Analysing Students’ Learning Behaviours in E-learning embedded with Learning Analytics Intervention based on Learning Style: A Case Study

As online learning is developing with the arrival of the big data era, this has reformed the educational field from face-to-face classrooms to online learning and has resulted in the emergence of learning analytics. In this regard, a massive volume of data generated by students when they interact with online learning (e.g., number of logins, views, posts, etc.) becomes more available, and this data can be tracked and used to understand the learning behaviour of students. In other words, students’ online learning behaviours via log files in Learning Management Systems can be analysed to gain insight into what has been done by students in online learning through learning analytics. However, to date, there have only been a few studies investigating learning behaviour data of students with different learning styles through learning analytics in an e-learning environment. Due to the limited research, this study aims to fill in this gap by exploring the online learning behaviours of students based on learning styles in e-learning embedded with learning analytics intervention and the relationship between the number of log-ins, viewing activities, interactions in the discussion forum, and students’ academic performance. A quantitative research design was employed using different instruments such as students’ server log files and academic performance tests. The findings showed that students with different learning styles behaved differently in an e-learning environment. In addition, this study also discovered that there was a weak, negative correlation between the number of views and academic performance, which was statistically significant. The findings of this study can be a good reference for instructors who can use this information for the redesign of courses in e-learning.