E-Learning Agents

ERIC Educational Resources Information Center

Gregg, Dawn G.

2007-01-01

Purpose: The purpose of this paper is to illustrate the advantages of using intelligent agents to facilitate the location and customization of appropriate e-learning resources and to foster collaboration in e-learning environments. Design/methodology/approach: This paper proposes an e-learning environment that can be used to provide customized…

Personalized E- learning System Based on Intelligent Agent

NASA Astrophysics Data System (ADS)

Duo, Sun; Ying, Zhou Cai

Lack of personalized learning is the key shortcoming of traditional e-Learning system. This paper analyzes the personal characters in e-Learning activity. In order to meet the personalized e-learning, a personalized e-learning system based on intelligent agent was proposed and realized in the paper. The structure of system, work process, the design of intelligent agent and the realization of intelligent agent were introduced in the paper. After the test use of the system by certain network school, we found that the system could improve the learner's initiative participation, which can provide learners with personalized knowledge service. Thus, we thought it might be a practical solution to realize self- learning and self-promotion in the lifelong education age.

Quantum Speedup for Active Learning Agents

NASA Astrophysics Data System (ADS)

Paparo, Giuseppe Davide; Dunjko, Vedran; Makmal, Adi; Martin-Delgado, Miguel Angel; Briegel, Hans J.

2014-07-01

Can quantum mechanics help us build intelligent learning agents? A defining signature of intelligent behavior is the capacity to learn from experience. However, a major bottleneck for agents to learn in real-life situations is the size and complexity of the corresponding task environment. Even in a moderately realistic environment, it may simply take too long to rationally respond to a given situation. If the environment is impatient, allowing only a certain time for a response, an agent may then be unable to cope with the situation and to learn at all. Here, we show that quantum physics can help and provide a quadratic speedup for active learning as a genuine problem of artificial intelligence. This result will be particularly relevant for applications involving complex task environments.

Conversational Agents in E-Learning

NASA Astrophysics Data System (ADS)

Kerry, Alice; Ellis, Richard; Bull, Susan

This paper discusses the use of natural language or 'conversational' agents in e-learning environments. We describe and contrast the various applications of conversational agent technology represented in the e-learning literature, including tutors, learning companions, language practice and systems to encourage reflection. We offer two more detailed examples of conversational agents, one which provides learning support, and the other support for self-assessment. Issues and challenges for developers of conversational agent systems for e-learning are identified and discussed.

Web-Based Learning Environment Based on Students’ Needs

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Multi-agent Reinforcement Learning Model for Effective Action Selection

NASA Astrophysics Data System (ADS)

Youk, Sang Jo; Lee, Bong Keun

Reinforcement learning is a sub area of machine learning concerned with how an agent ought to take actions in an environment so as to maximize some notion of long-term reward. In the case of multi-agent, especially, which state space and action space gets very enormous in compared to single agent, so it needs to take most effective measure available select the action strategy for effective reinforcement learning. This paper proposes a multi-agent reinforcement learning model based on fuzzy inference system in order to improve learning collect speed and select an effective action in multi-agent. This paper verifies an effective action select strategy through evaluation tests based on Robocop Keep away which is one of useful test-beds for multi-agent. Our proposed model can apply to evaluate efficiency of the various intelligent multi-agents and also can apply to strategy and tactics of robot soccer system.

B-tree search reinforcement learning for model based intelligent agent

NASA Astrophysics Data System (ADS)

Bhuvaneswari, S.; Vignashwaran, R.

2013-03-01

Agents trained by learning techniques provide a powerful approximation of active solutions for naive approaches. In this study using B - Trees implying reinforced learning the data search for information retrieval is moderated to achieve accuracy with minimum search time. The impact of variables and tactics applied in training are determined using reinforcement learning. Agents based on these techniques perform satisfactory baseline and act as finite agents based on the predetermined model against competitors from the course.

The Time Factor: Leveraging Intelligent Agents and Directed Narratives in Online Learning Environments

ERIC Educational Resources Information Center

Jones, Greg; Warren, Scott

2009-01-01

Using video games, virtual simulations, and other digital spaces for learning can be a time-consuming process; aside from technical issues that may absorb class time, students take longer to achieve gains in learning in virtual environments. Greg Jones and Scott Warren describe how intelligent agents, in-game characters that respond to the context…

Hypercompetitive Environments: An Agent-based model approach

NASA Astrophysics Data System (ADS)

Dias, Manuel; Araújo, Tanya

Information technology (IT) environments are characterized by complex changes and rapid evolution. Globalization and the spread of technological innovation have increased the need for new strategic information resources, both from individual firms and management environments. Improvements in multidisciplinary methods and, particularly, the availability of powerful computational tools, are giving researchers an increasing opportunity to investigate management environments in their true complex nature. The adoption of a complex systems approach allows for modeling business strategies from a bottom-up perspective — understood as resulting from repeated and local interaction of economic agents — without disregarding the consequences of the business strategies themselves to individual behavior of enterprises, emergence of interaction patterns between firms and management environments. Agent-based models are at the leading approach of this attempt.

An Active Learning Exercise for Introducing Agent-Based Modeling

ERIC Educational Resources Information Center

Pinder, Jonathan P.

2013-01-01

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

Impacts of Pedagogical Agent Gender in an Accessible Learning Environment

ERIC Educational Resources Information Center

Schroeder, Noah L.; Adesope, Olusola O.

2015-01-01

Advances in information technologies have resulted in the use of pedagogical agents to facilitate learning. Although several studies have been conducted to examine the effects of pedagogical agents on learning, little is known about gender stereotypes of agents and how those stereotypes influence student learning and attitudes. This study…

Animated Pedagogical Agents Effects on Enhancing Student Motivation and Learning in a Science Inquiry Learning Environment

ERIC Educational Resources Information Center

van der Meij, Hans; van der Meij, Jan; Harmsen, Ruth

2015-01-01

This study focuses on the design and testing of a motivational animated pedagogical agent (APA) in an inquiry learning environment on kinematics. The aim of including the APA was to enhance students' perceptions of task relevance and self-efficacy. Given the under-representation of girls in science classrooms, special attention was given to…

Using Agent-Based Technologies to Enhance Learning in Educational Games

ERIC Educational Resources Information Center

Tumenayu, Ogar Ofut; Shabalina, Olga; Kamaev, Valeriy; Davtyan, Alexander

2014-01-01

Recent research has shown that educational games positively motivate learning. However, there is a little evidence that they can trigger learning to a large extent if the game-play is supported by additional activities. We aim to support educational games development with an Agent-Based Technology (ABT) by using intelligent pedagogical agents that…

The Effects of a Pedagogical Agent's Smiling Expression on the Learner's Emotions and Motivation in a Virtual Learning Environment

ERIC Educational Resources Information Center

Liew, Tze Wei; Zin, Nor Azan Mat; Sahari, Noraidah; Tan, Su-Mae

2016-01-01

The present study aimed to test the hypothesis that a smiling expression on the face of a talking pedagogical agent could positively affect a learner's emotions, motivation, and learning outcomes in a virtual learning environment. Contrary to the hypothesis, results from Experiment 1 demonstrated that the pedagogical agent's smile induced negative…

Teachable Agents and the Protege Effect: Increasing the Effort towards Learning

ERIC Educational Resources Information Center

Chase, Catherine C.; Chin, Doris B.; Oppezzo, Marily A.; Schwartz, Daniel L.

2009-01-01

Betty's Brain is a computer-based learning environment that capitalizes on the social aspects of learning. In Betty's Brain, students instruct a character called a Teachable Agent (TA) which can reason based on how it is taught. Two studies demonstrate the "protege effect": students make greater effort to learn for their TAs than they do…

Reinforcement learning algorithms for robotic navigation in dynamic environments.

PubMed

Yen, Gary G; Hickey, Travis W

2004-04-01

The purpose of this study was to examine improvements to reinforcement learning (RL) algorithms in order to successfully interact within dynamic environments. The scope of the research was that of RL algorithms as applied to robotic navigation. Proposed improvements include: addition of a forgetting mechanism, use of feature based state inputs, and hierarchical structuring of an RL agent. Simulations were performed to evaluate the individual merits and flaws of each proposal, to compare proposed methods to prior established methods, and to compare proposed methods to theoretically optimal solutions. Incorporation of a forgetting mechanism did considerably improve the learning times of RL agents in a dynamic environment. However, direct implementation of a feature-based RL agent did not result in any performance enhancements, as pure feature-based navigation results in a lack of positional awareness, and the inability of the agent to determine the location of the goal state. Inclusion of a hierarchical structure in an RL agent resulted in significantly improved performance, specifically when one layer of the hierarchy included a feature-based agent for obstacle avoidance, and a standard RL agent for global navigation. In summary, the inclusion of a forgetting mechanism, and the use of a hierarchically structured RL agent offer substantially increased performance when compared to traditional RL agents navigating in a dynamic environment.

The Impact of a Peer-Learning Agent Based on Pair Programming in a Programming Course

ERIC Educational Resources Information Center

Han, Keun-Woo; Lee, EunKyoung; Lee, YoungJun

2010-01-01

This paper analyzes the educational effects of a peer-learning agent based on pair programming in programming courses. A peer-learning agent system was developed to facilitate the learning of a programming language through the use of pair programming strategies. This system is based on the role of a peer-learning agent from pedagogical and…

Personalisation in Web-Based Learning Environments

ERIC Educational Resources Information Center

Santally, Mohammad Issack; Alain, Senteni

2006-01-01

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

Online Bahavior Aquisition of an Agent based on Coaching as Learning Assistance

NASA Astrophysics Data System (ADS)

Hirokawa, Masakazu; Suzuki, Kenji

This paper describes a novel methodology, namely ``Coaching'', which allows humans to give a subjective evaluation to an agent in an iterative manner. This is an interactive learning method to improve the reinforcement learning by modifying a reward function dynamically according to given evaluations by a trainer and the learning situation of the agent. We demonstrate that the agent can learn different reward functions by given instructions such as ``good or bad'' by human's observation, and can also obtain a set of behavior based on the learnt reward functions through several experiments.

Collaborating Fuzzy Reinforcement Learning Agents

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1997-01-01

Earlier, we introduced GARIC-Q, a new method for doing incremental Dynamic Programming using a society of intelligent agents which are controlled at the top level by Fuzzy Relearning and at the local level, each agent learns and operates based on ANTARCTIC, a technique for fuzzy reinforcement learning. In this paper, we show that it is possible for these agents to compete in order to affect the selected control policy but at the same time, they can collaborate while investigating the state space. In this model, the evaluator or the critic learns by observing all the agents behaviors but the control policy changes only based on the behavior of the winning agent also known as the super agent.

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

ERIC Educational Resources Information Center

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

2015-01-01

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

Modeling Peer Assessment as Agent Negotiation in a Computer Supported Collaborative Learning Environment

ERIC Educational Resources Information Center

Lai, K. Robert; Lan, Chung Hsien

2006-01-01

This work presents a novel method for modeling collaborative learning as multi-issue agent negotiation using fuzzy constraints. Agent negotiation is an iterative process, through which, the proposed method aggregates student marks to reduce personal bias. In the framework, students define individual fuzzy membership functions based on their…

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

Exploration for Agents with Different Personalities in Unknown Environments

NASA Astrophysics Data System (ADS)

Doumit, Sarjoun; Minai, Ali

We present in this paper a personality-based architecture (PA) that combines elements from the subsumption architecture and reinforcement learning to find alternate solutions for problems facing artificial agents exploring unknown environments. The underlying PA algorithm is decomposed into layers according to the different (non-contiguous) stages that our agent passes in, which in turn are influenced by the sources of rewards present in the environment. The cumulative rewards collected by an agent, in addition to its internal composition serve as factors in shaping its personality. In missions where multiple agents are deployed, our solution-goal is to allow each of the agents develop its own distinct personality in order for the collective to reach a balanced society, which then can accumulate the largest possible amount of rewards for the agent and society as well. The architecture is tested in a simulated matrix world which embodies different types of positive rewards and negative rewards. Varying experiments are performed to compare the performance of our algorithm with other algorithms under the same environment conditions. The use of our architecture accelerates the overall adaptation of the agents to their environment and goals by allowing the emergence of an optimal society of agents with different personalities. We believe that our approach achieves much efficient results when compared to other more restrictive policy designs.

Agent-Based Simulation of Learning Dissemination in a Project-Based Learning Context Considering the Human Aspects

ERIC Educational Resources Information Center

Seman, Laio Oriel; Hausmann, Romeu; Bezerra, Eduardo Augusto

2018-01-01

Contribution: This paper presents the "PBL classroom model," an agent-based simulation (ABS) that allows testing of several scenarios of a project-based learning (PBL) application by considering different levels of soft-skills, and students' perception of the methodology. Background: While the community has made great advances in…

Strategies to Enhance Online Learning Teams. Team Assessment and Diagnostics Instrument and Agent-based Modeling

DTIC Science & Technology

2010-08-12

Strategies to Enhance Online Learning Teams Team Assessment and Diagnostics Instrument and Agent-based Modeling Tristan E. Johnson, Ph.D. Learning ...REPORT DATE AUG 2010 2. REPORT TYPE 3. DATES COVERED 00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE Strategies to Enhance Online Learning ...TeamsTeam Strategies to Enhance Online Learning Teams: Team Assessment and Diagnostics Instrument and Agent-based Modeling 5a. CONTRACT NUMBER 5b. GRANT

Observer-based distributed adaptive iterative learning control for linear multi-agent systems

NASA Astrophysics Data System (ADS)

Li, Jinsha; Liu, Sanyang; Li, Junmin

2017-10-01

This paper investigates the consensus problem for linear multi-agent systems from the viewpoint of two-dimensional systems when the state information of each agent is not available. Observer-based fully distributed adaptive iterative learning protocol is designed in this paper. A local observer is designed for each agent and it is shown that without using any global information about the communication graph, all agents achieve consensus perfectly for all undirected connected communication graph when the number of iterations tends to infinity. The Lyapunov-like energy function is employed to facilitate the learning protocol design and property analysis. Finally, simulation example is given to illustrate the theoretical analysis.

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

ERIC Educational Resources Information Center

So, Winnie Wing Mui; Ching, Fiona Ngai Ying

2012-01-01

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

A learning-based agent for home neurorehabilitation.

PubMed

Lydakis, Andreas; Meng, Yuanliang; Munroe, Christopher; Wu, Yi-Ning; Begum, Momotaz

2017-07-01

This paper presents the iterative development of an artificially intelligent system to promote home-based neurorehabilitation. Although proper, structured practice of rehabilitation exercises at home is the key to successful recovery of motor functions, there is no home-program out there which can monitor a patient's exercise-related activities and provide corrective feedback in real time. To this end, we designed a Learning from Demonstration (LfD) based home-rehabilitation framework that combines advanced robot learning algorithms with commercially available wearable technologies. The proposed system uses exercise-related motion information and electromyography signals (EMG) of a patient to train a Markov Decision Process (MDP). The trained MDP model can enable an agent to serve as a coach for a patient. On a system level, this is the first initiative, to the best of our knowledge, to employ LfD in an health-care application to enable lay users to program an intelligent system. From a rehabilitation research perspective, this is a completely novel initiative to employ machine learning to provide interactive corrective feedback to a patient in home settings.

Personalized Messages That Promote Science Learning in Virtual Environments

ERIC Educational Resources Information Center

Moreno, Roxana; Mayer, Richard E.

2004-01-01

College students learned how to design the roots, stem, and leaves of plants to survive in five different virtual reality environments through an agent-based multimedia educational game. For each student, the agent used personalized speech (e.g., including I and you) or nonpersonalized speech (e.g., 3rd-person monologue), and the game was…

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

ERIC Educational Resources Information Center

Hakverdi-Can, Meral; Sonmez, Duygu

2012-01-01

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

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

PubMed

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

2017-01-01

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

Construction of a Learning Agent Handling Its Rewards According to Environmental Situations

NASA Astrophysics Data System (ADS)

Moriyama, Koichi; Numao, Masayuki

The authors aim at constructing an agent which learns appropriate actions in a Multi-Agent environment with and without social dilemmas. For this aim, the agent must have nonrationality that makes it give up its own profit when it should do that. Since there are many studies on rational learning that brings more and more profit, it is desirable to utilize them for constructing the agent. Therefore, we use a reward-handling manner that makes internal evaluation from the agent's rewards, and then the agent learns actions by a rational learning method with the internal evaluation. If the agent has only a fixed manner, however, it does not act well in the environment with and without dilemmas. Thus, the authors equip the agent with several reward-handling manners and criteria for selecting an effective one for the environmental situation. In the case of humans, what generates the internal evaluation is usually called emotion. Hence, this study also aims at throwing light on emotional activities of humans from a constructive view. In this paper, we divide a Multi-Agent environment into three situations and construct an agent having the reward-handling manners and the criteria. We observe that the agent acts well in all the three Multi-Agent situations composed of homogeneous agents.

Agent-Based Models in Social Physics

NASA Astrophysics Data System (ADS)

Quang, Le Anh; Jung, Nam; Cho, Eun Sung; Choi, Jae Han; Lee, Jae Woo

2018-06-01

We review the agent-based models (ABM) on social physics including econophysics. The ABM consists of agent, system space, and external environment. The agent is autonomous and decides his/her behavior by interacting with the neighbors or the external environment with the rules of behavior. Agents are irrational because they have only limited information when they make decisions. They adapt using learning from past memories. Agents have various attributes and are heterogeneous. ABM is a non-equilibrium complex system that exhibits various emergence phenomena. The social complexity ABM describes human behavioral characteristics. In ABMs of econophysics, we introduce the Sugarscape model and the artificial market models. We review minority games and majority games in ABMs of game theory. Social flow ABM introduces crowding, evacuation, traffic congestion, and pedestrian dynamics. We also review ABM for opinion dynamics and voter model. We discuss features and advantages and disadvantages of Netlogo, Repast, Swarm, and Mason, which are representative platforms for implementing ABM.

Conducting and Supporting a Goal-Based Scenario Learning Environment.

ERIC Educational Resources Information Center

Montgomery, Joel; And Others

1994-01-01

Discussion of goal-based scenario (GBS) learning environments focuses on a training module designed to prepare consultants with new skills in managing clients, designing user-friendly graphical computer interfaces, and working in a client/server computing environment. Transforming the environment from teaching focused to learning focused is…

Pedagogical Agents as Learning Companions: The Impact of Agent Emotion and Gender

ERIC Educational Resources Information Center

Kim, Yanghee; Baylor, A. L.; Shen, E.

2007-01-01

The potential of emotional interaction between human and computer has recently interested researchers in human-computer interaction. The instructional impact of this interaction in learning environments has not been established, however. This study examined the impact of emotion and gender of a pedagogical agent as a learning companion (PAL) on…

Fostering Multimedia Learning of Science: Exploring the Role of an Animated Agent's Image

ERIC Educational Resources Information Center

Dunsworth, Qi; Atkinson, Robert K.

2007-01-01

Research suggests that students learn better when studying a picture coupled with narration rather than on-screen text in a computer-based multimedia learning environment. Moreover, combining narration with the visual presence of an animated pedagogical agent may also encourage students to process information deeper than narration or on-screen…

QUICR-learning for Multi-Agent Coordination

NASA Technical Reports Server (NTRS)

Agogino, Adrian K.; Tumer, Kagan

2006-01-01

Coordinating multiple agents that need to perform a sequence of actions to maximize a system level reward requires solving two distinct credit assignment problems. First, credit must be assigned for an action taken at time step t that results in a reward at time step t > t. Second, credit must be assigned for the contribution of agent i to the overall system performance. The first credit assignment problem is typically addressed with temporal difference methods such as Q-learning. The second credit assignment problem is typically addressed by creating custom reward functions. To address both credit assignment problems simultaneously, we propose the "Q Updates with Immediate Counterfactual Rewards-learning" (QUICR-learning) designed to improve both the convergence properties and performance of Q-learning in large multi-agent problems. QUICR-learning is based on previous work on single-time-step counterfactual rewards described by the collectives framework. Results on a traffic congestion problem shows that QUICR-learning is significantly better than a Q-learner using collectives-based (single-time-step counterfactual) rewards. In addition QUICR-learning provides significant gains over conventional and local Q-learning. Additional results on a multi-agent grid-world problem show that the improvements due to QUICR-learning are not domain specific and can provide up to a ten fold increase in performance over existing methods.

Gendered Socialization with an Embodied Agent: Creating a Social and Affable Mathematics Learning Environment for Middle-Grade Females

ERIC Educational Resources Information Center

Kim, Yanghee; Lim, Jae Hoon

2013-01-01

This study examined whether or not embodied-agent-based learning would help middle-grade females have more positive mathematics learning experiences. The study used an explanatory mixed methods research design. First, a classroom-based experiment was conducted with one hundred twenty 9th graders learning introductory algebra (53% male and 47%…

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

ERIC Educational Resources Information Center

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

2015-01-01

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

Investigating Effects of Problem-Based versus Lecture-Based Learning Environments on Student Motivation

ERIC Educational Resources Information Center

Wijnia, Lisette; Loyens, Sofie M. M.; Derous, Eva

2011-01-01

This study examines the effects of two learning environments (i.e., problem-based learning [PBL] versus lecture-based [LB] environments) on undergraduates' study motivation. Survey results demonstrated that PBL students scored higher on competence but did not differ from LB students on autonomous motivation. Analyses of focus groups further…

Sustaining Teacher Control in a Blog-Based Personal Learning Environment

ERIC Educational Resources Information Center

Tomberg, Vladimir; Laanpere, Mart; Ley, Tobias; Normak, Peeter

2013-01-01

Various tools and services based on Web 2.0 (mainly blogs, wikis, social networking tools) are increasingly used in formal education to create personal learning environments, providing self-directed learners with more freedom, choice, and control over their learning. In such distributed and personalized learning environments, the traditional role…

Problem-Based Educational Game Becomes Student-Centered Learning Environment

ERIC Educational Resources Information Center

Rodkroh, Pornpimon; Suwannatthachote, Praweenya; Kaemkate, Wannee

2013-01-01

Problem-based educational games are able to provide a fun and motivating environment for teaching and learning of certain subjects. However, most educational game models do not address the learning elements of problem-based educational games. This study aims to synthesize and to propose the important elements to facilitate the learning process and…

Vector-based navigation using grid-like representations in artificial agents.

PubMed

Banino, Andrea; Barry, Caswell; Uria, Benigno; Blundell, Charles; Lillicrap, Timothy; Mirowski, Piotr; Pritzel, Alexander; Chadwick, Martin J; Degris, Thomas; Modayil, Joseph; Wayne, Greg; Soyer, Hubert; Viola, Fabio; Zhang, Brian; Goroshin, Ross; Rabinowitz, Neil; Pascanu, Razvan; Beattie, Charlie; Petersen, Stig; Sadik, Amir; Gaffney, Stephen; King, Helen; Kavukcuoglu, Koray; Hassabis, Demis; Hadsell, Raia; Kumaran, Dharshan

2018-05-01

Deep neural networks have achieved impressive successes in fields ranging from object recognition to complex games such as Go 1,2 . Navigation, however, remains a substantial challenge for artificial agents, with deep neural networks trained by reinforcement learning 3-5 failing to rival the proficiency of mammalian spatial behaviour, which is underpinned by grid cells in the entorhinal cortex 6 . Grid cells are thought to provide a multi-scale periodic representation that functions as a metric for coding space 7,8 and is critical for integrating self-motion (path integration) 6,7,9 and planning direct trajectories to goals (vector-based navigation) 7,10,11 . Here we set out to leverage the computational functions of grid cells to develop a deep reinforcement learning agent with mammal-like navigational abilities. We first trained a recurrent network to perform path integration, leading to the emergence of representations resembling grid cells, as well as other entorhinal cell types 12 . We then showed that this representation provided an effective basis for an agent to locate goals in challenging, unfamiliar, and changeable environments-optimizing the primary objective of navigation through deep reinforcement learning. The performance of agents endowed with grid-like representations surpassed that of an expert human and comparison agents, with the metric quantities necessary for vector-based navigation derived from grid-like units within the network. Furthermore, grid-like representations enabled agents to conduct shortcut behaviours reminiscent of those performed by mammals. Our findings show that emergent grid-like representations furnish agents with a Euclidean spatial metric and associated vector operations, providing a foundation for proficient navigation. As such, our results support neuroscientific theories that see grid cells as critical for vector-based navigation 7,10,11 , demonstrating that the latter can be combined with path-based strategies to

Self-Regulated Learning in Learning Environments with Pedagogical Agents that Interact in Natural Language

ERIC Educational Resources Information Center

Graesser, Arthur; McNamara, Danielle

2010-01-01

This article discusses the occurrence and measurement of self-regulated learning (SRL) both in human tutoring and in computer tutors with agents that hold conversations with students in natural language and help them learn at deeper levels. One challenge in building these computer tutors is to accommodate, encourage, and scaffold SRL because these…

Agent-Based Phytoplankton Models of Cellular and Population Processes: Fostering Individual-Based Learning in Undergraduate Research

NASA Astrophysics Data System (ADS)

Berges, J. A.; Raphael, T.; Rafa Todd, C. S.; Bate, T. C.; Hellweger, F. L.

2016-02-01

Engaging undergraduate students in research projects that require expertise in multiple disciplines (e.g. cell biology, population ecology, and mathematical modeling) can be challenging because they have often not developed the expertise that allows them to participate at a satisfying level. Use of agent-based modeling can allow exploration of concepts at more intuitive levels, and encourage experimentation that emphasizes processes over computational skills. Over the past several years, we have involved undergraduate students in projects examining both ecological and cell biological aspects of aquatic microbial biology, using the freely-downloadable, agent-based modeling environment NetLogo (https://ccl.northwestern.edu/netlogo/). In Netlogo, actions of large numbers of individuals can be simulated, leading to complex systems with emergent behavior. The interface features appealing graphics, monitors, and control structures. In one example, a group of sophomores in a BioMathematics program developed an agent-based model of phytoplankton population dynamics in a pond ecosystem, motivated by observed macroscopic changes in cell numbers (due to growth and death), and driven by responses to irradiance, temperature and a limiting nutrient. In a second example, junior and senior undergraduates conducting Independent Studies created a model of the intracellular processes governing stress and cell death for individual phytoplankton cells (based on parameters derived from experiments using single-cell culturing and flow cytometry), and then this model was embedded in the agents in the pond ecosystem model. In our experience, students with a range of mathematical abilities learned to code quickly and could use the software with varying degrees of sophistication, for example, creation of spatially-explicit two and three-dimensional models. Skills developed quickly and transferred readily to other platforms (e.g. Matlab).

Supporting Multimedia Learning with Visual Signalling and Animated Pedagogical Agent: Moderating Effects of Prior Knowledge

ERIC Educational Resources Information Center

Johnson, A. M.; Ozogul, G.; Reisslein, M.

