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Record W4404326436 · doi:10.3102/00346543241288240

Academic Cheating, Achievement Orientations, and Culture Values: A Meta-Analysis

2024· article· en· W4404326436 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReview of Educational Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicAcademic integrity and plagiarism
Canadian institutionsUniversity of Toronto
FundersMinistry of Education
KeywordsCheatingPsychologyAcademic achievementMathematics educationMeta-analysisSocial psychology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.746
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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.

Opus teacher head0.267
GPT teacher head0.562
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it