Academic Misconduct: An Investigation into Male Students’ Perceptions, Experiences & Attitudes towards Cheating and Plagiarism in a Middle Eastern University Context
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
Academic misconduct in many educational institutions in the Middle East is an inherent problem. This has been particularly true amongst the university student population. The proliferation of the Internet and the ownership of mobile and electronic devices, have, in part, witnessed rates of cheating, plagiarism and academic misconduct cases steadily increase across higher education contexts. Though the growth of the Internet as an information source and gateway to knowledge has increased substantially in recent years, it has, however, opened up a plethora of varying forms and rates of academic dishonesty. This study was conducted through an online Likert scale questionnaire. Its purpose was to investigate first year male undergraduate students’ attitudes, experiences and perceptions towards plagiarism and cheating in a university located in Saudi Arabia. The study aimed at addressing themes in relation to the meaning, forms, source, frequency and reasons of cheating and plagiarism. The study indicates that cheating and plagiarism is common among students, while a need to address student awareness and clarify student expectations towards academic integrity was also identified. The study also proposes several recommendations to alleviate the levels of academic misconduct, be it cheating in exams or plagiarising content, in the Saudi university context.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Research integrity Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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