Ontological descriptions for eye movement data and mental states in taking computer-based multiple-choice tests

Recently, the research in intelligent educational systems has much interest in exploring data from educational settings to understand learners behavior and mental states. To further understand learners based on such the data and sophisticate supportive interventions by educational systems, knowledge of relationships between learners' behavior and mental states must be shared. To propose a framework to share the knowledge, this study attempted ontological descriptions for learners' eye-movement and mental states in solving computer-based multiple-choice problems. The current study forms a technical basis for development of an IMS (Intelligent Mentoring System) in which an automatic mentoring function is implemented with ITS (Intelligent Tutoring System).