Student Feedback about the Medical Humanities Module in a Caribbean Medical School
Bibliographic record
Abstract
Introduction: A medical humanities (MH) course has been conducted at the institution from February 2013.The school admits students from the United States, Canada and other countries to the undergraduate medical course.The present study was conducted among first to sixth semester basic science students to obtain their feedback about various aspects of the module and suggestions for further improvement.Materials & Methods: Focus group discussions (FGDs) were organised with interested students during the last two weeks of October 2015.Written informed consent was obtained from all participants.The FGDs were audio recorded and lasted between 90 to 100 minutes.An FGD guide was used to facilitate the deliberations.Written transcripts of recordings were prepared and read through multiple times.Transcripts were coded and items with similar codes were grouped together into themes.Results: Twenty-one of the 100 students (21%) participated.Overall response to the module was positive.Students who participated in the FGDs felt the module offered a different perspective compared to other basic science subjects.Feedback regarding small groups and group dynamics were also obtained.The literature excerpts used were appreciated by the respondents.The paintings and the activities encouraged the process of creativity, reflection and taught participants the importance of reconciling varied views.Role-plays encouraged student participation and active learning.MH encouraged active learning and students appeared to have fun while learning.Conclusion: MH and movie screening and activities are slowly becoming established in the institution.Respondent feedback was positive.Suggestions for future modules were obtained.
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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 | 0.008 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".