A Parallel Education Based Intelligent Tutoring Systems Framework

although online education has improved efficiency of learners' access to high-quality educational resources, real-time interaction between instructors and learners have not yet been achieved in online personalized learning. Intelligent Tutoring Systems (ITS) provides a feasible way to realize realtime personalized learning guidance and resource recommendations by applying AI to capture and analyze online learners' characteristics and behaviors. In this paper, reviews and trends of ITS are discussed and three challenges of ITS research & development are pointed out: learner model, guidance mechanism and human-computer interaction mechanism. In order to address these issues, parallel intelligence theory is introduced and a parallel intelligence education based ITS framework is proposed.