Educating College Students on Academic Integrity: What Roles do Teachers Play in the Quebec Province?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Over the past 15 years, there has been a shift from detecting and sanctioning academic misconduct to preventing and promoting desired academic practices (Ferguson et al., 2007). According to Gray and Jordan (2012), teachers represent an influential figure to enhance students’ understanding of academic standards. However, a study conducted by Löfström et al. (2014) reveals that educators do not share the same perspectives on how academic integrity should be taught and whose responsibility it is to teach it. Moreover, Peters et al. (2019) developed a conceptual framework illustrating seven roles adopted by educators when teaching academic integrity, with each end of the spectrum identified as acting as “Ambassador” to being completely “Detached” (p. 6). These two teams of scholars examined the teaching of academic integrity at the university level, but little is known about how this is taught at the college level. This is why we explored the situation in seven colleges[1] across the province of Quebec in Canada. During our communication, we will present results from semi-structured interviews with 17 college teachers. A discussion will follow on winning strategies utilized by college teachers for promoting academic integrity among the student population. Finally, we will recommend further avenues of exploration in the domain of teaching and learning at institutions of higher education to foster a culture of academic integrity. [1] In the Quebec province, colleges are called cégep (collège d’enseignement general et professionnel) to prepare students for university studies or provide them with technical skills to enter the labour market.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.012 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it