and their relation to the interplay between use and appropriation of digital tools and the learning environment. Method: The participants in the present study are 249 pre-school teacher trainees in…

Identifying Active Travel Behaviors in Challenging Environments Using GPS, Accelerometers, and Machine Learning Algorithms.

PubMed

Ellis, Katherine; Godbole, Suneeta; Marshall, Simon; Lanckriet, Gert; Staudenmayer, John; Kerr, Jacqueline

2014-01-01

Active travel is an important area in physical activity research, but objective measurement of active travel is still difficult. Automated methods to measure travel behaviors will improve research in this area. In this paper, we present a supervised machine learning method for transportation mode prediction from global positioning system (GPS) and accelerometer data. We collected a dataset of about 150 h of GPS and accelerometer data from two research assistants following a protocol of prescribed trips consisting of five activities: bicycling, riding in a vehicle, walking, sitting, and standing. We extracted 49 features from 1-min windows of this data. We compared the performance of several machine learning algorithms and chose a random forest algorithm to classify the transportation mode. We used a moving average output filter to smooth the output predictions over time. The random forest algorithm achieved 89.8% cross-validated accuracy on this dataset. Adding the moving average filter to smooth output predictions increased the cross-validated accuracy to 91.9%. Machine learning methods are a viable approach for automating measurement of active travel, particularly for measuring travel activities that traditional accelerometer data processing methods misclassify, such as bicycling and vehicle travel.

Active-learning strategies in computer-assisted drug discovery.

PubMed

Reker, Daniel; Schneider, Gisbert

2015-04-01

High-throughput compound screening is time and resource consuming, and considerable effort is invested into screening compound libraries, profiling, and selecting the most promising candidates for further testing. Active-learning methods assist the selection process by focusing on areas of chemical space that have the greatest chance of success while considering structural novelty. The core feature of these algorithms is their ability to adapt the structure-activity landscapes through feedback. Instead of full-deck screening, only focused subsets of compounds are tested, and the experimental readout is used to refine molecule selection for subsequent screening cycles. Once implemented, these techniques have the potential to reduce costs and save precious materials. Here, we provide a comprehensive overview of the various computational active-learning approaches and outline their potential for drug discovery. Copyright © 2014 Elsevier Ltd. All rights reserved.

Teaching Research Methods and Statistics in eLearning Environments: Pedagogy, Practical Examples, and Possible Futures

PubMed Central

Rock, Adam J.; Coventry, William L.; Morgan, Methuen I.; Loi, Natasha M.

2016-01-01

Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology. PMID:27014147

Teaching Research Methods and Statistics in eLearning Environments: Pedagogy, Practical Examples, and Possible Futures.

PubMed

Rock, Adam J; Coventry, William L; Morgan, Methuen I; Loi, Natasha M

2016-01-01

Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology.

An efficient cardiac mapping strategy for radiofrequency catheter ablation with active learning.

PubMed

Feng, Yingjing; Guo, Ziyan; Dong, Ziyang; Zhou, Xiao-Yun; Kwok, Ka-Wai; Ernst, Sabine; Lee, Su-Lin

2017-07-01

A major challenge in radiofrequency catheter ablation procedures is the voltage and activation mapping of the endocardium, given a limited mapping time. By learning from expert interventional electrophysiologists (operators), while also making use of an active-learning framework, guidance on performing cardiac voltage mapping can be provided to novice operators or even directly to catheter robots. A learning from demonstration (LfD) framework, based upon previous cardiac mapping procedures performed by an expert operator, in conjunction with Gaussian process (GP) model-based active learning, was developed to efficiently perform voltage mapping over right ventricles (RV). The GP model was used to output the next best mapping point, while getting updated towards the underlying voltage data pattern as more mapping points are taken. A regularized particle filter was used to keep track of the kernel hyperparameter used by GP. The travel cost of the catheter tip was incorporated to produce time-efficient mapping sequences. The proposed strategy was validated on a simulated 2D grid mapping task, with leave-one-out experiments on 25 retrospective datasets, in an RV phantom using the Stereotaxis Niobe ® remote magnetic navigation system, and on a tele-operated catheter robot. In comparison with an existing geometry-based method, regression error was reduced and was minimized at a faster rate over retrospective procedure data. A new method of catheter mapping guidance has been proposed based on LfD and active learning. The proposed method provides real-time guidance for the procedure, as well as a live evaluation of mapping sufficiency.

Identifying Active Travel Behaviors in Challenging Environments Using GPS, Accelerometers, and Machine Learning Algorithms

PubMed Central

Ellis, Katherine; Godbole, Suneeta; Marshall, Simon; Lanckriet, Gert; Staudenmayer, John; Kerr, Jacqueline

2014-01-01

Background: Active travel is an important area in physical activity research, but objective measurement of active travel is still difficult. Automated methods to measure travel behaviors will improve research in this area. In this paper, we present a supervised machine learning method for transportation mode prediction from global positioning system (GPS) and accelerometer data. Methods: We collected a dataset of about 150 h of GPS and accelerometer data from two research assistants following a protocol of prescribed trips consisting of five activities: bicycling, riding in a vehicle, walking, sitting, and standing. We extracted 49 features from 1-min windows of this data. We compared the performance of several machine learning algorithms and chose a random forest algorithm to classify the transportation mode. We used a moving average output filter to smooth the output predictions over time. Results: The random forest algorithm achieved 89.8% cross-validated accuracy on this dataset. Adding the moving average filter to smooth output predictions increased the cross-validated accuracy to 91.9%. Conclusion: Machine learning methods are a viable approach for automating measurement of active travel, particularly for measuring travel activities that traditional accelerometer data processing methods misclassify, such as bicycling and vehicle travel. PMID:24795875

Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets.

PubMed

Korotcov, Alexandru; Tkachenko, Valery; Russo, Daniel P; Ekins, Sean

2017-12-04

Machine learning methods have been applied to many data sets in pharmaceutical research for several decades. The relative ease and availability of fingerprint type molecular descriptors paired with Bayesian methods resulted in the widespread use of this approach for a diverse array of end points relevant to drug discovery. Deep learning is the latest machine learning algorithm attracting attention for many of pharmaceutical applications from docking to virtual screening. Deep learning is based on an artificial neural network with multiple hidden layers and has found considerable traction for many artificial intelligence applications. We have previously suggested the need for a comparison of different machine learning methods with deep learning across an array of varying data sets that is applicable to pharmaceutical research. End points relevant to pharmaceutical research include absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties, as well as activity against pathogens and drug discovery data sets. In this study, we have used data sets for solubility, probe-likeness, hERG, KCNQ1, bubonic plague, Chagas, tuberculosis, and malaria to compare different machine learning methods using FCFP6 fingerprints. These data sets represent whole cell screens, individual proteins, physicochemical properties as well as a data set with a complex end point. Our aim was to assess whether deep learning offered any improvement in testing when assessed using an array of metrics including AUC, F1 score, Cohen's kappa, Matthews correlation coefficient and others. Based on ranked normalized scores for the metrics or data sets Deep Neural Networks (DNN) ranked higher than SVM, which in turn was ranked higher than all the other machine learning methods. Visualizing these properties for training and test sets using radar type plots indicates when models are inferior or perhaps over trained. These results also suggest the need for assessing deep learning further

Passing the baton: Mentoring for adoption of active-learning pedagogies by research-active junior faculty.

PubMed

Grimes, Catherine Leimkuhler; White, Harold B

2015-01-01

There are barriers to adoption of research-based teaching methods. Professional development workshops may inform faculty of these methods, but effective adoption often does not follow. In addition, newly-minted research-active faculty are often overwhelmed by the many new responsibilities (grant writing, group management, laboratory setup, teaching) that accompany the position and normally do not have the time to consider novel teaching approaches. This case study documents how over a three-year period, the responsibility for teaching a nontraditional "Introduction to Biochemistry" course in a problem-based learning format was successfully transferred from a senior faculty member nearing retirement (HBW) to a newly-hired research-active assistant professor (CLG). We describe our apprenticeship project involving modeling, scaffolding, fading, and coaching. We suggest that involving faculty in active-learning pedagogy early in their career with mentoring by senior faculty overcomes barriers to adopting these methods. This case describes a specific example from which potentially useful elements can be adopted and adapted wherever biochemistry is taught. © 2015 The International Union of Biochemistry and Molecular Biology.

An active learning curriculum improves fellows' knowledge and faculty teaching skills.

PubMed

Inra, Jennifer A; Pelletier, Stephen; Kumar, Navin L; Barnes, Edward L; Shields, Helen M

2017-01-01

Traditional didactic lectures are the mainstay of teaching for graduate medical education, although this method may not be the most effective way to transmit information. We created an active learning curriculum for Brigham and Women's Hospital (BWH) gastroenterology fellows to maximize learning. We evaluated whether this new curriculum improved perceived knowledge acquisition and knowledge base. In addition, our study assessed whether coaching faculty members in specific methods to enhance active learning improved their perceived teaching and presentation skills. We compared the Gastroenterology Training Exam (GTE) scores before and after the implementation of this curriculum to assess whether an improved knowledge base was documented. In addition, fellows and faculty members were asked to complete anonymous evaluations regarding their learning and teaching experiences. Fifteen fellows were invited to 12 lectures over a 2-year period. GTE scores improved in the areas of stomach ( p <0.001), general gastroenterology ( p =0.005), esophagus ( p <0.001), and small bowel ( p =0.001), and the total score ( p =0.001) between pre- and postimplementation of the active learning curriculum. Scores in hepatology, as well as biliary and pancreatic study, showed a trend toward improvement ( p >0.05). All fellows believed the lectures were helpful, felt more prepared to take the GTE, and preferred the interactive format to traditional didactic lectures. All lecturers agreed that they acquired new teaching skills, improved teaching and presentation skills, and learned new tools that could help them teach better in the future. An active learning curriculum is preferred by GI fellows and may be helpful for improving transmission of information in any specialty in medical education. Individualized faculty coaching sessions demonstrating new ways to transmit information may be important for an individual faculty member's teaching excellence.

Active Learning in Engineering Education: A (Re)Introduction

ERIC Educational Resources Information Center

Lima, Rui M.; Andersson, Pernille Hammar; Saalman, Elisabeth

2017-01-01

The informal network "Active Learning in Engineering Education" (ALE) has been promoting Active Learning since 2001. ALE creates opportunity for practitioners and researchers of engineering education to collaboratively learn how to foster learning of engineering students. The activities in ALE are centred on the vision that learners…

ASPECT: A Survey to Assess Student Perspective of Engagement in an Active-Learning Classroom

PubMed Central

Wiggins, Benjamin L.; Eddy, Sarah L.; Wener-Fligner, Leah; Freisem, Karen; Grunspan, Daniel Z.; Theobald, Elli J.; Timbrook, Jerry; Crowe, Alison J.

2017-01-01

The primary measure used to determine relative effectiveness of in-class activities has been student performance on pre/posttests. However, in today’s active-learning classrooms, learning is a social activity, requiring students to interact and learn from their peers. To develop effective active-learning exercises that engage students, it is important to gain a more holistic view of the student experience in an active-learning classroom. We have taken a mixed-methods approach to iteratively develop and validate a 16-item survey to measure multiple facets of the student experience during active-learning exercises. The instrument, which we call Assessing Student Perspective of Engagement in Class Tool (ASPECT), was administered to a large introductory biology class, and student responses were subjected to exploratory factor analysis. The 16 items loaded onto three factors that cumulatively explained 52% of the variation in student response: 1) value of activity, 2) personal effort, and 3) instructor contribution. ASPECT provides a rapid, easily administered means to measure student perception of engagement in an active-learning classroom. Gaining a better understanding of students’ level of engagement will help inform instructor best practices and provide an additional measure for comprehensively assessing the impact of different active-learning strategies. PMID:28495936

Learning Style Differences in the Perceived Effectiveness of Learning Activities

ERIC Educational Resources Information Center

Karns, Gary L.

2006-01-01

The learning style individual difference factor has long been a basis for understanding student preferences for various learning activities. Marketing educators have been advised to heavily invest in tailoring course design based on the learning style groups in their classes. A further exploration of the effects of learning style differences on…

Narratives of Experiential Learning: Students' Engagement in a Physical Activity-Based Service-Learning Course

ERIC Educational Resources Information Center

Whitley, Meredith A.; Walsh, David; Hayden, Laura; Gould, Daniel

2017-01-01

Purpose: Three undergraduate students' experiences in a physical activity-based service learning course are chronicled using narrative inquiry. Method: Data collection included demographics questionnaires, pre- and postservice interviews, reflection journals, postservice written reflections, and participant observations. The data were analyzed…

Incorporation of Socio-scientific Content into Active Learning Activities

NASA Astrophysics Data System (ADS)

King, D. B.; Lewis, J. E.; Anderson, K.; Latch, D.; Sutheimer, S.; Webster, G.; Moog, R.

2014-12-01

Active learning has gained increasing support as an effective pedagogical technique to improve student learning. One way to promote active learning in the classroom is the use of in-class activities in place of lecturing. As part of an NSF-funded project, a set of in-class activities have been created that use climate change topics to teach chemistry content. These activities use the Process Oriented Guided Inquiry Learning (POGIL) methodology. In this pedagogical approach a set of models and a series of critical thinking questions are used to guide students through the introduction to or application of course content. Students complete the activities in their groups, with the faculty member as a facilitator of learning. Through assigned group roles and intentionally designed activity structure, process skills, such as teamwork, communication, and information processing, are developed during completion of the activity. Each of these climate change activities contains a socio-scientific component, e.g., social, ethical and economic data. In one activity, greenhouse gases are used to explain the concept of dipole moment. Data about natural and anthropogenic production rates, global warming potential and atmospheric lifetimes for a list of greenhouse gases are presented. The students are asked to identify which greenhouse gas they would regulate, with a corresponding explanation for their choice. They are also asked to identify the disadvantages of regulating the gas they chose in the previous question. In another activity, where carbon sequestration is used to demonstrate the utility of a phase diagram, students use economic and environmental data to choose the best location for sequestration. Too often discussions about climate change (both in and outside the classroom) consist of purely emotional responses. These activities force students to use data to support their arguments and hypothesize about what other data could be used in the corresponding discussion to

Effect of Methods of Learning and Self Regulated Learning toward Outcomes of Learning Social Studies

ERIC Educational Resources Information Center

Tjalla, Awaluddin; Sofiah, Evi

2015-01-01

This research aims to reveal the influence of learning methods and self-regulated learning on students learning scores for Social Studies object. The research was done in Islamic Junior High School (MTs Manba'ul Ulum), Batuceper City Tangerang using quasi-experimental method. The research employed simple random technique to 28 students. Data were…

Automatic Earthquake Detection by Active Learning

NASA Astrophysics Data System (ADS)

Bergen, K.; Beroza, G. C.

2017-12-01

In recent years, advances in machine learning have transformed fields such as image recognition, natural language processing and recommender systems. Many of these performance gains have relied on the availability of large, labeled data sets to train high-accuracy models; labeled data sets are those for which each sample includes a target class label, such as waveforms tagged as either earthquakes or noise. Earthquake seismologists are increasingly leveraging machine learning and data mining techniques to detect and analyze weak earthquake signals in large seismic data sets. One of the challenges in applying machine learning to seismic data sets is the limited labeled data problem; learning algorithms need to be given examples of earthquake waveforms, but the number of known events, taken from earthquake catalogs, may be insufficient to build an accurate detector. Furthermore, earthquake catalogs are known to be incomplete, resulting in training data that may be biased towards larger events and contain inaccurate labels. This challenge is compounded by the class imbalance problem; the events of interest, earthquakes, are infrequent relative to noise in continuous data sets, and many learning algorithms perform poorly on rare classes. In this work, we investigate the use of active learning for automatic earthquake detection. Active learning is a type of semi-supervised machine learning that uses a human-in-the-loop approach to strategically supplement a small initial training set. The learning algorithm incorporates domain expertise through interaction between a human expert and the algorithm, with the algorithm actively posing queries to the user to improve detection performance. We demonstrate the potential of active machine learning to improve earthquake detection performance with limited available training data.

An active learning approach to Bloom's Taxonomy.

PubMed

Weigel, Fred K; Bonica, Mark

2014-01-01

As educators strive toward improving student learning outcomes, many find it difficult to instill their students with a deep understanding of the material the instructors share. One challenge lies in how to provide the material with a meaningful and engaging method that maximizes student understanding and synthesis. By following a simple strategy involving Active Learning across the 3 primary domains of Bloom's Taxonomy (cognitive, affective, and psychomotor), instructors can dramatically improve the quality of the lesson and help students retain and understand the information. By applying our strategy, instructors can engage their students at a deeper level and may even find themselves enjoying the process more.

Strategies for active learning in online continuing education.

PubMed

Phillips, Janet M

2005-01-01

Online continuing education and staff development is on the rise as the benefits of access, convenience, and quality learning are continuing to take shape. Strategies to enhance learning call for learner participation that is self-directed and independent, thus changing the educator's role from expert to coach and facilitator. Good planning of active learning strategies promotes optimal learning whether the learning content is presented in a course or a just-in-time short module. Active learning strategies can be used to enhance online learning during all phases of the teaching-learning process and can accommodate a variety of learning styles. Feedback from peers, educators, and technology greatly influences learner satisfaction and must be harnessed to provide effective learning experiences. Outcomes of active learning can be assessed online and implemented conveniently and successfully from the initiation of the course or module planning to the end of the evaluation process. Online learning has become accessible and convenient and allows the educator to track learner participation. The future of online education will continue to grow, and using active learning strategies will ensure that quality learning will occur, appealing to a wide variety of learning needs.

Technology Learning Activities I.

ERIC Educational Resources Information Center

International Technology Education Association, Reston, VA.

