Artistic Production Processes as Venues for Positive Youth Development. WCER Working Paper No. 2010-2

ERIC Educational Resources Information Center

Halverson, Erica

2010-01-01

Educators must consider how learning environments can structure experiences to produce desired learning outcomes. In this paper, the author describes one type of learning environment where youth have the opportunity to construct adaptive, emergent identities--a "dramaturgical" process that structures the telling, adapting, and…

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…

Usability Evaluation of an Adaptive 3D Virtual Learning Environment

ERIC Educational Resources Information Center

Ewais, Ahmed; De Troyer, Olga

2013-01-01

Using 3D virtual environments for educational purposes is becoming attractive because of their rich presentation and interaction capabilities. Furthermore, dynamically adapting the 3D virtual environment to the personal preferences, prior knowledge, skills and competence, learning goals, and the personal or (social) context in which the learning…

A New Approach for Constructing the Concept Map

ERIC Educational Resources Information Center

Tseng, Shian-Shyong; Sue, Pei-Chi; Su, Jun-Ming; Weng, Jui-Feng; Tsai, Wen-Nung

2007-01-01

In recent years, e-learning system has become more and more popular and many adaptive learning environments have been proposed to offer learners customized courses in accordance with their aptitudes and learning results. For achieving the adaptive learning, a predefined concept map of a course is often used to provide adaptive learning guidance…

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…

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

ERIC Educational Resources Information Center

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

2011-01-01

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

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 permits the discovery of the unknown problems, ones that are not yet recognized but may be critical to survival or success.

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

ERIC Educational Resources Information Center

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

2011-01-01

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

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…

The Framework of Intervention Engine Based on Learning Analytics

ERIC Educational Resources Information Center

Sahin, Muhittin; Yurdugül, Halil

2017-01-01

Learning analytics primarily deals with the optimization of learning environments and the ultimate goal of learning analytics is to improve learning and teaching efficiency. Studies on learning analytics seem to have been made in the form of adaptation engine and intervention engine. Adaptation engine studies are quite widespread, but intervention…

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…

Structure learning in action

PubMed Central

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

2010-01-01

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

Criteria, Strategies and Research Issues of Context-Aware Ubiquitous Learning

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Tsai, Chin-Chung; Yang, Stephen J. H.

2008-01-01

Recent progress in wireless and sensor technologies has lead to a new development of learning environments, called context-aware ubiquitous learning environment, which is able to sense the situation of learners and provide adaptive supports. Many researchers have been investigating the development of such new learning environments; nevertheless,…

Human Machine Learning Symbiosis

ERIC Educational Resources Information Center

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

2017-01-01

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

Adaptive User Model for Web-Based Learning Environment.

ERIC Educational Resources Information Center

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

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

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…

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…

U-ALS: A Ubiquitous Learning Environment

ERIC Educational Resources Information Center

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

2012-01-01

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

A Hybrid Approach for Supporting Adaptivity in E-Learning Environments

ERIC Educational Resources Information Center

Al-Omari, Mohammad; Carter, Jenny; Chiclana, Francisco

2016-01-01

Purpose: The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity…

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

ERIC Educational Resources Information Center

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

2014-01-01

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

Adaptive 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…

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

PubMed

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

2011-01-01

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

Online Adaptation and Over-Trial Learning in Macaque Visuomotor Control

PubMed Central

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

2011-01-01

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

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.

Mobile Adaptive Communication Support for Vocabulary Acquisition

ERIC Educational Resources Information Center

Epp, Carrie Demmans

2014-01-01

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

Analysis of Means for Building Context-Aware Recommendation System for Mobile Learning

ERIC Educational Resources Information Center

Shcherbachenko, Larysa; Nowakowski, Samuel

2017-01-01

One of the rapidly developing tools for online learning is learning through a mobile environment. Therefore, developing and improving mobile learning environments is an active topic now. One of the ways to adapt the learning environment to the user's needs is to use his context. Context of the user consists of the current context in online…

Adaptive Intelligent Support to Improve Peer Tutoring in Algebra

ERIC Educational Resources Information Center

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

2014-01-01

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

[Social learning as an uncertainty-reduction strategy: an adaptationist approach].

PubMed

Nakanishi, Daisuke; Kameda, Tatsuya; Shinada, Mizuho

2003-04-01

Social learning is an effective mechanism to reduce uncertainty about environmental knowledge, helping individuals adopt an adaptive behavior in the environment at small cost. Although this is evident for learning about temporally stable targets (e.g., acquiring avoidance of toxic foods culturally), the functional value of social learning in a temporally unstable environment is less clear; knowledge acquired by social learning may be outdated. This paper addressed adaptive values of social learning in a non-stationary environment empirically. When individual learning about the non-stationary environment is costly, a hawk-dove-game-like equilibrium is expected to emerge in the population, where members who engage in costly individual learning and members who skip the information search and free-ride on other members' search efforts coexist at a stable ratio. Such a "producer-scrounger" structure should qualify effectiveness of social/cultural learning severely, especially "conformity bias" when using social information (Boyd & Richerson, 1985). We tested these predictions by an experiment implementing a non-stationary uncertain environment in a laboratory. The results supported our thesis. Implications of these findings and some future directions were discussed.

A Decision-Tree-Oriented Guidance Mechanism for Conducting Nature Science Observation Activities in a Context-Aware Ubiquitous Learning

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Chu, Hui-Chun; Shih, Ju-Ling; Huang, Shu-Hsien; Tsai, Chin-Chung

2010-01-01

A context-aware ubiquitous learning environment is an authentic learning environment with personalized digital supports. While showing the potential of applying such a learning environment, researchers have also indicated the challenges of providing adaptive and dynamic support to individual students. In this paper, a decision-tree-oriented…

Metacognitive components in smart learning environment

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Evaluation of Hybrid and Distance Education Learning Environments in Spain

ERIC Educational Resources Information Center

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

2011-01-01

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

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

ERIC Educational Resources Information Center

Fan, Weiqiao

2012-01-01

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

Adjusted Framework of M-Learning in Blended Learning System for Mathematics Study Field of Junior High School Level VII

NASA Astrophysics Data System (ADS)

Sugiyanta, Lipur; Sukardjo, Moch.

2018-04-01

The 2013 curriculum requires teachers to be more productive, creative, and innovative in encouraging students to be more independent by strengthening attitudes, skills and knowledge. Teachers are given the options to create lesson plan according to the environment and conditions of their students. At the junior level, Core Competence (KI) and Basic Competence (KD) have been completely designed. In addition, there had already guidebooks, both for teacher manuals (Master’s Books) and for learners (Student Books). The lesson plan and guidebooks which already exist are intended only for learning in the classroom/in-school. Many alternative classrooms and alternatives learning models opened up using educational technology. The advance of educational technology opened opportunity for combination of class interaction using mobile learning applications. Mobile learning has rapidly evolved in education for the last ten years and many initiatives have been conducted worldwide. However, few of these efforts have produced any lasting outcomes. It is evident that mobile education applications are complex and hence, will not become sustainable. Long-term sustainability remains a risk. Long-term sustainability usually was resulted from continuous adaptation to changing conditions [4]. Frameworks are therefore required to avoid sustainability pitfalls. The implementation should start from simple environment then gradually become complex through adaptation steps. Therefore, our paper developed the framework of mobile learning (m-learning) adaptation for grade 7th (junior high school). The environment setup was blended mobile learning (not full mobile learning) and emphasize on Algebra. The research is done by R&D method (research and development). Results of the framework includes requirements and adaptation steps. The adjusted m-learning framework is designed to be a guidance for teachers to adopt m-learning to support blended learning environments. During mock-up prototype, the adjusted framework demonstrates how to make successful implementation of early blended mobile learning through framework. The Social area is in focus of adaptation because participation is important to improve the sustainability. From the short practice of mock-up prototype, blended mobile learning can be an effective pedagogical model in supporting students in inquiry-based learning.

Individualized Special Education with Cognitive Skill Assessment.

ERIC Educational Resources Information Center

Kurhila, Jaakko; Laine, Tei

2000-01-01

Describes AHMED (Adaptive and Assistive Hypermedia in Education), a computer learning environment which supports the evaluation of disabled children's cognitive skills in addition to supporting openness in learning materials and adaptivity in learning events. Discusses cognitive modeling and compares it to previous intelligent tutoring systems.…

Emergent Fields through Adaptation and Identity: Overcoming Social Distance

ERIC Educational Resources Information Center

DeGennaro, Donna; Brown, Tiffany

2009-01-01

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

A Novel Approach for Enhancing Lifelong Learning Systems by Using Hybrid Recommender System

ERIC Educational Resources Information Center

Kardan, Ahmad A.; Speily, Omid R. B.; Modaberi, Somayyeh

2011-01-01

The majority of current web-based learning systems are closed learning environments where courses and learning materials are fixed, and the only dynamic aspect is the organization of the material that can be adapted to allow a relatively individualized learning environment. In this paper, we propose an evolving web-based learning system which can…

Learning for intelligent mobile robots

NASA Astrophysics Data System (ADS)

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

2003-10-01

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

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

ERIC Educational Resources Information Center

Scott, Ezequiel; Soria, Alvaro; Campo, Marcelo

2017-01-01

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

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

ERIC Educational Resources Information Center

Chang, Yoo Kyung

2010-01-01

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

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

ERIC Educational Resources Information Center

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

2016-01-01

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

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

ERIC Educational Resources Information Center

Komlenov, Zivana; Budimac, Zoran; Ivanovic, Mirjana

2010-01-01

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

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.…

Discussion of the enabling environments for decentralised water systems.

PubMed

Moglia, M; Alexander, K S; Sharma, A

2011-01-01

Decentralised water supply systems are becoming increasingly affordable and commonplace in Australia and have the potential to alleviate urban water shortages and reduce pollution into natural receiving marine and freshwater streams. Learning processes are necessary to support the efficient implementation of decentralised systems. These processes reveal the complex socio-technical and institutional factors to be considered when developing an enabling environment supporting decentralised water and wastewater servicing solutions. Critical to the technological transition towards established decentralised systems is the ability to create strategic and adaptive capacity to promote learning and dialogue. Learning processes require institutional mechanisms to ensure the lessons are incorporated into the formulation of policy and regulation, through constructive involvement of key government institutions. Engagement of stakeholders is essential to the enabling environment. Collaborative learning environments using systems analysis with communities (social learning) and adaptive management techniques are useful in refining and applying scientists' and managers' knowledge (knowledge management).

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

ERIC Educational Resources Information Center

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

2007-01-01

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

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

ERIC Educational Resources Information Center

Yao, Ching-Bang

2017-01-01

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

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

ERIC Educational Resources Information Center

Mercurio, Marco; Torre, Ilaria; Torsani, Simone

2014-01-01

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

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…

Towards Individualized Online Learning: The Design and Development of an Adaptive Web Based Learning Environment

ERIC Educational Resources Information Center

Inan, Fethi A.; Flores, Raymond; Ari, Fatih; Arslan-Ari, Ismahan

2011-01-01

The purpose of this study was to document the design and development of an adaptive system which individualizes instruction such as content, interfaces, instructional strategies, and resources dependent on two factors, namely student motivation and prior knowledge levels. Combining adaptive hypermedia methods with strategies proposed by…

An Examination of the Role of the E-Tutor

ERIC Educational Resources Information Center

Goold, Annegret; Coldwell, Jo; Craig, Annemieke

2010-01-01

As online learning environments continue to evolve, both teachers and students need to adapt to make the most of opportunities afforded by these environments for teaching and learning. The focus of this paper is on the changing role undertaken by tutors in online learning environments. We present a brief review of the current perspectives on the…

Multi Car Elevator Control by using Learning Automaton

NASA Astrophysics Data System (ADS)

Shiraishi, Kazuaki; Hamagami, Tomoki; Hirata, Hironori

We study an adaptive control technique for multi car elevators (MCEs) by adopting learning automatons (LAs.) The MCE is a high performance and a near-future elevator system with multi shafts and multi cars. A strong point of the system is that realizing a large carrying capacity in small shaft area. However, since the operation is too complicated, realizing an efficient MCE control is difficult for top-down approaches. For example, “bunching up together" is one of the typical phenomenon in a simple traffic environment like the MCE. Furthermore, an adapting to varying environment in configuration requirement is a serious issue in a real elevator service. In order to resolve these issues, having an autonomous behavior is required to the control system of each car in MCE system, so that the learning automaton, as the solutions for this requirement, is supposed to be appropriate for the simple traffic control. First, we assign a stochastic automaton (SA) to each car control system. Then, each SA varies its stochastic behavior distributions for adapting to environment in which its policy is evaluated with each passenger waiting times. That is LA which learns the environment autonomously. Using the LA based control technique, the MCE operation efficiency is evaluated through simulation experiments. Results show the technique enables reducing waiting times efficiently, and we confirm the system can adapt to the dynamic environment.

Hold it! The influence of lingering rewards on choice diversification and persistence.

PubMed

Schulze, Christin; van Ravenzwaaij, Don; Newell, Ben R

2017-11-01

Learning to choose adaptively when faced with uncertain and variable outcomes is a central challenge for decision makers. This study examines repeated choice in dynamic probability learning tasks in which outcome probabilities changed either as a function of the choices participants made or independently of those choices. This presence/absence of sequential choice-outcome dependencies was implemented by manipulating a single task aspect between conditions: the retention/withdrawal of reward across individual choice trials. The study addresses how people adapt to these learning environments and to what extent they engage in 2 choice strategies often contrasted as paradigmatic examples of striking violation of versus nominal adherence to rational choice: diversification and persistent probability maximizing, respectively. Results show that decisions approached adaptive choice diversification and persistence when sufficient feedback was provided on the dynamic rules of the probabilistic environments. The findings of divergent behavior in the 2 environments indicate that diversified choices represented a response to the reward retention manipulation rather than to the mere variability of outcome probabilities. Choice in both environments was well accounted for by the generalized matching law, and computational modeling-based strategy analyses indicated that adaptive choice arose mainly from reliance on reinforcement learning strategies. (PsycINFO Database Record (c) 2017 APA, 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.

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

ERIC Educational Resources Information Center

Yang, Xinrong

2015-01-01

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

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

ERIC Educational Resources Information Center

Chase, Anthony; Pakhira, Deblina; Stains, Marilyne

2013-01-01

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

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 student), pedagogy ontology, and learner ontology (defines time constraint, comment, profile).

A Web-Based Educational Setting Supporting Individualized Learning, Collaborative Learning and Assessment

ERIC Educational Resources Information Center

Gogoulou, Agoritsa; Gouli, Evangelia; Grigoriadou, Maria; Samarakou, Maria; Chinou, Dionisia

2007-01-01

In this paper, we present a web-based educational setting, referred to as SCALE (Supporting Collaboration and Adaptation in a Learning Environment), which aims to serve learning and assessment. SCALE enables learners to (i) work on individual and collaborative activities proposed by the environment with respect to learners' knowledge level, (ii)…

The Adaptation and Validation of the CEQ and the R-SPQ-2F to the Japanese Tertiary Environment

ERIC Educational Resources Information Center

Fryer, Luke K.; Ginns, Paul; Walker, Richard A.; Nakao, Kaori

2012-01-01

Background: Student learning theory (SLT) has established associations between students' approaches to learning and their perceptions of the learning environment. SLT may provide a useful framework for researching student learning within the Japanese tertiary sector. Aims: The study aims to explore and validate the Course Experience Questionnaire…

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

ERIC Educational Resources Information Center

Own, Zangyuan

2006-01-01

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

The Complex Experience of Learning to Do Research

ERIC Educational Resources Information Center

Emo, Kenneth; Emo, Wendy; Kimn, Jung-Han; Gent, Stephen

2015-01-01

This article examines how student learning is a product of the experiential interaction between person and environment. We draw from the theoretical perspective of complexity to shed light on the emergent, adaptive, and unpredictable nature of students' learning experiences. To understand the relationship between the environment and the student…

Web Geometry Laboratory: Case Studies in Portugal and Serbia

ERIC Educational Resources Information Center

Santos, Vanda; Quaresma, Pedro; Maric, Milena; Campos, Helena

2018-01-01

The role of information and communication technologies (ICT) in education is well recognised--learning environments where the ICT features included are being proposed for many years now. The Web Geometry Laboratory (WGL) innovates in proposing a blended learning, collaborative and adaptive learning Web-environment for geometry. It integrates a…

The Relative Merits of Transparency: Investigating Situations that Support the Use of Robotics in Developing Student Learning Adaptability across Virtual and Physical Computing Platforms

ERIC Educational Resources Information Center

Okita, Sandra Y.

2014-01-01

This study examined whether developing earlier forms of knowledge in specific learning environments prepares students better for future learning when they are placed in an unfamiliar learning environment. Forty-one students in the fifth and sixth grades learned to program robot movements using abstract concepts of speed, distance and direction.…

How do general practice residents use social networking sites in asynchronous distance learning?

PubMed

Maisonneuve, Hubert; Chambe, Juliette; Lorenzo, Mathieu; Pelaccia, Thierry

2015-09-21

Blended learning environments - involving both face-to-face and remote interactions - make it easier to adapt learning programs to constraints such as residents' location and low teacher-student ratio. Social networking sites (SNS) such as Facebook®, while not originally intended to be used as learning environments, may be adapted for the distance-learning part of training programs. The purpose of our study was to explore the use of SNS for asynchronous distance learning in a blended learning environment as well as its influence on learners' face-to-face interactions. We conducted a qualitative study and carried out semi-structured interviews. We performed purposeful sampling for maximal variation to include eight general practice residents in 2(nd) and 3(rd) year training. A thematic analysis was performed. The social integration of SNS facilitates the engagement of users in their learning tasks. This may also stimulate students' interactions and group cohesion when members meet up in person. Most of the general practice residents who work in the blended learning environment we studied had a positive appraisal on their use of SNS. In particular, we report a positive impact on their engagement in learning and their participation in discussions during face-to-face instruction. Further studies are needed in order to evaluate the effectiveness of SNS in blended learning environments and the appropriation of SNS by teachers.

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

ERIC Educational Resources Information Center

Drexler, Wendy

2010-01-01

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

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

ERIC Educational Resources Information Center

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

2011-01-01

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

Modeling and Intervening across Time in Scientific Inquiry Exploratory Learning Environment

ERIC Educational Resources Information Center

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

2008-01-01

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

Facilitation of Learning by Social-Emotional Feedback in Humans Is Beta-Noradrenergic-Dependent

ERIC Educational Resources Information Center

Mihov, Yoan; Mayer, Simon; Musshoff, Frank; Maier, Wolfgang; Kendrick, Keith M.; Hurlemann, Rene

2010-01-01

Adaptive behavior in dynamic environments critically depends on the ability to learn rapidly and flexibly from the outcomes of prior choices. In social environments, facial expressions of emotion often serve as performance feedback and thereby guide declarative learning. Abundant evidence implicates beta-noradrenergic signaling in the modulatory…

Alternating prism exposure causes dual adaptation and generalization to a novel displacement

NASA Technical Reports Server (NTRS)

Welch, Robert B.; Bridgeman, Bruce; Anand, Sulekha; Browman, Kaitlin E.

1993-01-01

In two experiments, we examined the hypothesis that repeatedly adapting and readapting to two mutually conflicting sensory environments fosters the development of a separate adaptation to each situation (dual adaptation) as well as an increased ability to adapt to a novel displacement (adaptive generalization). In the preliminary study, subjects alternated between adapting their visuomotor coordination to 30-diopter prismatic displacement and readapting to normal vision. Dual adaptation was observed by the end of 10 alternation cycles. However, an unconfounded test of adaptive generalization was prevented by an unexpected prism-adaptive shift in preexposure baselines for the dual-adapted subjects. In the primary experiment, the subjects adapted and readapted to opposite 15-diopter displacements for a total of 12 cycles. Both dual adaptation and adaptive generalization to a 30-diopter displacement were obtained. These findings may be understood in terms of serial reversal learning and 'learning to learn'.

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

ERIC Educational Resources Information Center

Alterator, Scott; Deed, Craig

2016-01-01

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

Using Cognitive Load Theory to Tailor Instruction to Levels of Accounting Students' Expertise

ERIC Educational Resources Information Center

Blayney, Paul; Kalyuga, Slava; Sweller, John

2015-01-01

Tailoring of instructional methods to learner levels of expertise may reduce extraneous cognitive load and improve learning. Contemporary technology-based learning environments have the potential to substantially enable learner-adapted instruction. This paper investigates the effects of adaptive instruction based on using the isolated-interactive…

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.

Visuomotor adaptation in head-mounted virtual reality versus conventional training

PubMed Central

Anglin, J. M.; Sugiyama, T.; Liew, S.-L.

2017-01-01

Immersive, head-mounted virtual reality (HMD-VR) provides a unique opportunity to understand how changes in sensory environments affect motor learning. However, potential differences in mechanisms of motor learning and adaptation in HMD-VR versus a conventional training (CT) environment have not been extensively explored. Here, we investigated whether adaptation on a visuomotor rotation task in HMD-VR yields similar adaptation effects in CT and whether these effects are achieved through similar mechanisms. Specifically, recent work has shown that visuomotor adaptation may occur via both an implicit, error-based internal model and a more cognitive, explicit strategic component. We sought to measure both overall adaptation and balance between implicit and explicit mechanisms in HMD-VR versus CT. Twenty-four healthy individuals were placed in either HMD-VR or CT and trained on an identical visuomotor adaptation task that measured both implicit and explicit components. Our results showed that the overall timecourse of adaption was similar in both HMD-VR and CT. However, HMD-VR participants utilized a greater cognitive strategy than CT, while CT participants engaged in greater implicit learning. These results suggest that while both conditions produce similar results in overall adaptation, the mechanisms by which visuomotor adaption occurs in HMD-VR appear to be more reliant on cognitive strategies. PMID:28374808

Wireless Adaptive Therapeutic TeleGaming in a Pervasive Computing Environment

NASA Astrophysics Data System (ADS)

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

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

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

ERIC Educational Resources Information Center

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

2011-01-01

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

Analyzing User Interaction to Design an Intelligent e-Learning Environment

ERIC Educational Resources Information Center

Sharma, Richa

2011-01-01

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

Closing the 21st-Century Knowledge Gap: Reconceptualizing Teaching and Learning to Transform Business Education

ERIC Educational Resources Information Center

Longmore, Anne-Liisa; Grant, Ginger; Golnaraghi, Golnaz

2018-01-01

The 21st century is seeing dramatic shifts in the business environment. In order for organizations to adapt to these shifts, they must be more flexible and learning oriented. To thrive in this environment, organizational leaders must facilitate and build the capacity for learning throughout the organization. Organizational leadership is looking…

Environments for Development

ERIC Educational Resources Information Center

Grabinski, C. Joanne

2005-01-01

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

Cultural Dimensions of Learning: Addressing the Challenges of Multicultural Instruction

ERIC Educational Resources Information Center

Parrish, Patrick; Linder-VanBerschot, Jennifer A.

2010-01-01

The growing multicultural nature of education and training environments makes it critical that instructors and instructional designers, especially those working in online learning environments, develop skills to deliver culturally sensitive and culturally adaptive instruction. This article explores research into cultural differences to identify…

Environments for Lifelong Learning in Senior Centers

ERIC Educational Resources Information Center

Eaton, Jacqueline; Salari, Sonia

2005-01-01

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

Robotic action acquisition with cognitive biases in coarse-grained state space.

PubMed

Uragami, Daisuke; Kohno, Yu; Takahashi, Tatsuji

2016-07-01

Some of the authors have previously proposed a cognitively inspired reinforcement learning architecture (LS-Q) that mimics cognitive biases in humans. LS-Q adaptively learns under uniform, coarse-grained state division and performs well without parameter tuning in a giant-swing robot task. However, these results were shown only in simulations. In this study, we test the validity of the LS-Q implemented in a robot in a real environment. In addition, we analyze the learning process to elucidate the mechanism by which the LS-Q adaptively learns under the partially observable environment. We argue that the LS-Q may be a versatile reinforcement learning architecture, which is, despite its simplicity, easily applicable and does not require well-prepared settings. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

What if Learning Analytics Were Based on Learning Science?

ERIC Educational Resources Information Center

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

2016-01-01

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

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

ERIC Educational Resources Information Center

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

2017-01-01

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

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

DTIC Science & Technology

2015-11-01

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

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

ERIC Educational Resources Information Center

Hendriks, Stefan

2017-01-01

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

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

PubMed

Hurst, Jacob; Bull, Larry

2006-01-01

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

Designing Empathetic Animated Agents for a B-Learning Training Environment within the Electrical Domain

ERIC Educational Resources Information Center

Hernández, Yasmin; Pérez-Ramírez, Miguel; Zatarain-Cabada, Ramon; Barrón-Estrada, Lucia; Alor-Hernández, Giner

2016-01-01

Electrical tests involve high risk; therefore utility companies require highly qualified electricians and efficient training. Recently, training for electrical tests has been supported by virtual reality systems; nonetheless, these training systems are not yet adaptive. We propose a b-learning model to support adaptive and distance training. The…

Coordinating Decentralized Learning and Conflict Resolution across Agent Boundaries

ERIC Educational Resources Information Center

Cheng, Shanjun

2012-01-01

It is crucial for embedded systems to adapt to the dynamics of open environments. This adaptation process becomes especially challenging in the context of multiagent systems because of scalability, partial information accessibility and complex interaction of agents. It is a challenge for agents to learn good policies, when they need to plan and…

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

PubMed

Kenzig, Melissa J

2015-09-01

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

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 the non-adapted groups on the immediate posttest. No significant difference was found between the adapted and the non-adapted groups on the retention posttest. However, results also revealed that the adapted group scored significantly higher on the retention posttest when compared with the immediate posttest. Interestingly, the non-adapted group scored significantly higher on the immediate posttest when compared with the retention posttest. When queried about the perception of benefit of the lesson style, 42% of the adapted group replied in the affirmative following the immediate posttest, yet that percentage grew to 81% following the retention posttest. The non-adapted group had 28% reply in the affirmative following the immediate posttest, and that percentage grew to 48% following the retention posttest. Both groups found benefit, yet the numbers associated with the adapted group were higher. Overall perceptions of benefit corresponded to higher test scores as opposed to those who did not find benefit, who had a lower score.

TEx-Sys Model for Building Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Stankov, Slavomir; Rosic, Marko; Zitko, Branko; Grubisic, Ani

2008-01-01

Special classes of asynchronous e-learning systems are the intelligent tutoring systems which represent an advanced learning and teaching environment adaptable to individual student's characteristics. Authoring shells have an environment that enables development of the intelligent tutoring systems. In this paper we present, in entirety, for the…

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

ERIC Educational Resources Information Center

Kember, David; Leung, Doris Y. P.

2005-01-01

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

Bridging the Gap: Adaptive Games and Student-Centered VLEs

NASA Astrophysics Data System (ADS)

Del Blanco, Ángel; Torrente, Javier; Moreno-Ger, Pablo; Fernández-Manjón, Baltasar

The widely used e-learning technology is facing new challenges such as how to produce student-centered systems that can be adapted to the needs of each student. Those objectives should be met in a standard compliant way to simplify general adoption. In this context, educational videogames are proposed as an ideal medium to facilitate adaptation and tracking of the students’ performance for assessment purposes. However, there are still barriers between the gaming and e-learning worlds preventing their mutual interaction. In this paper we propose a middleware to bridge this gap, integrating adaptive educational videogames in e-learning environments with a special focus on the ongoing standardization efforts.

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

PubMed

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

2017-02-07

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

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

PubMed

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

2011-12-01

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

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

ERIC Educational Resources Information Center

Wong-Lo, Mickie; Cortez, Gabriel A.

2014-01-01

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

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

Multiagent cooperation and competition with deep reinforcement learning.

PubMed

Tampuu, Ardi; Matiisen, Tambet; Kodelja, Dorian; Kuzovkin, Ilya; Korjus, Kristjan; Aru, Juhan; Aru, Jaan; Vicente, Raul

2017-01-01

Evolution of cooperation and competition can appear when multiple adaptive agents share a biological, social, or technological niche. In the present work we study how cooperation and competition emerge between autonomous agents that learn by reinforcement while using only their raw visual input as the state representation. In particular, we extend the Deep Q-Learning framework to multiagent environments to investigate the interaction between two learning agents in the well-known video game Pong. By manipulating the classical rewarding scheme of Pong we show how competitive and collaborative behaviors emerge. We also describe the progression from competitive to collaborative behavior when the incentive to cooperate is increased. Finally we show how learning by playing against another adaptive agent, instead of against a hard-wired algorithm, results in more robust strategies. The present work shows that Deep Q-Networks can become a useful tool for studying decentralized learning of multiagent systems coping with high-dimensional environments.

Multiagent cooperation and competition with deep reinforcement learning

PubMed Central

Kodelja, Dorian; Kuzovkin, Ilya; Korjus, Kristjan; Aru, Juhan; Aru, Jaan; Vicente, Raul

2017-01-01

Evolution of cooperation and competition can appear when multiple adaptive agents share a biological, social, or technological niche. In the present work we study how cooperation and competition emerge between autonomous agents that learn by reinforcement while using only their raw visual input as the state representation. In particular, we extend the Deep Q-Learning framework to multiagent environments to investigate the interaction between two learning agents in the well-known video game Pong. By manipulating the classical rewarding scheme of Pong we show how competitive and collaborative behaviors emerge. We also describe the progression from competitive to collaborative behavior when the incentive to cooperate is increased. Finally we show how learning by playing against another adaptive agent, instead of against a hard-wired algorithm, results in more robust strategies. The present work shows that Deep Q-Networks can become a useful tool for studying decentralized learning of multiagent systems coping with high-dimensional environments. PMID:28380078

Developing a new experimental system for an undergraduate laboratory exercise to teach theories of visuomotor learning.

PubMed

Kasuga, Shoko; Ushiba, Junichi

2014-01-01

Humans have a flexible motor ability to adapt their movements to changes in the internal/external environment. For example, using arm-reaching tasks, a number of studies experimentally showed that participants adapt to a novel visuomotor environment. These results helped develop computational models of motor learning implemented in the central nervous system. Despite the importance of such experimental paradigms for exploring the mechanisms of motor learning, because of the cost and preparation time, most students are unable to participate in such experiments. Therefore, in the current study, to help students better understand motor learning theories, we developed a simple finger-reaching experimental system using commonly used laptop PC components with an open-source programming language (Processing Motor Learning Toolkit: PMLT). We found that compared to a commercially available robotic arm-reaching device, our PMLT accomplished similar learning goals (difference in the error reduction between the devices, P = 0.10). In addition, consistent with previous reports from visuomotor learning studies, the participants showed after-effects indicating an adaptation of the motor learning system. The results suggest that PMLT can serve as a new experimental system for an undergraduate laboratory exercise of motor learning theories with minimal time and cost for instructors.

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

ERIC Educational Resources Information Center

Kaler, Collier Butler

2012-01-01

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

Recent Contributions to a Generic Architecture Design that Supports Learning Objects Interoperability

ERIC Educational Resources Information Center

Botsios, Sotirios; Georgiou, Dimitrios A.

2009-01-01

Adaptation and personalization services in e-learning environments are considered the turning point of recent research efforts, as the "one-size-fits-all" approach has some important drawbacks, from the educational point of view. Adaptive Educational Hypermedia Systems in World Wide Web became a very active research field and the need of…

Cases on Technological Adaptability and Transnational Learning: Issues and Challenges

ERIC Educational Resources Information Center

Mukerji, Siran, Ed.; Tripathi, Purnendu, Ed.

2010-01-01

Technology holds the key for bridging the gap between access to quality education and the need for enhanced learning experiences. This book contains case studies on divergent themes of personalized learning environments, inclusive learning for social change, innovative learning and assessment techniques, technology and international partnership…

Examining Online Learning Patterns with Data Mining Techniques in Peer-Moderated and Teacher-Moderated Courses

ERIC Educational Resources Information Center

Hung, Jui-Long; Crooks, Steven M.

2009-01-01

The student learning process is important in online learning environments. If instructors can "observe" online learning behaviors, they can provide adaptive feedback, adjust instructional strategies, and assist students in establishing patterns of successful learning activities. This study used data mining techniques to examine and…

Functionally dissociable influences on learning rate in a dynamic environment

PubMed Central

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

2015-01-01

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

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

ERIC Educational Resources Information Center

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

2014-01-01

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

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.

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.

Learning, climate and the evolution of cultural capacity.

PubMed

Whitehead, Hal

2007-03-21

Patterns of environmental variation influence the utility, and thus evolution, of different learning strategies. I use stochastic, individual-based evolutionary models to assess the relative advantages of 15 different learning strategies (genetic determination, individual learning, vertical social learning, horizontal/oblique social learning, and contingent combinations of these) when competing in variable environments described by 1/f noise. When environmental variation has little effect on fitness, then genetic determinism persists. When environmental variation is large and equal over all time-scales ("white noise") then individual learning is adaptive. Social learning is advantageous in "red noise" environments when variation over long time-scales is large. Climatic variability increases with time-scale, so that short-lived organisms should be able to rely largely on genetic determination. Thermal climates usually are insufficiently red for social learning to be advantageous for species whose fitness is very determined by temperature. In contrast, population trajectories of many species, especially large mammals and aquatic carnivores, are sufficiently red to promote social learning in their predators. The ocean environment is generally redder than that on land. Thus, while individual learning should be adaptive for many longer-lived organisms, social learning will often be found in those dependent on the populations of other species, especially if they are marine. This provides a potential explanation for the evolution of a prevalence of social learning, and culture, in humans and cetaceans.

Wiki-Based Rapid Prototyping for Teaching-Material Design in E-Learning Grids

ERIC Educational Resources Information Center

Shih, Wen-Chung; Tseng, Shian-Shyong; Yang, Chao-Tung

2008-01-01

Grid computing environments with abundant resources can support innovative e-Learning applications, and are promising platforms for e-Learning. To support individualized and adaptive learning, teachers are encouraged to develop various teaching materials according to different requirements. However, traditional methodologies for designing teaching…

Globally Sustainable Management: A Dynamic Model of IHRM Learning and Control

ERIC Educational Resources Information Center

Takeda, Margaret B.; Helms, Marilyn M.

2010-01-01

Purpose: After a thorough literature review on multinational learning, it is apparent organizations "learn" when they capitalize on expatriate management, a "learning strategy" (international work teams, employee involvement and other human resource policies), technology transfer and political environment and cross-cultural adaptation. This…

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

ERIC Educational Resources Information Center

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

2017-01-01

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

Internationalising a Learning Environment Instrument for Evaluating Transnational Online University Courses

ERIC Educational Resources Information Center

Yeo, Shelley; Taylor, Peter; Kulski, Martijntje

2006-01-01

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

Passionate Practitioners: Engaging Not Just the Head but also the Heart

ERIC Educational Resources Information Center

Reynolds, Sue; Welch, Bernadette; Carroll, Mary

2012-01-01

This conceptual paper will discuss how Australian library and information science (LIS) educators have adapted passion-based learning theory for the post-graduate environment. The learning environment has been developed to both facilitate the acquisition of short-term employability skills for the industry and also to allow students to connect more…

Personalized Recommender System for e-Learning Environment

ERIC Educational Resources Information Center

Benhamdi, Soulef; Babouri, Abdesselam; Chiky, Raja

2017-01-01

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

Application of Mobile Agents in Web-Based Learning Environment.

