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
Shaker, Noor; Abou-Zleikha, Mohamed; Shaker, Mohammad
Learning models of player behavior has been the focus of several studies. This work is motivated by better understanding of player behavior, a knowledge that can ultimately be employed to provide player-adapted or personalized content. In this paper, we propose the use of active learning for player...... experience modeling. We use a dataset from hundreds of players playing Infinite Mario Bros. as a case study and we employ the random forest method to learn mod- els of player experience through the active learning approach. The results obtained suggest that only part of the dataset (up to half the size...... that the method can be used online during the content generation process where the mod- els can improve and better content can be presented as the game is being played....
Kjeldsen, Tinne Hoff; Blomhøj, Morten
Ten years of experience with analyses of students’ learning in a modelling course for first year university students, led us to see modelling as a didactical activity with the dual goal of developing students’ modelling competency and enhancing their conceptual learning of mathematical concepts i...... create and help overcome hidden cognitive conflicts in students’ understanding; that reflections within modelling can play an important role for the students’ learning of mathematics. These findings are illustrated with a modelling project concerning the world population....
Manfredotti, Cristina; Pedersen, Kim Steenstrup; Hamilton, Howard J.
We propose the LEMAIO multi-layer framework, which makes use of hierarchical abstraction to learn models for activities involving multiple interacting objects from time sequences of data concerning the individual objects. Experiments in the sea navigation domain yielded learned models that were t...
Bull, Susan; Kickmeier-Rust, Michael; Vatrapu, Ravi
This paper draws on visualisation approaches in learning analytics, considering how classroom visualisations can come together in practice. We suggest an open learner model in situations where many tools and activity visualisations produce more visual information than can be readily interpreted....
IMS Learning Design provides a counter to the trend towards designing for lone-learners reading from screens. It guides staff and educational developers to start not with content, but with learning activities and the achievement of learning objectives. It recognises that learning can happen without
Luo, Zhipeng; Hauskrecht, Milos
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.
Xue, Yanbing; Hauskrecht, Milos
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.
Pinder, Jonathan P.
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…
Cevik, Mucahit; Ergun, Mehmet Ali; Stout, Natasha K; Trentham-Dietz, Amy; Craven, Mark; Alagoz, Oguzhan
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.
Lingashetty, Krishna Chaithanya
This paper reports the results on methods of comparing the memory retrieval capacity of the Hebbian neural network which implements the B-Matrix approach, by using the Widrow-Hoff rule of learning. We then, extend the recently proposed Active Sites model by developing a delta rule to increase memory capacity. Also, this paper extends the binary neural network to a multi-level (non-binary) neural network.
Phillips, Richard L.; Chang, Kyu Hyun; Friedler, Sorelle A.
Active learning has long been a topic of study in machine learning. However, as increasingly complex and opaque models have become standard practice, the process of active learning, too, has become more opaque. There has been little investigation into interpreting what specific trends and patterns an active learning strategy may be exploring. This work expands on the Local Interpretable Model-agnostic Explanations framework (LIME) to provide explanations for active learning recommendations. W...
Pulkkinen, A. A.; Welling, D. T.
Due to concerns pertaining to geomagnetically induced current impact on ground-based infrastructure, there has been significantly elevated interest in applying models for local geomagnetic disturbance or "delta-B" predictions. Correspondingly there has been elevated need for testing the quality of the delta-B predictions generated by the modern empirical and physics-based models. To address this need, community-wide activities were launched under the GEM Challenge framework and one culmination of the activities was the validation and selection of models that were transitioned into operations at NOAA SWPC. The community-wide delta-B action is continued under the CCMC-facilitated International Forum for Space Weather Capabilities Assessment and its "Ground Magnetic Perturbations: dBdt, delta-B, GICs, FACs" working group. The new delta-B working group builds on the past experiences and expands the collaborations to cover the entire international space weather community. In this paper, we discuss the key lessons learned from the past delta-B validation exercises and lay out the path forward for building on those experience under the new delta-B working group.
Currenti, Gilda M.; Napoli, Rosalba
Motivated by ongoing efforts to understand the nature and the energy potential of geothermal resources, we devise a coupled numerical model (hydrological, thermal, mechanical), which may help in the characterization and monitoring of hydrothermal systems through computational experiments. Hydrothermal areas in volcanic regions arise from a unique combination of geological and hydrological features which regulate the movement of fluids in the vicinity of magmatic sources capable of generating large quantities of steam and hot water. Numerical simulations help in understanding and characterizing rock-fluid interaction processes and the geophysical observations associated with them. Our aim is the quantification of the response of different geophysical observables (i.e. deformation, gravity and magnetic field) to hydrothermal activity on the basis of a sound geological framework (e.g. distribution and pathways of the flows, the presence of fractured zones, caprock). A detailed comprehension and quantification of the evolution and dynamics of the geothermal systems and the definition of their internal state through a geophysical modeling approach are essential to identify the key parameters for which the geothermal system may fulfill the requirements to be exploited as a source of energy. For the sake of illustration only, the numerical computations are focused on a conceptual model of the hydrothermal system of Vulcano Island by simulating a generic 1-year unrest and estimating different geophysical changes. We solved (i) the mass and energy balance equations of flow in porous media for temperature, pressure and density changes, (ii) the elastostatic equation for the deformation field and (iii) the Poisson’s equations for gravity and magnetic potential fields. Under the model assumptions, a generic unrest of 1-year engenders on the ground surface low amplitude changes in the investigated geophysical observables, that are, however, above the accuracies of the modern
Vera V. Lyubchenko
Full Text Available The adoption of Law of Ukraine “On Higher Education” (2014 involves the increase in students’ self-learning activity part in the curriculum. Therefore the self-learning activities’ arrangement in a way augmenting the result quality becomes a top priority task. This research objective consists in elaborating the scenario for organization of the students’ qualitative self-study, based on blended learning models. The author analyzes four blended learning models: the rotation model, flex-model, self-blend model and online driver model, and gives examples of their use. It is shown that first two models are the most suitable for full-time students. A general scenario for the use of blended learning models is described. Although the use of blended learning models causes several difficulties, it also essentially contributes into students’ self-study monitoring and control support.
Gilda M. Currenti
Full Text Available Motivated by ongoing efforts to understand the nature and the energy potential of geothermal resources, we devise a coupled numerical model (hydrological, thermal, mechanical, which may help in the characterization and monitoring of hydrothermal systems through computational experiments. Hydrothermal areas in volcanic regions arise from a unique combination of geological and hydrological features which regulate the movement of fluids in the vicinity of magmatic sources capable of generating large quantities of steam and hot water. Numerical simulations help in understanding and characterizing rock-fluid interaction processes and the geophysical observations associated with them. Our aim is the quantification of the response of different geophysical observables (i.e., deformation, gravity, and magnetic fields to hydrothermal activity on the basis of a sound geological framework (e.g., distribution and pathways of the flows, the presence of fractured zones, caprock. A detailed comprehension and quantification of the evolution and dynamics of the geothermal systems and the definition of their internal state through a geophysical modeling approach are essential to identify the key parameters for which the geothermal system may fulfill the requirements to be exploited as a source of energy. For the sake of illustration only, the numerical computations are focused on a conceptual model of the hydrothermal system of Vulcano Island by simulating a generic 1-year unrest and estimating different geophysical changes. We solved (i the mass and energy balance equations of flow in porous media for temperature, pressure and density changes, (ii the elastostatic equation for the deformation field and (iii the Poisson's equations for gravity and magnetic potential fields. Under the model assumptions, a generic unrest of 1-year engenders on the ground surface low amplitude changes in the investigated geophysical observables, that, being above the accuracies of
Nam, Nguyen Hoai
Model of active and collaborative learning (ACLM) applied in training specific subject makes clear advantage due to the goals of knowledge, skills that students got to develop successful future job. The author exploits the learning management system (LMS) of Hanoi National University of Education (HNUE) to establish a learning environment in the…
Han Tantri Hardini
Full Text Available This research aims to know the influence of problem based learning model toward students’ activities and achievement on Financial Management subject for undergraduate program students of Accounting Education. It was a quantitative research that used true experimental design. Samples of this study were undergraduate program students of Accounting Education in the year of 2014. Class A were control class and class B were experimental class. Data were analyzed by using t-test in order to determine the differences of learning outcomes between control class and experimental class. Then, questionnaires were distributed to gather students’ activities information in their students’ learning model. Findings show that there is an influence of Problem Based Learning model toward students’ activities and learning outcomes on Financial Management subject for undergraduate program students of Accounting Education since t-count ≥ t-table. It is 6.120 ≥ 1.9904. Students’ learning activities with Problem Based Learning model are better than students who are taught by conventional learning model.
Chen, Gwo-Dong; Nurkhamid; Wang, Chin-Yeh; Yang, Shu-Han; Chao, Po-Yao
In a classroom, obtaining active, whole-focused, and engaging learning results from a design is often difficult. In this study, we propose a self-observation model that employs an instinctive interface for classroom active learning. Students can communicate with virtual avatars in the vertical screen and can react naturally according to the…
I study the informational complexity of active learning in a statistical learning theory framework. Specifically, I derive bounds on the rates of...convergence achievable by active learning , under various noise models and under general conditions on the hypothesis class. I also study the theoretical...advantages of active learning over passive learning, and develop procedures for transforming passive learning algorithms into active learning algorithms
Gross, Alden L; Rebok, George W; Brandt, Jason; Tommet, Doug; Marsiske, Michael; Jones, Richard N
To investigate the influence of memory training on initial recall and learning. The Advanced Cognitive Training for Independent and Vital Elderly study of community-dwelling adults older than age 65 (n = 1,401). We decomposed trial-level recall in the Auditory Verbal Learning Test (AVLT) and Hopkins Verbal Learning Test (HVLT) into initial recall and learning across trials using latent growth models. Trial-level increases in words recalled in the AVLT and HVLT at each follow-up visit followed an approximately logarithmic shape. Over the 5-year study period, memory training was associated with slower decline in Trial 1 AVLT recall (Cohen's d = 0.35, p = .03) and steep pre- and posttraining acceleration in learning (d = 1.56, p learning, d = 3.10, p memory-trained group had a higher level of recall than the control group through the end of the 5-year study period despite faster decline in learning. This study contributes to the understanding of the mechanisms by which training benefits memory and expands current knowledge by reporting long-term changes in initial recall and learning, as measured from growth models and by characterization of the impact of memory training on these components. Results reveal that memory training delays the worsening of memory span and boosts learning.
Hansen, Bodil Winther; Hatt, Camusa
at Metropolitan University College. Since 2013 all UCS have worked with a nationally decided study activity model. The model outlines four different types of learning activities. Students are introduced to courses via the model to heighten their understanding of course design and the expectations...... combining quantitative surveys, interviews, observation and focus groups. Comparisonldiscussion: The presentation will discuss the ambition to optimize dialogue about learning between lecturers and students by using a model of study activity. Results related to the value and potential of the model as seen...... by both lecturers and students will be presented. Findings/results/outcomes/effects: Students point out that the model can be a useful tool to gain an overview of learning activities and the amount of time they are expected to spend in courses. When lecturers introduce courses via the model it deepens...
Hamdy AHMED ABDELAZIZ
Full Text Available The present theoretical paper aims to develop a grounded model for designing instructional activities appropriate to e-learning and online learning environments. The suggested model is guided by learning principles of cognitivism, constructivism, and connectivism learning principles to help online learners constructing meaningful experiences and moving from knowledge acquisition to knowledge creation process. The proposed model consists of five dynamic and grounded domains that assure the quality of designing and using e-learning activities: Ø Social Domain; Ø Technological Domain; Ø Epistemological Domain; Ø Psychological domain; and Ø Pedagogical Domain. Each of these domains needs four types of presences to reflect the design and the application process of e-learning activities. These four presences are: Ø cognitive presence, Ø human presence, Ø psychological presence and Ø mental presence. Applying the proposed model (STEPP throughout all online and adaptive e-learning environments may improve the process of designing and developing e-learning activities to be used as mindtools for current and future learners.
Full Text Available In Interactive Learning Environment (ILE, the cognitive activity and behavior of learners are the center of the researchers’ concerns. The improvement of learning through combining these axes as a structure of indicators for well-designed learning environment, encloses the measurement of the educational activity as a part of the learning process. In this paper, we propose a mathematical modeling approach based on learners actions to estimate the cognitive activity, learning behavior and motivation, in accordance with a proposed course content structure. This Cognitive indicator includes the study of knowledge, memory and reasoning. While, activity indicator aims to study effort, resistance and intensity. The results recovered on a sample of students with different levels of education, assume that the proposed approach presents a relation among all these indicators which is relatively reliable in the term of cognitive system.
Fitri Mawaddah Lubis
Full Text Available This study aimed to analyze the differences in learning outcomes of students taught by cooperative learning model NHT using simulation PhET and conventional learning, analyzing the differences in learning outcomes of students who have high activity and low activity, as well as the interaction between learning model with the level of student activity in influencing the outcome students learn physics. This research is a quasi experimental. The population in this study were students of class X SMK Tritech Informatika Medan. The tests were used to obtain the data is in the form of multiple choice. Test requirements have been carried out in the form of normality and homogeneity, which showed that the normal data and homogeneous. The data were analyzed using Anova analysis of two paths. The results showed that: The physics learning outcomes of students who use cooperative learning model NHT using PhET simulations media is better than students who use conventional learning models. The physics learning outcomes of students who have high learning activities is better than students who have Low learning activities. There is an interaction between cooperative learning model NHT PhET simulations using the media and the level of learning activity in influencing student learning outcomes. Average increase learning outcomes in the control class is greater than the experimental class.
Ningsih; Soetjipto, Budi Eko; Sumarmi
The purpose of this study was: (1) to analyze increasing students' learning activity and learning outcomes. Student activities which were observed include the visual, verbal, listening, writing and mental visual activity; (2) to analyze the improvement of student learning outcomes using "Round Table" and "Rally Coach" Model of…
Foster, Aroutis; Shah, Mamta
This article elucidates the process of game-based learning in classrooms through the use of the Play Curricular activity Reflection Discussion (PCaRD) model. A mixed-methods study was conducted at a high school to implement three games with the PCaRD model in a year-long elective course. Data sources included interviews and observations for…
Tang, Jin-ya; Huang, Min; Zhu, Qi-bing
Seed purity reflects the degree of seed varieties in typical consistent characteristics, so it is great important to improve the reliability and accuracy of seed purity detection to guarantee the quality of seeds. Hyperspectral imaging can reflect the internal and external characteristics of seeds at the same time, which has been widely used in nondestructive detection of agricultural products. The essence of nondestructive detection of agricultural products using hyperspectral imaging technique is to establish the mathematical model between the spectral information and the quality of agricultural products. Since the spectral information is easily affected by the sample growth environment, the stability and generalization of model would weaken when the test samples harvested from different origin and year. Active learning algorithm was investigated to add representative samples to expand the sample space for the original model, so as to implement the rapid update of the model's ability. Random selection (RS) and Kennard-Stone algorithm (KS) were performed to compare the model update effect with active learning algorithm. The experimental results indicated that in the division of different proportion of sample set (1:1, 3:1, 4:1), the updated purity detection model for maize seeds from 2010 year which was added 40 samples selected by active learning algorithm from 2011 year increased the prediction accuracy for 2011 new samples from 47%, 33.75%, 49% to 98.89%, 98.33%, 98.33%. For the updated purity detection model of 2011 year, its prediction accuracy for 2010 new samples increased by 50.83%, 54.58%, 53.75% to 94.57%, 94.02%, 94.57% after adding 56 new samples from 2010 year. Meanwhile the effect of model updated by active learning algorithm was better than that of RS and KS. Therefore, the update for purity detection model of maize seeds is feasible by active learning algorithm.
Sanchez, Christopher A.; Ruddell, Benjamin L.; Schiesser, Roy; Merwade, Venkatesh
Previous research has suggested that the use of more authentic learning activities can produce more robust and durable knowledge gains. This is consistent with calls within civil engineering education, specifically hydrology, that suggest that curricula should more often include professional perspective and data analysis skills to better develop the "T-shaped" knowledge profile of a professional hydrologist (i.e., professional breadth combined with technical depth). It was expected that the inclusion of a data-driven simulation lab exercise that was contextualized within a real-world situation and more consistent with the job duties of a professional in the field, would provide enhanced learning and appreciation of job duties beyond more conventional paper-and-pencil exercises in a lower-division undergraduate course. Results indicate that while students learned in both conditions, learning was enhanced for the data-driven simulation group in nearly every content area. This pattern of results suggests that the use of data-driven modeling and visualization activities can have a significant positive impact on instruction. This increase in learning likely facilitates the development of student perspective and conceptual mastery, enabling students to make better choices about their studies, while also better preparing them for work as a professional in the field.
Yulindar, Arvitri; Djudin, Tomo; Hamdani
This study aims to determine effectiveness of remediation application of active learning models that have misconceptions on rectilinear motion in class VIII SMP Negeri 2 Pontianak. This research is the form of pre-experiment using a one group pretest-postest. The study sample consisted of 38 students of class VIII B SMP Negeri 2 Pontianak. Data collection technique used in the form of a measurement technique using multiple choice diagnostic tests with reason that have total 10 questions. The ...
Yang, Xufeng; Liu, Yongshou; Ma, Panke
Structural reliability analysis under evidence theory is investigated. It is rigorously proved that a surrogate model providing only correct sign prediction of the performance function can meet the accuracy requirement of evidence-theory-based reliability analysis. Accordingly, a method based on the active learning kriging model which only correctly predicts the sign of the performance function is proposed. Interval Monte Carlo simulation and a modified optimization method based on Karush-Kuhn-Tucker conditions are introduced to make the method more efficient in estimating the bounds of failure probability based on the kriging model. Four examples are investigated to demonstrate the efficiency and accuracy of the proposed method.
Full Text Available Despite the imperatives of policy and rhetoric about their integration in formal education, Information and Communication Technologies (ICTs are often used as an "add-on" in many classrooms and in many lesson plans. Nevertheless, many teachers find that interesting and well-planned tasks, projects, and resources provide a key to harnessing the educational potential of digital resources, Internet communications and interactive multimedia to engage the interest, interaction, and knowledge construction of young learners. To the extent that such approaches go beyond and transform traditional "transmission" models of teaching and formal lesson planning, this paper investigates the changing requirements and new possibilities represented by the challenge of integrating ICTs in education in a way which at the same time connects more effectively with both the specific contents of the curriculum and the various stages and elements of the learning process. Case studies from teacher education foundation courses provide an exemplary focus of inquiry in order to better link relevant new theories or models of learning with practice, to build upon related learner-centered strategies for integrating ICT resources and tools, and to incorporate interdependent functions of learning as information access, communication, and applied interactions. As one possible strategy in this direction, the concept of an "ICT-supported learning activity" suggests the need for teachers to approach this increasing challenge more as "designers" of effective and integrated learning rather than mere "transmitters" of skills or information through an add-on use of ICTs.
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
Zhao, Lifei; Li, Zhen; Caswell, Bruce; Ouyang, Jie; Karniadakis, George Em
We simulate complex fluids by means of an on-the-fly coupling of the bulk rheology to the underlying microstructure dynamics. In particular, a continuum model of polymeric fluids is constructed without a pre-specified constitutive relation, but instead it is actively learned from mesoscopic simulations where the dynamics of polymer chains is explicitly computed. To couple the bulk rheology of polymeric fluids and the microscale dynamics of polymer chains, the continuum approach (based on the finite volume method) provides the transient flow field as inputs for the (mesoscopic) dissipative particle dynamics (DPD), and in turn DPD returns an effective constitutive relation to close the continuum equations. In this multiscale modeling procedure, we employ an active learning strategy based on Gaussian process regression (GPR) to minimize the number of expensive DPD simulations, where adaptively selected DPD simulations are performed only as necessary. Numerical experiments are carried out for flow past a circular cylinder of a non-Newtonian fluid, modeled at the mesoscopic level by bead-spring chains. The results show that only five DPD simulations are required to achieve an effective closure of the continuum equations at Reynolds number Re = 10. Furthermore, when Re is increased to 100, only one additional DPD simulation is required for constructing an extended GPR-informed model closure. Compared to traditional message-passing multiscale approaches, applying an active learning scheme to multiscale modeling of non-Newtonian fluids can significantly increase the computational efficiency. Although the method demonstrated here obtains only a local viscosity from the polymer dynamics, it can be extended to other multiscale models of complex fluids whose macro-rheology is unknown.
Shreeve, Michael W.
In a chiropractic college that utilizes a hybrid curriculum model composed of adult-based learning strategies along with traditional lecture-based course delivery, a literature search for educational delivery methods that would integrate the affective domain and the cognitive domain of learning provided some insights into the use of problem-based learning (PBL), experiential learning theory (ELT), and the emerging use of appreciative inquiry (AI) to enhance the learning experience. The purpos...
Kryshchyshyn, Anna; Devinyak, Oleg; Kaminskyy, Danylo; Grellier, Philippe; Lesyk, Roman
This paper presents novel QSAR models for the prediction of antitrypanosomal activity among thiazolidines and related heterocycles. The performance of four machine learning algorithms: Random Forest regression, Stochastic gradient boosting, Multivariate adaptive regression splines and Gaussian processes regression have been studied in order to reach better levels of predictivity. The results for Random Forest and Gaussian processes regression are comparable and outperform other studied methods. The preliminary descriptor selection with Boruta method improved the outcome of machine learning methods. The two novel QSAR-models developed with Random Forest and Gaussian processes regression algorithms have good predictive ability, which was proved by the external evaluation of the test set with corresponding Q 2 ext =0.812 and Q 2 ext =0.830. The obtained models can be used further for in silico screening of virtual libraries in the same chemical domain in order to find new antitrypanosomal agents. Thorough analysis of descriptors influence in the QSAR models and interpretation of their chemical meaning allows to highlight a number of structure-activity relationships. The presence of phenyl rings with electron-withdrawing atoms or groups in para-position, increased number of aromatic rings, high branching but short chains, high HOMO energy, and the introduction of 1-substituted 2-indolyl fragment into the molecular structure have been recognized as trypanocidal activity prerequisites. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Djouad, Tarek; Mille, Alain
Although learning indicators are now properly studied and published, it is still very difficult to manage them freely within most distance learning platforms. As all activity indicators need to collect and analyze properly traces of the learning activity, we propose to use these traces as a starting point for a platform independent Trace…
Zayapragassarazan, Z.; Kumar, Santosh
Present generation students are primarily active learners with varied learning experiences and lecture courses may not suit all their learning needs. Effective learning involves providing students with a sense of progress and control over their own learning. This requires creating a situation where learners have a chance to try out or test their…
In many computer vision applications, objects have to be learned and recognized in images or image sequences. This book presents new probabilistic hierarchical models that allow an efficient representation of multiple objects of different categories, scales, rotations, and views. The idea is to exploit similarities between objects and object parts in order to share calculations and avoid redundant information. Furthermore inference approaches for fast and robust detection are presented. These new approaches combine the idea of compositional and similarity hierarchies and overcome limitations of previous methods. Besides classical object recognition the book shows the use for detection of human poses in a project for gait analysis. The use of activity detection is presented for the design of environments for ageing, to identify activities and behavior patterns in smart homes. In a presented project for parking spot detection using an intelligent vehicle, the proposed approaches are used to hierarchically model...
Kim, Yongsoo; Perova, Zinaida; Mirrione, Martine M; Pradhan, Kith; Henn, Fritz A; Shea, Stephen; Osten, Pavel; Li, Bo
Some individuals are resilient, whereas others succumb to despair in repeated stressful situations. The neurobiological mechanisms underlying such divergent behavioral responses remain unclear. Here, we employed an automated method for mapping neuronal activity in search of signatures of stress responses in the entire mouse brain. We used serial two-photon tomography to detect expression of c-FosGFP - a marker of neuronal activation - in c-fosGFP transgenic mice subjected to the learned helplessness (LH) procedure, a widely used model of stress-induced depression-like phenotype in laboratory animals. We found that mice showing "helpless" behavior had an overall brain-wide reduction in the level of neuronal activation compared with mice showing "resilient" behavior, with the exception of a few brain areas, including the locus coeruleus, that were more activated in the helpless mice. In addition, the helpless mice showed a strong trend of having higher similarity in whole-brain activity profile among individuals, suggesting that helplessness is represented by a more stereotypic brain-wide activation pattern. This latter effect was confirmed in rats subjected to the LH procedure, using 2-deoxy-2[18F]fluoro-D-glucose positron emission tomography to assess neural activity. Our findings reveal distinct brain activity markings that correlate with adaptive and maladaptive behavioral responses to stress, and provide a framework for further studies investigating the contribution of specific brain regions to maladaptive stress responses.
Full Text Available Some individuals are resilient, whereas others succumb to despair in repeated stressful situations. The neurobiological mechanisms underlying such divergent behavioral responses remain unclear. Here, we employed an automated method for mapping neuronal activity in search of signatures of stress responses in the entire mouse brain. We used serial two-photon tomography to detect expression of c-FosGFP – a marker of neuronal activation – in c-fosGFP transgenic mice subjected to the learned helplessness (LH procedure, a widely used model of stress-induced depression-like phenotype in laboratory animals. We found that mice showing helpless behavior had an overall brain-wide reduction in the level of neuronal activation compared with mice showing resilient behavior, with the exception of a few brain areas, including the locus coeruleus, that were more activated in the helpless mice. In addition, the helpless mice showed a strong trend of having higher similarity in whole brain activity profile among individuals, suggesting that helplessness is represented by a more stereotypic brain-wide activation pattern. This latter effect was confirmed in rats subjected to the LH procedure, using 2-deoxy-2[18F]fluoro-D-glucose positron emission tomography to assess neural activity. Our findings reveal distinct brain activity markings that correlate with adaptive and maladaptive behavioral responses to stress, and provide a framework for further studies investigating the contribution of specific brain regions to maladaptive stress responses.
Full Text Available This study aims to design learning Problem Based Learning Model based on syntax study recommendations and content issues on Physics Impulse materials through experiments. This research is a development research with Kemp model. The reference for making the learning design is the result of the syntax study and the content of existing PBL implementation problems from Agustina research. This instructional design is applied to the physics material about Impulse done through experimental activity. Limited trials were conducted on the SWCU Physics Education Study Program students group Salatiga, while the validity test was conducted by high school teachers and physics education lecturers. The results of the trial evaluation are limited and the validity test is used to improve the designs that have been made. The conclusion of this research is the design of learning by using PBL model on Impuls material by referring the result of syntax study and the problem content of existing PBL implementation can be produced by learning activity designed in laboratory experiment activity. The actual problem for Impuls material can be used car crash test video at factory. The results of validation tests and limited trials conducted by researchers assessed that the design of learning made by researchers can be used with small revisions. Suggestions from this research are in making learning design by using PBL model to get actual problem can by collecting news that come from newspaper, YouTube, internet, and television.
Pierce, Richard; Fox, Jeremy
To implement a "flipped classroom" model for a renal pharmacotherapy topic module and assess the impact on pharmacy students' performance and attitudes. Students viewed vodcasts (video podcasts) of lectures prior to the scheduled class and then discussed interactive cases of patients with end-stage renal disease in class. A process-oriented guided inquiry learning (POGIL) activity was developed and implemented that complemented, summarized, and allowed for application of the material contained in the previously viewed lectures. Students' performance on the final examination significantly improved compared to performance of students the previous year who completed the same module in a traditional classroom setting. Students' opinions of the POGIL activity and the flipped classroom instructional model were mostly positive. Implementing a flipped classroom model to teach a renal pharmacotherapy module resulted in improved student performance and favorable student perceptions about the instructional approach. Some of the factors that may have contributed to students' improved scores included: student mediated contact with the course material prior to classes, benchmark and formative assessments administered during the module, and the interactive class activities.
Häusser, Jan Alexander; Schulz-Hardt, Stefan; Mojzisch, Andreas
The active learning hypothesis of the job-demand-control model [Karasek, R. A. 1979. "Job Demands, Job Decision Latitude, and Mental Strain: Implications for Job Redesign." Administration Science Quarterly 24: 285-307] proposes positive effects of high job demands and high job control on performance. We conducted a 2 (demands: high vs. low) × 2 (control: high vs. low) experimental office workplace simulation to examine this hypothesis. Since performance during a work simulation is confounded by the boundaries of the demands and control manipulations (e.g. time limits), we used a post-test, in which participants continued working at their task, but without any manipulation of demands and control. This post-test allowed for examining active learning (transfer) effects in an unconfounded fashion. Our results revealed that high demands had a positive effect on quantitative performance, without affecting task accuracy. In contrast, high control resulted in a speed-accuracy tradeoff, that is participants in the high control conditions worked slower but with greater accuracy than participants in the low control conditions.
Development and Study the Usage of Blended Learning Environment Model Using Engineering Design Concept Learning Activities to Computer Programming Courses for Undergraduate Students of Rajabhat Universities
Full Text Available The objectives of this research were to study and Synthesise the components, to develop, and to study the usage of blended learning environment model using engineering design concept learning activities to computer programming courses for undergraduate students of Rajabhat universities. The research methodology was divided into 3 phases. Phase I: surveying presents, needs and problems in teaching computer programming of 52 lecturers by using in-depth interview from 5 experienced lecturers. The model’s elements were evaluated by 5 experts. The tools were questionnaire, interview form, and model’s elements assessment form. Phase II: developing the model of blended learning environment and learning activities based on engineering design processes and confirming model by 8 experts. The tools were the draft of learning environment, courseware, and assessment forms. Phase III evaluating the effects of using the implemented environment. The samples were students which formed into 2 groups, 25 people in the experiment group and 27 people in the control group by cluster random sampling. The tools were learning environment, courseware, and assessment tools. The statistics used in this research were means, standard deviation, t-test dependent, and one-way MANOVA. The results found that: 1 Lecturers quite agreed with the physical, mental, social, and information learning environment, learning processes, and assessments. There were all needs in high level. However there were physical environment problems in high level yet quite low in other aspects. 2 The developed learning environment had 4 components which were a 4 types of environments b the inputs included blended learning environment, learning motivation factors, and computer programming content c the processes were analysis of state objectives, design learning environment and activities, developing learning environment and testing materials, implement, ation evaluation and evaluate, 4 the outputs
Friston, Karl; FitzGerald, Thomas; Rigoli, Francesco; Schwartenbeck, Philipp; O Doherty, John; Pezzulo, Giovanni
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.
Lin, Jang-Long; Cheng, Meng-Fei; Chang, Ying-Chi; Li, Hsiao-Wen; Chang, Jih-Yuan; Lin, Deng-Min
The purpose of this study was to investigate how learning materials based on Science Magic activities affect student attitudes to science. A quasi-experimental design was conducted to explore the combination of Science Magic with the 5E Instructional Model to develop learning materials for teaching a science unit about friction. The participants…
Burini, D.; De Lillo, S.; Gibelli, L.
This paper proposes a systems approach to the theory of perception and learning in populations composed of many living entities. Starting from a phenomenological description of these processes, a mathematical structure is derived which is deemed to incorporate their complexity features. The modeling is based on a generalization of kinetic theory methods where interactions are described by theoretical tools of game theory. As an application, the proposed approach is used to model the learning processes that take place in a classroom.
This paper discusses and questions the current metadata standards for learning objects from a pedagogical point of view. From a social constructivist approach, the paper discusses how learning objects can support problem based, self-governed learning activities. In order to support this approach......, it is argued that it is necessary to focus on learning activities rather than on learning objects. Further, it is argued that descriptions of learning objectives and learning activities should be separated from learning objects. The paper presents a new conception of learning objects which supports problem...... based, self-governed activities. Further, a new way of thinking pedagogy into learning objects is introduced. It is argued that a lack of pedagogical thinking in learning objects is not solved through pedagogical metadata. Instead, the paper suggests the concept of references as an alternative...
Reng, Lars; Schoenau-Fog, Henrik
will describe the levels of the model, which is based on our experience in teaching professional game development at university level. Furthermore, we have been using the model to inspire numerous educators to improve their students’ motivation and skills. The model presents various game-based learning...... activities, and depicts their required planning and expected outcome through eight levels. At its lower levels, the model contains the possibilities of using stand-alone analogue and digital games as teachers, utilizing games as a facilitator of learning activities, exploiting gamification and motivating......In this paper, we will introduce the Game Enhanced learning Model (GEM), which describes a range of gameoriented learning activities. The model is intended to give an overview of the possibilities of game-based learning in general and all the way up to purposive game productions. In the paper, we...
Beltrame, Thomas; Amelard, Robert; Wong, Alexander; Hughson, Richard L
sensors in unsupervised activities of daily living in combination with novel machine learning algorithms to investigate the aerobic system dynamics with the potential to contribute to models of functional health status and guide future individualized health care in the normal population.
The learning phenomena, their complexity, concepts, structure, suitable theories and models, have been extensively treated in the mathematical literature in the last century, and  contains a very good introduction to the literature describing the many approaches and lines of research developed about them. Two main schools have to be pointed out  in order to understand the two -not exclusive- kinds of existing models: the stimulus sampling models and the stochastic learning models. Also  should be mentioned as a survey where two methods of learning are pointed out, the cognitive and the social, and where the knowledge looks like a mathematical unknown. Finally, as the authors do, we refer to the works [9,10], where the concept of population thinking was introduced and which motivate the game theory rules as a tool (both included in  to develop their theory) and , where the ideas of developing a mathematical kinetic theory of perception and learning were proposed.
Burini, D; De Lillo, S; Gibelli, L
This paper proposes a systems approach to the theory of perception and learning in populations composed of many living entities. Starting from a phenomenological description of these processes, a mathematical structure is derived which is deemed to incorporate their complexity features. The modeling is based on a generalization of kinetic theory methods where interactions are described by theoretical tools of game theory. As an application, the proposed approach is used to model the learning processes that take place in a classroom. Copyright © 2015 Elsevier B.V. All rights reserved.
This study aimed to determine the effect of mastery learning model supported with reflective thinking activities on the fifth grade medical students' academic achievement. Mixed methods approach was applied in two samples (n = 64 and n = 6). Quantitative part of the study was based on a pre-test-post-test control group design with an experiment…
Campigotto, Paolo; Passerini, Andrea; Battiti, Roberto
This paper introduces the active learning of Pareto fronts (ALP) algorithm, a novel approach to recover the Pareto front of a multiobjective optimization problem. ALP casts the identification of the Pareto front into a supervised machine learning task. This approach enables an analytical model of the Pareto front to be built. The computational effort in generating the supervised information is reduced by an active learning strategy. In particular, the model is learned from a set of informative training objective vectors. The training objective vectors are approximated Pareto-optimal vectors obtained by solving different scalarized problem instances. The experimental results show that ALP achieves an accurate Pareto front approximation with a lower computational effort than state-of-the-art estimation of distribution algorithms and widely known genetic techniques.
This article presents the Elder Academy (EA) Network as the policy and practice in promoting active ageing through elder learning in Hong Kong. First, the article examines how the change in demographics and the prevalent trend of an ageing population have propelled the government in Hong Kong to tackle issues and challenges brought about by an…
Castro, R.M.; Nowak, R.