2015-01-01

An experiment examined the effects of visual signalling to relevant information in multiple external representations and the visual presence of an animated pedagogical agent (APA). Students learned electric circuit analysis using a computer-based learning environment that included Cartesian graphs, equations and electric circuit diagrams. The…

A FAQ-Based e-Learning Environment to Support Japanese Language Learning

ERIC Educational Resources Information Center

Liu, Yuqin; Yin, Chengjiu; Ogata, Hiroaki; Qiao, Guojun; Yano, Yoneo

2011-01-01

In traditional classes, having many questions from learners is important because these questions indicate difficult points for learners and for teachers. This paper proposes a FAQ-based e-Learning environment to support Japanese language learning that focuses on learner questions. This knowledge sharing system enables learners to interact and…

A study on expertise of agents and its effects on cooperative Q-learning.

PubMed

Araabi, Babak Nadjar; Mastoureshgh, Sahar; Ahmadabadi, Majid Nili

2007-04-01

Cooperation in learning (CL) can be realized in a multiagent system, if agents are capable of learning from both their own experiments and other agents' knowledge and expertise. Extra resources are exploited into higher efficiency and faster learning in CL as compared to that of individual learning (IL). In the real world, however, implementation of CL is not a straightforward task, in part due to possible differences in area of expertise (AOE). In this paper, reinforcement-learning homogenous agents are considered in an environment with multiple goals or tasks. As a result, they become expert in different domains with different amounts of expertness. Each agent uses a one-step Q-learning algorithm and is capable of exchanging its Q-table with those of its teammates. Two crucial questions are addressed in this paper: "How the AOE of an agent can be extracted?" and "How agents can improve their performance in CL by knowing their AOEs?" An algorithm is developed to extract the AOE based on state transitions as a gold standard from a behavioral point of view. Moreover, it is discussed that the AOE can be implicitly obtained through agents' expertness in the state level. Three new methods for CL through the combination of Q-tables are developed and examined for overall performance after CL. The performances of developed methods are compared with that of IL, strategy sharing (SS), and weighted SS (WSS). Obtained results show the superior performance of AOE-based methods as compared to that of existing CL methods, which do not use the notion of AOE. These results are very encouraging in support of the idea that "cooperation based on the AOE" performs better than the general CL methods.

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.

Do Pedagogical Agents Make a Difference to Student Motivation and Learning?

ERIC Educational Resources Information Center

Heidig, Steffi; Clarebout, Geraldine

2011-01-01

Pedagogical agents, characters that guide through multimedia learning environments, recently gained increasing interest. A review was published by Clarebout, Elen, Johnson and Shaw in 2002 where a lot of promises were made, but research on the motivational and learning effects of pedagogical agents was scarce. More than 70 articles on pedagogical…

Using narrative-based design scaffolds within a mobile learning environment to support learning outdoors with young children

NASA Astrophysics Data System (ADS)

Seely, Brian J.

This study aims to advance learning outdoors with mobile devices. As part of the ongoing Tree Investigators design-based research study, this research investigated a mobile application to support observation, identification, and explanation of the tree life cycle within an authentic, outdoor setting. Recognizing the scientific and conceptual complexity of this topic for young children, the design incorporated technological and design scaffolds within a narrative-based learning environment. In an effort to support learning, 14 participants (aged 5-9) were guided through the mobile app on tree life cycles by a comic-strip pedagogical agent, "Nutty the Squirrel", as they looked to explore and understand through guided observational practices and artifact creation tasks. In comparison to previous iterations of this DBR study, the overall patterns of talk found in this study were similar, with perceptual and conceptual talk being the first and second most frequently coded categories, respectively. However, this study coded considerably more instances of affective talk. This finding of the higher frequency of affective talk could possibly be explained by the relatively younger age of this iteration's participants, in conjunction with the introduced pedagogical agent, who elicited playfulness and delight from the children. The results also indicated a significant improvement when comparing the pretest results (mean score of .86) with the posttest results (mean score of 4.07, out of 5). Learners were not only able to recall the phases of a tree life cycle, but list them in the correct order. The comparison reports a significant increase, showing evidence of increased knowledge and appropriation of scientific vocabulary. The finding suggests the narrative was effective in structuring the complex material into a story for sense making. Future research with narratives should consider a design to promote learner agency through more interactions with the pedagogical agent and a

Programming secure mobile agents in healthcare environments using role-based permissions.

PubMed

Georgiadis, C K; Baltatzis, J; Pangalos, G I

2003-01-01

The healthcare environment consists of vast amounts of dynamic and unstructured information, distributed over a large number of information systems. Mobile agent technology is having an ever-growing impact on the delivery of medical information. It supports acquiring and manipulating information distributed in a large number of information systems. Moreover is suitable for the computer untrained medical stuff. But the introduction of mobile agents generates advanced threads to the sensitive healthcare information, unless the proper countermeasures are taken. By applying the role-based approach to the authorization problem, we ease the sharing of information between hospital information systems and we reduce the administering part. The different initiative of the agent's migration method, results in different methods of assigning roles to the agent.

Needs, Pains, and Motivations in Autonomous Agents.

PubMed

Starzyk, Janusz A; Graham, James; Puzio, Leszek

This paper presents the development of a motivated learning (ML) agent with symbolic I/O. Our earlier work on the ML agent was enhanced, giving it autonomy for interaction with other agents. Specifically, we equipped the agent with drives and pains that establish its motivations to learn how to respond to desired and undesired events and create related abstract goals. The purpose of this paper is to explore the autonomous development of motivations and memory in agents within a simulated environment. The ML agent has been implemented in a virtual environment created within the NeoAxis game engine. Additionally, to illustrate the benefits of an ML-based agent, we compared the performance of our algorithm against various reinforcement learning (RL) algorithms in a dynamic test scenario, and demonstrated that our ML agent learns better than any of the tested RL agents.This paper presents the development of a motivated learning (ML) agent with symbolic I/O. Our earlier work on the ML agent was enhanced, giving it autonomy for interaction with other agents. Specifically, we equipped the agent with drives and pains that establish its motivations to learn how to respond to desired and undesired events and create related abstract goals. The purpose of this paper is to explore the autonomous development of motivations and memory in agents within a simulated environment. The ML agent has been implemented in a virtual environment created within the NeoAxis game engine. Additionally, to illustrate the benefits of an ML-based agent, we compared the performance of our algorithm against various reinforcement learning (RL) algorithms in a dynamic test scenario, and demonstrated that our ML agent learns better than any of the tested RL agents.

Mining Learning Social Networks for Cooperative Learning with Appropriate Learning Partners in a Problem-Based Learning Environment

ERIC Educational Resources Information Center

Chen, Chih-Ming; Chang, Chia-Cheng

2014-01-01

Many studies have identified web-based cooperative learning as an increasingly popular educational paradigm with potential to increase learner satisfaction and interactions. However, peer-to-peer interaction often suffers barriers owing to a failure to explore useful social interaction information in web-based cooperative learning environments.…

Constructing of Research-Oriented Learning Mode Based on Network Environment

ERIC Educational Resources Information Center

Wang, Ying; Li, Bing; Xie, Bai-zhi

2007-01-01

Research-oriented learning mode that based on network is significant to cultivate comprehensive-developing innovative person with network teaching in education for all-around development. This paper establishes a research-oriented learning mode by aiming at the problems existing in research-oriented learning based on network environment, and…

A Multi-Agent Question-Answering System for E-Learning and Collaborative Learning Environment

ERIC Educational Resources Information Center

Alinaghi, Tannaz; Bahreininejad, Ardeshir

2011-01-01

The increasing advances of new Internet technologies in all application domains have changed life styles and interactions. E-learning and collaborative learning environment systems are originated through such changes and aim at providing facilities for people in different times and geographical locations to cooperate, collaborate, learn and work…

An Autonomous Mobile Agent-Based Distributed Learning Architecture: A Proposal and Analytical Analysis

ERIC Educational Resources Information Center

Ahmed, Iftikhar; Sadeq, Muhammad Jafar

2006-01-01

Current distance learning systems are increasingly packing highly data-intensive contents on servers, resulting in the congestion of network and server resources at peak service times. A distributed learning system based on faded information field (FIF) architecture that employs mobile agents (MAs) has been proposed and simulated in this work. The…

PLATE: Powerful Learning and Teaching Environments

ERIC Educational Resources Information Center

Housand, Angela

2009-01-01

The environment has a profound effect on the ability of students to regulate their behavior or disposition and effectively engage in the learning processes. Active engagement is important because it increases performance. Certain types of environmental structures actually increase students' ability to be agents of their own learning. These…

Learning Tools for Knowledge Nomads: Using Personal Digital Assistants (PDAs) in Web-based Learning Environments.

ERIC Educational Resources Information Center

Loh, Christian Sebastian

2001-01-01

Examines how mobile computers, or personal digital assistants (PDAs), can be used in a Web-based learning environment. Topics include wireless networks on college campuses; online learning; Web-based learning technologies; synchronous and asynchronous communication via the Web; content resources; Web connections; and collaborative learning. (LRW)

Pupils' Views on an ICT-Based Learning Environment in Health Learning

ERIC Educational Resources Information Center

Räihä, Teija; Tossavainen, Kerttu; Enkenberg, Jorma; Turunen, Hannele

2014-01-01

This paper presents a study that examined pupils' views on an ICT-based learning environment in health learning. The study was a part of the wider European Network of Health Promoting Schools programme (ENHPS; since 2008, Schools for Health in Europe, SHE) in Finland, and particularly its sub-project, From Puijo to the World with Health Lunch,…

Design Principles of an Open Agent Architecture for Web-Based Learning Community.

ERIC Educational Resources Information Center

Jin, Qun; Ma, Jianhua; Huang, Runhe; Shih, Timothy K.

A Web-based learning community involves much more than putting learning materials into a Web site. It can be seen as a complex virtual organization involved with people, facilities, and cyber-environment. Tremendous work and manpower for maintaining, upgrading, and managing facilities and the cyber-environment are required. There is presented an…

Design and Control of Large Collections of Learning Agents

NASA Technical Reports Server (NTRS)

Agogino, Adrian

2001-01-01

The intelligent control of multiple autonomous agents is an important yet difficult task. Previous methods used to address this problem have proved to be either too brittle, too hard to use, or not scalable to large systems. The 'Collective Intelligence' project at NASA/Ames provides an elegant, machine-learning approach to address these problems. This approach mathematically defines some essential properties that a reward system should have to promote coordinated behavior among reinforcement learners. This work has focused on creating additional key properties and algorithms within the mathematics of the Collective Intelligence framework. One of the additions will allow agents to learn more quickly, in a more coordinated manner. The other will let agents learn with less knowledge of their environment. These additions will allow the framework to be applied more easily, to a much larger domain of multi-agent problems.

A Two-Stage Multi-Agent Based Assessment Approach to Enhance Students' Learning Motivation through Negotiated Skills Assessment

ERIC Educational Resources Information Center

Chadli, Abdelhafid; Bendella, Fatima; Tranvouez, Erwan

2015-01-01

In this paper we present an Agent-based evaluation approach in a context of Multi-agent simulation learning systems. Our evaluation model is based on a two stage assessment approach: (1) a Distributed skill evaluation combining agents and fuzzy sets theory; and (2) a Negotiation based evaluation of students' performance during a training…

Understanding and Predicting Student Self-Regulated Learning Strategies in Game-Based Learning Environments

ERIC Educational Resources Information Center

Sabourin, Jennifer L.; Shores, Lucy R.; Mott, Bradford W.; Lester, James C.

2013-01-01

Self-regulated learning behaviors such as goal setting and monitoring have been found to be crucial to students' success in computer-based learning environments. Consequently, understanding students' self-regulated learning behavior has been the subject of increasing attention. Unfortunately, monitoring these behaviors in real-time has…

A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

ERIC Educational Resources Information Center

Xiang, Lin

2011-01-01

This is a collective case study seeking to develop detailed descriptions of how programming an agent-based simulation influences a group of 8th grade students' model-based inquiry (MBI) by examining students' agent-based programmable modeling (ABPM) processes and the learning outcomes. The context of the present study was a biology unit on…

Cooperation and Coordination Between Fuzzy Reinforcement Learning Agents in Continuous State Partially Observable Markov Decision Processes

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.; Vengerov, David

1999-01-01

Successful operations of future multi-agent intelligent systems require efficient cooperation schemes between agents sharing learning experiences. We consider a pseudo-realistic world in which one or more opportunities appear and disappear in random locations. Agents use fuzzy reinforcement learning to learn which opportunities are most worthy of pursuing based on their promise rewards, expected lifetimes, path lengths and expected path costs. We show that this world is partially observable because the history of an agent influences the distribution of its future states. We consider a cooperation mechanism in which agents share experience by using and-updating one joint behavior policy. We also implement a coordination mechanism for allocating opportunities to different agents in the same world. Our results demonstrate that K cooperative agents each learning in a separate world over N time steps outperform K independent agents each learning in a separate world over K*N time steps, with this result becoming more pronounced as the degree of partial observability in the environment increases. We also show that cooperation between agents learning in the same world decreases performance with respect to independent agents. Since cooperation reduces diversity between agents, we conclude that diversity is a key parameter in the trade off between maximizing utility from cooperation when diversity is low and maximizing utility from competitive coordination when diversity is high.

Time-Extended Policies in Mult-Agent Reinforcement Learning

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Agogino, Adrian K.

2004-01-01

Reinforcement learning methods perform well in many domains where a single agent needs to take a sequence of actions to perform a task. These methods use sequences of single-time-step rewards to create a policy that tries to maximize a time-extended utility, which is a (possibly discounted) sum of these rewards. In this paper we build on our previous work showing how these methods can be extended to a multi-agent environment where each agent creates its own policy that works towards maximizing a time-extended global utility over all agents actions. We show improved methods for creating time-extended utilities for the agents that are both "aligned" with the global utility and "learnable." We then show how to crate single-time-step rewards while avoiding the pi fall of having rewards aligned with the global reward leading to utilities not aligned with the global utility. Finally, we apply these reward functions to the multi-agent Gridworld problem. We explicitly quantify a utility's learnability and alignment, and show that reinforcement learning agents using the prescribed reward functions successfully tradeoff learnability and alignment. As a result they outperform both global (e.g., team games ) and local (e.g., "perfectly learnable" ) reinforcement learning solutions by as much as an order of magnitude.

Shallow Strategy Development in a Teachable Agent Environment Designed to Support Self-Regulated Learning

ERIC Educational Resources Information Center

Roscoe, Rod D.; Segedy, James R.; Sulcer, Brian; Jeong, Hogyeong; Biswas, Gautam

2013-01-01

To support self-regulated learning (SRL), computer-based learning environments (CBLEs) are often designed to be open-ended and multidimensional. These systems incorporate diverse features that allow students to enact and reveal their SRL strategies via the choices they make. However, research shows that students' use of such features is limited;…

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…

Using Wikis as a Support and Assessment Tool in Collaborative Digital Game-Based Learning Environments

ERIC Educational Resources Information Center

Samur, Yavuz

2011-01-01

In computer-supported collaborative learning (CSCL) environments, there are many researches done on collaborative learning activities; however, in game-based learning environments, more research and literature on collaborative learning activities are required. Actually, both game-based learning environments and wikis enable us to use new chances…

An embodiment effect in computer-based learning with animated pedagogical agents.

PubMed

Mayer, Richard E; DaPra, C Scott

2012-09-01

How do social cues such as gesturing, facial expression, eye gaze, and human-like movement affect multimedia learning with onscreen agents? To help address this question, students were asked to twice view a 4-min narrated presentation on how solar cells work in which the screen showed an animated pedagogical agent standing to the left of 11 successive slides. Across three experiments, learners performed better on a transfer test when a human-voiced agent displayed human-like gestures, facial expression, eye gaze, and body movement than when the agent did not, yielding an embodiment effect. In Experiment 2 the embodiment effect was found when the agent spoke in a human voice but not in a machine voice. In Experiment 3, the embodiment effect was found both when students were told the onscreen agent was consistent with their choice of agent characteristics and when inconsistent. Students who viewed a highly embodied agent also rated the social attributes of the agent more positively than did students who viewed a nongesturing agent. The results are explained by social agency theory, in which social cues in a multimedia message prime a feeling of social partnership in the learner, which leads to deeper cognitive processing during learning, and results in a more meaningful learning outcome as reflected in transfer test performance.

Incremental learning of skill collections based on intrinsic motivation

PubMed Central

Metzen, Jan H.; Kirchner, Frank

2013-01-01

Life-long learning of reusable, versatile skills is a key prerequisite for embodied agents that act in a complex, dynamic environment and are faced with different tasks over their lifetime. We address the question of how an agent can learn useful skills efficiently during a developmental period, i.e., when no task is imposed on him and no external reward signal is provided. Learning of skills in a developmental period needs to be incremental and self-motivated. We propose a new incremental, task-independent skill discovery approach that is suited for continuous domains. Furthermore, the agent learns specific skills based on intrinsic motivation mechanisms that determine on which skills learning is focused at a given point in time. We evaluate the approach in a reinforcement learning setup in two continuous domains with complex dynamics. We show that an intrinsically motivated, skill learning agent outperforms an agent which learns task solutions from scratch. Furthermore, we compare different intrinsic motivation mechanisms and how efficiently they make use of the agent's developmental period. PMID:23898265

Agent Based Fault Tolerance for the Mobile Environment

NASA Astrophysics Data System (ADS)

Park, Taesoon

This paper presents a fault-tolerance scheme based on mobile agents for the reliable mobile computing systems. Mobility of the agent is suitable to trace the mobile hosts and the intelligence of the agent makes it efficient to support the fault tolerance services. This paper presents two approaches to implement the mobile agent based fault tolerant service and their performances are evaluated and compared with other fault-tolerant schemes.

Model-based reinforcement learning with dimension reduction.

PubMed

Tangkaratt, Voot; Morimoto, Jun; Sugiyama, Masashi

2016-12-01

The goal of reinforcement learning is to learn an optimal policy which controls an agent to acquire the maximum cumulative reward. The model-based reinforcement learning approach learns a transition model of the environment from data, and then derives the optimal policy using the transition model. However, learning an accurate transition model in high-dimensional environments requires a large amount of data which is difficult to obtain. To overcome this difficulty, in this paper, we propose to combine model-based reinforcement learning with the recently developed least-squares conditional entropy (LSCE) method, which simultaneously performs transition model estimation and dimension reduction. We also further extend the proposed method to imitation learning scenarios. The experimental results show that policy search combined with LSCE performs well for high-dimensional control tasks including real humanoid robot control. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

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

ERIC Educational Resources Information Center

Vandewaetere, Mieke; Vandercruysse, Sylke; Clarebout, Geraldine

2012-01-01

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

Work-based learning in health care environments.

PubMed

Spouse, J

2001-03-01

In reviewing contemporary literature and theories about work-based learning, this paper explores recent trends promoting life-long learning. In the process the paper reviews and discusses some implications of implementing recent policies and fostering le arning in health care practice settings. Recent Government policies designed to provide quality health care services and to improve staffing levels in the nursing workforce, have emphasized the importance of life-long learning whilst learning-on-the-job and the need to recognize and credit experiential learning. Such calls include negotiation of personal development plans tailored to individual educational need and context-sensitive learning activities. To be implemented effectively, this policy cann ot be seen as a cheap option but requires considerable financial resourcing for preparation of staff and the conduct of such activities. Successful work-based learning requires investment in staff at all levels as well as changes to staffing structures in organizations and trusts; changes designed to free people up to work and learn collaboratively. Creating an organizational environment where learning is prized depends upon a climate of trust; a climate where investigation and speculation are fostered and where time is protected for engaging in discussions about practice. Such a change may be radical for many health care organizations and may require a review of current policies and practices ensuring that they include education at all levels. The nature of such education also requires reconceptualizing. In the past, learning in practice settings was seen as formal lecturing or demonstration, and relied upon behaviourist principles of learning. Contemporary thinking suggests effective learning in work-settings is multi-faceted and draws on previously acquired formal knowledge, contextualizes it and moulds it according to situations at hand. Thinking about work-based learning in this way raises questions about how such

Social Learning Preferences of Adult Women Learners in a Competency-Based Online Learning Environment

ERIC Educational Resources Information Center

Lyman, Emily

2013-01-01

In this study a post-assessment survey was analyzed to seek for social learning preferences among women in a competency-based online learning environment. The survey asked what learning resources students used to prepare for the assessment. Each learning resource was given a relative sociability rating. This rating acts as the weighting for a…

Designing a Virtual-Reality-Based, Gamelike Math Learning Environment

ERIC Educational Resources Information Center

Xu, Xinhao; Ke, Fengfeng

2016-01-01

This exploratory study examined the design issues related to a virtual-reality-based, gamelike learning environment (VRGLE) developed via OpenSimulator, an open-source virtual reality server. The researchers collected qualitative data to examine the VRGLE's usability, playability, and content integration for math learning. They found it important…

Agent-specific learning signals for self-other distinction during mentalising.

PubMed

Ereira, Sam; Dolan, Raymond J; Kurth-Nelson, Zeb

2018-04-01

Humans have a remarkable ability to simulate the minds of others. How the brain distinguishes between mental states attributed to self and mental states attributed to someone else is unknown. Here, we investigated how fundamental neural learning signals are selectively attributed to different agents. Specifically, we asked whether learning signals are encoded in agent-specific neural patterns or whether a self-other distinction depends on encoding agent identity separately from this learning signal. To examine this, we tasked subjects to learn continuously 2 models of the same environment, such that one was selectively attributed to self and the other was selectively attributed to another agent. Combining computational modelling with magnetoencephalography (MEG) enabled us to track neural representations of prediction errors (PEs) and beliefs attributed to self, and of simulated PEs and beliefs attributed to another agent. We found that the representational pattern of a PE reliably predicts the identity of the agent to whom the signal is attributed, consistent with a neural self-other distinction implemented via agent-specific learning signals. Strikingly, subjects exhibiting a weaker neural self-other distinction also had a reduced behavioural capacity for self-other distinction and displayed more marked subclinical psychopathological traits. The neural self-other distinction was also modulated by social context, evidenced in a significantly reduced decoding of agent identity in a nonsocial control task. Thus, we show that self-other distinction is realised through an encoding of agent identity intrinsic to fundamental learning signals. The observation that the fidelity of this encoding predicts psychopathological traits is of interest as a potential neurocomputational psychiatric biomarker.

Self-Efficacy in Internet-Based Learning Environments: A Literature Review

ERIC Educational Resources Information Center

Tsai, Chin-Chung; Chuang, Shih-Chyueh; Liang, Jyh-Chong; Tsai, Meng-Jung

2011-01-01

This paper reviews 46 papers from 1999 to 2009 regarding self-efficacy in Internet-based learning environments, and discusses three major categories of research: (1) learners' Internet self-efficacy, assessing learners' confidence in their skills or knowledge of operating general Internet functions or applications in Internet-based learning; (2)…

Knowledge-Based Reinforcement Learning for Data Mining

NASA Astrophysics Data System (ADS)

Kudenko, Daniel; Grzes, Marek

experts have developed heuristics that help them in planning and scheduling resources in their work place. However, this domain knowledge is often rough and incomplete. When the domain knowledge is used directly by an automated expert system, the solutions are often sub-optimal, due to the incompleteness of the knowledge, the uncertainty of environments, and the possibility to encounter unexpected situations. RL, on the other hand, can overcome the weaknesses of the heuristic domain knowledge and produce optimal solutions. In the talk we propose two techniques, which represent first steps in the area of knowledge-based RL (KBRL). The first technique [1] uses high-level STRIPS operator knowledge in reward shaping to focus the search for the optimal policy. Empirical results show that the plan-based reward shaping approach outperforms other RL techniques, including alternative manual and MDP-based reward shaping when it is used in its basic form. We showed that MDP-based reward shaping may fail and successful experiments with STRIPS-based shaping suggest modifications which can overcome encountered problems. The STRIPSbased method we propose allows expressing the same domain knowledge in a different way and the domain expert can choose whether to define an MDP or STRIPS planning task. We also evaluated the robustness of the proposed STRIPS-based technique to errors in the plan knowledge. In case that STRIPS knowledge is not available, we propose a second technique [2] that shapes the reward with hierarchical tile coding. Where the Q-function is represented with low-level tile coding, a V-function with coarser tile coding can be learned in parallel and used to approximate the potential for ground states. In the context of data mining, our KBRL approaches can also be used for any data collection task where the acquisition of data may incur considerable cost. In addition, observing the data collection agent in specific scenarios may lead to new insights into optimal data

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.

An Electronic Library-Based Learning Environment for Supporting Web-Based Problem-Solving Activities

ERIC Educational Resources Information Center

Tsai, Pei-Shan; Hwang, Gwo-Jen; Tsai, Chin-Chung; Hung, Chun-Ming; Huang, Iwen

2012-01-01

This study aims to develop an electronic library-based learning environment to support teachers in developing web-based problem-solving activities and analyzing the online problem-solving behaviors of students. Two experiments were performed in this study. In study 1, an experiment on 103 elementary and high school teachers (the learning activity…

Interaction in Asynchronous Web-Based Learning Environments

ERIC Educational Resources Information Center

Woo, Younghee; Reeves, Thomas C.

2008-01-01

Because of the perceived advantages and the promotion of Web-based learning environments (WBLEs) by commercial interests as well as educational technologists, knowing how to develop and implement WBLEs will probably not be a choice, but a necessity for most educators and trainers in the future. However, many instructors still don't understand the…

A Neural Network Model to Learn Multiple Tasks under Dynamic Environments

NASA Astrophysics Data System (ADS)

Tsumori, Kenji; Ozawa, Seiichi

When environments are dynamically changed for agents, the knowledge acquired in an environment might be useless in future. In such dynamic environments, agents should be able to not only acquire new knowledge but also modify old knowledge in learning. However, modifying all knowledge acquired before is not efficient because the knowledge once acquired may be useful again when similar environment reappears and some knowledge can be shared among different environments. To learn efficiently in such environments, we propose a neural network model that consists of the following modules: resource allocating network, long-term & short-term memory, and environment change detector. We evaluate the model under a class of dynamic environments where multiple function approximation tasks are sequentially given. The experimental results demonstrate that the proposed model possesses stable incremental learning, accurate environmental change detection, proper association and recall of old knowledge, and efficient knowledge transfer.

Creating Effective Web-Based Learning Environments: Relevant Research and Practice

ERIC Educational Resources Information Center

Wijekumar, Kay

2005-01-01

Web-based learning environments are a great asset only if they are designed well and used as intended. The urgency to create courses in response to the growing demand for online learning has resulted in a hurried push to drop PowerPoint notes into Web-based course management systems (WBCMSs), devise an electronic quiz, put together a few…

Agent-specific learning signals for self–other distinction during mentalising

PubMed Central

Dolan, Raymond J.; Kurth-Nelson, Zeb

2018-01-01

Humans have a remarkable ability to simulate the minds of others. How the brain distinguishes between mental states attributed to self and mental states attributed to someone else is unknown. Here, we investigated how fundamental neural learning signals are selectively attributed to different agents. Specifically, we asked whether learning signals are encoded in agent-specific neural patterns or whether a self–other distinction depends on encoding agent identity separately from this learning signal. To examine this, we tasked subjects to learn continuously 2 models of the same environment, such that one was selectively attributed to self and the other was selectively attributed to another agent. Combining computational modelling with magnetoencephalography (MEG) enabled us to track neural representations of prediction errors (PEs) and beliefs attributed to self, and of simulated PEs and beliefs attributed to another agent. We found that the representational pattern of a PE reliably predicts the identity of the agent to whom the signal is attributed, consistent with a neural self–other distinction implemented via agent-specific learning signals. Strikingly, subjects exhibiting a weaker neural self–other distinction also had a reduced behavioural capacity for self–other distinction and displayed more marked subclinical psychopathological traits. The neural self–other distinction was also modulated by social context, evidenced in a significantly reduced decoding of agent identity in a nonsocial control task. Thus, we show that self–other distinction is realised through an encoding of agent identity intrinsic to fundamental learning signals. The observation that the fidelity of this encoding predicts psychopathological traits is of interest as a potential neurocomputational psychiatric biomarker. PMID:29689053

A multi-agent intelligent environment for medical knowledge.

