Biologically-inspired adaptive obstacle negotiation behavior of hexapod robots

PubMed Central

Goldschmidt, Dennis; Wörgötter, Florentin; Manoonpong, Poramate

2014-01-01

Neurobiological studies have shown that insects are able to adapt leg movements and posture for obstacle negotiation in changing environments. Moreover, the distance to an obstacle where an insect begins to climb is found to be a major parameter for successful obstacle negotiation. Inspired by these findings, we present an adaptive neural control mechanism for obstacle negotiation behavior in hexapod robots. It combines locomotion control, backbone joint control, local leg reflexes, and neural learning. While the first three components generate locomotion including walking and climbing, the neural learning mechanism allows the robot to adapt its behavior for obstacle negotiation with respect to changing conditions, e.g., variable obstacle heights and different walking gaits. By successfully learning the association of an early, predictive signal (conditioned stimulus, CS) and a late, reflex signal (unconditioned stimulus, UCS), both provided by ultrasonic sensors at the front of the robot, the robot can autonomously find an appropriate distance from an obstacle to initiate climbing. The adaptive neural control was developed and tested first on a physical robot simulation, and was then successfully transferred to a real hexapod robot, called AMOS II. The results show that the robot can efficiently negotiate obstacles with a height up to 85% of the robot's leg length in simulation and 75% in a real environment. PMID:24523694

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.…

Teacher Report versus Adaptive Behavior Scale in Assessment of Mental Retardation.

ERIC Educational Resources Information Center

Al-Ansari, Ahmed

1993-01-01

This study assessed the degree of agreement between teacher report and an adapted Adaptive Behavior Scale in the identification of mental retardation and associated learning difficulties in 257 young Bahraini school children. Findings indicated that the instrument is sensitive in identification of children with mental retardation and exhibits high…

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

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.

Vineland-II adaptive behavior profile of children with attention-deficit/hyperactivity disorder or specific learning disorders.

PubMed

Balboni, Giulia; Incognito, Oriana; Belacchi, Carmen; Bonichini, Sabrina; Cubelli, Roberto

2017-02-01

The evaluation of adaptive behavior is informative in children with attention-deficit/hyperactivity disorder (ADHD) or specific learning disorders (SLD). However, the few investigations available have focused only on the gross level of domains of adaptive behavior. To investigate which item subsets of the Vineland-II can discriminate children with ADHD or SLD from peers with typical development. Student's t-tests, ROC analysis, logistic regression, and linear discriminant function analysis were used to compare 24 children with ADHD, 61 elementary students with SLD, and controls matched on age, sex, school level attended, and both parents' education level. Several item subsets that address not only ADHD core symptoms, but also understanding in social context and development of interpersonal relationships, allowed discrimination of children with ADHD from controls. The combination of four item subsets (Listening and attending, Expressing complex ideas, Social communication, and Following instructions) classified children with ADHD with both sensitivity and specificity of 87.5%. Only Reading skills, Writing skills, and Time and dates discriminated children with SLD from controls. Evaluation of Vineland-II scores at the level of item content categories is a useful procedure for an efficient clinical description. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identifying Students' Characteristic Learning Behaviors in an Intelligent Tutoring System Fostering Self-Regulated Learning

ERIC Educational Resources Information Center

Bouchet, Francois; Azevedo, Roger; Kinnebrew, John S.; Biswas, Gautam

2012-01-01

Identification of student learning behaviors, especially those that characterize or distinguish students, can yield important insights for the design of adaptation and feedback mechanisms in Intelligent Tutoring Systems (ITS). In this paper, we analyze trace data to identify distinguishing patterns of behavior in a study of 51 college students…

Adaptive Learning in Psychology: Wayfinding in the Digital Age

ERIC Educational Resources Information Center

Dziuban, Charles D.; Moskal, Patsy D.; Cassisi, Jeffrey; Fawcett, Alexis

2016-01-01

This paper presents the results of a pilot study investigating the use of the Realizeit adaptive learning platform to deliver a fully online General Psychology course across two semesters. Through mutual cooperation, UCF and vendor (CCKF) researchers examined students' affective, behavioral, and cognitive reactions to the system. Student survey…

From modulated Hebbian plasticity to simple behavior learning through noise and weight saturation.

PubMed

Soltoggio, Andrea; Stanley, Kenneth O

2012-10-01

Synaptic plasticity is a major mechanism for adaptation, learning, and memory. Yet current models struggle to link local synaptic changes to the acquisition of behaviors. The aim of this paper is to demonstrate a computational relationship between local Hebbian plasticity and behavior learning by exploiting two traditionally unwanted features: neural noise and synaptic weight saturation. A modulation signal is employed to arbitrate the sign of plasticity: when the modulation is positive, the synaptic weights saturate to express exploitative behavior; when it is negative, the weights converge to average values, and neural noise reconfigures the network's functionality. This process is demonstrated through simulating neural dynamics in the autonomous emergence of fearful and aggressive navigating behaviors and in the solution to reward-based problems. The neural model learns, memorizes, and modifies different behaviors that lead to positive modulation in a variety of settings. The algorithm establishes a simple relationship between local plasticity and behavior learning by demonstrating the utility of noise and weight saturation. Moreover, it provides a new tool to simulate adaptive behavior, and contributes to bridging the gap between synaptic changes and behavior in neural computation. Copyright © 2012 Elsevier Ltd. All rights reserved.

A Self-Regulated Learning Approach for Children with Learning/Behavior Disorders

ERIC Educational Resources Information Center

Benevento, Joan A.

2004-01-01

This book is designed to be an intervention model based on the concepts of Piaget's study of constructivism. The application of this approach will help children with learning/ behavioral disorders actively participate in a fuller integration of their own psychomotor, affective, and cognitive information processing skills and adaptation. The work…

Complex adaptive behavior and dexterous action

PubMed Central

Harrison, Steven J.; Stergiou, Nicholas

2016-01-01

Dexterous action, as conceptualized by Bernstein in his influential ecological analysis of human behavior, is revealed in the ability to flexibly generate behaviors that are adaptively tailored to the demands of the context in which they are embedded. Conceived as complex adaptive behavior, dexterity depends upon the qualities of robustness and degeneracy, and is supported by the functional complexity of the agent-environment system. Using Bernstein’s and Gibson’s ecological analyses of behavior situated in natural environments as conceptual touchstones, we consider the hypothesis that complex adaptive behavior capitalizes upon general principles of self-organization. Here, we outline a perspective in which the complex interactivity of nervous-system, body, and environment is revealed as an essential resource for adaptive behavior. From this perspective, we consider the implications for interpreting the functionality and dysfunctionality of human behavior. This paper demonstrates that, optimal variability, the topic of this special issue, is a logical consequence of interpreting the functionality of human behavior as complex adaptive behavior. PMID:26375932

Adaptive behavior in young children with neurofibromatosis type 1.

PubMed

Klein-Tasman, Bonita P; Colon, Alina M; Brei, Natalie; van der Fluit, Faye; Casnar, Christina L; Janke, Kelly M; Basel, Donald; Siegel, Dawn H; Walker, Jasmine A

2013-01-01

Neurofibromatosis-1 is the most common single gene disorder affecting 1 in 3000. In children, it is associated not only with physical features but also with attention and learning problems. Research has identified a downward shift in intellectual functioning as well, but to date, there are no published studies about the everyday adaptive behavior of children with NF1. In this study, parental reports of adaptive behavior of 61 children with NF1 ages 3 through 8 were compared to an unaffected contrast group (n = 55) that comprised siblings and community members. Significant group differences in adaptive skills were evident and were largely related to group differences in intellectual functioning. In a subsample of children with average-range intellectual functioning, group differences in parent-reported motor skills were apparent even after controlling statistically for group differences in intellectual functioning. The implications of the findings for the care of children with NF1 are discussed.

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

CACNA1C gene regulates behavioral strategies in operant rule learning.

PubMed

Koppe, Georgia; Mallien, Anne Stephanie; Berger, Stefan; Bartsch, Dusan; Gass, Peter; Vollmayr, Barbara; Durstewitz, Daniel

2017-06-01

Behavioral experiments are usually designed to tap into a specific cognitive function, but animals may solve a given task through a variety of different and individual behavioral strategies, some of them not foreseen by the experimenter. Animal learning may therefore be seen more as the process of selecting among, and adapting, potential behavioral policies, rather than mere strengthening of associative links. Calcium influx through high-voltage-gated Ca2+ channels is central to synaptic plasticity, and altered expression of Cav1.2 channels and the CACNA1C gene have been associated with severe learning deficits and psychiatric disorders. Given this, we were interested in how specifically a selective functional ablation of the Cacna1c gene would modulate the learning process. Using a detailed, individual-level analysis of learning on an operant cue discrimination task in terms of behavioral strategies, combined with Bayesian selection among computational models estimated from the empirical data, we show that a Cacna1c knockout does not impair learning in general but has a much more specific effect: the majority of Cacna1c knockout mice still managed to increase reward feedback across trials but did so by adapting an outcome-based strategy, while the majority of matched controls adopted the experimentally intended cue-association rule. Our results thus point to a quite specific role of a single gene in learning and highlight that much more mechanistic insight could be gained by examining response patterns in terms of a larger repertoire of potential behavioral strategies. The results may also have clinical implications for treating psychiatric disorders.

Adaptive Behavior and Problem Behavior in Young Children with Williams Syndrome

ERIC Educational Resources Information Center

Hahn, Laura J.; Fidler, Deborah J.; Hepburn, Susan L.

2014-01-01

The present study compares the adaptive behavior profile of 18 young children with Williams syndrome (WS) and a developmentally matched group of 19 children with developmental disabilities and examines the relationship between adaptive behavior and problem behaviors in WS. Parents completed the Vineland Adaptive Behavioral Scales--Interview…

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.

Using Learning Labs for Culturally Responsive Positive Behavioral Interventions and Supports

ERIC Educational Resources Information Center

Bal, Aydin; Schrader, Elizabeth M.; Afacan, Kemal; Mawene, Dian

2016-01-01

Culturally responsive positive behavioral interventions and supports (CRPBIS) is a statewide research project designed to renovate behavioral support systems to become more inclusive, adaptive, and supportive for all. The CRPBIS methodology, called "learning lab," provides a research-based process to bring together local stakeholders and…

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.

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

Error-Induced Learning as a Resource-Adaptive Process in Young and Elderly Individuals

NASA Astrophysics Data System (ADS)

Ferdinand, Nicola K.; Weiten, Anja; Mecklinger, Axel; Kray, Jutta

Thorndike described in his law of effect [44] that actions followed by positive events are more likely to be repeated in the future, whereas actions that are followed by negative outcomes are less likely to be repeated. This implies that behavior is evaluated in the light of its potential consequences, and non-reward events (i.e., errors) must be detected for reinforcement learning to take place. In short, humans have to monitor their performance in order to detect and correct errors, and this allows them to successfully adapt their behavior to changing environmental demands and acquire new behavior, i.e., to learn.

Associative learning rapidly establishes neuronal representations of upcoming behavioral choices in crows

PubMed Central

Veit, Lena; Pidpruzhnykova, Galyna; Nieder, Andreas

2015-01-01

The ability to form associations between behaviorally relevant sensory stimuli is fundamental for goal-directed behaviors. We investigated neuronal activity in the telencephalic area nidopallium caudolaterale (NCL) while two crows (Corvus corone) performed a delayed association task. Whereas some paired associates were familiar to the crows, novel associations had to be learned and mapped to the same target stimuli within a single session. We found neurons that prospectively encoded the chosen test item during the delay for both familiar and newly learned associations. These neurons increased their selectivity during learning in parallel with the crows' increased behavioral performance. Thus, sustained activity in the NCL actively processes information for the upcoming behavioral choice. These data provide new insights into memory representations of behaviorally meaningful stimuli in birds, and how such representations are formed during learning. The findings suggest that the NCL plays a role in learning arbitrary associations, a cornerstone of corvids’ remarkable behavioral flexibility and adaptability. PMID:26598669

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.

CACNA1C gene regulates behavioral strategies in operant rule learning

PubMed Central

Berger, Stefan; Bartsch, Dusan; Gass, Peter

2017-01-01

Behavioral experiments are usually designed to tap into a specific cognitive function, but animals may solve a given task through a variety of different and individual behavioral strategies, some of them not foreseen by the experimenter. Animal learning may therefore be seen more as the process of selecting among, and adapting, potential behavioral policies, rather than mere strengthening of associative links. Calcium influx through high-voltage-gated Ca2+ channels is central to synaptic plasticity, and altered expression of Cav1.2 channels and the CACNA1C gene have been associated with severe learning deficits and psychiatric disorders. Given this, we were interested in how specifically a selective functional ablation of the Cacna1c gene would modulate the learning process. Using a detailed, individual-level analysis of learning on an operant cue discrimination task in terms of behavioral strategies, combined with Bayesian selection among computational models estimated from the empirical data, we show that a Cacna1c knockout does not impair learning in general but has a much more specific effect: the majority of Cacna1c knockout mice still managed to increase reward feedback across trials but did so by adapting an outcome-based strategy, while the majority of matched controls adopted the experimentally intended cue-association rule. Our results thus point to a quite specific role of a single gene in learning and highlight that much more mechanistic insight could be gained by examining response patterns in terms of a larger repertoire of potential behavioral strategies. The results may also have clinical implications for treating psychiatric disorders. PMID:28604818

Relevance of a neurophysiological marker of attention allocation for children's learning-related behaviors and academic performance.

PubMed

Willner, Cynthia J; Gatzke-Kopp, Lisa M; Bierman, Karen L; Greenberg, Mark T; Segalowitz, Sidney J

2015-08-01

Learning-related behaviors are important for school success. Socioeconomic disadvantage confers risk for less adaptive learning-related behaviors at school entry, yet substantial variability in school readiness exists within socioeconomically disadvantaged populations. Investigation of neurophysiological systems associated with learning-related behaviors in high-risk populations could illuminate resilience processes. This study examined the relevance of a neurophysiological measure of controlled attention allocation, amplitude of the P3b event-related potential, for learning-related behaviors and academic performance in a sample of socioeconomically disadvantaged kindergarteners. The sample consisted of 239 children from an urban, low-income community, approximately half of whom exhibited behavior problems at school entry (45% aggressive/oppositional; 64% male; 69% African American, 21% Hispanic). Results revealed that higher P3b amplitudes to target stimuli in a go/no-go task were associated with more adaptive learning-related behaviors in kindergarten. Furthermore, children's learning-related behaviors in kindergarten mediated a positive indirect effect of P3b amplitude on growth in academic performance from kindergarten to 1st grade. Given that P3b amplitude reflects attention allocation processes, these findings build on the scientific justification for interventions targeting young children's attention skills in order to promote effective learning-related behaviors and academic achievement within socioeconomically disadvantaged populations. (c) 2015 APA, all rights reserved).

A Network Neuroscience of Human Learning: Potential To Inform Quantitative Theories of Brain and Behavior

PubMed Central

Bassett, Danielle S.; Mattar, Marcelo G.

2017-01-01

Humans adapt their behavior to their external environment in a process often facilitated by learning. Efforts to describe learning empirically can be complemented by quantitative theories that map changes in neurophysiology to changes in behavior. In this review we highlight recent advances in network science that offer a sets of tools and a general perspective that may be particularly useful in understanding types of learning that are supported by distributed neural circuits. We describe recent applications of these tools to neuroimaging data that provide unique insights into adaptive neural processes, the attainment of knowledge, and the acquisition of new skills, forming a network neuroscience of human learning. While promising, the tools have yet to be linked to the well-formulated models of behavior that are commonly utilized in cognitive psychology. We argue that continued progress will require the explicit marriage of network approaches to neuroimaging data and quantitative models of behavior. PMID:28259554

A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior.

PubMed

Bassett, Danielle S; Mattar, Marcelo G

2017-04-01

Humans adapt their behavior to their external environment in a process often facilitated by learning. Efforts to describe learning empirically can be complemented by quantitative theories that map changes in neurophysiology to changes in behavior. In this review we highlight recent advances in network science that offer a sets of tools and a general perspective that may be particularly useful in understanding types of learning that are supported by distributed neural circuits. We describe recent applications of these tools to neuroimaging data that provide unique insights into adaptive neural processes, the attainment of knowledge, and the acquisition of new skills, forming a network neuroscience of human learning. While promising, the tools have yet to be linked to the well-formulated models of behavior that are commonly utilized in cognitive psychology. We argue that continued progress will require the explicit marriage of network approaches to neuroimaging data and quantitative models of behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

Designing an Adaptive Web-Based Learning System Based on Students' Cognitive Styles Identified Online

ERIC Educational Resources Information Center

Lo, Jia-Jiunn; Chan, Ya-Chen; Yeh, Shiou-Wen

2012-01-01

This study developed an adaptive web-based learning system focusing on students' cognitive styles. The system is composed of a student model and an adaptation model. It collected students' browsing behaviors to update the student model for unobtrusively identifying student cognitive styles through a multi-layer feed-forward neural network (MLFF).…

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…

Neurodevelopmental Status and Adaptive Behaviors in Preschool Children with Chronic Kidney Disease

ERIC Educational Resources Information Center

Duquette, Peter J.; Hooper, Stephen R.; Icard, Phil F.; Hower, Sarah J.; Mamak, Eva G.; Wetherington, Crista E.; Gipson, Debbie S.

2009-01-01

This study examines the early neurodevelopmental function of infants and preschool children who have chronic kidney disease (CKD). Fifteen patients with CKD are compared to a healthy control group using the "Mullen Scales of Early Learning" (MSEL) and the "Vineland Adaptive Behavior Scale" (VABS). Multivariate analysis reveals…

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.

Adaptive Semantic and Social Web-based learning and assessment environment for the STEM

NASA Astrophysics Data System (ADS)

Babaie, Hassan; Atchison, Chris; Sunderraman, Rajshekhar

2014-05-01

We are building a cloud- and Semantic Web-based personalized, adaptive learning environment for the STEM fields that integrates and leverages Social Web technologies to allow instructors and authors of learning material to collaborate in semi-automatic development and update of their common domain and task ontologies and building their learning resources. The semi-automatic ontology learning and development minimize issues related to the design and maintenance of domain ontologies by knowledge engineers who do not have any knowledge of the domain. The social web component of the personal adaptive system will allow individual and group learners to interact with each other and discuss their own learning experience and understanding of course material, and resolve issues related to their class assignments. The adaptive system will be capable of representing key knowledge concepts in different ways and difficulty levels based on learners' differences, and lead to different understanding of the same STEM content by different learners. It will adapt specific pedagogical strategies to individual learners based on their characteristics, cognition, and preferences, allow authors to assemble remotely accessed learning material into courses, and provide facilities for instructors to assess (in real time) the perception of students of course material, monitor their progress in the learning process, and generate timely feedback based on their understanding or misconceptions. The system applies a set of ontologies that structure the learning process, with multiple user friendly Web interfaces. These include the learning ontology (models learning objects, educational resources, and learning goal); context ontology (supports adaptive strategy by detecting student situation), domain ontology (structures concepts and context), learner ontology (models student profile, preferences, and behavior), task ontologies, technological ontology (defines devices and places that surround the

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…

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.

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

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.

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…

Information theory of adaptation in neurons, behavior, and mood.

PubMed

Sharpee, Tatyana O; Calhoun, Adam J; Chalasani, Sreekanth H

2014-04-01

The ability to make accurate predictions of future stimuli and consequences of one's actions are crucial for the survival and appropriate decision-making. These predictions are constantly being made at different levels of the nervous system. This is evidenced by adaptation to stimulus parameters in sensory coding, and in learning of an up-to-date model of the environment at the behavioral level. This review will discuss recent findings that actions of neurons and animals are selected based on detailed stimulus history in such a way as to maximize information for achieving the task at hand. Information maximization dictates not only how sensory coding should adapt to various statistical aspects of stimuli, but also that reward function should adapt to match the predictive information from past to future. Copyright © 2013 Elsevier Ltd. All rights reserved.

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…

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

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

Social Learning Theory and Behavioral Therapy: Considering Human Behaviors within the Social and Cultural Context of Individuals and Families.

PubMed

McCullough Chavis, Annie

2011-01-01

This article examines theoretical thoughts of social learning theory and behavioral therapy and their influences on human behavior within a social and cultural context. The article utilizes two case illustrations with applications for consumers. It points out the abundance of research studies concerning the effectiveness of social learning theory, and the paucity of research studies regarding effectiveness and evidence-based practices with diverse groups. Providing a social and cultural context in working with diverse groups with reference to social learning theory adds to the literature for more cultural considerations in adapting the theory to women, African Americans, and diverse groups.

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…

Authoring Adaptive 3D Virtual Learning Environments

ERIC Educational Resources Information Center

Ewais, Ahmed; De Troyer, Olga

2014-01-01

The use of 3D and Virtual Reality is gaining interest in the context of academic discussions on E-learning technologies. However, the use of 3D for learning environments also has drawbacks. One way to overcome these drawbacks is by having an adaptive learning environment, i.e., an environment that dynamically adapts to the learner and the…

Neural correlates of the age-related changes in motor sequence learning and motor adaptation in older adults

PubMed Central

King, Bradley R.; Fogel, Stuart M.; Albouy, Geneviève; Doyon, Julien

2013-01-01

As the world's population ages, a deeper understanding of the relationship between aging and motor learning will become increasingly relevant in basic research and applied settings. In this context, this review aims to address the effects of age on motor sequence learning (MSL) and motor adaptation (MA) with respect to behavioral, neurological, and neuroimaging findings. Previous behavioral research investigating the influence of aging on motor learning has consistently reported the following results. First, the initial acquisition of motor sequences is not altered, except under conditions of increased task complexity. Second, older adults demonstrate deficits in motor sequence memory consolidation. And, third, although older adults demonstrate deficits during the exposure phase of MA paradigms, the aftereffects following removal of the sensorimotor perturbation are similar to young adults, suggesting that the adaptive ability of older adults is relatively intact. This paper will review the potential neural underpinnings of these behavioral results, with a particular emphasis on the influence of age-related dysfunctions in the cortico-striatal system on motor learning. PMID:23616757

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.

[Adaptive behaviour and learning in children with neurodevelopmental disorders (autism spectrum disorders and attention deficit hyperactivity disorder). Effects of executive functioning].

PubMed

Rosello-Miranda, B; Berenguer-Forner, C; Miranda-Casas, A

2018-03-01

Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) present difficulties in adaptive functioning and learning, possibly associated with failures in executive functioning characteristic of both disorders. To analyze the impact of executive functioning in the adaptive behaviors of socialization and daily life and in learning behaviors in children with ASD and children with ADHD. The participants were 124 children matched in age and intellectual quotient: 37 children with typical development, 52 children with ASD and 35 children with ADHD. Parents reported on their children's adaptive behaviors, while teachers provided information on learning behaviors and executive functioning in daily life. There are significant differences between the groups with ASD and ADHD with the typical development group in all domains evaluated. In addition, the group with ASD had worse socialization skills while persistence in learning was more affected in children with ADHD. Finally, the metacognitive index of executive functioning predicted the socialization and persistence of children with ASD. On the other hand, the index of behavioral regulation and the educational level of the parents predicted the socialization skills in children with ADHD. The results highlight the need to include differentiated executive strategies in the intervention of children with ASD and children with ADHD.

Adaptive learning and control for MIMO system based on adaptive dynamic programming.

PubMed

Fu, Jian; He, Haibo; Zhou, Xinmin

2011-07-01

Adaptive dynamic programming (ADP) is a promising research field for design of intelligent controllers, which can both learn on-the-fly and exhibit optimal behavior. Over the past decades, several generations of ADP design have been proposed in the literature, which have demonstrated many successful applications in various benchmarks and industrial applications. While many of the existing researches focus on multiple-inputs-single-output system with steepest descent search, in this paper we investigate a generalized multiple-input-multiple-output (GMIMO) ADP design for online learning and control, which is more applicable to a wide range of practical real-world applications. Furthermore, an improved weight-updating algorithm based on recursive Levenberg-Marquardt methods is presented and embodied in the GMIMO approach to improve its performance. Finally, we test the performance of this approach based on a practical complex system, namely, the learning and control of the tension and height of the looper system in a hot strip mill. Experimental results demonstrate that the proposed approach can achieve effective and robust performance.

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

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

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.

Learning and Behavior

MedlinePlus

... Aggression Sensory Processing Disorder Social Interactions Book: The Psychology of Duchenne (download) Guide: Learning & Behavior (download) Home ❯ ... a teen and adult. Additional Resources Book: The Psychology of Duchenne (download) Education Matters Guide: Learning & Behavior ( ...

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

Patient-Centeredness as Physician Behavioral Adaptability to Patient Preferences.

PubMed

Carrard, Valérie; Schmid Mast, Marianne; Jaunin-Stalder, Nicole; Junod Perron, Noëlle; Sommer, Johanna

2018-05-01

A physician who communicates in a patient-centered way is a physician who adapts his or her communication style to what each patient needs. In order to do so, the physician has to (1) accurately assess each patient's states and traits (interpersonal accuracy) and (2) possess a behavioral repertoire to choose from in order to actually adapt his or her behavior to different patients (behavioral adaptability). Physician behavioral adaptability describes the change in verbal or nonverbal behavior a physician shows when interacting with patients who have different preferences in terms of how the physician should interact with them. We hypothesized that physician behavioral adaptability to their patients' preferences would lead to better patient outcomes and that physician interpersonal accuracy was positively related to behavioral adaptability. To test these hypotheses, we recruited 61 physicians who completed an interpersonal accuracy test before being videotaped during four consultations with different patients. The 244 participating patients indicated their preferences for their physician's interaction style prior to the consultation and filled in a consultation outcomes questionnaire directly after the consultation. We coded the physician's verbal and nonverbal behavior for each of the consultations and compared it to the patients' preferences to obtain a measure of physician behavioral adaptability. Results partially confirmed our hypotheses in that female physicians who adapted their nonverbal (but not their verbal) behavior had patients who reported more positive consultation outcomes. Moreover, the more female physicians were accurate interpersonally, the more they showed verbal and nonverbal behavioral adaptability. For male physicians, more interpersonal accuracy was linked to less nonverbal adaptability.

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.

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.

Development and Standardization of the Diagnostic Adaptive Behavior Scale: Application of Item Response Theory to the Assessment of Adaptive Behavior.

PubMed

Tassé, Marc J; Schalock, Robert L; Thissen, David; Balboni, Giulia; Bersani, Henry Hank; Borthwick-Duffy, Sharon A; Spreat, Scott; Widaman, Keith F; Zhang, Dalun; Navas, Patricia

2016-03-01

The Diagnostic Adaptive Behavior Scale (DABS) was developed using item response theory (IRT) methods and was constructed to provide the most precise and valid adaptive behavior information at or near the cutoff point of making a decision regarding a diagnosis of intellectual disability. The DABS initial item pool consisted of 260 items. Using IRT modeling and a nationally representative standardization sample, the item set was reduced to 75 items that provide the most precise adaptive behavior information at the cutoff area determining the presence or not of significant adaptive behavior deficits across conceptual, social, and practical skills. The standardization of the DABS is described and discussed.

Taking Aim at the Cognitive Side of Learning in Sensorimotor Adaptation Tasks.

PubMed

McDougle, Samuel D; Ivry, Richard B; Taylor, Jordan A

2016-07-01

Sensorimotor adaptation tasks have been used to characterize processes responsible for calibrating the mapping between desired outcomes and motor commands. Research has focused on how this form of error-based learning takes place in an implicit and automatic manner. However, recent work has revealed the operation of multiple learning processes, even in this simple form of learning. This review focuses on the contribution of cognitive strategies and heuristics to sensorimotor learning, and how these processes enable humans to rapidly explore and evaluate novel solutions to enable flexible, goal-oriented behavior. This new work points to limitations in current computational models, and how these must be updated to describe the conjoint impact of multiple processes in sensorimotor learning. Copyright © 2016 Elsevier Ltd. All rights reserved.

