Preparing Students for Practical Exams: The Dreaded Anatomy Bell Ringer
Bibliographic record
Abstract
Undergraduate students in the health sciences typically perform poorly on practical exams. For example, the bell ringer is a stressful part of anatomy courses. This poor performance may be due to the fact that students often struggle with âtransferringâ content from lecture (i.e., classroom) to a clinical setting (i.e., lab; Bolander et al., 2008). Although students are provided with weekly lab periods to interact with anatomical models, this learning is typically quite passive. As no assessments occur before the bell ringer, students have no early opportunities to test their knowledge. Course teaching assistants (TAs) are uniquely positioned to prepare students for the exam and to ensure they are meeting required learning outcomes. Workshop participants will explore facilitation strategies to actively involve students in the lab, thus aiding students to deepen their understanding of human anatomy and motivating reflection on these lessons. Moreover, this workshop will highlight the importance and utility of practical exams in anatomy courses and will also help increase participantsâ confidence in helping students apply and evaluate their lecture-based knowledge in lab.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".