This guide contains 30 technology learning activities. Activities may contain all or some of the following: an introduction, objectives, materials and equipment, challenges, limitations, notes and investigations, resources and references used, and evaluation ideas. Activity titles are: (1) Occupations in Construction Technology; (2) Designing a…

Students' Satisfaction on Their Learning Process in Active Learning and Traditional Classrooms

ERIC Educational Resources Information Center

Hyun, Jung; Ediger, Ruth; Lee, Donghun

2017-01-01

Studies have shown Active Learning Classrooms [ALCs] help increase student engagement and improve student performance. However, remodeling all traditional classrooms to ALCs entails substantial financial burdens. Thus, an imperative question for institutions of higher education is whether active learning pedagogies can improve learning outcomes…

Minimization of annotation work: diagnosis of mammographic masses via active learning

NASA Astrophysics Data System (ADS)

Zhao, Yu; Zhang, Jingyang; Xie, Hongzhi; Zhang, Shuyang; Gu, Lixu

2018-06-01

The prerequisite for establishing an effective prediction system for mammographic diagnosis is the annotation of each mammographic image. The manual annotation work is time-consuming and laborious, which becomes a great hindrance for researchers. In this article, we propose a novel active learning algorithm that can adequately address this problem, leading to the minimization of the labeling costs on the premise of guaranteed performance. Our proposed method is different from the existing active learning methods designed for the general problem as it is specifically designed for mammographic images. Through its modified discriminant functions and improved sample query criteria, the proposed method can fully utilize the pairing of mammographic images and select the most valuable images from both the mediolateral and craniocaudal views. Moreover, in order to extend active learning to the ordinal regression problem, which has no precedent in existing studies, but is essential for mammographic diagnosis (mammographic diagnosis is not only a classification task, but also an ordinal regression task for predicting an ordinal variable, viz. the malignancy risk of lesions), multiple sample query criteria need to be taken into consideration simultaneously. We formulate it as a criteria integration problem and further present an algorithm based on self-adaptive weighted rank aggregation to achieve a good solution. The efficacy of the proposed method was demonstrated on thousands of mammographic images from the digital database for screening mammography. The labeling costs of obtaining optimal performance in the classification and ordinal regression task respectively fell to 33.8 and 19.8 percent of their original costs. The proposed method also generated 1228 wins, 369 ties and 47 losses for the classification task, and 1933 wins, 258 ties and 185 losses for the ordinal regression task compared to the other state-of-the-art active learning algorithms. By taking the

Minimization of annotation work: diagnosis of mammographic masses via active learning.

PubMed

Zhao, Yu; Zhang, Jingyang; Xie, Hongzhi; Zhang, Shuyang; Gu, Lixu

2018-05-22

The prerequisite for establishing an effective prediction system for mammographic diagnosis is the annotation of each mammographic image. The manual annotation work is time-consuming and laborious, which becomes a great hindrance for researchers. In this article, we propose a novel active learning algorithm that can adequately address this problem, leading to the minimization of the labeling costs on the premise of guaranteed performance. Our proposed method is different from the existing active learning methods designed for the general problem as it is specifically designed for mammographic images. Through its modified discriminant functions and improved sample query criteria, the proposed method can fully utilize the pairing of mammographic images and select the most valuable images from both the mediolateral and craniocaudal views. Moreover, in order to extend active learning to the ordinal regression problem, which has no precedent in existing studies, but is essential for mammographic diagnosis (mammographic diagnosis is not only a classification task, but also an ordinal regression task for predicting an ordinal variable, viz. the malignancy risk of lesions), multiple sample query criteria need to be taken into consideration simultaneously. We formulate it as a criteria integration problem and further present an algorithm based on self-adaptive weighted rank aggregation to achieve a good solution. The efficacy of the proposed method was demonstrated on thousands of mammographic images from the digital database for screening mammography. The labeling costs of obtaining optimal performance in the classification and ordinal regression task respectively fell to 33.8 and 19.8 percent of their original costs. The proposed method also generated 1228 wins, 369 ties and 47 losses for the classification task, and 1933 wins, 258 ties and 185 losses for the ordinal regression task compared to the other state-of-the-art active learning algorithms. By taking the

Kinaesthetic Learning Activities and Learning about Solar Cells

ERIC Educational Resources Information Center

Richards, A. J.; Etkina, Eugenia

2013-01-01

Kinaesthetic learning activities (KLAs) can be a valuable pedagogical tool for physics instructors. They have been shown to increase engagement, encourage participation and improve learning outcomes. This paper details several KLAs developed at Rutgers University for inclusion in an instructional unit about semiconductors, p-n junctions and solar…

Scene recognition based on integrating active learning with dictionary learning

NASA Astrophysics Data System (ADS)

Wang, Chengxi; Yin, Xueyan; Yang, Lin; Gong, Chengrong; Zheng, Caixia; Yi, Yugen

2018-04-01

Scene recognition is a significant topic in the field of computer vision. Most of the existing scene recognition models require a large amount of labeled training samples to achieve a good performance. However, labeling image manually is a time consuming task and often unrealistic in practice. In order to gain satisfying recognition results when labeled samples are insufficient, this paper proposed a scene recognition algorithm named Integrating Active Learning and Dictionary Leaning (IALDL). IALDL adopts projective dictionary pair learning (DPL) as classifier and introduces active learning mechanism into DPL for improving its performance. When constructing sampling criterion in active learning, IALDL considers both the uncertainty and representativeness as the sampling criteria to effectively select the useful unlabeled samples from a given sample set for expanding the training dataset. Experiment results on three standard databases demonstrate the feasibility and validity of the proposed IALDL.

Active Learning Crosses Generations.

ERIC Educational Resources Information Center

Woodard, Diane K.

2002-01-01

Describes the benefits of intergenerational programs, highlighting a child care program that offers age-appropriate and mutually beneficial activities for children and elders within a nearby retirement community. The program has adopted High/Scope's active learning approach to planning and implementing activities that involve both generations. The…

Active Learning: The Way Children Construct Knowledge.

ERIC Educational Resources Information Center

Hohmann, Mary; Weikart, David P.

2002-01-01

The High/Scope approach to early childhood education promotes the belief that active learning is fundamental to the development of human potential and occurs most effectively in settings that provide developmentally appropriate learning opportunities. Describes five ingredients of active learning (materials, manipulation, choice, language from…

Evaluating Attitudes, Skill, and Performance in a Learning-Enhanced Quantitative Methods Course: A Structural Modeling Approach.

ERIC Educational Resources Information Center

Harlow, Lisa L.; Burkholder, Gary J.; Morrow, Jennifer A.

2002-01-01

Used a structural modeling approach to evaluate relations among attitudes, initial skills, and performance in a Quantitative Methods course that involved students in active learning. Results largely confirmed hypotheses offering support for educational reform efforts that propose actively involving students in the learning process, especially in…

Active learning based segmentation of Crohns disease from abdominal MRI.

PubMed

Mahapatra, Dwarikanath; Vos, Franciscus M; Buhmann, Joachim M

2016-05-01

This paper proposes a novel active learning (AL) framework, and combines it with semi supervised learning (SSL) for segmenting Crohns disease (CD) tissues from abdominal magnetic resonance (MR) images. Robust fully supervised learning (FSL) based classifiers require lots of labeled data of different disease severities. Obtaining such data is time consuming and requires considerable expertise. SSL methods use a few labeled samples, and leverage the information from many unlabeled samples to train an accurate classifier. AL queries labels of most informative samples and maximizes gain from the labeling effort. Our primary contribution is in designing a query strategy that combines novel context information with classification uncertainty and feature similarity. Combining SSL and AL gives a robust segmentation method that: (1) optimally uses few labeled samples and many unlabeled samples; and (2) requires lower training time. Experimental results show our method achieves higher segmentation accuracy than FSL methods with fewer samples and reduced training effort. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Active learning of introductory optics: real-time physics labs, interactive lecture demonstrations and magic

NASA Astrophysics Data System (ADS)

Sokoloff, David R.

2005-10-01

Widespread physics education research has shown that most introductory physics students have difficulty learning essential optics concepts - even in the best of traditional courses, and that well-designed active learning approaches can remedy this problem. This mini-workshop and the associated poster session will provide direct experience with methods for promoting students' active involvement in the learning process in lecture and laboratory. Participants will have hands-on experience with activities from RealTime Physics labs and Interactive Lecture Demonstrations - a learning strategy for large (and small) lectures, including specially designed Optics Magic Tricks. The poster will provide more details on these highly effective curricula.

Learning Outcomes between Socioscientific Issues-Based Learning and Conventional Learning Activities

ERIC Educational Resources Information Center

Wongsri, Piyaluk; Nuangchalerm, Prasart

2010-01-01

Problem statement: Socioscientific issues-based learning activity is essential for scientific reasoning skills and it could be used for analyzing problems be applied to each situation for more successful and suitable. The purposes of this research aimed to compare learning achievement, analytical thinking and moral reasoning of seventh grade…

Is Peer Interaction Necessary for Optimal Active Learning?

PubMed

Linton, Debra L; Farmer, Jan Keith; Peterson, Ernie

2014-01-01

Meta-analyses of active-learning research consistently show that active-learning techniques result in greater student performance than traditional lecture-based courses. However, some individual studies show no effect of active-learning interventions. This may be due to inexperienced implementation of active learning. To minimize the effect of inexperience, we should try to provide more explicit implementation recommendations based on research into the key components of effective active learning. We investigated the optimal implementation of active-learning exercises within a "lecture" course. Two sections of nonmajors biology were taught by the same instructor, in the same semester, using the same instructional materials and assessments. Students in one section completed in-class active-learning exercises in cooperative groups, while students in the other section completed the same activities individually. Performance on low-level, multiple-choice assessments was not significantly different between sections. However, students who worked in cooperative groups on the in-class activities significantly outperformed students who completed the activities individually on the higher-level, extended-response questions. Our results provide additional evidence that group processing of activities should be the recommended mode of implementation for in-class active-learning exercises. © 2014 D. L. Linton et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Incorporating conditional random fields and active learning to improve sentiment identification.

PubMed

Zhang, Kunpeng; Xie, Yusheng; Yang, Yi; Sun, Aaron; Liu, Hengchang; Choudhary, Alok

2014-10-01

Many machine learning, statistical, and computational linguistic methods have been developed to identify sentiment of sentences in documents, yielding promising results. However, most of state-of-the-art methods focus on individual sentences and ignore the impact of context on the meaning of a sentence. In this paper, we propose a method based on conditional random fields to incorporate sentence structure and context information in addition to syntactic information for improving sentiment identification. We also investigate how human interaction affects the accuracy of sentiment labeling using limited training data. We propose and evaluate two different active learning strategies for labeling sentiment data. Our experiments with the proposed approach demonstrate a 5%-15% improvement in accuracy on Amazon customer reviews compared to existing supervised learning and rule-based methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

A comparison of professional-level faculty and student perceptions of active learning: its current use, effectiveness, and barriers

PubMed Central

Metz, Michael J.

2014-01-01

Active learning is an instructional method in which students become engaged participants in the classroom through the use of in-class written exercises, games, problem sets, audience-response systems, debates, class discussions, etc. Despite evidence supporting the effectiveness of active learning strategies, minimal adoption of the technique has occurred in many professional programs. The goal of this study was to compare the perceptions of active learning between students who were exposed to active learning in the classroom (n = 116) and professional-level physiology faculty members (n = 9). Faculty members reported a heavy reliance on lectures and minimal use of educational games and activities, whereas students indicated that they learned best via the activities. A majority of faculty members (89%) had observed active learning in the classroom and predicted favorable effects of the method on student performance and motivation. The main reported barriers by faculty members to the adoption of active learning were a lack of necessary class time, a high comfort level with traditional lectures, and insufficient time to develop materials. Students hypothesized similar obstacles for faculty members but also associated many negative qualities with the traditional lecturers. Despite these barriers, a majority of faculty members (78%) were interested in learning more about the alternative teaching strategy. Both faculty members and students indicated that active learning should occupy portions (29% vs. 40%) of face-to-face class time. PMID:25179615

Active Learning by Querying Informative and Representative Examples.

PubMed

Huang, Sheng-Jun; Jin, Rong; Zhou, Zhi-Hua

2014-10-01

Active learning reduces the labeling cost by iteratively selecting the most valuable data to query their labels. It has attracted a lot of interests given the abundance of unlabeled data and the high cost of labeling. Most active learning approaches select either informative or representative unlabeled instances to query their labels, which could significantly limit their performance. Although several active learning algorithms were proposed to combine the two query selection criteria, they are usually ad hoc in finding unlabeled instances that are both informative and representative. We address this limitation by developing a principled approach, termed QUIRE, based on the min-max view of active learning. The proposed approach provides a systematic way for measuring and combining the informativeness and representativeness of an unlabeled instance. Further, by incorporating the correlation among labels, we extend the QUIRE approach to multi-label learning by actively querying instance-label pairs. Extensive experimental results show that the proposed QUIRE approach outperforms several state-of-the-art active learning approaches in both single-label and multi-label learning.

Iranian Clinical Nurses’ Activities for Self-Directed Learning: A Qualitative Study

PubMed Central

Ghiyasvandian, Shahrzad; Malekian, Morteza; Cheraghi, Mohammad Ali

2016-01-01

Background: Clinical nurses need lifelong learning skills for responding to the rapid changes of clinical settings. One of the best strategies for lifelong learning is self-directed learning. The aim of this study was to explore Iranian clinical nurses’ activities for self-directed learning. Methods: In this qualitative study, 23 semi-structured personal interviews were conducted with nineteen clinical nurses working in all four hospitals affiliated to Isfahan Social Security Organization, Isfahan, Iran. Study data were analyzed by using the content analysis approach. The study was conducted from June 2013 to October 2014. Findings: Study participants’ activities for self-directed learning fell into two main categories of striving for knowledge acquisition and striving for skill development. The main theme of the study was ‘Revising personal performance based on intellectual-experiential activities’. Conclusions: Study findings suggest that Iranian clinical nurses continually revise their personal performance by performing self-directed intellectual and experiential activities to acquire expertise. The process of acquiring expertise is a linear process which includes two key steps of knowledge acquisition and knowledge development. In order to acquire and advance their knowledge, nurses perform mental learning activities such as sensory perception, self-evaluation, and suspended judgment step-by-step. Moreover, they develop their skills through doing activities like apprenticeship, masterly performance, and self-regulation. The absolute prerequisite to expertise acquisition is that a nurse needs to follow these two steps in a sequential manner. PMID:26652072

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,…

Stages of Concern Profiles for Active Learning Strategies of Agricultural Technical School Teachers in Egypt

ERIC Educational Resources Information Center

Myers, Brian E.; Barrick, R. Kirby; Samy, Mohamed M.

2012-01-01

Purpose: The purpose of the study was to assess Egyptian Agricultural Technical School (ATS) teachers' implementation of active learning strategies in their classrooms. Methods: The Stages of Concern Questionnaire was administered to 230 participants in active learning workshops. After eliminating headmasters, supervisors and people no longer…

Teaching for Engagement: Part 2: Technology in the Service of Active Learning

ERIC Educational Resources Information Center

Hunter, William J.

2015-01-01

In the first piece in this series ("Teaching for Engagement: Part 1: Constructivist Principles, Case-Based Teaching, and Active Learning"), William Hunter sought to make the case that a wide range of teaching methods (e.g., case-based teaching, problem-based learning, anchored instruction) that share an intellectual grounding in…

The Effect of Active Learning Methodologies on the Teaching of Pharmaceutical Care in a Brazilian Pharmacy Faculty

PubMed Central

2015-01-01

Background In recent years, pharmacists have been involved in expanded patient care responsibilities, for example patient counseling in self-medication, medication review and pharmaceutical care, which require graduates to develop the necessary competences. Consequently, reorientation of pharmacy education has become necessary. As such, active learning strategies have been introduced into classrooms to increase problem-solving and critical thinking skills of students. The objective of this study was to evaluate the performance and perceptions of competency of students in a new pharmaceutical care course that uses active learning methodologies. Methods This pharmaceutical care course was conducted in the first semester of 2014, in the Federal University of Sergipe. In the pharmaceutical care course, active learning methods were used, consisting of dialogic classroom expository, simulation and case studies. Student learning was evaluated using classroom tests and instruments that evaluated the perception of competency in pharmaceutical care practice. Furthermore, students' satisfaction with the course was evaluated. Results Thirty-three students completed the four evaluations used in the course (i.e., a discursive written exam, seminars, OSCE, and virtual patient); 25 were female (75.75%), and the median age was 23.43 (SD 2.82) years. The overall mean of student scores, in all evaluation methods was 7.97 (SD 0.59) on a scale of 0 to 10 points, and student performance on the virtual patient method was statistically superior to other methods. With respect to the perception of competency in pharmaceutical care practice, a comparison of pre- and post-test scores revealed statistically significant improvement for all evaluated competences. At the end of the semester, the students presented positive opinions of the pharmaceutical care course. Conclusions The results suggest that an active learning course can enhance the learning of pharmaceutical care competences. In

Implementation and evaluation of a community-based interprofessional learning activity.

PubMed

Luebbers, Ellen L; Dolansky, Mary A; Vehovec, Anton; Petty, Gayle

2017-01-01

Implementation of large-scale, meaningful interprofessional learning activities for pre-licensure students has significant barriers and requires novel approaches to ensure success. To accomplish this goal, faculty at Case Western Reserve University, Ohio, USA, used the Ottawa Model of Research Use (OMRU) framework to create, improve, and sustain a community-based interprofessional learning activity for large numbers of medical students (N = 177) and nursing students (N = 154). The model guided the process and included identification of context-specific barriers and facilitators, continual monitoring and improvement using data, and evaluation of student learning outcomes as well as programme outcomes. First year Case Western Reserve University medical students and undergraduate nursing students participated in team-structured prevention screening clinics in the Cleveland Metropolitan Public School District. Identification of barriers and facilitators assisted with overcoming logistic and scheduling issues, large class size, differing ages and skill levels of students and creating sustainability. Continual monitoring led to three distinct phases of improvement and resulted in the creation of an authentic team structure, role clarification, and relevance for students. Evaluation of student learning included both qualitative and quantitative methods, resulting in statistically significant findings and qualitative themes of learner outcomes. The OMRU implementation model provided a useful framework for successful implementation resulting in a sustainable interprofessional learning activity.