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…

Adaptation of community health worker-delivered behavioral activation for torture survivors in Kurdistan, Iraq.

PubMed

Magidson, J F; Lejuez, C W; Kamal, T; Blevins, E J; Murray, L K; Bass, J K; Bolton, P; Pagoto, S

2015-12-01

Growing evidence supports the use of Western therapies for the treatment of depression, trauma, and stress delivered by community health workers (CHWs) in conflict-affected, resource-limited countries. A recent randomized controlled trial (Bolton et al . 2014 a ) supported the efficacy of two CHW-delivered interventions, cognitive processing therapy (CPT) and brief behavioral activation treatment for depression (BATD), for reducing depressive symptoms and functional impairment among torture survivors in the Kurdish region of Iraq. This study describes the adaptation of the CHW-delivered BATD approach delivered in this trial (Bolton et al .2014 a ), informed by the Assessment-Decision-Administration-Production-Topical experts-Integration-Training-Testing (ADAPT-ITT) framework for intervention adaptation (Wingood & DiClemente, 2008). Cultural modifications, adaptations for low-literacy, and tailored training and supervision for non-specialist CHWs are presented, along with two clinical case examples to illustrate delivery of the adapted intervention in this setting. Eleven CHWs, a study psychiatrist, and the CHW clinical supervisor were trained in BATD. The adaptation process followed the ADAPT-ITT framework and was iterative with significant input from the on-site supervisor and CHWs. Modifications were made to fit Kurdish culture, including culturally relevant analogies, use of stickers for behavior monitoring, cultural modifications to behavioral contracts, and including telephone-delivered sessions to enhance feasibility. BATD was delivered by CHWs in a resource-poor, conflict-affected area in Kurdistan, Iraq, with some important modifications, including low-literacy adaptations, increased cultural relevancy of clinical materials, and tailored training and supervision for CHWs. Barriers to implementation, lessons learned, and recommendations for future efforts to adapt behavioral therapies for resource-limited, conflict-affected areas are discussed.

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…

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…

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.

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.…

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…

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…

OPUS One: An Intelligent Adaptive Learning Environment Using Artificial Intelligence Support

NASA Astrophysics Data System (ADS)

Pedrazzoli, Attilio

2010-06-01

AI based Tutoring and Learning Path Adaptation are well known concepts in e-Learning scenarios today and increasingly applied in modern learning environments. In order to gain more flexibility and to enhance existing e-learning platforms, the OPUS One LMS Extension package will enable a generic Intelligent Tutored Adaptive Learning Environment, based on a holistic Multidimensional Instructional Design Model (PENTHA ID Model), allowing AI based tutoring and adaptation functionality to existing Web-based e-learning systems. Relying on "real time" adapted profiles, it allows content- / course authors to apply a dynamic course design, supporting tutored, collaborative sessions and activities, as suggested by modern pedagogy. The concept presented combines a personalized level of surveillance, learning activity- and learning path adaptation suggestions to ensure the students learning motivation and learning success. The OPUS One concept allows to implement an advanced tutoring approach combining "expert based" e-tutoring with the more "personal" human tutoring function. It supplies the "Human Tutor" with precise, extended course activity data and "adaptation" suggestions based on predefined subject matter rules. The concept architecture is modular allowing a personalized platform configuration.

Adaptive Behavior of Children and Adolescents with Visual Impairments

ERIC Educational Resources Information Center

Papadopoulos, Konstantinos; Metsiou, Katerina; Agaliotis, Ioannis

2011-01-01

The present study explored the total adaptive behavior of children and adolescents with visual impairments, as well as their adaptive behavior in each of the domains of Communication, Daily Living Skills, and Socialization. Moreover, the predictors of the performance and developmental delay in adaptive behavior were investigated. Instrumentation…

Amygdala subsystems and control of feeding behavior by learned cues.

PubMed

Petrovich, Gorica D; Gallagher, Michela

2003-04-01

A combination of behavioral studies and a neural systems analysis approach has proven fruitful in defining the role of the amygdala complex and associated circuits in fear conditioning. The evidence presented in this chapter suggests that this approach is also informative in the study of other adaptive functions that involve the amygdala. In this chapter we present a novel model to study learning in an appetitive context. Furthermore, we demonstrate that long-recognized connections between the amygdala and the hypothalamus play a crucial role in allowing learning to modulate feeding behavior. In the first part we describe a behavioral model for motivational learning. In this model a cue that acquires motivational properties through pairings with food delivery when an animal is hungry can override satiety and promote eating in sated rats. Next, we present evidence that a specific amygdala subsystem (basolateral area) is responsible for allowing such learned cues to control eating (override satiety and promote eating in sated rats). We also show that basolateral amygdala mediates these actions via connectivity with the lateral hypothalamus. Lastly, we present evidence that the amygdalohypothalamic system is specific for the control of eating by learned motivational cues, as it does not mediate another function that depends on intact basolateral amygdala, namely, the ability of a conditioned cue to support new learning based on its acquired value. Knowledge about neural systems through which food-associated cues specifically control feeding behavior provides a defined model for the study of learning. In addition, this model may be informative for understanding mechanisms of maladaptive aspects of learned control of eating that contribute to eating disorders and more moderate forms of overeating.

Modeling choice and reaction time during arbitrary visuomotor learning through the coordination of adaptive working memory and reinforcement learning

PubMed Central

Viejo, Guillaume; Khamassi, Mehdi; Brovelli, Andrea; Girard, Benoît

2015-01-01

Current learning theory provides a comprehensive description of how humans and other animals learn, and places behavioral flexibility and automaticity at heart of adaptive behaviors. However, the computations supporting the interactions between goal-directed and habitual decision-making systems are still poorly understood. Previous functional magnetic resonance imaging (fMRI) results suggest that the brain hosts complementary computations that may differentially support goal-directed and habitual processes in the form of a dynamical interplay rather than a serial recruitment of strategies. To better elucidate the computations underlying flexible behavior, we develop a dual-system computational model that can predict both performance (i.e., participants' choices) and modulations in reaction times during learning of a stimulus–response association task. The habitual system is modeled with a simple Q-Learning algorithm (QL). For the goal-directed system, we propose a new Bayesian Working Memory (BWM) model that searches for information in the history of previous trials in order to minimize Shannon entropy. We propose a model for QL and BWM coordination such that the expensive memory manipulation is under control of, among others, the level of convergence of the habitual learning. We test the ability of QL or BWM alone to explain human behavior, and compare them with the performance of model combinations, to highlight the need for such combinations to explain behavior. Two of the tested combination models are derived from the literature, and the latter being our new proposal. In conclusion, all subjects were better explained by model combinations, and the majority of them are explained by our new coordination proposal. PMID:26379518

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.

Mechanisms of social avoidance learning can explain the emergence of adaptive and arbitrary behavioral traditions in humans.

PubMed

Lindström, Björn; Olsson, Andreas

2015-06-01

Many nonhuman animals preferentially copy the actions of others when the environment contains predation risk or other types of danger. In humans, the role of social learning in avoidance of danger is still unknown, despite the fundamental importance of social learning for complex social behaviors. Critically, many social behaviors, such as cooperation and adherence to religious taboos, are maintained by threat of punishment. However, the psychological mechanisms allowing threat of punishment to generate such behaviors, even when actual punishment is rare or absent, are largely unknown. To address this, we used both computer simulations and behavioral experiments. First, we constructed a model where simulated agents interacted under threat of punishment and showed that mechanisms' (a) tendency to copy the actions of others through social learning, together with (b) the rewarding properties of avoiding a threatening punishment, could explain the emergence, maintenance, and transmission of large-scale behavioral traditions, both when punishment is common and when it is rare or nonexistent. To provide empirical support for our model, including the 2 mechanisms, we conducted 4 experiments, showing that humans, if threatened with punishment, are exceptionally prone to copy and transmit the behavior observed in others. Our results show that humans, similar to many nonhuman animals, use social learning if the environment is perceived as dangerous. We provide a novel psychological and computational basis for a range of human behaviors characterized by the threat of punishment, such as the adherence to cultural norms and religious taboos. (c) 2015 APA, all rights reserved).

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.…

Teacher-Led Design of an Adaptive Learning Environment

ERIC Educational Resources Information Center

Mavroudi, Anna; Hadzilacos, Thanasis; Kalles, Dimitris; Gregoriades, Andreas

2016-01-01

This paper discusses a requirements engineering process that exemplifies teacher-led design in the case of an envisioned system for adaptive learning. Such a design poses various challenges and still remains an open research issue in the field of adaptive learning. Starting from a scenario-based elicitation method, the whole process was highly…

Self-organizing adaptive map: autonomous learning of curves and surfaces from point samples.

PubMed

Piastra, Marco

2013-05-01

Competitive Hebbian Learning (CHL) (Martinetz, 1993) is a simple and elegant method for estimating the topology of a manifold from point samples. The method has been adopted in a number of self-organizing networks described in the literature and has given rise to related studies in the fields of geometry and computational topology. Recent results from these fields have shown that a faithful reconstruction can be obtained using the CHL method only for curves and surfaces. Within these limitations, these findings constitute a basis for defining a CHL-based, growing self-organizing network that produces a faithful reconstruction of an input manifold. The SOAM (Self-Organizing Adaptive Map) algorithm adapts its local structure autonomously in such a way that it can match the features of the manifold being learned. The adaptation process is driven by the defects arising when the network structure is inadequate, which cause a growth in the density of units. Regions of the network undergo a phase transition and change their behavior whenever a simple, local condition of topological regularity is met. The phase transition is eventually completed across the entire structure and the adaptation process terminates. In specific conditions, the structure thus obtained is homeomorphic to the input manifold. During the adaptation process, the network also has the capability to focus on the acquisition of input point samples in critical regions, with a substantial increase in efficiency. The behavior of the network has been assessed experimentally with typical data sets for surface reconstruction, including suboptimal conditions, e.g. with undersampling and noise. Copyright © 2012 Elsevier Ltd. All rights reserved.

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:…

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…

Towards Adaptive Open Learning Environments: Evaluating the Precision of Identifying Learning Styles by Tracking Learners' Behaviours

ERIC Educational Resources Information Center

Fasihuddin, Heba; Skinner, Geoff; Athauda, Rukshan

2017-01-01

Open learning represents a new form of online learning where courses are provided freely online for large numbers of learners. MOOCs are examples of this form of learning. The authors see an opportunity for personalising open learning environments by adapting to learners' learning styles and providing adaptive support to meet individual learner…

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

PubMed

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

2014-05-21

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

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

Control of cognition and adaptive behavior by the GLP/G9a epigenetic suppressor complex

PubMed Central

Schaefer, Anne; Sampath, Srihari C.; Intrator, Adam; Min, Alice; Gertler, Tracy S.; Surmeier, D. James; Tarakhovsky, Alexander; Greengard, Paul

2009-01-01

SUMMARY The genetic basis of cognition and behavioral adaptation to the environment remains poorly understood. Here we demonstrate that the histone methyltransferase complex GLP/G9a controls cognition and adaptive responses in a region-specific fashion in the adult brain. Using conditional mutagenesis in mice, we show that postnatal, neuron-specific deficiency of GLP/G9a leads to de-repression of numerous non-neuronal and neuron progenitor genes in adult neurons. This transcriptional alteration is associated with complex behavioral abnormalities, including defects in learning, motivation and environmental adaptation. The behavioral changes triggered by GLP/G9a deficiency are similar to key symptoms of the human 9q34 mental retardation syndrome that is associated with structural alterations of the GLP gene. The likely causal role of GLP/G9a in mental retardation in mice and humans suggests a key role for the GLP/G9a controlled histone H3K9 di-methylation in regulation of brain function through maintenance of the transcriptional homeostasis in adult neurons. PMID:20005824

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.

A Learning-Style Theory for Understanding Autistic Behaviors

PubMed Central

Qian, Ning; Lipkin, Richard M.

2011-01-01

Understanding autism's ever-expanding array of behaviors, from sensation to cognition, is a major challenge. We posit that autistic and typically developing brains implement different algorithms that are better suited to learn, represent, and process different tasks; consequently, they develop different interests and behaviors. Computationally, a continuum of algorithms exists, from lookup table (LUT) learning, which aims to store experiences precisely, to interpolation (INT) learning, which focuses on extracting underlying statistical structure (regularities) from experiences. We hypothesize that autistic and typical brains, respectively, are biased toward LUT and INT learning, in low- and high-dimensional feature spaces, possibly because of their narrow and broad tuning functions. The LUT style is good at learning relationships that are local, precise, rigid, and contain little regularity for generalization (e.g., the name–number association in a phonebook). However, it is poor at learning relationships that are context dependent, noisy, flexible, and do contain regularities for generalization (e.g., associations between gaze direction and intention, language and meaning, sensory input and interpretation, motor-control signal and movement, and social situation and proper response). The LUT style poorly compresses information, resulting in inefficiency, sensory overload (overwhelm), restricted interests, and resistance to change. It also leads to poor prediction and anticipation, frequent surprises and over-reaction (hyper-sensitivity), impaired attentional selection and switching, concreteness, strong local focus, weak adaptation, and superior and inferior performances on simple and complex tasks. The spectrum nature of autism can be explained by different degrees of LUT learning among different individuals, and in different systems of the same individual. Our theory suggests that therapy should focus on training autistic LUT algorithm to learn regularities

Behavioral and physiological adaptation to repeated chair restraint in rhesus macaques.

PubMed

Ruys, J D; Mendoza, S P; Capitanio, J P; Mason, W A

2004-09-15

Physical restraint is a commonly used procedure when working closely with nonhuman primates. Nonhuman primates show rapid behavioral changes when learning the restraint procedure, and these changes have been taken to reflect behavioral and physiological habituation to the procedure. This study examined the behavioral and adrenocortical responses to repeated physical restraint in a large sample of adult male rhesus monkeys. Subjects showed a decline in behavioral agitation and cortisol concentrations across seven consecutive days of restraint. The changes in adrenocortical responsiveness were also coincident with an increased sensitivity to dexamethasone and a change in early morning basal cortisol secretion. The subjects were restrained for a single session 6 months later, and while the reduction in behavioral agitation was still present, the majority of changes in adrenocortical responsiveness were no longer present. These data show that behavior is not necessarily an indicator of underlying physiological processes and that the reduction of hypothalamic-pituitary-adrenal (HPA) activity with repeated restraint is due to physiological adaptation to high glucocorticoid concentrations and not to psychological habituation to the restraint procedures.

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…

Patterns of Adaptive Behavior in Very Young Children with Autism.

ERIC Educational Resources Information Center

Stone, Wendy L.; Ousley, Opal Y.; Hepburn, Susan L.; Hogan, Kerry L.; Brown, Christia S.

1999-01-01

A study used the Vineland Adaptive Behavior Scales to investigate patterns of adaptive behavior in 30 children with autism who were under 3 years. Relative to controls, participants demonstrated weaker socialization and communication skills and greater discrepancies between adaptive behavior and mental age. The utility of the scales is discussed.…

Adaptive Computerized Instruction.

ERIC Educational Resources Information Center

Ray, Roger D.; And Others

1995-01-01

Describes an artificially intelligent multimedia computerized instruction system capable of developing a conceptual image of what a student is learning while the student is learning it. It focuses on principles of learning and adaptive behavioral control systems theory upon which the system is designed and demonstrates multiple user modes.…

Learners' Perceptions and Illusions of Adaptivity in Computer-Based Learning Environments

ERIC Educational Resources Information Center

Vandewaetere, Mieke; Vandercruysse, Sylke; Clarebout, Geraldine

2012-01-01

Research on computer-based adaptive learning environments has shown exemplary growth. Although the mechanisms of effective adaptive instruction are unraveled systematically, little is known about the relative effect of learners' perceptions of adaptivity in adaptive learning environments. As previous research has demonstrated that the learners'…

Improving Voluntary Environmental Management Programs: Facilitating Learning and Adaptation

NASA Astrophysics Data System (ADS)

Genskow, Kenneth D.; Wood, Danielle M.

2011-05-01

Environmental planners and managers face unique challenges understanding and documenting the effectiveness of programs that rely on voluntary actions by private landowners. Programs, such as those aimed at reducing nonpoint source pollution or improving habitat, intend to reach those goals by persuading landowners to adopt behaviors and management practices consistent with environmental restoration and protection. Our purpose with this paper is to identify barriers for improving voluntary environmental management programs and ways to overcome them. We first draw upon insights regarding data, learning, and adaptation from the adaptive management and performance management literatures, describing three key issues: overcoming information constraints, structural limitations, and organizational culture. Although these lessons are applicable to a variety of voluntary environmental management programs, we then present the issues in the context of on-going research for nonpoint source water quality pollution. We end the discussion by highlighting important elements for advancing voluntary program efforts.

Executive Function and Adaptive Behavior in Muenke Syndrome.

PubMed

Yarnell, Colin M P; Addissie, Yonit A; Hadley, Donald W; Guillen Sacoto, Maria J; Agochukwu, Nneamaka B; Hart, Rachel A; Wiggs, Edythe A; Platte, Petra; Paelecke, Yvonne; Collmann, Hartmut; Schweitzer, Tilmann; Kruszka, Paul; Muenke, Maximilian

2015-08-01

To investigate executive function and adaptive behavior in individuals with Muenke syndrome using validated instruments with a normative population and unaffected siblings as controls. Participants in this cross-sectional study included individuals with Muenke syndrome (P250R mutation in FGFR3) and their mutation-negative siblings. Participants completed validated assessments of executive functioning (Behavior Rating Inventory of Executive Function [BRIEF]) and adaptive behavior skills (Adaptive Behavior Assessment System, Second Edition [ABAS-II]). Forty-four with a positive FGFR3 mutation, median age 9 years, range 7 months to 52 years were enrolled. In addition, 10 unaffected siblings served as controls (5 males, 5 females; median age, 13 years; range, 3-18 years). For the General Executive Composite scale of the BRIEF, 32.1% of the cohort had scores greater than +1.5 SD, signifying potential clinical significance. For the General Adaptive Composite of the ABAS-II, 28.2% of affected individuals scored in the 3rd-8th percentile of the normative population, and 56.4% were below the average category (<25th percentile). Multiple regression analysis did not identify craniosynostosis as a predictor of BRIEF (P = .70) or ABAS-II scores (P = .70). In the sibling pair analysis, affected siblings performed significantly poorer on the BRIEF General Executive Composite and the ABAS-II General Adaptive Composite. Individuals with Muenke syndrome are at an increased risk for developing adaptive and executive function behavioral changes compared with a normative population and unaffected siblings. Published by Elsevier Inc.

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…

Neural Dynamics of Autistic Repetitive Behaviors and Fragile X Syndrome: Basal Ganglia Movement Gating and mGluR-Modulated Adaptively Timed Learning.

PubMed

Grossberg, Stephen; Kishnan, Devika

2018-01-01

This article develops the iSTART neural model that proposes how specific imbalances in cognitive, emotional, timing, and motor processes that involve brain regions like prefrontal cortex, temporal cortex, amygdala, hypothalamus, hippocampus, and cerebellum may interact together to cause behavioral symptoms of autism. These imbalances include underaroused emotional depression in the amygdala/hypothalamus, learning of hyperspecific recognition categories that help to cause narrowly focused attention in temporal and prefrontal cortices, and breakdowns of adaptively timed motivated attention and motor circuits in the hippocampus and cerebellum. The article expands the model's explanatory range by, first, explaining recent data about Fragile X syndrome (FXS), mGluR, and trace conditioning; and, second, by explaining distinct causes of stereotyped behaviors in individuals with autism. Some of these stereotyped behaviors, such as an insistence on sameness and circumscribed interests, may result from imbalances in the cognitive and emotional circuits that iSTART models. These behaviors may be ameliorated by operant conditioning methods. Other stereotyped behaviors, such as repetitive motor behaviors, may result from imbalances in how the direct and indirect pathways of the basal ganglia open or close movement gates, respectively. These repetitive behaviors may be ameliorated by drugs that augment D2 dopamine receptor responses or reduce D1 dopamine receptor responses. The article also notes the ubiquitous role of gating by basal ganglia loops in regulating all the functions that iSTART models.

Development and Standardization of the Diagnostic Adaptive Behavior Scale: Application of Item Response Theory to the Assessment of Adaptive Behavior

ERIC Educational Resources Information Center

Tassé, Marc J.; Schalock, Robert L.; Thissen, David; Balboni, Giulia; Bersani, Henry, Jr.; Borthwick-Duffy, Sharon A.; Spreat, Scott; Widaman, Keith F.; Zhang, Dalun; Navas, Patricia

2016-01-01

The Diagnostic Adaptive Behavior Scale (DABS) was developed using item response theory (IRT) methods and was constructed to provide the most precise and valid adaptive behavior information at or near the cutoff point of making a decision regarding a diagnosis of intellectual disability. The DABS initial item pool consisted of 260 items. Using IRT…

Online EEG-Based Workload Adaptation of an Arithmetic Learning Environment.

PubMed

Walter, Carina; Rosenstiel, Wolfgang; Bogdan, Martin; Gerjets, Peter; Spüler, Martin

2017-01-01

In this paper, we demonstrate a closed-loop EEG-based learning environment, that adapts instructional learning material online, to improve learning success in students during arithmetic learning. The amount of cognitive workload during learning is crucial for successful learning and should be held in the optimal range for each learner. Based on EEG data from 10 subjects, we created a prediction model that estimates the learner's workload to obtain an unobtrusive workload measure. Furthermore, we developed an interactive learning environment that uses the prediction model to estimate the learner's workload online based on the EEG data and adapt the difficulty of the learning material to keep the learner's workload in an optimal range. The EEG-based learning environment was used by 13 subjects to learn arithmetic addition in the octal number system, leading to a significant learning effect. The results suggest that it is feasible to use EEG as an unobtrusive measure of cognitive workload to adapt the learning content. Further it demonstrates that a promptly workload prediction is possible using a generalized prediction model without the need for a user-specific calibration.

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.

Criticality as a Set-Point for Adaptive Behavior in Neuromorphic Hardware

PubMed Central

Srinivasa, Narayan; Stepp, Nigel D.; Cruz-Albrecht, Jose

2015-01-01

Neuromorphic hardware are designed by drawing inspiration from biology to overcome limitations of current computer architectures while forging the development of a new class of autonomous systems that can exhibit adaptive behaviors. Several designs in the recent past are capable of emulating large scale networks but avoid complexity in network dynamics by minimizing the number of dynamic variables that are supported and tunable in hardware. We believe that this is due to the lack of a clear understanding of how to design self-tuning complex systems. It has been widely demonstrated that criticality appears to be the default state of the brain and manifests in the form of spontaneous scale-invariant cascades of neural activity. Experiment, theory and recent models have shown that neuronal networks at criticality demonstrate optimal information transfer, learning and information processing capabilities that affect behavior. In this perspective article, we argue that understanding how large scale neuromorphic electronics can be designed to enable emergent adaptive behavior will require an understanding of how networks emulated by such hardware can self-tune local parameters to maintain criticality as a set-point. We believe that such capability will enable the design of truly scalable intelligent systems using neuromorphic hardware that embrace complexity in network dynamics rather than avoiding it. PMID:26648839

Longitudinal Profiles of Adaptive Behavior in Fragile X Syndrome

PubMed Central

Quintin, Eve-Marie; Jo, Booil; Lightbody, Amy A.; Hazlett, Heather Cody; Piven, Joseph; Hall, Scott S.; Reiss, Allan L.

2014-01-01

OBJECTIVE: To examine longitudinally the adaptive behavior patterns in fragile X syndrome. METHOD: Caregivers of 275 children and adolescents with fragile X syndrome and 225 typically developing children and adolescents (2–18 years) were interviewed with the Vineland Adaptive Behavior Scales every 2 to 4 years as part of a prospective longitudinal study. RESULTS: Standard scores of adaptive behavior in people with fragile X syndrome are marked by a significant decline over time in all domains for males and in communication for females. Socialization skills are a relative strength as compared with the other domains for males with fragile X syndrome. Females with fragile X syndrome did not show a discernible pattern of developmental strengths and weaknesses. CONCLUSIONS: This is the first large-scale longitudinal study to show that the acquisition of adaptive behavior slows as individuals with fragile X syndrome age. It is imperative to ensure that assessments of adaptive behavior skills are part of intervention programs focusing on childhood and adolescence in this condition. PMID:25070318

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…

Cross-National Assessment of Adaptive Behavior in Three Countries

ERIC Educational Resources Information Center

Oakland, Thomas; Iliescu, Dragos; Chen, Hsin-Yi; Chen, Juliet Honglei

2013-01-01

Measures of adaptive behaviors provide an important tool in the repertoire of clinical and school/educational psychologists. Measures that assess adaptive behaviors typically have been built in Western cultures and developed in light of behaviors common to them. Nevertheless, these measures are used elsewhere despite a paucity of data that examine…

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.

Industry Cluster's Adaptive Co-competition Behavior Modeling Inspired by Swarm Intelligence

NASA Astrophysics Data System (ADS)

Xiang, Wei; Ye, Feifan

Adaptation helps the individual enterprise to adjust its behavior to uncertainties in environment and hence determines a healthy growth of both the individuals and the whole industry cluster as well. This paper is focused on the study on co-competition adaptation behavior of industry cluster, which is inspired by swarm intelligence mechanisms. By referencing to ant cooperative transportation and ant foraging behavior and their related swarm intelligence approaches, the cooperative adaptation and competitive adaptation behavior are studied and relevant models are proposed. Those adaptive co-competition behaviors model can be integrated to the multi-agent system of industry cluster to make the industry cluster model more realistic.

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…

Adapting Phonological Awareness Interventions for Children with Down Syndrome Based on the Behavioral Phenotype: A Promising Approach?

ERIC Educational Resources Information Center

Lemons, Christopher J.; King, Seth A.; Davidson, Kimberly A.; Puranik, Cynthia S.; Fulmer, Deborah; Mrachko, Alicia A.; Partanen, Jane; Al Otaiba, Stephanie; Fidler, Deborah J.

2015-01-01

Many children with Down syndrome demonstrate deficits in phonological awareness, a prerequisite to learning to read in an alphabetic language. The purpose of this study was to determine whether adapting a commercially available phonological awareness program to better align with characteristics associated with the behavioral phenotype of Down…

A Context-Adaptive Teacher Training Model in a Ubiquitous Learning Environment

ERIC Educational Resources Information Center

Chen, Min; Chiang, Feng Kuang; Jiang, Ya Na; Yu, Sheng Quan

2017-01-01

In view of the discrepancies in teacher training and teaching practice, this paper put forward a context-adaptive teacher training model in a ubiquitous learning (u-learning) environment. The innovative model provides teachers of different subjects with adaptive and personalized learning content in a u-learning environment, implements intra- and…

Implication of Dopaminergic Modulation in Operant Reward Learning and the Induction of Compulsive-Like Feeding Behavior in "Aplysia"

ERIC Educational Resources Information Center

Bedecarrats, Alexis; Cornet, Charles; Simmers, John; Nargeot, Romuald

2013-01-01

Feeding in "Aplysia" provides an amenable model system for analyzing the neuronal substrates of motivated behavior and its adaptability by associative reward learning and neuromodulation. Among such learning processes, appetitive operant conditioning that leads to a compulsive-like expression of feeding actions is known to be associated…

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…

A Model for the Transfer of Perceptual-Motor Skill Learning in Human Behaviors

ERIC Educational Resources Information Center

Rosalie, Simon M.; Muller, Sean

2012-01-01

This paper presents a preliminary model that outlines the mechanisms underlying the transfer of perceptual-motor skill learning in sport and everyday tasks. Perceptual-motor behavior is motivated by performance demands and evolves over time to increase the probability of success through adaptation. Performance demands at the time of an event…

Learning Behaviors and Learning Spaces

ERIC Educational Resources Information Center

Bennett, Scott

2011-01-01

What specific learning behaviors are important to students and faculty members? Does the campus provide spaces that foster these behaviors? Where are those spaces? Asking these three questions at six colleges and universities reveals notable differences in the ways students and faculty members answer them. Student and faculty member answers also…

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.…

Behavioral and neural Darwinism: selectionist function and mechanism in adaptive behavior dynamics.