PubMed

Vicari, Rosa M; Flores, Cecilia D; Silvestre, André M; Seixas, Louise J; Ladeira, Marcelo; Coelho, Helder

2003-03-01

AMPLIA is a multi-agent intelligent learning environment designed to support training of diagnostic reasoning and modelling of domains with complex and uncertain knowledge. AMPLIA focuses on the medical area. It is a system that deals with uncertainty under the Bayesian network approach, where learner-modelling tasks will consist of creating a Bayesian network for a problem the system will present. The construction of a network involves qualitative and quantitative aspects. The qualitative part concerns the network topology, that is, causal relations among the domain variables. After it is ready, the quantitative part is specified. It is composed of the distribution of conditional probability of the variables represented. A negotiation process (managed by an intelligent MediatorAgent) will treat the differences of topology and probability distribution between the model the learner built and the one built-in in the system. That negotiation process occurs between the agents that represent the expert knowledge domain (DomainAgent) and the agent that represents the learner knowledge (LearnerAgent).

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

PubMed Central

Lindström, Björn; Selbing, Ida; Olsson, Andreas

2016-01-01

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

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

PubMed

Lindström, Björn; Selbing, Ida; Olsson, Andreas

2016-01-01

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

The Effects of Study Tasks in a Computer-Based Chemistry Learning Environment

ERIC Educational Resources Information Center

Urhahne, Detlef; Nick, Sabine; Poepping, Anna Christin; Schulz , Sarah Jayne

2013-01-01

The present study examines the effects of different study tasks on the acquisition of knowledge about acids and bases in a computer-based learning environment. Three different task formats were selected to create three treatment conditions: learning with gap-fill and matching tasks, learning with multiple-choice tasks, and learning only from text…

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.

Investigating Learners' Attitudes toward Virtual Reality Learning Environments: Based on a Constructivist Approach

ERIC Educational Resources Information Center

Huang, Hsiu-Mei; Rauch, Ulrich; Liaw, Shu-Sheng

2010-01-01

The use of animation and multimedia for learning is now further extended by the provision of entire Virtual Reality Learning Environments (VRLE). This highlights a shift in Web-based learning from a conventional multimedia to a more immersive, interactive, intuitive and exciting VR learning environment. VRLEs simulate the real world through the…

Teacher in a Problem-Based Learning Environment--Jack of All Trades?

ERIC Educational Resources Information Center

Dahms, Mona Lisa; Spliid, Claus Monrad; Nielsen, Jens Frederik Dalsgaard

2017-01-01

Problem-based learning (PBL) is one among several approaches to active learning. Being a teacher in a PBL environment can, however, be a challenge because of the need to support students' learning within a broad "landscape of learning". In this article we will analyse the landscape of learning by use of the study activity model (SAM)…

Web-Based History Learning Environments: Helping All Students Learn and Like History

ERIC Educational Resources Information Center

Okolo, Cynthia M.; Englert, Carol Sue; Bouck, Emily C.; Heutsche, Anne M.

2007-01-01

This article explores the benefits of the Internet to enhance history instruction for all learners. The authors describe a Web-based learning environment, the Virtual History Museum (VHM), that helps teachers create motivating, inquiry-based history units. VHM also allows teachers to build supports for learners with disabilities or other learning…

Examining High-School Students' Preferences toward Learning Environments, Personal Beliefs and Concept Learning in Web-Based Contexts

ERIC Educational Resources Information Center

Yang, Fang-Ying; Chang, Cheng-Chieh

2009-01-01

The purpose of the study is to explore three kinds of personal affective traits among high-school students and their effects on web-based concept learning. The affective traits include personal preferences about web-based learning environments, personal epistemological beliefs, and beliefs about web-based learning. One hundred 11th graders…

Intelligent judgements over health risks in a spatial agent-based model.

PubMed

Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

2018-03-20

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of

The Effects of Study Tasks in a Computer-Based Chemistry Learning Environment

NASA Astrophysics Data System (ADS)

Urhahne, Detlef; Nick, Sabine; Poepping, Anna Christin; Schulz, Sarah Jayne

2013-12-01

The present study examines the effects of different study tasks on the acquisition of knowledge about acids and bases in a computer-based learning environment. Three different task formats were selected to create three treatment conditions: learning with gap-fill and matching tasks, learning with multiple-choice tasks, and learning only from text and figures without any additional tasks. Participants were 196 ninth-grade students who learned with a self-developed multimedia program in a pretest-posttest control group design. Research results reveal that gap-fill and matching tasks were most effective in promoting knowledge acquisition, followed by multiple-choice tasks, and no tasks at all. The findings are in line with previous research on this topic. The effects can possibly be explained by the generation-recognition model, which predicts that gap-fill and matching tasks trigger more encompassing learning processes than multiple-choice tasks. It is concluded that instructional designers should incorporate more challenging study tasks for enhancing the effectiveness of computer-based learning environments.

Learning in Virtual Forest: A Forest Ecosystem in the Web-Based Learning Environment

ERIC Educational Resources Information Center

Jussila, Terttu; Virtanen, Viivi

2014-01-01

Virtual Forest is a web-based, open-access learning environment about forests designed for primary-school pupils between the ages of 10 and 13 years. It is pedagogically designed to develop an understanding of ecology, to enhance conceptual development and to give a holistic view of forest ecosystems. Various learning tools, such as concept maps,…

Peer Feedback to Facilitate Project-Based Learning in an Online Environment

ERIC Educational Resources Information Center

Ching, Yu-Hui; Hsu, Yu-Chang

2013-01-01

There has been limited research examining the pedagogical benefits of peer feedback for facilitating project-based learning in an online environment. Using a mixed method approach, this paper examines graduate students' participation and perceptions of peer feedback activity that supports project-based learning in an online instructional design…

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

Introducing social cues in multimedia learning: The role of pedagogic agents' image and language in a scientific lesson

NASA Astrophysics Data System (ADS)

Moreno, Roxana Arleen

The present dissertation tested the hypothesis that software pedagogical agents can promote constructivist learning in a discovery-based multimedia environment. In a preliminary study, students who received a computer-based lesson on environmental science performed better on subsequent tests of problem solving and motivation when they learned with the mediation of a fictional agent compared to when they learned the same material from text. In order to investigate further the basis for this personal agent effect, I varied whether the agent's words were presented as speech or on-screen text and whether or not the agent's image appeared on the screen. Both with a fictional agent (Experiment 1) and a video of a human face (Experiment 2), students performed better on tests of retention, problem-solving transfer, and program ratings when words were presented as speech rather than on-screen text (producing a modality effect) but visual presence of the agent did not affect test performance (producing no image effect). Next, I varied whether or not the agent's words were presented in conversational style (i.e., as dialogue) or formal style (i.e., as monologue) both using speech (Experiment 3) and on-screen text (Experiment 4). In both experiments, there was a dialogue effect in which conversational-style produced better retention and transfer performance. Students who learned with conversational-style text rated the program more favorably than those who learned with monologue-style text. The results support cognitive principles of multimedia learning which underlie the understanding of a computer lesson about a complex scientific system.

Students' Expectations of the Learning Process in Virtual Reality and Simulation-Based Learning Environments

ERIC Educational Resources Information Center

Keskitalo, Tuulikki

2012-01-01

Expectations for simulations in healthcare education are high; however, little is known about healthcare students' expectations of the learning process in virtual reality (VR) and simulation-based learning environments (SBLEs). This research aims to describe first-year healthcare students' (N=97) expectations regarding teaching, studying, and…

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.

Learning Sequences of Actions in Collectives of Autonomous Agents

NASA Technical Reports Server (NTRS)

Turner, Kagan; Agogino, Adrian K.; Wolpert, David H.; Clancy, Daniel (Technical Monitor)

2001-01-01

In this paper we focus on the problem of designing a collective of autonomous agents that individually learn sequences of actions such that the resultant sequence of joint actions achieves a predetermined global objective. We are particularly interested in instances of this problem where centralized control is either impossible or impractical. For single agent systems in similar domains, machine learning methods (e.g., reinforcement learners) have been successfully used. However, applying such solutions directly to multi-agent systems often proves problematic, as agents may work at cross-purposes, or have difficulty in evaluating their contribution to achievement of the global objective, or both. Accordingly, the crucial design step in multiagent systems centers on determining the private objectives of each agent so that as the agents strive for those objectives, the system reaches a good global solution. In this work we consider a version of this problem involving multiple autonomous agents in a grid world. We use concepts from collective intelligence to design goals for the agents that are 'aligned' with the global goal, and are 'learnable' in that agents can readily see how their behavior affects their utility. We show that reinforcement learning agents using those goals outperform both 'natural' extensions of single agent algorithms and global reinforcement, learning solutions based on 'team games'.

Agent Reward Shaping for Alleviating Traffic Congestion

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Agogino, Adrian

2006-01-01

Traffic congestion problems provide a unique environment to study how multi-agent systems promote desired system level behavior. What is particularly interesting in this class of problems is that no individual action is intrinsically "bad" for the system but that combinations of actions among agents lead to undesirable outcomes, As a consequence, agents need to learn how to coordinate their actions with those of other agents, rather than learn a particular set of "good" actions. This problem is ubiquitous in various traffic problems, including selecting departure times for commuters, routes for airlines, and paths for data routers. In this paper we present a multi-agent approach to two traffic problems, where far each driver, an agent selects the most suitable action using reinforcement learning. The agent rewards are based on concepts from collectives and aim to provide the agents with rewards that are both easy to learn and that if learned, lead to good system level behavior. In the first problem, we study how agents learn the best departure times of drivers in a daily commuting environment and how following those departure times alleviates congestion. In the second problem, we study how agents learn to select desirable routes to improve traffic flow and minimize delays for. all drivers.. In both sets of experiments,. agents using collective-based rewards produced near optimal performance (93-96% of optimal) whereas agents using system rewards (63-68%) barely outperformed random action selection (62-64%) and agents using local rewards (48-72%) performed worse than random in some instances.

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

ERIC Educational Resources Information Center

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

2011-01-01

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

Multi-objective optimization of radiotherapy: distributed Q-learning and agent-based simulation

NASA Astrophysics Data System (ADS)

Jalalimanesh, Ammar; Haghighi, Hamidreza Shahabi; Ahmadi, Abbas; Hejazian, Hossein; Soltani, Madjid

2017-09-01

Radiotherapy (RT) is among the regular techniques for the treatment of cancerous tumours. Many of cancer patients are treated by this manner. Treatment planning is the most important phase in RT and it plays a key role in therapy quality achievement. As the goal of RT is to irradiate the tumour with adequately high levels of radiation while sparing neighbouring healthy tissues as much as possible, it is a multi-objective problem naturally. In this study, we propose an agent-based model of vascular tumour growth and also effects of RT. Next, we use multi-objective distributed Q-learning algorithm to find Pareto-optimal solutions for calculating RT dynamic dose. We consider multiple objectives and each group of optimizer agents attempt to optimise one of them, iteratively. At the end of each iteration, agents compromise the solutions to shape the Pareto-front of multi-objective problem. We propose a new approach by defining three schemes of treatment planning created based on different combinations of our objectives namely invasive, conservative and moderate. In invasive scheme, we enforce killing cancer cells and pay less attention about irradiation effects on normal cells. In conservative scheme, we take more care of normal cells and try to destroy cancer cells in a less stressed manner. The moderate scheme stands in between. For implementation, each of these schemes is handled by one agent in MDQ-learning algorithm and the Pareto optimal solutions are discovered by the collaboration of agents. By applying this methodology, we could reach Pareto treatment plans through building different scenarios of tumour growth and RT. The proposed multi-objective optimisation algorithm generates robust solutions and finds the best treatment plan for different conditions.

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.

Narrative-Based Interactive Learning Environments from Modelling Reasoning

ERIC Educational Resources Information Center

Yearwood, John; Stranieri, Andrew

2007-01-01

Narrative and story telling has a long history of use in structuring, organising and communicating human experience. This paper describes a narrative based interactive intelligent learning environment which aims to elucidate practical reasoning using interactive emergent narratives that can be used in training novices in decision making. Its…

Advances in Web-Based Education: Personalized Learning Environments

ERIC Educational Resources Information Center

Magoulas, George, Ed.; Chen, Sherry, Ed.

2006-01-01

Advances in technology are increasingly impacting the way in which curriculum is delivered and assessed. The emergence of the Internet has offered learners a new instructional delivery system that connects them with educational resources. "Advances in Web-Based Education: Personalized Learning Environments" covers a wide range of factors that…

Teacher in a problem-based learning environment - Jack of all trades?

NASA Astrophysics Data System (ADS)

Dahms, Mona Lisa; Spliid, Claus Monrad; Nielsen, Jens Frederik Dalsgaard

2017-11-01

Problem-based learning (PBL) is one among several approaches to active learning. Being a teacher in a PBL environment can, however, be a challenge because of the need to support students' learning within a broad 'landscape of learning'. In this article we will analyse the landscape of learning by use of the study activity model (SAM) developed by the Danish University Colleges, with the aim of investigating to which extent this may lead to explication and clarification concerning the challenges faced by teachers in a PBL environment. In the case study, the SAM is applied to the first semester of an engineering programme at Aalborg University, a university setting where the PBL approach to teaching and learning is dominant. The results of the analysis are presented and discussed, and the conclusion is that the model, in spite of some shortcomings, is useful in clarifying the role of the teacher in a PBL environment.

Problem-Based Learning in Multimodal Learning Environments: Learners' Technology Adoption Experiences

ERIC Educational Resources Information Center

Ioannou, Andri; Vasiliou, Christina; Zaphiris, Panayiotis

2016-01-01

In this study, we enhanced a problem-based learning (PBL) environment with affordable, everyday technologies that can be found in most university classrooms (e.g., projectors, tablets, students' own smartphones, traditional paper-pencil, and Facebook). The study was conducted over a 3-year period, with 60 postgraduate learners in a human-computer…

Development of Mechanistic Reasoning and Multilevel Explanations of Ecology in Third Grade Using Agent-Based Models

ERIC Educational Resources Information Center

Dickes, Amanda Catherine; Sengupta, Pratim; Farris, Amy Voss; Satabdi, Basu

2016-01-01

In this paper, we present a third-grade ecology learning environment that integrates two forms of modeling--embodied modeling and agent-based modeling (ABMs)--through the generation of mathematical representations that are common to both forms of modeling. The term "agent" in the context of ABMs indicates individual computational objects…

Designing a Web-Based Science Learning Environment for Model-Based Collaborative Inquiry

NASA Astrophysics Data System (ADS)

Sun, Daner; Looi, Chee-Kit

2013-02-01

The paper traces a research process in the design and development of a science learning environment called WiMVT (web-based inquirer with modeling and visualization technology). The WiMVT system is designed to help secondary school students build a sophisticated understanding of scientific conceptions, and the science inquiry process, as well as develop critical learning skills through model-based collaborative inquiry approach. It is intended to support collaborative inquiry, real-time social interaction, progressive modeling, and to provide multiple sources of scaffolding for students. We first discuss the theoretical underpinnings for synthesizing the WiMVT design framework, introduce the components and features of the system, and describe the proposed work flow of WiMVT instruction. We also elucidate our research approach that supports the development of the system. Finally, the findings of a pilot study are briefly presented to demonstrate of the potential for learning efficacy of the WiMVT implementation in science learning. Implications are drawn on how to improve the existing system, refine teaching strategies and provide feedback to researchers, designers and teachers. This pilot study informs designers like us on how to narrow the gap between the learning environment's intended design and its actual usage in the classroom.

Self-Regulation and Gender within a Game-Based Learning Environment

ERIC Educational Resources Information Center

Nietfeld, John L.; Shores, Lucy R.; Hoffmann, Kristin F.

2014-01-01

In this study, we examined how self-regulated learning (SRL) and gender influences performance in an educational game for 8th-grade students (N = 130). Crystal Island--Outbreak is an immersive, inquiry-based, narrative-centered learning environment featuring a microbiology science mystery aligned with 8th-grade science curriculum. SRL variables…

Cognitive and Affective Benefits of an Animated Pedagogical Agent for Learning English as a Second Language

ERIC Educational Resources Information Center

Choi, Sunhee; Clark, Richard E.

2006-01-01

This study compared the use of an animated pedagogical agent (agent) with an electronic arrow and voice narration (arrow and voice) in a multimedia learning environment where 74 college level English as a Second Language (ESL) students learned English relative clauses. No significant differences in learning or performance were found between the…

Quicker Q-Learning in Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Agogino, Adrian K.; Tumer, Kagan

2005-01-01

Multi-agent learning in Markov Decisions Problems is challenging because of the presence ot two credit assignment problems: 1) How to credit an action taken at time step t for rewards received at t' greater than t; and 2) How to credit an action taken by agent i considering the system reward is a function of the actions of all the agents. The first credit assignment problem is typically addressed with temporal difference methods such as Q-learning OK TD(lambda) The second credit assi,onment problem is typically addressed either by hand-crafting reward functions that assign proper credit to an agent, or by making certain independence assumptions about an agent's state-space and reward function. To address both credit assignment problems simultaneously, we propose the Q Updates with Immediate Counterfactual Rewards-learning (QUICR-learning) designed to improve both the convergence properties and performance of Q-learning in large multi-agent problems. Instead of assuming that an agent s value function can be made independent of other agents, this method suppresses the impact of other agents using counterfactual rewards. Results on multi-agent grid-world problems over multiple topologies show that QUICR-learning can achieve up to thirty fold improvements in performance over both conventional and local Q-learning in the largest tested systems.

University Students' Emotions, Interest and Activities in a Web-Based Learning Environment

ERIC Educational Resources Information Center

Nummenmaa, Minna; Nummenmaa, Lauri

2008-01-01

Background: Within academic settings, students experience varied emotions and interest towards learning. Although both emotions and interest can increase students' likelihood to engage in traditional learning, little is known about the influence of emotions and interest in learning activities in a web-based learning environment (WBLE). Aims: This…

Game-Based Learning in an OpenSim-Supported Virtual Environment on Perceived Motivational Quality of Learning

ERIC Educational Resources Information Center

Kim, Heesung; Ke, Fengfeng; Paek, Insu

2017-01-01

This experimental study was intended to examine whether game-based learning (GBL) that encompasses four particular game characteristics (challenges, a storyline, immediate rewards and the integration of game-play with learning content) in an OpenSimulator-supported virtual reality learning environment can improve perceived motivational quality of…

Multi-issue Agent Negotiation Based on Fairness

NASA Astrophysics Data System (ADS)

Zuo, Baohe; Zheng, Sue; Wu, Hong

Agent-based e-commerce service has become a hotspot now. How to make the agent negotiation process quickly and high-efficiently is the main research direction of this area. In the multi-issue model, MAUT(Multi-attribute Utility Theory) or its derived theory usually consider little about the fairness of both negotiators. This work presents a general model of agent negotiation which considered the satisfaction of both negotiators via autonomous learning. The model can evaluate offers from the opponent agent based on the satisfaction degree, learn online to get the opponent's knowledge from interactive instances of history and negotiation of this time, make concessions dynamically based on fair object. Through building the optimal negotiation model, the bilateral negotiation achieved a higher efficiency and fairer deal.

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…

The Acquisition of Integrated Science Process Skills in a Web-Based Learning Environment

ERIC Educational Resources Information Center

Saat, Rohaida Mohd

2004-01-01

Web-based learning is becoming prevalent in science learning. Some use specially designed programs, while others use materials available on the Internet. This qualitative case study examined the process of acquisition of integrated science process skills, particularly the skill of controlling variables, in a web-based learning environment among…

Enhancing Learning Outcomes with an Interactive Knowledge-Based Learning Environment Providing Narrative Feedback

ERIC Educational Resources Information Center

Stranieri, Andrew; Yearwood, John

2008-01-01

This paper describes a narrative-based interactive learning environment which aims to elucidate reasoning using interactive scenarios that may be used in training novices in decision-making. Its design is based on an approach to generating narrative from knowledge that has been modelled in specific decision/reasoning domains. The approach uses a…

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…

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…

Impact of audio narrated animation on students' understanding and learning environment based on gender

NASA Astrophysics Data System (ADS)

Nasrudin, Ajeng Ratih; Setiawan, Wawan; Sanjaya, Yayan

2017-05-01

This study is titled the impact of audio narrated animation on students' understanding in learning humanrespiratory system based on gender. This study was conducted in eight grade of junior high school. This study aims to investigate the difference of students' understanding and learning environment at boys and girls classes in learning human respiratory system using audio narrated animation. Research method that is used is quasy experiment with matching pre-test post-test comparison group design. The procedures of study are: (1) preliminary study and learning habituation using audio narrated animation; (2) implementation of learning using audio narrated animation and taking data; (3) analysis and discussion. The result of analysis shows that there is significant difference on students' understanding and learning environment at boys and girls classes in learning human respiratory system using audio narrated animation, both in general and specifically in achieving learning indicators. The discussion related to the impact of audio narrated animation, gender characteristics, and constructivist learning environment. It can be concluded that there is significant difference of students' understanding at boys and girls classes in learning human respiratory system using audio narrated animation. Additionally, based on interpretation of students' respond, there is the difference increment of agreement level in learning environment.

VET Students' Integration of Knowledge Engaged with in School-Based and Workplace-Based Learning Environments in the Netherlands

ERIC Educational Resources Information Center

Baartman, L. K. J.; Kilbrink, N.; de Bruijn, E.

2018-01-01

In vocational education, students learn in different school-based and workplace-based learning environments and engage with different types of knowledge in these environments. Students are expected to integrate these experiences and make meaning of them in relation to their own professional knowledge base. This study focuses both on…

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

NASA Astrophysics Data System (ADS)

Takaoka, Ryo; Shimokawa, Masayuki; Okamoto, Toshio

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

Learning other agents` preferences in multiagent negotiation

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

Bui, H.H.; Kieronska, D.; Venkatesh, S.

In multiagent systems, an agent does not usually have complete information about the preferences and decision making processes of other agents. This might prevent the agents from making coordinated choices, purely due to their ignorance of what others want. This paper describes the integration of a learning module into a communication-intensive negotiating agent architecture. The learning module gives the agents the ability to learn about other agents` preferences via past interactions. Over time, the agents can incrementally update their models of other agents` preferences and use them to make better coordinated decisions. Combining both communication and learning, as two complementmore » knowledge acquisition methods, helps to reduce the amount of communication needed on average, and is justified in situations where communication is computationally costly or simply not desirable (e.g. to preserve the individual privacy).« less

Instructional Designers' Media Selection Practices for Distributed Problem-Based Learning Environments

ERIC Educational Resources Information Center

Fells, Stephanie

2012-01-01

The design of online or distributed problem-based learning (dPBL) is a nascent, complex design problem. Instructional designers are challenged to effectively unite the constructivist principles of problem-based learning (PBL) with appropriate media in order to create quality dPBL environments. While computer-mediated communication (CMC) tools and…

Development and Evaluation of Mechatronics Learning System in a Web-Based Environment

ERIC Educational Resources Information Center

Shyr, Wen-Jye

2011-01-01

The development of remote laboratory suitable for the reinforcement of undergraduate level teaching of mechatronics is important. For the reason, a Web-based mechatronics learning system, called the RECOLAB (REmote COntrol LABoratory), for remote learning in engineering education has been developed in this study. The web-based environment is an…

A Competence-Based Service for Supporting Self-Regulated Learning in Virtual Environments

ERIC Educational Resources Information Center

Nussbaumer, Alexander; Hillemann, Eva-Catherine; Gütl, Christian; Albert, Dietrich

2015-01-01

This paper presents a conceptual approach and a Web-based service that aim at supporting self-regulated learning in virtual environments. The conceptual approach consists of four components: 1) a self-regulated learning model for supporting a learner-centred learning process, 2) a psychological model for facilitating competence-based…

Examining Collaborative Knowledge Construction in Microblogging-Based Learning Environments

ERIC Educational Resources Information Center

Luo, Tian; Clifton, Lacey

2017-01-01

Aim/Purpose: The purpose of the study is to provide foundational research to exemplify how knowledge construction takes place in microblogging-based learning environments, to understand learner interaction representing the knowledge construction process, and to analyze learner perception, thereby suggesting a model of delivery for microblogging.…

Gendered Practices of Constructing an Engineering Identity in a Problem-Based Learning Environment

ERIC Educational Resources Information Center

Du, Xiang-Yun

2006-01-01

This article examines the learning experiences of engineering students of both genders in a problem-based and project-organized learning environment (PBL) at a Danish university. This study relates an amalgam of theories on learning and gender to the context of engineering education. Based on data from a qualitative study of an electrical and…

Dynamic Educational e-Content Selection Using Multiple Criteria in Web-Based Personalized Learning Environments.

ERIC Educational Resources Information Center

Manouselis, Nikos; Sampson, Demetrios

This paper focuses on the way a multi-criteria decision making methodology is applied in the case of agent-based selection of offered learning objects. The problem of selection is modeled as a decision making one, with the decision variables being the learner model and the learning objects' educational description. In this way, selection of…

Reinforcement Learning Multi-Agent Modeling of Decision-Making Agents for the Study of Transboundary Surface Water Conflicts with Application to the Syr Darya River Basin

NASA Astrophysics Data System (ADS)

Riegels, N.; Siegfried, T.; Pereira Cardenal, S. J.; Jensen, R. A.; Bauer-Gottwein, P.

