Design and Implementation of the Individualized Intelligent Teachable Agent.

The traditional ITS have considered the learners as a knowledge receiver. The recent development of teachable agent make it possible to provide the learner with an active role as a knowledge constructor and to take initiatives to persist in learning. In order to make an adaptive teachable agent that responds intelligently for individual learner, it should reflect the individual differences in the level of cognition and motivation, and its ongoing changes. For the purpose of developing individualized teachable agent, it is proposed to a student model based on the correlation among three dimensions: individual differences, learner responses, and learning outcome. A correlation analysis among the log data, questionnaire scores, and learning measurements was conducted. We delineated the relationships among three dimensions, learner responses (mouse-click pattern, duration & frequency at particular task, individual choice etc), individual characteristics (metacognitive awareness, self-efficacy, learning goal, and performance goal), and learning outcomes (interest and comprehension) during interacting with the teachable agent. The results suggest that certain type of learner responses or the combination of the responses would be useful indices to predict the learners' individual characteristics and ongoing learning outcome. [ABSTRACT FROM AUTHOR]