Exploring the Factors of Students’ Online Learning Based On Structural Equation Modeling

Abstract

Due to the COVID-19 pandemic, traditional teaching has been migrated online. Different from traditional face-to-face teaching, when students learn online, the online learning platform will generate various data. And these data make it possible for us to analyze students’ final academic performance. In this paper, we use structural equation modeling (SEM) to analyze the relationship between students’ learning factors. It is found that students’ lab scores (LS), exercise scores (LS) and participation in the discussion (PID) have a direct impact on their final programming scores (FPS). This paper also finds that students’ assignment submissions have an indirect influence on their final programming scores (FPS) but have a direct effect on lab scores (LS). In addition, students’ participation in the discussion (PID) has an indirect influence on assignment submissions (AS) and lab scores (LS). The research in this paper can provide instructional designers with references for instructional design.