2008-12-01

In most economics--driven approaches to optimizing water use at the river basin scale, the system is modelled deterministically with the goal of maximizing overall benefits. However, actual operation and allocation decisions must be made under hydrologic and economic uncertainty. In addition, river basins often cross political boundaries, and different states may not be motivated to cooperate so as to maximize basin- scale benefits. Even within states, competing agents such as irrigation districts, municipal water agencies, and large industrial users may not have incentives to cooperate to realize efficiency gains identified in basin- level studies. More traditional simulation--optimization approaches assume pre-commitment by individual agents and stakeholders and unconditional compliance on each side. While this can help determine attainable gains and tradeoffs from efficient management, such hardwired policies do not account for dynamic feedback between agents themselves or between agents and their environments (e.g. due to climate change etc.). In reality however, we are dealing with an out-of-equilibrium multi-agent system, where there is neither global knowledge nor global control, but rather continuous strategic interaction between decision making agents. Based on the theory of stochastic games, we present a computational framework that allows for studying the dynamic feedback between decision--making agents themselves and an inherently uncertain environment in a spatially and temporally distributed manner. Agents with decision-making control over water allocation such as countries, irrigation districts, and municipalities are represented by reinforcement learning agents and coupled to a detailed hydrologic--economic model. This approach emphasizes learning by agents from their continuous interaction with other agents and the environment. It provides a convenient framework for the solution of the problem of dynamic decision-making in a mixed cooperative / non

Dynamic Scaffolding of Socially Regulated Learning in a Computer-Based Learning Environment

ERIC Educational Resources Information Center

Molenaar, Inge; Roda, Claudia; van Boxtel, Carla; Sleegers, Peter

2012-01-01

The aim of this study is to test the effects of dynamically scaffolding social regulation of middle school students working in a computer-based learning environment. Dyads in the scaffolding condition (N=56) are supported with computer-generated scaffolds and students in the control condition (N=54) do not receive scaffolds. The scaffolds are…

Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle

PubMed Central

Cerezo, Rebeca; Esteban, María; Sánchez-Santillán, Miguel; Núñez, José C.

2017-01-01

Introduction: Research about student performance has traditionally considered academic procrastination as a behavior that has negative effects on academic achievement. Although there is much evidence for this in class-based environments, there is a lack of research on Computer-Based Learning Environments (CBLEs). Therefore, the purpose of this study is to evaluate student behavior in a blended learning program and specifically procrastination behavior in relation to performance through Data Mining techniques. Materials and Methods: A sample of 140 undergraduate students participated in a blended learning experience implemented in a Moodle (Modular Object Oriented Developmental Learning Environment) Management System. Relevant interaction variables were selected for the study, taking into account student achievement and analyzing data by means of association rules, a mining technique. The association rules were arrived at and filtered through two selection criteria: 1, rules must have an accuracy over 0.8 and 2, they must be present in both sub-samples. Results: The findings of our study highlight the influence of time management in online learning environments, particularly on academic achievement, as there is an association between procrastination variables and student performance. Conclusion: Negative impact of procrastination in learning outcomes has been observed again but in virtual learning environments where practical implications, prevention of, and intervention in, are different from class-based learning. These aspects are discussed to help resolve student difficulties at various ages. PMID:28883801

Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle.

PubMed

Cerezo, Rebeca; Esteban, María; Sánchez-Santillán, Miguel; Núñez, José C

2017-01-01

Introduction: Research about student performance has traditionally considered academic procrastination as a behavior that has negative effects on academic achievement. Although there is much evidence for this in class-based environments, there is a lack of research on Computer-Based Learning Environments (CBLEs) . Therefore, the purpose of this study is to evaluate student behavior in a blended learning program and specifically procrastination behavior in relation to performance through Data Mining techniques. Materials and Methods: A sample of 140 undergraduate students participated in a blended learning experience implemented in a Moodle (Modular Object Oriented Developmental Learning Environment) Management System. Relevant interaction variables were selected for the study, taking into account student achievement and analyzing data by means of association rules, a mining technique. The association rules were arrived at and filtered through two selection criteria: 1, rules must have an accuracy over 0.8 and 2, they must be present in both sub-samples. Results: The findings of our study highlight the influence of time management in online learning environments, particularly on academic achievement, as there is an association between procrastination variables and student performance. Conclusion: Negative impact of procrastination in learning outcomes has been observed again but in virtual learning environments where practical implications, prevention of, and intervention in, are different from class-based learning. These aspects are discussed to help resolve student difficulties at various ages.

Real-time modeling of primitive environments through wavelet sensors and Hebbian learning

NASA Astrophysics Data System (ADS)

Vaccaro, James M.; Yaworsky, Paul S.

1999-06-01

Modeling the world through sensory input necessarily provides a unique perspective for the observer. Given a limited perspective, objects and events cannot always be encoded precisely but must involve crude, quick approximations to deal with sensory information in a real- time manner. As an example, when avoiding an oncoming car, a pedestrian needs to identify the fact that a car is approaching before ascertaining the model or color of the vehicle. In our methodology, we use wavelet-based sensors with self-organized learning to encode basic sensory information in real-time. The wavelet-based sensors provide necessary transformations while a rank-based Hebbian learning scheme encodes a self-organized environment through translation, scale and orientation invariant sensors. Such a self-organized environment is made possible by combining wavelet sets which are orthonormal, log-scale with linear orientation and have automatically generated membership functions. In earlier work we used Gabor wavelet filters, rank-based Hebbian learning and an exponential modulation function to encode textural information from images. Many different types of modulation are possible, but based on biological findings the exponential modulation function provided a good approximation of first spike coding of `integrate and fire' neurons. These types of Hebbian encoding schemes (e.g., exponential modulation, etc.) are useful for quick response and learning, provide several advantages over contemporary neural network learning approaches, and have been found to quantize data nonlinearly. By combining wavelets with Hebbian learning we can provide a real-time front-end for modeling an intelligent process, such as the autonomous control of agents in a simulated environment.

Optimizing T-Learning Course Scheduling Based on Genetic Algorithm in Benefit-Oriented Data Broadcast Environments

ERIC Educational Resources Information Center

Huang, Yong-Ming; Chen, Chao-Chun; Wang, Ding-Chau

2012-01-01

Ubiquitous learning receives much attention in these few years due to its wide spectrum of applications, such as the T-learning application. The learner can use mobile devices to watch the digital TV based course content, and thus, the T-learning provides the ubiquitous learning environment. However, in real-world data broadcast environments, the…

Creating a Project-Based Learning Environment to Improve Project Management Skills of Graduate Students

ERIC Educational Resources Information Center

Arantes do Amaral, Joao Alberto; Gonçalves, Paulo; Hess, Aurélio

2015-01-01

This article describes the project-based learning environment created to support project management graduate courses. The paper will focus on the learning context and procedures followed for 13 years, in 47 project-based learning MBA courses, involving approximately 1,400 students and 34 community partners.

A Multi-Agent Environment for Negotiation

NASA Astrophysics Data System (ADS)

Hindriks, Koen V.; Jonker, Catholijn M.; Tykhonov, Dmytro

In this chapter we introduce the System for Analysis of Multi-Issue Negotiation (SAMIN). SAMIN offers a negotiation environment that supports and facilitates the setup of various negotiation setups. The environment has been designed to analyse negotiation processes between human negotiators, between human and software agents, and between software agents. It offers a range of different agents, different domains, and other options useful to define a negotiation setup. The environment has been used to test and evaluate a range of negotiation strategies in various domains playing against other negotiating agents as well as humans. We discuss some of the results obtained by means of these experiments.

Construction of a Digital Learning Environment Based on Cloud Computing

ERIC Educational Resources Information Center

Ding, Jihong; Xiong, Caiping; Liu, Huazhong

2015-01-01

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

Effects of Pedagogical Agent Gestures on Social Acceptance and Learning: Virtual Real Relationships in an Elementary Foreign Language Classroom

ERIC Educational Resources Information Center

Davis, Robert; Antonenko, Pavlo

2017-01-01

Pedagogical agents (PAs) are lifelike characters in virtual environments that help facilitate learning through social interactions and the virtual real relationships with the learners. This study explored whether and how PA gesture design impacts learning and agent social acceptance when used with elementary students learning foreign language…

Development and Evaluation of an RFID-Based Ubiquitous Learning Environment for Outdoor Learning

ERIC Educational Resources Information Center

Tan, Tan-Hsu; Liu, Tsung-Yu; Chang, Chi-Cheng

2007-01-01

Many issues have been identified in outdoor teaching, especially in places that lack the capacity to effectively present information about such subjects as historical relics, rare animals, and geological landscapes. This study proposes an Environment of Ubiquitous Learning with Educational Resources (EULER) based on radio frequency identification…

Mapping Context-Based Learning Environments: The Construction of an Instrument

ERIC Educational Resources Information Center

de Putter-Smits, L. G. A.; Taconis, R.; Jochems, W. M. G.

2013-01-01

The current trend in science curricula is to adopt a context-based pedagogical approach to teaching. New study materials for this innovation are often designed by teachers working with university experts. In this article, it is proposed that teachers need to acquire corresponding teaching competences to create a context-based learning environment.…

A validated agent-based model to study the spatial and temporal heterogeneities of malaria incidence in the rainforest environment.

PubMed

Pizzitutti, Francesco; Pan, William; Barbieri, Alisson; Miranda, J Jaime; Feingold, Beth; Guedes, Gilvan R; Alarcon-Valenzuela, Javiera; Mena, Carlos F

2015-12-22

The Amazon environment has been exposed in the last decades to radical changes that have been accompanied by a remarkable rise of both Plasmodium falciparum and Plasmodium vivax malaria. The malaria transmission process is highly influenced by factors such as spatial and temporal heterogeneities of the environment and individual-based characteristics of mosquitoes and humans populations. All these determinant factors can be simulated effectively trough agent-based models. This paper presents a validated agent-based model of local-scale malaria transmission. The model reproduces the environment of a typical riverine village in the northern Peruvian Amazon, where the malaria transmission is highly seasonal and apparently associated with flooding of large areas caused by the neighbouring river. Agents representing humans, mosquitoes and the two species of Plasmodium (P. falciparum and P. vivax) are simulated in a spatially explicit representation of the environment around the village. The model environment includes: climate, people houses positions and elevation. A representation of changes in the mosquito breeding areas extension caused by the river flooding is also included in the simulation environment. A calibration process was carried out to reproduce the variations of the malaria monthly incidence over a period of 3 years. The calibrated model is also able to reproduce the spatial heterogeneities of local scale malaria transmission. A "what if" eradication strategy scenario is proposed: if the mosquito breeding sites are eliminated through mosquito larva habitat management in a buffer area extended at least 200 m around the village, the malaria transmission is eradicated from the village. The use of agent-based models can reproduce effectively the spatiotemporal variations of the malaria transmission in a low endemicity environment dominated by river floodings like in the Amazon.

Humor as a facilitative style in problem-based learning environments for nursing students.

PubMed

Chauvet, Seanna; Hofmeyer, Anne

2007-05-01

Although the nursing and education literature confirm that humor has a role to play in the learning experience, there is little evidence available about the impact and the challenges of using humor to facilitate group process and learning in problem-based learning environments for nursing students. In this paper, we explore humor as a style of communication in PBL environments using examples from the classroom. We then propose a range of strategies to build capacity in PBL tutors and to infuse humor into the PBL classroom such as: acceptance that fun and humor are components of the ground rules in the group; appropriate humor and boundaries; mutual story sharing; and creative activities to moderate stress and build coping strategies to thrive in clinical practice. It is timely for nurse academics and researchers to examine the contribution of humor as a facilitative communication style in the PBL environment. Findings could inform evidence-based teaching of nursing students and foster life-long learning and communication skills.

Scenario-Based Spoken Interaction with Virtual Agents

ERIC Educational Resources Information Center

Morton, Hazel; Jack, Mervyn A.

2005-01-01

This paper describes a CALL approach which integrates software for speaker independent continuous speech recognition with embodied virtual agents and virtual worlds to create an immersive environment in which learners can converse in the target language in contextualised scenarios. The result is a self-access learning package: SPELL (Spoken…

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

ERIC Educational Resources Information Center

Yilmaz, M. Betul; Orhan, Feza

2010-01-01

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

The "proactive" model of learning: Integrative framework for model-free and model-based reinforcement learning utilizing the associative learning-based proactive brain concept.

PubMed

Zsuga, Judit; Biro, Klara; Papp, Csaba; Tajti, Gabor; Gesztelyi, Rudolf

2016-02-01

Reinforcement learning (RL) is a powerful concept underlying forms of associative learning governed by the use of a scalar reward signal, with learning taking place if expectations are violated. RL may be assessed using model-based and model-free approaches. Model-based reinforcement learning involves the amygdala, the hippocampus, and the orbitofrontal cortex (OFC). The model-free system involves the pedunculopontine-tegmental nucleus (PPTgN), the ventral tegmental area (VTA) and the ventral striatum (VS). Based on the functional connectivity of VS, model-free and model based RL systems center on the VS that by integrating model-free signals (received as reward prediction error) and model-based reward related input computes value. Using the concept of reinforcement learning agent we propose that the VS serves as the value function component of the RL agent. Regarding the model utilized for model-based computations we turned to the proactive brain concept, which offers an ubiquitous function for the default network based on its great functional overlap with contextual associative areas. Hence, by means of the default network the brain continuously organizes its environment into context frames enabling the formulation of analogy-based association that are turned into predictions of what to expect. The OFC integrates reward-related information into context frames upon computing reward expectation by compiling stimulus-reward and context-reward information offered by the amygdala and hippocampus, respectively. Furthermore we suggest that the integration of model-based expectations regarding reward into the value signal is further supported by the efferent of the OFC that reach structures canonical for model-free learning (e.g., the PPTgN, VTA, and VS). (c) 2016 APA, all rights reserved).

The Impact of Learner Attributes and Learner Choice in an Agent-Based Environment

ERIC Educational Resources Information Center

Kim, Yanghee; Wei, Quan

2011-01-01

This study examined the impact of learners' attributes (gender and ethnicity) on their choice of a pedagogical agent and the impact of the attributes and choice on their perceptions of agent affability, task-specific attitudes, task-specific self-efficacy, and learning gains. Participants were 210 high-school male and female, Caucasian and…

EvoBuild: A Quickstart Toolkit for Programming Agent-Based Models of Evolutionary Processes

NASA Astrophysics Data System (ADS)

Wagh, Aditi; Wilensky, Uri

2018-04-01

Extensive research has shown that one of the benefits of programming to learn about scientific phenomena is that it facilitates learning about mechanisms underlying the phenomenon. However, using programming activities in classrooms is associated with costs such as requiring additional time to learn to program or students needing prior experience with programming. This paper presents a class of programming environments that we call quickstart: Environments with a negligible threshold for entry into programming and a modest ceiling. We posit that such environments can provide benefits of programming for learning without incurring associated costs for novice programmers. To make this claim, we present a design-based research study conducted to compare programming models of evolutionary processes with a quickstart toolkit with exploring pre-built models of the same processes. The study was conducted in six seventh grade science classes in two schools. Students in the programming condition used EvoBuild, a quickstart toolkit for programming agent-based models of evolutionary processes, to build their NetLogo models. Students in the exploration condition used pre-built NetLogo models. We demonstrate that although students came from a range of academic backgrounds without prior programming experience, and all students spent the same number of class periods on the activities including the time students took to learn programming in this environment, EvoBuild students showed greater learning about evolutionary mechanisms. We discuss the implications of this work for design research on programming environments in K-12 science education.

Feedback and Feed-Forward for Promoting Problem-Based Learning in Online Learning Environments

ERIC Educational Resources Information Center

Webb, Ashley; Moallem, Mahnaz

2016-01-01

Purpose: The study aimed to (1) review the literature to construct conceptual models that could guide instructional designers in developing problem/project-based learning environments while applying effective feedback strategies, (2) use the models to design, develop, and implement an online graduate course, and (3) assess the efficiency of the…

Teachable Agents and the Protégé Effect: Increasing the Effort Towards Learning

NASA Astrophysics Data System (ADS)

Chase, Catherine C.; Chin, Doris B.; Oppezzo, Marily A.; Schwartz, Daniel L.

2009-08-01

Betty's Brain is a computer-based learning environment that capitalizes on the social aspects of learning. In Betty's Brain, students instruct a character called a Teachable Agent (TA) which can reason based on how it is taught. Two studies demonstrate the protégé effect: students make greater effort to learn for their TAs than they do for themselves. The first study involved 8th-grade students learning biology. Although all students worked with the same Betty's Brain software, students in the TA condition believed they were teaching their TAs, while in another condition, they believed they were learning for themselves. TA students spent more time on learning activities (e.g., reading) and also learned more. These beneficial effects were most pronounced for lower achieving children. The second study used a verbal protocol with 5th-grade students to determine the possible causes of the protégé effect. As before, students learned either for their TAs or for themselves. Like study 1, students in the TA condition spent more time on learning activities. These children treated their TAs socially by attributing mental states and responsibility to them. They were also more likely to acknowledge errors by displaying negative affect and making attributions for the causes of failures. Perhaps having a TA invokes a sense of responsibility that motivates learning, provides an environment in which knowledge can be improved through revision, and protects students' egos from the psychological ramifications of failure.

Designing a Web-Based Science Learning Environment for Model-Based Collaborative Inquiry

ERIC Educational Resources Information Center

Sun, Daner; Looi, Chee-Kit

2013-01-01

The paper traces a research process in the design and development of a science learning environment called WiMVT (web-based inquirer with modeling and visualization technology). The WiMVT system is designed to help secondary school students build a sophisticated understanding of scientific conceptions, and the science inquiry process, as well as…

Software Agents to Assist in Distance Learning Environments

ERIC Educational Resources Information Center

Choy, Sheung-On; Ng, Sin-Chun; Tsang, Yiu-Chung

2005-01-01

The Open University of Hong Kong (OUHK) is a distance education university with about 22,500 students. In fulfilling its mission, the university has adopted various Web-based and electronic means to support distance learning. For instance, OUHK uses a Web-based course management system (CMS) to provide students with a flexible way to obtain course…

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

ERIC Educational Resources Information Center

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

2017-01-01

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

The Asset-Based Context Matrix: A Tool for Assessing Children's Learning Opportunities and Participation in Natural Environments

ERIC Educational Resources Information Center

Wilson, Linda L.; Mott, Donald W.; Batman, Deb

2004-01-01

This article provides a description of the "Asset-Based Context Matrix" (ABC Matrix). The ABC Matrix is an assessment tool for designing interventions for children in natural learning environments. The tool is based on research evidence indicating that children's learning is enhanced in contextually meaningful learning environments. The ABC Matrix…

Multi-agents and learning: Implications for Webusage mining.

PubMed

Lotfy, Hewayda M S; Khamis, Soheir M S; Aboghazalah, Maie M

2016-03-01

Characterization of user activities is an important issue in the design and maintenance of websites. Server weblog files have abundant information about the user's current interests. This information can be mined and analyzed therefore the administrators may be able to guide the users in their browsing activity so they may obtain relevant information in a shorter span of time to obtain user satisfaction. Web-based technology facilitates the creation of personally meaningful and socially useful knowledge through supportive interactions, communication and collaboration among educators, learners and information. This paper suggests a new methodology based on learning techniques for a Web-based Multiagent-based application to discover the hidden patterns in the user's visited links. It presents a new approach that involves unsupervised, reinforcement learning, and cooperation between agents. It is utilized to discover patterns that represent the user's profiles in a sample website into specific categories of materials using significance percentages. These profiles are used to make recommendations of interesting links and categories to the user. The experimental results of the approach showed successful user pattern recognition, and cooperative learning among agents to obtain user profiles. It indicates that combining different learning algorithms is capable of improving user satisfaction indicated by the percentage of precision, recall, the progressive category weight and F 1-measure.

Students' Views about the Problem Based Collaborative Learning Environment Supported by Dynamic Web Technologies

ERIC Educational Resources Information Center

Ünal, Erhan; Çakir, Hasan

2017-01-01

The purpose of this study was to design a problem based collaborative learning environment supported by dynamic web technologies and to examine students' views about this learning environment. The study was designed as a qualitative research. Some 36 students who took an Object Oriented Programming I-II course at the department of computer…

An Immune Agent for Web-Based AI Course

ERIC Educational Resources Information Center

Gong, Tao; Cai, Zixing

2006-01-01

To overcome weakness and faults of a web-based e-learning course such as Artificial Intelligence (AI), an immune agent was proposed, simulating a natural immune mechanism against a virus. The immune agent was built on the multi-dimension education agent model and immune algorithm. The web-based AI course was comprised of many files, such as HTML…

Fuzzy Q-Learning for Generalization of Reinforcement Learning

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1996-01-01

Fuzzy Q-Learning, introduced earlier by the author, is an extension of Q-Learning into fuzzy environments. GARIC is a methodology for fuzzy reinforcement learning. In this paper, we introduce GARIC-Q, a new method for doing incremental Dynamic Programming using a society of intelligent agents which are controlled at the top level by Fuzzy Q-Learning and at the local level, each agent learns and operates based on GARIC. GARIC-Q improves the speed and applicability of Fuzzy Q-Learning through generalization of input space by using fuzzy rules and bridges the gap between Q-Learning and rule based intelligent systems.

An evaluation of an interprofessional practice-based learning environment using student reflections.

PubMed

Housley, Cora L; Neill, Kathryn K; White, Lanita S; Tedder, Andrea T; Castleberry, Ashley N

2018-01-01

The 12th Street Health and Wellness Center is an interprofessional, student-led, community-based clinic. Students from all University of Arkansas for Medical Sciences colleges work together to provide healthcare services for residents of an underserved community. Interprofessional student teams assess patients and present to an interprofessional preceptor team. At the conclusion of clinic, teams reflect on their experience. The objective of this study is to generate key themes from the end of clinic reflections to describe learning outcomes in an interprofessional practice environment. Student teams were asked to reflect on what they learned about patient care and interprofessional practice while volunteering at the clinic. Three hundred eighty reflection statements were assessed using the constant comparative approach with open coding by three researchers who identified and categorised themes by selecting key phrases from reflections. Eight themes emerged from this process which illuminated students' self-perceived development during practice-based learning and interprofessional collaboration. Key phrases were also coded to the four core Interprofessional Education Collaborative competency domains. These results suggest learners' perception that the Center is a practice-based environment that provides an opportunity to learn, integrate, and apply interprofessional curricular content.

Student perceptions of a virtual learning environment for a problem-based learning undergraduate medical curriculum.

PubMed

de Leng, Bas A; Dolmans, Diana H J M; Muijtjens, Arno M M; van der Vleuten, Cees P M

2006-06-01

To investigate the effects of a virtual learning environment (VLE) on group interaction and consultation of information resources during the preliminary phase, self-study phase and reporting phase of the problem-based learning process in an undergraduate medical curriculum. A questionnaire was administered to 355 medical students in Years 1 and 2 to ask them about the perceived usefulness of a virtual learning environment that was created with Blackboard for group interaction and the use of learning resources. The students indicated that the VLE supported face-to-face interaction in the preliminary discussion and in the reporting phase but did not stimulate computer-mediated distance interaction during the self-study phase. They perceived that the use of multimedia in case presentations led to a better quality of group discussion than if case presentations were exclusively text-based. They also indicated that the information resources that were hyperlinked in the VLE stimulated the consultation of these resources during self-study, but not during the reporting phase. Students indicated that the use of a VLE in the tutorial room and the inclusion of multimedia in case presentations supported processes of active learning in the tutorial groups. However, if we want to exploit the full potential of asynchronous computer-mediated communication to initiate in-depth discussion during the self-study phase, its application will have to be selective and deliberate. Students indicated that the links in the VLE to selected information in library repositories supported their learning.

Transformation for Adults in an Internet-Based Learning Environment--Is It Necessary to Be Self-Directed?

ERIC Educational Resources Information Center

Chu, Regina Juchun; Chu, Anita Zichun; Weng, Cathy; Tsai, Chin-Chung; Lin, Chia-chun

2012-01-01

This research explores the relationships between self-directed learning readiness and transformative learning theory (TLT) reflected by the Constructivist Internet-based Learning Environment Scale (CILES). A questionnaire survey about adult learner's perceptions of Internet-based learning was administered to adults enrolled in classes in community…

An instrument to characterize the environment for residents' evidence-based medicine learning and practice.

PubMed

Mi, Misa; Moseley, James L; Green, Michael L

2012-02-01

Many residency programs offer training in evidence-based medicine (EBM). However, these curricula often fail to achieve optimal learning outcomes, perhaps because they neglect various contextual factors in the learning environment. We developed and validated an instrument to characterize the environment for EBM learning and practice in residency programs. An EBM Environment Scale was developed following scale development principles. A survey was administered to residents across six programs in primary care specialties at four medical centers. Internal consistency reliability was analyzed with Cronbach's coefficient alpha. Validity was assessed by comparing predetermined subscales with the survey's internal structure as assessed via factor analysis. Scores were also compared for subgroups based on residency program affiliation and residency characteristics. Out of 262 eligible residents, 124 completed the survey (response rate 47%). The overall mean score was 3.89 (standard deviation=0.56). The initial reliability analysis of the 48-item scale had a high reliability coefficient (Cronbach α=.94). Factor analysis and further item analysis resulted in a shorter 36-item scale with a satisfactory reliability coefficient (Cronbach α=.86). Scores were higher for residents with prior EBM training in medical school (4.14 versus 3.62) and in residency (4.25 versus 3.69). If further testing confirms its properties, the EBM Environment Scale may be used to understand the influence of the learning environment on the effectiveness of EBM training. Additionally, it may detect changes in the EBM learning environment in response to programmatic or institutional interventions.

A Web-Based Learning Support System for Inquiry-Based Learning

NASA Astrophysics Data System (ADS)

Kim, Dong Won; Yao, Jingtao

The emergence of the Internet and Web technology makes it possible to implement the ideals of inquiry-based learning, in which students seek truth, information, or knowledge by questioning. Web-based learning support systems can provide a good framework for inquiry-based learning. This article presents a study on a Web-based learning support system called Online Treasure Hunt. The Web-based learning support system mainly consists of a teaching support subsystem, a learning support subsystem, and a treasure hunt game. The teaching support subsystem allows instructors to design their own inquiry-based learning environments. The learning support subsystem supports students' inquiry activities. The treasure hunt game enables students to investigate new knowledge, develop ideas, and review their findings. Online Treasure Hunt complies with a treasure hunt model. The treasure hunt model formalizes a general treasure hunt game to contain the learning strategies of inquiry-based learning. This Web-based learning support system empowered with the online-learning game and founded on the sound learning strategies furnishes students with the interactive and collaborative student-centered learning environment.

College Students' Conceptions of Learning Management: The Difference between Traditional (Face-to-Face) Instruction and Web-Based Learning Environments

ERIC Educational Resources Information Center

Lin, Hung-Ming; Tsai, Chin-Chung

2011-01-01

This study investigates the differences between students' conceptions of learning management via traditional instruction and Web-based learning environments. The Conceptions of Learning Management Inventory (COLM) was administered to 259 Taiwanese college students majoring in Business Administration. The COLM has six factors (categories), namely,…

Engaging Learners through Interactive Media: Findings and Implications from a Technology Enhanced Problem-Based Learning Environment

ERIC Educational Resources Information Center

Horton, Lucas; Liu, Min; Olmanson, Justin; Toprac, Paul

2011-01-01

In this paper we explore students' engagement in a new media enhanced problem-based learning (PBL) environment and investigate the characteristics of these environments that facilitate learning. We investigated both student experiences using a new media enhanced PBL environment and the specific elements students found most supportive of their…

Fifth Graders' Flow Experience in a Digital Game-Based Science Learning Environment

ERIC Educational Resources Information Center

Zheng, Meixun

2012-01-01

This mixed methods study examined the flow experience of 5th graders in the CRYSTAL ISLAND game-based science learning environment. Participants were 73 5th graders from a suburban public school in the southeastern US. Quantitative data about students' science content learning and attitudes towards science was collected via pre-and post surveys.…

The Influence of Self-Regulated Learning and Prior Knowledge on Knowledge Acquisition in Computer-Based Learning Environments

ERIC Educational Resources Information Center

Bernacki, Matthew

2010-01-01

This study examined how learners construct textbase and situation model knowledge in hypertext computer-based learning environments (CBLEs) and documented the influence of specific self-regulated learning (SRL) tactics, prior knowledge, and characteristics of the learner on posttest knowledge scores from exposure to a hypertext. A sample of 160…

Multi-agents and learning: Implications for Webusage mining

PubMed Central

Lotfy, Hewayda M.S.; Khamis, Soheir M.S.; Aboghazalah, Maie M.

