Academic Cheating, Achievement Orientations, and Culture Values: A Meta-Analysis
Bibliographic record
Abstract
This preregistered meta-analysis investigated whether cultural values moderate the relations between students’ achievement orientations and their tendency to cheat. We identified 80 studies on the associations between performance/learning orientations and academic cheating in 27 countries with 40,867 participants. Performance orientation positively correlates with academic cheating ( r = .09, 95% CI = 0.04 to 0.13), and learning orientation negatively correlates with academic cheating ( r = −.16, 95% CI = −0.20 to –0.13). Univariate meta-analysis, hierarchical meta-regression, and meta-analytic structural equation modeling (MASEM) revealed that cultural values at the country level significantly moderate the relations between achievement orientations and cheating. These findings suggested that cultural values play a significant role in influencing the relations between achievement orientations and academic cheating, and, thus, cheating prevention programs must consider culture to achieve optimal effects. Based on these findings, we propose a new model that integrates cultural values into the existing model of academic cheating decision-making.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.031 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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 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".