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

本研究对智能辅导系统中基于学习者与系统低层次交互的附加功能——智能辅导功能的开发进行了基础研究。因此，从学习者的行为信息（鼠标操作日志数据、网络摄像头调查的姿势数据和眼动追踪数据）中推断学习者心理状态的方法出现了。此外，本文还提出了对学习者行为与心理状态的一般关系的本体描述，作为智能导师制的知识模型。

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.