Peer-related help-seeking and learner-learner engagement strategies appear less often in profiles of students with lower digital distraction¶

Claim · All claims
Evidence · 1 study · associational r2 · q2
Currency · newest study 2025 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Students reporting fewer digital distractions reported less frequent peer-related help-seeking behaviors, such as sharing problems with classmates or seeking help from knowledgeable peers. → Shi 2025

Evidence¶

Shi 2025¶

Shi, H., Bi, R., Lin, X., & Dai, Y. (2025). Decreasing Digital Distraction in College Students: Associated Online Learning Strategies Identified by Unsupervised Data Mining Approaches. https://doi.org/10.17605/OSF.IO/P85S3

q2 · i? · associational · r2

ARM single-antecedent rules from the 530-student survey. Two help-seeking (HS) rules from the SRLQ showed negative association with distraction; e.g., disagreement with sharing problems with classmates online had phi = -0.129, odds ratio 0.590, chi-square p = .003 in Table 2.

"Interestingly, some rules (see HS rules in Table 2) revealed that students experiencing fewer distractions reported less frequent peer-related help-seeking behaviors, such as sharing problems with classmates or seeking help from knowledgeable peers."

Discussion¶

Related Claims¶

• Demographic characteristics (gender, age, race, major) showed no significant association with lower digital distraction in the rule-mining profiles — related
• Clustering of association rules yields four distinct strategy-combination profiles characterizing lower digital distraction — related
• Learner-instructor and learner-content engagement strategies are negatively associated with digital distraction in online courses — related
• In association-rule mining of survey data from 530 college students in online courses, goal setting, environment structuring and time management were the strategies most often associated with lower digital distraction — related
• Technical confidence using digital learning tools is positively associated with lower distraction levels among online learners — related
• Effort regulation negatively predicts, and general academic help seeking positively predicts, reported AI dependency; time management is non-significant — related
• The four profiles differ in academic self-efficacy, time/study management, and effort regulation, with HL highest, but not in help seeking — related
• Lower academic self-efficacy is associated with membership of three less engaged momentary-engagement profiles and lower peer support with two, while educational goals and family support do not differ across the four profiles tested — related