2015-01-01

Characterization of user activities is an important issue in the design and maintenance of websites. Server weblog files have abundant information about the user’s current interests. This information can be mined and analyzed therefore the administrators may be able to guide the users in their browsing activity so they may obtain relevant information in a shorter span of time to obtain user satisfaction. Web-based technology facilitates the creation of personally meaningful and socially useful knowledge through supportive interactions, communication and collaboration among educators, learners and information. This paper suggests a new methodology based on learning techniques for a Web-based Multiagent-based application to discover the hidden patterns in the user’s visited links. It presents a new approach that involves unsupervised, reinforcement learning, and cooperation between agents. It is utilized to discover patterns that represent the user’s profiles in a sample website into specific categories of materials using significance percentages. These profiles are used to make recommendations of interesting links and categories to the user. The experimental results of the approach showed successful user pattern recognition, and cooperative learning among agents to obtain user profiles. It indicates that combining different learning algorithms is capable of improving user satisfaction indicated by the percentage of precision, recall, the progressive category weight and F1-measure. PMID:26966569

Virtual Solar System Project: Learning through a Technology-Rich, Inquiry-Based, Participatory Learning Environment.

ERIC Educational Resources Information Center

Barab, Sasha A.; Hay, Kenneth E.; Squire, Kurt; Barnett, Michael; Schmidt, Rae; Karrigan, Kristen; Yamagata-Lynch, Lisa; Johnson, Christine

2000-01-01

Describes an introductory undergraduate astronomy course in which the large-lecture format was moved to one in which students were immersed in a technologically-rich, inquiry-based, participatory learning environment. Finds that virtual reality can be used effectively in regular undergraduate university courses as a tool through which students can…

Enriching Project-Based Learning Environments with Virtual Manipulatives: A Comparative Study

ERIC Educational Resources Information Center

Çakiroglu, Ünal

2014-01-01

Problem statement: Although there is agreement on the potential of project based learning (PBL) and virtual manipulatives (VMs), their positive impact depends on how they are used. This study was based on supporting the use of online PBL environments and improving the efficacy of the instructional practices in PBL by combining the potentials of…

Understanding Player Activity in a Game-Based Virtual Learning Environment

ERIC Educational Resources Information Center

Boyer, David Matthew

2011-01-01

This study examines player activity in a game-based virtual learning environment as a means toward evaluating instructional and game design. By determining the goals embedded in project development and the availability and structure of in-game activities, the first part of this research highlights opportunities for players to engage with learning…

Gender and Participation in an Engineering Problem-Based Learning Environment

ERIC Educational Resources Information Center

Hirshfield, Laura; Koretsky, Milo D.

2018-01-01

The use of problem-based learning (PBL) is gaining attention in the engineering classroom as a way to help students synthesize foundational knowledge and to better prepare students for practice. In this work, we study the discourse interactions between 27 student teams and two instructors in an engineering PBL environment to analyze how…

Online Collaborative Learning in a Project-Based Learning Environment in Taiwan: A Case Study on Undergraduate Students' Perspectives

ERIC Educational Resources Information Center

Zhang, Ke; Peng, Shiang Wuu; Hung, Jui-long

2009-01-01

This case study investigated undergraduate students' first experience in online collaborative learning in a project-based learning (PBL) environment in Taiwan. Data were collected through interviews of 48 students, instructor's field notes, researchers' online observations, students' online discourse, and group artifacts. The findings revealed…

University students' emotions, interest and activities in a web-based learning environment.

PubMed

Nummenmaa, Minna; Nummenmaa, Lauri

2008-03-01

Within academic settings, students experience varied emotions and interest towards learning. Although both emotions and interest can increase students' likelihood to engage in traditional learning, little is known about the influence of emotions and interest in learning activities in a web-based learning environment (WBLE). This study examined how emotions experienced while using a WBLE, students' interest towards the course topic and interest towards web-based learning are associated with collaborative visible and non-collaborative invisible activities and 'lurking' in the WBLE. Participants were 99 Finnish university students from five web-based courses. All the students enrolled in the courses filled out pre- and post-test questionnaires of interest, and repeatedly completed an on-line questionnaire on emotions experienced while using the WBLE during the courses. The fluctuation of emotional reactions was positively associated with both visible collaborative and invisible non-collaborative activities in the WBLE. Further, interest towards the web-based learning was positively associated with invisible activity. The results also demonstrated that students not actively participating in the collaborative activities (i.e. lurkers) had more negative emotional experiences during the courses than other students. The results highlight the distinct impacts that emotions and interest have on different web-based learning activities and that they should be considered when designing web-based courses.

Agent-based real-time signal coordination in congested networks.

DOT National Transportation Integrated Search

2014-01-01

This study is the continuation of a previous NEXTRANS study on agent-based reinforcement : learning methods for signal coordination in congested networks. In the previous study, the : formulation of a real-time agent-based traffic signal control in o...

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

ERIC Educational Resources Information Center

Chan, Carol K. K.

2012-01-01

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

Conversational Agents Improve Peer Learning through Building on Prior Knowledge

ERIC Educational Resources Information Center

Tegos, Stergios; Demetriadis, Stavros

2017-01-01

Research in computer-supported collaborative learning has indicated that conversational agents can be pedagogically beneficial when used to scaffold students' online discussions. In this study, we investigate the impact of an agile conversational agent that triggers student dialogue by making interventions based on the academically productive talk…

A Simultaneous Mobile E-Learning Environment and Application

ERIC Educational Resources Information Center

Karal, Hasan; Bahcekapili, Ekrem; Yildiz, Adil

2010-01-01

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

The VREST learning environment.

PubMed

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

2005-01-01

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

Virtual Learning Spaces in the Web: An Agent-Based Architecture of Personalized Collaborative Learning Environment.

ERIC Educational Resources Information Center

Nunez Esquer, Gustavo; Sheremetov, Leonid

This paper reports on the results and future research work within the paradigm of Configurable Collaborative Distance Learning, called Espacios Virtuales de Apredizaje (EVA). The paper focuses on: (1) description of the main concepts, including virtual learning spaces for knowledge, collaboration, consulting, and experimentation, a…

Reinforcement Learning with Autonomous Small Unmanned Aerial Vehicles in Cluttered Environments

NASA Technical Reports Server (NTRS)

Tran, Loc; Cross, Charles; Montague, Gilbert; Motter, Mark; Neilan, James; Qualls, Garry; Rothhaar, Paul; Trujillo, Anna; Allen, B. Danette

2015-01-01

We present ongoing work in the Autonomy Incubator at NASA Langley Research Center (LaRC) exploring the efficacy of a data set aggregation approach to reinforcement learning for small unmanned aerial vehicle (sUAV) flight in dense and cluttered environments with reactive obstacle avoidance. The goal is to learn an autonomous flight model using training experiences from a human piloting a sUAV around static obstacles. The training approach uses video data from a forward-facing camera that records the human pilot's flight. Various computer vision based features are extracted from the video relating to edge and gradient information. The recorded human-controlled inputs are used to train an autonomous control model that correlates the extracted feature vector to a yaw command. As part of the reinforcement learning approach, the autonomous control model is iteratively updated with feedback from a human agent who corrects undesired model output. This data driven approach to autonomous obstacle avoidance is explored for simulated forest environments furthering autonomous flight under the tree canopy research. This enables flight in previously inaccessible environments which are of interest to NASA researchers in Earth and Atmospheric sciences.

Agent-Based Negotiation in Uncertain Environments

NASA Astrophysics Data System (ADS)

Debenham, John; Sierra, Carles

An agent aims to secure his projected needs by attempting to build a set of (business) relationships with other agents. A relationship is built by exchanging private information, and is characterised by its intimacy — degree of closeness — and balance — degree of fairness. Each argumentative interaction between two agents then has two goals: to satisfy some immediate need, and to do so in a way that develops the relationship in a desired direction. An agent's desire to develop each relationship in a particular way then places constraints on the argumentative utterances. The form of negotiation described is argumentative interaction constrained by a desire to develop such relationships.

Fusing terrain and goals: agent control in urban environments

NASA Astrophysics Data System (ADS)

Kaptan, Varol; Gelenbe, Erol

2006-04-01

The changing face of contemporary military conflicts has forced a major shift of focus in tactical planning and evaluation from the classical Cold War battlefield to an asymmetric guerrilla-type warfare in densely populated urban areas. The new arena of conflict presents unique operational difficulties due to factors like complex mobility restrictions and the necessity to preserve civilian lives and infrastructure. In this paper we present a novel method for autonomous agent control in an urban environment. Our approach is based on fusing terrain information and agent goals for the purpose of transforming the problem of navigation in a complex environment with many obstacles into the easier problem of navigation in a virtual obstacle-free space. The main advantage of our approach is its ability to act as an adapter layer for a number of efficient agent control techniques which normally show poor performance when applied to an environment with many complex obstacles. Because of the very low computational and space complexity at runtime, our method is also particularly well suited for simulation or control of a huge number of agents (military as well as civilian) in a complex urban environment where traditional path-planning may be too expensive or where a just-in-time decision with hard real-time constraints is required.

Argumentation Based Joint Learning: A Novel Ensemble Learning Approach

PubMed Central

Xu, Junyi; Yao, Li; Li, Le

2015-01-01

Recently, ensemble learning methods have been widely used to improve classification performance in machine learning. In this paper, we present a novel ensemble learning method: argumentation based multi-agent joint learning (AMAJL), which integrates ideas from multi-agent argumentation, ensemble learning, and association rule mining. In AMAJL, argumentation technology is introduced as an ensemble strategy to integrate multiple base classifiers and generate a high performance ensemble classifier. We design an argumentation framework named Arena as a communication platform for knowledge integration. Through argumentation based joint learning, high quality individual knowledge can be extracted, and thus a refined global knowledge base can be generated and used independently for classification. We perform numerous experiments on multiple public datasets using AMAJL and other benchmark methods. The results demonstrate that our method can effectively extract high quality knowledge for ensemble classifier and improve the performance of classification. PMID:25966359

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

ERIC Educational Resources Information Center

Tilchin, Oleg; Kittany, Mohamed

2016-01-01

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

Efficient Agent-Based Cluster Ensembles

NASA Technical Reports Server (NTRS)

Agogino, Adrian; Tumer, Kagan

2006-01-01

Numerous domains ranging from distributed data acquisition to knowledge reuse need to solve the cluster ensemble problem of combining multiple clusterings into a single unified clustering. Unfortunately current non-agent-based cluster combining methods do not work in a distributed environment, are not robust to corrupted clusterings and require centralized access to all original clusterings. Overcoming these issues will allow cluster ensembles to be used in fundamentally distributed and failure-prone domains such as data acquisition from satellite constellations, in addition to domains demanding confidentiality such as combining clusterings of user profiles. This paper proposes an efficient, distributed, agent-based clustering ensemble method that addresses these issues. In this approach each agent is assigned a small subset of the data and votes on which final cluster its data points should belong to. The final clustering is then evaluated by a global utility, computed in a distributed way. This clustering is also evaluated using an agent-specific utility that is shown to be easier for the agents to maximize. Results show that agents using the agent-specific utility can achieve better performance than traditional non-agent based methods and are effective even when up to 50% of the agents fail.

Reinforcement learning agents providing advice in complex video games

NASA Astrophysics Data System (ADS)

Taylor, Matthew E.; Carboni, Nicholas; Fachantidis, Anestis; Vlahavas, Ioannis; Torrey, Lisa

2014-01-01

This article introduces a teacher-student framework for reinforcement learning, synthesising and extending material that appeared in conference proceedings [Torrey, L., & Taylor, M. E. (2013)]. Teaching on a budget: Agents advising agents in reinforcement learning. {Proceedings of the international conference on autonomous agents and multiagent systems}] and in a non-archival workshop paper [Carboni, N., &Taylor, M. E. (2013, May)]. Preliminary results for 1 vs. 1 tactics in StarCraft. {Proceedings of the adaptive and learning agents workshop (at AAMAS-13)}]. In this framework, a teacher agent instructs a student agent by suggesting actions the student should take as it learns. However, the teacher may only give such advice a limited number of times. We present several novel algorithms that teachers can use to budget their advice effectively, and we evaluate them in two complex video games: StarCraft and Pac-Man. Our results show that the same amount of advice, given at different moments, can have different effects on student learning, and that teachers can significantly affect student learning even when students use different learning methods and state representations.

A spatial web/agent-based model to support stakeholders' negotiation regarding land development.

PubMed

Pooyandeh, Majeed; Marceau, Danielle J

2013-11-15

Decision making in land management can be greatly enhanced if the perspectives of concerned stakeholders are taken into consideration. This often implies negotiation in order to reach an agreement based on the examination of multiple alternatives. This paper describes a spatial web/agent-based modeling system that was developed to support the negotiation process of stakeholders regarding land development in southern Alberta, Canada. This system integrates a fuzzy analytic hierarchy procedure within an agent-based model in an interactive visualization environment provided through a web interface to facilitate the learning and negotiation of the stakeholders. In the pre-negotiation phase, the stakeholders compare their evaluation criteria using linguistic expressions. Due to the uncertainty and fuzzy nature of such comparisons, a fuzzy Analytic Hierarchy Process is then used to prioritize the criteria. The negotiation starts by a development plan being submitted by a user (stakeholder) through the web interface. An agent called the proposer, which represents the proposer of the plan, receives this plan and starts negotiating with all other agents. The negotiation is conducted in a step-wise manner where the agents change their attitudes by assigning a new set of weights to their criteria. If an agreement is not achieved, a new location for development is proposed by the proposer agent. This process is repeated until a location is found that satisfies all agents to a certain predefined degree. To evaluate the performance of the model, the negotiation was simulated with four agents, one of which being the proposer agent, using two hypothetical development plans. The first plan was selected randomly; the other one was chosen in an area that is of high importance to one of the agents. While the agents managed to achieve an agreement about the location of the land development after three rounds of negotiation in the first scenario, seven rounds were required in the second

Murder on Grimm Isle: The Impact of Game Narrative Design in an Educational Game-Based Learning Environment

ERIC Educational Resources Information Center

Dickey, Michele D.

2011-01-01

The purpose of this research is to investigate the impact of narrative design in a game-based learning environment. Specifically, this investigation focuses the narrative design in an adventure-styled, game-based learning environment for fostering argumentation writing by looking at how the game narrative impacted player/learner (1) intrinsic…

Development and Evaluation of Intelligent Agent-Based Teaching Assistant in e-Learning Portals

ERIC Educational Resources Information Center

Rouhani, Saeed; Mirhosseini, Seyed Vahid

2015-01-01

Today, several educational portals established by organizations to enhance web E-learning. Intelligence agent's usage is necessary to improve the system's quality and cover limitations such as face-to-face relation. In this research, after finding two main approaches in this field that are fundamental use of intelligent agents in systems design…

Learning System Design Consideration in Creating an Online Learning Environment.

ERIC Educational Resources Information Center

Schaffer, Scott

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

Preparing Students for Future Learning with Teachable Agents

ERIC Educational Resources Information Center

Chin, Doris B.; Dohmen, Ilsa M.; Cheng, Britte H.; Oppezzo, Marily A.; Chase, Catherine C.; Schwartz, Daniel L.

2010-01-01

One valuable goal of instructional technologies in K-12 education is to prepare students for future learning. Two classroom studies examined whether Teachable Agents (TA) achieves this goal. TA is an instructional technology that draws on the social metaphor of teaching a computer agent to help students learn. Students teach their agent by…

Validation of the Clinical Learning Environment Inventory.

PubMed

Chan, Dominic S

2003-08-01

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

The Integration of Personal Learning Environments & Open Network Learning Environments

ERIC Educational Resources Information Center

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

2012-01-01

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

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

PubMed

Baeten, Marlies; Dochy, Filip; Struyven, Katrien

2013-09-01

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

Towards a genetics-based adaptive agent to support flight testing

NASA Astrophysics Data System (ADS)

Cribbs, Henry Brown, III

Although the benefits of aircraft simulation have been known since the late 1960s, simulation almost always entails interaction with a human test pilot. This "pilot-in-the-loop" simulation process provides useful evaluative information to the aircraft designer and provides a training tool to the pilot. Emulation of a pilot during the early phases of the aircraft design process might provide designers a useful evaluative tool. Machine learning might emulate a pilot in a simulated aircraft/cockpit setting. Preliminary work in the application of machine learning techniques, such as reinforcement learning, to aircraft maneuvering have shown promise. These studies used simplified interfaces between machine learning agent and the aircraft simulation. The simulations employed low order equivalent system models. High-fidelity aircraft simulations exist, such as the simulations developed by NASA at its Dryden Flight Research Center. To expand the applicational domain of reinforcement learning to aircraft designs, this study presents a series of experiments that examine a reinforcement learning agent in the role of test pilot. The NASA X-31 and F-106 high-fidelity simulations provide realistic aircraft for the agent to maneuver. The approach of the study is to examine an agent possessing a genetic-based, artificial neural network to approximate long-term, expected cost (Bellman value) in a basic maneuvering task. The experiments evaluate different learning methods based on a common feedback function and an identical task. The learning methods evaluated are: Q-learning, Q(lambda)-learning, SARSA learning, and SARSA(lambda) learning. Experimental results indicate that, while prediction error remain quite high, similar, repeatable behaviors occur in both aircraft. Similar behavior exhibits portability of the agent between aircraft with different handling qualities (dynamics). Besides the adaptive behavior aspects of the study, the genetic algorithm used in the agent is shown to

Development of Web-Based Learning Environment Model to Enhance Cognitive Skills for Undergraduate Students in the Field of Electrical Engineering

ERIC Educational Resources Information Center

Lakonpol, Thongmee; Ruangsuwan, Chaiyot; Terdtoon, Pradit

2015-01-01

This research aimed to develop a web-based learning environment model for enhancing cognitive skills of undergraduate students in the field of electrical engineering. The research is divided into 4 phases: 1) investigating the current status and requirements of web-based learning environment models. 2) developing a web-based learning environment…

The Self-Formation of Collaborative Groups in a Problem Based Learning Environment

ERIC Educational Resources Information Center

Raiyn, Jamal; Tilchin, Oleg

2016-01-01

The aim of this paper is to present "the three steps method" of the self-formation of collaborative groups in a problem-based learning environment. The self-formation of collaborative groups is based on sharing of accountability among students for solving instructional problems. The steps of the method are planning collaborative problem…

The Effectiveness of Self-Regulated Learning Scaffolds on Academic Performance in Computer-Based Learning Environments: A Meta-Analysis

ERIC Educational Resources Information Center

Zheng, Lanqin

2016-01-01

This meta-analysis examined research on the effects of self-regulated learning scaffolds on academic performance in computer-based learning environments from 2004 to 2015. A total of 29 articles met inclusion criteria and were included in the final analysis with a total sample size of 2,648 students. Moderator analyses were performed using a…

Collective Machine Learning: Team Learning and Classification in Multi-Agent Systems

ERIC Educational Resources Information Center

Gifford, Christopher M.

2009-01-01

This dissertation focuses on the collaboration of multiple heterogeneous, intelligent agents (hardware or software) which collaborate to learn a task and are capable of sharing knowledge. The concept of collaborative learning in multi-agent and multi-robot systems is largely under studied, and represents an area where further research is needed to…

Creating Learning Environments for Indigenous Students through Cultured-Based Math Modules

ERIC Educational Resources Information Center

Yao, Ru-Fen

2016-01-01

The main purposes of this one-year case study are to create learning environments for indigenous students through culture-based mathematics instructional modules, and what teachers' responds are in two tribes. The researcher leads sixteen in-service teachers and seven pre-service teachers to enter two indigenous tribes- "Cado" and…

Using Scenarios to Design Complex Technology-Enhanced Learning Environments

ERIC Educational Resources Information Center

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

2012-01-01

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

From Agents to Continuous Change via Aesthetics: Learning Mechanics with Visual Agent-Based Computational Modeling

ERIC Educational Resources Information Center

Sengupta, Pratim; Farris, Amy Voss; Wright, Mason

2012-01-01

Novice learners find motion as a continuous process of change challenging to understand. In this paper, we present a pedagogical approach based on agent-based, visual programming to address this issue. Integrating agent-based programming, in particular, Logo programming, with curricular science has been shown to be challenging in previous research…

On the Bus and Online: Instantiating an Interactive Learning Environment through Design-Based Research

ERIC Educational Resources Information Center

Kartoglu, Ümit; Vesper, James L.; Reeves, Thomas C.

2017-01-01

The World Health Organization converted an award-winning experiential learning course that takes place on a bus traveling down the "cold chain" for time- and temperature-sensitive pharmaceutical products in Turkey to an online interactive learning environment through design-based research. Similarities and differences in the objectives…

A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

NASA Astrophysics Data System (ADS)

Xiang, Lin

This is a collective case study seeking to develop detailed descriptions of how programming an agent-based simulation influences a group of 8 th grade students' model-based inquiry (MBI) by examining students' agent-based programmable modeling (ABPM) processes and the learning outcomes. The context of the present study was a biology unit on natural selection implemented in a charter school of a major California city during spring semester of 2009. Eight 8th grade students, two boys and six girls, participated in this study. All of them were low socioeconomic status (SES). English was a second language for all of them, but they had been identified as fluent English speakers at least a year before the study. None of them had learned either natural selection or programming before the study. The study spanned over 7 weeks and was comprised of two study phases. In phase one the subject students learned natural selection in science classroom and how to do programming in NetLogo, an ABPM tool, in a computer lab; in phase two, the subject students were asked to program a simulation of adaptation based on the natural selection model in NetLogo. Both qualitative and quantitative data were collected in this study. The data resources included (1) pre and post test questionnaire, (2) student in-class worksheet, (3) programming planning sheet, (4) code-conception matching sheet, (5) student NetLogo projects, (6) videotaped programming processes, (7) final interview, and (8) investigator's field notes. Both qualitative and quantitative approaches were applied to analyze the gathered data. The findings suggested that students made progress on understanding adaptation phenomena and natural selection at the end of ABPM-supported MBI learning but the progress was limited. These students still held some misconceptions in their conceptual models, such as the idea that animals need to "learn" to adapt into the environment. Besides, their models of natural selection appeared to be

The Internet: A Learning Environment.

ERIC Educational Resources Information Center

McGreal, Rory

1997-01-01

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

Multi Agent Systems with Symbiotic Learning and Evolution using GNP

NASA Astrophysics Data System (ADS)

Eguchi, Toru; Hirasawa, Kotaro; Hu, Jinglu; Murata, Junichi

Recently, various attempts relevant to Multi Agent Systems (MAS) which is one of the most promising systems based on Distributed Artificial Intelligence have been studied to control large and complicated systems efficiently. In these trends of MAS, Multi Agent Systems with Symbiotic Learning and Evolution named Masbiole has been proposed. In Masbiole, symbiotic phenomena among creatures are considered in the process of learning and evolution of MAS. So we can expect more flexible and sophisticated solutions than conventional MAS. In this paper, we apply Masbiole to Iterative Prisoner’s Dilemma Games (IPD Games) using Genetic Network Programming (GNP) which is a newly developed evolutionary computation method for constituting agents. Some characteristics of Masbiole using GNP in IPD Games are clarified.

Evaluating and Implementing Learning Environments: A United Kingdom Experience.

ERIC Educational Resources Information Center

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

2002-01-01

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

Designing Collaborative E-Learning Environments Based upon Semantic Wiki: From Design Models to Application Scenarios

ERIC Educational Resources Information Center

Li, Yanyan; Dong, Mingkai; Huang, Ronghuai

2011-01-01

The knowledge society requires life-long learning and flexible learning environment that enables fast, just-in-time and relevant learning, aiding the development of communities of knowledge, linking learners and practitioners with experts. Based upon semantic wiki, a combination of wiki and Semantic Web technology, this paper designs and develops…

Modeling vs. Coaching of Argumentation in a Case-Based Learning Environment.

ERIC Educational Resources Information Center

Li, Tiancheng; And Others

The major purposes of this study are: (1) to investigate and compare the effectiveness of two instructional strategies, modeling and coaching on helping students to articulate and support their decisions in a case-based learning environment; (2) to compare the effectiveness of modeling and coaching on helping students address essential criteria in…

The Workplace as Learning Environment in Early Childhood Teacher Education: An Investigation of Work-Based Education

ERIC Educational Resources Information Center

Kaarby, Karen Marie Eid; Lindboe, Inger Marie

2016-01-01

The article focuses on the workplace as a learning environment in work-based early childhood teacher education in Norway. The main question is: Which understandings of the workplace as a learning environment are to be found in regulations and policy documents, among students and among staff managers? Taking as the point of departure, a theoretical…

Building v/s Exploring Models: Comparing Learning of Evolutionary Processes through Agent-based Modeling

NASA Astrophysics Data System (ADS)

Wagh, Aditi

Two strands of work motivate the three studies in this dissertation. Evolutionary change can be viewed as a computational complex system in which a small set of rules operating at the individual level result in different population level outcomes under different conditions. Extensive research has documented students' difficulties with learning about evolutionary change (Rosengren et al., 2012), particularly in terms of levels slippage (Wilensky & Resnick, 1999). Second, though building and using computational models is becoming increasingly common in K-12 science education, we know little about how these two modalities compare. This dissertation adopts agent-based modeling as a representational system to compare these modalities in the conceptual context of micro-evolutionary processes. Drawing on interviews, Study 1 examines middle-school students' productive ways of reasoning about micro-evolutionary processes to find that the specific framing of traits plays a key role in whether slippage explanations are cued. Study 2, which was conducted in 2 schools with about 150 students, forms the crux of the dissertation. It compares learning processes and outcomes when students build their own models or explore a pre-built model. Analysis of Camtasia videos of student pairs reveals that builders' and explorers' ways of accessing rules, and sense-making of observed trends are of a different character. Builders notice rules through available blocks-based primitives, often bypassing their enactment while explorers attend to rules primarily through the enactment. Moreover, builders' sense-making of observed trends is more rule-driven while explorers' is more enactment-driven. Pre and posttests reveal that builders manifest a greater facility with accessing rules, providing explanations manifesting targeted assembly. Explorers use rules to construct explanations manifesting non-targeted assembly. Interviews reveal varying degrees of shifts away from slippage in both

Toward an Integrated Online Learning Environment

NASA Astrophysics Data System (ADS)

Teodorescu, Raluca E.; Pawl, Andrew; Rayyan, Saif; Barrantes, Analia; Pritchard, David E.

