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Building a Recommender Agent for e-Learning Systems

Published: 03 December 2002 Publication History

Abstract

A recommender system in an e-learning context is a software agent that tries to "intelligently" recommend actions to a learner based on the actions of previous learners. This recommendation could be an on-line activity such as doing an exercise, reading posted messages on a conferencing system, or running an on-line simulation, or could be simply a web resource. These recommendation systems have been tried in e-commerce to entice purchasing of goods, but haven't been tried in e-learning. This paper suggests the use of web mining techniques to build such an agent that could recommend on-line learning activities or shortcuts in a course web site based on learners' access history to improve course material navigation as well as assist the online learning process. These techniques are considered integrated web mining as opposed to off-line web mining used by expert users to discover online access patterns.

Cited By

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  • (2018)Educational Data Mining and Recommender Systems SurveyInternational Journal of Web Portals10.4018/IJWP.201801010410:1(39-53)Online publication date: 1-Jan-2018
  • (2018)A Framework for Recommender System to Support Personalization in an E-Learning SystemInternational Journal of Web-Based Learning and Teaching Technologies10.4018/IJWLTT.201807010413:3(51-68)Online publication date: 1-Jul-2018
  • (2018)Career Goal-based E-Learning Recommendation Using Enhanced Collaborative Filtering and PrefixSpanInternational Journal of Mobile and Blended Learning10.4018/IJMBL.201807010310:3(23-37)Online publication date: 1-Jul-2018
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cover image Guide Proceedings
ICCE '02: Proceedings of the International Conference on Computers in Education
December 2002
ISBN:0769515096

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IEEE Computer Society

United States

Publication History

Published: 03 December 2002

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Cited By

View all
  • (2018)Educational Data Mining and Recommender Systems SurveyInternational Journal of Web Portals10.4018/IJWP.201801010410:1(39-53)Online publication date: 1-Jan-2018
  • (2018)A Framework for Recommender System to Support Personalization in an E-Learning SystemInternational Journal of Web-Based Learning and Teaching Technologies10.4018/IJWLTT.201807010413:3(51-68)Online publication date: 1-Jul-2018
  • (2018)Career Goal-based E-Learning Recommendation Using Enhanced Collaborative Filtering and PrefixSpanInternational Journal of Mobile and Blended Learning10.4018/IJMBL.201807010310:3(23-37)Online publication date: 1-Jul-2018
  • (2017)Dynamic Grover searchQuantum Information Processing10.1007/s11128-017-1600-416:6(1-21)Online publication date: 1-Jun-2017
  • (2016)A Collaborative Location Based Travel Recommendation System through Enhanced Rating Prediction for the Group of UsersComputational Intelligence and Neuroscience10.1155/2016/12913582016(7)Online publication date: 1-Mar-2016
  • (2016)An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge BasesProceedings of the 12th International Symposium on Open Collaboration10.1145/2957792.2957804(1-8)Online publication date: 17-Aug-2016
  • (2016)The Use of Predictive Models in Intelligent Recommendation SystemsProcedia Computer Science10.1016/j.procs.2016.09.436102:C(515-519)Online publication date: 1-Dec-2016
  • (2016)An ACO-based personalized learning technique in support of people with acquired brain injuryApplied Soft Computing10.1016/j.asoc.2016.04.03947:C(316-331)Online publication date: 1-Oct-2016
  • (2015)Practical guidelines for designing and evaluating educationally oriented recommendationsComputers & Education10.1016/j.compedu.2014.10.00881:C(354-374)Online publication date: 1-Feb-2015
  • (2015)An evolutionary algorithm for the discovery of rare class association rules in learning management systemsApplied Intelligence10.1007/s10489-014-0603-442:3(501-513)Online publication date: 1-Apr-2015
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