Motivators for student academic dishonesty at a medium sized university in Alberta, Canada: Faculty and student perspectives
Bibliographic record
Abstract
Academic misconduct describes a complex set of behaviours with many reported motivating factors. However, most research investigating the motivating factors behind academic misconduct has been conducted on American college students. To assess academic misconduct at our mid-sized university in Alberta, Canada, we conducted focus groups with students and faculty to further explore the motivational factors underlying academic misconduct. We conducted a thematic analysis on the interview responses in which two thematic categories of motivations arose: dispositional (or psychological) factors and situational (or contextual) factors. Both student and faculty participants reported a variety of motivating factors for academic misconduct, including but not limited to dispositional aspects, such as attitudes concerning academic misconduct or a lack of understanding, as well as contextual factors, such as taking a full course load and familial pressure. However, unlike their American counterparts, our participants did not discuss the impact that their peers have on motivating academic misconduct. We add our results to the growing body of research which focuses on identifying and analyzing Canadian trends in academic misconduct research.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.029 | 0.007 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".