PubMed

McDowell, J J

2010-05-01

An evolutionary theory of behavior dynamics and a theory of neuronal group selection share a common selectionist framework. The theory of behavior dynamics instantiates abstractly the idea that behavior is selected by its consequences. It implements Darwinian principles of selection, reproduction, and mutation to generate adaptive behavior in virtual organisms. The behavior generated by the theory has been shown to be quantitatively indistinguishable from that of live organisms. The theory of neuronal group selection suggests a mechanism whereby the abstract principles of the evolutionary theory may be implemented in the nervous systems of biological organisms. According to this theory, groups of neurons subserving behavior may be selected by synaptic modifications that occur when the consequences of behavior activate value systems in the brain. Together, these theories constitute a framework for a comprehensive account of adaptive behavior that extends from brain function to the behavior of whole organisms in quantitative detail. Copyright (c) 2009 Elsevier B.V. All rights reserved.

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…

Web-Based Instruction, Learning Effectiveness and Learning Behavior: The Impact of Relatedness

ERIC Educational Resources Information Center

Shieh, Chich-Jen; Liao, Ying; Hu, Ridong

2013-01-01

This study aims to discuss the effects of Web-based Instruction and Learning Behavior on Learning Effectiveness. Web-based Instruction contains the dimensions of Active Learning, Simulation-based Learning, Interactive Learning, and Accumulative Learning; and, Learning Behavior covers Learning Approach, Learning Habit, and Learning Attitude. The…

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.

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…

Neural Dynamics of Autistic Repetitive Behaviors and Fragile X Syndrome: Basal Ganglia Movement Gating and mGluR-Modulated Adaptively Timed Learning

PubMed Central

Grossberg, Stephen; Kishnan, Devika

2018-01-01

This article develops the iSTART neural model that proposes how specific imbalances in cognitive, emotional, timing, and motor processes that involve brain regions like prefrontal cortex, temporal cortex, amygdala, hypothalamus, hippocampus, and cerebellum may interact together to cause behavioral symptoms of autism. These imbalances include underaroused emotional depression in the amygdala/hypothalamus, learning of hyperspecific recognition categories that help to cause narrowly focused attention in temporal and prefrontal cortices, and breakdowns of adaptively timed motivated attention and motor circuits in the hippocampus and cerebellum. The article expands the model’s explanatory range by, first, explaining recent data about Fragile X syndrome (FXS), mGluR, and trace conditioning; and, second, by explaining distinct causes of stereotyped behaviors in individuals with autism. Some of these stereotyped behaviors, such as an insistence on sameness and circumscribed interests, may result from imbalances in the cognitive and emotional circuits that iSTART models. These behaviors may be ameliorated by operant conditioning methods. Other stereotyped behaviors, such as repetitive motor behaviors, may result from imbalances in how the direct and indirect pathways of the basal ganglia open or close movement gates, respectively. These repetitive behaviors may be ameliorated by drugs that augment D2 dopamine receptor responses or reduce D1 dopamine receptor responses. The article also notes the ubiquitous role of gating by basal ganglia loops in regulating all the functions that iSTART models. PMID:29593596

Sensorimotor Learning Biases Choice Behavior: A Learning Neural Field Model for Decision Making

PubMed Central

Schöner, Gregor; Gail, Alexander

2012-01-01

According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making) should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action selection required for

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.

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

Adaptive Behavior of Young Urban Children with Developmental Disabilities.

ERIC Educational Resources Information Center

Vig, Susan; Jedrysek, Eleonora

1995-01-01

Assessment of 497 urban preschool children with developmental disabilities using the Vineland Adaptive Behavior Scales indicated a strong positive relationship between adaptive behavior and intelligence if measured globally. When Vineland domains were assessed separately, this relationship varied across domains and disability groups. With…

Adaptive Controller Effects on Pilot Behavior

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Gregory, Irene M.; Hempley, Lucas E.

2014-01-01

Adaptive control provides robustness and resilience for highly uncertain, and potentially unpredictable, flight dynamics characteristic. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the software adaptive control system and the pilot. An experiment was conducted to categorize these interactions on the pilot with an adaptive controller during control surface failures. One of the objectives of this experiment was to determine how the adaptation time of the controller affects pilots. The pitch and roll errors, and stick input increased for increasing adaptation time and during the segment when the adaptive controller was adapting. Not surprisingly, altitude, cross track and angle deviations, and vertical velocity also increase during the failure and then slowly return to pre-failure levels. Subjects may change their behavior even as an adaptive controller is adapting with additional stick inputs. Therefore, the adaptive controller should adapt as fast as possible to minimize flight track errors. This will minimize undesirable interactions between the pilot and the adaptive controller and maintain maneuvering precision.

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…

Assessing heat-adaptive behaviors among older, urban-dwelling adults

PubMed Central

White-Newsome, Jalonne L.; Sánchez, Brisa N.; Parker, Edith A.; Dvonch, J. Timothy; Zhang, Zhenzhen; O’Neill, Marie S.

2015-01-01

Objectives Health studies have shown that the elderly are at a greater risk to extreme heat. The frequency and intensity of summer heat waves will continue to increase as a result of climate change. It is important that we understand the environmental and structural factors that increase heat vulnerability, as well as examine the behaviors used by the elderly to adapt to hot indoor temperatures. Study design From June 1 to August 31, 2009, residents in 29 homes in Detroit, MI, kept an hourly log of eight heat-adaptive behaviors: opening windows/doors, turning fans or the air conditioner on, changing clothes, taking a shower, going to the basement, the porch/yard, or leaving the house. Percentages of hourly behavior were calculated, overall and stratified by housing type and percent surface imperviousness. The frequency of behavior use, as a result of indoor and outdoor predetermined temperature intervals was compared to a reference temperature range of 21.1–23.8 °C. Results The use of all adaptive behaviors, except going to the porch or yard, was significantly associated with indoor temperature. Non-mechanical adaptations such as changing clothes, taking showers, and going outside or to the basement were rarely used. Residents living in high-rises and highly impervious areas reported a higher use of adaptive behaviors. The odds of leaving the house significantly increased as outdoor temperature increased. Conclusions These findings suggest that the full range of heat adaptation measures may be underused by the elderly and public health interventions need to focus on outreach to these populations. PMID:21782363

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.

Grounding the Meanings in Sensorimotor Behavior using Reinforcement Learning

PubMed Central

Farkaš, Igor; Malík, Tomáš; Rebrová, Kristína

2012-01-01

The recent outburst of interest in cognitive developmental robotics is fueled by the ambition to propose ecologically plausible mechanisms of how, among other things, a learning agent/robot could ground linguistic meanings in its sensorimotor behavior. Along this stream, we propose a model that allows the simulated iCub robot to learn the meanings of actions (point, touch, and push) oriented toward objects in robot’s peripersonal space. In our experiments, the iCub learns to execute motor actions and comment on them. Architecturally, the model is composed of three neural-network-based modules that are trained in different ways. The first module, a two-layer perceptron, is trained by back-propagation to attend to the target position in the visual scene, given the low-level visual information and the feature-based target information. The second module, having the form of an actor-critic architecture, is the most distinguishing part of our model, and is trained by a continuous version of reinforcement learning to execute actions as sequences, based on a linguistic command. The third module, an echo-state network, is trained to provide the linguistic description of the executed actions. The trained model generalizes well in case of novel action-target combinations with randomized initial arm positions. It can also promptly adapt its behavior if the action/target suddenly changes during motor execution. PMID:22393319

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…

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…

Linking Individual and Collective Behavior in Adaptive Social Networks

NASA Astrophysics Data System (ADS)

Pinheiro, Flávio L.; Santos, Francisco C.; Pacheco, Jorge M.

2016-03-01

Adaptive social structures are known to promote the evolution of cooperation. However, up to now the characterization of the collective, population-wide dynamics resulting from the self-organization of individual strategies on a coevolving, adaptive network has remained unfeasible. Here we establish a (reversible) link between individual (micro)behavior and collective (macro)behavior for coevolutionary processes. We demonstrate that an adaptive network transforms a two-person social dilemma locally faced by individuals into a collective dynamics that resembles that associated with an N -person coordination game, whose characterization depends sensitively on the relative time scales between the entangled behavioral and network evolutions. In particular, we show that the faster the relative rate of adaptation of the network, the smaller the critical fraction of cooperators required for cooperation to prevail, thus establishing a direct link between network adaptation and the evolution of cooperation. The framework developed here is general and may be readily applied to other dynamical processes occurring on adaptive networks, notably, the spreading of contagious diseases or the diffusion of innovations.

Differential roles of nonsynaptic and synaptic plasticity in operant reward learning-induced compulsive behavior.

PubMed

Sieling, Fred; Bédécarrats, Alexis; Simmers, John; Prinz, Astrid A; Nargeot, Romuald

2014-05-05

Rewarding stimuli in associative learning can transform the irregularly and infrequently generated motor patterns underlying motivated behaviors into output for accelerated and stereotyped repetitive action. This transition to compulsive behavioral expression is associated with modified synaptic and membrane properties of central neurons, but establishing the causal relationships between cellular plasticity and motor adaptation has remained a challenge. We found previously that changes in the intrinsic excitability and electrical synapses of identified neurons in Aplysia's central pattern-generating network for feeding are correlated with a switch to compulsive-like motor output expression induced by in vivo operant conditioning. Here, we used specific computer-simulated ionic currents in vitro to selectively replicate or suppress the membrane and synaptic plasticity resulting from this learning. In naive in vitro preparations, such experimental manipulation of neuronal membrane properties alone increased the frequency but not the regularity of feeding motor output found in preparations from operantly trained animals. On the other hand, changes in synaptic strength alone switched the regularity but not the frequency of feeding output from naive to trained states. However, simultaneously imposed changes in both membrane and synaptic properties reproduced both major aspects of the motor plasticity. Conversely, in preparations from trained animals, experimental suppression of the membrane and synaptic plasticity abolished the increase in frequency and regularity of the learned motor output expression. These data establish direct causality for the contributions of distinct synaptic and nonsynaptic adaptive processes to complementary facets of a compulsive behavior resulting from operant reward learning. Copyright © 2014 Elsevier Ltd. All rights reserved.

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…

Brief Report: Developmental Trajectories of Adaptive Behavior in Children and Adolescents with ASD.

PubMed

Meyer, Allison T; Powell, Patrick S; Butera, Nicole; Klinger, Mark R; Klinger, Laura G

2018-03-17

Research suggests that individuals with autism spectrum disorder (ASD) have significant difficulties with adaptive behavior skills including daily living and functional communication skills. Few studies have examined the developmental trajectory of adaptive behavior across childhood and adolescence. The present study examined longitudinal trajectories of adaptive behavior in a community-based clinic sample of 186 individuals with ASD. The overall pattern indicated an initial increase in adaptive behavior during early childhood followed by a plateau in skills during adolescence for individuals of all IQ groups. Given the importance of adaptive behavior for employment and quality of life, this study emphasizes the importance of targeting adaptive behavior during adolescence to insure continued gains.

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

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…

Allergies and Learning/Behavioral Disorders.

ERIC Educational Resources Information Center

McLoughlin, James A.; Nall, Michael

1994-01-01

This article describes various types of allergies, how they are diagnosed medically, and the different forms of medical treatment. It also considers how allergies may affect school learning and behavior, the connection between allergies and learning and behavioral disorders, the impact of allergy medications upon classroom performance, and various…

Trust-based learning and behaviors for convoy obstacle avoidance

NASA Astrophysics Data System (ADS)

Mikulski, Dariusz G.; Karlsen, Robert E.

2015-05-01

In many multi-agent systems, robots within the same team are regarded as being fully trustworthy for cooperative tasks. However, the assumption of trustworthiness is not always justified, which may not only increase the risk of mission failure, but also endanger the lives of friendly forces. In prior work, we addressed this issue by using RoboTrust to dynamically adjust to observed behaviors or recommendations in order to mitigate the risks of illegitimate behaviors. However, in the simulations in prior work, all members of the convoy had knowledge of the convoy goal. In this paper, only the lead vehicle has knowledge of the convoy goals and the follow vehicles must infer trustworthiness strictly from lead vehicle performance. In addition, RoboTrust could only respond to observed performance and did not dynamically learn agent behavior. In this paper, we incorporate an adaptive agent-specific bias into the RoboTrust algorithm that modifies its trust dynamics. This bias is learned incrementally from agent interactions, allowing good agents to benefit from faster trust growth and slower trust decay and bad agents to be penalized with slower trust growth and faster trust decay. We then integrate this new trust model into a trust-based controller for decentralized autonomous convoy operations. We evaluate its performance in an obstacle avoidance mission, where the convoy attempts to learn the best speed and following distances combinations for an acceptable obstacle avoidance probability.

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…

[Effects of family cohesion and adaptability on behavioral problems in preschool children].

PubMed

Wang, Yan-Ni; Xue, Hong-Li; Chen, Qian

2016-05-01

To investigate the effects of family cohesion and adaptability on behavioral problems in preschool children. The stratified cluster multistage sampling method was used to perform a questionnaire survey in the parents of 1 284 children aged 3-6 years in the urban area of Lanzhou, China. The general status questionnaire, Conners Child Behavior Checklist (Parent Symptom Question), and Family Adaptability and Cohesion Scale, Second edition, Chinese version (FACESII-CV) were used to investigate behavioral problems and family cohesion and adaptability. The overall detection rate of behavioral problems in preschool children was 17.13%. The children with different types of family cohesion had different detection rates of behavioral problems, and those with free-type family cohesion showed the highest detection rate of behavioral problems (40.2%). The children with different types of family adaptability also had different detection rates of behavioral problems, and those with stiffness type showed the highest detection rate of behavioral problems (25.1%). The behavioral problems in preschool children were negatively correlated with family cohesion and adaptability. During the growth of preschool children, family cohesion and adaptability have certain effects on the mental development of preschool children.

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.

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.

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).

An adaptive signal-processing approach to online adaptive tutoring.

PubMed

Bergeron, Bryan; Cline, Andrew

2011-01-01

Conventional intelligent or adaptive tutoring online systems rely on domain-specific models of learner behavior based on rules, deep domain knowledge, and other resource-intensive methods. We have developed and studied a domain-independent methodology of adaptive tutoring based on domain-independent signal-processing approaches that obviate the need for the construction of explicit expert and student models. A key advantage of our method over conventional approaches is a lower barrier to entry for educators who want to develop adaptive online learning materials.

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.

Family behavior, adaptation, and treatment adherence of pediatric nephrology patients.

PubMed

Davis, M C; Tucker, C M; Fennell, R S

1996-04-01

In this exploratory study we investigated the relationships among family behavior variables (e.g., family expressiveness), adaptive functioning skills, maladaptive behavior, and adherence to treatment in pediatric renal failure patients. The study included 22 pediatric outpatients with renal failure who had not yet received dialysis or transplantation (RF) and their parents, and 12 pediatric outpatients with kidney transplants (TX) and their parents. For the RF patients, significant correlations were found between some of their adaptive functioning skills and measures of their medication adherence, diet adherence, and clinic appointment adherence; however, for the TX patients significant correlations were found only between some of their adaptive functioning skills and measures of their medication adherence. For the RF patients only, some measures of their family behavior were significantly correlated with measures of their medication adherence and diet adherence. Additionally, some measures of the RF patients' family behavior were significantly related to their communication skills, socialization skills, overall adaptive functioning skills, and maladaptive behavior. For the TX patients, only their socialization skill level was significantly correlated with one measure of their family behavior. It is concluded that facilitation of adaptive and physical functioning among renal pediatric patients likely requires multidimensional training and/or counselling interventions with the children and their families, and that some of the content and/or emphasis of this training likely needs to differ for RF patients versus TX patients.

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…

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…

Adaptive behaviors in multi-agent source localization using passive sensing.

PubMed

Shaukat, Mansoor; Chitre, Mandar

2016-12-01

In this paper, the role of adaptive group cohesion in a cooperative multi-agent source localization problem is investigated. A distributed source localization algorithm is presented for a homogeneous team of simple agents. An agent uses a single sensor to sense the gradient and two sensors to sense its neighbors. The algorithm is a set of individualistic and social behaviors where the individualistic behavior is as simple as an agent keeping its previous heading and is not self-sufficient in localizing the source. Source localization is achieved as an emergent property through agent's adaptive interactions with the neighbors and the environment. Given a single agent is incapable of localizing the source, maintaining team connectivity at all times is crucial. Two simple temporal sampling behaviors, intensity-based-adaptation and connectivity-based-adaptation, ensure an efficient localization strategy with minimal agent breakaways. The agent behaviors are simultaneously optimized using a two phase evolutionary optimization process. The optimized behaviors are estimated with analytical models and the resulting collective behavior is validated against the agent's sensor and actuator noise, strong multi-path interference due to environment variability, initialization distance sensitivity and loss of source signal.

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.

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

A Behavioral and Genetic Dissection of Two Forms of Olfactory Plasticity in Caenorhabditis elegans: Adaptation and Habituation

PubMed Central

Bernhard, Nirit; van der Kooy, Derek

2000-01-01

Continuous presentation of an olfactory stimulus causes a decrement of the chemotaxis response in the nematode Caenorhabditis elegans. However, the differences between the learning process of habituation (a readily reversible decrease in behavioral response) and other types of olfactory plasticity such as adaptation (a decrement in response due to sensory fatigue, which cannot be dishabituated) have not been addressed. The volatile odorant diacetyl (DA) was used within a single paradigm to assess the distinct processes of olfactory adaptation and habituation. Preexposing and testing worms to 100% DA vapors caused a chemotaxis decrement that was not reversible despite the presentation of potentially dishabituating stimuli. This DA adaptation was abolished in worms with an odr-10 mutation (encoding a high-affinity DA receptor on the AWA neuron), even though naive chemotaxis remained unaffected. Conversely, DA adaptation remained intact in odr-1 mutants (defective in AWC neuron-mediated olfactory behavior), even though naive chemotaxis to DA decreased. Surprisingly, exposure to vapors of intermediate concentrations of DA (0.01% and 25%) did not cause worms to exhibit any response decrement. In contrast to preexposure to high DA concentrations, preexposure to low DA concentrations (0.001%) produced habituation of the chemotaxis response (a dishabituating stimulus could reverse the response decrement back to baseline levels). The distinct behavioral effects produced by DA preexposure highlight a concentration-dependent dissociation between two decremental olfactory processes: adaptation at high DA concentrations versus habituation at low DA concentrations. PMID:10940320

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…

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.…

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…

Physician behavioral adaptability: A model to outstrip a "one size fits all" approach.

PubMed

Carrard, Valérie; Schmid Mast, Marianne

2015-10-01

Based on a literature review, we propose a model of physician behavioral adaptability (PBA) with the goal of inspiring new research. PBA means that the physician adapts his or her behavior according to patients' different preferences. The PBA model shows how physicians infer patients' preferences and adapt their interaction behavior from one patient to the other. We claim that patients will benefit from better outcomes if their physicians show behavioral adaptability rather than a "one size fits all" approach. This literature review is based on a literature search of the PsycINFO(®) and MEDLINE(®) databases. The literature review and first results stemming from the authors' research support the validity and viability of parts of the PBA model. There is evidence suggesting that physicians are able to show behavioral flexibility when interacting with their different patients, that a match between patients' preferences and physician behavior is related to better consultation outcomes, and that physician behavioral adaptability is related to better consultation outcomes. Training of physicians' behavioral flexibility and their ability to infer patients' preferences can facilitate physician behavioral adaptability and positive patient outcomes. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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.

Three timescales in prism adaptation.

PubMed

Inoue, Masato; Uchimura, Motoaki; Karibe, Ayaka; O'Shea, Jacinta; Rossetti, Yves; Kitazawa, Shigeru

2015-01-01

It has been proposed that motor adaptation depends on at least two learning systems, one that learns fast but with poor retention and another that learns slowly but with better retention (Smith MA, Ghazizadeh A, Shadmehr R. PLoS Biol 4: e179, 2006). This two-state model has been shown to account for a range of behavior in the force field adaptation task. In the present study, we examined whether such a two-state model could also account for behavior arising from adaptation to a prismatic displacement of the visual field. We first confirmed that an "adaptation rebound," a critical prediction of the two-state model, occurred when visual feedback was deprived after an adaptation-extinction episode. We then examined the speed of decay of the prism aftereffect (without any visual feedback) after repetitions of 30, 150, and 500 trials of prism exposure. The speed of decay decreased with the number of exposure trials, a phenomenon that was best explained by assuming an "ultraslow" system, in addition to the fast and slow systems. Finally, we compared retention of aftereffects 24 h after 150 or 500 trials of exposure: retention was significantly greater after 500 than 150 trials. This difference in retention could not be explained by the two-state model but was well explained by the three-state model as arising from the difference in the amount of adaptation of the "ultraslow process." These results suggest that there are not only fast and slow systems but also an ultraslow learning system in prism adaptation that is activated by prolonged prism exposure of 150-500 trials. Copyright © 2015 the American Physiological Society.

The lifecycle of e-learning course in the adaptive educational environment

NASA Astrophysics Data System (ADS)

Gustun, O. N.; Budaragin, N. V.

2017-01-01

In the article we have considered the lifecycle model of the e-learning course in the electronic educational environment. This model consists of three stages and nine phases. In order to implement the adaptive control of the learning process we have determined the actions which are necessary to undertake at different phases of the e-learning course lifecycle. The general characteristics of the SPACEL-technology is given for creating adaptive educational environments of the next generation.

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.

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…

Computational model for behavior shaping as an adaptive health intervention strategy.

PubMed

Berardi, Vincent; Carretero-González, Ricardo; Klepeis, Neil E; Ghanipoor Machiani, Sahar; Jahangiri, Arash; Bellettiere, John; Hovell, Melbourne

2018-03-01

Adaptive behavioral interventions that automatically adjust in real-time to participants' changing behavior, environmental contexts, and individual history are becoming more feasible as the use of real-time sensing technology expands. This development is expected to improve shortcomings associated with traditional behavioral interventions, such as the reliance on imprecise intervention procedures and limited/short-lived effects. JITAI adaptation strategies often lack a theoretical foundation. Increasing the theoretical fidelity of a trial has been shown to increase effectiveness. This research explores the use of shaping, a well-known process from behavioral theory for engendering or maintaining a target behavior, as a JITAI adaptation strategy. A computational model of behavior dynamics and operant conditioning was modified to incorporate the construct of behavior shaping by adding the ability to vary, over time, the range of behaviors that were reinforced when emitted. Digital experiments were performed with this updated model for a range of parameters in order to identify the behavior shaping features that optimally generated target behavior. Narrowing the range of reinforced behaviors continuously in time led to better outcomes compared with a discrete narrowing of the reinforcement window. Rapid narrowing followed by more moderate decreases in window size was more effective in generating target behavior than the inverse scenario. The computational shaping model represents an effective tool for investigating JITAI adaptation strategies. Model parameters must now be translated from the digital domain to real-world experiments so that model findings can be validated.

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

Behavioral ecology of captive species: using behavioral adaptations to assess and enhance welfare of nonhuman zoo animals.

PubMed

Koene, Paul

2013-01-01

This project aimed to estimate a species' adaptations in nature and in captivity, assess welfare, suggest environmental changes, and find species characteristics that underlie welfare problems in nonhuman animals in the zoo. First, the current status of zoo animal welfare assessment was reviewed, and the behavioral ecology approach was outlined. In this approach, databases of species characteristics were developed using (a) literature of natural behavior and (b) captive behavior. Species characteristics were grouped in 8 functional behavioral ecological fitness-related categories: space, time, metabolic, safety, reproductive, comfort, social, and information adaptations. Assessments of the strength of behavioral adaptations in relation to environmental demands were made based on the results available from the literature. The databases with literature at the species level were coupled with databases of (c) behavioral observations and (d) welfare assessments under captive conditions. Observation and welfare assessment methods were adapted from the animal on the farm realm and applied to zoo species. It was expected that the comparison of the repertoire of behaviors in natural and captive environments would highlight welfare problems, provide solutions to welfare problems by environmental changes, and identify species characteristics underlying zoo animal welfare problems.

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.

Dynamic route and departure time choice model based on self-adaptive reference point and reinforcement learning

NASA Astrophysics Data System (ADS)

Li, Xue-yan; Li, Xue-mei; Yang, Lingrun; Li, Jing

2018-07-01

Most of the previous studies on dynamic traffic assignment are based on traditional analytical framework, for instance, the idea of Dynamic User Equilibrium has been widely used in depicting both the route choice and the departure time choice. However, some recent studies have demonstrated that the dynamic traffic flow assignment largely depends on travelers' rationality degree, travelers' heterogeneity and what the traffic information the travelers have. In this paper, we develop a new self-adaptive multi agent model to depict travelers' behavior in Dynamic Traffic Assignment. We use Cumulative Prospect Theory with heterogeneous reference points to illustrate travelers' bounded rationality. We use reinforcement-learning model to depict travelers' route and departure time choosing behavior under the condition of imperfect information. We design the evolution rule of travelers' expected arrival time and the algorithm of traffic flow assignment. Compared with the traditional model, the self-adaptive multi agent model we proposed in this paper can effectively help travelers avoid the rush hour. Finally, we report and analyze the effect of travelers' group behavior on the transportation system, and give some insights into the relation between travelers' group behavior and the performance of transportation system.

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

The role of context in preschool learning: a multilevel examination of the contribution of context-specific problem behaviors and classroom process quality to low-income children's approaches to learning.

PubMed

Domínguez, Ximena; Vitiello, Virginia E; Fuccillo, Janna M; Greenfield, Daryl B; Bulotsky-Shearer, Rebecca J

2011-04-01

Research suggests that promoting adaptive approaches to learning early in childhood may help close the gap between advantaged and disadvantaged children. Recent research has identified specific child-level and classroom-level variables that are significantly associated with preschoolers' approaches to learning. However, further research is needed to understand the interactive effects of these variables and determine whether classroom-level variables buffer the detrimental effects of child-level risk variables. Using a largely urban and minority sample (N=275) of preschool children, the present study examined the additive and interactive effects of children's context-specific problem behaviors and classroom process quality dimensions on children's approaches to learning. Teachers rated children's problem behavior and approaches to learning and independent assessors conducted classroom observations to assess process quality. Problem behaviors in structured learning situations and in peer and teacher interactions were found to negatively predict variance in approaches to learning. Classroom process quality domains did not independently predict variance in approaches to learning. Nonetheless, classroom process quality played an important role in these associations; high emotional support buffered the detrimental effects of problem behavior, whereas high instructional support exacerbated them. The findings of this study have important implications for classroom practices aimed at helping children who exhibit problem behaviors. Copyright © 2010 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Panel V: Adaptive Health Behaviors Among Ethnic Minorities

PubMed Central

Bagley, Shirley P.; Angel, Ronald; Dilworth-Anderson, Peggye; Liu, William; Schinke, Steven

2006-01-01

Race, ethnicity, and cultural attitudes and practices are among the variables that influence health behaviors, including adaptive health behaviors. The following discussions highlight the important role of social conditions in shaping health behaviors and the central role of family in promoting health across the Asian, Hispanic, Native American, and African American ethnic groups. Factors that may lead to health-damaging behaviors are also discussed. The need for additional research that identifies correlations among physiological, social, and behavioral factors and health behaviors, as well as underlying mechanisms, is called for. PMID:8654341

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.

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…

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…

An embodied biologically constrained model of foraging: from classical and operant conditioning to adaptive real-world behavior in DAC-X.

