Personalisation in Web-Based Learning Environments

ERIC Educational Resources Information Center

Santally, Mohammad Issack; Alain, Senteni

2006-01-01

It is postulated that one of the main problems with e-learning environments is their lack of personalisation. This article presents a comprehensive review of the current work in the field and proposes a framework for research in promoting personalisation in Web-based learning environments. The concepts of adaptability, adaptivity and the…

Adaptive User Model for Web-Based Learning Environment.

ERIC Educational Resources Information Center

Garofalakis, John; Sirmakessis, Spiros; Sakkopoulos, Evangelos; Tsakalidis, Athanasios

This paper describes the design of an adaptive user model and its implementation in an advanced Web-based Virtual University environment that encompasses combined and synchronized adaptation between educational material and well-known communication facilities. The Virtual University environment has been implemented to support a postgraduate…

Reinforcement learning and counterfactual reasoning explain adaptive behavior in a changing environment.

PubMed

Zhang, Yunfeng; Paik, Jaehyon; Pirolli, Peter

2015-04-01

Animals routinely adapt to changes in the environment in order to survive. Though reinforcement learning may play a role in such adaptation, it is not clear that it is the only mechanism involved, as it is not well suited to producing rapid, relatively immediate changes in strategies in response to environmental changes. This research proposes that counterfactual reasoning might be an additional mechanism that facilitates change detection. An experiment is conducted in which a task state changes over time and the participants had to detect the changes in order to perform well and gain monetary rewards. A cognitive model is constructed that incorporates reinforcement learning with counterfactual reasoning to help quickly adjust the utility of task strategies in response to changes. The results show that the model can accurately explain human data and that counterfactual reasoning is key to reproducing the various effects observed in this change detection paradigm. Copyright © 2015 Cognitive Science Society, Inc.

Metacognitive components in smart learning environment

NASA Astrophysics Data System (ADS)

Sumadyo, M.; Santoso, H. B.; Sensuse, D. I.

2018-03-01

Metacognitive ability in digital-based learning process helps students in achieving learning goals. So that digital-based learning environment should make the metacognitive component as a facility that must be equipped. Smart Learning Environment is the concept of a learning environment that certainly has more advanced components than just a digital learning environment. This study examines the metacognitive component of the smart learning environment to support the learning process. A review of the metacognitive literature was conducted to examine the components involved in metacognitive learning strategies. Review is also conducted on the results of study smart learning environment, ranging from design to context in building smart learning. Metacognitive learning strategies certainly require the support of adaptable, responsive and personalize learning environments in accordance with the principles of smart learning. The current study proposed the role of metacognitive component in smart learning environment, which is useful as the basis of research in building environment in smart learning.

Adaptive Global Innovative Learning Environment for Glioblastoma: GBM AGILE.

PubMed

Alexander, Brian M; Ba, Sujuan; Berger, Mitchel S; Berry, Donald A; Cavenee, Webster K; Chang, Susan M; Cloughesy, Timothy F; Jiang, Tao; Khasraw, Mustafa; Li, Wenbin; Mittman, Robert; Poste, George H; Wen, Patrick Y; Yung, W K Alfred; Barker, Anna D

2018-02-15

Glioblastoma (GBM) is a deadly disease with few effective therapies. Although much has been learned about the molecular characteristics of the disease, this knowledge has not been translated into clinical improvements for patients. At the same time, many new therapies are being developed. Many of these therapies have potential biomarkers to identify responders. The result is an enormous amount of testable clinical questions that must be answered efficiently. The GBM Adaptive Global Innovative Learning Environment (GBM AGILE) is a novel, multi-arm, platform trial designed to address these challenges. It is the result of the collective work of over 130 oncologists, statisticians, pathologists, neurosurgeons, imagers, and translational and basic scientists from around the world. GBM AGILE is composed of two stages. The first stage is a Bayesian adaptively randomized screening stage to identify effective therapies based on impact on overall survival compared with a common control. This stage also finds the population in which the therapy shows the most promise based on clinical indication and biomarker status. Highly effective therapies transition in an inferentially seamless manner in the identified population to a second confirmatory stage. The second stage uses fixed randomization to confirm the findings from the first stage to support registration. Therapeutic arms with biomarkers may be added to the trial over time, while others complete testing. The design of GBM AGILE enables rapid clinical testing of new therapies and biomarkers to speed highly effective therapies to clinical practice. Clin Cancer Res; 24(4); 737-43. ©2017 AACR . ©2017 American Association for Cancer Research.

Adaptive Learning Systems: Beyond Teaching Machines

ERIC Educational Resources Information Center

Kara, Nuri; Sevim, Nese

2013-01-01

Since 1950s, teaching machines have changed a lot. Today, we have different ideas about how people learn, what instructor should do to help students during their learning process. We have adaptive learning technologies that can create much more student oriented learning environments. The purpose of this article is to present these changes and its…

Applying a Framework for Student Modeling in Exploratory Learning Environments: Comparing Data Representation Granularity to Handle Environment Complexity

ERIC Educational Resources Information Center

Fratamico, Lauren; Conati, Cristina; Kardan, Samad; Roll, Ido

2017-01-01

Interactive simulations can facilitate inquiry learning. However, similarly to other Exploratory Learning Environments, students may not always learn effectively in these unstructured environments. Thus, providing adaptive support has great potential to help improve student learning with these rich activities. Providing adaptive support requires a…

Integrating Model-Driven and Data-Driven Techniques for Analyzing Learning Behaviors in Open-Ended Learning Environments

ERIC Educational Resources Information Center

Kinnebrew, John S.; Segedy, James R.; Biswas, Gautam

2017-01-01

Research in computer-based learning environments has long recognized the vital role of adaptivity in promoting effective, individualized learning among students. Adaptive scaffolding capabilities are particularly important in open-ended learning environments, which provide students with opportunities for solving authentic and complex problems, and…

Integrating Adaptive Games in Student-Centered Virtual Learning Environments

ERIC Educational Resources Information Center

del Blanco, Angel; Torrente, Javier; Moreno-Ger, Pablo; Fernandez-Manjon, Baltasar

2010-01-01

The increasing adoption of e-Learning technology is facing new challenges, such as how to produce student-centered systems that can be adapted to each student's needs. In this context, educational video games are proposed as an ideal medium to facilitate adaptation and tracking of students' performance for assessment purposes, but integrating the…

Beyond adaptive-critic creative learning for intelligent mobile robots

NASA Astrophysics Data System (ADS)

Liao, Xiaoqun; Cao, Ming; Hall, Ernest L.

2001-10-01

Intelligent industrial and mobile robots may be considered proven technology in structured environments. Teach programming and supervised learning methods permit solutions to a variety of applications. However, we believe that to extend the operation of these machines to more unstructured environments requires a new learning method. Both unsupervised learning and reinforcement learning are potential candidates for these new tasks. The adaptive critic method has been shown to provide useful approximations or even optimal control policies to non-linear systems. The purpose of this paper is to explore the use of new learning methods that goes beyond the adaptive critic method for unstructured environments. The adaptive critic is a form of reinforcement learning. A critic element provides only high level grading corrections to a cognition module that controls the action module. In the proposed system the critic's grades are modeled and forecasted, so that an anticipated set of sub-grades are available to the cognition model. The forecasting grades are interpolated and are available on the time scale needed by the action model. The success of the system is highly dependent on the accuracy of the forecasted grades and adaptability of the action module. Examples from the guidance of a mobile robot are provided to illustrate the method for simple line following and for the more complex navigation and control in an unstructured environment. The theory presented that is beyond the adaptive critic may be called creative theory. Creative theory is a form of learning that models the highest level of human learning - imagination. The application of the creative theory appears to not only be to mobile robots but also to many other forms of human endeavor such as educational learning and business forecasting. Reinforcement learning such as the adaptive critic may be applied to known problems to aid in the discovery of their solutions. The significance of creative theory is that it

Arousal regulation and affective adaptation to human responsiveness by a robot that explores and learns a novel environment.

PubMed

Hiolle, Antoine; Lewis, Matthew; Cañamero, Lola

2014-01-01

In the context of our work in developmental robotics regarding robot-human caregiver interactions, in this paper we investigate how a "baby" robot that explores and learns novel environments can adapt its affective regulatory behavior of soliciting help from a "caregiver" to the preferences shown by the caregiver in terms of varying responsiveness. We build on two strands of previous work that assessed independently (a) the differences between two "idealized" robot profiles-a "needy" and an "independent" robot-in terms of their use of a caregiver as a means to regulate the "stress" (arousal) produced by the exploration and learning of a novel environment, and (b) the effects on the robot behaviors of two caregiving profiles varying in their responsiveness-"responsive" and "non-responsive"-to the regulatory requests of the robot. Going beyond previous work, in this paper we (a) assess the effects that the varying regulatory behavior of the two robot profiles has on the exploratory and learning patterns of the robots; (b) bring together the two strands previously investigated in isolation and take a step further by endowing the robot with the capability to adapt its regulatory behavior along the "needy" and "independent" axis as a function of the varying responsiveness of the caregiver; and (c) analyze the effects that the varying regulatory behavior has on the exploratory and learning patterns of the adaptive robot.

Approach for Using Learner Satisfaction to Evaluate the Learning Adaptation Policy

ERIC Educational Resources Information Center

Jeghal, Adil; Oughdir, Lahcen; Tairi, Hamid; Radouane, Abdelhay

2016-01-01

The learning adaptation is a very important phase in a learning situation in human learning environments. This paper presents the authors' approach used to evaluate the effectiveness of learning adaptive systems. This approach is based on the analysis of learner satisfaction notices collected by a questionnaire on a learning situation; to analyze…

Arousal regulation and affective adaptation to human responsiveness by a robot that explores and learns a novel environment

PubMed Central

Hiolle, Antoine; Lewis, Matthew; Cañamero, Lola

2014-01-01

In the context of our work in developmental robotics regarding robot–human caregiver interactions, in this paper we investigate how a “baby” robot that explores and learns novel environments can adapt its affective regulatory behavior of soliciting help from a “caregiver” to the preferences shown by the caregiver in terms of varying responsiveness. We build on two strands of previous work that assessed independently (a) the differences between two “idealized” robot profiles—a “needy” and an “independent” robot—in terms of their use of a caregiver as a means to regulate the “stress” (arousal) produced by the exploration and learning of a novel environment, and (b) the effects on the robot behaviors of two caregiving profiles varying in their responsiveness—“responsive” and “non-responsive”—to the regulatory requests of the robot. Going beyond previous work, in this paper we (a) assess the effects that the varying regulatory behavior of the two robot profiles has on the exploratory and learning patterns of the robots; (b) bring together the two strands previously investigated in isolation and take a step further by endowing the robot with the capability to adapt its regulatory behavior along the “needy” and “independent” axis as a function of the varying responsiveness of the caregiver; and (c) analyze the effects that the varying regulatory behavior has on the exploratory and learning patterns of the adaptive robot. PMID:24860492

Online adaptation and over-trial learning in macaque visuomotor control.

PubMed

Braun, Daniel A; Aertsen, Ad; Paz, Rony; Vaadia, Eilon; Rotter, Stefan; Mehring, Carsten

2011-01-01

When faced with unpredictable environments, the human motor system has been shown to develop optimized adaptation strategies that allow for online adaptation during the control process. Such online adaptation is to be contrasted to slower over-trial learning that corresponds to a trial-by-trial update of the movement plan. Here we investigate the interplay of both processes, i.e., online adaptation and over-trial learning, in a visuomotor experiment performed by macaques. We show that simple non-adaptive control schemes fail to perform in this task, but that a previously suggested adaptive optimal feedback control model can explain the observed behavior. We also show that over-trial learning as seen in learning and aftereffect curves can be explained by learning in a radial basis function network. Our results suggest that both the process of over-trial learning and the process of online adaptation are crucial to understand visuomotor learning.

Towards Motivation-Based Adaptation of Difficulty in E-Learning Programs

ERIC Educational Resources Information Center

Endler, Anke; Rey, Gunter Daniel; Butz, Martin V.

2012-01-01

The objective of this study was to investigate if an e-learning environment may use measurements of the user's current motivation to adapt the level of task difficulty for more effective learning. In the reported study, motivation-based adaptation was applied randomly to collect a wide range of data for different adaptations in a variety of…

Online Adaptation and Over-Trial Learning in Macaque Visuomotor Control

PubMed Central

Braun, Daniel A.; Aertsen, Ad; Paz, Rony; Vaadia, Eilon; Rotter, Stefan; Mehring, Carsten

2011-01-01

When faced with unpredictable environments, the human motor system has been shown to develop optimized adaptation strategies that allow for online adaptation during the control process. Such online adaptation is to be contrasted to slower over-trial learning that corresponds to a trial-by-trial update of the movement plan. Here we investigate the interplay of both processes, i.e., online adaptation and over-trial learning, in a visuomotor experiment performed by macaques. We show that simple non-adaptive control schemes fail to perform in this task, but that a previously suggested adaptive optimal feedback control model can explain the observed behavior. We also show that over-trial learning as seen in learning and aftereffect curves can be explained by learning in a radial basis function network. Our results suggest that both the process of over-trial learning and the process of online adaptation are crucial to understand visuomotor learning. PMID:21720526

MEAT: An Authoring Tool for Generating Adaptable Learning Resources

ERIC Educational Resources Information Center

Kuo, Yen-Hung; Huang, Yueh-Min

2009-01-01

Mobile learning (m-learning) is a new trend in the e-learning field. The learning services in m-learning environments are supported by fundamental functions, especially the content and assessment services, which need an authoring tool to rapidly generate adaptable learning resources. To fulfill the imperious demand, this study proposes an…

Moving Past Curricula and Strategies: Language and the Development of Adaptive Pedagogy for Immersive Learning Environments

NASA Astrophysics Data System (ADS)

Hand, Brian; Cavagnetto, Andy; Chen, Ying-Chih; Park, Soonhye

2016-04-01

Given current concerns internationally about student performance in science and the need to shift how science is being learnt in schools, as a community, we need to shift how we approach the issue of learning and teaching in science. In the future, we are going to have to close the gap between how students construct and engage with knowledge in a media-rich environment, and how school classroom environments engage them. This is going to require a shift to immersive environments where attention is paid to the knowledge bases and resources students bring into the classroom. Teachers will have to adopt adaptive pedagogical approaches that are framed around a more nuanced understanding of epistemological orientation, language and the nature of prosocial environments.

U-ALS: A Ubiquitous Learning Environment

ERIC Educational Resources Information Center

Piovesan, Sandra Dutra; Passerino, Liliana Maria; Medina, Roseclea Duarte

2012-01-01

The diffusion of the use of the learning virtual environments presents a great potential for the development of an application which meet the necessities in the education area. In view of the importance of a more dynamic application and that can adapt itself continuously to the students' necessities, the "U-ALS" (Ubiquitous Adapted Learning…

Wireless Adaptive Therapeutic TeleGaming in a Pervasive Computing Environment

NASA Astrophysics Data System (ADS)

Peters, James F.; Szturm, Tony; Borkowski, Maciej; Lockery, Dan; Ramanna, Sheela; Shay, Barbara

This chapter introduces a wireless, pervasive computing approach to adaptive therapeutic telegaming considered in the context of near set theory. Near set theory provides a formal basis for observation, comparison and classification of perceptual granules. A perceptual granule is defined by a collection of objects that are graspable by the senses or by the mind. In the proposed pervasive computing approach to telegaming, a handicapped person (e.g., stroke patient with limited hand, finger, arm function) plays a video game by interacting with familiar instrumented objects such as cups, cutlery, soccer balls, nozzles, screw top-lids, spoons, so that the technology that makes therapeutic exercise game-playing possible is largely invisible (Archives of Physical Medicine and Rehabilitation 89:2213-2217, 2008). The basic approach to adaptive learning (AL) in the proposed telegaming environment is ethology-inspired and is quite different from the traditional approach to reinforcement learning. In biologically-inspired learning, organisms learn to achieve some goal by durable modification of behaviours in response to signals from the environment resulting from specific experiences (Animal Behavior, 1995). The term adaptive is used here in an ethological sense, where learning by an organism results from modifying behaviour in response to perceived changes in the environment. To instill adaptivity in a video game, it is assumed that learning by a video game is episodic. During an episode, the behaviour of a player is measured indirectly by tracking the occurrence of gaming events such as a hit or a miss of a target (e.g., hitting a moving ball with a game paddle). An ethogram provides a record of behaviour feature values that provide a basis a functional registry for handicapped players for gaming adaptivity. An important practical application of adaptive gaming is therapeutic rehabilitation exercise carried out in parallel with playing action video games. Enjoyable and

Can More Become Less? Effects of an Intensive Assessment Environment on Students' Learning Performance

ERIC Educational Resources Information Center

Khawaja, M. Asif; Prusty, Gangadhara B.; Ford, Robin A. J.; Marcus, Nadine; Russell, Carol

2013-01-01

Online interactive systems offer the beguiling prospect of an improved environment for learning at minimum extra cost. We have developed online interactive tutorials that adapt the learning environment to the current learning status of each individual student. These Adaptive Tutorials (ATs) modify the tasks given to each student according to their…

Learning Experiences Reuse Based on an Ontology Modeling to Improve Adaptation in E-Learning Systems

ERIC Educational Resources Information Center

Hadj M'tir, Riadh; Rumpler, Béatrice; Jeribi, Lobna; Ben Ghezala, Henda

2014-01-01

Current trends in e-Learning focus mainly on personalizing and adapting the learning environment and learning process. Although their increasingly number, theses researches often ignore the concepts of capitalization and reuse of learner experiences which can be exploited later by other learners. Thus, the major challenge of distance learning is…

Adaptive 3D Virtual Learning Environments--A Review of the Literature

ERIC Educational Resources Information Center

Scott, Ezequiel; Soria, Alvaro; Campo, Marcelo

2017-01-01

New ways of learning have emerged in the last years by using computers in education. For instance, many Virtual Learning Environments have been widely adopted by educators, obtaining promising outcomes. Recently, these environments have evolved into more advanced ones using 3D technologies and taking into account the individual learner needs and…

Co-Evolution of Social Learning and Evolutionary Preparedness in Dangerous Environments

PubMed Central

Lindström, Björn; Selbing, Ida; Olsson, Andreas

2016-01-01

Danger is a fundamental aspect of the lives of most animals. Adaptive behavior therefore requires avoiding actions, objects, and environments associated with danger. Previous research has shown that humans and non-human animals can avoid such dangers through two types of behavioral adaptions, (i) genetic preparedness to avoid certain stimuli or actions, and (ii) social learning. These adaptive mechanisms reduce the fitness costs associated with danger but still allow flexible behavior. Despite the empirical prevalence and importance of both these mechanisms, it is unclear when they evolve and how they interact. We used evolutionary agent-based simulations, incorporating empirically based learning mechanisms, to clarify if preparedness and social learning typically both evolve in dangerous environments, and if these mechanisms generally interact synergistically or antagonistically. Our simulations showed that preparedness and social learning often co-evolve because they provide complimentary benefits: genetic preparedness reduced foraging efficiency, but resulted in a higher rate of survival in dangerous environments, while social learning generally came to dominate the population, especially when the environment was stochastic. However, even in this case, genetic preparedness reliably evolved. Broadly, our results indicate that the relationship between preparedness and social learning is important as it can result in trade-offs between behavioral flexibility and safety, which can lead to seemingly suboptimal behavior if the evolutionary environment of the organism is not taken into account. PMID:27487079

Co-Evolution of Social Learning and Evolutionary Preparedness in Dangerous Environments.

PubMed

Lindström, Björn; Selbing, Ida; Olsson, Andreas

2016-01-01

Danger is a fundamental aspect of the lives of most animals. Adaptive behavior therefore requires avoiding actions, objects, and environments associated with danger. Previous research has shown that humans and non-human animals can avoid such dangers through two types of behavioral adaptions, (i) genetic preparedness to avoid certain stimuli or actions, and (ii) social learning. These adaptive mechanisms reduce the fitness costs associated with danger but still allow flexible behavior. Despite the empirical prevalence and importance of both these mechanisms, it is unclear when they evolve and how they interact. We used evolutionary agent-based simulations, incorporating empirically based learning mechanisms, to clarify if preparedness and social learning typically both evolve in dangerous environments, and if these mechanisms generally interact synergistically or antagonistically. Our simulations showed that preparedness and social learning often co-evolve because they provide complimentary benefits: genetic preparedness reduced foraging efficiency, but resulted in a higher rate of survival in dangerous environments, while social learning generally came to dominate the population, especially when the environment was stochastic. However, even in this case, genetic preparedness reliably evolved. Broadly, our results indicate that the relationship between preparedness and social learning is important as it can result in trade-offs between behavioral flexibility and safety, which can lead to seemingly suboptimal behavior if the evolutionary environment of the organism is not taken into account.

The Effects of Rapid Assessments and Adaptive Restudy Prompts in Multimedia Learning

ERIC Educational Resources Information Center

Renkl, Alexander; Skuballa, Irene T.; Schwonke, Rolf; Harr, Nora; Leber, Jasmin

2015-01-01

We investigated the effects of rapid assessment tasks and different adaptive restudy prompts in multimedia learning. The adaptivity was based on rapid assessment tasks that were interspersed throughout a multimedia learning environment. In Experiment 1 (N = 52 university students), we analyzed to which extent rapid assessment tasks were reactive…

Providing Adaptation and Guidance for Design Learning by Problem Solving: The Design Planning Approach in DomoSim-TPC Environment

ERIC Educational Resources Information Center

Redondo, Miguel A.; Bravo, Crescencio; Ortega, Manuel; Verdejo, M. Felisa

2007-01-01

Experimental learning environments based on simulation usually require monitoring and adaptation to the actions the users carry out. Some systems provide this functionality, but they do so in a way which is static or cannot be applied to problem solving tasks. In response to this problem, we propose a method based on the use of intermediate…

Evaluation of Hybrid and Distance Education Learning Environments in Spain

ERIC Educational Resources Information Center

Ferrer-Cascales, Rosario; Walker, Scott L.; Reig-Ferrer, Abilio; Fernandez-Pascual, Maria Dolores; Albaladejo-Blazquez, Natalia

2011-01-01

This article describes the adaptation and validation of the "Distance Education Learning Environments Survey" (DELES) for use in investigating the qualities found in distance and hybrid education psycho-social learning environments in Spain. As Europe moves toward post-secondary student mobility, equanimity in access to higher education,…

Ontology-Based Multimedia Authoring Tool for Adaptive E-Learning

ERIC Educational Resources Information Center

Deng, Lawrence Y.; Keh, Huan-Chao; Liu, Yi-Jen

2010-01-01

More video streaming technologies supporting distance learning systems are becoming popular among distributed network environments. In this paper, the authors develop a multimedia authoring tool for adaptive e-learning by using characterization of extended media streaming technologies. The distributed approach is based on an ontology-based model.…

Adaptable, Personalised E-Learning Incorporating Learning Styles

ERIC Educational Resources Information Center

Peter, Sophie E.; Bacon, Elizabeth; Dastbaz, Mohammad

2010-01-01

Purpose: The purpose of this paper is to discuss how learning styles and theories are currently used within personalised adaptable e-learning adaptive systems. This paper then aims to describe the e-learning platform iLearn and how this platform is designed to incorporate learning styles as part of the personalisation offered by the system.…

Appreciation of learning environment and development of higher-order learning skills in a problem-based learning medical curriculum.

PubMed

Mala-Maung; Abdullah, Azman; Abas, Zoraini W

2011-12-01

This cross-sectional study determined the appreciation of the learning environment and development of higher-order learning skills among students attending the Medical Curriculum at the International Medical University, Malaysia which provides traditional and e-learning resources with an emphasis on problem based learning (PBL) and self-directed learning. Of the 708 participants, the majority preferred traditional to e-resources. Students who highly appreciated PBL demonstrated a higher appreciation of e-resources. Appreciation of PBL is positively and significantly correlated with higher-order learning skills, reflecting the inculcation of self-directed learning traits. Implementers must be sensitive to the progress of learners adapting to the higher education environment and innovations, and to address limitations as relevant.

Optimal structure of metaplasticity for adaptive learning

PubMed Central

2017-01-01

Learning from reward feedback in a changing environment requires a high degree of adaptability, yet the precise estimation of reward information demands slow updates. In the framework of estimating reward probability, here we investigated how this tradeoff between adaptability and precision can be mitigated via metaplasticity, i.e. synaptic changes that do not always alter synaptic efficacy. Using the mean-field and Monte Carlo simulations we identified ‘superior’ metaplastic models that can substantially overcome the adaptability-precision tradeoff. These models can achieve both adaptability and precision by forming two separate sets of meta-states: reservoirs and buffers. Synapses in reservoir meta-states do not change their efficacy upon reward feedback, whereas those in buffer meta-states can change their efficacy. Rapid changes in efficacy are limited to synapses occupying buffers, creating a bottleneck that reduces noise without significantly decreasing adaptability. In contrast, more-populated reservoirs can generate a strong signal without manifesting any observable plasticity. By comparing the behavior of our model and a few competing models during a dynamic probability estimation task, we found that superior metaplastic models perform close to optimally for a wider range of model parameters. Finally, we found that metaplastic models are robust to changes in model parameters and that metaplastic transitions are crucial for adaptive learning since replacing them with graded plastic transitions (transitions that change synaptic efficacy) reduces the ability to overcome the adaptability-precision tradeoff. Overall, our results suggest that ubiquitous unreliability of synaptic changes evinces metaplasticity that can provide a robust mechanism for mitigating the tradeoff between adaptability and precision and thus adaptive learning. PMID:28658247

Personalized e-Learning Environments: Considering Students' Contexts

NASA Astrophysics Data System (ADS)

Eyharabide, Victoria; Gasparini, Isabela; Schiaffino, Silvia; Pimenta, Marcelo; Amandi, Analía

Personalization in e-learning systems is vital since they are used by a wide variety of students with different characteristics. There are several approaches that aim at personalizing e-learning environments. However, they focus mainly on technological and/or networking aspects without caring of contextual aspects. They consider only a limited version of context while providing personalization. In our work, the objective is to improve e-learning environment personalization making use of a better understanding and modeling of the user’s educational and technological context using ontologies. We show an example of the use of our proposal in the AdaptWeb system, in which content and navigation recommendations are provided depending on the student’s context.

Adaptive functional systems: learning with chaos.

PubMed

Komarov, M A; Osipov, G V; Burtsev, M S

2010-12-01

We propose a new model of adaptive behavior that combines a winnerless competition principle and chaos to learn new functional systems. The model consists of a complex network of nonlinear dynamical elements producing sequences of goal-directed actions. Each element describes dynamics and activity of the functional system which is supposed to be a distributed set of interacting physiological elements such as nerve or muscle that cooperates to obtain certain goal at the level of the whole organism. During "normal" behavior, the dynamics of the system follows heteroclinic channels, but in the novel situation chaotic search is activated and a new channel leading to the target state is gradually created simulating the process of learning. The model was tested in single and multigoal environments and had demonstrated a good potential for generation of new adaptations. © 2010 American Institute of Physics.

Biomimetic molecular design tools that learn, evolve, and adapt.

PubMed

Winkler, David A

2017-01-01

A dominant hallmark of living systems is their ability to adapt to changes in the environment by learning and evolving. Nature does this so superbly that intensive research efforts are now attempting to mimic biological processes. Initially this biomimicry involved developing synthetic methods to generate complex bioactive natural products. Recent work is attempting to understand how molecular machines operate so their principles can be copied, and learning how to employ biomimetic evolution and learning methods to solve complex problems in science, medicine and engineering. Automation, robotics, artificial intelligence, and evolutionary algorithms are now converging to generate what might broadly be called in silico-based adaptive evolution of materials. These methods are being applied to organic chemistry to systematize reactions, create synthesis robots to carry out unit operations, and to devise closed loop flow self-optimizing chemical synthesis systems. Most scientific innovations and technologies pass through the well-known "S curve", with slow beginning, an almost exponential growth in capability, and a stable applications period. Adaptive, evolving, machine learning-based molecular design and optimization methods are approaching the period of very rapid growth and their impact is already being described as potentially disruptive. This paper describes new developments in biomimetic adaptive, evolving, learning computational molecular design methods and their potential impacts in chemistry, engineering, and medicine.

Environments for Lifelong Learning in Senior Centers

ERIC Educational Resources Information Center

Eaton, Jacqueline; Salari, Sonia

2005-01-01

Senior-center learning opportunities must adapt, as new retirees are better educated than their predecessors. We examined 3 multipurpose senior centers using 120 hours of observations and 30 participant interviews. Variation existed in the ability to maximize synomorphic relationships, where the physical environment supported educational…

Facilitating peer based learning through summative assessment - An adaptation of the Objective Structured Clinical Assessment tool for the blended learning environment.

PubMed

Wikander, Lolita; Bouchoucha, Stéphane L

2018-01-01

Adapting a course from face to face to blended delivery necessitates that assessments are modified accordingly. In Australia the Objective Structured Clinical Assessment tool, as a derivative from the Objective Structured Clinical Examination, has been used in the face-to-face delivery mode as a formative or summative assessment tool in medicine and nursing since 1990. The Objective Structured Clinical Assessment has been used at Charles Darwin University to assess nursing students' simulated clinical skills prior to the commencement of their clinical placements since 2008. Although the majority of the course is delivered online, students attend a one-week intensive clinical simulation block yearly, prior to attending clinical placements. Initially, the Objective Structured Clinical Assessment was introduced as a lecturer assessed summative assessment, over time it was adapted to better suit the blended learning environment. The modification of the tool from an academic to peer assessed assessment tool, was based on the empirical literature, student feedback and a cross-sectional, qualitative study exploring academics' perceptions of the Objective Structured Clinical Assessment (Bouchoucha et al., 2013a, b). This paper presents an overview of the process leading to the successful adaptation of the Objective Structured Clinical Assessment to suit the requirements of a preregistration nursing course delivered through blended learning. This is significant as many universities are moving their curriculum to fully online or blended delivery, yet little attention has been paid to adapting the assessment of simulated clinical skills. The aim is to identify the benefits and drawbacks of using the peer assessed Objective Structured Clinical Assessment and share recommendations for successful implementation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Students' Personal Networks in Virtual and Personal Learning Environments: A Case Study in Higher Education Using Learning Analytics Approach

ERIC Educational Resources Information Center

Casquero, Oskar; Ovelar, Ramón; Romo, Jesús; Benito, Manuel; Alberdi, Mikel

2016-01-01

The main objective of this paper is to analyse the effect of the affordances of a virtual learning environment and a personal learning environment (PLE) in the configuration of the students' personal networks in a higher education context. The results are discussed in light of the adaptation of the students to the learning network made up by two…

Novel Hybrid Adaptive Controller for Manipulation in Complex Perturbation Environments

PubMed Central

Smith, Alex M. C.; Yang, Chenguang; Ma, Hongbin; Culverhouse, Phil; Cangelosi, Angelo; Burdet, Etienne

2015-01-01

In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing. PMID:26029916

Adaptive Effects on Locomotion Performance Following Exposure to a Rotating Virtual Environment

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; Richards, J. T.; Marshburn, A. M.; Bucello, R.; Bloomberg, J. J.

2003-01-01

During long-duration spaceflight, astronauts experience alterations in vestibular and somatosensory cues that result in adaptive disturbances in balance and coordination upon return to Earth. These changes can pose a risk to crew safety and to mission objectives if nominal or emergency vehicle egress is required immediately following long-duration spaceflight. At present, no operational countermeasure is available to mitigate the adaptive sensorimotor component underlying the locomotor disturbances that occur after spaceflight. Therefore, the goal of this study is to develop an inflight training regimen that facilitates recovery of locomotor function after long-duration spaceflight. The countermeasure we are proposing is based on the concept of adaptive generalization. During this type of training the subject gains experience producing the appropriate adaptive motor behavior under a variety of sensory conditions and response constraints. As a result of this training a subject learns to solve a class of motor problems, rather than a specific motor solution to one problem, i.e., the subject learns response generalizability or the ability to "learn to learn." under a variety of environmental constraints. We are developing an inflight countermeasure built around treadmill exercise activities. By manipulating the sensory conditions of exercise by varying visual flow patterns, body load and speed we will systematically and repeatedly promote adaptive change in locomotor behavior. It has been shown that variable practice training increases adaptability to novel visuo-motor situations. While walking over ground in a stereoscopic virtual environment that oscillated in roll, subjects have shown compensatory torso rotation in the direction of scene rotation that resulted in positional variation away from a desired linear path. Thus, postural sway and locomotor stability in 1-g can be modulated by visual flow patterns and used during inflight treadmill training to promote

Use of Adaptive Study Material in Education in E-Learning Environment

ERIC Educational Resources Information Center

Kostolányová, Katerina; Šarmanová, Jana

2014-01-01

Personalised education is a topical matter today and the impact of ICT on education has been covered extensively. The adaptation of education to various types of student is an issue of a vast number of papers presented at diverse conferences. The topic incorporates the fields of information technologies and eLearning, but in no small part also the…

Biomimetic molecular design tools that learn, evolve, and adapt

PubMed Central

2017-01-01

A dominant hallmark of living systems is their ability to adapt to changes in the environment by learning and evolving. Nature does this so superbly that intensive research efforts are now attempting to mimic biological processes. Initially this biomimicry involved developing synthetic methods to generate complex bioactive natural products. Recent work is attempting to understand how molecular machines operate so their principles can be copied, and learning how to employ biomimetic evolution and learning methods to solve complex problems in science, medicine and engineering. Automation, robotics, artificial intelligence, and evolutionary algorithms are now converging to generate what might broadly be called in silico-based adaptive evolution of materials. These methods are being applied to organic chemistry to systematize reactions, create synthesis robots to carry out unit operations, and to devise closed loop flow self-optimizing chemical synthesis systems. Most scientific innovations and technologies pass through the well-known “S curve”, with slow beginning, an almost exponential growth in capability, and a stable applications period. Adaptive, evolving, machine learning-based molecular design and optimization methods are approaching the period of very rapid growth and their impact is already being described as potentially disruptive. This paper describes new developments in biomimetic adaptive, evolving, learning computational molecular design methods and their potential impacts in chemistry, engineering, and medicine. PMID:28694872

Adaptive social learning strategies in temporally and spatially varying environments : how temporal vs. spatial variation, number of cultural traits, and costs of learning influence the evolution of conformist-biased transmission, payoff-biased transmission, and individual learning.

