The Design of Web-learning Navigator Based on Artificial Psychology

Emphasizing particularly on emotional interactions, this paper proposes a WEB-based, personalized e-learning navigation design, which is composed of emotion modeling based on Artificial Psychology, Image Recognition, web log analysis and knowledge level evaluation based on cognitive psychology. In this paper, eye-sight track and student-computer interaction are presented. Eye-sight track aims at tracking on-line which contents on computer's screen are concentrated on by the learner. Through the interactions between test-pages and learners, their real-time learning interests as well as encountered difficulties in learning process can he identified. By adopting Artificial Psychology theories and knowledge level-structure evaluation method, each individual student's knowledge level and knowledge background are evaluated. Then bases on the information fusion with respect to the above attained information, an optimal learning plan or curriculum structure can be provided via the ultimate evaluation result, some constructive suggestions are provided as well. The design will greatly improve the learning efficiency of student and promote human-computer interaction.