Animated Pedagogical Agent Based on Decision Tree for e-Learning

Authors:
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Venue:
ICALT '05 Proceedings of the Fifth IEEE International Conference on Advanced Learning Technologies
Year:
2005

Citing 2
Cited 1

Induction of Decision Trees

Machine Learning
Student Adaptivity in TILE: A Client-Server Approach

ICALT '01 Proceedings of the IEEE International Conference on Advanced Learning Technologies

Human---Computer input and output techniques: an analysis of current research and promising applications

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Abstract

This paper proposes a LMS (Learning Management System) with intelligent agent to provide effective adaptive messages to a learner. The unique features of this paper are shown as follows: The agent system proposed in this paper has a Learner Model, which is automatically and continually constructed by applying the decision tree model constructed from the learning histories data stored in the data-base. The constructed Leaner Model predicts a learnerýs future final status (1.Failed, 2. Abandon, 3. Successful, 4.Excellent) using his/her current learning history data. The constructed Leaner Model becomes more exact as the amount of data accumulated in the Data-Base increases .The agent system presents the optimal instructional message based on the learnerýs predicted future state. .. The agent provides some attention cues according to [1] at the timing when a learner begins to be bored with his/her learning. In addition, this paper demonstrates the effectiveness of this system through actual e-Learning classes.