PubMed

Nakahashi, Wataru; Wakano, Joe Yuichiro; Henrich, Joseph

2012-12-01

Long before the origins of agriculture human ancestors had expanded across the globe into an immense variety of environments, from Australian deserts to Siberian tundra. Survival in these environments did not principally depend on genetic adaptations, but instead on evolved learning strategies that permitted the assembly of locally adaptive behavioral repertoires. To develop hypotheses about these learning strategies, we have modeled the evolution of learning strategies to assess what conditions and constraints favor which kinds of strategies. To build on prior work, we focus on clarifying how spatial variability, temporal variability, and the number of cultural traits influence the evolution of four types of strategies: (1) individual learning, (2) unbiased social learning, (3) payoff-biased social learning, and (4) conformist transmission. Using a combination of analytic and simulation methods, we show that spatial-but not temporal-variation strongly favors the emergence of conformist transmission. This effect intensifies when migration rates are relatively high and individual learning is costly. We also show that increasing the number of cultural traits above two favors the evolution of conformist transmission, which suggests that the assumption of only two traits in many models has been conservative. We close by discussing how (1) spatial variability represents only one way of introducing the low-level, nonadaptive phenotypic trait variation that so favors conformist transmission, the other obvious way being learning errors, and (2) our findings apply to the evolution of conformist transmission in social interactions. Throughout we emphasize how our models generate empirical predictions suitable for laboratory testing.

Examining Metacognitive Processes in Exploratory Computer-Based Learning Environments Using Activity Log Analysis

ERIC Educational Resources Information Center

Chang, Yoo Kyung

2010-01-01

Metacognition is widely studied for its influence on the effectiveness of learning. With Exploratory Computer-Based Learning Environments (ECBLE), metacognition is found to be especially important because these environments require adaptive metacognitive control by the learners due to their open-ended structure that allows for multiple learning…

Gearsketch: An Adaptive Drawing-Based Learning Environment for the Gears Domain

ERIC Educational Resources Information Center

Leenaars, Frank A.; Joolingen, Wouter R.; Gijlers, Hannie; Bollen, Lars

2014-01-01

GearSketch is a learning environment for the gears domain, aimed at students in the final years of primary school. It is designed for use with a touchscreen device and is based on ideas from drawing-based learning and research on cognitive tutors. At the heart of GearSketch is a domain model that is used to transform learners' strokes into…

E-learning environment as intelligent tutoring system

NASA Astrophysics Data System (ADS)

Nagyová, Ingrid

2017-07-01

The development of computers and artificial intelligence theory allow their application in the field of education. Intelligent tutoring systems reflect student learning styles and adapt the curriculum according to their individual needs. The building of intelligent tutoring systems requires not only the creation of suitable software, but especially the search and application of the rules enabling ICT to individually adapt the curriculum. The main idea of this paper is to attempt to specify the rules for dividing the students to systematically working students and more practically or pragmatically inclined students. The paper shows that monitoring the work of students in e-learning environment, analysis of various approaches to educational materials and correspondence assignments show different results for the defined groups of students.

A Networked Learning Model for Construction of Personal Learning Environments in Seventh Grade Life Science

ERIC Educational Resources Information Center

Drexler, Wendy

2010-01-01

The purpose of this design-based research case study was to apply a networked learning approach to a seventh grade science class at a public school in the southeastern United States. Students adapted Web applications to construct personal learning environments for in-depth scientific inquiry of poisonous and venomous life forms. API widgets were…

Long-term adaptation to change in implicit contextual learning.

PubMed

Zellin, Martina; von Mühlenen, Adrian; Müller, Hermann J; Conci, Markus

2014-08-01

The visual world consists of spatial regularities that are acquired through experience in order to guide attentional orienting. For instance, in visual search, detection of a target is faster when a layout of nontarget items is encountered repeatedly, suggesting that learned contextual associations can guide attention (contextual cuing). However, scene layouts sometimes change, requiring observers to adapt previous memory representations. Here, we investigated the long-term dynamics of contextual adaptation after a permanent change of the target location. We observed fast and reliable learning of initial context-target associations after just three repetitions. However, adaptation of acquired contextual representations to relocated targets was slow and effortful, requiring 3 days of training with overall 80 repetitions. A final test 1 week later revealed equivalent effects of contextual cuing for both target locations, and these were comparable to the effects observed on day 1. That is, observers learned both initial target locations and relocated targets, given extensive training combined with extended periods of consolidation. Thus, while implicit contextual learning efficiently extracts statistical regularities of our environment at first, it is rather insensitive to change in the longer term, especially when subtle changes in context-target associations need to be acquired.

Personalized Recommender System for e-Learning Environment

ERIC Educational Resources Information Center

Benhamdi, Soulef; Babouri, Abdesselam; Chiky, Raja

2017-01-01

Traditional e-Learning environments are based on static contents considering that all learners are similar, so they are not able to respond to each learner's needs. These systems are less adaptive and once a system that supports a particular strategy has been designed and implemented, it is less likely to change according to student's interactions…

Analyzing User Interaction to Design an Intelligent e-Learning Environment

ERIC Educational Resources Information Center

Sharma, Richa

2011-01-01

Building intelligent course designing systems adaptable to the learners' needs is one of the key goals of research in e-learning. This goal is all the more crucial as gaining knowledge in an e-learning environment depends solely on computer mediated interaction within the learner group and among the learners and instructors. The patterns generated…

SU-D-BRB-05: Quantum Learning for Knowledge-Based Response-Adaptive Radiotherapy

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

El Naqa, I; Ten, R

Purpose: There is tremendous excitement in radiotherapy about applying data-driven methods to develop personalized clinical decisions for real-time response-based adaptation. However, classical statistical learning methods lack in terms of efficiency and ability to predict outcomes under conditions of uncertainty and incomplete information. Therefore, we are investigating physics-inspired machine learning approaches by utilizing quantum principles for developing a robust framework to dynamically adapt treatments to individual patient’s characteristics and optimize outcomes. Methods: We studied 88 liver SBRT patients with 35 on non-adaptive and 53 on adaptive protocols. Adaptation was based on liver function using a split-course of 3+2 fractions with amore » month break. The radiotherapy environment was modeled as a Markov decision process (MDP) of baseline and one month into treatment states. The patient environment was modeled by a 5-variable state represented by patient’s clinical and dosimetric covariates. For comparison of classical and quantum learning methods, decision-making to adapt at one month was considered. The MDP objective was defined by the complication-free tumor control (P{sup +}=TCPx(1-NTCP)). A simple regression model represented state-action mapping. Single bit in classical MDP and a qubit of 2-superimposed states in quantum MDP represented the decision actions. Classical decision selection was done using reinforcement Q-learning and quantum searching was performed using Grover’s algorithm, which applies uniform superposition over possible states and yields quadratic speed-up. Results: Classical/quantum MDPs suggested adaptation (probability amplitude ≥0.5) 79% of the time for splitcourses and 100% for continuous-courses. However, the classical MDP had an average adaptation probability of 0.5±0.22 while the quantum algorithm reached 0.76±0.28. In cases where adaptation failed, classical MDP yielded 0.31±0.26 average amplitude while

Development and Evaluation of an E-Learning Course for Deaf and Hard of Hearing Based on the Advanced Adapted Pedagogical Index Method

ERIC Educational Resources Information Center

Debevc, Matjaž; Stjepanovic, Zoran; Holzinger, Andreas

2014-01-01

Web-based and adapted e-learning materials provide alternative methods of learning to those used in a traditional classroom. Within the study described in this article, deaf and hard of hearing people used an adaptive e-learning environment to improve their computer literacy. This environment included streaming video with sign language interpreter…

Evidence of Molecular Adaptation to Extreme Environments and Applicability to Space Environments

NASA Astrophysics Data System (ADS)

Filipovic, M. D.; Ognjanovic, S.; Ognjanovic, M.

2008-06-01

This is initial investigation of gene signatures responsible for adapting microscopic life to the extreme Earth environments. We present preliminary results on identification of the clusters of orthologous groups (COGs) common to several hyperthermophiles and exclusion of those common to a mesophile (non-hyperthermophile): Escherichia coli (E. coli K12), will yield a group of proteins possibly involved in adaptation to life under extreme temperatures. Comparative genome analyses represent a powerful tool in discovery of novel genes responsible for adaptation to specific extreme environments. Methanogens stand out as the only group of organisms that have species capable of growth at 0° C (Metarhizium frigidum (M.~frigidum) and Methanococcoides burtonii (M.~burtonii)) and 110° C (Methanopyrus kandleri (M.~kandleri)). Although not all the components of heat adaptation can be attributed to novel genes, the chaperones known as heat shock proteins stabilize the enzymes under elevated temperature. However, highly conserved chaperons found in bacteria and eukaryots are not present in hyperthermophilic Archea, rather, they have a unique chaperone TF55. Our aim was to use software which we specifically developed for extremophile genome comparative analyses in order to search for additional novel genes involved in hyperthermophile adaptation. The following hyperthermophile genomes incorporated in this software were used for these studies: Methanocaldococcus jannaschii (M.~jannaschii), M.~kandleri, Archaeoglobus fulgidus (A.~fulgidus) and three species of Pyrococcus. Common genes were annotated and grouped according to their roles in cellular processes where such information was available and proteins not previously implicated in the heat-adaptation of hyperthermophiles were identified. Additional experimental data are needed in order to learn more about these proteins. To address non-gene based components of thermal adaptation, all sequenced extremophiles were analysed for

The Application of an Adaptive, Web-Based Learning Environment on Oxidation-Reduction Reactions

ERIC Educational Resources Information Center

Own, Zangyuan

2006-01-01

The World Wide Web is increasingly being used as a vehicle for flexible learning, where learning is seen to be free from time, geographical, and participation constraints. In addition to flexibility, the Web facilitates student-centered approaches, creating a motivating and active learning environment. The purpose of this study is to set up an…

A neural learning classifier system with self-adaptive constructivism for mobile robot control.

PubMed

Hurst, Jacob; Bull, Larry

2006-01-01

For artificial entities to achieve true autonomy and display complex lifelike behavior, they will need to exploit appropriate adaptable learning algorithms. In this context adaptability implies flexibility guided by the environment at any given time and an open-ended ability to learn appropriate behaviors. This article examines the use of constructivism-inspired mechanisms within a neural learning classifier system architecture that exploits parameter self-adaptation as an approach to realize such behavior. The system uses a rule structure in which each rule is represented by an artificial neural network. It is shown that appropriate internal rule complexity emerges during learning at a rate controlled by the learner and that the structure indicates underlying features of the task. Results are presented in simulated mazes before moving to a mobile robot platform.

Cooperative Learning in Virtual Environments: The Jigsaw Method in Statistical Courses

ERIC Educational Resources Information Center

Vargas-Vargas, Manuel; Mondejar-Jimenez, Jose; Santamaria, Maria-Letica Meseguer; Alfaro-Navarro, Jose-Luis; Fernandez-Aviles, Gema

2011-01-01

This document sets out a novel teaching methodology as used in subjects with statistical content, traditionally regarded by students as "difficult". In a virtual learning environment, instructional techniques little used in mathematical courses were employed, such as the Jigsaw cooperative learning method, which had to be adapted to the…

Becoming a Coach in Developmental Adaptive Sailing: A Lifelong Learning Perspective

PubMed Central

Duarte, Tiago; Culver, Diane M.

2014-01-01

Life-story methodology and innovative methods were used to explore the process of becoming a developmental adaptive sailing coach. Jarvis's (2009) lifelong learning theory framed the thematic analysis. The findings revealed that the coach, Jenny, was exposed from a young age to collaborative environments. Social interactions with others such as mentors, colleagues, and athletes made major contributions to her coaching knowledge. As Jenny was exposed to a mixture of challenges and learning situations, she advanced from recreational para-swimming instructor to developmental adaptive sailing coach. The conclusions inform future research in disability sport coaching, coach education, and applied sport psychology. PMID:25210408

Becoming a Coach in Developmental Adaptive Sailing: A Lifelong Learning Perspective.

PubMed

Duarte, Tiago; Culver, Diane M

2014-10-02

Life-story methodology and innovative methods were used to explore the process of becoming a developmental adaptive sailing coach. Jarvis's (2009) lifelong learning theory framed the thematic analysis. The findings revealed that the coach, Jenny, was exposed from a young age to collaborative environments. Social interactions with others such as mentors, colleagues, and athletes made major contributions to her coaching knowledge. As Jenny was exposed to a mixture of challenges and learning situations, she advanced from recreational para-swimming instructor to developmental adaptive sailing coach. The conclusions inform future research in disability sport coaching, coach education, and applied sport psychology.

Modeling and Intervening across Time in Scientific Inquiry Exploratory Learning Environment

ERIC Educational Resources Information Center

Ting, Choo-Yee; Phon-Amnuaisuk, Somnuk; Chong, Yen-Kuan

2008-01-01

This article aims at discussing how Dynamic Decision Network (DDN) can be employed to tackle the challenges in modeling temporally variable scientific inquiry skills and provision of adaptive pedagogical interventions in INQPRO, a scientific inquiry exploratory learning environment for learning O'level Physics. We begin with an overview of INQPRO…

Adaptable Computing Environment/Self-Assembling Software

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

Osbourn, Gordon C.; Bouchard, Ann M.; Bartholomew, John W.

Complex software applications are difficult to learn to use and to remember how to use. Further, the user has no control over the functionality available in a given application. The software we use can be created and modified only by a relatively small group of elite, highly skilled artisans known as programmers. "Normal users" are powerless to create and modify software themselves, because the tools for software development, designed by and for programmers, are a barrier to entry. This software, when completed, will be a user-adaptable computing environment in which the user is really in control of his/her own software,more » able to adapt the system, make new parts of the system interactive, and even modify the behavior of the system itself. Som key features of the basic environment that have been implemented are (a) books in bookcases, where all data is stored, (b) context-sensitive compass menus (compass, because the buttons are located in compass directions relative to the mouose cursor position), (c) importing tabular data and displaying it in a book, (d) light-weight table querying/sorting, (e) a Reach&Get capability (sort of a "smart" copy/paste that prevents the user from copying invalid data), and (f) a LogBook that automatically logs all user actions that change data or the system itself. To bootstrap toward full end-user adaptability, we implemented a set of development tools. With the development tools, compass menus can be made and customized.« less

The Integration of Personal Learning Environments & Open Network Learning Environments

ERIC Educational Resources Information Center

Tu, Chih-Hsiung; Sujo-Montes, Laura; Yen, Cherng-Jyh; Chan, Junn-Yih; Blocher, Michael

2012-01-01

Learning management systems traditionally provide structures to guide online learners to achieve their learning goals. Web 2.0 technology empowers learners to create, share, and organize their personal learning environments in open network environments; and allows learners to engage in social networking and collaborating activities. Advanced…

Adapting the Speed of Reproduction of Audio Content and Using Text Reinforcement for Maximizing the Learning Outcome though Mobile Phones

ERIC Educational Resources Information Center

Munoz-Organero, M.; Munoz-Merino, P. J.; Kloos, Carlos Delgado

2011-01-01

The use of technology in learning environments should be targeted at improving the learning outcome of the process. Several technology enhanced techniques can be used for maximizing the learning gain of particular students when having access to learning resources. One of them is content adaptation. Adapting content is especially important when…

Recommendation System for Adaptive Learning.

PubMed

Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang

2018-01-01

An adaptive learning system aims at providing instruction tailored to the current status of a learner, differing from the traditional classroom experience. The latest advances in technology make adaptive learning possible, which has the potential to provide students with high-quality learning benefit at a low cost. A key component of an adaptive learning system is a recommendation system, which recommends the next material (video lectures, practices, and so on, on different skills) to the learner, based on the psychometric assessment results and possibly other individual characteristics. An important question then follows: How should recommendations be made? To answer this question, a mathematical framework is proposed that characterizes the recommendation process as a Markov decision problem, for which decisions are made based on the current knowledge of the learner and that of the learning materials. In particular, two plain vanilla systems are introduced, for which the optimal recommendation at each stage can be obtained analytically.

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

NASA Astrophysics Data System (ADS)

Satoh, Hideki

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

The Usability Analysis of an E-Learning Environment

ERIC Educational Resources Information Center

Torun, Fulya; Tekedere, Hakan

2015-01-01

In this research, an E-learning environment is developed for the teacher candidates taking the course on Scientific Research Methods. The course contents were adapted to one of the constructivist approach models referred to as 5E, and an expert opinion was received for the compliance of this model. An usability analysis was also performed to…

Functionally dissociable influences on learning rate in a dynamic environment

PubMed Central

McGuire, Joseph T.; Nassar, Matthew R.; Gold, Joshua I.; Kable, Joseph W.

2015-01-01

Summary Maintaining accurate beliefs in a changing environment requires dynamically adapting the rate at which one learns from new experiences. Beliefs should be stable in the face of noisy data, but malleable in periods of change or uncertainty. Here we used computational modeling, psychophysics and fMRI to show that adaptive learning is not a unitary phenomenon in the brain. Rather, it can be decomposed into three computationally and neuroanatomically distinct factors that were evident in human subjects performing a spatial-prediction task: (1) surprise-driven belief updating, related to BOLD activity in visual cortex; (2) uncertainty-driven belief updating, related to anterior prefrontal and parietal activity; and (3) reward-driven belief updating, a context-inappropriate behavioral tendency related to activity in ventral striatum. These distinct factors converged in a core system governing adaptive learning. This system, which included dorsomedial frontal cortex, responded to all three factors and predicted belief updating both across trials and across individuals. PMID:25459409

Towards adaptation in e-learning 2.0

NASA Astrophysics Data System (ADS)

Cristea, Alexandra I.; Ghali, Fawaz

2011-04-01

This paper presents several essential steps from an overall study on shaping new ways of learning and teaching, by using the synergetic merger of three different fields: Web 2.0, e-learning and adaptation (in particular, personalisation to the learner). These novel teaching and learning ways-the latter focus of this paper-are reflected in and finally adding to various versions of the My Online Teacher 2.0 adaptive system. In particular, this paper focuses on a study of how to more effectively use and combine the recommendation of peers and content adaptation to enhance the learning outcome in e-learning systems based on Web 2.0. In order to better isolate and examine the effects of peer recommendation and adaptive content presentation, we designed experiments inspecting collaboration between individuals based on recommendation of peers who have greater knowledge, and compare this to adaptive content recommendation, as well as to "simple" learning in a system with a minimum of Web 2.0 support. Overall, the results of adding peer recommendation and adaptive content presentation were encouraging, and are further discussed in detail in this paper.

Using an improved virtual learning environment for engineering students

NASA Astrophysics Data System (ADS)

Lourdes Martínez Cartas, Ma

2012-06-01

In recent years, e-learning has been used in a chemical engineering subject in the final course of a mining engineering degree, a subject concerned with fuel technology. The low results obtained by students in this subject have led the teacher to search for new strategies to increase grades. Such strategies have consisted of incorporating into the existing virtual environment a dynamics of work with conceptual maps and a consideration of the different learning styles in the classroom. In an attempt to adapt teaching to the individual methods of learning for each student, various activities aimed at strengthening different learning styles have been proposed and concept maps have been used to create meaningful learning experiences. In addition, different modalities of assessment have been proposed, which can be selected by each student according to his or her particular method of learning to avoid penalising one style preference in contrast to another. This combination of e-learning, use of concept maps and catering for different learning styles has involved the implementation of the improved virtual learning environment. This has led to an increase in participation in the subject and has improved student assessment results.

The evolution of continuous learning of the structure of the environment

PubMed Central

Kolodny, Oren; Edelman, Shimon; Lotem, Arnon

2014-01-01

Continuous, ‘always on’, learning of structure from a stream of data is studied mainly in the fields of machine learning or language acquisition, but its evolutionary roots may go back to the first organisms that were internally motivated to learn and represent their environment. Here, we study under what conditions such continuous learning (CL) may be more adaptive than simple reinforcement learning and examine how it could have evolved from the same basic associative elements. We use agent-based computer simulations to compare three learning strategies: simple reinforcement learning; reinforcement learning with chaining (RL-chain) and CL that applies the same associative mechanisms used by the other strategies, but also seeks statistical regularities in the relations among all items in the environment, regardless of the initial association with food. We show that a sufficiently structured environment favours the evolution of both RL-chain and CL and that CL outperforms the other strategies when food is relatively rare and the time for learning is limited. This advantage of internally motivated CL stems from its ability to capture statistical patterns in the environment even before they are associated with food, at which point they immediately become useful for planning. PMID:24402920

Investigating the Effect of an Adaptive Learning Intervention on Students' Learning

ERIC Educational Resources Information Center

Liu, Min; McKelroy, Emily; Corliss, Stephanie B.; Carrigan, Jamison

2017-01-01

Educators agree on the benefits of adaptive learning, but evidence-based research remains limited as the field of adaptive learning is still evolving within higher education. In this study, we investigated the impact of an adaptive learning intervention to provide remedial instruction in biology, chemistry, math, and information literacy to…

Application of Mobile Agents in Web-Based Learning Environment.

ERIC Educational Resources Information Center

Hong Hong, Kinshuk; He, Xiaoqin; Patel, Ashok; Jesshope, Chris

Web-based learning environments are strongly driven by the information revolution and the Internet, but they have a number of common deficiencies, such as slow access, no adaptivity to the individual student, limitation by bandwidth, and more. This paper outlines the benefits of mobile agents technology, and describes its application in Web-based…

Reacting to 'Irregular' Learning Environments in a Senior Secondary School

ERIC Educational Resources Information Center

Alterator, Scott; Deed, Craig

2016-01-01

Modern school design continues to incorporate openness and irregularity as a means of achieving improvement. Irregular learning environments can act as a catalyst for student unsettling and enable possibilities of teacher practice. We outline a case study of teacher adaptation to irregular environments in a senior school setting. We argue that…

Utilization of virtual learning environments in the allied health professions.

PubMed

Butina, Michelle; Brooks, Donna; Dominguez, Paul J; Mahon, Gwendolyn M

2013-01-01

Multiple technology based tools have been used to enhance skill development in allied health education, which now includes virtual learning environments. The purpose of this study was to explore whether, and how, this latest instructional technology is being adapted in allied health education. An online survey was circulated to all Association of Schools of Allied Health Professions (ASAHP) member institutions and focused on three broad areas of virtual learning environments: the uses of, the perceived pros and cons of, and the outcomes of utilizing them. Results show 40% (17 of 42) of the respondent use some form of the technology. The use of virtual learning technology in other healthcare professions (e.g., medicine) demonstrates the potential benefits to allied health education.

Adaptive Learning Resources Sequencing in Educational Hypermedia Systems

ERIC Educational Resources Information Center

Karampiperis, Pythagoras; Sampson, Demetrios

2005-01-01

Adaptive learning resources selection and sequencing is recognized as among the most interesting research questions in adaptive educational hypermedia systems (AEHS). In order to adaptively select and sequence learning resources in AEHS, the definition of adaptation rules contained in the Adaptation Model, is required. Although, some efforts have…

Introducing Adaptivity Features to a Regular Learning Management System to Support Creation of Advanced eLessons

ERIC Educational Resources Information Center

Komlenov, Zivana; Budimac, Zoran; Ivanovic, Mirjana

2010-01-01

In order to improve the learning process for students with different pre-knowledge, personal characteristics and preferred learning styles, a certain degree of adaptability must be introduced to online courses. In learning environments that support such kind of functionalities students can explicitly choose different paths through course contents…

An Experimental Comparison of the Flexibility in the Use of Thinking Styles in Traditional and Hypermedia Learning Environments

ERIC Educational Resources Information Center

Fan, Weiqiao

2012-01-01

The objective of the instructional experiment was to examine if the use of thinking styles is flexible in traditional and hypermedia learning environments, and if a hypermedia learning environment possesses obvious advantages than a traditional environment in adapting to students with different thinking styles. The participant university students…

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

PubMed

Bryant, D P; Bryant, B R

1998-01-01

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

Adaptive nodes enrich nonlinear cooperative learning beyond traditional adaptation by links.

PubMed

Sardi, Shira; Vardi, Roni; Goldental, Amir; Sheinin, Anton; Uzan, Herut; Kanter, Ido

2018-03-23

Physical models typically assume time-independent interactions, whereas neural networks and machine learning incorporate interactions that function as adjustable parameters. Here we demonstrate a new type of abundant cooperative nonlinear dynamics where learning is attributed solely to the nodes, instead of the network links which their number is significantly larger. The nodal, neuronal, fast adaptation follows its relative anisotropic (dendritic) input timings, as indicated experimentally, similarly to the slow learning mechanism currently attributed to the links, synapses. It represents a non-local learning rule, where effectively many incoming links to a node concurrently undergo the same adaptation. The network dynamics is now counterintuitively governed by the weak links, which previously were assumed to be insignificant. This cooperative nonlinear dynamic adaptation presents a self-controlled mechanism to prevent divergence or vanishing of the learning parameters, as opposed to learning by links, and also supports self-oscillations of the effective learning parameters. It hints on a hierarchical computational complexity of nodes, following their number of anisotropic inputs and opens new horizons for advanced deep learning algorithms and artificial intelligence based applications, as well as a new mechanism for enhanced and fast learning by neural networks.

Spatial features of synaptic adaptation affecting learning performance.

PubMed

Berger, Damian L; de Arcangelis, Lucilla; Herrmann, Hans J

2017-09-08

Recent studies have proposed that the diffusion of messenger molecules, such as monoamines, can mediate the plastic adaptation of synapses in supervised learning of neural networks. Based on these findings we developed a model for neural learning, where the signal for plastic adaptation is assumed to propagate through the extracellular space. We investigate the conditions allowing learning of Boolean rules in a neural network. Even fully excitatory networks show very good learning performances. Moreover, the investigation of the plastic adaptation features optimizing the performance suggests that learning is very sensitive to the extent of the plastic adaptation and the spatial range of synaptic connections.

Science Learning Outcomes in Alignment with Learning Environment Preferences

NASA Astrophysics Data System (ADS)

Chang, Chun-Yen; Hsiao, Chien-Hua; Chang, Yueh-Hsia

2011-04-01

This study investigated students' learning environment preferences and compared the relative effectiveness of instructional approaches on students' learning outcomes in achievement and attitude among 10th grade earth science classes in Taiwan. Data collection instruments include the Earth Science Classroom Learning Environment Inventory and Earth Science Learning Outcomes Inventory. The results showed that most students preferred learning in a classroom environment where student-centered and teacher-centered instructional approaches coexisted over a teacher-centered learning environment. A multivariate analysis of covariance also revealed that the STBIM students' cognitive achievement and attitude toward earth science were enhanced when the learning environment was congruent with their learning environment preference.

Lost in Translation: Adapting a Face-to-Face Course Into an Online Learning Experience.

PubMed

Kenzig, Melissa J

2015-09-01

Online education has grown dramatically over the past decade. Instructors who teach face-to-face courses are being called on to adapt their courses to the online environment. Many instructors do not have sufficient training to be able to effectively move courses to an online format. This commentary discusses the growth of online learning, common challenges faced by instructors adapting courses from face-to-face to online, and best practices for translating face-to-face courses into online learning opportunities. © 2015 Society for Public Health Education.

How to Represent Adaptation in e-Learning with IMS Learning Design

ERIC Educational Resources Information Center

Burgos, Daniel; Tattersall, Colin; Koper, Rob

2007-01-01

Adaptation in e-learning has been an important research topic for the last few decades in computer-based education. In adaptivity the behaviour of the user triggers some actions in the system that guides the learning process. In adaptability, the user makes changes and takes decisions. Progressing from computer-based training and adaptive…

An Adaptive Scaffolding E-Learning System for Middle School Students' Physics Learning

ERIC Educational Resources Information Center

Chen, Ching-Huei

2014-01-01

This study presents a framework that utilizes cognitive and motivational aspects of learning to design an adaptive scaffolding e-learning system. It addresses scaffolding processes and conditions for designing adaptive scaffolds. The features and effectiveness of this adaptive scaffolding e-learning system are discussed and evaluated. An…

Constructing a User-Friendly and Smart Ubiquitous Personalized Learning Environment by Using a Context-Aware Mechanism

ERIC Educational Resources Information Center

Yao, Ching-Bang

2017-01-01

Although m-learning applications have been widely researched, few studies have investigated applying adaptive learning content to various learning environments and efficient input interfaces. This study combined a context-aware mechanism, which can be used to provide suitable learning information anytime and anyplace by using GPS technology, with…

Adaptive Units of Learning and Educational Videogames

ERIC Educational Resources Information Center

Moreno-Ger, Pablo; Thomas, Pilar Sancho; Martinez-Ortiz, Ivan; Sierra, Jose Luis; Fernandez-Manjon, Baltasar

2007-01-01

In this paper, we propose three different ways of using IMS Learning Design to support online adaptive learning modules that include educational videogames. The first approach relies on IMS LD to support adaptation procedures where the educational games are considered as Learning Objects. These games can be included instead of traditional content…

Linking Immersive Virtual Field Trips with an Adaptive Learning Platform

NASA Astrophysics Data System (ADS)

Bruce, G.; Taylor, W.; Anbar, A. D.; Semken, S. C.; Buxner, S.; Mead, C.; El-Moujaber, E.; Summons, R. E.; Oliver, C.

2016-12-01

The use of virtual environments in science education has been constrained by the difficulty of guiding a learner's actions within the those environments. In this work, we demonstrate how advances in education software technology allow educators to create interactive learning experiences that respond and adapt intelligently to learner input within the virtual environment. This innovative technology provides a far greater capacity for delivering authentic inquiry-driven educational experiences in unique settings from around the world. Our immersive virtual field trips (iVFT) bring students virtually to geologically significant but inaccessible environments, where they learn through authentic practices of scientific inquiry. In one recent example, students explore the fossil beds in Nilpena, South Australia to learn about the Ediacaran fauna. Students interactively engage in 360° recreations of the environment, uncover the nature of the historical ecosystem by identifying fossils with a dichotomous key, explore actual fossil beds in high resolution imagery, and reconstruct what an ecosystem might have looked like millions of years ago in an interactive simulation. With the new capacity to connect actions within the iVFT to an intelligent tutoring system, these learning experiences can be tracked, guided, and tailored individually to the immediate actions of the student. This new capacity also has great potential for learning designers to take a data-driven approach to lesson improvement and for education researchers to study learning in virtual environments. Thus, we expect iVFT will be fertile ground for novel research. Such iVFT are currently in use in several introductory classes offered online at Arizona State University in anthropology, introductory biology, and astrobiology, reaching thousands of students to date. Drawing from these experiences, we are designing a curriculum for historical geology that will be built around iVFT-based exploration of Earth

Learning to speciate: The biased learning of mate preferences promotes adaptive radiation

PubMed Central

Gilman, R. Tucker; Kozak, Genevieve M.

2015-01-01

Bursts of rapid repeated speciation called adaptive radiations have generated much of Earth's biodiversity and fascinated biologists since Darwin, but we still do not know why some lineages radiate and others do not. Understanding what causes assortative mating to evolve rapidly and repeatedly in the same lineage is key to understanding adaptive radiation. Many species that have undergone adaptive radiations exhibit mate preference learning, where individuals acquire mate preferences by observing the phenotypes of other members of their populations. Mate preference learning can be biased if individuals also learn phenotypes to avoid in mates, and shift their preferences away from these avoided phenotypes. We used individual‐based computational simulations to study whether biased and unbiased mate preference learning promotes ecological speciation and adaptive radiation. We found that ecological speciation can be rapid and repeated when mate preferences are biased, but is inhibited when mate preferences are learned without bias. Our results suggest that biased mate preference learning may play an important role in generating animal biodiversity through adaptive radiation. PMID:26459795

Thai nursing students' adaption to problem-based learning: a qualitative study.

PubMed

Klunklin, Areewan; Subpaiboongid, Pornpun; Keitlertnapha, Pongsri; Viseskul, Nongkran; Turale, Sue

2011-11-01

Student-centred forms of learning have gained favour internationally over the last few decades including problem based learning, an approach now incorporated in medicine, nursing and other disciplines' education in many countries. However, it is still new in Thailand and being piloted to try to offset traditional forms of didactic, teacher-centred forms of teaching. In this qualitative study, 25 undergraduate nursing students in northern Thailand were interviewed about their experiences with problem-based learning in a health promotion subject. Content analysis was used to interrogate interview data, which revealed four categories: adapting, seeking assistance, self-development, and thinking process development. Initially participants had mixed emotions of confusion, negativity or boredom in the adaption process, but expressed satisfaction with creativity in learning, group work, and leadership development. They described increased abilities to problem solve and think critically, but struggled to develop questioning behaviours in learning. Socio-culturally in Thai education, students have great respect for teachers, but rarely question or challenge them or their learning. We conclude that problem-based learning has great potential in Thai nursing education, but educators and systems need to systematically prepare appropriate learning environments, their staff and students, to incorporate this within curricula. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Model for an Adaptive e-Learning Hypermedia System

ERIC Educational Resources Information Center

Mahnane, Lamia; Tayeb, Laskri Mohamed; Trigano, Philippe

2013-01-01

Recent years have shown increasing awareness for the importance of adaptivity in e-learning. Since the learning style of each learner is different. Adaptive e-learning hypermedia system (AEHS) must fit different learner's needs. A number of AEHS have been developed to support learning styles as a source for adaptation. However, these systems…

Specialized hybrid learners resolve Rogers' paradox about the adaptive value of social learning.

PubMed

Kharratzadeh, Milad; Montrey, Marcel; Metz, Alex; Shultz, Thomas R

2017-02-07

Culture is considered an evolutionary adaptation that enhances reproductive fitness. A common explanation is that social learning, the learning mechanism underlying cultural transmission, enhances mean fitness by avoiding the costs of individual learning. This explanation was famously contradicted by Rogers (1988), who used a simple mathematical model to show that cheap social learning can invade a population without raising its mean fitness. He concluded that some crucial factor remained unaccounted for, which would reverse this surprising result. Here we extend this model to include a more complex environment and limited resources, where individuals cannot reliably learn everything about the environment on their own. Under such conditions, cheap social learning evolves and enhances mean fitness, via hybrid learners capable of specializing their individual learning. We then show that while spatial or social constraints hinder the evolution of hybrid learners, a novel social learning strategy, complementary copying, can mitigate these effects. Copyright © 2016 Elsevier Ltd. All rights reserved.

