19 CREATING A WEB-BASED Multimedia resource for medical students learning pediatric clinical skills.
Bibliographic record
Abstract
Background Our department of pediatrics has sponsored a student-led initiative to create an interactive audiovisual database of pediatric clinical skills. Learnpediatrics.com, is an on-line educational tool made up of modules developed by medical students, with resident and faculty oversight, for the educational benefit of those learning clinical skills in pediatrics. The initial material was very positively received and has been used as a model by other educators. However, the development process used with early modules proved inefficient. We report a new and effective process. Objectives (1) To create a comprehensive Web-based resource for medical students learning pediatric clinical skills; (2) to incorporate multimedia elements as learning aids; (3) to retain the project9s core vision of creating a resource built and organized by medical students. Methods The content and links of the initial module (Respiratory) were developed by students from UBC Medical School, working with education and clinical faculty over a 2-month time frame, then filmed and posted on the Web by a contracted software company. In subsequent years, similar summer-based activity failed to complete the modules on schedule. In the spring of 2005, a new approach for creating content was adopted. The project leaders approached students prior to their 2-month clinical pediatric clerkship rotation. Interested medical students then developed relevant content for the Web site as part of their rotation requirements under the direction of a pediatric resident. This also gave them opportunities to liaise with medical educators and clinical faculty. Results This approach ensured enthusiastic delivery of content, continuity, manageable tasks for the students, residents, and faculty, and completion of an entire Neurology module. Using guidelines provided by the project leaders, 15 medical students could write on topic areas, pose questions, have ongoing input, and learn from the filming of the clinical examination skills component demonstrated by faculty. The material was collected 8 weeks later and then reviewed and edited by a team of residents, teaching fellows, and faculty. Discussion Our new method of content creation during clinical rotations has resulted in a new module and generated sufficient enthusiasm across the team that we are continuing with this method and anticipate completion of our next module, Cardiology, by January 2006. Once Learnpediatrics.com is completed, we hope that it will continue to be an educational tool that can be accessed by medical students around the world.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.053 | 0.019 |
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".