How Do Veterinary Students' Motivation and Study Practices Relate to Academic Success?
Bibliographic record
Abstract
The aim of the present study was to explore the factors associated with veterinary students' study success. All veterinary students who began their studies at the University of Helsinki in 2005 participated in this qualitative longitudinal study (N=52). The data consisted of assignments that the students completed at the beginning of their studies and again after three years of studying. The focus was on differences in motivation and study practices as well as possible changes in these over the three-year period. The students were divided into three groups according to their study success (grade point average and study progress). These groups were compared according to group-level differences in the categorized data. The most successful students already described themselves using more positive words than other students at the beginning of their veterinary studies. In addition, they seemed more adaptive in relation to the study's demands. However, there were drops in both the most and least successful students' motivation during their studies. The findings suggest that it is possible to predict forthcoming study problems by analyzing students' study practices and their own descriptions of themselves as learners. In addition, the results show that veterinary students' high motivation cannot be taken for granted. The comparative and longitudinal perspective of the present study can be useful in the development of curricula and in student support.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".