A novel data-driven learning method for radar target detection in nonstationary environments

DOE PAGES

Akcakaya, Murat; Nehorai, Arye; Sen, Satyabrata

2016-04-12

Most existing radar algorithms are developed under the assumption that the environment (clutter) is stationary. However, in practice, the characteristics of the clutter can vary enormously depending on the radar-operational scenarios. If unaccounted for, these nonstationary variabilities may drastically hinder the radar performance. Therefore, to overcome such shortcomings, we develop a data-driven method for target detection in nonstationary environments. In this method, the radar dynamically detects changes in the environment and adapts to these changes by learning the new statistical characteristics of the environment and by intelligibly updating its statistical detection algorithm. Specifically, we employ drift detection algorithms to detectmore » changes in the environment; incremental learning, particularly learning under concept drift algorithms, to learn the new statistical characteristics of the environment from the new radar data that become available in batches over a period of time. The newly learned environment characteristics are then integrated in the detection algorithm. Furthermore, we use Monte Carlo simulations to demonstrate that the developed method provides a significant improvement in the detection performance compared with detection techniques that are not aware of the environmental changes.« less

Apprentissage et Environment (Learning and Environment)

ERIC Educational Resources Information Center

Care, Jean-Marc

1977-01-01

Detailed typical daily program in the life of an American and a Moroccan teenager introduces the discussion of the influence of the environment on the learning process, particularly on foreign language learning. A "kit" method for responding to needs determined by the environment is described. (Text is in French.) (AMH)

Adolescent Learning in the Zoo: Embedding a Non-Formal Learning Environment to Teach Formal Aspects of Vertebrate Biology

NASA Astrophysics Data System (ADS)

Randler, Christoph; Kummer, Barbara; Wilhelm, Christian

2012-06-01

The aim of this study was to assess the outcome of a zoo visit in terms of learning and retention of knowledge concerning the adaptations and behavior of vertebrate species. Basis of the work was the concept of implementing zoo visits as an out-of-school setting for formal, curriculum based learning. Our theoretical framework centers on the self-determination theory, therefore, we used a group-based, hands-on learning environment. To address this questions, we used a treatment—control design (BACI) with different treatments and a control group. Pre-, post- and retention tests were applied. All treatments led to a substantial increase of learning and retention knowledge compared to the control group. Immediately after the zoo visit, the zoo-guide tour provided the highest scores, while after a delay of 6 weeks, the learner-centered environment combined with a teacher-guided summarizing scored best. We suggest incorporating the zoo as an out-of-school environment into formal school learning, and we propose different methods to improve learning in zoo settings.

Seamless Integration of Desktop and Mobile Learning Experience through an Ontology-Based Adaptation Engine: Report of a Pilot-Project

ERIC Educational Resources Information Center

Mercurio, Marco; Torre, Ilaria; Torsani, Simone

2014-01-01

The paper describes a module within the distance language learning environment of the Language Centre at the Genoa University which adapts, through an ontology, learning activities to the device in use. Adaptation means not simply resizing a page but also the ability to transform the nature of a task so that it fits the device with the smallest…

Associative visual learning by tethered bees in a controlled visual environment.

PubMed

Buatois, Alexis; Pichot, Cécile; Schultheiss, Patrick; Sandoz, Jean-Christophe; Lazzari, Claudio R; Chittka, Lars; Avarguès-Weber, Aurore; Giurfa, Martin

2017-10-10

Free-flying honeybees exhibit remarkable cognitive capacities but the neural underpinnings of these capacities cannot be studied in flying insects. Conversely, immobilized bees are accessible to neurobiological investigation but display poor visual learning. To overcome this limitation, we aimed at establishing a controlled visual environment in which tethered bees walking on a spherical treadmill learn to discriminate visual stimuli video projected in front of them. Freely flying bees trained to walk into a miniature Y-maze displaying these stimuli in a dark environment learned the visual discrimination efficiently when one of them (CS+) was paired with sucrose and the other with quinine solution (CS-). Adapting this discrimination to the treadmill paradigm with a tethered, walking bee was successful as bees exhibited robust discrimination and preferred the CS+ to the CS- after training. As learning was better in the maze, movement freedom, active vision and behavioral context might be important for visual learning. The nature of the punishment associated with the CS- also affects learning as quinine and distilled water enhanced the proportion of learners. Thus, visual learning is amenable to a controlled environment in which tethered bees learn visual stimuli, a result that is important for future neurobiological studies in virtual reality.

Neural Mechanisms for Adaptive Learned Avoidance of Mental Effort.

PubMed

Mitsuto Nagase, Asako; Onoda, Keiichi; Clifford Foo, Jerome; Haji, Tomoki; Akaishi, Rei; Yamaguchi, Shuhei; Sakai, Katsuyuki; Morita, Kenji

2018-02-05

Humans tend to avoid mental effort. Previous studies have demonstrated this tendency using various demand-selection tasks; participants generally avoid options associated with higher cognitive demand. However, it remains unclear whether humans avoid mental effort adaptively in uncertain and non-stationary environments, and if so, what neural mechanisms underlie this learned avoidance and whether they remain the same irrespective of cognitive-demand types. We addressed these issues by developing novel demand-selection tasks where associations between choice options and cognitive-demand levels change over time, with two variations using mental arithmetic and spatial reasoning problems (29:4 and 18:2 males:females). Most participants showed avoidance, and their choices depended on the demand experienced on multiple preceding trials. We assumed that participants updated the expected cost of mental effort through experience, and fitted their choices by reinforcement learning models, comparing several possibilities. Model-based fMRI analyses revealed that activity in the dorsomedial and lateral frontal cortices was positively correlated with the trial-by-trial expected cost for the chosen option commonly across the different types of cognitive demand, and also revealed a trend of negative correlation in the ventromedial prefrontal cortex. We further identified correlates of cost-prediction-error at time of problem-presentation or answering the problem, the latter of which partially overlapped with or were proximal to the correlates of expected cost at time of choice-cue in the dorsomedial frontal cortex. These results suggest that humans adaptively learn to avoid mental effort, having neural mechanisms to represent expected cost and cost-prediction-error, and the same mechanisms operate for various types of cognitive demand. SIGNIFICANCE STATEMENT In daily life, humans encounter various cognitive demands, and tend to avoid high-demand options. However, it remains unclear

Seeing is believing: effects of visual contextual cues on learning and transfer of locomotor adaptation.

PubMed

Torres-Oviedo, Gelsy; Bastian, Amy J

2010-12-15

Devices such as robots or treadmills are often used to drive motor learning because they can create novel physical environments. However, the learning (i.e., adaptation) acquired on these devices only partially generalizes to natural movements. What determines the specificity of motor learning, and can this be reliably made more general? Here we investigated the effect of visual cues on the specificity of split-belt walking adaptation. We systematically removed vision to eliminate the visual-proprioceptive mismatch that is a salient cue specific to treadmills: vision indicates that we are not moving while leg proprioception indicates that we are. We evaluated the adaptation of temporal and spatial features of gait (i.e., timing and location of foot landing), their transfer to walking over ground, and washout of adaptation when subjects returned to the treadmill. Removing vision during both training (i.e., on the treadmill) and testing (i.e., over ground) strongly improved the transfer of treadmill adaptation to natural walking. Removing vision only during training increased transfer of temporal adaptation, whereas removing vision only during testing increased the transfer of spatial adaptation. This dissociation reveals differences in adaptive mechanisms for temporal and spatial features of walking. Finally training without vision increased the amount that was learned and was linked to the variability in the behavior during adaptation. In conclusion, contextual cues can be manipulated to modulate the magnitude, transfer, and washout of device-induced learning in humans. These results bring us closer to our ultimate goal of developing rehabilitation strategies that improve movements beyond the clinical setting.

Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning.

PubMed

Stark-Inbar, Alit; Raza, Meher; Taylor, Jordan A; Ivry, Richard B

2017-01-01

In standard taxonomies, motor skills are typically treated as representative of implicit or procedural memory. We examined two emblematic tasks of implicit motor learning, sensorimotor adaptation and sequence learning, asking whether individual differences in learning are correlated between these tasks, as well as how individual differences within each task are related to different performance variables. As a prerequisite, it was essential to establish the reliability of learning measures for each task. Participants were tested twice on a visuomotor adaptation task and on a sequence learning task, either the serial reaction time task or the alternating reaction time task. Learning was evident in all tasks at the group level and reliable at the individual level in visuomotor adaptation and the alternating reaction time task but not in the serial reaction time task. Performance variability was predictive of learning in both domains, yet the relationship was in the opposite direction for adaptation and sequence learning. For the former, faster learning was associated with lower variability, consistent with models of sensorimotor adaptation in which learning rates are sensitive to noise. For the latter, greater learning was associated with higher variability and slower reaction times, factors that may facilitate the spread of activation required to form predictive, sequential associations. Interestingly, learning measures of the different tasks were not correlated. Together, these results oppose a shared process for implicit learning in sensorimotor adaptation and sequence learning and provide insight into the factors that account for individual differences in learning within each task domain. We investigated individual differences in the ability to implicitly learn motor skills. As a prerequisite, we assessed whether individual differences were reliable across test sessions. We found that two commonly used tasks of implicit learning, visuomotor adaptation and the

Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning

PubMed Central

Raza, Meher; Ivry, Richard B.

2016-01-01

In standard taxonomies, motor skills are typically treated as representative of implicit or procedural memory. We examined two emblematic tasks of implicit motor learning, sensorimotor adaptation and sequence learning, asking whether individual differences in learning are correlated between these tasks, as well as how individual differences within each task are related to different performance variables. As a prerequisite, it was essential to establish the reliability of learning measures for each task. Participants were tested twice on a visuomotor adaptation task and on a sequence learning task, either the serial reaction time task or the alternating reaction time task. Learning was evident in all tasks at the group level and reliable at the individual level in visuomotor adaptation and the alternating reaction time task but not in the serial reaction time task. Performance variability was predictive of learning in both domains, yet the relationship was in the opposite direction for adaptation and sequence learning. For the former, faster learning was associated with lower variability, consistent with models of sensorimotor adaptation in which learning rates are sensitive to noise. For the latter, greater learning was associated with higher variability and slower reaction times, factors that may facilitate the spread of activation required to form predictive, sequential associations. Interestingly, learning measures of the different tasks were not correlated. Together, these results oppose a shared process for implicit learning in sensorimotor adaptation and sequence learning and provide insight into the factors that account for individual differences in learning within each task domain. NEW & NOTEWORTHY We investigated individual differences in the ability to implicitly learn motor skills. As a prerequisite, we assessed whether individual differences were reliable across test sessions. We found that two commonly used tasks of implicit learning, visuomotor

Adaptive and perceptual learning technologies in medical education and training.

PubMed

Kellman, Philip J

2013-10-01

Recent advances in the learning sciences offer remarkable potential to improve medical education and maximize the benefits of emerging medical technologies. This article describes 2 major innovation areas in the learning sciences that apply to simulation and other aspects of medical learning: Perceptual learning (PL) and adaptive learning technologies. PL technology offers, for the first time, systematic, computer-based methods for teaching pattern recognition, structural intuition, transfer, and fluency. Synergistic with PL are new adaptive learning technologies that optimize learning for each individual, embed objective assessment, and implement mastery criteria. The author describes the Adaptive Response-Time-based Sequencing (ARTS) system, which uses each learner's accuracy and speed in interactive learning to guide spacing, sequencing, and mastery. In recent efforts, these new technologies have been applied in medical learning contexts, including adaptive learning modules for initial medical diagnosis and perceptual/adaptive learning modules (PALMs) in dermatology, histology, and radiology. Results of all these efforts indicate the remarkable potential of perceptual and adaptive learning technologies, individually and in combination, to improve learning in a variety of medical domains. Reprint & Copyright © 2013 Association of Military Surgeons of the U.S.

Dental students' and staff perceptions of the impact of learning environment disruption on their learning and teaching experiences.

PubMed

The, A J M; Adam, L; Meldrum, A; Brunton, P

2017-10-06

This project is a qualitative investigation into student and staff experiences of the effect of a major building redevelopment on their Dental School learning and teaching environments. Currently, there is little research exploring the impact of disruptions to the learning environment on students' learning and staff teaching experiences. Data were collected in 2016 using an online survey, semi-structured interviews and focus groups with students and staff. Data were analysed using a general inductive approach. Four broad themes emerged as follows: (i) students valued having a space for personal and collaborative work within the Dental School; (ii) both staff and students positioned staff contributions to learning experiences above the role of the physical learning environment; (iii) the majority of staff and students not feel that the physical environment limited their clinical training; and (iv) staff and students were able to adapt to the impact of building redevelopment through resilience and organisation. Results of this research have informed the provision of collegial spaces at the School, both as the building redevelopment continues, and in planning for the completed building. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Dynamic learning from adaptive neural network control of a class of nonaffine nonlinear systems.

PubMed

Dai, Shi-Lu; Wang, Cong; Wang, Min

2014-01-01

This paper studies the problem of learning from adaptive neural network (NN) control of a class of nonaffine nonlinear systems in uncertain dynamic environments. In the control design process, a stable adaptive NN tracking control design technique is proposed for the nonaffine nonlinear systems with a mild assumption by combining a filtered tracking error with the implicit function theorem, input-to-state stability, and the small-gain theorem. The proposed stable control design technique not only overcomes the difficulty in controlling nonaffine nonlinear systems but also relaxes constraint conditions of the considered systems. In the learning process, the partial persistent excitation (PE) condition of radial basis function NNs is satisfied during tracking control to a recurrent reference trajectory. Under the PE condition and an appropriate state transformation, the proposed adaptive NN control is shown to be capable of acquiring knowledge on the implicit desired control input dynamics in the stable control process and of storing the learned knowledge in memory. Subsequently, an NN learning control design technique that effectively exploits the learned knowledge without re-adapting to the controller parameters is proposed to achieve closed-loop stability and improved control performance. Simulation studies are performed to demonstrate the effectiveness of the proposed design techniques.

Enhancing Learning Performance and Adaptability for Complex Tasks

DTIC Science & Technology

2005-03-30

development of active learning interventions and techniques that influence the focus and quality of learner regulatory activity (Kozlowski Toney et al...what are the effects of these goal representations on learning strategies, performance, and adaptability? Can active learning inductions, that influence...and mindful process - active learning - are generally associated with improved skill acquisition and adaptability for complex tasks (Smith et al

Selection, adaptation, and predictive information in changing environments

NASA Astrophysics Data System (ADS)

Feltgen, Quentin; Nemenman, Ilya

2014-03-01

Adaptation by means of natural selection is a key concept in evolutionary biology. Individuals better matched to the surrounding environment outcompete the others. This increases the fraction of the better adapted individuals in the population, and hence increases its collective fitness. Adaptation is also prominent on the physiological scale in neuroscience and cell biology. There each individual infers properties of the environment and changes to become individually better, improving the overall population as well. Traditionally, these two notions of adaption have been considered distinct. Here we argue that both types of adaptation result in the same population growth in a broad class of analytically tractable population dynamics models in temporally changing environments. In particular, both types of adaptation lead to subextensive corrections to the population growth rates. These corrections are nearly universal and are equal to the predictive information in the environment time series, which is also the characterization of the time series complexity. This work has been supported by the James S. McDonnell Foundation.

Electroencephalographic identifiers of motor adaptation learning

NASA Astrophysics Data System (ADS)

Özdenizci, Ozan; Yalçın, Mustafa; Erdoğan, Ahmetcan; Patoğlu, Volkan; Grosse-Wentrup, Moritz; Çetin, Müjdat

2017-08-01

Objective. Recent brain-computer interface (BCI) assisted stroke rehabilitation protocols tend to focus on sensorimotor activity of the brain. Relying on evidence claiming that a variety of brain rhythms beyond sensorimotor areas are related to the extent of motor deficits, we propose to identify neural correlates of motor learning beyond sensorimotor areas spatially and spectrally for further use in novel BCI-assisted neurorehabilitation settings. Approach. Electroencephalographic (EEG) data were recorded from healthy subjects participating in a physical force-field adaptation task involving reaching movements through a robotic handle. EEG activity recorded during rest prior to the experiment and during pre-trial movement preparation was used as features to predict motor adaptation learning performance across subjects. Main results. Subjects learned to perform straight movements under the force-field at different adaptation rates. Both resting-state and pre-trial EEG features were predictive of individual adaptation rates with relevance of a broad network of beta activity. Beyond sensorimotor regions, a parieto-occipital cortical component observed across subjects was involved strongly in predictions and a fronto-parietal cortical component showed significant decrease in pre-trial beta-powers for users with higher adaptation rates and increase in pre-trial beta-powers for users with lower adaptation rates. Significance. Including sensorimotor areas, a large-scale network of beta activity is presented as predictive of motor learning. Strength of resting-state parieto-occipital beta activity or pre-trial fronto-parietal beta activity can be considered in BCI-assisted stroke rehabilitation protocols with neurofeedback training or volitional control of neural activity for brain-robot interfaces to induce plasticity.

Learning from adaptive neural dynamic surface control of strict-feedback systems.

PubMed

Wang, Min; Wang, Cong

2015-06-01

Learning plays an essential role in autonomous control systems. However, how to achieve learning in the nonstationary environment for nonlinear systems is a challenging problem. In this paper, we present learning method for a class of n th-order strict-feedback systems by adaptive dynamic surface control (DSC) technology, which achieves the human-like ability of learning by doing and doing with learned knowledge. To achieve the learning, this paper first proposes stable adaptive DSC with auxiliary first-order filters, which ensures the boundedness of all the signals in the closed-loop system and the convergence of tracking errors in a finite time. With the help of DSC, the derivative of the filter output variable is used as the neural network (NN) input instead of traditional intermediate variables. As a result, the proposed adaptive DSC method reduces greatly the dimension of NN inputs, especially for high-order systems. After the stable DSC design, we decompose the stable closed-loop system into a series of linear time-varying perturbed subsystems. Using a recursive design, the recurrent property of NN input variables is easily verified since the complexity is overcome using DSC. Subsequently, the partial persistent excitation condition of the radial basis function NN is satisfied. By combining a state transformation, accurate approximations of the closed-loop system dynamics are recursively achieved in a local region along recurrent orbits. Then, the learning control method using the learned knowledge is proposed to achieve the closed-loop stability and the improved control performance. Simulation studies are performed to demonstrate the proposed scheme can not only reuse the learned knowledge to achieve the better control performance with the faster tracking convergence rate and the smaller tracking error but also greatly alleviate the computational burden because of reducing the number and complexity of NN input variables.

Visual learning with reduced adaptation is eccentricity-specific.

PubMed

Harris, Hila; Sagi, Dov

2018-01-12

Visual learning is known to be specific to the trained target location, showing little transfer to untrained locations. Recently, learning was shown to transfer across equal-eccentricity retinal-locations when sensory adaptation due to repetitive stimulation was minimized. It was suggested that learning transfers to previously untrained locations when the learned representation is location invariant, with sensory adaptation introducing location-dependent representations, thus preventing transfer. Spatial invariance may also fail when the trained and tested locations are at different distance from the center of gaze (different retinal eccentricities), due to differences in the corresponding low-level cortical representations (e.g. allocated cortical area decreases with eccentricity). Thus, if learning improves performance by better classifying target-dependent early visual representations, generalization is predicted to fail when locations of different retinal eccentricities are trained and tested in the absence sensory adaptation. Here, using the texture discrimination task, we show specificity of learning across different retinal eccentricities (4-8°) using reduced adaptation training. The existence of generalization across equal-eccentricity locations but not across different eccentricities demonstrates that learning accesses visual representations preceding location independent representations, with specificity of learning explained by inhomogeneous sensory representation.

How Customer Facing Professionals Adapt to Changing Customer Needs in a Digital Environment: A Single Case Study

ERIC Educational Resources Information Center

Hendriks, Stefan

2017-01-01

This qualitative single case study explored how customer facing professionals (CFPs) adapt to changing customer needs in a digital environment. This study focuses on: (1) Changing customer needs; (2) Competencies needed in a digital environment; (3) How they learn; and (4) What factors help or hinder their success. The site is a global Human…

Exploring Adaptability through Learning Layers and Learning Loops

ERIC Educational Resources Information Center

Lof, Annette

2010-01-01

Adaptability in social-ecological systems results from individual and collective action, and multi-level interactions. It can be understood in a dual sense as a system's ability to adapt to disturbance and change, and to navigate system transformation. Inherent in this conception, as found in resilience thinking, are the concepts of learning and…

Internationalising a Learning Environment Instrument for Evaluating Transnational Online University Courses

ERIC Educational Resources Information Center

Yeo, Shelley; Taylor, Peter; Kulski, Martijntje

2006-01-01

This article describes the adaptation and validation of the Constructivist OnLine Learning Environment Survey (COLLES) for use in the transnational higher education context. As higher education becomes a more global phenomenon, "borderless" education, either online or by distance education, is becoming a reality and there is a need for…

Clinical quality needs complex adaptive systems and machine learning.

PubMed

Marsland, Stephen; Buchan, Iain

2004-01-01

The vast increase in clinical data has the potential to bring about large improvements in clinical quality and other aspects of healthcare delivery. However, such benefits do not come without cost. The analysis of such large datasets, particularly where the data may have to be merged from several sources and may be noisy and incomplete, is a challenging task. Furthermore, the introduction of clinical changes is a cyclical task, meaning that the processes under examination operate in an environment that is not static. We suggest that traditional methods of analysis are unsuitable for the task, and identify complexity theory and machine learning as areas that have the potential to facilitate the examination of clinical quality. By its nature the field of complex adaptive systems deals with environments that change because of the interactions that have occurred in the past. We draw parallels between health informatics and bioinformatics, which has already started to successfully use machine learning methods.

Dynamically analyzing cell interactions in biological environments using multiagent social learning framework.

PubMed

Zhang, Chengwei; Li, Xiaohong; Li, Shuxin; Feng, Zhiyong

2017-09-20

Biological environment is uncertain and its dynamic is similar to the multiagent environment, thus the research results of the multiagent system area can provide valuable insights to the understanding of biology and are of great significance for the study of biology. Learning in a multiagent environment is highly dynamic since the environment is not stationary anymore and each agent's behavior changes adaptively in response to other coexisting learners, and vice versa. The dynamics becomes more unpredictable when we move from fixed-agent interaction environments to multiagent social learning framework. Analytical understanding of the underlying dynamics is important and challenging. In this work, we present a social learning framework with homogeneous learners (e.g., Policy Hill Climbing (PHC) learners), and model the behavior of players in the social learning framework as a hybrid dynamical system. By analyzing the dynamical system, we obtain some conditions about convergence or non-convergence. We experimentally verify the predictive power of our model using a number of representative games. Experimental results confirm the theoretical analysis. Under multiagent social learning framework, we modeled the behavior of agent in biologic environment, and theoretically analyzed the dynamics of the model. We present some sufficient conditions about convergence or non-convergence and prove them theoretically. It can be used to predict the convergence of the system.

Adaptable Learning Pathway Generation with Ant Colony Optimization

ERIC Educational Resources Information Center

Wong, Lung-Hsiang; Looi, Chee-Kit

2009-01-01

One of the new major directions in research on web-based educational systems is the notion of adaptability: the educational system adapts itself to the learning profile, preferences and ability of the student. In this paper, we look into the issues of providing adaptability with respect to learning pathways. We explore the state of the art with…

Reinforcement Learning in a Nonstationary Environment: The El Farol Problem

NASA Technical Reports Server (NTRS)

Bell, Ann Maria

1999-01-01

This paper examines the performance of simple learning rules in a complex adaptive system based on a coordination problem modeled on the El Farol problem. The key features of the El Farol problem are that it typically involves a medium number of agents and that agents' pay-off functions have a discontinuous response to increased congestion. First we consider a single adaptive agent facing a stationary environment. We demonstrate that the simple learning rules proposed by Roth and Er'ev can be extremely sensitive to small changes in the initial conditions and that events early in a simulation can affect the performance of the rule over a relatively long time horizon. In contrast, a reinforcement learning rule based on standard practice in the computer science literature converges rapidly and robustly. The situation is reversed when multiple adaptive agents interact: the RE algorithms often converge rapidly to a stable average aggregate attendance despite the slow and erratic behavior of individual learners, while the CS based learners frequently over-attend in the early and intermediate terms. The symmetric mixed strategy equilibria is unstable: all three learning rules ultimately tend towards pure strategies or stabilize in the medium term at non-equilibrium probabilities of attendance. The brittleness of the algorithms in different contexts emphasize the importance of thorough and thoughtful examination of simulation-based results.

Animal social learning: associations and adaptations.

PubMed

Reader, Simon M

2016-01-01

Social learning, learning from others, is a powerful process known to impact the success and survival of humans and non-human animals alike. Yet we understand little about the neurocognitive and other processes that underpin social learning. Social learning has often been assumed to involve specialized, derived cognitive processes that evolve and develop independently from other processes. However, this assumption is increasingly questioned, and evidence from a variety of organisms demonstrates that current, recent, and early life experience all predict the reliance on social information and thus can potentially explain variation in social learning as a result of experiential effects rather than evolved differences. General associative learning processes, rather than adaptive specializations, may underpin much social learning, as well as social learning strategies. Uncovering these distinctions is important to a variety of fields, for example by widening current views of the possible breadth and adaptive flexibility of social learning. Nonetheless, just like adaptationist evolutionary explanations, associationist explanations for social learning cannot be assumed, and empirical work is required to uncover the mechanisms involved and their impact on the efficacy of social learning. This work is being done, but more is needed. Current evidence suggests that much social learning may be based on 'ordinary' processes but with extraordinary consequences.

Genome-environment associations in sorghum landraces predict adaptive traits

PubMed Central

Lasky, Jesse R.; Upadhyaya, Hari D.; Ramu, Punna; Deshpande, Santosh; Hash, C. Tom; Bonnette, Jason; Juenger, Thomas E.; Hyma, Katie; Acharya, Charlotte; Mitchell, Sharon E.; Buckler, Edward S.; Brenton, Zachary; Kresovich, Stephen; Morris, Geoffrey P.

2015-01-01

Improving environmental adaptation in crops is essential for food security under global change, but phenotyping adaptive traits remains a major bottleneck. If associations between single-nucleotide polymorphism (SNP) alleles and environment of origin in crop landraces reflect adaptation, then these could be used to predict phenotypic variation for adaptive traits. We tested this proposition in the global food crop Sorghum bicolor, characterizing 1943 georeferenced landraces at 404,627 SNPs and quantifying allelic associations with bioclimatic and soil gradients. Environment explained a substantial portion of SNP variation, independent of geographical distance, and genic SNPs were enriched for environmental associations. Further, environment-associated SNPs predicted genotype-by-environment interactions under experimental drought stress and aluminum toxicity. Our results suggest that genomic signatures of environmental adaptation may be useful for crop improvement, enhancing germplasm identification and marker-assisted selection. Together, genome-environment associations and phenotypic analyses may reveal the basis of environmental adaptation. PMID:26601206

Diminished Neural Adaptation during Implicit Learning in Autism

PubMed Central

Schipul, Sarah E.; Just, Marcel Adam

2015-01-01

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

Yet Another Adaptive Learning Management System Based on Felder and Silverman's Learning Styles and Mashup

ERIC Educational Resources Information Center

Chang, Yi-Hsing; Chen, Yen-Yi; Chen, Nian-Shing; Lu, You-Te; Fang, Rong-Jyue

2016-01-01

This study designs and implements an adaptive learning management system based on Felder and Silverman's Learning Style Model and the Mashup technology. In this system, Felder and Silverman's Learning Style model is used to assess students' learning styles, in order to provide adaptive learning to leverage learners' learning preferences.…

Establishing Positive Learning Environments for Students of Chinese American and Latino Backgrounds

ERIC Educational Resources Information Center

Wong-Lo, Mickie; Cortez, Gabriel A.

2014-01-01

Cultivating positive learning environments for underrepresented groups such as students of Chinese American and Latino backgrounds require careful planning and consideration. As our society strives to embrace individual differences of all cultures, educators must equip themselves with effective tools to adapt to the ever-changing dynamics within…

Exploring Collaborative Learning Effect in Blended Learning Environments

ERIC Educational Resources Information Center

Sun, Z.; Liu, R.; Luo, L.; Wu, M.; Shi, C.

2017-01-01

The use of new technology encouraged exploration of the effectiveness and difference of collaborative learning in blended learning environments. This study investigated the social interactive network of students, level of knowledge building and perception level on usefulness in online and mobile collaborative learning environments in higher…

Adaptive Batch Mode Active Learning.

PubMed

Chakraborty, Shayok; Balasubramanian, Vineeth; Panchanathan, Sethuraman

2015-08-01

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

Concept Based Approach for Adaptive Personalized Course Learning System

ERIC Educational Resources Information Center

Salahli, Mehmet Ali; Özdemir, Muzaffer; Yasar, Cumali

2013-01-01

One of the most important factors for improving the personalization aspects of learning systems is to enable adaptive properties to them. The aim of the adaptive personalized learning system is to offer the most appropriate learning path and learning materials to learners by taking into account their profiles. In this paper, a new approach to…

Adaptive Learning and Risk Taking

ERIC Educational Resources Information Center

Denrell, Jerker

2007-01-01

Humans and animals learn from experience by reducing the probability of sampling alternatives with poor past outcomes. Using simulations, J. G. March (1996) illustrated how such adaptive sampling could lead to risk-averse as well as risk-seeking behavior. In this article, the author develops a formal theory of how adaptive sampling influences risk…

Improving Adaptive Learning Technology through the Use of Response Times

ERIC Educational Resources Information Center

Mettler, Everett; Massey, Christine M.; Kellman, Philip J.

2011-01-01

Adaptive learning techniques have typically scheduled practice using learners' accuracy and item presentation history. We describe an adaptive learning system (Adaptive Response Time Based Sequencing--ARTS) that uses both accuracy and response time (RT) as direct inputs into sequencing. Response times are used to assess learning strength and…

Organization of Distributed Adaptive Learning

ERIC Educational Resources Information Center

Vengerov, Alexander

2009-01-01

The growing sensitivity of various systems and parts of industry, society, and even everyday individual life leads to the increased volume of changes and needs for adaptation and learning. This creates a new situation where learning from being purely academic knowledge transfer procedure is becoming a ubiquitous always-on essential part of all…

Deep reinforcement learning for automated radiation adaptation in lung cancer.

PubMed

Tseng, Huan-Hsin; Luo, Yi; Cui, Sunan; Chien, Jen-Tzung; Ten Haken, Randall K; Naqa, Issam El

2017-12-01

To investigate deep reinforcement learning (DRL) based on historical treatment plans for developing automated radiation adaptation protocols for nonsmall cell lung cancer (NSCLC) patients that aim to maximize tumor local control at reduced rates of radiation pneumonitis grade 2 (RP2). In a retrospective population of 114 NSCLC patients who received radiotherapy, a three-component neural networks framework was developed for deep reinforcement learning (DRL) of dose fractionation adaptation. Large-scale patient characteristics included clinical, genetic, and imaging radiomics features in addition to tumor and lung dosimetric variables. First, a generative adversarial network (GAN) was employed to learn patient population characteristics necessary for DRL training from a relatively limited sample size. Second, a radiotherapy artificial environment (RAE) was reconstructed by a deep neural network (DNN) utilizing both original and synthetic data (by GAN) to estimate the transition probabilities for adaptation of personalized radiotherapy patients' treatment courses. Third, a deep Q-network (DQN) was applied to the RAE for choosing the optimal dose in a response-adapted treatment setting. This multicomponent reinforcement learning approach was benchmarked against real clinical decisions that were applied in an adaptive dose escalation clinical protocol. In which, 34 patients were treated based on avid PET signal in the tumor and constrained by a 17.2% normal tissue complication probability (NTCP) limit for RP2. The uncomplicated cure probability (P+) was used as a baseline reward function in the DRL. Taking our adaptive dose escalation protocol as a blueprint for the proposed DRL (GAN + RAE + DQN) architecture, we obtained an automated dose adaptation estimate for use at ∼2/3 of the way into the radiotherapy treatment course. By letting the DQN component freely control the estimated adaptive dose per fraction (ranging from 1-5 Gy), the DRL automatically favored dose

The Impact of an Automated Learning Component against a Traditional Lecturing Environment

ERIC Educational Resources Information Center

Maycock, Keith W.; Keating, J. G.

2017-01-01

This experimental study investigates the effect on the examination performance of a cohort of first-year undergraduate learners undertaking a Unified Modelling Language (UML) course using an adaptive learning system against a control group of learners undertaking the same UML course through a traditional lecturing environment. The adaptive…

Scaffolding in Connectivist Mobile Learning Environment

ERIC Educational Resources Information Center

Ozan, Ozlem

2013-01-01

Social networks and mobile technologies are transforming learning ecology. In this changing learning environment, we find a variety of new learner needs. The aim of this study is to investigate how to provide scaffolding to the learners in connectivist mobile learning environment: (1) to learn in a networked environment; (2) to manage their…

Rural Junior Secondary School Students' Perceptions of Classroom Learning Environments and Their Attitude and Achievement in Mathematics in West China

ERIC Educational Resources Information Center

Yang, Xinrong

2015-01-01

This paper reports findings from a survey of how rural junior secondary school students in the western part of China perceive their mathematics classroom learning environments and associations of learning environment with their attitudes toward mathematics and mathematics achievement. Using adaptations of the widely-used What Is Happening In this…

Perceptual learning in sensorimotor adaptation.

PubMed

Darainy, Mohammad; Vahdat, Shahabeddin; Ostry, David J

2013-11-01

Motor learning often involves situations in which the somatosensory targets of movement are, at least initially, poorly defined, as for example, in learning to speak or learning the feel of a proper tennis serve. Under these conditions, motor skill acquisition presumably requires perceptual as well as motor learning. That is, it engages both the progressive shaping of sensory targets and associated changes in motor performance. In the present study, we test the idea that perceptual learning alters somatosensory function and in so doing produces changes to human motor performance and sensorimotor adaptation. Subjects in these experiments undergo perceptual training in which a robotic device passively moves the subject's arm on one of a set of fan-shaped trajectories. Subjects are required to indicate whether the robot moved the limb to the right or the left and feedback is provided. Over the course of training both the perceptual boundary and acuity are altered. The perceptual learning is observed to improve both the rate and extent of learning in a subsequent sensorimotor adaptation task and the benefits persist for at least 24 h. The improvement in the present studies varies systematically with changes in perceptual acuity and is obtained regardless of whether the perceptual boundary shift serves to systematically increase or decrease error on subsequent movements. The beneficial effects of perceptual training are found to be substantially dependent on reinforced decision-making in the sensory domain. Passive-movement training on its own is less able to alter subsequent learning in the motor system. Overall, this study suggests perceptual learning plays an integral role in motor learning.

