🧠 AI Ed Wiki

A scenario-based survey (Fall 2024) comparing how computing students at Canadian and South Korean universities judged the ethicality and policy compliance of AI-assisted coding practices. Despite functionally identical institutional policies, Canadian students were consistently and significantly more likely to rate GenAI use as unethical and against the rules (Mann-Whitney U tests across nearly all scenarios). Culture, not policy text, drove the perceived wrongness of identical behaviors.\n\nThe result complicates the wiki's Academic Integrity thread: policy harmonization does not produce perception harmonization, so multi-national or culturally diverse cohorts will interpret the same rules differently \u2014 an Equity concern for enforcement and grading. It extends Student Perception AI Use Collaboration and GenAI Impact Chinese Students Hss with direct cross-national comparison in computing education, and argues that GenAI Policies Higher Ed Computing need culturally aware communication, worked examples, and scenario-based clarification rather than abstract rule statements.

Connected Concepts

  • Plagiarism Detection
  • Administrator
  • Equity
  • Engagement Metrics
  • Academic Integrity
  • Math Education
  • Higher Ed
  • Prompt Engineering
  • Connected Articles

  • Student Perception AI Use Collaboration
  • GenAI Impact Chinese Students Hss
  • GenAI Policies Higher Ed Computing
  • A4l Analytics Pipeline
  • Aaai2026 Prompting Literacy K12
  • Academiclaw Student Agent Benchmark
  • Access Not Enough AI Tutoring 2026
  • Adapt Adaptive Lesson Plan Transformer
  • Adaptive Pretesting Retention
  • Adhd Video Segmentation Computing Education
  • Citation

    Harrington, B., Zlotnikova, I., Nadarajan, G., & Ekundayo, S. (2026). Did Alice Do Wrong? Cross-Cultural Differences in Student Perceptions of Generative AI Use in University Computing Education. arXiv:2607.19699. arXiv preprint (cs.CY).