Topic detection using paragraph vectors to support active learning in systematic reviews.

PubMed

Hashimoto, Kazuma; Kontonatsios, Georgios; Miwa, Makoto; Ananiadou, Sophia

2016-08-01

Systematic reviews require expert reviewers to manually screen thousands of citations in order to identify all relevant articles to the review. Active learning text classification is a supervised machine learning approach that has been shown to significantly reduce the manual annotation workload by semi-automating the citation screening process of systematic reviews. In this paper, we present a new topic detection method that induces an informative representation of studies, to improve the performance of the underlying active learner. Our proposed topic detection method uses a neural network-based vector space model to capture semantic similarities between documents. We firstly represent documents within the vector space, and cluster the documents into a predefined number of clusters. The centroids of the clusters are treated as latent topics. We then represent each document as a mixture of latent topics. For evaluation purposes, we employ the active learning strategy using both our novel topic detection method and a baseline topic model (i.e., Latent Dirichlet Allocation). Results obtained demonstrate that our method is able to achieve a high sensitivity of eligible studies and a significantly reduced manual annotation cost when compared to the baseline method. This observation is consistent across two clinical and three public health reviews. The tool introduced in this work is available from https://nactem.ac.uk/pvtopic/. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Active learning strategies for the deduplication of electronic patient data using classification trees.

PubMed

Sariyar, M; Borg, A; Pommerening, K

2012-10-01

Supervised record linkage methods often require a clerical review to gain informative training data. Active learning means to actively prompt the user to label data with special characteristics in order to minimise the review costs. We conducted an empirical evaluation to investigate whether a simple active learning strategy using binary comparison patterns is sufficient or if string metrics together with a more sophisticated algorithm are necessary to achieve high accuracies with a small training set. Based on medical registry data with different numbers of attributes, we used active learning to acquire training sets for classification trees, which were then used to classify the remaining data. Active learning for binary patterns means that every distinct comparison pattern represents a stratum from which one item is sampled. Active learning for patterns consisting of the Levenshtein string metric values uses an iterative process where the most informative and representative examples are added to the training set. In this context, we extended the active learning strategy by Sarawagi and Bhamidipaty (2002). On the original data set, active learning based on binary comparison patterns leads to the best results. When dropping four or six attributes, using string metrics leads to better results. In both cases, not more than 200 manually reviewed training examples are necessary. In record linkage applications where only forename, name and birthday are available as attributes, we suggest the sophisticated active learning strategy based on string metrics in order to achieve highly accurate results. We recommend the simple strategy if more attributes are available, as in our study. In both cases, active learning significantly reduces the amount of manual involvement in training data selection compared to usual record linkage settings. Copyright © 2012 Elsevier Inc. All rights reserved.

The Intelligent Method of Learning

ERIC Educational Resources Information Center

Moula, Alireza; Mohseni, Simin; Starrin, Bengt; Scherp, Hans Ake; Puddephatt, Antony J.

2010-01-01

Early psychologist William James [1842-1910] and philosopher John Dewey [1859-1952] described intelligence as a method which can be learned. That view of education is integrated with knowledge about the brain's executive functions to empower pupils to intelligently organize their learning. This article links the pragmatist philosophy of…

History and Evolution of Active Learning Spaces

ERIC Educational Resources Information Center

Beichner, Robert J.

2014-01-01

This chapter examines active learning spaces as they have developed over the years. Consistently well-designed classrooms can facilitate active learning even though the details of implementing pedagogies may differ.

GeoMapApp Learning Activities: Enabling the democratisation of geoscience learning

NASA Astrophysics Data System (ADS)

Goodwillie, A. M.; Kluge, S.

2011-12-01

GeoMapApp Learning Activities (http://serc.carleton.edu/geomapapp) are step-by-step guided inquiry geoscience education activities that enable students to dictate the pace of learning. They can be used in the classroom or out of class, and their guided nature means that the requirement for teacher intervention is minimised which allows students to spend increased time analysing and understanding a broad range of geoscience data, content and concepts. Based upon GeoMapApp (http://www.geomapapp.org), a free, easy-to-use map-based data exploration and visualisation tool, each activity furnishes the educator with an efficient package of downloadable documents. This includes step-by-step student instructions and answer sheet; a teacher's edition annotated worksheet containing teaching tips, additional content and suggestions for further work; quizzes for use before and after the activity to assess learning; and a multimedia tutorial. The activities can be used by anyone at any time in any place with an internet connection. In essence, GeoMapApp Learning Activities provide students with cutting-edge technology, research-quality geoscience data sets, and inquiry-based learning in a virtual lab-like environment. Examples of activities so far created are student calculation and analysis of the rate of seafloor spreading, and present-day evidence on the seafloor for huge ancient landslides around the Hawaiian islands. The activities are designed primarily for students at the community college, high school and introductory undergraduate levels, exposing students to content and concepts typically found in those settings.

Square Pegs, Round Holes: An Exploration of Teaching Methods and Learning Styles of Millennial College Students

ERIC Educational Resources Information Center

Bailey, Regina M.

2012-01-01

In an information-saturated world, today's college students desire to be engaged both in and out of their college classrooms. This mixed-methods study sought to explore how replacing traditional teaching methods with engaged learning activities affects millennial college student attitudes and perceptions about learning. The sub-questions…

Learning Activity Predictors from Sensor Data: Algorithms, Evaluation, and Applications.

PubMed

Minor, Bryan; Doppa, Janardhan Rao; Cook, Diane J

2017-12-01

Recent progress in Internet of Things (IoT) platforms has allowed us to collect large amounts of sensing data. However, there are significant challenges in converting this large-scale sensing data into decisions for real-world applications. Motivated by applications like health monitoring and intervention and home automation we consider a novel problem called Activity Prediction , where the goal is to predict future activity occurrence times from sensor data. In this paper, we make three main contributions. First, we formulate and solve the activity prediction problem in the framework of imitation learning and reduce it to a simple regression learning problem. This approach allows us to leverage powerful regression learners that can reason about the relational structure of the problem with negligible computational overhead. Second, we present several metrics to evaluate activity predictors in the context of real-world applications. Third, we evaluate our approach using real sensor data collected from 24 smart home testbeds. We also embed the learned predictor into a mobile-device-based activity prompter and evaluate the app for 9 participants living in smart homes. Our results indicate that our activity predictor performs better than the baseline methods, and offers a simple approach for predicting activities from sensor data.

Three dimensions of learning: experiential activity for engineering innovation education and research

NASA Astrophysics Data System (ADS)

Killen, Catherine P.

2015-09-01

This paper outlines a novel approach to engineering education research that provides three dimensions of learning through an experiential class activity. A simulated decision activity brought current research into the classroom, explored the effect of experiential activity on learning outcomes and contributed to the research on innovation decision making. The 'decision task' was undertaken by more than 480 engineering students. It increased their reported measures of learning and retention by an average of 0.66 on a five-point Likert scale, and revealed positive correlations between attention, enjoyment, ongoing interest and learning and retention. The study also contributed to innovation management research by revealing the influence of different data visualisation methods on decision quality, providing an example of research-integrated education that forms part of the research process. Such a dovetailing of different research studies demonstrates how engineering educators can enhance educational impact while multiplying the outcomes from their research efforts.

A comparison of professional-level faculty and student perceptions of active learning: its current use, effectiveness, and barriers.

PubMed

Miller, Cynthia J; Metz, Michael J

2014-09-01

Active learning is an instructional method in which students become engaged participants in the classroom through the use of in-class written exercises, games, problem sets, audience-response systems, debates, class discussions, etc. Despite evidence supporting the effectiveness of active learning strategies, minimal adoption of the technique has occurred in many professional programs. The goal of this study was to compare the perceptions of active learning between students who were exposed to active learning in the classroom (n = 116) and professional-level physiology faculty members (n = 9). Faculty members reported a heavy reliance on lectures and minimal use of educational games and activities, whereas students indicated that they learned best via the activities. A majority of faculty members (89%) had observed active learning in the classroom and predicted favorable effects of the method on student performance and motivation. The main reported barriers by faculty members to the adoption of active learning were a lack of necessary class time, a high comfort level with traditional lectures, and insufficient time to develop materials. Students hypothesized similar obstacles for faculty members but also associated many negative qualities with the traditional lecturers. Despite these barriers, a majority of faculty members (78%) were interested in learning more about the alternative teaching strategy. Both faculty members and students indicated that active learning should occupy portions (29% vs. 40%) of face-to-face class time. Copyright © 2014 The American Physiological Society.

Critical Communication Pedagogy and Service Learning in a Mixed-Method Communication Research Course

ERIC Educational Resources Information Center

Rudick, C. Kyle; Golsan, Kathryn B.; Freitag, Jennifer

2018-01-01

Course: Mixed-Method Communication Research Methods. Objective: The purpose of this semester-long activity is to provide students with opportunities to cultivate mixed-method communication research skills through a social justice-informed service-learning format. Completing this course, students will be able to: recognize the unique strengths of…

Active Learning Environment with Lenses in Geometric Optics

ERIC Educational Resources Information Center

Tural, Güner

2015-01-01

Geometric optics is one of the difficult topics for students within physics discipline. Students learn better via student-centered active learning environments than the teacher-centered learning environments. So this study aimed to present a guide for middle school teachers to teach lenses in geometric optics via active learning environment…

Learning Style Activities for Computer Applications. Field Review.

ERIC Educational Resources Information Center

Patton, Jan

This document contains a composite of learning activities for use in a secondary-level course in business computer applications. The collection is unique in that the individual learning activities constituting it have each been tailored to one or more of the diverse learning styles possessed by individual students. The activities are grouped into…

A Sourcebook of Cooperative Learning Activities for Introductory Undergraduate Astronomy for Non-Science Majors

NASA Astrophysics Data System (ADS)

Deming, Grace L.; Miller, Scott T.; Trasco, John D.

1996-05-01

Students become more interested in learning and retain more in courses that rely on active rather than passive teaching methods. Cooperative learning activities can be structured to engage students toward greater participation in their own education. We have developed a sourcebook containing a variety of cooperative learning methods and activities to aid in the teaching of astronomy at the undergraduate level. Special effort has been made to include activities that can be used within the classroom or as a group homework assignment, in courses with teaching assistants and those without, and in large or small classes. In addition to reinforcing concepts taught in introductory astronomy, the activities are structured to strengthen skills associated with a scientifically literate person. A goal of undergraduate science education is to produce citizens who can understand and share in the excitement of scientific discoveries as well as make informed decisions regarding scientific and technological issues. The sourcebook, available in August, 1996, will contain sections on the advantages/disadvantages of group activities, basic cooperative learning techniques, in class/out of class activities, and how to use peer instruction to expose students to the wonderfaul astronomy resources on the internet. Each activity includes suggestions to the instructor as to how the assignment can be incorporated into an introductory astronomy course. This project funded by NSF DUE-9354503.

Collegewide Promotion of E-Learning/Active Learning and Faculty Development

ERIC Educational Resources Information Center

Ogawa, Nobuyuki; Shimizu, Akira

2016-01-01

Japanese National Institutes of Technology have revealed a plan to strongly promote e-Learning and active learning under the common schematization of education in over 50 campuses nationwide. Our e-Learning and ICT-driven education practiced for more than fifteen years were highly evaluated, and is playing a leading role in promoting e-Learning…

Pedagogical Distance: Explaining Misalignment in Student-Driven Online Learning Activities Using Activity Theory

ERIC Educational Resources Information Center

Westberry, Nicola; Franken, Margaret

2015-01-01

This paper provides an Activity Theory analysis of two online student-driven interactive learning activities to interrogate assumptions that such groups can effectively learn in the absence of the teacher. Such an analysis conceptualises learning tasks as constructed objects that drive pedagogical activity. The analysis shows a disconnect between…

The effect of active learning on student characteristics in a human physiology course for nonmajors.

PubMed

Wilke, R Russell

2003-12-01

This study investigated the effect of active-learning strategies on college students' achievement, motivation, and self-efficacy in a human physiology course for nonmajors. Variables were studied via a quasi-experimental, Solomon four-group design on 141 students at a small west-Texas university. Treatment groups were taught using a continuum-based, active-learning model implemented over the course of a semester. Control groups were taught using traditional didactic lecture methods. To assess the effects of the continuum-based active learning strategies, students were administered a comprehensive physiology content exam, the Motivated Strategies for Learning Questionnaire, and attitude surveys. Factorial analyses indicated that the treatment groups acquired significantly more content knowledge and were significantly more self-efficacious than students in the control groups. There were no significant differences in motivation. Attitude surveys indicated that students in both the treatment and control groups demonstrated a positive attitude toward active learning, believed it helped (or would help) them to learn the material, and would choose an active learning course in the future.

Using assistive technology adaptations to include students with learning disabilities in cooperative learning activities.

PubMed

Bryant, D P; Bryant, B R

1998-01-01

Cooperative learning (CL) is a common instructional arrangement that is used by classroom teachers to foster academic achievement and social acceptance of students with and without learning disabilities. Cooperative learning is appealing to classroom teachers because it can provide an opportunity for more instruction and feedback by peers than can be provided by teachers to individual students who require extra assistance. Recent studies suggest that students with LD may need adaptations during cooperative learning activities. The use of assistive technology adaptations may be necessary to help some students with LD compensate for their specific learning difficulties so that they can engage more readily in cooperative learning activities. A process for integrating technology adaptations into cooperative learning activities is discussed in terms of three components: selecting adaptations, monitoring the use of the adaptations during cooperative learning activities, and evaluating the adaptations' effectiveness. The article concludes with comments regarding barriers to and support systems for technology integration, technology and effective instructional practices, and the need to consider technology adaptations for students who have learning disabilities.

The effect of active learning methodologies on the teaching of pharmaceutical care in a Brazilian pharmacy faculty.

PubMed

Mesquita, Alessandra R; Souza, Werlissandra M; Boaventura, Thays C; Barros, Izadora M C; Antoniolli, Angelo R; Silva, Wellington B; Lyra Júnior, Divaldo P

2015-01-01

In recent years, pharmacists have been involved in expanded patient care responsibilities, for example patient counseling in self-medication, medication review and pharmaceutical care, which require graduates to develop the necessary competences. Consequently, reorientation of pharmacy education has become necessary. As such, active learning strategies have been introduced into classrooms to increase problem-solving and critical thinking skills of students. The objective of this study was to evaluate the performance and perceptions of competency of students in a new pharmaceutical care course that uses active learning methodologies. This pharmaceutical care course was conducted in the first semester of 2014, in the Federal University of Sergipe. In the pharmaceutical care course, active learning methods were used, consisting of dialogic classroom expository, simulation and case studies. Student learning was evaluated using classroom tests and instruments that evaluated the perception of competency in pharmaceutical care practice. Furthermore, students' satisfaction with the course was evaluated. Thirty-three students completed the four evaluations used in the course (i.e., a discursive written exam, seminars, OSCE, and virtual patient); 25 were female (75.75%), and the median age was 23.43 (SD 2.82) years. The overall mean of student scores, in all evaluation methods was 7.97 (SD 0.59) on a scale of 0 to 10 points, and student performance on the virtual patient method was statistically superior to other methods. With respect to the perception of competency in pharmaceutical care practice, a comparison of pre- and post-test scores revealed statistically significant improvement for all evaluated competences. At the end of the semester, the students presented positive opinions of the pharmaceutical care course. The results suggest that an active learning course can enhance the learning of pharmaceutical care competences. In future studies it will be necessary to

The Effect of Cooperative Learning Method and Systematic Teaching on Students' Achievement and Retention of Knowledge in Social Studies Lesson

ERIC Educational Resources Information Center

Korkmaz Toklucu, Selma; Tay, Bayram

2016-01-01

Problem Statement: Many effective instructional strategies, methods, and techniques, which were developed in accordance with constructivist approach, can be used together in social studies lessons. Constructivist education comprises active learning processes. Two active learning approaches are cooperative learning and systematic teaching. Purpose…

Student Achievement in Basic College Mathematics: Its Relationship to Learning Style and Learning Method

ERIC Educational Resources Information Center

Gunthorpe, Sydney

2006-01-01

From the assumption that matching a student's learning style with the learning method best suited for the student, it follows that developing courses that correlate learning method with learning style would be more successful for students. Albuquerque Technical Vocational Institute (TVI) in New Mexico has attempted to provide students with more…

Adaptive Batch Mode Active Learning.

PubMed

Chakraborty, Shayok; Balasubramanian, Vineeth; Panchanathan, Sethuraman

2015-08-01

Active learning techniques have gained popularity to reduce human effort in labeling data instances for inducing a classifier. When faced with large amounts of unlabeled data, such algorithms automatically identify the exemplar and representative instances to be selected for manual annotation. More recently, there have been attempts toward a batch mode form of active learning, where a batch of data points is simultaneously selected from an unlabeled set. Real-world applications require adaptive approaches for batch selection in active learning, depending on the complexity of the data stream in question. However, the existing work in this field has primarily focused on static or heuristic batch size selection. In this paper, we propose two novel optimization-based frameworks for adaptive batch mode active learning (BMAL), where the batch size as well as the selection criteria are combined in a single formulation. We exploit gradient-descent-based optimization strategies as well as properties of submodular functions to derive the adaptive BMAL algorithms. The solution procedures have the same computational complexity as existing state-of-the-art static BMAL techniques. Our empirical results on the widely used VidTIMIT and the mobile biometric (MOBIO) data sets portray the efficacy of the proposed frameworks and also certify the potential of these approaches in being used for real-world biometric recognition applications.