PubMed

Maffei, Giovanni; Santos-Pata, Diogo; Marcos, Encarni; Sánchez-Fibla, Marti; Verschure, Paul F M J

2015-12-01

Animals successfully forage within new environments by learning, simulating and adapting to their surroundings. The functions behind such goal-oriented behavior can be decomposed into 5 top-level objectives: 'how', 'why', 'what', 'where', 'when' (H4W). The paradigms of classical and operant conditioning describe some of the behavioral aspects found in foraging. However, it remains unclear how the organization of their underlying neural principles account for these complex behaviors. We address this problem from the perspective of the Distributed Adaptive Control theory of mind and brain (DAC) that interprets these two paradigms as expressing properties of core functional subsystems of a layered architecture. In particular, we propose DAC-X, a novel cognitive architecture that unifies the theoretical principles of DAC with biologically constrained computational models of several areas of the mammalian brain. DAC-X supports complex foraging strategies through the progressive acquisition, retention and expression of task-dependent information and associated shaping of action, from exploration to goal-oriented deliberation. We benchmark DAC-X using a robot-based hoarding task including the main perceptual and cognitive aspects of animal foraging. We show that efficient goal-oriented behavior results from the interaction of parallel learning mechanisms accounting for motor adaptation, spatial encoding and decision-making. Together, our results suggest that the H4W problem can be solved by DAC-X building on the insights from the study of classical and operant conditioning. Finally, we discuss the advantages and limitations of the proposed biologically constrained and embodied approach towards the study of cognition and the relation of DAC-X to other cognitive architectures. Copyright © 2015 Elsevier Ltd. All rights reserved.

Organisational learning and self-adaptation in dynamic disaster environments.

PubMed

Corbacioglu, Sitki; Kapucu, Naim

2006-06-01

This paper examines the problems associated with inter-organisational learning and adaptation in the dynamic environments that characterise disasters. The research uses both qualitative and quantitative methods to investigate whether organisational learning took place during and in the time in between five disaster response operations in Turkey. The availability of information and its exchange and distribution within and among organisational actors determine whether self-adaptation happens in the course of a disaster response operation. Organisational flexibility supported by an appropriate information infrastructure creates conditions conducive to essential interaction and permits the flow of information. The study found that no significant organisational learning occurred within Turkish disaster management following the earthquakes in Erzincan (1992), Dinar (1995) and Ceyhan (1998). By contrast, the 'symmetry-breaking' Marmara earthquake of 1999 initiated a 'double loop' learning process that led to change in the organisational, technical and cultural aspects of Turkish disaster management, as revealed by the Duzce earthquake response operations.

Maximization, learning, and economic behavior

PubMed Central

Erev, Ido; Roth, Alvin E.

2014-01-01

The rationality assumption that underlies mainstream economic theory has proved to be a useful approximation, despite the fact that systematic violations to its predictions can be found. That is, the assumption of rational behavior is useful in understanding the ways in which many successful economic institutions function, although it is also true that actual human behavior falls systematically short of perfect rationality. We consider a possible explanation of this apparent inconsistency, suggesting that mechanisms that rest on the rationality assumption are likely to be successful when they create an environment in which the behavior they try to facilitate leads to the best payoff for all agents on average, and most of the time. Review of basic learning research suggests that, under these conditions, people quickly learn to maximize expected return. This review also shows that there are many situations in which experience does not increase maximization. In many cases, experience leads people to underweight rare events. In addition, the current paper suggests that it is convenient to distinguish between two behavioral approaches to improve economic analyses. The first, and more conventional approach among behavioral economists and psychologists interested in judgment and decision making, highlights violations of the rational model and proposes descriptive models that capture these violations. The second approach studies human learning to clarify the conditions under which people quickly learn to maximize expected return. The current review highlights one set of conditions of this type and shows how the understanding of these conditions can facilitate market design. PMID:25024182

Maximization, learning, and economic behavior.

PubMed

Erev, Ido; Roth, Alvin E

2014-07-22

The rationality assumption that underlies mainstream economic theory has proved to be a useful approximation, despite the fact that systematic violations to its predictions can be found. That is, the assumption of rational behavior is useful in understanding the ways in which many successful economic institutions function, although it is also true that actual human behavior falls systematically short of perfect rationality. We consider a possible explanation of this apparent inconsistency, suggesting that mechanisms that rest on the rationality assumption are likely to be successful when they create an environment in which the behavior they try to facilitate leads to the best payoff for all agents on average, and most of the time. Review of basic learning research suggests that, under these conditions, people quickly learn to maximize expected return. This review also shows that there are many situations in which experience does not increase maximization. In many cases, experience leads people to underweight rare events. In addition, the current paper suggests that it is convenient to distinguish between two behavioral approaches to improve economic analyses. The first, and more conventional approach among behavioral economists and psychologists interested in judgment and decision making, highlights violations of the rational model and proposes descriptive models that capture these violations. The second approach studies human learning to clarify the conditions under which people quickly learn to maximize expected return. The current review highlights one set of conditions of this type and shows how the understanding of these conditions can facilitate market design.

Schema-based learning of adaptable and flexible prey- catching in anurans II. Learning after lesioning.

PubMed

Corbacho, Fernando; Nishikawa, Kiisa C; Weerasuriya, Ananda; Liaw, Jim-Shih; Arbib, Michael A

2005-12-01

The previous companion paper describes the initial (seed) schema architecture that gives rise to the observed prey-catching behavior. In this second paper in the series we describe the fundamental adaptive processes required during learning after lesioning. Following bilateral transections of the hypoglossal nerve, anurans lunge toward mealworms with no accompanying tongue or jaw movement. Nevertheless anurans with permanent hypoglossal transections eventually learn to catch their prey by first learning to open their mouth again and then lunging their body further and increasing their head angle. In this paper we present a new learning framework, called schema-based learning (SBL). SBL emphasizes the importance of the current existent structure (schemas), that defines a functioning system, for the incremental and autonomous construction of ever more complex structure to achieve ever more complex levels of functioning. We may rephrase this statement into the language of Schema Theory (Arbib 1992, for a comprehensive review) as the learning of new schemas based on the stock of current schemas. SBL emphasizes a fundamental principle of organization called coherence maximization, that deals with the maximization of congruence between the results of an interaction (external or internal) and the expectations generated for that interaction. A central hypothesis consists of the existence of a hierarchy of predictive internal models (predictive schemas) all over the control center-brain-of the agent. Hence, we will include predictive models in the perceptual, sensorimotor, and motor components of the autonomous agent architecture. We will then show that predictive models are fundamental for structural learning. In particular we will show how a system can learn a new structural component (augment the overall network topology) after being lesioned in order to recover (or even improve) its original functionality. Learning after lesioning is a special case of structural

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.…

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…

The Relation Between Intellectual Functioning and Adaptive Behavior in the Diagnosis of Intellectual Disability.

PubMed

Tassé, Marc J; Luckasson, Ruth; Schalock, Robert L

2016-12-01

Intellectual disability originates during the developmental period and is characterized by significant limitations both in intellectual functioning and in adaptive behavior as expressed in conceptual, social, and practical adaptive skills. In this article, we present a brief history of the diagnostic criteria of intellectual disability for both the DSM-5 and AAIDD. The article also (a) provides an update of the understanding of adaptive behavior, (b) dispels two thinking errors regarding mistaken temporal or causal link between intellectual functioning and adaptive behavior, (c) explains that there is a strong correlational, but no causative, relation between intellectual functioning and adaptive behavior, and (d) asserts that once a question of determining intellectual disability is raised, both intellectual functioning and adaptive behavior are assessed and considered jointly and weighed equally in the diagnosis of intellectual disability. We discuss the problems created by an inaccurate statement that appears in the DSM-5 regarding a causal link between deficits in intellectual functioning and adaptive behavior and propose an immediate revision to remove this erroneous and confounding statement.

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

Adaptive Behavior of Primary School Students with Visual Impairments: The Impact of Educational Settings

ERIC Educational Resources Information Center

Metsiou, Katerina; Papadopoulos, Konstantinos; Agaliotis, Ioannis

2011-01-01

This study explored the adaptive behavior of primary school students with visual impairments, as well as the impact of educational setting on their adaptive behavior. Instrumentation included an informal questionnaire and the Vineland Adaptive Behavior Scales. Participants were 36 primary school students with visual impairments. The educational…

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot.

PubMed

Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot

PubMed Central

Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles

Cultural Adaptations of Behavioral Health Interventions: A Progress Report

PubMed Central

Barrera, Manuel

2014-01-01

Objective To reduce health disparities, behavioral health interventions must reach subcultural groups and demonstrate effectiveness in improving their health behaviors and outcomes. One approach to developing such health interventions is to culturally adapt original evidence-based interventions. The goals of the paper are to (a) describe consensus on the stages involved in developing cultural adaptations, (b) identify common elements in cultural adaptations, (c) examine evidence on the effectiveness of culturally enhanced interventions for various health conditions, and (d) pose questions for future research. Method Influential literature from the past decade was examined to identify points of consensus. Results There is agreement that cultural adaptation can be organized into five stages: information gathering, preliminary design, preliminary testing, refinement, and final trial. With few exceptions, reviews of several health conditions (e.g., AIDS, asthma, diabetes) concluded that culturally enhanced interventions are more effective in improving health outcomes than usual care or other control conditions. Conclusion Progress has been made in establishing methods for conducting cultural adaptations and providing evidence of their effectiveness. Future research should include evaluations of cultural adaptations developed in stages, tests to determine the effectiveness of cultural adaptations relative to the original versions, and studies that advance our understanding of cultural constructs’ contributions to intervention engagement and efficacy. PMID:22289132

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,…

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…

Data-Driven Design: Learning from Student Experiences and Behaviors

NASA Astrophysics Data System (ADS)

Horodyskyj, L.; Mead, C.; Buxner, S.; Semken, S. C.; Anbar, A. D.

2015-12-01

Good instructors know that lessons and courses change over time. Limitations in time and data often prevent instructors from making changes that will most benefit their students. For example, in traditional in-person classrooms an instructor may only have access to the final product of a student's thought processes (such as a term paper, homework assignment, or exam). The thought processes that lead to a given answer are opaque to the instructor, making future modifications to course content an exercise in trial-and-error and instinct. Modern online intelligent tutoring systems can provide insight into a student's behavior, providing transparency to a previously opaque process and providing the instructor with better information for course modification. Habitable Worlds is an introductory level online-only astrobiology lab course that has been offered at Arizona State University since Fall 2011. The course is built and offered through an intelligent tutoring system, Smart Sparrow's Adaptive eLearning Platform, which provides in-depth analytics that allow the instructor to investigate detailed student behavior, from time spent on question to number of attempts to patterns of answers. We will detail the process we employ of informed modification of course content, including time and trial comparisons between semesters, analysis of submitted answers, analysis of alternative learning pathways taken, and A/B testing.

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…

The temporal dynamics of reversal learning: P3 amplitude predicts valence-specific behavioral adjustment.

PubMed

Donaldson, Kayla R; Ait Oumeziane, Belel; Hélie, Sebastien; Foti, Dan

2016-07-01

Adapting behavior to dynamic stimulus-reward contingences is a core feature of reversal learning and a capacity thought to be critical to socio-emotional behavior. Impairment in reversal learning has been linked to multiple psychiatric outcomes, including depression, Parkinson's disorder, and substance abuse. A recent influential study introduced an innovative laboratory reversal-learning paradigm capable of disentangling the roles of feedback valence and expectancy. Here, we sought to use this paradigm in order to examine the time-course of reward and punishment learning using event-related potentials among a large, representative sample (N=101). Three distinct phases of processing were examined: initial feedback evaluation (reward positivity, or RewP), allocation of attention (P3), and sustained processing (late positive potential, or LPP). Results indicate a differential pattern of valence and expectancy across these processing stages: the RewP was uniquely related to valence (i.e., positive vs. negative feedback), the P3 was uniquely associated with expectancy (i.e., unexpected vs. expected feedback), and the LPP was sensitive to both valence and expectancy (i.e., main effects of each, but no interaction). The link between ERP amplitudes and behavioral performance was strongest for the P3, and this association was valence-specific. Overall, these findings highlight the potential utility of the P3 as a neural marker for feedback processing in reversal-based learning and establish a foundation for future research in clinical populations. Copyright © 2016 Elsevier Inc. All rights reserved.

Learning Theory and Prosocial Behavior

ERIC Educational Resources Information Center

Rosenhan, D. L.

1972-01-01

Although theories of learning which stress the role of reinforcement can help us understand altruistic behaviors, it seems clear that a more complete comprehension calls for an expansion of our notions of learning, such that they incorporate affect and cognition. (Author/JM)

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…

Exploring the Structure of Adaptive Behavior: Project Report Number 87-1.

ERIC Educational Resources Information Center

Bruininks, Robert H.; McGrew, Kevin

This report presents results from three research studies that were designed to explore both the definition and the structure of the adaptive behavior construct. The first study investigated the structure of adaptive behavior as a function of age, developmental level, and type of handicap through an exploratory factor analysis of both the…

Shifting workplace behavior to inspire learning: a journey to building a learning culture.

PubMed

Schoonbeek, Sue; Henderson, Amanda

2011-01-01

This article discusses the process of building a learning culture. It began with establishing acceptance and connection with the nurse unit manager and the ward team. In the early phases of developing rapport, bullying became apparent. Because bullying undermines sharing and trust, the hallmarks of learning environments, the early intervention work assisted staff to recognize and counteract bullying behaviors. When predominantly positive relationships were restored, interactions that facilitated open communication, including asking questions and providing feedback-behaviors commensurate with learning in the workplace-were developed during regular in-service sessions. Staff participated in role-play and role modeling desired behaviors. Once staff became knowledgeable about positive learning interactions, reward and recognition strategies began to reinforce attitudes and behaviors that align with learning. Through rewards, all nurses had the opportunity to be recognized for their contribution. Nurses who excelled were invited to become champions to continue engaging the key stakeholders to further build the learning environment. Copyright 2011, SLACK Incorporated.

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

The role of urgency, frequency, and nocturia in defining overactive bladder adaptive behavior.

PubMed

Minassian, Vatche; Stewart, Walter; Hirsch, Annemarie; Kolodner, Ken; Fitzgerald, Mary; Burgio, Kathryn; Cundiff, Geoffrey; Blaivas, Jerry; Newman, Diane; Dilley, Anne

2011-03-01

To determine the relation between urgency alone, or in combination with frequency and nocturia, and adaptive behavior in overactive bladder (OAB) syndrome. We used survey data from the General Longitudinal Overactive Bladder Evaluation (GLOBE) of primary care patients over 40. Participants (n=2,752: 1,557 females; 1,195 males) completed the same survey at two time points, 6 months apart. Questions assessed OAB symptoms and adaptive behavior. We estimated correlation coefficients (R(2)) between urgency, frequency, and nocturia symptom scores (alone and in combination) and adaptive behavior measures at baseline and change in symptom scores and behavioral measures from baseline to 6 months. At baseline, urgency was the dominant predictor of all behavioral measures for females (R(2)=0.19-0.48) and males (R(2)=0.15-0.39). Lower R(2) values were observed for the change in measures from baseline to 6 months, but again change in urgency was the strongest predictor of change in adaptive behavior (R(2)=0.04-0.13 in females, and 0.02-0.08 in males). The correlation between symptoms and measures of adaptive behavior was almost completely explained by the urgency score. Frequency and nocturia did not substantially improve the overall correlation. The relation between measures of OAB symptoms and adaptive behavior at baseline and over time are largely explained by urgency, not by frequency and nocturia. Copyright © 2011 Wiley-Liss, Inc.

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…

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

Adaptive behavior in Chinese children with Williams syndrome

PubMed Central

2014-01-01

Background Williams syndrome (WS) is a neurodevelopmental disease characterized by compelling psychological phenotypes. The symptoms span multiple cognitive domains and include a distinctive pattern of social behavior. The goal of this study was to explore adaptive behavior in WS patients in China. Methods We conducted a structured interview including the Infants-Junior Middle School Students Social-life Abilities Scale in three participant groups: children with WS (n = 26), normally-developing children matched for mental age (MA, n = 30), and normally-developing children matched for chronological age (CA, n = 40). We compared the mean scores for each domain between the three groups. Results Children with WS had more siblings than children in the two control groups. The educational level of the caregivers of WS children was lower than that of the control children. We found no differences in locomotion, work skill, socialization, or self-management between the WS and MA groups. WS children obtained higher scores of self-dependence (df = 54, Z = −2.379, p = 0.017) and had better communication skills (df = 54, Z = −2.222, p = 0.026) compared with MA children. The CA children achieved higher scores than the WS children for all dimensions of adaptive behavior. Conclusions WS children have better adaptive behavior skills regarding communication and self-dependence than normal children matched for mental age. Targeted intervention techniques should be designed to promote social development in this population. PMID:24708693

Long term treadmill exercise performed to chronic social isolated rats regulate anxiety behavior without improving learning.

PubMed

Cevik, Ozge Selin; Sahin, Leyla; Tamer, Lulufer

2018-05-01

The type and duration of exposure to stress is an important influence on emotional and cognitive functions. Learning is the adaptive response of the central nervous system that occurs in hippocampus which affects from environmental factors like exercise. In this study, we investigated effects of long term treadmill exercise on learning and behavior on chronic social isolated rat. Male Wistar rats (n = 32) randomly assigned into four groups: control, exercised, social isolation, social isolation + exercise during postnatal days (PNDs) 21-34. Social isolation protocol was applied during 14 days by placing rat in a cage one by one. Rats were exercised during 5 days, days were chosen randomly for overall 4 weeks (20, 30, 50, 60 min respectively). Finally, learning performance was evaluated by Morris water maze (MWM). Anxiety behavior was evaluated by Open field and elevated plus maze test. At the end of learning and behavior tests, the rats were decapitated to collect blood samples via intracardiac puncture and corticosterone analysis was performed with ELISA method. Animal weights and water consumption did not change significantly but food intake differed among groups. Corticosterone level did not change between groups. The frequency of entering to the target quadrant increased in exercised rat significantly. However, there was no difference in learning and memory in rats. Treadmill exercise reduced anxiety behavior significantly. Taken together these findings may point out that, long term treadmill exercise did not change learning and memory but reduced anxiety level of rat without changing corticosterone level. Copyright © 2018 Elsevier Inc. All rights reserved.

Application of persuasion and health behavior theories for behavior change counseling: design of the ADAPT (Avoiding Diabetes Thru Action Plan Targeting) program.

PubMed

Lin, Jenny J; Mann, Devin M

2012-09-01

Diabetes incidence is increasing worldwide and providers often do not feel they can effectively counsel about preventive lifestyle changes. The goal of this paper is to describe the development and initial feasibility testing of the Avoiding Diabetes Thru Action Plan Targeting (ADAPT) program to enhance counseling about behavior change for patients with pre-diabetes. Primary care providers and patients were interviewed about their perspectives on lifestyle changes to prevent diabetes. A multidisciplinary design team incorporated this data to translate elements from behavior change theories to create the ADAPT program. The ADAPT program was pilot tested to evaluate feasibility. Leveraging elements from health behavior theories and persuasion literature, the ADAPT program comprises a shared goal-setting module, implementation intentions exercise, and tailored reminders to encourage behavior change. Feasibility data demonstrate that patients were able to use the program to achieve their behavior change goals. Initial findings show that the ADAPT program is feasible for helping improve primary care providers' counseling for behavior change in patients with pre-diabetes. If successful, the ADAPT program may represent an adaptable and scalable behavior change tool for providers to encourage lifestyle changes to prevent diabetes. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Adaptive E-Learning Environments: Research Dimensions and Technological Approaches

ERIC Educational Resources Information Center

Di Bitonto, Pierpaolo; Roselli, Teresa; Rossano, Veronica; Sinatra, Maria

2013-01-01

One of the most closely investigated topics in e-learning research has always been the effectiveness of adaptive learning environments. The technological evolutions that have dramatically changed the educational world in the last six decades have allowed ever more advanced and smarter solutions to be proposed. The focus of this paper is to depict…

Communicating to Farmers about Skin Cancer: The Behavior Adaptation Model.

ERIC Educational Resources Information Center

Parrott, Roxanne; Monahan, Jennifer; Ainsworth, Stuart; Steiner, Carol

1998-01-01

States health campaign messages designed to encourage behavior adaptation have greater likelihood of success than campaigns promoting avoidance of at-risk behaviors that cannot be avoided. Tests a model of health risk behavior using four different behaviors in a communication campaign aimed at reducing farmers' risk for skin cancer--questions…

Reliability and Validity of the Vietnamese Vineland Adaptive Behavior Scales with Preschool-Age Children

ERIC Educational Resources Information Center

Goldberg, Michael R.; Dill, Charles A.; Shin, Jin Y.; Nhan, Nguyen Viet

2009-01-01

This study was conducted to examine an adaptation of the Vineland Adaptive Behavior Scale (VABS) [Sparrow, S. S., Balla, D. A., & Cicchetti, D. V. (1984). "The Vineland Adaptive Behavior Scales." Circle Pines, MN: America Guidance Service; Sparrow, S. S., Balla, D. A., & Cicchetti, D. V. (2005). "Vineland Adaptive Behavior…

Adaptive Locomotor Behavior in Larval Zebrafish

PubMed Central

Portugues, Ruben; Engert, Florian

2011-01-01

In this study we report that larval zebrafish display adaptive locomotor output that can be driven by unexpected visual feedback. We develop a new assay that addresses visuomotor integration in restrained larval zebrafish. The assay involves a closed-loop environment in which the visual feedback a larva receives depends on its own motor output in a way that resembles freely swimming conditions. The experimenter can control the gain of this closed feedback loop, so that following a given motor output the larva experiences more or less visual feedback depending on whether the gain is high or low. We show that increases and decreases in this gain setting result in adaptive changes in behavior that lead to a generalized decrease or increase of motor output, respectively. Our behavioral analysis shows that both the duration and tail beat frequency of individual swim bouts can be modified, as well as the frequency with which bouts are elicited. These changes can be implemented rapidly, following an exposure to a new gain of just 175 ms. In addition, modifications in some behavioral parameters accumulate over tens of seconds and effects last for at least 30 s from trial to trial. These results suggest that larvae establish an internal representation of the visual feedback expected from a given motor output and that the behavioral modifications are driven by an error signal that arises from the discrepancy between this expectation and the actual visual feedback. The assay we develop presents a unique possibility for studying visuomotor integration using imaging techniques available in the larval zebrafish. PMID:21909325

Adaptive locomotor behavior in larval zebrafish.

PubMed

Portugues, Ruben; Engert, Florian

2011-01-01

In this study we report that larval zebrafish display adaptive locomotor output that can be driven by unexpected visual feedback. We develop a new assay that addresses visuomotor integration in restrained larval zebrafish. The assay involves a closed-loop environment in which the visual feedback a larva receives depends on its own motor output in a way that resembles freely swimming conditions. The experimenter can control the gain of this closed feedback loop, so that following a given motor output the larva experiences more or less visual feedback depending on whether the gain is high or low. We show that increases and decreases in this gain setting result in adaptive changes in behavior that lead to a generalized decrease or increase of motor output, respectively. Our behavioral analysis shows that both the duration and tail beat frequency of individual swim bouts can be modified, as well as the frequency with which bouts are elicited. These changes can be implemented rapidly, following an exposure to a new gain of just 175 ms. In addition, modifications in some behavioral parameters accumulate over tens of seconds and effects last for at least 30 s from trial to trial. These results suggest that larvae establish an internal representation of the visual feedback expected from a given motor output and that the behavioral modifications are driven by an error signal that arises from the discrepancy between this expectation and the actual visual feedback. The assay we develop presents a unique possibility for studying visuomotor integration using imaging techniques available in the larval zebrafish.

Factors Influencing Maternal Behavioral Adaptability: Maternal Depressive Symptoms and Child Negative Affect.

PubMed

Hummel, Alexandra C; Kiel, Elizabeth J

2016-01-01

In early childhood, parents play an important role in children's socioemotional development. As such, parent training is a central component of many psychological interventions for young children (Reyno & McGrath, 2006). Maternal depressive symptoms have consistently been linked to maladaptive parenting behaviors (e.g., disengagement, intrusiveness), as well as to lower parent training efficacy in the context of child psychological intervention, suggesting that mothers with higher symptomatology may be less able to be adapt their behavior according to situational demands. The goal of the current study was to examine both maternal and child factors that may influence maternal behavioral adaptability. Ninety-one mothers and their toddlers ( M = 23.93 months, 59% male) participated in a laboratory visit during which children engaged in a variety of novelty episodes designed to elicit individual differences in fear/withdrawal behaviors. Mothers also completed a questionnaire battery. Maternal behavioral adaptability was operationalized as the difference in scores for maternal involvement, comforting, and protective behavior between episodes in which mothers were instructed to refrain from interaction and those in which they were instructed to act naturally. Results indicated that when children displayed high levels of negative affect in the restricted episodes, mothers with higher levels of depressive symptoms were less able to adapt their involved behavior because they exhibited low rates of involvement across episodes regardless of instruction given. The current study serves as an intermediary step in understanding how maternal depressive symptoms may influence daily interactions with their children as well as treatment implementation and outcomes, and provides initial evidence that maternal internalizing symptoms may contribute to lower behavioral adaptability in the context of certain child behaviors due to consistent low involvement.

Learning to push and learning to move: the adaptive control of contact forces

PubMed Central

Casadio, Maura; Pressman, Assaf; Mussa-Ivaldi, Ferdinando A.

2015-01-01

To be successful at manipulating objects one needs to apply simultaneously well controlled movements and contact forces. We present a computational theory of how the brain may successfully generate a vast spectrum of interactive behaviors by combining two independent processes. One process is competent to control movements in free space and the other is competent to control contact forces against rigid constraints. Free space and rigid constraints are singularities at the boundaries of a continuum of mechanical impedance. Within this continuum, forces and motions occur in “compatible pairs” connected by the equations of Newtonian dynamics. The force applied to an object determines its motion. Conversely, inverse dynamics determine a unique force trajectory from a movement trajectory. In this perspective, we describe motor learning as a process leading to the discovery of compatible force/motion pairs. The learned compatible pairs constitute a local representation of the environment's mechanics. Experiments on force field adaptation have already provided us with evidence that the brain is able to predict and compensate the forces encountered when one is attempting to generate a motion. Here, we tested the theory in the dual case, i.e., when one attempts at applying a desired contact force against a simulated rigid surface. If the surface becomes unexpectedly compliant, the contact point moves as a function of the applied force and this causes the applied force to deviate from its desired value. We found that, through repeated attempts at generating the desired contact force, subjects discovered the unique compatible hand motion. When, after learning, the rigid contact was unexpectedly restored, subjects displayed after effects of learning, consistent with the concurrent operation of a motion control system and a force control system. Together, theory and experiment support a new and broader view of modularity in the coordinated control of forces and motions

Hoarding behaviors in children with learning disabilities.

PubMed

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

2011-05-01

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

Direction-Specific Adaptation in Neuronal and Behavioral Responses of an Insect Mechanosensory System.