ERIC Educational Resources Information Center

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

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

‘Newcomer adaptation’: a lens through which to understand how nursing students fit in with the real world of practice

PubMed Central

Houghton, Catherine E

2014-01-01

Aims and objectives To present a discussion on newcomer adaptation as a lens through which to understand how nursing students adapt to clinical practice and raise awareness of strategies that can be used to enhance their learning experiences. Background Socialisation is an important factor that facilitates students’ learning in the clinical setting. Therefore, it is beneficial to examine organisational socialisation literature, particularly that pertaining to newcomer adaptation. Design This is a critical review of organisational socialisation literature. Methods Seminal literature and more recent research in the field of organisational socialisation and newcomer adaptation were accessed. In addition, nursing and allied health literature examining students’ socialisation and the clinical learning environment was retrieved. Conclusions It is revealed in this article that to create an appropriate clinical learning environment, an understanding of socialisation tactics could be beneficial. Role modelling is deemed crucial to successful newcomer adaptation. Peer support is necessary but must be advocated with caution as it can have a negative impact when students form a ‘parallel community’. Students with some knowledge of the workplace tend to adapt more easily. Likewise, students’ disposition and, in particular, their confidence can also enhance the socialisation process. Relevance to clinical practice Both the organisation and the student can impact on how successfully the nursing student ‘fits in’. Understanding this through the lens of newcomer adaptation means that strategies can be put in place to facilitate this process. PMID:24455974

Adaptive Technologies. Research Report. ETS RR-07-05

ERIC Educational Resources Information Center

Shute, Valerie J.; Zapata-Rivera, Diego

2007-01-01

This paper describes research and development efforts related to adaptive technologies, which can be combined with other technologies and processes to form an adaptive system. The goal of an adaptive system, in the context of this paper, is to create an instructionally sound and flexible environment that supports learning for students with a range…

Novel Hybrid Adaptive Controller for Manipulation in Complex Perturbation Environments

PubMed Central

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

2015-01-01

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

Changing Places: A Study of Chinese Students in the UK

ERIC Educational Resources Information Center

Gu, Qing; Maley, Alan

2008-01-01

This article explores the way tertiary level Chinese students in the UK adapt, in varying degrees, to their new learning and living environment. A questionnaire and interview study that includes both Chinese students and their British teachers attempts to ascertain key issues with a view to helping sojourning students adapt to their environment,…

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

ERIC Educational Resources Information Center

Kostolányová, Katerina; Šarmanová, Jana

2014-01-01

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

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

PubMed Central

Mathew, Sarah; Perreault, Charles

2015-01-01

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

Applying Adaptive Swarm Intelligence Technology with Structuration in Web-Based Collaborative Learning

ERIC Educational Resources Information Center

Huang, Yueh-Min; Liu, Chien-Hung

2009-01-01

One of the key challenges in the promotion of web-based learning is the development of effective collaborative learning environments. We posit that the structuration process strongly influences the effectiveness of technology used in web-based collaborative learning activities. In this paper, we propose an ant swarm collaborative learning (ASCL)…

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

ERIC Educational Resources Information Center

Hugerat, Muhamad

2016-01-01

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

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 the quantum approach averaged a more optimistic 0.57±0.4, but with high phase fluctuations. Conclusion: Our results demonstrate that quantum machine learning approaches provide a feasible and promising framework for real-time and sequential clinical decision-making in adaptive radiotherapy.« less

Envisioning engineering education and practice in the coming intelligence convergence era — a complex adaptive systems approach

NASA Astrophysics Data System (ADS)

Noor, Ahmed K.

2013-12-01

Some of the recent attempts for improving and transforming engineering education are reviewed. The attempts aim at providing the entry level engineers with the skills needed to address the challenges of future large-scale complex systems and projects. Some of the frontier sectors and future challenges for engineers are outlined. The major characteristics of the coming intelligence convergence era (the post-information age) are identified. These include the prevalence of smart devices and environments, the widespread applications of anticipatory computing and predictive / prescriptive analytics, as well as a symbiotic relationship between humans and machines. Devices and machines will be able to learn from, and with, humans in a natural collaborative way. The recent game changers in learnscapes (learning paradigms, technologies, platforms, spaces, and environments) that can significantly impact engineering education in the coming era are identified. Among these are open educational resources, knowledge-rich classrooms, immersive interactive 3D learning, augmented reality, reverse instruction / flipped classroom, gamification, robots in the classroom, and adaptive personalized learning. Significant transformative changes in, and mass customization of, learning are envisioned to emerge from the synergistic combination of the game changers and other technologies. The realization of the aforementioned vision requires the development of a new multidisciplinary framework of emergent engineering for relating innovation, complexity and cybernetics, within the future learning environments. The framework can be used to treat engineering education as a complex adaptive system, with dynamically interacting and communicating components (instructors, individual, small, and large groups of learners). The emergent behavior resulting from the interactions can produce progressively better, and continuously improving, learning environment. As a first step towards the realization of the vision, intelligent adaptive cyber-physical ecosystems need to be developed to facilitate collaboration between the various stakeholders of engineering education, and to accelerate the development of a skilled engineering workforce. The major components of the ecosystems include integrated knowledge discovery and exploitation facilities, blended learning and research spaces, novel ultra-intelligent software agents, multimodal and autonomous interfaces, and networked cognitive and tele-presence robots.

Adaptive critic autopilot design of bank-to-turn missiles using fuzzy basis function networks.

PubMed

Lin, Chuan-Kai

2005-04-01

A new adaptive critic autopilot design for bank-to-turn missiles is presented. In this paper, the architecture of adaptive critic learning scheme contains a fuzzy-basis-function-network based associative search element (ASE), which is employed to approximate nonlinear and complex functions of bank-to-turn missiles, and an adaptive critic element (ACE) generating the reinforcement signal to tune the associative search element. In the design of the adaptive critic autopilot, the control law receives signals from a fixed gain controller, an ASE and an adaptive robust element, which can eliminate approximation errors and disturbances. Traditional adaptive critic reinforcement learning is the problem faced by an agent that must learn behavior through trial-and-error interactions with a dynamic environment, however, the proposed tuning algorithm can significantly shorten the learning time by online tuning all parameters of fuzzy basis functions and weights of ASE and ACE. Moreover, the weight updating law derived from the Lyapunov stability theory is capable of guaranteeing both tracking performance and stability. Computer simulation results confirm the effectiveness of the proposed adaptive critic autopilot.

Predicting Student Performance in a Collaborative Learning Environment

ERIC Educational Resources Information Center

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

2015-01-01

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

Integrating Augmented Reality Technology to Enhance Children's Learning in Marine Education

ERIC Educational Resources Information Center

Lu, Su-Ju; Liu, Ying-Chieh

2015-01-01

Marine education comprises rich and multifaceted issues. Raising general awareness of marine environments and issues demands the development of new learning materials. This study adapts concepts from digital game-based learning to design an innovative marine learning program integrating augmented reality (AR) technology for lower grade primary…

The Integrative Learning Value of Field Courses

ERIC Educational Resources Information Center

Durrant, Kate L.; Hartman, Thomas P. V.

2015-01-01

The integrative learning ethos pervades modern higher education. Broadly speaking, this aims to produce well-rounded, adaptable graduates suited to a range of working environments. In a more narrow sense it should produce students that are able to make connections across learning experiences and achieve learning at the highest cognitive level. Our…

Reusable Models of Pedagogical Concepts--A Framework for Pedagogical and Content Design.

ERIC Educational Resources Information Center

Pawlowski, Jan M.

Standardization initiatives in the field of learning technologies have produced standards for the interoperability of learning environments and learning management systems. Learning resources based on these standards can be reused, recombined, and adapted to the user. However, these standards follow a content-oriented approach; the process of…

International Students' Culture Learning and Cultural Adaptation in China

ERIC Educational Resources Information Center

An, Ran; Chiang, Shiao-Yun

2015-01-01

This article examines international students' cultural adaptation at a major national university in China. A survey was designed to measure international students' adaptation to the Chinese sociocultural and educational environments in terms of five dimensions: (1) cultural empathy, (2) open-mindedness, (3) emotional stability, (4) social…

E-learning environment as intelligent tutoring system

NASA Astrophysics Data System (ADS)

Nagyová, Ingrid

2017-07-01

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

Humanoids Learning to Walk: A Natural CPG-Actor-Critic Architecture.

PubMed

Li, Cai; Lowe, Robert; Ziemke, Tom

2013-01-01

The identification of learning mechanisms for locomotion has been the subject of much research for some time but many challenges remain. Dynamic systems theory (DST) offers a novel approach to humanoid learning through environmental interaction. Reinforcement learning (RL) has offered a promising method to adaptively link the dynamic system to the environment it interacts with via a reward-based value system. In this paper, we propose a model that integrates the above perspectives and applies it to the case of a humanoid (NAO) robot learning to walk the ability of which emerges from its value-based interaction with the environment. In the model, a simplified central pattern generator (CPG) architecture inspired by neuroscientific research and DST is integrated with an actor-critic approach to RL (cpg-actor-critic). In the cpg-actor-critic architecture, least-square-temporal-difference based learning converges to the optimal solution quickly by using natural gradient learning and balancing exploration and exploitation. Futhermore, rather than using a traditional (designer-specified) reward it uses a dynamic value function as a stability indicator that adapts to the environment. The results obtained are analyzed using a novel DST-based embodied cognition approach. Learning to walk, from this perspective, is a process of integrating levels of sensorimotor activity and value.

Humanoids Learning to Walk: A Natural CPG-Actor-Critic Architecture

PubMed Central

Li, Cai; Lowe, Robert; Ziemke, Tom

2013-01-01

The identification of learning mechanisms for locomotion has been the subject of much research for some time but many challenges remain. Dynamic systems theory (DST) offers a novel approach to humanoid learning through environmental interaction. Reinforcement learning (RL) has offered a promising method to adaptively link the dynamic system to the environment it interacts with via a reward-based value system. In this paper, we propose a model that integrates the above perspectives and applies it to the case of a humanoid (NAO) robot learning to walk the ability of which emerges from its value-based interaction with the environment. In the model, a simplified central pattern generator (CPG) architecture inspired by neuroscientific research and DST is integrated with an actor-critic approach to RL (cpg-actor-critic). In the cpg-actor-critic architecture, least-square-temporal-difference based learning converges to the optimal solution quickly by using natural gradient learning and balancing exploration and exploitation. Futhermore, rather than using a traditional (designer-specified) reward it uses a dynamic value function as a stability indicator that adapts to the environment. The results obtained are analyzed using a novel DST-based embodied cognition approach. Learning to walk, from this perspective, is a process of integrating levels of sensorimotor activity and value. PMID:23675345

The Usability Analysis of an E-Learning Environment

ERIC Educational Resources Information Center

Torun, Fulya; Tekedere, Hakan

2015-01-01

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

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

ERIC Educational Resources Information Center

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

2010-01-01

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

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

ERIC Educational Resources Information Center

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

2016-01-01

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

Designing Adaptive Instructional Environments: Insights from Empirical Evidence

DTIC Science & Technology

2011-10-01

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

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

Internet-based Interactive Construction Management Learning System.

ERIC Educational Resources Information Center

Sawhney, Anil; Mund, Andre; Koczenasz, Jeremy

2001-01-01

Describes a way to incorporate practical content into the construction engineering and management curricula: the Internet-based Interactive Construction Management Learning System, which uses interactive and adaptive learning environments to train students in the areas of construction methods, equipment and processes using multimedia, databases,…

Teaching Technology Education to Visually Impaired Students.

ERIC Educational Resources Information Center

Mann, Rene

1987-01-01

Discusses various types of visual impairments and how the learning environment can be adapted to limit their effect. Presents suggestions for adapting industrial arts laboratory activities to maintain safety standards while allowing the visually impaired to participate. (CH)

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

NASA Astrophysics Data System (ADS)

Satoh, Hideki

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

The Correlates and Influences of Career-Related Continuous Learning: Implications for Management Professionals

ERIC Educational Resources Information Center

Kuznia, Kevin D.; Kerno, Steven J., Jr.; Gilley, Ann

2010-01-01

Management personnel are increasingly aware that career success depends on the ability to continuously learn and adapt to the environment. However, scant attention has been paid to how learning activities contribute to managerial success. This study examines the degree to which involvement in career-related continuous learning affects managerial…

The Application of Learning Organization to Enhance Learning in Singapore Schools

ERIC Educational Resources Information Center

Retna, Kala S.; Ng, Pak Tee

2016-01-01

The rise of interest in the learning organization (LO) concept attests to the value of learning by individuals and organizations for continuous improvement and adaptability to the ever-changing environment. Although the LO concept originated from business contexts, it was subsequently extended to educational organizations, particularly to schools.…

Teaching and Learning Hand in Hand: Adaptive Teaching and Self-Regulated Learning

ERIC Educational Resources Information Center

Randi, Judi

2017-01-01

This article presents case studies of two novice teachers and their mentors who, without formal knowledge of self-regulation theory, established a classroom environment that promoted self-regulated learning. This case was drawn from a larger descriptive study of novice teachers learning to integrate a student-centered visual literacy instructional…

Blended Learning and Team Teaching: Adapting Pedagogy in Response to the Changing Digital Tertiary Environment

ERIC Educational Resources Information Center

Crawford, Renée; Jenkins, Louise

2017-01-01

Increased accessibility of advanced technology, the targeted use of online learning platforms, student flexible learning expectations and the pressures of faculty budget constraints and priorities have called into question the effectiveness of traditional tertiary teaching and learning models. The tertiary education context must evolve at a pace…

Learning Social Responsibility in Schools: A Restorative Practice

ERIC Educational Resources Information Center

Macready, Tom

2009-01-01

Vygotsky regarded the site of learning to be within a matrix of relational action. From this perspective, learning social responsibility will involve a focus on the learning environments that are made available in schools. Adapting the concept of restorative justice to a school context, restorative practice offers a range of relevant learning…

Classrooms without Borders: New Spaces and Places of Learning

ERIC Educational Resources Information Center

Pawson, Eric

2016-01-01

This article identifies what can be learned from seeking to adapt teaching and learning styles in a post-disaster environment. It focuses on the development of student research through community-based learning as a means of increasing engagement and contributing to recovery in an earthquake-damaged city. It urges consideration of the…

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

How evolution learns to generalise: Using the principles of learning theory to understand the evolution of developmental organisation.

PubMed

Kouvaris, Kostas; Clune, Jeff; Kounios, Loizos; Brede, Markus; Watson, Richard A

2017-04-01

One of the most intriguing questions in evolution is how organisms exhibit suitable phenotypic variation to rapidly adapt in novel selective environments. Such variability is crucial for evolvability, but poorly understood. In particular, how can natural selection favour developmental organisations that facilitate adaptive evolution in previously unseen environments? Such a capacity suggests foresight that is incompatible with the short-sighted concept of natural selection. A potential resolution is provided by the idea that evolution may discover and exploit information not only about the particular phenotypes selected in the past, but their underlying structural regularities: new phenotypes, with the same underlying regularities, but novel particulars, may then be useful in new environments. If true, we still need to understand the conditions in which natural selection will discover such deep regularities rather than exploiting 'quick fixes' (i.e., fixes that provide adaptive phenotypes in the short term, but limit future evolvability). Here we argue that the ability of evolution to discover such regularities is formally analogous to learning principles, familiar in humans and machines, that enable generalisation from past experience. Conversely, natural selection that fails to enhance evolvability is directly analogous to the learning problem of over-fitting and the subsequent failure to generalise. We support the conclusion that evolving systems and learning systems are different instantiations of the same algorithmic principles by showing that existing results from the learning domain can be transferred to the evolution domain. Specifically, we show that conditions that alleviate over-fitting in learning systems successfully predict which biological conditions (e.g., environmental variation, regularity, noise or a pressure for developmental simplicity) enhance evolvability. This equivalence provides access to a well-developed theoretical framework from learning theory that enables a characterisation of the general conditions for the evolution of evolvability.

Print and Non-Print Materials: Adapting for Classroom Use. The ACTFL Foreign Language Education Series, Vol. 10.

ERIC Educational Resources Information Center

Mollica, Anthony S.

It has been said that the classroom must be a multidimensional environment where learning takes place and students are encouraged to realize their own potential. How all the relationships between the student and the components of the environment are cultivated will in large part determine the effectiveness of the teaching-learning process. This…

Linking Immersive Virtual Field Trips with an Adaptive Learning Platform

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Structure Learning in Bayesian Sensorimotor Integration

PubMed Central

Genewein, Tim; Hez, Eduard; Razzaghpanah, Zeynab; Braun, Daniel A.

2015-01-01

Previous studies have shown that sensorimotor processing can often be described by Bayesian learning, in particular the integration of prior and feedback information depending on its degree of reliability. Here we test the hypothesis that the integration process itself can be tuned to the statistical structure of the environment. We exposed human participants to a reaching task in a three-dimensional virtual reality environment where we could displace the visual feedback of their hand position in a two dimensional plane. When introducing statistical structure between the two dimensions of the displacement, we found that over the course of several days participants adapted their feedback integration process in order to exploit this structure for performance improvement. In control experiments we found that this adaptation process critically depended on performance feedback and could not be induced by verbal instructions. Our results suggest that structural learning is an important meta-learning component of Bayesian sensorimotor integration. PMID:26305797

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.

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

PubMed

Mathew, Sarah; Perreault, Charles

2015-07-07

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

JointZone: Users' Views of an Adaptive Online Learning Resource for Rheumatology

ERIC Educational Resources Information Center

Maier, Pat; Armstrong, Ray; Hall, Wendy; Ng, Muan Hong

2005-01-01

This paper describes an online learning resource for rheumatology that was designed for a wide constituency of users including primarily undergraduate medical students and health professionals. Although the online resources afford an informal learning environment, the site was pedagogically designed to comply with the general recommendations of…

An Ontology for Learning Services on the Shop Floor

ERIC Educational Resources Information Center

Ullrich, Carsten

2016-01-01

An ontology expresses a common understanding of a domain that serves as a basis of communication between people or systems, and enables knowledge sharing, reuse of domain knowledge, reasoning and thus problem solving. In Technology-Enhanced Learning, especially in Intelligent Tutoring Systems and Adaptive Learning Environments, ontologies serve as…

The Complexity of Language Learning

ERIC Educational Resources Information Center

Nelson, Charles

2011-01-01

This paper takes a complexity theory approach to looking at language learning, an approach that investigates how language learners adapt to and interact with people and their environment. Based on interviews with four graduate students, it shows how complexity theory can help us understand both the situatedness of language learning and also…

Complex Mobile Learning That Adapts to Learners' Cognitive Load

ERIC Educational Resources Information Center

Deegan, Robin

2015-01-01

Mobile learning is cognitively demanding and frequently the ubiquitous nature of mobile computing means that mobile devices are used in cognitively demanding environments. This paper examines the use of mobile devices from a Learning, Usability and Cognitive Load Theory perspective. It suggests scenarios where these fields interact and presents an…

Semantic-Aware Components and Services of ActiveMath

ERIC Educational Resources Information Center

Melis, Erica; Goguadze, Giorgi; Homik, Martin; Libbrecht, Paul; Ullrich, Carsten; Winterstein, Stefan

2006-01-01

ActiveMath is a complex web-based adaptive learning environment with a number of components and interactive learning tools. The basis for handling semantics of learning content is provided by its semantic (mathematics) content markup, which is additionally annotated with educational metadata. Several components, tools and external services can…

Community-Embedded Learning Experiences: Putting the Pedagogy of Service-Learning to Work in Online Courses

ERIC Educational Resources Information Center

Becnel, Kim; Moeller, Robin A.

2017-01-01

This paper considers the applicability and adaptability of service-learning pedagogy to online and distance education teaching environments. More specifically, it looks at the community-embedded learning model (CEL), which asks distance students to conduct service projects in their local communities, as manifested in a project undertaken by online…

Disability-Aware Adaptive and Personalised Learning for Students with Multiple Disabilities

ERIC Educational Resources Information Center

Nganji, Julius T.; Brayshaw, Mike

2017-01-01

Purpose: The purpose of this paper is to address how virtual learning environments (VLEs) can be designed to include the needs of learners with multiple disabilities. Specifically, it employs AI to show how specific learning materials from a huge repository of learning materials can be recommended to learners with various disabilities. This is…

Development of Advanced Verification and Validation Procedures and Tools for the Certification of Learning Systems in Aerospace Applications

NASA Technical Reports Server (NTRS)

Jacklin, Stephen; Schumann, Johann; Gupta, Pramod; Richard, Michael; Guenther, Kurt; Soares, Fola

2005-01-01

Adaptive control technologies that incorporate learning algorithms have been proposed to enable automatic flight control and vehicle recovery, autonomous flight, and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments. In order for adaptive control systems to be used in safety-critical aerospace applications, they must be proven to be highly safe and reliable. Rigorous methods for adaptive software verification and validation must be developed to ensure that control system software failures will not occur. Of central importance in this regard is the need to establish reliable methods that guarantee convergent learning, rapid convergence (learning) rate, and algorithm stability. This paper presents the major problems of adaptive control systems that use learning to improve performance. The paper then presents the major procedures and tools presently developed or currently being developed to enable the verification, validation, and ultimate certification of these adaptive control systems. These technologies include the application of automated program analysis methods, techniques to improve the learning process, analytical methods to verify stability, methods to automatically synthesize code, simulation and test methods, and tools to provide on-line software assurance.

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

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.

Learning with Interactive Computer Graphics in the Undergraduate Neuroscience Classroom

PubMed Central

Pani, John R.; Chariker, Julia H.; Naaz, Farah; Mattingly, William; Roberts, Joshua; Sephton, Sandra E.

2014-01-01

Instruction of neuroanatomy depends on graphical representation and extended self-study. As a consequence, computer-based learning environments that incorporate interactive graphics should facilitate instruction in this area. The present study evaluated such a system in the undergraduate neuroscience classroom. The system used the method of adaptive exploration, in which exploration in a high fidelity graphical environment is integrated with immediate testing and feedback in repeated cycles of learning. The results of this study were that students considered the graphical learning environment to be superior to typical classroom materials used for learning neuroanatomy. Students managed the frequency and duration of study, test, and feedback in an efficient and adaptive manner. For example, the number of tests taken before reaching a minimum test performance of 90% correct closely approximated the values seen in more regimented experimental studies. There was a wide range of student opinion regarding the choice between a simpler and a more graphically compelling program for learning sectional anatomy. Course outcomes were predicted by individual differences in the use of the software that reflected general work habits of the students, such as the amount of time committed to testing. The results of this introduction into the classroom are highly encouraging for development of computer-based instruction in biomedical disciplines. PMID:24449123

The Psychology of Isolated and Confined Environments: Understanding Human Behavior in Antarctica.

ERIC Educational Resources Information Center

Palinkas, Lawrence A.

2003-01-01

Reviews lessons learned from research in Antarctica with relevance to understanding human behavior in other isolated and confined environments. Outlines four distinct characteristics of psychosocial adaptation to such environments and discusses some of the benefits for individuals seeking challenging experiences. (Contains references.) (SLD)

Personalized e-Learning Environments: Considering Students' Contexts

NASA Astrophysics Data System (ADS)

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

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

Design of a biochemical circuit motif for learning linear functions

PubMed Central

Lakin, Matthew R.; Minnich, Amanda; Lane, Terran; Stefanovic, Darko

2014-01-01

Learning and adaptive behaviour are fundamental biological processes. A key goal in the field of bioengineering is to develop biochemical circuit architectures with the ability to adapt to dynamic chemical environments. Here, we present a novel design for a biomolecular circuit capable of supervised learning of linear functions, using a model based on chemical reactions catalysed by DNAzymes. To achieve this, we propose a novel mechanism of maintaining and modifying internal state in biochemical systems, thereby advancing the state of the art in biomolecular circuit architecture. We use simulations to demonstrate that the circuit is capable of learning behaviour and assess its asymptotic learning performance, scalability and robustness to noise. Such circuits show great potential for building autonomous in vivo nanomedical devices. While such a biochemical system can tell us a great deal about the fundamentals of learning in living systems and may have broad applications in biomedicine (e.g. autonomous and adaptive drugs), it also offers some intriguing challenges and surprising behaviours from a machine learning perspective. PMID:25401175

Design of a biochemical circuit motif for learning linear functions.

PubMed

Lakin, Matthew R; Minnich, Amanda; Lane, Terran; Stefanovic, Darko

2014-12-06

Learning and adaptive behaviour are fundamental biological processes. A key goal in the field of bioengineering is to develop biochemical circuit architectures with the ability to adapt to dynamic chemical environments. Here, we present a novel design for a biomolecular circuit capable of supervised learning of linear functions, using a model based on chemical reactions catalysed by DNAzymes. To achieve this, we propose a novel mechanism of maintaining and modifying internal state in biochemical systems, thereby advancing the state of the art in biomolecular circuit architecture. We use simulations to demonstrate that the circuit is capable of learning behaviour and assess its asymptotic learning performance, scalability and robustness to noise. Such circuits show great potential for building autonomous in vivo nanomedical devices. While such a biochemical system can tell us a great deal about the fundamentals of learning in living systems and may have broad applications in biomedicine (e.g. autonomous and adaptive drugs), it also offers some intriguing challenges and surprising behaviours from a machine learning perspective.

Development of a Countermeasure to Enhance Postflight Locomotor Adaptability

NASA Technical Reports Server (NTRS)

Bloomberg, Jacob J.

2006-01-01

Astronauts returning from space flight experience locomotor dysfunction following their return to Earth. Our laboratory is currently developing a gait adaptability training program that is designed to facilitate recovery of locomotor function following a return to a gravitational environment. The training program exploits the ability of the sensorimotor system to generalize from exposure to multiple adaptive challenges during training so that the gait control system essentially learns to learn and therefore can reorganize more rapidly when faced with a novel adaptive challenge. We have previously confirmed that subjects participating in adaptive generalization training programs using a variety of visuomotor distortions can enhance their ability to adapt to a novel sensorimotor environment. Importantly, this increased adaptability was retained even one month after completion of the training period. Adaptive generalization has been observed in a variety of other tasks requiring sensorimotor transformations including manual control tasks and reaching (Bock et al., 2001, Seidler, 2003) and obstacle avoidance during walking (Lam and Dietz, 2004). Taken together, the evidence suggests that a training regimen exposing crewmembers to variation in locomotor conditions, with repeated transitions among states, may enhance their ability to learn how to reassemble appropriate locomotor patterns upon return from microgravity. We believe exposure to this type of training will extend crewmembers locomotor behavioral repertoires, facilitating the return of functional mobility after long duration space flight. Our proposed training protocol will compel subjects to develop new behavioral solutions under varying sensorimotor demands. Over time subjects will learn to create appropriate locomotor solution more rapidly enabling acquisition of mobility sooner after long-duration space flight. Our laboratory is currently developing adaptive generalization training procedures and the associated flight hardware to implement such a training program during regular inflight treadmill operations. A visual display system will provide variation in visual flow patterns during treadmill exercise. Crewmembers will be exposed to a virtual scene that can translate and rotate in six-degrees-of freedom during their regular treadmill exercise period. Associated ground based studies are focused on determining optimal combinations of sensory manipulations (visual flow, body loading and support surface variation) and training schedules that will produce the greatest potential for adaptive flexibility in gait function during exposure to challenging and novel environments. An overview of our progress in these areas will be discussed during the presentation.

The interference effects of non-rotated versus counter-rotated trials in visuomotor adaptation.

PubMed

Hinder, Mark R; Walk, Laura; Woolley, Daniel G; Riek, Stephan; Carson, Richard G

2007-07-01

An isometric torque-production task was used to investigate interference and retention in adaptation to multiple visuomotor environments. Subjects produced isometric flexion-extension and pronation-supination elbow torques to move a cursor to acquire targets as quickly as possible. Adaptation to a 30 degrees counter-clockwise (CCW) rotation (task A), was followed by a period of rest (control), trials with no rotation (task B0), or trials with a 60 degrees clockwise (CW) rotation (task B60). For all groups, retention of task A was assessed 5 h later. With initial training, all groups reduced the angular deviation of cursor paths early in the movements, indicating feedforward adaptation. For the control group, performance at commencement of the retest was significantly better than that at the beginning of the initial learning. For the B0 group, performance in the retest of task A was not dissimilar to that at the start of the initial learning, while for the B60 group retest performance in task A was markedly worse than initially observed. Our results indicate that close juxtaposition of two visuomotor environments precludes improved retest performance in the initial environment. Data for the B60 group, specifically larger angular errors upon retest compared with initial exposures, are consistent with the presence of anterograde interference. Furthermore, full interference occurred even when the visuomotor environment encountered in the second task was not rotated (B0). This latter novel result differs from those obtained for force field learning, where interference does not occur when task B does not impose perturbing forces, i.e., when B consists of a null field (Brashers-Krug et al., Nature 382:252-255, 1996). The results are consistent with recent proposals suggesting different interference mechanisms for visuomotor (kinematic) compared to force field (dynamic) adaptations, and have implications for the use of washout trials when studying interference between multiple visuomotor environments.

All about Animal Adaptations. Animal Life for Children. [Videotape].

ERIC Educational Resources Information Center

2000

Animals change to better adapt to their environment. Over long periods of time, nature helps the animals adapt by changing their body shape and color as well as adjusting their methods of getting and eating food, defending themselves, and caring for their young. In this videotape, students learn what changes different animals go through in order…

Web-Based Learning Support System

NASA Astrophysics Data System (ADS)

Fan, Lisa

Web-based learning support system offers many benefits over traditional learning environments and has become very popular. The Web is a powerful environment for distributing information and delivering knowledge to an increasingly wide and diverse audience. Typical Web-based learning environments, such as Web-CT, Blackboard, include course content delivery tools, quiz modules, grade reporting systems, assignment submission components, etc. They are powerful integrated learning management systems (LMS) that support a number of activities performed by teachers and students during the learning process [1]. However, students who study a course on the Internet tend to be more heterogeneously distributed than those found in a traditional classroom situation. In order to achieve optimal efficiency in a learning process, an individual learner needs his or her own personalized assistance. For a web-based open and dynamic learning environment, personalized support for learners becomes more important. This chapter demonstrates how to realize personalized learning support in dynamic and heterogeneous learning environments by utilizing Adaptive Web technologies. It focuses on course personalization in terms of contents and teaching materials that is according to each student's needs and capabilities. An example of using Rough Set to analyze student personal information to assist students with effective learning and predict student performance is presented.

A meta-learning system based on genetic algorithms

NASA Astrophysics Data System (ADS)

Pellerin, Eric; Pigeon, Luc; Delisle, Sylvain

2004-04-01

The design of an efficient machine learning process through self-adaptation is a great challenge. The goal of meta-learning is to build a self-adaptive learning system that is constantly adapting to its specific (and dynamic) environment. To that end, the meta-learning mechanism must improve its bias dynamically by updating the current learning strategy in accordance with its available experiences or meta-knowledge. We suggest using genetic algorithms as the basis of an adaptive system. In this work, we propose a meta-learning system based on a combination of the a priori and a posteriori concepts. A priori refers to input information and knowledge available at the beginning in order to built and evolve one or more sets of parameters by exploiting the context of the system"s information. The self-learning component is based on genetic algorithms and neural Darwinism. A posteriori refers to the implicit knowledge discovered by estimation of the future states of parameters and is also applied to the finding of optimal parameters values. The in-progress research presented here suggests a framework for the discovery of knowledge that can support human experts in their intelligence information assessment tasks. The conclusion presents avenues for further research in genetic algorithms and their capability to learn to learn.

Improvisation as an adaptive strategy for occupational therapy practice.

PubMed

Krusen, Nancy E

2012-01-01

ABSTRACT As health care environments become increasingly complex, practitioners must develop new adaptive skills to master practice. The idea of using theatrical improvisation (improv) in health care is relatively new. Occupational therapy students were taught a module of improvisational techniques as part of an academic seminar, learning improvisation rules, and enacting solutions to typical daily professional challenges. The purpose of this article is to recommend improvisational techniques as an adaptive skill to effectively blend art and science for occupational therapy practice in fast-paced and unpredictable health care environments.

Development of a Countermeasure to Mitigate Postflight Locomotor Dysfunction

NASA Technical Reports Server (NTRS)

Bloomberg, J. J.; Mulavara, A. P.; Peters, B. T.; Cohen, H. S.; Richards, J. T.; Miller, C. A.; Brady, R.; Warren, L. E.; Ruttley, T. M.

2006-01-01

Astronauts returning from space flight experience locomotor dysfunction following their return to Earth. Our laboratory is currently developing a gait adaptability training program that is designed to facilitate recovery of locomotor function following a return to a gravitational environment. The training program exploits the ability of the sensorimotor system to generalize from exposure to multiple adaptive challenges during training so that the gait control system essentially learns to learn and therefore can reorganize more rapidly when faced with a novel adaptive challenge. Evidence for the potential efficacy of an adaptive generalization gait training program can be obtained from numerous studies in the motor learning literature which have demonstrated that systematically varying the conditions of training enhances the ability of the performer to learn and retain a novel motor task. These variable practice training approaches have been used in applied contexts to improve motor skills required in a number of different sports. The central nervous system (CNS) can produce voluntary movement in an almost infinite number of ways. For example, locomotion can be achieved with many different combinations of joint angles, muscle activation patterns and forces. The CNS can exploit these degrees of freedom to enhance motor response adaptability during periods of adaptive flux like that encountered during a change in gravitational environment. Ultimately, the functional goal of an adaptive generalization countermeasure is not necessarily to immediately return movement patterns back to normal. Rather the training regimen should facilitate the reorganization of available sensory and motor subsystems to achieve safe and effective locomotion as soon as possible after long duration space flight. Indeed, this approach has been proposed as a basic feature underlying effective neurological rehabilitation. We have previously confirmed that subjects participating in an adaptive generalization training program using a variety of visuomotor distortions and throwing as the dependent measure can learn to enhance their ability to adapt to a novel sensorimotor environment (Roller et al., 2001). Importantly, this increased adaptability was retained even one month after completion of the training period. Adaptive generalization has been observed in a variety of other tasks requiring sensorimotor transformations including manual control tasks and reaching (Bock et al., 2001, Seidler, 2003) and obstacle avoidance during walking (Lam and Dietz, 2004). Taken together, the evidence suggests that a training regimen exposing crewmembers to variation in locomotor conditions, with repeated transitions among states, may enhance their ability to learn how to reassemble appropriate locomotor patterns upon return from microgravity. We believe exposure to this type of training will extend crewmembers locomotor behavioral repertoires, facilitating the return of functional mobility after long duration space flight. In other words, our proposed training protocol will compel subjects to develop new behavioral solutions under varying sensorimotor demands. Over time subjects will learn to create appropriate locomotor solution more rapidly enabling acquisition of mobility sooner after long-duration space flight. A gait adaptability training program can be superimposed on nominal treadmill exercise activities thus ensuring that no additional crew time is required to perform this type of training regimen and that it can be implemented with current in-flight exercise systems available on the International Space Station.

The remapping of space in motor learning and human-machine interfaces

PubMed Central

Mussa-Ivaldi, F.A.; Danziger, Z.

2009-01-01

Studies of motor adaptation to patterns of deterministic forces have revealed the ability of the motor control system to form and use predictive representations of the environment. One of the most fundamental elements of our environment is space itself. This article focuses on the notion of Euclidean space as it applies to common sensory motor experiences. Starting from the assumption that we interact with the world through a system of neural signals, we observe that these signals are not inherently endowed with metric properties of the ordinary Euclidean space. The ability of the nervous system to represent these properties depends on adaptive mechanisms that reconstruct the Euclidean metric from signals that are not Euclidean. Gaining access to these mechanisms will reveal the process by which the nervous system handles novel sophisticated coordinate transformation tasks, thus highlighting possible avenues to create functional human-machine interfaces that can make that task much easier. A set of experiments is presented that demonstrate the ability of the sensory-motor system to reorganize coordination in novel geometrical environments. In these environments multiple degrees of freedom of body motions are used to control the coordinates of a point in a two-dimensional Euclidean space. We discuss how practice leads to the acquisition of the metric properties of the controlled space. Methods of machine learning based on the reduction of reaching errors are tested as a means to facilitate learning by adaptively changing he map from body motions to controlled device. We discuss the relevance of the results to the development of adaptive human machine interfaces and optimal control. PMID:19665553

Technology Integration Experiences of Teachers

ERIC Educational Resources Information Center

Çoklar, Ahmet Naci; Yurdakul, Isil Kabakçi

2017-01-01

Teachers are important providers of educational sustainability. Teachers' ability to adapt themselves to rapidly developing technologies applicable to learning environments is connected with technology integration. The purpose of this study is to investigate teachers' technology integration experiences in the course of learning and teaching…

Learning from Software Localization.

