Path Recommendation Using Sequential Pattern Mining in Intelligent Tutoring System

Path recommendation plays an important role for learners to obtaining good action in e-learning environment. Without appropriate guiding service, learners might miss some resource and waste time. Therefore, how to provide visitors customized path becomes an important task for learners. To bridge the gap, this research uses sequential pattern mining for intelligent touring system to generate personalized path for learners. Through this paper, we will focus on guidance learners to appropriate path. This paper suggests the use of web mining techniques to build an agent that could recommend on-line learning activities or shortcuts in a e-learning environment based on learners’ access history to improve course material navigation.