A Cultural and Global Perspective on Academic Integrity Policies and Misconduct Procedures, and their Impact on International Student Success
Bibliographic record
Abstract
Canada is a top destination for international students, attracting students from diverse cultures and academic backgrounds. However, international students often encounter challenges in adapting to Canadian academic integrity standards due to differing definitions of plagiarism, citation practices, and academic misconduct procedures in their home country. This study explores how native academic culture shapes one’s understanding of academic integrity and how this perspective influences academic success in first or second year of study in Canada. Through semi-structured interviews with sixteen international students and analyses of twelve academic integrity policies and misconduct procedures, this study examines the gap in institutional support, the effectiveness of current academic integrity education, and the impact of cultural differences in academic integrity standards and academic misconduct management. The findings suggest that many international students experience a steep learning curve in understanding and applying Canadian academic integrity standards, often due to lack of prior exposure. Additionally, academic integrity policies and misconduct procedures often neglect explicit consideration of international students and diverse academic backgrounds. This study concludes by providing recommendations for Ontario post-secondary institutions to enhance clarity, accessibility, and cultural inclusivity when revising academic integrity policies, misconduct procedures, and support services. By fostering a more inclusive approach that emphasizes educational equity, colleges and universities can equip international students for academic success while maintaining the quality of Canadian higher education. Keywords: Academic integrity, international students, academic misconduct, enculturation, acculturation, policy review, language acquisition, English language learners
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".