Evaluating the Effectiveness of Paper Modelling as an Active Learning Approach in the Musculoskeletal Module for the MBBS Students
Bibliographic record
Abstract
Objective: Understanding the body's anatomical structures is critical for surgical safety and a crucial pillar of medical curricula, whether integrated or traditional. The students need to comprehend and memorize a significant amount of Anatomical information that seems to burden them. Hence, the paper modelling strategy is designed to help better learning with proper knowledge retention. Our study aims to assess the effectiveness of the modeling technique; concerning the students' performance and feedback at the module's conclusion. Methods: The study used a quasi-experimental study involving 88 medical students who performed the paper modeling for seven weeks and included two weekly activity sessions. We used overhead projector sheets, color markers, and measuring tape for the students to create the muscle models and stick them to the skeleton with poster tack. Results: Data analysis revealed that the students in the treatment groups achieved significantly higher scores (72.7%) than their peers (21.3 %), with a substantial disparity in the mean ratings between the two groups, p<0.001. Moreover, the students' feedback about this method showed that 70 to 73% agreed that the new approach helped them to comprehend and retain information about muscle locations, attachment sites, and actions and allowed them to have in-depth discussions with their peers. Conclusions: The modeling method used in the current study was well appreciated by the students and enhanced their performance because it relied on the benefits of peer-to-peer instruction and embraced combined visual and kinesthetic learning styles.
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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 | 0.006 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".