This paper analyzes the potential advantages and theoretical challenges of "active learning" algorithms. Active learning involves sequential sampling procedures that use information gleaned from previous samples in order to focus the sampling and accelerate the learning process relative to "passive
N. R. Fitriani; A. Widiyatmoko; M. Khusniati
Science learning in school can be applied by connecting the material in the learning with real life. However in fact science learning process in SMP Negeri 10 Magelang has not emphasized students’ activity to relate science to real life. Learning science using CTL guided inquiry-based model implement the learning in where teacher provides initial questions related issues or events in everyday life, then students do experiments to prove concepts of science guided by teacher.The purpose of this...
Shreeve, Michael W
In a chiropractic college that utilizes a hybrid curriculum model composed of adult-based learning strategies along with traditional lecture-based course delivery, a literature search for educational delivery methods that would integrate the affective domain and the cognitive domain of learning provided some insights into the use of problem-based learning (PBL), experiential learning theory (ELT), and the emerging use of appreciative inquiry (AI) to enhance the learning experience. The purpose of this literature review is to provide a brief overview of key components of PBL, ELT, and AI in educational methodology and to discuss how these might be used within the chiropractic curriculum to supplement traditional didactic lecture courses. A growing body of literature describes the use of PBL and ELT in educational settings across many disciplines, both at the undergraduate and graduate levels. The use of appreciative inquiry as an instructional methodology presents a new area for exploration and study in the academic environment. Educational research in the chiropractic classroom incorporating ELT and appreciative inquiry might provide some valuable insights for future curriculum development.
Nissim, Nir; Shahar, Yuval; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert
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
Nissim, Nir; Shahar, Yuval; Boland, Mary Regina; Tatonetti, Nicholas P; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert
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
Rorabaugh, Jacki M; Chalermpalanupap, Termpanit; Botz-Zapp, Christian A; Fu, Vanessa M; Lembeck, Natalie A; Cohen, Robert M; Weinshenker, David
See Grinberg and Heinsen (doi:10.1093/brain/awx261) for a scientific commentary on this article. Clinical evidence suggests that aberrant tau accumulation in the locus coeruleus and noradrenergic dysfunction may be a critical early step in Alzheimer’s disease progression. Yet, an accurate preclinical model of these phenotypes that includes early pretangle tau accrual in the locus coeruleus, loss of locus coeruleus innervation and deficits locus coeruleus/norepinephrine modulated behaviours, does not exist, hampering the identification of underlying mechanisms and the development of locus coeruleus-based therapies. Here, a transgenic rat (TgF344-AD) expressing disease-causing mutant amyloid precursor protein (APPsw) and presenilin-1 (PS1ΔE9) was characterized for histological and behavioural signs of locus coeruleus dysfunction reminiscent of mild cognitive impairment/early Alzheimer’s disease. In TgF344-AD rats, hyperphosphorylated tau was detected in the locus coeruleus prior to accrual in the medial entorhinal cortex or hippocampus, and tau pathology in the locus coeruleus was negatively correlated with noradrenergic innervation in the medial entorhinal cortex. Likewise, TgF344-AD rats displayed progressive loss of hippocampal norepinephrine levels and locus coeruleus fibres in the medial entorhinal cortex and dentate gyrus, with no frank noradrenergic cell body loss. Cultured mouse locus coeruleus neurons expressing hyperphosphorylation-prone mutant human tau had shorter neurites than control neurons, but similar cell viability, suggesting a causal link between pretangle tau accrual and altered locus coeruleus fibre morphology. TgF344-AD rats had impaired reversal learning in the Morris water maze compared to their wild-type littermates, which was rescued by chemogenetic locus coeruleus activation via designer receptors exclusively activated by designer drugs (DREADDs). Our results indicate that TgF344-AD rats uniquely meet several key criteria for a
Full Text Available The search for small molecule inhibitors of Ebola virus (EBOV has led to several high throughput screens over the past 3 years. These have identified a range of FDA-approved active pharmaceutical ingredients (APIs with anti-EBOV activity in vitro and several of which are also active in a mouse infection model. There are millions of additional commercially-available molecules that could be screened for potential activities as anti-EBOV compounds. One way to prioritize compounds for testing is to generate computational models based on the high throughput screening data and then virtually screen compound libraries. In the current study, we have generated Bayesian machine learning models with viral pseudotype entry assay and the EBOV replication assay data. We have validated the models internally and externally. We have also used these models to computationally score the MicroSource library of drugs to select those likely to be potential inhibitors. Three of the highest scoring molecules that were not in the model training sets, quinacrine, pyronaridine and tilorone, were tested in vitro and had EC50 values of 350, 420 and 230 nM, respectively. Pyronaridine is a component of a combination therapy for malaria that was recently approved by the European Medicines Agency, which may make it more readily accessible for clinical testing. Like other known antimalarial drugs active against EBOV, it shares the 4-aminoquinoline scaffold. Tilorone, is an investigational antiviral agent that has shown a broad array of biological activities including cell growth inhibition in cancer cells, antifibrotic properties, α7 nicotinic receptor agonist activity, radioprotective activity and activation of hypoxia inducible factor-1. Quinacrine is an antimalarial but also has use as an anthelmintic. Our results suggest data sets with less than 1,000 molecules can produce validated machine learning models that can in turn be utilized to identify novel EBOV inhibitors in
Full Text Available The search for small molecule inhibitors of Ebola virus (EBOV has led to several high throughput screens over the past 3 years. These have identified a range of FDA-approved active pharmaceutical ingredients (APIs with anti-EBOV activity in vitro and several of which are also active in a mouse infection model. There are millions of additional commercially-available molecules that could be screened for potential activities as anti-EBOV compounds. One way to prioritize compounds for testing is to generate computational models based on the high throughput screening data and then virtually screen compound libraries. In the current study, we have generated Bayesian machine learning models with viral pseudotype entry assay and the EBOV replication assay data. We have validated the models internally and externally. We have also used these models to computationally score the MicroSource library of drugs to select those likely to be potential inhibitors. Three of the highest scoring molecules that were not in the model training sets, quinacrine, pyronaridine and tilorone, were tested in vitro and had EC50 values of 350, 420 and 230 nM, respectively. Pyronaridine is a component of a combination therapy for malaria that was recently approved by the European Medicines Agency, which may make it more readily accessible for clinical testing. Like other known antimalarial drugs active against EBOV, it shares the 4-aminoquinoline scaffold. Tilorone, is an investigational antiviral agent that has shown a broad array of biological activities including cell growth inhibition in cancer cells, antifibrotic properties, α7 nicotinic receptor agonist activity, radioprotective activity and activation of hypoxia inducible factor-1. Quinacrine is an antimalarial but also has use as an anthelmintic. Our results suggest data sets with less than 1,000 molecules can produce validated machine learning models that can in turn be utilized to identify novel EBOV inhibitors in
Full Text Available The search for small molecule inhibitors of Ebola virus (EBOV has led to several high throughput screens over the past 3 years. These have identified a range of FDA-approved active pharmaceutical ingredients (APIs with anti-EBOV activity in vitro and several of which are also active in a mouse infection model. There are millions of additional commercially-available molecules that could be screened for potential activities as anti-EBOV compounds. One way to prioritize compounds for testing is to generate computational models based on the high throughput screening data and then virtually screen compound libraries. In the current study, we have generated Bayesian machine learning models with viral pseudotype entry assay and the EBOV replication assay data. We have validated the models internally and externally. We have also used these models to computationally score the MicroSource library of drugs to select those likely to be potential inhibitors. Three of the highest scoring molecules that were not in the model training sets, quinacrine, pyronaridine and tilorone, were tested in vitro and had EC50 values of 350, 420 and 230 nM, respectively. Pyronaridine is a component of a combination therapy for malaria that was recently approved by the European Medicines Agency, which may make it more readily accessible for clinical testing. Like other known antimalarial drugs active against EBOV, it shares the 4-aminoquinoline scaffold. Tilorone, is an investigational antiviral agent that has shown a broad array of biological activities including cell growth inhibition in cancer cells, antifibrotic properties, α7 nicotinic receptor agonist activity, radioprotective activity and activation of hypoxia inducible factor-1. Quinacrine is an antimalarial but also has use as an anthelmintic. Our results suggest data sets with less than 1,000 molecules can produce validated machine learning models that can in turn be utilized to identify novel EBOV inhibitors in
The presentation is concerned with general course planning philosophy and a specific case study (boomerang flight geometro-dynamics) for active learning of mathematics via computer assisted and hands-on unfolding of first principles - in this case the understanding of rotations and Eulers equatio...
Andersen, Thomas Dyreborg; Levinsen, Henrik; Philipps, Morten
Action research is conducted in three physics classes over a period of eighteen weeks with the aim of studying the effect of flipped classroom on the pupils agency and learning processes. The hypothesis is that flipped classroom teaching will potentially allocate more time to work actively...
A set of ten teacher-prepared Learning Activity Packages (LAPs) in beginning algebra and nine in intermediate algebra, these units cover sets, properties of operations, number systems, open expressions, solution sets of equations and inequalities in one and two variables, exponents, factoring and polynomials, relations and functions, radicals,…
This learning activity package on grooming for health workers is one of a series of 12 titles developed for use in health occupations education programs. Materials in the package include objectives, a list of materials needed, information sheets, reviews (self evaluations) of portions of the content, and answers to reviews. These topics are…
Mulder, Y.G.; Bollen, Lars; de Jong, Anthonius J.M.
Dynamic phenomena are common in science education. Students can learn about such system dynamic processes through model based learning activities. This paper describes a study on the effects of a learning from erroneous models approach using the learning environment SCYDynamics. The study compared
Schuetze, Hans G.
To answer the question "Financing what?" this article distinguishes several models of lifelong learning as well as a variety of lifelong learning activities. Several financing methods are briefly reviewed, however the principal focus is on Individual Learning Accounts (ILAs) which were seen by some analysts as a promising model for…
Kjær, Christopher; Hansen, Pernille Stenkil; Christensen, Inger-Marie F.
This paper reports on the effect of a lecturer training model in the shape of an e-learning project based on research on adult and work-based learning. A survey was conducted to explore participants’ learning experiences. Findings show high overall satisfaction, motivation and engagement. Suggest......This paper reports on the effect of a lecturer training model in the shape of an e-learning project based on research on adult and work-based learning. A survey was conducted to explore participants’ learning experiences. Findings show high overall satisfaction, motivation and engagement...
Li, Chun-Liang; Ferng, Chun-Sung; Lin, Hsuan-Tien
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.
Bassam A. Hussein
Full Text Available The paper demonstrates and evaluates the effectiveness of a blended learning approach to create a meaningful learning environment. We use the term blended learning approach in this paper to refer to the use of multiple or hybrid instructional methods that emphasize the role of learners as contributors to the learning process rather than recipients of learning. Contribution to learning is attained by using in class gaming as pathways that ensure active involvement of learners. Using a blended learning approach is important in order to be able to address different learning styles of the target group. The approach was also important in order to be able to demonstrate different types of challenges, issues and competences needed in project management. Student evaluations of the course confirmed that the use of multiple learning methods and, in particular, in class gaming was beneficial and contributed to a meaningful learning experience.
Schifferdecker, Karen E; Adachi-Mejia, Anna M; Butcher, Rebecca L; O'Connor, Sharon; Li, Zhigang; Bazos, Dorothy A
Action Learning Collaboratives (ALCs), whereby teams apply quality improvement (QI) tools and methods, have successfully improved patient care delivery and outcomes. We adapted and tested the ALC model as a community-based obesity prevention intervention focused on physical activity and healthy eating. The intervention used QI tools (e.g., progress monitoring) and team-based activities and was implemented in three communities through nine monthly meetings. To assess process and outcomes, we used a longitudinal repeated-measures and mixed-methods triangulation approach with a quasi-experimental design including objective measures at three time points. Most of the 97 participants were female (85.4%), White (93.8%), and non-Hispanic/Latino (95.9%). Average age was 52 years; 28.0% had annual household income of $20,000 or less; and mean body mass index was 35. Through mixed-effects models, we found some physical activity outcomes improved. Other outcomes did not significantly change. Although participants favorably viewed the QI tools, components of the QI process such as sharing goals and data on progress in teams and during meetings were limited. Participants' requests for more education or activities around physical activity and healthy eating, rather than progress monitoring and data sharing required for QI activities, challenged ALC model implementation. An ALC model for community-based obesity prevention may be more effective when applied to preexisting teams in community-based organizations. © 2015 Society for Public Health Education.
Gu, Xiaoyu; Yu, Yang; Li, Jianchun; Li, Yancheng
Magnetorheological elastomer (MRE) base isolations have attracted considerable attention over the last two decades thanks to its self-adaptability and high-authority controllability in semi-active control realm. Due to the inherent nonlinearity and hysteresis of the devices, it is challenging to obtain a reasonably complicated mathematical model to describe the inverse dynamics of MRE base isolators and hence to realise control synthesis of the MRE base isolation system. Two aims have been achieved in this paper: i) development of an inverse model for MRE base isolator based on optimal general regression neural network (GRNN); ii) numerical and experimental validation of a real-time semi-active controlled MRE base isolation system utilising LQR controller and GRNN inverse model. The superiority of GRNN inverse model lays in fewer input variables requirement, faster training process and prompt calculation response, which makes it suitable for online training and real-time control. The control system is integrated with a three-storey shear building model and control performance of the MRE base isolation system is compared with bare building, passive-on isolation system and passive-off isolation system. Testing results show that the proposed GRNN inverse model is able to reproduce desired control force accurately and the MRE base isolation system can effectively suppress the structural responses when compared to the passive isolation system.
Naylor, Patti-Jean; Macdonald, Heather M; Zebedee, Janelle A; Reed, Katherine E; McKay, Heather A
The 'active school' model offers promise for promoting school-based physical activity (PA); however, few intervention trials have evaluated its effectiveness. Thus, our purpose was to: (1) describe Action Schools! BC (AS! BC) and its implementation (fidelity and feasibility) and (2) evaluate the impact of AS! BC on school provision of PA. Ten elementary schools were randomly assigned to one of the three conditions: Usual Practice (UP, three schools), Liaison (LS, four schools) or Champion (CS, three schools). Teachers in LS and CS schools received AS! BC training and resources but differed on the level of facilitation provided. UP schools continued with regular PA. Delivery of PA during the 11-month intervention was assessed with weekly Activity Logs and intervention fidelity and feasibility were assessed using Action Plans, workshop evaluations, teacher surveys and focus groups with administrators, teachers, parents and students. Physical activity delivered was significantly greater in LS (+67.4 min/week; 95% CI: 18.7-116.1) and CS (+55.2 min/week; 95% CI: 26.4-83.9) schools than UP schools. Analysis of Action Plans and Activity Logs showed fidelity to the model and moderate levels of compliance (75%). Teachers were highly satisfied with training and support. Benefits of AS! BC included positive changes in the children and school climate, including provision of resources, improved communication and program flexibility. These results support the use of the 'active school' model to positively alter the school environment. The AS! BC model was effective, providing more opportunities for "more children to be more active more often" and as such has the potential to provide health benefits to elementary school children.
Full Text Available This research was motivated by the low activities and student learning outcomes on mathematics. The purpose of this research was to increase the activities and student learning outcomes on mathematics by applying the active learning model of card sort game. The method of this research was classroom action research that consist of planning, implementation, observation, and reflection. The instrument of data collection used was observation sheet and test questions. The technique of analysis data used were qualitative analysis and quantitative analysis. The results of this research showed that aplication of active learning model of card sort game on mathematics learning can increase the activities and student learning outcomes. It can be showed that students learning completeness reached 75%, the average activities of students in the first cycle were 59.80% and 78.39% in the second cycle with the increasing of 18.59%. The average student learning outcomes in the first cycle and the second cycle were 69.52 78.70, with an increase of 9.18.
Hovelja, Tomaž; Vavpotic, Damjan; Žvanut, Boštjan
The evaluation of e-learning and conventional pedagogical activities in nursing programmes has focused either on a single pedagogical activity or the entire curriculum, and only on students' or teachers' perspective. The goal of this study was to design and test a novel approach for evaluation of e-learning and conventional pedagogical activities…
Habib, E. H.; Tarboton, D. G.; Lall, U.; Bodin, M.; Rahill-Marier, B.; Chimmula, S.; Meselhe, E. A.; Ali, A.; Williams, D.; Ma, Y.
The hydrologic community has long recognized the need for broad reform in hydrologic education. A paradigm shift is critically sought in undergraduate hydrology and water resource education by adopting context-rich, student-centered, and active learning strategies. Hydrologists currently deal with intricate issues rooted in complex natural ecosystems containing a multitude of interconnected processes. Advances in the multi-disciplinary field include observational settings such as Critical Zone and Water, Sustainability and Climate Observatories, Hydrologic Information Systems, instrumentation and modeling methods. These research advances theory and practices call for similar efforts and improvements in hydrologic education. The typical, text-book based approach in hydrologic education has focused on specific applications and/or unit processes associated with the hydrologic cycle with idealizations, rather than the contextual relations in the physical processes and the spatial and temporal dynamics connecting climate and ecosystems. An appreciation of the natural variability of these processes will lead to graduates with the ability to develop independent learning skills and understanding. This appreciation cannot be gained in curricula where field components such as observational and experimental data are deficient. These types of data are also critical when using simulation models to create environments that support this type of learning. Additional sources of observations in conjunction with models and field data are key to students understanding of the challenges associated with using models to represent such complex systems. Recent advances in scientific visualization and web-based technologies provide new opportunities for the development of active learning techniques utilizing ongoing research. The overall goal of the current study is to develop visual, case-based, data and simulation driven learning experiences to instructors and students through a web
Dall'Alba, Gloria; Bengtsen, Søren Smedegaard
is largely lacking in the literature on active learning. In this article, we explore the possibility of re-imagining, or at least extending, the meaning of active learning by drawing out dimensions that are neither readily visible nor instrumental, as much of this literature implies. Drawing from educational......Ample attention is being paid in the higher education literature to promoting active learning among students. Where studies on active learning report student outcomes, they indicate improved or equivalent outcomes when compared with traditional lectures, which are considered more passive...... philosophy and, in particular, existential philosophies, we argue that active learning may also be partly invisible, unfocused, unsettling, and not at all instrumentalsometimes even leaving the learner more confused and (temporarily) incompetent. However, such forms of undisclosed or ‘dark’ learning, we...
Full Text Available Pemecahan masalah merupakan kegiatan matematika yang sulit baik dalam mempelajari maupun mengajarkannya, sehingga diperlukan adanya suatu model pembelajaran yang dapat memberikan pengaruh positif terhadap kemampuan pemecahan masalah siswa. Salah satu model pembelajaran yang dapat digunakan yaitu model pembelajaran ARIAS dengan strategi active learning tipe ICM. Penelitian ini bertujuan untuk mengetahui: (1 model pembelajaran ARIAS dengan strategi active learning tipe ICM berpengaruh terhadap kemampuan pemecahan masalah matematik siswa SMA; (2 Sikap siswa terhadap pembelajaran matematika menggunakan model pembelajaran ARIAS dengan strategi active learning tipe ICM. Subjek penelitian ini adalah siswa kelas XI IPA 1 dengan jumlah 38 siswa sebagai kelas kontrol dan XI IPA 2 dengan jumlah 39 siswa sebagai kelas eksperimen di SMAN 19 Kabupaten Tangerang pada tahun ajaran 2015-2016. Metode penelitian yang digunakan adalah metode penelitian eksperimen dengan adalah desain kuasi eksperimen dengan bentuk Nonequivalent Control Group serta Cluster Sampling sebagai teknik pengambilan sampel. Analisis data dalam penelitian ini menggunakan SPSS Statistics Version 22. Hasil penelitian :(1 model pembelajaran ARIAS dengan strategi active learning tipe ICM berpengaruh terhadap kemampuan pemecahan masalah matematik siswa SMA dan memberikan pengaruh yang positif; (2 sikap siswa positif terhadap model pembelajaran ARIAS dengan strategi active learning tipe ICM. Kata Kunci: Assurance Relevance Interest Assessment Satisfaction, Index Card Match, Kemampuan Pemecahan Masalah
Fiorini, Laura; Cavallo, Filippo; Dario, Paolo; Eavis, Alexandra; Caleb-Solly, Praminda
The goal of this study is to address two major issues that undermine the large scale deployment of smart home sensing solutions in people's homes. These include the costs associated with having to install and maintain a large number of sensors, and the pragmatics of annotating numerous sensor data streams for activity classification. Our aim was therefore to propose a method to describe individual users' behavioural patterns starting from unannotated data analysis of a minimal number of sensors and a "blind" approach for activity recognition. The methodology included processing and analysing sensor data from 17 older adults living in community-based housing to extract activity information at different times of the day. The findings illustrate that 55 days of sensor data from a sensor configuration comprising three sensors, and extracting appropriate features including a "busyness" measure, are adequate to build robust models which can be used for clustering individuals based on their behaviour patterns with a high degree of accuracy (>85%). The obtained clusters can be used to describe individual behaviour over different times of the day. This approach suggests a scalable solution to support optimising the personalisation of care by utilising low-cost sensing and analysis. This approach could be used to track a person's needs over time and fine-tune their care plan on an ongoing basis in a cost-effective manner.
Full Text Available The goal of this study is to address two major issues that undermine the large scale deployment of smart home sensing solutions in people’s homes. These include the costs associated with having to install and maintain a large number of sensors, and the pragmatics of annotating numerous sensor data streams for activity classification. Our aim was therefore to propose a method to describe individual users’ behavioural patterns starting from unannotated data analysis of a minimal number of sensors and a ”blind” approach for activity recognition. The methodology included processing and analysing sensor data from 17 older adults living in community-based housing to extract activity information at different times of the day. The findings illustrate that 55 days of sensor data from a sensor configuration comprising three sensors, and extracting appropriate features including a “busyness” measure, are adequate to build robust models which can be used for clustering individuals based on their behaviour patterns with a high degree of accuracy (>85%. The obtained clusters can be used to describe individual behaviour over different times of the day. This approach suggests a scalable solution to support optimising the personalisation of care by utilising low-cost sensing and analysis. This approach could be used to track a person’s needs over time and fine-tune their care plan on an ongoing basis in a cost-effective manner.
Poland, J.; Knoedler, K.; Zell, A. [Tuebingen Univ. (Germany). Lehrstuhl fuer Rechnerarchitektur; Fleischhauer, T.; Mitterer, A.; Ullmann, S. [BMW Group (Germany)
This two-part article presents the model-based optimisation algorithm ''mbminimize''. It was developed in a corporate project of the University Tuebingen and the BMW Group for the purpose of optimising internal combustion engines online on the engine test bed. The first part concentrates on the basic algorithmic design, as well as on modelling, experimental design and active learning. The second part will discuss strategies for dealing with limits such as knocking. (orig.) [German] Dieser zweiteilige Beitrag stellt den modellbasierten Optimierungsalgorithmus ''mbminimize'' vor, der in Kooperation von der Universitaet Tuebingen und der BMW Group fuer die Online-Optimierung von Verbrennungsmotoren entwickelt wurde. Der vorliegende erste Teil konzentriert sich auf das grundlegende algorithmische Design, auf Modellierung, Versuchsplanung und aktives Lernen. Der zweite Teil diskutiert Strategien zur Behandlung von Limits wie Motorklopfen.
Rezende-Filho, Flávio Moura; da Fonseca, Lucas José Sá; Nunes-Souza, Valéria; Guedes, Glaucevane da Silva; Rabelo, Luiza Antas
Teaching physiology, a complex and constantly evolving subject, is not a simple task. A considerable body of knowledge about cognitive processes and teaching and learning methods has accumulated over the years, helping teachers to determine the most efficient way to teach, and highlighting student's active participation as a means to improve learning outcomes. In this context, this paper describes and qualitatively analyzes an experience of a student-centered teaching-learning methodology based on the construction of physiological-physical models, focusing on their possible application in the practice of teaching physiology. After having Physiology classes and revising the literature, students, divided in small groups, built physiological-physical models predominantly using low-cost materials, for studying different topics in Physiology. Groups were followed by monitors and guided by teachers during the whole process, finally presenting the results in a Symposium on Integrative Physiology. Along the proposed activities, students were capable of efficiently creating physiological-physical models (118 in total) highly representative of different physiological processes. The implementation of the proposal indicated that students successfully achieved active learning and meaningful learning in Physiology while addressing multiple learning styles. The proposed method has proved to be an attractive, accessible and relatively simple approach to facilitate the physiology teaching-learning process, while facing difficulties imposed by recent requirements, especially those relating to the use of experimental animals and professional training guidelines. Finally, students' active participation in the production of knowledge may result in a holistic education, and possibly, better professional practices.
Salakhutdinov, Ruslan; Tenenbaum, Joshua B; Torralba, Antonio
We introduce HD (or “Hierarchical-Deep”) models, a new compositional learning architecture that integrates deep learning models with structured hierarchical Bayesian (HB) models. Specifically, we show how we can learn a hierarchical Dirichlet process (HDP) prior over the activities of the top-level features in a deep Boltzmann machine (DBM). This compound HDP-DBM model learns to learn novel concepts from very few training example by learning low-level generic features, high-level features that capture correlations among low-level features, and a category hierarchy for sharing priors over the high-level features that are typical of different kinds of concepts. We present efficient learning and inference algorithms for the HDP-DBM model and show that it is able to learn new concepts from very few examples on CIFAR-100 object recognition, handwritten character recognition, and human motion capture datasets.
Lumpkin, Angela; Achen, Rebecca M.; Dodd, Regan K.
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…
Abstract electronics concepts are difficult to develop because the phenomena of interest cannot be readily observed. Visualisation skills support learning about electronics and can be applied at different levels of representation and understanding (observable, symbolic and abstract). Providing learners with opportunities to make transitions…
Kim, Mi Song
In light of the challenges facing science educators and special education teachers in Singapore, this study entails design-based research to develop participatory learning environments. Drawing upon Vygotskian perspectives, this case study was situated in an informal workshop around the theme of "day and night" working for Special Needs…
Ambar Susilo Murti
Full Text Available Constitution No. 20 of 2003, concerning Citizenship Education (PKN is a compulsory subject for primary education, secondary, and compulsory subjects for higher education. The purpose of this study is to improve learning outcomes Civics using Active Learning Model Type Question Role Reversal in Class V SDN 4 Doplang Jati district of Blora. This research was a class action (classroom action research. The stages as follows: (1 planning, (2 implementation, (3 observation and (4 reflection. The result of research indicating that students who received grades ≥70 the first cycle increased by 25% from the initial 44% to 69%. Then students who scored ≥70 on the second cycle increased 28% to 97%. The average value of the first cycle increased by 8.75% from 66.53 into 75.28 early in the first cycle and then the second cycle of the average value increased again by 10.97% to 86.25. Researchers suggest teachers should encourage students to be more daring in expressing opinions, questions and ideas that are not held only in Civics alone but on other subjects. In addition, teachers are expected to use active learning model of the type of role reversal question in improving student learning outcomes in other subjects. As for the school is expected to provide training to teachers on implementing learning activities are innovative and creative. Keywords: active learning, civic education, learning outcomes.
Boulton-Lewis, Gillian M.; Buys, Laurie; Lovie-Kitchin, Jan
Learning is an important aspect of aging productively. This paper describes results from 2645 respondents (aged from 50 to 74+ years) to a 165-variable postal survey in Australia. The focus is on learning and its relation to work; social, spiritual, and emotional status; health; vision; home; life events; and demographic details. Clustering…
Full Text Available Applying the engaging and motivating aspects of video games in non-game contexts is known as gamification. Education can benefit from gamification by improving the learning environment to make it more enjoyable and engaging for students. Factors that influence students’ preference for use of gamification are identified. Students are surveyed on their experiences of playing a gamified quiz, named Quick Quiz, during class. Quick Quiz features several gamification elements such as points, progress bars, leader boards, timers, and charts. Data collected from the survey is analysed using Partial Least Squares. Factors including ‘usefulness’, ‘preference for use’, ‘knowledge improvement’, ‘engagement’, ‘immersion’ and ‘enjoyment’ were found to be significant determinants. Students were found to have a preference for use for gamification in their learning environment.
Wang, Chengxi; Yin, Xueyan; Yang, Lin; Gong, Chengrong; Zheng, Caixia; Yi, Yugen
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.
Beygelzimer, Alina; Hsu, Daniel; Langford, John; Zhang, Tong
We present and analyze an agnostic active learning algorithm that works without keeping a version space. This is unlike all previous approaches where a restricted set of candidate hypotheses is maintained throughout learning, and only hypotheses from this set are ever returned. By avoiding this version space approach, our algorithm sheds the computational burden and brittleness associated with maintaining version spaces, yet still allows for substantial improvements over supervised learning f...
The very stimulating paper  discusses an approach to perception and learning in a large population of living agents. The approach is based on a generalization of kinetic theory methods in which the interactions between agents are described in terms of game theory. Such an approach was already discussed in Ref. [2-4] (see also references therein) in various contexts. The processes of perception and learning are based on the interactions between agents and therefore the general kinetic theory is a suitable tool for modeling them. However the main question that rises is how the perception and learning processes may be treated in the mathematical modeling. How may we precisely deliver suitable mathematical structures that are able to capture various aspects of perception and learning?
Christensen, Hans Peter
Learning is an active process, and in engineering education authentic projects is often used to activate the students and promote learning. However, it is not all activity that leads to deep learning; and in a rapid changing society deep understanding is necessary for life-long learning. Empirical...... findings at DTU question the direct link between high activity and a deep approach to learning. Active learning is important to obtain engineering competencies, but active learning requires more than activity. Feedback and reflection is crucial to the learning process, since new knowledge is built...... on the student’s existing understanding. A model for an active learning process with a double-loop feedback is suggested - the first loop gives the student experience through experimentation, the second conceptual understanding through reflection. Students often miss the second loop, so it is important...
Full Text Available Temporal difference learning models propose phasic dopamine signalling encodes reward prediction errors that drive learning. This is supported by studies where optogenetic stimulation of dopamine neurons can stand in lieu of actual reward. Nevertheless, a large body of data also shows that dopamine is not necessary for learning, and that dopamine depletion primarily affects task performance. We offer a resolution to this paradox based on an hypothesis that dopamine encodes the precision of beliefs about alternative actions, and thus controls the outcome-sensitivity of behaviour. We extend an active inference scheme for solving Markov decision processes to include learning, and show that simulated dopamine dynamics strongly resemble those actually observed during instrumental conditioning. Furthermore, simulated dopamine depletion impairs performance but spares learning, while simulated excitation of dopamine neurons drives reward learning, through aberrant inference about outcome states. Our formal approach provides a novel and parsimonious reconciliation of apparently divergent experimental findings.
FitzGerald, Thomas H B; Dolan, Raymond J; Friston, Karl
Temporal difference learning models propose phasic dopamine signaling encodes reward prediction errors that drive learning. This is supported by studies where optogenetic stimulation of dopamine neurons can stand in lieu of actual reward. Nevertheless, a large body of data also shows that dopamine is not necessary for learning, and that dopamine depletion primarily affects task performance. We offer a resolution to this paradox based on an hypothesis that dopamine encodes the precision of beliefs about alternative actions, and thus controls the outcome-sensitivity of behavior. We extend an active inference scheme for solving Markov decision processes to include learning, and show that simulated dopamine dynamics strongly resemble those actually observed during instrumental conditioning. Furthermore, simulated dopamine depletion impairs performance but spares learning, while simulated excitation of dopamine neurons drives reward learning, through aberrant inference about outcome states. Our formal approach provides a novel and parsimonious reconciliation of apparently divergent experimental findings.
Del Gandio, Jason
For Frey and Palmer (2014), communication activism pedagogy (CAP) "teaches students how to use their communication knowledge and resources (e.g., theories, research methods, pedagogies, and other practices) to work with community members to intervene into and reconstruct unjust discourses in more just ways." The author of this response…
Active learning is generally made by a lecturer in learning face to face. In the face to face learning, lecturer can implement a variety of teaching methods to make students actively involved in learning. This is different from learning that is actuating in e-learning. The main characteristic of e-learning is learning that can take place anytime and anywhere. Special strategies are needed so that lecturer can make students play an active role in the course of e-learning. Research in order to ...
Lombardi, Sara A.; Hicks, Reimi E.; Thompson, Katerina V.; Marbach-Ad, Gili
This study investigated the impact of three commonly used cardiovascular model-assisted activities on student learning and student attitudes and perspectives about science. College students enrolled in a Human Anatomy and Physiology course were randomly assigned to one of three experimental groups (organ dissections, virtual dissections, or…
Due to the performance and certification criteria, complex mechanical systems have to taken into account several constraints, which can be associated with a series of performance functions. Different software are generally used to evaluate such functions, whose computational cost can vary a lot. In conception or reliability analysis, we thus are interested in the identification of the boundaries of the domain where all these constraints are satisfied, at the minimal total computational cost. To this end, the present work proposes an iterative method to maximize the knowledge about these limits while trying to minimize the required number of evaluations of each performance function. This method is based first on Gaussian process surrogate models that are defined on nested sub-spaces, and second, on an original selection criterion that takes into account the computational cost associated with each performance function. After presenting the theoretical basis of this approach, this paper compares its efficiency to alternative methods on an example. - Highlights: • An iterative method to identify the limits of a system is proposed. • The method is based on nested Gaussian process surrogate models. • A new selection criterion that is adapted to the system case is presented. • The interest of the method is illustrated on an analytical example.
Sison , Raymund; Shimura , Masamichi
After identifying essential student modeling issues and machine learning approaches, this paper examines how machine learning techniques have been used to automate the construction of student models as well as the background knowledge necessary for student modeling. In the process, the paper sheds light on the difficulty, suitability and potential of using machine learning for student modeling processes, and, to a lesser extent, the potential of using student modeling techniques in machine le...
Manners, Ian James
-Danish students receive the basic international and intercultural skills and knowledge they need in current society. The English-language masters’ seminars I teach at the Department of Political Science are international in terms of students and teacher, but they are also Active Learning seminars......-Danish students (and sometimes teachers) rarely speak to each other or learn each other’s names. In the international AL spaces I create, students must work together on joint tasks which require interaction to address tasks and integration in order to benefit from the multinational activity groups. Planning AL...... that complete the seminar soon become vocal advocates of international AL. Ultimately, enriching student learning through immersing Danish and international students in an international AL space is, for me, the best way of ensuring an internationalised learning outcome, rather than just international mobility....
Bergen, K.; Beroza, G. C.
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.
Olivia Frances Rivan
Full Text Available The objective of this study is to analyze implementation of SQ4R learning method, students ' active participation and students ' achievement in the subject " Public Administration of Public Relations and Protocol " for students of class XI ADMINISTRATIVE OFFICE 1 at SMK PGRI Turen. This type of research is a Classroom Action Research (CAR. Data collection was done by interview, observation, documentation, test, and field note. The result of the research shows that (1 the implementation of learning goes well, proved by the increase of students ' active participation and students ' achievement, (2 the students ' active participation increased from the percentage of 61% in the circle 1 to 82% in circle 2, (3 Students ' achievement from the cognitive aspect increased from the average of 6.7 in circle 1 to 88.7 on circle 2.
