Discovery of action patterns in task-oriented learning processes

Xiaokang Zhou, Jian Chen, Qun Jin

Research output: Contribution to journalConference articlepeer-review

4 Citations (Scopus)


In this study, in order to support and facilitate the web-based learning, we concentrate on user learning behavior pattern discovery in a task-oriented learning process. Based on a hierarchical graph model which can describe relations among learning actions, learning activities, learning sub-tasks and learning tasks, we introduce the formal definitions for Learning Action Pattern and Goal-driven Learning Group to discover and represent users' learning behavior patterns within a learning task process. Two integrated algorithms are developed to calculate and generate the Learning Action Patterns for an individual user and the Goal-driven Learning Groups for a number of users, which can benefit sharing of learning activities and improve learning efficiency in e-learning environments. Finally, the design of a prototype system with experiment results is discussed.

Original languageEnglish
Pages (from-to)121-130
Number of pages10
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8167 LNCS
Publication statusPublished - 2013 Oct 23
Event12th International Conference on Web-based Learning, ICWL 2013 - Kenting, Taiwan, Province of China
Duration: 2013 Oct 62013 Oct 9


  • Learning Activity
  • Learning Pattern
  • Learning Task
  • User Behavior Modeling

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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