Goal-Driven Navigation for Learning Activities Based on Process Optimization

This paper describes an integrated approach to provide an optimized learning process to students by analyzing the log data of learning activities and extracting their learning patterns. Our analysis results show that most of students almost always use their main learning patterns in their learning activities, and the learning achievement is affected by the learning process. Based on these findings, we try to optimize the process of earning actions using the extracted learning patterns, infer the learning goal of students, and then navigate them a personalized learning process according to the similarity of the extracted learning patterns.