Full Text Available In traditional teaching most of the class time is spent with the professor lecturing and the students watching and listening. The students work individually, and cooperation is discouraged. On the other hand, active learning changes the focus of activity from the teacher to the learners, in which students solve problems, answer questions, formulate questions of their own, discuss, explain, debate during class; moreover, students work in teams on problems and projects under conditions that assure positive interdependence and individual accountability. Although student-centered methods have repeatedly been shown to be superior to the traditional teacher-centered approach to instruction, the literature regarding the efficacy of various teaching methods is inconclusive. The purpose of this study was to compare the student perceptions of course and instructor effectiveness, course difficulty, and amount learned between the active learning and lecture sections in Health Sciences´ courses by statistical data from Anhembi Morumbi University. Results indicated significant difference between active learning and traditional teaching. Our conclusions were that strategies promoting active learning to traditional lectures could increase knowledge and understanding.
Zhang, Lining; Shum, Hubert P H; Shao, Ling
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.
Aarts, F.; Kuppens, H.; Tretmans, J.; Vaandrager, F.; Verwer, S.
Using a well-known industrial case study from the verification literature, the bounded retransmission protocol, we show how active learning can be used to establish the correctness of protocol implementation I relative to a given reference implementation R. Using active learning, we learn a model M
Bagus Addin Hutomo
Full Text Available Abstrak ____________________________________________________________________ Telah dilakukan penelitian yang bertujuan untuk mengetahui pengaruh model active learning berbantuan media flash terhadap pemahaman konsep dan aktivitas belajar siswa pada tema kalor dan perpindahannya. Jenis penelitian ini yaitu quasi experiment dengan desain non-equivalent control group design. Sampel diambil dengan teknik purposive sampling. Sampel dalam penelitian ini adalah kelas VII C (kelas eksperimen dan VII A (kelas kontrol SMPN 1 Ungaran. Data diambil dengan metode tes (pemahaman konsep dan observasi (aktivitas belajar siswa.Hasil penelitian menunjukkan bahwa rata-rata pemahaman konsep (posttest kelas eksperimen (87,22 lebih tinggi dari kelas kontrol (75,83. Besarnya rata-rata aktivitas belajar siswa kelas eksperimen (83,90 juga lebih besar daripada kelas kontrol (76,28. Berdasarkan hasil penelitian dapat disimpulkan model active learning berbantuan media flash pada tema kalor dan perpindahannya berpengaruh positif terhadap pemahaman konsep siswa sebesar 54,06 % dengan nilai koefisen korelasi sebesar 0,74 (kategori kuat dan berpengaruh positif terhadap aktivitas belajar siswa sebesar 85,54 % dengan nilai koefisen korelasi sebesar 0,92 (kategori sangat kuat. Abstract Studies have been conducted to determine the effect of active learning model of flash media aided the understanding of concepts and learning activities of students on the theme of heat and displacement. This type of research is a quasi-experimental design with non-equivalent control group design. The sample was taken by purposive sampling technique. The sample in this research is class VII C (experimental class and VII A (control group SMPN 1 Ungaran. Data taken with test method (understanding of the concept and observation (student activity. The results showed that the average understanding of the concept (posttest experimental class (87.22 higher than the control class (75.83. The average size
Dosher, Barbara; Lu, Zhong-Lin
Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision. Models, especially computational models, play a key role in behavioral and physiological investigations of the mechanisms of perceptual learning and for understanding, predicting, and optimizing human perceptual processes, learning, and performance. Performance improvements resulting from reweighting or readout of sensory inputs to decision provide a strong theoretical framework for interpreting perceptual learning and transfer that may prove useful in optimizing learning in real-world applications.
Dormann, Christian; Demerouti, Eva; Bakker, Arnold; Zlatkin-Troitschanskaia, O.; Wittum, G.; Dengel, A.
This chapter proposes a model of positive and negative learning (PNL model). We use the term negative learning when stress among students occurs, and when knowledge and abilities are not properly developed. We use the term positive learning if motivation is high and active learning occurs. The PNL
Baack, Dominik; Temme, Fabian; Buss, Jens; Noethe, Max; Bruegge, Kai [TU Dortmund, Dortmund (Germany); Collaboration: FACT-Collaboration
Modern Cosmic-Ray experiments need a huge amount of simulated data. In many cases, only a portion of the data is actually needed for following steps in the analysis chain, for example training of different machine learning algorithms. The other parts are thrown away by the trigger simulation of the experiment or so not increase the quality of following analysis steps. In this talk, I present a new developed package for the air shower simulation software CORSIKA. This extension includes different approaches to reduce the amount of unnecessary computation. One approach is a new internal particle stack implementation that allows to priorize the processing of special intermediate shower particles and the removal of not needed shower particles. The second approach is the possibility to sent various information of the initial particle and parameters of the status of the partial simulated event to an external application to approximate the information gain of the current simulator event. If the information gain is to low, the current event simulation gets terminated and all information get stored into a central database. For the Simulation - Server communication a simple network protocol has been developed.
Olivia Frances Rivan; Suharto -; Neny Chuinda
The objective of this study is to analyze implementation of SQ4R learning method, students ' active participation and students ' achievement in the subject " Public Administration of Public Relations and Protocol " for students of class XI ADMINISTRATIVE OFFICE 1 at SMK PGRI Turen. This type of research is a Classroom Action Research (CAR). Data collection was done by interview, observation, documentation, test, and field note. The result of the research shows that (1) the implementation of l...
Full Text Available This data article contains supporting information regarding the research article entitled “Traumatic brain injury accelerates amyloid-β deposition and impairs spatial learning in the triple-transgenic mouse model of Alzheimer׳s disease” (H. Shishido, Y. Kishimoto, N. Kawai, Y. Toyota, M. Ueno, T. Kubota, Y. Kirino, T. Tamiya, 2016 . Triple-transgenic (3×Tg-Alzheimer׳s disease (AD model mice exhibited significantly poorer spatial learning than sham-treated 3×Tg-AD mice 28 days after traumatic brain injury (TBI. Correspondingly, amyloid-β (Aβ deposition within the hippocampus was significantly greater in 3×Tg-AD mice 28 days after TBI. However, data regarding the short-term and long-term influences of TBI on amyloid precursor protein (APP accumulation in AD model mice remain limited. Furthermore, there is little data showing whether physical activity and motor learning are affected by TBI in AD model mice. Here, we provide immunocytochemistry data confirming that TBI induces significant increases in APP accumulation in 3×Tg-AD mice at both 7 days and 28 days after TBI. Furthermore, 3×Tg-AD model mice exhibit a reduced ability to acquire conditioned responses (CRs during delay eyeblink conditioning compared to sham-treated 3×Tg-AD model mice 28 days after TBI. However, physical activity and motor performance are not significantly changed in TBI-treated 3×Tg-AD model mice.
Christensen, Henrik Bærbak; Corry, Aino Vonge
Traditional lecture-based courses are widely criticised for be- ing less eective in teaching. The question is of course what should replace the lectures and various active learning tech- niques have been suggested and studied. In this paper, we report on our experiences of redesigning a software ......- tive seminars as a replacement of traditional lectures, an activity template for the contents of active seminars, an ac- count on how storytelling supported the seminars, as well as reports on our and the students' experiences....
Baroni, Pietro; Fogli, Daniela; Guida, Giovanni
This paper aims at laying down the foundations of a new approach to learning in autonomous mobile robots. It is based on the assumption that robots can be provided with built-in action plans and with mechanisms to modify and improve such plans. This requires that robots are equipped with some form of high-level reasoning capabilities. Therefore, the proposed learning technique is embedded in a novel distributed control architecture featuring an explicit model of robot's cognitive activity. In particular, cognitive activity is obtained by the interaction of active mental entities, such as intentions, persuasions and expectations. Learning capabilities are implemented starting from the interaction of such mental entities. The proposal is illustrated through an example concerning a robot in charge of reaching a target in an unknown environment cluttered with obstacles
Dewey, Kenneth F.; Meyer, Steven J.
Introduces a software package available for the climatology curriculum that determines possible climatic events according to a long-term climate history. Describes the integration of the software into the curriculum and presents examples of active learning. (Contains 19 references.) (YDS)
This learning activity package on oral hygiene is one of a series of 12 titles developed for use in health occupations education programs. Materials in the package include objectives, a list of materials needed, a list of definitions, information sheets, reviews (self evaluations) of portions of the content, and answers to reviews. These topics…
Castro, R.M.; Nowak, R.; Bshouty, N.H.; Gentile, C.
This paper aims to shed light on achievable limits in active learning. Using minimax analysis techniques, we study the achievable rates of classification error convergence for broad classes of distributions characterized by decision boundary regularity and noise conditions. The results clearly
Full Text Available This paper discusses a project carried out with thirty six final year undergraduate students, studying the Bachelor of Science in Business and Management and taking the module Small Business Management during the academic year 2012 and 2013 in Dublin Institute of Technology. The research had two separate objectives, 1 to engage in active learning by having students work on a consulting project in groups for a real life business and 2 to improve student learning. The Small Business Management previously had a group assignment that was to choose an article related to entrepreneurship and critic it and present it to the class. Anecdotally, from student feedback, it was felt that this process did not engage students and also did not contribute to the key competencies necessary in order to be an entrepreneur. The desire was for students on successful completion of this module to have better understood how business is conducted and equip them with core skills such as innovation, critical thinking, problem solving and decision making .Student buy in was achieved by getting the students to select their own groups and also work out between each group from a one page brief provided by the businesses which business they would like to work with. It was important for the businesses to also feel their time spent with students was worthwhile so they were presented with a report from the students at the end of the twelve weeks and invited into the College to hear the presentations from students. Students were asked to provide a reflection on their three key learning points from the assignment and to answer specific questions designed to understand what they learnt and how and their strengths and weaknesses. A survey was sent to the businesses that took part to understand their experiences. The results were positive with student engagement and learning rating very highly and feedback from the businesses demonstrated an appreciation of having a different
Wagstaff, Kiri; Mazzoni, Dominic
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
Gubaev, Konstantin; Podryabinkin, Evgeny V.; Shapeev, Alexander V.
In recent years, the machine learning techniques have shown great potent1ial in various problems from a multitude of disciplines, including materials design and drug discovery. The high computational speed on the one hand and the accuracy comparable to that of density functional theory on another hand make machine learning algorithms efficient for high-throughput screening through chemical and configurational space. However, the machine learning algorithms available in the literature require large training datasets to reach the chemical accuracy and also show large errors for the so-called outliers—the out-of-sample molecules, not well-represented in the training set. In the present paper, we propose a new machine learning algorithm for predicting molecular properties that addresses these two issues: it is based on a local model of interatomic interactions providing high accuracy when trained on relatively small training sets and an active learning algorithm of optimally choosing the training set that significantly reduces the errors for the outliers. We compare our model to the other state-of-the-art algorithms from the literature on the widely used benchmark tests.
Yew, Tee Meng; Dawood, Fauziah K. P.; a/p S. Narayansany, Kannaki; a/p Palaniappa Manickam, M. Kamala; Jen, Leong Siok; Hoay, Kuan Chin
When students and teachers behave in ways that reinforce learning as a spectator sport, the result can often be a classroom and overall learning environment that is mostly limited to transmission of information and rote learning rather than deep approaches towards meaningful construction and application of knowledge. A group of college instructors…
Du, Bo; Wang, Zengmao; Zhang, Lefei; Zhang, Liangpei; Liu, Wei; Shen, Jialie; Tao, Dacheng
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.
Shengqiang Chen; Xuegang Luo; Quan Yang; Weiwen Sun; Kaiyi Cao; Xi Chen; Yueling Huang; Lijun Dai; Yonghong Yi
In the present study, Fmr1 knockout mice (KO mice) were used as the model for fragile X syndrome. The results of step-through and step-down tests demonstrated that Fmr1 KO mice had shorter latencies and more error counts, indicating a learning and memory disorder. After treatment with 30, 60, 90, 120, or 200 mg/kg lithium chloride, the learning and memory abilities of the Fmr1 KO mice were significantly ameliorated, in particular, the 200 mg/kg lithium chloride treatment had the most significant effect. Western blot analysis showed that lithium chloride significantly enhanced the expression of phosphorylated glycogen synthase kinase 3 beta, an inactive form of glycogen synthase kinase 3 beta, in the cerebral cortex and hippocampus of the Fmr1 KO mice. These results indicated that lithium chloride improved learning and memory in the Fmr1 KO mice, possibly by inhibiting glycogen synthase kinase 3 beta activity.
Garina, D V; Mekhtiev, A A
Effect of serotonin-modulated anticonsolidation protein (SMAP) that has property of disturbing formation of memory trace in mammals and of learning and memory in teleost fish was studied in the model of active avoidance learning. The experiment was performed in three stages: (1) fry of carps Cyprinus carpio L. was injected intracerebrovenricularly with the SMAP protein at a dose of 0.3 μg/g; control individuals were administered with equal amount of the buffered saline for poikilothermic animals; (2) 24 h after the injection, fish were learnt during 8 sèances for 2 days the conditioned reflex of active avoidance; (3) 48 h after the learning the testing of the skill was performed. The administration of the protein was shown to lead to disturbance of reproduction of the skill in the fish: the latent time of the skill reproduction in experimental individuals exceeded that in control fish more than two times, while the number of individuals succeeding the task in the experimental group was non-significantly lower than in the control group. However, unlike mammals, injection of the SMAP protein in this model produced no effect on the process of learning in carps. Thus, there was first demonstrated the inhibiting effect of the SMAP protein whose concentration correlated positively with the content of the neurotransmitter serotonin in brain on consolidation of memory traces in teleost fish.
Everly, Marcee C
To report the transformation from lecture to more active learning methods in a maternity nursing course and to evaluate whether student perception of improved learning through active-learning methods is supported by improved test scores. The process of transforming a course into an active-learning model of teaching is described. A voluntary mid-semester survey for student acceptance of the new teaching method was conducted. Course examination results, from both a standardized exam and a cumulative final exam, among students who received lecture in the classroom and students who had active learning activities in the classroom were compared. Active learning activities were very acceptable to students. The majority of students reported learning more from having active-learning activities in the classroom rather than lecture-only and this belief was supported by improved test scores. Students who had active learning activities in the classroom scored significantly higher on a standardized assessment test than students who received lecture only. The findings support the use of student reflection to evaluate the effectiveness of active-learning methods and help validate the use of student reflection of improved learning in other research projects. Copyright © 2011 Elsevier Ltd. All rights reserved.
McConell, David A.; Chapman, LeeAnna; Czaijka, C. Douglas; Jones, Jason P.; Ryker, Katherine D.; Wiggen, Jennifer
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…
National Aeronautics and Space Administration — IMPROVING CAUSE DETECTION SYSTEMS WITH ACTIVE LEARNING ISAAC PERSING AND VINCENT NG Abstract. Active learning has been successfully applied to many natural language...
Beichner, Robert J.
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.
Text classification approaches are used extensively to solve real-world challenges. The success or failure of text classification systems hangs on the datasets used to train them, without a good dataset it is impossible to build a quality system. This thesis examines the applicability of active learning in text classification for the rapid and economical creation of labelled training data. Four main contributions are made in this thesis. First, we present two novel selection strategies to cho...
Linsky, J. L.
Progress in understanding active dwarf stars based on recent IUE, Einstein, and ground-based observations is reviewed. The extent of magnetic field control over nonflare phenomena in active dwarf stars is considered, and the spatial homogeneity and time variability of active dwarf atmospheres is discussed. The possibility that solar like flux tubes can explain enhanced heating in active dwarf stars in examined, and the roles of systematic flows in active dwarf star atmospheres are considered. The relation between heating rates in different layers of active dwarf stars is summarized, and the mechanism of chromosphere and transition region heating in these stars are discussed. The results of one-component and two-component models of active dwarf stars are addressed.
Bishop, Christopher M
Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.
Khoiriyah, U.; Roberts, C.; Jorm, C.; Vleuten, C.P. van der
BACKGROUND: 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
Bi, Weihong; Fu, Guangwei; Fu, Xinghu; Zhang, Baojun; Liu, Qiang; Jin, Wa
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.
Haruno, M; Wolpert, D M; Kawato, M
Humans demonstrate a remarkable ability to generate accurate and appropriate motor behavior under many different and often uncertain environmental conditions. We previously proposed a new modular architecture, the modular selection and identification for control (MOSAIC) model, for motor learning and control based on multiple pairs of forward (predictor) and inverse (controller) models. The architecture simultaneously learns the multiple inverse models necessary for control as well as how to select the set of inverse models appropriate for a given environment. It combines both feedforward and feedback sensorimotor information so that the controllers can be selected both prior to movement and subsequently during movement. This article extends and evaluates the MOSAIC architecture in the following respects. The learning in the architecture was implemented by both the original gradient-descent method and the expectation-maximization (EM) algorithm. Unlike gradient descent, the newly derived EM algorithm is robust to the initial starting conditions and learning parameters. Second, simulations of an object manipulation task prove that the architecture can learn to manipulate multiple objects and switch between them appropriately. Moreover, after learning, the model shows generalization to novel objects whose dynamics lie within the polyhedra of already learned dynamics. Finally, when each of the dynamics is associated with a particular object shape, the model is able to select the appropriate controller before movement execution. When presented with a novel shape-dynamic pairing, inappropriate activation of modules is observed followed by on-line correction.
Maurer, Todd J; Weiss, Elizabeth M; Barbeite, Francisco G
Eight hundred employees from across the U.S. work force participated in a detailed 13-month longitudinal study of involvement in learning and development activities. A new model was posited and tested in which the hypothesized sequence was as follows: worker age --> individual and situational antecedents --> perceived benefits of participation and self-efficacy for development --> attitudes toward development --> intentions to participate --> participation. The results depict a person who is oriented toward employee development as having participated in development activities before, perceiving themselves as possessing qualities needed for learning, having social support for development at work and outside of work, being job involved, having insight into his or her career, and believing in the need for development, in his or her ability to develop skills and to receive intrinsic benefits from participating. Given the aging work force, a detailed treatment of age differences in development is presented. Implications for new ideas in practice and future research are discussed.
Hussein, Bassam A.
The paper demonstrates and evaluates the effectiveness of a blended learning approach to create a meaningful learning environment. We use the term blended learning approach in this paper to refer to the use of multiple or hybrid instructional methods that emphasize the role of learners as contributors to the learning process rather than recipients…
The article "Socio-political development of private school children mobilising for disadvantaged others" by Darren Hoeg, Natalie Lemelin, and Lawrence Bencze described a language-learning curriculum that drew on elements of Socioscientific issues and Science, Technology, Society and Environment. Results showed that with a number of enabling factors acting in concert, learning about and engagement in practical action for social justice and equity are possible. An alternative but highly compatible framework is now introduced—phronetic social research—as an action-oriented, wisdom-seeking research stance for the social sciences. By so doing, it is hoped that forms of phronetic social research can gain wider currency among those that promote activism as one of many valued outcomes of an education in science.
Policymakers and education scholars recommend incorporating mathematical modeling into mathematics education. Limited implementation of modeling instruction in schools, however, has constrained research on how students learn to model, leaving unresolved debates about whether modeling should be reified and explicitly taught as a competence, whether…
Vos, Henk; de Graaff, E.
The reasons to introduce formats of Active Learning in Engineering (ALE) like 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
Full Text Available ABSTRACT The learning model is one of the enabling factors that influence the achievement of students. That students have a good learning outcomes the lecturer must choose appropriate learning models. But in fact not all lecturers choose the most appropriate learning model with the demands of learning outcomes and student characteristics.The study design was descriptive quantitative correlation. Total population of 785 the number of samples are 202 were taken by purposive sampling. Techniques of data collection is done by cross-sectional and then processed through the Spearman test. The results showed no significant relationship between classroom lecture method in the context of blended learning models to study the effectiveness perspective the p value of 0.001. There is a significant relationship between e-learning methods in the context of blended learning models with perspective of activities study of nursing students the p value of 0.028. There is a significant relationship between learning model of blended learning with the perspective of nursing students learning effectiveness p value 0.167. Researchers recommend to future researchers conduct more research on the comparison between the effectiveness of the learning model based on student learning centers with the e-learning models and its impact on student achievement of learning competencies as well as to the implications for other dimensions of learning outcomes and others.
Brdiczka, Oliver; Crowley, James L; Reignier, Patrick
This paper addresses the problem of learning situation models for providing context-aware services. Context for modeling human behavior in a smart environment is represented by a situation model describing environment, users, and their activities. A framework for acquiring and evolving different layers of a situation model in a smart environment is proposed. Different learning methods are presented as part of this framework: role detection per entity, unsupervised extraction of situations from multimodal data, supervised learning of situation representations, and evolution of a predefined situation model with feedback. The situation model serves as frame and support for the different methods, permitting to stay in an intuitive declarative framework. The proposed methods have been integrated into a whole system for smart home environment. The implementation is detailed, and two evaluations are conducted in the smart home environment. The obtained results validate the proposed approach.
Lombardi, Sara A; Hicks, Reimi E; Thompson, Katerina V; Marbach-Ad, Gili
This study investigated the impact of three commonly used cardiovascular model-assisted activities on student learning and student attitudes and perspectives about science. College students enrolled in a Human Anatomy and Physiology course were randomly assigned to one of three experimental groups (organ dissections, virtual dissections, or plastic models). Each group received a 15-min lecture followed by a 45-min activity with one of the treatments. Immediately after the lesson and then 2 mo later, students were tested on anatomy and physiology knowledge and completed an attitude survey. Students who used plastic models achieved significantly higher overall scores on both the initial and followup exams than students who performed organ or virtual dissections. On the initial exam, students in the plastic model and organ dissection treatments scored higher on anatomy questions than students who performed virtual dissections. Students in the plastic model group scored higher than students who performed organ dissections on physiology questions. On the followup exam, when asked anatomy questions, students in the plastic model group scored higher than dissection students and virtual dissection students. On attitude surveys, organ dissections had higher perceived value and were requested for inclusion in curricula twice as often as any other activity. Students who performed organ dissections were more likely than the other treatment groups to agree with the statement that "science is fun," suggesting that organ dissections may promote positive attitudes toward science. The findings of this study provide evidence for the importance of multiple types of hands-on activities in anatomy laboratory courses.
Blake, Tim K
Journaling is a method frequently discussed in nursing literature and educational literature as an active learning technique that is meant to enhance reflective practice. Reflective practice is a means of self-examination that involves looking back over what has happened in practice in an effort to improve, or encourage professional growth. Some of the benefits of reflective practice include discovering meaning, making connections between experiences and the classroom, instilling values of the profession, gaining the perspective of others, reflection on professional roles, and development of critical thinking. A review of theory and research is discussed, as well as suggestions for implementation of journaling into coursework.
Friston, Karl J; Daunizeau, Jean; Kiebel, Stefan J
This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain.
Karl J Friston
Full Text Available This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain.
Kurilovas, Eugenijus; Juskeviciene, Anita; Bireniene, Virginija
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…
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…
Full Text Available The present research aims at presenting a conceptual model for effective distance learning in higher education. Findings of this research shows that an understanding of the technological capabilities and learning theories especially constructive theory and independent learning theory and communicative and interaction theory in Distance learning is an efficient factor in the planning of effective Distance learning in higher education. Considering the theoretical foundations of the present research, in the effective distance learning model, the learner is situated at the center of learning environment. For this purpose, the learner needs to be ready for successful learning and the teacher has to be ready to design the teaching- learning activities when they initially enter the environment. In the present model, group and individual active teaching-learning approach, timely feedback, using IT and eight types of interactions have been designed with respect to theoretical foundations and current university missions. From among the issues emphasized in this model, one can refer to the Initial, Formative and Summative evaluations. In an effective distance learning environment, evaluation should be part of the learning process and the feedback resulting from it should be used to improve learning. For validating the specified features, the opinions of Distance learning experts in Payame Noor, Shiraz, Science and Technology and Amirkabir Universities have been used which verified a high percentage of the statistical sample of the above mentioned features.
Kumar, Sonia; McLean, Loyola; Nash, Louise; Trigwell, Keith
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.
King, D. B.; Lewis, J. E.; Anderson, K.; Latch, D.; Sutheimer, S.; Webster, G.; Moog, R.
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
Bell, Thorsten; Urhahne, Detlef; Schanze, Sascha; Ploetzner, Rolf
Collaborative inquiry learning is one of the most challenging and exciting ventures for today's schools. It aims at bringing a new and promising culture of teaching and learning into the classroom where students in groups engage in self-regulated learning activities supported by the teacher. It is expected that this way of learning fosters students' motivation and interest in science, that they learn to perform steps of inquiry similar to scientists and that they gain knowledge on scientific processes. Starting from general pedagogical reflections and science standards, the article reviews some prominent models of inquiry learning. This comparison results in a set of inquiry processes being the basis for cooperation in the scientific network NetCoIL. Inquiry learning is conceived in several ways with emphasis on different processes. For an illustration of the spectrum, some main conceptions of inquiry and their focuses are described. In the next step, the article describes exemplary computer tools and environments from within and outside the NetCoIL network that were designed to support processes of collaborative inquiry learning. These tools are analysed by describing their functionalities as well as effects on student learning known from the literature. The article closes with challenges for further developments elaborated by the NetCoIL network.
Zhang, Suyi; Mano, Hiroaki; Lee, Michael; Yoshida, Wako; Kawato, Mitsuo; Robbins, Trevor W; Seymour, Ben
Tonic pain after injury characterises a behavioural state that prioritises recovery. Although generally suppressing cognition and attention, tonic pain needs to allow effective relief learning to reduce the cause of the pain. Here, we describe a central learning circuit that supports learning of relief and concurrently suppresses the level of ongoing pain. We used computational modelling of behavioural, physiological and neuroimaging data in two experiments in which subjects learned to terminate tonic pain in static and dynamic escape-learning paradigms. In both studies, we show that active relief-seeking involves a reinforcement learning process manifest by error signals observed in the dorsal putamen. Critically, this system uses an uncertainty ('associability') signal detected in pregenual anterior cingulate cortex that both controls the relief learning rate, and endogenously and parametrically modulates the level of tonic pain. The results define a self-organising learning circuit that reduces ongoing pain when learning about potential relief. © 2018, Zhang et al.
Mano, Hiroaki; Lee, Michael; Yoshida, Wako; Kawato, Mitsuo; Robbins, Trevor W
Tonic pain after injury characterises a behavioural state that prioritises recovery. Although generally suppressing cognition and attention, tonic pain needs to allow effective relief learning to reduce the cause of the pain. Here, we describe a central learning circuit that supports learning of relief and concurrently suppresses the level of ongoing pain. We used computational modelling of behavioural, physiological and neuroimaging data in two experiments in which subjects learned to terminate tonic pain in static and dynamic escape-learning paradigms. In both studies, we show that active relief-seeking involves a reinforcement learning process manifest by error signals observed in the dorsal putamen. Critically, this system uses an uncertainty (‘associability’) signal detected in pregenual anterior cingulate cortex that both controls the relief learning rate, and endogenously and parametrically modulates the level of tonic pain. The results define a self-organising learning circuit that reduces ongoing pain when learning about potential relief. PMID:29482716
Scarpetta, Silvia; Li, Zhaoping; Hertz, John
We study a model of generalized-Hebbian learning in asymmetric oscillatory neural networks modeling cortical areas such as hippocampus and olfactory cortex. The learning rule is based on the synaptic plasticity observed experimentally, in particular long-term potentiation and long-term depression of the synaptic efficacies depending on the relative timing of the pre- and postsynaptic activities during learning. The learned memory or representational states can be encoded by both the amplitude and the phase patterns of the oscillating neural populations, enabling more efficient and robust information coding than in conventional models of associative memory or input representation. Depending on the class of nonlinearity of the activation function, the model can function as an associative memory for oscillatory patterns (nonlinearity of class II) or can generalize from or interpolate between the learned states, appropriate for the function of input representation (nonlinearity of class I). In the former case, simulations of the model exhibits a first order transition between the "disordered state" and the "ordered" memory state.
Kholghi, Mahnoosh; Sitbon, Laurianne; Zuccon, Guido; Nguyen, Anthony
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: email@example.com.
Myers, Catherine E.; Smith, Ian M.; Servatius, Richard J.; Beck, Kevin D.
Avoidance behaviors, in which a learned response causes omission of an upcoming punisher, are a core feature of many psychiatric disorders. While reinforcement learning (RL) models have been widely used to study the development of appetitive behaviors, less attention has been paid to avoidance. Here, we present a RL model of lever-press avoidance learning in Sprague-Dawley (SD) rats and in the inbred Wistar Kyoto (WKY) rat, which has been proposed as a model of anxiety vulnerability. We focus on “warm-up,” transiently decreased avoidance responding at the start of a testing session, which is shown by SD but not WKY rats. We first show that a RL model can correctly simulate key aspects of acquisition, extinction, and warm-up in SD rats; we then show that WKY behavior can be simulated by altering three model parameters, which respectively govern the tendency to explore new behaviors vs. exploit previously reinforced ones, the tendency to repeat previous behaviors regardless of reinforcement, and the learning rate for predicting future outcomes. This suggests that several, dissociable mechanisms may contribute independently to strain differences in behavior. The model predicts that, if the “standard” inter-session interval is shortened from 48 to 24 h, SD rats (but not WKY) will continue to show warm-up; we confirm this prediction in an empirical study with SD and WKY rats. The model further predicts that SD rats will continue to show warm-up with inter-session intervals as short as a few minutes, while WKY rats will not show warm-up, even with inter-session intervals as long as a month. Together, the modeling and empirical data indicate that strain differences in warm-up are qualitative rather than just the result of differential sensitivity to task variables. Understanding the mechanisms that govern expression of warm-up behavior in avoidance may lead to better understanding of pathological avoidance, and potential pathways to modify these processes. PMID
The rapid progress in understanding active dwarf stars, which has been stimulated by recent IUE, Einstein and ground-based observations, is reviewed. Active phenomena in late-type dwarf stars are seen as somehow a direct consequence of strong magnetic fields. The nonflare phenomena in the chromosphere and transition regions of these stars are discussed, while some suggestions are given about the way in which magnetic fields control these phenomena. Especially, the review deals with a description and comparison of those activities which are similar in active and quiescent dwarf stars and summarizes the various roles which magnetic fields likely play in modifying the chromospheres and transition regions of active stars. Successively, the following subjects are discussed: the basic structure of the stars, the enhanced heating and solar-like flux tubes, the consequences of plasma flows, heating rates in different layers, heating mechanism of chromosphere and transition region, semi-empirical models. The author finishes with some suggestions for future work. (G.J.P.)
Judit Vidiella Pagés
Full Text Available This article begins with an analysis of some theoretical contributions about the conceptualization of body in contemporary societies. These allow us to set a dialogue with the reflective experiences of a group of teenagers about how they learn masculinitiesi in their lives. Phenomenological and political emphasis on the body carried out by Feminists -with the notion of embodiment- have been essential in giving complexity to embodied issues such as gender, race, age, social class (disabilities, etc. which not only operate in a relation of power in our selves, but also as a locus of resistance and agency. Queer theory and its deconstruction of normative sexuality -with the concept of performativity- will be basic to understand the fundamental role that sexuality has in the construction of subjectivities. The accounts of teens will allow us to explore the paper that physical activities and sport have in their lives as mediators in the construction of their "masculine" subjectivities, many times as an oppressor space of their sexual and gender identity, and open an analysis of the hegemonic body representations that mediate not only physical education in schools, but also sport of competition and elite, and their representations in mass media.
Nesbit, Kathryn C; Jensen, Gail M; Delany, Clare
The purpose of this case report is to explore the active engagement model as a tool to illuminate the ethical reflections of student physical therapists in the context of service learning in a developing country. The study participants were a convenience sample of six students. The study design is a case report using a phenomenological perspective. Data were collected from students' narrative writing and semi-structured interviews. The steps of the active engagement model provided the structural framework for student responses. The analysis process included open coding, selective coding, and member checking. Results showed the emergence of two main themes: 1) gathering rich detail and 2) developing independent moral identity. Students' descriptions of their relationships were detailed and included explanations about the complexities of the sociocultural context. Independent and deliberate agency was evident by the students' preparedness to be collaborative, to raise ethical questions, to identify ethically important aspects of their practice and to describe their professional roles. The students noted that the use of the model increased their engagement in the ethical decision-making process and their recognition of ethical questions. This case report illustrates attributes of the active engagement model which have implications for teaching ethical reflection: scaffolding for ethical reflection, use of narrative for reflection, reflection in action, and illumination of relevant themes. Each of these attributes leads to the development of meaningful ethical reflection. The attributes of this model shown by this case report have potential applications to teaching ethical reflection.
Chen, Yukun; Cao, Hongxin; Mei, Qiaozhu; Zheng, Kai; Xu, Hua
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
Chen, Yukun; Cao, Hongxin; Mei, Qiaozhu; Zheng, Kai; Xu, Hua
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.
Beard, Bettina L.; Ahumada, Albert J., Jr.; Trejo, Leonard (Technical Monitor)
Our learning model has memory templates representing the target-plus-noise and noise-alone stimulus sets. The best correlating template determines the response. The correlations and the feedback participate in the additive template updating rule. The model can predict the relative thresholds for detection in random, fixed and twin noise.
of organizational transition, and 3) demonstrating the efficacy of the model by using it to explain empirical research findings. It is argued that learning new cultural currency involves the use of active intelligence to locate and answer relevant questions, and further that this process requires the interplay......This paper addresses the problem of resistance to attempted changes in organizational culture, particularly those involving diversity, by 1) identifying precisely what is meant by organizational as opposed to societal culture, 2) developing a theoretical model of learning useful in contexts...... is useful for both management and labor in regulating transition processes, thus making a contribution to industrial relations....
Sogawa, Yasuhiro; Ueno, Tsuyoshi; Kawahara, Yoshinobu; Washio, Takashi
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.
Bartholomew, John B; Jowers, Esbelle M; Roberts, Gregory; Fall, Anna-Mária; Errisuriz, Vanessa L; Vaughn, Sharon
Given the need to find more opportunities for physical activity within the elementary school day, this study was designed to asses the impact of I-CAN!, active lessons on: 1) student physical activity (PA) outcomes via accelerometry; and 2) socioeconomic status (SES), race, sex, body mass index (BMI), or fitness as moderators of this impact. Participants were 2,493 fourth grade students (45.9% male, 45.8% white, 21.7% low SES) from 28 central Texas elementary schools randomly assigned to intervention (n=19) or control (n=9). Multilevel regression models evaluated the effect of I-CAN! on PA and effect sizes were calculated. The moderating effects of SES, race, sex, BMI, and fitness were examined in separate models. Students in treatment schools took significantly more steps than those in control schools (β = 125.267, SE = 41.327, p = .002, d = .44). I-CAN! had a significant effect on MVPA with treatment schools realizing 80% (β = 0.796, SE =0.251, p = .001; d = .38) more MVPA than the control schools. There were no significant school-level differences on sedentary behavior (β = -0.177, SE = 0.824, p = .83). SES, race, sex, BMI, and fitness level did not moderate the impact of active learning on step count and MVPA. Active learning increases PA within elementary students, and does so consistently across demographic sub-groups. This is important as these sub-groups represent harder to reach populations for PA interventions. While these lessons may not be enough to help children reach daily recommendations of PA, they can supplement other opportunities for PA. This speaks to the potential of schools to adopt policy change to require active learning.