Faculty and second-year medical student perceptions of active learning in an integrated curriculum.

PubMed

Tsang, Alexander; Harris, David M

2016-12-01

Patients expect physicians to be lifelong learners who are able to interpret and evaluate diagnostic tests, and most medical schools list the development of lifelong learning in their program objectives. However, lecture is the most often utilized form of teaching in the first two years and is considered passive learning. The current generation of medical students has many characteristics that should support active learning pedagogies. The purpose of this study was to analyze student and faculty perceptions of active learning in an integrated medical curriculum at the second-year mark, where students have been exposed to multiple educational pedagogies. The first hypothesis of the study was that faculty would favor active learning methods. The second hypothesis was that Millennial medical students would favor active learning due to their characteristics. Primary faculty for years 1 and 2 and second-year medical students were recruited for an e-mail survey consisting of 12 questions about active learning and lecture. Students perceived that lecture and passive pedagogies were more effective for learning, whereas faculty felt active and collaborative learning was more effective. Students believed that more content should be covered by lecture than faculty. There were also significant differences in perceptions of what makes a good teacher. Students and faculty both felt that lack of time in the curriculum and preparation time were barriers for faculty. The data suggest that students are not familiar with the process of learning and that more time may be needed to help students develop lifelong learning skills. Copyright © 2016 The American Physiological Society.

Effective, Active Learning Strategies for the Oceanography Classroom

NASA Astrophysics Data System (ADS)

Dmochowski, J. E.; Marinov, I.

2014-12-01

A decline in enrollment in STEM fields at the university level has prompted extensive research on alternative ways of teaching and learning science. Inquiry-based learning as well as the related "flipped" or "active" lectures, and similar teaching methods and philosophies have been proposed as more effective ways to disseminate knowledge in science classes than the traditional lecture. We will provide a synopsis of our experiences in implementing some of these practices into our Introductory Oceanography, Global Climate Change, and Ocean Atmosphere Dynamics undergraduate courses at the University of Pennsylvania, with both smaller and larger enrollments. By implementing tools such as at-home modules; computer labs; incorporation of current research; pre- and post-lecture quizzes; reflective, qualitative writing assignments; peer review; and a variety of in-class learning strategies, we aim to increase the science literacy of the student population and help students gain a more comprehensive knowledge of the topic, enhance their critical thinking skills, and correct misconceptions. While implementing these teaching techniques with college students is not without complications, we argue that a blended class that flexibly and creatively accounts for class size and science level improves the learning experience and the acquired knowledge. We will present examples of student assignments and activities as well as describe the lessons we have learned, and propose ideas for moving forward to best utilize innovative teaching tools in order to increase science literacy in oceanography and other climate-related courses.

Origami: An Active Learning Exercise for Scrum Project Management

ERIC Educational Resources Information Center

Sibona, Christopher; Pourreza, Saba; Hill, Stephen

2018-01-01

Scrum is a popular project management model for iterative delivery of software that subscribes to Agile principles. This paper describes an origami active learning exercise to teach the principles of Scrum in management information systems courses. The exercise shows students how Agile methods respond to changes in requirements during project…

An Active Learning Exercise for Introducing Agent-Based Modeling

ERIC Educational Resources Information Center

Pinder, Jonathan P.

2013-01-01

Recent developments in agent-based modeling as a method of systems analysis and optimization indicate that students in business analytics need an introduction to the terminology, concepts, and framework of agent-based modeling. This article presents an active learning exercise for MBA students in business analytics that demonstrates agent-based…

Active Learning Is Not Enough

ERIC Educational Resources Information Center

Casem, Merri Lynn

2006-01-01

I have examined how frequency of assessment impacts learning in an undergraduate biology course employing a student-centered, active-learning pedagogy. Frequent assessment was associated with better student performance and greater retention of course concepts. Improvement of higher-order thinking skills may require more classroom practice.…

Transfer Learning for Activity Recognition: A Survey

PubMed Central

Cook, Diane; Feuz, Kyle D.; Krishnan, Narayanan C.

2013-01-01

Many intelligent systems that focus on the needs of a human require information about the activities being performed by the human. At the core of this capability is activity recognition, which is a challenging and well-researched problem. Activity recognition algorithms require substantial amounts of labeled training data yet need to perform well under very diverse circumstances. As a result, researchers have been designing methods to identify and utilize subtle connections between activity recognition datasets, or to perform transfer-based activity recognition. In this paper we survey the literature to highlight recent advances in transfer learning for activity recognition. We characterize existing approaches to transfer-based activity recognition by sensor modality, by differences between source and target environments, by data availability, and by type of information that is transferred. Finally, we present some grand challenges for the community to consider as this field is further developed. PMID:24039326

Transfer Learning for Improved Audio-Based Human Activity Recognition.

PubMed

Ntalampiras, Stavros; Potamitis, Ilyas

2018-06-25

Human activities are accompanied by characteristic sound events, the processing of which might provide valuable information for automated human activity recognition. This paper presents a novel approach addressing the case where one or more human activities are associated with limited audio data, resulting in a potentially highly imbalanced dataset. Data augmentation is based on transfer learning; more specifically, the proposed method: (a) identifies the classes which are statistically close to the ones associated with limited data; (b) learns a multiple input, multiple output transformation; and (c) transforms the data of the closest classes so that it can be used for modeling the ones associated with limited data. Furthermore, the proposed framework includes a feature set extracted out of signal representations of diverse domains, i.e., temporal, spectral, and wavelet. Extensive experiments demonstrate the relevance of the proposed data augmentation approach under a variety of generative recognition schemes.

Weekly active-learning activities in a drug information and literature evaluation course.

PubMed

Timpe, Erin M; Motl, Susannah E; Eichner, Samantha F

2006-06-15

To incorporate learning activities into the weekly 2-hour Drug Information and Literature Evaluation class sessions to improve student ability and confidence in performing course objectives, as well as to assess student perception of the value of these activities. In-class activities that emphasized content and skills taught within class periods were created and implemented. Three different surveys assessing student ability and confidence in completing drug information and literature retrieval and evaluation tasks were administered prior to and following the appropriate class sessions. At the completion of the course, an additional evaluation was administered to assess the students' impressions of the value of the learning activities. Students reported increased ability and confidence in all course objectives. The teaching activities were also stated to be useful in students' learning of the material. Incorporation of weekly learning activities resulted in an improvement in student ability and confidence to perform course objectives. Students considered these activities to be beneficial and to contribute to the completion of course objectives.

A Simple Deep Learning Method for Neuronal Spike Sorting

NASA Astrophysics Data System (ADS)

Yang, Kai; Wu, Haifeng; Zeng, Yu

2017-10-01

Spike sorting is one of key technique to understand brain activity. With the development of modern electrophysiology technology, some recent multi-electrode technologies have been able to record the activity of thousands of neuronal spikes simultaneously. The spike sorting in this case will increase the computational complexity of conventional sorting algorithms. In this paper, we will focus spike sorting on how to reduce the complexity, and introduce a deep learning algorithm, principal component analysis network (PCANet) to spike sorting. The introduced method starts from a conventional model and establish a Toeplitz matrix. Through the column vectors in the matrix, we trains a PCANet, where some eigenvalue vectors of spikes could be extracted. Finally, support vector machine (SVM) is used to sort spikes. In experiments, we choose two groups of simulated data from public databases availably and compare this introduced method with conventional methods. The results indicate that the introduced method indeed has lower complexity with the same sorting errors as the conventional methods.

Active Ageing, Active Learning: Policy and Provision in Hong Kong

ERIC Educational Resources Information Center

Tam, M.

2011-01-01

This paper discusses the relationship between ageing and learning, previous literature having confirmed that participation in continued learning in old age contributes to good health, satisfaction with life, independence and self-esteem. Realizing that learning is vital to active ageing, the Hong Kong government has implemented policies and…

Experiential Learning and Learning Environments: The Case of Active Listening Skills

ERIC Educational Resources Information Center

Huerta-Wong, Juan Enrique; Schoech, Richard

2010-01-01

Social work education research frequently has suggested an interaction between teaching techniques and learning environments. However, this interaction has never been tested. This study compared virtual and face-to-face learning environments and included active listening concepts to test whether the effectiveness of learning environments depends…

Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks

PubMed Central

Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S.

2017-01-01

Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a=(u,v) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages. PMID:28771201

Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks.

PubMed

Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S

2017-08-03

Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a = ( u , v ) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages.

Teacher Perspectives on Technology Integration Professional Development: Formal, Informal, and Independent Learning Activities

ERIC Educational Resources Information Center

Jones, Monty; Dexter, Sara

2018-01-01

This mixed-methods study examined the technology integration learning activities of four teachers throughout one year using weekly quantitative surveys and a series of three qualitative individual interviews. Through the teachers' own voices an illustration of their learning processes is presented, and the gap between what is supported by their…

Students awareness of learning styles and their perceptions to a mixed method approach for learning

PubMed Central

Bhagat, Anumeha; Vyas, Rashmi; Singh, Tejinder

2015-01-01

Background: Individualization of instructional method does not contribute significantly to learning outcomes although it is known that students have differing learning styles (LSs). Hence, in order to maximally enhance learning, one must try to use a mixed method approach. Hypothesis: Our hypothesis was that awareness of preferred LS and motivation to incorporate multiple learning strategies might enhance learning outcomes. Aim: Our aim was to determine the impact of awareness of LS among medical undergraduates and motivating students to use mixed methods of learning. Materials and Methods: Before awareness lecture, LS preferences were determined using Visual, Aural, Read/Write, and Kinesthetic (VARK) questionnaire. Awareness of LS was assessed using a validated questionnaire. Through a lecture, students were oriented to various LSs, impact of LS on their performance, and benefit of using mixed method approach for learning. Subsequently, group discussions were organized. After 3 months, VARK preferences and awareness of LSs were reassessed. Student narratives were collected. Qualitative analysis of the data was done. Results: There was a significant increase in the number of students who were aware of LS. The number of participants showing a change in VARK scores for various modalities of learning was also significant (P < 0.001). Conclusion: Thus, awareness of LSs motivated students to adapt other learning strategies and use mixed methods for learning. PMID:26380214

Designing for Inquiry-Based Learning with the Learning Activity Management System

ERIC Educational Resources Information Center

Levy, P.; Aiyegbayo, O.; Little, S.

2009-01-01

This paper explores the relationship between practitioners' pedagogical purposes, values and practices in designing for inquiry-based learning in higher education, and the affordances of the Learning Activity Management System (LAMS) as a tool for creating learning designs in this context. Using a qualitative research methodology, variation was…

Active learning reduces annotation time for clinical concept extraction.

PubMed

Kholghi, Mahnoosh; Sitbon, Laurianne; Zuccon, Guido; Nguyen, Anthony

2017-10-01

To investigate: (1) the annotation time savings by various active learning query strategies compared to supervised learning and a random sampling baseline, and (2) the benefits of active learning-assisted pre-annotations in accelerating the manual annotation process compared to de novo annotation. There are 73 and 120 discharge summary reports provided by Beth Israel institute in the train and test sets of the concept extraction task in the i2b2/VA 2010 challenge, respectively. The 73 reports were used in user study experiments for manual annotation. First, all sequences within the 73 reports were manually annotated from scratch. Next, active learning models were built to generate pre-annotations for the sequences selected by a query strategy. The annotation/reviewing time per sequence was recorded. The 120 test reports were used to measure the effectiveness of the active learning models. When annotating from scratch, active learning reduced the annotation time up to 35% and 28% compared to a fully supervised approach and a random sampling baseline, respectively. Reviewing active learning-assisted pre-annotations resulted in 20% further reduction of the annotation time when compared to de novo annotation. The number of concepts that require manual annotation is a good indicator of the annotation time for various active learning approaches as demonstrated by high correlation between time rate and concept annotation rate. Active learning has a key role in reducing the time required to manually annotate domain concepts from clinical free text, either when annotating from scratch or reviewing active learning-assisted pre-annotations. Copyright © 2017 Elsevier B.V. All rights reserved.

Combining Active Learning with Service Learning: A Student-Driven Demonstration Project.

ERIC Educational Resources Information Center

Hatcher-Skeers, Mary; Aragon, Ellen

2002-01-01

Describes a project that integrates active learning into service learning targeting both college students and middle schools students wherein college students perform chemical demonstrations for middle school students. (YDS)

Students awareness of learning styles and their perceptions to a mixed method approach for learning.

PubMed

Bhagat, Anumeha; Vyas, Rashmi; Singh, Tejinder

2015-08-01

Individualization of instructional method does not contribute significantly to learning outcomes although it is known that students have differing learning styles (LSs). Hence, in order to maximally enhance learning, one must try to use a mixed method approach. Our hypothesis was that awareness of preferred LS and motivation to incorporate multiple learning strategies might enhance learning outcomes. Our aim was to determine the impact of awareness of LS among medical undergraduates and motivating students to use mixed methods of learning. Before awareness lecture, LS preferences were determined using Visual, Aural, Read/Write, and Kinesthetic (VARK) questionnaire. Awareness of LS was assessed using a validated questionnaire. Through a lecture, students were oriented to various LSs, impact of LS on their performance, and benefit of using mixed method approach for learning. Subsequently, group discussions were organized. After 3 months, VARK preferences and awareness of LSs were reassessed. Student narratives were collected. Qualitative analysis of the data was done. There was a significant increase in the number of students who were aware of LS. The number of participants showing a change in VARK scores for various modalities of learning was also significant (P < 0.001). Thus, awareness of LSs motivated students to adapt other learning strategies and use mixed methods for learning.

Supporting traditional instructional methods with a constructivist approach to learning: Promoting conceputal change and understanding of stoichiometry using e-learning tools

NASA Astrophysics Data System (ADS)

Abayan, Kenneth Munoz

Stoichiometry is a fundamental topic in chemistry that measures a quantifiable relationship between atoms, molecules, etc. Stoichiometry is usually taught using expository teaching methods. Students are passively given information, in the hopes they will retain the transmission of information to be able to solve stoichiometry problems masterfully. Cognitive science research has shown that this kind of instructional teaching method is not very effecting in meaningful learning practice. Instead, students must take ownership of their learning. The students need to actively construct their own knowledge by receiving, interpreting, integrating and reorganizing that information into their own mental schemas. In the absence of active learning practices, tools must be created in such a way to be able to scaffold difficult problems by encoding opportunities necessary to make the construction of knowledge memorable, thereby creating a usable knowledge base. Using an online e-learning tool and its potential to create a dynamic and interactive learning environment may facilitate the learning of stoichiometry. The study entailed requests from volunteer students, IRB consent form, a baseline questionnaire, random assignment of treatment, pre- and post-test assessment, and post assessment survey. These activities were given online. A stoichiometry-based assessment was given in a proctored examination at the University of Texas at Arlington (UTA) campus. The volunteer students who took part in these studies were at least 18 of age and were enrolled in General Chemistry 1441, at the University of Texas at Arlington. Each participant gave their informed consent to use their data in the following study. Students were randomly assigned to one of 4 treatments groups based on teaching methodology, (Dimensional Analysis, Operational Method, Ratios and Proportions) and a control group who just received instruction through lecture only. In this study, an e-learning tool was created to

ASPECT: A Survey to Assess Student Perspective of Engagement in an Active-Learning Classroom.

PubMed

Wiggins, Benjamin L; Eddy, Sarah L; Wener-Fligner, Leah; Freisem, Karen; Grunspan, Daniel Z; Theobald, Elli J; Timbrook, Jerry; Crowe, Alison J

2017-01-01

The primary measure used to determine relative effectiveness of in-class activities has been student performance on pre/posttests. However, in today's active-learning classrooms, learning is a social activity, requiring students to interact and learn from their peers. To develop effective active-learning exercises that engage students, it is important to gain a more holistic view of the student experience in an active-learning classroom. We have taken a mixed-methods approach to iteratively develop and validate a 16-item survey to measure multiple facets of the student experience during active-learning exercises. The instrument, which we call A ssessing S tudent P erspective of E ngagement in C lass T ool (ASPECT), was administered to a large introductory biology class, and student responses were subjected to exploratory factor analysis. The 16 items loaded onto three factors that cumulatively explained 52% of the variation in student response: 1) value of activity, 2) personal effort, and 3) instructor contribution. ASPECT provides a rapid, easily administered means to measure student perception of engagement in an active-learning classroom. Gaining a better understanding of students' level of engagement will help inform instructor best practices and provide an additional measure for comprehensively assessing the impact of different active-learning strategies. © 2017 B. L. Wiggins, S. L. Eddy, et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Environmental Monitoring Networks Optimization Using Advanced Active Learning Algorithms

NASA Astrophysics Data System (ADS)

Kanevski, Mikhail; Volpi, Michele; Copa, Loris

2010-05-01

The problem of environmental monitoring networks optimization (MNO) belongs to one of the basic and fundamental tasks in spatio-temporal data collection, analysis, and modeling. There are several approaches to this problem, which can be considered as a design or redesign of monitoring network by applying some optimization criteria. The most developed and widespread methods are based on geostatistics (family of kriging models, conditional stochastic simulations). In geostatistics the variance is mainly used as an optimization criterion which has some advantages and drawbacks. In the present research we study an application of advanced techniques following from the statistical learning theory (SLT) - support vector machines (SVM) and the optimization of monitoring networks when dealing with a classification problem (data are discrete values/classes: hydrogeological units, soil types, pollution decision levels, etc.) is considered. SVM is a universal nonlinear modeling tool for classification problems in high dimensional spaces. The SVM solution is maximizing the decision boundary between classes and has a good generalization property for noisy data. The sparse solution of SVM is based on support vectors - data which contribute to the solution with nonzero weights. Fundamentally the MNO for classification problems can be considered as a task of selecting new measurement points which increase the quality of spatial classification and reduce the testing error (error on new independent measurements). In SLT this is a typical problem of active learning - a selection of the new unlabelled points which efficiently reduce the testing error. A classical approach (margin sampling) to active learning is to sample the points closest to the classification boundary. This solution is suboptimal when points (or generally the dataset) are redundant for the same class. In the present research we propose and study two new advanced methods of active learning adapted to the solution of

AAC menu interface: effectiveness of active versus passive learning to master abbreviation-expansion codes.