Planning the Learning Environment.

ERIC Educational Resources Information Center

Singel, Raymond J.

The learning environment and its interrelationship with educational policies and the coordinated planning and design of schools and their facilities are discussed in the light of the human organism or student. The problems and hazards of present learning environments are reviewed in conjunction with environmental control and its influence on…

Learning in a Changing Environment

ERIC Educational Resources Information Center

Speekenbrink, Maarten; Shanks, David R.

2010-01-01

Multiple cue probability learning studies have typically focused on stationary environments. We present 3 experiments investigating learning in changing environments. A fine-grained analysis of the learning dynamics shows that participants were responsive to both abrupt and gradual changes in cue-outcome relations. We found no evidence that…

Effectiveness of Adaptive E-Learning Environments on Knowledge, Competence, and Behavior in Health Professionals and Students: Protocol for a Systematic Review and Meta-Analysis.

PubMed

Fontaine, Guillaume; Cossette, Sylvie; Maheu-Cadotte, Marc-André; Mailhot, Tanya; Deschênes, Marie-France; Mathieu-Dupuis, Gabrielle

2017-07-05

Adaptive e-learning environments (AEEs) can provide tailored instruction by adapting content, navigation, presentation, multimedia, and tools to each user's navigation behavior, individual objectives, knowledge, and preferences. AEEs can have various levels of complexity, ranging from systems using a simple adaptive functionality to systems using artificial intelligence. While AEEs are promising, their effectiveness for the education of health professionals and health professions students remains unclear. The purpose of this systematic review is to assess the effectiveness of AEEs in improving knowledge, competence, and behavior in health professionals and students. We will follow the Cochrane Collaboration and the Effective Practice and Organisation of Care (EPOC) Group guidelines on systematic review methodology. A systematic search of the literature will be conducted in 6 bibliographic databases (CINAHL, EMBASE, ERIC, PsycINFO, PubMed, and Web of Science) using the concepts "adaptive e-learning environments," "health professionals/students," and "effects on knowledge/skills/behavior." We will include randomized and nonrandomized controlled trials, in addition to controlled before-after, interrupted time series, and repeated measures studies published between 2005 and 2017. The title and the abstract of each study followed by a full-text assessment of potentially eligible studies will be independently screened by 2 review authors. Using the EPOC extraction form, 1 review author will conduct data extraction and a second author will validate the data extraction. The methodological quality of included studies will be independently assessed by 2 review authors using the EPOC risk of bias criteria. Included studies will be synthesized by a descriptive analysis. Where appropriate, data will be pooled using meta-analysis by applying the RevMan software version 5.1, considering the heterogeneity of studies. The review is in progress. We plan to submit the results in the

Investigating Work and Learning through Complex Adaptive Organisations

ERIC Educational Resources Information Center

Lizier, Amanda Louise

2017-01-01

Purpose: The purpose of this paper is to outline an empirical study of how professionals experience work and learning in complex adaptive organisations. The study uses a complex adaptive systems approach, which forms the basis of a specifically developed conceptual framework for explaining professionals' experiences of work and learning.…

Design Approach of Mathematics Learning Activities in a Digital Environment for Children with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Santos, Maria Isabel; Breda, Ana; Almeida, Ana Margarida

2017-01-01

Learning environment on mathematics for autistic children is a prototype of a digital environment with dynamic adaptation features designed to offer activities towards the development of mathematical reasoning in children aged 6-12 years, diagnosed with autism spectrum disorders (ASD), a neurodevelopmental disorder characterized by deficits in…

Learning with Hypertext Learning Environments: Theory, Design, and Research.

ERIC Educational Resources Information Center

Jacobson, Michael J.; And Others

1996-01-01

Studied 69 undergraduates who used conceptually-indexed hypertext learning environments with differently structured thematic criss-crossing (TCC) treatments: guided and learner selected. Found that students need explicit modeling and scaffolding support to learn complex knowledge from these learning environments, and considers implications for…

Instructional Management for Adaptive Training and Education in Support of the US Army Learning Model-Research Outline

DTIC Science & Technology

2015-11-01

within adaptive training environments. This line of research associates with tenets of Social Cognitive Theory in that learning is theorized to be an...Challenges 17 6.1 Guidance and Scaffolding 17 6.2 Social Dynamics and Virtual Humans 21 6.3 Metacognition and Self-Regulated Learning 23 6.4...and develop prototype authoring tools grounded in learning and instructional theory and informed by empirical research to assist training managers

Science Learning Outcomes in Alignment with Learning Environment Preferences

ERIC Educational Resources Information Center

Chang, Chun-Yen; Hsiao, Chien-Hua; Chang, Yueh-Hsia

2011-01-01

This study investigated students' learning environment preferences and compared the relative effectiveness of instructional approaches on students' learning outcomes in achievement and attitude among 10th grade earth science classes in Taiwan. Data collection instruments include the Earth Science Classroom Learning Environment Inventory and Earth…

Integrating Learning, Problem Solving, and Engagement in Narrative-Centered Learning Environments

ERIC Educational Resources Information Center

Rowe, Jonathan P.; Shores, Lucy R.; Mott, Bradford W.; Lester, James C.

2011-01-01

A key promise of narrative-centered learning environments is the ability to make learning engaging. However, there is concern that learning and engagement may be at odds in these game-based learning environments. This view suggests that, on the one hand, students interacting with a game-based learning environment may be engaged but unlikely to…

Adult learners in a novel environment use prestige-biased social learning.

PubMed

Atkisson, Curtis; O'Brien, Michael J; Mesoudi, Alex

2012-08-13

Social learning (learning from others) is evolutionarily adaptive under a wide range of conditions and is a long-standing area of interest across the social and biological sciences. One social-learning mechanism derived from cultural evolutionary theory is prestige bias, which allows a learner in a novel environment to quickly and inexpensively gather information as to the potentially best teachers, thus maximizing his or her chances of acquiring adaptive behavior. Learners provide deference to high-status individuals in order to ingratiate themselves with, and gain extended exposure to, that individual. We examined prestige-biased social transmission in a laboratory experiment in which participants designed arrowheads and attempted to maximize hunting success, measured in caloric return. Our main findings are that (1) participants preferentially learned from prestigious models (defined as those models at whom others spent longer times looking), and (2) prestige information and success-related information were used to the same degree, even though the former was less useful in this experiment than the latter. We also found that (3) participants were most likely to use social learning over individual (asocial) learning when they were performing poorly, in line with previous experiments, and (4) prestige information was not used more often following environmental shifts, contrary to predictions.  These results support previous discussions of the key role that prestige-biased transmission plays in social learning.

Development of Adaptive Kanji Learning System for Mobile Phone

ERIC Educational Resources Information Center

Li, Mengmeng; Ogata, Hiroaki; Hou, Bin; Hashimoto, Satoshi; Liu, Yuqin; Uosaki, Noriko; Yano, Yoneo

2010-01-01

This paper describes an adaptive learning system based on mobile phone email to support the study of Japanese Kanji. In this study, the main emphasis is on using the adaptive learning to resolve one common problem of the mobile-based email or SMS language learning systems. To achieve this goal, the authors main efforts focus on three aspects:…

Performance & Emotion--A Study on Adaptive E-Learning Based on Visual/Verbal Learning Styles

ERIC Educational Resources Information Center

Beckmann, Jennifer; Bertel, Sven; Zander, Steffi

2015-01-01

Adaptive e-Learning systems are able to adjust to a user's learning needs, usually by user modeling or tracking progress. Such learner-adaptive behavior has rapidly become a hot topic for e-Learning, furthered in part by the recent rapid increase in the use of MOOCs (Massive Open Online Courses). A lack of general, individual, and situational data…

Using Data to Understand How to Better Design Adaptive Learning

ERIC Educational Resources Information Center

Liu, Min; Kang, Jina; Zou, Wenting; Lee, Hyeyeon; Pan, Zilong; Corliss, Stephanie

2017-01-01

There is much enthusiasm in higher education about the benefits of adaptive learning and using big data to investigate learning processes to make data-informed educational decisions. The benefits of adaptive learning to achieve personalized learning are obvious. Yet, there lacks evidence-based research to understand how data such as user behavior…

Group Modeling in Social Learning Environments

ERIC Educational Resources Information Center

Stankov, Slavomir; Glavinic, Vlado; Krpan, Divna

2012-01-01

Students' collaboration while learning could provide better learning environments. Collaboration assumes social interactions which occur in student groups. Social theories emphasize positive influence of such interactions on learning. In order to create an appropriate learning environment that enables social interactions, it is important to…

Scaffolding and Integrated Assessment in Computer Assisted Learning (CAL) for Children with Learning Disabilities

ERIC Educational Resources Information Center

Beale, Ivan L.

2005-01-01

Computer assisted learning (CAL) can involve a computerised intelligent learning environment, defined as an environment capable of automatically, dynamically and continuously adapting to the learning context. One aspect of this adaptive capability involves automatic adjustment of instructional procedures in response to each learner's performance,…

Adaptation and transformation through (un)learning: lived experiences of immigrant Chinese nurses in US healthcare environment.

PubMed

Xu, Yu; Gutierrez, Antonio; Kim, Su Hyun

2008-01-01

This phenomenological study examined the lived experiences of Chinese nurses working in the US healthcare environment. In-depth interviews with 9 self-identified Chinese nurses were conducted in English and transcribed verbatim. Using Colaizzi's (In: Valle RS, King M, eds. Existential-Phenomenological Alternatives for Psychology. New York: Oxford University Press; 1978:48-71) 7-step procedure, the narrative data were independently analyzed by a team of researchers. Five primary themes emerged from the data: (a) communication as the most daunting challenge, especially during initial transition of their first job; (b) different and even conflicting professional values and roles/expectations of the nurse between the United States and China; (c) marginalization, inequality, and discrimination; (d) transformation through clinging to hope, (un)learning, and resilience; and (e) cultural dissonance. To a large extent, this study supported the findings in the general literature on international nurses, especially those from Asia. It also documented the uniqueness of this group of Chinese nurses, namely their ingenuity to turn challenges into opportunities, their high-level job satisfaction in spite of adversity, their desire for learning and execution of strategic plans for performance and career enhancement through further education, and their proactive measures to adapt to workplace demands. In addition, this study revealed both real and potential risks to patient safety and quality of care during the transition of these Chinese nurses. In light of these findings, implications for both practice and future research are elaborated, particularly in the context of the accreditation standards of healthcare organizations and national agenda for patient safety research.

Adaptivity in Game-Based Learning: A New Perspective on Story

NASA Astrophysics Data System (ADS)

Berger, Florian; Müller, Wolfgang

Game-based learning as a novel form of e-learning still has issues in fundamental questions, the lack of a general model for adaptivity being one of them. Since adaptive techniques in traditional e-learning applications bear close similarity to certain interactive storytelling approaches, we propose a new notion of story as the joining element of arbitraty learning paths.

Effects of repeated walking in a perturbing environment: a 4-day locomotor learning study.

PubMed

Blanchette, Andreanne; Moffet, Helene; Roy, Jean-Sébastien; Bouyer, Laurent J

2012-07-01

Previous studies have shown that when subjects repeatedly walk in a perturbing environment, initial movement error becomes smaller, suggesting that retention of the adapted locomotor program occurred (learning). It has been proposed that the newly learned locomotor program may be stored separately from the baseline program. However, how locomotor performance evolves with repeated sessions of walking with the perturbation is not yet known. To address this question, 10 healthy subjects walked on a treadmill on 4 consecutive days. Each day, locomotor performance was measured using kinematics and surface electromyography (EMGs), before, during, and after exposure to a perturbation, produced by an elastic tubing that pulled the foot forward and up during swing, inducing a foot velocity error in the first strides. Initial movement error decreased significantly between days 1 and 2 and then remained stable. Associated changes in medial hamstring EMG activity stabilized only on day 3, however. Aftereffects were present after perturbation removal, suggesting that daily adaptation involved central command recalibration of the baseline program. Aftereffects gradually decreased across days but were still visible on day 4. Separation between the newly learned and baseline programs may take longer than suggested by the daily improvement in initial performance in the perturbing environment or may never be complete. These results therefore suggest that reaching optimal performance in a perturbing environment should not be used as the main indicator of a completed learning process, as central reorganization of the motor commands continues days after initial performance has stabilized.

Effects of Matching Teaching Strategy to Thinking Style on Learner's Quality of Reflection in an Online Learning Environment

ERIC Educational Resources Information Center

Chen, Nian-Shing; Kinshuk; Wei, Chun-Wang; Liu, Chia-Chi

2011-01-01

Reflection plays an important role in improving learning performance. This study, therefore, attempted to explore whether learners' reflection levels can be improved if teaching strategies are adapted to fit with learners' thinking styles in an online learning environment. Three teaching strategies, namely constructive, guiding, and inductive,…

Adaptive Social Learning Based on Crowdsourcing

ERIC Educational Resources Information Center

Karataev, Evgeny; Zadorozhny, Vladimir

2017-01-01

Many techniques have been developed to enhance learning experience with computer technology. A particularly great influence of technology on learning came with the emergence of the web and adaptive educational hypermedia systems. While the web enables users to interact and collaborate with each other to create, organize, and share knowledge via…

Information-educational environment with adaptive control of learning process

NASA Astrophysics Data System (ADS)

Modjaev, A. D.; Leonova, N. M.

2017-01-01

Recent years, a new scientific branch connected with the activities in social sphere management developing intensively and it is called "Social Cybernetics". In the framework of this scientific branch, theory and methods of management of social sphere are formed. Considerable attention is paid to the management, directly in real time. However, the decision of such management tasks is largely constrained by the lack of or insufficiently deep study of the relevant sections of the theory and methods of management. The article discusses the use of cybernetic principles in solving problems of control in social systems. Applying to educational activities a model of composite interrelated objects representing the behaviour of students at various stages of educational process is introduced. Statistical processing of experimental data obtained during the actual learning process is being done. If you increase the number of features used, additionally taking into account the degree and nature of variability of levels of current progress of students during various types of studies, new properties of students' grouping are discovered. L-clusters were identified, reflecting the behaviour of learners with similar characteristics during lectures. It was established that the characteristics of the clusters contain information about the dynamics of learners' behaviour, allowing them to be used in additional lessons. The ways of solving the problem of adaptive control based on the identified dynamic characteristics of the learners are planned.

Higher rates of sex evolve during adaptation to more complex environments

PubMed Central

Luijckx, Pepijn; Ho, Eddie Ka Ho; Gasim, Majid; Chen, Suyang; Stanic, Andrijana; Yanchus, Connor; Kim, Yun Seong; Agrawal, Aneil F.

2017-01-01

A leading hypothesis for the evolutionary maintenance of sexual reproduction proposes that sex is advantageous because it facilitates adaptation. Changes in the environment stimulate adaptation but not all changes are equivalent; a change may occur along one or multiple environmental dimensions. In two evolution experiments with the facultatively sexual rotifer Brachionus calyciflorus, we test how environmental complexity affects the evolution of sex by adapting replicate populations to various environments that differ from the original along one, two, or three environmental dimensions. Three different estimates of fitness (growth, lifetime reproduction, and population density) confirmed that populations adapted to their new environment. Growth measures revealed an intriguing cost of complex adaptations: populations that adapted to more complex environments lost greater amounts of fitness in the original environment. Furthermore, both experiments showed that B. calyciflorus became more sexual when adapting to a greater number of environmental dimensions. Common garden experiments confirmed that observed changes in sex were heritable. As environments in nature are inherently complex these findings help explain why sex is maintained in natural populations. PMID:28053226

Higher rates of sex evolve during adaptation to more complex environments.

PubMed

Luijckx, Pepijn; Ho, Eddie Ka Ho; Gasim, Majid; Chen, Suyang; Stanic, Andrijana; Yanchus, Connor; Kim, Yun Seong; Agrawal, Aneil F

2017-01-17

A leading hypothesis for the evolutionary maintenance of sexual reproduction proposes that sex is advantageous because it facilitates adaptation. Changes in the environment stimulate adaptation but not all changes are equivalent; a change may occur along one or multiple environmental dimensions. In two evolution experiments with the facultatively sexual rotifer Brachionus calyciflorus, we test how environmental complexity affects the evolution of sex by adapting replicate populations to various environments that differ from the original along one, two, or three environmental dimensions. Three different estimates of fitness (growth, lifetime reproduction, and population density) confirmed that populations adapted to their new environment. Growth measures revealed an intriguing cost of complex adaptations: populations that adapted to more complex environments lost greater amounts of fitness in the original environment. Furthermore, both experiments showed that B. calyciflorus became more sexual when adapting to a greater number of environmental dimensions. Common garden experiments confirmed that observed changes in sex were heritable. As environments in nature are inherently complex these findings help explain why sex is maintained in natural populations.

The Learning Environment.

ERIC Educational Resources Information Center

American Electric Power System, New York, NY.

The basic factors in personal comfort, the nature of the processes of teaching and learning, and the effects of environment on these functions are discussed. The role of climate conditioning and space conditioning as interpreted by sensory factors during the learning process gives guidelines for design solutions. Technical supplements on climate…

Nursing students' perceptions of factors influencing their learning environment in a clinical skills laboratory: A qualitative study.

PubMed

Haraldseid, Cecilie; Friberg, Febe; Aase, Karina

2015-09-01

The mastery of clinical skills learning is required to become a trained nurse. Due to limited opportunities for clinical skills training in clinical practice, undergraduate training at clinical skills laboratories (CSLs) is an essential part of nursing education. In a sociocultural learning perspective learning is situated in an environment. Growing student cohorts, rapid introduction of technology-based teaching methods and a shift from a teaching- to a learning-centered education all influence the environment of the students. These changes also affect CSLs and therefore compel nursing faculties to adapt to the changing learning environment. This study aimed to explore students' perceptions of their learning environment in a clinical skills laboratory, and to increase the knowledge base for improving CSL learning conditions identifying the most important environmental factors according to the students. An exploratory qualitative methodology was used. Nineteen second-year students enrolled in an undergraduate nursing program in Norway participated in the study. They took the same clinical skills course. Eight were part-time students (group A) and 11 were full-time students (group B). Focus group interviews and content analysis were conducted to capture the students' perception of the CSL learning environment. The study documents students' experience of the physical (facilities, material equipment, learning tools, standard procedures), psychosocial (expectations, feedback, relations) and organizational (faculty resources, course structure) factors that affect the CSL learning environment. Creating an authentic environment, facilitating motivation, and providing resources for multiple methods and repetitions within clinical skills training are all important for improving CSL learning environments from the student perspective. Copyright © 2015 Elsevier Ltd. All rights reserved.

An adaptive deep Q-learning strategy for handwritten digit recognition.

PubMed

Qiao, Junfei; Wang, Gongming; Li, Wenjing; Chen, Min

2018-02-22

Handwritten digits recognition is a challenging problem in recent years. Although many deep learning-based classification algorithms are studied for handwritten digits recognition, the recognition accuracy and running time still need to be further improved. In this paper, an adaptive deep Q-learning strategy is proposed to improve accuracy and shorten running time for handwritten digit recognition. The adaptive deep Q-learning strategy combines the feature-extracting capability of deep learning and the decision-making of reinforcement learning to form an adaptive Q-learning deep belief network (Q-ADBN). First, Q-ADBN extracts the features of original images using an adaptive deep auto-encoder (ADAE), and the extracted features are considered as the current states of Q-learning algorithm. Second, Q-ADBN receives Q-function (reward signal) during recognition of the current states, and the final handwritten digits recognition is implemented by maximizing the Q-function using Q-learning algorithm. Finally, experimental results from the well-known MNIST dataset show that the proposed Q-ADBN has a superiority to other similar methods in terms of accuracy and running time. Copyright © 2018 Elsevier Ltd. All rights reserved.

Exposure to Stressful Environments: Strategy of Adaptive Responses

NASA Technical Reports Server (NTRS)

Farhi, Leon E.

1991-01-01

Any new natural environment may generate a number of stresses (such as hypoxia, water lack, and heat exposure), each of which can produce strains in more than a single organ system. Every strain may in turn stimulate the body to adapt in multiple ways. Nevertheless, a general strategy of the various adaptive responses emerges when the challenges are divided into three groups. The first category includes conditions that affect the supply of essential molecules, while the second is made up by those stresses that prevent the body from regulating properly the output of waste products, such as CO2 and heat. In both classes, there is a small number of responses, similar in principle, regardless of the specific situation. The third unit is created by environments that disrupt body transport systems. Problems may arise when there is a conflict between two stresses requiring conflicting adaptive changes. An alternative to adaptation, creation of micro-environment, is often favored by the animal.

Learning gait of quadruped robot without prior knowledge of the environment

NASA Astrophysics Data System (ADS)

Xu, Tao; Chen, Qijun

2012-09-01

Walking is the basic skill of a legged robot, and one of the promising ways to improve the walking performance and its adaptation to environment changes is to let the robot learn its walking by itself. Currently, most of the walking learning methods are based on robot vision system or some external sensing equipment to estimate the walking performance of certain walking parameters, and therefore are usually only applicable under laboratory condition, where environment can be pre-defined. Inspired by the rhythmic swing movement during walking of legged animals and the behavior of their adjusting their walking gait on different walking surfaces, a concept of walking rhythmic pattern(WRP) is proposed to evaluate the walking specialty of legged robot, which is just based on the walking dynamics of the robot. Based on the onboard acceleration sensor data, a method to calculate WRP using power spectrum in frequency domain and diverse smooth filters is also presented. Since the evaluation of WRP is only based on the walking dynamics data of the robot's body, the proposed method doesn't require prior knowledge of environment and thus can be applied in unknown environment. A gait learning approach of legged robots based on WRP and evolution algorithm(EA) is introduced. By using the proposed approach, a quadruped robot can learn its locomotion by its onboard sensing in an unknown environment, where the robot has no prior knowledge about this place. The experimental result proves proportional relationship exits between WRP match score and walking performance of legged robot, which can be used to evaluate the walking performance in walking optimization under unknown environment.

A Blended Mobile Learning Environment for Museum Learning

ERIC Educational Resources Information Center

Hou, Huei-Tse; Wu, Sheng-Yi; Lin, Peng-Chun; Sung, Yao-Ting; Lin, Jhe-Wei; Chang, Kuo-En

2014-01-01

The use of mobile devices for informal learning has gained attention over recent years. Museum learning is also regarded as an important research topic in the field of informal learning. This study explored a blended mobile museum learning environment (BMMLE). Moreover, this study applied three blended museum learning modes: (a) the traditional…

Implementing Process-Oriented, Guided-Inquiry Learning for the First Time: Adaptations and Short-Term Impacts on Students' Attitude and Performance

ERIC Educational Resources Information Center

Chase, Anthony; Pakhira, Deblina; Stains, Marilyne

2013-01-01

Innovative, research-based instructional practices are critical to transforming the conventional undergraduate instructional landscape into a student-centered learning environment. Research on dissemination of innovation indicates that instructors often adapt rather than adopt these practices. These adaptations can lead to the loss of critical…

Ready or Not: Microbial Adaptive Responses in Dynamic Symbiosis Environments.

PubMed

Cao, Mengyi; Goodrich-Blair, Heidi

2017-08-01

In mutually beneficial and pathogenic symbiotic associations, microbes must adapt to the host environment for optimal fitness. Both within an individual host and during transmission between hosts, microbes are exposed to temporal and spatial variation in environmental conditions. The phenomenon of phenotypic variation, in which different subpopulations of cells express distinctive and potentially adaptive characteristics, can contribute to microbial adaptation to a lifestyle that includes rapidly changing environments. The environments experienced by a symbiotic microbe during its life history can be erratic or predictable, and each can impact the evolution of adaptive responses. In particular, the predictability of a rhythmic or cyclical series of environments may promote the evolution of signal transduction cascades that allow preadaptive responses to environments that are likely to be encountered in the future, a phenomenon known as adaptive prediction. In this review, we summarize environmental variations known to occur in some well-studied models of symbiosis and how these may contribute to the evolution of microbial population heterogeneity and anticipatory behavior. We provide details about the symbiosis between Xenorhabdus bacteria and Steinernema nematodes as a model to investigate the concept of environmental adaptation and adaptive prediction in a microbial symbiosis. Copyright © 2017 American Society for Microbiology.

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

ERIC Educational Resources Information Center

Huerta-Wong, Juan Enrique; Schoech, Richard

2010-01-01

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

Effectiveness of Adaptive E-Learning Environments on Knowledge, Competence, and Behavior in Health Professionals and Students: Protocol for a Systematic Review and Meta-Analysis

PubMed Central

Cossette, Sylvie; Maheu-Cadotte, Marc-André; Mailhot, Tanya; Deschênes, Marie-France; Mathieu-Dupuis, Gabrielle

2017-01-01

Background Adaptive e-learning environments (AEEs) can provide tailored instruction by adapting content, navigation, presentation, multimedia, and tools to each user’s navigation behavior, individual objectives, knowledge, and preferences. AEEs can have various levels of complexity, ranging from systems using a simple adaptive functionality to systems using artificial intelligence. While AEEs are promising, their effectiveness for the education of health professionals and health professions students remains unclear. Objective The purpose of this systematic review is to assess the effectiveness of AEEs in improving knowledge, competence, and behavior in health professionals and students. Methods We will follow the Cochrane Collaboration and the Effective Practice and Organisation of Care (EPOC) Group guidelines on systematic review methodology. A systematic search of the literature will be conducted in 6 bibliographic databases (CINAHL, EMBASE, ERIC, PsycINFO, PubMed, and Web of Science) using the concepts “adaptive e-learning environments,” “health professionals/students,” and “effects on knowledge/skills/behavior.” We will include randomized and nonrandomized controlled trials, in addition to controlled before-after, interrupted time series, and repeated measures studies published between 2005 and 2017. The title and the abstract of each study followed by a full-text assessment of potentially eligible studies will be independently screened by 2 review authors. Using the EPOC extraction form, 1 review author will conduct data extraction and a second author will validate the data extraction. The methodological quality of included studies will be independently assessed by 2 review authors using the EPOC risk of bias criteria. Included studies will be synthesized by a descriptive analysis. Where appropriate, data will be pooled using meta-analysis by applying the RevMan software version 5.1, considering the heterogeneity of studies. Results The review is

How Language Supports Adaptive Teaching through a Responsive Learning Culture

ERIC Educational Resources Information Center

Johnston, Peter; Dozier, Cheryl; Smit, Julie

2016-01-01

For students to learn optimally, teachers must design classrooms that are responsive to the full range of student development. The teacher must be adaptive, but so must each student and the learning culture itself. In other words, adaptive teaching means constructing a responsive learning culture that accommodates and even capitalizes on diversity…

The Binding of Learning to Action in Motor Adaptation

PubMed Central

Gonzalez Castro, Luis Nicolas; Monsen, Craig Bryant; Smith, Maurice A.

2011-01-01

In motor tasks, errors between planned and actual movements generally result in adaptive changes which reduce the occurrence of similar errors in the future. It has commonly been assumed that the motor adaptation arising from an error occurring on a particular movement is specifically associated with the motion that was planned. Here we show that this is not the case. Instead, we demonstrate the binding of the adaptation arising from an error on a particular trial to the motion experienced on that same trial. The formation of this association means that future movements planned to resemble the motion experienced on a given trial benefit maximally from the adaptation arising from it. This reflects the idea that actual rather than planned motions are assigned ‘credit’ for motor errors because, in a computational sense, the maximal adaptive response would be associated with the condition credited with the error. We studied this process by examining the patterns of generalization associated with motor adaptation to novel dynamic environments during reaching arm movements in humans. We found that these patterns consistently matched those predicted by adaptation associated with the actual rather than the planned motion, with maximal generalization observed where actual motions were clustered. We followed up these findings by showing that a novel training procedure designed to leverage this newfound understanding of the binding of learning to action, can improve adaptation rates by greater than 50%. Our results provide a mechanistic framework for understanding the effects of partial assistance and error augmentation during neurologic rehabilitation, and they suggest ways to optimize their use. PMID:21731476

Blended Learning in Personalized Assistive Learning Environments

ERIC Educational Resources Information Center

Marinagi, Catherine; Skourlas, Christos

2013-01-01

In this paper, the special needs/requirements of disabled students and cost-benefits for applying blended learning in Personalized Educational Learning Environments (PELE) in Higher Education are studied. The authors describe how blended learning can form an attractive and helpful framework for assisting Deaf and Hard-of-Hearing (D-HH) students to…

Learning environment, learning styles and conceptual understanding

NASA Astrophysics Data System (ADS)

Ferrer, Lourdes M.

1990-01-01

In recent years there have been many studies on learners developing conceptions of natural phenomena. However, so far there have been few attempts to investigate how the characteristics of the learners and their environment influence such conceptions. This study began with an attempt to use an instrument developed by McCarthy (1981) to describe learners in Malaysian primary schools. This proved inappropriate as Asian primary classrooms do not provide the same kind of environment as US classrooms. It was decided to develop a learning style checklist to suit the local context and which could be used to describe differences between learners which teachers could appreciate and use. The checklist included four dimensions — perceptual, process, self-confidence and motivation. The validated instrument was used to determine the learning style preferences of primary four pupils in Penang, Malaysia. Later, an analysis was made regarding the influence of learning environment and learning styles on conceptual understanding in the topics of food, respiration and excretion. This study was replicated in the Philippines with the purpose of investigating the relationship between learning styles and achievement in science, where the topics of food, respiration and excretion have been taken up. A number of significant relationships were observed in these two studies.

The Study and Design of Adaptive Learning System Based on Fuzzy Set Theory

NASA Astrophysics Data System (ADS)

Jia, Bing; Zhong, Shaochun; Zheng, Tianyang; Liu, Zhiyong

Adaptive learning is an effective way to improve the learning outcomes, that is, the selection of learning content and presentation should be adapted to each learner's learning context, learning levels and learning ability. Adaptive Learning System (ALS) can provide effective support for adaptive learning. This paper proposes a new ALS based on fuzzy set theory. It can effectively estimate the learner's knowledge level by test according to learner's target. Then take the factors of learner's cognitive ability and preference into consideration to achieve self-organization and push plan of knowledge. This paper focuses on the design and implementation of domain model and user model in ALS. Experiments confirmed that the system providing adaptive content can effectively help learners to memory the content and improve their comprehension.

Distributing vs. Blocking Learning Questions in a Web-Based Learning Environment

ERIC Educational Resources Information Center

Kapp, Felix; Proske, Antje; Narciss, Susanne; Körndle, Hermann

2015-01-01

Effective studying in web-based learning environments (web-LEs) requires cognitive engagement and demands learners to regulate their learning activities. One way to support learners in web-LEs is to provide interactive learning questions within the learning environment. Even though research on learning questions has a long tradition, there are…

Learning with Collaborative Inquiry: A Science Learning Environment for Secondary Students

ERIC Educational Resources Information Center

Sun, Daner; Looi, Chee-Kit; Xie, Wenting

2017-01-01

When inquiry-based learning is designed for a collaborative context, the interactions that arise in the learning environment can become fairly complex. While the learning effectiveness of such learning environments has been reported in the literature, there have been fewer studies on the students' learning processes. To address this, the article…

Adaptive functioning in children with epilepsy and learning problems.

PubMed

Buelow, Janice M; Perkins, Susan M; Johnson, Cynthia S; Byars, Anna W; Fastenau, Philip S; Dunn, David W; Austin, Joan K

2012-10-01

In the study we describe adaptive functioning in children with epilepsy whose primary caregivers identified them as having learning problems. This was a cross-sectional study of 50 children with epilepsy and learning problems. Caregivers supplied information regarding the child's adaptive functioning and behavior problems. Children rated their self-concept and completed a battery of neuropsychological tests. Mean estimated IQ (PPVT-III) in the participant children was 72.8 (SD = 18.3). On average, children scored 2 standard deviations below the norm on the Vineland Adaptive Behavior Scale-II and this was true even for children with epilepsy who had estimated IQ in the normal range. In conclusion, children with epilepsy and learning problems had relatively low adaptive functioning scores and substantial neuropsychological and mental health problems. In epilepsy, adaptive behavior screening can be very informative and guide further evaluation and intervention, even in those children whose IQ is in the normal range.

Individualization of Foreign Language Teaching through Adaptive eLearning

ERIC Educational Resources Information Center

Kostolanyova, Katerina; Nedbalova, Stepanka

2017-01-01

Lifelong learning has become an essential part of each profession. For this reason, personalized and adaptive learning has been drawing attention of professionals in the field of formal as well as informal education in the last few years. The effort has been made to design adaptive study supports regarding students' requirements, abilities and…

Learning Environment and Student Effort

ERIC Educational Resources Information Center

Hopland, Arnt O.; Nyhus, Ole Henning

2016-01-01

Purpose: The purpose of this paper is to explore the relationship between satisfaction with learning environment and student effort, both in class and with homework assignments. Design/methodology/approach: The authors use data from a nationwide and compulsory survey to analyze the relationship between learning environment and student effort. The…

Hypermedia in Vocational Learning: A Hypermedia Learning Environment for Training Management Skills

ERIC Educational Resources Information Center

Konradt, Udo

2004-01-01

A learning environment is defined as an arrangement of issues, methods, techniques, and media in a given domain. Besides temporal and spatial features a learning environment considers the social situation in which learning takes place. In (hypermedia) learning environments the concept of exploration and the active role of the learner is…

Social influences on adaptive criterion learning.

PubMed

Cassidy, Brittany S; Dubé, Chad; Gutchess, Angela H

2015-07-01

People adaptively shift decision criteria when given biased feedback encouraging specific types of errors. Given that work on this topic has been conducted in nonsocial contexts, we extended the literature by examining adaptive criterion learning in both social and nonsocial contexts. Specifically, we compared potential differences in criterion shifting given performance feedback from social sources varying in reliability and from a nonsocial source. Participants became lax when given false positive feedback for false alarms, and became conservative when given false positive feedback for misses, replicating prior work. In terms of a social influence on adaptive criterion learning, people became more lax in response style over time if feedback was provided by a nonsocial source or by a social source meant to be perceived as unreliable and low-achieving. In contrast, people adopted a more conservative response style over time if performance feedback came from a high-achieving and reliable source. Awareness that a reliable and high-achieving person had not provided their feedback reduced the tendency to become more conservative, relative to those unaware of the source manipulation. Because teaching and learning often occur in a social context, these findings may have important implications for many scenarios in which people fine-tune their behaviors, given cues from others.

