LO12: ClerkCast: a novel online free open access emergency medicine curriculum for medical students
Bibliographic record
Abstract
Innovation Concept: Canadian medical students completing their Emergency Medicine (EM) clerkship rotations must develop approaches to undifferentiated patients. Increasingly used in postgraduate EM education, Open Educational Resources (OERs) are a convenient and flexible solution to meeting medical student educational needs on their EM rotation. We hoped to supplement Canadian medical student EM education through the development of ‘ClerkCast’, a novel OER and podcast-based curriculum on CanadiEM.org. Methods: We utilized the Kern Six Step approach to curriculum development for ‘ClerkCast’. A general needs assessment involved a review of available OERs and identified a lack of effective EM OERs specific for medical students. A specific online needs assessment was used to determine which EM topics required further education for medical students. The survey was shared directly with key Canadian medical student and undergraduate medical educator stakeholder groups, and distributed globally through the CanadiEM social media networks. Results of the needs assessment highlighted shared perceptions of educational needs for medical students, with an emphasis on increased need for education on critical care and common EM presentations. We used the topics determined to be highest priority for the development of our first ten episodes of ‘ClerkCast’. Curriculum, Tool or Material: Podcast episodes are released from CanadiEM biweekly. Episodes are 30 to 45 min in length, and focus on cognitive approaches to a common EM presentation for medical students. Content is anchored on medical student interactions with a staff or resident EM co-host. Podcasts are supplemented by infographics and blog posts highlighting the key points from each episode. Learners are also encouraged to interact with the content through review quizzes on a provided question bank. Quality assurance of the content is provided by physician co-hosts who review episode scripts both prior to recording. Post-production feedback is elicited via comments on the curriculum's host website, CanadiEM.org, and through direct email correspondence to the ClerkCast address. Conclusion: With an ever increasing number of OERs in EM and critical care, the systematic development of new resources is important to avoid redundancies in content and medium while also addressing unmet learner needs. We describe the successful use of the Kern Six Steps for curriculum development for the creation of our novel EM OER for Canadian medical students, ‘ClerkCast’.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.048 | 0.010 |
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".