PubMed

Gregory, Ellyn; Soderman, Melinda; Ward, Christy; Beukelman, David R; Hux, Karen

2006-06-01

This study investigated the accuracy with which 30 young adults without disabilities learned abbreviation expansion codes associated with specific vocabulary items that were stored in an AAC device with two accessing methods: mouse access and keyboard access. Both accessing methods utilized a specialized computer application, called AAC Menu, which allowed for errorless practice. Mouse access prompted passive learning, whereas keyboard access prompted active learning. Results revealed that participants who accessed words via a keyboard demonstrated significantly higher mastery of abbreviation-expansion codes than those who accessed words via a computer mouse.

Kinespell: Kinesthetic Learning Activity and Assessment in a Digital Game-Based Learning Environment

NASA Astrophysics Data System (ADS)

Cariaga, Ada Angeli; Salvador, Jay Andrae; Solamo, Ma. Rowena; Feria, Rommel

Various approaches in learning are commonly classified into visual, auditory and kinesthetic (VAK) learning styles. One way of addressing the VAK learning styles is through game-based learning which motivates learners pursue knowledge holistically. The paper presents Kinespell, an unconventional method of learning through digital game-based learning. Kinespell is geared towards enhancing not only the learner’s spelling abilities but also the motor skills through utilizing wireless controllers. It monitors player’s performance through integrated assessment scheme. Results show that Kinespell may accommodate the VAK learning styles and is a promising alternative to established methods in learning and assessing students’ performance in Spelling.

A visual tracking method based on improved online multiple instance learning

NASA Astrophysics Data System (ADS)

He, Xianhui; Wei, Yuxing

2016-09-01

Visual tracking is an active research topic in the field of computer vision and has been well studied in the last decades. The method based on multiple instance learning (MIL) was recently introduced into the tracking task, which can solve the problem that template drift well. However, MIL method has relatively poor performance in running efficiency and accuracy, due to its strong classifiers updating strategy is complicated, and the speed of the classifiers update is not always same with the change of the targets' appearance. In this paper, we present a novel online effective MIL (EMIL) tracker. A new update strategy for strong classifier was proposed to improve the running efficiency of MIL method. In addition, to improve the t racking accuracy and stability of the MIL method, a new dynamic mechanism for learning rate renewal of the classifier and variable search window were proposed. Experimental results show that our method performs good performance under the complex scenes, with strong stability and high efficiency.

A Machine Learning Method for the Prediction of Receptor Activation in the Simulation of Synapses

PubMed Central

Montes, Jesus; Gomez, Elena; Merchán-Pérez, Angel; DeFelipe, Javier; Peña, Jose-Maria

2013-01-01

Chemical synaptic transmission involves the release of a neurotransmitter that diffuses in the extracellular space and interacts with specific receptors located on the postsynaptic membrane. Computer simulation approaches provide fundamental tools for exploring various aspects of the synaptic transmission under different conditions. In particular, Monte Carlo methods can track the stochastic movements of neurotransmitter molecules and their interactions with other discrete molecules, the receptors. However, these methods are computationally expensive, even when used with simplified models, preventing their use in large-scale and multi-scale simulations of complex neuronal systems that may involve large numbers of synaptic connections. We have developed a machine-learning based method that can accurately predict relevant aspects of the behavior of synapses, such as the percentage of open synaptic receptors as a function of time since the release of the neurotransmitter, with considerably lower computational cost compared with the conventional Monte Carlo alternative. The method is designed to learn patterns and general principles from a corpus of previously generated Monte Carlo simulations of synapses covering a wide range of structural and functional characteristics. These patterns are later used as a predictive model of the behavior of synapses under different conditions without the need for additional computationally expensive Monte Carlo simulations. This is performed in five stages: data sampling, fold creation, machine learning, validation and curve fitting. The resulting procedure is accurate, automatic, and it is general enough to predict synapse behavior under experimental conditions that are different to the ones it has been trained on. Since our method efficiently reproduces the results that can be obtained with Monte Carlo simulations at a considerably lower computational cost, it is suitable for the simulation of high numbers of synapses and it is

Active Learning and Teaching: Improving Postsecondary Library Instruction.

ERIC Educational Resources Information Center

Allen, Eileen E.

1995-01-01

Discusses ways to improve postsecondary library instruction based on theories of active learning. Topics include a historical background of active learning; student achievement and attitudes; cognitive development; risks; active teaching; and instructional techniques, including modified lectures, brainstorming, small group work, cooperative…

Learning styles: The learning methods of air traffic control students

NASA Astrophysics Data System (ADS)

Jackson, Dontae L.

In the world of aviation, air traffic controllers are an integral part in the overall level of safety that is provided. With a number of controllers reaching retirement age, the Air Traffic Collegiate Training Initiative (AT-CTI) was created to provide a stronger candidate pool. However, AT-CTI Instructors have found that a number of AT-CTI students are unable to memorize types of aircraft effectively. This study focused on the basic learning styles (auditory, visual, and kinesthetic) of students and created a teaching method to try to increase memorization in AT-CTI students. The participants were asked to take a questionnaire to determine their learning style. Upon knowing their learning styles, participants attended two classroom sessions. The participants were given a presentation in the first class, and divided into a control and experimental group for the second class. The control group was given the same presentation from the first classroom session while the experimental group had a group discussion and utilized Middle Tennessee State University's Air Traffic Control simulator to learn the aircraft types. Participants took a quiz and filled out a survey, which tested the new teaching method. An appropriate statistical analysis was applied to determine if there was a significant difference between the control and experimental groups. The results showed that even though the participants felt that the method increased their learning, there was no significant difference between the two groups.

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

PubMed Central

Omar, Esam

2017-01-01

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

Sparse feature learning for instrument identification: Effects of sampling and pooling methods.

PubMed

Han, Yoonchang; Lee, Subin; Nam, Juhan; Lee, Kyogu

2016-05-01

Feature learning for music applications has recently received considerable attention from many researchers. This paper reports on the sparse feature learning algorithm for musical instrument identification, and in particular, focuses on the effects of the frame sampling techniques for dictionary learning and the pooling methods for feature aggregation. To this end, two frame sampling techniques are examined that are fixed and proportional random sampling. Furthermore, the effect of using onset frame was analyzed for both of proposed sampling methods. Regarding summarization of the feature activation, a standard deviation pooling method is used and compared with the commonly used max- and average-pooling techniques. Using more than 47 000 recordings of 24 instruments from various performers, playing styles, and dynamics, a number of tuning parameters are experimented including the analysis frame size, the dictionary size, and the type of frequency scaling as well as the different sampling and pooling methods. The results show that the combination of proportional sampling and standard deviation pooling achieve the best overall performance of 95.62% while the optimal parameter set varies among the instrument classes.

E-Collaboration Technologies in Teaching/Learning Activity

ERIC Educational Resources Information Center

Zascerinska, Jelena; Ahrens, Andreas

2009-01-01

A proper use of e-collaboration technologies in the teaching/learning process is provided by varied cooperative networks, which penetrate teachers' and students' activity more thoroughly with the availability of broadband services. However, the successful use of e-collaboration technologies in teaching/learning activity within a multicultural…

Active learning: learning a motor skill without a coach.

PubMed

Huang, Vincent S; Shadmehr, Reza; Diedrichsen, Jörn

2008-08-01

When we learn a new skill (e.g., golf) without a coach, we are "active learners": we have to choose the specific components of the task on which to train (e.g., iron, driver, putter, etc.). What guides our selection of the training sequence? How do choices that people make compare with choices made by machine learning algorithms that attempt to optimize performance? We asked subjects to learn the novel dynamics of a robotic tool while moving it in four directions. They were instructed to choose their practice directions to maximize their performance in subsequent tests. We found that their choices were strongly influenced by motor errors: subjects tended to immediately repeat an action if that action had produced a large error. This strategy was correlated with better performance on test trials. However, even when participants performed perfectly on a movement, they did not avoid repeating that movement. The probability of repeating an action did not drop below chance even when no errors were observed. This behavior led to suboptimal performance. It also violated a strong prediction of current machine learning algorithms, which solve the active learning problem by choosing a training sequence that will maximally reduce the learner's uncertainty about the task. While we show that these algorithms do not provide an adequate description of human behavior, our results suggest ways to improve human motor learning by helping people choose an optimal training sequence.

Active appearance model and deep learning for more accurate prostate segmentation on MRI

NASA Astrophysics Data System (ADS)

Cheng, Ruida; Roth, Holger R.; Lu, Le; Wang, Shijun; Turkbey, Baris; Gandler, William; McCreedy, Evan S.; Agarwal, Harsh K.; Choyke, Peter; Summers, Ronald M.; McAuliffe, Matthew J.

2016-03-01

Prostate segmentation on 3D MR images is a challenging task due to image artifacts, large inter-patient prostate shape and texture variability, and lack of a clear prostate boundary specifically at apex and base levels. We propose a supervised machine learning model that combines atlas based Active Appearance Model (AAM) with a Deep Learning model to segment the prostate on MR images. The performance of the segmentation method is evaluated on 20 unseen MR image datasets. The proposed method combining AAM and Deep Learning achieves a mean Dice Similarity Coefficient (DSC) of 0.925 for whole 3D MR images of the prostate using axial cross-sections. The proposed model utilizes the adaptive atlas-based AAM model and Deep Learning to achieve significant segmentation accuracy.

Instilling positive beliefs about disabilities: pilot testing a novel experiential learning activity for rehabilitation students.

PubMed

Silverman, Arielle M; Pitonyak, Jennifer S; Nelson, Ian K; Matsuda, Patricia N; Kartin, Deborah; Molton, Ivan R

2018-05-01

To develop and test a novel impairment simulation activity to teach beginning rehabilitation students how people adapt to physical impairments. Masters of Occupational Therapy students (n = 14) and Doctor of Physical Therapy students (n = 18) completed the study during the first month of their program. Students were randomized to the experimental or control learning activity. Experimental students learned to perform simple tasks while simulating paraplegia and hemiplegia. Control students viewed videos of others completing tasks with these impairments. Before and after the learning activities, all students estimated average self-perceived health, life satisfaction, and depression ratings among people with paraplegia and hemiplegia. Experimental students increased their estimates of self-perceived health, and decreased their estimates of depression rates, among people with paraplegia and hemiplegia after the learning activity. The control activity had no effect on these estimates. Impairment simulation can be an effective way to teach rehabilitation students about the adaptations that people make to physical impairments. Positive impairment simulations should allow students to experience success in completing activities of daily living with impairments. Impairment simulation is complementary to other pedagogical methods, such as simulated clinical encounters using standardized patients. Implication of Rehabilitation It is important for rehabilitation students to learn how people live well with disabilities. Impairment simulations can improve students' assessments of quality of life with disabilities. To be beneficial, impairment simulations must include guided exposure to effective methods for completing daily tasks with disabilities.

Empathy and feedback processing in active and observational learning.

PubMed

Rak, Natalia; Bellebaum, Christian; Thoma, Patrizia

2013-12-01

The feedback-related negativity (FRN) and the P300 have been related to the processing of one's own and other individuals' feedback during both active and observational learning. The aim of the present study was to elucidate the role of trait-empathic responding with regard to the modulation of the neural correlates of observational learning in particular. Thirty-four healthy participants completed an active and an observational learning task. On both tasks, the participants' aim was to maximize their monetary gain by choosing from two stimuli the one that showed the higher probability of reward. Participants gained insight into the stimulus-reward contingencies according to monetary feedback presented after they had made an active choice or by observing the choices of a virtual partner. Participants showed a general improvement in learning performance on both learning tasks. P200, FRN, and P300 amplitudes were larger during active, as compared with observational, learning. Furthermore, nonreward elicited a significantly more negative FRN than did reward in the active learning task, while only a trend was observed for observational learning. Distinct subcomponents of trait cognitive empathy were related to poorer performance and smaller P300 amplitudes for observational learning only. Taken together, both the learning performance and event-related potentials during observational learning are affected by different aspects of trait cognitive empathy, and certain types of observational learning may actually be disrupted by a higher tendency to understand and adopt other people's perspectives.

Developing Metacognition: A Basis for Active Learning

ERIC Educational Resources Information Center

Vos, Henk; de Graaff, E.

2004-01-01

The reasons to introduce formats of active learning in engineering (ALE) such as project work, problem-based learning, use of cases, etc. are mostly based on practical experience, and sometimes from applied research on teaching and learning. Such research shows that students learn more and different abilities than in traditional formats of…

Effect of Chemistry Triangle Oriented Learning Media on Cooperative, Individual and Conventional Method on Chemistry Learning Result

NASA Astrophysics Data System (ADS)

Latisma D, L.; Kurniawan, W.; Seprima, S.; Nirbayani, E. S.; Ellizar, E.; Hardeli, H.

2018-04-01

The purpose of this study was to see which method are well used with the Chemistry Triangle-oriented learning media. This quasi experimental research involves first grade of senior high school students in six schools namely each two SMA N in Solok city, in Pasaman and two SMKN in Pariaman. The sampling technique was done by Cluster Random Sampling. Data were collected by test and analyzed by one-way anova and Kruskall Wallish test. The results showed that the high school students in Solok learning taught by cooperative method is better than the results of student learning taught by conventional and Individual methods, both for students who have high initial ability and low-ability. Research in SMK showed that the overall student learning outcomes taught by conventional method is better than the student learning outcomes taught by cooperative and individual methods. Student learning outcomes that have high initial ability taught by individual method is better than student learning outcomes that are taught by cooperative method and for students who have low initial ability, there is no difference in student learning outcomes taught by cooperative, individual and conventional methods. Learning in high school in Pasaman showed no significant difference in learning outcomes of the three methods undertaken.

Tractor Mechanics: Learning Activity Packages 1-19.

ERIC Educational Resources Information Center

Clemson Univ., SC. Vocational Education Media Center.

Learning activity packages are presented for teaching tractor mechanics. The first of two sections deals with miscellaneous tasks and contains learning activity packages on cleaning the tractor and receiving new tractor parts. Section 2 is concerned with maintaining and servicing the electrical system, and it includes the following learning…

Identifying Key Features of Effective Active Learning: The Effects of Writing and Peer Discussion

PubMed Central

Pangle, Wiline M.; Wyatt, Kevin H.; Powell, Karli N.; Sherwood, Rachel E.

2014-01-01

We investigated some of the key features of effective active learning by comparing the outcomes of three different methods of implementing active-learning exercises in a majors introductory biology course. Students completed activities in one of three treatments: discussion, writing, and discussion + writing. Treatments were rotated weekly between three sections taught by three different instructors in a full factorial design. The data set was analyzed by generalized linear mixed-effect models with three independent variables: student aptitude, treatment, and instructor, and three dependent (assessment) variables: change in score on pre- and postactivity clicker questions, and coding scores on in-class writing and exam essays. All independent variables had significant effects on student performance for at least one of the dependent variables. Students with higher aptitude scored higher on all assessments. Student scores were higher on exam essay questions when the activity was implemented with a writing component compared with peer discussion only. There was a significant effect of instructor, with instructors showing different degrees of effectiveness with active-learning techniques. We suggest that individual writing should be implemented as part of active learning whenever possible and that instructors may need training and practice to become effective with active learning. PMID:25185230

Students' Perceptions of an Experiential Learning Activity Designed to Develop Knowledge of Food and Food Preparation Methods

ERIC Educational Resources Information Center

Leveritt, Michael; Ball, Lauren; Desbrow, Jane

2013-01-01

The aim of this study was to describe student learning after completing an experiential learning task that was designed to develop students' knowledge of food and food preparation methods. The task required students to follow a special diet and then complete a daily online journal entry about the experience for other students to read and review.…

Transforming an Introductory Programming Course: From Lectures to Active Learning via Wireless Laptops

NASA Astrophysics Data System (ADS)

Barak, Miri; Harward, Judson; Kocur, George; Lerman, Steven

2007-08-01

Within the framework of MIT's course 1.00: Introduction to Computers and Engineering Problem Solving, this paper describes an innovative project entitled: Studio 1.00 that integrates lectures with in-class demonstrations, active learning sessions, and on-task feedback, through the use of wireless laptop computers. This paper also describes a related evaluation study that investigated the effectiveness of different instructional strategies, comparing traditional teaching with two models of the studio format. Students' learning outcomes, specifically, their final grades and conceptual understanding of computational methods and programming, were examined. Findings indicated that Studio-1.00, in both its extensive- and partial-active learning modes, enhanced students' learning outcomes in Java programming. Comparing to the traditional courses, more students in the studio courses received "A" as their final grade and less failed. Moreover, students who regularly attended the active learning sessions were able to conceptualize programming principles better than their peers. We have also found two weaknesses in the teaching format of Studio-1.00 that can guide future versions of the course.

Efficient model learning methods for actor-critic control.

PubMed

Grondman, Ivo; Vaandrager, Maarten; Buşoniu, Lucian; Babuska, Robert; Schuitema, Erik

2012-06-01

We propose two new actor-critic algorithms for reinforcement learning. Both algorithms use local linear regression (LLR) to learn approximations of the functions involved. A crucial feature of the algorithms is that they also learn a process model, and this, in combination with LLR, provides an efficient policy update for faster learning. The first algorithm uses a novel model-based update rule for the actor parameters. The second algorithm does not use an explicit actor but learns a reference model which represents a desired behavior, from which desired control actions can be calculated using the inverse of the learned process model. The two novel methods and a standard actor-critic algorithm are applied to the pendulum swing-up problem, in which the novel methods achieve faster learning than the standard algorithm.

