Fundamental Research of Intelligent Mentoring Function for Intelligent Tutoring System based on Low Level Interaction

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In this study we carried out fundamental research for development the intelligent mentoring function for intelligent tutoring systems as additional function based on Low Level Interaction between learners and systems. As a result, some inference methods of learners' mental states from information on learners' behavior i.e., log data of mouse operations, postures investigated via Web camera and eye tracking tracing data. Additionally, ontological description on general relationship between some log data on learners' behavior and their mental states are proposed as a knowledge model for the intelligent mentoring system.