Date
Publisher
arXiv
The rise of generative AI (GenAI) in higher education has prompted urgent debates surrounding academic integrity and ethical use. This study examines cross-cultural differences in student perceptions of GenAI use, comparing responses from students at Canadian and South Korean universities. Using a scenario-based survey administered in Fall 2024, we analyzed how students judged the ethicality and rule compliance of AI-assisted coding practices. Results reveal that Canadian students were consistently more likely to perceive the use of GenAI as both unethical and against institutional policies compared to Korean students, despite functionally identical institutional policies. Statistical analysis, including Mann-Whitney U tests and correlation coefficients, demonstrated significant differences across nearly all scenarios. Analysis of the factors used in generating scenarios indicated that the amount of AI-generated code incorporated into assignments most strongly influenced ethical judgments. Findings were interpreted through Hofstede's cultural dimensions framework, suggesting that cultural factors such as power distance, individualism, and uncertainty avoidance significantly shape students' ethical reasoning regarding GenAI. Our results contribute to the growing body of evidence emphasizing that equitable AI integration in education must be culturally responsive, taking into account diverse conceptions of academic integrity. We advocate for the development of nuanced AI-use guidelines that are sensitive to local cultural contexts while upholding fundamental principles of academic honesty. This study highlights the need for ongoing cross-cultural research to inform ethical AI policies and support responsible GenAI use in global higher education settings.
Study at a glance
- Question: How do Canadian and South Korean university students differ in judging the ethics and rules of generative AI use?
- Setting and data: University of Toronto Scarborough (Canada) and Sungkyunkwan University (South Korea), Fall 2024, 262 Canadian students and 48 South Korean students.
- Method: Scenario-based survey comparing responses across hypothetical vignettes using Mann-Whitney U tests and ANOVA.
Why it matters
The rise of generative AI has prompted urgent debates about academic integrity, but research on how students from different cultural backgrounds judge ethical use remains limited.
Key findings
- Canadian students were consistently more likely to view AI-assisted coding as unethical (mean 2.6 versus 1.78) and against institutional rules (mean 2.81 versus 1.80) than Korean students.
- The amount of AI-generated code incorporated into an assignment was the dominant factor influencing students' ethical judgments across both universities.
- Students' perceptions of whether an action was unethical were strongly correlated with whether they viewed it as violating institutional rules.
Summary drafted with AI from the full paper and may contain errors. See the full paper for details.
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