Active Learning and Engagement with the Wireless Indoor Location Device (WILD) Learning System

NASA Astrophysics Data System (ADS)

Moldwin, M.; Samson, P. J.; Ojeda, L.; Miller, T.; Yu, J.

2016-12-01

The Wireless Indoor Location Device (WILD) Learning System being developed at the University of Michigan and the Education Technology company A2 Motus LLC provides a unique platform for social learning by allowing students to become active participants in live simulations of complex systems, like hurricane formation. The WILD Learning System enables teachers to engage students in kinesthetic activities that explore complex models from a wide variety of STEAM (Science, Technology, Engineering, Art and Math) disciplines. The system provides students' location, orientation and motion within the classroom and assigns each student different parameters depending on the activity. For example, students learning about hurricanes could be assigned atmospheric pressure levels and asked to arrange themselves around the room to simulate a hurricane. The Wild Learning System software then takes the students' pressure readings and locations and projects their locations overlaid onto a real-time generated simulated pressure weather map enabling the observation of how their arrangement influences the pressure structure. The teacher then could have the students orient themselves in the direction they think the resulting wind field will be based on the pressure contours as the system can show an arrow originating from each of the students position in the direction that they are facing. The system also could incorporate a student response-type system for the instructor to then directly question students about other concepts and record their response to both the kinesthetic activity and other formative assessment questions. The WILD Learning System consists of a sensor package for each student in the class, beacons to enable precise localization of the students, software to calculate student location information, and educational software for a variety of activities. In addition, a software development kit (SDK) is under development that would allow others to create additional learning

Psychological and Pedagogic Conditions of Activating Creative Activity in Students for Successful Learning

ERIC Educational Resources Information Center

Abykanova, Bakytgul; Bilyalova, Zhupar; Makhatova, Valentina; Idrissov, Salamat; Nugumanov, Samal

2016-01-01

Creative activity of a pedagogic process subject depends on the pedagogue's position, on his faith in the abilities to learn successfully, on encouragement of achievements, stimulating the initiative and activity. Successful learning by activating creative activity is possible with the presence of respectful attitude towards the pedagogic process…

Inquiring into Three Approaches to Hands-On Learning in Elementary and Secondary Science Methods Courses.

ERIC Educational Resources Information Center

Barnes, Marianne B.; Foley, Kathleen R.

1999-01-01

Investigates three approaches to hands-on science learning in two contexts, an elementary science methods class and a secondary science methods class. Focused on an activity on foam. Concludes that when developing models for teaching science methods courses, methods instructors need to share power with prospective teachers. (Author/MM)

Incorporating Active Learning Techniques into a Genetics Class

ERIC Educational Resources Information Center

Lee, W. Theodore; Jabot, Michael E.

2011-01-01

We revised a sophomore-level genetics class to more actively engage the students in their learning. The students worked in groups on quizzes using the Immediate Feedback Assessment Technique (IF-AT) and active-learning projects. The IF-AT quizzes allowed students to discuss key concepts in small groups and learn the correct answers in class. The…

Faculty Perceptions about Barriers to Active Learning

ERIC Educational Resources Information Center

Michael, Joel

2007-01-01

Faculty may perceive many barriers to active learning in their classrooms. Four groups of participants in a faculty development workshop were asked to list their perceived barriers to active learning. Many of the problems identified were present on more than one list. The barriers fall into three categories: student characteristics, issues…

Active Learning: The Importance of Developing a Comprehensive Measure

ERIC Educational Resources Information Center

Carr, Rodney; Palmer, Stuart; Hagel, Pauline

2015-01-01

This article reports on an investigation into the validity of a widely used scale for measuring the extent to which higher education students employ active learning strategies. The scale is the active learning scale in the Australasian Survey of Student Engagement. This scale is based on the Active and Collaborative Learning scale of the National…

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.

E-Learning as New Method of Medical Education

PubMed Central

Masic, Izet

2008-01-01

CONFLICT OF INTEREST: NONE DECLARED Distance learning refers to use of technologies based on health care delivered on distance and covers areas such as electronic health, tele-health (e-health), telematics, telemedicine, tele-education, etc. For the need of e-health, telemedicine, tele-education and distance learning there are various technologies and communication systems from standard telephone lines to the system of transmission digitalized signals with modem, optical fiber, satellite links, wireless technologies, etc. Tele-education represents health education on distance, using Information Communication Technologies (ICT), as well as continuous education of a health system beneficiaries and use of electronic libraries, data bases or electronic data with data bases of knowledge. Distance learning (E-learning) as a part of tele-education has gained popularity in the past decade; however, its use is highly variable among medical schools and appears to be more common in basic medical science courses than in clinical education. Distance learning does not preclude traditional learning processes; frequently it is used in conjunction with in-person classroom or professional training procedures and practices. Tele-education has mostly been used in biomedical education as a blended learning method, which combines tele-education technology with traditional instructor-led training, where, for example, a lecture or demonstration is supplemented by an online tutorial. Distance learning is used for self-education, tests, services and for examinations in medicine i.e. in terms of self-education and individual examination services. The possibility of working in the exercise mode with image files and questions is an attractive way of self education. Automated tracking and reporting of learners’ activities lessen faculty administrative burden. Moreover, e-learning can be designed to include outcomes assessment to determine whether learning has occurred. This review article

E-learning as new method of medical education.

PubMed

Masic, Izet

2008-01-01

NONE DECLARED Distance learning refers to use of technologies based on health care delivered on distance and covers areas such as electronic health, tele-health (e-health), telematics, telemedicine, tele-education, etc. For the need of e-health, telemedicine, tele-education and distance learning there are various technologies and communication systems from standard telephone lines to the system of transmission digitalized signals with modem, optical fiber, satellite links, wireless technologies, etc. Tele-education represents health education on distance, using Information Communication Technologies (ICT), as well as continuous education of a health system beneficiaries and use of electronic libraries, data bases or electronic data with data bases of knowledge. Distance learning (E-learning) as a part of tele-education has gained popularity in the past decade; however, its use is highly variable among medical schools and appears to be more common in basic medical science courses than in clinical education. Distance learning does not preclude traditional learning processes; frequently it is used in conjunction with in-person classroom or professional training procedures and practices. Tele-education has mostly been used in biomedical education as a blended learning method, which combines tele-education technology with traditional instructor-led training, where, for example, a lecture or demonstration is supplemented by an online tutorial. Distance learning is used for self-education, tests, services and for examinations in medicine i.e. in terms of self-education and individual examination services. The possibility of working in the exercise mode with image files and questions is an attractive way of self education. Automated tracking and reporting of learners' activities lessen faculty administrative burden. Moreover, e-learning can be designed to include outcomes assessment to determine whether learning has occurred. This review article evaluates the current

[Can medical students' motivation for a course of basic physiology education integrating into lectures some active learning methods be improved?

PubMed

Bentata, Yassamine; Delfosse, Catherine

2017-01-01

Students' motivation is a critical component of learning and students' perception of activity value is one of the three major components of their motivation. How can we make students perceive the usefulness and the interest of their university courses while increasing their motivation? The aim of our study was to determine students' perception of basic physiology education value and to assess the impact of lecture integration into some active learning methods on the motivation of the students of the first cycle of Medicine in a junior faculty. We conducted a prospective study, involving the students in their second year of medical studies. At first, we assessed students' motivation for university courses through a first questionnaire, after we integrated two educational activities: the case study and the realization of a conceptual map for the lectures of the physiology module and then we evaluated, through a second questionnaire, the impact of these two activities on students' motivation. Out of 249 students in their second year of medical studies 131 and 109 students have completed and returned the 1st and 2nd questionnaire respectively. Overall students' motivation for their university courses was very favorable, even if the motivation for physiology course (70.8%) was slightly lower than for all the courses (80%). Our students enjoyed the two proposed activities and only 13% (for the case study) and 16.8% (for the map) were not satisfied. 40.9% of students completed a conceptual map whose quality judged on the identification of concepts and of the links between concepts was globally satisfactory for a first experience. Students' motivation is influenced by multiple internal and external factors and is a big problem in the university environment. In this context, a rigorous planning of diversified and active educational activities is one of the main gateways for teacher to encourage motivation.

Deep learning methods for protein torsion angle prediction.

PubMed

Li, Haiou; Hou, Jie; Adhikari, Badri; Lyu, Qiang; Cheng, Jianlin

2017-09-18

Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition. In this work, we developed deep learning methods to improve the prediction of torsion (dihedral) angles of proteins. We design four different deep learning architectures to predict protein torsion angles. The architectures including deep neural network (DNN) and deep restricted Boltzmann machine (DRBN), deep recurrent neural network (DRNN) and deep recurrent restricted Boltzmann machine (DReRBM) since the protein torsion angle prediction is a sequence related problem. In addition to existing protein features, two new features (predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments) are used as input to each of the four deep learning architectures to predict phi and psi angles of protein backbone. The mean absolute error (MAE) of phi and psi angles predicted by DRNN, DReRBM, DRBM and DNN is about 20-21° and 29-30° on an independent dataset. The MAE of phi angle is comparable to the existing methods, but the MAE of psi angle is 29°, 2° lower than the existing methods. On the latest CASP12 targets, our methods also achieved the performance better than or comparable to a state-of-the art method. Our experiment demonstrates that deep learning is a valuable method for predicting protein torsion angles. The deep recurrent network architecture performs slightly better than deep feed-forward architecture, and the predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments are useful features for improving prediction accuracy.

Collegial Activity Learning between Heterogeneous Sensors.

PubMed

Feuz, Kyle D; Cook, Diane J

2017-11-01

Activity recognition algorithms have matured and become more ubiquitous in recent years. However, these algorithms are typically customized for a particular sensor platform. In this paper we introduce PECO, a Personalized activity ECOsystem, that transfers learned activity information seamlessly between sensor platforms in real time so that any available sensor can continue to track activities without requiring its own extensive labeled training data. We introduce a multi-view transfer learning algorithm that facilitates this information handoff between sensor platforms and provide theoretical performance bounds for the algorithm. In addition, we empirically evaluate PECO using datasets that utilize heterogeneous sensor platforms to perform activity recognition. These results indicate that not only can activity recognition algorithms transfer important information to new sensor platforms, but any number of platforms can work together as colleagues to boost performance.

Activity confrontation methods: A reflexive and metacognitive approach for interprofessional collaboration training.

PubMed

Aiguier, Gregory; Oboeuf, Alexandre; Cobbaut, Jean-Philippe; Vanpee, Dominique

2015-01-01

Integration of interprofessional collaboration into healthcare education and training programmes has become a fundamental issue. Its objective is to learn how to collectively build collaborative care practice that addresses the uniqueness of each context and the specific situation of the patient. It is also about understanding the process of collectively building collaborative care practice in order to be able to apply it in different contexts. This article describes a study that aimed to examine the value of relying on activity confrontation methods to develop training. These methods consist of filming practitioners during an activity and encouraging them to analyse it. It was found that these methods encourage reflexive analysis of the motives for pursuing interprofessional action (identifying constitutive factors) but also a metacognitive approach on the conditions of learning (p < 0.01). In addition to the educational dimensions (methods and leadership positions) and organisational dimensions (frameworks), it was found that the patient's role is essential in developing interprofessional care practice and training (p < 0.01). Given the nature of these findings, this article goes on to suggest that the patient must be considered a "partner" in development and delivery of interprofessional learning and care.

Optimization methods for activities selection problems

NASA Astrophysics Data System (ADS)

Mahad, Nor Faradilah; Alias, Suriana; Yaakop, Siti Zulaika; Arshad, Norul Amanina Mohd; Mazni, Elis Sofia

2017-08-01

Co-curriculum activities must be joined by every student in Malaysia and these activities bring a lot of benefits to the students. By joining these activities, the students can learn about the time management and they can developing many useful skills. This project focuses on the selection of co-curriculum activities in secondary school using the optimization methods which are the Analytic Hierarchy Process (AHP) and Zero-One Goal Programming (ZOGP). A secondary school in Negeri Sembilan, Malaysia was chosen as a case study. A set of questionnaires were distributed randomly to calculate the weighted for each activity based on the 3 chosen criteria which are soft skills, interesting activities and performances. The weighted was calculated by using AHP and the results showed that the most important criteria is soft skills. Then, the ZOGP model will be analyzed by using LINGO Software version 15.0. There are two priorities to be considered. The first priority which is to minimize the budget for the activities is achieved since the total budget can be reduced by RM233.00. Therefore, the total budget to implement the selected activities is RM11,195.00. The second priority which is to select the co-curriculum activities is also achieved. The results showed that 9 out of 15 activities were selected. Thus, it can concluded that AHP and ZOGP approach can be used as the optimization methods for activities selection problem.

An integrative review of in-class activities that enable active learning in college science classroom settings

NASA Astrophysics Data System (ADS)

Arthurs, Leilani A.; Kreager, Bailey Zo

2017-10-01

Engaging students in active learning is linked to positive learning outcomes. This study aims to synthesise the peer-reviewed literature about 'active learning' in college science classroom settings. Using the methodology of an integrative literature review, 337 articles archived in the Educational Resources Information Center (ERIC) are examined. Four categories of in-class activities emerge: (i) individual non-polling activities, (ii) in-class polling activities, (iii) whole-class discussion or activities, and (iv) in-class group activities. Examining the collection of identified in-class activities through the lens of a theoretical framework informed by constructivism and social interdependence theory, we synthesise the reviewed literature to propose the active learning strategies (ALSs) model and the instructional decisions to enable active learning (IDEAL) theory. The ALS model characterises in-class activities in terms of the degrees to which they are designed to promote (i) peer interaction and (ii) social interdependence. The IDEAL theory includes the ALS model and provides a framework for conceptualising different levels of the general concept 'active learning' and how these levels connect to instructional decision-making about using in-class activities. The proposed ALS model and IDEAL theory can be utilised to inform instructional decision-making and future research about active learning in college science courses.

Teaching massage to nursing students of geriatrics through active learning.

PubMed

Adler, Patricia A

2009-03-01

The use of massage in nursing practice has declined through the years in favor of high-tech interventions. This article describes a project using active learning to teach nursing students massage with dementia residents in assisted living. Students participated in a workshop to practice basic relaxation massage techniques with the guidance of their clinical instructor and then provided massages to resident volunteers. Afterward, students discussed their experience and completed a resident assessment form. The students requested more such activities, and the residents and facility management invited the students to return for another session. The instructor observed growth in the students' assessment skills and in their confidence. Use of massage to teach nursing students how to care for and relate to older adults with cognitive impairment is recommended. Further research is needed on the use of massage as an active learning method for nursing students in long-term care.

Effect of Learning Activity on Students' Motivation, Physical Activity Levels and Effort/Persistence

ERIC Educational Resources Information Center

Gao, Zan; Lee, Amelia M.; Xiang, Ping; Kosma, Maria

2011-01-01

The type of learning activity offered in physical education may influence students' motivational beliefs, physical activity participation and effort/persistence in class. However, most empirical studies have focused on the individual level rather than on the learner-content interactions. Accordingly, the potential effects of learning activities on…

Design and Implementation of an Object Oriented Learning Activity System

ERIC Educational Resources Information Center

Lin, Huan-Yu; Tseng, Shian-Shyong; Weng, Jui-Feng; Su, Jun-Ming

2009-01-01

With the development of e-learning technology, many specifications of instructional design have been proposed to make learning activity sharable and reusable. With the specifications and sufficient learning resources, the researches further focus on how to provide learners more appropriate learning activities to improve their learning performance.…

Preservice Physical Education Teachers' Service Learning Experiences Related to Comprehensive School Physical Activity Programming

ERIC Educational Resources Information Center

Webster, Collin A.; Nesbitt, Danielle; Lee, Heesu; Egan, Cate

2017-01-01

Purpose: The purpose of this study was to examine preservice physical education teachers' (PPET) service learning experiences planning and implementing course assignments aligned with comprehensive school physical activity program (CSPAP) recommendations. Methods: Based on service learning principles, PPETs (N = 18) enrolled in a physical…

Student Buy-In to Active Learning in a College Science Course

PubMed Central

Cavanagh, Andrew J.; Aragón, Oriana R.; Chen, Xinnian; Couch, Brian; Durham, Mary; Bobrownicki, Aiyana; Hanauer, David I.; Graham, Mark J.

2016-01-01

The benefits of introducing active learning in college science courses are well established, yet more needs to be understood about student buy-in to active learning and how that process of buy-in might relate to student outcomes. We test the exposure–persuasion–identification–commitment (EPIC) process model of buy-in, here applied to student (n = 245) engagement in an undergraduate science course featuring active learning. Student buy-in to active learning was positively associated with engagement in self-regulated learning and students’ course performance. The positive associations among buy-in, self-regulated learning, and course performance suggest buy-in as a potentially important factor leading to student engagement and other student outcomes. These findings are particularly salient in course contexts featuring active learning, which encourage active student participation in the learning process. PMID:27909026

Exploring Characteristics of Fine-Grained Behaviors of Learning Mathematics in Tablet-Based E-Learning Activities

ERIC Educational Resources Information Center

Yeung, Cheuk Yu; Shum, Kam Hong; Hui, Lucas Chi Kwong; Chu, Samuel Kai Wah; Chan, Tsing Yun; Kuo, Yung Nin; Ng, Yee Ling

2017-01-01

Attributes of teaching and learning contexts provide rich information about how students participate in learning activities. By tracking and analyzing snapshots of these attributes captured continuously throughout the duration of the learning activities, teachers can identify individual students who need special attention and apply different…

Teaching Qualitative Research Methods through Service-Learning

ERIC Educational Resources Information Center

Machtmes, Krisanna; Johnson, Earl; Fox, Janet; Burke, Mary S.; Harper, Jeannie; Arcemont, Lisa; Hebert, Lanette; Tarifa, Todd; Brooks, Roy C., Jr.; Reynaud, Andree L.; Deggs, David; Matzke, Brenda; Aguirre, Regina T. P.

