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.

目前的教学方式逐渐使用在线测评、在线教学、电子书等技术辅助工具。数字化学习方法让学生在学习上更加灵活，不受时间和地点的限制。除了使用科技外，适时调整教学方法以配合学生的学习方式，可取得更好的学习效果。然而，以往关于数字学习的研究要么缺乏与学生个性特征相关的因素，要么存在偏见，因为使用作业或考试的分数来预测学生的学习效果。因此，本研究使用关联规则挖掘和序列模式挖掘分析学习效果与学习特征之间的相关性，包括学生的个性特征、行为风格和学习策略。