Teaching Professionalism: Comparing Written and Video Case-Studies
Bibliographic record
Abstract
Purpose: Professionalism is a difficult concept to teach to healthcare professionals. Case-studies in written and video format have demonstrated to be effective teaching tools to improve a student’s knowledge, but little is known about their impact on student behaviour. The purpose of this research study was to investigate and compare the impact of the 2 teaching tools on a student’s behaviour during a simulation. Method: A 3-stage mixed method study was conducted with senior Medical Laboratory Science (MLS) undergraduate students. All students were randomly divided into a Written Group or Video Group to attend a mandatory professionalism workshop focused on bullying and gossip. Twenty-six students completed the voluntary assignment and 21 students participated in the voluntary group simulations. Thematic analysis was performed on the assignments and simulation. Frequencies of themes were calculated. A Group Simulation Assessment Rubric was used to score simulations and calculate an adjusted group performance average (AGPA). Results: The assignment demonstrates that students from both groups obtained a theoretical understanding of how to resolve gossip and bullying. From the Written Group and Video Group, 70%/18% of students discouraged/resolved gossiping and 80%/63% prevented bullying. The mean AGPA for the Written Group and Video Group was 5.4 and 4.9 respectively ( t (5) = 1.5, P = .2). Discussion: Students can successfully apply knowledge they have gained in written and video case-studies focused on the professionalism topics of bullying and gossip to a hypothetical situation. However, a discrepancy in their actions was found during the simulations. The data from the study suggests that written and video case-studies do not have different impacts on a student’s behaviour.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".