Toward a fully automatic learner modeling based on web usage mining with respect to educational preferences and learning styles

Mohamed Koutheair Khribi, Mohamed Jemni, Olfa Nasraoui, Sabine Graf, Kinshuk

Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

11 Citations (Scopus)

Abstract

In this paper, we describe a fully automatic learner modeling approach in learning management systems, taking into account learners' educational preferences including learning styles. We propose a learner model with three components: the learner's profile, learner's knowledge, and learner's educational preferences. The learner's profile represents the learner's general information such as identification data, the learner's knowledge implies the learner's interests on visited learning objects, and the learner's educational preferences are composed of the learner's preferences among visited learning objects and his/her learning style. In the proposed approach, all learner model components are automatically detected, without requiring explicit feedback. Indeed, all the basic learners' information is inferred from the learners' online activities and usage data, based on web usage mining techniques and a literature-based approach for the automatic detection of learning styles in learning management systems. Once learner models are built, we apply a hierarchical multi-level model based collaborative filtering approach, in order to gather learners with similar preferences and interests in the same groups.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE 13th International Conference on Advanced Learning Technologies, ICALT 2013
Pages403-407
Number of pages5
DOIs
Publication statusPublished - 2013
Event2013 IEEE 13th International Conference on Advanced Learning Technologies, ICALT 2013 - Beijing, China
Duration: 15 Jul. 201318 Jul. 2013

Publication series

NameProceedings - 2013 IEEE 13th International Conference on Advanced Learning Technologies, ICALT 2013

Conference

Conference2013 IEEE 13th International Conference on Advanced Learning Technologies, ICALT 2013
Country/TerritoryChina
CityBeijing
Period15/07/1318/07/13

Keywords

  • Collaborative Filtering
  • Learner Modeling
  • Learning Styles
  • Recommender Systems
  • Web Mining

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