Effectiveness of tutorials for promoting educational integrity: a synthesis paper
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
The prevalence of plagiarism, cheating, and other acts of academic dishonesty may be as high as 80% in populations of high school and post-secondary students. Various educational interventions have been developed and implemented in an effort to educate students about academic integrity and to prevent academic misconduct. We reviewed the peer-reviewed research literature describing face-to-face workshops, e-learning tutorials, or blended approaches for promoting academic integrity and the effectiveness of these approaches. In general, the educational interventions were described as effective in terms of satisfaction with the intervention, and changes in students’ attitudes and knowledge of academic integrity. Few studies provided evidence that the educational interventions changed student behaviour or outcomes outside the context of the intervention. Future research should explore how participation in educational interventions to promote academic integrity are linked to long-term student outcomes, such as graduate school admission, alumni career success, service to society, and personal stability.
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 | 0.010 | 0.037 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it