Analysis of Learning Behavior Based on MOOC Data

Abstract

With the continuous development of online teaching, it has become very common to combine MOOC teaching with traditional classes. This paper combines online learning data and offline test scores to study the correlation between students' online learning behavior and effect. The information obtained can help teachers adjust teaching strategies in a timely manner so that they can conduct more targeted teaching management for students. This paper introduces in detail the process of analyzing the data of two classes of students, which completes the cluster analysis and correlation analysis of the data of MOOC. According to the obtained indicators such as the graphs of clustering result and correlation coefficients, the value of the learning data is reflected by comprehensively analyzing the results. Finally, the paper puts forward specific suggestions for teaching practice from the perspective of learning dimensions and class characteristics.