Profiling medical school learning environments in Malaysia: a validation study of the Johns Hopkins Learning Environment Scale.

PubMed

Tackett, Sean; Bakar, Hamidah Abu; Shilkofski, Nicole A; Coady, Niamh; Rampal, Krishna; Wright, Scott

2015-01-01

While a strong learning environment is critical to medical student education, the assessment of medical school learning environments has confounded researchers. Our goal was to assess the validity and utility of the Johns Hopkins Learning Environment Scale (JHLES) for preclinical students at three Malaysian medical schools with distinct educational and institutional models. Two schools were new international partnerships, and the third was school leaver program established without international partnership. First- and second-year students responded anonymously to surveys at the end of the academic year. The surveys included the JHLES, a 28-item survey using five-point Likert scale response options, the Dundee Ready Educational Environment Measure (DREEM), the most widely used method to assess learning environments internationally, a personal growth scale, and single-item global learning environment assessment variables. The overall response rate was 369/429 (86%). After adjusting for the medical school year, gender, and ethnicity of the respondents, the JHLES detected differences across institutions in four out of seven domains (57%), with each school having a unique domain profile. The DREEM detected differences in one out of five categories (20%). The JHLES was more strongly correlated than the DREEM to two thirds of the single-item variables and the personal growth scale. The JHLES showed high internal reliability for the total score (α=0.92) and the seven domains (α, 0.56-0.85). The JHLES detected variation between learning environment domains across three educational settings, thereby creating unique learning environment profiles. Interpretation of these profiles may allow schools to understand how they are currently supporting trainees and identify areas needing attention.

Profiling medical school learning environments in Malaysia: a validation study of the Johns Hopkins Learning Environment Scale

PubMed Central

Tackett, Sean; Bakar, Hamidah Abu; Shilkofski, Nicole A.; Coady, Niamh; Rampal, Krishna; Wright, Scott

2015-01-01

Purpose: While a strong learning environment is critical to medical student education, the assessment of medical school learning environments has confounded researchers. Our goal was to assess the validity and utility of the Johns Hopkins Learning Environment Scale (JHLES) for preclinical students at three Malaysian medical schools with distinct educational and institutional models. Two schools were new international partnerships, and the third was school leaver program established without international partnership. Methods: First- and second-year students responded anonymously to surveys at the end of the academic year. The surveys included the JHLES, a 28-item survey using five-point Likert scale response options, the Dundee Ready Educational Environment Measure (DREEM), the most widely used method to assess learning environments internationally, a personal growth scale, and single-item global learning environment assessment variables. Results: The overall response rate was 369/429 (86%). After adjusting for the medical school year, gender, and ethnicity of the respondents, the JHLES detected differences across institutions in four out of seven domains (57%), with each school having a unique domain profile. The DREEM detected differences in one out of five categories (20%). The JHLES was more strongly correlated than the DREEM to two thirds of the single-item variables and the personal growth scale. The JHLES showed high internal reliability for the total score (α=0.92) and the seven domains (α, 0.56-0.85). Conclusion: The JHLES detected variation between learning environment domains across three educational settings, thereby creating unique learning environment profiles. Interpretation of these profiles may allow schools to understand how they are currently supporting trainees and identify areas needing attention. PMID:26165949

An Adaptive E-Learning System Based on Students' Learning Styles: An Empirical Study

ERIC Educational Resources Information Center

Drissi, Samia; Amirat, Abdelkrim

2016-01-01

Personalized e-learning implementation is recognized as one of the most interesting research areas in the distance web-based education. Since the learning style of each learner is different one must fit e-learning with the different needs of learners. This paper presents an approach to integrate learning styles into adaptive e-learning hypermedia.…

Relationship between learning environment characteristics and academic engagement.

PubMed

Opdenakker, Marie-Christine; Minnaert, Alexander

2011-08-01

The relationship between learning environment characteristics and academic engagement of 777 Grade 6 children located in 41 learning environments was explored. Questionnaires were used to tap learning environment perceptions of children, their academic engagement, and their ethnic-cultural background. The basis of the learning environment questionnaire was the International System for Teacher Observation and Feedback (ISTOF). Factor analysis indicated three factors: the teacher as a helpful and good instructor (having good instructional skills, clear instruction), the teacher as promoter of active learning and differentiation, and the teacher as manager and organizer of classroom activities. Multilevel analysis indicated that about 12% of the differences in engagement between children was related to the learning environment. All the mentioned learning environment characteristics mattered, but the teacher as a helpful, good instructor was most important followed by the teacher as promoter of active learning and differentiation.

Organizational Adaptation: Managing in Complexly Changing Environments.

ERIC Educational Resources Information Center

Zammuto, Raymond F.

A model of strategic adaptation that focuses on how organizations adapt to both conditions of growth and decline is presented. The theoretical structure underlying the model is considered, with attention to organizations, niches, and environments, as well as environmental change and evolving niches. The model attempts to reconcile the perspectives…

Development of an Adaptive Learning System with Two Sources of Personalization Information

ERIC Educational Resources Information Center

Tseng, J. C. R.; Chu, H. C.; Hwang, G. J.; Tsai, C. C.

2008-01-01

Previous research of adaptive learning mainly focused on improving student learning achievements based only on single-source of personalization information, such as learning style, cognitive style or learning achievement. In this paper, an innovative adaptive learning approach is proposed by basing upon two main sources of personalization…

Perceptual Learning of Time-Compressed Speech: More than Rapid Adaptation

PubMed Central

Banai, Karen; Lavner, Yizhar

2012-01-01

Background Time-compressed speech, a form of rapidly presented speech, is harder to comprehend than natural speech, especially for non-native speakers. Although it is possible to adapt to time-compressed speech after a brief exposure, it is not known whether additional perceptual learning occurs with further practice. Here, we ask whether multiday training on time-compressed speech yields more learning than that observed during the initial adaptation phase and whether the pattern of generalization following successful learning is different than that observed with initial adaptation only. Methodology/Principal Findings Two groups of non-native Hebrew speakers were tested on five different conditions of time-compressed speech identification in two assessments conducted 10–14 days apart. Between those assessments, one group of listeners received five practice sessions on one of the time-compressed conditions. Between the two assessments, trained listeners improved significantly more than untrained listeners on the trained condition. Furthermore, the trained group generalized its learning to two untrained conditions in which different talkers presented the trained speech materials. In addition, when the performance of the non-native speakers was compared to that of a group of naïve native Hebrew speakers, performance of the trained group was equivalent to that of the native speakers on all conditions on which learning occurred, whereas performance of the untrained non-native listeners was substantially poorer. Conclusions/Significance Multiday training on time-compressed speech results in significantly more perceptual learning than brief adaptation. Compared to previous studies of adaptation, the training induced learning is more stimulus specific. Taken together, the perceptual learning of time-compressed speech appears to progress from an initial, rapid adaptation phase to a subsequent prolonged and more stimulus specific phase. These findings are consistent with

M-Learning: Implications in Learning Domain Specificities, Adaptive Learning, Feedback, Augmented Reality, and the Future of Online Learning

ERIC Educational Resources Information Center

Squires, David R.

2014-01-01

The aim of this paper is to examine the potential and effectiveness of m-learning in the field of Education and Learning domains. The purpose of this research is to illustrate how mobile technology can and is affecting novel change in instruction, from m-learning and the link to adaptive learning, to the uninitiated learner and capacities of…

Utilizing Virtual and Personal Learning Environments for Optimal Learning

ERIC Educational Resources Information Center

Terry, Krista, Ed.; Cheney, Amy, Ed.

2016-01-01

The integration of emerging technologies in higher education presents a new set of challenges and opportunities for educators. With a growing need for customized lesson plans in online education, educators are rethinking the design and development of their learning environments. "Utilizing Virtual and Personal Learning Environments for…

Dynamic adaptive learning for decision-making supporting systems

NASA Astrophysics Data System (ADS)

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

2008-03-01

This paper proposes a novel adaptive learning method for data mining in support of decision-making systems. Due to the inherent characteristics of information ambiguity/uncertainty, high dimensionality and noisy in many homeland security and defense applications, such as surveillances, monitoring, net-centric battlefield, and others, it is critical to develop autonomous learning methods to efficiently learn useful information from raw data to help the decision making process. The proposed method is based on a dynamic learning principle in the feature spaces. Generally speaking, conventional approaches of learning from high dimensional data sets include various feature extraction (principal component analysis, wavelet transform, and others) and feature selection (embedded approach, wrapper approach, filter approach, and others) methods. However, very limited understandings of adaptive learning from different feature spaces have been achieved. We propose an integrative approach that takes advantages of feature selection and hypothesis ensemble techniques to achieve our goal. Based on the training data distributions, a feature score function is used to provide a measurement of the importance of different features for learning purpose. Then multiple hypotheses are iteratively developed in different feature spaces according to their learning capabilities. Unlike the pre-set iteration steps in many of the existing ensemble learning approaches, such as adaptive boosting (AdaBoost) method, the iterative learning process will automatically stop when the intelligent system can not provide a better understanding than a random guess in that particular subset of feature spaces. Finally, a voting algorithm is used to combine all the decisions from different hypotheses to provide the final prediction results. Simulation analyses of the proposed method on classification of different US military aircraft databases show the effectiveness of this method.

Auditory-Perceptual Learning Improves Speech Motor Adaptation in Children

PubMed Central

Shiller, Douglas M.; Rochon, Marie-Lyne

2015-01-01

Auditory feedback plays an important role in children’s speech development by providing the child with information about speech outcomes that is used to learn and fine-tune speech motor plans. The use of auditory feedback in speech motor learning has been extensively studied in adults by examining oral motor responses to manipulations of auditory feedback during speech production. Children are also capable of adapting speech motor patterns to perceived changes in auditory feedback, however it is not known whether their capacity for motor learning is limited by immature auditory-perceptual abilities. Here, the link between speech perceptual ability and the capacity for motor learning was explored in two groups of 5–7-year-old children who underwent a period of auditory perceptual training followed by tests of speech motor adaptation to altered auditory feedback. One group received perceptual training on a speech acoustic property relevant to the motor task while a control group received perceptual training on an irrelevant speech contrast. Learned perceptual improvements led to an enhancement in speech motor adaptation (proportional to the perceptual change) only for the experimental group. The results indicate that children’s ability to perceive relevant speech acoustic properties has a direct influence on their capacity for sensory-based speech motor adaptation. PMID:24842067

Validation of the Clinical Learning Environment Inventory.

PubMed

Chan, Dominic S

2003-08-01

One hundred eight preregistration nursing students took part in this survey study, which assessed their perceptions of the clinical learning environment. Statistical data based on the sample confirmed the reliability and validity of the Clinical Learning Environment Inventory (CLEI), which was developed using the concept of classroom learning environment studies. The study also found that there were significant differences between students' actual and preferred perceptions of the clinical learning environments. In terms of the CLEI scales, students preferred a more positive and favorable clinical environment than they perceived as being actually present. The achievement of certain outcomes of clinical field placements might be enhanced by attempting to change the actual clinical environment in ways that make it more congruent with that preferred by the students.

A Model of Successful Adaptation to Online Learning for College-Bound Native American High School Students

ERIC Educational Resources Information Center

Kaler, Collier Butler

2012-01-01

Purpose: The purpose of this paper is to examine the conditions for Native American high school students that result in successful adaptation to an online learning environment. Design/methodology/approach: In total, eight Native American students attending high schools located on Montana Indian reservations, and one urban city, were interviewed.…

An Intelligent E-Learning System Based on Learner Profiling and Learning Resources Adaptation

ERIC Educational Resources Information Center

Tzouveli, Paraskevi; Mylonas, Phivos; Kollias, Stefanos

2008-01-01

Taking advantage of the continuously improving, web-based learning systems plays an important role for self-learning, especially in the case of working people. Nevertheless, learning systems do not generally adapt to learners' profiles. Learners have to spend a lot of time before reaching the learning goal that is compatible with their knowledge…

The Costa Rica GLOBE (Global Learning and Observations to Benefit the Environment) Project as a Learning Science Environment

NASA Astrophysics Data System (ADS)

Castro Rojas, María Dolores; Zuñiga, Ana Lourdes Acuña; Ugalde, Emmanuel Fonseca

2015-12-01

GLOBE is a global educational program for elementary and high school levels, and its main purpose in Costa Rica is to develop scientific thinking and interest for science in high school students through hydrology research projects that allow them to relate science with environmental issues in their communities. Youth between 12 and 17 years old from public schools participate in science clubs outside of their regular school schedule. A comparison study was performed between different groups, in order to assess GLOBE's applicability as a learning science atmosphere and the motivation and interest it generates in students toward science. Internationally applied scales were used as tools for measuring such indicators, adapted to the Costa Rican context. The results provide evidence statistically significant that the students perceive the GLOBE atmosphere as an enriched environment for science learning in comparison with the traditional science class. Moreover, students feel more confident, motivated and interested in science than their peers who do not participate in the project. However, the results were not statistically significant in this last respect.

Influences of Formal Learning, Personal Learning Orientation, and Supportive Learning Environment on Informal Learning

ERIC Educational Resources Information Center

Choi, Woojae; Jacobs, Ronald L.

2011-01-01

While workplace learning includes formal and informal learning, the relationship between the two has been overlooked, because they have been viewed as separate entities. This study investigated the effects of formal learning, personal learning orientation, and supportive learning environment on informal learning among 203 middle managers in Korean…

Associative memory for online learning in noisy environments using self-organizing incremental neural network.

PubMed

Sudo, Akihito; Sato, Akihiro; Hasegawa, Osamu

2009-06-01

Associative memory operating in a real environment must perform well in online incremental learning and be robust to noisy data because noisy associative patterns are presented sequentially in a real environment. We propose a novel associative memory that satisfies these requirements. Using the proposed method, new associative pairs that are presented sequentially can be learned accurately without forgetting previously learned patterns. The memory size of the proposed method increases adaptively with learning patterns. Therefore, it suffers neither redundancy nor insufficiency of memory size, even in an environment in which the maximum number of associative pairs to be presented is unknown before learning. Noisy inputs in real environments are classifiable into two types: noise-added original patterns and faultily presented random patterns. The proposed method deals with two types of noise. To our knowledge, no conventional associative memory addresses noise of both types. The proposed associative memory performs as a bidirectional one-to-many or many-to-one associative memory and deals not only with bipolar data, but also with real-valued data. Results demonstrate that the proposed method's features are important for application to an intelligent robot operating in a real environment. The originality of our work consists of two points: employing a growing self-organizing network for an associative memory, and discussing what features are necessary for an associative memory for an intelligent robot and proposing an associative memory that satisfies those requirements.

Fast adaptation of the internal model of gravity for manual interceptions: evidence for event-dependent learning.

PubMed

Zago, Myrka; Bosco, Gianfranco; Maffei, Vincenzo; Iosa, Marco; Ivanenko, Yuri P; Lacquaniti, Francesco

2005-02-01

We studied how subjects learn to deal with two conflicting sensory environments as a function of the probability of each environment and the temporal distance between repeated events. Subjects were asked to intercept a visual target moving downward on a screen with randomized laws of motion. We compared five protocols that differed in the probability of constant speed (0g) targets and accelerated (1g) targets. Probability ranged from 9 to 100%, and the time interval between consecutive repetitions of the same target ranged from about 1 to 20 min. We found that subjects systematically timed their responses consistent with the assumption of gravity effects, for both 1 and 0g trials. With training, subjects rapidly adapted to 0g targets by shifting the time of motor activation. Surprisingly, the adaptation rate was independent of both the probability of 0g targets and their temporal distance. Very few 0g trials sporadically interspersed as catch trials during immersive practice with 1g trials were sufficient for learning and consolidation in long-term memory, as verified by retesting after 24 h. We argue that the memory store for adapted states of the internal gravity model is triggered by individual events and can be sustained for prolonged periods of time separating sporadic repetitions. This form of event-related learning could depend on multiple-stage memory, with exponential rise and decay in the initial stages followed by a sample-and-hold module.

Genome-environment associations in sorghum landraces predict adaptive traits

USDA-ARS?s Scientific Manuscript database

Improving environmental adaptation in crops is essential for food security under global change, but phenotyping adaptive traits remains a major bottleneck. If associations between single-nucleotide polymorphism (SNP) alleles and environment of origin in crop landraces reflect adaptation, then these ...

Rule-based mechanisms of learning for intelligent adaptive flight control

NASA Technical Reports Server (NTRS)

Handelman, David A.; Stengel, Robert F.

1990-01-01

How certain aspects of human learning can be used to characterize learning in intelligent adaptive control systems is investigated. Reflexive and declarative memory and learning are described. It is shown that model-based systems-theoretic adaptive control methods exhibit attributes of reflexive learning, whereas the problem-solving capabilities of knowledge-based systems of artificial intelligence are naturally suited for implementing declarative learning. Issues related to learning in knowledge-based control systems are addressed, with particular attention given to rule-based systems. A mechanism for real-time rule-based knowledge acquisition is suggested, and utilization of this mechanism within the context of failure diagnosis for fault-tolerant flight control is demonstrated.

Web-Based Learning Environment Based on Students’ Needs

NASA Astrophysics Data System (ADS)

Hamzah, N.; Ariffin, A.; Hamid, H.

2017-08-01

Traditional learning needs to be improved since it does not involve active learning among students. Therefore, in the twenty-first century, the development of internet technology in the learning environment has become the main needs of each student. One of the learning environments to meet the needs of the teaching and learning process is a web-based learning environment. This study aims to identify the characteristics of a web-based learning environment that supports students’ learning needs. The study involved 542 students from fifteen faculties in a public higher education institution in Malaysia. A quantitative method was used to collect the data via a questionnaire survey by randomly. The findings indicate that the characteristics of a web-based learning environment that support students’ needs in the process of learning are online discussion forum, lecture notes, assignments, portfolio, and chat. In conclusion, the students overwhelmingly agreed that online discussion forum is the highest requirement because the tool can provide a space for students and teachers to share knowledge and experiences related to teaching and learning.

Learning in a u-Museum: Developing a Context-Aware Ubiquitous Learning Environment

ERIC Educational Resources Information Center

Chen, Chia-Chen; Huang, Tien-Chi

2012-01-01

Context-awareness techniques can support learners in learning without time or location constraints by using mobile devices and associated learning activities in a real learning environment. Enrichment of context-aware technologies has enabled students to learn in an environment that integrates learning resources from both the real world and the…

Development of an Adaptive Learning System with Multiple Perspectives based on Students' Learning Styles and Cognitive Styles

ERIC Educational Resources Information Center

Yang, Tzu-Chi; Hwang, Gwo-Jen; Yang, Stephen Jen-Hwa

2013-01-01

In this study, an adaptive learning system is developed by taking multiple dimensions of personalized features into account. A personalized presentation module is proposed for developing adaptive learning systems based on the field dependent/independent cognitive style model and the eight dimensions of Felder-Silverman's learning style. An…

PERSO: Towards an Adaptive e-Learning System

ERIC Educational Resources Information Center

Chorfi, Henda; Jemni, Mohamed

2004-01-01

In today's information technology society, members are increasingly required to be up to date on new technologies, particularly for computers, regardless of their background social situation. In this context, our aim is to design and develop an adaptive hypermedia e-learning system, called PERSO (PERSOnalizing e-learning system), where learners…

Adaptive Educational Software by Applying Reinforcement Learning

ERIC Educational Resources Information Center

Bennane, Abdellah

2013-01-01

The introduction of the intelligence in teaching software is the object of this paper. In software elaboration process, one uses some learning techniques in order to adapt the teaching software to characteristics of student. Generally, one uses the artificial intelligence techniques like reinforcement learning, Bayesian network in order to adapt…

A Learning Style Perspective to Investigate the Necessity of Developing Adaptive Learning Systems

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Sung, Han-Yu; Hung, Chun-Ming; Huang, Iwen

2013-01-01

Learning styles are considered to be one of the factors that need to be taken into account in developing adaptive learning systems. However, few studies have been conducted to investigate if students have the ability to choose the best-fit e-learning systems or content presentation styles for themselves in terms of learning style perspective. In…

Behavioural variation in 172 small-scale societies indicates that social learning is the main mode of human adaptation

PubMed Central

Mathew, Sarah; Perreault, Charles

2015-01-01

The behavioural variation among human societies is vast and unmatched in the animal world. It is unclear whether this variation is due to variation in the ecological environment or to differences in cultural traditions. Underlying this debate is a more fundamental question: is the richness of humans’ behavioural repertoire due to non-cultural mechanisms, such as causal reasoning, inventiveness, reaction norms, trial-and-error learning and evoked culture, or is it due to the population-level dynamics of cultural transmission? Here, we measure the relative contribution of environment and cultural history in explaining the behavioural variation of 172 Native American tribes at the time of European contact. We find that the effect of cultural history is typically larger than that of environment. Behaviours also persist over millennia within cultural lineages. This indicates that human behaviour is not predominantly determined by single-generation adaptive responses, contra theories that emphasize non-cultural mechanisms as determinants of human behaviour. Rather, the main mode of human adaptation is social learning mechanisms that operate over multiple generations. PMID:26085589

Interoperability in Personalized Adaptive Learning

ERIC Educational Resources Information Center

Aroyo, Lora; Dolog, Peter; Houben, Geert-Jan; Kravcik, Milos; Naeve, Ambjorn; Nilsson, Mikael; Wild, Fridolin

2006-01-01

Personalized adaptive learning requires semantic-based and context-aware systems to manage the Web knowledge efficiently as well as to achieve semantic interoperability between heterogeneous information resources and services. The technological and conceptual differences can be bridged either by means of standards or via approaches based on the…

The Influence of Learning Behaviour on Team Adaptability

ERIC Educational Resources Information Center

Murray, Peter A.; Millett, Bruce

2011-01-01

Multiple contexts shape team activities and how they learn, and group learning is a dynamic construct that reflects a repertoire of potential behaviour. The purpose of this developmental paper is to examine how better learning behaviours in semi-autonomous teams improves the level of team adaptability and performance. The discussion suggests that…

Adaptive Dialogue Systems for Assistive Living Environments

ERIC Educational Resources Information Center

Papangelis, Alexandros

2013-01-01

Adaptive Dialogue Systems (ADS) are intelligent systems, able to interact with users via multiple modalities, such as speech, gestures, facial expressions and others. Such systems are able to make conversation with their users, usually on a specific, narrow topic. Assistive Living Environments are environments where the users are by definition not…

A Simultaneous Mobile E-Learning Environment and Application

ERIC Educational Resources Information Center

Karal, Hasan; Bahcekapili, Ekrem; Yildiz, Adil

2010-01-01

The purpose of the present study was to design a mobile learning environment that enables the use of a teleconference application used in simultaneous e-learning with mobile devices and to evaluate this mobile learning environment based on students' views. With the mobile learning environment developed in the study, the students are able to follow…

Individual Differences in Adaptability to Isolated, Confined, and Extreme Environments.

PubMed

Bartone, Paul T; Krueger, Gerald P; Bartone, Jocelyn V

2018-06-01

Future deep space missions will expose astronauts to more intense stressors than previously encountered. Isolation will be greater and more prolonged, living and work areas more confined, and communications and resupply channels to Earth longer and less reliable. Astronauts will need to function more autonomously, with less guidance and support from Earth. Thus, it is important to select and train astronauts who can adapt and function effectively under extreme and variable conditions. In order to identify factors linked to individual adaptability, we conducted a systematic review of the literature on cognitive and behavioral adaptation to isolated, confined, and extreme (ICE) environments. We searched PubMed, Embase, Web of Science, and PsychINFO databases for studies addressing individual adaptability to ICE environments. Studies were rated for quality and fidelity to long-duration space missions and key results extracted. There were 73 studies that met all inclusion criteria. Adaptability attributes for ICE environments include intelligence, emotional stability, self-control, openness, achievement facets of conscientiousness, optimism, mastery, introversion, hardiness, task-oriented coping, past experience, low need for social support, and adequate sleep. This review identifies individual factors linked to adaptability under ICE conditions. Further studies are needed to verify causal directions and determine the relative importance of these factors.Bartone PT, Krueger GP, Bartone JV. Individual differences in adaptability to isolated, confined, and extreme environments. Aerosp Med Hum Perform. 2018; 89(6):536-546.

MADNESS: A Multiresolution, Adaptive Numerical Environment for Scientific Simulation

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

Harrison, Robert J.; Beylkin, Gregory; Bischoff, Florian A.

2016-01-01

MADNESS (multiresolution adaptive numerical environment for scientific simulation) is a high-level software environment for solving integral and differential equations in many dimensions that uses adaptive and fast harmonic analysis methods with guaranteed precision based on multiresolution analysis and separated representations. Underpinning the numerical capabilities is a powerful petascale parallel programming environment that aims to increase both programmer productivity and code scalability. This paper describes the features and capabilities of MADNESS and briefly discusses some current applications in chemistry and several areas of physics.

Teaching Energy Metabolism Using Scientific Articles: Implementation of a Virtual Learning Environment for Medical Students

ERIC Educational Resources Information Center

de Espindola, Marina Bazzo; El-Bacha, Tatiana; Giannella, Tais Rabetti; Struchiner, Miriam; da Silva, Wagner S.; Da Poian, Andrea T.

2010-01-01

This work describes the use of a virtual learning environment (VLE) applied to the biochemistry class for undergraduate, first-year medical students at the Federal University of Rio de Janeiro. The course focused on the integration of energy metabolism, exploring metabolic adaptations in different physiological or pathological states such as…

Consolidation of visuomotor adaptation memory with consistent and noisy environments

PubMed Central

Maeda, Rodrigo S.; McGee, Steven E.

2016-01-01

Our understanding of how we learn and retain motor behaviors is still limited. For instance, there is conflicting evidence as to whether the memory of a learned visuomotor perturbation consolidates; i.e., the motor memory becomes resistant to interference from learning a competing perturbation over time. Here, we sought to determine the factors that influence consolidation during visually guided walking. Subjects learned a novel mapping relationship, created by prism lenses, between the perceived location of two targets and the motor commands necessary to direct the feet to their positions. Subjects relearned this mapping 1 wk later. Different groups experienced protocols with or without a competing mapping (and with and without washout trials), presented either on the same day as initial learning or before relearning on day 2. We tested identical protocols under constant and noisy mapping structures. In the latter, we varied, on a trial-by-trial basis, the strength of prism lenses around a non-zero mean. We found that a novel visuomotor mapping is retained at least 1 wk after initial learning. We also found reduced foot-placement error with relearning in constant and noisy mapping groups, despite learning a competing mapping beforehand, and with the exception of one protocol, with and without washout trials. Exposure to noisy mappings led to similar performance on relearning compared with the equivalent constant mapping groups for most protocols. Overall, our results support the idea of motor memory consolidation during visually guided walking and suggest that constant and noisy practices are effective for motor learning. NEW & NOTEWORTHY The adaptation of movement is essential for many daily activities. To interact with targets, this often requires learning the mapping to produce appropriate motor commands based on visual input. Here, we show that a novel visuomotor mapping is retained 1 wk after initial learning in a visually guided walking task. Furthermore, we

Designing Adaptive Instructional Environments: Insights from Empirical Evidence

DTIC Science & Technology

2011-10-01

theorems. Cohen’s f effect size for pretest to posttest gain, averaged across different problems = 0.46. 7 Basis for Adaptation Ability of...problems and took a posttest . Measures of Learning 26-item multiple choice pretest and posttest . Effect size on posttest scores as measured by...solving algebraic equations. Measures of Learning Pretest and posttest using rapid diagnostic testing procedure: Student had to provide their

Factors Influencing Learning Environments in an Integrated Experiential Program

NASA Astrophysics Data System (ADS)

Koci, Peter

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

Recasting Transfer as a Socio-Personal Process of Adaptable Learning

ERIC Educational Resources Information Center

Billett, Stephen

2013-01-01

Transfer is usually cast as an educational, rather than learning, problem. Yet, seeking to adapt what individuals know from one circumstance to another is a process more helpfully associated with learning, than a hybrid one called transfer. Adaptability comprises individuals construing what they experience, then aligning and reconciling with what…

Co-Regulation of Learning in Computer-Supported Collaborative Learning Environments: A Discussion

ERIC Educational Resources Information Center

Chan, Carol K. K.

2012-01-01

This discussion paper for this special issue examines co-regulation of learning in computer-supported collaborative learning (CSCL) environments extending research on self-regulated learning in computer-based environments. The discussion employs a socio-cognitive perspective focusing on social and collective views of learning to examine how…

The VREST learning environment.

PubMed

Kunst, E E; Geelkerken, R H; Sanders, A J B

2005-01-01

The VREST learning environment is an integrated architecture to improve the education of health care professionals. It is a combination of a learning, content and assessment management system based on virtual reality. The generic architecture is now being build and tested around the Lichtenstein protocol for hernia inguinalis repair.

Pre-Service English Teachers in Blended Learning Environment in Respect to Their Learning Approaches

ERIC Educational Resources Information Center

Yilmaz, M. Betul; Orhan, Feza

2010-01-01

Blended learning environment (BLE) is increasingly used in the world, especially in university degrees and it is based on integrating web-based learning and face-to-face (FTF) learning environments. Besides integrating different learning environments, BLE also addresses to students with different learning approaches. The "learning…

Prediction of human adaptation and performance in underwater environments.

PubMed

Colodro Plaza, Joaquín; Garcés de los Fayos Ruiz, Enrique J; López García, Juan J; Colodro Conde, Lucía

2014-01-01

Environmental stressors require the professional diver to undergo a complex process of psychophysiological adaptation in order to overcome the demands of an extreme environment and carry out effective and efficient work under water. The influence of cognitive and personality traits in predicting underwater performance and adaptation has been a common concern for diving psychology, and definitive conclusions have not been reached. In this ex post facto study, psychological and academic data were analyzed from a large sample of personnel participating in scuba diving courses carried out in the Spanish Navy Diving Center. In order to verify the relevance of individual differences in adaptation to a hostile environment, we evaluated the predictive validity of general mental ability and personality traits with regression techniques. The data indicated the existence of psychological variables that can predict the performance ( R² = .30, p <.001) and adaptation ( R²(N) = .51, p <.001) of divers in underwater environment. These findings support the hypothesis that individual differences are related to the probability of successful adaptation and effective performance in professional diving. These results also verify that dispositional traits play a decisive role in diving training and are significant factors in divers' psychological fitness.

MADNESS: A Multiresolution, Adaptive Numerical Environment for Scientific Simulation

DOE PAGES

Harrison, Robert J.; Beylkin, Gregory; Bischoff, Florian A.; ...

2016-01-01

We present MADNESS (multiresolution adaptive numerical environment for scientific simulation) that is a high-level software environment for solving integral and differential equations in many dimensions that uses adaptive and fast harmonic analysis methods with guaranteed precision that are based on multiresolution analysis and separated representations. Underpinning the numerical capabilities is a powerful petascale parallel programming environment that aims to increase both programmer productivity and code scalability. This paper describes the features and capabilities of MADNESS and briefly discusses some current applications in chemistry and several areas of physics.

Different Futures of Adaptive Collaborative Learning Support

ERIC Educational Resources Information Center

Rummel, Nikol; Walker, Erin; Aleven, Vincent

2016-01-01

In this position paper we contrast a Dystopian view of the future of adaptive collaborative learning support (ACLS) with a Utopian scenario that--due to better-designed technology, grounded in research--avoids the pitfalls of the Dystopian version and paints a positive picture of the practice of computer-supported collaborative learning 25 years…

How People Learn in an Asynchronous Online Learning Environment: The Relationships between Graduate Students' Learning Strategies and Learning Satisfaction

ERIC Educational Resources Information Center

Choi, Beomkyu

2016-01-01

The purpose of this study was to examine the relationships between learners' learning strategies and learning satisfaction in an asynchronous online learning environment. In an attempt to shed some light on how people learn in an online learning environment, one hundred and sixteen graduate students who were taking online learning courses…

The Influence of the Teaching and Learning Environment on the Development of Generic Capabilities Needed for a Knowledge-Based Society

ERIC Educational Resources Information Center

Kember, David; Leung, Doris Y. P.

2005-01-01

The effect of the teaching and learning environment on the development of generic capabilities was examined through a survey of 1756 undergraduate students at a university in Hong Kong. The survey assessed students' perceptions of the development of the six capabilities of critical thinking, self-managed learning, adaptability, problem solving,…

Human Machine Learning Symbiosis

ERIC Educational Resources Information Center

Walsh, Kenneth R.; Hoque, Md Tamjidul; Williams, Kim H.

2017-01-01

Human Machine Learning Symbiosis is a cooperative system where both the human learner and the machine learner learn from each other to create an effective and efficient learning environment adapted to the needs of the human learner. Such a system can be used in online learning modules so that the modules adapt to each learner's learning state both…

Parameter learning for performance adaptation

NASA Technical Reports Server (NTRS)

Peek, Mark D.; Antsaklis, Panos J.

1990-01-01

A parameter learning method is introduced and used to broaden the region of operability of the adaptive control system of a flexible space antenna. The learning system guides the selection of control parameters in a process leading to optimal system performance. A grid search procedure is used to estimate an initial set of parameter values. The optimization search procedure uses a variation of the Hooke and Jeeves multidimensional search algorithm. The method is applicable to any system where performance depends on a number of adjustable parameters. A mathematical model is not necessary, as the learning system can be used whenever the performance can be measured via simulation or experiment. The results of two experiments, the transient regulation and the command following experiment, are presented.

Student-Teacher Interaction in Online Learning Environments

ERIC Educational Resources Information Center

Wright, Robert D., Ed.

2015-01-01

As face-to-face interaction between student and instructor is not present in online learning environments, it is increasingly important to understand how to establish and maintain social presence in online learning. "Student-Teacher Interaction in Online Learning Environments" provides successful strategies and procedures for developing…

A Well Designed School Environment Facilitates Brain Learning.

ERIC Educational Resources Information Center

Chan, Tak Cheung; Petrie, Garth

2000-01-01

Examines how school design facilitates learning by complementing how the brain learns. How the brain learns is discussed and how an artistic environment, spaciousness in the learning areas, color and lighting, and optimal thermal and acoustical environments aid student learning. School design suggestions conclude the article. (GR)

Environments for Development

ERIC Educational Resources Information Center

Grabinski, C. Joanne

2005-01-01

This chapter considers Robert Kegan's concept of holding environments, as well as six steps necessary for creation of new or adaptation of existing learning environments that facilitate adult development across the life course.

