Student perceptions of academic misconduct amongst their peers during the rapid transition to remote instruction
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
Abstract The sudden move from traditional face-to-face teaching and learning to unfamiliar virtual spaces during the early weeks and months of the COVID-19 pandemic demanded many members of educational communities around the world to be flexible and teach and learn outside of their comfort zones. The abruptness of this transition contributed to instructors’ concerns about academic cheating as they could no longer assess learning and monitor student progress using their usual strategies and methods. Students also experienced disruptions to their usual ways of learning, which may have contributed to poor decision-making, including engagement in academic misconduct. The present study examined students’ beliefs about increased engagement in academic misconduct by their peers during the rapid obligatory transition to remote instruction due to the COVID-19 pandemic in March 2020. In January 2021, a retrospective online survey was distributed to students in undergraduate courses. We focused our analyses of the responses from students at a single university in Canada. We found that beliefs of increased cheating depended upon student gender (men vs women), status (domestic vs international), year of study (Years 1/2 vs Years 3 +), and discipline (Science, Technology, Engineering, and Mathematics vs Social Sciences and Humanities). These are important findings as they provide insight into the nature of the culture of academic integrity during a stressful and confusing period in postsecondary students’ lives.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it