Study on Relationship between Online Learning Behaviors and Learning Effects Based on Data Mining

Abstract

With the development of online education, learning behavior analysis is important to evaluate the effect of online learning and provide feedback for teachers and students. Thus, we explored the relationship between online learning behaviors and learning effects from the perspective of blended learning. Research subjects include 62 college students who take the course, College English 3. The data is collected from the platform of the Chinese University MOOC. Data mining and statistical methods are used to analyze students’ online behaviors. The correlation between online behaviors and learning effects is analyzed to reveal the impact of online behaviors on learning effects. The results show that assignments, unit tests, and SPOC exams have a significant positive correlation with learning effects. There is no significant correlation between the number of posting and commenting with learning effects. The duration of video watching is negatively correlated with learning effects. Based on the results, it is proposed that the assessment of online courses is adjusted and platform functions need to be optimized in order to promote effective learning behaviors.