Technical and Non-Technical Programme Students’ Attitudes and Reasons for Plagiarism
Bibliographic record
Abstract
To date, plagiarism continues to be a widespread problem in higher education. Deemed to be endemic, researchers continue to examine various aspects of plagiarism, including students’ perception, practices, attitudes and reasons for plagiarism, in addressing this growing concern. Most studies, however, tend to examine these aspects independently. This paper reports on a study that examined both the students’ attitudes and reasons for plagiarism, particularly among the Technical and Non-Technical programme students. A questionnaire was administered to 120 students, i.e. 60 each from each programme to gather quantitative data on their attitudes and reasons for plagiarising. The study found that students in both groups hold negative attitudes towards plagiarism. They deem it synonymous to cheating in final examinations and advocate severe penalty to offenders who submit free downloaded or purchased articles. However, they disagree on being penalised for permitting their peers to plagiarise their work. Significant differences were found for the latter two attitudes between the groups. Albeit, disfavouring plagiarism, the two most cited reasons that compel students in both groups to plagiarise are their self-inadequacy in writing skills and poor time management, followed by the temptation and opportunity to plagiarise from the internet and to cope with the institutional load. With an understanding of these variables, all parties will be able to make more informed decisions in addressing this malpractice and upholding academic integrity.
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How this classification was reachedexpand
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".