发表机构
University of Toronto Scarborough; Botswana International University of Science and Technology; Sungkyunkwan University; Open Polytechnic of New Zealand（多伦多大学士嘉堡分校; 博茨瓦纳国际科技大学; 成均馆大学; 新西兰开放理工学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究加拿大和韩国大学生对生成式人工智能使用认知的跨文化差异，通过基于场景的调查分析学生对其道德性和规则遵守的判断，发现文化因素影响学生道德推理，强调教育中人工智能整合需文化响应，要制定细致指南并持续跨文化研究。
AI 中文摘要
生成式人工智能在高等教育中的兴起引发了围绕学术诚信和道德使用的紧迫辩论。本研究考察了学生对生成式人工智能使用认知的跨文化差异，比较了加拿大和韩国大学学生的回答。通过在2024年秋季进行的基于场景的调查，分析学生如何判断人工智能辅助编码实践的道德性和规则遵守情况。结果显示，尽管机构政策功能相同，但加拿大学生比韩国学生更倾向于认为使用生成式人工智能不道德且违反机构政策。统计分析表明几乎所有场景都存在显著差异。纳入作业的人工智能生成代码量对道德判断影响最大。研究结果通过霍夫斯泰德文化维度框架进行解读，表明权力距离、个人主义和不确定性规避等文化因素显著影响学生对生成式人工智能的道德推理。我们的结果强调教育中公平的人工智能整合必须具有文化响应性，要考虑学术诚信的不同概念。我们主张制定对当地文化背景敏感同时坚持学术诚实基本原则的细致人工智能使用指南。本研究凸显了持续跨文化研究对为道德人工智能政策提供信息及支持全球高等教育中负责任的生成式人工智能使用的必要性。
英文摘要
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.
Journal refACM Transactions on Computing Education, Volume 26, Issue 1, Article No.: 15, 2025
DOI：10.1145/3776558
