Validation of a Questionnaire to Assess the Impact of Simulator-Based Learning on Student Satisfaction and Self-Confidence in Bovine Reproductive Veterinary Education
Bibliographic record
Abstract
This study aimed to assess the psychometric properties of a questionnaire designed to evaluate veterinary students' satisfaction and self-confidence within the realm of high-fidelity clinical simulation for bovine reproductive diagnostic techniques. The reliability analysis revealed a robust Cronbach's alpha coefficient of .753 for the entire questionnaire, indicating a high level of internal consistency. A confirmatory factor analysis supported a bifactorial model, affirming appropriate factorial loadings for all items. The model's fit indices demonstrated strong alignment, suggesting the questionnaire's adeptness in accurately capturing students' experiences. The evaluation of satisfaction and self-confidence levels unveiled predominantly positive perceptions overall, albeit with discernible reservations, particularly regarding specific diagnostic techniques. Despite limitations, such as the utilization of a single-site sample, this study establishes the questionnaire's validity and reliability in the context of simulator-based learning. Thus, these preliminary results about students' confidence underscore the pivotal role of clinical simulation in bolstering students' skills.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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, 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".