Clinical Environment as a Learning Environment: Student Nurses' Perceptions Concerning Clinical Learning Experiences.

ERIC Educational Resources Information Center

Papp, Inkeri; Markkanen, Marjatta; von Bonsdorff, Mikaela

2003-01-01

Finnish student nurses (n=16) described their clinical learning experiences. Several themes were identified: feeling appreciated and supported, the quality of mentoring and patient care, and self-directedness. School and clinical staff cooperation helped create a good learning environment in which theory and practice complemented each other.…

Adaptive categorization of ART networks in robot behavior learning using game-theoretic formulation.

PubMed

Fung, Wai-keung; Liu, Yun-hui

2003-12-01

Adaptive Resonance Theory (ART) networks are employed in robot behavior learning. Two of the difficulties in online robot behavior learning, namely, (1) exponential memory increases with time, (2) difficulty for operators to specify learning tasks accuracy and control learning attention before learning. In order to remedy the aforementioned difficulties, an adaptive categorization mechanism is introduced in ART networks for perceptual and action patterns categorization in this paper. A game-theoretic formulation of adaptive categorization for ART networks is proposed for vigilance parameter adaptation for category size control on the categories formed. The proposed vigilance parameter update rule can help improving categorization performance in the aspect of category number stability and solve the problem of selecting initial vigilance parameter prior to pattern categorization in traditional ART networks. Behavior learning using physical robot is conducted to demonstrate the effectiveness of the proposed adaptive categorization mechanism in ART networks.

CLEW: A Cooperative Learning Environment for the Web.

ERIC Educational Resources Information Center

Ribeiro, Marcelo Blois; Noya, Ricardo Choren; Fuks, Hugo

This paper outlines CLEW (collaborative learning environment for the Web). The project combines MUD (Multi-User Dimension), workflow, VRML (Virtual Reality Modeling Language) and educational concepts like constructivism in a learning environment where students actively participate in the learning process. The MUD shapes the environment structure.…

Virtual Representations in 3D Learning Environments

ERIC Educational Resources Information Center

Shonfeld, Miri; Kritz, Miki

2013-01-01

This research explores the extent to which virtual worlds can serve as online collaborative learning environments for students by increasing social presence and engagement. 3D environments enable learning, which simulates face-to-face encounters while retaining the advantages of online learning. Students in Education departments created avatars…

Creating Environments Conducive for Lifelong Learning

ERIC Educational Resources Information Center

Derrick, M. Gail

2003-01-01

A technological transformation during the past decade has eliminated the boundaries between formal and informal learning. As people adapt to a knowledge-driven society, a cultural transformation is occurring. Lifelong learning is an essential goal of education as a means to improve the quality of life for an individual, a culture, or a society.…

An Adaptive Web-Based Learning Environment for the Application of Remote Sensing in Schools

NASA Astrophysics Data System (ADS)

Wolf, N.; Fuchsgruber, V.; Riembauer, G.; Siegmund, A.

2016-06-01

Satellite images have great educational potential for teaching on environmental issues and can promote the motivation of young people to enter careers in natural science and technology. Due to the importance and ubiquity of remote sensing in science, industry and the public, the use of satellite imagery has been included into many school curricular in Germany. However, its implementation into school practice is still hesitant, mainly due to lack of teachers' know-how and education materials that align with the curricula. In the project "Space4Geography" a web-based learning platform is developed with the aim to facilitate the application of satellite imagery in secondary school teaching and to foster effective student learning experiences in geography and other related subjects in an interdisciplinary way. The platform features ten learning modules demonstrating the exemplary application of original high spatial resolution remote sensing data (RapidEye and TerraSAR-X) to examine current environmental issues such as droughts, deforestation and urban sprawl. In this way, students will be introduced into the versatile applications of spaceborne earth observation and geospatial technologies. The integrated web-based remote sensing software "BLIF" equips the students with a toolset to explore, process and analyze the satellite images, thereby fostering the competence of students to work on geographical and environmental questions without requiring prior knowledge of remote sensing. This contribution presents the educational concept of the learning environment and its realization by the example of the learning module "Deforestation of the rainforest in Brasil".

Learning Environments Designed According to Learning Styles and Its Effects on Mathematics Achievement

ERIC Educational Resources Information Center

Özerem, Aysen; Akkoyunlu, Buket

2015-01-01

Problem Statement: While designing a learning environment it is vital to think about learner characteristics (learning styles, approaches, motivation, interests… etc.) in order to promote effective learning. The learning environment and learning process should be designed not to enable students to learn in the same manner and at the same level,…

Importance of adaptation and genotype × environment interactions in tropical beef breeding systems.

PubMed

Burrow, H M

2012-05-01

This paper examines the relative importance of productive and adaptive traits in beef breeding systems based on Bos taurus and tropically adapted breeds across temperate and (sub)tropical environments. In the (sub)tropics, differences that exist between breeds in temperate environments are masked by the effects of environmental stressors. Hence in tropical environments, breeds are best categorised into breed types to compare their performance across environments. Because of the presence of environmental stressors, there are more sources of genetic variation in tropical breeding programmes. It is therefore necessary to examine the genetic basis of productive and adaptive traits for breeding programmes in those environments. This paper reviews the heritabilities and genetic relationships between economically important productive and adaptive traits relevant to (sub)tropical breeding programmes. It is concluded that it is possible to simultaneously genetically improve productive and adaptive traits in tropically adapted breeds of beef cattle grazed in tropical environments without serious detrimental consequences for either adaptation or production. However, breed-specific parameters are required for genetic evaluations. The paper also reviews the magnitude of genotype × environment (G × E) interactions impacting on production and adaptation of cattle, where 'genotype' is defined as breed (within a crossbreeding system), sire within breed (in a within-breed selection programme) or associations between economically important traits and single nucleotide polymorphisms (SNPs - within a marker-assisted selection programme). It is concluded that re-ranking of breeds across environments is best managed by the use of the breed type(s) best suited to the particular production environment. Re-ranking of sires across environments is apparent in poorly adapted breed types across extreme tropical and temperate environments or where breeding animals are selected in a temperate

Soft systems thinking and social learning for adaptive management.

PubMed

Cundill, G; Cumming, G S; Biggs, D; Fabricius, C

2012-02-01

The success of adaptive management in conservation has been questioned and the objective-based management paradigm on which it is based has been heavily criticized. Soft systems thinking and social-learning theory expose errors in the assumption that complex systems can be dispassionately managed by objective observers and highlight the fact that conservation is a social process in which objectives are contested and learning is context dependent. We used these insights to rethink adaptive management in a way that focuses on the social processes involved in management and decision making. Our approach to adaptive management is based on the following assumptions: action toward a common goal is an emergent property of complex social relationships; the introduction of new knowledge, alternative values, and new ways of understanding the world can become a stimulating force for learning, creativity, and change; learning is contextual and is fundamentally about practice; and defining the goal to be addressed is continuous and in principle never ends. We believe five key activities are crucial to defining the goal that is to be addressed in an adaptive-management context and to determining the objectives that are desirable and feasible to the participants: situate the problem in its social and ecological context; raise awareness about alternative views of a problem and encourage enquiry and deconstruction of frames of reference; undertake collaborative actions; and reflect on learning. ©2011 Society for Conservation Biology.

Genetic erosion impedes adaptive responses to stressful environments

PubMed Central

Bijlsma, R; Loeschcke, Volker

2012-01-01

Biodiversity is increasingly subjected to human-induced changes of the environment. To persist, populations continually have to adapt to these often stressful changes including pollution and climate change. Genetic erosion in small populations, owing to fragmentation of natural habitats, is expected to obstruct such adaptive responses: (i) genetic drift will cause a decrease in the level of adaptive genetic variation, thereby limiting evolutionary responses; (ii) inbreeding and the concomitant inbreeding depression will reduce individual fitness and, consequently, the tolerance of populations to environmental stress. Importantly, inbreeding generally increases the sensitivity of a population to stress, thereby increasing the amount of inbreeding depression. As adaptation to stress is most often accompanied by increased mortality (cost of selection), the increase in the ‘cost of inbreeding’ under stress is expected to severely hamper evolutionary adaptive processes. Inbreeding thus plays a pivotal role in this process and is expected to limit the probability of genetically eroded populations to successfully adapt to stressful environmental conditions. Consequently, the dynamics of small fragmented populations may differ considerably from large nonfragmented populations. The resilience of fragmented populations to changing and deteriorating environments is expected to be greatly decreased. Alleviating inbreeding depression, therefore, is crucial to ensure population persistence. PMID:25568035

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition.

PubMed

Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

2017-06-13

Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle).

Structure learning in action

PubMed Central

Braun, Daniel A.; Mehring, Carsten; Wolpert, Daniel M.

2010-01-01

‘Learning to learn’ phenomena have been widely investigated in cognition, perception and more recently also in action. During concept learning tasks, for example, it has been suggested that characteristic features are abstracted from a set of examples with the consequence that learning of similar tasks is facilitated—a process termed ‘learning to learn’. From a computational point of view such an extraction of invariants can be regarded as learning of an underlying structure. Here we review the evidence for structure learning as a ‘learning to learn’ mechanism, especially in sensorimotor control where the motor system has to adapt to variable environments. We review studies demonstrating that common features of variable environments are extracted during sensorimotor learning and exploited for efficient adaptation in novel tasks. We conclude that structure learning plays a fundamental role in skill learning and may underlie the unsurpassed flexibility and adaptability of the motor system. PMID:19720086

The Construction of an Ontology-Based Ubiquitous Learning Grid

ERIC Educational Resources Information Center

Liao, Ching-Jung; Chou, Chien-Chih; Yang, Jin-Tan David

2009-01-01

The purpose of this study is to incorporate adaptive ontology into ubiquitous learning grid to achieve seamless learning environment. Ubiquitous learning grid uses ubiquitous computing environment to infer and determine the most adaptive learning contents and procedures in anytime, any place and with any device. To achieve the goal, an…

The utility of adaptive eLearning in cervical cytopathology education.

PubMed

Samulski, T Danielle; Taylor, Laura A; La, Teresa; Mehr, Chelsea R; McGrath, Cindy M; Wu, Roseann I

2018-02-01

Adaptive eLearning allows students to experience a self-paced, individualized curriculum based on prior knowledge and learning ability. The authors investigated the effectiveness of adaptive online modules in teaching cervical cytopathology. eLearning modules were created that covered basic concepts in cervical cytopathology, including artifacts and infections, squamous lesions (SL), and glandular lesions (GL). The modules used student responses to individualize the educational curriculum and provide real-time feedback. Pathology trainees and faculty from the authors' institution were randomized into 2 groups (SL or GL), and identical pre-tests and post-tests were used to compare the efficacy of eLearning modules versus traditional study methods (textbooks and slide sets). User experience was assessed with a Likert scale and free-text responses. Sixteen of 17 participants completed the SL module, and 19 of 19 completed the GL module. Participants in both groups had improved post-test scores for content in the adaptive eLearning module. Users indicated that the module was effective in presenting content and concepts (Likert scale [from 1 to 5], 4.3 of 5.0), was an efficient and convenient way to review the material (Likert scale, 4.4 of 5.0), and was more engaging than lectures and texts (Likert scale, 4.6 of 5.0). Users favored the immediate feedback and interactivity of the module. Limitations included the inability to review prior content and slow upload time for images. Learners demonstrated improvement in their knowledge after the use of adaptive eLearning modules compared with traditional methods. Overall, the modules were viewed positively by participants. Adaptive eLearning modules can provide an engaging and effective adjunct to traditional teaching methods in cervical cytopathology. Cancer Cytopathol 2018;126:129-35. © 2017 American Cancer Society. © 2017 American Cancer Society.

Context Aware Ubiquitous Learning Environments for Peer-to-Peer Collaborative Learning

ERIC Educational Resources Information Center

Yang, Stephen J. H.

2006-01-01

A ubiquitous learning environment provides an interoperable, pervasive, and seamless learning architecture to connect, integrate, and share three major dimensions of learning resources: learning collaborators, learning contents, and learning services. Ubiquitous learning is characterized by providing intuitive ways for identifying right learning…

Students' perceptions of constructivist Internet learning environments by a physics virtual laboratory: the gap between ideal and reality and gender differences.

PubMed

Chuang, Shih-Chyueh; Hwang, Fu-Kwun; Tsai, Chin-Chung

2008-04-01

The purpose of this study was to investigate the perceptions of Internet users of a physics virtual laboratory, Demolab, in Taiwan. Learners' perceptions of Internet-based learning environments were explored and the role of gender was examined by using preferred and actual forms of a revised Constructivist Internet-based Learning Environment Survey (CILES). The students expressed a clear gap between ideal and reality, and they showed higher preferences for many features of constructivist Internet-based learning environments than for features they had actually learned in Demolab. The results further suggested that male users prefer to be involved in the process of discussion and to show critical judgments. In addition, male users indicated they enjoyed the process of negotiation and discussion with others and were able to engage in reflective thoughts while learning in Demolab. In light of these findings, male users seemed to demonstrate better adaptability to the constructivist Internet-based learning approach than female users did. Although this study indicated certain differences between males and females in their responses to Internet-based learning environments, they also shared numerous similarities. A well-established constructivist Internet-based learning environment may encourage more female learners to participate in the science community.

Learning System Design Consideration in Creating an Online Learning Environment.

ERIC Educational Resources Information Center

Schaffer, Scott

This paper describes the design of a Web-based learning environment for leadership facilitators in a United States military organization. The overall aim of this project was to design a prototype of an online learning environment that supports leadership facilitators' knowledge development in the content area of motivation. The learning…

Constructivist Learning Environment among Palestinian Science Students

ERIC Educational Resources Information Center

Zeidan, Afif

2015-01-01

The purpose of this study was to investigate the constructivist learning environment among Palestinian science students. The study also aimed to investigate the effects of gender and learning level of these students on their perceptions of the constructivist learning environment. Data were collected from 125 male and 101 female students from the…

Adaptive Intelligent Support to Improve Peer Tutoring in Algebra

ERIC Educational Resources Information Center

Walker, Erin; Rummel, Nikol; Koedinger, Kenneth R.

2014-01-01

Adaptive collaborative learning support (ACLS) involves collaborative learning environments that adapt their characteristics, and sometimes provide intelligent hints and feedback, to improve individual students' collaborative interactions. ACLS often involves a system that can automatically assess student dialogue, model effective and…

The Future of Adaptive Learning: Does the Crowd Hold the Key?

ERIC Educational Resources Information Center

Heffernan, Neil T.; Ostrow, Korinn S.; Kelly, Kim; Selent, Douglas; Van Inwegen, Eric G.; Xiong, Xiaolu; Williams, Joseph Jay

2016-01-01

Due to substantial scientific and practical progress, learning technologies can effectively adapt to the characteristics and needs of students. This article considers how learning technologies can adapt over time by crowdsourcing contributions from teachers and students--explanations, feedback, and other pedagogical interactions. Considering the…

Environment: A Learning Resource.

ERIC Educational Resources Information Center

Tasmanian Education Dept., Hobart (Australia).

The aim of this document is to give teachers in Tasmania an understanding of the importance and usefulness of the environment as a learning resource both as an immediate stimulus for learning and for the long term process of forming sound community values. The document provides schools with a basis for the development of environmental resources…

Enhancing Student Motivation and Learning within Adaptive Tutors

ERIC Educational Resources Information Center

Ostrow, Korinn S.

2015-01-01

My research is rooted in improving K-12 educational practice using motivational facets made possible through adaptive tutoring systems. In an attempt to isolate best practices within the science of learning, I conduct randomized controlled trials within ASSISTments, an online adaptive tutoring system that provides assistance and assessment to…

Student Motivation in Constructivist Learning Environment

ERIC Educational Resources Information Center

Cetin-Dindar, Ayla

2016-01-01

The purpose of this study was to investigate the relation between constructivist learning environment and students'motivation to learn science by testing whether students' self-efficacy in learning science, intrinsically and extrinsically motivated science learning increase and students' anxiety about science assessment decreases when more…

HEAT Sensor: Harsh Environment Adaptable Thermionic Sensor

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

Limb, Scott J.

2016-05-31

This document is the final report for the “HARSH ENVIRONMENT ADAPTABLE THERMIONIC SENSOR” project under NETL’s Crosscutting contract DE-FE0013062. This report addresses sensors that can be made with thermionic thin films along with the required high temperature hermetic packaging process. These sensors can be placed in harsh high temperature environments and potentially be wireless and self-powered.

The Predicaments of Language Learners in Traditional Learning Environments

ERIC Educational Resources Information Center

Shafie, Latisha Asmaak; Mansor, Mahani

2009-01-01

Some public universities in developing countries have traditional language learning environments such as classrooms with only blackboards and furniture which do not provide conducive learning environments. These traditional environments are unable to cater for digital learners who need to learn with learning technologies. In order to create…

Camelid genomes reveal evolution and adaptation to desert environments.

PubMed

Wu, Huiguang; Guang, Xuanmin; Al-Fageeh, Mohamed B; Cao, Junwei; Pan, Shengkai; Zhou, Huanmin; Zhang, Li; Abutarboush, Mohammed H; Xing, Yanping; Xie, Zhiyuan; Alshanqeeti, Ali S; Zhang, Yanru; Yao, Qiulin; Al-Shomrani, Badr M; Zhang, Dong; Li, Jiang; Manee, Manee M; Yang, Zili; Yang, Linfeng; Liu, Yiyi; Zhang, Jilin; Altammami, Musaad A; Wang, Shenyuan; Yu, Lili; Zhang, Wenbin; Liu, Sanyang; Ba, La; Liu, Chunxia; Yang, Xukui; Meng, Fanhua; Wang, Shaowei; Li, Lu; Li, Erli; Li, Xueqiong; Wu, Kaifeng; Zhang, Shu; Wang, Junyi; Yin, Ye; Yang, Huanming; Al-Swailem, Abdulaziz M; Wang, Jun

2014-10-21

Bactrian camel (Camelus bactrianus), dromedary (Camelus dromedarius) and alpaca (Vicugna pacos) are economically important livestock. Although the Bactrian camel and dromedary are large, typically arid-desert-adapted mammals, alpacas are adapted to plateaus. Here we present high-quality genome sequences of these three species. Our analysis reveals the demographic history of these species since the Tortonian Stage of the Miocene and uncovers a striking correlation between large fluctuations in population size and geological time boundaries. Comparative genomic analysis reveals complex features related to desert adaptations, including fat and water metabolism, stress responses to heat, aridity, intense ultraviolet radiation and choking dust. Transcriptomic analysis of Bactrian camels further reveals unique osmoregulation, osmoprotection and compensatory mechanisms for water reservation underpinned by high blood glucose levels. We hypothesize that these physiological mechanisms represent kidney evolutionary adaptations to the desert environment. This study advances our understanding of camelid evolution and the adaptation of camels to arid-desert environments.

Smile: Student Modification in Learning Environments. Establishing Congruence between Actual and Preferred Classroom Learning Environment.

ERIC Educational Resources Information Center

Yarrow, Allan; Millwater, Jan

1995-01-01

This study investigated whether classroom psychosocial environment, as perceived by student teachers, could be improved to their preferred level. Students completed the College and University Classroom Environment Inventory, discussed interventions, then completed it again. Significant deficiencies surfaced in the learning environment early in the…

Adaptive Learning in Medical Education: The Final Piece of Technology Enhanced Learning?

PubMed

Sharma, Neel; Doherty, Iain; Dong, Chaoyan

2017-09-01

Technology enhanced learning (TEL) is now common practice in the field of medical education. One of the primary examples of its use is that of high fidelity simulation and computerised mannequins. Further examples include online learning modules, electronic portfolios, virtual patient interactions, massive open online courses and the flipped classroom movement. The rise of TEL has occurred primarily due to the ease of internet access enabling the retrieval and sharing of information in an instant. Furthermore, the compact nature of internet ready devices such as smartphones and laptops has meant that access to information can occur anytime and anywhere. From an educational perspective however, the current utilisation of TEL has been hindered by its lack of understanding of learners' needs. This is concerning, particularly as evidence highlights that during medical training, each individual learner has their own learning requirements and often achieves competency at different rates. In view of this, there has been interest in ensuring TEL is more learner aware and that the learning process should be more personalised. Adaptive learning can aim to achieve this by ensuring content is delivered according to the needs of the learner. This commentary highlights the move towards adaptive learning and the benefits of such an intervention.

Clinical learning environment at Shiraz Medical School.

PubMed

Rezaee, Rita; Ebrahimi, Sedigheh

2013-01-01

Clinical learning occurs in the context of a dynamic environment. Learning environment found to be one of the most important factors in determining the success of an effective teaching program. To investigate, from the attending and resident's perspective, factors that may affect student leaning in the educational hospital setting at Shiraz University of Medical Sciences (SUMS). This study combined qualitative and quantitative methods to determine factors affecting effective learning in clinical setting. Residents evaluated the perceived effectiveness of the university hospital learning environment. Fifty two faculty members and 132 residents participated in this study. Key determinants that contribute to an effective clinical teaching were autonomy, supervision, social support, workload, role clarity, learning opportunity, work diversity and physical facilities. In a good clinical setting, residents should be appreciated and given appropriate opportunities to study in order to meet their objectives. They require a supportive environment to consolidate their knowledge, skills and judgment. © 2013 Tehran University of Medical Sciences. All rights reserved.

Behavioural variation in 172 small-scale societies indicates that social learning is the main mode of human adaptation.

PubMed

Mathew, Sarah; Perreault, Charles

2015-07-07

The behavioural variation among human societies is vast and unmatched in the animal world. It is unclear whether this variation is due to variation in the ecological environment or to differences in cultural traditions. Underlying this debate is a more fundamental question: is the richness of humans' behavioural repertoire due to non-cultural mechanisms, such as causal reasoning, inventiveness, reaction norms, trial-and-error learning and evoked culture, or is it due to the population-level dynamics of cultural transmission? Here, we measure the relative contribution of environment and cultural history in explaining the behavioural variation of 172 Native American tribes at the time of European contact. We find that the effect of cultural history is typically larger than that of environment. Behaviours also persist over millennia within cultural lineages. This indicates that human behaviour is not predominantly determined by single-generation adaptive responses, contra theories that emphasize non-cultural mechanisms as determinants of human behaviour. Rather, the main mode of human adaptation is social learning mechanisms that operate over multiple generations. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Active Learning Environment with Lenses in Geometric Optics

ERIC Educational Resources Information Center

Tural, Güner

2015-01-01

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

Building Adaptive Game-Based Learning Resources: The Integration of IMS Learning Design and

ERIC Educational Resources Information Center

Burgos, Daniel; Moreno-Ger, Pablo; Sierra, Jose Luis; Fernandez-Manjon, Baltasar; Specht, Marcus; Koper, Rob

2008-01-01

IMS Learning Design (IMS-LD) is a specification to create units of learning (UoLs), which express a certain pedagogical model or strategy (e.g., adaptive learning with games). However, the authoring process of a UoL remains difficult because of the lack of high-level authoring tools for IMS-LD, even more so when the focus is on specific topics,…

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition

PubMed Central

Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

2017-01-01

Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle). PMID:28608824

Using Scenarios to Design Complex Technology-Enhanced Learning Environments

ERIC Educational Resources Information Center

de Jong, Ton; Weinberger, Armin; Girault, Isabelle; Kluge, Anders; Lazonder, Ard W.; Pedaste, Margus; Ludvigsen, Sten; Ney, Muriel; Wasson, Barbara; Wichmann, Astrid; Geraedts, Caspar; Giemza, Adam; Hovardas, Tasos; Julien, Rachel; van Joolingen, Wouter R.; Lejeune, Anne; Manoli, Constantinos C.; Matteman, Yuri; Sarapuu, Tago; Verkade, Alex; Vold, Vibeke; Zacharia, Zacharias C.

2012-01-01

Science Created by You (SCY) learning environments are computer-based environments in which students learn about science topics in the context of addressing a socio-scientific problem. Along their way to a solution for this problem students produce many types of intermediate products or learning objects. SCY learning environments center the entire…

Learning classifier systems for single and multiple mobile robots in unstructured environments

NASA Astrophysics Data System (ADS)

Bay, John S.

1995-12-01

The learning classifier system (LCS) is a learning production system that generates behavioral rules via an underlying discovery mechanism. The LCS architecture operates similarly to a blackboard architecture; i.e., by posted-message communications. But in the LCS, the message board is wiped clean at every time interval, thereby requiring no persistent shared resource. In this paper, we adapt the LCS to the problem of mobile robot navigation in completely unstructured environments. We consider the model of the robot itself, including its sensor and actuator structures, to be part of this environment, in addition to the world-model that includes a goal and obstacles at unknown locations. This requires a robot to learn its own I/O characteristics in addition to solving its navigation problem, but results in a learning controller that is equally applicable, unaltered, in robots with a wide variety of kinematic structures and sensing capabilities. We show the effectiveness of this LCS-based controller through both simulation and experimental trials with a small robot. We then propose a new architecture, the Distributed Learning Classifier System (DLCS), which generalizes the message-passing behavior of the LCS from internal messages within a single agent to broadcast massages among multiple agents. This communications mode requires little bandwidth and is easily implemented with inexpensive, off-the-shelf hardware. The DLCS is shown to have potential application as a learning controller for multiple intelligent agents.

Personalized Virtual Learning Environment from the Detection of Learning Styles

ERIC Educational Resources Information Center

Martínez Cartas, M. L.; Cruz Pérez, N.; Deliche Quesada, D.; Mateo Quero, S.

2013-01-01

Through the previous detection of existing learning styles in a classroom, a Virtual Learning Environment (VLE) has been designed for students of several Engineering degrees, using the Learning Management System (LMS) utilized in the University of Jaen, ILIAS. Learning styles of three different Knowledge Areas; Chemical Engineering, Materials…

Learning Objects and Virtual Learning Environments Technical Evaluation Criteria

ERIC Educational Resources Information Center

Kurilovas, Eugenijus; Dagiene, Valentina

2009-01-01

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

Predicting Student Performance in a Collaborative Learning Environment

ERIC Educational Resources Information Center

Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol

2015-01-01

Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

Modelling Adaptive Learning Behaviours for Consensus Formation in Human Societies

NASA Astrophysics Data System (ADS)

Yu, Chao; Tan, Guozhen; Lv, Hongtao; Wang, Zhen; Meng, Jun; Hao, Jianye; Ren, Fenghui

2016-06-01

Learning is an important capability of humans and plays a vital role in human society for forming beliefs and opinions. In this paper, we investigate how learning affects the dynamics of opinion formation in social networks. A novel learning model is proposed, in which agents can dynamically adapt their learning behaviours in order to facilitate the formation of consensus among them, and thus establish a consistent social norm in the whole population more efficiently. In the model, agents adapt their opinions through trail-and-error interactions with others. By exploiting historical interaction experience, a guiding opinion, which is considered to be the most successful opinion in the neighbourhood, can be generated based on the principle of evolutionary game theory. Then, depending on the consistency between its own opinion and the guiding opinion, a focal agent can realize whether its opinion complies with the social norm (i.e., the majority opinion that has been adopted) in the population, and adapt its behaviours accordingly. The highlight of the model lies in that it captures the essential features of people’s adaptive learning behaviours during the evolution and formation of opinions. Experimental results show that the proposed model can facilitate the formation of consensus among agents, and some critical factors such as size of opinion space and network topology can have significant influences on opinion dynamics.

Modelling Adaptive Learning Behaviours for Consensus Formation in Human Societies.

PubMed

Yu, Chao; Tan, Guozhen; Lv, Hongtao; Wang, Zhen; Meng, Jun; Hao, Jianye; Ren, Fenghui

2016-06-10

Learning is an important capability of humans and plays a vital role in human society for forming beliefs and opinions. In this paper, we investigate how learning affects the dynamics of opinion formation in social networks. A novel learning model is proposed, in which agents can dynamically adapt their learning behaviours in order to facilitate the formation of consensus among them, and thus establish a consistent social norm in the whole population more efficiently. In the model, agents adapt their opinions through trail-and-error interactions with others. By exploiting historical interaction experience, a guiding opinion, which is considered to be the most successful opinion in the neighbourhood, can be generated based on the principle of evolutionary game theory. Then, depending on the consistency between its own opinion and the guiding opinion, a focal agent can realize whether its opinion complies with the social norm (i.e., the majority opinion that has been adopted) in the population, and adapt its behaviours accordingly. The highlight of the model lies in that it captures the essential features of people's adaptive learning behaviours during the evolution and formation of opinions. Experimental results show that the proposed model can facilitate the formation of consensus among agents, and some critical factors such as size of opinion space and network topology can have significant influences on opinion dynamics.

Modelling Adaptive Learning Behaviours for Consensus Formation in Human Societies

PubMed Central

Yu, Chao; Tan, Guozhen; Lv, Hongtao; Wang, Zhen; Meng, Jun; Hao, Jianye; Ren, Fenghui

2016-01-01

Learning is an important capability of humans and plays a vital role in human society for forming beliefs and opinions. In this paper, we investigate how learning affects the dynamics of opinion formation in social networks. A novel learning model is proposed, in which agents can dynamically adapt their learning behaviours in order to facilitate the formation of consensus among them, and thus establish a consistent social norm in the whole population more efficiently. In the model, agents adapt their opinions through trail-and-error interactions with others. By exploiting historical interaction experience, a guiding opinion, which is considered to be the most successful opinion in the neighbourhood, can be generated based on the principle of evolutionary game theory. Then, depending on the consistency between its own opinion and the guiding opinion, a focal agent can realize whether its opinion complies with the social norm (i.e., the majority opinion that has been adopted) in the population, and adapt its behaviours accordingly. The highlight of the model lies in that it captures the essential features of people’s adaptive learning behaviours during the evolution and formation of opinions. Experimental results show that the proposed model can facilitate the formation of consensus among agents, and some critical factors such as size of opinion space and network topology can have significant influences on opinion dynamics. PMID:27282089

Adaptive Synchronization of Semantically Compressed Instructional Videos for Collaborative Distance Learning

ERIC Educational Resources Information Center

Phung, Dan; Valetto, Giuseppe; Kaiser, Gail E.; Liu, Tiecheng; Kender, John R.

2007-01-01

The increasing popularity of online courses has highlighted the need for collaborative learning tools for student groups. In this article, we present an e-Learning architecture and adaptation model called AI2TV (Adaptive Interactive Internet Team Video), which allows groups of students to collaboratively view instructional videos in synchrony.…

An Assistive Computerized Learning Environment for Distance Learning Students with Learning Disabilities

ERIC Educational Resources Information Center

Klemes, Joel; Epstein, Alit; Zuker, Michal; Grinberg, Nira; Ilovitch, Tamar

2006-01-01

The current study examines how a computerized learning environment assists students with learning disabilities (LD) enrolled in a distance learning course at the Open University of Israel. The technology provides computer display of the text, synchronized with auditory output and accompanied by additional computerized study skill tools which…

The role of learning environment on high school chemistry students' motivation and self-regulatory processes

NASA Astrophysics Data System (ADS)

Judd, Jeffrey S.

Changes to the global workforce and technological advancements require graduating high school students to be more autonomous, self-directed, and critical in their thinking. To reflect societal changes, current educational reform has focused on developing more problem-based, collaborative, and student-centered classrooms to promote effective self-regulatory learning strategies, with the goal of helping students adapt to future learning situations and become life-long learners. This study identifies key features that may characterize these "powerful learning environments", which I term "high self-regulating learning environments" for ease of discussion, and examine the environment's role on students' motivation and self-regulatory processes. Using direct observation, surveys, and formal and informal interviews, I identified perceptions, motivations, and self-regulatory strategies of 67 students in my high school chemistry classes as they completed academic tasks in both high and low self-regulating learning environments. With social cognitive theory as a theoretical framework, I then examined how students' beliefs and processes changed after they moved from low to a high self-regulating learning environment. Analyses revealed that key features such as task meaning, utility, complexity, and control appeared to play a role in promoting positive changes in students' motivation and self-regulation. As embedded cases, I also included four students identified as high self-regulating, and four students identified as low self-regulating to examine whether the key features of high and low self-regulating learning environments played a similar role in both groups. Analysis of findings indicates that key features did play a significant role in promoting positive changes in both groups, with high self-regulating students' motivation and self-regulatory strategies generally remaining higher than the low self-regulating students; this was the case in both environments. Findings

Theoretical Foundations of Learning Environments. Second Edition

ERIC Educational Resources Information Center

Jonassen, David, Ed.; Land, Susan, Ed.

2012-01-01

"Theoretical Foundations of Learning Environments" provides students, faculty, and instructional designers with a clear, concise introduction to the major pedagogical and psychological theories and their implications for the design of new learning environments for schools, universities, or corporations. Leading experts describe the most…

The Internet: A Learning Environment.

ERIC Educational Resources Information Center

McGreal, Rory

1997-01-01

The Internet environment is suitable for many types of learning activities and teaching and learning styles. Every World Wide Web-based course should provide: home page; introduction; course overview; course requirements, vital information; roles and responsibilities; assignments; schedule; resources; sample tests; teacher biography; course…

On adaptive learning rate that guarantees convergence in feedforward networks.

PubMed

Behera, Laxmidhar; Kumar, Swagat; Patnaik, Awhan

2006-09-01

This paper investigates new learning algorithms (LF I and LF II) based on Lyapunov function for the training of feedforward neural networks. It is observed that such algorithms have interesting parallel with the popular backpropagation (BP) algorithm where the fixed learning rate is replaced by an adaptive learning rate computed using convergence theorem based on Lyapunov stability theory. LF II, a modified version of LF I, has been introduced with an aim to avoid local minima. This modification also helps in improving the convergence speed in some cases. Conditions for achieving global minimum for these kind of algorithms have been studied in detail. The performances of the proposed algorithms are compared with BP algorithm and extended Kalman filtering (EKF) on three bench-mark function approximation problems: XOR, 3-bit parity, and 8-3 encoder. The comparisons are made in terms of number of learning iterations and computational time required for convergence. It is found that the proposed algorithms (LF I and II) are much faster in convergence than other two algorithms to attain same accuracy. Finally, the comparison is made on a complex two-dimensional (2-D) Gabor function and effect of adaptive learning rate for faster convergence is verified. In a nutshell, the investigations made in this paper help us better understand the learning procedure of feedforward neural networks in terms of adaptive learning rate, convergence speed, and local minima.