PubMed

Ogawa, Hiroto; Oka, Kotaro

2015-08-19

Stimulus-specific adaptation (SSA) is considered to be the neural underpinning of habituation to frequent stimuli and novelty detection. However, neither the cellular mechanism underlying SSA nor the link between SSA-like neuronal plasticity and behavioral modulation is well understood. The wind-detection system in crickets is one of the best models for investigating the neural basis of SSA. We found that crickets exhibit stimulus-direction-specific adaptation in wind-elicited avoidance behavior. Repetitive air currents inducing this behavioral adaptation reduced firings to the stimulus and the amplitude of excitatory synaptic potentials in wind-sensitive giant interneurons (GIs) related to the avoidance behavior. Injection of a Ca(2+) chelator into GIs diminished both the attenuation of firings and the synaptic depression induced by the repetitive stimulation, suggesting that adaptation of GIs induced by this stimulation results in Ca(2+)-mediated modulation of postsynaptic responses, including postsynaptic short-term depression. Some types of GIs showed specific adaptation to the direction of repetitive stimuli, resulting in an alteration of their directional tuning curves. The types of GIs for which directional tuning was altered displayed heterogeneous direction selectivity in their Ca(2+) dynamics that was restricted to a specific area of dendrites. In contrast, other types of GIs with constant directionality exhibited direction-independent global Ca(2+) elevation throughout the dendritic arbor. These results suggest that depression induced by local Ca(2+) accumulation at repetitively activated synapses of key neurons underlies direction-specific behavioral adaptation. This input-selective depression mediated by heterogeneous Ca(2+) dynamics could confer the ability to detect novelty at the earliest stages of sensory processing in crickets. Stimulus-specific adaptation (SSA) is considered to be the neural underpinning of habituation and novelty detection. We

Biobehavioral Insights into Adaptive Behavior in Complex and Dynamic Operational Settings: Lessons learned from the Soldier Performance and Effective, Adaptable Response Task

PubMed Central

Haufler, Amy J.; Lewis, Gregory F.; Davila, Maria I.; Westhelle, Felipe; Gavrilis, James; Bryce, Crystal I.; Kolacz, Jacek; Granger, Douglas A.; McDaniel, William

2018-01-01

The purpose of this study was to explore the biobehavioral correlates of adaptive behavior in the context of a standardized laboratory-based mission-relevant challenge [the Soldier Performance and Effective, Adaptable Response (SPEAR) task]. Participants were 26 healthy male volunteers (M = 34.85 years, SD = 4.12) with active military duty and leadership experience within the last 5 years (i.e., multiple leadership positions, operational deployments in combat, interactions with civilians and partner nation forces on the battlefield, experience making decisions under fire). The SPEAR task simultaneously engages perception, cognition, and action aspects of human performance demands similar to those encountered in the operational setting. Participants must engage with military-relevant text, visual, and auditory stimuli, interpret new information, and retain the commander’s intent in working memory to create a new plan of action for mission success. Time-domain measures of heart period and respiratory sinus arrhythmia (RSA) were quantified, and saliva was sampled [later assayed for cortisol and alpha-amylase (sAA)] before-, during-, and post-SPEAR. Results revealed a predictable pattern of withdraw and recovery of the cardiac vagal tone during repeated presentation of battlefield challenges. Recovery of vagal inhibition following executive function challenge was strongly linked to better task-related performance. Rate of RSA recovery was also associated with better recall of the commander’s intent. Decreasing magnitude in the skin conductance response prior to the task was positively associated with better overall task-related performance. Lower levels of RSA were observed in participants who reported higher rates of combat deployments, and reduced RSA flexibility was associated with higher rates of casualty exposure. Greater RSA flexibility during SPEAR was associated with greater self-reported resilience. There was no consistent pattern of task

Biobehavioral Insights into Adaptive Behavior in Complex and Dynamic Operational Settings: Lessons learned from the Soldier Performance and Effective, Adaptable Response Task.

PubMed

Haufler, Amy J; Lewis, Gregory F; Davila, Maria I; Westhelle, Felipe; Gavrilis, James; Bryce, Crystal I; Kolacz, Jacek; Granger, Douglas A; McDaniel, William

2017-01-01

The purpose of this study was to explore the biobehavioral correlates of adaptive behavior in the context of a standardized laboratory-based mission-relevant challenge [the Soldier Performance and Effective, Adaptable Response (SPEAR) task]. Participants were 26 healthy male volunteers (M = 34.85 years, SD = 4.12) with active military duty and leadership experience within the last 5 years (i.e., multiple leadership positions, operational deployments in combat, interactions with civilians and partner nation forces on the battlefield, experience making decisions under fire). The SPEAR task simultaneously engages perception, cognition, and action aspects of human performance demands similar to those encountered in the operational setting. Participants must engage with military-relevant text, visual, and auditory stimuli, interpret new information, and retain the commander's intent in working memory to create a new plan of action for mission success. Time-domain measures of heart period and respiratory sinus arrhythmia (RSA) were quantified, and saliva was sampled [later assayed for cortisol and alpha-amylase (sAA)] before-, during-, and post-SPEAR. Results revealed a predictable pattern of withdraw and recovery of the cardiac vagal tone during repeated presentation of battlefield challenges. Recovery of vagal inhibition following executive function challenge was strongly linked to better task-related performance. Rate of RSA recovery was also associated with better recall of the commander's intent. Decreasing magnitude in the skin conductance response prior to the task was positively associated with better overall task-related performance. Lower levels of RSA were observed in participants who reported higher rates of combat deployments, and reduced RSA flexibility was associated with higher rates of casualty exposure. Greater RSA flexibility during SPEAR was associated with greater self-reported resilience. There was no consistent pattern of task

An Adaptive Approach to Managing Knowledge Development in a Project-Based Learning Environment

ERIC Educational Resources Information Center

Tilchin, Oleg; Kittany, Mohamed

2016-01-01

In this paper we propose an adaptive approach to managing the development of students' knowledge in the comprehensive project-based learning (PBL) environment. Subject study is realized by two-stage PBL. It shapes adaptive knowledge management (KM) process and promotes the correct balance between personalized and collaborative learning. The…

Robot Behavior Acquisition Superposition and Composting of Behaviors Learned through Teleoperation

NASA Technical Reports Server (NTRS)

Peters, Richard Alan, II

2004-01-01

Superposition of a small set of behaviors, learned via teleoperation, can lead to robust completion of a simple articulated reach-and-grasp task. Results support the hypothesis that a set of learned behaviors can be combined to generate new behaviors of a similar type. This supports the hypothesis that a robot can learn to interact purposefully with its environment through a developmental acquisition of sensory-motor coordination. Teleoperation bootstraps the process by enabling the robot to observe its own sensory responses to actions that lead to specific outcomes. A reach-and-grasp task, learned by an articulated robot through a small number of teleoperated trials, can be performed autonomously with success in the face of significant variations in the environment and perturbations of the goal. Superpositioning was performed using the Verbs and Adverbs algorithm that was developed originally for the graphical animation of articulated characters. Work was performed on Robonaut at NASA-JSC.

Extensible Adaptive System for STEM Learning

DTIC Science & Technology

2013-07-16

Copyright 2013 Raytheon BBN Technologies Corp. All Rights Reserved ONR STEM Grand Challenge Extensible Adaptive System for STEM Learning ...Contract # N00014-12-C-0535 Raytheon BBN Technologies Corp. (BBN) Reference # 14217 In partial fulfillment of contract deliverable item # A001...Quarterly Progress Report #2 April 7, 2013 –July 6, 2013 Submitted July 16, 2013 BBN Technical POC: John Makhoul Raytheon BBN Technologies

Fast but fleeting: adaptive motor learning processes associated with aging and cognitive decline.

PubMed

Trewartha, Kevin M; Garcia, Angeles; Wolpert, Daniel M; Flanagan, J Randall

2014-10-01

Motor learning has been shown to depend on multiple interacting learning processes. For example, learning to adapt when moving grasped objects with novel dynamics involves a fast process that adapts and decays quickly-and that has been linked to explicit memory-and a slower process that adapts and decays more gradually. Each process is characterized by a learning rate that controls how strongly motor memory is updated based on experienced errors and a retention factor determining the movement-to-movement decay in motor memory. Here we examined whether fast and slow motor learning processes involved in learning novel dynamics differ between younger and older adults. In addition, we investigated how age-related decline in explicit memory performance influences learning and retention parameters. Although the groups adapted equally well, they did so with markedly different underlying processes. Whereas the groups had similar fast processes, they had different slow processes. Specifically, the older adults exhibited decreased retention in their slow process compared with younger adults. Within the older group, who exhibited considerable variation in explicit memory performance, we found that poor explicit memory was associated with reduced retention in the fast process, as well as the slow process. These findings suggest that explicit memory resources are a determining factor in impairments in the both the fast and slow processes for motor learning but that aging effects on the slow process are independent of explicit memory declines. Copyright © 2014 the authors 0270-6474/14/3413411-11$15.00/0.

A Framework for Adaptive Learning Design in a Web-Conferencing Environment

ERIC Educational Resources Information Center

Bower, Matt

2016-01-01

Many recent technologies provide the ability to dynamically adjust the interface depending on the emerging cognitive and collaborative needs of the learning episode. This means that educators can adaptively re-design the learning environment during the lesson, rather than purely relying on preemptive learning design thinking. Based on a…

Making Mistakes: Emotional Adaptation and Classroom Learning

ERIC Educational Resources Information Center

McCaslin, Mary; Vriesema, Christine C.; Burggraf, Susan

2016-01-01

Background: We studied how students in Grades 4-6 participate in and emotionally adapt to the give-and-take of learning in classrooms, particularly when making mistakes. Our approach is consistent with researchers who (a) include cognitive appraisals in the study of emotional experiences, (b) consider how personal concerns might mediate…

Ontogeny of classical and operant learning behaviors in zebrafish.

PubMed

Valente, André; Huang, Kuo-Hua; Portugues, Ruben; Engert, Florian

2012-03-20

The performance of developing zebrafish in both classical and operant conditioning assays was tested with a particular focus on the emergence of these learning behaviors during development. Strategically positioned visual cues paired with electroshocks were used in two fully automated assays to investigate both learning paradigms. These allow the evaluation of the behavioral performance of zebrafish continuously throughout development, from larva to adult. We found that learning improves throughout development, starts reliably around week 3, and reaches adult performance levels at week 6. Adult fish quickly learned to perform perfectly, and the expression of the learned behavior is manifestly controlled by vision. The memory is behaviorally expressed in adults for at least 6 h and retrievable for at least 12 h.

Ontogeny of classical and operant learning behaviors in zebrafish

PubMed Central

Valente, André; Huang, Kuo-Hua; Portugues, Ruben; Engert, Florian

2012-01-01

The performance of developing zebrafish in both classical and operant conditioning assays was tested with a particular focus on the emergence of these learning behaviors during development. Strategically positioned visual cues paired with electroshocks were used in two fully automated assays to investigate both learning paradigms. These allow the evaluation of the behavioral performance of zebrafish continuously throughout development, from larva to adult. We found that learning improves throughout development, starts reliably around week 3, and reaches adult performance levels at week 6. Adult fish quickly learned to perform perfectly, and the expression of the learned behavior is manifestly controlled by vision. The memory is behaviorally expressed in adults for at least 6 h and retrievable for at least 12 h. PMID:22434824

Opportunistic Behavior in Motivated Learning Agents.

PubMed

Graham, James; Starzyk, Janusz A; Jachyra, Daniel

2015-08-01

This paper focuses on the novel motivated learning (ML) scheme and opportunistic behavior of an intelligent agent. It extends previously developed ML to opportunistic behavior in a multitask situation. Our paper describes the virtual world implementation of autonomous opportunistic agents learning in a dynamically changing environment, creating abstract goals, and taking advantage of arising opportunities to improve their performance. An opportunistic agent achieves better results than an agent based on ML only. It does so by minimizing the average value of all need signals rather than a dominating need. This paper applies to the design of autonomous embodied systems (robots) learning in real-time how to operate in a complex environment.

On the Evolution of Behaviors through Embodied Imitation.

PubMed

Erbas, Mehmet D; Bull, Larry; Winfield, Alan F T

2015-01-01

This article describes research in which embodied imitation and behavioral adaptation are investigated in collective robotics. We model social learning in artificial agents with real robots. The robots are able to observe and learn each others' movement patterns using their on-board sensors only, so that imitation is embodied. We show that the variations that arise from embodiment allow certain behaviors that are better adapted to the process of imitation to emerge and evolve during multiple cycles of imitation. As these behaviors are more robust to uncertainties in the real robots' sensors and actuators, they can be learned by other members of the collective with higher fidelity. Three different types of learned-behavior memory have been experimentally tested to investigate the effect of memory capacity on the evolution of movement patterns, and results show that as the movement patterns evolve through multiple cycles of imitation, selection, and variation, the robots are able to, in a sense, agree on the structure of the behaviors that are imitated.

Factors Influencing Maternal Behavioral Adaptability: Maternal Depressive Symptoms and Child Negative Affect

PubMed Central

Hummel, Alexandra C.; Kiel, Elizabeth J.

2017-01-01

In early childhood, parents play an important role in children’s socioemotional development. As such, parent training is a central component of many psychological interventions for young children (Reyno & McGrath, 2006). Maternal depressive symptoms have consistently been linked to maladaptive parenting behaviors (e.g., disengagement, intrusiveness), as well as to lower parent training efficacy in the context of child psychological intervention, suggesting that mothers with higher symptomatology may be less able to be adapt their behavior according to situational demands. The goal of the current study was to examine both maternal and child factors that may influence maternal behavioral adaptability. Ninety-one mothers and their toddlers (M =23.93 months, 59% male) participated in a laboratory visit during which children engaged in a variety of novelty episodes designed to elicit individual differences in fear/withdrawal behaviors. Mothers also completed a questionnaire battery. Maternal behavioral adaptability was operationalized as the difference in scores for maternal involvement, comforting, and protective behavior between episodes in which mothers were instructed to refrain from interaction and those in which they were instructed to act naturally. Results indicated that when children displayed high levels of negative affect in the restricted episodes, mothers with higher levels of depressive symptoms were less able to adapt their involved behavior because they exhibited low rates of involvement across episodes regardless of instruction given. The current study serves as an intermediary step in understanding how maternal depressive symptoms may influence daily interactions with their children as well as treatment implementation and outcomes, and provides initial evidence that maternal internalizing symptoms may contribute to lower behavioral adaptability in the context of certain child behaviors due to consistent low involvement. PMID:29576864

Learning and adaptation: neural and behavioural mechanisms behind behaviour change

NASA Astrophysics Data System (ADS)

Lowe, Robert; Sandamirskaya, Yulia

2018-01-01

This special issue presents perspectives on learning and adaptation as they apply to a number of cognitive phenomena including pupil dilation in humans and attention in robots, natural language acquisition and production in embodied agents (robots), human-robot game play and social interaction, neural-dynamic modelling of active perception and neural-dynamic modelling of infant development in the Piagetian A-not-B task. The aim of the special issue, through its contributions, is to highlight some of the critical neural-dynamic and behavioural aspects of learning as it grounds adaptive responses in robotic- and neural-dynamic systems.

The decay of motor adaptation to novel movement dynamics reveals an asymmetry in the stability of motion state-dependent learning

PubMed Central

Hosseini, Eghbal A.; Nguyen, Katrina P.; Joiner, Wilsaan M.

2017-01-01

Motor adaptation paradigms provide a quantitative method to study short-term modification of motor commands. Despite the growing understanding of the role motion states (e.g., velocity) play in this form of motor learning, there is little information on the relative stability of memories based on these movement characteristics, especially in comparison to the initial adaptation. Here, we trained subjects to make reaching movements perturbed by force patterns dependent upon either limb position or velocity. Following training, subjects were exposed to a series of error-clamp trials to measure the temporal characteristics of the feedforward motor output during the decay of learning. The compensatory force patterns were largely based on the perturbation kinematic (e.g., velocity), but also showed a small contribution from the other motion kinematic (e.g., position). However, the velocity contribution in response to the position-based perturbation decayed at a slower rate than the position contribution to velocity-based training, suggesting a difference in stability. Next, we modified a previous model of motor adaptation to reflect this difference and simulated the behavior for different learning goals. We were interested in the stability of learning when the perturbations were based on different combinations of limb position or velocity that subsequently resulted in biased amounts of motion-based learning. We trained additional subjects on these combined motion-state perturbations and confirmed the predictions of the model. Specifically, we show that (1) there is a significant separation between the observed gain-space trajectories for the learning and decay of adaptation and (2) for combined motion-state perturbations, the gain associated to changes in limb position decayed at a faster rate than the velocity-dependent gain, even when the position-dependent gain at the end of training was significantly greater. Collectively, these results suggest that the state

Features: Real-Time Adaptive Feature and Document Learning for Web Search.

ERIC Educational Resources Information Center

Chen, Zhixiang; Meng, Xiannong; Fowler, Richard H.; Zhu, Binhai

2001-01-01

Describes Features, an intelligent Web search engine that is able to perform real-time adaptive feature (i.e., keyword) and document learning. Explains how Features learns from users' document relevance feedback and automatically extracts and suggests indexing keywords relevant to a search query, and learns from users' keyword relevance feedback…

Selecting Learning Tasks: Effects of Adaptation and Shared Control on Learning Efficiency and Task Involvement

ERIC Educational Resources Information Center

Corbalan, Gemma; Kester, Liesbeth; van Merrienboer, Jeroen J. G.

2008-01-01

Complex skill acquisition by performing authentic learning tasks is constrained by limited working memory capacity [Baddeley, A. D. (1992). Working memory. "Science, 255", 556-559]. To prevent cognitive overload, task difficulty and support of each newly selected learning task can be adapted to the learner's competence level and perceived task…

Motor learning and cross-limb transfer rely upon distinct neural adaptation processes

PubMed Central

Carroll, Timothy J.; Summers, Jeffery J.; Hinder, Mark R.

2016-01-01

Performance benefits conferred in the untrained limb after unilateral motor practice are termed cross-limb transfer. Although the effect is robust, the neural mechanisms remain incompletely understood. In this study we used noninvasive brain stimulation to reveal that the neural adaptations that mediate motor learning in the trained limb are distinct from those that underlie cross-limb transfer to the opposite limb. Thirty-six participants practiced a ballistic motor task with their right index finger (150 trials), followed by intermittent theta-burst stimulation (iTBS) applied to the trained (contralateral) primary motor cortex (cM1 group), the untrained (ipsilateral) M1 (iM1 group), or the vertex (sham group). After stimulation, another 150 training trials were undertaken. Motor performance and corticospinal excitability were assessed before motor training, pre- and post-iTBS, and after the second training bout. For all groups, training significantly increased performance and excitability of the trained hand, and performance, but not excitability, of the untrained hand, indicating transfer at the level of task performance. The typical facilitatory effect of iTBS on MEPs was reversed for cM1, suggesting homeostatic metaplasticity, and prior performance gains in the trained hand were degraded, suggesting that iTBS interfered with learning. In stark contrast, iM1 iTBS facilitated both performance and excitability for the untrained hand. Importantly, the effects of cM1 and iM1 iTBS on behavior were exclusive to the hand contralateral to stimulation, suggesting that adaptations within the untrained M1 contribute to cross-limb transfer. However, the neural processes that mediate learning in the trained hemisphere vs. transfer in the untrained hemisphere appear distinct. PMID:27169508

Adaptive versus Learner Control in a Multiple Intelligence Learning Environment

ERIC Educational Resources Information Center

Kelly, Declan

2008-01-01

Within the field of technology enhanced learning, adaptive educational systems offer an advanced form of learning environment that attempts to meet the needs of different students. Such systems capture and represent, for each student, various characteristics such as knowledge and traits in an individual learner model. Subsequently, using the…

Psychopathological manifestations of children with intellectual disabilities according to their cognitive and adaptive behavior profile.

PubMed

Tremblay, Karine N; Richer, Louis; Lachance, Lise; Côté, Alain

2010-01-01

Children with intellectual disabilities show deficits in cognitive abilities and adaptive behavior which increase the risk of psychopathological disorders. This exploratory study aims at delineating profiles of children based on their cognitive functioning and adaptive behaviors, and to compare them on psychopathological manifestations. A cognitive assessment and an evaluation of adaptive behaviors are conducted with 52 school-age children receiving services from a rehabilitation center for people with intellectual disabilities. Adaptive behaviors are evaluated by a special educator and a questionnaire concerning psychopathology is filled out by a parent and a teacher. Cluster analyses highlight three profiles among children: Performing, Uncooperative and Non-performing. They differ on cognitive functions, collaboration and in terms of practical abilities of adaptive behaviors. Chi-square tests show significant differences in social competences, but not in problematic behaviors, according to the viewpoint of parents and teachers. Potential explanations are provided to understand the absence of significant differences in problematic behaviors between the three profiles.

Adaptive WTA with an analog VLSI neuromorphic learning chip.

PubMed

Häfliger, Philipp

2007-03-01

In this paper, we demonstrate how a particular spike-based learning rule (where exact temporal relations between input and output spikes of a spiking model neuron determine the changes of the synaptic weights) can be tuned to express rate-based classical Hebbian learning behavior (where the average input and output spike rates are sufficient to describe the synaptic changes). This shift in behavior is controlled by the input statistic and by a single time constant. The learning rule has been implemented in a neuromorphic very large scale integration (VLSI) chip as part of a neurally inspired spike signal image processing system. The latter is the result of the European Union research project Convolution AER Vision Architecture for Real-Time (CAVIAR). Since it is implemented as a spike-based learning rule (which is most convenient in the overall spike-based system), even if it is tuned to show rate behavior, no explicit long-term average signals are computed on the chip. We show the rule's rate-based Hebbian learning ability in a classification task in both simulation and chip experiment, first with artificial stimuli and then with sensor input from the CAVIAR system.

Adaptable Learning Assistant for Item Bank Management

ERIC Educational Resources Information Center

Nuntiyagul, Atorn; Naruedomkul, Kanlaya; Cercone, Nick; Wongsawang, Damras

2008-01-01

We present PKIP, an adaptable learning assistant tool for managing question items in item banks. PKIP is not only able to automatically assist educational users to categorize the question items into predefined categories by their contents but also to correctly retrieve the items by specifying the category and/or the difficulty level. PKIP adapts…

Adaptive System Modeling for Spacecraft Simulation

NASA Technical Reports Server (NTRS)

Thomas, Justin

2011-01-01

This invention introduces a methodology and associated software tools for automatically learning spacecraft system models without any assumptions regarding system behavior. Data stream mining techniques were used to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). Evaluation on historical ISS telemetry data shows that adaptive system modeling reduces simulation error anywhere from 50 to 90 percent over existing approaches. The purpose of the methodology is to outline how someone can create accurate system models from sensor (telemetry) data. The purpose of the software is to support the methodology. The software provides analysis tools to design the adaptive models. The software also provides the algorithms to initially build system models and continuously update them from the latest streaming sensor data. The main strengths are as follows: Creates accurate spacecraft system models without in-depth system knowledge or any assumptions about system behavior. Automatically updates/calibrates system models using the latest streaming sensor data. Creates device specific models that capture the exact behavior of devices of the same type. Adapts to evolving systems. Can reduce computational complexity (faster simulations).

A New Approach to Teaching Biomechanics Through Active, Adaptive, and Experiential Learning.

PubMed

Singh, Anita

2017-07-01

Demand of biomedical engineers continues to rise to meet the needs of healthcare industry. Current training of bioengineers follows the traditional and dominant model of theory-focused curricula. However, the unmet needs of the healthcare industry warrant newer skill sets in these engineers. Translational training strategies such as solving real world problems through active, adaptive, and experiential learning hold promise. In this paper, we report our findings of adding a real-world 4-week problem-based learning unit into a biomechanics capstone course for engineering students. Surveys assessed student perceptions of the activity and learning experience. While students, across three cohorts, felt challenged to solve a real-world problem identified during the simulation lab visit, they felt more confident in utilizing knowledge learned in the biomechanics course and self-directed research. Instructor evaluations indicated that the active and experiential learning approach fostered their technical knowledge and life-long learning skills while exposing them to the components of adaptive learning and innovation.

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.

Impact of Adapted Hypermedia on Undergraduate Students' Learning of Astronomy in an Elearning Environment

NASA Astrophysics Data System (ADS)

Zuel, Brian

The purpose of this dissertation was to examine the effectiveness of matching learners' optimal learning styles to their overall knowledge retention. The study attempted to determine if learners who are placed in an online learning environment that matches their optimal learning styles will retain the information at a higher rate than those learners who are not in an adapted learning environment. There were 56 participants that took one of two lessons; the first lesson was textual based, had no hypertext, and was not influenced heavily by the coherence principle, while the second lesson was multimedia based utilizing hypermedia guided by the coherence principle. Each participant took Felder and Soloman's (1991, 2000) Index of Learning Styles (ILS) questionnaire and was classified using the Felder-Silverman Learning Style Model (FSLSM; 1998) into four individual categories. Groups were separated using the Visual/Verbal section of the FSLSM with 55% (n = 31) of participants going to the adapted group, and 45% (n =25) of participants going to the non-adapted group. Each participant completed an immediate posttest directly after the lesson and a retention posttest a week later. Several repeated measures MANOVA tests were conducted to measure the significance of differences in the tests between groups and within groups. Repeated measures MANOVA tests were conducted to determine if significance existed between the immediate posttest results and the retention posttest results. Also, participants were asked their perspectives if the lesson type they received was beneficial to their perceived learning of the material. Of the 56 students who took part in this study, 31 students were placed in the adapted group and 25 in the non-adapted group based on outcomes of the ILS and the FLSSM. No significant differences were found between groups taking the multimedia lesson and the textual lesson in the immediate posttest. No significant differences were found between the adapted and

Educational Multimedia Profiling Recommendations for Device-Aware Adaptive Mobile Learning

ERIC Educational Resources Information Center

Moldovan, Arghir-Nicolae; Ghergulescu, Ioana; Muntean, Cristina Hava

2014-01-01

Mobile learning is seeing a fast adoption with the increasing availability and affordability of mobile devices such as smartphones and tablets. As the creation and consumption of educational multimedia content on mobile devices is also increasing fast, educators and mobile learning providers are faced with the challenge to adapt multimedia type…

Examining the Relationship between Learning Organization Characteristics and Change Adaptation, Innovation, and Organizational Performance

ERIC Educational Resources Information Center

Kontoghiorghes, Constantine; Awbre, Susan M.; Feurig, Pamela L.

2005-01-01

The main purpose of this exploratory study was to examine the relationship between certain learning organization characteristics and change adaptation, innovation, and bottom-line organizational performance. The following learning organization characteristics were found to be the strongest predictors of rapid change adaptation, quick product or…

Vocal learning in elephants: neural bases and adaptive context

PubMed Central

Stoeger, Angela S; Manger, Paul

2014-01-01

In the last decade clear evidence has accumulated that elephants are capable of vocal production learning. Examples of vocal imitation are documented in African (Loxodonta africana) and Asian (Elephas maximus) elephants, but little is known about the function of vocal learning within the natural communication systems of either species. We are also just starting to identify the neural basis of elephant vocalizations. The African elephant diencephalon and brainstem possess specializations related to aspects of neural information processing in the motor system (affecting the timing and learning of trunk movements) and the auditory and vocalization system. Comparative interdisciplinary (from behavioral to neuroanatomical) studies are strongly warranted to increase our understanding of both vocal learning and vocal behavior in elephants. PMID:25062469

Adaptive and accelerated tracking-learning-detection

NASA Astrophysics Data System (ADS)

Guo, Pengyu; Li, Xin; Ding, Shaowen; Tian, Zunhua; Zhang, Xiaohu

2013-08-01

An improved online long-term visual tracking algorithm, named adaptive and accelerated TLD (AA-TLD) based on Tracking-Learning-Detection (TLD) which is a novel tracking framework has been introduced in this paper. The improvement focuses on two aspects, one is adaption, which makes the algorithm not dependent on the pre-defined scanning grids by online generating scale space, and the other is efficiency, which uses not only algorithm-level acceleration like scale prediction that employs auto-regression and moving average (ARMA) model to learn the object motion to lessen the detector's searching range and the fixed number of positive and negative samples that ensures a constant retrieving time, but also CPU and GPU parallel technology to achieve hardware acceleration. In addition, in order to obtain a better effect, some TLD's details are redesigned, which uses a weight including both normalized correlation coefficient and scale size to integrate results, and adjusts distance metric thresholds online. A contrastive experiment on success rate, center location error and execution time, is carried out to show a performance and efficiency upgrade over state-of-the-art TLD with partial TLD datasets and Shenzhou IX return capsule image sequences. The algorithm can be used in the field of video surveillance to meet the need of real-time video tracking.

