A Human Collaborative Online Learning Environment Using Intelligent Agents

A Human Collaborative Online Learning Environment Using Intelligent Agents

Hilton José Silva de Azevedo (Parana Federal Center for Technological Education, Brazil) and Edson Emílio Scalabrin (Pontifical Catholic University of Parana, Brazil)
DOI: 10.4018/978-1-59140-500-9.ch001
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Abstract

This chapter introduces the design and implementation of a multiagent system based on a collaborative online learning environment (COLE). The purpose of developing such an environment is to improve social competences along with traditional content-related ones in lifelong learning. As educators would be unable to handle the huge amount of data concerning human interactions in such a learning environment, a multiagent system approach is adopted. The concept of human collaboration and the ways that project-based learning (PBL) and portfolios can be used to improve social competences are discussed based on the Social Theory of Learning. The way that the System Analysis for Agent Systems (SAAS) method was used to identify services and agents is presented. A general review of multiagent system architectures is presented to justify the choice of an open system. The basis and architecture of the COLE are explained. In order to facilitate the implementation of particular agents, a generic agent (GAg) and its functionalities are presented.

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Table of Contents
Acknowledgments
Fuhua Lin
Chapter 1
Hilton José Silva de Azevedo, Edson Emílio Scalabrin
This chapter introduces the design and implementation of a multiagent system based on a collaborative online learning environment (COLE). The... Sample PDF
A Human Collaborative Online Learning Environment Using Intelligent Agents
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Chapter 2
Weiqin Chen, Barbara Wasson
In the context of distributed collaborative learning, it is usually difficult for students to be aware of others’ activities and for instructors to... Sample PDF
Intelligent Agents Supporting Distributed Collaborative Learning
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Chapter 3
Larry Korba, George Yee, Yuefei Xu, Song Ronggong, Andrew S Patrick, Khalil El-Khatib
The objective of this chapter is to explore the challenges, issues, and solutions associated with satisfying requirements for privacy and trust in... Sample PDF
Privacy and Trust in Agent-Supported Distributed Learning
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Chapter 4
Chunsheng Yang
This chapter first addresses the issue of the importance of intelligence in MAS-based DLEs. Then, it stresses that there are three main intelligent... Sample PDF
Intelligence in MAS-Based Distributed Learning Environments
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Chapter 5
Ping Chen, Wei Ding
As the education field is becoming increasingly technology heavy, more educational systems involve line or interactive training and tutoring... Sample PDF
Knowledge Management for Agent-Based Tutoring Systems
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Chapter 6
Mohamed Ally
This chapter provides information on how to design intelligent tutoring systems for distributed learning to cater to individual learner needs and... Sample PDF
Intelligent Tutoring Systems for Distributed Learning
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Chapter 7
Fuhua Lin, Larbi Esmahi, Lawrence Poon
This chapter discusses an integrated approach to designing and developing adaptive distributed learning environments. It presents a distributed... Sample PDF
Integrating Tutoring Systems for Distributed Learning Environments
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Chapter 8
Larbi Esmahi, Fuhua Lin
This chapter describes a multiagent system for delivering adaptive e-learning. This chapter also provides a discussion of three issues related to... Sample PDF
A Multiagent Framework for an Adaptive E-Learning Systems
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Chapter 9
Hong Lin
In this chapter, we use the Chemical Reaction Metaphor (Banatre & Le Metayer, 1990, 1993, 1996) to model the interactions among program units... Sample PDF
A Language for Specifying Agent Systems in E-Learning Environments
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Chapter 10
Timothy K. Shih, Ying-Hong Wang, Yung-Hui Chen
Agent technology can be used to represent individuals participating in a virtual university. Avatars are virtual actors on behalf of students and... Sample PDF
A VR-Based Virtual Agent System
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