ERIC Educational Resources Information Center

Guo, She-Sen

2003-01-01

Localization is the process of adapting a product to meet the language, cultural and other requirements of a specific target environment or market. This article describes ways in which software localization impacts upon curriculum, and discusses what students will learn from software localization. (AEF)

An Enhanced Personal Learning Environment Using Social Semantic Web Technologies

ERIC Educational Resources Information Center

Halimi, Khaled; Seridi-Bouchelaghem, Hassina; Faron-Zucker, Catherine

2014-01-01

Compared with learning in classrooms, classical e-learning systems are less adaptive and once a system that supports a particular strategy has been designed and implemented, it is less likely to change according to student's interactions and preferences. Remote educational systems should be developed to ensure as much as necessary the…

Examining the Efficacy of Mobile Learning in the Military Education Institution

ERIC Educational Resources Information Center

Perot, Eddie, Sr.

2017-01-01

This three-article dissertation investigates the integration of mobile learning devices in the military education institution curriculum. The basis of this investigation advances the position that mobile learning devices are advantageous to promoting a learner centric environment that is responsive and adaptive to the needs of the learner. Mobile…

PUPIL-TEACHER ADJUSTEMENT AND MUTUAL ADAPTATION IN CREATING CLASSROOM LEARNING ENVIRONMENTS.

ERIC Educational Resources Information Center

FOX, ROBERT S.; AND OTHERS

AN ANALYSIS OF THE DYNAMICS OF THE LEARNING SITUATIONS IN A VARIETY OF PUBLIC SCHOOL CLASSROOMS WAS UNDERTAKEN. THE PROJECT MADE A COMPARATIVE ANALYSIS OF THE PATTERNS OF COOPERATION OR ALIENATION AMONG PARENTS, TEACHERS, PEERS, AND INDIVIDUAL PUPILS. THE PATTERNS CREATE LEARNING CULTURES OF DIFFERENT PRODUCTIVITY IN VARIOUS CLASSROOMS. THE DATA…

Expanding Omani Learners' Horizons through Project-Based Learning: A Case Study

ERIC Educational Resources Information Center

Dauletova, Victoria

2014-01-01

As a relatively innovative teaching/learning approach in the Arabian Gulf region, in general, and in Oman, in particular, project-based learning requires progressive amendments and adaptations to the national culture of the learner. This article offers analysis of the current state of the approach in the local educational environment. Furthermore,…

Creating Environments Conducive for Lifelong Learning

ERIC Educational Resources Information Center

Derrick, M. Gail

2003-01-01

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

Context-Aware Mobile Role Playing Game for Learning--A Case of Canada and Taiwan

ERIC Educational Resources Information Center

Lu, Chris; Chang, Maiga; Kinshuk; Huang, Echo; Chen, Ching-Wen

2014-01-01

The research presented in this paper is part of a 5-year renewable national research program in Canada, namely the NSERC/iCORE/Xerox/Markin research chair program that aims to explore possibilities of adaptive mobile learning and to provide learners with a learning environment which facilitates personalized learning at any time and any place. One…

The evolution of continuous learning of the structure of the environment

PubMed Central

Kolodny, Oren; Edelman, Shimon; Lotem, Arnon

2014-01-01

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

Bacterial computing: a form of natural computing and its applications.

PubMed

Lahoz-Beltra, Rafael; Navarro, Jorge; Marijuán, Pedro C

2014-01-01

The capability to establish adaptive relationships with the environment is an essential characteristic of living cells. Both bacterial computing and bacterial intelligence are two general traits manifested along adaptive behaviors that respond to surrounding environmental conditions. These two traits have generated a variety of theoretical and applied approaches. Since the different systems of bacterial signaling and the different ways of genetic change are better known and more carefully explored, the whole adaptive possibilities of bacteria may be studied under new angles. For instance, there appear instances of molecular "learning" along the mechanisms of evolution. More in concrete, and looking specifically at the time dimension, the bacterial mechanisms of learning and evolution appear as two different and related mechanisms for adaptation to the environment; in somatic time the former and in evolutionary time the latter. In the present chapter it will be reviewed the possible application of both kinds of mechanisms to prokaryotic molecular computing schemes as well as to the solution of real world problems.

Adaptation, Learning, and the Art of War: A Cybernetic Perspective

DTIC Science & Technology

2014-05-14

William Ross Ashby and contemporary cybernetic thought, the study modeled the adaptive systems as control loops and the processes of adaptive systems...as a Markov process . Using this model , the study concluded that systems would return to the same relative equilibrium point, expressed in terms of...uncertain and ever-changing environment. Drawing from the works of William Ross Ashby and contemporary cybernetic thought, the study modeled the adaptive

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

DOE PAGES

Akcakaya, Murat; Nehorai, Arye; Sen, Satyabrata

2016-04-12

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

The evolution of cultural adaptations: Fijian food taboos protect against dangerous marine toxins

PubMed Central

Henrich, Joseph; Henrich, Natalie

2010-01-01

The application of evolutionary theory to understanding the origins of our species' capacities for social learning has generated key insights into cultural evolution. By focusing on how our psychology has evolved to adaptively extract beliefs and practices by observing others, theorists have hypothesized how social learning can, over generations, give rise to culturally evolved adaptations. While much field research documents the subtle ways in which culturally transmitted beliefs and practices adapt people to their local environments, and much experimental work reveals the predicted patterns of social learning, little research connects real-world adaptive cultural traits to the patterns of transmission predicted by these theories. Addressing this gap, we show how food taboos for pregnant and lactating women in Fiji selectively target the most toxic marine species, effectively reducing a woman's chances of fish poisoning by 30 per cent during pregnancy and 60 per cent during breastfeeding. We further analyse how these taboos are transmitted, showing support for cultural evolutionary models that combine familial transmission with selective learning from locally prestigious individuals. In addition, we explore how particular aspects of human cognitive processes increase the frequency of some non-adaptive taboos. This case demonstrates how evolutionary theory can be deployed to explain both adaptive and non-adaptive behavioural patterns. PMID:20667878

An Australian Approach to School Design

ERIC Educational Resources Information Center

Robinson, Leigh; Robinson, Taylor

2009-01-01

Contemporary education design strongly emphasises stimulating, adaptable learning environments, with spaces able to support various styles of teaching and learning. Delivering successful school buildings requires a close collaborative relationship between the architect and all key stakeholders from initial briefing through to project handover. The…

Devices and Desires: Integrative Strategy Instruction from a Motivational Perspective.

ERIC Educational Resources Information Center

Vauras, Marja; And Others

1993-01-01

This critique of Edwin Ellis's Integrative Strategy Instruction model comments that analyses are needed concerning the mutual social adaptations of differently disposed (cognitively, motivationally, and emotionally) students with learning disabilities and teachers within the social frames of learning environments. (JDD)

Adaptive Process Control with Fuzzy Logic and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Karr, C. L.

1993-01-01

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision-making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

Genetic algorithms in adaptive fuzzy control

NASA Technical Reports Server (NTRS)

Karr, C. Lucas; Harper, Tony R.

1992-01-01

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.

Lessons from a Space Analog on Adaptation for Long-Duration Exploration Missions.

PubMed

Anglin, Katlin M; Kring, Jason P

2016-04-01

Exploration missions to asteroids and Mars will bring new challenges associated with communication delays and more autonomy for crews. Mission safety and success will rely on how well the entire system, from technology to the human elements, is adaptable and resilient to disruptive, novel, or potentially catastrophic events. The recent NASA Extreme Environment Missions Operations (NEEMO) 20 mission highlighted this need and produced valuable "lessons learned" that will inform future research on team adaptation and resilience. A team of NASA, industry, and academic members used an iterative process to design a tripod shaped structure, called the CORAL Tower, for two astronauts to assemble underwater with minimal tools. The team also developed assembly procedures, administered training to the crew, and provided support during the mission. During the design, training, and assembly of the Tower, the team learned first-hand how adaptation in extreme environments depends on incremental testing, thorough procedures and contingency plans that predict possible failure scenarios, and effective team adaptation and resiliency for the crew and support personnel. Findings from NEEMO 20 provide direction on the design and testing process for future space systems and crews to maximize adaptation. This experience also underscored the need for more research on team adaptation, particularly how input and process factors affect adaption outcomes, the team adaptation iterative process, and new ways to measure the adaptation process.

Adaptive thinking & leadership simulation game training for special forces officers.

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

Raybourn, Elaine Marie; Mendini, Kip; Heneghan, Jerry

Complex problem solving approaches and novel strategies employed by the military at the squad, team, and commander level are often best learned experimentally. Since live action exercises can be costly, advances in simulation game training technology offer exciting ways to enhance current training. Computer games provide an environment for active, critical learning. Games open up possibilities for simultaneous learning on multiple levels; players may learn from contextual information embedded in the dynamics of the game, the organic process generated by the game, and through the risks, benefits, costs, outcomes, and rewards of alternative strategies that result from decision making. Inmore » the present paper we discuss a multiplayer computer game simulation created for the Adaptive Thinking & Leadership (ATL) Program to train Special Forces Team Leaders. The ATL training simulation consists of a scripted single-player and an immersive multiplayer environment for classroom use which leverages immersive computer game technology. We define adaptive thinking as consisting of competencies such as negotiation and consensus building skills, the ability to communicate effectively, analyze ambiguous situations, be self-aware, think innovatively, and critically use effective problem solving skills. Each of these competencies is an essential element of leader development training for the U.S. Army Special Forces. The ATL simulation is used to augment experiential learning in the curriculum for the U.S. Army JFK Special Warfare Center & School (SWCS) course in Adaptive Thinking & Leadership. The school is incorporating the ATL simulation game into two additional training pipelines (PSYOPS and Civil Affairs Qualification Courses) that are also concerned with developing cultural awareness, interpersonal communication adaptability, and rapport-building skills. In the present paper, we discuss the design, development, and deployment of the training simulation, and emphasize how the multiplayer simulation game is successfully used in the Special Forces Officer training program.« less

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.

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.

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

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

Akcakaya, Murat; Nehorai, Arye; Sen, Satyabrata

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

External and internal factors influencing self-directed online learning of physiotherapy undergraduate students in Sweden: a qualitative study.

PubMed

Hammarlund, Catharina Sjödahl; Nilsson, Maria H; Gummesson, Christina

2015-01-01

Online courses have become common in health sciences education. This learning environment can be designed using different approaches to support student learning. To further develop online environment, it is important to understand how students perceive working and learning online. The aim of this study is to identify aspects influencing students' learning processes and their adaptation to self-directed learning online. Thirty-four physiotherapy students with a mean age of 25 years (range, 21 to 34 years) participated. Qualitative content analysis and triangulation was used when investigating the students' self-reflections, written during a five week self-directed, problem-oriented online course. Two categories emerged: 'the influence of the structured framework' and 'communication and interaction with teachers and peers.' The learning processes were influenced by external factors, e.g., a clear structure including a transparent alignment of assignments and assessment. Important challenges to over-come were primarily internal factors, e.g., low self-efficacy, difficulties to plan the work effectively and adapting to a new environment. The analyses reflected important perspectives targeting areas which enable further course development. The influences of external and internal factors on learning strategies and self-efficacy are important aspects to consider when designing online courses. Factors such as pedagogical design, clarity of purpose, goals, and guidelines were important as well as continuous opportunities for communication and collaboration. Further studies are needed to understand and scaffold the motivational factors among students with low self-efficacy.

Learning Beyond the Buzzwords: Developing the Adaptable, Competent CSS Soldier

DTIC Science & Technology

2005-05-26

interaction with the surrounding environment.27 Russian theorist Lev Vygotsky argued for a variant of Piaget’s approach. Vygotsky believed that social...ABSTRACT (Maximum 200 Words)TT This monograph examines junior CSS soldier training programs against current learning theory in order to determine how the...learner centered instructional techniques, and provide appropriate time to achieve learning goals. 14. SUBJECT TERMS Soldier development, learning theory

Students and Teachers' Perceptions into the Viability of Mobile Technology Implementation to Support Language Learning for First Year Business Students in a Middle Eastern University

ERIC Educational Resources Information Center

Tayan, Bilal M.

2017-01-01

Advancements in technology have enabled us to learn, adapt and exploit our skills and knowledge in new ways. Appreciating the potential of technology may yet give growth and enrich the process of language education, particularly through a student-centred mobile learning environment. Consequently, a constructivist approach to learning can create…

Utilization of virtual learning environments in the allied health professions.

PubMed

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

2013-01-01

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

Introducing New Learning Tools into a Standard Classroom: A Multi-Tool Approach to Integrating Fuel-Cell Concepts into Introductory College Chemistry

ERIC Educational Resources Information Center

D'Amato, Matthew J.; Lux, Kenneth W.; Walz, Kenneth A.; Kerby, Holly Walter; Anderegg, Barbara

2007-01-01

A multi-tool approach incorporating traditional lectures, multimedia learning objects, and a laboratory activity were introduced as the concepts surrounding hydrogen fuel-cell technology in college chemistry courses. The new tools are adaptable, facilitating use in different educational environments and address variety of learning styles to…

Integration and Implementation of Web Simulators in Experimental e-Learning: An Application for Capacity Auctions

ERIC Educational Resources Information Center

Otamendi, Francisco Javier; Doncel, Luis Miguel

2013-01-01

Experimental teaching in general, and simulation in particular, have primarily been used in lecture rooms but in the future must also be adapted to e-learning. The integration of web simulators into virtual learning environments, coupled with specific supporting video documentation and the use of videoconference tools, results in robust…

Predictive Coding Accelerates Word Recognition and Learning in the Early Stages of Language Development

ERIC Educational Resources Information Center

Ylinen, Sari; Bosseler, Alexis; Junttila, Katja; Huotilainen, Minna

2017-01-01

The ability to predict future events in the environment and learn from them is a fundamental component of adaptive behavior across species. Here we propose that inferring predictions facilitates speech processing and word learning in the early stages of language development. Twelve- and 24-month olds' electrophysiological brain responses to heard…

Pupil-Teacher Adjustment and Mutual Adaptation in Creating Classroom Learning Environments. Final Report.

ERIC Educational Resources Information Center

Fox, Robert S.; And Others

This investigation is directed toward an analysis of the dynamics of the learning situations in a variety of public school elementary and secondary classrooms. The focus of the project is to make a comparative analysis of the patterns of cooperation or alienation among parents, teachers, peers and individual pupils which create learning cultures…

Cognitive Tutoring based on Intelligent Decision Support in the PENTHA Instructional Design Model

NASA Astrophysics Data System (ADS)

dall'Acqua, Luisa

2010-06-01

The research finality of this paper is how to support Authors to develop rule driven—subject oriented, adaptable course content, meta-rules—representing the disciplinary epistemology, model of teaching, Learning Path structure, and assessment parameters—for intelligent Tutoring actions in a personalized, adaptive e-Learning environment. The focus is to instruct the student to be a decision manager for himself, able to recognize the elements of a problem, select the necessary information with the perspective of factual choices. In particular, our research intends to provide some fundamental guidelines for the definition of didactical rules and logical relations, that Authors should provide to a cognitive Tutoring system through the use of an Instructional Design method (PENTHA Model) which proposes an educational environment, able to: increase productivity and operability, create conditions for a cooperative dialogue, developing participatory research activities of knowledge, observations and discoveries, customizing the learning design in a complex and holistic vision of the learning / teaching processes.

Reinforcement learning or active inference?

PubMed

Friston, Karl J; Daunizeau, Jean; Kiebel, Stefan J

2009-07-29

This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain.

A Large-Scale Multi-Hop Localization Algorithm Based on Regularized Extreme Learning for Wireless Networks.

PubMed

Zheng, Wei; Yan, Xiaoyong; Zhao, Wei; Qian, Chengshan

2017-12-20

A novel large-scale multi-hop localization algorithm based on regularized extreme learning is proposed in this paper. The large-scale multi-hop localization problem is formulated as a learning problem. Unlike other similar localization algorithms, the proposed algorithm overcomes the shortcoming of the traditional algorithms which are only applicable to an isotropic network, therefore has a strong adaptability to the complex deployment environment. The proposed algorithm is composed of three stages: data acquisition, modeling and location estimation. In data acquisition stage, the training information between nodes of the given network is collected. In modeling stage, the model among the hop-counts and the physical distances between nodes is constructed using regularized extreme learning. In location estimation stage, each node finds its specific location in a distributed manner. Theoretical analysis and several experiments show that the proposed algorithm can adapt to the different topological environments with low computational cost. Furthermore, high accuracy can be achieved by this method without setting complex parameters.

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

PubMed

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

2008-04-01

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

A Comparison of Actual and Preferred Classroom Environments as Perceived by Middle School Students

ERIC Educational Resources Information Center

Lai, Hsiang-Ru; Chou, Wei-Lun; Miao, Nae-Fang; Wu, Yu-Ping; Lee, Pi-Hsia; Jwo, Jiunn-Chern

2015-01-01

Background: A good classroom environment can promote students' learning motivation and affect their academic efficacy and adaptation. This study compares the perceptions of Taiwanese middle school students regarding actual and preferred classroom environments and explores the association with sex and grade level. Methods: Data were collected using…

Adaptive control of nonlinear system using online error minimum neural networks.

PubMed

Jia, Chao; Li, Xiaoli; Wang, Kang; Ding, Dawei

2016-11-01

In this paper, a new learning algorithm named OEM-ELM (Online Error Minimized-ELM) is proposed based on ELM (Extreme Learning Machine) neural network algorithm and the spreading of its main structure. The core idea of this OEM-ELM algorithm is: online learning, evaluation of network performance, and increasing of the number of hidden nodes. It combines the advantages of OS-ELM and EM-ELM, which can improve the capability of identification and avoid the redundancy of networks. The adaptive control based on the proposed algorithm OEM-ELM is set up which has stronger adaptive capability to the change of environment. The adaptive control of chemical process Continuous Stirred Tank Reactor (CSTR) is also given for application. The simulation results show that the proposed algorithm with respect to the traditional ELM algorithm can avoid network redundancy and improve the control performance greatly. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Investigating a self-scoring interview simulation for learning and assessment in the medical consultation.

PubMed

Bruen, Catherine; Kreiter, Clarence; Wade, Vincent; Pawlikowska, Teresa

2017-01-01

Experience with simulated patients supports undergraduate learning of medical consultation skills. Adaptive simulations are being introduced into this environment. The authors investigate whether it can underpin valid and reliable assessment by conducting a generalizability analysis using IT data analytics from the interaction of medical students (in psychiatry) with adaptive simulations to explore the feasibility of adaptive simulations for supporting automated learning and assessment. The generalizability (G) study was focused on two clinically relevant variables: clinical decision points and communication skills. While the G study on the communication skills score yielded low levels of true score variance, the results produced by the decision points, indicating clinical decision-making and confirming user knowledge of the process of the Calgary-Cambridge model of consultation, produced reliability levels similar to what might be expected with rater-based scoring. The findings indicate that adaptive simulations have potential as a teaching and assessment tool for medical consultations.

Robot Competence Development by Constructive Learning

NASA Astrophysics Data System (ADS)

Meng, Q.; Lee, M. H.; Hinde, C. J.

This paper presents a constructive learning approach for developing sensor-motor mapping in autonomous systems. The system’s adaptation to environment changes is discussed and three methods are proposed to deal with long term and short term changes. The proposed constructive learning allows autonomous systems to develop network topology and adjust network parameters. The approach is supported by findings from psychology and neuroscience especially during infants cognitive development at early stages. A growing radial basis function network is introduced as a computational substrate for sensory-motor mapping learning. Experiments are conducted on a robot eye/hand coordination testbed and results show the incremental development of sensory-motor mapping and its adaptation to changes such as in tool-use.

Robot Competence Development by Constructive Learning

NASA Astrophysics Data System (ADS)

Meng, Q.; Lee, M. H.; Hinde, C. J.

This paper presents a constructive learning approach for developing sensor-motor mapping in autonomous systems. The system's adaptation to environment changes is discussed and three methods are proposed to deal with long term and short term changes. The proposed constructive learning allows autonomous systems to develop network topology and adjust network parameters. The approach is supported by findings from psychology and neuroscience especially during infants cognitive development at early stages. A growing radial basis function network is introduced as a computational substrate for sensory-motor mapping learning. Experiments are conducted on a robot eye/hand coordination testbed and results show the incremental development of sensory-motor mapping and its adaptation to changes such as in tool-use.

Maximizing Investment

ERIC Educational Resources Information Center

Stewart, David

2010-01-01

Classrooms are adapting to new teaching approaches, propelling the educational environment to new heights of learning. In this changing environment, education institutions need to make sure that each dollar spent is beneficial to students. With funding decisions scrutinized by teachers, parents and taxpayers, purchases must meet an institution's…

45 CFR 1308.10 - Eligibility criteria: Mental retardation.

Code of Federal Regulations, 2011 CFR

2011-10-01

... and exhibits deficits in adaptive behavior which adversely affect learning. Adaptive behavior refers to age-appropriate coping with the demands of the environment through independent skills in self-care... appropriate to the age range must be used. If they do not exist for the language and cultural group to which...

Restructuring Introductory Physics by Adapting an Active Learning Studio Model

ERIC Educational Resources Information Center

Gatch, Delena

2010-01-01

Despite efforts to engage students in the traditional lecture environment, faculty in Georgia Southern University's Physics Department became dissatisfied with lecture as the primary means of instruction. During the fall semester of 2006, our department began adapting the studio model to suit the needs of introductory calculus-based physics…

Dynamic User Modeling within a Game-Based ITS

ERIC Educational Resources Information Center

Snow, Erica L.

2015-01-01

Intelligent tutoring systems are adaptive learning environments designed to support individualized instruction. The adaptation embedded within these systems is often guided by user models that represent one or more aspects of students' domain knowledge, actions, or performance. The proposed project focuses on the development and testing of user…

"Institutional Autism" in Children Adopted Internationally: Myth or Reality?

ERIC Educational Resources Information Center

Gindis, Boris

2008-01-01

"Institutional autism" is understood as a "learned behavior" produced by an institutional environment such as an orphanage. Some autistic-like behaviors may be adaptive in an institution, but become mal-adaptive after the child's adoption into a family. A differential diagnosis between autism as a medical condition and learned…

Adapting human-machine interfaces to user performance.

PubMed

Danziger, Zachary; Fishbach, Alon; Mussa-Ivaldi, Ferdinando A

2008-01-01

The goal of this study was to create and examine machine learning algorithms that adapt in a controlled and cadenced way to foster a harmonious learning environment between the user of a human-machine interface and the controlled device. In this experiment, subjects' high-dimensional finger motions remotely controlled the joint angles of a simulated planar 2-link arm, which was used to hit targets on a computer screen. Subjects were required to move the cursor at the endpoint of the simulated arm.

The reward of seeing: Different types of visual reward and their ability to modify oculomotor learning.

PubMed

Meermeier, Annegret; Gremmler, Svenja; Richert, Kerstin; Eckermann, Til; Lappe, Markus

2017-10-01

Saccadic adaptation is an oculomotor learning process that maintains the accuracy of eye movements to ensure effective perception of the environment. Although saccadic adaptation is commonly considered an automatic and low-level motor calibration in the cerebellum, we recently found that strength of adaptation is influenced by the visual content of the target: pictures of humans produced stronger adaptation than noise stimuli. This suggests that meaningful images may be considered rewarding or valuable in oculomotor learning. Here we report three experiments that establish the boundaries of this effect. In the first, we tested whether stimuli that were associated with high and low value following long term self-administered reinforcement learning produce stronger adaptation. Twenty-eight expert gamers participated in two sessions of adaptation to game-related high- and low-reward stimuli, but revealed no difference in saccadic adaptation (Bayes Factor01 = 5.49). In the second experiment, we tested whether cognitive (literate) meaning could induce stronger adaptation by comparing targets consisting of words and nonwords. The results of twenty subjects revealed no difference in adaptation strength (Bayes Factor01 = 3.21). The third experiment compared images of human figures to noise patterns for reactive saccades. Twenty-two subjects adapted significantly more toward images of human figures in comparison to noise (p < 0.001). We conclude that only primary (human vs. noise), but not secondary, reinforcement affects saccadic adaptation (words vs. nonwords, high- vs. low-value video game images).

Adaptive Training and Education Research at the US Army Research Laboratory: Bibliography (2013-2015)

DTIC Science & Technology

2016-03-01

US); 2014. ISBN 978-0-9893923-2-7. Goldberg, B. Chapter 9: Metacognitive supports to drive self -regulated learning experiences. In: Sottilare R...Presented at Metacognition and Self -Regulated Learning: Preparing Individuals through Learning How to Learn Workshop, 11th Annual International Conference... metacognition in the UrbanSim open-ended learning environment. In: Sottilare R, Sinatra A, editors. Proceedings of the 3rd Annual Approved for public release

Clinical quality needs complex adaptive systems and machine learning.

PubMed

Marsland, Stephen; Buchan, Iain

2004-01-01

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

Electrophysiological evidence of heterogeneity in visual statistical learning in young children with ASD.

PubMed

Jeste, Shafali S; Kirkham, Natasha; Senturk, Damla; Hasenstab, Kyle; Sugar, Catherine; Kupelian, Chloe; Baker, Elizabeth; Sanders, Andrew J; Shimizu, Christina; Norona, Amanda; Paparella, Tanya; Freeman, Stephanny F N; Johnson, Scott P

2015-01-01

Statistical learning is characterized by detection of regularities in one's environment without an awareness or intention to learn, and it may play a critical role in language and social behavior. Accordingly, in this study we investigated the electrophysiological correlates of visual statistical learning in young children with autism spectrum disorder (ASD) using an event-related potential shape learning paradigm, and we examined the relation between visual statistical learning and cognitive function. Compared to typically developing (TD) controls, the ASD group as a whole showed reduced evidence of learning as defined by N1 (early visual discrimination) and P300 (attention to novelty) components. Upon further analysis, in the ASD group there was a positive correlation between N1 amplitude difference and non-verbal IQ, and a positive correlation between P300 amplitude difference and adaptive social function. Children with ASD and a high non-verbal IQ and high adaptive social function demonstrated a distinctive pattern of learning. This is the first study to identify electrophysiological markers of visual statistical learning in children with ASD. Through this work we have demonstrated heterogeneity in statistical learning in ASD that maps onto non-verbal cognition and adaptive social function. © 2014 John Wiley & Sons Ltd.

Why Are There Different Languages? The Role of Adaptation in Linguistic Diversity.

PubMed

Lupyan, Gary; Dale, Rick

2016-09-01

Why are there different languages? A common explanation is that different languages arise from the gradual accumulation of random changes. Here, we argue that, beyond these random factors, linguistic differences, from sounds to grammars, may also reflect adaptations to different environments in which the languages are learned and used. The aspects of the environment that could shape language include the social, the physical, and the technological. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Randler, Christoph; Kummer, Barbara; Wilhelm, Christian

2012-06-01

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

The Construction of Knowledge through Social Interaction via Computer-Mediated Communication

ERIC Educational Resources Information Center

Saritas, Tuncay

2008-01-01

With the advance in information and communication technologies, computer-mediated communication--more specifically computer conferencing systems (CCS)--has captured the interest of educators as an ideal tool to create a learning environment featuring active, participative, and reflective learning. Educators are increasingly adapting the features…

Adaptive Standard Operating Procedures for Complex Disasters

DTIC Science & Technology

2017-03-01

Developments in Business Simulation and Experiential Learning 33 (2014). 23 Patrick Lagadec and Benjamin Topper, “How Crises Model the Modern World...field of crisis response . Therefore, this experiment supports the argument for implementing the adaptive design proposals. The adaptive SOP enhancement...Kalay. “An Event- Based Model to Simulate Human Behaviour in Built Environments.” Proceedings of the 30th eCAADe Conference 1 (2012). Snowden

Age differences in spatial working memory contributions to visuomotor adaptation and transfer.

PubMed

Langan, Jeanne; Seidler, Rachael D

2011-11-20

Throughout our life span we encounter challenges that require us to adapt to the demands of our changing environment; this entails learning new skills. Two primary components of motor skill learning are motor acquisition, the initial process of learning the skill, and motor transfer, when learning a new skill is benefitted by the overlap with a previously learned one. Older adults typically exhibit declines in motor acquisition compared to young adults, but remarkably, do not demonstrate deficits in motor transfer [10]. Our recent work demonstrates that a failure to engage spatial working memory (SWM) is associated with skill learning deficits in older adults [16]. Here, we investigate the role that SWM plays in both motor learning and transfer in young and older adults. Both age groups exhibited performance savings, or positive transfer, at transfer of learning for some performance variables. Measures of spatial working memory performance and reaction time correlated with both motor learning and transfer for young adults. Young adults recruited overlapping brain regions in prefrontal, premotor, parietal and occipital cortex for performance of a SWM and a visuomotor adaptation task, most notably during motor learning, replicating our prior findings [12]. Neural overlap between the SWM task and visuomotor adaptation for the older adults was limited to parietal cortex, with minimal changes from motor learning to transfer. Combined, these results suggest that age differences in engagement of cognitive strategies have a differential impact on motor learning and transfer. Copyright © 2011 Elsevier B.V. All rights reserved.

Age differences in spatial working memory contributions to visuomotor adaptation and transfer

PubMed Central

Langan, Jeanne; Seidler, Rachael. D.

2011-01-01

Throughout our life span we encounter challenges that require us to adapt to the demands of our changing environment; this entails learning new skills. Two primary components of motor skill learning are motor acquisition, the initial process of learning the skill, and motor transfer, when learning a new skill is benefitted by the overlap with a previously learned one. Older adults typically exhibit declines in motor acquisition compared to young adults, but remarkably, do not demonstrate deficits in motor transfer (Seidler, 2007). Our recent work demonstrates that a failure to engage spatial working memory (SWM) is associated with skill learning deficits in older adults (Anguera et al., 2011). Here, we investigate the role that SWM plays in both motor learning and transfer in young and older adults. Both age groups exhibited performance savings, or positive transfer, at transfer of learning for some performance variables. Measures of spatial working memory performance and reaction time correlated with both motor learning and transfer for young adults. Young adults recruited overlapping brain regions in prefrontal, premotor, parietal and occipital cortex for performance of a SWM and a visuomotor adaptation task, most notably during motor learning, replicating our prior findings (Anguera et al., 2010). Neural overlap between the SWM task and visuomotor adaptation for the older adults was limited to parietal cortex, with minimal changes from motor learning to transfer. Combined, these results suggest that age differences in engagement of cognitive strategies have a differential impact on motor learning and transfer. PMID:21784106

Reinforcement Learning in a Nonstationary Environment: The El Farol Problem

NASA Technical Reports Server (NTRS)

Bell, Ann Maria

1999-01-01

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

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

ERIC Educational Resources Information Center

Randler, Christoph; Kummer, Barbara; Wilhelm, Christian

2012-01-01

The aim of this study was to assess the outcome of a zoo visit in terms of learning and retention of knowledge concerning the adaptations and behavior of vertebrate species. Basis of the work was the concept of implementing zoo visits as an out-of-school setting for formal, curriculum based learning. Our theoretical framework centers on the…

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

PubMed

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

2012-07-01

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

Kanaka Maoli and Kamáāina Seascapes - Knowing Our Ocean Through Times of Change

NASA Astrophysics Data System (ADS)

Puniwai, N.

2017-12-01

In Hawaíi our oceans define us, we come from the ocean. Our oceans change, and we change with them, as we always have. By learning from people who are dependent on their environment, we learn how to observe and how to adapt. Through the lens of climate change, we interviewed respected ocean observers and surfers to learn about changes they have witnessed over time and the spatial scales and ocean conditions important to them. We looked at our ancient and historical texts to see what processes they recorded and the language they used to ascribe their observations, interactions and relationships to these places. Yet, we also integrate what our mechanical data sensors have recorded over recent time. By expanding our time scales of reference, knowledge sources, and collaborators, these methods teach us how our ancestors adapted and how climate change may impact our subsistence, recreation, and interactions with the environment. Managing complex seascapes requires the integration of multiple ways of knowing; strengthening our understanding of seascapes and their resiliency in this changing environment.

Adaptive COIN in Sri Lanka: What Contributed to the Demise of the LTTE?

DTIC Science & Technology

2012-06-01

influence on the conflict, and the Sri Lankan military’s adaptations in order to determine what contributed to the demise of the LTTE. This thesis...exploring the internal political dynamics, external influence on the conflict, and the Sri Lankan military’s adaptations in order to determine what...ability to learn, understand, and adapt to the changes in an operational environment that determines the success or failure of that army.28 Also, based

Learning, Development, and Training: The Influence of Synergies through Educational Evolution

ERIC Educational Resources Information Center

Thoms, Charlotte L. V.; Burton, Sharon L.

2016-01-01

Continuous learning is essential in academic and business environments for the 21st century learner as success, survival, and growth lean toward the educator answering the question, "Which educational design best facilitates educators in becoming learner-focused while producing adaptive completers in this ubiquitous learning…

The Impact of Cultural Dimensions on Online Learning

ERIC Educational Resources Information Center

Gómez-Rey, Pilar; Barbera, Elena; Fernández-Navarro, Francisco

2016-01-01

Due to the increasingly multicultural nature of e-learning environments, it is critical that instructors and instructional designers be aware of the importance of cultural factors in education and that they deliver culturally adaptive instruction. The main challenge of this paper is identifying the critical success factors for multicultural online…

Developing Adaptable Online Information Literacy Modules for a Learning Management System

ERIC Educational Resources Information Center

Mune, Christina; Goldman, Crystal; Higgins, Silke; Eby, Laurel; Chan, Emily K.; Crotty, Linda

2015-01-01

Higher education institutions increasingly utilize learning management systems (LMS) to teach courses and programs in hybrid or online-only formats. Providing information literacy instruction in these emerging digital environments poses challenges to librarians as the delivery of instruction requires familiarity with navigating an LMS and…

Optimization of Educational Environment for Students

ERIC Educational Resources Information Center

Tausan, Liana

2015-01-01

The paradigm of adapting school to the learning necessities and possibilities of the student, characteristic for future systems of education and for contemporary type of educational system network requires a diversity of learning situations and experiences, built in accordance with the possibilities and the needs of all student categories, in…

Whose Classroom Is It, Anyway? Improvisation as a Teaching Tool

ERIC Educational Resources Information Center

Berk, Ronald A.; Trieber, Rosalind H.

2009-01-01

Improvisational techniques derived from the experiences in improvisational theatre can be adapted for the college classroom to leverage the characteristics of the Net Generation, their multiple intelligences and learning styles, and the variety of collaborative learning activities already in place in a learner-centered environment. When…

Preservice Elementary Teachers' Adaptation of Science Curriculum Materials for Inquiry-Based Elementary Science

ERIC Educational Resources Information Center

Forbes, Cory T.

2011-01-01

Curriculum materials are important resources with which teachers make pedagogical decisions about the design of science learning environments. To become well-started beginning elementary teachers capable of engaging their students in inquiry-based science, preservice elementary teachers need to learn to use science curriculum materials…

Neural network applications in telecommunications

NASA Technical Reports Server (NTRS)

Alspector, Joshua

1994-01-01

Neural network capabilities include automatic and organized handling of complex information, quick adaptation to continuously changing environments, nonlinear modeling, and parallel implementation. This viewgraph presentation presents Bellcore work on applications, learning chip computational function, learning system block diagram, neural network equalization, broadband access control, calling-card fraud detection, software reliability prediction, and conclusions.

