Learning activity sharing and individualized recommendation based on dynamical correlation discovery

Xiaokang Zhou*, Jian Chen, Qun Jin, Timothy K. Shih

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this study, we concentrate on learning activity sharing and individualized recommendation based on dynamical user correlations, in order to support and facilitate the web-based learning process integrated with social streams. A user correlation-based learning activity model is built to demonstrate the relations among user, learning task and learning activity. Based on these, an integrated method is proposed to provide a target user with the possible learning activity as the next learning step, which is expected to enhance the learning efficiency. Finally, design of a Moodle-based prototype system is discussed.

Original languageEnglish
Title of host publicationAdvances in Web-Based Learning, ICWL 2012 - 11th International Conference, Proceedings
Pages200-206
Number of pages7
DOIs
Publication statusPublished - 2012
Event11th International Conference on Advances in Web-Based Learning, ICWL 2012 - Sinaia, Romania
Duration: 2012 Sept 22012 Sept 4

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7558 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Advances in Web-Based Learning, ICWL 2012
Country/TerritoryRomania
CitySinaia
Period12/9/212/9/4

Keywords

  • Learning Activity
  • Learning Activity Sharing
  • Social Learning
  • Social Media
  • Social Stream

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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