Curriculum Development in The Netherlands: Introduction of Tracks in the 2001 Curriculum of Utrecht University, The Netherlands
Bibliographic record
Abstract
The Faculty of Veterinary Medicine in Utrecht has recently introduced two major curriculum changes in order to keep pace with developments in research (the vast increase in scientific knowledge), in society (the quality awareness of veterinary clients), and in the veterinary profession, where a species and sector differentiation can be observed. After about 15 years during which the curriculum remained more or less unchanged, a radical curriculum revision was introduced in 1995. A further revision, with the introduction of separate study tracks, began in 2001. The 2001 curriculum focuses on academic and scientific training, active learning and problem solving, training in communication and professional behavior, and lifelong learning. It is divided into a four-year core curriculum, in which a broad, cross-species pathobiological insight is central, and a two-year track curriculum, through which students achieve a starting competence in a specific species or sector. The main teaching methods are tutorials and group tasks; practical work is used mainly to achieve specific veterinary skills. Teaching hours represent 30-35% of all study hours. Self-teaching is encouraged by providing study materials, self-teaching questions, teachers assigned to assist with self-teaching, and adequate facilities. The five tracks offered are Companion Animals/Equine; Food Animals; Veterinary Public Health; Veterinary Research; and Veterinary Administration and Management. All students follow a uniform 30-week clinical rotation program, while the track program is 42 weeks. A summary of admission procedures is given, as well as the times and procedures for track selection.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".