An Instructional Design Framework to Improve Student Learning in a First-Year Engineering Class

ERIC Educational Resources Information Center

Yelamarthi, Kumar; Drake, Eron; Prewett, Matthew

2016-01-01

Increasingly, numerous universities have identified benefits of flipped learning environments and have been encouraging instructors to adapt such methodologies in their respective classrooms, at a time when departments are facing significant budget constraints. This article proposes an instructional design framework utilized to strategically…

A Multi-Agent System Approach for Distance Learning Architecture

ERIC Educational Resources Information Center

Turgay, Safiye

2005-01-01

The goal of this study is to suggest the agent systems by intelligence and adaptability properties in distance learning environment. The suggested system has flexible, agile, intelligence and cooperation features. System components are teachers, students (learners), and resources. Inter component relations are modeled and reviewed by using the…

Evaluating the Design and Development of an Adaptive E-Tutorial Module: A Rasch-Measurement Approach

ERIC Educational Resources Information Center

Barefah, Allaa; McKay, Elspeth

2016-01-01

Courseware designers aim to innovate information communications technology (ICT) tools to increase learning experiences, spending many hours developing eLearning programmes. This effort gives rise to a dynamic technological pedagogical environment. However, it is difficult to recognise whether these online programmes reflect an instructional…

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

PubMed

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

2005-02-01

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

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

PubMed

Haraldseid, Cecilie; Friberg, Febe; Aase, Karina

2015-09-01

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

Visually guided gait modifications for stepping over an obstacle: a bio-inspired approach.

PubMed

Silva, Pedro; Matos, Vitor; Santos, Cristina P

2014-02-01

There is an increasing interest in conceiving robotic systems that are able to move and act in an unstructured and not predefined environment, for which autonomy and adaptability are crucial features. In nature, animals are autonomous biological systems, which often serve as bio-inspiration models, not only for their physical and mechanical properties, but also their control structures that enable adaptability and autonomy-for which learning is (at least) partially responsible. This work proposes a system which seeks to enable a quadruped robot to online learn to detect and to avoid stumbling on an obstacle in its path. The detection relies in a forward internal model that estimates the robot's perceptive information by exploring the locomotion repetitive nature. The system adapts the locomotion in order to place the robot optimally before attempting to step over the obstacle, avoiding any stumbling. Locomotion adaptation is achieved by changing control parameters of a central pattern generator (CPG)-based locomotion controller. The mechanism learns the necessary alterations to the stride length in order to adapt the locomotion by changing the required CPG parameter. Both learning tasks occur online and together define a sensorimotor map, which enables the robot to learn to step over the obstacle in its path. Simulation results show the feasibility of the proposed approach.

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

PubMed

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

2017-10-06

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

Managing clinical failure: a complex adaptive system perspective.

PubMed

Matthews, Jean I; Thomas, Paul T

2007-01-01

The purpose of this article is to explore the knowledge capture process at the clinical level. It aims to identify factors that enable or constrain learning. The study applies complex adaptive system thinking principles to reconcile learning within the NHS. The paper uses a qualitative exploratory study with an interpretative methodological stance set in a secondary care NHS Trust. Semi-structured interviews were conducted with healthcare practitioners and managers involved at both strategic and operational risk management processes. A network structure is revealed that exhibits the communication and interdependent working practices to support knowledge capture and adaptive learning. Collaborative multidisciplinary communities, whose values reflect local priorities and promote open dialogue and reflection, are featured. The main concern is that the characteristics of bureaucracy; rational-legal authority, a rule-based culture, hierarchical lines of communication and a centralised governance focus, are hindering clinical learning by generating barriers. Locally emergent collaborative processes are a key strategic resource to capture knowledge, potentially fostering an environment that could learn from failure and translate lessons between contexts. What must be addressed is that reporting mechanisms serve not only the governance objectives, but also supplement learning by highlighting the potential lessons in context. Managers must nurture a collaborative infrastructure using networks in a co-evolutionary manner. Their role is not to direct and design processes but to influence, support and create effective knowledge capture. Although the study only investigated one site the findings and conclusions may well translate to other trusts--such as the risk of not enabling a learning environment at clinical levels.

ODL Education Environments Based on Adaptivity and Adaptability.

ERIC Educational Resources Information Center

Cristea, Alexandra; De Bra, Paul

In the Information Society of the new millennium, the use of Information and Communication Technology (ICT) is becoming essential for the rapid dissemination of information. In this context, Open and Distance Learning (ODL) will have a growing role in effectively training people to have active roles in society. However, modern learners have a…

Multi-Level Adaptation in End-User Development of 3D Virtual Chemistry Experiments

ERIC Educational Resources Information Center

Liu, Chang; Zhong, Ying

2014-01-01

Multi-level adaptation in end-user development (EUD) is an effective way to enable non-technical end users such as educators to gradually introduce more functionality with increasing complexity to 3D virtual learning environments developed by themselves using EUD approaches. Parameterization, integration, and extension are three levels of…

Adaptive Game Based Learning Using Brain Measures for Attention--Some Explorations

ERIC Educational Resources Information Center

van der Pal, Jelke; Roos, Christopher; Sewnath, Ghanshaam; Rosheuvel, Christian

2016-01-01

The prospective use of low fidelity simulation and gaming in aviation training is high, and may facilitate individual, personal training needs in usually asynchronous training setting. Without direct feedback from, or intervention by, an instructor, adaptivity of the training environment is in high demand to ensure training sessions maintain an…

Brain representations for acquiring and recalling visual-motor adaptations

PubMed Central

Bédard, Patrick; Sanes, Jerome N.

2014-01-01

Humans readily learn and remember new motor skills, a process that likely underlies adaptation to changing environments. During adaptation, the brain develops new sensory-motor relationships, and if consolidation occurs, a memory of the adaptation can be retained for extended periods. Considerable evidence exists that multiple brain circuits participate in acquiring new sensory-motor memories, though the networks engaged in recalling these and whether the same brain circuits participate in their formation and recall has less clarity. To address these issues, we assessed brain activation with functional MRI while young healthy adults learned and recalled new sensory-motor skills by adapting to world-view rotations of visual feedback that guided hand movements. We found cerebellar activation related to adaptation rate, likely reflecting changes related to overall adjustments to the visual rotation. A set of parietal and frontal regions, including inferior and superior parietal lobules, premotor area, supplementary motor area and primary somatosensory cortex, exhibited non-linear learning-related activation that peaked in the middle of the adaptation phase. Activation in some of these areas, including the inferior parietal lobule, intra-parietal sulcus and somatosensory cortex, likely reflected actual learning, since the activation correlated with learning after-effects. Lastly, we identified several structures having recall-related activation, including the anterior cingulate and the posterior putamen, since the activation correlated with recall efficacy. These findings demonstrate dynamic aspects of brain activation patterns related to formation and recall of a sensory-motor skill, such that non-overlapping brain regions participate in distinctive behavioral events. PMID:25019676

External and internal factors influencing self-directed online learning of physiotherapy undergraduate students in Sweden: a qualitative study

PubMed Central

Hammarlund, Catharina Sjödahl; Nilsson, Maria H.; Gummesson, Christina

2015-01-01

Purpose: Online courses have become common in health sciences education. This learning environment can be designed using different approaches to support student learning. To further develop online environment, it is important to understand how students perceive working and learning online. The aim of this study is to identify aspects influencing students’ learning processes and their adaptation to self-directed learning online. Methods: Thirty-four physiotherapy students with a mean age of 25 years (range, 21 to 34 years) participated. Qualitative content analysis and triangulation was used when investigating the students’ self-reflections, written during a five week self-directed, problem-oriented online course. Results: Two categories emerged: ‘the influence of the structured framework’ and ‘communication and interaction with teachers and peers.’ The learning processes were influenced by external factors, e.g., a clear structure including a transparent alignment of assignments and assessment. Important challenges to over-come were primarily internal factors, e.g., low self-efficacy, difficulties to plan the work effectively and adapting to a new environment. Conclusion: The analyses reflected important perspectives targeting areas which enable further course development. The influences of external and internal factors on learning strategies and self-efficacy are important aspects to consider when designing online courses. Factors such as pedagogical design, clarity of purpose, goals, and guidelines were important as well as continuous opportunities for communication and collaboration. Further studies are needed to understand and scaffold the motivational factors among students with low self-efficacy. PMID:26101401

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

PubMed

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

2017-10-10

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

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.

Context-Specific Adaptation of Gravity-Dependent Vestibular Reflex Responses (NSBRI Neurovestibular Project 1)

NASA Technical Reports Server (NTRS)

Shelhamer, Mark; Goldberg, Jefim; Minor, Lloyd B.; Paloski, William H.; Young, Laurence R.; Zee, David S.

1999-01-01

Impairment of gaze and head stabilization reflexes can lead to disorientation and reduced performance in sensorimotor tasks such as piloting of spacecraft. Transitions between different gravitoinertial force (gif) environments - as during different phases of space flight - provide an extreme test of the adaptive capabilities of these mechanisms. We wish to determine to what extent the sensorimotor skills acquired in one gravity environment will transfer to others, and to what extent gravity serves as a context cue for inhibiting such transfer. We use the general approach of adapting a response (saccades, vestibuloocular reflex: VOR, or vestibulocollic reflex: VCR) to a particular change in gain or phase in one gif condition, adapting to a different gain or phase in a second gif condition, and then seeing if gif itself - the context cue - can recall the previously-learned adapted responses. Previous evidence indicates that unless there is specific training to induce context-specificity, reflex adaptation is sequential rather than simultaneous. Various experiments in this project investigate the behavioral properties, neurophysiological basis, and anatomical substrate of context-specific learning, using otolith (gravity) signals as a context cue. In the following, we outline the methods for all experiments in this project, and provide details and results on selected experiments.

Clinical Growth: An Evolutionary Concept Analysis.

PubMed

Barkimer, Jessica

2016-01-01

Clinical growth is an essential component of nursing education, although challenging to evaluate. Considering the paradigm shift toward constructivism and student-centered learning, clinical growth requires an examination within contemporary practices. A concept analysis of clinical growth in nursing education produced defining attributes, antecedents, and consequences. Attributes included higher-level thinking, socialization, skill development, self-reflection, self-investment, interpersonal communication, and linking theory to practice. Identification of critical attributes allows educators to adapt to student-centered learning in the clinical environment. These findings allow educators to determine significant research questions, develop situation-specific theories, and identify strategies to enhance student learning in the clinical environment.

Adaptivity in Agent-Based Routing for Data Networks

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Kirshner, Sergey; Merz, Chris J.; Turner, Kagan

2000-01-01

Adaptivity, both of the individual agents and of the interaction structure among the agents, seems indispensable for scaling up multi-agent systems (MAS s) in noisy environments. One important consideration in designing adaptive agents is choosing their action spaces to be as amenable as possible to machine learning techniques, especially to reinforcement learning (RL) techniques. One important way to have the interaction structure connecting agents itself be adaptive is to have the intentions and/or actions of the agents be in the input spaces of the other agents, much as in Stackelberg games. We consider both kinds of adaptivity in the design of a MAS to control network packet routing. We demonstrate on the OPNET event-driven network simulator the perhaps surprising fact that simply changing the action space of the agents to be better suited to RL can result in very large improvements in their potential performance: at their best settings, our learning-amenable router agents achieve throughputs up to three and one half times better than that of the standard Bellman-Ford routing algorithm, even when the Bellman-Ford protocol traffic is maintained. We then demonstrate that much of that potential improvement can be realized by having the agents learn their settings when the agent interaction structure is itself adaptive.

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.

To Exist as a Case Manager Is to Constantly Change; to Be Successful, You Must Constantly Adapt.

PubMed

Tahan, Hussein M

Change is inevitable whether in personal or professional lives. Case management practice is always evolving on the basis of the dynamic nature of the U.S. health care environment. Effective case managers are those who possess an adaptive mind-set, recognize the importance to change to maintain success, and remain relevant. They also demonstrate a sense of accountability and responsibility for own learning, professional development, and acquisition of new skills and knowledge. This editorial discusses the nature of change and adaptation and presents key strategies for case managers to remain relevant and effective in dynamic practice environments.

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

PubMed

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

2017-09-20

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

Adaptive process control using fuzzy logic and genetic algorithms

NASA Technical Reports Server (NTRS)

Karr, C. L.

1993-01-01

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

Instructional changes based on cogenerative physics reform

NASA Astrophysics Data System (ADS)

Samuels, Natan; Brewe, Eric; Kramer, Laird

2013-01-01

We describe changes in a physics teacher's pedagogy and cultural awareness that resulted from her students' involvement in reforming their classroom. For this case study, we examined a veteran high school teacher's semester-long use of CMPLE (the Cogenerative Mediation Process for Learning Environments) in her Modeling Instruction classroom. CMPLE is a formative intervention designed to help students and instructors collaborate to change classroom dynamics, based on how closely the environment matches their learning preferences. Analysis of classroom videos, interviews, and other artifacts indicates that adapting the environment to align with the preferences of that shared culture affected the instructor in complex ways. We will trace her teaching practices and her self-described awareness of the culture of learning, to highlight notable changes. The teacher espoused deeper understanding of her students' physics learning experience, which she gained from including students in responding to their own individual and collective learning preferences.

The sensorimotor and social sides of the architecture of speech.

PubMed

Pezzulo, Giovanni; Barca, Laura; D'Ausilio, Alessando

2014-12-01

Speech is a complex skill to master. In addition to sophisticated phono-articulatory abilities, speech acquisition requires neuronal systems configured for vocal learning, with adaptable sensorimotor maps that couple heard speech sounds with motor programs for speech production; imitation and self-imitation mechanisms that can train the sensorimotor maps to reproduce heard speech sounds; and a "pedagogical" learning environment that supports tutor learning.

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

PubMed

Wikander, Lolita; Bouchoucha, Stéphane L

2018-01-01

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

Adaptive functional systems: learning with chaos.

PubMed

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

2010-12-01

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

A plastic corticostriatal circuit model of adaptation in perceptual decision making

PubMed Central

Hsiao, Pao-Yueh; Lo, Chung-Chuan

2013-01-01

The ability to optimize decisions and adapt them to changing environments is a crucial brain function that increase survivability. Although much has been learned about the neuronal activity in various brain regions that are associated with decision making, and about how the nervous systems may learn to achieve optimization, the underlying neuronal mechanisms of how the nervous systems optimize decision strategies with preference given to speed or accuracy, and how the systems adapt to changes in the environment, remain unclear. Based on extensive empirical observations, we addressed the question by extending a previously described cortico-basal ganglia circuit model of perceptual decisions with the inclusion of a dynamic dopamine (DA) system that modulates spike-timing dependent plasticity (STDP). We found that, once an optimal model setting that maximized the reward rate was selected, the same setting automatically optimized decisions across different task environments through dynamic balancing between the facilitating and depressing components of the DA dynamics. Interestingly, other model parameters were also optimal if we considered the reward rate that was weighted by the subject's preferences for speed or accuracy. Specifically, the circuit model favored speed if we increased the phasic DA response to the reward prediction error, whereas the model favored accuracy if we reduced the tonic DA activity or the phasic DA responses to the estimated reward probability. The proposed model provides insight into the roles of different components of DA responses in decision adaptation and optimization in a changing environment. PMID:24339814

Preserving a Quality Environment for Learning. International Symposium Proceedings (2nd, Columbus, Ohio, October 10-12, 1988).

ERIC Educational Resources Information Center

Gerber, Carole, Ed.

Designing campus environments integrates the efforts of architects, planners, landscape personnel, and administrators. At a symposium on preserving a quality environment, the concepts of planning, building, managing, preserving and questions such as: How can we plan buildings that can be readily adapted to future needs? What is the value of campus…

Incorporating Online Tools in Tertiary Education

ERIC Educational Resources Information Center

Steenkamp, Leon P.; Rudman, Riaan J.

2013-01-01

Students currently studying at tertiary institutions have developed a set of attitudes and aptitudes as a result of growing up in an IT and media-rich environment. These attitudes and aptitudes influence how they learn and in order to be effective, lecturers must adapt to address their learning preferences and use the online teaching tools that…

Private Capital and Public Education: Toward Quality at Scale. Working Paper 2009-02

ERIC Educational Resources Information Center

Vander Ark, Tom

2009-01-01

In this paper, the author sketches a vision depicting some of the ways in which technology could revolutionize the traditional school environment--with static, printed texts replaced by adaptive, digital learning and virtual learning communities supplementing seat time. He argues that any such transformation, however, is dependent upon investment…

Selected Lessons Learned through the ISS Design, Development, Assembly, and Operations: Applicability to International Cooperation for Standardization

NASA Technical Reports Server (NTRS)

Hirsch, David B.

2009-01-01

This slide presentation reviews selected lessons that were learned during the design, development, assembly and operation of the International Space Station. The critical importance of standards and common interfaces is emphasized to create a common operation environment that can lead to flexibility and adaptability.

Speeding Up Team Learning.

ERIC Educational Resources Information Center

Edmondson, Amy; Bohmer, Richard; Pisano, Gary

2001-01-01

A study of 16 cardiac surgery teams looked at how the teams adapted to new ways of working. The challenge of team management is to implement new processes as quickly as possible. Steps for creating a learning team include selecting a mix of skills and expertise, framing the challenge, and creating an environment of psychological safety. (JOW)

Mobile Learning Technology Based on iOS Devices to Support Students with Special Education Needs

ERIC Educational Resources Information Center

Fernandez-Lopez, Alvaro; Rodriguez-Fortiz, Maria Jose; Rodriguez-Almendros, Maria Luisa; Martinez-Segura, Maria Jose

2013-01-01

Students with special education have difficulties to develop cognitive abilities and acquire new knowledge. They could also need to improve their behavior, communication and relationships with their environment. The development of customizable and adaptable applications tailored to them provides many benefits as it helps mold the learning process…

Application of a Framework for Educational Provision--Research Findings and Implications for Education for Sustainability

ERIC Educational Resources Information Center

Hewitt, Nan A.

2007-01-01

Learning for sustainability has the potential to play a significant role in enhancing social ecological resilience--as individuals and institutions develop the capacity to adaptively manage the environment. This article outlines an audience and learning needs analysis of irrigators in Western Australia's East Wanneroo area. Interviews were…

The Self-Schedule System for Instructional-Learning Management in Adaptive School Learning Environments.

ERIC Educational Resources Information Center

Wang, Margaret C., Ed.

The studies in this monograph are designed to examine the implementation processes of an innovative instructional program and the relationship between the implementation process and the achievement of certain program goals in school settings. The monograph is a contribution to the technical aspects of designing and implementing innovative…

Technology-Enhanced Learning Environments. Case Studies in TESOL Practice Series.

ERIC Educational Resources Information Center

Hanson-Smith, Elizabeth, Ed.

This edited volume presents case studies from Europe, North America, Asia, and the Middle East in which teachers have adapted and pioneered teaching innovations. The book is divided into 4 parts, 12 chapters, and an introduction. Part one, "Building a Computer Learning Center," has two chapters: "Guerilla Tactics: Creating a…

Measuring User Experience of the Student-Centered e-Learning Environment

ERIC Educational Resources Information Center

Santoso, Harry B.; Schrepp, Martin; Isal, R. Yugo Kartono; Utomo, Andika Yudha; Priyogi, Bilih

2016-01-01

The aim of the current study is to develop an adapted version of User Experience Questionnaire (UEQ) and evaluate a learning management system. Although there is a growing interest on User Experience, there are still limited resources (i.e. measurement tools or questionnaires) available to measure user experience of any products, especially…

Culturally-Based Adaptive Learning and Concept Analytics to Guide Educational Website Content Integration

ERIC Educational Resources Information Center

Reiners, Torsten; Dreher, Heinz

2009-01-01

In modern learning environments, the lecturer or educational designer is often confronted with multi-national student cohorts, requiring special consideration regarding language, cultural norms and taboos, religion, and ethics. Through a somewhat provocative example we demonstrate that taking such factors into account can be essential to avoid…

Science Education in Rural America: Adaptations for the Ivory Tower

ERIC Educational Resources Information Center

Van Doren, Gregory S.

2010-01-01

This thesis illustrated what can happen when academic culture disconnects from the cultures surrounding it. It showed that formal school environments are not always the best places to learn. A discussion of the debate between coherence and fragmentation learning theories illustrated academic chasms and a mindset that science education must…

Learning Qualitative and Quantitative Reasoning in a Microworld for Elastic Impacts.

ERIC Educational Resources Information Center

Ploetzner, Rolf; And Others

1990-01-01

Discusses the artificial-intelligence-based microworld DiBi and MULEDS, a multilevel diagnosis system. Developed to adapt tutoring style to the individual learner. Explains that DiBi sets up a learning environment, and simulates elastic impacts as a subtopic of classical mechanics, and supporting reasoning on different levels of mental domain…

Hexacopter trajectory control using a neural network

NASA Astrophysics Data System (ADS)

Artale, V.; Collotta, M.; Pau, G.; Ricciardello, A.

2013-10-01

The modern flight control systems are complex due to their non-linear nature. In fact, modern aerospace vehicles are expected to have non-conventional flight envelopes and, then, they must guarantee a high level of robustness and adaptability in order to operate in uncertain environments. Neural Networks (NN), with real-time learning capability, for flight control can be used in applications with manned or unmanned aerial vehicles. Indeed, using proven lower level control algorithms with adaptive elements that exhibit long term learning could help in achieving better adaptation performance while performing aggressive maneuvers. In this paper we show a mathematical modeling and a Neural Network for a hexacopter dynamics in order to develop proper methods for stabilization and trajectory control.

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

Dental nursing education and the introduction of technology-assisted learning.

PubMed

Sheridan, C; Gorman, T; Claffey, N

2008-11-01

The aim of this paper is to explore the profile of dental nursing students in the National Dental Nurse Training Programme of Ireland and their adjustment to a technology-assisted learning environment. Evaluation by students of the course and their reactions to the course were analysed. Dental nurses must possess the skills and knowledge to proficiently function in the modern day dental surgery. The implementation of a dental nurse programme that is heavily reliant on technology has started to create a group of dental nurses equipped with basic skills to access and retrieve information over a lifetime. However, the transition to a technology-assisted learning environment including online learning activities requires adaptation and expertise by educators and students alike. Careful evaluation and stakeholder feedback is imperative in the creation and maintaining of a quality programme. In conclusion, the students in this study responded well to the transition to a technology-based learning environment. Furthermore, the findings of this study suggest that the use of an online environment is an effective and stimulating learning environment for the students of a dental nurse programme; however, familiarity skills and knowledge of information technology is a prerequisite for success.

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

PubMed

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

2012-08-13

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

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.

Neural network system for purposeful behavior based on foveal visual preprocessor

NASA Astrophysics Data System (ADS)

Golovan, Alexander V.; Shevtsova, Natalia A.; Klepatch, Arkadi A.

1996-10-01

Biologically plausible model of the system with an adaptive behavior in a priori environment and resistant to impairment has been developed. The system consists of input, learning, and output subsystems. The first subsystems classifies input patterns presented as n-dimensional vectors in accordance with some associative rule. The second one being a neural network determines adaptive responses of the system to input patterns. Arranged neural groups coding possible input patterns and appropriate output responses are formed during learning by means of negative reinforcement. Output subsystem maps a neural network activity into the system behavior in the environment. The system developed has been studied by computer simulation imitating a collision-free motion of a mobile robot. After some learning period the system 'moves' along a road without collisions. It is shown that in spite of impairment of some neural network elements the system functions reliably after relearning. Foveal visual preprocessor model developed earlier has been tested to form a kind of visual input to the system.

Learning-based traffic signal control algorithms with neighborhood information sharing: An application for sustainable mobility

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

Aziz, H. M. Abdul; Zhu, Feng; Ukkusuri, Satish V.

Here, this research applies R-Markov Average Reward Technique based reinforcement learning (RL) algorithm, namely RMART, for vehicular signal control problem leveraging information sharing among signal controllers in connected vehicle environment. We implemented the algorithm in a network of 18 signalized intersections and compare the performance of RMART with fixed, adaptive, and variants of the RL schemes. Results show significant improvement in system performance for RMART algorithm with information sharing over both traditional fixed signal timing plans and real time adaptive control schemes. Additionally, the comparison with reinforcement learning algorithms including Q learning and SARSA indicate that RMART performs better atmore » higher congestion levels. Further, a multi-reward structure is proposed that dynamically adjusts the reward function with varying congestion states at the intersection. Finally, the results from test networks show significant reduction in emissions (CO, CO 2, NO x, VOC, PM 10) when RL algorithms are implemented compared to fixed signal timings and adaptive schemes.« less

Tracks the Sand. Jockey's Ridge State Park: An Environmental Education Learning Experience Designed for Grades 4-6.

ERIC Educational Resources Information Center

Crutchfield, Fran

This learning packet, one in a group of eight, was developed by the Jockey's Ridge State Park in North Carolina for Grades 4-6 to learn about animal adaptation and behavior in the dune environment. Loose-leaf pages are presented in 10 sections that contain: (1) introductions to the North Carolina State Park System, the Jockey Ridge State Park, the…

Types of Homeschool Environments and Need Support for Children's Achievement Motivation

ERIC Educational Resources Information Center

Bell, Debra A.; Kaplan, Avi; Thurman, S. Kenneth

2016-01-01

Working within a self-determination theory (SDT) framework, this study used cluster analysis to examine the naturally occurring types of homeschool-learning environments parents (N = 457) have created. Measures of support for student autonomy, mastery goal structure, and use of conditional regard were adapted for a homeschool context and used as…

Caring Spaces, Learning Places: Children's Environments That Work.

ERIC Educational Resources Information Center

Greenman, Jim

This book is intended as a resource for those who create, adapt, and cope with settings for young children. It focuses particularly on all-day child care settings. Part 1, "Understanding Children's Settings," explores the power of the environment, or the "landscape" of children's lives--the array of settings they inhabit--and analyzes the…

Digital Native and Digital Immigrant Use of Scholarly Network for Doctoral Learners

ERIC Educational Resources Information Center

Berman, Ronald; Hassell, Deliesha

2014-01-01

The Doctoral Community Network (DC) is a learner driven, scholarly community designed to help online doctoral learners successfully complete their dissertation and program of study. While digital natives grew up in an environment immersed in technology, digital immigrants adapted to this environment through their ability to learn and adjust to…

Fostering Self-Regulation in Training Complex Cognitive Tasks

ERIC Educational Resources Information Center

van Meeuwen, Ludo W.; Brand-Gruwel, Saskia; Kirschner, Paul A.; de Bock, Jeano J. P. R.; van Merriënboer, Jeroen J. G.

2018-01-01

In complex cognitive domains such as air traffic control, professionals must be able to adapt to and act upon continuing changes in a highly advanced technological work environment. To function optimally in such an environment, the controllers must be able to regulate their learning. Although these regulation skills should be part of their…

Adapting Advanced Information Technology Network Training for Adults with Visual Impairments

ERIC Educational Resources Information Center

Armstrong, Helen L.; Murray, Iain D.

2010-01-01

This article describes an accessible e-learning environment that was designed to deliver advanced IT skills to legally blind students in preparation for employment. The aim was to convert industry-standard training materials in print into accessible formats and to deliver the learning materials in ways that are more suited to adult students with…

Learning Boolean Networks in HepG2 cells using ToxCast High-Content Imaging Data (SOT annual meeting)

EPA Science Inventory

Cells adapt to their environment via homeostatic processes that are regulated by complex molecular networks. Our objective was to learn key elements of these networks in HepG2 cells using ToxCast High-content imaging (HCI) measurements taken over three time points (1, 24, and 72h...

Reshaping Computer Literacy Teaching in Higher Education: Identification of Critical Success Factors

ERIC Educational Resources Information Center

Taylor, Estelle; Goede, Roelien; Steyn, Tjaart

2011-01-01

Purpose: Acquiring computer skills is more important today than ever before, especially in a developing country. Teaching of computer skills, however, has to adapt to new technology. This paper aims to model factors influencing the success of the learning of computer literacy by means of an e-learning environment. The research question for this…

Effectiveness of a Learner-Directed Model for e-Learning

ERIC Educational Resources Information Center

Lee, Stella; Barker, Trevor; Kumar, Vivekanandan Suresh

2016-01-01

It is a hard task to strike a balance between extents of control a learner exercises and the amount of guidance, active or passive, afforded by the learning environment to guide, support, and motivate the learner. Adaptive systems strive to find the right balance in a spectrum that spans between self-control and system-guidance. They also concern…

Students' Attitudes towards Edmodo, a Social Learning Network: A Scale Development Study

ERIC Educational Resources Information Center

Yunkul, Eyup; Cankaya, Serkan

2017-01-01

Social Learning Networks (SLNs) are the developed forms of Social Network Sites (SNSs) adapted to educational environments, and they are used by quite a large population throughout the world. In addition, in related literature, there is no scale for the measurement of students' attitudes towards such sites. The purpose of this study was to develop…

The Impact of Adaptive Complex Assessment on the HOT Skill Development of Students

ERIC Educational Resources Information Center

Raiyn, Jamal; Tilchin, Oleg

2016-01-01

In this paper we propose a method for the adaptive complex assessment (ACA) of the higher-order thinking (HOT) skills needed by students for problem solving, and we examine the impact of the method on the development of HOT skills in a problem-based learning (PBL) environment. Complexity in the assessment is provided by initial, formative, and…

Using an improved virtual learning environment for engineering students

NASA Astrophysics Data System (ADS)

Lourdes Martínez Cartas, Ma

2012-06-01

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

The training schedule affects the stability, not the magnitude, of the interlimb transfer of learned dynamics

PubMed Central

Joiner, Wilsaan M.; Brayanov, Jordan B.

2013-01-01

The way that a motor adaptation is trained, for example, the manner in which it is introduced or the duration of the training period, can influence its internal representation. However, recent studies examining the gradual versus abrupt introduction of a novel environment have produced conflicting results. Here we examined how these effects determine the effector specificity of motor adaptation during visually guided reaching. After adaptation to velocity-dependent dynamics in the right arm, we estimated the amount of adaptation transferred to the left arm, using error-clamp measurement trials to directly measure changes in learned dynamics. We found that a small but significant amount of generalization to the untrained arm occurs under three different training schedules: a short-duration (15 trials) abrupt presentation, a long-duration (160 trials) abrupt presentation, and a long-duration gradual presentation of the novel dynamic environment. Remarkably, we found essentially no difference between the amount of interlimb generalization when comparing these schedules, with 9–12% transfer of the trained adaptation for all three. However, the duration of training had a pronounced effect on the stability of the interlimb transfer: The transfer elicited from short-duration training decayed rapidly, whereas the transfer from both long-duration training schedules was considerably more persistent (<50% vs. >90% retention over the first 20 trials). These results indicate that the amount of interlimb transfer is similar for gradual versus abrupt training and that interlimb transfer of learned dynamics can occur after even a brief training period but longer training is required for an enduring effect. PMID:23719204

The training schedule affects the stability, not the magnitude, of the interlimb transfer of learned dynamics.

PubMed

Joiner, Wilsaan M; Brayanov, Jordan B; Smith, Maurice A

2013-08-01

The way that a motor adaptation is trained, for example, the manner in which it is introduced or the duration of the training period, can influence its internal representation. However, recent studies examining the gradual versus abrupt introduction of a novel environment have produced conflicting results. Here we examined how these effects determine the effector specificity of motor adaptation during visually guided reaching. After adaptation to velocity-dependent dynamics in the right arm, we estimated the amount of adaptation transferred to the left arm, using error-clamp measurement trials to directly measure changes in learned dynamics. We found that a small but significant amount of generalization to the untrained arm occurs under three different training schedules: a short-duration (15 trials) abrupt presentation, a long-duration (160 trials) abrupt presentation, and a long-duration gradual presentation of the novel dynamic environment. Remarkably, we found essentially no difference between the amount of interlimb generalization when comparing these schedules, with 9-12% transfer of the trained adaptation for all three. However, the duration of training had a pronounced effect on the stability of the interlimb transfer: The transfer elicited from short-duration training decayed rapidly, whereas the transfer from both long-duration training schedules was considerably more persistent (<50% vs. >90% retention over the first 20 trials). These results indicate that the amount of interlimb transfer is similar for gradual versus abrupt training and that interlimb transfer of learned dynamics can occur after even a brief training period but longer training is required for an enduring effect.

Adaptation and readaptation medical concerns of a Mars trip

NASA Technical Reports Server (NTRS)

Johnson, Philip C.

1986-01-01

The ability of the human body to adapt to microgravity environments and to later readapt to a gravity environment was examined. Issues specifically relating to the effects of long duration space flight on the adaptation/readaptation process are discussed. The need for better health prediction techniques is stressed in order to be able to better anticipate crew health problems and to perform corrective actions. Several specific examples are discussed of latent diseases which could occur during a long duration space mission, even after having subjected the crew to thorough premission checkups. The need for learning how to prevent or ameliorate such problems as space adaptation syndrome, bone and muscle (and possibly tissue) atrophy, immune system atrophy, and heart arrythmias is also discussed. The implications of the age of the crew, the influence of an onboard low level gravity field, and drugs are briefly addressed as factors in the adaptation/readaptation process.

Modeling the Player: Predictability of the Models of Bartle and Kolb Based on NEO-FFI (Big5) and the Implications for Game Based Learning

ERIC Educational Resources Information Center

Konert, Johannes; Gutjahr, Michael; Göbel, Stefan; Steinmetz, Ralf

2014-01-01

For adaptation and personalization of game play sophisticated player models and learner models are used in game-based learning environments. Thus, the game flow can be optimized to increase efficiency and effectiveness of gaming and learning in parallel. In the field of gaming still the Bartle model is commonly used due to its simplicity and good…

C3Conflict a Simulation Environment for Studying Teamwork in Command and Control

DTIC Science & Technology

2011-06-01

the Sciences (pp. 173- 217). Amsterdam/New York: Rodopi. Kolb , D. A. (1984). Experiential Learning – Experience as a source of learning and...increases dramatically when the students can see a replay and discuss their collaboration. Kolb has expressed a generally accepted model of experiential ... learning ( Kolb , 1998). The model can be adapted for research and team training performed with computer-based simulations (Granlund, 2008). The main

Interactive knowledge networks for interdisciplinary course navigation within Moodle.

PubMed

Scherl, Andre; Dethleffsen, Kathrin; Meyer, Michael

2012-12-01

Web-based hypermedia learning environments are widely used in modern education and seem particularly well suited for interdisciplinary learning. Previous work has identified guidance through these complex environments as a crucial problem of their acceptance and efficiency. We reasoned that map-based navigation might provide straightforward and effortless orientation. To achieve this, we developed a clickable and user-oriented concept map-based navigation plugin. This tool is implemented as an extension of Moodle, a widely used learning management system. It visualizes inner and interdisciplinary relations between learning objects and is generated dynamically depending on user set parameters and interactions. This plugin leaves the choice of navigation type to the user and supports direct guidance. Previously developed and evaluated face-to-face interdisciplinary learning materials bridging physiology and physics courses of a medical curriculum were integrated as learning objects, the relations of which were defined by metadata. Learning objects included text pages, self-assessments, videos, animations, and simulations. In a field study, we analyzed the effects of this learning environment on physiology and physics knowledge as well as the transfer ability of third-term medical students. Data were generated from pre- and posttest questionnaires and from tracking student navigation. Use of the hypermedia environment resulted in a significant increase of knowledge and transfer capability. Furthermore, the efficiency of learning was enhanced. We conclude that hypermedia environments based on Moodle and enriched by concept map-based navigation tools can significantly support interdisciplinary learning. Implementation of adaptivity may further strengthen this approach.

A service based adaptive U-learning system using UX.