Mukala, Patrick; Cerone, Antonio; Turini, Franco
Free\\Libre Open Source Software (FLOSS) environments are increasingly dubbed as learning environments where practical software engineering skills can be acquired. Numerous studies have extensively investigated how knowledge is acquired in these environments through a collaborative learning model that define a learning process. Such a learning…
Ibáñez, María Blanca; Maroto, David; García Rueda, José Jesús; Leony, Derick; Delgado Kloos, Carlos
3D virtual worlds are recognized as collaborative learning environments. However, the underlying technology is not sufficiently mature and the virtual worlds look cartoonish, unlinked to reality. Thus, it is important to enrich them with elements from the real world to enhance student engagement in learning activities. Our approach is to build learning environments where participants can either be in the real world or in its mirror world while sharing the same hybrid space in a collaborative ...
Chen, Wei James; Krajbich, Ian
Models of reinforcement learning (RL) are prevalent in the decision-making literature, but not all behavior seems to conform to the gradual convergence that is a central feature of RL. In some cases learning seems to happen all at once. Limited prior research on these "epiphanies" has shown evidence of sudden changes in behavior, but it remains unclear how such epiphanies occur. We propose a sequential-sampling model of epiphany learning (EL) and test it using an eye-tracking experiment. In the experiment, subjects repeatedly play a strategic game that has an optimal strategy. Subjects can learn over time from feedback but are also allowed to commit to a strategy at any time, eliminating all other options and opportunities to learn. We find that the EL model is consistent with the choices, eye movements, and pupillary responses of subjects who commit to the optimal strategy (correct epiphany) but not always of those who commit to a suboptimal strategy or who do not commit at all. Our findings suggest that EL is driven by a latent evidence accumulation process that can be revealed with eye-tracking data.
Introduction In recent years there have been a raising critique concerning PE as a subject which is more concerned with keeping pupils physically active than insuring that they learn something (Annerstedt, 2008). In Denmark, this issue has been actualized in a new sense. In 2014, a new school...... reform with 45 minutes of daily physical activity was introduced to enhance the pupils’ health, well-being and learning capabilities. Instead of focusing on learning bodily skills, physical activities has become an instrument to improve learning in the academic subjects. Physical activities.......g. Biesta, 2010; Standal, 2015) I will argue that the focus on learning outcome and effects on physical activity has gone too far in order to reach the objectives. If the notion of ‘keeping pupils physically active’ is understood as a representation of the core quality of physical activity, it seems...
Joksimovic, Srecko; Hatala, Marek; Gaševic, Dragan
Teaching and learning in networked settings has attracted significant attention recently. The central topic of networked learning research is human-human and human-information interactions occurring within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach to…
Full Text Available Weather recognition based on outdoor images is a brand-new and challenging subject, which is widely required in many fields. This paper presents a novel framework for recognizing different weather conditions. Compared with other algorithms, the proposed method possesses the following advantages. Firstly, our method extracts both visual appearance features of the sky region and physical characteristics features of the nonsky region in images. Thus, the extracted features are more comprehensive than some of the existing methods in which only the features of sky region are considered. Secondly, unlike other methods which used the traditional classifiers (e.g., SVM and K-NN, we use discriminative dictionary learning as the classification model for weather, which could address the limitations of previous works. Moreover, the active learning procedure is introduced into dictionary learning to avoid requiring a large number of labeled samples to train the classification model for achieving good performance of weather recognition. Experiments and comparisons are performed on two datasets to verify the effectiveness of the proposed method.
Chen, Yingke; Nielsen, Thomas Dyhre
deterministic Markov decision processes from data by actively guiding the selection of input actions. The algorithm is empirically analyzed by learning system models of slot machines, and it is demonstrated that the proposed active learning procedure can significantly reduce the amount of data required...... demanding process, and this shortcoming has motivated the development of algorithms for automatically learning system models from observed system behaviors. Recently, algorithms have been proposed for learning Markov decision process representations of reactive systems based on alternating sequences...... of input/output observations. While alleviating the problem of manually constructing a system model, the collection/generation of observed system behaviors can also prove demanding. Consequently we seek to minimize the amount of data required. In this paper we propose an algorithm for learning...
Romanov, Kalle; Nevgi, Anne
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…
Kholghi, Mahnoosh; Sitbon, Laurianne; Zuccon, Guido; Nguyen, Anthony
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.
Mohamd Hassan Hassan; Jehad Al-Sadi
This paper introduces a new model for m- Learning context adaptation due to the need of utilizing mobile technology in education. Mobile learning; m-Learning for short; in considered to be one of the hottest topics in the educational community, many researches had been done to conceptualize this new form of learning. We are presenting a promising design for a model to adapt the learning content in mobile learning applications in order to match the learner context, preferences and the educatio...
Kitchens, Brent; Means, Tawnya; Tan, Yinliang
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…
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…
Christensen, Hans Peter; Vigild, Martin Etchells; Thomsen, Erik Vilain
Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching. The resulting learning outcome is discussed.......Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching. The resulting learning outcome is discussed....
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…
Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A
Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Sivalingam, Udhayaraj; Wels, Michael; Rempfler, Markus; Grosskopf, Stefan; Suehling, Michael; Menze, Bjoern H.
In this paper, we present a fully automated approach to coronary vessel segmentation, which involves calcification or soft plaque delineation in addition to accurate lumen delineation, from 3D Cardiac Computed Tomography Angiography data. Adequately virtualizing the coronary lumen plays a crucial role for simulating blood ow by means of fluid dynamics while additionally identifying the outer vessel wall in the case of arteriosclerosis is a prerequisite for further plaque compartment analysis. Our method is a hybrid approach complementing Active Contour Model-based segmentation with an external image force that relies on a Random Forest Regression model generated off-line. The regression model provides a strong estimate of the distance to the true vessel surface for every surface candidate point taking into account 3D wavelet-encoded contextual image features, which are aligned with the current surface hypothesis. The associated external image force is integrated in the objective function of the active contour model, such that the overall segmentation approach benefits from the advantages associated with snakes and from the ones associated with machine learning-based regression alike. This yields an integrated approach achieving competitive results on a publicly available benchmark data collection (Rotterdam segmentation challenge).
Wijayanti, R.; Waluya, S. B.; Masrukan
The purpose of this research are (1) to analyze the learning quality of MEAs with MURDER strategy, (2) to analyze students’ mathematical literacy ability based on goal orientation in MEAs learning with MURDER strategy. This research is a mixed method research of concurrent embedded type where qualitative method as the primary method. The data were obtained using the methods of scale, observation, test and interviews. The results showed that (1) MEAs Learning with MURDER strategy on students' mathematical literacy ability is qualified, (2) Students who have mastery goal characteristics are able to master the seven components of mathematical literacy process although there are still two components that the solution is less than the maximum. Students who have performance goal characteristics have not mastered the components of mathematical literacy process with the maximum, they are only able to master the ability of using mathematics tool and the other components of mathematical literacy process is quite good.
Cooper, Terry L.; Sundeen, Richard
The urban studies learning model described in this article was found to increase students' self-esteem, imbue a more flexible and open perspective, contribute to the capacity for self-direction, produce increases on the feeling reactivity, spontaneity, and acceptance of aggression scales, and expand interpersonal competence. (Author/WI)
Kala, Sasikarn; Isaramalai, Sang-Arun; Pohthong, Amnart
Nurse educators are challenged to teach nursing students to become competent professionals, who have both in-depth knowledge and decision-making skills. The use of electronic learning methods has been found to facilitate the teaching-learning process in nursing education. Although learning theories are acknowledged as useful guides to design strategies and activities of learning, integration of these theories into technology-based courses appears limited. Constructivism is a theoretical paradigm that could prove to be effective in guiding the design of electronic learning experiences for the purpose of providing positive outcomes, such as the acquisition of knowledge and decision-making skills. Therefore, the purposes of this paper are to: describe electronic learning, present a brief overview of what is known about the outcomes of electronic learning, discuss constructivism theory, present a model for electronic learning using constructivism, and describe educators' roles emphasizing the utilization of the model in developing electronic learning experiences in nursing education.
Preparing students for a life as active citizens in a democratic society is one of the aims within the Bologna process. The Council of Europe has also stressed the importance of focus on democracy in Higher Education. Higher Education is seen as important to develop a democratic culture among...... students. Teaching democracy should be promoted in lessons and curricula. Creating democratic learning systems in institutions of higher education could be the answer to reaching the aim related to democracy. The Aalborg Model practised at Aalborg University is a learning system which has collaborative...
Caropreso, Edward J.; Haggerty, Mark
Describes an alternative approach to introductory economics based on a cooperative learning model, "Learning Together." Discussion of issues in economics education and cooperative learning in higher education leads to explanation of how to adapt the Learning Together Model to lesson planning in economics. A flow chart illustrates the process for a…
"Problem-based learning" (PBL) is one of an innovative learning model which can provide an active learning to student, include the motivation to achieve showed by student when the learning is in progress. This research is aimed to know: (1) differences of physic learning result for student group which taught by PBL versus expository…
Yu, Shengquan; Yang, Xianmin; Cheng, Gang; Wang, Minjuan
This paper presents a new model for organizing learning resources: Learning Cell. This model is open, evolving, cohesive, social, and context-aware. By introducing a time dimension into the organization of learning resources, Learning Cell supports the dynamic evolution of learning resources while they are being used. In addition, by introducing a…
This paper shows the results of research activities for building the representative model of the learning process in virtual spaces (e-Learning). The formal basis of the model are supported in the analysis of models of learning assessment in virtual spaces and specifically in Dembo´s teaching learning model, the systemic approach to evaluating…
Full Text Available This qualitative ethnographic study examines a collaborative leadership model focused on learning and socially just practices within a change context of a wide educational partnership. The study analyzes a range of perspectives of novice teachers, mentor teachers, teacher educators and district superintendents on leadership and learning. The findings reveal the emergence of a coalition of leaders crossing borders at all levels of the educational system: local school level, district level and teacher education level who were involved in coterminous collaborative learning. Four categories of learning were identified as critical to leading a change in the educational system: learning in professional communities, learning from practice, learning through theory and research and learning from and with leaders. The implications of the study for policy makers as well as for practitioners are to adopt a holistic approach to the educational environment and plan a collaborative learning continuum from initial pre-service programs through professional development learning at all levels.
Yulindar, A.; Setiawan, A.; Liliawati, W.
This study aims to influence the enhancement of problem solving ability before and after learning using Real Engagement in Active Problem Solving (REAPS) model on the concept of heat transfer. The research method used is quantitative method with 35 high school students in Pontianak as sample. The result of problem solving ability of students is obtained through the test in the form of 3 description questions. The instrument has tested the validity by the expert judgment and field testing that obtained the validity value of 0.84. Based on data analysis, the value of N-Gain is 0.43 and the enhancement of students’ problem solving ability is in medium category. This was caused of students who are less accurate in calculating the results of answers and they also have limited time in doing the questions given.
Nur Rokhimah Hanik, Anwari Adi Nugroho
Biology learning especially high plant system courses needs to be applied to active learning centered on the student (Active Learning In Higher Education) to enhance the students' learning activities so that the quality of learning for the better. Outdoor Learning is one of the active learning invites students to learn outside of the classroom by exploring the surrounding environment. This research aims to improve the students' learning activities in the course of high plant systems through t...
Janine E. Trempy
Full Text Available A microbiology course and its corresponding learning activities have been structured according to the Cooperative Learning Model. This course, The World According to Microbes, integrates science, math, engineering, and technology (SMET majors and non-SMET majors into teams of students charged with problem solving activities that are microbial in origin. In this study we describe development of learning activities that utilize key components of Cooperative Learning—positive interdependence, promotive interaction, individual accountability, teamwork skills, and group processing. Assessments and evaluations over an 8-year period demonstrate high retention of key concepts in microbiology and high student satisfaction with the course.
Full Text Available Current hypermedia learning environments do not have a common development basis. Their designers have often used ad-hoc solutions to solve the learning problems they have encountered. However, hypermedia technology can take advantage of employing a theoretical scheme - a model - which takes into account various kinds of learning activities, and solves some of the problems associated with its use in the learning process. The model can provide designers with the tools for creating a hypermedia learning system, by allowing the elements and functions involved in the definition of a specific application to be formally represented.
Falcone, Rossella; Brunamonti, Emiliano; Genovesio, Aldo
We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was app...
Full Text Available In this paper the author offers a practical view of the theory-grounded research on education action. She draws on studies carried out at the Center for Research on Activity, Development and Learning (CRADLE at the University of Helsinki in Finland. In its work, the Center draws on cultural-historical activity theory (CHAT and is well-known for the theory of Expansive Learning and its more practical application called Developmental Work Research (DWR. These approaches are widely used to understand professional learning and have served as a theoreticaland methodological foundation for studies examining change and professional development in various human activities.
Gosselin, Philippe Henri; Cord, Matthieu
Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensions are now being proposed to handle multimedia applications. This paper provides algorithms within a statistical framework to extend active learning for online content-based image retrieval (CBIR). The classification framework is presented with experiments to compare several powerful classification techniques in this information retrieval context. Focusing on interactive methods, active learning strategy is then described. The limitations of this approach for CBIR are emphasized before presenting our new active selection process RETIN. First, as any active method is sensitive to the boundary estimation between classes, the RETIN strategy carries out a boundary correction to make the retrieval process more robust. Second, the criterion of generalization error to optimize the active learning selection is modified to better represent the CBIR objective of database ranking. Third, a batch processing of images is proposed. Our strategy leads to a fast and efficient active learning scheme to retrieve sets of online images (query concept). Experiments on large databases show that the RETIN method performs well in comparison to several other active strategies.
Fernandes , Emmanuel; Madhour , Hend; Wentland Forte , Maia; Miniaoui , Sami
We try in this paper to propose a domain model for both author's and learner's needs concerning learning objects reuse. First of all, we present four key criteria for an efficient authoring tool: adaptive level of granularity, flexibility, integration and interoperability. Secondly, we introduce and describe our six-level Semantic Learning Model (SLM) designed to facilitate multi-level reuse of learning materials and search by defining a multi-layer model for metadata. Finally, after mapping ...
Engel, Susan; Pallas, Josh; Lambert, Sarah
This article demonstrates that the purposeful subject design, incorporating a Model United Nations (MUN), facilitated deep learning and professional skills attainment in the field of International Relations. Deep learning was promoted in subject design by linking learning objectives to Anderson and Krathwohl's (2001) four levels of knowledge or…
Levine, Laura E.; Munsch, Joyce
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.…
The purpose of this paper is to present an overview of how active learning took place in a class containing specific readings,cooperative and collaborative group work, and a writing assignment for college students at a Northern Virginia Community College campus (NVCC). Requisite knowledge, skills, learner characteristics, brain-based learning, and…
Piyaluk Wongsri; Prasart Nuangchalerm
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 students who were organized between socioscientific issues-based learning and conventional learning activities. Approach: The samples used in research we...
Tan, Kean Ming; London, Palma; Mohan, Karthik; Lee, Su-In; Fazel, Maryam; Witten, Daniela
We consider the problem of learning a high-dimensional graphical model in which there are a few hub nodes that are densely-connected to many other nodes. Many authors have studied the use of an ℓ 1 penalty in order to learn a sparse graph in the high-dimensional setting. However, the ℓ 1 penalty implicitly assumes that each edge is equally likely and independent of all other edges. We propose a general framework to accommodate more realistic networks with hub nodes, using a convex formulation that involves a row-column overlap norm penalty. We apply this general framework to three widely-used probabilistic graphical models: the Gaussian graphical model, the covariance graph model, and the binary Ising model. An alternating direction method of multipliers algorithm is used to solve the corresponding convex optimization problems. On synthetic data, we demonstrate that our proposed framework outperforms competitors that do not explicitly model hub nodes. We illustrate our proposal on a webpage data set and a gene expression data set.
Han, Q.; Arentze, T.A.; Timmermans, H.J.P.; Janssens, D.; Wets, G.; Lo, H.P.; Leung, Stephen C.H.; Tan, Susanna M.L.
Activity-based analysis has slowly shifted gear from analysis of daily activity patterns to analysis and modeling of dynamic activity-travel patterns. In this paper, we describe a dynamic model that is concerned with simulating cognitive and affective responses in spatial learning behavior for a
In this technology education activity, students learn the importance of advertising, conduct a day-long survey of advertising strategies, and design and produce a tabletop point-of-purchase advertisement. (JOW)
Christensen, Hans Peter; Vigild, Martin E.; Thomsen, Erik; Szabo, Peter; Horsewell, Andy
Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching. The resulting learning outcome is discussed. Peer Reviewed
Tavoni, Gaia; Balasubramanian, Vijay
We propose a mechanism, rooted in the known anatomy and physiology of the vertebrate olfactory system, by which presentations of rewarded and unrewarded odors lead to formation of odor-valence associations between piriform cortex (PC) and anterior olfactory nucleus (AON) which, in concert with neuromodulators release in the bulb, entrains a direct feedback from the AON representation of valence to a group of mitral cells (MCs). The model makes several predictions concerning MC activity during and after associative learning: (a) AON feedback produces synchronous divergent responses in a localized subset of MCs; (b) such divergence propagates to other MCs by lateral inhibition; (c) after learning, MC responses reconverge; (d) recall of the newly formed associations in the PC increases feedback inhibition in the MCs. These predictions have been confirmed in disparate experiments which we now explain in a unified framework. For cortex, our model further predicts that the response divergence developed during learning reshapes odor representations in the PC, with the effects of (a) decorrelating PC representations of odors with different valences, (b) increasing the size and reliability of those representations, and enabling recall correction and redundancy reduction after learning. Simons Foundation for Mathematical Modeling of Living Systems.
Full Text Available We present our approach on how smart city technologies may enhance the learning process. We have developed the CLIO urban computing system, which invites people to share personal memories and interact the collective city memory. Various educational scenarios and activities were performed exploiting CLIO; in this paper we present the methodology we followed and the experience we gained. Learning has always been the cognitive process of acquiring skills or knowledge, while teachers are often eager to experiment with novel technological means and methods; our aim was to explore the effect that urban computing could have to the learning process. We applied our methodology in the city of Corfu inviting schools to engage their students in learning through the collective city memory while exploiting urban computing. Results from our experience demonstrate the potential of exploiting urban computing in the learning process and the benefits of learning out of the classroom.
Foster, Liam; Boxall, Kathy
Background: People (with and without learning disabilities) are living longer. Demographic ageing creates challenges and the leading policy response to these challenges is "active ageing". "Active" does not just refer to the ability to be physically and economically active, but also includes ongoing social and civic engagement…
Otero, Beatriz; Rodríguez, Eva; Royo, Pablo
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…
Falcone, Rossella; Brunamonti, Emiliano; Genovesio, Aldo
We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was apparent from the first trial of the test phase, confirming the ability of monkeys to learn by vicarious observation of human models.
Full Text Available We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was apparent from the first trial of the test phase, confirming the ability of monkeys to learn by vicarious observation of human models.
Gulbahar, Yasemin; Kalelioglu, Filiz
This article explores the use of proper instructional techniques in online discussions that lead to meaningful learning. The research study looks at the effective use of two instructional techniques within online environments, based on qualitative measures. "Brainstorming" and "Six Thinking Hats" were selected and implemented…
Hoppe, Gabriela; Breitner, Michael H.
E(Electronic)-learning becomes more and more important. Reasons are the paramount importance of knowledge, life-time learning, globalization and mobility. Not all providers of e-learning products succeed in closing the gap between production costs and revenues. Especially in the academic sector e-learning projects suffer more and more from decreasing funding. For many currently active research groups it is essential to market their research results, e. g. e-learning applications, in order to ...
Bolander, Thomas; Gierasimczuk, Nina
In this article we study learnability of fully observable, universally applicable action models of dynamic epistemic logic. We introduce a framework for actions seen as sets of transitions between propositional states and we relate them to their dynamic epistemic logic representations as action...... in the limit (inconclusive convergence to the right action model). We show that deterministic actions are finitely identifiable, while arbitrary (non-deterministic) actions require more learning power—they are identifiable in the limit. We then move on to a particular learning method, i.e. learning via update......, which proceeds via restriction of a space of events within a learning-specific action model. We show how this method can be adapted to learn conditional and unconditional deterministic action models. We propose update learning mechanisms for the afore mentioned classes of actions and analyse...
Full Text Available Historical learning has not reached optimal in the learning process. It is caused by the history teachers’ learning model has not used the innovative learning models. Furthermore, it supported by the perception of students to the history subject because it does not become final exam (UN subject so it makes less improvement and builds less critical thinking in students’ daily learning. This is due to the lack of awareness of historical events and the availability of history books for students and teachers in the library are still lacking. Discovery learning with scientific approach encourages students to solve problems actively and able to improve students' critical thinking skills with scientific approach so student can build scientific thinking include observing, asking, reasoning, trying, and networking Keywords: discovery learning, scientific, critical thinking
Dawadi, Prafulla N; Cook, Diane J; Schmitter-Edgecombe, Maureen
Pervasive computing offers an unprecedented opportunity to unobtrusively monitor behavior and use the large amount of collected data to perform analysis of activity-based behavioral patterns. In this paper, we introduce the notion of an activity curve , which represents an abstraction of an individual's normal daily routine based on automatically-recognized activities. We propose methods to detect changes in behavioral routines by comparing activity curves and use these changes to analyze the possibility of changes in cognitive or physical health. We demonstrate our model and evaluate our change detection approach using a longitudinal smart home sensor dataset collected from 18 smart homes with older adult residents. Finally, we demonstrate how big data-based pervasive analytics such as activity curve-based change detection can be used to perform functional health assessment. Our evaluation indicates that correlations do exist between behavior and health changes and that these changes can be automatically detected using smart homes, machine learning, and big data-based pervasive analytics.
education will be delivered to the current and future force. This thesis examined the salient areas proposed by the ALM and its impact on P2P learning ...The Army Learning Model is the new educational model that develops adaptive leaders in an era of persistent conflict. Life-long, individual
Recent years many universities are involved in development of Massive Open Online Courses (MOOCs). Unfortunately an appropriate didactic model for cooperated network learning is lacking. In this paper we introduce inquiry based learning as didactic model. Students are assumed to ask themselves
Fletcher, Katherine A; Meyer, Mary
Health care employers demand that workers be skilled in clinical reasoning, able to work within complex interprofessional teams to provide safe, quality patient-centered care in a complex evolving system. To this end, there have been calls for radical transformation of nursing education including the development of a baccalaureate generalist nurse. Based on recommendations from the American Association of Colleges of Nursing, faculty concluded that clinical education must change moving beyond direct patient care by applying the concepts associated with designer, manager, and coordinator of care and being a member of a profession. To accomplish this, the faculty utilized a system of focused learning assignments (FLAs) that present transformative learning opportunities that expose students to "disorienting dilemmas," alternative perspectives, and repeated opportunities to reflect and challenge their own beliefs. The FLAs collected in a "Playbook" were scaffolded to build the student's competencies over the course of the clinical experience. The FLAs were centered on the 6 Quality and Safety Education for Nurses competencies, with 2 additional concepts of professionalism and systems-based practice. The FLAs were competency-based exercises that students performed when not assigned to direct patient care or had free clinical time. Each FLA had a lesson plan that allowed the student and faculty member to see the competency addressed by the lesson, resources, time on task, student instructions, guide for reflection, grading rubric, and recommendations for clinical instructor. The major advantages of the model included (a) consistent implementation of structured learning experiences by a diverse teaching staff using a coaching model of instruction; (b) more systematic approach to present learning activities that build upon each other; (c) increased time for faculty to interact with students providing direct patient care; (d) guaranteed capture of selected transformative
Chan, Kevin; Cheung, George; Wan, Kelvin; Brown, Ian; Luk, Green
In understanding how active and blended learning approaches with learning technologies engagement in undergraduate education, current research models tend to undermine the effect of learners' variations, particularly regarding their styles and approaches to learning, on intention and use of learning technologies. This study contributes to further…
Giuseppe Davide Paparo
Full Text Available Can quantum mechanics help us build intelligent learning agents? A defining signature of intelligent behavior is the capacity to learn from experience. However, a major bottleneck for agents to learn in real-life situations is the size and complexity of the corresponding task environment. Even in a moderately realistic environment, it may simply take too long to rationally respond to a given situation. If the environment is impatient, allowing only a certain time for a response, an agent may then be unable to cope with the situation and to learn at all. Here, we show that quantum physics can help and provide a quadratic speedup for active learning as a genuine problem of artificial intelligence. This result will be particularly relevant for applications involving complex task environments.
Full Text Available This article introduces the Learning Activity Design (LEAD framework for the development and implementation of mobile learning activities in primary schools. The LEAD framework draws on methodological perspectives suggested by design-based research and interaction design in the specific field of technology-enhanced learning (TEL. The LEAD framework is grounded in four design projects conducted over a period of six years. It contributes a new understanding of the intricacies and multifaceted aspects of the design-process characterizing the development and implementation of mobile devices (i.e. smart phones and tablets in curricular activities conducted in Swedish primary schools. This framework is intended to provide both designers and researchers with methodological tools that take account of the pedagogical foundations of technologically-based educational interventions, usability issues related to the interaction with the mobile application developed, multiple data streams generated during the design project, multiple stakeholders involved in the design process and sustainability aspects of the mobile learning activities implemented in the school classroom.
Balslev, Daniela; Nielsen, Finn Årup; Frutiger, Sally A.
Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel...... practice-related activity in a fronto-parieto-cerebellar network, in agreement with previous studies of motor learning. These voxels were separated from a group of voxels showing an unspecific time-effect and another group of voxels, whose activation was an artifact from smoothing. Hum. Brain Mapping 15...
Full Text Available In the article, the acute problem of implementation of pedagogical innovations and online technologies into the educational process is analyzed. The article explores the advantages of blended learning as a latter-day educational program in comparison with traditional campus learning. Blended learning is regarded worldwide as the combination of classroom face-to-face sessions with interactive learning opportunities created online. The purpose of the article is to identify blended learning transformational potential impacting students and teachers by ensuring a more personalized learning experience. The concept of blended learning, as a means to enhance foreign language teaching and learning in the classroom during the traditional face-to-face interaction between a teacher and a student, combined with computer-mediated activities, is examined. In the article, the main classification of blended learning models is established. There are four main blended learning models which include both face-to-face instruction time and online learning: Rotation Model, Flex Model, A La Carte Model, and Enriched Virtual Model. Once implemented successfully, a blended model can take advantage of both brick-and-mortar and digital worlds, providing significant benefits for the educational establishments and learners. To integrate any of the blended learning models, a teacher can create online activities that enable learners to explore the topic online at home, and then develop face-to-face interactions to dig deeper into the subject matter at the lesson. The use of blended learning models in order to expand educational opportunities for students while the foreign language acquisition, by increasing the availability and flexibility of education, taking into account student individual learning needs, with some element of student control over time, place and pace, is explored. The realization of blended learning models in regards to age and physiological peculiarities of
Bidarra, José; Rusman, Ellen
This paper proposes a framework to support science education through blended learning, based on a participatory and interactive approach supported by ICT-based tools, called Science Learning Activities Model (SLAM). The study constitutes a work in progress and started as a response to complex
This instructor's packet accompanies the learning activity package (LAP) on oral hygiene. Contents included in the packet are a time sheet, suggested uses for the LAP, an instruction sheet, final LAP reviews, a final LAP review answer key, suggested activities, additional resources (student handouts), student performance checklists for both…
Grant, Shelia I.
This collection of learning activities is intended for use in reinforcing mathematics instruction as it relates to building maintenance. Fifty activity sheets are provided. These are organized into units on the following topics: numeration, adding whole numbers, subtracting whole numbers, multiplying whole numbers, dividing whole numbers,…
This instructor's packet accompanies the learning activity package (LAP) on grooming. Contents included in the packet are a time sheet, suggested uses for the LAP, an instruction sheet, final LAP reviews, a final LAP review answer key, suggested activities, an additional resources list, and student completion cards to issue to students as an…
Activating teaching is an educational concept which is based on active participation of students in the study process. It is becoming an alternative to more typical approach where the teacher will just lecture and the students will take notes. The study described in this paper considers student...... activating teaching methods focusing on those based on knowledge dissemination. The practical aspects of the implemented teaching method are considered, and employed assessment methods and tools are discussed....
The most common form of teaching is still the form where a teacher presents the subject of the lecture to a listening audience. During teaching history this has proved to be an effective way of teaching, however the probability of students being inactive is high and the learning outcome may...... through the same curriculum as usual during a term? • Will Active Learning reduce failure rate? • Will Active Learning give a higher learning outcome than traditional teaching? This paper deals with the results of this experiment, answers the mentioned questions and presents a way to implement Active...
Ramirez, Olga; McCollough, Cherie A.; Diaz, Zulmaris
The following describes a culturally relevant mathematics and science content program implemented by preservice teachers (PSTs) at Family Math/Science Learning Events (FM/SLEs) conducted through two different university programs in south Texas. These experiences are required course activities designed to inform PSTs of the importance of…
Friston, Karl; Herreros, Ivan
This letter offers a computational account of Pavlovian conditioning in the cerebellum based on active inference and predictive coding. Using eyeblink conditioning as a canonical paradigm, we formulate a minimal generative model that can account for spontaneous blinking, startle responses, and (delay or trace) conditioning. We then establish the face validity of the model using simulated responses to unconditioned and conditioned stimuli to reproduce the sorts of behavior that are observed empirically. The scheme's anatomical validity is then addressed by associating variables in the predictive coding scheme with nuclei and neuronal populations to match the (extrinsic and intrinsic) connectivity of the cerebellar (eyeblink conditioning) system. Finally, we try to establish predictive validity by reproducing selective failures of delay conditioning, trace conditioning, and extinction using (simulated and reversible) focal lesions. Although rather metaphorical, the ensuing scheme can account for a remarkable range of anatomical and neurophysiological aspects of cerebellar circuitry-and the specificity of lesion-deficit mappings that have been established experimentally. From a computational perspective, this work shows how conditioning or learning can be formulated in terms of minimizing variational free energy (or maximizing Bayesian model evidence) using exactly the same principles that underlie predictive coding in perception.
Computers are now a major tool in research and development in almost all scientific and technological fields. Despite recent developments, this is far from true for learning environments in schools and most undergraduate studies. This thesis proposes a framework for designing curricula where computers, and computer modelling in particular, are a major tool for learning. The framework, based on research on learning science and mathematics and on computer user interface, assumes that: 1) learning is an active process of creating meaning from representations; 2) learning takes place in a community of practice where students learn both from their own effort and from external guidance; 3) learning is a process of becoming familiar with concepts, with links between concepts, and with representations; 4) direct manipulation user interfaces allow students to explore concrete-abstract objects such as those of physics and can be used by students with minimal computer knowledge. Physics is the science of constructing models and explanations about the physical world. And mathematical models are an important type of models that are difficult for many students. These difficulties can be rooted in the fact that most students do not have an environment where they can explore functions, differential equations and iterations as primary objects that model physical phenomena--as objects-to-think-with, reifying the formal objects of physics. The framework proposes that students should be introduced to modelling in a very early stage of learning physics and mathematics, two scientific areas that must be taught in very closely related way, as they were developed since Galileo and Newton until the beginning of our century, before the rise of overspecialisation in science. At an early stage, functions are the main type of objects used to model real phenomena, such as motions. At a later stage, rates of change and equations with rates of change play an important role. This type of equations
Linton, Debra L.; Farmer, Jan Keith; Peterson, Ernie
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…
Kobza, Stefan; Ferrea, Stefano; Schnitzler, Alfons; Pollok, Bettina; Südmeyer, Martin; Bellebaum, Christian
Feedback to both actively performed and observed behaviour allows adaptation of future actions. Positive feedback leads to increased activity of dopamine neurons in the substantia nigra, whereas dopamine neuron activity is decreased following negative feedback. Dopamine level reduction in unmedicated Parkinson's Disease patients has been shown to lead to a negative learning bias, i.e. enhanced learning from negative feedback. Recent findings suggest that the neural mechanisms of active and observational learning from feedback might differ, with the striatum playing a less prominent role in observational learning. Therefore, it was hypothesized that unmedicated Parkinson's Disease patients would show a negative learning bias only in active but not in observational learning. In a between-group design, 19 Parkinson's Disease patients and 40 healthy controls engaged in either an active or an observational probabilistic feedback-learning task. For both tasks, transfer phases aimed to assess the bias to learn better from positive or negative feedback. As expected, actively learning patients showed a negative learning bias, whereas controls learned better from positive feedback. In contrast, no difference between patients and controls emerged for observational learning, with both groups showing better learning from positive feedback. These findings add to neural models of reinforcement-learning by suggesting that dopamine-modulated input to the striatum plays a minor role in observational learning from feedback. Future research will have to elucidate the specific neural underpinnings of observational learning.
Kilfoil, W. R.
This article looks at the way in which people perceive learning and the impact of these perceptions on teaching methods within the context of learning development in distance education. The context could, in fact, be any type of teaching and learning environment. The point is to balance approaches to teaching and learning depending on student…
Isupova, Olga; Kuzin, Danil; Mihaylova, Lyudmila
Semisupervised and unsupervised systems provide operators with invaluable support and can tremendously reduce the operators' load. In the light of the necessity to process large volumes of video data and provide autonomous decisions, this paper proposes new learning algorithms for activity analysis in video. The activities and behaviors are described by a dynamic topic model. Two novel learning algorithms based on the expectation maximization approach and variational Bayes inference are proposed. Theoretical derivations of the posterior estimates of model parameters are given. The designed learning algorithms are compared with the Gibbs sampling inference scheme introduced earlier in the literature. A detailed comparison of the learning algorithms is presented on real video data. We also propose an anomaly localization procedure, elegantly embedded in the topic modeling framework. It is shown that the developed learning algorithms can achieve 95% success rate. The proposed framework can be applied to a number of areas, including transportation systems, security, and surveillance.
Model of moral cultivation in MTsN Bangunharja done using three methods, classical cultivation methods, extra-curricular activities in the form of religious activities, scouting, sports, and Islamic art, and habituation of morals. Problem base learning models in MTsN Bangunharja applied using the following steps: find the problem, define the…
Anglim, Jeromy; Wynton, Sarah K. A.
The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking…
The introduction of active learning exercises into a traditional lecture has been shown to improve students’ learning. Hands-on learning...opportunities in labs and projects provide are additional tools in the active learning toolbox. This paper presents a series of innovative hands-on active ... learning activities for mechanics of materials topics. These activities are based on a Methodology for Developing Hands-on Active Learning Activities, a
Gusnedi, G.; Ratnawulan, R.; Triana, L.
The purpose of this study is to determine the effect of the use of Integrated Science IPA books Using Networked Learning Model of knowledge competence through improved learning outcomes obtained. The experimental design used is one group pre test post test design to know the results before and after being treated. The number of samples used is one class that is divided into two categories of initial ability to see the improvement of knowledge competence. The sample used was taken from the students of grade VIII SMPN 2 Sawahlunto, Indonesia. The results of this study indicate that most students have increased knowledge competence.
