Social desirability bias in relation to academic cheating behaviors of nursing students
Bibliographic record
Abstract
The purpose of this study was to explore the relationship between academic cheating and a series of academic and demographic characteristics, as well as the relationship between the various characteristics and social desirability bias. The population for the study was comprised of 626 nursing students (pre-nursing, baccalaureate students formally admitted into the program, and graduate students) attending a regional comprehensive university located in the Midwest. The results of the study revealed that 53.8% of undergraduate students and 36.5% of graduate students self-reported having engaged in at least one of the 16 forms of academic cheating during the previous semester, primarily in acts classified as plagiarism. The current study further explored misconduct among students seeking a BSN and found that 35.2% of students participated in at least one act of professional misconduct in the clinical setting. There were statistically significant differences between the characteristics of age and prevalence of plagiarism-related academic cheating, planned cheating, spontaneous cheating, and professional misconduct, implying that older students cheat less frequently. Likewise, the more credits a student completed the less likely they were to plagiarize or engage in spontaneous cheating. Additionally, older students and students having completed higher number of credits received higher scores on the social desirability scale, implying they had a higher tendency to display social desirability bias.
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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 | 0.012 | 0.019 |
| 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 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".