PubMed

Jeong, Hwa-Young; Yi, Gangman

2014-01-01

In recent years, traditional development techniques for e-learning systems have been changing to become more convenient and efficient. One new technology in the development of application systems includes both cloud and ubiquitous computing. Cloud computing can support learning system processes by using services while ubiquitous computing can provide system operation and management via a high performance technical process and network. In the cloud computing environment, a learning service application can provide a business module or process to the user via the internet. This research focuses on providing the learning material and processes of courses by learning units using the services in a ubiquitous computing environment. And we also investigate functions that support users' tailored materials according to their learning style. That is, we analyzed the user's data and their characteristics in accordance with their user experience. We subsequently applied the learning process to fit on their learning performance and preferences. Finally, we demonstrate how the proposed system outperforms learning effects to learners better than existing techniques.

A Service Based Adaptive U-Learning System Using UX

PubMed Central

Jeong, Hwa-Young

2014-01-01

In recent years, traditional development techniques for e-learning systems have been changing to become more convenient and efficient. One new technology in the development of application systems includes both cloud and ubiquitous computing. Cloud computing can support learning system processes by using services while ubiquitous computing can provide system operation and management via a high performance technical process and network. In the cloud computing environment, a learning service application can provide a business module or process to the user via the internet. This research focuses on providing the learning material and processes of courses by learning units using the services in a ubiquitous computing environment. And we also investigate functions that support users' tailored materials according to their learning style. That is, we analyzed the user's data and their characteristics in accordance with their user experience. We subsequently applied the learning process to fit on their learning performance and preferences. Finally, we demonstrate how the proposed system outperforms learning effects to learners better than existing techniques. PMID:25147832

Probabilistic reversal learning is impaired in Parkinson's disease

PubMed Central

Peterson, David A.; Elliott, Christian; Song, David D.; Makeig, Scott; Sejnowski, Terrence J.; Poizner, Howard

2009-01-01

In many everyday settings, the relationship between our choices and their potentially rewarding outcomes is probabilistic and dynamic. In addition, the difficulty of the choices can vary widely. Although a large body of theoretical and empirical evidence suggests that dopamine mediates rewarded learning, the influence of dopamine in probabilistic and dynamic rewarded learning remains unclear. We adapted a probabilistic rewarded learning task originally used to study firing rates of dopamine cells in primate substantia nigra pars compacta (Morris et al. 2006) for use as a reversal learning task with humans. We sought to investigate how the dopamine depletion in Parkinson's disease (PD) affects probabilistic reward learning and adaptation to a reversal in reward contingencies. Over the course of 256 trials subjects learned to choose the more favorable from among pairs of images with small or large differences in reward probabilities. During a subsequent otherwise identical reversal phase, the reward probability contingencies for the stimuli were reversed. Seventeen Parkinson's disease (PD) patients of mild to moderate severity were studied off of their dopaminergic medications and compared to 15 age-matched controls. Compared to controls, PD patients had distinct pre- and post-reversal deficiencies depending upon the difficulty of the choices they had to learn. The patients also exhibited compromised adaptability to the reversal. A computational model of the subjects’ trial-by-trial choices demonstrated that the adaptability was sensitive to the gain with which patients weighted pre-reversal feedback. Collectively, the results implicate the nigral dopaminergic system in learning to make choices in environments with probabilistic and dynamic reward contingencies. PMID:19628022

Online faculty development for creating E-learning materials.

PubMed

Niebuhr, Virginia; Niebuhr, Bruce; Trumble, Julie; Urbani, Mary Jo

2014-01-01

Faculty who want to develop e-learning materials face pedagogical challenges of transforming instruction for the online environment, especially as many have never experienced online learning themselves. They face technical challenges of learning new software and time challenges of not all being able to be in the same place at the same time to learn these new skills. The objective of the Any Day Any Place Teaching (ADAPT) faculty development program was to create an online experience in which faculty could learn to produce e-learning materials. The ADAPT curriculum included units on instructional design, copyright principles and peer review, all for the online environment, and units on specific software tools. Participants experienced asynchronous and synchronous methods, including a learning management system, PC-based videoconferencing, online discussions, desktop sharing, an online toolbox and optional face-to-face labs. Project outcomes were e-learning materials developed and participants' evaluations of the experience. Likert scale responses for five instructional units (quantitative) were analyzed for distance from neutral using one-sample t-tests. Interview data (qualitative) were analyzed with assurance of data trustworthiness and thematic analysis techniques. Participants were 27 interprofessional faculty. They evaluated the program instruction as easy to access, engaging and logically presented. They reported increased confidence in new skills and increased awareness of copyright issues, yet continued to have time management challenges and remained uncomfortable about peer review. They produced 22 new instructional materials. Online faculty development methods are helpful for faculty learning to create e-learning materials. Recommendations are made to increase the success of such a faculty development program.

Task path planning, scheduling and learning for free-ranging robot systems

NASA Technical Reports Server (NTRS)

Wakefield, G. Steve

1987-01-01

The development of robotics applications for space operations is often restricted by the limited movement available to guided robots. Free ranging robots can offer greater flexibility than physically guided robots in these applications. Presented here is an object oriented approach to path planning and task scheduling for free-ranging robots that allows the dynamic determination of paths based on the current environment. The system also provides task learning for repetitive jobs. This approach provides a basis for the design of free-ranging robot systems which are adaptable to various environments and tasks.

Locomotor Dysfunction after Long-Duration Space Flight and Development of Countermeasures to Facilitate Faster Recovery

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; Wood, S. J.; Cohen, H. S.; Bloomberg, J. J.

2012-01-01

Exposure to the microgravity conditions of space flight induces adaptive modification in sensorimotor function allowing astronauts to operate in this unique environment. This adaptive state, however, is inappropriate for a 1-g environment. Consequently astronauts must spend time readapting to Earth s gravity following their return to Earth. During this readaptation period, alterations in sensorimotor function cause various disturbances in astronaut gait during postflight walking. They often rely more on vision for postural and gait stability and many report the need for greater cognitive supervision of motor actions that previous to space flight were fully automated. Over the last several years our laboratory has investigated postflight astronaut locomotion with the aim of better understanding how adaptive changes in underlying sensorimotor mechanisms contribute to postflight gait dysfunction. Exposure to the microgravity conditions of space flight induces adaptive modification in the control of vestibularly-mediated reflexive head movement during locomotion after space flight. Furthermore, during motor learning, adaptive transitions are composed of two main mechanisms: strategic and plastic. Strategic mechanisms represent immediate and transitory modifications in control to deal with changes in the prevailing environment that, if prolonged, induce plastic mechanisms designed to automate new behavioral responses. The goal of the present study was to examine the contributions of sensorimotor subsystems such as the vestibular and body load sensing (BLS) somatosensory influences on head movement control during locomotion after long-duration space flight. Further we present data on the two motor learning processes during readaptation of locomotor function after long-duration space flight.

Environnement et approche fonctionnelle ou les processus d'un systeme ouvert (The Environment and a Functional Approach or the Processes of an Open System).

ERIC Educational Resources Information Center

Catalan, Robert

1982-01-01

Discusses the relationship between the person learning a foreign language, the methodology employed, and the environment using the paradigms of T. Parsons. Notes that the functional method has adapted some of these functions and suggests ways to incorporate the others. (AMH)

Decision-Making in a Changing World: A Study in Autism Spectrum Disorders

ERIC Educational Resources Information Center

Robic, S.; Sonié, S.; Fonlupt, P.; Henaff, M.-A.; Touil, N.; Coricelli, G.; Mattout, J.; Schmitz, C.

2015-01-01

To learn to deal with the unexpected is essential to adaptation to a social, therefore often unpredictable environment. Fourteen adults with autism spectrum disorders (ASD) and 15 controls underwent a decision-making task aimed at investigating the influence of either a social or a non-social environment, and its interaction with either a stable…

Multi-Objective Reinforcement Learning-based Deep Neural Networks for Cognitive Space Communications

NASA Technical Reports Server (NTRS)

Ferreria, Paulo; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy; Bilen, Sven; Reinhart, Richard; Mortensen, Dale

2017-01-01

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

NASA Technical Reports Server (NTRS)

Ferreria, Paulo Victor R.; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy M.; Bilen, Sven G.; Reinhart, Richard C.; Mortensen, Dale J.

2017-01-01

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

Biologically inspired computation and learning in Sensorimotor Systems

NASA Astrophysics Data System (ADS)

Lee, Daniel D.; Seung, H. S.

2001-11-01

Networking systems presently lack the ability to intelligently process the rich multimedia content of the data traffic they carry. Endowing artificial systems with the ability to adapt to changing conditions requires algorithms that can rapidly learn from examples. We demonstrate the application of such learning algorithms on an inexpensive quadruped robot constructed to perform simple sensorimotor tasks. The robot learns to track a particular object by discovering the salient visual and auditory cues unique to that object. The system uses a convolutional neural network that automatically combines color, luminance, motion, and auditory information. The weights of the networks are adjusted using feedback from a teacher to reflect the reliability of the various input channels in the surrounding environment. Additionally, the robot is able to compensate for its own motion by adapting the parameters of a vestibular ocular reflex system.

Studio optics: Adapting interactive engagement pedagogy to upper-division physics

NASA Astrophysics Data System (ADS)

Sorensen, Christopher M.; McBride, Dyan L.; Rebello, N. Sanjay

2011-03-01

The use of interactive engagement strategies to improve learning in introductory physics is not new, but have not been used as often for upper-division physics courses. We describe the development and implementation of a Studio Optics course for upper-division physics majors at Kansas State University. The course adapts a three-stage Karplus learning cycle and other elements to foster an environment that promotes learning through an integration of lecture, laboratories, and problem solving. Some of the instructional materials are described. We discuss the evaluation of the course using data collected from student interviews, a conceptual survey, an attitudinal survey, and the instructor's reflections. Overall, students responded positively to the new format and showed modest gains in learning. The instructor's experiences compared favorably with the traditional course that he had taught in the past.

Adult age differences in information foraging in an interactive reading environment.

PubMed

Liu, Xiaomei; Chin, Jessie; Payne, Brennan R; Fu, Wai-Tat; Morrow, Daniel G; Stine-Morrow, Elizabeth A L

2016-05-01

When learning about a single topic in natural reading environments, readers are confronted with multiple sources varying in the type and amount of information. In this situation, readers are free to adaptively respond to the constraints of the environment (e.g., through selection of resources and time allocation for study), but there may be costs of exploring and switching between sources (e.g., disruption of attention, opportunity costs for study). From an ecological perspective, such properties of the environment are expected to influence learning strategies. In the current study, we used a novel reading paradigm to investigate age differences in the effects of information richness (i.e., sentence elaboration) and costs of switching between texts (i.e., time delay) on selection of sources and study time allocation. Consistent with the ecological view, participants progressed from less informative to more informative texts. Furthermore, increased switch cost led to a tendency to allocate more effort to easier materials and to greater persistence in reading, which in turn, led to better memory in both immediate and delayed recall. Older adults showed larger effects of switch cost, such that the age difference in delayed recall was eliminated in the high switch cost condition. Based on an ecological paradigm of reading that affords choice and self-regulation, our study provided evidence for preservation with age in the ability to adapt to changing learning environments so as to improve performance. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Virtual Reality as a Medium for Sensorimotor Adaptation Training and Spaceflight Countermeasures

NASA Technical Reports Server (NTRS)

Madansingh, S.; Bloomberg, J. J.

2015-01-01

With the upcoming shift to extra-long duration missions (1 year) aboard the ISS, sensorimotor adaptations during transitory periods in-and-out of microgravity are more important to understand and prepare for. Advances in virtual reality technology enables everyday adoption of these tools for entertainment and use in training. Experiencing virtual environments (VE) allows for the manipulation of visual flow to elicit automatic motor behavior and produce sensorimotor adaptation (SA). Recently, the ability to train individuals using repeatable and varied exposures to SA challenges has shown success by improving performance during exposure to a novel environment (Batson 2011). This capacity to 'learn to learn' is referred to as sensorimotor adaptive generalizability and, through the use of treadmill training, represents an untapped potential for individualized countermeasures. The goal of this study is to determine the feasibility of present head mounted displays (HMDs) to produce compelling visual flow information and the expected adaptations for use in future SA treadmill-based countermeasures. Participants experience infinite hallways providing congruent (baseline) or incongruent visual information (half or double speed) via HMD while walking on an instrumented treadmill at 1.1m/s. As gait performance approaches baseline levels, an adaptation time constant is derived to establish individual time-to-adapt (TTA). It is hypothesized that decreasing the TTA through SA treadmill training will facilitate sensorimotor adaptation during gravitational transitions. In this way, HMD technology represents a novel platform for SA training using off-the-shelf consumer products for greater training flexibility in astronaut and terrestrial applications alike.

Facebook Groups as an Academic Teaching Aid: Case Study and Recommendations for Educators

ERIC Educational Resources Information Center

Miron, Eli; Ravid, Gilad

2015-01-01

The move from a walled garden type Learning Management Systems (LMS) to open environments (like Facebook) forces us to adapt new teaching ways. This article offers a brief review of the use of Facebook groups in learning, describes the experience of using Facebook groups in an academic institute, explains the considerations for choosing the type…

Learning under Conditions of Hierarchy and Discipline: The Case of the German Army, 1939-1940

ERIC Educational Resources Information Center

Visser, Max

2008-01-01

To survive in and adapt to dynamic, turbulent, and complex environments, organizations need to engage in learning. This truism is particularly relevant for army organizations in times of war and armed conflict. In this article a case of army operations during World War II is analyzed on the basis of Ortenblad's integrated model of the learning…

Are You Smarter Than a Teenager? Maybe Not When It Comes to Reinforcement Learning.

PubMed

DiMenichi, Brynne C; Tricomi, Elizabeth

2016-10-05

Adolescence is a time of tumultuous behavior that may result, in part, from brain circuitry that enhances reward seeking. In this issue of Neuron, Davidow et al. (2016) present a convincing argument that adolescent brain functionality can be adaptive in certain contexts, particularly probabilistic learning environments. Copyright © 2016. Published by Elsevier Inc.

Theoretically Grounded Guidelines for Assessing Learning Progress: Cognitive Changes in Ill-Structured Complex Problem-Solving Contexts

ERIC Educational Resources Information Center

Kim, Min Kyu

2012-01-01

It is generally accepted that the cognitive development for a wide range of students can be improved through adaptive instruction-learning environments optimized to suit individual needs (e.g., Cronbach, Am Psychol 12:671-684, 1957; Lee and Park, in Handbook of research for educational communications and technology, Taylor & Francis Group,…

Learning the Discourse of Quality Assurance: A Case of Workplace Learning in Online In-Service Training

ERIC Educational Resources Information Center

Lundin, Mona; Lundin, Johan

2016-01-01

Purpose: In this study, online in-service training for people employed in the food production industry is scrutinized. The purpose of this study is to analyse how the participants adapt to such online environments in terms of the kind of discussions they establish. The more specific interest relates to how the participants discuss current work…

Assessment of Postflight Locomotor Performance Utilizing a Test of Functional Mobility: Strategic and Adaptive Responses

NASA Technical Reports Server (NTRS)

Warren, L. E.; Mulavara, A. P.; Peters, B. T.; Cohen, H. S.; Richards, J. T.; Miller, C. A.; Brady, R.; Ruttley, T. M.; Bloomberg, J. J.

2006-01-01

Space flight induces adaptive modification in sensorimotor function, allowing crewmembers to operate in the unique microgravity environment. This adaptive state, however, is inappropriate for a terrestrial environment. During a re-adaptation period upon their return to Earth, crewmembers experience alterations in sensorimotor function, causing various disturbances in perception, spatial orientation, posture, gait, and eye-head coordination. Following long duration space flight, sensorimotor dysfunction would prevent or extend the time required to make an emergency egress from the vehicle; compromising crew safety and mission objectives. We are investigating two types of motor learning that may interact with each other and influence a crewmember's ability to re-adapt to Earth's gravity environment. In strategic learning, crewmembers make rapid modifications in their motor control strategy emphasizing error reduction. This type of learning may be critical during the first minutes and hours after landing. In adaptive learning, long-term plastic transformations occur, involving morphological changes and synaptic modification. In recent literature these two behavioral components have been associated with separate brain structures that control the execution of motor strategies: the strategic component was linked to the posterior parietal cortex and the adaptive component was linked to the cerebellum (Pisella, et al. 2004). The goal of this paper was to demonstrate the relative contributions of the strategic and adaptive components to the re-adaptation process in locomotor control after long duration space flight missions on the International Space Station (ISS). The Functional Mobility Test (FMT) was developed to assess crewmember s ability to ambulate postflight from an operational and functional perspective. Sixteen crewmembers were tested preflight (3 sessions) and postflight (days 1, 2, 4, 7, 25) following a long duration space flight (approx 6 months) on the ISS. We have further analyzed the FMT data to characterize strategic and adaptive components during the postflight readaptation period. Crewmembers walked at a preferred pace through an obstacle course set up on a base of 10 cm thick medium density foam (Sunmate Foam, Dynamic Systems, Inc., Leicester, NC). The 6.0m X 4.0m course consisted of several pylons made of foam; a Styrofoam barrier 46.0cm high that crewmembers stepped over; and a portal constructed of two Styrofoam blocks, each 31cm high, with a horizontal bar covered by foam and suspended from the ceiling which was adjusted to the height of the crewmember s shoulder. The portal required crewmembers to bend at the waist and step over a barrier simultaneously. All obstacles were lightweight, soft and easily knocked over. Crewmembers were instructed to walk through the course as quickly and as safely as possible without touching any of the objects on the course. This task was performed three times in the clockwise direction and three times in the counterclockwise direction that was randomly chosen. The dependent measures for each trial were: time to complete the course (seconds) and the number of obstacles touched or knocked down. For each crewmember, the time to complete each FMT trial from postflight days 1, 2, 4, 7 and 25 were further analyzed. A single logarithmic curve using a least squares calculation was fit through these data to produce a single comprehensive curve (macro). This macro curve composed of data spanning 25 days, illustrates the re-adaptive learning function over the longer time scale term. Additionally, logarithmic curves were fit to the 6 data trials within each individual post flight test day to produce 5 separate daily curves. These micro curves, produced from data obtained over the course of minutes, illustrates the strategic learning function exhibited over a relative shorter time scale. The macro curve for all subjects exhibited adaptive motor learning patterns over the 25 day period. Howev, 9/16 crewmembers exhibited significant strategic motor learning patterns in their micro curves, as defined by m > 1 in the equation of the line y=m*LN(x) +b. These data indicate that postflight recovery in locomotor function involves both strategic and adaptive mechanisms. Future countermeasures will be designed to enhance both recovery processes.

Constructing Temporally Extended Actions through Incremental Community Detection

PubMed Central

Li, Ge

2018-01-01

Hierarchical reinforcement learning works on temporally extended actions or skills to facilitate learning. How to automatically form such abstraction is challenging, and many efforts tackle this issue in the options framework. While various approaches exist to construct options from different perspectives, few of them concentrate on options' adaptability during learning. This paper presents an algorithm to create options and enhance their quality online. Both aspects operate on detected communities of the learning environment's state transition graph. We first construct options from initial samples as the basis of online learning. Then a rule-based community revision algorithm is proposed to update graph partitions, based on which existing options can be continuously tuned. Experimental results in two problems indicate that options from initial samples may perform poorly in more complex environments, and our presented strategy can effectively improve options and get better results compared with flat reinforcement learning. PMID:29849543

A marching-walking hybrid induces step length adaptation and transfers to natural walking

PubMed Central

Long, Andrew W.; Finley, James M.

2015-01-01

Walking is highly adaptable to new demands and environments. We have previously studied adaptation of locomotor patterns via a split-belt treadmill, where subjects learn to walk with one foot moving faster than the other. Subjects learn to adapt their walking pattern by changing the location (spatial) and time (temporal) of foot placement. Here we asked whether we can induce adaptation of a specific walking pattern when one limb does not “walk” but instead marches in place (i.e., marching-walking hybrid). The marching leg's movement is limited during the stance phase, and thus certain sensory signals important for walking may be reduced. We hypothesized that this would produce a spatial-temporal strategy different from that of normal split-belt adaptation. Healthy subjects performed two experiments to determine whether they could adapt their spatial-temporal pattern of step lengths during the marching-walking hybrid and whether the learning transfers to over ground walking. Results showed that the hybrid group did adapt their step lengths, but the time course of adaptation and deadaption was slower than that for the split-belt group. We also observed that the hybrid group utilized a mostly spatial strategy whereas the split-belt group utilized both spatial and temporal strategies. Surprisingly, we found no significant difference between the hybrid and split-belt groups in over ground transfer. Moreover, the hybrid group retained more of the learned pattern when they returned to the treadmill. These findings suggest that physical rehabilitation with this marching-walking paradigm on conventional treadmills may produce changes in symmetry comparable to what is observed during split-belt training. PMID:25867742

A marching-walking hybrid induces step length adaptation and transfers to natural walking.

PubMed

Long, Andrew W; Finley, James M; Bastian, Amy J

2015-06-01

Walking is highly adaptable to new demands and environments. We have previously studied adaptation of locomotor patterns via a split-belt treadmill, where subjects learn to walk with one foot moving faster than the other. Subjects learn to adapt their walking pattern by changing the location (spatial) and time (temporal) of foot placement. Here we asked whether we can induce adaptation of a specific walking pattern when one limb does not "walk" but instead marches in place (i.e., marching-walking hybrid). The marching leg's movement is limited during the stance phase, and thus certain sensory signals important for walking may be reduced. We hypothesized that this would produce a spatial-temporal strategy different from that of normal split-belt adaptation. Healthy subjects performed two experiments to determine whether they could adapt their spatial-temporal pattern of step lengths during the marching-walking hybrid and whether the learning transfers to over ground walking. Results showed that the hybrid group did adapt their step lengths, but the time course of adaptation and deadaption was slower than that for the split-belt group. We also observed that the hybrid group utilized a mostly spatial strategy whereas the split-belt group utilized both spatial and temporal strategies. Surprisingly, we found no significant difference between the hybrid and split-belt groups in over ground transfer. Moreover, the hybrid group retained more of the learned pattern when they returned to the treadmill. These findings suggest that physical rehabilitation with this marching-walking paradigm on conventional treadmills may produce changes in symmetry comparable to what is observed during split-belt training. Copyright © 2015 the American Physiological Society.

Impedance learning for robotic contact tasks using natural actor-critic algorithm.

PubMed

Kim, Byungchan; Park, Jooyoung; Park, Shinsuk; Kang, Sungchul

2010-04-01

Compared with their robotic counterparts, humans excel at various tasks by using their ability to adaptively modulate arm impedance parameters. This ability allows us to successfully perform contact tasks even in uncertain environments. This paper considers a learning strategy of motor skill for robotic contact tasks based on a human motor control theory and machine learning schemes. Our robot learning method employs impedance control based on the equilibrium point control theory and reinforcement learning to determine the impedance parameters for contact tasks. A recursive least-square filter-based episodic natural actor-critic algorithm is used to find the optimal impedance parameters. The effectiveness of the proposed method was tested through dynamic simulations of various contact tasks. The simulation results demonstrated that the proposed method optimizes the performance of the contact tasks in uncertain conditions of the environment.

The simulated clinical environment: Cognitive and emotional impact among undergraduates.

PubMed

Tremblay, Marie-Laurence; Lafleur, Alexandre; Leppink, Jimmie; Dolmans, Diana H J M

2017-02-01

Simulated clinical immersion (SCI) is used in undergraduate healthcare programs to expose the learner to real-life situations in authentic simulated clinical environments. For novices, the environment in which the simulation occurs can be distracting and stressful, hence potentially compromising learning. This study aims to determine whether SCI (with environment) imposes greater extraneous cognitive load and stress on undergraduate pharmacy students than simulated patients (SP) (without environment). It also aims to explore how features of the simulated environment influence students' perception of learning. In this mixed-methods study, 143 undergraduate pharmacy students experienced both SCI and SP in a crossover design. After the simulations, participants rated their cognitive load and emotions. Thirty-five students met in focus groups to explore their perception of learning in simulation. Intrinsic and extraneous cognitive load and stress scores in SCI were significantly but modestly higher compared to SP. Qualitative findings reveal that the physical environment in SCI generated more stress and affected students? focus. In SP, students concentrated on clinical reasoning. SCI stimulated a focus on data collection but impeded in-depth problem solving processes. The physical environment in simulation influences what and how students learn. SCI was reported as more cognitively demanding than SP. Our findings emphasize the need for the development of adapted instructional design guidelines in simulation for novices.

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.

Adaptive Sampling for Urban Air Quality through Participatory Sensing

PubMed Central

Zeng, Yuanyuan; Xiang, Kai

2017-01-01

Air pollution is one of the major problems of the modern world. The popularization and powerful functions of smartphone applications enable people to participate in urban sensing to better know about the air problems surrounding them. Data sampling is one of the most important problems that affect the sensing performance. In this paper, we propose an Adaptive Sampling Scheme for Urban Air Quality (AS-air) through participatory sensing. Firstly, we propose to find the pattern rules of air quality according to the historical data contributed by participants based on Apriori algorithm. Based on it, we predict the on-line air quality and use it to accelerate the learning process to choose and adapt the sampling parameter based on Q-learning. The evaluation results show that AS-air provides an energy-efficient sampling strategy, which is adaptive toward the varied outside air environment with good sampling efficiency. PMID:29099766

Vision Systems with the Human in the Loop

NASA Astrophysics Data System (ADS)

Bauckhage, Christian; Hanheide, Marc; Wrede, Sebastian; Käster, Thomas; Pfeiffer, Michael; Sagerer, Gerhard

2005-12-01

The emerging cognitive vision paradigm deals with vision systems that apply machine learning and automatic reasoning in order to learn from what they perceive. Cognitive vision systems can rate the relevance and consistency of newly acquired knowledge, they can adapt to their environment and thus will exhibit high robustness. This contribution presents vision systems that aim at flexibility and robustness. One is tailored for content-based image retrieval, the others are cognitive vision systems that constitute prototypes of visual active memories which evaluate, gather, and integrate contextual knowledge for visual analysis. All three systems are designed to interact with human users. After we will have discussed adaptive content-based image retrieval and object and action recognition in an office environment, the issue of assessing cognitive systems will be raised. Experiences from psychologically evaluated human-machine interactions will be reported and the promising potential of psychologically-based usability experiments will be stressed.

Using wikis to stimulate collaborative learning in two online health sciences courses.

PubMed

Zitzelsberger, Hilde; Campbell, Karen A; Service, Dorothea; Sanchez, Otto

2015-06-01

The use of wiki technology fits well in courses that encourage constructive knowledge building and social learning by a community of learners. Pedagogically, wikis have attracted interest in higher education environments because they facilitate the collaborative processes required for developing student group assignments. This article describes a pilot project to assess the implementation of wikis in two online small- and mid-sized elective courses comprising nursing students in third- or fourth-year undergraduate levels within interdisciplinary health sciences courses. The need exists to further develop the pedagogical use of wiki environments before they can be expected to support collaboration among undergraduate nursing students. Adapting wiki implementation to suitable well-matched courses will make adaptation of wikis into nursing curricula more effective and may increase the chances that nursing students will hone the collaborative abilities that are essential in their future professional roles in communities of practice. Copyright 2015, SLACK Incorporated.

Dopamine Modulates Adaptive Prediction Error Coding in the Human Midbrain and Striatum.

PubMed

Diederen, Kelly M J; Ziauddeen, Hisham; Vestergaard, Martin D; Spencer, Tom; Schultz, Wolfram; Fletcher, Paul C

2017-02-15

Learning to optimally predict rewards requires agents to account for fluctuations in reward value. Recent work suggests that individuals can efficiently learn about variable rewards through adaptation of the learning rate, and coding of prediction errors relative to reward variability. Such adaptive coding has been linked to midbrain dopamine neurons in nonhuman primates, and evidence in support for a similar role of the dopaminergic system in humans is emerging from fMRI data. Here, we sought to investigate the effect of dopaminergic perturbations on adaptive prediction error coding in humans, using a between-subject, placebo-controlled pharmacological fMRI study with a dopaminergic agonist (bromocriptine) and antagonist (sulpiride). Participants performed a previously validated task in which they predicted the magnitude of upcoming rewards drawn from distributions with varying SDs. After each prediction, participants received a reward, yielding trial-by-trial prediction errors. Under placebo, we replicated previous observations of adaptive coding in the midbrain and ventral striatum. Treatment with sulpiride attenuated adaptive coding in both midbrain and ventral striatum, and was associated with a decrease in performance, whereas bromocriptine did not have a significant impact. Although we observed no differential effect of SD on performance between the groups, computational modeling suggested decreased behavioral adaptation in the sulpiride group. These results suggest that normal dopaminergic function is critical for adaptive prediction error coding, a key property of the brain thought to facilitate efficient learning in variable environments. Crucially, these results also offer potential insights for understanding the impact of disrupted dopamine function in mental illness. SIGNIFICANCE STATEMENT To choose optimally, we have to learn what to expect. Humans dampen learning when there is a great deal of variability in reward outcome, and two brain regions that are modulated by the brain chemical dopamine are sensitive to reward variability. Here, we aimed to directly relate dopamine to learning about variable rewards, and the neural encoding of associated teaching signals. We perturbed dopamine in healthy individuals using dopaminergic medication and asked them to predict variable rewards while we made brain scans. Dopamine perturbations impaired learning and the neural encoding of reward variability, thus establishing a direct link between dopamine and adaptation to reward variability. These results aid our understanding of clinical conditions associated with dopaminergic dysfunction, such as psychosis. Copyright © 2017 Diederen et al.

Use of Mobile Devices for E-Learning in Geomatics

NASA Astrophysics Data System (ADS)

Mills, H.

2015-05-01

For the last 4 years, the School of Civil Engineering & Geosciences at Newcastle University, UK adapted mobile devices as learning approach only for undergraduate within Geomatics. All incoming students were given a mobile device as learning tool, which was supposed to be there main way to accessing teaching material. This paper will present how students adopted the mobile devices and how their learning has changed using mobile devices. It will highlight which apps can be used in a Geomatics teaching environment to engage students in their learning and teaching environment. The paper will furthermore look into apps which help students within the area of Photogrammetry and Remote Sensing, such as the Autodesk 123D catch up or the Remote RDP app to remotely control surveying instrumentations, such as laser scanners. Those apps are easy tools to engage students within digital learning environment which the students are familiar with. The paper will show how students embrace the technology but also current limitation of using those within Higher education establishments, such as sufficient Wifi and student support for using mobile devices.

Habituation based synaptic plasticity and organismic learning in a quantum perovskite.

PubMed

Zuo, Fan; Panda, Priyadarshini; Kotiuga, Michele; Li, Jiarui; Kang, Mingu; Mazzoli, Claudio; Zhou, Hua; Barbour, Andi; Wilkins, Stuart; Narayanan, Badri; Cherukara, Mathew; Zhang, Zhen; Sankaranarayanan, Subramanian K R S; Comin, Riccardo; Rabe, Karin M; Roy, Kaushik; Ramanathan, Shriram

2017-08-14

A central characteristic of living beings is the ability to learn from and respond to their environment leading to habit formation and decision making. This behavior, known as habituation, is universal among all forms of life with a central nervous system, and is also observed in single-cell organisms that do not possess a brain. Here, we report the discovery of habituation-based plasticity utilizing a perovskite quantum system by dynamical modulation of electron localization. Microscopic mechanisms and pathways that enable this organismic collective charge-lattice interaction are elucidated by first-principles theory, synchrotron investigations, ab initio molecular dynamics simulations, and in situ environmental breathing studies. We implement a learning algorithm inspired by the conductance relaxation behavior of perovskites that naturally incorporates habituation, and demonstrate learning to forget: a key feature of animal and human brains. Incorporating this elementary skill in learning boosts the capability of neural computing in a sequential, dynamic environment.Habituation is a learning mechanism that enables control over forgetting and learning. Zuo, Panda et al., demonstrate adaptive synaptic plasticity in SmNiO 3 perovskites to address catastrophic forgetting in a dynamic learning environment via hydrogen-induced electron localization.

How copying affects the amount, evenness and persistence of cultural knowledge: insights from the social learning strategies tournament

PubMed Central

Rendell, L.; Boyd, R.; Enquist, M.; Feldman, M. W.; Fogarty, L.; Laland, K. N.

2011-01-01

Darwinian processes should favour those individuals that deploy the most effective strategies for acquiring information about their environment. We organized a computer-based tournament to investigate which learning strategies would perform well in a changing environment. The most successful strategies relied almost exclusively on social learning (here, learning a behaviour performed by another individual) rather than asocial learning, even when environments were changing rapidly; moreover, successful strategies focused learning effort on periods of environmental change. Here, we use data from tournament simulations to examine how these strategies might affect cultural evolution, as reflected in the amount of culture (i.e. number of cultural traits) in the population, the distribution of cultural traits across individuals, and their persistence through time. We found that high levels of social learning are associated with a larger amount of more persistent knowledge, but a smaller amount of less persistent expressed behaviour, as well as more uneven distributions of behaviour, as individuals concentrated on exploiting a smaller subset of behaviour patterns. Increased rates of environmental change generated increases in the amount and evenness of behaviour. These observations suggest that copying confers on cultural populations an adaptive plasticity, allowing them to respond to changing environments rapidly by drawing on a wider knowledge base. PMID:21357234

How copying affects the amount, evenness and persistence of cultural knowledge: insights from the social learning strategies tournament.

PubMed

Rendell, L; Boyd, R; Enquist, M; Feldman, M W; Fogarty, L; Laland, K N

2011-04-12

Darwinian processes should favour those individuals that deploy the most effective strategies for acquiring information about their environment. We organized a computer-based tournament to investigate which learning strategies would perform well in a changing environment. The most successful strategies relied almost exclusively on social learning (here, learning a behaviour performed by another individual) rather than asocial learning, even when environments were changing rapidly; moreover, successful strategies focused learning effort on periods of environmental change. Here, we use data from tournament simulations to examine how these strategies might affect cultural evolution, as reflected in the amount of culture (i.e. number of cultural traits) in the population, the distribution of cultural traits across individuals, and their persistence through time. We found that high levels of social learning are associated with a larger amount of more persistent knowledge, but a smaller amount of less persistent expressed behaviour, as well as more uneven distributions of behaviour, as individuals concentrated on exploiting a smaller subset of behaviour patterns. Increased rates of environmental change generated increases in the amount and evenness of behaviour. These observations suggest that copying confers on cultural populations an adaptive plasticity, allowing them to respond to changing environments rapidly by drawing on a wider knowledge base.

Psychotraumatology: What researchers and clinicians can learn from an evolutionary perspective.

PubMed

Troisi, Alfonso

2018-05-01

This review outlines the contribution of evolutionary science to experimental and clinical psychotraumatology. From an evolutionary perspective, traumatic and psychosocial stressors are conceived of as events or circumstances that thwart the achievement of biological goals. The more important is the adaptive value of the goal, the more painful is the emotional impact of the life event that endangers goal achievement. Life history theory and sexual selection theory help to explain why goal priorities differ between the sexes and across age groups. Cultural values and social learning interact with evolved inclinations in determining the hierarchy of goals for a specific person in a specific phase of his or her life. To illustrate the applicability of the evolutionary model, epidemiological and clinical data concerning individual differences in stress sensitivity and stress generation are reviewed and discussed. The final part of the review summarizes new hypotheses that explain how early and current psychosocial stressors can activate a series of adaptive mechanisms including developmental plasticity, predictive adaptive responses and differential susceptibility. Ultimately, the contribution of evolutionary science to psychotraumatology is the idea that experimental and clinical studies should shift the focus of research from the external environment (defined as all stressful factors external to the subjects under investigation) to the ecological environment (defined as those stressful factors of the external environment that have a greater potential to threaten the adaptive equilibrium of the subjects under investigation because of their evolved inclinations). Copyright © 2017 Elsevier Ltd. All rights reserved.

Experiments on Adaptive Techniques for Host-Based Intrusion Detection

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

DRAELOS, TIMOTHY J.; COLLINS, MICHAEL J.; DUGGAN, DAVID P.

