Decreasing Digital Distraction in College Students: Associated Online Learning Strategies Identified by Unsupervised Data Mining Approaches

A research study utilizing unsupervised data mining techniques identified effective online learning strategies that correlate with reduced digital distraction among college students. The findings indicate that self-regulated learning strategies, including goal setting, environment structuring, and time management, are most consistently associated with lower levels of digital distraction. Additionally, engagement strategies with instructors and content also play a role.

Why it matters

Addressing digital distraction is crucial for optimizing learning outcomes in increasingly digitized educational and professional settings. Understanding and implementing effective self-regulated learning and engagement strategies can enhance productivity and knowledge acquisition across various domains.

Key insights

• Digital tools in education contribute to digital distractions, impacting academic performance, particularly in online learning environments.
• Unsupervised data mining (association rule mining and clustering analysis) was employed to identify distraction-reducing strategies.
• Data from 530 participants were analyzed.
• Self-regulated learning strategies (goal setting, environment structuring, time management) consistently co-occurred with lower digital distractions.
• Learner-instructor and learner-content engagement strategies were also identified as significant.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2609.04125