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.

I. Introduction

There are two Chinese idioms usually used to describe the relation of learning process and learning result. One is “getting twice the result with half the effort,” and the other is “getting half the result with twice the effort.” What lead to these results? Many studies indicate that different learning process led to different results in students' learning activities [1] [2] [3]. Since a different learning process can lead to a different result, if the learning process of students can be regulated and navigated with a suitable principle, more efficient and better results can be expected.