Learner Characteristic Based Learning Effort Curve Mode: The Core Mechanism on Developing Personalized Adaptive E-Learning Platform

ERIC Educational Resources Information Center

Hsu, Pi-Shan

2012-01-01

This study aims to develop the core mechanism for realizing the development of personalized adaptive e-learning platform, which is based on the previous learning effort curve research and takes into account the learner characteristics of learning style and self-efficacy. 125 university students from Taiwan are classified into 16 groups according…

Someone has to give in: theta oscillations correlate with adaptive behavior in social bargaining.

PubMed

Billeke, Pablo; Zamorano, Francisco; López, Tamara; Rodriguez, Carlos; Cosmelli, Diego; Aboitiz, Francisco

2014-12-01

During social bargain, one has to both figure out the others' intentions and behave strategically in such a way that the others' behaviors will be consistent with one's expectations. To understand the neurobiological mechanisms underlying these behaviors, we used electroencephalography while subjects played as proposers in a repeated ultimatum game. We found that subjects adapted their offers to obtain more acceptances in the last round and that this adaptation correlated negatively with prefrontal theta oscillations. People with higher prefrontal theta activity related to a rejection did not adapt their offers along the game to maximize their earning. Moreover, between-subject variation in posterior theta oscillations correlated positively with how individual theta activity influenced the change of offer after a rejection, reflecting a process of behavioral adaptation to the others' demands. Interestingly, people adapted better their offers when they knew that they where playing against a computer, although the behavioral adaptation did not correlate with prefrontal theta oscillation. Behavioral changes between human and computer games correlated with prefrontal theta activity, suggesting that low adaptation in human games could be a strategy. Taken together, these results provide evidence for specific roles of prefrontal and posterior theta oscillations in social bargaining. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Someone has to give in: theta oscillations correlate with adaptive behavior in social bargaining

PubMed Central

Zamorano, Francisco; López, Tamara; Rodriguez, Carlos; Cosmelli, Diego; Aboitiz, Francisco

2014-01-01

During social bargain, one has to both figure out the others’ intentions and behave strategically in such a way that the others’ behaviors will be consistent with one’s expectations. To understand the neurobiological mechanisms underlying these behaviors, we used electroencephalography while subjects played as proposers in a repeated ultimatum game. We found that subjects adapted their offers to obtain more acceptances in the last round and that this adaptation correlated negatively with prefrontal theta oscillations. People with higher prefrontal theta activity related to a rejection did not adapt their offers along the game to maximize their earning. Moreover, between-subject variation in posterior theta oscillations correlated positively with how individual theta activity influenced the change of offer after a rejection, reflecting a process of behavioral adaptation to the others’ demands. Interestingly, people adapted better their offers when they knew that they where playing against a computer, although the behavioral adaptation did not correlate with prefrontal theta oscillation. Behavioral changes between human and computer games correlated with prefrontal theta activity, suggesting that low adaptation in human games could be a strategy. Taken together, these results provide evidence for specific roles of prefrontal and posterior theta oscillations in social bargaining. PMID:24493841

Implementation of an Adaptive Learning System Using a Bayesian Network

ERIC Educational Resources Information Center

Yasuda, Keiji; Kawashima, Hiroyuki; Hata, Yoko; Kimura, Hiroaki

2015-01-01

An adaptive learning system is proposed that incorporates a Bayesian network to efficiently gauge learners' understanding at the course-unit level. Also, learners receive content that is adapted to their measured level of understanding. The system works on an iPad via the Edmodo platform. A field experiment using the system in an elementary school…

Assessing Student Behaviors and Motivation for Actively Learning Biology

NASA Astrophysics Data System (ADS)

Moore, Michael Edward

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

Adaptive Web-Assisted Learning System for Students with Specific Learning Disabilities: A Needs Analysis Study

ERIC Educational Resources Information Center

Polat, Elif; Adiguzel, Tufan; Akgun, Ozcan Erkan

2012-01-01

Because there is, currently, no education system for primary school students in grades 1-3 who have specific learning disabilities in Turkey and because such students do not receive sufficient support from face-to-face counseling, a needs analysis was conducted in order to prepare an adaptive, web-assisted learning system according to variables…

Masters of adaptation: learning in late life adjustments.

PubMed

Roberson, Donald N

2005-01-01

The purpose of this research is to understand the relationship between human development in older adults and personal learning. Personal or self-directed learning (SDL) refers to a style of learning where the individual directs, controls, and evaluates what is learned. It may occur with formal classes, but most often takes place in non-formal situations. This study employed a descriptive qualitative design incorporating in-depth, semistructured interviews for data collection. The sample of 10 purposefully selected older adults from a rural area reflected diversity in gender, race, education, and employment. Data analysis was guided by the constant comparative method. The primary late life adjustments of these older adults were in response to having extra time, changes in family, and social and physical loss. This research also indicated that late life adjustments are a primary incentive for self-directed learning. The results of this study indicated that older adults become masters of adaptation through the use of self-directed learning activities.

Multidimensionality of Teachers' Graded Responses for Preschoolers' Stylistic Learning Behavior: The Learning-to-Learn Scales

ERIC Educational Resources Information Center

McDermott, Paul A.; Fantuzzo, John W.; Warley, Heather P.; Waterman, Clare; Angelo, Lauren E.; Gadsden, Vivian L.; Sekino, Yumiko

2011-01-01

Assessment of preschool learning behavior has become very popular as a mechanism to inform cognitive development and promote successful interventions. The most widely used measures offer sound predictions but distinguish only a few types of stylistic learning and lack sensitive growth detection. The Learning-to-Learn Scales was designed to…

Towards Increased Relevance: Context-Adapted Models of the Learning Organization

ERIC Educational Resources Information Center

Örtenblad, Anders

2015-01-01

Purpose: The purposes of this paper are to take a closer look at the relevance of the idea of the learning organization for organizations in different generalized organizational contexts; to open up for the existence of multiple, context-adapted models of the learning organization; and to suggest a number of such models.…

A Demographic Survey of Learning Behaviors among American Students

ERIC Educational Resources Information Center

Schaefer, Barbara A.

2004-01-01

A nationally representative survey of students' learning behaviors observed by classroom teachers of 1,500 school-aged American youth is presented. Participants comprised the standardization cohort of the Learning Behaviors Scale (McDermott, Green, Francis, & Stott, 1999) stratified according to the U.S. Census. Base rates of learning behaviors…

Impact of learning adaptability and time management disposition on study engagement among Chinese baccalaureate nursing students.

PubMed

Liu, Jing-Ying; Liu, Yan-Hui; Yang, Ji-Peng

2014-01-01

The aim of this study was to explore the relationships among study engagement, learning adaptability, and time management disposition in a sample of Chinese baccalaureate nursing students. A convenient sample of 467 baccalaureate nursing students was surveyed in two universities in Tianjin, China. Students completed a questionnaire that included their demographic information, Chinese Utrecht Work Engagement Scale-Student Questionnaire, Learning Adaptability Scale, and Adolescence Time Management Disposition Scale. One-way analysis of variance tests were used to assess the relationship between certain characteristics of baccalaureate nursing students. Pearson correlation was performed to test the correlation among study engagement, learning adaptability, and time management disposition. Hierarchical linear regression analyses were performed to explore the mediating role of time management disposition. The results revealed that study engagement (F = 7.20, P < .01) and learning adaptability (F = 4.41, P < .01) differed across grade groups. Learning adaptability (r = 0.382, P < .01) and time management disposition (r = 0.741, P < .01) were positively related with study engagement. Time management disposition had a partially mediating effect on the relationship between study engagement and learning adaptability. The findings implicate that educators should not only promote interventions to increase engagement of baccalaureate nursing students but also focus on development, investment in adaptability, and time management. Copyright © 2014 Elsevier Inc. All rights reserved.

Learning to recognize rat social behavior: Novel dataset and cross-dataset application.

PubMed

Lorbach, Malte; Kyriakou, Elisavet I; Poppe, Ronald; van Dam, Elsbeth A; Noldus, Lucas P J J; Veltkamp, Remco C

2018-04-15

Social behavior is an important aspect of rodent models. Automated measuring tools that make use of video analysis and machine learning are an increasingly attractive alternative to manual annotation. Because machine learning-based methods need to be trained, it is important that they are validated using data from different experiment settings. To develop and validate automated measuring tools, there is a need for annotated rodent interaction datasets. Currently, the availability of such datasets is limited to two mouse datasets. We introduce the first, publicly available rat social interaction dataset, RatSI. We demonstrate the practical value of the novel dataset by using it as the training set for a rat interaction recognition method. We show that behavior variations induced by the experiment setting can lead to reduced performance, which illustrates the importance of cross-dataset validation. Consequently, we add a simple adaptation step to our method and improve the recognition performance. Most existing methods are trained and evaluated in one experimental setting, which limits the predictive power of the evaluation to that particular setting. We demonstrate that cross-dataset experiments provide more insight in the performance of classifiers. With our novel, public dataset we encourage the development and validation of automated recognition methods. We are convinced that cross-dataset validation enhances our understanding of rodent interactions and facilitates the development of more sophisticated recognition methods. Combining them with adaptation techniques may enable us to apply automated recognition methods to a variety of animals and experiment settings. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Learning and Thinking: A Behavioral Treatise on Abuse and Antisocial Behavior in Young Criminal Offenders

ERIC Educational Resources Information Center

Prather, Walter; Golden, Jeannie A.

2009-01-01

Social learning theory provides a useful conceptual framework for understanding abuse and the teaching and learning of antisocial or criminal behavior in young offenders. This article examines social learning theory and the quality of parent-child relationships from the perspective of behavioral analysis, and provides a rationale for a…

Designing Adaptive Instruction for Teams: A Meta-Analysis

ERIC Educational Resources Information Center

Sottilare, Robert A.; Shawn Burke, C.; Salas, Eduardo; Sinatra, Anne M.; Johnston, Joan H.; Gilbert, Stephen B.

2018-01-01

The goal of this research was the development of a practical architecture for the computer-based tutoring of teams. This article examines the relationship of team behaviors as antecedents to successful team performance and learning during adaptive instruction guided by Intelligent Tutoring Systems (ITSs). Adaptive instruction is a training or…

Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

PubMed

Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

2011-07-01

In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Longitudinal Examination of Adaptive Behavior in Autism Spectrum Disorders: Influence of Executive Function

ERIC Educational Resources Information Center

Pugliese, Cara E.; Anthony, Laura Gutermuth; Strang, John F.; Dudley, Katerina; Wallace, Gregory L.; Naiman, Daniel Q.; Kenworthy, Lauren

2016-01-01

This study characterizes longitudinal change in adaptive behavior in 64 children and adolescents with autism spectrum disorder (ASD) without intellectual disability evaluated on multiple occasions, and examines whether prior estimate of executive function (EF) problems predicts future adaptive behavior scores. Compared to standardized estimates…

How Does Self-Regulated Learning Relate to Active Procrastination and Other Learning Behaviors?

ERIC Educational Resources Information Center

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

2016-01-01

This research investigates the relationship between self-regulated learning awareness, procrastination, and learning behaviors in a blended learning environment. Participants included 179 first-grade university students attending a blended learning-style class that used a learning management system. Data were collected using questionnaires on…

Behavior and adaptive functioning in adolescents with Down syndrome: specifying targets for intervention.

PubMed

Jacola, Lisa M; Hickey, Francis; Howe, Steven R; Esbensen, Anna; Shear, Paula K

2014-01-01

Research suggests that adolescents with Down syndrome experience increased behavior problems as compared to age matched peers; however, few studies have examined how these problems relate to adaptive functioning. The primary aim of this study was to characterize behavior in a sample of adolescents with Down syndrome using two widely-used caregiver reports: the Behavioral Assessment System for Children, 2 nd Edition (BASC-2) and Child Behavioral Checklist (CBCL). The clinical utility of the BASC-2 as a measure of behavior and adaptive functioning in adolescents with Down syndrome was also examined. Fifty-two adolescents with Down syndrome between the ages of 12 and 18 (24 males) completed the Peabody Picture Vocabulary Test, 4 th Edition (PPVT-IV) as an estimate of cognitive ability. Caregivers completed the BASC-2 and the CBCL for each participant. A significant proportion of the sample was reported to demonstrate behavior problems, particularly related to attention and social participation. The profile of adaptive function was variable, with caregivers most frequently rating impairment in skills related to activities of daily living and functional communication. Caregiver ratings did not differ by gender and were not related to age or estimated cognitive ability. Caregiver ratings of attention problems on the BASC-2 accounted for a significant proportion of variance in Activities of Daily Living ( Adj R 2 = 0.30) , Leadership ( Adj R 2 = 0.30) Functional Communication ( Adj R 2 = 0.28, Adaptability ( Adj R 2 = 0.29), and Social Skills ( Adj R 2 = 0.17). Higher frequencies of symptoms related to social withdrawal added incremental predictive validity for Functional Communication, Leadership, and Social Skills. Convergent validity between the CBCL and BASC-2 was poor when compared with expectations based on the normative sample. Our results confirm and extend previous findings by describing relationships between specific behavior problems and targeted areas of

Behavior and adaptive functioning in adolescents with Down syndrome: specifying targets for intervention

PubMed Central

Jacola, Lisa M.; Hickey, Francis; Howe, Steven R.; Esbensen, Anna; Shear, Paula K.

2016-01-01

Background Research suggests that adolescents with Down syndrome experience increased behavior problems as compared to age matched peers; however, few studies have examined how these problems relate to adaptive functioning. The primary aim of this study was to characterize behavior in a sample of adolescents with Down syndrome using two widely-used caregiver reports: the Behavioral Assessment System for Children, 2nd Edition (BASC-2) and Child Behavioral Checklist (CBCL). The clinical utility of the BASC-2 as a measure of behavior and adaptive functioning in adolescents with Down syndrome was also examined. Methods Fifty-two adolescents with Down syndrome between the ages of 12 and 18 (24 males) completed the Peabody Picture Vocabulary Test, 4th Edition (PPVT-IV) as an estimate of cognitive ability. Caregivers completed the BASC-2 and the CBCL for each participant. Results A significant proportion of the sample was reported to demonstrate behavior problems, particularly related to attention and social participation. The profile of adaptive function was variable, with caregivers most frequently rating impairment in skills related to activities of daily living and functional communication. Caregiver ratings did not differ by gender and were not related to age or estimated cognitive ability. Caregiver ratings of attention problems on the BASC-2 accounted for a significant proportion of variance in Activities of Daily Living (Adj R2 = 0.30), Leadership (Adj R2 = 0.30) Functional Communication (Adj R2 = 0.28, Adaptability (Adj R2 = 0.29), and Social Skills (Adj R2 = 0.17). Higher frequencies of symptoms related to social withdrawal added incremental predictive validity for Functional Communication, Leadership, and Social Skills. Convergent validity between the CBCL and BASC-2 was poor when compared with expectations based on the normative sample. Conclusion Our results confirm and extend previous findings by describing relationships between specific behavior problems

Learning Behaviors Mediating the Effects of Behavior Problems on Academic Outcomes

ERIC Educational Resources Information Center

Escalon, Ximena Dominguez; Greenfield, Daryl

2009-01-01

This study examined the relationships between behavior problems, learning behaviors, and educational outcomes for at-risk preschool children. A sample of Head Start children (N = 196) was selected in the southeast United States. Behavior problems were assessed using the Devereux Early Childhood Assessment (LeBuffe & Naglieri, 1999) and…

Second Graders Learn Animal Adaptations through Form and Function Analogy Object Boxes

ERIC Educational Resources Information Center

Rule, Audrey C.; Baldwin, Samantha; Schell, Robert

2008-01-01

This study examined the use of form and function analogy object boxes to teach second graders (n = 21) animal adaptations. The study used a pretest-posttest design to examine animal adaptation content learned through focused analogy activities as compared with reading and Internet searches for information about adaptations of animals followed by…

Frustration-Instigated Behavior and Learned Helplessness.

ERIC Educational Resources Information Center

Winefield, Anthony H.

1979-01-01

Compares M. E. P. Seligman's recent work on learned helplessness with N. R. F. Maier's 30-year-old work on frustration behavior. Notes striking similarities between the two approaches. Concludes that the learned helplessness model might explain the "abnormal fixations" that Maier reported. (Author/RL)

Behavioral consequences of innate preferences and olfactory learning in hawkmoth–flower interactions

PubMed Central

Riffell, Jeffrey A.; Alarcón, Ruben; Abrell, Leif; Davidowitz, Goggy; Bronstein, Judith L.; Hildebrand, John G.

2008-01-01

Spatiotemporal variability in floral resources can have ecological and evolutionary consequences for both plants and the pollinators on which they depend. Seldom, however, can patterns of flower abundance and visitation in the field be linked with the behavioral mechanisms that allow floral visitors to persist when a preferred resource is scarce. To explore these mechanisms better, we examined factors controlling floral preference in the hawkmoth Manduca sexta in the semiarid grassland of Arizona. Here, hawkmoths forage primarily on flowers of the bat-adapted agave, Agave palmeri, but shift to the moth-adapted flowers of their larval host plant, Datura wrightii, when these become abundant. Both plants emit similar concentrations of floral odor, but scent composition, nectar, and flower reflectance are distinct between the two species, and A. palmeri flowers provide six times as much chemical energy as flowers of D. wrightii. Behavioral experiments with both naïve and experienced moths revealed that hawkmoths learn to feed from agave flowers through olfactory conditioning but readily switch to D. wrightii flowers, for which they are the primary pollinator, based on an innate odor preference. Behavioral flexibility and the olfactory contrast between flowers permit the hawkmoths to persist within a dynamic environment, while at the same time to function as the major pollinator of one plant species. PMID:18305169

Fault-tolerant nonlinear adaptive flight control using sliding mode online learning.

PubMed

Krüger, Thomas; Schnetter, Philipp; Placzek, Robin; Vörsmann, Peter

2012-08-01

An expanded nonlinear model inversion flight control strategy using sliding mode online learning for neural networks is presented. The proposed control strategy is implemented for a small unmanned aircraft system (UAS). This class of aircraft is very susceptible towards nonlinearities like atmospheric turbulence, model uncertainties and of course system failures. Therefore, these systems mark a sensible testbed to evaluate fault-tolerant, adaptive flight control strategies. Within this work the concept of feedback linearization is combined with feed forward neural networks to compensate for inversion errors and other nonlinear effects. Backpropagation-based adaption laws of the network weights are used for online training. Within these adaption laws the standard gradient descent backpropagation algorithm is augmented with the concept of sliding mode control (SMC). Implemented as a learning algorithm, this nonlinear control strategy treats the neural network as a controlled system and allows a stable, dynamic calculation of the learning rates. While considering the system's stability, this robust online learning method therefore offers a higher speed of convergence, especially in the presence of external disturbances. The SMC-based flight controller is tested and compared with the standard gradient descent backpropagation algorithm in the presence of system failures. Copyright © 2012 Elsevier Ltd. All rights reserved.

Using Mobile Learning: Determinates Impacting Behavioral Intention

ERIC Educational Resources Information Center

Lowenthal, Jeffrey N.

2010-01-01

This study examined the factors or determinates that impact the behavioral intention of students to use mobile learning (m-learning) technology. These determinates include performance expectancy, effort expectancy, and self-management of learning, all mediated by age, gender, or both. Regression coefficients showed strong and significant…

On learning navigation behaviors for small mobile robots with reservoir computing architectures.

PubMed

Antonelo, Eric Aislan; Schrauwen, Benjamin

2015-04-01

This paper proposes a general reservoir computing (RC) learning framework that can be used to learn navigation behaviors for mobile robots in simple and complex unknown partially observable environments. RC provides an efficient way to train recurrent neural networks by letting the recurrent part of the network (called reservoir) be fixed while only a linear readout output layer is trained. The proposed RC framework builds upon the notion of navigation attractor or behavior that can be embedded in the high-dimensional space of the reservoir after learning. The learning of multiple behaviors is possible because the dynamic robot behavior, consisting of a sensory-motor sequence, can be linearly discriminated in the high-dimensional nonlinear space of the dynamic reservoir. Three learning approaches for navigation behaviors are shown in this paper. The first approach learns multiple behaviors based on the examples of navigation behaviors generated by a supervisor, while the second approach learns goal-directed navigation behaviors based only on rewards. The third approach learns complex goal-directed behaviors, in a supervised way, using a hierarchical architecture whose internal predictions of contextual switches guide the sequence of basic navigation behaviors toward the goal.

Motor learning and cross-limb transfer rely upon distinct neural adaptation processes.

PubMed

Stöckel, Tino; Carroll, Timothy J; Summers, Jeffery J; Hinder, Mark R

2016-08-01

Performance benefits conferred in the untrained limb after unilateral motor practice are termed cross-limb transfer. Although the effect is robust, the neural mechanisms remain incompletely understood. In this study we used noninvasive brain stimulation to reveal that the neural adaptations that mediate motor learning in the trained limb are distinct from those that underlie cross-limb transfer to the opposite limb. Thirty-six participants practiced a ballistic motor task with their right index finger (150 trials), followed by intermittent theta-burst stimulation (iTBS) applied to the trained (contralateral) primary motor cortex (cM1 group), the untrained (ipsilateral) M1 (iM1 group), or the vertex (sham group). After stimulation, another 150 training trials were undertaken. Motor performance and corticospinal excitability were assessed before motor training, pre- and post-iTBS, and after the second training bout. For all groups, training significantly increased performance and excitability of the trained hand, and performance, but not excitability, of the untrained hand, indicating transfer at the level of task performance. The typical facilitatory effect of iTBS on MEPs was reversed for cM1, suggesting homeostatic metaplasticity, and prior performance gains in the trained hand were degraded, suggesting that iTBS interfered with learning. In stark contrast, iM1 iTBS facilitated both performance and excitability for the untrained hand. Importantly, the effects of cM1 and iM1 iTBS on behavior were exclusive to the hand contralateral to stimulation, suggesting that adaptations within the untrained M1 contribute to cross-limb transfer. However, the neural processes that mediate learning in the trained hemisphere vs. transfer in the untrained hemisphere appear distinct. Copyright © 2016 the American Physiological Society.

The Impact on Career Development of Learning Opportunities and Learning Behavior at Work.

ERIC Educational Resources Information Center

Van der Sluis, Lidewey E. C.; Poell, Rob E.

2003-01-01

Survey responses were received in 1998 (n=63) and 1999 (n=98) from master's of business administration graduates. Hierarchical regression and difference of means tests found that career development depended on learning opportunities at work and on individual learning behavior. Behavior was more predictive of objective career development measures,…

A Context-Aware Self-Adaptive Fractal Based Generalized Pedagogical Agent Framework for Mobile Learning

ERIC Educational Resources Information Center

Boulehouache, Soufiane; Maamri, Ramdane; Sahnoun, Zaidi

2015-01-01

The Pedagogical Agents (PAs) for Mobile Learning (m-learning) must be able not only to adapt the teaching to the learner knowledge level and profile but also to ensure the pedagogical efficiency within unpredictable changing runtime contexts. Therefore, to deal with this issue, this paper proposes a Context-aware Self-Adaptive Fractal Component…

Does Visuomotor Adaptation Proceed in Stages? An Examination of the Learning Model by Chein and Schneider (2012).

PubMed

Simon, Anja; Bock, Otmar

2015-01-01

A new 3-stage model based on neuroimaging evidence is proposed by Chein and Schneider (2012). Each stage is associated with different brain regions, and draws on cognitive abilities: the first stage on creativity, the second on selective attention, and the third on automatic processing. The purpose of the present study was to scrutinize the validity of this model for 1 popular learning paradigm, visuomotor adaptation. Participants completed tests for creativity, selective attention and automated processing before attending in a pointing task with adaptation to a 60° rotation of visual feedback. To examine the relationship between cognitive abilities and motor learning at different times of practice, associations between cognitive and adaptation scores were calculated repeatedly throughout adaptation. The authors found no benefit of high creativity for adaptive performance. High levels of selective attention were positively associated with early adaptation, but hardly with late adaptation and de-adaptation. High levels of automated execution were beneficial for late adaptation, but hardly for early and de-adaptation. From this we conclude that Chein and Schneider's first learning stage is difficult to confirm by research on visuomotor adaptation, and that the other 2 learning stages rather relate to workaround strategies than to actual adaptive recalibration.

Distance learning education for mitigation/adaptation policy: a case study

NASA Astrophysics Data System (ADS)

Slini, T.; Giama, E.; Papadopoulou, Ch.-O.

2016-02-01

The efficient training of young environmental scientists has proven to be a challenging goal over the last years, while several dynamic initiatives have been developed aiming to provide complete and consistent education. A successful example is the e-learning course for participants mainly coming from emerging economy countries 'Development of mitigation/adaptation policy portfolios' organised in the frame of the project Promitheas4: Knowledge transfer and research needs for preparing mitigation/adaptation policy portfolios, aiming to provide knowledge transfer, enhance new skills and competencies, using modern didactic approaches and learning technologies. The present paper addresses the experience and the results of these actions, which seem promising and encouraging and were broadly welcomed by the participants.

Adaptation of Conceptions of Learning Science Questionnaire into Turkish and Science Teacher Candidates' Conceptions of Learning Science

ERIC Educational Resources Information Center

Bahçivan, Eralp; Kapucu, Serkan

2014-01-01

The purposes of this study were to (1) adapt an instrument "The Conceptions of Learning Science (COLS) questionnaire" into Turkish, and (2) to determine Turkish science teacher candidates' COLS. Adapting the instrument four steps were followed. Firstly, COLS questionnaire was translated into Turkish. Secondly, COLS questionnaire was…

Compensatory Expressive Behavior for Facial Paralysis: Adaptation to Congenital or Acquired Disability

PubMed Central

Bogart, Kathleen R.; Tickle-Degnen, Linda; Ambady, Nalini

2015-01-01

Purpose/Objective Although there has been little research on the adaptive behavior of people with congenital compared to acquired disability, there is reason to predict that people with congenital conditions may be better adapted because they have lived with their conditions for their entire lives (Smart, 2008). We examined whether people with congenital facial paralysis (FP), compared to people with acquired FP, compensate more for impoverished facial expression by using alternative channels of expression (i.e. voice and body). Research Method/Design Participants with congenital (n = 13) and acquired (n = 14) FP were videotaped while recalling emotional events. Main Outcome Measures Expressive verbal behavior was measured using the Linguistic Inquiry Word Count (Pennebaker, Booth & Francis, 2007). Nonverbal behavior and FP severity were rated by trained coders. Results People with congenital FP, compared to acquired FP, used more compensatory expressive verbal and nonverbal behavior in their language, voices, and bodies. The extent of FP severity had little effect on compensatory expressivity. Conclusions/Implications This study provides the first behavioral evidence that people with congenital FP use more adaptations to express themselves than people with acquired FP. These behaviors could inform social functioning interventions for people with FP. PMID:22369116

Compensatory expressive behavior for facial paralysis: adaptation to congenital or acquired disability.

PubMed

Bogart, Kathleen R; Tickle-Degnen, Linda; Ambady, Nalini

2012-02-01

Although there has been little research on the adaptive behavior of people with congenital compared to acquired disability, there is reason to predict that people with congenital conditions may be better adapted because they have lived with their conditions for their entire lives (Smart, 2008). We examined whether people with congenital facial paralysis (FP), compared to people with acquired FP, compensate more for impoverished facial expression by using alternative channels of expression (i.e., voice and body). Participants with congenital (n = 13) and acquired (n = 14) FP were videotaped while recalling emotional events. Expressive verbal behavior was measured using the Linguistic Inquiry Word Count (Pennebaker, Booth, & Francis, 2007). Nonverbal behavior and FP severity were rated by trained coders. People with congenital FP, compared to acquired FP, used more compensatory expressive verbal and nonverbal behavior in their language, voices, and bodies. The extent of FP severity had little effect on compensatory expressivity. This study provides the first behavioral evidence that people with congenital FP use more adaptations to express themselves than people with acquired FP. These behaviors could inform social functioning interventions for people with FP.