Zoya A. Reshetova
Full Text Available The paper is devoted to the issue of mechanisms of learning for understanding the nature of the human mind. Learning is regarded as a special activity that is important for developing the human mind in a specific cultural and historical setting and indirect activity. The author’s understanding of the ideas developed by the psychological theory of activity for establishing the principles of developing the human mind is highlighted. Interpretation of dialectical connections of brain processes and mind, and also the objective activity that emerges them is provided. According to the activity theory, the causes of the students’ psychological difficulties and the low efficacy of learning within predominant reproductive method or the use of the trial and error method are revealed. Thus, a new understanding of the renowned didactic principles of scientific rigour, accessibility, objectivity, the connection of learning with life and others is offered. The contribution of the psychological theory in organizing and managing the studies, increasing teaching activity and awareness, and the growth of the internal causes of motivation are shown. Particular attention is paid to the issue of intellectual development and creative abilities. The author believes the creative abilities of the student and the way the latter are taught are interconnected. At the same time, the developers and educators should make efforts to develop in the students a systemic orientation in the subject, primarily mastering the method of system analysis. Once the method of system analysis has been mastered, it becomes a general intellectual and developing tool through which activities are organized to solve any teaching problems with whatever type of content and difficulty level. Summing up, the organization and disclosure to the student of the process of learning as an activity with its social, consciously transformative and sense shaping meaning, the conditions of its development
Bruun, Jesper; Johannsen, Bjørn Friis
that students use bodily explorations to construct meaning and understanding from kinaesthetic learning that is relevant to school physics? To answer the question, we employ a semiotics perspective to analyse data from a 1-hour lesson for 8-9th graders which introduced students to kinaesthetic activities, where......?”). The analysis is conducted by searching the data to find episodes that illustrate student activity which can serve as a sign of the object that the ‘experiential gestalt of causation’ is employed in the construction of the intended learning outcome. In essence, we study a chaotic but authentic teaching...
A practical work outlining the theory and practice of using active learning techniques in library settings. It explains the theory of active learning and argues for its importance in our teaching and is illustrated using a large number of examples of techniques that can be easily transferred and used in teaching library and information skills to a range of learners within all library sectors. These practical examples recognise that for most of us involved in teaching library and information skills the one off session is the norm, so we need techniques that allow us to quickly grab and hold our
Full Text Available By using active and participatory methods it is hoped that pupils will not only come to a deeper understanding of the issues involved, but also that their motivation will be heightened. Pupil involvement in their learning is essential. Moreover, by using a variety of teaching techniques, we can help students make sense of the world in different ways, increasing the likelihood that they will develop a conceptual understanding. The teacher must be a good facilitator, monitoring and supporting group dynamics. Modeling is an instructional strategy in which the teacher demonstrates a new concept or approach to learning and pupils learn by observing. In the teaching of biology the didactic materials are fundamental tools in the teaching-learning process. Reading about scientific concepts or having a teacher explain them is not enough. Research has shown that modeling can be used across disciplines and in all grade and ability level classrooms. Using this type of instruction, teachers encourage learning.
Pilachowski, Catherine A.; Morris, Frank
Mao, Hua; Chen, Yingke; Jaeger, Manfred
. The proposed learning algorithm is adapted from algorithms for learning deterministic probabilistic finite automata, and extended to include both probabilistic and nondeterministic transitions. The algorithm is empirically analyzed and evaluated by learning system models of slot machines. The evaluation......Constructing an accurate system model for formal model verification can be both resource demanding and time-consuming. To alleviate this shortcoming, algorithms have been proposed for automatically learning system models based on observed system behaviors. In this paper we extend the algorithm...... on learning probabilistic automata to reactive systems, where the observed system behavior is in the form of alternating sequences of inputs and outputs. We propose an algorithm for automatically learning a deterministic labeled Markov decision process model from the observed behavior of a reactive system...
Sibona, Christopher; Pourreza, Saba; Hill, Stephen
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…
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
Cavanagh, Andrew J.; Aragón, Oriana R.; Chen, Xinnian; Couch, Brian; Durham, Mary; Bobrownicki, Aiyana; Hanauer, David I.; Graham, Mark J.
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
Felisa Irawani Hutabarat
Full Text Available This research aims to know the effect of learning model of inquiry learning results students training material measurement. This type of research is quasi experiment. Sampling done by cluster random sampling by taking 2 classes from grade 9 i.e. class X SCIENCE experiments as a class-B that add up to 35 people and class X SCIENCE-C as control classes that add up to 35 people. The instruments used to find out the results of student learning is the learning outcomes tests have been validated in multiple choice form numbered 15 reserved and activity sheets students. The results of the value obtained 37.71 pretes and postest 70.11. The t-test analysis retrieved thitung greater than ttabel so that it can be concluded no difference due to the influence of the learning model of inquiry learning results students training material measurement.
Full Text Available Recent experimental measurements have demonstrated that spontaneous neural activity in the absence of explicit external stimuli has remarkable spatiotemporal structure. This spontaneous activity has also been shown to play a key role in the response to external stimuli. To better understand this role, we proposed a viewpoint, "memories-as-bifurcations," that differs from the traditional "memories-as-attractors" viewpoint. Memory recall from the memories-as-bifurcations viewpoint occurs when the spontaneous neural activity is changed to an appropriate output activity upon application of an input, known as a bifurcation in dynamical systems theory, wherein the input modifies the flow structure of the neural dynamics. Learning, then, is a process that helps create neural dynamical systems such that a target output pattern is generated as an attractor upon a given input. Based on this novel viewpoint, we introduce in this paper an associative memory model with a sequential learning process. Using a simple hebbian-type learning, the model is able to memorize a large number of input/output mappings. The neural dynamics shaped through the learning exhibit different bifurcations to make the requested targets stable upon an increase in the input, and the neural activity in the absence of input shows chaotic dynamics with occasional approaches to the memorized target patterns. These results suggest that these dynamics facilitate the bifurcations to each target attractor upon application of the corresponding input, which thus increases the capacity for learning. This theoretical finding about the behavior of the spontaneous neural activity is consistent with recent experimental observations in which the neural activity without stimuli wanders among patterns evoked by previously applied signals. In addition, the neural networks shaped by learning properly reflect the correlations of input and target-output patterns in a similar manner to those designed in
Lima, Rui M.; Andersson, Pernille Hammar; Saalman, Elisabeth
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…
Arthurs, Leilani A.; Kreager, Bailey Zo
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.
McCoy, Lise; Pettit, Robin K; Kellar, Charlyn; Morgan, Christine
Background: 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. Methods: 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. Results: 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. Conclusions: 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. PMID:29707649
McCoy, Lise; Pettit, Robin K; Kellar, Charlyn; Morgan, Christine
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.
Gorsev, Gonca; Turkmen, Ugur; Askin, Cihat
In today's world, in order to obtain the information in education, various approaches, methods and devices have been developed. Like many developing countries, e-learning and distance learning (internet based learning) are used today in many areas of education in Turkey. This research aims to contribute to education systems and develop a…
Nielsen, Bjørn Gilbert
. It is proposed that the neural machinery required in such a learning/retrieval mechanism could involve the NMDA receptor, in conjunction with the ability of dendrites to maintain differentially activated regions. In particular, it is suggested that such a parcellation of the dendrite allows the neuron......Differentially activated areas of a dendrite permit the existence of zones with distinct rates of synaptic modification, and such areas can be individually accessed using a reference signal which localizes synaptic plasticity and memory trace retrieval to certain subregions of the dendrite...... to participate in multiple sequences, which can be learned without suffering from the 'wash-out' of synaptic efficacy associated with superimposition of training patterns. This is a biologically plausible solution to the stability-plasticity dilemma of learning in neural networks....
Full Text Available Learning a Bayesian network from a numeric set of data is a challenging task because of dual nature of learning process: initial need to learn network structure, and then to find out the distribution probability tables. In this paper, we propose a machine-learning algorithm based on hill climbing search combined with Tabu list. The aim of learning process is to discover the best network that represents dependences between nodes. Another issue in machine learning procedure is handling numeric attributes. In order to do that, we must perform an attribute discretization pre-processes. This discretization operation can influence the results of learning network structure. Therefore, we make a comparative study to find out the most suitable combination between discretization method and learning algorithm, for a specific data set.
Braun, Kathryn L; Cheang, Michael; Shigeta, Dennis
We describe the development of a 24-hr curriculum for nonclinical direct care workers in elder care that features active-learning strategies and consumer-directed approaches. Our curricular design was based on adult education theory and a survey of 70% of the community's service providers. Training was completed by 88 participants, 90% of whom had no prior formal training in elder care. Questionnaires measured participant knowledge, attitudes, and perceived improvements in understanding, empathy, and skills. A subgroup of participants and employers provided additional feedback through focus groups. Participants significantly improved their scores on knowledge and attitude measures. In addition, direct care workers and employers gave the training high marks and identified ways in which the course helped increase workers' competence, empathy toward elders, and self-esteem. Lack of time and funds for training were two major barriers to broader participation. This active-learning curriculum represents a frugal yet effective way to train current and future direct care workers.
Zhang, Xiao-Yu; Wang, Shupeng; Yun, Xiaochun
In practical machine learning applications, human instruction is indispensable for model construction. To utilize the precious labeling effort effectively, active learning queries the user with selective sampling in an interactive way. Traditional active learning techniques merely focus on the unlabeled data set under a unidirectional exploration framework and suffer from model deterioration in the presence of noise. To address this problem, this paper proposes a novel bidirectional active learning algorithm that explores into both unlabeled and labeled data sets simultaneously in a two-way process. For the acquisition of new knowledge, forward learning queries the most informative instances from unlabeled data set. For the introspection of learned knowledge, backward learning detects the most suspiciously unreliable instances within the labeled data set. Under the two-way exploration framework, the generalization ability of the learning model can be greatly improved, which is demonstrated by the encouraging experimental results.
Khoiriyah, Umatul; Roberts, Chris; Jorm, Christine; Van der Vleuten, C P M
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.
Ramadiani; Rodziah, A.; Hasan, S. M.; Rusli, A.; Noraini, C.
E-learning is not going to work if the system is not used in accordance with user needs. User Interface is very important to encourage using the application. Many theories had discuss about user interface usability evaluation and technology acceptance separately, actually why we do not make it correlation between interface usability evaluation and user acceptance to enhance e-learning process. Therefore, the evaluation model for e-learning interface acceptance is considered important to investigate. The aim of this study is to propose the integrated e-learning user interface acceptance evaluation model. This model was combined some theories of e-learning interface measurement such as, user learning style, usability evaluation, and the user benefit. We formulated in constructive questionnaires which were shared at 125 English Language School (ELS) students. This research statistics used Structural Equation Model using LISREL v8.80 and MANOVA analysis.
Gehret, Austin U.; Elliot, Lisa B.; MacDonald, Jonathan H. C.
An exploratory case study approach was used to describe remote tutoring in biochemistry and general chemistry with students who are deaf or hard of hearing (D/HH). Data collected for analysis were based on the observations of the participant tutor. The research questions guiding this study included (1) How is active learning accomplished in…
The purpose of this study was to determine physics teachers' opinions about student-centered activities applicable in physics teaching and learning in context. A case study approach was used in this research. First, semi-structured interviews were carried out with 6 physics teachers. Then, a questionnaire was developed based on the data obtained…
Tennessee State Dept. of Education, Nashville.
These learning activities can help students get the most out of a visit to the Tennessee World War II Memorial, a group of ten pylons located in Nashville (Tennessee). Each pylon contains informational text about the events of World War II. The ten pylons are listed as: (1) "Pylon E-1--Terror: America Enters the War against Fascism, June…
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…
Barakova, E.I; Spaanenburg, L
The composition of the example set has a major impact on the quality of neural learning. The popular approach is focused on extensive pre-processing to bridge the representation gap between process measurement and neural presentation. In contrast, windowed active sampling attempts to solve these
Gusc, Joanna; van Veen-Dirks, Paula
Purpose: Sustainability is one of the newer topics in the accounting courses taught in university teaching programs. The active learning assignment as described in this paper was developed for use in an accounting course in an undergraduate program. The aim was to enhance teaching about sustainability within such a course. The purpose of this…
Full Text Available Learning is a process that helps create neural dynamical systems so that an appropriate output pattern is generated for a given input. Often, such a memory is considered to be included in one of the attractors in neural dynamical systems, depending on the initial neural state specified by an input. Neither neural activities observed in the absence of inputs nor changes caused in the neural activity when an input is provided were studied extensively in the past. However, recent experimental studies have reported existence of structured spontaneous neural activity and its changes when an input is provided. With this background, we propose that memory recall occurs when the spontaneous neural activity changes to an appropriate output activity upon the application of an input, and this phenomenon is known as bifurcation in the dynamical systems theory. We introduce a reinforcement-learning-based layered neural network model with two synaptic time scales; in this network, I/O relations are successively memorized when the difference between the time scales is appropriate. After the learning process is complete, the neural dynamics are shaped so that it changes appropriately with each input. As the number of memorized patterns is increased, the generated spontaneous neural activity after learning shows itineration over the previously learned output patterns. This theoretical finding also shows remarkable agreement with recent experimental reports, where spontaneous neural activity in the visual cortex without stimuli itinerate over evoked patterns by previously applied signals. Our results suggest that itinerant spontaneous activity can be a natural outcome of successive learning of several patterns, and it facilitates bifurcation of the network when an input is provided.
Love, Bradley C; Medin, Douglas L; Gureckis, Todd M
SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a model of how humans learn categories from examples. SUSTAIN initially assumes a simple category structure. If simple solutions prove inadequate and SUSTAIN is confronted with a surprising event (e.g., it is told that a bat is a mammal instead of a bird), SUSTAIN recruits an additional cluster to represent the surprising event. Newly recruited clusters are available to explain future events and can themselves evolve into prototypes-attractors-rules. SUSTAIN's discovery of category substructure is affected not only by the structure of the world but by the nature of the learning task and the learner's goals. SUSTAIN successfully extends category learning models to studies of inference learning, unsupervised learning, category construction, and contexts in which identification learning is faster than classification learning.
Levant, Yves; Coulmont, Michel; Sandu, Raluca
Business simulations are innovative instruction models for active or cooperative learning. In this paper, we look at the social constructionist roots of these education models in light of the current efforts to enhance employability skills in undergraduate and graduate studies. More specifically, we analyse the role of business simulations in…
da Silva, Ketia Kellen A.; Behar, Patricia A.
This article presents the development of a digital competency model of Distance Learning (DL) students in Brazil called CompDigAl_EAD. The following topics were addressed in this study: Educational Competences, Digital Competences, and Distance Learning students. The model was developed between 2015 and 2016 and is being validated in 2017. It was…
Bossche, van den P.; Gijselaers, W.; Segers, M.; Woltjer, G.B.; Kirschner, P.
To gain insight in the social processes that underlie knowledge sharing in teams, this article questions which team learning behaviors lead to the construction of a shared mental model. Additionally, it explores how the development of shared mental models mediates the relation between team learning
Käser, Tanja; Busetto, Alberto Giovanni; Solenthaler, Barbara; Baschera, Gian-Marco; Kohn, Juliane; Kucian, Karin; von Aster, Michael; Gross, Markus
This study introduces a student model and control algorithm, optimizing mathematics learning in children. The adaptive system is integrated into a computer-based training system for enhancing numerical cognition aimed at children with developmental dyscalculia or difficulties in learning mathematics. The student model consists of a dynamic…
Baiq Sri Handayani
Full Text Available The learning process is a process of change in behavior as a form of the result of learning. The learning model is a crucial component of the success of the learning process. The learning model is growing fastly, and each model has different characteristics. Teachers are required to be able to understand each model to teach the students optimally by matching the materials and the learning model. The best of the learning model is the model that based on the brain system in learning that are the model of Brain Based Learning (BBL and the model of Whole Brain Teaching (WBT. The purposes of this article are to obtain information related to (1 the brain’s natural learning system, (2 analyze the characteristics of the model BBL and WBT based on theory, brain sections that play a role associated with syntax, similarities, and differences, (3 explain the distinctive characteristics of both models in comparison to other models. The results of this study are: (1 the brain’s natural learning system are: (a the nerves in each hemisphere do not work independently, (b doing more activities can connect more brain nerves, (c the right hemisphere controls the left side motoric sensor of the body, and vice versa; (2 the characteristics of BBL and WBT are: (a BBL is based on the brain’s structure and function, while the model WBT is based on the instructional approach, neurolinguistic, and body language, (b the parts of the brain that work in BBL are: cerebellum, cerebral cortex, frontal lobe, limbic system, and prefrontal cortex; whereas the parts that work WBT are: prefrontal cortex, visual cortex, motor cortex, limbic system, and amygdala, (c the similarities between them are that they both rely on the brain’s system and they both promote gesture in learning, whereas the differences are on the view of the purposes of gestures and the learning theory that they rely on. BBL relies on cognitive theory while WBT relies on social theory; (3 the typical
Hayati .; Retno Dwi Suyanti
The objective in this research: (1) Determine a better learning model to improve learning outcomes physics students among learning model Inquiry Training based multimedia and Inquiry Training learning model. (2) Determine the level of motivation to learn in affects physics student learning outcomes. (3) Knowing the interactions between the model of learning and motivation in influencing student learning outcomes. This research is a quasi experimental. The population in this research was all s...
Full Text Available Reverse-engineering of biological networks is a central problem in systems biology. The use of intervention data, such as gene knockouts or knockdowns, is typically used for teasing apart causal relationships among genes. Under time or resource constraints, one needs to carefully choose which intervention experiments to carry out. Previous approaches for selecting most informative interventions have largely been focused on discrete Bayesian networks. However, continuous Bayesian networks are of great practical interest, especially in the study of complex biological systems and their quantitative properties. In this work, we present an efficient, information-theoretic active learning algorithm for Gaussian Bayesian networks (GBNs, which serve as important models for gene regulatory networks. In addition to providing linear-algebraic insights unique to GBNs, leading to significant runtime improvements, we demonstrate the effectiveness of our method on data simulated with GBNs and the DREAM4 network inference challenge data sets. Our method generally leads to faster recovery of underlying network structure and faster convergence to final distribution of confidence scores over candidate graph structures using the full data, in comparison to random selection of intervention experiments.
Bavley, Charlotte C; Rice, Richard C; Fischer, Delaney K; Fakira, Amanda K; Byrne, Maureen; Kosovsky, Maria; Rizzo, Bryant K; Del Prete, Dolores; Alaedini, Armin; Morón, Jose A; Higgins, Joseph J; D'Adamio, Luciano; Rajadhyaksha, Anjali M
A homozygous nonsense mutation in the cereblon ( CRBN ) gene results in autosomal recessive, nonsyndromic intellectual disability that is devoid of other phenotypic features, suggesting a critical role of CRBN in mediating learning and memory. In this study, we demonstrate that adult male Crbn knock-out ( Crbn KO ) mice exhibit deficits in hippocampal-dependent learning and memory tasks that are recapitulated by focal knock-out of Crbn in the adult dorsal hippocampus, with no changes in social or repetitive behavior. Cellular studies identify deficits in long-term potentiation at Schaffer collateral CA1 synapses. We further show that Crbn is robustly expressed in the mouse hippocampus and Crbn KO mice exhibit hyperphosphorylated levels of AMPKα (Thr172). Examination of processes downstream of AMP-activated protein kinase (AMPK) finds that Crbn KO mice have a selective impairment in mediators of the mTORC1 translation initiation pathway in parallel with lower protein levels of postsynaptic density glutamatergic proteins and higher levels of excitatory presynaptic markers in the hippocampus with no change in markers of the unfolded protein response or autophagy pathways. Acute pharmacological inhibition of AMPK activity in adult Crbn KO mice rescues learning and memory deficits and normalizes hippocampal mTORC1 activity and postsynaptic glutamatergic proteins without altering excitatory presynaptic markers. Thus, this study identifies that loss of Crbn results in learning, memory, and synaptic defects as a consequence of exaggerated AMPK activity, inhibition of mTORC1 signaling, and decreased glutamatergic synaptic proteins. Thus, Crbn KO mice serve as an ideal model of intellectual disability to further explore molecular mechanisms of learning and memory. SIGNIFICANCE STATEMENT Intellectual disability (ID) is one of the most common neurodevelopmental disorders. The cereblon ( CRBN ) gene has been linked to autosomal recessive, nonsyndromic ID, characterized by an
Ribeiro, Marco Tulio; Singh, Sameer; Guestrin, Carlos
Understanding why machine learning models behave the way they do empowers both system designers and end-users in many ways: in model selection, feature engineering, in order to trust and act upon the predictions, and in more intuitive user interfaces. Thus, interpretability has become a vital concern in machine learning, and work in the area of interpretable models has found renewed interest. In some applications, such models are as accurate as non-interpretable ones, and thus are preferred f...
Ali, R.; Ashraf, I.
Active learning in Optics (ALO) is a self-funded program under the umbrella of the Abdus Salam International Centre for Theoretical Physics (ICTP) and Quaid-i-Azam University (QAU) to bring physical sciences to traditionally underserved Girls high schools and colleges in Pakistan. There is a significant gender disparity in physical Sciences in Pakistan. In Department of Physics at QAU, approximately 10 to 20% of total students were used to be females from past many decades, but now this percentage is increasing. To keep it up at same pace, we started ALO in January 2016 as a way to provide girls an enriching science experiences, in a very friendly atmosphere. We have organized many one-day activities, to support and encourage girls' students of government high schools and colleges to pursue careers in sciences. In this presentation we will describe our experience and lesson learned in these activities.
Lucas, D. D.
From the analysis of ensemble variability to improving simulation performance, machine learning algorithms can play a powerful role in understanding the behavior of atmospheric and climate models. To learn about model behavior, we create training and testing data sets through ensemble techniques that sample different model configurations and values of input parameters, and then use supervised machine learning to map the relationships between the inputs and outputs. Following this procedure, we have used support vector machines, random forests, gradient boosting and other methods to investigate a variety of atmospheric and climate model phenomena. We have used machine learning to predict simulation crashes, estimate the probability density function of climate sensitivity, optimize simulations of the Madden Julian oscillation, assess the impacts of weather and emissions uncertainty on atmospheric dispersion, and quantify the effects of model resolution changes on precipitation. This presentation highlights recent examples of our applications of machine learning to improve the understanding of climate and atmospheric models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
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…
Kammer, Rebecca; Schreiner, Laurie; Kim, Young K.; Denial, Aurora
There is a need for an assessment tool for evaluating the effectiveness of active learning strategies such as problem-based learning in promoting deep learning and clinical reasoning skills within the dual environments of didactic and clinical settings in health professions education. The Active Learning in Health Professions Scale (ALPHS)…
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…
The Aalborg PBL Model [Kjersdam & Enemark, 1997; Kolmos et al., 2004] is an example of a democratic learning system [Qvist, 2008]. Writing one project each semester in teams is an important element in the model. Medicine with Industrial Specialisation - a study at the Faculties of Engineering......, Science and Medicine at Aalborg University - has combined the Aalborg Model with solving cases as used by other models. A questionnaire survey related to democratic learning indicates that the democratic learning has been enhanced. This paper presents the results....
Full Text Available In response to the fact that college students complain on their unsuccessful story of their EFL learning experience such as the limited number of vocabulary, English Grammar confusion, low competence of English language skills, this article explores an alternative effective way of helping them to improve their English through Text-Based Learning (TBL model. This article is then intended to narrate the implementation of TBL to teach English for college students of non English Department of Post Graduate Program of State Islamic Institute of Tulungagung, Indonesia. The result of implementing this teaching model proves to be able to not only stimulate joyful learning atmosphere but to attract the students’ active participation during the EFL instructional process as well. This further brings about their better practical understanding on English language skills as their expectation. Therefore, for English lecturers, this model is pedagogically good to be implemented in their English instructional practices.
, it was compared with multiple other state-of-the-art machine learning algorithms. Moreover, the thesis presents the application of the proposed learning method on robot control for achieving trajectory execution while learning the inverse dynamics models on-the-fly . Also it is presented the application...... of the dynamics models. Those mainly derive from physics-based methods and thus they are based on physical properties which are hard to be calculated. In this thesis, is presented, a novel online machine learning approach which is able to model both inverse and forward dynamics models of industrial manipulators....... The proposed method belongs to the class of deep learning and exploits the concepts of self-organization, recurrent neural networks and iterative multivariate Bayesian regression. It has been evaluated on multiple datasets captured from industrial robots while they were performing various tasks. Also...
Chen, Yingke; Mao, Hua; Jaeger, Manfred
to a single long observation sequence, and in these situations existing automatic learning methods cannot be applied. In this paper, we adapt algorithms for learning variable order Markov chains from a single observation sequence of a target system, so that stationary system properties can be verified using......Establishing an accurate model for formal verification of an existing hardware or software system is often a manual process that is both time consuming and resource demanding. In order to ease the model construction phase, methods have recently been proposed for automatically learning accurate...... the learned model. Experiments demonstrate that system properties (formulated as stationary probabilities of LTL formulas) can be reliably identified using the learned model....
Rucker, Sydney Y; Ozdogan, Zulfukar; Al Achkar, Morhaf
Journal club (JC), as a pedagogical strategy, has long been used in graduate medical education (GME). As evidence-based medicine (EBM) becomes a mainstay in GME, traditional models of JC present a number of insufficiencies and call for novel models of instruction. A flipped classroom model appears to be an ideal strategy to meet the demands to connect evidence to practice while creating engaged, culturally competent, and technologically literate physicians. In this article, we describe a novel model of flipped classroom in JC. We present the flow of learning activities during the online and face-to-face instruction, and then we highlight specific considerations for implementing a flipped classroom model. We show that implementing a flipped classroom model to teach EBM in a residency program not only is possible but also may constitute improved learning opportunity for residents. Follow-up work is needed to evaluate the effectiveness of this model on both learning and clinical practice.
Juhary, Jowati Binti
This paper aims at analysing the needs for a specific teaching and learning model for the National Defence University of Malaysia (NDUM). The main argument is that whether there are differences between teaching and learning for academic component versus military component at the university. It is further argued that in order to achieve excellence, there should be one teaching and learning culture. Data were collected through interviews with military cadets. It is found that there are variations of teaching and learning strategies for academic courses, in comparison to a dominant teaching and learning style for military courses. Thus, in the interest of delivering quality education and training for students at the university, the paper argues that possibly a hybrid model for teaching and learning is fundamental in order to generate a one culture of academic and military excellence for the NDUM.
Yoshimura, Seichi; Hasegawa, Naoko
One effective method to analyze the causes of human errors is to model the behavior of human and to simulate it. The Central Research Institute of Electric Power Industry (CRIEPI) has developed an operator team behavior simulation system called SYBORG (Simulation System for the Behavior of an Operating Group) to analyze the human errors and to establish the countermeasures for them. As an operator behavior model which composes SYBORG has no learning mechanism and the knowledge of a plant is fixed, it cannot take suitable actions when unknown situations occur nor learn anything from the experience. However, considering actual operators, learning is an essential human factor to enhance their abilities to diagnose plant anomalies. In this paper, Q learning with 1/f fluctuation was proposed as a learning mechanism of an operator and simulation using the mechanism was conducted. The results showed the effectiveness of the learning mechanism. (author)
Cavanaugh, James T; Konrad, Shelley Cohen
To describe the implementation of an interprofessional shared learning model designed to promote the development of person-centered healthcare communication skills. Master of social work (MSW) and doctor of physical therapy (DPT) degree students. The model used evidence-based principles of effective healthcare communication and shared learning methods; it was aligned with student learning outcomes contained in MSW and DPT curricula. Students engaged in 3 learning sessions over 2 days. Sessions involved interactive reflective learning, simulated role-modeling with peer assessment, and context-specific practice of communication skills. The perspective of patients/clients was included in each learning activity. Activities were evaluated through narrative feedback. Students valued opportunities to learn directly from each other and from healthcare consumers. Important insights and directions for future interprofessional learning experiences were gleaned from model implementation. The interprofessional shared learning model shows promise as an effective method for developing person-centered communication skills.
Zaikin, Oleg; Malinowska, Magdalena; Kofoed, Lise B.
The article contains the concept of developing a motivation model aimed at supporting activity of both students and teachers in the process of implementing and using an open and distance learning system. Proposed motivation model is focused on the task of filling the knowledge repository with high...... quality didactic material. Open and distance learning system assures a computer space for the teaching/learning process in open environment. The structure of the motivation model and formal assumptions are described. Additionally, there is presented a structure of the linguistic database, helping...... the teacher to assess the student's motivation and the basic simulation model to analysis the teaching/learning process constrains. The proposed approach is based on the games theory and simulation approach....
Lima, Rui M.; Andersson, Pernille Hammar; Saalman, Elisabeth
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...... 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...
The aims of this research were to determine the effect of cooperative learning model and learning styles on learning result. This quasi-experimental study employed a 2x2 treatment by level, involved independent variables, i.e. cooperative learning model and learning styles, and learning result as the dependent variable. Findings signify that: (1)…
Full Text Available Abstract This study examines the influence of the learning model guided findings on student learning outcomes in subjects PAI eighth grade students of SMP Plus al Masoem. The research method used in this study is a quantitative method in the form of quasi-experiment Quasi-Experimental Design. The findings of the study are expected to demonstrate 1 the difference significant increase in learning outcomes between the experimental class using guided discovery method that uses the control class discussion of learning models 2 Constraints in the method of guided discovery activities and the limited ability of educators in the experimental class in implements the method of guided discovery and constraints faced by students while digging the information they need so we need special strategies to motivate students in the experimental class in order for them creatively find the right way to gather information that supports learning PAI.
Monaci, Gianluca; Sommer, Friedrich T.; Vandergheynst, Pierre
This paper presents a novel framework to learn sparse represen- tations for audiovisual signals. An audiovisual signal is modeled as a sparse sum of audiovisual kernels. The kernels are bimodal functions made of synchronous audio and video components that can be positioned independently and arbitrarily in space and time. We design an algorithm capable of learning sets of such audiovi- sual, synchronous, shift-invariant functions by alternatingly solving a coding and a learning pr...
To keep pace with our adversaries, we must expand the scope of machine learning and reasoning to address the breadth of possible attacks. One approach is to employ an algorithm to learn a set of causal models that describes the entire cyber network and each host end node. Such a learning algorithm would run continuously on the system and monitor activity in real time. With a set of causal models, the algorithm could anticipate novel attacks, take actions to thwart them, and predict the second-order effects flood of information, and the algorithm would have to determine which streams of that flood were relevant in which situations. This paper will present the results of efforts toward the application of a developmental learning algorithm to the problem of cyber security. The algorithm is modeled on the principles of human developmental learning and is designed to allow an agent to learn about the computer system in which it resides through active exploration. Children are flexible learners who acquire knowledge by actively exploring their environment and making predictions about what they will find,1, 2 and our algorithm is inspired by the work of the developmental psychologist Jean Piaget.3 Piaget described how children construct knowledge in stages and learn new concepts on top of those they already know. Developmental learning allows our algorithm to focus on subsets of the environment that are most helpful for learning given its current knowledge. In experiments, the algorithm was able to learn the conditions for file exfiltration and use that knowledge to protect sensitive files.
Shaharanee, Izwan Nizal Mohd; Jamil, Jastini Mohd; Rodzi, Sarah Syamimi Mohamad
As the world is being developed with the new technologies, discovering and manipulating new ideas and concepts of online education are changing rapidly. In response to these changes, many states, institutions, and organizations have been working on strategic plans to implement online education. At the same time, misconceptions and myths related to the difficulty of teaching and learning online, technologies available to support online instruction, the support and compensation needed for high-quality instructors, and the needs of online students create challenges for such vision statements and planning documents. This paper provides analysis and evaluation of the effectiveness of Google Classroom's active learning activities for data mining subject under the Decision Sciences program. Technology Acceptance Model (TAM) has been employed to measure the effectiveness of the learning activities. A total of 100 valid unduplicated responses from students who enrolled data mining subject were used in this study. The results indicated that majority of the students satisfy with the Google Classroom's tool that were introduced in the class. Results of data analyzed showed that all ratios are above averages. In particular, comparative performance is good in the areas of ease of access, perceived usefulness, communication and interaction, instruction delivery and students' satisfaction towards the Google Classroom's active learning activities.
Melnikov, Alexey A; Poulsen Nautrup, Hendrik; Krenn, Mario; Dunjko, Vedran; Tiersch, Markus; Zeilinger, Anton; Briegel, Hans J
How useful can machine learning be in a quantum laboratory? Here we raise the question of the potential of intelligent machines in the context of scientific research. A major motivation for the present work is the unknown reachability of various entanglement classes in quantum experiments. We investigate this question by using the projective simulation model, a physics-oriented approach to artificial intelligence. In our approach, the projective simulation system is challenged to design complex photonic quantum experiments that produce high-dimensional entangled multiphoton states, which are of high interest in modern quantum experiments. The artificial intelligence system learns to create a variety of entangled states and improves the efficiency of their realization. In the process, the system autonomously (re)discovers experimental techniques which are only now becoming standard in modern quantum optical experiments-a trait which was not explicitly demanded from the system but emerged through the process of learning. Such features highlight the possibility that machines could have a significantly more creative role in future research.
Chevillon, G.; Massmann, M.; Mavroeidis, S.
Identification of structural parameters in models with adaptive learning can be weak, causing standard inference procedures to become unreliable. Learning also induces persistent dynamics, and this makes the distribution of estimators and test statistics non-standard. Valid inference can be
Barreto, L; Kypreos, S [Paul Scherrer Inst. (PSI), Villigen (Switzerland)
This study describes the endogenous representation of investment cost learning curves into the MARKAL energy planning model. A piece-wise representation of the learning curves is implemented using Mixed Integer Programming. The approach is briefly described and some results are presented. (author) 3 figs., 5 refs.
The process of introduction of a new technology supposes that while its production and utilisation increases, also its operation improves and its investment costs and production decreases. The accumulation of experience and learning of a new technology increase in parallel with the increase of its market share. This process is represented by the technological learning curves and the energy sector is not detached from this process of substitution of old technologies by new ones. The present paper carries out a brief revision of the main energy models that include the technology dynamics (learning). The energy scenarios, developed by global energy models, assume that the characteristics of the technologies are variables with time. But this trend is incorporated in a exogenous way in these energy models, that is to say, it is only a time function. This practice is applied to the cost indicators of the technology such as the specific investment costs or to the efficiency of the energy technologies. In the last years, the new concept of endogenous technological learning has been integrated within these global energy models. This paper examines the concept of technological learning in global energy models. It also analyses the technological dynamics of the energy system including the endogenous modelling of the process of technological progress. Finally, it makes a comparison of several of the most used global energy models (MARKAL, MESSAGE and ERIS) and, more concretely, about the use these models make of the concept of technological learning. (Author) 17 refs
Teguh Febri Sudarma
Full Text Available Research was aimed to determine: (1 Students’ learning outcomes that was taught with just in time teaching based STAD cooperative learning method and STAD cooperative learning method (2 Students’ outcomes on Physics subject that had high learning activity compared with low learning activity. The research sample was random by raffling four classes to get two classes. The first class taught with just in time teaching based STAD cooperative learning method, while the second class was taught with STAD cooperative learning method. The instrument used was conceptual understanding that had been validated with 7 essay questions. The average gain values of students learning results with just in time teaching based STAD cooperative learning method 0,47 higher than average gain values of students learning results with STAD cooperative learning method. The high learning activity and low learning activity gave different learning results. In this case the average gain values of students learning results with just in time teaching based STAD cooperative learning method 0,48 higher than average gain values of students learning results with STAD cooperative learning method. There was interaction between learning model and learning activity to the physics learning result test in students
Hadžibegovic, Zalkida; Sliško, Josip
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…
Rockich-Winston, Nicole; Train, Brian C; Rudolph, Michael J; Gillette, Chris
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 active learning methods used in the last year (r = 0.259, p 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.