2010-10-01

We are building in LON-CAPA an integrated learning environment that will enable the development, dissemination and evaluation of PER-based material. This environment features a collection of multi-level research-based homework sets organized by topic and cognitive complexity. These sets are associated with learning modules that contain very short exposition of the content supplemented by integrated open-access videos, worked examples, simulations, and tutorials (some from ANDES). To assess students' performance accurately with respect to a system-wide standard, we plan to implement Item Response Theory. Together with other PER assessments and purposeful solicitation of student feedback, this will allow us to measure and improve the efficacy of various research-based materials, while getting insights into teaching and learning.

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

PubMed

Restrepo-Palacio, Sonia; Amaya-Guio, Jairo

2016-01-01

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

Reverse engineering a social agent-based hidden markov model--visage.

PubMed

Chen, Hung-Ching Justin; Goldberg, Mark; Magdon-Ismail, Malik; Wallace, William A

2008-12-01

We present a machine learning approach to discover the agent dynamics that drives the evolution of the social groups in a community. We set up the problem by introducing an agent-based hidden Markov model for the agent dynamics: an agent's actions are determined by micro-laws. Nonetheless, We learn the agent dynamics from the observed communications without knowing state transitions. Our approach is to identify the appropriate micro-laws corresponding to an identification of the appropriate parameters in the model. The model identification problem is then formulated as a mixed optimization problem. To solve the problem, we develop a multistage learning process for determining the group structure, the group evolution, and the micro-laws of a community based on the observed set of communications among actors, without knowing the semantic contents. Finally, to test the quality of our approximations and the feasibility of the approach, we present the results of extensive experiments on synthetic data as well as the results on real communities, such as Enron email and Movie newsgroups. Insight into agent dynamics helps us understand the driving forces behind social evolution.

A Pilot Study: Facilitating Cross-Cultural Understanding with Project-Based Collaborative Learning in an Online Environment

ERIC Educational Resources Information Center

Shadiev, Rustam; Hwang, Wu-Yuin; Huang, Yueh-Min

2015-01-01

This study investigated three aspects: how project-based collaborative learning facilitates cross-cultural understanding; how students perceive project-based collaborative learning implementation in a collaborative cyber community (3C) online environment; and what types of communication among students are used. A qualitative case study approach…

Perceptions of the Effectiveness of System Dynamics-Based Interactive Learning Environments: An Empirical Study

ERIC Educational Resources Information Center

Qudrat-Ullah, Hassan

2010-01-01

The use of simulations in general and of system dynamics simulation based interactive learning environments (SDILEs) in particular is well recognized as an effective way of improving users' decision making and learning in complex, dynamic tasks. However, the effectiveness of SDILEs in classrooms has rarely been evaluated. This article describes…

Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

NASA Astrophysics Data System (ADS)

Dickes, Amanda Catherine; Sengupta, Pratim

2013-06-01

In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these agents obey simple rules assigned or manipulated by the user (e.g., speeding up, slowing down, etc.). It is the interactions between these agents, based on the rules assigned by the user, that give rise to emergent, aggregate-level behavior (e.g., formation and movement of the traffic jam). Natural selection is such an emergent phenomenon, which has been shown to be challenging for novices (K16 students) to understand. Whereas prior research on learning evolutionary phenomena with MABMs has typically focused on high school students and beyond, we investigate how elementary students (4th graders) develop multi-level explanations of some introductory aspects of natural selection—species differentiation and population change—through scaffolded interactions with an MABM that simulates predator-prey dynamics in a simple birds-butterflies ecosystem. We conducted a semi-clinical interview based study with ten participants, in which we focused on the following: a) identifying the nature of learners' initial interpretations of salient events or elements of the represented phenomena, b) identifying the roles these interpretations play in the development of their multi-level explanations, and c) how attending to different levels of the relevant phenomena can make explicit different mechanisms to the learners. In addition, our analysis also shows that although there were differences between high- and low-performing students (in terms of being able to explain population-level behaviors) in the pre-test, these differences disappeared in the post-test.

Virtual Learning Environments as Sociomaterial Agents in the Network of Teaching Practice

ERIC Educational Resources Information Center

Johannesen, Monica; Erstad, Ola; Habib, Laurence

2012-01-01

This article presents findings related to the sociomaterial agency of educators and their practice in Norwegian education. Using actor-network theory, we ask how Virtual Learning Environments (VLEs) negotiate the agency of educators and how they shape their teaching practice. Since the same kinds of VLE tools have been widely implemented…

Comparing 2D and 3D Game-Based Learning Environments in Terms of Learning Gains and Student Perceptions

ERIC Educational Resources Information Center

Ak, Oguz; Kutlu, Birgul

2017-01-01

The aim of this study was to investigate the effectiveness of traditional, 2D and 3D game-based environments assessed by student achievement scores and to reveal student perceptions of the value of these learning environments. A total of 60 university students from the Faculty of Education who were registered in three sections of a required…

Risk, individual differences, and environment: an Agent-Based Modeling approach to sexual risk-taking.

PubMed

Nagoski, Emily; Janssen, Erick; Lohrmann, David; Nichols, Eric

2012-08-01

Risky sexual behaviors, including the decision to have unprotected sex, result from interactions between individuals and their environment. The current study explored the use of Agent-Based Modeling (ABM)-a methodological approach in which computer-generated artificial societies simulate human sexual networks-to assess the influence of heterogeneity of sexual motivation on the risk of contracting HIV. The models successfully simulated some characteristics of human sexual systems, such as the relationship between individual differences in sexual motivation (sexual excitation and inhibition) and sexual risk, but failed to reproduce the scale-free distribution of number of partners observed in the real world. ABM has the potential to inform intervention strategies that target the interaction between an individual and his or her social environment.

Proposed Methodology for Application of Human-like gradual Multi-Agent Q-Learning (HuMAQ) for Multi-robot Exploration

NASA Astrophysics Data System (ADS)

Narayan Ray, Dip; Majumder, Somajyoti

2014-07-01

Several attempts have been made by the researchers around the world to develop a number of autonomous exploration techniques for robots. But it has been always an important issue for developing the algorithm for unstructured and unknown environments. Human-like gradual Multi-agent Q-leaming (HuMAQ) is a technique developed for autonomous robotic exploration in unknown (and even unimaginable) environments. It has been successfully implemented in multi-agent single robotic system. HuMAQ uses the concept of Subsumption architecture, a well-known Behaviour-based architecture for prioritizing the agents of the multi-agent system and executes only the most common action out of all the different actions recommended by different agents. Instead of using new state-action table (Q-table) each time, HuMAQ uses the immediate past table for efficient and faster exploration. The proof of learning has also been established both theoretically and practically. HuMAQ has the potential to be used in different and difficult situations as well as applications. The same architecture has been modified to use for multi-robot exploration in an environment. Apart from all other existing agents used in the single robotic system, agents for inter-robot communication and coordination/ co-operation with the other similar robots have been introduced in the present research. Current work uses a series of indigenously developed identical autonomous robotic systems, communicating with each other through ZigBee protocol.

Multi Agent Reward Analysis for Learning in Noisy Domains

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Agogino, Adrian K.

2005-01-01

In many multi agent learning problems, it is difficult to determine, a priori, the agent reward structure that will lead to good performance. This problem is particularly pronounced in continuous, noisy domains ill-suited to simple table backup schemes commonly used in TD(lambda)/Q-learning. In this paper, we present a new reward evaluation method that allows the tradeoff between coordination among the agents and the difficulty of the learning problem each agent faces to be visualized. This method is independent of the learning algorithm and is only a function of the problem domain and the agents reward structure. We then use this reward efficiency visualization method to determine an effective reward without performing extensive simulations. We test this method in both a static and a dynamic multi-rover learning domain where the agents have continuous state spaces and where their actions are noisy (e.g., the agents movement decisions are not always carried out properly). Our results show that in the more difficult dynamic domain, the reward efficiency visualization method provides a two order of magnitude speedup in selecting a good reward. Most importantly it allows one to quickly create and verify rewards tailored to the observational limitations of the domain.

Virtual Learning Environments.

ERIC Educational Resources Information Center

Follows, Scott B.

1999-01-01

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

A Social Contract for University-Industry Collaboration: A Case of Project-Based Learning Environment

NASA Astrophysics Data System (ADS)

Vartiainen, Tero

This study determines a social contract for a form of university-industry collaboration to a project-based learning environment in close collaboration with industry. The author's previous studies on moral conflicts in a project-based learning (PjBL) environment and his 5-year engagement in the PjBL environment are used as background knowledge, and John Rawls' veil of ignorance is used as a method in the contract formulation. Fair and impartial treatment of actors is strived for with the contract which constitutes of sets of obligations for each party, students, clients, and university (instructors) in the chosen project course. With the contract fair and impartial treatment of actors is strived for and the most dilemmatic moral conflicts are tried to be avoided. The forming of the social contract is evaluated, and implications for research and collaborations in practice are offered.

Creating and Nurturing Distributed Asynchronous Learning Environments.

ERIC Educational Resources Information Center

Kochtanek, Thomas R.; Hein, Karen K.

2000-01-01

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

The Effect of Contextualized Conversational Feedback in a Complex Open-Ended Learning Environment

ERIC Educational Resources Information Center

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

2013-01-01

Betty's Brain is an open-ended learning environment in which students learn about science topics by teaching a virtual agent named Betty through the construction of a visual causal map that represents the relevant science phenomena. The task is complex, and success requires the use of metacognitive strategies that support knowledge acquisition,…

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…

Psychosocial Learning Environments and the Mediating Effect of Personal Meaning upon Satisfaction with Education

ERIC Educational Resources Information Center

Smith, Prapanna Randall

2013-01-01

This article reports the quantitative phase of a mixed-methods study that was conducted to investigate the relationships between psychosocial learning environments and student satisfaction with their education as mediated by Agentic Personal Meaning. The interdisciplinary approach of the study integrated the fields of learning environment…

Investigation of learning environment for arithmetic word problems by problem posing as sentence integration in Indonesian language

NASA Astrophysics Data System (ADS)

Hasanah, N.; Hayashi, Y.; Hirashima, T.

2017-02-01

Arithmetic word problems remain one of the most difficult area of teaching mathematics. Learning by problem posing has been suggested as an effective way to improve students’ understanding. However, the practice in usual classroom is difficult due to extra time needed for assessment and giving feedback to students’ posed problems. To address this issue, we have developed a tablet PC software named Monsakun for learning by posing arithmetic word problems based on Triplet Structure Model. It uses the mechanism of sentence-integration, an efficient implementation of problem-posing that enables agent-assessment of posed problems. The learning environment has been used in actual Japanese elementary school classrooms and the effectiveness has been confirmed in previous researches. In this study, ten Indonesian elementary school students living in Japan participated in a learning session of problem posing using Monsakun in Indonesian language. We analyzed their learning activities and show that students were able to interact with the structure of simple word problem using this learning environment. The results of data analysis and questionnaire suggested that the use of Monsakun provides a way of creating an interactive and fun environment for learning by problem posing for Indonesian elementary school students.

The Effects of Integrating Social Learning Environment with Online Learning

ERIC Educational Resources Information Center

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

2017-01-01

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

Virtual agents in a simulated virtual training environment

NASA Technical Reports Server (NTRS)

Achorn, Brett; Badler, Norman L.

1993-01-01

A drawback to live-action training simulations is the need to gather a large group of participants in order to train a few individuals. One solution to this difficulty is the use of computer-controlled agents in a virtual training environment. This allows a human participant to be replaced by a virtual, or simulated, agent when only limited responses are needed. Each agent possesses a specified set of behaviors and is capable of limited autonomous action in response to its environment or the direction of a human trainee. The paper describes these agents in the context of a simulated hostage rescue training session, involving two human rescuers assisted by three virtual (computer-controlled) agents and opposed by three other virtual agents.

Optimal control in microgrid using multi-agent reinforcement learning.

PubMed

Li, Fu-Dong; Wu, Min; He, Yong; Chen, Xin

2012-11-01

This paper presents an improved reinforcement learning method to minimize electricity costs on the premise of satisfying the power balance and generation limit of units in a microgrid with grid-connected mode. Firstly, the microgrid control requirements are analyzed and the objective function of optimal control for microgrid is proposed. Then, a state variable "Average Electricity Price Trend" which is used to express the most possible transitions of the system is developed so as to reduce the complexity and randomicity of the microgrid, and a multi-agent architecture including agents, state variables, action variables and reward function is formulated. Furthermore, dynamic hierarchical reinforcement learning, based on change rate of key state variable, is established to carry out optimal policy exploration. The analysis shows that the proposed method is beneficial to handle the problem of "curse of dimensionality" and speed up learning in the unknown large-scale world. Finally, the simulation results under JADE (Java Agent Development Framework) demonstrate the validity of the presented method in optimal control for a microgrid with grid-connected mode. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Model-free learning on robot kinematic chains using a nested multi-agent topology

NASA Astrophysics Data System (ADS)

Karigiannis, John N.; Tzafestas, Costas S.

2016-11-01

This paper proposes a model-free learning scheme for the developmental acquisition of robot kinematic control and dexterous manipulation skills. The approach is based on a nested-hierarchical multi-agent architecture that intuitively encapsulates the topology of robot kinematic chains, where the activity of each independent degree-of-freedom (DOF) is finally mapped onto a distinct agent. Each one of those agents progressively evolves a local kinematic control strategy in a game-theoretic sense, that is, based on a partial (local) view of the whole system topology, which is incrementally updated through a recursive communication process according to the nested-hierarchical topology. Learning is thus approached not through demonstration and training but through an autonomous self-exploration process. A fuzzy reinforcement learning scheme is employed within each agent to enable efficient exploration in a continuous state-action domain. This paper constitutes in fact a proof of concept, demonstrating that global dexterous manipulation skills can indeed evolve through such a distributed iterative learning of local agent sensorimotor mappings. The main motivation behind the development of such an incremental multi-agent topology is to enhance system modularity, to facilitate extensibility to more complex problem domains and to improve robustness with respect to structural variations including unpredictable internal failures. These attributes of the proposed system are assessed in this paper through numerical experiments in different robot manipulation task scenarios, involving both single and multi-robot kinematic chains. The generalisation capacity of the learning scheme is experimentally assessed and robustness properties of the multi-agent system are also evaluated with respect to unpredictable variations in the kinematic topology. Furthermore, these numerical experiments demonstrate the scalability properties of the proposed nested-hierarchical architecture, where

Foreign language learning in immersive virtual environments

NASA Astrophysics Data System (ADS)

Chang, Benjamin; Sheldon, Lee; Si, Mei; Hand, Anton

2012-03-01

Virtual reality has long been used for training simulations in fields from medicine to welding to vehicular operation, but simulations involving more complex cognitive skills present new design challenges. Foreign language learning, for example, is increasingly vital in the global economy, but computer-assisted education is still in its early stages. Immersive virtual reality is a promising avenue for language learning as a way of dynamically creating believable scenes for conversational training and role-play simulation. Visual immersion alone, however, only provides a starting point. We suggest that the addition of social interactions and motivated engagement through narrative gameplay can lead to truly effective language learning in virtual environments. In this paper, we describe the development of a novel application for teaching Mandarin using CAVE-like VR, physical props, human actors and intelligent virtual agents, all within a semester-long multiplayer mystery game. Students travel (virtually) to China on a class field trip, which soon becomes complicated with intrigue and mystery surrounding the lost manuscript of an early Chinese literary classic. Virtual reality environments such as the Forbidden City and a Beijing teahouse provide the setting for learning language, cultural traditions, and social customs, as well as the discovery of clues through conversation in Mandarin with characters in the game.

A virtual therapeutic environment with user projective agents.

PubMed

Ookita, S Y; Tokuda, H

2001-02-01

Today, we see the Internet as more than just an information infrastructure, but a socializing place and a safe outlet of inner feelings. Many personalities develop aside from real world life due to its anonymous environment. Virtual world interactions are bringing about new psychological illnesses ranging from netaddiction to technostress, as well as online personality disorders and conflicts in multiple identities that exist in the virtual world. Presently, there are no standard therapy models for the virtual environment. There are very few therapeutic environments, or tools especially made for virtual therapeutic environments. The goal of our research is to provide the therapy model and middleware tools for psychologists to use in virtual therapeutic environments. We propose the Cyber Therapy Model, and Projective Agents, a tool used in the therapeutic environment. To evaluate the effectiveness of the tool, we created a prototype system, called the Virtual Group Counseling System, which is a therapeutic environment that allows the user to participate in group counseling through the eyes of their Projective Agent. Projective Agents inherit the user's personality traits. During the virtual group counseling, the user's Projective Agent interacts and collaborates to recover and increase their psychological growth. The prototype system provides a simulation environment where psychologists can adjust the parameters and customize their own simulation environment. The model and tool is a first attempt toward simulating online personalities that may exist only online, and provide data for observation.

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

ERIC Educational Resources Information Center

Boulehouache, Soufiane; Maamri, Ramdane; Sahnoun, Zaidi

2015-01-01

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

Science Learning Outcomes in Alignment with Learning Environment Preferences

NASA Astrophysics Data System (ADS)

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

2011-04-01

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

Students' Perceptions of Computer-Based Learning Environments, Their Attitude towards Business Statistics, and Their Academic Achievement: Implications from a UK University

ERIC Educational Resources Information Center

Nguyen, ThuyUyen H.; Charity, Ian; Robson, Andrew

2016-01-01

This study investigates students' perceptions of computer-based learning environments, their attitude towards business statistics, and their academic achievement in higher education. Guided by learning environments concepts and attitudinal theory, a theoretical model was proposed with two instruments, one for measuring the learning environment and…

Training Language Teachers to Sustain Self-Directed Language Learning: An Exploration of Advisers' Experiences on a Web-Based Open Virtual Learning Environment

ERIC Educational Resources Information Center

Bailly, Sophie; Ciekanski, Maud; Guély-Costa, Eglantine

2013-01-01

This article describes the rationale for pedagogical, technological and organizational choices in the design of a web-based and open virtual learning environment (VLE) promoting and sustaining self-directed language learning. Based on the last forty years of research on learner autonomy at the CRAPEL according to Holec's definition (1988), we…

Data-driven agent-based modeling, with application to rooftop solar adoption

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

Zhang, Haifeng; Vorobeychik, Yevgeniy; Letchford, Joshua

Agent-based modeling is commonly used for studying complex system properties emergent from interactions among many agents. We present a novel data-driven agent-based modeling framework applied to forecasting individual and aggregate residential rooftop solar adoption in San Diego county. Our first step is to learn a model of individual agent behavior from combined data of individual adoption characteristics and property assessment. We then construct an agent-based simulation with the learned model embedded in artificial agents, and proceed to validate it using a holdout sequence of collective adoption decisions. We demonstrate that the resulting agent-based model successfully forecasts solar adoption trends andmore » provides a meaningful quantification of uncertainty about its predictions. We utilize our model to optimize two classes of policies aimed at spurring solar adoption: one that subsidizes the cost of adoption, and another that gives away free systems to low-income house- holds. We find that the optimal policies derived for the latter class are significantly more efficacious, whereas the policies similar to the current California Solar Initiative incentive scheme appear to have a limited impact on overall adoption trends.« less

Data-driven agent-based modeling, with application to rooftop solar adoption

DOE PAGES

Zhang, Haifeng; Vorobeychik, Yevgeniy; Letchford, Joshua; ...

2016-01-25

Agent-based modeling is commonly used for studying complex system properties emergent from interactions among many agents. We present a novel data-driven agent-based modeling framework applied to forecasting individual and aggregate residential rooftop solar adoption in San Diego county. Our first step is to learn a model of individual agent behavior from combined data of individual adoption characteristics and property assessment. We then construct an agent-based simulation with the learned model embedded in artificial agents, and proceed to validate it using a holdout sequence of collective adoption decisions. We demonstrate that the resulting agent-based model successfully forecasts solar adoption trends andmore » provides a meaningful quantification of uncertainty about its predictions. We utilize our model to optimize two classes of policies aimed at spurring solar adoption: one that subsidizes the cost of adoption, and another that gives away free systems to low-income house- holds. We find that the optimal policies derived for the latter class are significantly more efficacious, whereas the policies similar to the current California Solar Initiative incentive scheme appear to have a limited impact on overall adoption trends.« less

Effect of Educational Agent and Its Form Characteristics on Problem Solving Ability Perception of Students in Online Task Based Learning Media

ERIC Educational Resources Information Center

Akyuz, Halil Ibrahim; Keser, Hafize

2015-01-01

The aim of this study is to investigate the effect of an educational agent, used in online task based learning media, and its form characteristics on problem solving ability perceptions of students. 2x2 factorial design is used in this study. The first study factor is the role of the educational agent and the second factor is form characteristics…

Students using visual thinking to learn science in a Web-based environment

NASA Astrophysics Data System (ADS)

Plough, Jean Margaret

United States students' science test scores are low, especially in problem solving, and traditional science instruction could be improved. Consequently, visual thinking, constructing science structures, and problem solving in a web-based environment may be valuable strategies for improving science learning. This ethnographic study examined the science learning of fifteen fourth grade students in an after school computer club involving diverse students at an inner city school. The investigation was done from the perspective of the students, and it described the processes of visual thinking, web page construction, and problem solving in a web-based environment. The study utilized informal group interviews, field notes, Visual Learning Logs, and student web pages, and incorporated a Standards-Based Rubric which evaluated students' performance on eight science and technology standards. The Visual Learning Logs were drawings done on the computer to represent science concepts related to the Food Chain. Students used the internet to search for information on a plant or animal of their choice. Next, students used this internet information, with the information from their Visual Learning Logs, to make web pages on their plant or animal. Later, students linked their web pages to form Science Structures. Finally, students linked their Science Structures with the structures of other students, and used these linked structures as models for solving problems. Further, during informal group interviews, students answered questions about visual thinking, problem solving, and science concepts. The results of this study showed clearly that (1) making visual representations helped students understand science knowledge, (2) making links between web pages helped students construct Science Knowledge Structures, and (3) students themselves said that visual thinking helped them learn science. In addition, this study found that when using Visual Learning Logs, the main overall ideas of the

Concurrent Learning of Control in Multi agent Sequential Decision Tasks

DTIC Science & Technology

2018-04-17

Concurrent Learning of Control in Multi-agent Sequential Decision Tasks The overall objective of this project was to develop multi-agent reinforcement...learning (MARL) approaches for intelligent agents to autonomously learn distributed control policies in decentral- ized partially observable...shall be subject to any oenalty for failing to comply with a collection of information if it does not display a currently valid OMB control number

Implementing a Case-Based E-Learning Environment in a Lecture-Oriented Anaesthesiology Class: Do Learning Styles Matter in Complex Problem Solving over Time?

ERIC Educational Resources Information Center

Choi, Ikseon; Lee, Sang Joon; Kang, Jeongwan

2009-01-01

This study explores how students' learning styles influence their learning while solving complex problems when a case-based e-learning environment is implemented in a conventional lecture-oriented classroom. Seventy students from an anaesthesiology class at a dental school participated in this study over a 3-week period. Five learning-outcome…

Emerging Technologies, ISD, and Learning Environments: Critical Perspectives.

ERIC Educational Resources Information Center

Hannafin, Michael J.

1992-01-01

Reviews the evolution of instructional systems design and computer-based learning environments, focusing on the effects of technological advances. Classification of learning environments is discussed in the context of the dimensions of scope (macrolevel or microlevel), user activity (generative or mathemagenic), educational activity (goal-directed…

Toward Agent Programs with Circuit Semantics

NASA Technical Reports Server (NTRS)

Nilsson, Nils J.

1992-01-01

New ideas are presented for computing and organizing actions for autonomous agents in dynamic environments-environments in which the agent's current situation cannot always be accurately discerned and in which the effects of actions cannot always be reliably predicted. The notion of 'circuit semantics' for programs based on 'teleo-reactive trees' is introduced. Program execution builds a combinational circuit which receives sensory inputs and controls actions. These formalisms embody a high degree of inherent conditionality and thus yield programs that are suitably reactive to their environments. At the same time, the actions computed by the programs are guided by the overall goals of the agent. The paper also speculates about how programs using these ideas could be automatically generated by artificial intelligence planning systems and adapted by learning methods.

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

ERIC Educational Resources Information Center

Hawke, Geof; Chappell, Clive

2008-01-01

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

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.

Drilling Students’ Communication Skill through Science, Environment, Technology, and Society (SETS)-Based Learning

NASA Astrophysics Data System (ADS)

Al-Farisi, B. L.; Tjandrakirana; Agustini, R.

2018-01-01

Student’s communication skill paid less attention in learning activity at school, even though communication skill is needed by students in the 21st century based on the demands of new curriculum in Indonesia (K13). This study focuses on drilling students’ communication skill through science, environment, technology, and society (SETS)-based learning. The research is a pre-experimental design with a one-shot case study model involving 10 students of ninth-grader of SMPN 2 Manyar, Gresik. The research data were collected through observation method using communication observation sheet. The data were analyzed using the descriptive qualitative method. The result showed that students’ communication skill reached the completeness of skills decided both individually and classically in the curriculum. The fundamental result of this research that SETS-based learning can be used to drill students’ communication skill in K13 context.

Connectionist agent-based learning in bank-run decision making

NASA Astrophysics Data System (ADS)

Huang, Weihong; Huang, Qiao

2018-05-01

It is of utter importance for the policy makers, bankers, and investors to thoroughly understand the probability of bank-run (PBR) which was often neglected in the classical models. Bank-run is not merely due to miscoordination (Diamond and Dybvig, 1983) or deterioration of bank assets (Allen and Gale, 1998) but various factors. This paper presents the simulation results of the nonlinear dynamic probabilities of bank runs based on the global games approach, with the distinct assumption that heterogenous agents hold highly correlated but unidentical beliefs about the true payoffs. The specific technique used in the simulation is to let agents have an integrated cognitive-affective network. It is observed that, even when the economy is good, agents are significantly affected by the cognitive-affective network to react to bad news which might lead to bank-run. Both the rise of the late payoffs, R, and the early payoffs, r, will decrease the effect of the affective process. The increased risk sharing might or might not increase PBR, and the increase in late payoff is beneficial for preventing the bank run. This paper is one of the pioneers that links agent-based computational economics and behavioral economics.

Problem-Based Learning and Problem-Solving Tools: Synthesis and Direction for Distributed Education Environments.

ERIC Educational Resources Information Center

Friedman, Robert S.; Deek, Fadi P.

2002-01-01

Discusses how the design and implementation of problem-solving tools used in programming instruction are complementary with both the theories of problem-based learning (PBL), including constructivism, and the practices of distributed education environments. Examines how combining PBL, Web-based distributed education, and a problem-solving…

When Creative Problem Solving Strategy Meets Web-Based Cooperative Learning Environment in Accounting Education

ERIC Educational Resources Information Center

Cheng, Kai Wen

2011-01-01

Background: Facing highly competitive and changing environment, cultivating citizens with problem-solving attitudes is one critical vision of education. In brief, the importance of education is to cultivate students with practical abilities. Realizing the advantages of web-based cooperative learning (web-based CL) and creative problem solving…

Incremental learning of concept drift in nonstationary environments.