Sleep benefits consolidation of visuo-motor adaptation learning in older adults.

PubMed

Mantua, Janna; Baran, Bengi; Spencer, Rebecca M C

2016-02-01

Sleep is beneficial for performance across a range of memory tasks in young adults, but whether memories are similarly consolidated in older adults is less clear. Performance benefits have been observed following sleep in older adults for declarative learning tasks, but this benefit may be reduced for non-declarative, motor skill learning tasks. To date, studies of sleep-dependent consolidation of motor learning in older adults are limited to motor sequence tasks. To examine whether reduced sleep-dependent consolidation in older adults is generalizable to other forms of motor skill learning, we examined performance changes over intervals of sleep and wake in young (n = 62) and older adults (n = 61) using a mirror-tracing task, which assesses visuo-motor adaptation learning. Participants learned the task either in the morning or in evening, and performance was assessed following a 12-h interval containing overnight sleep or daytime wake. Contrary to our prediction, both young adults and older adults exhibited sleep-dependent gains in visuo-motor adaptation. There was a correlation between performance improvement over sleep and percent of the night in non-REM stage 2 sleep. These results indicate that motor skill consolidation remains intact with increasing age although this relationship may be limited to specific forms of motor skill learning.

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.

Adaptive Modeling of the International Space Station Electrical Power System

NASA Technical Reports Server (NTRS)

Thomas, Justin Ray

2007-01-01

Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

The Impact of Individual Differences on E-Learning System Behavioral Intention

NASA Astrophysics Data System (ADS)

Liao, Peiwen; Yu, Chien; Yi, Chincheh

This study investigated the impact of contingent variables on the relationship between four predictors and employees' behavioral intention with e-learning. Seven hundred and twenty-two employees in online training and education were asked to answer questionnaires about their learning styles, perceptions of the quality of the proposed predictors and behavioral intention with e-learning systems. The results of analysis showed that three contingent variables, gender, job title and industry, significantly influenced the perceptions of predictors and employees' behavioral intention with the e-learning system. This study also found a statistically significant moderating effect of two contingent variables, gender, job title and industry, on the relationship between predictors and e-learning system behavioral intention. The results suggest that a serious consideration of contingent variables is crucial for improving e-learning system behavioral intention. The implications of these results for the management of e-learning systems are discussed.

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.

Providing QoS through machine-learning-driven adaptive multimedia applications.

PubMed

Ruiz, Pedro M; Botía, Juan A; Gómez-Skarmeta, Antonio

2004-06-01

We investigate the optimization of the quality of service (QoS) offered by real-time multimedia adaptive applications through machine learning algorithms. These applications are able to adapt in real time their internal settings (i.e., video sizes, audio and video codecs, among others) to the unpredictably changing capacity of the network. Traditional adaptive applications just select a set of settings to consume less than the available bandwidth. We propose a novel approach in which the selected set of settings is the one which offers a better user-perceived QoS among all those combinations which satisfy the bandwidth restrictions. We use a genetic algorithm to decide when to trigger the adaptation process depending on the network conditions (i.e., loss-rate, jitter, etc.). Additionally, the selection of the new set of settings is done according to a set of rules which model the user-perceived QoS. These rules are learned using the SLIPPER rule induction algorithm over a set of examples extracted from scores provided by real users. We will demonstrate that the proposed approach guarantees a good user-perceived QoS even when the network conditions are constantly changing.

Variability in Adaptive Behavior in Autism: Evidence for the Importance of Family History

ERIC Educational Resources Information Center

Mazefsky, Carla A.; Williams, Diane L.; Minshew, Nancy J.

2008-01-01

Adaptive behavior in autism is highly variable and strongly related to prognosis. This study explored family history as a potential source of variability in adaptive behavior in autism. Participants included 77 individuals (mean age = 18) with average or better intellectual ability and autism. Parents completed the Family History Interview about…

Static aeroelastic behavior of an adaptive laminated piezoelectric composite wing

NASA Technical Reports Server (NTRS)

Weisshaar, T. A.; Ehlers, S. M.

1990-01-01

The effect of using an adaptive material to modify the static aeroelastic behavior of a uniform wing is examined. The wing structure is idealized as a laminated sandwich structure with piezoelectric layers in the upper and lower skins. A feedback system that senses the wing root loads applies a constant electric field to the piezoelectric actuator. Modification of pure torsional deformaton behavior and pure bending deformation are investigated, as is the case of an anisotropic composite swept wing. The use of piezoelectric actuators to create an adaptive structure is found to alter static aeroelastic behavior in that the proper choice of the feedback gain can increase or decrease the aeroelastic divergence speed. This concept also may be used to actively change the lift effectiveness of a wing. The ability to modify static aeroelastic behavior is limited by physical limitations of the piezoelectric material and the manner in which it is integrated into the parent structure.

Cerebellar contribution to locomotor behavior: A neurodevelopmental perspective.

PubMed

Sathyanesan, Aaron; Gallo, Vittorio

2018-04-30

The developmental trajectory of the formation of cerebellar circuitry has significant implications for locomotor plasticity and adaptive learning at later stages. While there is a wealth of knowledge on the development of locomotor behavior in human infants, children, and adolescents, pre-clinical animal models have fallen behind on the study of the emergence of behavioral motifs in locomotor function across postnatal development. Since cerebellar development is protracted, it is subject to higher risk of genetic or environmental disruption, potentially leading to abnormal behavioral development. This highlights the need for more sophisticated and specific functional analyses of adaptive cerebellar behavior within the context of whole-body locomotion across the entire span of postnatal development. Here we review evidence on cerebellar contribution to adaptive locomotor behavior, highlighting methodologies employed to quantify and categorize behavior at different developmental stages, with the ultimate goal of following the course of early behavioral alterations in neurodevelopmental disorders. Since experimental paradigms used to study cerebellar behavior are lacking in both specificity and applicability to locomotor contexts, we highlight the use of the Erasmus Ladder - an advanced, computerized, fully automated system to quantify adaptive cerebellar learning in conjunction with locomotor function. Finally, we emphasize the need to develop objective, quantitative, behavioral tasks which can track changes in developmental trajectories rather than endpoint measurement at the adult stage of behavior. Copyright © 2018 Elsevier Inc. All rights reserved.

Adaptation Criteria for the Personalised Delivery of Learning Materials: A Multi-Stage Empirical Investigation

ERIC Educational Resources Information Center

Thalmann, Stefan

2014-01-01

Personalised e-Learning represents a major step-change from the one-size-fits-all approach of traditional learning platforms to a more customised and interactive provision of learning materials. Adaptive learning can support the learning process by tailoring learning materials to individual needs. However, this requires the initial preparation of…

A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

PubMed

Ingram, James N; Howard, Ian S; Flanagan, J Randall; Wolpert, Daniel M

2011-09-01

Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics

Contrarian behavior in a complex adaptive system

NASA Astrophysics Data System (ADS)

Liang, Y.; An, K. N.; Yang, G.; Huang, J. P.

2013-01-01

Contrarian behavior is a kind of self-organization in complex adaptive systems (CASs). Here we report the existence of a transition point in a model resource-allocation CAS with contrarian behavior by using human experiments, computer simulations, and theoretical analysis. The resource ratio and system predictability serve as the tuning parameter and order parameter, respectively. The transition point helps to reveal the positive or negative role of contrarian behavior. This finding is in contrast to the common belief that contrarian behavior always has a positive role in resource allocation, say, stabilizing resource allocation by shrinking the redundancy or the lack of resources. It is further shown that resource allocation can be optimized at the transition point by adding an appropriate size of contrarians. This work is also expected to be of value to some other fields ranging from management and social science to ecology and evolution.

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.

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.

An adaptive learning control system for large flexible structures

NASA Technical Reports Server (NTRS)

Thau, F. E.

1985-01-01

The objective of the research has been to study the design of adaptive/learning control systems for the control of large flexible structures. In the first activity an adaptive/learning control methodology for flexible space structures was investigated. The approach was based on using a modal model of the flexible structure dynamics and an output-error identification scheme to identify modal parameters. In the second activity, a least-squares identification scheme was proposed for estimating both modal parameters and modal-to-actuator and modal-to-sensor shape functions. The technique was applied to experimental data obtained from the NASA Langley beam experiment. In the third activity, a separable nonlinear least-squares approach was developed for estimating the number of excited modes, shape functions, modal parameters, and modal amplitude and velocity time functions for a flexible structure. In the final research activity, a dual-adaptive control strategy was developed for regulating the modal dynamics and identifying modal parameters of a flexible structure. A min-max approach was used for finding an input to provide modal parameter identification while not exceeding reasonable bounds on modal displacement.

Behavioral Profiling of Scada Network Traffic Using Machine Learning Algorithms

DTIC Science & Technology

2014-03-27

BEHAVIORAL PROFILING OF SCADA NETWORK TRAFFIC USING MACHINE LEARNING ALGORITHMS THESIS Jessica R. Werling, Captain, USAF AFIT-ENG-14-M-81 DEPARTMENT...subject to copyright protection in the United States. AFIT-ENG-14-M-81 BEHAVIORAL PROFILING OF SCADA NETWORK TRAFFIC USING MACHINE LEARNING ...AFIT-ENG-14-M-81 BEHAVIORAL PROFILING OF SCADA NETWORK TRAFFIC USING MACHINE LEARNING ALGORITHMS Jessica R. Werling, B.S.C.S. Captain, USAF Approved

Self-regulatory Behaviors and Approaches to Learning of Arts Students: A Comparison Between Professional Training and English Learning.

PubMed

Tseng, Min-Chen; Chen, Chia-Cheng

2017-06-01

This study investigated the self-regulatory behaviors of arts students, namely memory strategy, goal-setting, self-evaluation, seeking assistance, environmental structuring, learning responsibility, and planning and organizing. We also explored approaches to learning, including deep approach (DA) and surface approach (SA), in a comparison between students' professional training and English learning. The participants consisted of 344 arts majors. The Academic Self-Regulation Questionnaire and the Revised Learning Process Questionnaire were adopted to examine students' self-regulatory behaviors and their approaches to learning. The results show that a positive and significant correlation was found in students' self-regulatory behaviors between professional training and English learning. The results indicated that increases in using self-regulatory behaviors in professional training were associated with increases in applying self-regulatory behaviors in learning English. Seeking assistance, self-evaluation, and planning and organizing were significant predictors for learning English. In addition, arts students used the deep approach more often than the surface approach in both their professional training and English learning. A positive correlation was found in DA, whereas a negative correlation was shown in SA between students' self-regulatory behaviors and their approaches to learning. Students with high self-regulation adopted a deep approach, and they applied the surface approach less in professional training and English learning. In addition, a SEM model confirmed that DA had a positive influence; however, SA had a negative influence on self-regulatory behaviors.

Cognitive and adaptive behavior profiles in Smith-Magenis syndrome.

PubMed

Madduri, Niru; Peters, Sarika U; Voigt, Robert G; Llorente, Antolin M; Lupski, James R; Potocki, Lorraine

2006-06-01

Smith-Magenis syndrome (SMS) is a multiple congenital anomalies and mental retardation syndrome associated with an interstitial deletion of chromosome 17 band p11.2. The incidence of this microdeletion syndrome is estimated to be 1 in 25,000 individuals. Persons with SMS have a distinctive neurobehavioral phenotype that is characterized by aggressive and self-injurious behaviors and significant sleep disturbances. From December 1990 through September 1999, 58 persons with SMS were enrolled in a 5-day multidisciplinary clinical protocol. Developmental assessments consisting of cognitive level and adaptive behavior were completed in 57 persons. Most patients functioned in the mild-to-moderate range of mental retardation. In addition, we report that patients with SMS have low adaptive functioning with relative strengths in socialization and relative weakness in daily living skills. These data were analyzed in light of the molecular extent of the microdeletion within 17p11.2. We found that the level of cognitive and adaptive functioning does depend on deletion size, and that a small percentage of SMS patients have cognitive function in the borderline range.

Caregiver Behaviors and Adaptive Behavior Development of Very Young Children in Home Care and Daycare.

ERIC Educational Resources Information Center

Altman, Jennifer Schroer; Mills, Belen Collantes

The purpose of this study was to determine the effect of home-mother care and day care caregiver behaviors on the adaptive behavior development of infants between 18 and 24 months of age. Other variables under investigation included two indices of socioeconomic status: occupation and education of parents. The sample consisted of 72 children.…

Evaluation Framework Based on Fuzzy Measured Method in Adaptive Learning Systems

ERIC Educational Resources Information Center

Ounaies, Houda Zouari; Jamoussi, Yassine; Ben Ghezala, Henda Hajjami

2008-01-01

Currently, e-learning systems are mainly web-based applications and tackle a wide range of users all over the world. Fitting learners' needs is considered as a key issue to guaranty the success of these systems. Many researches work on providing adaptive systems. Nevertheless, evaluation of the adaptivity is still in an exploratory phase.…

ActiveTutor: Towards More Adaptive Features in an E-Learning Framework

ERIC Educational Resources Information Center

Fournier, Jean-Pierre; Sansonnet, Jean-Paul

2008-01-01

Purpose: This paper aims to sketch the emerging notion of auto-adaptive software when applied to e-learning software. Design/methodology/approach: The study and the implementation of the auto-adaptive architecture are based on the operational framework "ActiveTutor" that is used for teaching the topic of computer science programming in first-grade…

Brain-behavioral adaptability predicts response to cognitive behavioral therapy for emotional disorders: A person-centered event-related potential study.

PubMed

Stange, Jonathan P; MacNamara, Annmarie; Kennedy, Amy E; Hajcak, Greg; Phan, K Luan; Klumpp, Heide

2017-06-23

Single-trial-level analyses afford the ability to link neural indices of elaborative attention (such as the late positive potential [LPP], an event-related potential) with downstream markers of attentional processing (such as reaction time [RT]). This approach can provide useful information about individual differences in information processing, such as the ability to adapt behavior based on attentional demands ("brain-behavioral adaptability"). Anxiety and depression are associated with maladaptive information processing implicating aberrant cognition-emotion interactions, but whether brain-behavioral adaptability predicts response to psychotherapy is not known. We used a novel person-centered, trial-level analysis approach to link neural indices of stimulus processing to behavioral responses and to predict treatment outcome. Thirty-nine patients with anxiety and/or depression received 12 weeks of cognitive behavioral therapy (CBT). Prior to treatment, patients performed a speeded reaction-time task involving briefly-presented pairs of aversive and neutral pictures while electroencephalography was recorded. Multilevel modeling demonstrated that larger LPPs predicted slower responses on subsequent trials, suggesting that increased attention to the task-irrelevant nature of pictures interfered with reaction time on subsequent trials. Whereas using LPP and RT averages did not distinguish CBT responders from nonresponders, in trial-level analyses individuals who demonstrated greater ability to benefit behaviorally (i.e., faster RT) from smaller LPPs on the previous trial (greater brain-behavioral adaptability) were more likely to respond to treatment and showed greater improvements in depressive symptoms. These results highlight the utility of trial-level analyses to elucidate variability in within-subjects, brain-behavioral attentional coupling in the context of emotion processing, in predicting response to CBT for emotional disorders. Copyright © 2017 Elsevier Ltd

Neural robust stabilization via event-triggering mechanism and adaptive learning technique.

PubMed

Wang, Ding; Liu, Derong

2018-06-01

The robust control synthesis of continuous-time nonlinear systems with uncertain term is investigated via event-triggering mechanism and adaptive critic learning technique. We mainly focus on combining the event-triggering mechanism with adaptive critic designs, so as to solve the nonlinear robust control problem. This can not only make better use of computation and communication resources, but also conduct controller design from the view of intelligent optimization. Through theoretical analysis, the nonlinear robust stabilization can be achieved by obtaining an event-triggered optimal control law of the nominal system with a newly defined cost function and a certain triggering condition. The adaptive critic technique is employed to facilitate the event-triggered control design, where a neural network is introduced as an approximator of the learning phase. The performance of the event-triggered robust control scheme is validated via simulation studies and comparisons. The present method extends the application domain of both event-triggered control and adaptive critic control to nonlinear systems possessing dynamical uncertainties. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Cultural Adaptation of Dialectical Behavior Therapy in Nepal

PubMed Central

Ramaiya, Megan K.; Fiorillo, Devika; Regmi, Upasana; Robins, Clive J.; Kohrt, Brandon A.

2017-01-01

Growing evidence exists on the potential for adapting evidence-based interventions for low- and-middle-income countries (LMIC). One opportunity that has received limited attention is the adaptation of psychotherapies developed in high-income countries (HIC) based on principles from LMIC cultural groups. Dialectical behavior therapy (DBT) is one such treatment with significant potential for acceptability in South Asian settings with high suicide rates. We describe a tri-phasic approach to adapt DBT in Nepal that consists of qualitative interviews with major Nepali mental health stakeholders (Study 1), an adaptation workshop with 15 Nepali counselors (Study 2), and a small-scale treatment pilot with eligible clients in one rural district (Study 3). Due to low literacy levels, distinct conceptualizations of mind and body, and program adherence barriers, numerous adaptations were required. DBT concepts attributable to Asian belief systems were least comprehensible to clients. However, the 82% program completion rate suggests utility of a structured, skills-based treatment. This adaptation process informs future research regarding the effectiveness of culturally adapted DBT in South Asia. PMID:29056846

Construction of a Computerized Adaptive Testing Version of the Quebec Adaptive Behavior Scale.

ERIC Educational Resources Information Center

Tasse, Marc J.; And Others

Multilog (Thissen, 1991) was used to estimate parameters of 225 items from the Quebec Adaptive Behavior Scale (QABS). A database containing actual data from 2,439 subjects was used for the parameterization procedures. The two-parameter-logistic model was used in estimating item parameters and in the testing strategy. MicroCAT (Assessment Systems…

Adolescent adaptive behavior profiles in Williams-Beuren syndrome, Down syndrome, and autism spectrum disorder.

PubMed

Del Cole, Carolina Grego; Caetano, Sheila Cavalcante; Ribeiro, Wagner; Kümmer, Arthur Melo E E; Jackowski, Andrea Parolin

2017-01-01

Adaptive behavior can be impaired in different neurodevelopmental disorders and may be influenced by confounding factors, such as intelligence quotient (IQ) and socioeconomic classification. Our main objective was to verify whether adaptive behavior profiles differ in three conditions-Williams Beuren syndrome (WBS), Down syndrome (DS), and autism spectrum disorder (ASD), as compared with healthy controls (HC) and with each other. Although the literature points towards each disorder having a characteristic profile, no study has compared profiles to establish the specificity of each one. A secondary objective was to explore potential interactions between the conditions and socioeconomic status, and whether this had any effect on adaptive behavior profiles. One hundred and five adolescents were included in the study. All adolescents underwent the following evaluations: the Vineland Adaptive Behavior Scale (VABS), the Wechsler Intelligence Scale for Children (WISC), and the Brazilian Economic Classification Criteria. Our results demonstrated that the WBS group performed better than the DS group in the communication domain, β = -15.08, t(3.45), p = .005, and better than the ASD group in the socialization domain, β = 8.92, t(-2.08), p = .013. The DS group also performed better than the ASD group in socialization, β = 16.98, t(-2.32), p = .024. IQ was an important confounding factor, and socioeconomic status had an important effect on the adaptive behavior of all groups. There is a heterogeneity regarding adaptive behavior profiles in WBS, DS, and ASD. These data are important to better design specific strategies related to the health and social care of each particular group.

Analyzing Online Behaviors, Roles, and Learning Communities via Online Discussions

ERIC Educational Resources Information Center

Yeh, Yu-Chu

2010-01-01

Online learning communities are an important means of sharing and creating knowledge. Online behaviors and online roles can reveal how online learning communities function. However, no study has elucidated the relationships among online behaviors, online roles, and online learning communities. In this study, 32 preservice teachers participated in…

Hierarchically organized behavior and its neural foundations: A reinforcement-learning perspective

PubMed Central

Botvinick, Matthew M.; Niv, Yael; Barto, Andrew C.

2009-01-01

Research on human and animal behavior has long emphasized its hierarchical structure — the divisibility of ongoing behavior into discrete tasks, which are comprised of subtask sequences, which in turn are built of simple actions. The hierarchical structure of behavior has also been of enduring interest within neuroscience, where it has been widely considered to reflect prefrontal cortical functions. In this paper, we reexamine behavioral hierarchy and its neural substrates from the point of view of recent developments in computational reinforcement learning. Specifically, we consider a set of approaches known collectively as hierarchical reinforcement learning, which extend the reinforcement learning paradigm by allowing the learning agent to aggregate actions into reusable subroutines or skills. A close look at the components of hierarchical reinforcement learning suggests how they might map onto neural structures, in particular regions within the dorsolateral and orbital prefrontal cortex. It also suggests specific ways in which hierarchical reinforcement learning might provide a complement to existing psychological models of hierarchically structured behavior. A particularly important question that hierarchical reinforcement learning brings to the fore is that of how learning identifies new action routines that are likely to provide useful building blocks in solving a wide range of future problems. Here and at many other points, hierarchical reinforcement learning offers an appealing framework for investigating the computational and neural underpinnings of hierarchically structured behavior. PMID:18926527

The Impact of Cognitive Dissonance on Learning Work Behavior

ERIC Educational Resources Information Center

Dechawatanapaisal, Decha; Siengthai, Sununta

2006-01-01

Purpose: This research proposes a framework, which identifies the underlying factors that shape learning behavior in the workplace. It takes organizational members' perspectives into consideration to gain better understanding on managing people and their behavior in the organizational learning process. Design/methodology/approach: Primary data…

Failing to learn from negative prediction errors: Obesity is associated with alterations in a fundamental neural learning mechanism.

PubMed

Mathar, David; Neumann, Jane; Villringer, Arno; Horstmann, Annette

2017-10-01

Prediction errors (PEs) encode the difference between expected and actual action outcomes in the brain via dopaminergic modulation. Integration of these learning signals ensures efficient behavioral adaptation. Obesity has recently been linked to altered dopaminergic fronto-striatal circuits, thus implying impairments in cognitive domains that rely on its integrity. 28 obese and 30 lean human participants performed an implicit stimulus-response learning paradigm inside an fMRI scanner. Computational modeling and psycho-physiological interaction (PPI) analysis was utilized for assessing PE-related learning and associated functional connectivity. We show that human obesity is associated with insufficient incorporation of negative PEs into behavioral adaptation even in a non-food context, suggesting differences in a fundamental neural learning mechanism. Obese subjects were less efficient in using negative PEs to improve implicit learning performance, despite proper coding of PEs in striatum. We further observed lower functional coupling between ventral striatum and supplementary motor area in obese subjects subsequent to negative PEs. Importantly, strength of functional coupling predicted task performance and negative PE utilization. These findings show that obesity is linked to insufficient behavioral adaptation specifically in response to negative PEs, and to associated alterations in function and connectivity within the fronto-striatal system. Recognition of neural differences as a central characteristic of obesity hopefully paves the way to rethink established intervention strategies: Differential behavioral sensitivity to negative and positive PEs should be considered when designing intervention programs. Measures relying on penalization of unwanted behavior may prove less effective in obese subjects than alternative approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

Relationship between Family Adaptability, Cohesion and Adolescent Problem Behaviors: Curvilinearity of Circumplex Model.

PubMed

Joh, Ju Youn; Kim, Sun; Park, Jun Li; Kim, Yeon Pyo

2013-05-01

The Family Adaptability and Cohesion Evaluation Scale (FACES) III using the circumplex model has been widely used in investigating family function. However, the criticism of the curvilinear hypothesis of the circumplex model has always been from an empirical point of view. This study examined the relationship between adolescent adaptability, cohesion, and adolescent problem behaviors, and especially testing the consistency of the curvilinear hypotheses with FACES III. We used the data from 398 adolescent participants who were in middle school. A self-reported questionnaire was used to evaluate the FACES III and Youth Self Report. According to the level of family adaptability, significant differences were evident in internalizing problems (P = 0.014). But, in externalizing problems, the results were not significant (P = 0.305). Also, according to the level of family cohesion, significant differences were in internalizing problems (P = 0.002) and externalizing problems (P = 0.004). The relationship between the dimensions of adaptability, cohesion and adolescent problem behaviors was not curvilinear. In other words, adolescents with high adaptability and high cohesion showed low problem behaviors.

Relationship between Family Adaptability, Cohesion and Adolescent Problem Behaviors: Curvilinearity of Circumplex Model

PubMed Central

Joh, Ju Youn; Kim, Sun; Park, Jun Li

2013-01-01

Background The Family Adaptability and Cohesion Evaluation Scale (FACES) III using the circumplex model has been widely used in investigating family function. However, the criticism of the curvilinear hypothesis of the circumplex model has always been from an empirical point of view. This study examined the relationship between adolescent adaptability, cohesion, and adolescent problem behaviors, and especially testing the consistency of the curvilinear hypotheses with FACES III. Methods We used the data from 398 adolescent participants who were in middle school. A self-reported questionnaire was used to evaluate the FACES III and Youth Self Report. Results According to the level of family adaptability, significant differences were evident in internalizing problems (P = 0.014). But, in externalizing problems, the results were not significant (P = 0.305). Also, according to the level of family cohesion, significant differences were in internalizing problems (P = 0.002) and externalizing problems (P = 0.004). Conclusion The relationship between the dimensions of adaptability, cohesion and adolescent problem behaviors was not curvilinear. In other words, adolescents with high adaptability and high cohesion showed low problem behaviors. PMID:23730484

Mediodorsal thalamus hypofunction impairs flexible goal-directed behavior.

PubMed

Parnaudeau, Sébastien; Taylor, Kathleen; Bolkan, Scott S; Ward, Ryan D; Balsam, Peter D; Kellendonk, Christoph

2015-03-01

Cognitive inflexibility is a core symptom of several mental disorders including schizophrenia. Brain imaging studies in schizophrenia patients performing cognitive tasks have reported decreased activation of the mediodorsal thalamus (MD). Using a pharmacogenetic approach to model MD hypofunction, we recently showed that decreasing MD activity impairs reversal learning in mice. While this demonstrates causality between MD hypofunction and cognitive inflexibility, questions remain about the elementary cognitive processes that account for the deficit. Using the Designer Receptors Exclusively Activated by Designer Drugs system, we reversibly decreased MD activity during behavioral tasks assessing elementary cognitive processes inherent to flexible goal-directed behaviors, including extinction, contingency degradation, outcome devaluation, and Pavlovian-to-instrumental transfer (n = 134 mice). While MD hypofunction impaired reversal learning, it did not affect the ability to learn about nonrewarded cues or the ability to modulate action selection based on the outcome value. In contrast, decreasing MD activity delayed the ability to adapt to changes in the contingency between actions and their outcomes. In addition, while Pavlovian learning was not affected by MD hypofunction, decreasing MD activity during Pavlovian learning impaired the ability of conditioned stimuli to modulate instrumental behavior. Mediodorsal thalamus hypofunction causes cognitive inflexibility reflected by an impaired ability to adapt actions when their consequences change. Furthermore, it alters the encoding of environmental stimuli so that they cannot be properly utilized to guide behavior. Modulating MD activity could be a potential therapeutic strategy for promoting adaptive behavior in human subjects with cognitive inflexibility. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Social stratification, classroom climate, and the behavioral adaptation of kindergarten children

PubMed Central

Boyce, W. Thomas; Obradović, Jelena; Bush, Nicole R.; Stamperdahl, Juliet; Kim, Young Shin; Adler, Nancy

2012-01-01

Socioeconomic status (SES) is the single most potent determinant of health within human populations, from infancy through old age. Although the social stratification of health is nearly universal, there is persistent uncertainty regarding the dimensions of SES that effect such inequalities and thus little clarity about the principles of intervention by which inequalities might be abated. Guided by animal models of hierarchical organization and the health correlates of subordination, this prospective study examined the partitioning of children's adaptive behavioral development by their positions within kindergarten classroom hierarchies. A sample of 338 5-y-old children was recruited from 29 Berkeley, California public school classrooms. A naturalistic observational measure of social position, parent-reported family SES, and child-reported classroom climate were used in estimating multilevel, random-effects models of children's adaptive behavior at the end of the kindergarten year. Children occupying subordinate positions had significantly more maladaptive behavioral outcomes than their dominant peers. Further, interaction terms revealed that low family SES and female sex magnified, and teachers’ child-centered pedagogical practices diminished, the adverse influences of social subordination. Taken together, results suggest that, even within early childhood groups, social stratification is associated with a partitioning of adaptive behavioral outcomes and that the character of larger societal and school structures in which such groups are nested can moderate rank–behavior associations. PMID:23045637

Social stratification, classroom climate, and the behavioral adaptation of kindergarten children.

