Intelligent LMS with an Agent that Learns from Log Data in a Virtual Community

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Author(s): Maomi Ueno (The University of Electro-Communications, Japan)
Copyright: 2011
Pages: 15
Source title: Handbook of Research on Methods and Techniques for Studying Virtual Communities: Paradigms and Phenomena
Source Author(s)/Editor(s): Ben Kei Daniel (University of Saskatchewan, Canada)
DOI: 10.4018/978-1-60960-040-2.ch017

Keywords: Information Science Reference / Media & Communications / Social Computing / Virtual Communities & Virtual Reality

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Abstract

This study describes an agent that acquires domain knowledge related to the content from a learning history log database in a learning community and automatically generates motivational messages for the learner. The unique features of this system are as follows: The agent builds a learner model automatically by applying the decision tree model. The agent predicts a learner’s final status (Failed; Abandon; Successful; or Excellent) using the learner model and his/her current learning history log data. The constructed learner model becomes more exact as the amount of data accumulated in the database increases. Furthermore, the agent compares a learner’s learning processes with “Excellent” status learners’ learning processes stored in the database, diagnoses the learner’s learning processes, and generates adaptive instructional messages for the learner. A comparison between a class of students that used the system and one that did not demonstrates the effectiveness of the system.

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Intelligent LMS with an Agent that Learns from Log Data in a Virtual Community

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