2001-09-01

This research explores four experiments of adaptive host-based intrusion detection (ID) techniques in an attempt to develop systems that can detect novel exploits. The technique considered to have the most potential is adaptive critic designs (ACDs) because of their utilization of reinforcement learning, which allows learning exploits that are difficult to pinpoint in sensor data. Preliminary results of ID using an ACD, an Elman recurrent neural network, and a statistical anomaly detection technique demonstrate an ability to learn to distinguish between clean and exploit data. We used the Solaris Basic Security Module (BSM) as a data source and performed considerablemore » preprocessing on the raw data. A detection approach called generalized signature-based ID is recommended as a middle ground between signature-based ID, which has an inability to detect novel exploits, and anomaly detection, which detects too many events including events that are not exploits. The primary results of the ID experiments demonstrate the use of custom data for generalized signature-based intrusion detection and the ability of neural network-based systems to learn in this application environment.« less

Learning Predictive Statistics: Strategies and Brain Mechanisms.

PubMed

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe

2017-08-30

When immersed in a new environment, we are challenged to decipher initially incomprehensible streams of sensory information. However, quite rapidly, the brain finds structure and meaning in these incoming signals, helping us to predict and prepare ourselves for future actions. This skill relies on extracting the statistics of event streams in the environment that contain regularities of variable complexity from simple repetitive patterns to complex probabilistic combinations. Here, we test the brain mechanisms that mediate our ability to adapt to the environment's statistics and predict upcoming events. By combining behavioral training and multisession fMRI in human participants (male and female), we track the corticostriatal mechanisms that mediate learning of temporal sequences as they change in structure complexity. We show that learning of predictive structures relates to individual decision strategy; that is, selecting the most probable outcome in a given context (maximizing) versus matching the exact sequence statistics. These strategies engage distinct human brain regions: maximizing engages dorsolateral prefrontal, cingulate, sensory-motor regions, and basal ganglia (dorsal caudate, putamen), whereas matching engages occipitotemporal regions (including the hippocampus) and basal ganglia (ventral caudate). Our findings provide evidence for distinct corticostriatal mechanisms that facilitate our ability to extract behaviorally relevant statistics to make predictions. SIGNIFICANCE STATEMENT Making predictions about future events relies on interpreting streams of information that may initially appear incomprehensible. Past work has studied how humans identify repetitive patterns and associative pairings. However, the natural environment contains regularities that vary in complexity from simple repetition to complex probabilistic combinations. Here, we combine behavior and multisession fMRI to track the brain mechanisms that mediate our ability to adapt to changes in the environment's statistics. We provide evidence for an alternate route for learning complex temporal statistics: extracting the most probable outcome in a given context is implemented by interactions between executive and motor corticostriatal mechanisms compared with visual corticostriatal circuits (including hippocampal cortex) that support learning of the exact temporal statistics. Copyright © 2017 Wang et al.

Adaptation and visual salience

PubMed Central

McDermott, Kyle C.; Malkoc, Gokhan; Mulligan, Jeffrey B.; Webster, Michael A.

2011-01-01

We examined how the salience of color is affected by adaptation to different color distributions. Observers searched for a color target on a dense background of distractors varying along different directions in color space. Prior adaptation to the backgrounds enhanced search on the same background while adaptation to orthogonal background directions slowed detection. Advantages of adaptation were seen for both contrast adaptation (to different color axes) and chromatic adaptation (to different mean chromaticities). Control experiments, including analyses of eye movements during the search, suggest that these aftereffects are unlikely to reflect simple learning or changes in search strategies on familiar backgrounds, and instead result from how adaptation alters the relative salience of the target and background colors. Comparable effects were observed along different axes in the chromatic plane or for axes defined by different combinations of luminance and chromatic contrast, consistent with visual search and adaptation mediated by multiple color mechanisms. Similar effects also occurred for color distributions characteristic of natural environments with strongly selective color gamuts. Our results are consistent with the hypothesis that adaptation may play an important functional role in highlighting the salience of novel stimuli by discounting ambient properties of the visual environment. PMID:21106682

Locomotor function after long-duration space flight: effects and motor learning during recovery.

PubMed

Mulavara, Ajitkumar P; Feiveson, Alan H; Fiedler, James; Cohen, Helen; Peters, Brian T; Miller, Chris; Brady, Rachel; Bloomberg, Jacob J

2010-05-01

Astronauts returning from space flight and performing Earth-bound activities must rapidly transition from the microgravity-adapted sensorimotor state to that of Earth's gravity. The goal of the current study was to assess locomotor dysfunction and recovery of function after long-duration space flight using a test of functional mobility. Eighteen International Space Station crewmembers experiencing an average flight duration of 185 days performed the functional mobility test (FMT) pre-flight and post-flight. To perform the FMT, subjects walked at a self selected pace through an obstacle course consisting of several pylons and obstacles set up on a base of 10-cm-thick, medium-density foam for a total of six trials per test session. The primary outcome measure was the time to complete the course (TCC, in seconds). To assess the long-term recovery trend of locomotor function after return from space flight, a multilevel exponential recovery model was fitted to the log-transformed TCC data. All crewmembers exhibited altered locomotor function after space flight, with a median 48% increase in the TCC. From the fitted model we calculated that a typical subject would recover to 95% of his/her pre-flight level at approximately 15 days post-flight. In addition, to assess the early motor learning responses after returning from space flight, we modeled performance over the six trials during the first post-flight session by a similar multilevel exponential relation. We found a significant positive correlation between measures of long-term recovery and early motor learning (P < 0.001) obtained from the respective models. We concluded that two types of recovery processes influence an astronaut's ability to re-adapt to Earth's gravity environment. Early motor learning helps astronauts make rapid modifications in their motor control strategies during the first hours after landing. Further, this early motor learning appears to reinforce the adaptive realignment, facilitating re-adaptation to Earth's 1-g environment on return from space flight.

Adaptation of Foreign Students to the Foreign Culture Learning Environment Using the Six Thinking Hats Method

ERIC Educational Resources Information Center

Stanislavovna, Vershinina Tatiana; Leopoldovna, Kocheva Olga

2015-01-01

The contemporary life is characterized by various ways and forms of communication, sometimes but not always successful and leading to conflict situations. When a man occurs in the environment, alien to him, he meets misunderstanding and is overwhelmed with incomprehensible emotions as if he were covered with an avalanche. He has to solve problems…

Exploring Two Teachers' Engagement with Their Students in an Online Writing Environment

ERIC Educational Resources Information Center

Annamalai, Nagaletchimee; Tan, Kok Eng

2015-01-01

Little research in the ESL context has examined the online teaching and learning activities in high schools. One main reason is the lack of appropriate theoretical framework rather than the learners or the environment. Using data from twelve high school students and two teachers from two Malaysian schools, the current study adapted Borup et al.'s…

Locomotor Dysfunction after Spaceflight: Characterization and Countermeasure Development

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; Cohen, H. S.; Peters, B. T.; Miller, C. A.; Brady, R.; Bloomberg, Jacob J.

2007-01-01

Astronauts returning from space flight show disturbances in locomotor control manifested by changes in various sub-systems including head-trunk coordination, dynamic visual acuity, lower limb muscle activation patterning and kinematics (Glasauer, et al., 1995; Bloomberg, et al., 1997; McDonald, et al., 1996; 1997; Layne, et al., 1997; 1998, 2001, 2004; Newman, et al., 1997; Bloomberg and Mulavara, 2003). These post flight changes in locomotor performance, due to neural adaptation to the microgravity conditions of space flight, affect the ability of crewmembers especially after a long duration mission to egress their vehicle and perform extravehicular activities soon after landing on Earth or following a landing on the surface of the Moon or Mars. At present, no operational training intervention is available pre- or in- flight to mitigate post flight locomotor disturbances. Our laboratory is currently developing a gait adaptability training program that is designed to facilitate recovery of locomotor function following a return to a gravitational environment. The training program exploits the ability of the sensorimotor system to generalize from exposure to multiple adaptive challenges during training so that the gait control system essentially "learns to learn" and therefore can reorganize more rapidly when faced with a novel adaptive challenge. Ultimately, the functional goal of an adaptive generalization countermeasure is not necessarily to immediately return movement patterns back to "normal". Rather the training regimen should facilitate the reorganization of available sensorimotor sub-systems to achieve safe and effective locomotion as soon as possible after space flight. We have previously confirmed that subjects participating in adaptive generalization training programs, using a variety of visuomotor distortions and different motor tasks from throwing to negotiating an obstacle course as the dependent measure, can learn to enhance their ability to adapt to a novel sensorimotor environment (Roller et al., 2001; Cohen et al. 2005). Importantly, this increased adaptability is retained even one month after completion of the training period. Our laboratory is currently developing adaptive generalization training procedures and the associated flight hardware to implement such a training program, using variations of visual flow, subject loading, and treadmill speed; during regular in-flight treadmill operations.

Illusory Reversal of Causality between Touch and Vision has No Effect on Prism Adaptation Rate.

PubMed

Tanaka, Hirokazu; Homma, Kazuhiro; Imamizu, Hiroshi

2012-01-01

Learning, according to Oxford Dictionary, is "to gain knowledge or skill by studying, from experience, from being taught, etc." In order to learn from experience, the central nervous system has to decide what action leads to what consequence, and temporal perception plays a critical role in determining the causality between actions and consequences. In motor adaptation, causality between action and consequence is implicitly assumed so that a subject adapts to a new environment based on the consequence caused by her action. Adaptation to visual displacement induced by prisms is a prime example; the visual error signal associated with the motor output contributes to the recovery of accurate reaching, and a delayed feedback of visual error can decrease the adaptation rate. Subjective feeling of temporal order of action and consequence, however, can be modified or even reversed when her sense of simultaneity is manipulated with an artificially delayed feedback. Our previous study (Tanaka et al., 2011; Exp. Brain Res.) demonstrated that the rate of prism adaptation was unaffected when the subjective delay of visual feedback was shortened. This study asked whether subjects could adapt to prism adaptation and whether the rate of prism adaptation was affected when the subjective temporal order was illusory reversed. Adapting to additional 100 ms delay and its sudden removal caused a positive shift of point of simultaneity in a temporal order judgment experiment, indicating an illusory reversal of action and consequence. We found that, even in this case, the subjects were able to adapt to prism displacement with the learning rate that was statistically indistinguishable to that without temporal adaptation. This result provides further evidence to the dissociation between conscious temporal perception and motor adaptation.

Communication and Control in Organizations: Applying the Work of James Thompson and Gregory Bateson to Interpretive Research.

DTIC Science & Technology

1985-07-01

learning ’, ’adaptations’, ’process’, and ’ abstraction ...hierarchy. Rather, he argues through a combina- tion of cybernetic epistemology, learning theory, and cognitive models, that patterned collective...systemic ability to perceive and respond to pattern and variance in the ’environment’. Each level of abstraction can be considered a ’meta’

Content and Language Integrated Learning in Higher Technical Education Using the "InGenio" Online Multimedia Authoring Tool

ERIC Educational Resources Information Center

Gimeno, Ana; Seiz, Rafael; de Siqueira, Jose Macario; Martinez, Antonio

2010-01-01

The future professional world of today's students is becoming a life-long learning process where they have to adapt to a changing market and an environment full of new opportunities and challenges. Thus, the development of a number of personal and professional skills, in addition to technical content and knowledge, is a crucial part of their…

Turkish Adaptation of the Educational-Learning Capital Questionnaire: Results for Gifted and Non-Gifted Students

ERIC Educational Resources Information Center

Leana-Tascilar, Marilena Z.

2016-01-01

The Actiotope Model of Giftedness (AMG) focuses on person--environment interactions to define giftedness. The development of the Questionnaire of Educational and Learning Capital (QELC) was based on the AMG. The first aim of this study was to present the reliability and validity of a Turkish version of the QELC for 10th grade students. The second…

Building adaptive connectionist-based controllers: review of experiments in human-robot interaction, collective robotics, and computational neuroscience

NASA Astrophysics Data System (ADS)

Billard, Aude

2000-10-01

This paper summarizes a number of experiments in biologically inspired robotics. The common feature to all experiments is the use of artificial neural networks as the building blocks for the controllers. The experiments speak in favor of using a connectionist approach for designing adaptive and flexible robot controllers, and for modeling neurological processes. I present 1) DRAMA, a novel connectionist architecture, which has general property for learning time series and extracting spatio-temporal regularities in multi-modal and highly noisy data; 2) Robota, a doll-shaped robot, which imitates and learns a proto-language; 3) an experiment in collective robotics, where a group of 4 to 15 Khepera robots learn dynamically the topography of an environment whose features change frequently; 4) an abstract, computational model of primate ability to learn by imitation; 5) a model for the control of locomotor gaits in a quadruped legged robot.

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

PubMed

Villaverde, Monica; Perez, David; Moreno, Felix

2015-11-17

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

Adapting physics courses in an engineering school to the b-learning philosophy

NASA Astrophysics Data System (ADS)

Borondo, J.; Benito, R. M.; Losada, J. C.

2014-09-01

In this paper we introduce the methodology that we have followed to convert traditional notes into interactive online materials. The idea behind this has been to make self-consistent and interactive online materials capable of motivating the students to get involved in the learning process. For this purpose, we have used the e-learning environment Moodle, which is a platform with a high interactivity potential. We conclude that the academic performance reaches its maximum when correctly combining self-organising with minimum teacher guidance.

An insula-frontostriatal network mediates flexible cognitive control by adaptively predicting changing control demands

PubMed Central

Jiang, Jiefeng; Beck, Jeffrey; Heller, Katherine; Egner, Tobias

2015-01-01

The anterior cingulate and lateral prefrontal cortices have been implicated in implementing context-appropriate attentional control, but the learning mechanisms underlying our ability to flexibly adapt the control settings to changing environments remain poorly understood. Here we show that human adjustments to varying control demands are captured by a reinforcement learner with a flexible, volatility-driven learning rate. Using model-based functional magnetic resonance imaging, we demonstrate that volatility of control demand is estimated by the anterior insula, which in turn optimizes the prediction of forthcoming demand in the caudate nucleus. The caudate's prediction of control demand subsequently guides the implementation of proactive and reactive attentional control in dorsal anterior cingulate and dorsolateral prefrontal cortices. These data enhance our understanding of the neuro-computational mechanisms of adaptive behaviour by connecting the classic cingulate-prefrontal cognitive control network to a subcortical control-learning mechanism that infers future demands by flexibly integrating remote and recent past experiences. PMID:26391305

Identifying clinical learning needs using structured group feedback: first year evaluation of pre-registration nursing and midwifery degree programmes.

PubMed

Frazer, Kate; Connolly, Michael; Naughton, Corina; Kow, Veronica

2014-07-01

Facilitating and supporting clinical learning for student nurses and midwives are essential within their practice environments. Clinical placements provide unique opportunities in preparation for future roles. Understanding the experiences of first year student nurses and midwives following clinical exposures and examining the clinical facilitators and barriers can assist in maintaining and developing clinical supports. The study used a structured group feedback approach with a convenience sample of 223 first year nursing and midwifery students in one Irish university in April 2011 to ascertain feedback on the clinical aspects of their degree programme. Approximately 200 students participated in the process. Two key clinical issues were identified by students: facilitating clinical learning and learning experiences and needs. Positive learning environments, supportive staff and increased opportunities for reflection were important issues for first year students. The role of supportive mentoring staff in clinical practice is essential to enhance student learning. Students value reflection in practice and require more opportunities to engage during placements. More collaborative approaches are required to ensure evolving and adapting practice environments can accommodate student learning. Copyright © 2014 Elsevier Ltd. All rights reserved.

Clipping in neurocontrol by adaptive dynamic programming.

PubMed

Fairbank, Michael; Prokhorov, Danil; Alonso, Eduardo

2014-10-01

In adaptive dynamic programming, neurocontrol, and reinforcement learning, the objective is for an agent to learn to choose actions so as to minimize a total cost function. In this paper, we show that when discretized time is used to model the motion of the agent, it can be very important to do clipping on the motion of the agent in the final time step of the trajectory. By clipping, we mean that the final time step of the trajectory is to be truncated such that the agent stops exactly at the first terminal state reached, and no distance further. We demonstrate that when clipping is omitted, learning performance can fail to reach the optimum, and when clipping is done properly, learning performance can improve significantly. The clipping problem we describe affects algorithms that use explicit derivatives of the model functions of the environment to calculate a learning gradient. These include backpropagation through time for control and methods based on dual heuristic programming. However, the clipping problem does not significantly affect methods based on heuristic dynamic programming, temporal differences learning, or policy-gradient learning algorithms.

The networked student: A design-based research case study of student constructed personal learning environments in a middle school science course

NASA Astrophysics Data System (ADS)

Drexler, Wendy

This design-based research case study applied a networked learning approach to a seventh grade science class at a public school in the southeastern United States. Students adapted emerging Web applications to construct personal learning environments for in-depth scientific inquiry of poisonous and venomous life forms. The personal learning environments constructed used Application Programming Interface (API) widgets to access, organize, and synthesize content from a number of educational Internet resources and social network connections. This study examined the nature of personal learning environments; the processes students go through during construction, and patterns that emerged. The project was documented from both an instructional and student-design perspective. Findings revealed that students applied the processes of: practicing digital responsibility; practicing digital literacy; organizing content; collaborating and socializing; and synthesizing and creating. These processes informed a model of the networked student that will serve as a framework for future instructional designs. A networked learning approach that incorporates these processes into future designs has implications for student learning, teacher roles, professional development, administrative policies, and delivery. This work is significant in that it shifts the focus from technology innovations based on tools to student empowerment based on the processes required to support learning. It affirms the need for greater attention to digital literacy and responsibility in K12 schools as well as consideration for those skills students will need to achieve success in the 21st century. The design-based research case study provides a set of design principles for teachers to follow when facilitating student construction of personal learning environments.

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

PubMed

Sudo, Akihito; Sato, Akihiro; Hasegawa, Osamu

2009-06-01

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

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.

College Philosophy and Teaching

ERIC Educational Resources Information Center

Nikolaros, John

2015-01-01

This article delineates critical practices for effective college teaching and learning. In addition, the author contends an internal transformation in philosophy, to facilitate a better college teaching environment. Moreover, a review and adaptation of Socratic paradigm techniques are included. The author outlines specific instructional and…

Hooks and Shifts: A Dialectical Study of Mediated Discovery

ERIC Educational Resources Information Center

Abrahamson, Dor; Trninic, Dragan; Gutierrez, Jose F.; Huth, Jacob; Lee, Rosa G.

2011-01-01

Radical constructivists advocate discovery-based pedagogical regimes that enable students to incrementally and continuously adapt their cognitive structures to the instrumented cultural environment. Some sociocultural theorists, however, maintain that learning implies discontinuity in conceptual development, because novices must appropriate expert…

Error amplification to promote motor learning and motivation in therapy robotics.

PubMed

Shirzad, Navid; Van der Loos, H F Machiel

2012-01-01

To study the effects of different feedback error amplification methods on a subject's upper-limb motor learning and affect during a point-to-point reaching exercise, we developed a real-time controller for a robotic manipulandum. The reaching environment was visually distorted by implementing a thirty degrees rotation between the coordinate systems of the robot's end-effector and the visual display. Feedback error amplification was provided to subjects as they trained to learn reaching within the visually rotated environment. Error amplification was provided either visually or through both haptic and visual means, each method with two different amplification gains. Subjects' performance (i.e., trajectory error) and self-reports to a questionnaire were used to study the speed and amount of adaptation promoted by each error amplification method and subjects' emotional changes. We found that providing haptic and visual feedback promotes faster adaptation to the distortion and increases subjects' satisfaction with the task, leading to a higher level of attentiveness during the exercise. This finding can be used to design a novel exercise regimen, where alternating between error amplification methods is used to both increase a subject's motor learning and maintain a minimum level of motivational engagement in the exercise. In future experiments, we will test whether such exercise methods will lead to a faster learning time and greater motivation to pursue a therapy exercise regimen.

Countermeasures to Enhance Sensorimotor Adaptability

NASA Technical Reports Server (NTRS)

Bloomberg, J. J.; Peters, B. T.; Mulavara, A. P.; Brady, R. A.; Batson, C. C.; Miller, C. A.; Cohen, H. S.

2011-01-01

During exploration-class missions, sensorimotor disturbances may lead to disruption in the ability to ambulate and perform functional tasks during the initial introduction to a novel gravitational environment following a landing on a planetary surface. The goal of our current project is to develop a sensorimotor adaptability (SA) training program to facilitate rapid adaptation to novel gravitational environments. We have developed a unique training system comprised of a treadmill placed on a motion-base facing a virtual visual scene that provides an unstable walking surface combined with incongruent visual flow designed to enhance sensorimotor adaptability. We have conducted a series of studies that have shown: Training using a combination of modified visual flow and support surface motion during treadmill walking enhances locomotor adaptability to a novel sensorimotor environment. Trained individuals become more proficient at performing multiple competing tasks while walking during adaptation to novel discordant sensorimotor conditions. Trained subjects can retain their increased level of adaptability over a six months period. SA training is effective in producing increased adaptability in a more complex over-ground ambulatory task on an obstacle course. This confirms that for a complex task like walking, treadmill training contains enough of the critical features of overground walking to be an effective training modality. The structure of individual training sessions can be optimized to promote fast/strategic motor learning. Training sessions that each contain short-duration exposures to multiple perturbation stimuli allows subjects to acquire a greater ability to rapidly reorganize appropriate response strategies when encountering a novel sensory environment. Individual sensory biases (i.e. increased visual dependency) can predict adaptive responses to novel sensory environments suggesting that customized training prescriptions can be developed to enhance adaptability. These results indicate that SA training techniques can be added to existing treadmill exercise equipment and procedures to produce a single integrated countermeasure system to improve performance of astro/cosmonauts during prolonged exploratory space missions.

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

ERIC Educational Resources Information Center

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

2016-01-01

Given current concerns internationally about student performance in science and the need to shift how science is being learnt in schools, as a community, we need to shift how we approach the issue of learning and teaching in science. In the future, we are going to have to close the gap between how students construct and engage with knowledge in a…

A New Concept Map Model for E-Learning Environments

NASA Astrophysics Data System (ADS)

Dattolo, Antonina; Luccio, Flaminia L.

Web-based education enables learners and teachers to access a wide quantity of continuously updated educational sources. In order to support the learning process, a system has to provide some fundamental features, such as simple mechanisms for the identification of the collection of “interesting” documents, adequate structures for storing, organizing and visualizing these documents, and appropriate mechanisms for creating personalized adaptive paths and views for learners.

A fast and precise indoor localization algorithm based on an online sequential extreme learning machine.

PubMed

Zou, Han; Lu, Xiaoxuan; Jiang, Hao; Xie, Lihua

2015-01-15

Nowadays, developing indoor positioning systems (IPSs) has become an attractive research topic due to the increasing demands on location-based service (LBS) in indoor environments. WiFi technology has been studied and explored to provide indoor positioning service for years in view of the wide deployment and availability of existing WiFi infrastructures in indoor environments. A large body of WiFi-based IPSs adopt fingerprinting approaches for localization. However, these IPSs suffer from two major problems: the intensive costs of manpower and time for offline site survey and the inflexibility to environmental dynamics. In this paper, we propose an indoor localization algorithm based on an online sequential extreme learning machine (OS-ELM) to address the above problems accordingly. The fast learning speed of OS-ELM can reduce the time and manpower costs for the offline site survey. Meanwhile, its online sequential learning ability enables the proposed localization algorithm to adapt in a timely manner to environmental dynamics. Experiments under specific environmental changes, such as variations of occupancy distribution and events of opening or closing of doors, are conducted to evaluate the performance of OS-ELM. The simulation and experimental results show that the proposed localization algorithm can provide higher localization accuracy than traditional approaches, due to its fast adaptation to various environmental dynamics.

Empowering Students in Science through Active Learning: Voices From Inside the Classroom

NASA Astrophysics Data System (ADS)

Erickson, Sabrina Ann

Preparing students for success in the 21st century has shifted the focus of science education from acquiring information and knowledge to mastery of critical thinking and problem-solving skills. The purpose of this qualitative case study was to examine teacher and student perspectives of the relationship between (a) active learning, problem solving, and achievement in science and (b) the conditions that help facilitate this environment. Adapting a social constructivist theoretical framework, high school science teachers and students were interviewed, school records analyzed, curriculum documents studied, and classes observed. The findings revealed that students were engaged with the material in an active learning environment, which led to a sense of involvement, interest, and meaningful learning. Students felt empowered to take ownership of their learning, developed the critical thinking skills necessary to solve problems independently and became aware of how they learn best, which students reported as interactive learning. Moreover, student reflections revealed that an active environment contributed to deeper understanding and higher skills through interaction and discussion, including questioning, explaining, arguing, and contemplating scientific concepts with their peers. Recommendations are for science teachers to provide opportunities for students to work actively, collaborate in groups, and discuss their ideas to develop the necessary skills for achievement and for administrators to facilitate the conditions needed for active learning to occur.

The effects of age, rank and neophobia on social learning in horses.

PubMed

Krueger, Konstanze; Farmer, Kate; Heinze, Jürgen

2014-05-01

Social learning is said to meet the demands of complex environments in which individuals compete over resources and cooperate to share resources. Horses (Equus caballus) were thought to lack social learning skills because they feed on homogenously distributed resources with few reasons for conflict. However, the horse's social environment is complex, which raises the possibility that its capacity for social transfer of feeding behaviour has been underestimated. We conducted a social learning experiment using 30 socially kept horses of different ages. Five horses, one from each group, were chosen as demonstrators, and the remaining 25 horses were designated observers. Observers from each group were allowed to watch their group demonstrator opening a feeding apparatus. We found that young, low-ranking and more exploratory horses learned by observing older members of their own group, and the older the horse, the more slowly it appeared to learn. Social learning may be an adaptive specialisation to the social environment. Older animals may avoid the potential costs of acquiring complex and potentially disadvantageous feeding behaviours from younger group members. We argue that horses show social learning in the context of their social ecology and that research procedures must take such contexts into account. Misconceptions about the horse's sociality may have hampered earlier studies.

Remediation to Restoration to Revitalization - Adaptive Learning in AOCs

EPA Science Inventory

The ability to recognize and articulate the value of ecosystem services is, at least in part, a function of the connection between an Area of Concern (aquatic environment) and the adjacent community (society). Ongoing contaminated sediment remediation and habitat restoration in G...

Physical Education Programming for Exceptional Learners.

ERIC Educational Resources Information Center

Folio, M. Rhonda

This book provides programming ideas, methods, strategies, and adaptations of the learning environment for implementing physical education programs for handicapped students. Part I, "Legislation and the Challenge," introduces Public Law 94-142, the Education for All Handicapped Children Act, its mandates, and its procedures for…

Interactive lecture demonstrations, active learning, and the ALOP project

NASA Astrophysics Data System (ADS)

Lakshminarayanan, Vasudevan

2011-05-01

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

Building a learning organisation in a child and adolescent mental health service.

PubMed

Birleson, P

1998-01-01

In recent business literature, the model of the learning organisation has been proposed as a solution to the problem of continually changing environments and increasing consumer expectations of maximum quality and value for money. The model seems highly appropriate for health services, which are staffed by educated professional staff who must become more adaptive and concerned with improving consumer outcomes. This case study describes how the principles of learning organisations have been applied to the design of a new structure and the creation of a learning culture within a mental health service for children and adolescents.

Enhancing astronaut performance using sensorimotor adaptability training.

PubMed

Bloomberg, Jacob J; Peters, Brian T; Cohen, Helen S; Mulavara, Ajitkumar P

2015-01-01

Astronauts experience disturbances in balance and gait function when they return to Earth. The highly plastic human brain enables individuals to modify their behavior to match the prevailing environment. Subjects participating in specially designed variable sensory challenge training programs can enhance their ability to rapidly adapt to novel sensory situations. This is useful in our application because we aim to train astronauts to rapidly formulate effective strategies to cope with the balance and locomotor challenges associated with new gravitational environments-enhancing their ability to "learn to learn." We do this by coupling various combinations of sensorimotor challenges with treadmill walking. A unique training system has been developed that is comprised of a treadmill mounted on a motion base to produce movement of the support surface during walking. This system provides challenges to gait stability. Additional sensory variation and challenge are imposed with a virtual visual scene that presents subjects with various combinations of discordant visual information during treadmill walking. This experience allows them to practice resolving challenging and conflicting novel sensory information to improve their ability to adapt rapidly. Information obtained from this work will inform the design of the next generation of sensorimotor countermeasures for astronauts.

A neural fuzzy controller learning by fuzzy error propagation

NASA Technical Reports Server (NTRS)

Nauck, Detlef; Kruse, Rudolf

1992-01-01

In this paper, we describe a procedure to integrate techniques for the adaptation of membership functions in a linguistic variable based fuzzy control environment by using neural network learning principles. This is an extension to our work. We solve this problem by defining a fuzzy error that is propagated back through the architecture of our fuzzy controller. According to this fuzzy error and the strength of its antecedent each fuzzy rule determines its amount of error. Depending on the current state of the controlled system and the control action derived from the conclusion, each rule tunes the membership functions of its antecedent and its conclusion. By this we get an unsupervised learning technique that enables a fuzzy controller to adapt to a control task by knowing just about the global state and the fuzzy error.

Policy improvement by a model-free Dyna architecture.

PubMed

Hwang, Kao-Shing; Lo, Chia-Yue

2013-05-01

The objective of this paper is to accelerate the process of policy improvement in reinforcement learning. The proposed Dyna-style system combines two learning schemes, one of which utilizes a temporal difference method for direct learning; the other uses relative values for indirect learning in planning between two successive direct learning cycles. Instead of establishing a complicated world model, the approach introduces a simple predictor of average rewards to actor-critic architecture in the simulation (planning) mode. The relative value of a state, defined as the accumulated differences between immediate reward and average reward, is used to steer the improvement process in the right direction. The proposed learning scheme is applied to control a pendulum system for tracking a desired trajectory to demonstrate its adaptability and robustness. Through reinforcement signals from the environment, the system takes the appropriate action to drive an unknown dynamic to track desired outputs in few learning cycles. Comparisons are made between the proposed model-free method, a connectionist adaptive heuristic critic, and an advanced method of Dyna-Q learning in the experiments of labyrinth exploration. The proposed method outperforms its counterparts in terms of elapsed time and convergence rate.

Climate change vulnerability assessments as catalysts for social learning: four case studies in south-eastern Australia

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

Preston, Benjamin L

2012-01-01

Technical assessments of vulnerability and/or risk are increasingly being undertaken to assess the impacts of climate change. Underlying this is the belief that they will bring clarity to questions regarding the scale of institutional investments required, plausible adaptation policies and measures, and the timing of their implementation. Despite the perceived importance of technical assessments in 'evidence-based' decision environments, assessments cannot be undertaken independent of values and politics, nor are they capable of eliminating the uncertainty that clouds decision-making on climate adaptation As such, assessments can trigger as many questions as they answer, leaving practitioners and stakeholders to question their value.more » This paper explores the value of vulnerability/risk assessments in climate change adaptation planning processes as a catalyst for learning in four case studies in Southeastern Australia. Data were collected using qualitative interviews with stakeholders involved in the assessments and analysed using a social learning framework. This analysis revealed that detailed and tangible strategies or actions often do not emerge directly from technical assessments. However, it also revealed that the assessments became important platforms for social learning. In providing these platforms, assessments present opportunities to question initial assumptions, explore multiple framings of an issue, generate new information, and galvanise support for collective actions. This study highlights the need for more explicit recognition and understanding of the important role social learning plays in climate change vulnerability assessments and adaptation planning more broadly.« less

Family Matters: Promoting the Academic Adaptation of Latino Youth in New and Established Destination.

PubMed

Spees, Lisa; Perreira, Krista M; Fuligni, Andrew

2017-03-01

As primary agents of socialization, families and schools can powerfully shape the academic adaptation of youth. Using data from the SIAA studies, we compare the family and school environments of Latino high school seniors living in a new destination, North Carolina, with those living in an established destination, Los Angeles. We then evaluate how family and school environments influence their educational aspirations, expectations, and performance. We find that parents' achievement expectations promote Latino youths' academic success while perceived future family obligations inhibit them. Additionally, we find that schools remain essential in promoting Latino immigrant youths' achievement by providing a supportive and safe learning environment. Discrimination in schools and the broader community is associated with lower educational expectations and aspirations but not lower academic performance.

A reductionist approach to the analysis of learning in brain-computer interfaces.

PubMed

Danziger, Zachary

2014-04-01

The complexity and scale of brain-computer interface (BCI) studies limit our ability to investigate how humans learn to use BCI systems. It also limits our capacity to develop adaptive algorithms needed to assist users with their control. Adaptive algorithm development is forced offline and typically uses static data sets. But this is a poor substitute for the online, dynamic environment where algorithms are ultimately deployed and interact with an adapting user. This work evaluates a paradigm that simulates the control problem faced by human subjects when controlling a BCI, but which avoids the many complications associated with full-scale BCI studies. Biological learners can be studied in a reductionist way as they solve BCI-like control problems, and machine learning algorithms can be developed and tested in closed loop with the subjects before being translated to full BCIs. The method is to map 19 joint angles of the hand (representing neural signals) to the position of a 2D cursor which must be piloted to displayed targets (a typical BCI task). An investigation is presented on how closely the joint angle method emulates BCI systems; a novel learning algorithm is evaluated, and a performance difference between genders is discussed.

Social Fear Learning: from Animal Models to Human Function.

PubMed

Debiec, Jacek; Olsson, Andreas

2017-07-01

Learning about potential threats is critical for survival. Learned fear responses are acquired either through direct experiences or indirectly through social transmission. Social fear learning (SFL), also known as vicarious fear learning, is a paradigm successfully used for studying the transmission of threat information between individuals. Animal and human studies have begun to elucidate the behavioral, neural and molecular mechanisms of SFL. Recent research suggests that social learning mechanisms underlie a wide range of adaptive and maladaptive phenomena, from supporting flexible avoidance in dynamic environments to intergenerational transmission of trauma and anxiety disorders. This review discusses recent advances in SFL studies and their implications for basic, social and clinical sciences. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Quality Education Challenge.

ERIC Educational Resources Information Center

Downey, Carolyn J.; And Others

Attempts to implement W. Edwards Deming's Total Quality Management (TQM) principles in education and transform school systems into world-class, quality learning environments have proved somewhat disappointing. This book asserts that educators need a way to translate the ideas about corporate quality for adaptation and use in schools. The…

"WGL," a Web Laboratory for Geometry

ERIC Educational Resources Information Center

Quaresma, Pedro; Santos, Vanda; Maric, Milena

2018-01-01

The role of information and communication technologies (ICT) in education is nowadays well recognised. The "Web Geometry Laboratory," is an e-learning, collaborative and adaptive, Web environment for geometry, integrating a well known dynamic geometry system. In a collaborative session, teachers and students, engaged in solving…

Institutional, Financial, Legal, and Cultural Factors in a Distance Learning Program.

PubMed

Blakeman, Rachel; Haseley, Dennis

2015-06-01

As psychoanalytic institutes evolve, adapting to the contemporary financial and social environment, the integration of new technologies into psychoanalytic education presents opportunities for expansion to candidates residing beyond the usual geographic boundaries. While the teaching of analytic content through distance learning programs appears to be relatively straightforward, factors including legalities, traditional mind-sets, and cross-cultural issues need to be considered as complicating the situation, as illustrated by one U.S. institute's distance learning initiative with a group in South Korea. © 2015 by the American Psychoanalytic Association.

Think Locally, Act Globally! Linking Local and Global Communities through Democracy and Environment. Hands-On! Developing Active Learning Modules on the Human Dimensions of Global Change.

ERIC Educational Resources Information Center

Dowler, Lorraine

Designed so that it can be adapted to a wide range of student abilities and institutional settings, this learning module on the human dimensions of global change seeks to: actively engage students in problem solving, challenge them to think critically, invite them to participate in the process of scientific inquiry, and involve them in cooperative…

Organisational adaptation in an activist network: social networks, leadership, and change in al-Muhajiroun.

