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A Voting-Based Agent System for Course Selection in E-Learning

Record type: Conference or Workshop Item (Other)

Agent technology is a good approach for solving a number of problems concerned with personalized learning. In personal learning contexts individual students are given an environment that takes into account of their needs, interests and aspirations, and this is intended to lead to an enhanced learning experience. The aim of this paper is to show how agent systems can not only form a good framework for distributed e-learning systems, but also how they can be applied in personal learning contexts where the learners are autonomous and independent. We present an e-learning scenario where students try to register for their preferred courses but where courses will only run if enough students register. In this context, we introduce, for the first time, a prototype of an agent-based voting system in e-learning, where autonomous software agents vote on behalf of the students. We present a number of different voting strategies that student agents could use. Finally, through simulation we empirically investigate the resulting satisfaction of the students in the system.

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Citation

Aseere, Ali, Gerding, Enrico and Millard, David (2010) A Voting-Based Agent System for Course Selection in E-Learning At IEEE/WIC/ACM International Conference on Intelligent Agent Technology, Canada. 31 Aug - 03 Sep 2010. , pp. 303-310.

More information

Published date: 2010
Additional Information: Event Dates: 31 August-3 September
Venue - Dates: IEEE/WIC/ACM International Conference on Intelligent Agent Technology, Canada, 2010-08-31 - 2010-09-03
Organisations: Web & Internet Science, Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 271292
URI: http://eprints.soton.ac.uk/id/eprint/271292
ISBN: 978-0-7695-4191-4
PURE UUID: 1120c7b8-60bf-45e9-9fba-fe0530463a20
ORCID for David Millard: ORCID iD orcid.org/0000-0002-7512-2710

Catalogue record

Date deposited: 23 Jun 2010 10:32
Last modified: 18 Jul 2017 06:44

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Contributors

Author: Ali Aseere
Author: Enrico Gerding
Author: David Millard ORCID iD

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