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A Human Collaborative Online Learning Environment Using Intelligent Agents

A Human Collaborative Online Learning Environment Using Intelligent Agents

Hilton José Silva de Azevedo, Edson Emílio Scalabrin
ISBN13: 9781591405009|ISBN10: 1591405009|ISBN13 Softcover: 9781591405016|EISBN13: 9781591405023
DOI: 10.4018/978-1-59140-500-9.ch001
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MLA

Silva de Azevedo, Hilton José, and Edson Emílio Scalabrin. "A Human Collaborative Online Learning Environment Using Intelligent Agents." Designing Distributed Learning Environments with Intelligent Software Agents, edited by Fuhua Lin, IGI Global, 2005, pp. 1-32. https://doi.org/10.4018/978-1-59140-500-9.ch001

APA

Silva de Azevedo, H. J. & Scalabrin, E. E. (2005). A Human Collaborative Online Learning Environment Using Intelligent Agents. In F. Lin (Ed.), Designing Distributed Learning Environments with Intelligent Software Agents (pp. 1-32). IGI Global. https://doi.org/10.4018/978-1-59140-500-9.ch001

Chicago

Silva de Azevedo, Hilton José, and Edson Emílio Scalabrin. "A Human Collaborative Online Learning Environment Using Intelligent Agents." In Designing Distributed Learning Environments with Intelligent Software Agents, edited by Fuhua Lin, 1-32. Hershey, PA: IGI Global, 2005. https://doi.org/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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