Demographic characteristics (gender, age, race, major) showed no significant association with lower digital distraction in the rule-mining profiles¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r1–r2 · q2
Currency · newest study 2025 · checked against its sources 2026-10-20 (automated, 2 of 2 entries) · not reviewed by a person

Subclaims¶

q2 i? No significant ARM rules included student demographic characteristics or majors, and a t-test found no significant gender difference in digital distraction. → Shi 2025 q2 i? An independent samples t-test indicated no significant difference in digital distraction between male and female students (t = 0.86, p = .39). → Shi 2025 (2)

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 · r1

ARM on the 530-student survey: demographics did not appear in significant rules under the stated thresholds, so "demographics did not play a role in the behavioral profiles that characterize lower distraction". The same held in the two-antecedent step.

"We found no significant rules that included student demographic characteristics (i.e., gender, age, race) and majors, which filtered out demographics as meaningful predictors because they did not co-occur with lower distraction patterns under our significant rule extraction thresholds (support > .20 and confidence > .50)."

Shi 2025 (2)¶

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

Independent samples t-test comparing digital distraction between male and female participants in the full sample of 530; the test was not significant (t = 0.86, p = .39). Equivalence was not tested; the result addresses possible gender-imbalance bias.

"an independent samples t-test indicated that no significant difference in digital distraction between male and female students (t = 0.86, p = .39), suggesting that gender imbalance in the sample is unlikely to bias the findings"

Discussion¶

Related Claims¶

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