Mentor Agent: An Intelligent Virtual Teacher for Personalized Learning Environments

A key issue in pedagogy is individualization, i.e., adapting the teaching to the needs of various learners. In many cases, however, current e-learning systems have so far focused most on porting existing courses with traditional teaching methods onto the web/virtual environments without any fine-tuning and adaptation to the learner needs, just making non-individualized teaching even more widely available. The intelligent agent technology has potential regarding the creation of more intelligent, personalized, adaptive and interactive e-learning applications, providing individualization and therefore enhancing the effects of learning. In this paper, an intelligent virtual teacher is presented to provide personalized content management, learner model, and adaptive instant interaction in virtual learning environment. Mentor provides information for the student, and rises to help whenever the student has lost the clues. The mind model of the mentor agent is proposed on top of the Dempster-Shafer Goal-Net architecture. User-awareness and context-awareness are both achieved by reasoning student activities and context evolvement. Proposed architecture is validated by applying on Singapore River City, an agent augmented virtual environment designed to engage and motivate students at the lower secondary level in Singapore. Extensive experiments illustrate the effectiveness of the proposed intelligent mentor where students have found the mentor agent as believable as a virtual teacher. Key-Words: Personalization, Agent augmented virtual environment, Goal-net agent modeling, Pedagogical Agent, Stock management, Dempster-Shafer Theory.