Evaluating and Implementing Learning Environments: A United Kingdom Experience.

ERIC Educational Resources Information Center

Ingraham, Bruce; Watson, Barbara; McDowell, Liz; Brockett, Adrian; Fitzpatrick, Simon

2002-01-01

Reports on ongoing work at five universities in northeastern England that have been evaluating and implementing online learning environments known as virtual learning environments (VLEs) or managed learning environments (MLEs). Discusses do-it-yourself versus commercial systems; transferability; Web-based versus client-server; integration with…

T Cell Adaptive Immunity Proceeds through Environment-Induced Adaptation from the Exposure of Cryptic Genetic Variation

PubMed Central

Whitacre, James M.; Lin, Joseph; Harding, Angus

2011-01-01

Evolution is often characterized as a process involving incremental genetic changes that are slowly discovered and fixed in a population through genetic drift and selection. However, a growing body of evidence is finding that changes in the environment frequently induce adaptations that are much too rapid to occur by an incremental genetic search process. Rapid evolution is hypothesized to be facilitated by mutations present within the population that are silent or “cryptic” within the first environment but are co-opted or “exapted” to the new environment, providing a selective advantage once revealed. Although cryptic mutations have recently been shown to facilitate evolution in RNA enzymes, their role in the evolution of complex phenotypes has not been proven. In support of this wider role, this paper describes an unambiguous relationship between cryptic genetic variation and complex phenotypic responses within the immune system. By reviewing the biology of the adaptive immune system through the lens of evolution, we show that T cell adaptive immunity constitutes an exemplary model system where cryptic alleles drive rapid adaptation of complex traits. In naive T cells, normally cryptic differences in T cell receptor reveal diversity in activation responses when the cellular population is presented with a novel environment during infection. We summarize how the adaptive immune response presents a well studied and appropriate experimental system that can be used to confirm and expand upon theoretical evolutionary models describing how seemingly small and innocuous mutations can drive rapid cellular evolution. PMID:22363338

Adaptation to Temporally Fluctuating Environments by the Evolution of Maternal Effects.

PubMed

Dey, Snigdhadip; Proulx, Stephen R; Teotónio, Henrique

2016-02-01

All organisms live in temporally fluctuating environments. Theory predicts that the evolution of deterministic maternal effects (i.e., anticipatory maternal effects or transgenerational phenotypic plasticity) underlies adaptation to environments that fluctuate in a predictably alternating fashion over maternal-offspring generations. In contrast, randomizing maternal effects (i.e., diversifying and conservative bet-hedging), are expected to evolve in response to unpredictably fluctuating environments. Although maternal effects are common, evidence for their adaptive significance is equivocal since they can easily evolve as a correlated response to maternal selection and may or may not increase the future fitness of offspring. Using the hermaphroditic nematode Caenorhabditis elegans, we here show that the experimental evolution of maternal glycogen provisioning underlies adaptation to a fluctuating normoxia-anoxia hatching environment by increasing embryo survival under anoxia. In strictly alternating environments, we found that hermaphrodites evolved the ability to increase embryo glycogen provisioning when they experienced normoxia and to decrease embryo glycogen provisioning when they experienced anoxia. At odds with existing theory, however, populations facing irregularly fluctuating normoxia-anoxia hatching environments failed to evolve randomizing maternal effects. Instead, adaptation in these populations may have occurred through the evolution of fitness effects that percolate over multiple generations, as they maintained considerably high expected growth rates during experimental evolution despite evolving reduced fecundity and reduced embryo survival under one or two generations of anoxia. We develop theoretical models that explain why adaptation to a wide range of patterns of environmental fluctuations hinges on the existence of deterministic maternal effects, and that such deterministic maternal effects are more likely to contribute to adaptation than

Adaptation to Temporally Fluctuating Environments by the Evolution of Maternal Effects

PubMed Central

Dey, Snigdhadip; Proulx, Stephen R.; Teotónio, Henrique

2016-01-01

All organisms live in temporally fluctuating environments. Theory predicts that the evolution of deterministic maternal effects (i.e., anticipatory maternal effects or transgenerational phenotypic plasticity) underlies adaptation to environments that fluctuate in a predictably alternating fashion over maternal-offspring generations. In contrast, randomizing maternal effects (i.e., diversifying and conservative bet-hedging), are expected to evolve in response to unpredictably fluctuating environments. Although maternal effects are common, evidence for their adaptive significance is equivocal since they can easily evolve as a correlated response to maternal selection and may or may not increase the future fitness of offspring. Using the hermaphroditic nematode Caenorhabditis elegans, we here show that the experimental evolution of maternal glycogen provisioning underlies adaptation to a fluctuating normoxia–anoxia hatching environment by increasing embryo survival under anoxia. In strictly alternating environments, we found that hermaphrodites evolved the ability to increase embryo glycogen provisioning when they experienced normoxia and to decrease embryo glycogen provisioning when they experienced anoxia. At odds with existing theory, however, populations facing irregularly fluctuating normoxia–anoxia hatching environments failed to evolve randomizing maternal effects. Instead, adaptation in these populations may have occurred through the evolution of fitness effects that percolate over multiple generations, as they maintained considerably high expected growth rates during experimental evolution despite evolving reduced fecundity and reduced embryo survival under one or two generations of anoxia. We develop theoretical models that explain why adaptation to a wide range of patterns of environmental fluctuations hinges on the existence of deterministic maternal effects, and that such deterministic maternal effects are more likely to contribute to adaptation than

Behavioral Feature Extraction to Determine Learning Styles in e-Learning Environments

ERIC Educational Resources Information Center

Fatahi, Somayeh; Moradi, Hadi; Farmad, Elaheh

2015-01-01

Learning Style (LS) is an important parameter in the learning process. Therefore, learning styles should be considered in the design, development, and implementation of e-learning environments. Consequently, an important capability of an e-learning system could be the automatic determination of a student's learning style. In this paper, a set of…

The Relationship among Self-Regulated Learning, Procrastination, and Learning Behaviors in Blended Learning Environment

ERIC Educational Resources Information Center

Yamada, Masanori; Goda, Yoshiko; Matsuda, Takeshi; Kato, Hiroshi; Miyagawa, Hiroyuki

2015-01-01

This research aims to investigate the relationship among the awareness of self-regulated learning (SRL), procrastination, and learning behaviors in blended learning environment. One hundred seventy nine freshmen participated in this research, conducted in the blended learning style class using learning management system. Data collection was…

Swarm Intelligence: New Techniques for Adaptive Systems to Provide Learning Support

ERIC Educational Resources Information Center

Wong, Lung-Hsiang; Looi, Chee-Kit

2012-01-01

The notion of a system adapting itself to provide support for learning has always been an important issue of research for technology-enabled learning. One approach to provide adaptivity is to use social navigation approaches and techniques which involve analysing data of what was previously selected by a cluster of users or what worked for…

How Teaching Science Using Project-Based Learning Strategies Affects the Classroom Learning Environment

ERIC Educational Resources Information Center

Hugerat, Muhamad

2016-01-01

This study involved 458 ninth-grade students from two different Arab middle schools in Israel. Half of the students learned science using project-based learning strategies and the other half learned using traditional methods (non-project-based). The classes were heterogeneous regarding their achievements in the sciences. The adapted questionnaire…

A Development of Learning Widget on M-Learning and E-Learning Environments

ERIC Educational Resources Information Center

Kim, SooHwan; Kim, HyeonCheol; Han, SeonKwan

2013-01-01

This article describes the development of learning widget on m-learning and e-learning environments. A widget is a small, simple and useful application supporting user-oriented contents. The user may select and install widgets that are convenient as well as an auto-updating application including weather or calendar. These widgets are especially…

The Influence of Student Characteristics on the Use of Adaptive E-Learning Material

ERIC Educational Resources Information Center

van Seters, J. R.; Ossevoort, M. A.; Tramper, J.; Goedhart, M. J.

2012-01-01

Adaptive e-learning materials can help teachers to educate heterogeneous student groups. This study provides empirical data about the way academic students differ in their learning when using adaptive e-learning materials. Ninety-four students participated in the study. We determined characteristics in a heterogeneous student group by collecting…

Evolutionary perspectives on learning: conceptual and methodological issues in the study of adaptive specializations.

PubMed

Krause, Mark A

2015-07-01

Inquiry into evolutionary adaptations has flourished since the modern synthesis of evolutionary biology. Comparative methods, genetic techniques, and various experimental and modeling approaches are used to test adaptive hypotheses. In psychology, the concept of adaptation is broadly applied and is central to comparative psychology and cognition. The concept of an adaptive specialization of learning is a proposed account for exceptions to general learning processes, as seen in studies of Pavlovian conditioning of taste aversions, sexual responses, and fear. The evidence generally consists of selective associations forming between biologically relevant conditioned and unconditioned stimuli, with conditioned responses differing in magnitude, persistence, or other measures relative to non-biologically relevant stimuli. Selective associations for biologically relevant stimuli may suggest adaptive specializations of learning, but do not necessarily confirm adaptive hypotheses as conceived of in evolutionary biology. Exceptions to general learning processes do not necessarily default to an adaptive specialization explanation, even if experimental results "make biological sense". This paper examines the degree to which hypotheses of adaptive specializations of learning in sexual and fear response systems have been tested using methodologies developed in evolutionary biology (e.g., comparative methods, quantitative and molecular genetics, survival experiments). A broader aim is to offer perspectives from evolutionary biology for testing adaptive hypotheses in psychological science.

Methods of Psychological and Pedagogical Accompaniment of First-Year Students in Process of Adapting to Learning at University

ERIC Educational Resources Information Center

Maralova, Tatyana P.; Filipenkova, Olesya G.; Galitskikh, Elena O.; Shulga, Tatiana I.; Sidyacheva, Natalya V.; Ovsyanik, Olga A.

2016-01-01

The relevance of the study is conditioned by the complexity of students' adaptation to learning at University due to the change of social environment, an alarming feelings about the precise self-determination, lack of knowledge in opportunities for self-expression in art, science, sport and public life. The purpose of the paper is to identify…

What if Learning Analytics Were Based on Learning Science?

ERIC Educational Resources Information Center

Marzouk, Zahia; Rakovic, Mladen; Liaqat, Amna; Vytasek, Jovita; Samadi, Donya; Stewart-Alonso, Jason; Ram, Ilana; Woloshen, Sonya; Winne, Philip H.; Nesbit, John C.

2016-01-01

Learning analytics are often formatted as visualisations developed from traced data collected as students study in online learning environments. Optimal analytics inform and motivate students' decisions about adaptations that improve their learning. We observe that designs for learning often neglect theories and empirical findings in learning…

Agent-Based Learning Environments as a Research Tool for Investigating Teaching and Learning.

ERIC Educational Resources Information Center

Baylor, Amy L.

2002-01-01

Discusses intelligent learning environments for computer-based learning, such as agent-based learning environments, and their advantages over human-based instruction. Considers the effects of multiple agents; agents and research design; the use of Multiple Intelligent Mentors Instructing Collaboratively (MIMIC) for instructional design for…

The effects of different learning environments on students' motivation for learning and their achievement.

PubMed

Baeten, Marlies; Dochy, Filip; Struyven, Katrien

2013-09-01

Research in higher education on the effects of student-centred versus lecture-based learning environments generally does not take into account the psychological need support provided in these learning environments. From a self-determination theory perspective, need support is important to study because it has been associated with benefits such as autonomous motivation and achievement. The purpose of the study is to investigate the effects of different learning environments on students' motivation for learning and achievement, while taking into account the perceived need support. First-year student teachers (N= 1,098) studying a child development course completed questionnaires assessing motivation and perceived need support. In addition, a prior knowledge test and case-based assessment were administered. A quasi-experimental pre-test/post-test design was set up consisting of four learning environments: (1) lectures, (2) case-based learning (CBL), (3) alternation of lectures and CBL, and (4) gradual implementation with lectures making way for CBL. Autonomous motivation and achievement were higher in the gradually implemented CBL environment, compared to the CBL environment. Concerning achievement, two additional effects were found; students in the lecture-based learning environment scored higher than students in the CBL environment, and students in the gradually implemented CBL environment scored higher than students in the alternated learning environment. Additionally, perceived need support was positively related to autonomous motivation, and negatively to controlled motivation. The study shows the importance of gradually introducing students to CBL, in terms of their autonomous motivation and achievement. Moreover, the study emphasizes the importance of perceived need support for students' motivation. © 2012 The British Psychological Society.

Personal Learning Environments: A Solution for Self-Directed Learners

ERIC Educational Resources Information Center

Haworth, Ryan

2016-01-01

In this paper I discuss "personal learning environments" and their diverse benefits, uses, and implications for life-long learning. Personal Learning Environments (PLEs) are Web 2.0 and social media technologies that enable individual learners the ability to manage their own learning. Self-directed learning is explored as a foundation…

Guiding Learners into Reengagement through the SCALE Environment: An Empirical Study

ERIC Educational Resources Information Center

Verginis, Ilias; Gouli, Evangelia; Gogoulou, Agoritsa; Grigoriadou, Maria

2011-01-01

The paper presents the facilities offered by the open learner model maintained in the web-based, adaptive, activity-oriented learning environment SCALE (Supporting Collaboration and Adaptation in a Learning Environment), in order to guide online students who become disengaged and support their reengagement. The open learner model (OLM_SCALE)…

Learning How to Design a Technology Supported Inquiry-Based Learning Environment

ERIC Educational Resources Information Center

Hakverdi-Can, Meral; Sonmez, Duygu

2012-01-01

This paper describes a study focusing on pre-service teachers' experience of learning how to design a technology supported inquiry-based learning environment using the Internet. As part of their elective course, pre-service science teachers were asked to develop a WebQuest environment targeting middle school students. A WebQuest is an…

Emergent Fields through Adaptation and Identity: Overcoming Social Distance

ERIC Educational Resources Information Center

DeGennaro, Donna; Brown, Tiffany

2009-01-01

We examine the inseparability of one's environment with the elements of adaptation and identity. Specifically, we revisit the Project H.O.M.E. learning environment as we suggest that the entities of adaption and environment are not only binding, but also naturally in constant flux as they interact with each other. Contrary to nature, however, the…

Virtual Learning Environments.

ERIC Educational Resources Information Center

Follows, Scott B.

1999-01-01

Illustrates the possibilities and educational benefits of virtual learning environments (VLEs), based on experiences with "Thirst for Knowledge," a VLE that simulates the workplace of a major company. While working in this virtual office world, students walk through the building, attend meetings, read reports, receive e-mail, answer the telephone,…

Stimulating the cerebellum affects visuomotor adaptation but not intermanual transfer of learning.

PubMed

Block, Hannah; Celnik, Pablo

2013-12-01

When systematic movement errors occur, the brain responds with a systematic change in motor behavior. This type of adaptive motor learning can transfer intermanually; adaptation of movements of the right hand in response to training with a perturbed visual signal (visuomotor adaptation) may carry over to the left hand. While visuomotor adaptation has been studied extensively, it is unclear whether the cerebellum, a structure involved in adaptation, is important for intermanual transfer as well. We addressed this question with three experiments in which subjects reached with their right hands as a 30° visuomotor rotation was introduced. Subjects received anodal or sham transcranial direct current stimulation on the trained (experiment 1) or untrained (experiment 2) hemisphere of the cerebellum, or, for comparison, motor cortex (M1). After the training period, subjects reached with their left hand, without visual feedback, to assess intermanual transfer of learning aftereffects. Stimulation of the right cerebellum caused faster adaptation, but none of the stimulation sites affected transfer. To ascertain whether cerebellar stimulation would increase transfer if subjects learned faster as well as a larger amount, in experiment 3 anodal and sham cerebellar groups experienced a shortened training block such that the anodal group learned more than sham. Despite the difference in adaptation magnitude, transfer was similar across these groups, although smaller than in experiment 1. Our results suggest that intermanual transfer of visuomotor learning does not depend on cerebellar activity and that the number of movements performed at plateau is an important predictor of transfer.

Stimulating the cerebellum affects visuomotor adaptation but not intermanual transfer of learning

PubMed Central

Block, Hannah; Celnik, Pablo

2013-01-01

When systematic movement errors occur, the brain responds with a systematic change in motor behavior. This type of adaptive motor learning can transfer intermanually; adaptation of movements of the right hand in response to training with a perturbed visual signal (visuomotor adaptation) may carry over to the left hand. While visuomotor adaptation has been studied extensively, it is unclear whether the cerebellum, a structure involved in adaptation, is important for intermanual transfer as well. We addressed this question with three experiments in which subjects reached with their right hands as a 30° visuomotor rotation was introduced. Subjects received anodal or sham transcranial direct current stimulation (tDCS) on the trained (Experiment 1) or untrained (Experiment 2) hemisphere of the cerebellum, or, for comparison, motor cortex (M1). After the training period, subjects reached with their left hand, without visual feedback, to assess intermanual transfer of learning aftereffects. Stimulation of the right cerebellum caused faster adaptation, but none of the stimulation sites affected transfer. To ascertain whether cerebellar stimulation would increase transfer if subjects learned faster as well as a larger amount, in Experiment 3 anodal and sham cerebellar groups experienced a shortened training block such that the anodal group learned more than sham. Despite the difference in adaptation magnitude, transfer was similar across these groups, although smaller than in Experiment 1. Our results suggest that intermanual transfer of visuomotor learning does not depend on cerebellar activity, and that the number of movements performed at plateau is an important predictor of transfer. PMID:23625383

Reading a Story: Different Degrees of Learning in Different Learning Environments.

PubMed

Giannini, Anna Maria; Cordellieri, Pierluigi; Piccardi, Laura

2017-01-01

The learning environment in which material is acquired may produce differences in delayed recall and in the elements that individuals focus on. These differences may appear even during development. In the present study, we compared three different learning environments in 450 normally developing 7-year-old children subdivided into three groups according to the type of learning environment. Specifically, children were asked to learn the same material shown in three different learning environments: reading illustrated books (TB); interacting with the same text displayed on a PC monitor and enriched with interactive activities (PC-IA); reading the same text on a PC monitor but not enriched with interactive narratives (PC-NoIA). Our results demonstrated that TB and PC-NoIA elicited better verbal memory recall. In contrast, PC-IA and PC-NoIA produced higher scores for visuo-spatial memory, enhancing memory for spatial relations, positions and colors with respect to TB. Interestingly, only TB seemed to produce a deeper comprehension of the story's moral. Our results indicated that PC-IA offered a different type of learning that favored visual details. In this sense, interactive activities demonstrate certain limitations, probably due to information overabundance, emotional mobilization, emphasis on images and effort exerted in interactive activities. Thus, interactive activities, although entertaining, act as disruptive elements which interfere with verbal memory and deep moral comprehension.

Reading a Story: Different Degrees of Learning in Different Learning Environments

PubMed Central

Giannini, Anna Maria; Cordellieri, Pierluigi; Piccardi, Laura

2017-01-01

The learning environment in which material is acquired may produce differences in delayed recall and in the elements that individuals focus on. These differences may appear even during development. In the present study, we compared three different learning environments in 450 normally developing 7-year-old children subdivided into three groups according to the type of learning environment. Specifically, children were asked to learn the same material shown in three different learning environments: reading illustrated books (TB); interacting with the same text displayed on a PC monitor and enriched with interactive activities (PC-IA); reading the same text on a PC monitor but not enriched with interactive narratives (PC-NoIA). Our results demonstrated that TB and PC-NoIA elicited better verbal memory recall. In contrast, PC-IA and PC-NoIA produced higher scores for visuo-spatial memory, enhancing memory for spatial relations, positions and colors with respect to TB. Interestingly, only TB seemed to produce a deeper comprehension of the story’s moral. Our results indicated that PC-IA offered a different type of learning that favored visual details. In this sense, interactive activities demonstrate certain limitations, probably due to information overabundance, emotional mobilization, emphasis on images and effort exerted in interactive activities. Thus, interactive activities, although entertaining, act as disruptive elements which interfere with verbal memory and deep moral comprehension. PMID:29085296

Exposure to stressful environments - Strategy of adaptive responses

NASA Technical Reports Server (NTRS)

Farhi, Leon E.

1991-01-01

Stresses such as hypoxia, water lack, and heat exposure can produce strains in more than a single organ system, in turn stimulating the body to adapt in multiple ways. Nevertheless, a general strategy of the various adaptive responses emerges when the challenges are divided into three groups: (1) conditions that affect the supply of essential molecules, (2) stresses that prevent the body from regulating properly the output of waste products such as CO2 and heat, and (3) environments that disrupt body transport systems. Problems may arise when there is a conflict between two stresses requiring conflicting adaptive changes. An alternative to adaptation, creation of microenvironment, is often favored by the animal.

The cultural niche: Why social learning is essential for human adaptation

PubMed Central

Boyd, Robert; Richerson, Peter J.; Henrich, Joseph

2011-01-01

In the last 60,000 y humans have expanded across the globe and now occupy a wider range than any other terrestrial species. Our ability to successfully adapt to such a diverse range of habitats is often explained in terms of our cognitive ability. Humans have relatively bigger brains and more computing power than other animals, and this allows us to figure out how to live in a wide range of environments. Here we argue that humans may be smarter than other creatures, but none of us is nearly smart enough to acquire all of the information necessary to survive in any single habitat. In even the simplest foraging societies, people depend on a vast array of tools, detailed bodies of local knowledge, and complex social arrangements and often do not understand why these tools, beliefs, and behaviors are adaptive. We owe our success to our uniquely developed ability to learn from others. This capacity enables humans to gradually accumulate information across generations and develop well-adapted tools, beliefs, and practices that are too complex for any single individual to invent during their lifetime. PMID:21690340

The Prepared Environment and Its Relationship to Learning.

ERIC Educational Resources Information Center

Loeffler, Margaret Howard

A "prepared environment" is a planned learning facility for young children which offers a supportive and stimulating environment. Current thinking on early learning and the resultant implications for the design of a physical environment which would encourage conceptual development are examined in this book. Each section considers a particular…

Optimizing the learning rate for adaptive estimation of neural encoding models

PubMed Central

2018-01-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel

Optimizing the learning rate for adaptive estimation of neural encoding models.

PubMed

Hsieh, Han-Lin; Shanechi, Maryam M

2018-05-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel

Creating and Nurturing Distributed Asynchronous Learning Environments.

ERIC Educational Resources Information Center

Kochtanek, Thomas R.; Hein, Karen K.

2000-01-01

Describes the evolution of a university course from a face-to-face experience to a Web-based asynchronous learning environment. Topics include cognition and learning; distance learning and distributed learning; student learning communities and the traditional classroom; the future as it relates to education and technology; collaborative student…

Architecture and Children: Learning Environments and Design Education.

ERIC Educational Resources Information Center

Taylor, Anne, Ed.; Muhlberger, Joe, Ed.

1998-01-01

This issue addresses (1) growing international interest in learning environments and their effects on behavior, and (2) design education, an integrated model for visual-spatial lifelong learning. It focuses on this new and emerging integrated field which integrates elements in education, new learning environment design, and the use of more two-…

Learning to soar in turbulent environments

NASA Astrophysics Data System (ADS)

Reddy, Gautam; Celani, Antonio; Sejnowski, Terrence; Vergassola, Massimo

Birds and gliders exploit warm, rising atmospheric currents (thermals) to reach heights comparable to low-lying clouds with a reduced expenditure of energy. Soaring provides a remarkable instance of complex decision-making in biology and requires a long-term strategy to effectively use the ascending thermals. Furthermore, the problem is technologically relevant to extend the flying range of autonomous gliders. The formation of thermals unavoidably generates strong turbulent fluctuations, which make deriving an efficient policy harder and thus constitute an essential element of soaring. Here, we approach soaring flight as a problem of learning to navigate highly fluctuating turbulent environments. We simulate the atmospheric boundary layer by numerical models of turbulent convective flow and combine them with model-free, experience-based, reinforcement learning algorithms to train the virtual gliders. For the learned policies in the regimes of moderate and strong turbulence levels, the virtual glider adopts an increasingly conservative policy as turbulence levels increase, quantifying the degree of risk affordable in turbulent environments. Reinforcement learning uncovers those sensorimotor cues that permit effective control over soaring in turbulent environments.

An Environment for Mobile Experiential Learning

ERIC Educational Resources Information Center

Petrovic, Otto; Babcicky, Philipp; Puchleitner, Thomas

2014-01-01

In experiential learning courses students acquire new knowledge through learning that takes place in real-life scenarios. By utilizing mobile devices to conduct observations outside of the classroom, learners can arrive at a broader and deeper understanding of their inquiries. In this paper, we propose a learning environment that integrates mobile…

The clinical learning environment in nursing education: a concept analysis.

PubMed

Flott, Elizabeth A; Linden, Lois

2016-03-01

The aim of this study was to report an analysis of the clinical learning environment concept. Nursing students are evaluated in clinical learning environments where skills and knowledge are applied to patient care. These environments affect achievement of learning outcomes, and have an impact on preparation for practice and student satisfaction with the nursing profession. Providing clarity of this concept for nursing education will assist in identifying antecedents, attributes and consequences affecting student transition to practice. The clinical learning environment was investigated using Walker and Avant's concept analysis method. A literature search was conducted using WorldCat, MEDLINE and CINAHL databases using the keywords clinical learning environment, clinical environment and clinical education. Articles reviewed were written in English and published in peer-reviewed journals between 1995-2014. All data were analysed for recurring themes and terms to determine possible antecedents, attributes and consequences of this concept. The clinical learning environment contains four attribute characteristics affecting student learning experiences. These include: (1) the physical space; (2) psychosocial and interaction factors; (3) the organizational culture and (4) teaching and learning components. These attributes often determine achievement of learning outcomes and student self-confidence. With better understanding of attributes comprising the clinical learning environment, nursing education programmes and healthcare agencies can collaborate to create meaningful clinical experiences and enhance student preparation for the professional nurse role. © 2015 John Wiley & Sons Ltd.

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

ERIC Educational Resources Information Center

Huang, Shiu-Li; Yang, Chia-Wei

2009-01-01

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

Adaptation and learning: characteristic time scales of performance dynamics.

PubMed

Newell, Karl M; Mayer-Kress, Gottfried; Hong, S Lee; Liu, Yeou-Teh

2009-12-01

A multiple time scales landscape model is presented that reveals structures of performance dynamics that were not resolved in the traditional power law analysis of motor learning. It shows the co-existence of separate processes during and between practice sessions that evolve in two independent dimensions characterized by time scales that differ by about an order of magnitude. Performance along the slow persistent dimension of learning improves often as much and sometimes more during rest (memory consolidation and/or insight generation processes) than during a practice session itself. In contrast, the process characterized by the fast, transient dimension of adaptation reverses direction between practice sessions, thereby significantly degrading performance at the beginning of the next practice session (warm-up decrement). The theoretical model fits qualitatively and quantitatively the data from Snoddy's [Snoddy, G. S. (1926). Learning and stability. Journal of Applied Psychology, 10, 1-36] classic learning study of mirror tracing and other averaged and individual data sets, and provides a new account of the processes of change in adaptation and learning. 2009 Elsevier B.V. All rights reserved.

Mobile Adaptive Communication Support for Vocabulary Acquisition

ERIC Educational Resources Information Center

Epp, Carrie Demmans

2014-01-01

This work explores the use of an adaptive mobile tool for language learning. A school-based deployment study showed that the tool supported learning. A second study is being conducted in informal learning environments. Current work focuses on building models that increase our understanding of the relationship between application usage and learning.

Advanced Training Technologies and Learning Environments

NASA Technical Reports Server (NTRS)

Noor, Ahmed K. (Compiler); Malone, John B. (Compiler)

1999-01-01

This document contains the proceedings of the Workshop on Advanced Training Technologies and Learning Environments held at NASA Langley Research Center, Hampton, Virginia, March 9-10, 1999. The workshop was jointly sponsored by the University of Virginia's Center for Advanced Computational Technology and NASA. Workshop attendees were from NASA, other government agencies, industry, and universities. The objective of the workshop was to assess the status and effectiveness of different advanced training technologies and learning environments.

Online Resource-Based Learning Environment: Case Studies in Primary Classrooms

ERIC Educational Resources Information Center

So, Winnie Wing Mui; Ching, Fiona Ngai Ying

2012-01-01

This paper discusses the creation of learning environments with online resources by three primary school teachers for pupil's learning of science-related topics with reference to the resource-based e-learning environments (RBeLEs) framework. Teachers' choice of contexts, resources, tools, and scaffolds in designing the learning environments are…

Perceived Satisfaction, Perceived Usefulness and Interactive Learning Environments as Predictors to Self-Regulation in e-Learning Environments

ERIC Educational Resources Information Center

Liaw, Shu-Sheng; Huang, Hsiu-Mei

2013-01-01

The research purpose is to investigate learner self-regulation in e-learning environments. In order to better understand learner attitudes toward e-learning, 196 university students answer a questionnaire survey after use an e-learning system few months. The statistical results showed that perceived satisfaction, perceived usefulness, and…

FODEM: Developing Digital Learning Environments in Widely Dispersed Learning Communities

ERIC Educational Resources Information Center

Suhonen, Jarkko; Sutinen, Erkki

2006-01-01

FODEM (FOrmative DEvelopment Method) is a design method for developing digital learning environments for widely dispersed learning communities. These are communities in which the geographical distribution and density of learners is low when compared to the kind of learning communities in which there is a high distribution and density of learners…

The Effects of Integrating Social Learning Environment with Online Learning

ERIC Educational Resources Information Center

Raspopovic, Miroslava; Cvetanovic, Svetlana; Medan, Ivana; Ljubojevic, Danijela

2017-01-01

The aim of this paper is to present the learning and teaching styles using the Social Learning Environment (SLE), which was developed based on the computer supported collaborative learning approach. To avoid burdening learners with multiple platforms and tools, SLE was designed and developed in order to integrate existing systems, institutional…

Incremental learning of concept drift in nonstationary environments.

PubMed

Elwell, Ryan; Polikar, Robi

2011-10-01

We introduce an ensemble of classifiers-based approach for incremental learning of concept drift, characterized by nonstationary environments (NSEs), where the underlying data distributions change over time. The proposed algorithm, named Learn(++). NSE, learns from consecutive batches of data without making any assumptions on the nature or rate of drift; it can learn from such environments that experience constant or variable rate of drift, addition or deletion of concept classes, as well as cyclical drift. The algorithm learns incrementally, as other members of the Learn(++) family of algorithms, that is, without requiring access to previously seen data. Learn(++). NSE trains one new classifier for each batch of data it receives, and combines these classifiers using a dynamically weighted majority voting. The novelty of the approach is in determining the voting weights, based on each classifier's time-adjusted accuracy on current and past environments. This approach allows the algorithm to recognize, and act accordingly, to the changes in underlying data distributions, as well as to a possible reoccurrence of an earlier distribution. We evaluate the algorithm on several synthetic datasets designed to simulate a variety of nonstationary environments, as well as a real-world weather prediction dataset. Comparisons with several other approaches are also included. Results indicate that Learn(++). NSE can track the changing environments very closely, regardless of the type of concept drift. To allow future use, comparison and benchmarking by interested researchers, we also release our data used in this paper. © 2011 IEEE

Effectiveness of Adaptive Assessment versus Learner Control in a Multimedia Learning System

ERIC Educational Resources Information Center

Chen, Ching-Huei; Chang, Shu-Wei

2015-01-01

The purpose of this study was to explore the effectiveness of adaptive assessment versus learner control in a multimedia learning system designed to help secondary students learn science. Unlike other systems, this paper presents a workflow of adaptive assessment following instructional materials that better align with learners' cognitive…

Achieving diversity in nursing through multicontextual learning environments.

PubMed

Giddens, Jean Foret

2008-01-01

Attempts to increase diversity within the nursing profession have resulted in the admission of more ethnically diverse students into nursing education programs. However, traditional curricular and pedagogical practices seen in many nursing programs do not accommodate the learning needs of diverse learners. Nurse educators are encouraged to adopt learner-centered pedagogical approaches and embrace multicontextual learning environments. The purpose of this article is to describe the concept of multicontextuality and to introduce an exemplar of a multicontextual learning environment that has been recently developed and implemented in an undergraduate nursing program. The virtual community, known as The Neighborhood, presents nursing concepts in a rich personal and community context through stories and supplemental multimedia. The perceived benefit is enhancement of conceptual learning in a student-oriented learning environment.

Relationships between Learning Environment and Mathematics Anxiety

ERIC Educational Resources Information Center

Taylor, Bret A.; Fraser, Barry J.

2013-01-01

We investigated relationships between the learning environment and students' mathematics anxiety, as well as differences between the sexes in perceptions of learning environment and anxiety. A sample of 745 high-school students in 34 different mathematics classrooms in four high schools in Southern California was used to cross-validate the What Is…

Sociocultural Perspective of Science in Online Learning Environments. Communities of Practice in Online Learning Environments

ERIC Educational Resources Information Center

Erdogan, Niyazi

2016-01-01

Present study reviews empirical research studies related to learning science in online learning environments as a community. Studies published between 1995 and 2015 were searched by using ERIC and EBSCOhost databases. As a result, fifteen studies were selected for review. Identified studies were analyzed with a qualitative content analysis method…

Investigation of the Relationship between Learning Process and Learning Outcomes in E-Learning Environments

ERIC Educational Resources Information Center

Yurdugül, Halil; Menzi Çetin, Nihal

2015-01-01

Problem Statement: Learners can access and participate in online learning environments regardless of time and geographical barriers. This brings up the umbrella concept of learner autonomy that contains self-directed learning, self-regulated learning and the studying process. Motivation and learning strategies are also part of this umbrella…

Self-Regulated Learning in Technology Enhanced Learning Environments: An Investigation with University Students

ERIC Educational Resources Information Center

Lenne, Dominique; Abel, Marie-Helene; Trigano, Philippe; Leblanc, Adeline

2008-01-01

In Technology Enhanced Learning Environments, self-regulated learning (SRL) partly relies on the features of the technological tools. The authors present two environments they designed in order to facilitate SRL: the first one (e-Dalgo) is a website dedicated to the learning of algorithms and computer programming. It is structured as a classical…

The Design of Learning Environments.

ERIC Educational Resources Information Center

Stueck, Lawrence E.

