Evaluation of Student Attitudes to Cooperative Learning in Undergraduate Veterinary Medicine
Bibliographic record
Abstract
RATIONALE FOR THE STUDY: Recent studies have demonstrated that collaborative or cooperative learning (CL) provides students and teachers with a variety of advantages over traditional instructional methods. To explore the possibility of introducing CL into the veterinary undergraduate curriculum on a larger scale-to facilitate the development of professional competencies-a cooperative learning assignment (CLA) was introduced into the fourth year Bachelor of Veterinary Medicine and Surgery (BVMS) degree course at the University of Glasgow. An evaluation was carried out as a basis for optimizing subsequent CL activities in the undergraduate course. METHODOLOGY: Evaluation of student attitudes to the CLA was conducted using pre- and post-task questionnaires and a focusgroup discussion involving student representatives from several of the small groups. Quantitative questionnaire data were imported into SPSS and a statistical test was used to identify any significant shifts in student attitudes. RESULTS AND CONCLUSIONS: Analysis of the quantitative questionnaire results indicates that students-who regarded themselves generally as team players rather than competing individuals-had few concerns before or after the CLA. There were some significant shifts (negative and positive) in response to some of the questions, but generally the results were encouraging. However, a number of issues emerged from the focus-group discussion with regards to the administration of CL and matching students' expectations to their experiences. In particular, students need to be adequately informed at the outset about the CL process and about how it will be assessed, have access to the required facilities, and be comfortable with learning different skills sets from those their peers are learning. Staff facilitators require adequate guidance on what they are expected to contribute to the CL process.
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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 | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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".