Veterinary Student Attitudes toward Curriculum Integration at James Cook University
Bibliographic record
Abstract
The aim of this study was to investigate the attitudes of veterinary science students to activities designed to promote curriculum integration. Students (N = 33) in their second year of a five-year veterinary degree were surveyed in regard to their attitudes to activities that aimed to promote integration. Imaging, veterinary practice practicals, and a field trip to a cattle property were classified as the three most valuable learning activities that were designed to promote integration. Veterinary practice practicals, case studies, and palpable anatomy were regarded by students as helping them to learn information presented in other teaching sessions. They also appeared to enhance student motivation, and students indicated that the activities assisted them with their preparation for and performance at examinations. Attitudes to whether the learning exercises helped improve a range of skills and specific knowledge varied, with 39-88% of students agreeing that specific skills and knowledge were enhanced to a large or very large extent by the learning activities. The results indicate that learning activities designed to promote curriculum integration helped improve motivation, reinforced learning, created links between foundational knowledge and its application, and assisted with the development of skills that are related to what students will do in their future careers.
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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 | 0.002 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".