Uncovering Online Learning Strategies to Reduce Digital Distraction in College Students Through Association Rules Mining

• In Event: Persistence in Online Learning Environments

Abstract

Digital distraction, characterized by diverting attention from learning tasks to off-task digital activities, poses significant challenges in online education, especially for college students. This study utilized association rule mining to identify patterns of online learning strategies that reduce digital distraction among 530 college students from a public university in southeastern America. Key findings revealed that robust self-regulated learning strategies, including goal setting, environment structuring, and time management, were significantly associated with lower digital distraction. Conversely, high learner-to-learner engagement was linked to higher distraction levels. The study suggests incorporating structured self-regulated learning activities and fostering meaningful instructor-student interactions to mitigate digital distractions in online courses. These insights offer practical implications for enhancing student focus and engagement in online learning environments.

Authors

• Hui Shi, Florida State University

• Ran Bi, SAS Institute Inc.