PubMed

Boyce, W Thomas; Obradovic, Jelena; Bush, Nicole R; Stamperdahl, Juliet; Kim, Young Shin; Adler, Nancy

2012-10-16

Socioeconomic status (SES) is the single most potent determinant of health within human populations, from infancy through old age. Although the social stratification of health is nearly universal, there is persistent uncertainty regarding the dimensions of SES that effect such inequalities and thus little clarity about the principles of intervention by which inequalities might be abated. Guided by animal models of hierarchical organization and the health correlates of subordination, this prospective study examined the partitioning of children's adaptive behavioral development by their positions within kindergarten classroom hierarchies. A sample of 338 5-y-old children was recruited from 29 Berkeley, California public school classrooms. A naturalistic observational measure of social position, parent-reported family SES, and child-reported classroom climate were used in estimating multilevel, random-effects models of children's adaptive behavior at the end of the kindergarten year. Children occupying subordinate positions had significantly more maladaptive behavioral outcomes than their dominant peers. Further, interaction terms revealed that low family SES and female sex magnified, and teachers' child-centered pedagogical practices diminished, the adverse influences of social subordination. Taken together, results suggest that, even within early childhood groups, social stratification is associated with a partitioning of adaptive behavioral outcomes and that the character of larger societal and school structures in which such groups are nested can moderate rank-behavior associations.

A model for the transfer of perceptual-motor skill learning in human behaviors.

PubMed

Rosalie, Simon M; Müller, Sean

2012-09-01

This paper presents a preliminary model that outlines the mechanisms underlying the transfer of perceptual-motor skill learning in sport and everyday tasks. Perceptual-motor behavior is motivated by performance demands and evolves over time to increase the probability of success through adaptation. Performance demands at the time of an event create a unique transfer domain that specifies a range of potentially successful actions. Transfer comprises anticipatory subconscious and conscious mechanisms. The model also outlines how transfer occurs across a continuum, which depends on the individual's expertise and contextual variables occurring at the incidence of transfer

Organizational Adaptative Behavior: The Complex Perspective of Individuals-Tasks Interaction

NASA Astrophysics Data System (ADS)

Wu, Jiang; Sun, Duoyong; Hu, Bin; Zhang, Yu

Organizations with different organizational structures have different organizational behaviors when responding environmental changes. In this paper, we use a computational model to examine organizational adaptation on four dimensions: Agility, Robustness, Resilience, and Survivability. We analyze the dynamics of organizational adaptation by a simulation study from a complex perspective of the interaction between tasks and individuals in a sales enterprise. The simulation studies in different scenarios show that more flexible communication between employees and less hierarchy level with the suitable centralization can improve organizational adaptation.

A Structure-Adaptive Hybrid RBF-BP Classifier with an Optimized Learning Strategy

PubMed Central

Wen, Hui; Xie, Weixin; Pei, Jihong

2016-01-01

This paper presents a structure-adaptive hybrid RBF-BP (SAHRBF-BP) classifier with an optimized learning strategy. SAHRBF-BP is composed of a structure-adaptive RBF network and a BP network of cascade, where the number of RBF hidden nodes is adjusted adaptively according to the distribution of sample space, the adaptive RBF network is used for nonlinear kernel mapping and the BP network is used for nonlinear classification. The optimized learning strategy is as follows: firstly, a potential function is introduced into training sample space to adaptively determine the number of initial RBF hidden nodes and node parameters, and a form of heterogeneous samples repulsive force is designed to further optimize each generated RBF hidden node parameters, the optimized structure-adaptive RBF network is used for adaptively nonlinear mapping the sample space; then, according to the number of adaptively generated RBF hidden nodes, the number of subsequent BP input nodes can be determined, and the overall SAHRBF-BP classifier is built up; finally, different training sample sets are used to train the BP network parameters in SAHRBF-BP. Compared with other algorithms applied to different data sets, experiments show the superiority of SAHRBF-BP. Especially on most low dimensional and large number of data sets, the classification performance of SAHRBF-BP outperforms other training SLFNs algorithms. PMID:27792737

Reactive behavior, learning, and anticipation

NASA Technical Reports Server (NTRS)

Whitehead, Steven D.; Ballard, Dana H.

1989-01-01

Reactive systems always act, thinking only long enough to 'look up' the action to execute. Traditional planning systems think a lot, and act only after generating fairly precise plans. Each represents an endpoint on a spectrum. It is argued that primitive forms of reasoning, like anticipation, play an important role in reducing the cost of learning and that the decision to act or think should be based on the uncertainty associated with the utility of executing an action in a particular situation. An architecture for an adaptable reactive system is presented and it is shown how it can be augmented with a simple anticipation mechanism that can substantially reduce the cost and time of learning.

Application of real-time machine learning to myoelectric prosthesis control: A case series in adaptive switching.

PubMed

Edwards, Ann L; Dawson, Michael R; Hebert, Jacqueline S; Sherstan, Craig; Sutton, Richard S; Chan, K Ming; Pilarski, Patrick M

2016-10-01

Myoelectric prostheses currently used by amputees can be difficult to control. Machine learning, and in particular learned predictions about user intent, could help to reduce the time and cognitive load required by amputees while operating their prosthetic device. The goal of this study was to compare two switching-based methods of controlling a myoelectric arm: non-adaptive (or conventional) control and adaptive control (involving real-time prediction learning). Case series study. We compared non-adaptive and adaptive control in two different experiments. In the first, one amputee and one non-amputee subject controlled a robotic arm to perform a simple task; in the second, three able-bodied subjects controlled a robotic arm to perform a more complex task. For both tasks, we calculated the mean time and total number of switches between robotic arm functions over three trials. Adaptive control significantly decreased the number of switches and total switching time for both tasks compared with the conventional control method. Real-time prediction learning was successfully used to improve the control interface of a myoelectric robotic arm during uninterrupted use by an amputee subject and able-bodied subjects. Adaptive control using real-time prediction learning has the potential to help decrease both the time and the cognitive load required by amputees in real-world functional situations when using myoelectric prostheses. © The International Society for Prosthetics and Orthotics 2015.

Observing Animal Behavior at the Zoo: A Learning Laboratory

ERIC Educational Resources Information Center

Hull, Debra B.

2003-01-01

Undergraduate students in a learning laboratory course initially chose a species to study; researched that species' physical and behavioral characteristics; then learned skills necessary to select, operationalize, observe, and record animal behavior accurately. After their classroom preparation, students went to a local zoo to observe the behavior…

Mispronunciation Detection for Language Learning and Speech Recognition Adaptation

ERIC Educational Resources Information Center

Ge, Zhenhao

2013-01-01

The areas of "mispronunciation detection" (or "accent detection" more specifically) within the speech recognition community are receiving increased attention now. Two application areas, namely language learning and speech recognition adaptation, are largely driving this research interest and are the focal points of this work.…

Exploring the Effects of Intercultural Learning on Cross-Cultural Adaptation in a Study Abroad Context

ERIC Educational Resources Information Center

Tsai, Yau

2011-01-01

This study targets Asian students studying abroad and explores the effects of intercultural learning on their cross-cultural adaptation by drawing upon a questionnaire survey. On the one hand, the results of this study find that under the influence of intercultural learning, students respond differently in their cross-cultural adaptation and no…

Adaptation of Timing Behavior to a Regular Change in Criterion

PubMed Central

Sanabria, Federico; Oldenburg, Liliana

2013-01-01

This study examined how operant behavior adapted to an abrupt but regular change in the timing of reinforcement. Pigeons were trained on a fixed interval (FI) 15-s schedule of reinforcement during half of each experimental session, and on an FI 45-s (Experiment 1), FI 60-s (Experiment 2), or extinction schedule (Experiment 3) during the other half. FI performance was well characterized by a mixture of two gamma-shaped distributions of responses. When a longer FI schedule was in effect in the first half of the session (Experiment 1), a constant interference by the shorter FI was observed. When a shorter FI schedule was in effect in the first half of the session (Experiments 1, 2, and 3), the transition between schedules involved a decline in responding and a progressive rightward shift in the mode of the response distribution initially centered around the short FI. These findings are discussed in terms of the constraints they impose to quantitative models of timing, and in relation to the implications for information-based models of associative learning. PMID:23962672

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.

Long-Lasting Modifications of Saccadic Eye Movements Following Adaptation Induced in the Double-Step Target Paradigm

ERIC Educational Resources Information Center

Alahyane, Nadia; Pelisson, Denis

2005-01-01

The adaptation of saccadic eye movements to environmental changes occurring throughout life is a good model of motor learning and motor memory. Numerous studies have analyzed the behavioral properties and neural substrate of oculomotor learning in short-term saccadic adaptation protocols, but to our knowledge, none have tested the persistence of…

Training adaptations in the behavior of human motor units.

PubMed

Duchateau, Jacques; Semmler, John G; Enoka, Roger M

2006-12-01

The purpose of this brief review is to examine the neural adaptations associated with training, by focusing on the behavior of single motor units. The review synthesizes current understanding on motor unit recruitment and rate coding during voluntary contractions, briefly describes the techniques used to record motor unit activity, and then evaluates the adaptations that have been observed in motor unit activity during maximal and submaximal contractions. Relatively few studies have directly compared motor unit behavior before and after training. Although some studies suggest that the voluntary activation of muscle can increase slightly with strength training, it is not known how the discharge of motor units changes to produce this increase in activation. The evidence indicates that the increase is not attributable to changes in motor unit synchronization. It has been demonstrated, however, that training can increase both the rate of torque development and the discharge rate of motor units. Furthermore, both strength training and practice of a force-matching task can evoke adaptations in the discharge characteristics of motor units. Because the variability in discharge rate has a significant influence on the fluctuations in force during submaximal contractions, the changes produced with training can influence motor performance during activities of daily living. Little is known, however, about the relative contributions of the descending drive, afferent feedback, spinal circuitry, and motor neuron properties to the observed adaptations in motor unit activity.

Students with Learning Disabilities and Challenging Behaviors in Jordan

ERIC Educational Resources Information Center

Abu-Hamour, Bashir

2014-01-01

This paper reports the findings of a study which aimed to explore the learning and behavioral characteristics of students with Learning Disabilities (LDs) in Jordan. Specifically, variables that related to challenging behaviors, school's type, and gender differences were investigated. Four resource room teachers in public and private schools were…

Visuomotor coordination and cortical connectivity of modular motor learning.

PubMed

Burgos, Pablo I; Mariman, Juan J; Makeig, Scott; Rivera-Lillo, Gonzalo; Maldonado, Pedro E

2018-05-15

The ability to transfer sensorimotor skill components to new actions and the capacity to use skill components from whole actions are characteristic of the adaptability of the human sensorimotor system. However, behavioral evidence suggests complex limitations for transfer after combined or modular learning of motor adaptations. Also, to date, only behavioral analysis of the consequences of the modular learning has been reported, with little understanding of the sensorimotor mechanisms of control and the interaction between cortical areas. We programmed a video game with distorted kinematic and dynamic features to test the ability to combine sensorimotor skill components learned modularly (composition) and the capacity to use separate sensorimotor skill components learned in combination (decomposition). We examined motor performance, eye-hand coordination, and EEG connectivity. When tested for integrated learning, we found that combined practice initially performed better than separated practice, but differences disappeared after integrated practice. Separate learning promotes fewer anticipatory control mechanisms (depending more on feedback control), evidenced in a lower gaze leading behavior and in higher connectivity between visual and premotor domains, in comparison with the combined practice. The sensorimotor system can acquire motor modules in a separated or integrated manner. However, the system appears to require integrated practice to coordinate the adaptations with the skill learning and the networks involved in the integrated behavior. This integration seems to be related to the acquisition of anticipatory mechanism of control and with the decrement of feedback control. © 2018 Wiley Periodicals, Inc.

Sensory Cortical Population Dynamics Uniquely Track Behavior across Learning and Extinction

PubMed Central

Katz, Donald B.

2014-01-01

Neural responses in many cortical regions encode information relevant to behavior: information that necessarily changes as that behavior changes with learning. Although such responses are reasonably theorized to be related to behavior causation, the true nature of that relationship cannot be clarified by simple learning studies, which show primarily that responses change with experience. Neural activity that truly tracks behavior (as opposed to simply changing with experience) will not only change with learning but also change back when that learning is extinguished. Here, we directly probed for this pattern, recording the activity of ensembles of gustatory cortical single neurons as rats that normally consumed sucrose avidly were trained first to reject it (i.e., conditioned taste aversion learning) and then to enjoy it again (i.e., extinction), all within 49 h. Both learning and extinction altered cortical responses, consistent with the suggestion (based on indirect evidence) that extinction is a novel form of learning. But despite the fact that, as expected, postextinction single-neuron responses did not resemble “naive responses,” ensemble response dynamics changed with learning and reverted with extinction: both the speed of stimulus processing and the relationships among ensemble responses to the different stimuli tracked behavioral relevance. These data suggest that population coding is linked to behavior with a fidelity that single-neuron coding is not. PMID:24453316

Observations of Student Behavior in Collaborative Learning Groups

NASA Astrophysics Data System (ADS)

Adams, Jeffrey P.; Brissenden, Gina; Lindell, Rebecca S.; Slater, Timothy F.; Wallace, Joy

In an effort to determine how our students were responding to the use of collaborative learning groups in our large enrollment introductory astronomy (ASTRO 101) courses, we systematically observed the behavior of 270 undergraduate students working in 48 self-formed groups. Their observed behaviors were classified as: (i) actively engaged; (ii) watching actively; (iii) watching passively; and (iv) disengaged. We found that male behavior is consistent regardless of the sex-composition of the groups. However, females were categorized as watching passively and or disengaged significantly more frequently when working in groups that contained uneven numbers of males and females. This case study observation suggests that faculty who use collaborative learning groups might find that the level of student participation in collaborative group learning activities can depend on the sex-composition of the group.

Adaptive Equilibrium Regulation: A Balancing Act in Two Timescales

PubMed Central

Boker, Steven M.

2015-01-01

An equilibrium involves a balancing of forces. Just as one maintains upright posture in standing or walking, many self-regulatory and interpersonal behaviors can be framed as a balancing act between an ever changing environment and within-person processes. The emerging balance between person and environment, the equilibria, are dynamic and adaptive in response to development and learning. A distinction is made between equilibrium achieved solely due to a short timescale balancing of forces and a longer timescale preferred equilibrium which we define as a state towards which the system slowly adapts. Together, these are developed into a framework that this article calls Adaptive Equilibrium Regulation (ÆR), which separates a regulatory process into two timescales: a faster regulation that automatically balances forces and a slower timescale adaptation process that reconfigures the fast regulation so as to move the system towards its preferred equilibrium when an environmental force persists over the longer timescale. This way of thinking leads to novel models for the interplay between multiple timescales of behavior, learning, and development. PMID:27066197

Examining the Role of Emotional Intelligence between Organizational Learning and Adaptive Performance in Indian Manufacturing Industries

ERIC Educational Resources Information Center

Pradhan, Rabindra Kumar; Jena, Lalatendu Kesari; Singh, Sanjay Kumar

2017-01-01

Purpose: The purpose of this study is to examine the relationship between organisational learning and adaptive performance. Furthermore, the study investigates the moderating role of emotional intelligence in the perspective of organisational learning for addressing adaptive performance of executives employed in manufacturing organisations.…

Psychosocial and Adaptive Deficits Associated with Learning Disability Subtypes

ERIC Educational Resources Information Center

Backenson, Erica M.; Holland, Sara C.; Kubas, Hanna A.; Fitzer, Kim R.; Wilcox, Gabrielle; Carmichael, Jessica A.; Fraccaro, Rebecca L.; Smith, Amanda D.; Macoun, Sarah J.; Harrison, Gina L.; Hale, James B.

2015-01-01

Children with specific learning disabilities (SLD) have deficits in the basic psychological processes that interfere with learning and academic achievement, and for some SLD subtypes, these deficits can also lead to emotional and/or behavior problems. This study examined psychosocial functioning in 123 students, aged 6 to 11, who underwent…

Adaptivity and Autonomy Development in a Learning Personalization Process

ERIC Educational Resources Information Center

Verpoorten, D.

2009-01-01

Within the iClass (Integrated Project 507922) and Enhanced Learning Experience and Knowledge Transfer (ELEKTRA; Specific Targeted Research or Innovation Project 027986) European projects, the author was requested to harness his pedagogical knowledge to the production of educational adaptive systems. The article identifies and documents the…

The Emotions of Socialization-Related Learning: Understanding Workplace Adaptation as a Learning Process.

ERIC Educational Resources Information Center

Reio, Thomas G., Jr.

The influence of selected discrete emotions on socialization-related learning and perception of workplace adaptation was examined in an exploratory study. Data were collected from 233 service workers in 4 small and medium-sized companies in metropolitan Washington, D.C. The sample members' average age was 32.5 years, and the sample's racial makeup…

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

NASA Technical Reports Server (NTRS)

Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

1988-01-01

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

Predicting Adaptive Behavior in the Environment from Central Nervous System Dynamics

PubMed Central

Proekt, Alex; Wong, Jane; Zhurov, Yuriy; Kozlova, Nataliya; Weiss, Klaudiusz R.; Brezina, Vladimir

2008-01-01

To generate adaptive behavior, the nervous system is coupled to the environment. The coupling constrains the dynamical properties that the nervous system and the environment must have relative to each other if adaptive behavior is to be produced. In previous computational studies, such constraints have been used to evolve controllers or artificial agents to perform a behavioral task in a given environment. Often, however, we already know the controller, the real nervous system, and its dynamics. Here we propose that the constraints can also be used to solve the inverse problem—to predict from the dynamics of the nervous system the environment to which they are adapted, and so reconstruct the production of the adaptive behavior by the entire coupled system. We illustrate how this can be done in the feeding system of the sea slug Aplysia. At the core of this system is a central pattern generator (CPG) that, with dynamics on both fast and slow time scales, integrates incoming sensory stimuli to produce ingestive and egestive motor programs. We run models embodying these CPG dynamics—in effect, autonomous Aplysia agents—in various feeding environments and analyze the performance of the entire system in a realistic feeding task. We find that the dynamics of the system are tuned for optimal performance in a narrow range of environments that correspond well to those that Aplysia encounter in the wild. In these environments, the slow CPG dynamics implement efficient ingestion of edible seaweed strips with minimal sensory information about them. The fast dynamics then implement a switch to a different behavioral mode in which the system ignores the sensory information completely and follows an internal “goal,” emergent from the dynamics, to egest again a strip that proves to be inedible. Key predictions of this reconstruction are confirmed in real feeding animals. PMID:18989362

Soil-pipe interaction modeling for pipe behavior prediction with super learning based methods

NASA Astrophysics Data System (ADS)

Shi, Fang; Peng, Xiang; Liu, Huan; Hu, Yafei; Liu, Zheng; Li, Eric

2018-03-01

Underground pipelines are subject to severe distress from the surrounding expansive soil. To investigate the structural response of water mains to varying soil movements, field data, including pipe wall strains in situ soil water content, soil pressure and temperature, was collected. The research on monitoring data analysis has been reported, but the relationship between soil properties and pipe deformation has not been well-interpreted. To characterize the relationship between soil property and pipe deformation, this paper presents a super learning based approach combining feature selection algorithms to predict the water mains structural behavior in different soil environments. Furthermore, automatic variable selection method, e.i. recursive feature elimination algorithm, were used to identify the critical predictors contributing to the pipe deformations. To investigate the adaptability of super learning to different predictive models, this research employed super learning based methods to three different datasets. The predictive performance was evaluated by R-squared, root-mean-square error and mean absolute error. Based on the prediction performance evaluation, the superiority of super learning was validated and demonstrated by predicting three types of pipe deformations accurately. In addition, a comprehensive understand of the water mains working environments becomes possible.

An Online Adaptive Learning Environment for Critical-Thinking-Infused English Literacy Instruction

ERIC Educational Resources Information Center

Yang, Ya-Ting Carolyn; Gamble, Jeffrey Hugh; Hung, Yu-Wan; Lin, Tzu-Yun

2014-01-01

Critical thinking (CT) and English literacy are two essential 21st century competencies that are a priority for teaching and learning in an increasingly digital learning environment. Taking advantage of innovations in educational technology, this study empirically investigates the effectiveness of CT-infused adaptive English literacy instruction…

Cooperative Learning Groups and the Evolution of Human Adaptability : (Another Reason) Why Hermits Are Rare in Tonga and Elsewhere.

PubMed

Bell, Adrian Viliami; Hernandez, Daniel

2017-03-01

Understanding the prevalence of adaptive culture in part requires understanding the dynamics of learning. Here we explore the adaptive value of social learning in groups and how formal social groups function as effective mediums of information exchange. We discuss the education literature on Cooperative Learning Groups (CLGs), which outlines the potential of group learning for enhancing learning outcomes. Four qualities appear essential for CLGs to enhance learning: (1) extended conversations, (2) regular interactions, (3) gathering of experts, and (4) incentives for sharing knowledge. We analyze these four qualities within the context of a small-scale agricultural society using data we collected in 2010 and 2012. Through an analysis of surveys, interviews, and observations in the Tongan islands, we describe the role CLGs likely plays in facilitating individuals' learning of adaptive information. Our analysis of group affiliation, membership, and topics of conversation suggest that the first three CLG qualities reflect conditions for adaptive learning in groups. We utilize ethnographic anecdotes to suggest the fourth quality is also conducive to adaptive group learning. Using an evolutionary model, we further explore the scope for CLGs outside the Tongan socioecological context. Model analysis shows that environmental volatility and migration rates among human groups mediate the scope for CLGs. We call for wider attention to how group structure facilitates learning in informal settings, which may be key to assessing the contribution of groups to the evolution of complex, adaptive culture.

Modeling and Simulation of An Adaptive Neuro-Fuzzy Inference System (ANFIS) for Mobile Learning

ERIC Educational Resources Information Center

Al-Hmouz, A.; Shen, Jun; Al-Hmouz, R.; Yan, Jun

2012-01-01

With recent advances in mobile learning (m-learning), it is becoming possible for learning activities to occur everywhere. The learner model presented in our earlier work was partitioned into smaller elements in the form of learner profiles, which collectively represent the entire learning process. This paper presents an Adaptive Neuro-Fuzzy…

The cerebellum does more than sensory prediction error-based learning in sensorimotor adaptation tasks.

PubMed

Butcher, Peter A; Ivry, Richard B; Kuo, Sheng-Han; Rydz, David; Krakauer, John W; Taylor, Jordan A

2017-09-01

Individuals with damage to the cerebellum perform poorly in sensorimotor adaptation paradigms. This deficit has been attributed to impairment in sensory prediction error-based updating of an internal forward model, a form of implicit learning. These individuals can, however, successfully counter a perturbation when instructed with an explicit aiming strategy. This successful use of an instructed aiming strategy presents a paradox: In adaptation tasks, why do individuals with cerebellar damage not come up with an aiming solution on their own to compensate for their implicit learning deficit? To explore this question, we employed a variant of a visuomotor rotation task in which, before executing a movement on each trial, the participants verbally reported their intended aiming location. Compared with healthy control participants, participants with spinocerebellar ataxia displayed impairments in both implicit learning and aiming. This was observed when the visuomotor rotation was introduced abruptly ( experiment 1 ) or gradually ( experiment 2 ). This dual deficit does not appear to be related to the increased movement variance associated with ataxia: Healthy undergraduates showed little change in implicit learning or aiming when their movement feedback was artificially manipulated to produce similar levels of variability ( experiment 3 ). Taken together the results indicate that a consequence of cerebellar dysfunction is not only impaired sensory prediction error-based learning but also a difficulty in developing and/or maintaining an aiming solution in response to a visuomotor perturbation. We suggest that this dual deficit can be explained by the cerebellum forming part of a network that learns and maintains action-outcome associations across trials. NEW & NOTEWORTHY Individuals with cerebellar pathology are impaired in sensorimotor adaptation. This deficit has been attributed to an impairment in error-based learning, specifically, from a deficit in using sensory

Spatiotemporal Spike Coding of Behavioral Adaptation in the Dorsal Anterior Cingulate Cortex

PubMed Central

Logiaco, Laureline; Quilodran, René; Procyk, Emmanuel; Arleo, Angelo

2015-01-01

The frontal cortex controls behavioral adaptation in environments governed by complex rules. Many studies have established the relevance of firing rate modulation after informative events signaling whether and how to update the behavioral policy. However, whether the spatiotemporal features of these neuronal activities contribute to encoding imminent behavioral updates remains unclear. We investigated this issue in the dorsal anterior cingulate cortex (dACC) of monkeys while they adapted their behavior based on their memory of feedback from past choices. We analyzed spike trains of both single units and pairs of simultaneously recorded neurons using an algorithm that emulates different biologically plausible decoding circuits. This method permits the assessment of the performance of both spike-count and spike-timing sensitive decoders. In response to the feedback, single neurons emitted stereotypical spike trains whose temporal structure identified informative events with higher accuracy than mere spike count. The optimal decoding time scale was in the range of 70–200 ms, which is significantly shorter than the memory time scale required by the behavioral task. Importantly, the temporal spiking patterns of single units were predictive of the monkeys’ behavioral response time. Furthermore, some features of these spiking patterns often varied between jointly recorded neurons. All together, our results suggest that dACC drives behavioral adaptation through complex spatiotemporal spike coding. They also indicate that downstream networks, which decode dACC feedback signals, are unlikely to act as mere neural integrators. PMID:26266537

Boldness behavior and stress physiology in a novel urban environment suggest rapid correlated evolutionary adaptation.

PubMed

Atwell, Jonathan W; Cardoso, Gonçalo C; Whittaker, Danielle J; Campbell-Nelson, Samuel; Robertson, Kyle W; Ketterson, Ellen D

2012-09-01

Novel or changing environments expose animals to diverse stressors that likely require coordinated hormonal and behavioral adaptations. Predicted adaptations to urban environments include attenuated physiological responses to stressors and bolder exploratory behaviors, but few studies to date have evaluated the impact of urban life on codivergence of these hormonal and behavioral traits in natural systems. Here, we demonstrate rapid adaptive shifts in both stress physiology and correlated boldness behaviors in a songbird, the dark-eyed junco, following its colonization of a novel urban environment. We compared elevation in corticosterone (CORT) in response to handling and flight initiation distances in birds from a recently established urban population in San Diego, California to birds from a nearby wildland population in the species' ancestral montane breeding range. We also measured CORT and exploratory behavior in birds raised from early life in a captive common garden study. We found persistent population differences for both reduced CORT responses and bolder exploratory behavior in birds from the colonist population, as well as significant negative covariation between maximum CORT and exploratory behavior. Although early developmental effects cannot be ruled out, these results suggest contemporary adaptive evolution of correlated hormonal and behavioral traits associated with colonization of an urban habitat.