PubMed

Kenney, Michael; Horgan, John; Horne, Cale; Vining, Peter; Carley, Kathleen M; Bigrigg, Michael W; Bloom, Mia; Braddock, Kurt

2013-09-01

Social networks are said to facilitate learning and adaptation by providing the connections through which network nodes (or agents) share information and experience. Yet, our understanding of how this process unfolds in real-world networks remains underdeveloped. This paper explores this gap through a case study of al-Muhajiroun, an activist network that continues to call for the establishment of an Islamic state in Britain despite being formally outlawed by British authorities. Drawing on organisation theory and social network analysis, we formulate three hypotheses regarding the learning capacity and social network properties of al-Muhajiroun (AM) and its successor groups. We then test these hypotheses using mixed methods. Our methods combine quantitative analysis of three agent-based networks in AM measured for structural properties that facilitate learning, including connectedness, betweenness centrality and eigenvector centrality, with qualitative analysis of interviews with AM activists focusing organisational adaptation and learning. The results of these analyses confirm that al-Muhajiroun activists respond to government pressure by changing their operations, including creating new platforms under different names and adjusting leadership roles among movement veterans to accommodate their spiritual leader's unwelcome exodus to Lebanon. Simple as they are effective, these adaptations have allowed al-Muhajiroun and its successor groups to continue their activism in an increasingly hostile environment. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Neuro Inspired Adaptive Perception and Control for Agile Mobility of Autonomous Vehicles in Uncertain and Hostile Environments

DTIC Science & Technology

2017-02-08

Georgia Tech Research Corporation 505 Tenth Street NW Atlanta, GA 30332 -0420 ABSTRACT Final Report: MURI: Neuro-Inspired Adaptive Perception and...Conquer Strategy for Optimal Trajectory Planning via Mixed-Integer Programming, IEEE Transactions on Robotics, (12 2015): 0. doi: 10.1109/TRO...Learning Day, Microsoft Corporation , Cambridge, MA, May 18, 2015. (c) Presentations 09/06/2015 09/08/2015 125 131 Ali Borji, Dicky N. Sihite, Laurent Itti

Intelligent control based on fuzzy logic and neural net theory

NASA Technical Reports Server (NTRS)

Lee, Chuen-Chien

1991-01-01

In the conception and design of intelligent systems, one promising direction involves the use of fuzzy logic and neural network theory to enhance such systems' capability to learn from experience and adapt to changes in an environment of uncertainty and imprecision. Here, an intelligent control scheme is explored by integrating these multidisciplinary techniques. A self-learning system is proposed as an intelligent controller for dynamical processes, employing a control policy which evolves and improves automatically. One key component of the intelligent system is a fuzzy logic-based system which emulates human decision making behavior. It is shown that the system can solve a fairly difficult control learning problem. Simulation results demonstrate that improved learning performance can be achieved in relation to previously described systems employing bang-bang control. The proposed system is relatively insensitive to variations in the parameters of the system environment.

A cholinergic feedback circuit to regulate striatal population uncertainty and optimize reinforcement learning.

PubMed

Franklin, Nicholas T; Frank, Michael J

2015-12-25

Convergent evidence suggests that the basal ganglia support reinforcement learning by adjusting action values according to reward prediction errors. However, adaptive behavior in stochastic environments requires the consideration of uncertainty to dynamically adjust the learning rate. We consider how cholinergic tonically active interneurons (TANs) may endow the striatum with such a mechanism in computational models spanning three Marr's levels of analysis. In the neural model, TANs modulate the excitability of spiny neurons, their population response to reinforcement, and hence the effective learning rate. Long TAN pauses facilitated robustness to spurious outcomes by increasing divergence in synaptic weights between neurons coding for alternative action values, whereas short TAN pauses facilitated stochastic behavior but increased responsiveness to change-points in outcome contingencies. A feedback control system allowed TAN pauses to be dynamically modulated by uncertainty across the spiny neuron population, allowing the system to self-tune and optimize performance across stochastic environments.

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

NASA Astrophysics Data System (ADS)

Judd, Jeffrey S.

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

Coupling internal cerebellar models enhances online adaptation and supports offline consolidation in sensorimotor tasks

PubMed Central

Passot, Jean-Baptiste; Luque, Niceto R.; Arleo, Angelo

2013-01-01

The cerebellum is thought to mediate sensorimotor adaptation through the acquisition of internal models of the body-environment interaction. These representations can be of two types, identified as forward and inverse models. The first predicts the sensory consequences of actions, while the second provides the correct commands to achieve desired state transitions. In this paper, we propose a composite architecture consisting of multiple cerebellar internal models to account for the adaptation performance of humans during sensorimotor learning. The proposed model takes inspiration from the cerebellar microcomplex circuit, and employs spiking neurons to process information. We investigate the intrinsic properties of the cerebellar circuitry subserving efficient adaptation properties, and we assess the complementary contributions of internal representations by simulating our model in a procedural adaptation task. Our simulation results suggest that the coupling of internal models enhances learning performance significantly (compared with independent forward and inverse models), and it allows for the reproduction of human adaptation capabilities. Furthermore, we provide a computational explanation for the performance improvement observed after one night of sleep in a wide range of sensorimotor tasks. We predict that internal model coupling is a necessary condition for the offline consolidation of procedural memories. PMID:23874289

Design of a completely model free adaptive control in the presence of parametric, non-parametric uncertainties and random control signal delay.

PubMed

Tutsoy, Onder; Barkana, Duygun Erol; Tugal, Harun

2018-05-01

In this paper, an adaptive controller is developed for discrete time linear systems that takes into account parametric uncertainty, internal-external non-parametric random uncertainties, and time varying control signal delay. Additionally, the proposed adaptive control is designed in such a way that it is utterly model free. Even though these properties are studied separately in the literature, they are not taken into account all together in adaptive control literature. The Q-function is used to estimate long-term performance of the proposed adaptive controller. Control policy is generated based on the long-term predicted value, and this policy searches an optimal stabilizing control signal for uncertain and unstable systems. The derived control law does not require an initial stabilizing control assumption as in the ones in the recent literature. Learning error, control signal convergence, minimized Q-function, and instantaneous reward are analyzed to demonstrate the stability and effectiveness of the proposed adaptive controller in a simulation environment. Finally, key insights on parameters convergence of the learning and control signals are provided. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Preparing new nurses with complexity science and problem-based learning.

PubMed

Hodges, Helen F

2011-01-01

Successful nurses function effectively with adaptability, improvability, and interconnectedness, and can see emerging and unpredictable complex problems. Preparing new nurses for complexity requires a significant change in prevalent but dated nursing education models for rising graduates. The science of complexity coupled with problem-based learning and peer review contributes a feasible framework for a constructivist learning environment to examine real-time systems data; explore uncertainty, inherent patterns, and ambiguity; and develop skills for unstructured problem solving. This article describes a pilot study of a problem-based learning strategy guided by principles of complexity science in a community clinical nursing course. Thirty-five senior nursing students participated during a 3-year period. Assessments included peer review, a final project paper, reflection, and a satisfaction survey. Results were higher than expected levels of student satisfaction, increased breadth and analysis of complex data, acknowledgment of community as complex adaptive systems, and overall higher level thinking skills than in previous years. 2011, SLACK Incorporated.

Genetic algorithm learning in a New Keynesian macroeconomic setup.

PubMed

Hommes, Cars; Makarewicz, Tomasz; Massaro, Domenico; Smits, Tom

2017-01-01

In order to understand heterogeneous behavior amongst agents, empirical data from Learning-to-Forecast (LtF) experiments can be used to construct learning models. This paper follows up on Assenza et al. (2013) by using a Genetic Algorithms (GA) model to replicate the results from their LtF experiment. In this GA model, individuals optimize an adaptive, a trend following and an anchor coefficient in a population of general prediction heuristics. We replicate experimental treatments in a New-Keynesian environment with increasing complexity and use Monte Carlo simulations to investigate how well the model explains the experimental data. We find that the evolutionary learning model is able to replicate the three different types of behavior, i.e. convergence to steady state, stable oscillations and dampened oscillations in the treatments using one GA model. Heterogeneous behavior can thus be explained by an adaptive, anchor and trend extrapolating component and the GA model can be used to explain heterogeneous behavior in LtF experiments with different types of complexity.

Cerebellar-M1 Connectivity Changes Associated with Motor Learning Are Somatotopic Specific.

PubMed

Spampinato, Danny A; Block, Hannah J; Celnik, Pablo A

2017-03-01

One of the functions of the cerebellum in motor learning is to predict and account for systematic changes to the body or environment. This form of adaptive learning is mediated by plastic changes occurring within the cerebellar cortex. The strength of cerebellar-to-cerebral pathways for a given muscle may reflect aspects of cerebellum-dependent motor adaptation. These connections with motor cortex (M1) can be estimated as cerebellar inhibition (CBI): a conditioning pulse of transcranial magnetic stimulation delivered to the cerebellum before a test pulse over motor cortex. Previously, we have demonstrated that changes in CBI for a given muscle representation correlate with learning a motor adaptation task with the involved limb. However, the specificity of these effects is unknown. Here, we investigated whether CBI changes in humans are somatotopy specific and how they relate to motor adaptation. We found that learning a visuomotor rotation task with the right hand changed CBI, not only for the involved first dorsal interosseous of the right hand, but also for an uninvolved right leg muscle, the tibialis anterior, likely related to inter-effector transfer of learning. In two follow-up experiments, we investigated whether the preparation of a simple hand or leg movement would produce a somatotopy-specific modulation of CBI. We found that CBI changes only for the effector involved in the movement. These results indicate that learning-related changes in cerebellar-M1 connectivity reflect a somatotopy-specific interaction. Modulation of this pathway is also present in the context of interlimb transfer of learning. SIGNIFICANCE STATEMENT Connectivity between the cerebellum and motor cortex is a critical pathway for the integrity of everyday movements and understanding the somatotopic specificity of this pathway in the context of motor learning is critical to advancing the efficacy of neurorehabilitation. We found that adaptive learning with the hand affects cerebellar-motor cortex connectivity, not only for the trained hand, but also for an untrained leg muscle, an effect likely related to intereffector transfer of learning. Furthermore, we introduce a novel method to measure cerebellar-motor cortex connectivity during movement preparation. With this technique, we show that, outside the context of learning, modulation of cerebellar-motor cortex connectivity is somatotopically specific to the effector being moved. Copyright © 2017 the authors 0270-6474/17/372377-10$15.00/0.

Learning gait of quadruped robot without prior knowledge of the environment

NASA Astrophysics Data System (ADS)

Xu, Tao; Chen, Qijun

2012-09-01

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

Design of cognitive engine for cognitive radio based on the rough sets and radial basis function neural network

NASA Astrophysics Data System (ADS)

Yang, Yanchao; Jiang, Hong; Liu, Congbin; Lan, Zhongli

2013-03-01

Cognitive radio (CR) is an intelligent wireless communication system which can dynamically adjust the parameters to improve system performance depending on the environmental change and quality of service. The core technology for CR is the design of cognitive engine, which introduces reasoning and learning methods in the field of artificial intelligence, to achieve the perception, adaptation and learning capability. Considering the dynamical wireless environment and demands, this paper proposes a design of cognitive engine based on the rough sets (RS) and radial basis function neural network (RBF_NN). The method uses experienced knowledge and environment information processed by RS module to train the RBF_NN, and then the learning model is used to reconfigure communication parameters to allocate resources rationally and improve system performance. After training learning model, the performance is evaluated according to two benchmark functions. The simulation results demonstrate the effectiveness of the model and the proposed cognitive engine can effectively achieve the goal of learning and reconfiguration in cognitive radio.

Confidence and psychosis: a neuro-computational account of contingency learning disruption by NMDA blockade

PubMed Central

Vinckier, F; Gaillard, R; Palminteri, S; Rigoux, L; Salvador, A; Fornito, A; Adapa, R; Krebs, M O; Pessiglione, M; Fletcher, P C

2016-01-01

A state of pathological uncertainty about environmental regularities might represent a key step in the pathway to psychotic illness. Early psychosis can be investigated in healthy volunteers under ketamine, an NMDA receptor antagonist. Here, we explored the effects of ketamine on contingency learning using a placebo-controlled, double-blind, crossover design. During functional magnetic resonance imaging, participants performed an instrumental learning task, in which cue-outcome contingencies were probabilistic and reversed between blocks. Bayesian model comparison indicated that in such an unstable environment, reinforcement learning parameters are downregulated depending on confidence level, an adaptive mechanism that was specifically disrupted by ketamine administration. Drug effects were underpinned by altered neural activity in a fronto-parietal network, which reflected the confidence-based shift to exploitation of learned contingencies. Our findings suggest that an early characteristic of psychosis lies in a persistent doubt that undermines the stabilization of behavioral policy resulting in a failure to exploit regularities in the environment. PMID:26055423

Confidence and psychosis: a neuro-computational account of contingency learning disruption by NMDA blockade.

PubMed

Vinckier, F; Gaillard, R; Palminteri, S; Rigoux, L; Salvador, A; Fornito, A; Adapa, R; Krebs, M O; Pessiglione, M; Fletcher, P C

2016-07-01

A state of pathological uncertainty about environmental regularities might represent a key step in the pathway to psychotic illness. Early psychosis can be investigated in healthy volunteers under ketamine, an NMDA receptor antagonist. Here, we explored the effects of ketamine on contingency learning using a placebo-controlled, double-blind, crossover design. During functional magnetic resonance imaging, participants performed an instrumental learning task, in which cue-outcome contingencies were probabilistic and reversed between blocks. Bayesian model comparison indicated that in such an unstable environment, reinforcement learning parameters are downregulated depending on confidence level, an adaptive mechanism that was specifically disrupted by ketamine administration. Drug effects were underpinned by altered neural activity in a fronto-parietal network, which reflected the confidence-based shift to exploitation of learned contingencies. Our findings suggest that an early characteristic of psychosis lies in a persistent doubt that undermines the stabilization of behavioral policy resulting in a failure to exploit regularities in the environment.

Embodied niche construction in the hominin lineage: semiotic structure and sustained attention in human embodied cognition

PubMed Central

Stutz, Aaron J.

2014-01-01

Human evolution unfolded through a rather distinctive, dynamically constructed ecological niche. The human niche is not only generally terrestrial in habitat, while being flexibly and extensively heterotrophic in food-web connections. It is also defined by semiotically structured and structuring embodied cognitive interfaces, connecting the individual organism with the wider environment. The embodied dimensions of niche-population co-evolution have long involved semiotic system construction, which I hypothesize to be an evolutionarily primitive aspect of learning and higher-level cognitive integration and attention in the great apes and humans alike. A clearly pre-linguistic form of semiotic cognitive structuration is suggested to involve recursively learned and constructed object icons. Higher-level cognitive iconic representation of visually, auditorily, or haptically perceived extrasomatic objects would be learned and evoked through indexical connections to proprioceptive and affective somatic states. Thus, private cognitive signs would be defined, not only by their learned and perceived extrasomatic referents, but also by their associations to iconically represented somatic states. This evolutionary modification of animal associative learning is suggested to be adaptive in ecological niches occupied by long-lived, large-bodied ape species, facilitating memory construction and recall in highly varied foraging and social contexts, while sustaining selective attention during goal-directed behavioral sequences. The embodied niche construction (ENC) hypothesis of human evolution posits that in the early hominin lineage, natural selection further modified the ancestral ape semiotic adaptations, favoring the recursive structuration of concise iconic narratives of embodied interaction with the environment. PMID:25136323

Embodied niche construction in the hominin lineage: semiotic structure and sustained attention in human embodied cognition.

PubMed

Stutz, Aaron J

2014-01-01

Human evolution unfolded through a rather distinctive, dynamically constructed ecological niche. The human niche is not only generally terrestrial in habitat, while being flexibly and extensively heterotrophic in food-web connections. It is also defined by semiotically structured and structuring embodied cognitive interfaces, connecting the individual organism with the wider environment. The embodied dimensions of niche-population co-evolution have long involved semiotic system construction, which I hypothesize to be an evolutionarily primitive aspect of learning and higher-level cognitive integration and attention in the great apes and humans alike. A clearly pre-linguistic form of semiotic cognitive structuration is suggested to involve recursively learned and constructed object icons. Higher-level cognitive iconic representation of visually, auditorily, or haptically perceived extrasomatic objects would be learned and evoked through indexical connections to proprioceptive and affective somatic states. Thus, private cognitive signs would be defined, not only by their learned and perceived extrasomatic referents, but also by their associations to iconically represented somatic states. This evolutionary modification of animal associative learning is suggested to be adaptive in ecological niches occupied by long-lived, large-bodied ape species, facilitating memory construction and recall in highly varied foraging and social contexts, while sustaining selective attention during goal-directed behavioral sequences. The embodied niche construction (ENC) hypothesis of human evolution posits that in the early hominin lineage, natural selection further modified the ancestral ape semiotic adaptations, favoring the recursive structuration of concise iconic narratives of embodied interaction with the environment.

Adaptive Tracking Control for Robots With an Interneural Computing Scheme.

PubMed

Tsai, Feng-Sheng; Hsu, Sheng-Yi; Shih, Mau-Hsiang

2018-04-01

Adaptive tracking control of mobile robots requires the ability to follow a trajectory generated by a moving target. The conventional analysis of adaptive tracking uses energy minimization to study the convergence and robustness of the tracking error when the mobile robot follows a desired trajectory. However, in the case that the moving target generates trajectories with uncertainties, a common Lyapunov-like function for energy minimization may be extremely difficult to determine. Here, to solve the adaptive tracking problem with uncertainties, we wish to implement an interneural computing scheme in the design of a mobile robot for behavior-based navigation. The behavior-based navigation adopts an adaptive plan of behavior patterns learning from the uncertainties of the environment. The characteristic feature of the interneural computing scheme is the use of neural path pruning with rewards and punishment interacting with the environment. On this basis, the mobile robot can be exploited to change its coupling weights in paths of neural connections systematically, which can then inhibit or enhance the effect of flow elimination in the dynamics of the evolutionary neural network. Such dynamical flow translation ultimately leads to robust sensory-to-motor transformations adapting to the uncertainties of the environment. A simulation result shows that the mobile robot with the interneural computing scheme can perform fault-tolerant behavior of tracking by maintaining suitable behavior patterns at high frequency levels.

Bacterial computing: a form of natural computing and its applications

PubMed Central

Lahoz-Beltra, Rafael; Navarro, Jorge; Marijuán, Pedro C.

2014-01-01

The capability to establish adaptive relationships with the environment is an essential characteristic of living cells. Both bacterial computing and bacterial intelligence are two general traits manifested along adaptive behaviors that respond to surrounding environmental conditions. These two traits have generated a variety of theoretical and applied approaches. Since the different systems of bacterial signaling and the different ways of genetic change are better known and more carefully explored, the whole adaptive possibilities of bacteria may be studied under new angles. For instance, there appear instances of molecular “learning” along the mechanisms of evolution. More in concrete, and looking specifically at the time dimension, the bacterial mechanisms of learning and evolution appear as two different and related mechanisms for adaptation to the environment; in somatic time the former and in evolutionary time the latter. In the present chapter it will be reviewed the possible application of both kinds of mechanisms to prokaryotic molecular computing schemes as well as to the solution of real world problems. PMID:24723912

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Generic skills in medical education: developing the tools for successful lifelong learning.

PubMed

Murdoch-Eaton, Deborah; Whittle, Sue

2012-01-01

Higher education has invested in defining the role of generic skills in developing effective, adaptable graduates fit for a changing workplace. Research confirms that the development of generic skills that underpin effectiveness and adaptability in graduates is highly context-dependent and is shaped by the discipline within which these skills are conceptualised, valued and taught. This places the responsibility for generic skills enhancement clearly within the remit of global medical education. Many factors will influence the skill set with which students begin their medical training and experience at entry needs to be taken into account. Learning and teaching environments enhance effective skill development through active learning, teaching for understanding, feedback, and teacher-student and student-student interaction. Medical curricula need to provide students with opportunities to practise and develop their generic skills in a range of discipline-specific contexts. Curricular design should include explicit and integrated generic skills objectives against which students' progress can be monitored. Assessment and feedback serve as valuable reinforcements of the professed importance of generic skills to both learner and teacher, and will encourage students to self-evaluate and take responsibility for their own skill development. The continual need for students to modify their practice in response to changes in their environment and the requirements of their roles will help students to develop the ability to transfer these skills at transition points in their training and future careers. If they are to take their place in an ever-changing profession, medical students need to be competent in the skills that underpin lifelong learning. Only then will the doctors of the future be well placed to adapt to changes in knowledge, update their practice in line with the changing evidence base, and continue to contribute effectively as societal needs change. © Blackwell Publishing Ltd 2012.

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 beginning of 2018. Providing tailored instruction to health professionals and students is a priority in order to optimize learning and clinical outcomes. This systematic review will synthesize the best available evidence regarding the effectiveness of AEEs in improving knowledge, competence, and behavior in health professionals and students. It will provide guidance to policy makers, hospital managers, and researchers in terms of AEE development, implementation, and evaluation in health care. ©Guillaume Fontaine, Sylvie Cossette, Marc-André Maheu-Cadotte, Tanya Mailhot, Marie-France Deschênes, Gabrielle Mathieu-Dupuis. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 05.07.2017.

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 in progress. We plan to submit the results in the beginning of 2018. Conclusions Providing tailored instruction to health professionals and students is a priority in order to optimize learning and clinical outcomes. This systematic review will synthesize the best available evidence regarding the effectiveness of AEEs in improving knowledge, competence, and behavior in health professionals and students. It will provide guidance to policy makers, hospital managers, and researchers in terms of AEE development, implementation, and evaluation in health care. Trial Registration PROSPERO International Prospective Register of Systematic Reviews: CRD42017065585; https://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42017065585 (Archived by WebCite® at http://www.webcitation.org/6rXGdDwf4) PMID:28679491

Localization Transition Induced by Learning in Random Searches

NASA Astrophysics Data System (ADS)

Falcón-Cortés, Andrea; Boyer, Denis; Giuggioli, Luca; Majumdar, Satya N.

2017-10-01

We solve an adaptive search model where a random walker or Lévy flight stochastically resets to previously visited sites on a d -dimensional lattice containing one trapping site. Because of reinforcement, a phase transition occurs when the resetting rate crosses a threshold above which nondiffusive stationary states emerge, localized around the inhomogeneity. The threshold depends on the trapping strength and on the walker's return probability in the memoryless case. The transition belongs to the same class as the self-consistent theory of Anderson localization. These results show that similarly to many living organisms and unlike the well-studied Markovian walks, non-Markov movement processes can allow agents to learn about their environment and promise to bring adaptive solutions in search tasks.

Match and mismatch: conservation physiology, nutritional ecology and the timescales of biological adaptation

PubMed Central

Raubenheimer, David; Simpson, Stephen J.; Tait, Alice H.

2012-01-01

Conservation physiology (CP) and nutritional ecology (NE) are both integrative sciences that share the fundamental aim of understanding the patterns, mechanisms and consequences of animal responses to changing environments. Here, we explore the high-level similarities and differences between CP and NE, identifying as central themes to both fields the multiple timescales over which animals adapt (and fail to adapt) to their environments, and the need for integrative models to study these processes. At one extreme are the short-term regulatory responses that modulate the state of animals in relation to the environment, which are variously considered under the concepts of homeostasis, homeorhesis, enantiostasis, heterostasis and allostasis. In the longer term are developmental responses, including phenotypic plasticity and transgenerational effects mediated by non-genomic influences such as parental physiology, epigenetic effects and cultural learning. Over a longer timescale still are the cumulative genetic changes that take place in Darwinian evolution. We present examples showing how the adaptive responses of animals across these timescales have been represented in an integrative framework from NE, the geometric framework (GF) for nutrition, and close with an illustration of how GF can be applied to the central issue in CP, animal conservation. PMID:22566672

Match and mismatch: conservation physiology, nutritional ecology and the timescales of biological adaptation.

PubMed

Raubenheimer, David; Simpson, Stephen J; Tait, Alice H

2012-06-19

Conservation physiology (CP) and nutritional ecology (NE) are both integrative sciences that share the fundamental aim of understanding the patterns, mechanisms and consequences of animal responses to changing environments. Here, we explore the high-level similarities and differences between CP and NE, identifying as central themes to both fields the multiple timescales over which animals adapt (and fail to adapt) to their environments, and the need for integrative models to study these processes. At one extreme are the short-term regulatory responses that modulate the state of animals in relation to the environment, which are variously considered under the concepts of homeostasis, homeorhesis, enantiostasis, heterostasis and allostasis. In the longer term are developmental responses, including phenotypic plasticity and transgenerational effects mediated by non-genomic influences such as parental physiology, epigenetic effects and cultural learning. Over a longer timescale still are the cumulative genetic changes that take place in Darwinian evolution. We present examples showing how the adaptive responses of animals across these timescales have been represented in an integrative framework from NE, the geometric framework (GF) for nutrition, and close with an illustration of how GF can be applied to the central issue in CP, animal conservation.

A Fast and Precise Indoor Localization Algorithm Based on an Online Sequential Extreme Learning Machine †

PubMed Central

Zou, Han; Lu, Xiaoxuan; Jiang, Hao; Xie, Lihua

2015-01-01

Nowadays, developing indoor positioning systems (IPSs) has become an attractive research topic due to the increasing demands on location-based service (LBS) in indoor environments. WiFi technology has been studied and explored to provide indoor positioning service for years in view of the wide deployment and availability of existing WiFi infrastructures in indoor environments. A large body of WiFi-based IPSs adopt fingerprinting approaches for localization. However, these IPSs suffer from two major problems: the intensive costs of manpower and time for offline site survey and the inflexibility to environmental dynamics. In this paper, we propose an indoor localization algorithm based on an online sequential extreme learning machine (OS-ELM) to address the above problems accordingly. The fast learning speed of OS-ELM can reduce the time and manpower costs for the offline site survey. Meanwhile, its online sequential learning ability enables the proposed localization algorithm to adapt in a timely manner to environmental dynamics. Experiments under specific environmental changes, such as variations of occupancy distribution and events of opening or closing of doors, are conducted to evaluate the performance of OS-ELM. The simulation and experimental results show that the proposed localization algorithm can provide higher localization accuracy than traditional approaches, due to its fast adaptation to various environmental dynamics. PMID:25599427

Spatial education: improving conservation delivery through space-structured decision making

USGS Publications Warehouse

Moore, Clinton T.; Shaffer, Terry L.; Gannon, Jill J.

2013-01-01

Adaptive management is a form of structured decision making designed to guide management of natural resource systems when their behaviors are uncertain. Where decision making can be replicated across units of a landscape, learning can be accelerated, and biological processes can be understood in a larger spatial context. Broad-based partnerships among land management agencies, exemplified by Landscape Conservation Cooperatives (conservation partnerships created through the U.S. Department of the Interior), are potentially ideal environments for implementing spatially structured adaptive management programs.

Primary Care Practice Development: A Relationship-Centered Approach

PubMed Central

Miller, William L.; Crabtree, Benjamin F.; Nutting, Paul A.; Stange, Kurt C.; Jaén, Carlos Roberto

2010-01-01

PURPOSE Numerous primary care practice development efforts, many related to the patient-centered medical home (PCMH), are emerging across the United States with few guides available to inform them. This article presents a relationship-centered practice development approach to understand practice and to aid in fostering practice development to advance key attributes of primary care that include access to first-contact care, comprehensive care, coordination of care, and a personal relationship over time. METHODS Informed by complexity theory and relational theories of organizational learning, we built on discoveries from the American Academy of Family Physicians’ National Demonstration Project (NDP) and 15 years of research to understand and improve primary care practice. RESULTS Primary care practices can fruitfully be understood as complex adaptive systems consisting of a core (a practice’s key resources, organizational structure, and functional processes), adaptive reserve (practice features that enhance resilience, such as relationships), and attentiveness to the local environment. The effectiveness of these attributes represents the practice’s internal capability. With adequate motivation, healthy, thriving practices advance along a pathway of slow, continuous developmental change with occasional rapid periods of transformation as they evolve better fits with their environment. Practice development is enhanced through systematically using strategies that involve setting direction and boundaries, implementing sensing systems, focusing on creative tensions, and fostering learning conversations. CONCLUSIONS Successful practice development begins with changes that strengthen practices’ core, build adaptive reserve, and expand attentiveness to the local environment. Development progresses toward transformation through enhancing primary care attributes. PMID:20530396

Neural Mechanisms for Adaptive Learned Avoidance of Mental Effort.

PubMed

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

2018-02-05

Humans tend to avoid mental effort. Previous studies have demonstrated this tendency using various demand-selection tasks; participants generally avoid options associated with higher cognitive demand. However, it remains unclear whether humans avoid mental effort adaptively in uncertain and non-stationary environments, and if so, what neural mechanisms underlie this learned avoidance and whether they remain the same irrespective of cognitive-demand types. We addressed these issues by developing novel demand-selection tasks where associations between choice options and cognitive-demand levels change over time, with two variations using mental arithmetic and spatial reasoning problems (29:4 and 18:2 males:females). Most participants showed avoidance, and their choices depended on the demand experienced on multiple preceding trials. We assumed that participants updated the expected cost of mental effort through experience, and fitted their choices by reinforcement learning models, comparing several possibilities. Model-based fMRI analyses revealed that activity in the dorsomedial and lateral frontal cortices was positively correlated with the trial-by-trial expected cost for the chosen option commonly across the different types of cognitive demand, and also revealed a trend of negative correlation in the ventromedial prefrontal cortex. We further identified correlates of cost-prediction-error at time of problem-presentation or answering the problem, the latter of which partially overlapped with or were proximal to the correlates of expected cost at time of choice-cue in the dorsomedial frontal cortex. These results suggest that humans adaptively learn to avoid mental effort, having neural mechanisms to represent expected cost and cost-prediction-error, and the same mechanisms operate for various types of cognitive demand. SIGNIFICANCE STATEMENT In daily life, humans encounter various cognitive demands, and tend to avoid high-demand options. However, it remains unclear whether humans avoid mental effort adaptively under dynamically changing environments, and if so, what are the underlying neural mechanisms and whether they operate irrespective of cognitive-demand types. To address these issues, we developed novel tasks, where participants could learn to avoid high-demand options under uncertain and non-stationary environments. Through model-based fMRI analyses, we found regions whose activity was correlated with the expected mental effort cost, or cost-prediction-error, regardless of demand-type, with overlap or adjacence in the dorsomedial frontal cortex. This finding contributes to clarifying the mechanisms for cognitive-demand avoidance, and provides empirical building blocks for the emerging computational theory of mental effort. Copyright © 2018 the authors.

Adaptive Behavioral Outcomes: Assurance of Learning and Assessment

ERIC Educational Resources Information Center

Baker, David S.; Stewart, Geoffrey T.

2012-01-01

Business schools are currently being criticized for lacking relevance to the applied working environment in which students are supposed to be prepared to make immediate contributions and reasoned independent decisions in a fluidly changing market (Haskell and Beliveau, 2010, and Michlitsch and Sidle, 2002). While technical skills (accounting,…

Adaptive or Transactional Leadership in Current Higher Education: A Brief Comparison

ERIC Educational Resources Information Center

Khan, Natalie

2017-01-01

Higher education institutions operate in a complex environment that includes influence from external factors, new technologies for teaching and learning, globalization, and changing student demographics to name a few. Maneuvering such complexity and change requires a leadership strategy that is flexible and supportive. This paper reviews two…

Training Implications for Our Graying Work Force.

ERIC Educational Resources Information Center

Clark, Susan K.

1994-01-01

Discusses future increases in the number of older employees in the workforce; outlines physiological changes in vision, hearing, and memory that are known to occur as part of the aging process; and suggests training adaptations to diminish or eliminate the adverse consequences of these changes in a learning environment. (LRW)

Technology Leadership Preparedness: Principals' Perceptions

ERIC Educational Resources Information Center

Metcalf, Wendy; LaFrance, Jason

2013-01-01

Adopting technology in the K-12 classroom is evolving from adapting lessons that highlight a technology to pervasive use of interactive and handheld devices. In this environment, school leaders have the complex task of incorporating technologies to enhance teaching and learning. The purpose of this quasi-experimental quantitative study was to…

Trading Places: When Teachers Utilize Student Expertise in Technology-Intensive Classrooms.

ERIC Educational Resources Information Center

Ringstaff, Cathy; And Others

Utilizing self-report data from 32 elementary and secondary teachers, this longitudinal, qualitative study examines the role shifts of both teachers and students as they adapted to teaching and learning in educational, technology-rich, Apple Classrooms of Tomorrow environments. At first, teachers in these instructionally innovative classrooms…

Personalization in an Interactive Learning Environment through a Virtual Character

ERIC Educational Resources Information Center

Reategui, E.; Boff, E.; Campbell, J. A.

2008-01-01

Traditional hypermedia applications present the same content and provide identical navigational support to all users. Adaptive Hypermedia Systems (AHS) make it possible to construct personalized presentations to each user, according to preferences and needs identified. We present in this paper an alternative approach to educational AHS where a…

Orientation/Time Management Skill Training Lesson: Development and Evaluation. Final Report.

ERIC Educational Resources Information Center

Dobrovolny, Jacqueline L.; And Others

A lesson was developed containing materials designed to assist students in their adaptation to the novelties of a computer assisted or managed instructional environment, providing students with appropriate role models for increasing acceptance of their increased responsibility for learning and introducing a progress tracking approach to assist…

Case Study in Modeling Accessibility for Online Instruction

ERIC Educational Resources Information Center

Conway, Thomas Hayes

2017-01-01

The purpose of this qualitative multiple case study was to explore how accessibility standards are adapted to create online learning environments that are accessible to people who use assistive technology, or have navigational challenges due to physical or intellectual disabilities. Rogers diffusion of innovation was used as the contextual…

Potential of Audiographic Computerized Telelearning for Distance Extension Education.

ERIC Educational Resources Information Center

Verma, Satish; And Others

In the last 10 years, an approach to electronic distance education called audiographic computerized telelearning using standard telephone lines has come to the fore. Telelearning is a cost-effective system which optimizes existing computer facilities and creates a teaching-learning environment that is interactive, efficient, and adaptable to a…

The Effect of Differentiated Instruction on Standardized Assessment Performance of Students in the Middle School Mathematics Classroom

ERIC Educational Resources Information Center

Williams, Kimberly Gail

2012-01-01

Changing demographics, student diversity, and increased accountability have compelled educators to challenge the uniform constraints of traditional instruction and create an environment focused on individual achievement. Differentiated instruction empowers teachers to target multiple learning styles through varied themes, adapted content delivery,…

Skills for Innovation and Research

ERIC Educational Resources Information Center

OECD Publishing (NJ3), 2011

2011-01-01

Innovation holds the key to ongoing improvements in living standards, as well as to solving pressing social challenges. Skilled people play a crucial role in innovation through the new knowledge they generate, how they adopt and develop existing ideas, and through their ability to learn new competencies and adapt to a changing environment. This…

Age of Creative Insecurity: Student-Centered Learning. Historical Paper 7

ERIC Educational Resources Information Center

Martell, Charles

2015-01-01

Trapped by inflexible mechanisms, many institutions are unable to adapt smoothly to the changing expectations and needs of their clients. Our educational system is particularly out-of-sync. Student-centered teaching--participative education--through unstructuring is one method for encouraging a flexible, creative, classroom environment. However,…

Key Factors for Developing a Cross-Cultural Education Program

ERIC Educational Resources Information Center

Yang, Keeyung; Chung, Sock H.

2015-01-01

Purpose: As universities and colleges face an increasingly global environment, internationalization is viewed as a critical aspect of education, a fact that has significant academic and economic implications for higher educational institutions worldwide which need to be current with cultural education to adapt to change. Learning from other…

Common-Sense Classroom Management: Surviving September and Beyond in the Elementary Classroom.

