International undergraduate students’ perspectives on academic integrity: a phenomenological approach
Bibliographic record
Abstract
Anecdotal evidence suggests that international undergraduate students are engaging in academically dishonest behavior on an increasing basis (Marcus, 2011; McGowan & Lightbody, 2008). In other words, they are found to occupy more time and resources than domestic students in the promotion of academic integrity and in administering punishments for academic dishonesty. This study explores international undergraduate student perspectives on issues related to academic integrity at a large, Western-Canadian university. Hofstede’s (1980) six cultural dimensions are used to learn to what extent, if any, culture and academic integrity are intertwined. Participants of the study were international undergraduate students in various faculties, years of study, and from various countries of origin: Azerbaijan, China, Hong Kong, India, Malta, Pakistan, South Korea, and United States of America. The findings of this study indicate that international undergraduate students have the impression that their group is more susceptible to engaging in academic dishonesty. Conversely, international undergraduate students are also found to possess a more advanced understanding of moral behavior, although they are sometimes unable to translate this fully to their academic lives. Implications for practice include: shifting to a taxonomy that frames positive or desired behaviors as opposed to the negative, sharing the burden of dealing with academic dishonesty, and better supporting faculty in relaying the message of academic integrity at the university using a bottom up approach.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.016 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".