Dyad pedagogy in practical anatomy: A description of the implementation and student perceptions of an adaptive approach to cadaveric teaching
Bibliographic record
Abstract
Prior to the challenges imposed by the Covid-19 pandemic, anatomy practical sessions at Trinity College Dublin involved eight to 10 students per donor station, rotating between digital learning, anatomical models/osteology, and dissection activities for three hours weekly. To maintain cadaveric participation in the anatomy laboratory while adhering to distancing guidelines, a transition to dyad pedagogy was implemented. This mode of delivery allowed two students per donor station to spend one hour per week in the anatomy laboratory with all digital learning elements transferred to the virtual learning platform Blackboard as pre- and post-practical session learning activities. Dyad pedagogy has been explored in clinical settings and simulation procedural-based training but is yet to be fully verified in anatomy education. To determine the effectiveness of hybrid practical sessions and reduced donor to student ratios, the opinions of first year medical students were examined using an online questionnaire with a 51% response rate. Although students recognized the merits of more time in the anatomy laboratory, including opportunities for self-directed study and exposure to anatomical variation, they felt that having two students per station enabled sufficient hands-on time with the donor body and fostered learning opportunities that would not be possible with larger groups. Strong preferences for quality time with the donor body supported by online resources suggests this modality should be a key consideration in course design for anatomy curricula and emphasizes the importance of gauging students' preferences to optimize satisfaction and learning output when pivoting to blended learning strategies in anatomy education.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".