This study, using the Eisner's Educational Criticism Model, examines the role school architecture plays in eliciting creative, self-directed, child-centered responses in elementary school students. An evaluation of 11 play environments; 7 learning environments; an integrated third grade curriculum known as the City Classroom is presented; and the…

E-Learning Environment for Hearing Impaired Students

ERIC Educational Resources Information Center

Hashim, Hisyamuddin; Tasir, Zaidatun; Mohamad, Siti Khadijah

2013-01-01

The usage of technology within the educational department has become more vital by each year passing. One of the most popular technological approaches used is the e-learning environment. The usage of e-learning environment in education involves a wide range of types of students, and this includes the hearing impaired ones. Some adjustment or…

Learning feedback and feedforward control in a mirror-reversed visual environment.

PubMed

Kasuga, Shoko; Telgen, Sebastian; Ushiba, Junichi; Nozaki, Daichi; Diedrichsen, Jörn

2015-10-01

When we learn a novel task, the motor system needs to acquire both feedforward and feedback control. Currently, little is known about how the learning of these two mechanisms relate to each other. In the present study, we tested whether feedforward and feedback control need to be learned separately, or whether they are learned as common mechanism when a new control policy is acquired. Participants were trained to reach to two lateral and one central target in an environment with mirror (left-right)-reversed visual feedback. One group was allowed to make online movement corrections, whereas the other group only received visual information after the end of the movement. Learning of feedforward control was assessed by measuring the accuracy of the initial movement direction to lateral targets. Feedback control was measured in the responses to sudden visual perturbations of the cursor when reaching to the central target. Although feedforward control improved in both groups, it was significantly better when online corrections were not allowed. In contrast, feedback control only adaptively changed in participants who received online feedback and remained unchanged in the group without online corrections. Our findings suggest that when a new control policy is acquired, feedforward and feedback control are learned separately, and that there may be a trade-off in learning between feedback and feedforward controllers. Copyright © 2015 the American Physiological Society.

Learning feedback and feedforward control in a mirror-reversed visual environment

PubMed Central

Kasuga, Shoko; Telgen, Sebastian; Ushiba, Junichi; Nozaki, Daichi

2015-01-01

When we learn a novel task, the motor system needs to acquire both feedforward and feedback control. Currently, little is known about how the learning of these two mechanisms relate to each other. In the present study, we tested whether feedforward and feedback control need to be learned separately, or whether they are learned as common mechanism when a new control policy is acquired. Participants were trained to reach to two lateral and one central target in an environment with mirror (left-right)-reversed visual feedback. One group was allowed to make online movement corrections, whereas the other group only received visual information after the end of the movement. Learning of feedforward control was assessed by measuring the accuracy of the initial movement direction to lateral targets. Feedback control was measured in the responses to sudden visual perturbations of the cursor when reaching to the central target. Although feedforward control improved in both groups, it was significantly better when online corrections were not allowed. In contrast, feedback control only adaptively changed in participants who received online feedback and remained unchanged in the group without online corrections. Our findings suggest that when a new control policy is acquired, feedforward and feedback control are learned separately, and that there may be a trade-off in learning between feedback and feedforward controllers. PMID:26245313

Assessing culturally sensitive factors in the learning environment of science classrooms

NASA Astrophysics Data System (ADS)

Fisher, Darrell L.; Waldrip, Bruce G.

1997-03-01

As schools are becoming increasingly diverse in their scope and clientele, any examination of the interaction of culturally sensitive factors of students' learning environments with learning science assumes critical importance. The purpose of this exploratory study was to develop an instrument to assess learning environment factors that are culturally sensitive, to provide initial validation information on the instrument and to examine associations between students' perceptions of their learning environments and their attitudes towards science and achievement of enquiry skills. A measure of these factors of science student's learning environment, namely the Cultural Learning Environment Questionnaire (CLEQ), was developed from past learning environment instruments and influenced by Hofstede's four dimensions of culture (Power Distance, Uncertainty Avoidance, Individualism, and Masculinity/Femininity). The reliability and discriminant validity for each scale were obtained and associations between learning environment, attitude to science and enquiry skills achievement were found.

Human Pathophysiological Adaptations to the Space Environment

PubMed Central

Demontis, Gian C.; Germani, Marco M.; Caiani, Enrico G.; Barravecchia, Ivana; Passino, Claudio; Angeloni, Debora

2017-01-01

Space is an extreme environment for the human body, where during long-term missions microgravity and high radiation levels represent major threats to crew health. Intriguingly, space flight (SF) imposes on the body of highly selected, well-trained, and healthy individuals (astronauts and cosmonauts) pathophysiological adaptive changes akin to an accelerated aging process and to some diseases. Such effects, becoming manifest over a time span of weeks (i.e., cardiovascular deconditioning) to months (i.e., loss of bone density and muscle atrophy) of exposure to weightlessness, can be reduced through proper countermeasures during SF and in due time are mostly reversible after landing. Based on these considerations, it is increasingly accepted that SF might provide a mechanistic insight into certain pathophysiological processes, a concept of interest to pre-nosological medicine. In this article, we will review the main stress factors encountered in space and their impact on the human body and will also discuss the possible lessons learned with space exploration in reference to human health on Earth. In fact, this is a productive, cross-fertilized, endeavor in which studies performed on Earth yield countermeasures for protection of space crew health, and space research is translated into health measures for Earth-bound population. PMID:28824446

Human Pathophysiological Adaptations to the Space Environment.

PubMed

Demontis, Gian C; Germani, Marco M; Caiani, Enrico G; Barravecchia, Ivana; Passino, Claudio; Angeloni, Debora

2017-01-01

Space is an extreme environment for the human body, where during long-term missions microgravity and high radiation levels represent major threats to crew health. Intriguingly, space flight (SF) imposes on the body of highly selected, well-trained, and healthy individuals (astronauts and cosmonauts) pathophysiological adaptive changes akin to an accelerated aging process and to some diseases. Such effects, becoming manifest over a time span of weeks (i.e., cardiovascular deconditioning) to months (i.e., loss of bone density and muscle atrophy) of exposure to weightlessness, can be reduced through proper countermeasures during SF and in due time are mostly reversible after landing. Based on these considerations, it is increasingly accepted that SF might provide a mechanistic insight into certain pathophysiological processes, a concept of interest to pre-nosological medicine. In this article, we will review the main stress factors encountered in space and their impact on the human body and will also discuss the possible lessons learned with space exploration in reference to human health on Earth. In fact, this is a productive, cross-fertilized, endeavor in which studies performed on Earth yield countermeasures for protection of space crew health, and space research is translated into health measures for Earth-bound population.

Learning about Environments: The Significance of Primal Landscapes

NASA Astrophysics Data System (ADS)

Measham, Thomas G.

2006-09-01

The way we learn about our environments—be they farms, forests, or tribal lands—has implications for the formulation of environmental policy. This article presents the findings of how residents learned about their environments in two rural case studies conducted in northern Queensland and relates these to the concept of “primal landscapes,” which is concerned with the interaction that occurs between children and the environments in which they mature. Rather than focusing specifically on built environments or natural environments, the article draws on an approach that conceptualizes environment as meaning-laden places in which we live and work, which integrate social, cultural, biological, physical, and economic dimensions. In drawing insights for environmental policy, the article draws attention to the timing of policy interventions, the significance of experiential environmental education, the potential to learn from place-based festivals, and the importance of learning from extreme events such as fires and floods.

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

ERIC Educational Resources Information Center

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

2001-01-01

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

Engaging students in a community of learning: Renegotiating the learning environment.

PubMed

Theobald, Karen A; Windsor, Carol A; Forster, Elizabeth M

2018-03-01

Promoting student engagement in a student led environment can be challenging. This article reports on the process of design, implementation and evaluation of a student led learning approach in a small group tutorial environment in a three year Bachelor of Nursing program at an Australian university. The research employed three phases of data collection. The first phase explored student perceptions of learning and engagement in tutorials. The results informed the development of a web based learning resource. Phase two centred on implementation of a community of learning approach where students were supported to lead tutorial learning with peers. The final phase constituted an evaluation of the new approach. Findings suggest that students have the capacity to lead and engage in a community of learning and to assume greater ownership and responsibility where scaffolding is provided. Nonetheless, an ongoing whole of course approach to pedagogical change would better support this form of teaching and learning innovation. Copyright © 2018 Elsevier Ltd. All rights reserved.

Creating Dynamic Learning Environment to Enhance Students’ Engagement in Learning Geometry

NASA Astrophysics Data System (ADS)

Sariyasa

2017-04-01

Learning geometry gives many benefits to students. It strengthens the development of deductive thinking and reasoning; it also provides an opportunity to improve visualisation and spatial ability. Some studies, however, have pointed out the difficulties that students encountered when learning geometry. A preliminary study by the author in Bali revealed that one of the main problems was teachers’ difficulties in delivering geometry instruction. It was partly due to the lack of appropriate instructional media. Coupling with dynamic geometry software, dynamic learning environments is a promising solution to this problem. Employing GeoGebra software supported by the well-designed instructional process may result in more meaningful learning, and consequently, students are motivated to engage in the learning process more deeply and actively. In this paper, we provide some examples of GeoGebra-aided learning activities that allow students to interactively explore and investigate geometry concepts and the properties of geometry objects. Thus, it is expected that such learning environment will enhance students’ internalisation process of geometry concepts.

Adaptations to local environments in modern human populations.

PubMed

Jeong, Choongwon; Di Rienzo, Anna

2014-12-01

After leaving sub-Saharan Africa around 50000-100000 years ago, anatomically modern humans have quickly occupied extremely diverse environments. Human populations were exposed to further environmental changes resulting from cultural innovations, such as the spread of farming, which gave rise to new selective pressures related to pathogen exposures and dietary shifts. In addition to changing the frequency of individual adaptive alleles, natural selection may also shape the overall genetic architecture of adaptive traits. Here, we review recent advances in understanding the genetic architecture of adaptive human phenotypes based on insights from the studies of lactase persistence, skin pigmentation and high-altitude adaptation. These adaptations evolved in parallel in multiple human populations, providing a chance to investigate independent realizations of the evolutionary process. We suggest that the outcome of adaptive evolution is often highly variable even under similar selective pressures. Finally, we highlight a growing need for detecting adaptations that did not follow the classical sweep model and for incorporating new sources of genetic evidence such as information from ancient DNA. Copyright © 2014 Elsevier Ltd. All rights reserved.

Soft Systems Methodology for Personalized Learning Environment

ERIC Educational Resources Information Center

Nair, Uday

2015-01-01

There are two sides to a coin when it comes to implementing technology at universities; on one side, there is the university using technologies via the virtual learning environment that seems to be outdated with the digital needs of the students, and on the other side, while implementing technology at the university learning environment the focus…

Higher-Order Thinking Development through Adaptive Problem-Based Learning

ERIC Educational Resources Information Center

Raiyn, Jamal; Tilchin, Oleg

2015-01-01

In this paper we propose an approach to organizing Adaptive Problem-Based Learning (PBL) leading to the development of Higher-Order Thinking (HOT) skills and collaborative skills in students. Adaptability of PBL is expressed by changes in fixed instructor assessments caused by the dynamics of developing HOT skills needed for problem solving,…

Improving the Adaptability of Simulated Evolutionary Swarm Robots in Dynamically Changing Environments

PubMed Central

Yao, Yao; Marchal, Kathleen; Van de Peer, Yves

2014-01-01

One of the important challenges in the field of evolutionary robotics is the development of systems that can adapt to a changing environment. However, the ability to adapt to unknown and fluctuating environments is not straightforward. Here, we explore the adaptive potential of simulated swarm robots that contain a genomic encoding of a bio-inspired gene regulatory network (GRN). An artificial genome is combined with a flexible agent-based system, representing the activated part of the regulatory network that transduces environmental cues into phenotypic behaviour. Using an artificial life simulation framework that mimics a dynamically changing environment, we show that separating the static from the conditionally active part of the network contributes to a better adaptive behaviour. Furthermore, in contrast with most hitherto developed ANN-based systems that need to re-optimize their complete controller network from scratch each time they are subjected to novel conditions, our system uses its genome to store GRNs whose performance was optimized under a particular environmental condition for a sufficiently long time. When subjected to a new environment, the previous condition-specific GRN might become inactivated, but remains present. This ability to store ‘good behaviour’ and to disconnect it from the novel rewiring that is essential under a new condition allows faster re-adaptation if any of the previously observed environmental conditions is reencountered. As we show here, applying these evolutionary-based principles leads to accelerated and improved adaptive evolution in a non-stable environment. PMID:24599485

Performance benefits of adaptive, multimicrophone, interference-canceling systems in everyday environments

NASA Astrophysics Data System (ADS)

Desloge, Joseph G.; Zimmer, Martin J.; Zurek, Patrick M.

2004-05-01

Adaptive multimicrophone systems are currently used for a variety of noise-cancellation applications (such as hearing aids) to preserve signals arriving from a particular (target) direction while canceling other (jammer) signals in the environment. Although the performance of these systems is known to degrade with increasing reverberation, there are few measurements of adaptive performance in everyday reverberant environments. In this study, adaptive performance was compared to that of a simple, nonadaptive cardioid microphone to determine a measure of adaptive benefit. Both systems used recordings (at an Fs of 22050 Hz) from the same two omnidirectional microphones, which were separated by 1 cm. Four classes of environment were considered: outdoors, household, parking garage, and public establishment. Sources were either environmental noises (e.g., household appliances, restaurant noise) or a controlled noise source. In all situations, no target was present (i.e., all signals were jammers) to obtain maximal jammer cancellation. Adaptive processing was based upon the Griffiths-Jim generalized sidelobe canceller using filter lengths up to 400 points. Average intelligibility-weighted adaptive benefit levels at a source distance of 1 m were, at most, 1.5 dB for public establishments, 2 dB for household rooms and the parking garage, and 3 dB outdoors. [Work supported by NIOSH.

Molecular specificity, convergence and constraint shape adaptive evolution in nutrient-poor environments.

PubMed

Hong, Jungeui; Gresham, David

2014-01-01

One of the central goals of evolutionary biology is to explain and predict the molecular basis of adaptive evolution. We studied the evolution of genetic networks in Saccharomyces cerevisiae (budding yeast) populations propagated for more than 200 generations in different nitrogen-limiting conditions. We find that rapid adaptive evolution in nitrogen-poor environments is dominated by the de novo generation and selection of copy number variants (CNVs), a large fraction of which contain genes encoding specific nitrogen transporters including PUT4, DUR3 and DAL4. The large fitness increases associated with these alleles limits the genetic heterogeneity of adapting populations even in environments with multiple nitrogen sources. Complete identification of acquired point mutations, in individual lineages and entire populations, identified heterogeneity at the level of genetic loci but common themes at the level of functional modules, including genes controlling phosphatidylinositol-3-phosphate metabolism and vacuole biogenesis. Adaptive strategies shared with other nutrient-limited environments point to selection of genetic variation in the TORC1 and Ras/PKA signaling pathways as a general mechanism underlying improved growth in nutrient-limited environments. Within a single population we observed the repeated independent selection of a multi-locus genotype, comprised of the functionally related genes GAT1, MEP2 and LST4. By studying the fitness of individual alleles, and their combination, as well as the evolutionary history of the evolving population, we find that the order in which these mutations are acquired is constrained by epistasis. The identification of repeatedly selected variation at functionally related loci that interact epistatically suggests that gene network polymorphisms (GNPs) may be a frequent outcome of adaptive evolution. Our results provide insight into the mechanistic basis by which cells adapt to nutrient-limited environments and suggest that

Combining Adaptive Hypermedia with Project and Case-Based Learning

ERIC Educational Resources Information Center

Papanikolaou, Kyparisia; Grigoriadou, Maria

2009-01-01

In this article we investigate the design of educational hypermedia based on constructivist learning theories. According to the principles of project and case-based learning we present the design rational of an Adaptive Educational Hypermedia system prototype named MyProject; learners working with MyProject undertake a project and the system…

Potentiating mGluR5 function with a positive allosteric modulator enhances adaptive learning.

PubMed

Xu, Jian; Zhu, Yongling; Kraniotis, Stephen; He, Qionger; Marshall, John J; Nomura, Toshihiro; Stauffer, Shaun R; Lindsley, Craig W; Conn, P Jeffrey; Contractor, Anis

2013-07-18

Metabotropic glutamate receptor 5 (mGluR5) plays important roles in modulating neural activity and plasticity and has been associated with several neuropathological disorders. Previous work has shown that genetic ablation or pharmacological inhibition of mGluR5 disrupts fear extinction and spatial reversal learning, suggesting that mGluR5 signaling is required for different forms of adaptive learning. Here, we tested whether ADX47273, a selective positive allosteric modulator (PAM) of mGluR5, can enhance adaptive learning in mice. We found that systemic administration of the ADX47273 enhanced reversal learning in the Morris Water Maze, an adaptive task. In addition, we found that ADX47273 had no effect on single-session and multi-session extinction, but administration of ADX47273 after a single retrieval trial enhanced subsequent fear extinction learning. Together these results demonstrate a role for mGluR5 signaling in adaptive learning, and suggest that mGluR5 PAMs represent a viable strategy for treatment of maladaptive learning and for improving behavioral flexibility.

Potentiating mGluR5 function with a positive allosteric modulator enhances adaptive learning

PubMed Central

Xu, Jian; Zhu, Yongling; Kraniotis, Stephen; He, Qionger; Marshall, John J.; Nomura, Toshihiro; Stauffer, Shaun R.; Lindsley, Craig W.; Conn, P. Jeffrey; Contractor, Anis

2013-01-01

Metabotropic glutamate receptor 5 (mGluR5) plays important roles in modulating neural activity and plasticity and has been associated with several neuropathological disorders. Previous work has shown that genetic ablation or pharmacological inhibition of mGluR5 disrupts fear extinction and spatial reversal learning, suggesting that mGluR5 signaling is required for different forms of adaptive learning. Here, we tested whether ADX47273, a selective positive allosteric modulator (PAM) of mGluR5, can enhance adaptive learning in mice. We found that systemic administration of the ADX47273 enhanced reversal learning in the Morris Water Maze, an adaptive task. In addition, we found that ADX47273 had no effect on single-session and multi-session extinction, but administration of ADX47273 after a single retrieval trial enhanced subsequent fear extinction learning. Together these results demonstrate a role for mGluR5 signaling in adaptive learning, and suggest that mGluR5 PAMs represent a viable strategy for treatment of maladaptive learning and for improving behavioral flexibility. PMID:23869026

Effectiveness of Personalised Learning Paths on Students Learning Experiences in an e-Learning Environment

ERIC Educational Resources Information Center

Santally, Mohammad Issack; Senteni, Alain

2013-01-01

Personalisation of e-learning environments is an interesting research area in which the learning experience of learners is generally believed to be improved when his or her personal learning preferences are taken into account. One such learning preference is the V-A-K instrument that classifies learners as visual, auditory or kinaesthetic. In this…

Adaptive Knowledge Management of Project-Based Learning

ERIC Educational Resources Information Center

Tilchin, Oleg; Kittany, Mohamed

2016-01-01

The goal of an approach to Adaptive Knowledge Management (AKM) of project-based learning (PBL) is to intensify subject study through guiding, inducing, and facilitating development knowledge, accountability skills, and collaborative skills of students. Knowledge development is attained by knowledge acquisition, knowledge sharing, and knowledge…

Construction of a Digital Learning Environment Based on Cloud Computing

ERIC Educational Resources Information Center

Ding, Jihong; Xiong, Caiping; Liu, Huazhong

2015-01-01

Constructing the digital learning environment for ubiquitous learning and asynchronous distributed learning has opened up immense amounts of concrete research. However, current digital learning environments do not fully fulfill the expectations on supporting interactive group learning, shared understanding and social construction of knowledge.…

Learning to soar in turbulent environments

PubMed Central

Reddy, Gautam; Celani, Antonio; Sejnowski, Terrence J.; Vergassola, Massimo

2016-01-01

Birds and gliders exploit warm, rising atmospheric currents (thermals) to reach heights comparable to low-lying clouds with a reduced expenditure of energy. This strategy of flight (thermal soaring) is frequently used by migratory birds. Soaring provides a remarkable instance of complex decision making in biology and requires a long-term strategy to effectively use the ascending thermals. Furthermore, the problem is technologically relevant to extend the flying range of autonomous gliders. Thermal soaring is commonly observed in the atmospheric convective boundary layer on warm, sunny days. The formation of thermals unavoidably generates strong turbulent fluctuations, which constitute an essential element of soaring. Here, we approach soaring flight as a problem of learning to navigate complex, highly fluctuating turbulent environments. We simulate the atmospheric boundary layer by numerical models of turbulent convective flow and combine them with model-free, experience-based, reinforcement learning algorithms to train the gliders. For the learned policies in the regimes of moderate and strong turbulence levels, the glider adopts an increasingly conservative policy as turbulence levels increase, quantifying the degree of risk affordable in turbulent environments. Reinforcement learning uncovers those sensorimotor cues that permit effective control over soaring in turbulent environments. PMID:27482099

Learning to soar in turbulent environments.

PubMed

Reddy, Gautam; Celani, Antonio; Sejnowski, Terrence J; Vergassola, Massimo

2016-08-16

Birds and gliders exploit warm, rising atmospheric currents (thermals) to reach heights comparable to low-lying clouds with a reduced expenditure of energy. This strategy of flight (thermal soaring) is frequently used by migratory birds. Soaring provides a remarkable instance of complex decision making in biology and requires a long-term strategy to effectively use the ascending thermals. Furthermore, the problem is technologically relevant to extend the flying range of autonomous gliders. Thermal soaring is commonly observed in the atmospheric convective boundary layer on warm, sunny days. The formation of thermals unavoidably generates strong turbulent fluctuations, which constitute an essential element of soaring. Here, we approach soaring flight as a problem of learning to navigate complex, highly fluctuating turbulent environments. We simulate the atmospheric boundary layer by numerical models of turbulent convective flow and combine them with model-free, experience-based, reinforcement learning algorithms to train the gliders. For the learned policies in the regimes of moderate and strong turbulence levels, the glider adopts an increasingly conservative policy as turbulence levels increase, quantifying the degree of risk affordable in turbulent environments. Reinforcement learning uncovers those sensorimotor cues that permit effective control over soaring in turbulent environments.

Clinical learning environments: place, artefacts and rhythm.

PubMed

Sheehan, Dale; Jowsey, Tanisha; Parwaiz, Mariam; Birch, Mark; Seaton, Philippa; Shaw, Susan; Duggan, Alison; Wilkinson, Tim

2017-10-01

Health care practitioners learn through experience in clinical environments in which supervision is a key component, but how that learning occurs outside the supervision relationship remains largely unknown. This study explores the environmental factors that inform and support workplace learning within a clinical environment. An observational study drawing on ethnographic methods was undertaken in a general medicine ward. Observers paid attention to interactions among staff members that involved potential teaching and learning moments that occurred and were visible in the course of routine work. General purpose thematic analysis of field notes was undertaken. A total of 376 observations were undertaken and documented. The findings suggest that place (location of interaction), rhythm (regularity of activities occurring in the ward) and artefacts (objects and equipment) were strong influences on the interactions and exchanges that occurred. Each of these themes had inherent tensions that could promote or inhibit engagement and therefore learning opportunities. Although many learning opportunities were available, not all were taken up or recognised by the participants. We describe and make explicit how the natural environment of a medical ward and flow of work through patient care contribute to the learning architecture, and how this creates or inhibits opportunities for learning. Awareness of learning opportunities was often tacit and not explicit for either supervisor or learner. We identify strategies through which tensions inherent within space, artefacts and the rhythms of work can be resolved and learning opportunities maximised. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Evaluation of students' perception of their learning environment and approaches to learning

NASA Astrophysics Data System (ADS)

Valyrakis, Manousos; Cheng, Ming

2015-04-01

This work presents the results of two case studies designed to assess the various approaches undergraduate and postgraduate students undertake for their education. The first study describes the results and evaluation of an undergraduate course in Water Engineering which aims to develop the fundamental background knowledge of students on introductory practical applications relevant to the practice of water and hydraulic engineering. The study assesses the effectiveness of the course design and learning environment from the perception of students using a questionnaire addressing several aspects that may affect student learning, performance and satisfaction, such as students' motivation, factors to effective learning, and methods of communication and assessment. The second study investigates the effectiveness of supervisory arrangements based on the perceptions of engineering undergraduate and postgraduate students. Effective supervision requires leadership skills that are not taught in the University, yet there is rarely a chance to get feedback, evaluate this process and reflect. Even though the results are very encouraging there are significant lessons to learn in improving ones practice and develop an effective learning environment to student support and guidance. The findings from these studies suggest that students with high level of intrinsic motivation are deep learners and are also top performers in a student-centered learning environment. A supportive teaching environment with a plethora of resources and feedback made available over different platforms that address students need for direct communication and feedback has the potential to improve student satisfaction and their learning experience. Finally, incorporating a multitude of assessment methods is also important in promoting deep learning. These results have deep implications about student learning and can be used to further improve course design and delivery in the future.

Ubiquitous Learning Environments in Higher Education: A Scoping Literature Review

ERIC Educational Resources Information Center

Virtanen, Mari Aulikki; Haavisto, Elina; Liikanen, Eeva; Kääriäinen, Maria

2018-01-01

Ubiquitous learning and the use of ubiquitous learning environments heralds a new era in higher education. Ubiquitous learning environments enhance context-aware and seamless learning experiences available from any location at any time. They support smooth interaction between authentic and digital learning resources and provide personalized…

RASCAL: A Rudimentary Adaptive System for Computer-Aided Learning.

ERIC Educational Resources Information Center

Stewart, John Christopher

Both the background of computer-assisted instruction (CAI) systems in general and the requirements of a computer-aided learning system which would be a reasonable assistant to a teacher are discussed. RASCAL (Rudimentary Adaptive System for Computer-Aided Learning) is a first attempt at defining a CAI system which would individualize the learning…

Supporting Adaptive Learning Pathways through the Use of Learning Analytics: Developments, Challenges and Future Opportunities

ERIC Educational Resources Information Center

Mavroudi, Anna; Giannakos, Michail; Krogstie, John

2018-01-01

Learning Analytics (LA) and adaptive learning are inextricably linked since they both foster technology-supported learner-centred education. This study identifies developments focusing on their interplay and emphasises insufficiently investigated directions which display a higher innovation potential. Twenty-one peer-reviewed studies are…

Adaptive distance metric learning for diffusion tensor image segmentation.

PubMed

Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C N; Chu, Winnie C W

2014-01-01

High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework.

Adaptive Distance Metric Learning for Diffusion Tensor Image Segmentation

PubMed Central

Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C. N.; Chu, Winnie C. W.

2014-01-01

High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework. PMID:24651858

[Learning about social determinants of health through chronicles, using a virtual learning environment].

PubMed

Restrepo-Palacio, Sonia; Amaya-Guio, Jairo

2016-01-01

To describe the contributions of a pedagogical strategy based on the construction of chronicles, using a Virtual Learning Environment for training medical students from Universidad de La Sabana on social determinants of health. Descriptive study with a qualitative approach. Design and implementation of a Virtual Learning Environment based on the ADDIE instructional model. A Virtual Learning Environment was implemented with an instructional design based on the five phases of the ADDIE model, on the grounds of meaningful learning and social constructivism, and through the narration of chronicles or life stories as a pedagogical strategy. During the course, the structural determinants and intermediaries were addressed, and nine chronicles were produced by working groups made up of four or five students, who demonstrated meaningful learning from real life stories, presented a coherent sequence, and kept a thread; 82% of these students incorporated in their contents most of the social determinants of health, emphasizing on the concepts of equity or inequity, equality or inequality, justice or injustice and social cohesion. A Virtual Learning Environment, based on an appropriate instructional design, allows to facilitate learning of social determinants of health through a constructivist pedagogical approach by analyzing chronicles or life stories created by ninth-semester students of medicine from Universidad de La Sabana.

Adaptation of the Patterns of Adaptive Learning Scales (PALS) to Turkish Students: Factorial Validity and Reliability

ERIC Educational Resources Information Center

Cikrikci-Demirtash, R. Nukhet

2005-01-01

The study presented in this article was conducted to determine psychometric features of scales for Turkish students by adapting the Patterns of Adaptive Learning Scales (PALS) developed by Midgley and others (2000) to the Turkish language in order to measure personal and classroom goal orientations. The scales were developed to test…

Farm Education and the Value of Learning in an Authentic Learning Environment

ERIC Educational Resources Information Center

Smeds, Pia; Jeronen, Eila; Kurppa, Sirpa

2015-01-01

Farm education is a newly emerging field of research that utilises authentic learning environments, environments that combine a subject of academic study with its real-world surroundings, actors, and activities--in this case, the practical context of a farm. The aim of the study was to investigate the effects of various learning environments…

Understanding teacher responses to constructivist learning environments: Challenges and resolutions

NASA Astrophysics Data System (ADS)

Rosenfeld, Melodie; Rosenfeld, Sherman

2006-05-01

The research literature is just beginning to uncover factors involved in sustaining constructivist learning environments, such as Project-Based Learning (PBL). Our case study investigates teacher responses to the challenges of constructivist environments, since teachers can play strong roles in supporting or undermining even the best constructivist environments or materials. We were invited to work as mediators with a middle-school science staff that was experiencing conflicts regarding two learning environments, PBL (which was the school's politically correc learning environment) and traditional. With mediated group workshops, teachers were sensitized to their own and colleagues' individual learning differences (ILDs), as measured by two styles inventories (the LSI - Kolb, 1976; and the LCI - Johnston & Dainton, 1997). Using these inventories, a learning-environment questionnaire, field notes, and delayed interviews a year later, we found that there was a relationship between teachers' preferred styles, epistemological beliefs, and their preferred teaching environment. Moreover, when the participating teachers, including early-adopters and nonvolunteers to PBL, became more sensitive to their colleagues' preferences, many staff conflicts were resolved and some mismatched teachers expressed more openness to PBL. We argue that having teachers understand their own ILDs and related responses to constructivist learning environments can contribute to resolving staff conflicts and sustaining such environments. We present a cognitive model and a strategy which illustrate this argument.

Nursing students' perceptions of learning in practice environments: a review.

PubMed

Henderson, Amanda; Cooke, Marie; Creedy, Debra K; Walker, Rachel

2012-04-01

Effective clinical learning requires integration of nursing students into ward activities, staff engagement to address individual student learning needs, and innovative teaching approaches. Assessing characteristics of practice environments can provide useful insights for development. This study identified predominant features of clinical learning environments from nursing students' perspectives across studies using the same measure in different countries over the last decade. Six studies, from three different countries, using the Clinical Leaning Environment Inventory (CLEI) were reviewed. Studies explored consistent trends about learning environment. Students rated sense of task accomplishment high. Affiliation also rated highly though was influenced by models of care. Feedback measuring whether students' individual needs and views were accommodated consistently rated lower. Across different countries students report similar perceptions about learning environments. Clinical learning environments are most effective in promoting safe practice and are inclusive of student learners, but not readily open to innovation and challenges to routine practices. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

Learning for intelligent mobile robots

NASA Astrophysics Data System (ADS)

Hall, Ernest L.; Liao, Xiaoqun; Alhaj Ali, Souma M.

2003-10-01

Unlike intelligent industrial robots which often work in a structured factory setting, intelligent mobile robots must often operate in an unstructured environment cluttered with obstacles and with many possible action paths. However, such machines have many potential applications in medicine, defense, industry and even the home that make their study important. Sensors such as vision are needed. However, in many applications some form of learning is also required. The purpose of this paper is to present a discussion of recent technical advances in learning for intelligent mobile robots. During the past 20 years, the use of intelligent industrial robots that are equipped not only with motion control systems but also with sensors such as cameras, laser scanners, or tactile sensors that permit adaptation to a changing environment has increased dramatically. However, relatively little has been done concerning learning. Adaptive and robust control permits one to achieve point to point and controlled path operation in a changing environment. This problem can be solved with a learning control. In the unstructured environment, the terrain and consequently the load on the robot"s motors are constantly changing. Learning the parameters of a proportional, integral and derivative controller (PID) and artificial neural network provides an adaptive and robust control. Learning may also be used for path following. Simulations that include learning may be conducted to see if a robot can learn its way through a cluttered array of obstacles. If a situation is performed repetitively, then learning can also be used in the actual application. To reach an even higher degree of autonomous operation, a new level of learning is required. Recently learning theories such as the adaptive critic have been proposed. In this type of learning a critic provides a grade to the controller of an action module such as a robot. The creative control process is used that is "beyond the adaptive critic." A

Understanding the science-learning environment: A genetically sensitive approach.

PubMed

Haworth, Claire M A; Davis, Oliver S P; Hanscombe, Ken B; Kovas, Yulia; Dale, Philip S; Plomin, Robert

2013-02-01

Previous studies have shown that environmental influences on school science performance increase in importance from primary to secondary school. Here we assess for the first time the relationship between the science-learning environment and science performance using a genetically sensitive approach to investigate the aetiology of this link. 3000 pairs of 14-year-old twins from the UK Twins Early Development Study reported on their experiences of the science-learning environment and were assessed for their performance in science using a web-based test of scientific enquiry. Multivariate twin analyses were used to investigate the genetic and environmental links between environment and outcome. The most surprising result was that the science-learning environment was almost as heritable (43%) as performance on the science test (50%), and showed negligible shared environmental influence (3%). Genetic links explained most (56%) of the association between learning environment and science outcome, indicating gene-environment correlation.

Benefits of Informal Learning Environments: A Focused Examination of STEM-Based Program Environments

ERIC Educational Resources Information Center

Denson, Cameron D.; Austin Stallworth, Chandra; Hailey, Christine; Householder, Daniel L.

2015-01-01

This paper examines STEM-based informal learning environments for underrepresented students and reports on the aspects of these programs that are beneficial to students. This qualitative study provides a nuanced look into informal learning environments and determines what is unique about these experiences and makes them beneficial for students. We…

Investigating Learning through Work: Learning Environment Scale & User Guide to the Provider. Support Document

ERIC Educational Resources Information Center

Hawke, Geof; Chappell, Clive

2008-01-01

This Support Document was produced by the authors based on their research for the report, "Investigating Learning through Work: The Development of the 'Provider Learning Environment Scale'" (ED503392). It provides readers with a complete copy of the "Provider Learning Environment Scale" (version 2.0); and an accompanying user…