Validation of a Psychometric Instrument to Assess Motivation in Veterinary Bachelor Students
Bibliographic record
Abstract
There are indications that motivation correlates with better performance for those studying veterinary medicine. To assess objectively whether motivation profiles influence both veterinary students' attitudes towards educational interventions and their academic success and whether changes in curriculum can affect students' motivation, there is need for an instrument that can provide a valid measurement of the strength of motivation for the study of veterinary medicine. Our objectives were to design and validate a questionnaire that can be used as a psychometric scale to capture the motivation profiles of veterinary students. Question items were obtained from semi-structured interviews with students and from a review of the relevant literature. Each item was scored on a 5-point scale. The preliminary instrument was trialed on a cohort of 450 students. Responses were subjected to reliability and principal component analysis. A 14-item scale was designed, within which two factors explained 53.4% of the variance among the items. The scale had good face, content, and construct validities as well as a good internal consistency (Cronbach's alpha=.88).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.034 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".