Investigating Teachers and Students’ Perceptions of Academic Plagiarism at the University Level
Bibliographic record
Abstract
Plagiarism is a prevalent issue in academic settings that demoralises the integrity of learning and assessment processes. This study aimed to explore students’ perceptions towards plagiarism, their level of plagiarism awareness, the causes of plagiarism, and potential strategies to tackle this issue. Data was collected through surveys and interviews with both students (N = 267) and teachers (N = 4) at a university. The findings indicated that while students acknowledged plagiarism as unethical and detrimental to their learning progress, many lacked a clear understanding of what plagiarism involves. Students’ level of plagiarism awareness did not necessarily develop as they progressed in their academic studies. The causes of plagiarism identified in the study included easy accessibility to online resources, a lack of research writing skills, cultural influences, and perceived time constraints. Teachers emphasized the importance of technical writing training, providing constructive feedback, and intensifying penalties as strategies to combat plagiarism. The study underscores the critical need for comprehensive educational interventions that enhance academic writing skills, promote time management and stress management, provide constructive feedback, and enforce clear plagiarism policies. Therefore, educational institutions should consider implementing a multifaceted approach, encompassing academic writing skill development to efficiently address plagiarism and promote academic integrity among students. Further research should involve policymakers and explore the effectiveness of interventions in reducing plagiarism rates.
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.
How this classification was reachedexpand
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 | Research integrity Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | MetaresearchResearch integrity Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
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 | 0.001 | 0.002 |
| 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 | 0.000 |
| 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 itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".