Carr, Rodney; Palmer, Stuart; Hagel, Pauline
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…
Deming, Grace L.
The lecture is the most common teaching method used at colleges and universities, but does this format facilitate student learning? Lectures can be brilliantly delivered, but they are received by a passive audience. As time passes during a lecture, student attention and effective notetaking diminish. Many students become more interested in a subject and retain information longer in courses that rely on active rather than passive teaching methods. Interactive teaching strategies such as the think-pair-share-(write), the 3-minute paper, and the misconception confrontation can be used to actively engage students during lecture. As a cooperative learning strategy, the think-pair-share-(write) technique requires active discussion by everyone in the class. The "write" component structures individual accountability into the activity. The 3-minute paper is an expansion of the standard 1-minute paper feedback technique, but is required of all students rather than voluntary or anonymous. The misconception confrontation technique allows students to focus on how their pre- conceived notions differ from the scientific explanation. These techniques can be easily adopted by anyone currently using a standard lecture format for introductory astronomy. The necessary components are a commitment by the instructor to require active participation by all students and a willingness to try new teaching methods.
ICARE is a learning model that directly ensure the students to actively participate in the learning process using animation media visualization. ICARE have five key elements of learning experience from children and adult that is introduction, connection, application, reflection and extension. The use of Icare system to ensure that participants have opportunity to apply what have been they learned. So that, the message delivered by lecture to students can be understood and recorded by students in a long time. Learning model that was deemed capable of improving learning outcomes and interest to learn in following learning process Biotechnology with applying the ICARE learning model using visualization animation. This learning model have been giving motivation to participate in the learning process and learning outcomes obtained becomes more increased than before. From the results of student learning in subjects Biotechnology by applying the ICARE learning model using Visualization Animation can improving study results of student from the average value of middle test amounted to 70.98 with the percentage of 75% increased value of final test to be 71.57 with the percentage of 68.63%. The interest to learn from students more increasing visits of student activities at each cycle, namely the first cycle obtained average value by 33.5 with enough category. The second cycle is obtained an average value of 36.5 to good category and third cycle the average value of 36.5 with a student activity to good category.
A democratic learning system can be defined as a system where decisions, processes and behaviour related to learning are established through argumentation (discussion) or negotiation (dialog), voting or consensus (alone or in combination) between those affected by the decision simultaneously...... reaching the learning outcomes, the technical and professional knowledge and insight. In principle the participants must be equal with equal rights and feel committed to the values of rationality and impartiality. The Aalborg Model is an example of a democratic learning system although not 100% democratic......, processes and behaviour related to learning can be established through argumentation (discussion) or negotiation (dialog), voting or consensus (alone or in combination) within the group simultaneously reaching the learning outcomes, the technical and professional knowledge and insight. This article...
Bergsteiner, Harald; Avery, Gayle C.; Neumann, Ruth
Kolb's experiential learning theory has been widely influential in adult learning. The theory and associated instruments continue to be criticized, but rarely is the graphical model itself examined. This is significant because models can aid scientific understanding and progress, as well as theory development and research. Applying accepted…
Jamieson, Kevin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Davis, IV, Warren L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Active learning methods automatically adapt data collection by selecting the most informative samples in order to accelerate machine learning. Because of this, real-world testing and comparing active learning algorithms requires collecting new datasets (adaptively), rather than simply applying algorithms to benchmark datasets, as is the norm in (passive) machine learning research. To facilitate the development, testing and deployment of active learning for real applications, we have built an open-source software system for large-scale active learning research and experimentation. The system, called NEXT, provides a unique platform for realworld, reproducible active learning research. This paper details the challenges of building the system and demonstrates its capabilities with several experiments. The results show how experimentation can help expose strengths and weaknesses of active learning algorithms, in sometimes unexpected and enlightening ways.
Pallone, Stephen N.; Frazier, Peter I.; Henderson, Shane G.
We analyze the problem of learning a single user's preferences in an active learning setting, sequentially and adaptively querying the user over a finite time horizon. Learning is conducted via choice-based queries, where the user selects her preferred option among a small subset of offered alternatives. These queries have been shown to be a robust and efficient way to learn an individual's preferences. We take a parametric approach and model the user's preferences through a linear classifier...
Hattie, John A. C.; Donoghue, Gregory M.
The purpose of this article is to explore a model of learning that proposes that various learning strategies are powerful at certain stages in the learning cycle. The model describes three inputs and outcomes (skill, will and thrill), success criteria, three phases of learning (surface, deep and transfer) and an acquiring and consolidation phase within each of the surface and deep phases. A synthesis of 228 meta-analyses led to the identification of the most effective strategies. The results indicate that there is a subset of strategies that are effective, but this effectiveness depends on the phase of the model in which they are implemented. Further, it is best not to run separate sessions on learning strategies but to embed the various strategies within the content of the subject, to be clearer about developing both surface and deep learning, and promoting their associated optimal strategies and to teach the skills of transfer of learning. The article concludes with a discussion of questions raised by the model that need further research.
Alberida, H.; Lufri; Festiyed; Barlian, E.
This research aims to develop problem solving model for science learning in junior high school. The learning model was developed using the ADDIE model. An analysis phase includes curriculum analysis, analysis of students of SMP Kota Padang, analysis of SMP science teachers, learning analysis, as well as the literature review. The design phase includes product planning a science-learning problem-solving model, which consists of syntax, reaction principle, social system, support system, instructional impact and support. Implementation of problem-solving model in science learning to improve students' science process skills. The development stage consists of three steps: a) designing a prototype, b) performing a formative evaluation and c) a prototype revision. Implementation stage is done through a limited trial. A limited trial was conducted on 24 and 26 August 2015 in Class VII 2 SMPN 12 Padang. The evaluation phase was conducted in the form of experiments at SMPN 1 Padang, SMPN 12 Padang and SMP National Padang. Based on the development research done, the syntax model problem solving for science learning at junior high school consists of the introduction, observation, initial problems, data collection, data organization, data analysis/generalization, and communicating.
Chen, Jianzhong; Muggleton, Stephen; Santos, José
We revisit an application developed originally using abductive Inductive Logic Programming (ILP) for modeling inhibition in metabolic networks. The example data was derived from studies of the effects of toxins on rats using Nuclear Magnetic Resonance (NMR) time-trace analysis of their biofluids together with background knowledge representing a subset of the Kyoto Encyclopedia of Genes and Genomes (KEGG). We now apply two Probabilistic ILP (PILP) approaches - abductive Stochastic Logic Programs (SLPs) and PRogramming In Statistical modeling (PRISM) to the application. Both approaches support abductive learning and probability predictions. Abductive SLPs are a PILP framework that provides possible worlds semantics to SLPs through abduction. Instead of learning logic models from non-probabilistic examples as done in ILP, the PILP approach applied in this paper is based on a general technique for introducing probability labels within a standard scientific experimental setting involving control and treated data. Our results demonstrate that the PILP approach provides a way of learning probabilistic logic models from probabilistic examples, and the PILP models learned from probabilistic examples lead to a significant decrease in error accompanied by improved insight from the learned results compared with the PILP models learned from non-probabilistic examples.
Fardilha, M.; Schrader, M.; da Cruz e Silva, O. A. B.; da Cruz e Silva, E. F.
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…
Wu, Yun-Wu; Weng, Kuo-Hua; Young, Li-Ming
Generally, in the foundation course of architectural design, much emphasis is placed on teaching of the basic design skills without focusing on teaching students to apply the basic design concepts in their architectural designs or promoting students' own creativity. Therefore, this study aims to propose a concept transformation learning model to…
Full Text Available Monkeys readily learn to discriminate between rewarded and unrewarded items or actions by observing their conspecifics. However, they do not systematically learn from humans. Understanding what makes human-to-monkey transmission of knowledge work or fail could help identify mediators and moderators of social learning that operate regardless of language or culture, and transcend inter-species differences. Do monkeys fail to learn when human models show a behavior too dissimilar from the animals' own, or when they show a faultless performance devoid of error? To address this question, six rhesus macaques trained to find which object within a pair concealed a food reward were successively tested with three models: a familiar conspecific, a 'stimulus-enhancing' human actively drawing the animal's attention to one object of the pair without actually performing the task, and a 'monkey-like' human performing the task in the same way as the monkey model did. Reward was manipulated to ensure that all models showed equal proportions of errors and successes. The 'monkey-like' human model improved the animals' subsequent object discrimination learning as much as a conspecific did, whereas the 'stimulus-enhancing' human model tended on the contrary to retard learning. Modeling errors rather than successes optimized learning from the monkey and 'monkey-like' models, while exacerbating the adverse effect of the 'stimulus-enhancing' model. These findings identify error modeling as a moderator of social learning in monkeys that amplifies the models' influence, whether beneficial or detrimental. By contrast, model-observer similarity in behavior emerged as a mediator of social learning, that is, a prerequisite for a model to work in the first place. The latter finding suggests that, as preverbal infants, macaques need to perceive the model as 'like-me' and that, once this condition is fulfilled, any agent can become an effective model.
Byun, Chong Hyun Christie
The importance of active learning in the classroom has been well established in the field of Economic education. This paper examines the connection between active learning and performance outcomes in an Economics 101 course. Students participated in single play simultaneous move game with a clear dominant strategy, modeled after the Prisoner's…
Cavanagh, Andrew J.; Aragón, Oriana R.; Chen, Xinnian; Couch, Brian; Durham, Mary; Bobrownicki, Aiyana; Hanauer, David I.; Graham, Mark J.
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 =…
Benjamin L. Wiggins
Full Text Available STEM classrooms (science, technology, engineering, and mathematics in postsecondary education are rapidly improved by the proper use of active learning techniques. These techniques occupy a descriptive spectrum that transcends passive teaching toward active, constructive, and, finally, interactive methods. While aspects of this framework have been examined, no large-scale or actual classroom-based data exist to inform postsecondary education STEM instructors about possible learning gains. We describe the results of a quasi-experimental study to test the apex of the ICAP framework (interactive, constructive, active, and passive in this ecological classroom environment. Students in interactive classrooms demonstrate significantly improved learning outcomes relative to students in constructive classrooms. This improvement in learning is relatively subtle; similar experimental designs without repeated measures would be unlikely to have the power to observe this significance. We discuss the importance of seemingly small learning gains that might propagate throughout a course or departmental curriculum, as well as improvements with the necessity for faculty to develop and implement similar activities.
Liu, Jiamin; Udupa, Jayaram K
Active shape models (ASM) are widely employed for recognizing anatomic structures and for delineating them in medical images. In this paper, a novel strategy called oriented active shape models (OASM) is presented in an attempt to overcome the following five limitations of ASM: 1) lower delineation accuracy, 2) the requirement of a large number of landmarks, 3) sensitivity to search range, 4) sensitivity to initialization, and 5) inability to fully exploit the specific information present in the given image to be segmented. OASM effectively combines the rich statistical shape information embodied in ASM with the boundary orientedness property and the globally optimal delineation capability of the live wire methodology of boundary segmentation. The latter characteristics allow live wire to effectively separate an object boundary from other nonobject boundaries with similar properties especially when they come very close in the image domain. The approach leads to a two-level dynamic programming method, wherein the first level corresponds to boundary recognition and the second level corresponds to boundary delineation, and to an effective automatic initialization method. The method outputs a globally optimal boundary that agrees with the shape model if the recognition step is successful in bringing the model close to the boundary in the image. Extensive evaluation experiments have been conducted by utilizing 40 image (magnetic resonance and computed tomography) data sets in each of five different application areas for segmenting breast, liver, bones of the foot, and cervical vertebrae of the spine. Comparisons are made between OASM and ASM based on precision, accuracy, and efficiency of segmentation. Accuracy is assessed using both region-based false positive and false negative measures and boundary-based distance measures. The results indicate the following: 1) The accuracy of segmentation via OASM is considerably better than that of ASM; 2) The number of landmarks
Of all the activity observed on the Sun, two of the most energetic events are flares and coronal mass ejections. However, we do not, as of yet, fully understand the physical mechanism that triggers solar eruptions. A machine-learning algorithm, which is favorable in cases where the amount of data is large, is one way to  empirically determine the signatures of this mechanism in solar image data and  use them to predict solar activity. In this talk, we discuss the application of various machine learning algorithms - specifically, a Support Vector Machine, a sparse linear regression (Lasso), and Convolutional Neural Network - to image data from the photosphere, chromosphere, transition region, and corona taken by instruments aboard the Solar Dynamics Observatory in order to predict solar activity on a variety of time scales. Such an approach may be useful since, at the present time, there are no physical models of flares available for real-time prediction. We discuss our results (Bobra and Couvidat, 2015; Bobra and Ilonidis, 2016; Jonas et al., 2017) as well as other attempts to predict flares using machine-learning (e.g. Ahmed et al., 2013; Nishizuka et al. 2017) and compare these results with the more traditional techniques used by the NOAA Space Weather Prediction Center (Crown, 2012). We also discuss some of the challenges in using machine-learning algorithms for space science applications.
Ito, Makoto; Doya, Kenji
Computational models of reinforcement learning have recently been applied to analysis of brain imaging and neural recording data to identity neural correlates of specific processes of decision making, such as valuation of action candidates and parameters of value learning. However, for such model-based analysis paradigms, selecting an appropriate model is crucial. In this study we analyze the process of choice learning in rats using stochastic rewards. We show that "Q-learning," which is a standard reinforcement learning algorithm, does not adequately reflect the features of choice behaviors. Thus, we propose a generalized reinforcement learning (GRL) algorithm that incorporates the negative reward effect of reward loss and forgetting of values of actions not chosen. Using the Bayesian estimation method for time-varying parameters, we demonstrated that the GRL algorithm can predict an animal's choice behaviors as efficiently as the best Markov model. The results suggest the usefulness of the GRL for the model-based analysis of neural processes involved in decision making.
While blended learning combines online and face-to-face teaching, research on blended learning has primarily focused on the role of technology and the opportunities it creates for engaging students. Less focus has been put on face-to-face activities in blended learning. This paper argues...... that it is not only the online activities in blended learning that provide new opportunities for rethinking pedagogy in higher education, it is also imperative to reconsider the face-to-face activities when part of the learning is provided online. Based on a review of blended learning in business and management...... education, we identify what forms of teaching and learning are suggested to take place face-to-face when other activities are moved online. We draw from the Community of Inquiry framework to analyze how face-to-face activities contribute to a blended learning pedagogy and discuss the implications...
Smith, Justin S.; Nebgen, Ben; Lubbers, Nicholas; Isayev, Olexandr; Roitberg, Adrian E.
The development of accurate and transferable machine learning (ML) potentials for predicting molecular energetics is a challenging task. The process of data generation to train such ML potentials is a task neither well understood nor researched in detail. In this work, we present a fully automated approach for the generation of datasets with the intent of training universal ML potentials. It is based on the concept of active learning (AL) via Query by Committee (QBC), which uses the disagreement between an ensemble of ML potentials to infer the reliability of the ensemble's prediction. QBC allows the presented AL algorithm to automatically sample regions of chemical space where the ML potential fails to accurately predict the potential energy. AL improves the overall fitness of ANAKIN-ME (ANI) deep learning potentials in rigorous test cases by mitigating human biases in deciding what new training data to use. AL also reduces the training set size to a fraction of the data required when using naive random sampling techniques. To provide validation of our AL approach, we develop the COmprehensive Machine-learning Potential (COMP6) benchmark (publicly available on GitHub) which contains a diverse set of organic molecules. Active learning-based ANI potentials outperform the original random sampled ANI-1 potential with only 10% of the data, while the final active learning-based model vastly outperforms ANI-1 on the COMP6 benchmark after training to only 25% of the data. Finally, we show that our proposed AL technique develops a universal ANI potential (ANI-1x) that provides accurate energy and force predictions on the entire COMP6 benchmark. This universal ML potential achieves a level of accuracy on par with the best ML potentials for single molecules or materials, while remaining applicable to the general class of organic molecules composed of the elements CHNO.
Timothy K. Kock
Full Text Available As Kyrgyzstan recovers from the collapse of the Soviet Union, the youth of this Newly Independent State (NIS face troubling times. Poverty has become all to familiar throughout the country; its people, including youth, are losing hope and question their ability to be productive members of society (Lines & Kock, 2004. Kyrgyzstan’s future leaders – like all nations - are found among its youth of today. Therefore, it behooves the government and citizens of Kyrgyzstan to develop youth centers designed to enhance the skills young people need to succeed now and in the future. This paper describes a program designed to teach Kyrgyz youth and adults teamwork, and civic responsibility through experiential learning activities. The paper outlines the steps taken and results derived from the hands-on trainings provided to the participants in one location in Kyrgyzstan. Findings from this study may have implications for other international youth development projects.
Xiong, Sicheng; Rosales, Rómer; Pei, Yuanli; Fern, Xiaoli Z.
This work focuses on active learning of distance metrics from relative comparison information. A relative comparison specifies, for a data point triplet $(x_i,x_j,x_k)$, that instance $x_i$ is more similar to $x_j$ than to $x_k$. Such constraints, when available, have been shown to be useful toward defining appropriate distance metrics. In real-world applications, acquiring constraints often require considerable human effort. This motivates us to study how to select and query the most useful ...
Phillips, Janet M
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.
Miguel Ángel Montero
Full Text Available The experience which we count with in the university education, the development of the ICT (Information and Communications Technology, the integration in the ESSE, the new qualifications (or Grades and mainly the desire to improve push us to innovate and to put into practice new methodologies in the teaching and learning of the subjects of Mathematics and Statistic assigned to our department. These methods totally renovate the lecturer’s roll and the traditional teaching, introducing multimedia tools, support platforms and new resources that provide students an autonomy which before they did not have, modifying the organization of time and space, increasing modalities and strategies of teaching-learning-tutorization and therefore developing more flexible models. It is tried to facilitate the learning of these subjects, providing a model b-learning, a comple- ment or alternative to the attendance classes, reinforcing the student’s active self-training.
Andrews, T. M.; Leonard, M. J.; Colgrove, C. A.; Kalinowski, S. T.
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
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
Stegemann, Nicole; Sutton-Brady, Catherine
This paper introduces an activity used in class to allow students to apply previously acquired information to a hands-on task. As the authors have previously shown active learning is a way to effectively facilitate and improve students' learning outcomes. As a result to improve learning outcomes we have overtime developed a series of learning…
Camacho, Danielle J.; Legare, Jill M.
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…
Cattaneo, Kelsey Hood
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…
Daniel, Todd; Tivener, Kristin
Scientific research into learning enhancement gained by the use of clickers in active classrooms has largely focused on the use of individual clickers. In this study, we compared the learning experiences of participants in active learning groups in which an entire small group shared a single clicker to groups in which each member of the group had…
This paper presents a model of learning in a workplace, in which an online course provides flexibility for staff to learn at their convenient hours. A motivation was brought into an account of the success of learning in a workplace program, based upon Behaviorist learning approach--an online mentor and an accumulated learning activities score was…
Deliyska, B.; Rozeva, A.
The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e-learning in an online learner-centered environment. ILS is a distributed e-learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e-learning is achieved through the resources of the Semantic Web and is designed and developed around a course, group of courses or specialty. An essential part of ILS is learner model database which contains structured data about learner profile and temporal status in the learning process of one or more courses. In the paper a learner model position in ILS is considered and a relational database is designed from learner's domain ontology. Multidimensional modeling agent for the source database is designed and resultant learner data cube is presented. Agent's modules are proposed with corresponding algorithms and procedures. Multidimensional (OLAP) analysis guidelines on the resultant learner module for designing dynamic learning strategy have been highlighted.
LeDonne Norman C
Full Text Available Abstract Background Standard approaches to address the performance of predictive models that used common statistical measurements for the entire data set provide an overview of the average performance of the models across the entire predictive space, but give little insight into applicability of the model across the prediction space. Guha and Van Drie recently proposed the use of structure-activity landscape index (SALI curves via the SALI curve integral (SCI as a means to map the predictive power of computational models within the predictive space. This approach evaluates model performance by assessing the accuracy of pairwise predictions, comparing compound pairs in a manner similar to that done by medicinal chemists. Results The SALI approach was used to evaluate the performance of continuous prediction models for MDR1-MDCK in vitro efflux potential. Efflux models were built with ADMET Predictor neural net, support vector machine, kernel partial least squares, and multiple linear regression engines, as well as SIMCA-P+ partial least squares, and random forest from Pipeline Pilot as implemented by AstraZeneca, using molecular descriptors from SimulationsPlus and AstraZeneca. Conclusion The results indicate that the choice of training sets used to build the prediction models is of great importance in the resulting model quality and that the SCI values calculated for these models were very similar to their Kendall τ values, leading to our suggestion of an approach to use this SALI/SCI paradigm to evaluate predictive model performance that will allow more informed decisions regarding model utility. The use of SALI graphs and curves provides an additional level of quality assessment for predictive models.
Ledonne, Norman C; Rissolo, Kevin; Bulgarelli, James; Tini, Leonard
Standard approaches to address the performance of predictive models that used common statistical measurements for the entire data set provide an overview of the average performance of the models across the entire predictive space, but give little insight into applicability of the model across the prediction space. Guha and Van Drie recently proposed the use of structure-activity landscape index (SALI) curves via the SALI curve integral (SCI) as a means to map the predictive power of computational models within the predictive space. This approach evaluates model performance by assessing the accuracy of pairwise predictions, comparing compound pairs in a manner similar to that done by medicinal chemists. The SALI approach was used to evaluate the performance of continuous prediction models for MDR1-MDCK in vitro efflux potential. Efflux models were built with ADMET Predictor neural net, support vector machine, kernel partial least squares, and multiple linear regression engines, as well as SIMCA-P+ partial least squares, and random forest from Pipeline Pilot as implemented by AstraZeneca, using molecular descriptors from SimulationsPlus and AstraZeneca. The results indicate that the choice of training sets used to build the prediction models is of great importance in the resulting model quality and that the SCI values calculated for these models were very similar to their Kendall τ values, leading to our suggestion of an approach to use this SALI/SCI paradigm to evaluate predictive model performance that will allow more informed decisions regarding model utility. The use of SALI graphs and curves provides an additional level of quality assessment for predictive models.
Abraham, Reem Rachel; Vashe, Asha; Torke, Sharmila
The present study aimed to provide undergraduate medical students at Melaka Manipal Medical College (Manipal Campus), Manipal University, in Karnataka, India, an opportunity to apply their knowledge in cardiovascular concepts to real-life situations. A group activity named "Heart Shots" was implemented for a batch of first-year undergraduate students (n = 105) at the end of a block (teaching unit). Students were divided into 10 groups each having 10-11 students. They were requested to make a video/PowerPoint presentation about the application of cardiovascular principles to real-life situations. The presentation was required to be of only pictures/photos and no text material, with a maximum duration of 7 min. More than 95% of students considered that the activity helped them to apply their knowledge in cardiovascular concepts to real-life situations and understand the relevance of physiology in medicine and to revise the topic. More than 90% of students agreed that the activity helped them to apply their creativity in improving their knowledge and to establish a link between concepts rather than learning them as isolated facts. Based on the feedback, we conclude that the activity was student centered and that it facilitated learning. Copyright © 2015 The American Physiological Society.
Han, Wenjing; Coutinho, Eduardo; Li, Haifeng; Schuller, Björn; Yu, Xiaojie; Zhu, Xuan
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
Han, Wenjing; Coutinho, Eduardo; Ruan, Huabin; Li, Haifeng; Schuller, Björn; Yu, Xiaojie; Zhu, Xuan
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.
Wang, C.; Hindriks, K.V.; Babuska, R.
Learning object affordances and manipulation skills is essential for developing cognitive service robots. We propose an active affordance learning approach in continuous state and action spaces without manual discretization of states or exploratory motor primitives. During exploration in the action
Full Text Available The aim of the paper is to develop a model of successful collaborative learning for company innovativeness. First of all, the paper explores the issue of inter-firm learning, focusing its attention on collaborative learning. Secondly, inter-firm learning relationships are considered. Thirdly, the ex ante conditions of collaborative learning and the intra-organizational enhancers of inter-firm learning processes are studied. Finally, a model of the critical success factors for collaborative learning is developed.
Full Text Available Most e-Learning systems provide web-based learning so that students can access the same online courses via the Internet without adaptation, based on each student's profile and behavior. In an e-Learning system, one size does not fit all. Therefore, it is a challenge to make e-Learning systems that are suitably “adaptive”. The aim of adaptive e-Learning is to provide the students the appropriate content at the right time, means that the system is able to determine the knowledge level, keep track of usage, and arrange content automatically for each student for the best learning result. This study presents a proposed system which includes major adaptive features based on a student model. The proposed system is able to initialize the student model for determining the knowledge level of a student when the student registers for the course. After a student starts learning the lessons and doing many activities, the system can track information of the student until he/she takes a test. The student’s knowledge level, based on the test scores, is updated into the system for use in the adaptation process, which combines the student model with the domain model in order to deliver suitable course contents to the students. In this study, the proposed adaptive e-Learning system is implemented on an “Introduction to Java Programming Language” course, using LearnSquare software. After the system was tested, the results showed positive feedback towards the proposed system, especially in its adaptive capability.
Burl, Michael C.; Wang, Esther
Physics-based simulation codes are widely used in science and engineering to model complex systems that would be infeasible to study otherwise. Such codes provide the highest-fidelity representation of system behavior, but are often so slow to run that insight into the system is limited. For example, conducting an exhaustive sweep over a d-dimensional input parameter space with k-steps along each dimension requires k(sup d) simulation trials (translating into k(sup d) CPU-days for one of our current simulations). An alternative is directed exploration in which the next simulation trials are cleverly chosen at each step. Given the results of previous trials, supervised learning techniques (SVM, KDE, GP) are applied to build up simplified predictive models of system behavior. These models are then used within an active learning framework to identify the most valuable trials to run next. Several active learning strategies are examined including a recently-proposed information-theoretic approach. Performance is evaluated on a set of thirteen synthetic oracles, which serve as surrogates for the more expensive simulations and enable the experiments to be replicated by other researchers.
Yata, Chikahiko; Hamamoto, Kengo; Oguri, Takenori
This study analyzed the learning activities in a textbook on technology education for teachers, in order to examine the learning processes and learning scenes detailed therein. Results of analyzing learning process, primary learning activity found each contents framework. Other learning activities designated to be related to complementary in learning process. Results of analyzing learning scene, 14 learning scenes, among them "Scene to recognize the impact on social life and progress of techn...
Griswold, Elise N.; Klionsky, Daniel J.
To anyone familiar with the extensive literature on teaching and learning, there is little question that active learning is more effective than passive learning. Thus, we are not directing this letter to that particular audience. Instead, we are attempting to address the question of the best way to convince instructors who have not tried to incorporate elements of active learning into their courses to make such an attempt. There are numerous examples where it becomes immediately clear that ac...
Lee, Seung Hwan; Hoffman, K. Douglas
The AIDA Model (Attention-Interest-Desire-Action) is one of the classical promotional theories in marketing. Through active-learning techniques and peer critiques, we use infomercials as an innovative educational tool to instruct the four components of the AIDA model. Student evaluations regarding this active-learning assignment reveal that the…
Smith, C. Veronica; Cardaciotto, LeeAnn
Although research suggests that active learning is associated with positive outcomes (e.g., memory, test performance), use of such techniques can be difficult to implement in large lecture-based classes. In the current study, 1,091 students completed out-of-class group exercises to complement course material in an Introductory Psychology class.…
Dowrick, Peter W.
Self modeling (SM) offers a unique expansion of learning theory. For several decades, a steady trickle of empirical studies has reported consistent evidence for the efficacy of SM as a procedure for positive behavior change across physical, social, educational, and diagnostic variations. SM became accepted as an extreme case of model similarity;…
In this paper, car driving is considered at the level of human tracking and maneuvering in the context of other traffic. A model analysis revealed the most salient features determining driving performance and safety. Learning car driving is modelled based on a system theoretical approach and based
Chen, Yukun; Mani, Subramani; Xu, Hua
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
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.
Bolander, Thomas; Gierasimczuk, Nina
In dynamic epistemic logic, actions are described using action models. In this paper we introduce a framework for studying learnability of action models from observations. We present first results concerning propositional action models. First we check two basic learnability criteria: finite ident...
Full Text Available A learning situation can be structured in different ways, as an individual, competitive, or cooperative activity. Each of these structures can be used for different purposes and can lead to different learning outcomes. This paper focuses on cooperative activity and its potential for learning in tertiary education. After defining cooperative activity (or, in a broader sense, learning in interaction and introducing the CAMS theoretical framework to analyse cooperative activity, the main discussion focuses on the theoretical reasons for the usefulness of group learning and on the research of effects of cooperative learning on cognitive (metacognitive, affective-motivational and social processes in university students. The key elements that should be established for successful cooperation are also discussed. At the end, a new direction in using cooperative activity in learning—computer supported collaborative learning (CSCL, which emerged with rapid technology development in the last two decades—is presented and discussed.
Kannan, Jaya; Kurup, Viji
Educators in anesthesia residency programs across the country are facing a number of challenges as they attempt to integrate blended learning techniques in their curriculum. Compared with the rest of higher education, which has made advances to varying degrees in the adoption of online learning anesthesiology education has been sporadic in the active integration of blended learning. The purpose of this review is to discuss the challenges in anesthesiology education and relevance of the Universal Design for Learning framework in addressing them. There is a wide chasm between student demand for online education and the availability of trained faculty to teach. The design of the learning interface is important and will significantly affect the learning experience for the student. This review examines recent literature pertaining to this field, both in the realm of higher education in general and medical education in particular, and proposes the application of a comprehensive learning model that is new to anesthesiology education and relevant to its goals of promoting self-directed learning.
Hyun, Jung; Ediger, Ruth; Lee, Donghun
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…
Sesen, Burcin Acar; Tarhan, Leman
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…
Turnip, Betty; Wahyuni, Ida; Tanjung, Yul Ifda
One of the factors that can support successful learning activity is the use of learning models according to the objectives to be achieved. This study aimed to analyze the differences in problem-solving ability Physics student learning model Inquiry Training based on Just In Time Teaching [JITT] and conventional learning taught by cooperative model…
Bathellier, Brice; Tee, Sui Poh; Hrovat, Christina; Rumpel, Simon
Learning speed can strongly differ across individuals. This is seen in humans and animals. Here, we measured learning speed in mice performing a discrimination task and developed a theoretical model based on the reinforcement learning framework to account for differences between individual mice. We found that, when using a multiplicative learning rule, the starting connectivity values of the model strongly determine the shape of learning curves. This is in contrast to current learning models ...
Rogo, Ellen J; Portillo, Karen M
The purpose of this study was to explore the students' perspectives on the phenomenon of online learning communities while enrolled in a graduate dental hygiene program. A qualitative case study method was designed to investigate the learners' experiences with communities in an online environment. A cross-sectional purposive sampling method was used. Interviews were the data collection method. As the original data were being analyzed, the researchers noted a pattern evolved indicating the phenomenon developed in stages. The data were re-analyzed and validated by 2 member checks. The participants' experiences revealed an e-model consisting of 3 stages of formal learning community development as core courses in the curriculum were completed and 1 stage related to transmuting the community to an informal entity as students experienced the independent coursework in the program. The development of the formal learning communities followed 3 stages: Building a Foundation for the Learning Community, Building a Supportive Network within the Learning Community and Investing in the Community to Enhance Learning. The last stage, Transforming the Learning Community, signaled a transition to an informal network of learners. The e-model was represented by 3 key elements: metamorphosis of relationships, metamorphosis through the affective domain and metamorphosis through the cognitive domain, with the most influential element being the affective development. The e-model describes a 4 stage process through which learners experience a metamorphosis in their affective, relationship and cognitive development. Synergistic learning was possible based on the interaction between synergistic relationships and affective actions. Copyright © 2015 The American Dental Hygienists’ Association.
Elise N. Griswold
Full Text Available To anyone familiar with the extensive literature on teaching and learning, there is little question that active learning is more effective than passive learning. Thus, we are not directing this letter to that particular audience. Instead, we are attempting to address the question of the best way to convince instructors who have not tried to incorporate elements of active learning into their courses to make such an attempt. There are numerous examples where it becomes immediately clear that active learning is preferable to a lecture/note-taking approach. Here, we provide a question for group discussion that can be used as one such illustration.
Thiessen, Erik D
Statistical learning has been studied in a variety of different tasks, including word segmentation, object identification, category learning, artificial grammar learning and serial reaction time tasks (e.g. Saffran et al. 1996 Science 274: , 1926-1928; Orban et al. 2008 Proceedings of the National Academy of Sciences 105: , 2745-2750; Thiessen & Yee 2010 Child Development 81: , 1287-1303; Saffran 2002 Journal of Memory and Language 47: , 172-196; Misyak & Christiansen 2012 Language Learning 62: , 302-331). The difference among these tasks raises questions about whether they all depend on the same kinds of underlying processes and computations, or whether they are tapping into different underlying mechanisms. Prior theoretical approaches to statistical learning have often tried to explain or model learning in a single task. However, in many cases these approaches appear inadequate to explain performance in multiple tasks. For example, explaining word segmentation via the computation of sequential statistics (such as transitional probability) provides little insight into the nature of sensitivity to regularities among simultaneously presented features. In this article, we will present a formal computational approach that we believe is a good candidate to provide a unifying framework to explore and explain learning in a wide variety of statistical learning tasks. This framework suggests that statistical learning arises from a set of processes that are inherent in memory systems, including activation, interference, integration of information and forgetting (e.g. Perruchet & Vinter 1998 Journal of Memory and Language 39: , 246-263; Thiessen et al. 2013 Psychological Bulletin 139: , 792-814). From this perspective, statistical learning does not involve explicit computation of statistics, but rather the extraction of elements of the input into memory traces, and subsequent integration across those memory traces that emphasize consistent information (Thiessen and Pavlik
Full Text Available Self-regulation and self-regulated learning (SRL are important features in music education. In this research self-regulated learning model is presented as a complex, multidimensional structure. SRL starts with the self-regulation. Self-regulation is formed through interaction with the environment, thus self-learning, self-analysis, self-judgment, self-instruction, and self-monitoring are the main functions in self-regulatory structure. Co-regulation is needed, and helps self-regulation to be activated and monitored. In music education, co-regulation refers to the instructions that teacher introduces in the lessons. These instructions have to enhance learning and develop regulation over emotions, cognitive, auditor, and motor skills in students. Learning techniques and learning strategies are core components in music education. Adapting those, students become aware of their learning processes, actions, thoughts, feelings and behaviors that are involved in learning. It is suggested that every teaching methodology has to develop learning techniques, as well as metamemory and metacognition in students, in order to gain expertise. The author has emphasized her attention to every aspect that is believed to belong to SRL. There are not many articles on the SRL in music education, written by musicians, in compare with those written by psychologists and neurologists,. Therefore, the author has suggested that this paper would encourage music teachers and performers to take an advantage in the research of SRL. These researches would help music educational systems and teachers to develop and promote learning techniques and strategies. The results would show improvement in student’s learning and self-regulation.