2009-01-01

This paper is the result of a voluntary service-learning component in a qualitative research methods course. For this course, the service-learning project was the evaluation of the benefits to volunteers who work a crisis hotline for a local crisis intervention center. The service-learning course model used in this paper most closely resembles the…

Preferred Methods of Learning for Nursing Students in an On-Line Degree Program.

PubMed

Hampton, Debra; Pearce, Patricia F; Moser, Debra K

more effective for learning (P<.0167) than did Baby Boomer and Generation X students. In conclusion, the results of this study demonstrate that there are distinct student preferences and generational differences in preferred teaching/learning methods for on-line students. Faculty need to incorporate various teaching methodologies within on-line courses to include both synchronous and asynchronous activities and interactive and passive methodologies. Copyright © 2016 Elsevier Inc. All rights reserved.

A comparison of the cooperative learning and traditional learning methods in theory classes on nursing students' communication skill with patients at clinical settings.

PubMed

Baghcheghi, Nayereh; Koohestani, Hamid Reza; Rezaei, Koresh

2011-11-01

The purpose of this study was to compare the effect of traditional learning and cooperative learning methods on nursing students' communication skill with patients. This was an experimental study in which 34 nursing students in their 2nd semester of program participated. They were divided randomly into two groups, a control group who were taught their medical/surgical nursing course by traditional learning method and an experimental group, who were taught the same material using cooperative learning method. Before and after the teaching intervention, the students' communication skills with patients at clinical settings were examined. The results showed that no significant difference between the two groups in students' communication skills scores before the teaching intervention, but did show a significant difference between the two groups in the interaction skills and problem follow up sub-scales scores after the teaching intervention. This study provides evidence that cooperative learning is an effective method for improving and increasing communication skills of nursing students especially in interactive skills and follow up the problems sub-scale, thereby it is recommended to increase nursing students' participation in arguments by applying active teaching methods which can provide the opportunity for increased communication skills. Copyright © 2011 Elsevier Ltd. All rights reserved.

Telling Active Learning Pedagogies Apart: From Theory to Practice

ERIC Educational Resources Information Center

Cattaneo, Kelsey Hood

2017-01-01

Designing learning environments to incorporate active learning pedagogies is difficult as definitions are often contested and intertwined. This article seeks to determine whether classification of active learning pedagogies (i.e., project-based, problem-based, inquiry-based, case-based, and discovery-based), through theoretical and practical…

A Comparison between the Effect of Cooperative Learning Teaching Method and Lecture Teaching Method on Students' Learning and Satisfaction Level

ERIC Educational Resources Information Center

Mohammadjani, Farzad; Tonkaboni, Forouzan

2015-01-01

The aim of the present research is to investigate a comparison between the effect of cooperative learning teaching method and lecture teaching method on students' learning and satisfaction level. The research population consisted of all the fourth grade elementary school students of educational district 4 in Shiraz. The statistical population…

Active-learning implementation in an advanced elective course on infectious diseases.

PubMed

Hidayat, Levita; Patel, Shreya; Veltri, Keith

2012-06-18

To describe the development, implementation, and assessment of an advanced elective course on infectious diseases using active-learning strategies. Pedagogy for active learning was incorporated by means of mini-lecture, journal club, and debate with follow-up discussion. Forty-eight students were enrolled in this 4-week elective course, in which 30% of course time was allocated for active-learning exercises. All activities were fundamentally designed as a stepwise approach in complementing each active-learning exercise. Achievement of the course learning objectives was assessed using a 5-point Likert scale survey instrument. Students' awareness of the significance of antimicrobial resistance was improved (p ≤ 0.05). Students' ability to critically evaluate the infectious-disease literature and its application in informed clinical judgments was also enhanced through these active-learning exercises (p ≤ 0.05). Students agreed that active learning should be part of the pharmacy curriculum and that active-learning exercises improved their critical-thinking, literature-evaluation, and self-learning skills. An elective course using active-learning strategies allowed students to combine information gained from the evaluation of infectious-disease literature, critical thinking, and informed clinical judgment. This blended approach ultimately resulted in an increased knowledge and awareness of infectious diseases.

Active-Learning Implementation in an Advanced Elective Course on Infectious Diseases

PubMed Central

Patel, Shreya; Veltri, Keith

2012-01-01

Objectives. To describe the development, implementation, and assessment of an advanced elective course on infectious diseases using active-learning strategies. Design. Pedagogy for active learning was incorporated by means of mini-lecture, journal club, and debate with follow-up discussion. Forty-eight students were enrolled in this 4-week elective course, in which 30% of course time was allocated for active-learning exercises. All activities were fundamentally designed as a stepwise approach in complementing each active-learning exercise. Assessment. Achievement of the course learning objectives was assessed using a 5-point Likert scale survey instrument. Students’ awareness of the significance of antimicrobial resistance was improved (p ≤ 0.05). Students’ ability to critically evaluate the infectious-disease literature and its application in informed clinical judgments was also enhanced through these active-learning exercises (p ≤ 0.05). Students agreed that active learning should be part of the pharmacy curriculum and that active-learning exercises improved their critical-thinking, literature-evaluation, and self-learning skills. Conclusion. An elective course using active-learning strategies allowed students to combine information gained from the evaluation of infectious-disease literature, critical thinking, and informed clinical judgment. This blended approach ultimately resulted in an increased knowledge and awareness of infectious diseases. PMID:22761528

Student Activity and Learning Outcomes in a Virtual Learning Environment

ERIC Educational Resources Information Center

Romanov, Kalle; Nevgi, Anne

2008-01-01

The aim of the study was to explore the relationship between degree of participation and learning outcomes in an e-learning course on medical informatics. Overall activity in using course materials and degree of participation in the discussion forums of an online course were studied among 39 medical students. Students were able to utilise the…

Active inference and learning.

PubMed

Friston, Karl; FitzGerald, Thomas; Rigoli, Francesco; Schwartenbeck, Philipp; O Doherty, John; Pezzulo, Giovanni

2016-09-01

This paper offers an active inference account of choice behaviour and learning. It focuses on the distinction between goal-directed and habitual behaviour and how they contextualise each other. We show that habits emerge naturally (and autodidactically) from sequential policy optimisation when agents are equipped with state-action policies. In active inference, behaviour has explorative (epistemic) and exploitative (pragmatic) aspects that are sensitive to ambiguity and risk respectively, where epistemic (ambiguity-resolving) behaviour enables pragmatic (reward-seeking) behaviour and the subsequent emergence of habits. Although goal-directed and habitual policies are usually associated with model-based and model-free schemes, we find the more important distinction is between belief-free and belief-based schemes. The underlying (variational) belief updating provides a comprehensive (if metaphorical) process theory for several phenomena, including the transfer of dopamine responses, reversal learning, habit formation and devaluation. Finally, we show that active inference reduces to a classical (Bellman) scheme, in the absence of ambiguity. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Unpacking "Active Learning": A Combination of Flipped Classroom and Collaboration Support Is More Effective but Collaboration Support Alone Is Not

ERIC Educational Resources Information Center

Rau, Martina A.; Kennedy, Kristopher; Oxtoby, Lucas; Bollom, Mark; Moore, John W.

2017-01-01

Much evidence shows that instruction that actively engages students with learning materials is more effective than traditional, lecture-centric instruction. These "active learning" models comprise an extremely heterogeneous set of instructional methods: they often include collaborative activities, flipped classrooms, or a combination of…

Color image definition evaluation method based on deep learning method

NASA Astrophysics Data System (ADS)

Liu, Di; Li, YingChun

2018-01-01

In order to evaluate different blurring levels of color image and improve the method of image definition evaluation, this paper proposed a method based on the depth learning framework and BP neural network classification model, and presents a non-reference color image clarity evaluation method. Firstly, using VGG16 net as the feature extractor to extract 4,096 dimensions features of the images, then the extracted features and labeled images are employed in BP neural network to train. And finally achieve the color image definition evaluation. The method in this paper are experimented by using images from the CSIQ database. The images are blurred at different levels. There are 4,000 images after the processing. Dividing the 4,000 images into three categories, each category represents a blur level. 300 out of 400 high-dimensional features are trained in VGG16 net and BP neural network, and the rest of 100 samples are tested. The experimental results show that the method can take full advantage of the learning and characterization capability of deep learning. Referring to the current shortcomings of the major existing image clarity evaluation methods, which manually design and extract features. The method in this paper can extract the images features automatically, and has got excellent image quality classification accuracy for the test data set. The accuracy rate is 96%. Moreover, the predicted quality levels of original color images are similar to the perception of the human visual system.

Understanding Mathematic Concept in Relation and Function Method through Active Learning Type Group to Group Distributed LKS

NASA Astrophysics Data System (ADS)

Kudri, F.; Rahmi, R.; Haryono, Y.

2018-04-01

This research is motivated by the lack of understanding of mathematical concepts students and teachers have not familiarize students discussed in groups. This researchaims to determine whether an understanding of mathematical concepts junior class VIII SMPN 2 in Ranah Batahan Kabupaten Pasaman Barat by applying active learning strategy group to group types with LKS better than conventional learning. The type of research is experimental the design of randomized trials on the subject. The population in the study were all students VIII SMPN 2 Ranah Batahan Kabupaten Pasaman Barat in year 2012/2013 which consists of our class room experiment to determine the grade and control class with do nerandomly, so that classes VIII1 elected as a experiment class and class VIII4 as a control class. The instruments used in the test empirically understanding mathematical concepts are shaped by the essay with rt=0,82 greater than rt=0,468 means reliable tests used. The data analysis technique used is the test with the help of MINITAB. Based on the results of the data analisis known that both of the sample are normal and homogenity in real rate α = 0,05, so the hypothesis of this research is received. So, it can be concluded students’ understanding mathematical concept applied the active Group to Group learning strategy with LKS is better than the students’ understanding mathematical concept with Conventional Learning.

Inquiry-based Laboratory Activities on Drugs Analysis for High School Chemistry Learning

NASA Astrophysics Data System (ADS)

Rahmawati, I.; Sholichin, H.; Arifin, M.

2017-09-01

Laboratory activity is an important part of chemistry learning, but cookbook instructions is still commonly used. However, the activity with that way do not improve students thinking skill, especially students creativity. This study aims to improve high school students creativity through inquiry-based laboratory on drugs analysis activity. Acid-base titration is used to be method for drugs analysis involving a color changing indicator. The following tools were used to assess the activity achievement: creative thinking test on acid base titration, creative attitude and action observation sheets, questionnaire of inquiry-based lab activities, and interviews. The results showed that the inquiry-based laboratory activity improving students creative thinking, creative attitude and creative action. The students reacted positively to this teaching strategy as demonstrated by results from questionnaire responses and interviews. This result is expected to help teachers to overcome the shortcomings in other laboratory learning.

Improving Student Engagement in Learning Activities.

ERIC Educational Resources Information Center

Adams, Nancy; And Others

Engaging students seriously in their own academic learning is a persistent difficulty for teachers. The goal of this action research project was to actively involve elementary school students in their learning. The program was implemented at three elementary schools in northern Illinois serving multicultural populations; special education…

Multi-Stage Convex Relaxation Methods for Machine Learning

DTIC Science & Technology

2013-03-01

Many problems in machine learning can be naturally formulated as non-convex optimization problems. However, such direct nonconvex formulations have...original nonconvex formulation. We will develop theoretical properties of this method and algorithmic consequences. Related convex and nonconvex machine learning methods will also be investigated.

DASL-Data and Activities for Solar Learning

NASA Technical Reports Server (NTRS)

Jones, Harrison P.; Henney, Carl; Hill, Frank; Gearen, Michael; Pompca, Stephen; Stagg, Travis; Stefaniak, Linda; Walker, Connie

2004-01-01

DASL-Data and Activities for Solar Learning Data and Activities for Solar Learning (DASL) provides a classroom learning environment based on a twenty-five year record of solar magnetograms from the National Solar Observatory (NSO) at Kitt Peak, AZ. The data, together with image processing software for Macs or PCs, can be used to learn basic facts about the Sun and astronomy at the middle school level. At the high school level, students can study properties of the Sun's magnetic cycle with classroom exercises emphasizing data and error analysis and can participate in a new scientific study, Research in Active Solar Longitudes (RASL), in collaboration with classrooms throughout the country and scientists at NSO and NASA. We present a half-day course to train teachers in the scientific content of the project and its classroom use. We will provide a compact disc with the data and software and will demonstrate software installation and use, classroom exercises, and participation in RASL with computer projection.

A Development of Game-Based Learning Environment to Activate Interaction among Learners

NASA Astrophysics Data System (ADS)

Takaoka, Ryo; Shimokawa, Masayuki; Okamoto, Toshio

Many studies and systems that incorporate elements such as “pleasure” and “fun” in the game to improve a learner's motivation have been developed in the field of learning environments. However, few are the studies of situations where many learners gather at a single computer and participate in a game-based learning environment (GBLE), and where the GBLE designs the learning process by controlling the interactions between learners such as competition, collaboration, and learning by teaching. Therefore, the purpose of this study is to propose a framework of educational control that induces and activates interaction between learners intentionally to create a learning opportunity that is based on the knowledge understanding model of each learner. In this paper, we explain the design philosophy and the framework of our GBLE called “Who becomes the king in the country of mathematics?” from a game viewpoint and describe the method of learning support control in the learning environment. In addition, we report the results of the learning experiment with our GBLE, which we carried out in a junior high school, and include some comments by a principal and a teacher. From the results of the experiment and some comments, we noticed that a game may play a significant role in weakening the learning relationship among students and creating new relationships in the world of the game. Furthermore, we discovered that learning support control of the GBLE has led to activation of the interaction between learners to some extent.

It takes biking to learn: Physical activity improves learning a second language.

PubMed

Liu, Fengqin; Sulpizio, Simone; Kornpetpanee, Suchada; Job, Remo

2017-01-01

Recent studies have shown that concurrent physical activity enhances learning a completely unfamiliar L2 vocabulary as compared to learning it in a static condition. In this paper we report a study whose aim is twofold: to test for possible positive effects of physical activity when L2 learning has already reached some level of proficiency, and to test whether the assumed better performance when engaged in physical activity is limited to the linguistic level probed at training (i.e. L2 vocabulary tested by means of a Word-Picture Verification task), or whether it extends also to the sentence level (which was tested by means of a Sentence Semantic Judgment Task). The results show that Chinese speakers with basic knowledge of English benefited from physical activity while learning a set of new words. Furthermore, their better performance emerged also at the sentential level, as shown by their performance in a Semantic Judgment task. Finally, an interesting temporal asymmetry between the lexical and the sentential level emerges, with the difference between the experimental and control group emerging from the 1st testing session at the lexical level but after several weeks at the sentential level.

It takes biking to learn: Physical activity improves learning a second language.

PubMed Central

Liu, Fengqin; Sulpizio, Simone; Kornpetpanee, Suchada; Job, Remo

2017-01-01

Recent studies have shown that concurrent physical activity enhances learning a completely unfamiliar L2 vocabulary as compared to learning it in a static condition. In this paper we report a study whose aim is twofold: to test for possible positive effects of physical activity when L2 learning has already reached some level of proficiency, and to test whether the assumed better performance when engaged in physical activity is limited to the linguistic level probed at training (i.e. L2 vocabulary tested by means of a Word-Picture Verification task), or whether it extends also to the sentence level (which was tested by means of a Sentence Semantic Judgment Task). The results show that Chinese speakers with basic knowledge of English benefited from physical activity while learning a set of new words. Furthermore, their better performance emerged also at the sentential level, as shown by their performance in a Semantic Judgment task. Finally, an interesting temporal asymmetry between the lexical and the sentential level emerges, with the difference between the experimental and control group emerging from the 1st testing session at the lexical level but after several weeks at the sentential level. PMID:28542333

Medical Student Perspectives of Active Learning: A Focus Group Study.

PubMed

Walling, Anne; Istas, Kathryn; Bonaminio, Giulia A; Paolo, Anthony M; Fontes, Joseph D; Davis, Nancy; Berardo, Benito A

2017-01-01

Phenomenon: Medical student perspectives were sought about active learning, including concerns, challenges, perceived advantages and disadvantages, and appropriate role in the educational process. Focus groups were conducted with students from all years and campuses of a large U.S. state medical school. Students had considerable experience with active learning prior to medical school and conveyed accurate understanding of the concept and its major strategies. They appreciated the potential of active learning to deepen and broaden learning and its value for long-term professional development but had significant concerns about the efficiency of the process, the clarity of expectations provided, and the importance of receiving preparatory materials. Most significantly, active learning experiences were perceived as disconnected from grading and even as impeding preparation for school and national examinations. Insights: Medical students understand the concepts of active learning and have considerable experience in several formats prior to medical school. They are generally supportive of active learning concepts but frustrated by perceived inefficiencies and lack of contribution to the urgencies of achieving optimal grades and passing United States Medical Licensing Examinations, especially Step 1.

Student Perceptions of Information Literacy Instruction: The Importance of Active Learning

ERIC Educational Resources Information Center

Detlor, Brian; Booker, Lorne; Serenko, Alexander; Julien, Heidi

2012-01-01

This study investigates the merits of employing active learning strategies in the delivery of information literacy instruction (ILI). Traditional approaches to the teaching of information literacy skills--where students are passive recipients of the information they receive--are challenged. Rather, methods that encourage students to actively…

Teacher feedback during active learning: current practices in primary schools.

