A Pilot Study of a Physical Therapy Cadaveric Anatomy Course: Assessing the Impact of Examination Format on the Learning Environment
Bibliographic record
Abstract
Anatomy education continues to evolve in health professional programs as curricula shift to competency-based models and contact hours decrease. These changes in curricula may significantly alter the learning environment for students. Importantly, changes in learning environment have been shown to impact student learning strategies and well-being. It follows, then, that an investigation of students' perceptions of the learning environment is key to understand the impact of modern anatomy curriculum alterations. The current pilot study evaluated the impact of modifying examination format on the learning environment of physical therapy students participating in a human cadaveric anatomy course. Two study cohorts of first year (entry-level) physical therapy students were invited to complete a preliminary learning environment questionnaire with 13 visual analog scale items and four short answer items. One study cohort was tested with a viva (oral) practical examination, and the other, with a bell-ringer practical examination. Analysis of quantitative items revealed two significant findings: physical therapy students in the bell-ringer cohort found it was more difficult to prepare for their examination, and that they had inadequate time to respond to questions compared to the viva cohort. Analysis of qualitative items revealed distinct themes that concerned physical therapy student learning environment specific to cadaveric anatomy. These results demonstrate that examination format can influence the learning environment of physical therapy students studying cadaveric anatomy. As a result, care needs to be taken to ensure that modernized curricula align the examination format to the method of instruction and the future application of students' knowledge in clinical practice.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".