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

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

Maomi Ueno
Copyright: © 2011 |Pages: 15
ISBN13: 9781609600402|ISBN10: 1609600401|EISBN13: 9781609600419
DOI: 10.4018/978-1-60960-040-2.ch017
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MLA

Ueno, Maomi. "Intelligent LMS with an Agent that Learns from Log Data in a Virtual Community." Handbook of Research on Methods and Techniques for Studying Virtual Communities: Paradigms and Phenomena, edited by Ben Kei Daniel, IGI Global, 2011, pp. 303-317. https://doi.org/10.4018/978-1-60960-040-2.ch017

APA

Ueno, M. (2011). Intelligent LMS with an Agent that Learns from Log Data in a Virtual Community. In B. Daniel (Ed.), Handbook of Research on Methods and Techniques for Studying Virtual Communities: Paradigms and Phenomena (pp. 303-317). IGI Global. https://doi.org/10.4018/978-1-60960-040-2.ch017

Chicago

Ueno, Maomi. "Intelligent LMS with an Agent that Learns from Log Data in a Virtual Community." In Handbook of Research on Methods and Techniques for Studying Virtual Communities: Paradigms and Phenomena, edited by Ben Kei Daniel, 303-317. Hershey, PA: IGI Global, 2011. https://doi.org/10.4018/978-1-60960-040-2.ch017

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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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