PubMed

van den Bergh, Linda; Ros, Anje; Beijaard, Douwe

2013-06-01

Feedback is one of the most powerful tools, which teachers can use to enhance student learning. It appears difficult for teachers to give qualitatively good feedback, especially during active learning. In this context, teachers should provide facilitative feedback that is focused on the development of meta-cognition and social learning. The purpose of the present study is to contribute to the existing knowledge about feedback and to give directions to improve teacher feedback in the context of active learning. The participants comprised 32 teachers who practiced active learning in the domain of environmental studies in the sixth, seventh, or eighth grade of 13 Dutch primary schools. A total of 1,465 teacher-student interactions were examined. Video observations were made of active learning lessons in the domain of environmental studies. A category system was developed based on the literature and empirical data. Teacher-student interactions were assessed using this system. Results. About half of the teacher-student interactions contained feedback. This feedback was usually focused on the tasks that were being performed by the students and on the ways in which these tasks were processed. Only 5% of the feedback was explicitly related to a learning goal. In their feedback, the teachers were directing (rather than facilitating) the learning processes. During active learning, feedback on meta-cognition and social learning is important. Feedback should be explicitly related to learning goals. In practice, these kinds of feedback appear to be scarce. Therefore, giving feedback during active learning seems to be an important topic for teachers' professional development. © 2012 The British Psychological Society.

Correlation of the summary method with learning styles.

PubMed

Sarikcioglu, Levent; Senol, Yesim; Yildirim, Fatos B; Hizay, Arzu

2011-09-01

The summary is the last part of the lesson but one of the most important. We aimed to study the relationship between the preference of the summary method (video demonstration, question-answer, or brief review of slides) and learning styles. A total of 131 students were included in the present study. An inventory was prepared to understand the students' learning styles, and a satisfaction questionnaire was provided to determine the summary method selection. The questionnaire and inventory were collected and analyzed. A comparison of the data revealed that the summary method with video demonstration received the highest score among all the methods tested. Additionally, there were no significant differences between learning styles and summary method with video demonstration. We suggest that such a summary method should be incorporated into neuroanatomy lessons. Since anatomy has a large amount of visual material, we think that it is ideally suited for this summary method.

Child Development: An Active Learning Approach

ERIC Educational Resources Information Center

Levine, Laura E.; Munsch, Joyce

2010-01-01

Within each chapter of this innovative topical text, the authors engage students by demonstrating the wide range of real-world applications of psychological research connected to child development. In particular, the distinctive Active Learning features incorporated throughout the book foster a dynamic and personal learning process for students.…

Activating Metacognition through Online Learning Log (OLL)

ERIC Educational Resources Information Center

Kurt, Mustafa

2007-01-01

This study aims to investigate the activation process of metacognition of learners who systematically reflect on their learning using Online Learning Logs (OLL) which were designed to encourage them to think about learning. The study is qualitative and attempts to identify the metacognitive strategies of learners and their attitudes towards OLL.…

Generation of Tutorial Dialogues: Discourse Strategies for Active Learning

DTIC Science & Technology

1998-05-29

AND SUBTITLE Generation of Tutorial Dialogues: Discourse Strategies for active Learning AUTHORS Dr. Martha Evens 7. PERFORMING ORGANI2ATION NAME...time the student starts in on a new topic. Michael and Rovick constantly attempt to promote active learning . They regularly use hints and only resort...Controlling active learning : How tutors decide when to generate hints. Proceedings of FLAIRS 󈨣. Melbourne Beach, FL. 157-161. Hume, G., Michael

Costs of Success: Financial Implications of Implementation of Active Learning in Introductory Physics Courses for Students and Administrators

ERIC Educational Resources Information Center

Brewe, Eric; Dou, Remy; Shand, Robert

2018-01-01

Although active learning is supported by strong evidence of efficacy in undergraduate science instruction, institutions of higher education have yet to embrace comprehensive change. Costs of transforming instruction are regularly cited as a key factor in not adopting active-learning instructional practices. Some cite that alternative methods to…

A Comparison of Professional-Level Faculty and Student Perceptions of Active Learning: Its Current Use, Effectiveness, and Barriers

ERIC Educational Resources Information Center

Miller, Cynthia J.; Metz, Michael J.

2014-01-01

Active learning is an instructional method in which students become engaged participants in the classroom through the use of in-class written exercises, games, problem sets, audience-response systems, debates, class discussions, etc. Despite evidence supporting the effectiveness of active learning strategies, minimal adoption of the technique has…

An Active Learning Activity to Reinforce the Design Components of the Corticosteroids

PubMed Central

Mandela, Prashant

2018-01-01

Despite the popularity of active learning applications over the past few decades, few activities have been reported for the field of medicinal chemistry. The purpose of this study is to report a new active learning activity, describe participant contributions, and examine participant performance on the assessment questions mapped to the objective covered by the activity. In this particular activity, students are asked to design two novel corticosteroids as a group (6–8 students per group) based on the design characteristics of marketed corticosteroids covered in lecture coupled with their pharmaceutics knowledge from the previous semester and then defend their design to the class through an interactive presentation model. Although class performance on the objective mapped to this material on the assessment did not reach statistical significance, use of this activity has allowed fruitful discussion of misunderstood concepts and facilitated multiple changes to the lecture presentation. As pharmacy schools continue to emphasize alternative learning pedagogies, publication of previously implemented activities demonstrating their use will help others apply similar methodologies. PMID:29401733

An Active Learning Activity to Reinforce the Design Components of the Corticosteroids.

PubMed

Slauson, Stephen R; Mandela, Prashant

2018-02-05

Despite the popularity of active learning applications over the past few decades, few activities have been reported for the field of medicinal chemistry. The purpose of this study is to report a new active learning activity, describe participant contributions, and examine participant performance on the assessment questions mapped to the objective covered by the activity. In this particular activity, students are asked to design two novel corticosteroids as a group (6-8 students per group) based on the design characteristics of marketed corticosteroids covered in lecture coupled with their pharmaceutics knowledge from the previous semester and then defend their design to the class through an interactive presentation model. Although class performance on the objective mapped to this material on the assessment did not reach statistical significance, use of this activity has allowed fruitful discussion of misunderstood concepts and facilitated multiple changes to the lecture presentation. As pharmacy schools continue to emphasize alternative learning pedagogies, publication of previously implemented activities demonstrating their use will help others apply similar methodologies.

H2Oh!: Classroom demonstrations and activities for improving student learning of water concepts

NASA Astrophysics Data System (ADS)

Chan-Hilton, A.; Neupauer, R. M.; Burian, S. J.; Lauer, J. W.; Mathisen, P. P.; Mays, D. C.; Olson, M. S.; Pomeroy, C. A.; Ruddell, B. L.; Sciortino, A.

2012-12-01

Research has shown that the use of demonstrations and hands-on activities in the classroom enhances student learning. Students learn more and enjoy classes more when visual and active learning are incorporated into the lecture. Most college-aged students prefer visual modes of learning, while most instruction is conducted in a lecture, or auditory, format. The use of classroom demonstrations provides opportunities for incorporating visual and active learning into the classroom environment. However, while most instructors acknowledge the benefits of these teaching methods, they typically do not have the time and resources to develop and test such activities and to develop plans to incorporate them into their lectures. Members of the Excellence in Water Resources Education Task Committee of the Environmental and Water Resources Institute (EWRI) of the American Society of Civil Engineers (ASCE) have produced a publication that contains a collection of activities aimed to foster excellence in water resources and hydrology education and improve student learning of principles. The book contains forty-five demonstrations and activities that can be used in water-related classes with topics in fluid mechanics, hydraulics, surface water hydrology, groundwater hydrology, and water quality. We present examples of these activities, including topics such as conservation of momentum, buoyancy, Bernoulli's principle, drag force, pipe flow, watershed delineation, reservoir networks, head distribution in aquifers, and molecular diffusion in a porous medium. Unlike full laboratory exercises, these brief demonstrations and activities (most of which take less than fifteen minutes) can be easily incorporated into classroom lectures. For each demonstration, guidance for preparing and conducting the activity, along with a brief overview of the principles that are demonstrated, is provided. The target audience of the activities is undergraduate students, although the activities also may be

Low fidelity model making activity by students: A novel way of learning concepts of neuroanatomy.

PubMed

Dixit, Shilpi Gupta; Potaliya, Pushpa; Nayeemudin, S M; Ghatak, Surajit

2018-06-01

Teaching and learning anatomy has always been an integral part of medical education. Teaching neuroanatomy has always faced innate and contextual challenges therefore various innovative teaching-learning methods have been devised on the idea of engaging learners in meaningful learning activities through apt guidance, communication among peers and cluster activities. The present study aims at such an innovative method. The study was conducted in practical sessions of first year MBBS at the Institute during second semester. Neuroanatomy topic selected for present study was 'Neural Pathways/tracts'. Participants were divided into 8 groups and each was allotted a specific activity related to a particular cross-sectional level and allowed to build with the material provided by the department. Student feedback was taken through a structured questionnaire. 81 and 82.4% of students stated that the activity was clearly explained and should be offered more frequently in curriculum. The activity also developed a positive attitude and good coordination amongst peers with increase in communication skills (89.1%, 91.8%, 89% respectively). 87.8% of students agreed that small group learning is better than didactic lectures in neuroanatomy. In current medical scenario with reduced anatomy teaching hours and a continuous pressure on undergraduates, a low-cost learning intervention formulated to deliver a complex 3-D model of tracts passing through various parts of nervous system by simple materials would show better access and understanding of the tracts with improvement of 3D visualization skills. Copyright © 2018 Elsevier Ltd. All rights reserved.

Improving Nursing Students' Learning Outcomes in Fundamentals of Nursing Course through Combination of Traditional and e-Learning Methods

PubMed Central

Sheikhaboumasoudi, Rouhollah; Bagheri, Maryam; Hosseini, Sayed Abbas; Ashouri, Elaheh; Elahi, Nasrin

2018-01-01

Background: Fundamentals of nursing course are prerequisite to providing comprehensive nursing care. Despite development of technology on nursing education, effectiveness of using e-learning methods in fundamentals of nursing course is unclear in clinical skills laboratory for nursing students. The aim of this study was to compare the effect of blended learning (combining e-learning with traditional learning methods) with traditional learning alone on nursing students' scores. Materials and Methods: A two-group post-test experimental study was administered from February 2014 to February 2015. Two groups of nursing students who were taking the fundamentals of nursing course in Iran were compared. Sixty nursing students were selected as control group (just traditional learning methods) and experimental group (combining e-learning with traditional learning methods) for two consecutive semesters. Both groups participated in Objective Structured Clinical Examination (OSCE) and were evaluated in the same way using a prepared checklist and questionnaire of satisfaction. Statistical analysis was conducted through SPSS software version 16. Results: Findings of this study reflected that mean of midterm (t = 2.00, p = 0.04) and final score (t = 2.50, p = 0.01) of the intervention group (combining e-learning with traditional learning methods) were significantly higher than the control group (traditional learning methods). The satisfaction of male students in intervention group was higher than in females (t = 2.60, p = 0.01). Conclusions: Based on the findings, this study suggests that the use of combining traditional learning methods with e-learning methods such as applying educational website and interactive online resources for fundamentals of nursing course instruction can be an effective supplement for improving nursing students' clinical skills. PMID:29861761

Active Learning in PhysicsTechnology and Research-based Techniques Emphasizing Interactive Lecture Demonstrations

NASA Astrophysics Data System (ADS)

Thornton, Ronald

2010-10-01

Physics education research has shown that learning environments that engage students and allow them to take an active part in their learning can lead to large conceptual gains compared to traditional instruction. Examples of successful curricula and methods include Peer Instruction, Just in Time Teaching, RealTime Physics, Workshop Physics, Scale-Up, and Interactive Lecture Demonstrations (ILDs). An active learning environment is often difficult to achieve in lecture sessions. This presentation will demonstrate the use of sequences of Interactive Lecture Demonstrations (ILDs) that use real experiments often involving real-time data collection and display combined with student interaction to create an active learning environment in large or small lecture classes. Interactive lecture demonstrations will be done in the area of mechanics using real-time motion probes and the Visualizer. A video tape of students involved in interactive lecture demonstrations will be shown. The results of a number of research studies at various institutions (including international) to measure the effectiveness of ILDs and guided inquiry conceptual laboratories will be presented.

Changing University Students' Alternative Conceptions of Optics by Active Learning

ERIC Educational Resources Information Center

Hadžibegovic, Zalkida; Sliško, Josip

2013-01-01

Active learning is individual and group participation in effective activities such as in-class observing, writing, experimenting, discussion, solving problems, and talking about to-be-learned topics. Some instructors believe that active learning is impossible, or at least extremely difficult to achieve in large lecture sessions. Nevertheless, the…

An active-learning laboratory on immunizations.

PubMed

Donohoe, Krista L; Mawyer, Tonya M; Stevens, J Tyler; Morgan, Laura A; Harpe, Spencer E

2012-12-12

To implement and evaluate an active-learning laboratory activity to teach pharmacy students about influenza, pneumococcal, and shingles vaccines. The laboratory session was divided into 6 immunization stations: 3 stations on influenza including a pediatrics station, and 1 station each for pneumococcal, shingles, and anaphylaxis. Although 118 of 123 (95.9%) students had completed an immunization training certificate prior to attending the laboratory, the average score on a pre-assessment to measure immunization knowledge and confidence was 56%. The post-assessment score was 87.4%. Students' confidence improved by 18.7% to 51.2% in each of the 5 areas assessed. Most respondents rated the activity overall as good or excellent on a post-activity evaluation. An active-learning approach to teaching immunizations allowed students to gain knowledge in simulated real-world experiences and reinforced key concepts on influenza, pneumococcal, and shingles vaccines.

e-Learning Business Research Methods

ERIC Educational Resources Information Center

Cowie, Jonathan

2004-01-01

This paper outlines the development of a generic Business Research Methods course from a simple name in a box to a full e-Learning web based module. It highlights particular issues surrounding the nature of the discipline and the integration of a large number of cross faculty subject specific research methods courses into a single generic module.…

Active Learning Strategies in Face-to-Face Courses. IDEA Paper #53

ERIC Educational Resources Information Center

Millis, Barbara J.

2012-01-01

As numerous research studies suggest, teachers who desire increased student learning should adopt active learning. This article explores the research, defines active learning, discusses its value, offers suggestions for implementing it, and provides six concrete examples of active learning approaches: Thinking-Aloud Pair Problem-Solving;…

Predicting reading and mathematics from neural activity for feedback learning.

PubMed

Peters, Sabine; Van der Meulen, Mara; Zanolie, Kiki; Crone, Eveline A

2017-01-01

Although many studies use feedback learning paradigms to study the process of learning in laboratory settings, little is known about their relevance for real-world learning settings such as school. In a large developmental sample (N = 228, 8-25 years), we investigated whether performance and neural activity during a feedback learning task predicted reading and mathematics performance 2 years later. The results indicated that feedback learning performance predicted both reading and mathematics performance. Activity during feedback learning in left superior dorsolateral prefrontal cortex (DLPFC) predicted reading performance, whereas activity in presupplementary motor area/anterior cingulate cortex (pre-SMA/ACC) predicted mathematical performance. Moreover, left superior DLPFC and pre-SMA/ACC activity predicted unique variance in reading and mathematics ability over behavioral testing of feedback learning performance alone. These results provide valuable insights into the relationship between laboratory-based learning tasks and learning in school settings, and the value of neural assessments for prediction of school performance over behavioral testing alone. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Teaching Engineering with Autonomous Learning Activities

ERIC Educational Resources Information Center

Otero, Beatriz; Rodríguez, Eva; Royo, Pablo

2015-01-01

This paper proposes several activities that encourage self-learning in engineering courses. For each activity, the context and the pedagogical issues addressed are described emphasizing strengths and weaknesses. Specifically, this work describes and implements five activities, which are: questionnaires, conceptual maps, videos, jigsaw and…

Opportunities to Create Active Learning Techniques in the Classroom

ERIC Educational Resources Information Center

Camacho, Danielle J.; Legare, Jill M.

2015-01-01

The purpose of this article is to contribute to the growing body of research that focuses on active learning techniques. Active learning techniques require students to consider a given set of information, analyze, process, and prepare to restate what has been learned--all strategies are confirmed to improve higher order thinking skills. Active…

Mobile-Assisted Seamless Learning Activities in Higher Distance Education

ERIC Educational Resources Information Center

Amhag, Lisbeth

2017-01-01

Among online learning factors stated in the research literature, it is argued that online activities is the strongest factor which contributes to online learning. This article illuminates mobile-assisted seamless learning activities by using laptops, tablets, or smart phones. Two conditions are compared, a) face-to-face (F2F) online webinars…

Active Learning in Secondary Schools: Educational Media and Technology.

ERIC Educational Resources Information Center

Page, Marilyn

The incorporation of media and technology into the classroom does not ensure the enhancement of student learning. Research has shown that students learn more through active participation in their own learning process. From 1984 to 1987, a teacher's secondary social studies students were actively involved in the National History Day Program (NHDP),…

Musical Peddy-Paper: A Collaborative Learning Activity Suported by Augmented Reality

ERIC Educational Resources Information Center

Gomes, José Duarte Cardoso; Figueiredo, Mauro Jorge Guerreiro; Amante, Lúcia da Graça Cruz Domingues; Gomes, Cristina Maria Cardoso

2014-01-01

Gaming activities are an integral part of the human learning process, in particular for children. Game-based learning focuses on motivation and children's engagement towards learning. Educational game-based activities are becoming effective strategies to enhance the learning process. This paper presents an educational activity focusing to merge…

Supervised machine learning and active learning in classification of radiology reports.