LaDage, Lara D; Tornello, Samantha L; Vallejera, Jennilyn M; Baker, Emily E; Yan, Yue; Chowdhury, Anik
There are many pedagogical techniques used by educators in higher education; however, some techniques and activities have been shown to be more beneficial to student learning than others. Research has demonstrated that active learning and learning in which students cognitively engage with the material in a multitude of ways result in better understanding and retention. The aim of the present study was to determine which of three pedagogical techniques led to improvement in learning and retention in undergraduate college students. Subjects partook in one of three different types of pedagogical engagement: hands-on learning with a model, observing someone else manipulate the model, and traditional lecture-based presentation. Students were then asked to take an online quiz that tested their knowledge of the new material, both immediately after learning the material and 2 wk later. Students who engaged in direct manipulation of the model scored higher on the assessment immediately after learning the material compared with the other two groups. However, there were no differences among the three groups when assessed after a 2-wk retention interval. Thus active learning techniques that involve direct interaction with the material can lead to learning benefits; however, how these techniques benefit long-term retention of the information is equivocal.
Reinkensmeyer, David J; Burdet, Etienne; Casadio, Maura; Krakauer, John W; Kwakkel, Gert; Lang, Catherine E; Swinnen, Stephan P; Ward, Nick S; Schweighofer, Nicolas
Despite progress in using computational approaches to inform medicine and neuroscience in the last 30 years, there have been few attempts to model the mechanisms underlying sensorimotor rehabilitation. We argue that a fundamental understanding of neurologic recovery, and as a result accurate predictions at the individual level, will be facilitated by developing computational models of the salient neural processes, including plasticity and learning systems of the brain, and integrating them into a context specific to rehabilitation. Here, we therefore discuss Computational Neurorehabilitation, a newly emerging field aimed at modeling plasticity and motor learning to understand and improve movement recovery of individuals with neurologic impairment. We first explain how the emergence of robotics and wearable sensors for rehabilitation is providing data that make development and testing of such models increasingly feasible. We then review key aspects of plasticity and motor learning that such models will incorporate. We proceed by discussing how computational neurorehabilitation models relate to the current benchmark in rehabilitation modeling - regression-based, prognostic modeling. We then critically discuss the first computational neurorehabilitation models, which have primarily focused on modeling rehabilitation of the upper extremity after stroke, and show how even simple models have produced novel ideas for future investigation. Finally, we conclude with key directions for future research, anticipating that soon we will see the emergence of mechanistic models of motor recovery that are informed by clinical imaging results and driven by the actual movement content of rehabilitation therapy as well as wearable sensor-based records of daily activity.
Leontidis, Makis; Halatsis, Constantin
The aim of this paper is to present a model in order to integrate the learning style and the personality traits of a learner into an enhanced Affective Style which is stored in the learner’s model. This model which can deal with the cognitive abilities as well as the affective preferences of the learner is called Learner Affective Model (LAM). The LAM is used to retain learner’s knowledge and activities during his interaction with a Web-based learning environment and also to provide him with the appropriate pedagogical guidance. The proposed model makes use of an ontological approach in combination with the Bayesian Network model and contributes to the efficient management of the LAM in an Affective Module.
Slauson, Stephen R; Mandela, Prashant
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.
Rak, Natalia; Bellebaum, Christian; Thoma, Patrizia
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.
Skwarchuk, Sheri-Lynn; Sowinski, Carla; LeFevre, Jo-Anne
The purpose of this study was to propose and test a model of children's home numeracy experience based on Sénéchal and LeFevre's home literacy model (Child Development, 73 (2002) 445-460). Parents of 183 children starting kindergarten in the fall (median child age=58 months) completed an early home learning experiences questionnaire. Most of the children whose parents completed the questionnaire were recruited for numeracy and literacy testing 1 year later (along with 32 children from the inner city). Confirmatory factor analyses were used to reduce survey items, and hierarchical regression analyses were used to predict the relation among parents' attitudes, academic expectations for their children, reports of formal and informal numeracy, and literacy home practices on children's test scores. Parental reports of formal home numeracy practices (e.g., practicing simple sums) predicted children's symbolic number system knowledge, whereas reports of informal exposure to games with numerical content (measured indirectly through parents' knowledge of children's games) predicted children's non-symbolic arithmetic, as did numeracy attitudes (e.g., parents' enjoyment of numeracy). The home literacy results replicated past findings; parental reports of formal literacy practices (e.g., helping their children to read words) predicted children's word reading, whereas reports of informal experiences (i.e., frequency of shared reading measured indirectly through parents' storybook knowledge) predicted children's vocabulary. These findings support a multifaceted model of children's early numeracy environment, with different types of early home experiences (formal and informal) predicting different numeracy outcomes. Copyright © 2013 Elsevier Inc. All rights reserved.
Soroush, Masoud; Weinberger, Charles B.
This manuscript presents a successful application of inductive learning in process modeling. It describes two process modeling courses that use inductive learning methods such as inquiry learning and problem-based learning, among others. The courses include a novel collection of multi-disciplinary complementary process modeling examples. They were…
Eagleton, Saramarie; Muller, Anton
In this report, a model was developed for whole brain learning based on Curry's onion model. Curry described the effect of personality traits as the inner layer of learning, information-processing styles as the middle layer of learning, and environmental and instructional preferences as the outer layer of learning. The model that was developed…
This paper addresses the very important problem of the effectiveness of teaching methodologies in fundamental engineering courses such as transport phenomena. An active learning strategy, termed the colloquial approach, is proposed in order to increase student involvement in the learning process. This methodology is a considerable departure from traditional methods that use solo lecturing. It is based on guided discussions, and it promotes student understanding of new concepts by directing the student to construct new ideas by building upon the current knowledge and by focusing on key cases that capture the essential aspects of new concepts. The colloquial approach motivates the student to participate in discussions, to develop detailed notes, and to design (or construct) his or her own explanation for a given problem. This paper discusses the main features of the colloquial approach within the framework of other current and previous techniques. Problem-solving strategies and the need for new textbooks and for future investigations based on the colloquial approach are also outlined.
Full Text Available Active learning has been linked with increased student motivation, engagement and understanding of course material. It promotes deep learning, helping to develop critical thinking and writing skills in students. Less well understood, however, are the responses of international students to active learning. Using social constructivist theory, the purpose of this study is to examine domestic and international student perceptions of active learning introduced into large undergraduate Accounting Information Systems lectures. Several active learning strategies were implemented over one semester and examined through the use of semi-structured interviews as well as pre- and post- implementation surveys. Our results suggest broad improvements for international students in student engagement and understanding of unit material when implementing active learning strategies. Other key implications include international student preference for active learning compared with passive learning styles, and that international students may receive greater benefits from active learning strategies than domestic students due to social factors. Based on these findings this paper proposes that educators should seek to implement active learning to better assist and integrate students of diverse backgrounds.
Biehl, Michael; Hammer, Barbara; Villmann, Thomas
An overview is given of prototype-based models in machine learning. In this framework, observations, i.e., data, are stored in terms of typical representatives. Together with a suitable measure of similarity, the systems can be employed in the context of unsupervised and supervised analysis of potentially high-dimensional, complex datasets. We discuss basic schemes of competitive vector quantization as well as the so-called neural gas approach and Kohonen's topology-preserving self-organizing map. Supervised learning in prototype systems is exemplified in terms of learning vector quantization. Most frequently, the familiar Euclidean distance serves as a dissimilarity measure. We present extensions of the framework to nonstandard measures and give an introduction to the use of adaptive distances in relevance learning. © 2016 Wiley Periodicals, Inc.
Gujer, W.; Henze, M.; Mino, T.
The Activated Sludge Model No. 3 (ASM3) can predict oxygen consumption, sludge production, nitrification and denitrification of activated sludge systems. It relates to the Activated Sludge Model No. 1 (ASM1) and corrects for some defects of ASM I. In addition to ASM1, ASM3 includes storage of org...
El Shaban, Abir
The online student response system (SRS) is a technological tool that can be effectively implemented in English language classroom contexts and be used to promote students' active learning. In this qualitative study, "Socrative", a Web 2.0 software, was integrated with active learning activities and used as an SRS to explore English…
Allen, Eileen E.
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…
Álvarez Mesa, Mauricio
In the 2009 edition of the conference on “Active Learning in Engineering Education”, there were several and fruitful discussions within a small workgroup about the essence of active learning. At the end we came with an attempt to sum up our whole discussion with one question. Our question is the same as the title of this essay. Taking this question as a starting point this article propose a specific purpose from which active learning can be based. Peer Reviewed
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
Full Text Available Simulation modelling was in the mainstream of CAL development in the 1980s when the late David Squires introduced this author to the Dynamic Modelling System. Since those early days, it seems that simulation modelling has drifted into a learning technology backwater to become a member of Laurillard's underutilized, 'adaptive and productive' media. Referring to her Conversational Framework, Laurillard constructs a pedagogic case for modelling as a productive student activity but provides few references to current practice and available resources. This paper seeks to complement her account by highlighting the pioneering initiatives of the Computers in the Curriculum Project and more recent developments in systems modelling within geographic and business education. The latter include improvements to system dynamics modelling programs such as STELLA®, the publication of introductory textbooks, and the emergence of online resources. The paper indicates several ways in which modelling activities may be approached and identifies some educational development roles for learning technologists. The paper concludes by advocating simulation modelling as an exemplary use of learning technologies - one that realizes their creative-transformative potential.
Full Text Available The objective in this research: (1 Determine a better learning model to improve learning outcomes physics students among learning model Inquiry Training based multimedia and Inquiry Training learning model. (2 Determine the level of motivation to learn in affects physics student learning outcomes. (3 Knowing the interactions between the model of learning and motivation in influencing student learning outcomes. This research is a quasi experimental. The population in this research was all students in class XI SMA Negeri 1 T.P Sunggal Semester I 2012/2013. The sample of this research was consisted of two classes with a sample of 70 peoples who are determined by purposive sampling, the IPA XI-2 as a class experiment using a model-based multimedia learning Training Inquiry as many as 35 peoples and XI IPA-3 as a control class using learning model Inquiry Training 35 peoples. Hypotheses were analyzed using the GLM at significant level of 0.05 using SPSS 17.0 for Windows. Based on data analysis and hypothesis testing conducted found that: (1 Training Inquiry-based multimedia learning model in improving student learning outcomes rather than learning model physics Inquiry Training. (2 The results of studying physics students who have high motivation to learn better than students who have a low learning motivation. (3 From this research there was an interaction between learning model inquiry-based multimedia training and motivation to study on learning outcomes of students.
Verpoorten, Dominique; Poumay, M; Leclercq, D
Please, cite this publication as: Verpoorten, D., Poumay, M., & Leclercq, D. (2006). The 8 Learning Events Model: a Pedagogic Conceptual Tool Supporting Diversification of Learning Methods. Proceedings of International Workshop in Learning Networks for Lifelong Competence Development, TENCompetence
.... In the computer age, highly accurate models and simulations of the enemy can be created. However, including the effects of motivations, capabilities, and weaknesses of adversaries in current wars is still extremely difficult...
Full Text Available Aim/Purpose: This paper provides a review of previously published work related to active learning in information systems (IS courses. Background: There are a rising number of strategies in higher education that offer promise in regards to getting students’ attention and helping them learn, such as flipped classrooms and offering courses online. These learning strategies are part of the pedagogical technique known as active learning. Active learning is a strategy that became popular in the early 1990s and has proven itself as a valid tool for helping students to be engaged with learning. Methodology: This work follows a systematic method for identifying and coding previous research based on an aspect of interest. The authors identified and assessed research through a search of ABI/Inform scholarly journal abstracts and keywords, as well as additional research databases, using the search terms “active learning” and “information systems” from 2000 through June 2016. Contribution: This synthesis of active learning exercises provides guidance for information technology faculty looking to implement active learning strategies in their classroom by demonstrating how IS faculty might begin to introduce more active learning techniques in their teaching as well as by presenting a sample teaching agenda for a class that uses a mix of active and passive learning techniques to engage student learning. Findings: Twenty successful types of active learning exercises in IS courses are presented. Recommendations for Practitioners\t: This paper offers a “how to” resource of successful active learning strategies for IS faculty interested in implementing active learning in the classroom. Recommendation for Researchers: This work provides an example of a systematic literature review as a means to assess successful implementations of active learning in IS. Impact on Society: An updated definition of active learning is presented as well as a meaningful
Dalsgaard, Christian; Godsk, Mikkel
The paper presents a model for developing blended and online learning based on a given curriculum and typical learning objectives for university courses. The model consists of a three-step-process in which the instructor formulates product-oriented tasks, develops and structures the learning...... materials and tools, outlines a schedule, and supports the students' learning activity in developing a product. The model is based on our experiences with transforming traditional lecture-based lessons into problem-based blended and online learning using a social constructivist approach and a standard...... virtual learning environment (VLE). Our initial experiments indicate that our model is useful to develop blended and online modules and, furthermore, it seems fruitful to use a social constructivist framework and orienting learning activities towards the development of products....
Montrezor, Luís H.
The evaluation process is complex and extremely important in the teaching/learning process. Evaluations are constantly employed in the classroom to assist students in the learning process and to help teachers improve the teaching process. The use of active methodologies encourages students to participate in the learning process, encourages…
van den Bergh, Linda; Ros, Anje; Beijaard, Douwe
Background: Feedback is one of the most powerful tools, which teachers can use to enhance student learning. It appears dif?cult 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.…
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.
Westberry, Nicola; Franken, Margaret
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…
Traditional teaching practice based on the textbook-whiteboard- lecture-homework-test paradigm is not very effective in helping students with diverse academic backgrounds achieve higher-order critical thinking skills such as analysis, synthesis, and evaluation. Consequently, there is a critical need for developing a new pedagogical approach to create a collaborative and interactive learning environment in which students with complementary academic backgrounds and learning skills can work together to enhance their learning outcomes. In this presentation, I will discuss an innovative teaching method ('Team-Based Learning (TBL)") which I recently developed at National University of Singapore to promote active learning among students in the environmental engineering program with learning abilities. I implemented this new educational activity in a graduate course. Student feedback indicates that this pedagogical approach is appealing to most students, and promotes active & interactive learning in class. Data will be presented to show that the innovative teaching method has contributed to improved student learning and achievement.
Nasution, M. L.; Yerizon, Y.; Gusmiyanti, R.
One of the purpose mathematic learning is to develop problem solving abilities. Problem solving is obtained through experience in questioning non-routine. Improving students’ mathematical problem-solving abilities required an appropriate strategy in learning activities one of them is models problem based learning (PBL). Thus, the purpose of this research is to determine whether the problem solving abilities of mathematical students’ who learn to use PBL better than on the ability of students’ mathematical problem solving by applying conventional learning. This research included quasi experiment with static group design and population is students class XI MIA SMAN 1 Lubuk Alung. Class experiment in the class XI MIA 5 and class control in the class XI MIA 6. The instrument of final test students’ mathematical problem solving used essay form. The result of data final test in analyzed with t-test. The result is students’ mathematical problem solving abilities with PBL better then on the ability of students’ mathematical problem solving by applying conventional learning. It’s seen from the high percentage achieved by the group of students who learn to use PBL for each indicator of students’ mathematical problem solving.
Duffy, S. M.; Duffy, Alex
In this paper the need for Intelligent Computer Aided Design (Int.CAD) to jointly support design and learning assistance is introduced. The paper focuses on presenting and exploring the possibility of realizing ''learning'' assistance in Int.CAD by introducing a new concept called Shared Learning...
The most significant forces that are changing the business world and the society behaviors in this beginning of the twenty-first century can be identified into the globalization of the economy, technological evolution and convergence, change of the workers' expectations, workplace diversity and mobility, and mostly, knowledge and learning as major organizational assets. But which type of learning dynamics must be nurtured and pursued within the organizations, today, in order to generate valuable knowledge and its effective applications? After a brief discussion on the main changes observable in management, ICT and society/workplace in the last years, this chapter aims to answer to this question, through the proposition of the “Π-shaped” profile (a new professional archetype for leading change), and through the discussion of the open networked “i-Learning” model (a new framework to “incubate” innovation in learning processes). Actually, the “i” stands for “innovation” (to highlight the nature of the impact on traditional learning model), but also it stands for “incubation” (to underline the urgency to have new environments in which incubating new professional profiles). Specifically, the main key characteristics at the basis of the innovation of the learning processes will be presented and described, by highlighting the managerial, technological and societal aspects of their nature. A set of operational guidelines will be also provided to activate and sustain the innovation process, so implementing changes in the strategic dimensions of the model. Finally, the “i-Learning Radar” is presented as an operational tool to design, communicate and control an “i-Learning experience”. This tool is represented by a radar diagram with six strategic dimensions of a learning initiative.
Rayanto, Yudi Hari; Rusmawan, Putu Ngurah
The purposes of this research are to find out, (1) whether C-ID, R2D2 model is effective to be implemented on learning Reading comprehension, (2) college students' activity during the implementation of C-ID, R2D2 model on learning Reading comprehension, and 3) college students' learning achievement during the implementation of C-ID, R2D2 model on…
Lopes, Manuel; Montesano, Luis
In this survey we present different approaches that allow an intelligent agent to explore autonomous its environment to gather information and learn multiple tasks. Different communities proposed different solutions, that are in many cases, similar and/or complementary. These solutions include active learning, exploration/exploitation, online-learning and social learning. The common aspect of all these approaches is that it is the agent to selects and decides what information to gather next. ...
Foshee, Cecile M; Mehdi, Ali; Bierer, S Beth; Traboulsi, Elias I; Isaacson, J Harry; Spencer, Abby; Calabrese, Cassandra; Burkey, Brian B
Using the frameworks of transformational learning and situated learning theory, we developed a technology-enhanced professionalism curricular model to build a learning community aimed at promoting residents' self-reflection and self-awareness. The RAPR model had 4 components: (1) R ecognize : elicit awareness; (2) A ppreciate : question assumptions and take multiple perspectives; (3) P ractice : try new/changed perspectives; and (4) R eflect : articulate implications of transformed views on future actions. The authors explored the acceptability and practicality of the RAPR model in teaching professionalism in a residency setting, including how residents and faculty perceive the model, how well residents carry out the curricular activities, and whether these activities support transformational learning. A convenience sample of 52 postgraduate years 1 through 3 internal medicine residents participated in the 10-hour curriculum over 4 weeks. A constructivist approach guided the thematic analysis of residents' written reflections, which were a required curricular task. A total of 94% (49 of 52) of residents participated in 2 implementation periods (January and March 2015). Findings suggested that RAPR has the potential to foster professionalism transformation in 3 domains: (1) attitudinal, with participants reporting they viewed professionalism in a more positive light and felt more empathetic toward patients; (2) behavioral, with residents indicating their ability to listen to patients increased; and (3) cognitive, with residents indicating the discussions improved their ability to reflect, and this helped them create meaning from experiences. Our findings suggest that RAPR offers an acceptable and practical strategy to teach professionalism to residents.
Nardello, Marco; Møller, Charles; Gøtze, John
of an emerging technical standard specific for the manufacturing industry. Global manufacturing experts consider the Reference Architecture Model Industry 4.0 (RAMI4.0) as one of the corner stones for the implementation of Industry 4.0. The instantiation contributed to organizational learning in the laboratory...
Biehl, Michael; Hammer, Barbara; Villmann, Thomas
An overview is given of prototype-based models in machine learning. In this framework, observations, i.e., data, are stored in terms of typical representatives. Together with a suitable measure of similarity, the systems can be employed in the context of unsupervised and supervised analysis of
Rulloda, Rudolfo Barcena
Many classroom teachers are still using the traditional teaching methods. The traditional teaching methods are one-way learning process, where teachers would introduce subject contents such as language arts, English, mathematics, science, and reading separately. However, the school improvement model takes into account that all students have…
Liaw, Shu-Sheng; Huang, Hsiu-Mei
This paper investigates the use of e-books as learning tools in terms of learner satisfaction, usefulness, behavioral intention, and learning effectiveness. Based on the activity theory approach, this research develops a research model to understand learner attitudes toward e-books in two physical sizes: 10? and 7?. Results suggest that screen…
Lunenberg, Mieke L.; Volman, Monique
This article discusses how teachers and adult, female, immigrant students in basic education deal with active learning. The study orientations, mental models of learning and images of ideal students of the two groups are compared both with each other and with actual educational practice, in order to
Pepin, Jacinthe; Dubois, Sylvie; Girard, Francine; Tardif, Jacques; Ha, Laurence
Cognitive modeling of competencies is important to facilitate learning and evaluation. Clinical nursing leadership is considered a competency, as it is a "complex know-act" that students and nurses develop for the quality of care of patients and their families. Previous research on clinical leadership describes the attributes and characteristics of leaders and leadership, but, to our knowledge, a cognitive learning model (CLM) has yet to be developed. The purpose of our research was to develop a CLM of the clinical nursing leadership competency, from the beginning of a nursing program to expertise. An interpretative phenomenological study design was used 1) to document the experience of learning and practicing clinical leadership, and 2) to identify critical-learning turning points. Data was gathered from interviews with 32 baccalaureate students and 21 nurses from two clinical settings. An inductive analysis of data was conducted to determine the learning stages experienced: awareness of clinical leadership in nursing; integration of clinical leadership in actions; active leadership with patient/family; active leadership with the team; and, embedded clinical leadership extended to organizational level and beyond. The resulting CLM could have significant impact on both basic and continuing nursing education. Copyright © 2010 Elsevier Ltd. All rights reserved.
Balslev, Daniela; Nielsen, Finn Å; Futiger, Sally A
Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel......-time series. The optimal number of clusters was chosen using a cross-validated likelihood method, which highlights the clustering pattern that generalizes best over the subjects. Data were acquired with PET at different time points during practice of a visuomotor task. The results from cluster analysis show...
Patricia Alejandra Behar
This article brings forth an overview of the paradigmatic crisis and the introduction of new pedagogical practices. It also discusses the relationship between paradigm and pedagogical model, presenting a theoretical discussion on the concepts of pedagogical model for E-learning and its pedagogical architecture. To do so, the elements that are part of it such as organizational aspects, content, methodological and technological aspects are discussed. This theoretical discussion underlies the co...
This report is a part of the reporting of the work done in the project 'Active Control of Wind Turbines'. This project aim is to develop a simulation model for design of control systems for turbines with pitch control and to use that model to designcontrollers. This report describes the model...... validation as well as parameter estimation. The model includes a simple model of the structure of the turbine including tower and flapwise blade bending,a detailed model of the gear box and induction generator, a linearized aerodynamic model including modelling of induction lag and actuator and sensor models...
Alshareef, Abdurrahman; Sarjoughian, Hessam S.; Zarrin, Bahram
architecture and the UML concepts. In this paper, we further this work by grounding Activity-based DEVS modeling and developing a fully-fledged modeling engine to demonstrate applicability. We also detail the relevant aspects of the created metamodel in terms of modeling and simulation. A significant number......Use of model-driven approaches has been increasing to significantly benefit the process of building complex systems. Recently, an approach for specifying model behavior using UML activities has been devised to support the creation of DEVS models in a disciplined manner based on the model driven...... of the artifacts of the UML 2.5 activities and actions, from the vantage point of DEVS behavioral modeling, is covered in details. Their semantics are discussed to the extent of time-accurate requirements for simulation. We characterize them in correspondence with the specification of the atomic model behavior. We...
Pardede, Dahlia Megawati; Manurung, Sondang Rina
The purposes of the research are: (a) to determine differences in learning outcomes of students with Inquiry Training models and conventional models, (b) to determine differences in physics learning outcomes of students who have high motivation and low motivation, (c) to determine the interaction between learning models with the level of motivation in improving student Physics learning outcomes. The results were found: (a) there are differences in physical students learning outcomes are taugh...
Zeng, Jia; Cheung, William K; Liu, Jiming
Latent Dirichlet allocation (LDA) is an important hierarchical Bayesian model for probabilistic topic modeling, which attracts worldwide interest and touches on many important applications in text mining, computer vision and computational biology. This paper represents the collapsed LDA as a factor graph, which enables the classic loopy belief propagation (BP) algorithm for approximate inference and parameter estimation. Although two commonly used approximate inference methods, such as variational Bayes (VB) and collapsed Gibbs sampling (GS), have gained great success in learning LDA, the proposed BP is competitive in both speed and accuracy, as validated by encouraging experimental results on four large-scale document datasets. Furthermore, the BP algorithm has the potential to become a generic scheme for learning variants of LDA-based topic models in the collapsed space. To this end, we show how to learn two typical variants of LDA-based topic models, such as author-topic models (ATM) and relational topic models (RTM), using BP based on the factor graph representations.
Huerta-Wong, Juan Enrique; Schoech, Richard
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…
Ogawa, Nobuyuki; Shimizu, Akira
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…
Nguyen, Tam N.
Machine learning is gaining popularity in the network security domain as many more network-enabled devices get connected, as malicious activities become stealthier, and as new technologies like Software Defined Networking emerge. Compromising machine learning model is a desirable goal. In fact, spammers have been quite successful getting through machine learning enabled spam filters for years. While previous works have been done on adversarial machine learning, none has been considered within...
Strunk, Amber; Gazdovich, Jennifer; Redouté, Oriane; Reverte, Juan Manuel; Shelley, Samantha; Todorova, Vesela
This paper provides a brief introduction to antimatter and how it, along with other modern physics topics, is utilized in positron emission tomography (PET) scans. It further describes a hands-on activity for students to help them gain an understanding of how PET scans assist in detecting cancer. Modern physics topics provide an exciting way to introduce students to current applications of physics.
Agyei, D.D.; Voogt, J.
This study examined 100 beginning teachers’ transfer of learning when utilising Information Communication Technology-enhanced activity-based learning activities. The beginning teachers had participated in a professional development program that was characterised by ‘learning technology by
Doll, Bradley B; Bath, Kevin G; Daw, Nathaniel D; Frank, Michael J
Considerable evidence suggests that multiple learning systems can drive behavior. Choice can proceed reflexively from previous actions and their associated outcomes, as captured by "model-free" learning algorithms, or flexibly from prospective consideration of outcomes that might occur, as captured by "model-based" learning algorithms. However, differential contributions of dopamine to these systems are poorly understood. Dopamine is widely thought to support model-free learning by modulating plasticity in striatum. Model-based learning may also be affected by these striatal effects, or by other dopaminergic effects elsewhere, notably on prefrontal working memory function. Indeed, prominent demonstrations linking striatal dopamine to putatively model-free learning did not rule out model-based effects, whereas other studies have reported dopaminergic modulation of verifiably model-based learning, but without distinguishing a prefrontal versus striatal locus. To clarify the relationships between dopamine, neural systems, and learning strategies, we combine a genetic association approach in humans with two well-studied reinforcement learning tasks: one isolating model-based from model-free behavior and the other sensitive to key aspects of striatal plasticity. Prefrontal function was indexed by a polymorphism in the COMT gene, differences of which reflect dopamine levels in the prefrontal cortex. This polymorphism has been associated with differences in prefrontal activity and working memory. Striatal function was indexed by a gene coding for DARPP-32, which is densely expressed in the striatum where it is necessary for synaptic plasticity. We found evidence for our hypothesis that variations in prefrontal dopamine relate to model-based learning, whereas variations in striatal dopamine function relate to model-free learning. Decisions can stem reflexively from their previously associated outcomes or flexibly from deliberative consideration of potential choice outcomes
Naik, Armaghan W; Kangas, Joshua D; Sullivan, Devin P; Murphy, Robert F
High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or separate screens. Ideally, data-driven experimentation could be used to learn accurate models for many conditions and targets without doing all possible experiments. We have previously described an active machine learning algorithm that can iteratively choose small sets of experiments to learn models of multiple effects. We now show that, with no prior knowledge and with liquid handling robotics and automated microscopy under its control, this learner accurately learned the effects of 48 chemical compounds on the subcellular localization of 48 proteins while performing only 29% of all possible experiments. The results represent the first practical demonstration of the utility of active learning-driven biological experimentation in which the set of possible phenotypes is unknown in advance.
Ibáñez, María Blanca; Delgado Kloos, Carlos; Di Serio, Angela
Proceedings of: Across Spaces11 Workshop in conjunction with the EC-TEL2011, Palermo, Italy, September 21, 2011 In this paper we show how Augmented Reality (AR) technology restricted to the use of mobiles or PCs, can be used to develop learning activities with the minimun level of orchestation required by meaningful learning sequences. We use Popcode as programming language to deploy orchestrated learning activities specified with an AR framework. Publicado
Khumrin, Piyapong; Ryan, Anna; Judd, Terry; Verspoor, Karin
Computer-aided learning systems (e-learning systems) can help medical students gain more experience with diagnostic reasoning and decision making. Within this context, providing feedback that matches students' needs (i.e. personalised feedback) is both critical and challenging. In this paper, we describe the development of a machine learning model to support medical students' diagnostic decisions. Machine learning models were trained on 208 clinical cases presenting with abdominal pain, to predict five diagnoses. We assessed which of these models are likely to be most effective for use in an e-learning tool that allows students to interact with a virtual patient. The broader goal is to utilise these models to generate personalised feedback based on the specific patient information requested by students and their active diagnostic hypotheses.
Dahlia Megawati Pardede
Full Text Available The purposes of the research are: (a to determine differences in learning outcomes of students with Inquiry Training models and conventional models, (b to determine differences in physics learning outcomes of students who have high motivation and low motivation, (c to determine the interaction between learning models with the level of motivation in improving student Physics learning outcomes. The results were found: (a there are differences in physical students learning outcomes are taught by Inquiry Training models and conventional models. (b learning outcomes of students who are taught by Inquiry Learning Model Training better than student learning outcomes are taught with conventional model. (c there is a difference in student's learning outcomes that have high motivation and low motivation. (d Student learning outcomes that have a high motivation better than student learning outcomes than have a low motivation. (e there is interaction between learning and motivation to student learning outcomes. Learning outcomes of students who are taught by the model is influenced also by the motivation, while learning outcomes of students who are taught with conventional models are not affected by motivation.
Full Text Available In current eLearning models and implementations (e.g. Learning Management Systems-LMS there is a lack of engagement between formal and informal activities. Furthermore, the online methodology focuses on a standard set of units of learning and learning objects, along with pre-defined tests, and collateral resources like, i.e. discussion fora and message wall. They miss the huge potential of learning via the interlacement of social networks, LMS and external sources. Thanks to user behaviour, user interaction, and personalised counselling by a tutor, learning performance can be improved. We design and develop an adaptation eLearning model for restricted social networks, which supports this approach. In addition, we build an eLearning module that implements this conceptual model in a real application case, and present the preliminary analysis and positive results.
Hunter, William J.
In the first two parts of this series, ("Teaching for Engagement: Part 1: Constructivist Principles, Case-Based Teaching, and Active Learning") and ("Teaching for Engagement: Part 2: Technology in the Service of Active Learning"), William J. Hunter sought to outline the theoretical rationale and research basis for such active…
Elliott, Steven; Combs, Sue; Huelskamp, Amelia; Hritz, Nancy
Creative K-12 health teachers can engage students in large classes by utilizing active learning strategies. Active learning involves engaging students in higher-order tasks, such as analysis and synthesis, which is a crucial element of the movement toward what is commonly called "learner-centered" teaching. Health education teachers who…
Researchers from various disciplines have long been interested in analyzing and describing human mobility patterns. Activity space (AS), defined as an area encapsulating daily human mobility and activities, has been at the center of this interest. However, given the applied nature of research in this field and the complexity that advanced geographical modeling can pose to its users, the proposed models remain simplistic and inaccurate in many cases. Individualized Activity Space Modeler (IASM) is a geographic information system (GIS) toolbox, written in Python programming language using ESRI's Arcpy module, comprising four tools aiming to facilitate the use of advanced activity space models in empirical research. IASM provides individual-based and context-sensitive tools to estimate home range distances, delineate activity spaces, and model place exposures using individualized geographical data. In this paper, we describe the design and functionality of IASM, and provide an example of how it performs on a spatial dataset collected through an online map-based survey.
Genís, Carme Torras
While the ability of animals to learn rhythms is an unquestionable fact, the underlying neurophysiological mechanisms are still no more than conjectures. This monograph explores the requirements of such mechanisms, reviews those previously proposed and postulates a new one based on a direct electric coding of stimulation frequencies. Experi mental support for the option taken is provided both at the single neuron and neural network levels. More specifically, the material presented divides naturally into four parts: a description of the experimental and theoretical framework where this work becomes meaningful (Chapter 2), a detailed specifica tion of the pacemaker neuron model proposed together with its valida tion through simulation (Chapter 3), an analytic study of the behavior of this model when submitted to rhythmic stimulation (Chapter 4) and a description of the neural network model proposed for learning, together with an analysis of the simulation results obtained when varying seve ral factors r...
Full Text Available The study was to develop a Biology learning evaluation model in senior high schools that referred to the research and development model by Borg & Gall and the logic model. The evaluation model included the components of input, activities, output and outcomes. The developing procedures involved a preliminary study in the form of observation and theoretical review regarding the Biology learning evaluation in senior high schools. The product development was carried out by designing an evaluation model, designing an instrument, performing instrument experiment and performing implementation. The instrument experiment involved teachers and Students from Grade XII in senior high schools located in the City of Yogyakarta. For the data gathering technique and instrument, the researchers implemented observation sheet, questionnaire and test. The questionnaire was applied in order to attain information regarding teacher performance, learning performance, classroom atmosphere and scientific attitude; on the other hand, test was applied in order to attain information regarding Biology concept mastery. Then, for the analysis of instrument construct, the researchers performed confirmatory factor analysis by means of Lisrel 0.80 software and the results of this analysis showed that the evaluation instrument valid and reliable. The construct validity was between 0.43-0.79 while the reliability of measurement model was between 0.88-0.94. Last but not the least, the model feasibility test showed that the theoretical model had been supported by the empirical data.
O'Donnell, Eileen; Wade, Vincent; Sharp, Mary; O'Donnell, Liam
This book chapter reviews some of the challenges encountered by educators in creating personalised e-learning activities to suit students learning preferences. Technology-enhanced learning (TEL) alternatively known as e-learning has not yet reached its full potential in higher education. There are still many potential uses as yet undiscovered and other discovered uses which are not yet realisable by many educators. TEL is still predominantly used for e-dissemination and e-administration. This...