ERIC Educational Resources Information Center

Lindberg, Jill A.; Swick, April M.

This manual contains techniques for creating successful teaching and learning environments in diverse elementary classrooms. Using humor, drawings, and a conversational tone, it provides suggestions for teaching effectively and efficiently. Special highlights include five-steps-or-less strategies that can be adapted into any classroom, an outline…

Reimagining Christian Higher Education

ERIC Educational Resources Information Center

Hulme, E. Eileen; Groom, David E., Jr.; Heltzel, Joseph M.

2016-01-01

The challenges facing higher education continue to mount. The shifting of the U.S. ethnic and racial demographics, the proliferation of advanced digital technologies and data, and the move from traditional degrees to continuous learning platforms have created an unstable environment to which Christian higher education must adapt in order to remain…

What Learning Environments Help Improve Decision-Making?

ERIC Educational Resources Information Center

O'Connor, Donna; Larkin, Paul; Williams, A. Mark

2017-01-01

Background: Decision-making is a key component of performance in sport. However, there has been minimal investigation of how coaches may adapt practice sessions to specifically develop decision-making. Purpose: The aim in this exploratory study was to investigate the pedagogical approaches coaches use to develop decision-making in soccer. Method:…

Biomechanical Reconstruction Using the Tacit Learning System: Intuitive Control of Prosthetic Hand Rotation.

PubMed

Oyama, Shintaro; Shimoda, Shingo; Alnajjar, Fady S K; Iwatsuki, Katsuyuki; Hoshiyama, Minoru; Tanaka, Hirotaka; Hirata, Hitoshi

2016-01-01

Background: For mechanically reconstructing human biomechanical function, intuitive proportional control, and robustness to unexpected situations are required. Particularly, creating a functional hand prosthesis is a typical challenge in the reconstruction of lost biomechanical function. Nevertheless, currently available control algorithms are in the development phase. The most advanced algorithms for controlling multifunctional prosthesis are machine learning and pattern recognition of myoelectric signals. Despite the increase in computational speed, these methods cannot avoid the requirement of user consciousness and classified separation errors. "Tacit Learning System" is a simple but novel adaptive control strategy that can self-adapt its posture to environment changes. We introduced the strategy in the prosthesis rotation control to achieve compensatory reduction, as well as evaluated the system and its effects on the user. Methods: We conducted a non-randomized study involving eight prosthesis users to perform a bar relocation task with/without Tacit Learning System support. Hand piece and body motions were recorded continuously with goniometers, videos, and a motion-capture system. Findings: Reduction in the participants' upper extremity rotatory compensation motion was monitored during the relocation task in all participants. The estimated profile of total body energy consumption improved in five out of six participants. Interpretation: Our system rapidly accomplished nearly natural motion without unexpected errors. The Tacit Learning System not only adapts human motions but also enhances the human ability to adapt to the system quickly, while the system amplifies compensation generated by the residual limb. The concept can be extended to various situations for reconstructing lost functions that can be compensated.

Learning predictive statistics from temporal sequences: Dynamics and strategies

PubMed Central

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E.; Kourtzi, Zoe

2017-01-01

Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations. How do we learn these structures? Here we investigate the dynamics of structure learning by tracking human responses to temporal sequences that change in structure unbeknownst to the participants. Participants were asked to predict the upcoming item following a probabilistic sequence of symbols. Using a Markov process, we created a family of sequences, from simple frequency statistics (e.g., some symbols are more probable than others) to context-based statistics (e.g., symbol probability is contingent on preceding symbols). We demonstrate the dynamics with which individuals adapt to changes in the environment's statistics—that is, they extract the behaviorally relevant structures to make predictions about upcoming events. Further, we show that this structure learning relates to individual decision strategy; faster learning of complex structures relates to selection of the most probable outcome in a given context (maximizing) rather than matching of the exact sequence statistics. Our findings provide evidence for alternate routes to learning of behaviorally relevant statistics that facilitate our ability to predict future events in variable environments. PMID:28973111

Learning predictive statistics from temporal sequences: Dynamics and strategies.

PubMed

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe

2017-10-01

Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations. How do we learn these structures? Here we investigate the dynamics of structure learning by tracking human responses to temporal sequences that change in structure unbeknownst to the participants. Participants were asked to predict the upcoming item following a probabilistic sequence of symbols. Using a Markov process, we created a family of sequences, from simple frequency statistics (e.g., some symbols are more probable than others) to context-based statistics (e.g., symbol probability is contingent on preceding symbols). We demonstrate the dynamics with which individuals adapt to changes in the environment's statistics-that is, they extract the behaviorally relevant structures to make predictions about upcoming events. Further, we show that this structure learning relates to individual decision strategy; faster learning of complex structures relates to selection of the most probable outcome in a given context (maximizing) rather than matching of the exact sequence statistics. Our findings provide evidence for alternate routes to learning of behaviorally relevant statistics that facilitate our ability to predict future events in variable environments.

Adaptive Critic Nonlinear Robust Control: A Survey.

PubMed

Wang, Ding; He, Haibo; Liu, Derong

2017-10-01

Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H ∞ control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.

Normative evidence accumulation in unpredictable environments

PubMed Central

Glaze, Christopher M; Kable, Joseph W; Gold, Joshua I

2015-01-01

In our dynamic world, decisions about noisy stimuli can require temporal accumulation of evidence to identify steady signals, differentiation to detect unpredictable changes in those signals, or both. Normative models can account for learning in these environments but have not yet been applied to faster decision processes. We present a novel, normative formulation of adaptive learning models that forms decisions by acting as a leaky accumulator with non-absorbing bounds. These dynamics, derived for both discrete and continuous cases, depend on the expected rate of change of the statistics of the evidence and balance signal identification and change detection. We found that, for two different tasks, human subjects learned these expectations, albeit imperfectly, then used them to make decisions in accordance with the normative model. The results represent a unified, empirically supported account of decision-making in unpredictable environments that provides new insights into the expectation-driven dynamics of the underlying neural signals. DOI: http://dx.doi.org/10.7554/eLife.08825.001 PMID:26322383

A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load

NASA Astrophysics Data System (ADS)

Zhang, Wei; Li, Chuanhao; Peng, Gaoliang; Chen, Yuanhang; Zhang, Zhujun

2018-02-01

In recent years, intelligent fault diagnosis algorithms using machine learning technique have achieved much success. However, due to the fact that in real world industrial applications, the working load is changing all the time and noise from the working environment is inevitable, degradation of the performance of intelligent fault diagnosis methods is very serious. In this paper, a new model based on deep learning is proposed to address the problem. Our contributions of include: First, we proposed an end-to-end method that takes raw temporal signals as inputs and thus doesn't need any time consuming denoising preprocessing. The model can achieve pretty high accuracy under noisy environment. Second, the model does not rely on any domain adaptation algorithm or require information of the target domain. It can achieve high accuracy when working load is changed. To understand the proposed model, we will visualize the learned features, and try to analyze the reasons behind the high performance of the model.

Creating Successful Scientist-Teacher-Student Collaborations: Examples From the GLOBE Program

NASA Astrophysics Data System (ADS)

Geary, E.; Wright, E.; Yule, S.; Randolph, G.; Larsen, J.; Smith, D.

2007-12-01

Actively engaging students in research on the environment at local, regional, and globe scales is a primary objective of the GLOBE (Global Learning and Observations to Benefit the Environment) Program. During the past 18 months, GLOBE, an international education and science program in 109 countries and tens of thousands of schools worldwide, has been working with four NSF-funded Earth System Science Projects to involve K-12 students, teachers, and scientists in collaborative research investigations of Seasons and Biomes, the Carbon Cycle, Local and Extreme Environments, and Watersheds. This talk will discuss progress to date in each of these investigation areas and highlight successes and challenges in creating effective partnerships between diverse scientific and educational stakeholders. More specifically we will discuss lessons learned in the following areas: (a) mutual goal and responsibility setting, (b) resource allocation, (c) development of adaptable learning activities, tools, and services, (d) creation of scientist and school networks, and (e) development of evaluation metrics, all in support of student research.

A junction-tree based learning algorithm to optimize network wide traffic control: A coordinated multi-agent framework

DOE PAGES

Zhu, Feng; Aziz, H. M. Abdul; Qian, Xinwu; ...

2015-01-31

Our study develops a novel reinforcement learning algorithm for the challenging coordinated signal control problem. Traffic signals are modeled as intelligent agents interacting with the stochastic traffic environment. The model is built on the framework of coordinated reinforcement learning. The Junction Tree Algorithm (JTA) based reinforcement learning is proposed to obtain an exact inference of the best joint actions for all the coordinated intersections. Moreover, the algorithm is implemented and tested with a network containing 18 signalized intersections in VISSIM. Finally, our results show that the JTA based algorithm outperforms independent learning (Q-learning), real-time adaptive learning, and fixed timing plansmore » in terms of average delay, number of stops, and vehicular emissions at the network level.« less

Learning algorithms for human-machine interfaces.

PubMed

Danziger, Zachary; Fishbach, Alon; Mussa-Ivaldi, Ferdinando A

2009-05-01

The goal of this study is to create and examine machine learning algorithms that adapt in a controlled and cadenced way to foster a harmonious learning environment between the user and the controlled device. To evaluate these algorithms, we have developed a simple experimental framework. Subjects wear an instrumented data glove that records finger motions. The high-dimensional glove signals remotely control the joint angles of a simulated planar two-link arm on a computer screen, which is used to acquire targets. A machine learning algorithm was applied to adaptively change the transformation between finger motion and the simulated robot arm. This algorithm was either LMS gradient descent or the Moore-Penrose (MP) pseudoinverse transformation. Both algorithms modified the glove-to-joint angle map so as to reduce the endpoint errors measured in past performance. The MP group performed worse than the control group (subjects not exposed to any machine learning), while the LMS group outperformed the control subjects. However, the LMS subjects failed to achieve better generalization than the control subjects, and after extensive training converged to the same level of performance as the control subjects. These results highlight the limitations of coadaptive learning using only endpoint error reduction.

Learning Algorithms for Human–Machine Interfaces

PubMed Central

Fishbach, Alon; Mussa-Ivaldi, Ferdinando A.

2012-01-01

The goal of this study is to create and examine machine learning algorithms that adapt in a controlled and cadenced way to foster a harmonious learning environment between the user and the controlled device. To evaluate these algorithms, we have developed a simple experimental framework. Subjects wear an instrumented data glove that records finger motions. The high-dimensional glove signals remotely control the joint angles of a simulated planar two-link arm on a computer screen, which is used to acquire targets. A machine learning algorithm was applied to adaptively change the transformation between finger motion and the simulated robot arm. This algorithm was either LMS gradient descent or the Moore–Penrose (MP) pseudoinverse transformation. Both algorithms modified the glove-to-joint angle map so as to reduce the endpoint errors measured in past performance. The MP group performed worse than the control group (subjects not exposed to any machine learning), while the LMS group outperformed the control subjects. However, the LMS subjects failed to achieve better generalization than the control subjects, and after extensive training converged to the same level of performance as the control subjects. These results highlight the limitations of coadaptive learning using only endpoint error reduction. PMID:19203886

Place versus response learning in fish: a comparison between species.

PubMed

McAroe, Claire L; Craig, Cathy M; Holland, Richard A

2016-01-01

Place learning is thought to be an adaptive and flexible facet of navigation. Due to the flexibility of this learning, it is thought to be more complex than the simpler strategies such as learning a particular route or navigating through the use of cues. Place learning is crucial in a familiar environment as it allows an individual to successfully navigate to the same endpoint, regardless of where in the environment the journey begins. Much of the research to date focusing on different strategies employed for navigation has used human subjects or other mammals such as rodents. In this series of experiments, the spatial memory of four different species of fish (goldfish, killifish, zebrafish and Siamese fighting fish) was analysed using a plus maze set-up. Results suggest that three of the species showed a significant preference for the adoption of a place strategy during this task, whereas zebrafish showed no significant preference. Furthermore, zebrafish took significantly longer to learn the task than the other species. Finally, results suggest that zebrafish took the least amount of time (seconds) to complete trials both during training and probe.

Experiences and lessons learned for planning and supply of micronutrient powders interventions

PubMed Central

Schauer, Claudia; Sunley, Nigel; Nyhus Dhillon, Christina; Roca, Claudia; Tapia, Gustavo; Mathema, Pragya; Walton, Shelley; Situma, Ruth; Zlotkin, Stanley; DW Klemm, Rolf

2017-01-01

Abstract Realistic planning for a nutrition intervention is a critical component of implementation, yet effective approaches have been poorly documented. Under the auspices of “The Micronutrient Powders Consultation: Lessons Learned for Operational Guidance,” 3 working groups were formed to summarize experiences and lessons across countries regarding micronutrient powders (MNP) interventions for young children. This paper focuses on programmatic experiences in the planning stages of an MNP intervention, encompassing assessment, enabling environment and adaptation, as well as considerations for supply. Methods included a review of published and grey literature, key informant interviews, and deliberations throughout the consultation process. We found that assessments helped justify adopting an MNP intervention, but these assessments were often limited by their narrow scope and inadequate data. Establishing coordinating bodies and integrating MNP into existing policies and programmes have helped foster an enabling environment and support programme stability. Formative research and pilots have been used to adapt MNP interventions to specific contexts, but they have been insufficient to inform scale‐up. In terms of supply, most countries have opted to procure MNP through international suppliers, but this still requires understanding and navigating the local regulatory environment at the earliest stages of an intervention. Overall, these findings indicate that although some key planning and supply activities are generally undertaken, improvements are needed to plan for effective scale‐up. Much still needs to be learned on MNP planning, and we propose a set of research questions that require further investigation. PMID:28960875

Software evolution. What kind of evolution?

NASA Astrophysics Data System (ADS)

Torres-Carbonell, J. J.; Parets-Llorca, J.

2001-06-01

Most Software Systems capable of adapting to the environment or of performing some kind of adaptive activity (such as pattern learning, behavior simulations and the like) use concepts and models from Biology. Nevertheless, such approaches are based on the Modern Synthesis, i.e., Darwinism plus Mendelism, and this implies preadaptive mutations in, and subsequent selection of the better adapted individuals. These pre-adaptive changes usually do not produce the desired effect, are virtually useless and require some kind of backtracking for the system to obtain profit from adaptation. It is our contention that an evolutionary approach in Software Systems development cannot be based on pre-adaptive mutations, but rather on post-adaptive ones, that is, anticipatory mutations and modifications (Lamarkism). A novel way of understanding evolution in Software Systems based on applied Lamarkism is presented and a framework that allows the incorporation of modifications according to the necessities of the system and the will of the modeller is proposed.

Partial Adaptation of Obtained and Observed Value Signals Preserves Information about Gains and Losses

PubMed Central

Baddeley, Michelle; Tobler, Philippe N.; Schultz, Wolfram

2016-01-01

Given that the range of rewarding and punishing outcomes of actions is large but neural coding capacity is limited, efficient processing of outcomes by the brain is necessary. One mechanism to increase efficiency is to rescale neural output to the range of outcomes expected in the current context, and process only experienced deviations from this expectation. However, this mechanism comes at the cost of not being able to discriminate between unexpectedly low losses when times are bad versus unexpectedly high gains when times are good. Thus, too much adaptation would result in disregarding information about the nature and absolute magnitude of outcomes, preventing learning about the longer-term value structure of the environment. Here we investigate the degree of adaptation in outcome coding brain regions in humans, for directly experienced outcomes and observed outcomes. We scanned participants while they performed a social learning task in gain and loss blocks. Multivariate pattern analysis showed two distinct networks of brain regions adapt to the most likely outcomes within a block. Frontostriatal areas adapted to directly experienced outcomes, whereas lateral frontal and temporoparietal regions adapted to observed social outcomes. Critically, in both cases, adaptation was incomplete and information about whether the outcomes arose in a gain block or a loss block was retained. Univariate analysis confirmed incomplete adaptive coding in these regions but also detected nonadapting outcome signals. Thus, although neural areas rescale their responses to outcomes for efficient coding, they adapt incompletely and keep track of the longer-term incentives available in the environment. SIGNIFICANCE STATEMENT Optimal value-based choice requires that the brain precisely and efficiently represents positive and negative outcomes. One way to increase efficiency is to adapt responding to the most likely outcomes in a given context. However, too strong adaptation would result in loss of precise representation (e.g., when the avoidance of a loss in a loss-context is coded the same as receipt of a gain in a gain-context). We investigated an intermediate form of adaptation that is efficient while maintaining information about received gains and avoided losses. We found that frontostriatal areas adapted to directly experienced outcomes, whereas lateral frontal and temporoparietal regions adapted to observed social outcomes. Importantly, adaptation was intermediate, in line with influential models of reference dependence in behavioral economics. PMID:27683899

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

NASA Astrophysics Data System (ADS)

Bay, John S.

1995-12-01

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

Embodying a cognitive model in a mobile robot

NASA Astrophysics Data System (ADS)

Benjamin, D. Paul; Lyons, Damian; Lonsdale, Deryle

2006-10-01

The ADAPT project is a collaboration of researchers in robotics, linguistics and artificial intelligence at three universities to create a cognitive architecture specifically designed to be embodied in a mobile robot. There are major respects in which existing cognitive architectures are inadequate for robot cognition. In particular, they lack support for true concurrency and for active perception. ADAPT addresses these deficiencies by modeling the world as a network of concurrent schemas, and modeling perception as problem solving. Schemas are represented using the RS (Robot Schemas) language, and are activated by spreading activation. RS provides a powerful language for distributed control of concurrent processes. Also, The formal semantics of RS provides the basis for the semantics of ADAPT's use of natural language. We have implemented the RS language in Soar, a mature cognitive architecture originally developed at CMU and used at a number of universities and companies. Soar's subgoaling and learning capabilities enable ADAPT to manage the complexity of its environment and to learn new schemas from experience. We describe the issues faced in developing an embodied cognitive architecture, and our implementation choices.

An incremental knowledge assimilation system (IKAS) for mine detection

NASA Astrophysics Data System (ADS)

Porway, Jake; Raju, Chaitanya; Varadarajan, Karthik Mahesh; Nguyen, Hieu; Yadegar, Joseph

2010-04-01

In this paper we present an adaptive incremental learning system for underwater mine detection and classification that utilizes statistical models of seabed texture and an adaptive nearest-neighbor classifier to identify varied underwater targets in many different environments. The first stage of processing uses our Background Adaptive ANomaly detector (BAAN), which identifies statistically likely target regions using Gabor filter responses over the image. Using this information, BAAN classifies the background type and updates its detection using background-specific parameters. To perform classification, a Fully Adaptive Nearest Neighbor (FAAN) determines the best label for each detection. FAAN uses an extremely fast version of Nearest Neighbor to find the most likely label for the target. The classifier perpetually assimilates new and relevant information into its existing knowledge database in an incremental fashion, allowing improved classification accuracy and capturing concept drift in the target classes. Experiments show that the system achieves >90% classification accuracy on underwater mine detection tasks performed on synthesized datasets provided by the Office of Naval Research. We have also demonstrated that the system can incrementally improve its detection accuracy by constantly learning from new samples.

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

Differential diagnosis and management of human-directed aggression in cats.

PubMed

Frank, Diane; Dehasse, Joel

2003-03-01

Human-directed aggression in cats should be evaluated as a multifactorial problem. It results from the combined actions of heredity, environment, learning, human social requirements (or needs), client interactions, lack of understanding of normal feline behavior, unrealistic client expectations, and lack of meeting the cat's basic ethologic needs. Managing human-directed aggression in cats encompasses the use of environmental modification, therapies, and, when and if needed, regulatory drugs so as to increase learning capabilities and adaptation and decrease danger to the human victims.

Describing the on-line graduate science student: An examination of learning style, learning strategy, and motivation

NASA Astrophysics Data System (ADS)

Spevak, Arlene J.

Research in science education has presented investigations and findings related to the significance of particular learning variables. For example, the factors of learning style, learning strategy and motivational orientation have been shown to have considerable impact upon learning in a traditional classroom setting. Although these data have been somewhat generous for the face-to-face learning situation, this does not appear to be the case for distance education, particularly the Internet-based environment. The purpose of this study was to describe the on-line graduate science student, regarding the variables of learning style, learning strategy and motivational orientation. It was believed that by understanding the characteristics of adult science learners and by identifying their learning needs, Web course designers and science educators could create on-line learning programs that best utilized students' strengths in learning science. A case study method using a questionnaire, inventories, telephone interviews and documents was applied to nine graduate science students who participated for ten weeks in an asynchronous, exclusively Internet mediated graduate science course at a large, Northeastern university. Within-case and cross-case analysis indicated that these learners displayed several categories of learning styles as well as learning strategies. The students also demonstrated high levels of both intrinsic and extrinsic motivation, and this, together with varying strategy use, may have compensated for any mismatch between their preferred learning styles and their learning environment. Recommendations include replicating this study in other online graduate science courses, administration of learning style and learning strategy inventories to perspective online graduate science students, incorporation of synchronous communication into on-line science courses, and implementation of appropriate technology that supports visual and kinesthetic learners. Although the study was limited to nine participants, the implications of the findings are clear. Most adult science students experience learning in an on-line environment. Those who are independent, highly motivated learners and utilize a variety of learning strategies can adapt their learning style to the situational aspects of the learning environment. This further indicates that Internet-based graduate science education institutions should become aware of different learning styles and strategies, and be prepared to address this variety when developing and delivering such programming.

Brief Report: Evaluation of an Intelligent Learning Environment for Young Children with Autism Spectrum Disorder.

PubMed

Zheng, Zhi; Warren, Zachary; Weitlauf, Amy; Fu, Qiang; Zhao, Huan; Swanson, Amy; Sarkar, Nilanjan

2016-11-01

Researchers are increasingly attempting to develop and apply innovative technological platforms for early detection and intervention of autism spectrum disorder (ASD). This pilot study designed and evaluated a novel technologically-mediated intelligent learning environment with relevance to early social orienting skills. The environment was endowed with the capacity to administer social orienting cues and adaptively respond to autonomous real-time measurement of performance (i.e., non-contact gaze measurement). We evaluated the system with both toddlers with ASD (n = 8) as well as typically developing infants (n = 8). Children in both groups were able to ultimately respond accurately to social prompts delivered by the technological system. Results also indicated that the system was capable of attracting and pushing toward correct performance autonomously without user intervention.

A model of influences on the clinical learning environment: the case for change at one U.S. medical school.

PubMed

Fleit, Howard B; Iuli, Richard J; Fischel, Janet E; Lu, Wei-Hsin; Chandran, Latha

2017-03-23

The learning environment within a school of medicine influences medical students' values and their professional development. Despite national requirements to monitor the learning environment, mistreatment of medical students persists. We designed a program called WE SMILE: We can Eradicate Student Mistreatment In the Learning Environment with a vision to enhance trainee and faculty awareness and ultimately eliminate medical student mistreatment. We provide a description of our program and early outcomes. The program has enhanced student awareness of what constitutes mistreatment and how to report it. Faculty members are also aware of the formal processes and procedures for review of such incidents. Our proposed model of influences on the learning environment and the clinical workforce informs the quality of trainee education and safety of patient care. Institutional leadership and culture play a prominent role in this model. Our integrated institutional response to learning environment concerns is offered as a strategy to improve policy awareness, reporting and management of student mistreatment concerns. Our WE SMILE program was developed to enhance education and awareness of what constitutes mistreatment and to provide multiple pathways for student reporting, with clear responsibilities for review, adjudication and enforcement. The program is demonstrating several signs of early success and is offered as a strategy for other schools to adopt or adapt. We have recognized a delicate balance between preserving student anonymity and informing them of specific actions taken. Providing students and other stakeholders with clear evidence of institutional response and accountability remains a key challenge. Multiple methods of reporting have been advantageous in eliciting information on learning environment infringements. These routes and types of reporting have enhanced our understanding of student perceptions and the specific contexts in which mistreatment occurs, allowing for targeted interventions. A common platform across the healthcare professions to report and review concerns has afforded us opportunities to deal with interprofessional issues in a respectful and trustworthy manner. We offer a model of learning environment influences with leadership and institutional culture at the helm, as a way to frame a comprehensive perspective on this challenging and complex concern.

Beyond Risk and Protective Factors: An Adaptation-Based Approach to Resilience.

PubMed

Ellis, Bruce J; Bianchi, JeanMarie; Griskevicius, Vladas; Frankenhuis, Willem E

2017-07-01

How does repeated or chronic childhood adversity shape social and cognitive abilities? According to the prevailing deficit model, children from high-stress backgrounds are at risk for impairments in learning and behavior, and the intervention goal is to prevent, reduce, or repair the damage. Missing from this deficit approach is an attempt to leverage the unique strengths and abilities that develop in response to high-stress environments. Evolutionary-developmental models emphasize the coherent, functional changes that occur in response to stress over the life course. Research in birds, rodents, and humans suggests that developmental exposures to stress can improve forms of attention, perception, learning, memory, and problem solving that are ecologically relevant in harsh-unpredictable environments (as per the specialization hypothesis). Many of these skills and abilities, moreover, are primarily manifest in currently stressful contexts where they would provide the greatest fitness-relevant advantages (as per the sensitization hypothesis). This perspective supports an alternative adaptation-based approach to resilience that converges on a central question: "What are the attention, learning, memory, problem-solving, and decision-making strategies that are enhanced through exposures to childhood adversity?" At an applied level, this approach focuses on how we can work with, rather than against, these strengths to promote success in education, employment, and civic life.

Learning for sustainability among faith-based organizations in Kenya.

PubMed

Moyer, Joanne M; Sinclair, A John; Diduck, Alan P

2014-08-01

The complex and unpredictable contexts in which environmental and development work take place require an adaptable, learning approach. Faith-based organizations (FBOs) play a significant role in sustainability work around the world, and provide a unique setting in which to study learning. This paper explores individual learning for sustainability within two FBOs engaged in sustainability work in Kenya. Learning outcomes covered a broad range of areas, including the sustainability framework, environment/conservation, skills, community work, interpersonal engagement, and personal and faith development. These outcomes were acquired through embodied experience and activity, facilitation by the workplace, interpersonal interaction, personal reflection, and Bible study and worship. Grounded categories were compared to learning domains and processes described by Mezirow's transformative learning theory. The findings indicate that for learning in the sustainability field, instrumental learning and embodied learning processes are particularly important, and consequently they require greater attention in the theory when applied in this field.

Learning for Sustainability Among Faith-Based Organizations in Kenya

NASA Astrophysics Data System (ADS)

Moyer, Joanne M.; Sinclair, A. John; Diduck, Alan P.

2014-08-01

The complex and unpredictable contexts in which environmental and development work take place require an adaptable, learning approach. Faith-based organizations (FBOs) play a significant role in sustainability work around the world, and provide a unique setting in which to study learning. This paper explores individual learning for sustainability within two FBOs engaged in sustainability work in Kenya. Learning outcomes covered a broad range of areas, including the sustainability framework, environment/conservation, skills, community work, interpersonal engagement, and personal and faith development. These outcomes were acquired through embodied experience and activity, facilitation by the workplace, interpersonal interaction, personal reflection, and Bible study and worship. Grounded categories were compared to learning domains and processes described by Mezirow's transformative learning theory. The findings indicate that for learning in the sustainability field, instrumental learning and embodied learning processes are particularly important, and consequently they require greater attention in the theory when applied in this field.

Study of application of adaptive systems to the exploration of the solar system. Volume 1: Summary

NASA Technical Reports Server (NTRS)

1973-01-01

The field of artificial intelligence to identify practical applications to unmanned spacecraft used to explore the solar system in the decade of the 80s is examined. If an unmanned spacecraft can be made to adjust or adapt to the environment, to make decisions about what it measures and how it uses and reports the data, it can become a much more powerful tool for the science community in unlocking the secrets of the solar system. Within this definition of an adaptive spacecraft or system, there is a broad range of variability. In terms of sophistication, an adaptive system can be extremely simple or as complex as a chess-playing machine that learns from its mistakes.

Adaptive Global Innovative Learning Environment for Glioblastoma: GBM AGILE.

PubMed

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

2018-02-15

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

Affective Load and Engagement in Second Life: Experiencing Urgent, Persistent, and Long-Term Information Needs

ERIC Educational Resources Information Center

Nahl, Diane

2010-01-01

New users of virtual environments face a steep learning curve, requiring persistence and determination to overcome challenges experienced while acclimatizing to the demands of avatar-mediated behavior. Concurrent structured self-reports can be used to monitor the personal affective and cognitive struggles involved in virtual world adaptation to…

Learning for Today's Leader: The Changing State of Community College Training Programs

ERIC Educational Resources Information Center

Ullman, Ellen

2010-01-01

Today's environment requires community college leaders to put student success and equity at the top of their leadership agendas. Thus, higher education institutions have realized a need to change the philosophies and programs that underpin the training of community college leaders. Other schools of education are adapting to give college leaders…

Leveraging the Power of Social Media to Maximize Organizational Learning and Drive Performance

ERIC Educational Resources Information Center

Nguyen, Camilla C.

2014-01-01

This qualitative ethnographic study addresses the phenomenon of rapid social media expansion, which creates organizational challenges. Ongoing development of advanced technology products means that effective organizations must be more adaptive and receptive to new approaches and changes in their environment. In a hyper connected society, one where…

Otitis Media: Coping with the Effects in the Classroom.

ERIC Educational Resources Information Center

Davis, Dorinne S.

This curriculum adaptation provides a methodology that enables the classroom teacher to recognize the needs of the otitis media-affected child in the classroom. It discusses areas of concern related to otitis media; suggests activities that can enhance these children's language skills; and shows ways to enhance the learning environment by…

Multimodal Interaction on English Testing Academic Assessment

ERIC Educational Resources Information Center

Magal-Royo, T.; Gimenez-Lopez, J. L.; Garcia Laborda, Jesus

2012-01-01

Multimodal interaction methods applied to learning environments of the English language will be a line for future research from the use of adapted mobile phones or PDAs. Today's mobile devices allow access and data entry in a synchronized manner through different channels. At the academic level we made the first analysis of English language…

Education Faculty Students' Views about Use of E-Books

ERIC Educational Resources Information Center

Yalman, Murat

2015-01-01

Parallel to technological developments, numerous new tools are now available for people's use. Societies adapt these tools to their professional lives by learning how to use them. In this way, they try to establish more comfortable working environments. Universities giving vocational education are supposed to teach these new technologies to their…

Individual Differences: Interplay of Learner Characteristics and Learning Environment

ERIC Educational Resources Information Center

Dornyei, Zoltan

2009-01-01

The notion of language as a complex adaptive system has been conceived within an agent-based framework, which highlights the significance of individual-level variation in the characteristics and contextual circumstances of the learner/speaker. Yet, in spite of this emphasis, currently we know relatively little about the interplay among language,…

Perception of Competence in Middle School Physical Education: Instrument Development and Validation

ERIC Educational Resources Information Center

Scrabis-Fletcher, Kristin; Silverman, Stephen

2010-01-01

Perception of Competence (POC) has been studied extensively in physical activity (PA) research with similar instruments adapted for physical education (PE) research. Such instruments do not account for the unique PE learning environment. Therefore, an instrument was developed and the scores validated to measure POC in middle school PE. A…

Programming for Fun: MUDs as a Context for Collaborative Learning.

ERIC Educational Resources Information Center

Bruckman, Amy

Multi-User Dungeons (MUDs), are text-based virtual reality environments in which participants separated by great physical distances can communicate and collaborate in programming. Most MUDs started out as adventure games but are quickly being adapted for more "serious" endeavors. This paper presents a case study of the experiences of a…

Adapting Learning Contexts to Develop Desirable Personal and Vocational Traits.

ERIC Educational Resources Information Center

Abernathy, Tammy

This paper outlines a method for meeting the vocational needs of students with mild disabilities and the instructional demands placed on both teacher and student, without sacrificing time devoted to content areas. By manipulating the existing curriculum and environment, educators can cultivate the skills necessary for success in the working world.…

Required Skill Sets of Information Technology Workers in Managed Hosting Environments in Higher Education

ERIC Educational Resources Information Center

Wood, Scott

2017-01-01

Through the rise of online learning, the playing field has been leveled for colleges across the globe. As costs continue to increase, greater emphasis is being placed on higher education institutions to maximize existing resources while adapting to technological advances. Building on Christensen's theory of disruptive innovation, and further…

Gravity Sensor Plasticity in the Space Environment

NASA Technical Reports Server (NTRS)

Ross, Muriel D.

1996-01-01

The ability of the brain to learn from experience and to adapt to new environments is recognized to be profound. This ability, called 'neural plasticity,' depends directly on properties of neurons (nerve cells) that permit them to change in dimension, sprout new parts called spines, change the shape and/or size of existing parts, and to generate, alter, or delete synapses. (Synapses are communication sites between neurons.) These neuronal properties are most evident during development, when evolution guides the laying down of a general plan of the nervous system. However, once a nervous system is established, experience interacts with cellular and genetic mechanisms and the internal milieu to produce unique neuronal substrates that define each individual. The capacity for experience-related neuronal growth in the brain, as measured by the potential for synaptogenesis, is speculated to be in the trillions of synapses, but the range of increment possible for any one part of the nervous system is unknown. The question has been whether more primitive endorgans such as gravity sensors of the inner ear have a capacity for adaptive change, since this is a form of learning from experience.

An efficient incremental learning mechanism for tracking concept drift in spam filtering

PubMed Central

Sheu, Jyh-Jian; Chu, Ko-Tsung; Li, Nien-Feng; Lee, Cheng-Chi

2017-01-01

This research manages in-depth analysis on the knowledge about spams and expects to propose an efficient spam filtering method with the ability of adapting to the dynamic environment. We focus on the analysis of email’s header and apply decision tree data mining technique to look for the association rules about spams. Then, we propose an efficient systematic filtering method based on these association rules. Our systematic method has the following major advantages: (1) Checking only the header sections of emails, which is different from those spam filtering methods at present that have to analyze fully the email’s content. Meanwhile, the email filtering accuracy is expected to be enhanced. (2) Regarding the solution to the problem of concept drift, we propose a window-based technique to estimate for the condition of concept drift for each unknown email, which will help our filtering method in recognizing the occurrence of spam. (3) We propose an incremental learning mechanism for our filtering method to strengthen the ability of adapting to the dynamic environment. PMID:28182691

Smart-system of distance learning of visually impaired people based on approaches of artificial intelligence

NASA Astrophysics Data System (ADS)

Samigulina, Galina A.; Shayakhmetova, Assem S.

2016-11-01

Research objective is the creation of intellectual innovative technology and information Smart-system of distance learning for visually impaired people. The organization of the available environment for receiving quality education for visually impaired people, their social adaptation in society are important and topical issues of modern education.The proposed Smart-system of distance learning for visually impaired people can significantly improve the efficiency and quality of education of this category of people. The scientific novelty of proposed Smart-system is using intelligent and statistical methods of processing multi-dimensional data, and taking into account psycho-physiological characteristics of perception and awareness learning information by visually impaired people.

Evolutionary games under incompetence.

PubMed

Kleshnina, Maria; Filar, Jerzy A; Ejov, Vladimir; McKerral, Jody C

2018-02-26

The adaptation process of a species to a new environment is a significant area of study in biology. As part of natural selection, adaptation is a mutation process which improves survival skills and reproductive functions of species. Here, we investigate this process by combining the idea of incompetence with evolutionary game theory. In the sense of evolution, incompetence and training can be interpreted as a special learning process. With focus on the social side of the problem, we analyze the influence of incompetence on behavior of species. We introduce an incompetence parameter into a learning function in a single-population game and analyze its effect on the outcome of the replicator dynamics. Incompetence can change the outcome of the game and its dynamics, indicating its significance within what are inherently imperfect natural systems.