PubMed

Elwell, Ryan; Polikar, Robi

2011-10-01

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

Apprentissage et Environment (Learning and Environment)

ERIC Educational Resources Information Center

Care, Jean-Marc

1977-01-01

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

Understanding the Effects of Databases as Cognitive Tools in a Problem-Based Multimedia Learning Environment

ERIC Educational Resources Information Center

Li, Rui; Liu, Min

2007-01-01

The purpose of this study is to examine the potential of using computer databases as cognitive tools to share learners' cognitive load and facilitate learning in a multimedia problem-based learning (PBL) environment designed for sixth graders. Two research questions were: (a) can the computer database tool share sixth-graders' cognitive load? and…

A Watershed-Scale Agent-Based Model Incorporating Agent Learning and Interaction of Farmers' Decisions Subject to Carbon and Miscanthus Prices

NASA Astrophysics Data System (ADS)

Ng, T.; Eheart, J.; Cai, X.; Braden, J. B.

2010-12-01

Agricultural watersheds are coupled human-natural systems where the land use decisions of human agents (farmers) affect surface water quality, and in turn, are affected by the weather and yields. The reliable modeling of such systems requires an approach that considers both the human and natural aspects. Agent-based modeling (ABM), representing the human aspect, coupled with hydrologic modeling, representing the natural aspect, is one such approach. ABM is a relatively new modeling paradigm that formulates the system from the perspectives of the individual agents, i.e., each agent is modeled as a discrete autonomous entity with distinct goals and actions. The primary objective of this study is to demonstrate the applicability of this approach to agricultural watershed management. This is done using a semi-hypothetical case study of farmers in the Salt Creek watershed in East-Central Illinois under the influence markets for carbon and second-generation bioenergy crop (specifically, miscanthus). An agent-based model of the system is developed and linked to a hydrologic model of the watershed. The former is based on fundamental economic and mathematical programming principles, while the latter is based on the Soil and Water Assessment Tool (SWAT). Carbon and second-generation bioenergy crop markets are of interest here due to climate change and energy independence concerns. The agent-based model is applied to fifty hypothetical heterogeneous farmers. The farmers' decisions depend on their perceptions of future conditions. Those perceptions are updated, according to a pre-defined algorithm, as the farmers make new observations of prices, costs, yields and the weather with time. The perceptions are also updated as the farmers interact with each other as they share new information on initially unfamiliar activities (e.g., carbon trading, miscanthus cultivation). The updating algorithm is set differently for different farmers such that each is unique in his processing of

Chronic Heart Failure Follow-up Management Based on Agent Technology.

PubMed

Mohammadzadeh, Niloofar; Safdari, Reza

2015-10-01

Monitoring heart failure patients through continues assessment of sign and symptoms by information technology tools lead to large reduction in re-hospitalization. Agent technology is one of the strongest artificial intelligence areas; therefore, it can be expected to facilitate, accelerate, and improve health services especially in home care and telemedicine. The aim of this article is to provide an agent-based model for chronic heart failure (CHF) follow-up management. This research was performed in 2013-2014 to determine appropriate scenarios and the data required to monitor and follow-up CHF patients, and then an agent-based model was designed. Agents in the proposed model perform the following tasks: medical data access, communication with other agents of the framework and intelligent data analysis, including medical data processing, reasoning, negotiation for decision-making, and learning capabilities. The proposed multi-agent system has ability to learn and thus improve itself. Implementation of this model with more and various interval times at a broader level could achieve better results. The proposed multi-agent system is no substitute for cardiologists, but it could assist them in decision-making.

Chronic Heart Failure Follow-up Management Based on Agent Technology

PubMed Central

Safdari, Reza

2015-01-01

Objectives Monitoring heart failure patients through continues assessment of sign and symptoms by information technology tools lead to large reduction in re-hospitalization. Agent technology is one of the strongest artificial intelligence areas; therefore, it can be expected to facilitate, accelerate, and improve health services especially in home care and telemedicine. The aim of this article is to provide an agent-based model for chronic heart failure (CHF) follow-up management. Methods This research was performed in 2013-2014 to determine appropriate scenarios and the data required to monitor and follow-up CHF patients, and then an agent-based model was designed. Results Agents in the proposed model perform the following tasks: medical data access, communication with other agents of the framework and intelligent data analysis, including medical data processing, reasoning, negotiation for decision-making, and learning capabilities. Conclusions The proposed multi-agent system has ability to learn and thus improve itself. Implementation of this model with more and various interval times at a broader level could achieve better results. The proposed multi-agent system is no substitute for cardiologists, but it could assist them in decision-making. PMID:26618038

Implementation of an ICT-Based Learning Environment in a Nutrition Health Project

ERIC Educational Resources Information Center

Raiha, Teija; Tossavainen, Kerttu; Enkenberg, Jorma; Turunen, Hannele

2012-01-01

Purpose: The purpose of this study was to investigate the views of school staff on a nutrition health project implemented via an ICT-based learning environment in a secondary school (7th to 9th grades). Design/methodology/approach: The study was a part of the wider European Network for Health Promoting Schools programme (ENHPS; since 2008, Schools…

The distributed agent-based approach in the e-manufacturing environment

NASA Astrophysics Data System (ADS)

Sękala, A.; Kost, G.; Dobrzańska-Danikiewicz, A.; Banaś, W.; Foit, K.

2015-11-01

The deficiency of a coherent flow of information from a production department causes unplanned downtime and failures of machines and their equipment, which in turn results in production planning process based on incorrect and out-of-date information. All of these factors entail, as the consequence, the additional difficulties associated with the process of decision-making. They concern, among other, the coordination of components of a distributed system and providing the access to the required information, thereby generating unnecessary costs. The use of agent technology significantly speeds up the flow of information within the virtual enterprise. This paper includes the proposal of a multi-agent approach for the integration of processes within the virtual enterprise concept. The presented concept was elaborated to investigate the possible solutions of the ways of transmission of information in the production system taking into account the self-organization of constituent components. Thus it implicated the linking of the concept of multi-agent system with the system of managing the production information, based on the idea of e-manufacturing. The paper presents resulting scheme that should be the base for elaborating an informatics model of the target virtual system. The computer system itself is intended to be developed next.

Student Blogging: Implications for Learning in a Virtual Text-Based Environment

NASA Astrophysics Data System (ADS)

Deed, Craig; Edwards, Anthony

Realising the potential for web-based communication in learning and teaching is challenging for educators. The purpose of this paper is to report students' attitudes and perception of active learning when using an unrestricted blog in an academic context. It will examine if an unrestricted blog can be used to support reflective and critical discussion leading to the construction of knowledge whether. Unrestricted in this context refers to autonomous individual and group activity undertaken in an unstructured online environment. It will attempt provide an insight into what students make of working at the intersection between academic and online environments. Data was collected using an online survey with questions focused on student perceptions of the type, frequency and effectiveness of their strategy use. Analysis of the resulting material was conducted using Bloom's revised taxonomy to determine whether student strategy was useful in supporting the construction of knowledge. Our research indicates that students need to suitably prepare themselves or be prepared by others to make the most effective use of their prior familiarity with this form of communication technology (which is usually informal) in order to constructing knowledge in an academic context. Thus we conclude that effective learning will only emerge from considered pedagogical design, informed by the student experience and perspective.

Effects of Concept Map Extraction and a Test-Based Diagnostic Environment on Learning Achievement and Learners' Perceptions

ERIC Educational Resources Information Center

Lin, Yu-Shih; Chang, Yi-Chun; Liew, Keng-Hou; Chu, Chih-Ping

2016-01-01

Computerised testing and diagnostics are critical challenges within an e-learning environment, where the learners can assess their learning performance through tests. However, a test result based on only a single score is insufficient information to provide a full picture of learning performance. In addition, because test results implicitly…

A Case Study in User Support for Managing OpenSim Based Multi User Learning Environments

ERIC Educational Resources Information Center

Perera, Indika; Miller, Alan; Allison, Colin

2017-01-01

Immersive 3D Multi User Learning Environments (MULE) have shown sufficient success to warrant their consideration as a mainstream educational paradigm. These are based on 3D Multi User Virtual Environment platforms (MUVE), and although they have been used for various innovative educational projects their complex permission systems and large…

Designing across ages: Multi-agent-based models and learning electricity

NASA Astrophysics Data System (ADS)

Sengupta, Pratim

Electricity is regarded as one of the most challenging topics for students at all levels -- middle school -- college (Cohen, Eylon, & Ganiel, 1983; Belcher & Olbert, 2003; Eylon & Ganiel, 1990; Steinberg et al., 1985). Several researchers have suggested that naive misconceptions about electricity stem from a deep incommensurability (Slotta & Chi, 2006; Chi, 2005) or incompatibility (Chi, Slotta & Leauw, 1994; Reiner, Slotta, Chi, & Resnick, 2000) between naive and expert knowledge structures. I first present an alternative theoretical framework that adopts an emergent levels-based perspective as proposed by Wilensky & Resnick (1999). From this perspective, macro-level phenomena such as electric current and resistance, as well as behavior of linear electric circuits, can be conceived of as emergent from simple, body-syntonic interactions between electrons and ions in a circuit. I argue that adopting such a perspective enables us to reconceive commonly noted misconceptions in electricity as behavioral evidences of "slippage between levels" -- i.e., these misconceptions appear when otherwise productive knowledge elements are sometimes inappropriately activated due to certain macro-level phenomenological cues only -- and, that the same knowledge elements when activated due to phenomenological cues at both micro- and macro-levels, can engender a deeper, expert-like understanding. I will then introduce NIELS (NetLogo Investigations In Electromagnetism, Sengupta & Wilensky, 2006, 2008, 2009), a low-threshold high-ceiling (LTHC) learning environment of multi-agent-based computational models that represent phenomena such as electric current and resistance, as well as the behavior of linear electric circuits, as emergent. I also present results from implementations of NIELS in 5th, 7th and 12th grade classrooms that show the following: (a) how leveraging certain "design elements" over others in NIELS models can create new phenomenological cues, which in turn can be

Patterns of Use of an Agent-Based Model and a System Dynamics Model: The Application of Patterns of Use and the Impacts on Learning Outcomes

ERIC Educational Resources Information Center

Thompson, Kate; Reimann, Peter

2010-01-01

A classification system that was developed for the use of agent-based models was applied to strategies used by school-aged students to interrogate an agent-based model and a system dynamics model. These were compared, and relationships between learning outcomes and the strategies used were also analysed. It was found that the classification system…

Distributed Scaffolding: Synergy in Technology-Enhanced Learning Environments

ERIC Educational Resources Information Center

Ustunel, Hale H.; Tokel, Saniye Tugba

2018-01-01

When technology is employed challenges increase in learning environments. Kim et al. ("Sci Educ" 91(6):1010-1030, 2007) presented a pedagogical framework that provides a valid technology-enhanced learning environment. The purpose of the present design-based study was to investigate the micro context dimension of this framework and to…

Supporting Self-Regulated Learning in Computer-Based Learning Environments: Systematic Review of Effects of Scaffolding in the Domain of Science Education

ERIC Educational Resources Information Center

Devolder, A.; van Braak, J.; Tondeur, J.

2012-01-01

Despite the widespread assumption that students require scaffolding support for self-regulated learning (SRL) processes in computer-based learning environments (CBLEs), there is little clarity as to which types of scaffolds are most effective. This study offers a literature review covering the various scaffolds that support SRL processes in the…

A mobile agent-based moving objects indexing algorithm in location based service

NASA Astrophysics Data System (ADS)

Fang, Zhixiang; Li, Qingquan; Xu, Hong

2006-10-01

This paper will extends the advantages of location based service, specifically using their ability to management and indexing the positions of moving object, Moreover with this objective in mind, a mobile agent-based moving objects indexing algorithm is proposed in this paper to efficiently process indexing request and acclimatize itself to limitation of location based service environment. The prominent feature of this structure is viewing moving object's behavior as the mobile agent's span, the unique mapping between the geographical position of moving objects and span point of mobile agent is built to maintain the close relationship of them, and is significant clue for mobile agent-based moving objects indexing to tracking moving objects.

Designing a Structured and Interactive Learning Environment Based on GIS for Secondary Geography Education

ERIC Educational Resources Information Center

Liu, Suxia; Zhu, Xuan

2008-01-01

Geographic information systems (GIS) are computer-based tools for geographic data analysis and spatial visualization. They have become one of the information and communications technologies for education at all levels. This article reviews the current status of GIS in schools, analyzes the requirements of a GIS-based learning environment from…

Effect of reinforcement learning on coordination of multiangent systems

NASA Astrophysics Data System (ADS)

Bukkapatnam, Satish T. S.; Gao, Greg

2000-12-01

For effective coordination of distributed environments involving multiagent systems, learning ability of each agent in the environment plays a crucial role. In this paper, we develop a simple group learning method based on reinforcement, and study its effect on coordination through application to a supply chain procurement scenario involving a computer manufacturer. Here, all parties are represented by self-interested, autonomous agents, each capable of performing specific simple tasks. They negotiate with each other to perform complex tasks and thus coordinate supply chain procurement. Reinforcement learning is intended to enable each agent to reach a best negotiable price within a shortest possible time. Our simulations of the application scenario under different learning strategies reveals the positive effects of reinforcement learning on an agent's as well as the system's performance.

Transactional Distance in a Blended Learning Environment

ERIC Educational Resources Information Center

Dron, Jon; Seidel, Catharine; Litten, Gabrielle

2004-01-01

This paper presents a case study that describes and discusses the problems encountered during the design and implementation of a blended learning course, largely taught online through a web-based learning environment. Based on Moore's theory of transactional distance, the course was explicitly designed to have dialogue at its heart. However, the…

Deep Learning Based Binaural Speech Separation in Reverberant Environments.

PubMed

Zhang, Xueliang; Wang, DeLiang

2017-05-01

Speech signal is usually degraded by room reverberation and additive noises in real environments. This paper focuses on separating target speech signal in reverberant conditions from binaural inputs. Binaural separation is formulated as a supervised learning problem, and we employ deep learning to map from both spatial and spectral features to a training target. With binaural inputs, we first apply a fixed beamformer and then extract several spectral features. A new spatial feature is proposed and extracted to complement the spectral features. The training target is the recently suggested ideal ratio mask. Systematic evaluations and comparisons show that the proposed system achieves very good separation performance and substantially outperforms related algorithms under challenging multi-source and reverberant environments.

Peer Interaction in Three Collaborative Learning Environments

ERIC Educational Resources Information Center

Staarman, Judith Kleine; Krol, Karen; Meijden, Henny van der

2005-01-01

The aim of the study was to gain insight into the occurrence of different types of peer interaction and particularly the types of interaction beneficial for learning in different collaborative learning environments. Based on theoretical notions related to collaborative learning and peer interaction, a coding scheme was developed to analyze the…

A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling.

PubMed

Singh, Karandeep; Ahn, Chang-Won; Paik, Euihyun; Bae, Jang Won; Lee, Chun-Hee

2018-01-01

Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or "soft," aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing. Furthermore, we use this framework to implement a hybrid model using microsimulation and agent-based modeling techniques to generate an artificial society. We leverage this artificial society to simulate and analyze population dynamics using Korean population census data. The agents in this model derive their decisional behaviors from real data (microsimulation feature) and interact among themselves (agent-based modeling feature) to proceed in the simulation. The behaviors, interactions, and social scenarios of the agents are varied to perform an analysis of population dynamics. We also estimate the future cost of pension policies based on the future population structure of the artificial society. The proposed framework and model demonstrates how ALife techniques can be used by researchers in relation to social issues and policies.

High-Fidelity e-Learning: SEI’s Virtual Training Environment (VTE)

DTIC Science & Technology

2009-01-01

Assessment 2.4 Collaboration 2.4.1 Peer-Student Collaboration 2.4.2 Instructor Support 2.5 Accessibility 2.6 Modularity 2.6.1 Design for Re-Use 2.6.2 Design ...ing Environment as an implementation of a high-fidelity e-Ieaming system. This report does not cover concepts of pedagogy or instructional design in e...pedagogical agents. This is the basis for Clark and Mayer’s Personalization principle for designing media for e-learning [Clark & Mayer 2003]. E-learning

Developing a Conceptual Architecture for a Generalized Agent-based Modeling Environment (GAME)

DTIC Science & Technology

2008-03-01

4. REPAST (Java, Python , C#, Open Source) ........28 5. MASON: Multi-Agent Modeling Language (Swarm Extension... Python , C#, Open Source) Repast (Recursive Porous Agent Simulation Toolkit) was designed for building agent-based models and simulations in the...Repast makes it easy for inexperienced users to build models by including a built-in simple model and provide interfaces through which menus and Python

What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated.

PubMed

Kumaran, Dharshan; Hassabis, Demis; McClelland, James L

2016-07-01

We update complementary learning systems (CLS) theory, which holds that intelligent agents must possess two learning systems, instantiated in mammalians in neocortex and hippocampus. The first gradually acquires structured knowledge representations while the second quickly learns the specifics of individual experiences. We broaden the role of replay of hippocampal memories in the theory, noting that replay allows goal-dependent weighting of experience statistics. We also address recent challenges to the theory and extend it by showing that recurrent activation of hippocampal traces can support some forms of generalization and that neocortical learning can be rapid for information that is consistent with known structure. Finally, we note the relevance of the theory to the design of artificial intelligent agents, highlighting connections between neuroscience and machine learning. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

Agent-based modeling: a new approach for theory building in social psychology.

PubMed

Smith, Eliot R; Conrey, Frederica R

2007-02-01

Most social and psychological phenomena occur not as the result of isolated decisions by individuals but rather as the result of repeated interactions between multiple individuals over time. Yet the theory-building and modeling techniques most commonly used in social psychology are less than ideal for understanding such dynamic and interactive processes. This article describes an alternative approach to theory building, agent-based modeling (ABM), which involves simulation of large numbers of autonomous agents that interact with each other and with a simulated environment and the observation of emergent patterns from their interactions. The authors believe that the ABM approach is better able than prevailing approaches in the field, variable-based modeling (VBM) techniques such as causal modeling, to capture types of complex, dynamic, interactive processes so important in the social world. The article elaborates several important contrasts between ABM and VBM and offers specific recommendations for learning more and applying the ABM approach.

Modeling Students' Problem Solving Performance in the Computer-Based Mathematics Learning Environment

ERIC Educational Resources Information Center

Lee, Young-Jin

2017-01-01

Purpose: The purpose of this paper is to develop a quantitative model of problem solving performance of students in the computer-based mathematics learning environment. Design/methodology/approach: Regularized logistic regression was used to create a quantitative model of problem solving performance of students that predicts whether students can…

Impact of Blended Learning Environments Based on Algo-Heuristic Theory on Some Variables

ERIC Educational Resources Information Center

Aygün, Mustafa; Korkmaz, Özgen

2012-01-01

In this study, the effects of Algo-Heuristic Theory based blended learning environments on students' computer skills in their preparation of presentations, levels of attitudes towards computers, and levels of motivation regarding the information technology course were investigated. The research sample was composed of 71 students. A semi-empirical…

QSIA--A Web-Based Environment for Learning, Assessing and Knowledge Sharing in Communities

ERIC Educational Resources Information Center

Rafaeli, Sheizaf; Barak, Miri; Dan-Gur, Yuval; Toch, Eran

2004-01-01

This paper describes a Web-based and distributed system named QSIA that serves as an environment for learning, assessing and knowledge sharing. QSIA--Questions Sharing and Interactive Assignments--offers a unified infrastructure for developing, collecting, managing and sharing of knowledge items. QSIA enhances collaboration in authoring via online…

Design of Personalized Blended Learning Environments Based on Web-Assisted Modelling in Science Education

ERIC Educational Resources Information Center

Çetinkaya, Murat

2016-01-01

Positive results of science teaching studies supported with the means provided by technology require the enrichment of the content of blended learning environments to provide more benefits. Within this context, it is thought that preparing a web-assisted model-based teaching, which is frequently used in science teaching, based on the "Matter…

Blended learning approach improves teaching in a problem-based learning environment in orthopedics - a pilot study.

PubMed

Back, David A; Haberstroh, Nicole; Antolic, Andrea; Sostmann, Kai; Schmidmaier, Gerhard; Hoff, Eike

2014-01-27

While e-learning is enjoying increasing popularity as adjunct in modern teaching, studies on this topic should shift from mere evaluation of students' satisfaction towards assessing its benefits on enhancement of knowledge and skills. This pilot study aimed to detect the teaching effects of a blended learning program on students of orthopedics and traumatology in the context of a problem-based learning environment. The project NESTOR (network for students in traumatology and orthopedics) was offered to students in a problem-based learning course. Participants completed written tests before and directly after the course, followed by a final written test and an objective structured clinical examination (OSCE) as well as an evaluation questionnaire at the end of the semester. Results were compared within the group of NESTOR users and non-users and between these two groups. Participants (n = 53) rated their experiences very positively. An enhancement in knowledge was found directly after the course and at the final written test for both groups (p < 0.001). NESTOR users scored higher than non-users in the post-tests, while the OSCE revealed no differences between the groups. This pilot study showed a positive effect of the blended learning approach on knowledge enhancement and satisfaction of participating students. However, it will be an aim for the future to further explore the chances of this approach and internet-based technologies for possibilities to improve also practical examination skills.

Blended learning approach improves teaching in a problem-based learning environment in orthopedics - a pilot study

PubMed Central

2014-01-01

Background While e-learning is enjoying increasing popularity as adjunct in modern teaching, studies on this topic should shift from mere evaluation of students’ satisfaction towards assessing its benefits on enhancement of knowledge and skills. This pilot study aimed to detect the teaching effects of a blended learning program on students of orthopedics and traumatology in the context of a problem-based learning environment. Methods The project NESTOR (network for students in traumatology and orthopedics) was offered to students in a problem-based learning course. Participants completed written tests before and directly after the course, followed by a final written test and an objective structured clinical examination (OSCE) as well as an evaluation questionnaire at the end of the semester. Results were compared within the group of NESTOR users and non-users and between these two groups. Results Participants (n = 53) rated their experiences very positively. An enhancement in knowledge was found directly after the course and at the final written test for both groups (p < 0.001). NESTOR users scored higher than non-users in the post-tests, while the OSCE revealed no differences between the groups. Conclusions This pilot study showed a positive effect of the blended learning approach on knowledge enhancement and satisfaction of participating students. However, it will be an aim for the future to further explore the chances of this approach and internet-based technologies for possibilities to improve also practical examination skills. PMID:24690365

Face-to-Face Interaction with Pedagogical Agents, Twenty Years Later

ERIC Educational Resources Information Center

Johnson, W. Lewis; Lester, James C.

2016-01-01

Johnson et al. ("International Journal of Artificial Intelligence in Education," 11, 47-78, 2000) introduced and surveyed a new paradigm for interactive learning environments: animated pedagogical agents. The article argued for combining animated interface agent technologies with intelligent learning environments, yielding intelligent…

Virtual Slovak: Insight into Learning Slovak in an E-Learning Environment

ERIC Educational Resources Information Center

Kyppö, Anna

2015-01-01

This paper offers insight into learning Slovak in an e-learning environment. The need to reach distance-learners of Slovak led to the implementation of a web-based course on Slovak language and culture in 2008-2010. The pedagogical basis of the course, called Virtual Slovak, is the socioconstructivist approach to teaching and learning, in which…

An Approach to Folksonomy-Based Ontology Maintenance for Learning Environments

ERIC Educational Resources Information Center

Gasevic, D.; Zouaq, Amal; Torniai, Carlo; Jovanovic, J.; Hatala, Marek

2011-01-01

Recent research in learning technologies has demonstrated many promising contributions from the use of ontologies and semantic web technologies for the development of advanced learning environments. In spite of those benefits, ontology development and maintenance remain the key research challenges to be solved before ontology-enhanced learning…

Exceeding Expectations: Scaffolding Agentic Engagement through Assessment as Learning

ERIC Educational Resources Information Center

Fletcher, Anna Katarina

2016-01-01

Background: The active involvement of learners as critical, reflective and capable agents in the learning process is a core aim in contemporary education policy in Australia, and is regarded as a significant factor for academic success. However, within the relevant literature, the issue of positioning students as agents in the learning process has…

Fifth Graders' Flow Experience in a Digital Game-Based Science Learning Environment

ERIC Educational Resources Information Center

Zheng, Meixun; Spires, Hiller A.

2014-01-01

This mixed methods study examined 73 5th graders' flow experience in a game-based science learning environment using two gameplay approaches (solo and collaborative gameplay). Both survey and focus group interview findings revealed that students had high flow experience; however, there were no flow experience differences that were contingent upon…

Evolution of a multi-agent system in a cyclical environment.

PubMed

Baptista, Tiago; Costa, Ernesto

2008-06-01

The synchronisation phenomena in biological systems is a current and recurring subject of scientific study. This topic, namely that of circadian clocks, served as inspiration to develop an agent-based simulation that serves the main purpose of being a proof-of-concept of the model used in the BitBang framework, that implements a modern autonomous agent model. Despite having been extensively studied, circadian clocks still have much to be investigated. Rather than wanting to learn more about the internals of this biological process, we look to study the emergence of this kind of adaptation to a daily cycle. To that end we implemented a world with a day/night cycle, and analyse the ways the agents adapt to that cycle. The results show the evolution of the agents' ability to gather food. If we look at the total number of agents over the course of an experiment, we can pinpoint the time when reproductive technology emerges. We also show that the agents adapt to the daily cycle. This circadian rhythm can be shown by analysing the variation on the agents metabolic rate, which is affected by the variation of their movement patterns. In the experiments conducted we can observe that the metabolic rate of the agents varies according to the daily cycle.

Learning to Predict Consequences as a Method of Knowledge Transfer in Reinforcement Learning.

PubMed

Chalmers, Eric; Contreras, Edgar Bermudez; Robertson, Brandon; Luczak, Artur; Gruber, Aaron

2017-04-17

The reinforcement learning (RL) paradigm allows agents to solve tasks through trial-and-error learning. To be capable of efficient, long-term learning, RL agents should be able to apply knowledge gained in the past to new tasks they may encounter in the future. The ability to predict actions' consequences may facilitate such knowledge transfer. We consider here domains where an RL agent has access to two kinds of information: agent-centric information with constant semantics across tasks, and environment-centric information, which is necessary to solve the task, but with semantics that differ between tasks. For example, in robot navigation, environment-centric information may include the robot's geographic location, while agent-centric information may include sensor readings of various nearby obstacles. We propose that these situations provide an opportunity for a very natural style of knowledge transfer, in which the agent learns to predict actions' environmental consequences using agent-centric information. These predictions contain important information about the affordances and dangers present in a novel environment, and can effectively transfer knowledge from agent-centric to environment-centric learning systems. Using several example problems including spatial navigation and network routing, we show that our knowledge transfer approach can allow faster and lower cost learning than existing alternatives.

