Student and faculty perceptions of, and experiences with, academic dishonesty at a medium-sized Canadian university
Bibliographic record
Abstract
Abstract There is a paucity of research into the prevalence of academic dishonesty within Canada compared to other countries. Recently, there has been a call for a better understanding of the particular characteristics of educational integrity in Canada so that Canada can more meaningfully contribute to current discussions surrounding academic integrity. Here, we present findings from student (N = 1142) and faculty (N = 130) surveys conducted within a medium-sized (~ 8700 students) Canadian university. These surveys probed perceptions towards, and experiences with, academic dishonesty, in which we aimed to understand how students and faculty regarded academically dishonest practices during their postsecondary careers. We also aimed to understand how often students engaged in, and faculty had witnessed, academic dishonesty, whether or not witnessing incidents of academic dishonesty corresponded with gender, year of experience, highest level of educational attainment, discipline, or their personal perceptions towards the importance of academic honesty, and whether students had been adequately taught what constitutes academic dishonesty. We found that an overwhelming majority of students viewed academic honesty as important, and that most students reported not engaging in academic dishonesty themselves despite 45.8% reporting that they had witnessed others engage in academic dishonesty. We also found that students were more likely to witness cheating as their postsecondary experience increased, that witnessing varied across disciplines and educational attainment, and that witnessing varied with student perceptions. However, we found no such patterns in faculty responses, but found that faculty are split on whether or not they believe incidents of academic honesty are increasing.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.005 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".