McCullagh, P; Meyer, K N
It has been assumed that demonstrating the correct movement is the best way to impart task-relevant information. However, empirical verification with simple laboratory skills has shown that using a learning model (showing an individual in the process of acquiring the skill to be learned) may accelerate skill acquisition and increase retention more than using a correct model. The purpose of the present study was to compare the effectiveness of viewing correct versus learning models on the acquisition of a sport skill (free-weight squat lift). Forty female participants were assigned to four learning conditions: physical practice receiving feedback, learning model with model feedback, correct model with model feedback, and learning model without model feedback. Results indicated that viewing either a correct or learning model was equally effective in learning correct form in the squat lift.
Full Text Available Individuals differ in their ability to learn how to regulate the alpha activity by neurofeedback. This study aimed to investigate whether the resting alpha activity is related to the learning ability of alpha enhancement in neurofeedback and could be used as a predictor. A total of 25 subjects performed 20 sessions of individualized alpha neurofeedback in order to learn how to enhance activity in the alpha frequency band. The learning ability was assessed by three indices respectively: the training parameter changes between two periods, within a short period and across the whole training time. It was found that the resting alpha amplitude measured before training had significant positive correlations with all learning indices and could be used as a predictor for the learning ability prediction. This finding would help the researchers in not only predicting the training efficacy in individuals but also gaining further insight into the mechanisms of alpha neurofeedback.
Full Text Available Modern engineering programs have to address rapidly changing technical content and have to enable students to develop transferable skills such as critical evaluation, communication skills and lifelong learning. This paper introduces a combined learning and assessment activity that provides students with opportunities to develop and practice their soft skills, but also extends their theoretical knowledge base. Key tasks included self directed inquiry, oral and written communication as well as peer assessment. To facilitate the SPIDER activities (Select, Prepare and Investigate, Discuss, Evaluate, Reflect, a software tool has been implemented in the learning management system Moodle. Evidence shows increased student engagement and better learning outcomes for both transferable as well as technical skills. The study focuses on generalising the relationship between learning outcomes and assignment tasks as well as activities that drive these tasks. Trail results inform the approach. Staff evaluations and their views of assignments and intended learning outcomes also supported this analysis.
Madar, Ravit; Rotter, Aviva; Waldman Ben-Asher, Hiba; Mughal, Mohamed R; Arumugam, Thiruma V; Wood, W H; Becker, K G; Mattson, Mark P; Okun, Eitan
Neuroinflammation in the central nervous system is detrimental for learning and memory, as evident form epidemiological studies linking developmental defects and maternal exposure to harmful pathogens. Postnatal infections can also induce neuroinflammatory responses with long-term consequences. These inflammatory responses can lead to motor deficits and/or behavioral disabilities. Toll like receptors (TLRs) are a family of innate immune receptors best known as sensors of microbial-associated molecular patterns, and are the first responders to infection. TLR2 forms heterodimers with either TLR1 or TLR6, is activated in response to gram-positive bacterial infections, and is expressed in the brain during embryonic development. We hypothesized that early postnatal TLR2-mediated neuroinflammation would adversely affect cognitive behavior in the adult. Our data indicate that postnatal TLR2 activation affects learning and memory in adult mice in a heterodimer-dependent manner. TLR2/6 activation improved motor function and fear learning, while TLR2/1 activation impaired spatial learning and enhanced fear learning. Moreover, developmental TLR2 deficiency significantly impairs spatial learning and enhances fear learning, stressing the involvement of the TLR2 pathway in learning and memory. Analysis of the transcriptional effects of TLR2 activation reveals both common and unique transcriptional programs following heterodimer-specific TLR2 activation. These results imply that adult cognitive behavior could be influenced in part, by activation or alterations in the TLR2 pathway at birth. Copyright © 2015 Elsevier Inc. All rights reserved.
This paper reports on a study aiming to develop a metadata model for e-learning coordination based on semantic web languages. A survey of e-learning modes are done initially in order to identify content such as phases, activities, data schema, rules and relations, etc. relevant for a coordination model. In this respect, the study looks into the…
Johnson, Tristan E.; Lee, Youngmin
In an effort to better understand learning teams, this study examines the effects of shared mental models on team and individual performance. The results indicate that each team's shared mental model changed significantly over the time that subjects participated in team-based learning activities. The results also showed that the shared mental…
Research and development activities would involve the scaled modelling activities in order to investigate theory, facts, thesis or concepts. In commercialisation activities, scaling-up proses is necessary for the development of pilot plants or prototypes. The issue with scaled modelling is the similarity between the small scaled model and the full scaled prototype in all aspects of the system such as physical appearance, dimension and the system behaviour. Similarly, for scaling-up process, physical parameters and behaviour of a smaller model need to be developed into a bigger prototype with similar system. Either way, the modelling process must be able to produce a reliable representation of the system or process so that the objectives or functions of the system can be achieved. This paper discusses a modelling method which may be able to produce similar representation of any system or process either in scaled-model testing or scaling-up processes. (author)
Harrison, David J.; Saito, Laurel; Markee, Nancy; Herzog, Serge
To examine the impact of a hybrid-flipped model utilising active learning techniques, the researchers inverted one section of an undergraduate fluid mechanics course, reduced seat time, and engaged in active learning sessions in the classroom. We compared this model to the traditional section on four performance measures. We employed a propensity…
Each year thousands of students across the country and across the academic disciplines participate in service learning. Unfortunately, with no clear model for integrating community service into the physics curriculum, there are very few physics students engaged in service learning. To overcome this shortfall, a consultant based service-learning program has been developed and successfully implemented at Saint Anselm College (SAC). As consultants, students in upper level physics courses apply their problem solving skills in the service of others. Most recently, SAC students provided technical and managerial support to a group from Girl's Inc., a national empowerment program for girls in high-risk, underserved areas, who were participating in the national FIRST Lego League Robotics competition. In their role as consultants the SAC students provided technical information through brainstorming sessions and helped the girls stay on task with project management techniques, like milestone charting. This consultant model of service-learning, provides technical support to groups that may not have a great deal of resources and gives physics students a way to improve their interpersonal skills, test their technical expertise, and better define the marketable skill set they are developing through the physics curriculum.
Rau, Martina A.; Kennedy, Kristopher; Oxtoby, Lucas; Bollom, Mark; Moore, John W.
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…
van den Bergh, Linda; Ros, Anje; Beijaard, Douwe
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.
Holden, William R.
This article describes a variety of ways learners can help themselves remember new words, choosing the ones that best suit their learning styles. It is asserted that repeated exposure to new lexical items using a variety of means is the most consistent predictor of retention. The use of verbal, visual, tactile, textual, kinesthetic, and sonic…
Full Text Available Sydney Y Rucker,1 Zulfukar Ozdogan,1 Morhaf Al Achkar2 1School of Education, Indiana University, Bloomington, IN, 2Department of Family Medicine, School of Medicine, University of Washington, Seattle, WA, USA Abstract: Journal club (JC, as a pedagogical strategy, has long been used in graduate medical education (GME. As evidence-based medicine (EBM becomes a mainstay in GME, traditional models of JC present a number of insufficiencies and call for novel models of instruction. A flipped classroom model appears to be an ideal strategy to meet the demands to connect evidence to practice while creating engaged, culturally competent, and technologically literate physicians. In this article, we describe a novel model of flipped classroom in JC. We present the flow of learning activities during the online and face-to-face instruction, and then we highlight specific considerations for implementing a flipped classroom model. We show that implementing a flipped classroom model to teach EBM in a residency program not only is possible but also may constitute improved learning opportunity for residents. Follow-up work is needed to evaluate the effectiveness of this model on both learning and clinical practice. Keywords: evidence-based medicine, flipped classroom, residency education
Boulton-Lewis, Gillian M.; Buys, Laurie
This paper reports on the findings of qualitative, semistructured interviews conducted with 40 older Australian participants who either did or did not engage in organized learning. Phenomenology was used to guide the interviews and analysis to explore the lived learning experiences and perspectives of these older people. Their experiences of…
Hassan, Mohammad Mehedi; Huda, Shamsul; Uddin, Md Zia; Almogren, Ahmad; Alrubaian, Majed
In recent years, human activity recognition from body sensor data or wearable sensor data has become a considerable research attention from academia and health industry. This research can be useful for various e-health applications such as monitoring elderly and physical impaired people at Smart home to improve their rehabilitation processes. However, it is not easy to accurately and automatically recognize physical human activity through wearable sensors due to the complexity and variety of body activities. In this paper, we address the human activity recognition problem as a classification problem using wearable body sensor data. In particular, we propose to utilize a Deep Belief Network (DBN) model for successful human activity recognition. First, we extract the important initial features from the raw body sensor data. Then, a kernel principal component analysis (KPCA) and linear discriminant analysis (LDA) are performed to further process the features and make them more robust to be useful for fast activity recognition. Finally, the DBN is trained by these features. Various experiments were performed on a real-world wearable sensor dataset to verify the effectiveness of the deep learning algorithm. The results show that the proposed DBN outperformed other algorithms and achieves satisfactory activity recognition performance.
Burgos, Daniel; Tattersall, Colin; Koper, Rob
Burgos, D., Tattersall, C., & Koper, E. J. R. (2007). Representing adaptive and adaptable Units of Learning. How to model personalized eLearning in IMS Learning Design. In B. Fernández Manjon, J. M. Sanchez Perez, J. A. Gómez Pulido, M. A. Vega Rodriguez & J. Bravo (Eds.), Computers and Education: E-learning - from theory to practice. Germany: Kluwer.
Full Text Available Teachers who currently use the traditional method teacher-centered learning, are having various difficulties with the new generations of students. New learning methods are required to allow students to focus more positive attitudes towards their learning. In this paper, we show how the evaluation and activities based on Active Learning and Gamification, can be an alternative to generate a more positive attitude of students and create a more friendly environment in the classroom. This research was conducted using the qualitative research and ethnographic method as technique.
Jensen, Jamie L.; Kummer, Tyler A.; Godoy, Patricia D. d. M.
The "flipped classroom" is a learning model in which content attainment is shifted forward to outside of class, then followed by instructor-facilitated concept application activities in class. Current studies on the flipped model are limited. Our goal was to provide quantitative and controlled data about the effectiveness of this model.…
Cavanagh, Andrew J; Aragón, Oriana R; Chen, Xinnian; Couch, Brian; Durham, Mary; Bobrownicki, Aiyana; Hanauer, David I; Graham, Mark J
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. © 2016 A. J. Cavanagh et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Ellis, R. A.; Goodyear, P.
Learning space research is a relatively new field of study that seeks to inform the design, evaluation and management of learning spaces. This paper reviews a dispersed and fragmented literature relevant to understanding connections between university learning spaces and student learning activities. From this review, the paper distils a number of…
Talko B. Dijkhuis
Full Text Available Living a sedentary lifestyle is one of the major causes of numerous health problems. To encourage employees to lead a less sedentary life, the Hanze University started a health promotion program. One of the interventions in the program was the use of an activity tracker to record participants' daily step count. The daily step count served as input for a fortnightly coaching session. In this paper, we investigate the possibility of automating part of the coaching procedure on physical activity by providing personalized feedback throughout the day on a participant's progress in achieving a personal step goal. The gathered step count data was used to train eight different machine learning algorithms to make hourly estimations of the probability of achieving a personalized, daily steps threshold. In 80% of the individual cases, the Random Forest algorithm was the best performing algorithm (mean accuracy = 0.93, range = 0.88–0.99, and mean F1-score = 0.90, range = 0.87–0.94. To demonstrate the practical usefulness of these models, we developed a proof-of-concept Web application that provides personalized feedback about whether a participant is expected to reach his or her daily threshold. We argue that the use of machine learning could become an invaluable asset in the process of automated personalized coaching. The individualized algorithms allow for predicting physical activity during the day and provides the possibility to intervene in time.
Tille, Patricia M; Hall, Heather
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.
Kelsey Hood Cattaneo
Full Text Available 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 lenses, could function as a useful tool for researchers and practitioners in comparing pedagogies. This article classified five active learning pedagogies based on six constructivist elements. The comparison was completed through a comparative analysis and a content analysis informed by a systematic literature review. The findings were that learner-centeredness is a primary goal of all pedagogies; however, there is a strong dissonance between each pedagogy’s theoretical underpinnings and implementation realities. This dissonance complicates differentiating active learning pedagogies and classification as a comparative tool has proved to have limited usefulness.
Larsen, Douglas P; Wesevich, Austin; Lichtenfeld, Jana; Artino, Antony R; Brydges, Ryan; Varpio, Lara
Learning goal programmes are often created to help students develop self-regulated learning skills; however, these programmes do not necessarily consider the social contexts surrounding learning goals or how they fit into daily educational practice. We investigated a high-frequency learning goal programme in which students generated and shared weekly learning goals with their clinical teams in core Year 3 clerkships. Our study explores: (i) how learning goals were incorporated into the clinical work, and (ii) the factors that influenced the use of students' learning goals in work-based learning. We conducted semi-structured interviews with 14 students and 14 supervisors (attending physicians and residents) sampled from all participating core clerkships. Interviews were coded for emerging themes. Using cultural historical activity theory and knotworking as theoretical lenses, we developed a model of the factors that influenced students' learning goal usage in a work-based learning context. Students and supervisors often faced the challenge of reconciling contradictions that arose when the desired outcomes of student skill development, grading and patient care were not aligned. Learning goals could function as tools for developing new ways of acting that overcame those contradictions by facilitating collaborative effort between students and their supervisors. However, for new collaborations to take place, both students and supervisors had to engage with the goals, and the necessary patients needed to be present. When any one part of the system did not converge around the learning goals, the impact of the learning goals programme was limited. Learning goals are potentially powerful tools to mediate interactions between students, supervisors and patients, and to reconcile contradictions in work-based learning environments. Learning goals provide a means to develop not only learners, but also learning systems. © 2017 John Wiley & Sons Ltd and The Association for the
Van Niekerk, B
Full Text Available Constrained Model-based Reinforcement Learning Benjamin van Niekerk School of Computer Science University of the Witwatersrand South Africa Andreas Damianou∗ Amazon.com Cambridge, UK Benjamin Rosman Council for Scientific and Industrial Research, and School... MULTIPLE SHOOTING Using direct multiple shooting (Bock and Plitt, 1984), problem (1) can be transformed into a structured non- linear program (NLP). First, the time horizon [t0, t0 + T ] is partitioned into N equal subintervals [tk, tk+1] for k = 0...
Rădulescu, Anca; Cox, Kingsley; Adams, Paul
Recent work on long term potentiation in brain slices shows that Hebb's rule is not completely synapse-specific, probably due to intersynapse diffusion of calcium or other factors. We previously suggested that such errors in Hebbian learning might be analogous to mutations in evolution. We examine this proposal quantitatively, extending the classical Oja unsupervised model of learning by a single linear neuron to include Hebbian inspecificity. We introduce an error matrix E, which expresses possible crosstalk between updating at different connections. When there is no inspecificity, this gives the classical result of convergence to the first principal component of the input distribution (PC1). We show the modified algorithm converges to the leading eigenvector of the matrix EC, where C is the input covariance matrix. In the most biologically plausible case when there are no intrinsically privileged connections, E has diagonal elements Q and off-diagonal elements (1-Q)/(n-1), where Q, the quality, is expected to decrease with the number of inputs n and with a synaptic parameter b that reflects synapse density, calcium diffusion, etc. We study the dependence of the learning accuracy on b, n and the amount of input activity or correlation (analytically and computationally). We find that accuracy increases (learning becomes gradually less useful) with increases in b, particularly for intermediate (i.e., biologically realistic) correlation strength, although some useful learning always occurs up to the trivial limit Q=1/n. We discuss the relation of our results to Hebbian unsupervised learning in the brain. When the mechanism lacks specificity, the network fails to learn the expected, and typically most useful, result, especially when the input correlation is weak. Hebbian crosstalk would reflect the very high density of synapses along dendrites, and inevitably degrades learning.
Firdaus, F.; Priatna, N.; Suhendra, S.
One of the affective factors that affect student learning outcomes is student self-esteem in mathematics, learning achievement and self-esteem influence each other. The purpose of this research is to know whether self-esteem students who get 7E learning cycle model is better than students who get conventional learning. This research method is a non-control group design. Based on the results obtained that the normal and homogeneous data so that the t test and from the test results showed there are significant differences in self-esteem students learning with 7E learning cycle model compared with students who get conventional learning. The implications of the results of this study are that students should be required to conduct many discussions, presentations and evaluations on classroom activities as these learning stages can improve students’ self-esteem especially pride in the results achieved.
Incerti, Maddalena; Horowitz, Kari; Roberson, Robin; Abebe, Daniel; Toso, Laura; Caballero, Madeline; Spong, Catherine Y
Down syndrome is the most common genetic cause of mental retardation. Active fragments of neurotrophic factors release by astrocyte under the stimulation of vasoactive intestinal peptide, NAPVSIPQ (NAP) and SALLRSIPA (SAL) respectively, have shown therapeutic potential for developmental delay and learning deficits. Previous work demonstrated that NAP+SAL prevent developmental delay and glial deficit in Ts65Dn that is a well-characterized mouse model for Down syndrome. The objective of this study is to evaluate if prenatal treatment with these peptides prevents the learning deficit in the Ts65Dn mice. Pregnant Ts65Dn female and control pregnant females were randomly treated (intraperitoneal injection) on pregnancy days 8 through 12 with saline (placebo) or peptides (NAP 20 µg +SAL 20 µg) daily. Learning was assessed in the offspring (8-10 months) using the Morris Watermaze, which measures the latency to find the hidden platform (decrease in latency denotes learning). The investigators were blinded to the prenatal treatment and genotype. Pups were genotyped as trisomic (Down syndrome) or euploid (control) after completion of all tests. two-way ANOVA followed by Neuman-Keuls test for multiple comparisons, PDown syndrome-placebo; n = 11) did not demonstrate learning over the five day period. DS mice that were prenatally exposed to peptides (Down syndrome-peptides; n = 10) learned significantly better than Down syndrome-placebo (ptreatment with the neuroprotective peptides (NAP+SAL) prevented learning deficits in a Down syndrome model. These findings highlight a possibility for the prevention of sequelae in Down syndrome and suggest a potential pregnancy intervention that may improve outcome.
Bashforth, Hedley; Parmar, Nitin R
This article suggests that the concept of ‘active learning’ has different meanings. These meanings are created in the dynamic and variable relationships between the uses of learning technologies and approaches to pedagogy. Institutions play a key role in mediating these relationships, privileging some meanings of ‘active learning’ over others. More dialogical forms of active learning call for changes in the mediating role of the institution. This article draws on a case study of the use of El...
Autio, Erkko; Hameri, Ari-Pekka; CERN. Geneva
This report analyses the technological learning and innovation benefits derived from CERN's procurement activity during the period 1997-2001. The base population of our study, the technology-intensive suppliers to CERN, consisted of 629 companies out of 6806 companies during the same period, representing 1197 MCHF in procurement. The main findings from the study can be summarized as follows: the various learning and innovation benefits (e.g., technological learning, organizational capability development, market learning) tend to occur together. Learning and innovation benefits appear to be regulated by the quality of the supplier's relationship with CERN: the greater the amount of social capital built into the relationship, the greater the learning and innovation benefits. Regardless of relationship quality, virtually all suppliers derived significant marketing reference benefits from CERN. Many corollary benefits are associated with procurement activity. As an example, as many as 38% of the respondents devel...
Nikouei Mahani, Mohammad-Ali; Haghgoo, Hojjat Allah; Azizi, Solmaz; Nili Ahmadabadi, Majid
In our daily life, we continually exploit already learned multisensory associations and form new ones when facing novel situations. Improving our associative learning results in higher cognitive capabilities. We experimentally and computationally studied the learning performance of healthy subjects in a visual-auditory sensory associative learning task across active learning, attention cueing learning, and passive learning modes. According to our results, the learning mode had no significant effect on learning association of congruent pairs. In addition, subjects' performance in learning congruent samples was not correlated with their vigilance score. Nevertheless, vigilance score was significantly correlated with the learning performance of the non-congruent pairs. Moreover, in the last block of the passive learning mode, subjects significantly made more mistakes in taking non-congruent pairs as associated and consciously reported lower confidence. These results indicate that attention and activity equally enhanced visual-auditory associative learning for non-congruent pairs, while false alarm rate in the passive learning mode did not decrease after the second block. We investigated the cause of higher false alarm rate in the passive learning mode by using a computational model, composed of a reinforcement learning module and a memory-decay module. The results suggest that the higher rate of memory decay is the source of making more mistakes and reporting lower confidence in non-congruent pairs in the passive learning mode.
Christie, Michael; de Graaff, Erik
In this paper the authors draw on three sequential keynote addresses that they gave at Active Learning in Engineering Education (ALE) workshops in Copenhagen (2012), Caxias do Sol (2014) and San Sebastian (2015). Active Learning in Engineering Education is an informal international network of engineering educators dedicated to improving engineering education through active learning (http://www.ale-net.org/). The paper reiterates themes from those keynotes, namely, the philosophical and pedagogical underpinnings of Active Learning in Engineering Education, the scholarly questions that inspire engineering educators to go on improving their practice and exemplary models designed to activate the learning of engineering students. This paper aims to uncover the bedrock of established educational philosophies and theories that define and support active learning. The paper does not claim to present any new or innovative educational theory. There is already a surfeit of them. Rather, the aim is to assist Engineering Educators who wish to research how they can best activate the learning of their students by providing a readable, reasonable and solid underpinning for best practice in this field.
This report is a part of the reporting of the work done in the project `Active Control of Wind Turbines`. This project aim is to develop a simulation model for design of control systems for turbines with pitch control and to use that model to design controllers. This report describes the model developed for controller design and analysis. Emphasis has been put on establishment of simple models describing the dynamic behavior of the wind turbine in adequate details for controller design. This has been done with extensive use of measurements as the basis for selection of model complexity and model validation as well as parameter estimation. The model includes a simple model of the structure of the turbine including tower and flapwise blade bending, a detailed model of the gear box and induction generator, a linearized aerodynamic model including modelling of induction lag and actuator and sensor models. The models are all formulated as linear differential equations. The models are validated through comparisons with measurements performed on a Vestas WD 34 400 kW wind turbine. It is shown from a control point of view simple linear models can be used to describe the dynamic behavior of a pitch controlled wind turbine. The model and the measurements corresponds well in the relevant frequency range. The developed model is therefore applicable for controller design. (au) EFP-91. 18 ills., 22 refs.
Amalia Febri Aristi
Full Text Available This study aimed to determine: (1 Is there a difference in student's learning outcomes with the application of learning models Investigation Group and Direct Instruction teaching model. (2 Is there a difference in students' motivation with the application of learning models Investigation Group and Direct Instruction teaching model, (3 Is there an interaction between learning models Investigation Group and Direct Instruction to improve students' motivation in learning outcomes Physics. This research is a quasi experimental. The study population was a student of class XII Tanjung Balai MAN. Random sample selection is done by randomizing the class. The instrument used consisted of: (1 achievement test (2 students' motivation questionnaire. The tests are used to obtain the data is shaped essay. The data in this study were analyzed using ANOVA analysis of two paths. The results showed that: (1 there were differences in learning outcomes between students who used the physics model of Group Investigation learning compared with students who used the Direct Instruction teaching model. (2 There was a difference in student's learning outcomes that had a low learning motivation and high motivation to learn both in the classroom and in the classroom Investigation Group Direct Instruction. (3 There was interaction between learning models Instruction Direct Group Investigation and motivation to learn in improving learning outcomes Physics.
Duong, Tuan; Duong, Vu; Suri, Ronald
A neural-network mathematical model that, relative to prior such models, places greater emphasis on some of the temporal aspects of real neural physical processes, has been proposed as a basis for massively parallel, distributed algorithms that learn dynamic models of possibly complex external processes by means of learning rules that are local in space and time. The algorithms could be made to perform such functions as recognition and prediction of words in speech and of objects depicted in video images. The approach embodied in this model is said to be "hardware-friendly" in the following sense: The algorithms would be amenable to execution by special-purpose computers implemented as very-large-scale integrated (VLSI) circuits that would operate at relatively high speeds and low power demands.
Gong, Maoguo; Liu, Jia; Li, Hao; Cai, Qing; Su, Linzhi
Hierarchical deep neural networks are currently popular learning models for imitating the hierarchical architecture of human brain. Single-layer feature extractors are the bricks to build deep networks. Sparse feature learning models are popular models that can learn useful representations. But most of those models need a user-defined constant to control the sparsity of representations. In this paper, we propose a multiobjective sparse feature learning model based on the autoencoder. The parameters of the model are learnt by optimizing two objectives, reconstruction error and the sparsity of hidden units simultaneously to find a reasonable compromise between them automatically. We design a multiobjective induced learning procedure for this model based on a multiobjective evolutionary algorithm. In the experiments, we demonstrate that the learning procedure is effective, and the proposed multiobjective model can learn useful sparse features.
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.
Repperger, D. W.; Goodyear, C.
An active controller was used to help train naive subjects involved in a compensatory tracking task. The controller is called active in this context because it moves the subject's hand in a direction to improve tracking. It is of interest here to question whether the active controller helps the subject to learn a task more rapidly than the passive controller. Six subjects, inexperienced to compensatory tracking, were run to asymptote root mean square error tracking levels with an active controller or a passive controller. The time required to learn the task was defined several different ways. The results of the different measures of learning were examined across pools of subjects and across controllers using statistical tests. The comparison between the active controller and the passive controller as to their ability to accelerate the learning process as well as reduce levels of asymptotic tracking error is reported here.
Tao, Yu-Hui; Yeh, C. Rosa; Hung, Kung Chin
Several theoretical models have been constructed to determine the effects of buisness simulation games (BSGs) on learning performance. Although these models agree on the concept of learning-cycle effect, no empirical evidence supports the claim that the use of learning cycle activities with BSGs produces an effect on incremental gains in knowledge…
Huang, Sheng-Jun; Jin, Rong; Zhou, Zhi-Hua
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.
Walling, Anne; Istas, Kathryn; Bonaminio, Giulia A; Paolo, Anthony M; Fontes, Joseph D; Davis, Nancy; Berardo, Benito A
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.
Abdallah, Z.; Gaber, M.; Srinivasan, B.; Krishnaswamy, S.
Activity recognition focuses on inferring current user activities by leveraging sensory data available on today’s sensor rich environment. Supervised learning has been applied pervasively for activity recognition. Typical activity recognition techniques process sensory data based on point-by-point approaches. In this paper, we propose a novel cluster-based classification for activity recognition Systems, termed StreamAR. The system incorporates incremental and active learning for mining user ...
Kossaifi, Jean; Tzimiropoulos, Georgios; Pantic, Maja
Active Appearance Models (AAMs) are statistical models of shape and appearance widely used in computer vision to detect landmarks on objects like faces. Fitting an AAM to a new image can be formulated as a non-linear least-squares problem which is typically solved using iterative methods. Owing to
Valyrakis, Manousos; Cheng, Ming
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.
Full Text Available A model is proposed to characterize the type of knowledge acquired in Artificial Grammar Learning (AGL. In particular, Shannon entropy is employed to compute the complexity of different test items in an AGL task, relative to the training items. According to this model, the more predictable a test item is from the training items, the more likely it is that this item should be selected as compatible with the training items. The predictions of the entropy model are explored in relation to the results from several previous AGL datasets and compared to other AGL measures. This particular approach in AGL resonates well with similar models in categorization and reasoning which also postulate that cognitive processing is geared towards the reduction of entropy.
Magnell, Marie; Kolmos, Anette
The focus of this paper is on how academic staff perceive their roles and responsibilities regarding work-related learning, and how they approach and implement work-related learning activities in curricula across academic environments in higher education. The study is based on case studies...
Meltzer, David E.; Thornton, Ronald K.
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.
Vrellis, Ioannis; Papachristos, Nikiforos; Natsis, Antonios
interacting with and via virtual environments and seems to play an important role in learning. This chapter presents empirical data gathered from an exploratory study regarding a problem-based physics learning activity in Second Life (SL). Our aim is to gain knowledge and experience about the sense...
Murphy, Robert F.
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
Keen, Cheryl H.; Woods, Robert
In this article, we interpreted, in light of Mezirow's theory of transformative learning, interviews with 13 educators regarding their work with marginalized adult learners in prisons in the northeastern United States. Transformative learning may have been aided by the educators' response to unplanned activating events, humor, and respect, and…
This article reports analysis of students' written reflections as to what helps them learn in an active learning environment. Eight hundred and twenty seven responses from 403 students in four different studio courses over two years were analyzed. An emergent coding scheme identified 55% of the responses as associated with cognitive processes…
Christensen, H.-P.; Vos, Henk; de Graaff, E.; Lemoult, B.
The introduction of active learning in engineering education is often started by enthusiastic teachers or change agents. They usually encounter resistance from stakeholders such as colleagues, department boards or students. For a successful introduction these stakeholders all have to learn what
Connolly, Amy; Lampe, Michael
This article describes how our university built a unique classroom environment specifically for active learning. This classroom changed students' experience in the undergraduate executive information technology (IT) management class. Every college graduate should learn to think critically, solve problems, and communicate solutions, but 90% of…
Markant, Douglas B.; Ruggeri, Azzurra; Gureckis, Todd M.; Xu, Fei
Despite widespread consensus among educators that "active learning" leads to better outcomes than comparatively passive forms of instruction, it is often unclear why these benefits arise. In this article, we review research showing that the opportunity to control the information experienced while learning leads to improved memory…
Nardello, Marco; Møller, Charles; Gøtze, John
The wave of the fourth industrial revolution (Industry 4.0) is bringing a new vision of the manufacturing industry. In manufacturing, one of the buzzwords of the moment is “Smart production”. Smart production involves manufacturing equipment with many sensors that can generate and transmit large...... amounts of data. These data and information from manufacturing operations are however not shared in the organization. Therefore the organization is not using them to learn and improve their operations. To address this problem, the authors implemented in an Industry 4.0 laboratory an instance...... of an emerging technical standard specific for the manufacturing industry. Global manufacturing experts consider the Reference Architecture Model Industry 4.0 (RAMI4.0) as one of the corner stones for the implementation of Industry 4.0. The instantiation contributed to organizational learning in the laboratory...
Bryant, D P; Bryant, B R
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.
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.
Iversen, Steffen Møllegaard
In this paper a didactical model is presented. The goal of the model is to work as a didactical tool, or conceptual frame, for developing, carrying through and evaluating interdisciplinary activities involving the subject of mathematics and philosophy in the high schools. Through the terms...... of Horizontal Intertwining, Vertical Structuring and Horizontal Propagation the model consists of three phases, each considering different aspects of the nature of interdisciplinary activities. The theoretical modelling is inspired by work which focuses on the students abilities to concept formation in expanded...... domains (Michelsen, 2001, 2005a, 2005b). Furthermore the theoretical description rest on a series of qualitative interviews with teachers from the Danish high school (grades 9-11) conducted recently. The special case of concrete interdisciplinary activities between mathematics and philosophy is also...
Aaberg, Robin Garen
The web based learning resources is believed to be playing an active role in the learning environment of higher education today. This qualitative study is exploring how students at Bergen University College incorporate web-based learning resources in their learning activities. At the core of this research is the problem of retrieving good web-resources after their first discovery. Usefull and knowledge granting web-resources are discovered within a context of topics, objectives. It is here ar...
Full Text Available 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 truly impressive implementation results of theSCALE-UP learning environment suggest that such beliefs are false (Beichner et al., 2000. In this study, we present a design of an active learning environment with positive effect on students. The design is based on the following elements: (1 helping students to learn from interactive lecture experiment; (2 guiding students to use justified explanation and prediction after observing and exploring a phenomenon; (3 developing a conceptual question sequencedesigned for use in an interactive lecture with students answering questions in worksheets by writing and drawing; (4 evaluating students’ conceptual change and gains by questions related to light reflection, refraction, and image formation in an exam held a week after the active learning session. Data were collected from 95 science freshmen with different secondary school backgrounds. They participated in geometrical optics classes organized for collecting research results during and after only one active learning session.The results have showed that around 60% of the students changed their initial alternative conceptions of vision and of image formation. It was also found that a large group of university students is likely to be engaged in active learning, shifting from a passive role they usually play during teacher’s lectures.
Romanyshyn, Yuriy; Smerdov, Andriy; Petrytska, Svitlana
On the basis of the neurophysiological strength-duration (amplitude-duration) curve of neuron activation (which relates the threshold amplitude of a rectangular current pulse of neuron activation to the pulse duration), as well as with the use of activation energy constraint (the threshold curve corresponds to the energy threshold of neuron activation by a rectangular current pulse), an energy model of neuron activation by a single current pulse has been constructed. The constructed model of activation, which determines its spectral properties, is a bandpass filter. Under the condition of minimum-phase feature of the neuron activation model, on the basis of Hilbert transform, the possibilities of phase-frequency response calculation from its amplitude-frequency response have been considered. Approximation to the amplitude-frequency response by the response of the Butterworth filter of the first order, as well as obtaining the pulse response corresponding to this approximation, give us the possibility of analyzing the efficiency of activating current pulses of various shapes, including analysis in accordance with the energy constraint.
Full Text Available In this paper we propose a strategy learning model for autonomous agents based on classification. In the literature, the most commonly used learning method in agent-based systems is reinforcement learning. In our opinion, classification can be considered a good alternative. This type of supervised learning can be used to generate a classifier that allows the agent to choose an appropriate action for execution. Experimental results show that this model can be successfully applied for strategy generation even if rewards are delayed. We compare the efficiency of the proposed model and reinforcement learning using the farmer-pest domain and configurations of various complexity. In complex environments, supervised learning can improve the performance of agents much faster that reinforcement learning. If an appropriate knowledge representation is used, the learned knowledge may be analyzed by humans, which allows tracking the learning process
Full Text Available Teaching for active learning is a pedagogical technique that has been actively promoted in Indonesian education through government reform efforts and international development assistance projects for decades. Recently, elementary schools in Banten province received training in active learning instructional strategies from the USAID-funded project, Decentralized Basic Education 2. Post-training evaluations conducted by lecturers from the University of Sultan Ageng Tirtayasa (UNTIRTA: Universitas Sultan Ageng Tirtayasa suggested that teachers were successfully employing active learning strategies in some subjects, but not mathematics. In order to understand the difficulties teachers were having in teaching for active learning in mathematics, and to assist them in using active learning strategies, a team of lecturers from UNTIRTA designed and carried out an action research project to train teachers in an elementary school in the city of Cilegon to use a technique called Magic Fingers in teaching Grade 5 multiplication. During the course of the project the research team discovered that teachers were having problems transferring knowledge gained from training in one context and subject to other school subjects and contexts. Key Words: Mathematics, Teaching for Active Learning, Indonesia, Banten
The article "Personal Coaching: A Model for Effective Learning" (Griffiths, 2006) appeared in the "Journal of Learning Design" Volume 1, Issue 2 in 2006. Almost ten years on, Kerryn Griffiths reflects upon her original article. Specifically, Griffiths looks back at the combined coaching-learning model she suggested in her…