An Evaluation of an Inquiry-Based Computer-Assisted Learning Environment.

ERIC Educational Resources Information Center

Maor, Dorit; Fraser, Barry

1994-01-01

This study focused on students' development of inquiry skills in a computerized learning environment. Seven Year-11 classes (n=120) interacted with a computerized database, "Birds of Antarctica," and curriculum materials while the teacher used an inquiry approach to learning. Students perceived their classes as more investigative and…

Agent Based Modeling Applications for Geosciences

NASA Astrophysics Data System (ADS)

Stein, J. S.

2004-12-01

Agent-based modeling techniques have successfully been applied to systems in which complex behaviors or outcomes arise from varied interactions between individuals in the system. Each individual interacts with its environment, as well as with other individuals, by following a set of relatively simple rules. Traditionally this "bottom-up" modeling approach has been applied to problems in the fields of economics and sociology, but more recently has been introduced to various disciplines in the geosciences. This technique can help explain the origin of complex processes from a relatively simple set of rules, incorporate large and detailed datasets when they exist, and simulate the effects of extreme events on system-wide behavior. Some of the challenges associated with this modeling method include: significant computational requirements in order to keep track of thousands to millions of agents, methods and strategies of model validation are lacking, as is a formal methodology for evaluating model uncertainty. Challenges specific to the geosciences, include how to define agents that control water, contaminant fluxes, climate forcing and other physical processes and how to link these "geo-agents" into larger agent-based simulations that include social systems such as demographics economics and regulations. Effective management of limited natural resources (such as water, hydrocarbons, or land) requires an understanding of what factors influence the demand for these resources on a regional and temporal scale. Agent-based models can be used to simulate this demand across a variety of sectors under a range of conditions and determine effective and robust management policies and monitoring strategies. The recent focus on the role of biological processes in the geosciences is another example of an area that could benefit from agent-based applications. A typical approach to modeling the effect of biological processes in geologic media has been to represent these processes in

Socio-Technical Dimensions of an Outdoor Mobile Learning Environment: A Three-Phase Design-Based Research Investigation

ERIC Educational Resources Information Center

Land, Susan M.; Zimmerman, Heather Toomey

2015-01-01

This design-based research project examines three iterations of Tree Investigators, a learning environment designed to support science learning outdoors at an arboretum and nature center using mobile devices (iPads). Researchers coded videorecords and artifacts created by children and parents (n = 53) to understand how both social and…

Nash Equilibrium of Social-Learning Agents in a Restless Multiarmed Bandit Game.

PubMed

Nakayama, Kazuaki; Hisakado, Masato; Mori, Shintaro

2017-05-16

We study a simple model for social-learning agents in a restless multiarmed bandit (rMAB). The bandit has one good arm that changes to a bad one with a certain probability. Each agent stochastically selects one of the two methods, random search (individual learning) or copying information from other agents (social learning), using which he/she seeks the good arm. Fitness of an agent is the probability to know the good arm in the steady state of the agent system. In this model, we explicitly construct the unique Nash equilibrium state and show that the corresponding strategy for each agent is an evolutionarily stable strategy (ESS) in the sense of Thomas. It is shown that the fitness of an agent with ESS is superior to that of an asocial learner when the success probability of social learning is greater than a threshold determined from the probability of success of individual learning, the probability of change of state of the rMAB, and the number of agents. The ESS Nash equilibrium is a solution to Rogers' paradox.

A Study of Building a Resource-Based Learning Environment with the Inquiry Learning Approach: Knowledge of Family Trees

ERIC Educational Resources Information Center

Kong, Siu Cheung; So, Wing Mui Winnie

2008-01-01

This study aims to provide teachers with ways and means to facilitate learners to develop nomenclature knowledge of family trees through the establishment of resource-based learning environments (RBLEs). It discusses the design of an RBLE in the classroom by selecting an appropriate context with the assistance of computer-mediated learning…

Using Coherence Analysis to Characterize Self-Regulated Learning Behaviours in Open-Ended Learning Environments

ERIC Educational Resources Information Center

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

2015-01-01

Researchers have long recognized the potential benefits of open-ended computer- based learning environments (OELEs) to help students develop self-regulated learning (SRL) behaviours. However, measuring self-regulation in these environments is a difficult task. In this paper, we present our work in developing and evaluating "coherence…

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

ERIC Educational Resources Information Center

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

2017-01-01

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

Development of Constructivist-Based Distance Learning Environments: A Knowledge Base for K-12 Teachers

ERIC Educational Resources Information Center

Herring, Mary Corwin

2004-01-01

In response to societal shifts, K-12 teachers are struggling to design effective learning environments. The advent of increased access to world-linking technology has extended the use of distance education to enrich and expand the learning landscape for students. A number of individuals have suggested that a body of learning theory,…

Open Integrated Personal Learning Environment: Towards a New Conception of the ICT-Based Learning Processes

NASA Astrophysics Data System (ADS)

Conde, Miguel Ángel; García-Peñalvo, Francisco José; Casany, Marià José; Alier Forment, Marc

Learning processes are changing related to technological and sociological evolution, taking this in to account, a new learning strategy must be considered. Specifically what is needed is to give an effective step towards the eLearning 2.0 environments consolidation. This must imply the fusion of the advantages of the traditional LMS (Learning Management System) - more formative program control and planning oriented - with the social learning and the flexibility of the web 2.0 educative applications.

Causal Model Progressions as a Foundation for Intelligent Learning Environments.

DTIC Science & Technology

1987-11-01

Foundation for Intelligent Learning Environments 3Barbara Y. White and John R. Frederiksen ~DTIC Novemr1987 ELECTE November1987 JUNO 9 88 Approved I )’I...Learning Environments 12. PERSONAL AUTHOR(S? Barbara Y. White and John R. Frederiksen 13a. TYPE OF REPORT 13b TIME COVERED 14. DATE OF REPORT (Year...architecture of a new type of learning environment that incorporates features of microworlds and of intelligent tutorng systems. The environment is based on

Creating a Multimedia Enhanced Problem-Based Learning Environment for Middle School Science: Voices from the Developers

ERIC Educational Resources Information Center

Liu, Min; Horton, Lucas; Lee, Jaejin; Kang, Jina; Rosenblum, Jason; O'Hair, Matthew; Lu, Chu-Wei

2014-01-01

This paper describes the design and development process used to create Alien Rescue, a multimedia-enhanced learning environment that supports problem-based learning (PBL) in middle school science. The goal of the project is to further our understandings of technology, pedagogy, and instructional theories as they relate to the application of PBL…

Investigating the Quality of Project-Based Science and Technology Learning Environments in Elementary School: A Critical Review of Instruments

ERIC Educational Resources Information Center

Thys, Miranda; Verschaffel, Lieven; Van Dooren, Wim; Laevers, Ferre

2016-01-01

This paper provides a systematic review of instruments that have the potential to measure the quality of project-based science and technology (S&T) learning environments in elementary school. To this end, a comprehensive literature search was undertaken for the large field of S&T learning environments. We conducted a horizontal bottom-up…

Learning to soar in turbulent environments

NASA Astrophysics Data System (ADS)

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

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

Creative and Playful Learning: Learning through Game Co-Creation and Games in a Playful Learning Environment

ERIC Educational Resources Information Center

Kangas, Marjaana

2010-01-01

This paper reports on a pilot study in which children aged 7-12 (N = 68) had an opportunity to study in a novel formal and informal learning setting. The learning activities were extended from the classroom to the playful learning environment (PLE), an innovative playground enriched by technological tools. Curriculum-based learning was intertwined…

The Role of Agent Age and Gender for Middle-Grade Girls

ERIC Educational Resources Information Center

Kim, Yanghee

2016-01-01

Compared to boys, many girls are more aware of a social context in the learning process and perform better when the environment supports frequent interactions and social relationships. For these girls, embodied agents (animated on-screen characters acting as tutors) could afford simulated social interactions in computer-based learning and thereby…

The Effects of Different Learning Environments on Students' Motivation for Learning and Their Achievement

ERIC Educational Resources Information Center

Baeten, Marlies; Dochy, Filip; Struyven, Katrien

2013-01-01

Background: Research in higher education on the effects of student-centred versus lecture-based learning environments generally does not take into account the psychological need support provided in these learning environments. From a self-determination theory perspective, need support is important to study because it has been associated with…

The Agent-based Approach: A New Direction for Computational Models of Development.

ERIC Educational Resources Information Center

Schlesinger, Matthew; Parisi, Domenico

2001-01-01

Introduces the concepts of online and offline sampling and highlights the role of online sampling in agent-based models of learning and development. Compares the strengths of each approach for modeling particular developmental phenomena and research questions. Describes a recent agent-based model of infant causal perception. Discusses limitations…

The Methodology for Developing Mobile Agent Application for Ubiquitous Environment

NASA Astrophysics Data System (ADS)

Matsuzaki, Kazutaka; Yoshioka, Nobukazu; Honiden, Shinichi

A methodology which enables a flexible and reusable development of mobile agent application to a mobility aware indoor environment is provided in this study. The methodology is named Workflow-awareness model based on a concept of a pair of mobile agents cooperating to perform a given task. A monolithic mobile agent application with numerous concerns in a mobility aware setting is divided into a master agent (MA) and a shadow agent (SA) according to a type of tasks. The MA executes a main application logic which includes monitoring a user's physical movement and coordinating various services. The SA performs additional tasks depending on environments to aid the MA in achieving efficient execution without losing application logic. "Workflow-awareness (WFA)" means that the SA knows the MA's execution state transition so that the SA can provide a proper task at a proper timing. A prototype implementation of the methodology is done with a practical use of AspectJ. AspectJ is used to automate WFA by weaving communication modules to both MA and SA. Usefulness of this methodology concerning its efficiency and software engineering aspects are analyzed. As for the effectiveness, the overhead of WFA is relatively small to the whole expenditure time. And from the view of the software engineering, WFA is possible to provide a mechanism to deploy one application in various situations.

Evaluation of Intelligent Grouping Based on Learners' Collaboration Competence Level in Online Collaborative Learning Environment

ERIC Educational Resources Information Center

Muuro, Maina Elizaphan; Oboko, Robert; Wagacha, Waiganjo Peter

2016-01-01

In this paper we explore the impact of an intelligent grouping algorithm based on learners' collaborative competency when compared with (a) instructor based Grade Point Average (GPA) method level and (b) random method, on group outcomes and group collaboration problems in an online collaborative learning environment. An intelligent grouping…

Learning about Environments: The Significance of Primal Landscapes

NASA Astrophysics Data System (ADS)

Measham, Thomas G.

2006-09-01

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

Interactive Learning Environment: Web-based Virtual Hydrological Simulation System using Augmented and Immersive Reality

NASA Astrophysics Data System (ADS)

Demir, I.

2014-12-01

Recent developments in internet technologies make it possible to manage and visualize large data on the web. Novel visualization techniques and interactive user interfaces allow users to create realistic environments, and interact with data to gain insight from simulations and environmental observations. The hydrological simulation system is a web-based 3D interactive learning environment for teaching hydrological processes and concepts. The simulation systems provides a visually striking platform with realistic terrain information, and water simulation. Students can create or load predefined scenarios, control environmental parameters, and evaluate environmental mitigation alternatives. The web-based simulation system provides an environment for students to learn about the hydrological processes (e.g. flooding and flood damage), and effects of development and human activity in the floodplain. The system utilizes latest web technologies and graphics processing unit (GPU) for water simulation and object collisions on the terrain. Users can access the system in three visualization modes including virtual reality, augmented reality, and immersive reality using heads-up display. The system provides various scenarios customized to fit the age and education level of various users. This presentation provides an overview of the web-based flood simulation system, and demonstrates the capabilities of the system for various visualization and interaction modes.

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

PubMed

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

2018-03-01

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

Instructional Suggestions Supporting Science Learning in Digital Environments Based on a Review of Eye-Tracking Studies

ERIC Educational Resources Information Center

Yang, Fang-Ying; Tsai, Meng-Jung; Chiou, Guo-Li; Lee, Silvia Wen-Yu; Chang, Cheng-Chieh; Chen, Li-Ling

2018-01-01

The main purpose of this study was to provide instructional suggestions for supporting science learning in digital environments based on a review of eye tracking studies in e-learning related areas. Thirty-three eye-tracking studies from 2005 to 2014 were selected from the Social Science Citation Index (SSCI) database for review. Through a…

A Web-Based Blended Learning Environment for Programming Languages: Students' Opinions

ERIC Educational Resources Information Center

Yagci, Mustafa

2017-01-01

A learning environment which increases the desire and efforts of students to attain learning goals leads to greater motivation and success. This study examines the negative and positive opinions of students regarding the effectiveness of the learning process and students' success in a computer programming course in which face-to-face and web-based…

A technology path to tactical agent-based modeling

NASA Astrophysics Data System (ADS)

James, Alex; Hanratty, Timothy P.

2017-05-01

Wargaming is a process of thinking through and visualizing events that could occur during a possible course of action. Over the past 200 years, wargaming has matured into a set of formalized processes. One area of growing interest is the application of agent-based modeling. Agent-based modeling and its additional supporting technologies has potential to introduce a third-generation wargaming capability to the Army, creating a positive overmatch decision-making capability. In its simplest form, agent-based modeling is a computational technique that helps the modeler understand and simulate how the "whole of a system" responds to change over time. It provides a decentralized method of looking at situations where individual agents are instantiated within an environment, interact with each other, and empowered to make their own decisions. However, this technology is not without its own risks and limitations. This paper explores a technology roadmap, identifying research topics that could realize agent-based modeling within a tactical wargaming context.

Meeting the Informal Learning Challenges of the Free Agent Learner: Drawing Insights from Research-Based Lessons Learned. Innovative Session 1. [Concurrent Innovative Session at AHRD Annual Conference, 2000.

ERIC Educational Resources Information Center

Marsick, Victoria J.; Volpe, F. Marie; Brooks, Ann; Cseh, Maria; Lovin, Barbara Keelor; Vernon, Sally; Watkins, Karen E.; Ziegler, Mary

The concept of the free agent learner, which has roots in self-directed and informal learning theory, has recently emerged as a factor important to attracting, developing, and keeping knowledge workers. The literature on free agent learning holds important lessons for today's free agent learners, human resource developers, and work organizations.…

New Horizons: Designing and Measuring for Modern Learning Environments

ERIC Educational Resources Information Center

Carter, Richard Allen, Jr.

2017-01-01

This dissertation consists of five chapters. The first chapter serves to introduce the Modern Learning Environment (MLE) by discussing the challenges of designing and measuring student performance in these novel environments. Chapter two of the dissertation reviews the current research base of studying self-regulated learning in the modern…

Self-Directed Learning Readiness, Internet Self-Efficacy and Preferences towards Constructivist Internet-Based Learning Environments among Higher-Aged Adults

ERIC Educational Resources Information Center

Chu, R. J-C.; Tsai, C-C.

2009-01-01

This article examines several research questions to establish a theory model for explaining factors that influence adult learners' preferences for constructivist Internet-based learning environments (CILE). Data were gathered from 541 individual participants enrolled in adult education institutes in Taiwan for structural equation modelling (SEM)…

Exploring Collaborative Learning Effect in Blended Learning Environments

ERIC Educational Resources Information Center

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

2017-01-01

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

Using Design-Based Research in Informal Environments

ERIC Educational Resources Information Center

Reisman, Molly

2008-01-01

Design-Based Research (DBR) has been a tool of the learning sciences since the early 1990s, used as a way to improve and study learning environments. Using an iterative process of design with the goal of reining theories of learning, researchers and educators now use DBR seek to identify "how" to make a learning environment work. They then draw…

Use of Heuristics to Facilitate Scientific Discovery Learning in a Simulation Learning Environment in a Physics Domain

ERIC Educational Resources Information Center

Veermans, Koen; van Joolingen, Wouter; de Jong, Ton

2006-01-01

This article describes a study into the role of heuristic support in facilitating discovery learning through simulation-based learning. The study compares the use of two such learning environments in the physics domain of collisions. In one learning environment (implicit heuristics) heuristics are only used to provide the learner with guidance…

Learning in engineered multi-agent systems

NASA Astrophysics Data System (ADS)

Menon, Anup

Consider the problem of maximizing the total power produced by a wind farm. Due to aerodynamic interactions between wind turbines, each turbine maximizing its individual power---as is the case in present-day wind farms---does not lead to optimal farm-level power capture. Further, there are no good models to capture the said aerodynamic interactions, rendering model based optimization techniques ineffective. Thus, model-free distributed algorithms are needed that help turbines adapt their power production on-line so as to maximize farm-level power capture. Motivated by such problems, the main focus of this dissertation is a distributed model-free optimization problem in the context of multi-agent systems. The set-up comprises of a fixed number of agents, each of which can pick an action and observe the value of its individual utility function. An individual's utility function may depend on the collective action taken by all agents. The exact functional form (or model) of the agent utility functions, however, are unknown; an agent can only measure the numeric value of its utility. The objective of the multi-agent system is to optimize the welfare function (i.e. sum of the individual utility functions). Such a collaborative task requires communications between agents and we allow for the possibility of such inter-agent communications. We also pay attention to the role played by the pattern of such information exchange on certain aspects of performance. We develop two algorithms to solve this problem. The first one, engineered Interactive Trial and Error Learning (eITEL) algorithm, is based on a line of work in the Learning in Games literature and applies when agent actions are drawn from finite sets. While in a model-free setting, we introduce a novel qualitative graph-theoretic framework to encode known directed interactions of the form "which agents' action affect which others' payoff" (interaction graph). We encode explicit inter-agent communications in a directed

Learning from and with Museum Objects: Design Perspectives, Environment, and Emerging Learning Systems

ERIC Educational Resources Information Center

Vartiainen, Henriikka; Enkenberg, Jorma

2013-01-01

Sociocultural approaches emphasize the systemic, context-bound nature of learning, which is mediated by other people, physical and conceptual artifacts, and tools. However, current educational systems tend not to approach learning from the systemic perspective, and mostly situate learning within classroom environments. This design-based research…

Creating Electronic Learning Environments: Games, Flow, and the User Interface.

ERIC Educational Resources Information Center

Jones, Marshall G.

A difficult task in creating rich, exploratory interactive learning environments is building an environment that is truly engaging. Engagement can be defined as the nexus of intrinsic knowledge and/or interest and external stimuli that promote the initial interest in, and continued use of a computer-based learning environment. Complete and total…

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

PubMed

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

2013-02-01

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

Agent-oriented privacy-based information brokering architecture for healthcare environments.

PubMed

Masaud-Wahaishi, Abdulmutalib; Ghenniwa, Hamada

2009-01-01

Healthcare industry is facing a major reform at all levels-locally, regionally, nationally, and internationally. Healthcare services and systems become very complex and comprise of a vast number of components (software systems, doctors, patients, etc.) that are characterized by shared, distributed and heterogeneous information sources with varieties of clinical and other settings. The challenge now faced with decision making, and management of care is to operate effectively in order to meet the information needs of healthcare personnel. Currently, researchers, developers, and systems engineers are working toward achieving better efficiency and quality of service in various sectors of healthcare, such as hospital management, patient care, and treatment. This paper presents a novel information brokering architecture that supports privacy-based information gathering in healthcare. Architecturally, the brokering is viewed as a layer of services where a brokering service is modeled as an agent with a specific architecture and interaction protocol that are appropriate to serve various requests. Within the context of brokering, we model privacy in terms of the entities ability to hide or reveal information related to its identities, requests, and/or capabilities. A prototype of the proposed architecture has been implemented to support information-gathering capabilities in healthcare environments using FIPA-complaint platform JADE.

Courseware Development with Animated Pedagogical Agents in Learning System to Improve Learning Motivation

ERIC Educational Resources Information Center

Chin, Kai-Yi; Hong, Zeng-Wei; Huang, Yueh-Min; Shen, Wei-Wei; Lin, Jim-Min

2016-01-01

The addition of animated pedagogical agents (APAs) in computer-assisted learning (CAL) systems could successfully enhance students' learning motivation and engagement in learning activities. Conventionally, the APA incorporated multimedia materials are constructed through the cooperation of teachers and software programmers. However, the thinking…

An exploratory analysis of personality, attitudes, and study skills on the learning curve within a team-based learning environment.

PubMed

Persky, Adam M; Henry, Teague; Campbell, Ashley

2015-03-25

To examine factors that determine the interindividual variability of learning within a team-based learning environment. Students in a pharmacokinetics course were given 4 interim, low-stakes cumulative assessments throughout the semester and a cumulative final examination. Students' Myers-Briggs personality type was assessed, as well as their study skills, motivations, and attitudes towards team-learning. A latent curve model (LCM) was applied and various covariates were assessed to improve the regression model. A quadratic LCM was applied for the first 4 assessments to predict final examination performance. None of the covariates examined significantly impacted the regression model fit except metacognitive self-regulation, which explained some of the variability in the rate of learning. There were some correlations between personality type and attitudes towards team learning, with introverts having a lower opinion of team-learning than extroverts. The LCM could readily describe the learning curve. Extroverted and introverted personality types had the same learning performance even though preference for team-learning was lower in introverts. Other personality traits, study skills, or practice did not significantly contribute to the learning variability in this course.

Designing E-Learning Environments for Flexible Activity and Instruction

ERIC Educational Resources Information Center

Wilson, Brent G.

2004-01-01

The contributions to this issue share a focus on design of e-learning environments. Instructional designers stand at very early stages of knowledge in this area, but with great potential for growth and progress. This commentary offers an activity-based perspective on e-learning environments, resulting in a flexible stance toward instructional…

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.

Utilizing Formative Assessments to Guide Student Learning in an Interactive Physics Learning Environment

ERIC Educational Resources Information Center

Lee, Young-Jin

2011-01-01

In the last decades, many education researchers have been trying to use computerized learning environments to enhance student learning. Without proper instructional supports and guidance, however, students often failed to acquire knowledge from computer-based learning activities. The objective of this study was to demonstrate how research-based…

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

NASA Astrophysics Data System (ADS)

Pedrazzoli, Attilio

2010-06-01

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

Effects of WOE Presentation Types Used in Pre-Training on the Cognitive Load and Comprehension of Content in Animation-Based Learning Environments

ERIC Educational Resources Information Center

Jung, Jung,; Kim, Dongsik; Na, Chungsoo

2016-01-01

This study investigated the effectiveness of various types of worked-out examples used in pre-training to optimize the cognitive load and enhance learners' comprehension of the content in an animation-based learning environment. An animation-based learning environment was developed specifically for this study. The participants were divided into…

Scaffolding in Connectivist Mobile Learning Environment

ERIC Educational Resources Information Center

Ozan, Ozlem

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

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

Learning to soar in turbulent environments

PubMed Central

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

2016-01-01

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

Learning to soar in turbulent environments.

PubMed

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

2016-08-16

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

The Learning Environment Counts: Longitudinal Qualitative Analysis of Study Strategies Adopted by First-Year Medical Students in a Competency-Based Educational Program.

PubMed

Bierer, S Beth; Dannefer, Elaine F

2016-11-01

The move toward competency-based education will require medical schools and postgraduate training programs to restructure learning environments to motivate trainees to take personal ownership for learning. This qualitative study explores how medical students select and implement study strategies while enrolled in a unique, nontraditional program that emphasizes reflection on performance and competence rather than relying on high-stakes examinations or grades to motivate students to learn and excel. Fourteen first-year medical students volunteered to participate in three, 45-minute interviews (42 overall) scheduled three months apart during 2013-2014. Two medical educators used structured interview guides to solicit students' previous assessment experiences, preferred learning strategies, and performance monitoring processes. Interviews were digitally recorded and transcribed verbatim. Participants confirmed accuracy of transcripts. Researchers independently read transcripts and met regularly to discuss transcripts and judge when themes achieved saturation. Medical students can adopt an assessment for learning mind-set with faculty guidance and implement appropriate study strategies for mastery-learning demands. Though students developed new strategies at different rates during the year, they all eventually identified study and performance monitoring strategies to meet learning needs. Students who had diverse learning experiences in college embraced mastery-based study strategies sooner than peers after recognizing that the learning environment did not reward performance-based strategies. Medical students can take ownership for their learning and implement specific strategies to regulate behavior when learning environments contain building blocks emphasized in self-determination theory. Findings should generalize to educational programs seeking strategies to design learning environments that promote self-regulated learning.

WebIntera-Classroom: An Interaction-Aware Virtual Learning Environment for Augmenting Learning Interactions

ERIC Educational Resources Information Center

Chen, Jingjing; Xu, Jianliang; Tang, Tao; Chen, Rongchao

2017-01-01

Interaction is critical for successful teaching and learning in a virtual learning environment (VLE). This paper presents a web-based interaction-aware VLE--WebIntera-classroom--which aims to augment learning interactions by increasing the learner-to-content and learner-to-instructor interactions. We design a ubiquitous interactive interface that…

The Ontologies of Complexity and Learning about Complex Systems

ERIC Educational Resources Information Center

Jacobson, Michael J.; Kapur, Manu; So, Hyo-Jeong; Lee, June

2011-01-01

This paper discusses a study of students learning core conceptual perspectives from recent scientific research on complexity using a hypermedia learning environment in which different types of scaffolding were provided. Three comparison groups used a hypermedia system with agent-based models and scaffolds for problem-based learning activities that…

An Evaluation-Driven Design Approach to Develop Learning Environments Based on Full-Body Interaction

ERIC Educational Resources Information Center

Malinverni, Laura; Schaper, Marie-Monique; Pares, Narcís

2016-01-01

The development of learning environments based on full-body interaction has become an increasingly important field of research in recent years. However, the design and evaluation strategies currently used present some significant limitations. Two major shortcomings are: the inadequate involvement of children in the design process and a lack of…

Blending problem-based learning with Web technology positively impacts student learning outcomes in acid-base physiology.

PubMed

Taradi, Suncana Kukolja; Taradi, Milan; Radic, Kresimir; Pokrajac, Niksa

2005-03-01

World Wide Web (Web)-based learning (WBL), problem-based learning (PBL), and collaborative learning are at present the most powerful educational options in higher education. A blended (hybrid) course combines traditional face-to-face and WBL approaches in an educational environment that is nonspecific as to time and place. To provide educational services for an undergraduate second-year elective course in acid-base physiology, a rich, student-centered educational Web-environment designed to support PBL was created by using Web Course Tools courseware. The course is designed to require students to work in small collaborative groups using problem solving activities to develop topic understanding. The aim of the study was to identify the impact of the blended WBL-PBL-collaborative learning environment on student learning outcomes. Student test scores and satisfaction survey results from a blended WBL-PBL-based test group (n = 37) were compared with a control group whose instructional opportunities were from a traditional in-class PBL model (n = 84). WBL students scored significantly (t = 3.3952; P = 0.0009) better on the final acid-base physiology examination and expressed a positive attitude to the new learning environment in the satisfaction survey. Expressed in terms of a difference effect, the mean of the treated group (WBL) is at the 76th percentile of the untreated (face-to-face) group, which stands for a "medium" effect size. Thus student progress in the blended WBL-PBL collaborative environment was positively affected by the use of technology.