Mining relations between personality traits and learning styles

Current teaching methods gradually use technology-assisted tools such as online assessment, online teaching, and e-books. Digital learning methods give students more flexibility in learning without the limitations of time and location. Aside from using technology, the timely adjustment of teaching methods to match students’ learning styles may achieve better learning effectiveness. However, previous studies about digital learning either lacked factors related to students’ personality traits or were biased by using scores on homework or exams to make predictions of students’ learning effectiveness. Therefore, this study analyzes the correlation between learning effectiveness and learning characteristics, including personality traits, behavioral styles, and learning strategies of students using association rule mining and sequential pattern mining. The results can be used to identify key factors that affect students’ learning styles to determine students in need and provide a teaching reference for instructors to assist students in achieving better learning results.