Canadian and Korean students did not differ significantly in overall opinions about GenAI's impact on academic integrity and learning quality, and academic progress did not affect scenario judgments¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r? · q2
Currency · newest study 2025 · not yet checked against its sources · not reviewed by a person · recheck by 2030: baselines and conditions change

Subclaims¶

q2 i? Mann–Whitney U tests showed no statistically significant difference between Canadian and Korean students on overall-opinion prompts about GenAI's negative impact on academic integrity or learning quality. → Brian Harrington 2025 q2 i? A two-way ANOVA found year of study was not a significant factor for either judgment outcome, with very little country-by-year interaction (p > 0.99 in both categories). → Brian Harrington 2025 (2)

Evidence¶

Brian Harrington 2025¶

Brian Harrington, Irina Zlotnikova, Gayathri Nadarajan, and Samuel Ekundayo. (2025). Did Alice Do Wrong? Cross-Cultural Differences in Student Perceptions of Generative AI Use in University Computing Education. ACM Trans. Comput. Educ. 26, 1, Article 15. https://doi.org/10.1145/3776558

q2 · i? · associational · r?

Bias-assessment items administered after the scenario prompts showed very similar distributions between groups; no statistically significant country difference on either overall-opinion prompt (effect sizes 0.0085 and 0.0301, p = 0.88 and 0.59612). Equivalence was not tested.

"As shown in Table4, Mann–Whitney U tests showed no statistically significant difference in responses between the groups for either prompt."

Brian Harrington 2025 (2)¶

Brian Harrington, Irina Zlotnikova, Gayathri Nadarajan, and Samuel Ekundayo. (2025). Did Alice Do Wrong? Cross-Cultural Differences in Student Perceptions of Generative AI Use in University Computing Education. ACM Trans. Comput. Educ. 26, 1, Article 15. https://doi.org/10.1145/3776558

q2 · i? · associational · r?

Two-way ANOVA with factors Country and Year of Study across the full dataset ruled out academic progress as an explanation for the cross-country differences; Korean students were mostly in third and fourth year while Canadian students were mostly in their first two years.

"AsshowninTable3,theacademicprogresswasnotasignificantfactorforeitherjudgmentoutcome (“Acted unethically” p = 0.4891 or “Against the rules” p = 0.4406), with very little interaction effect (p > 0.99 in both categories)."

Discussion¶

Related Claims¶

• The amount of AI-generated code in a submission was the dominant factor influencing students' ethical and rule-compliance judgments — related
• Canadian students were more likely than South Korean students to judge GenAI-assisted coding as against institutional rules, despite functionally identical policies — related
• Canadian students were more likely than South Korean students to judge GenAI-assisted coding scenarios as unethical — related
• Student voices on GenAI and academic integrity are diverse, shaped by gender, academic level, discipline, psychological factors, and cultural context, though gender findings are inconsistent — a broader claim this one bears on