Using the Internet to Assess and Teach Medical Students in Dermatology
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: We wish to develop and evaluate a user-friendly online interactive teaching and examination model as an adjunct to traditional bedside teaching of medical students during a clinical rotation in dermatology. METHODS: Following completion of an online examination, senior medical students at the University of British Columbia (n = 178) were asked to complete an online survey to evaluate their acceptance of this new method. The online examination model was evaluated through students' responses to the questionnaire-based evaluation they were asked to complete following their examination. Responses were evaluated on a standardized 5-point scale. RESULTS: A high response rate was achieved (98.9%). Overall, 93% of senior medical students felt that the Internet was a useful and effective way to administer a dermatology examination. Most (90%) preferred the online examination to a traditional paper-and-pencil examination and the majority (88%) felt that the quality of digital images presented was sufficient to make an accurate diagnosis. In addition, students strongly supported the further development of teaching resources on the web and would use these resources in learning dermatology (93%). CONCLUSIONS: The development of an online interactive examination tool for dermatology is technically feasible with current technology. Senior medical students are not only accepting of this new technology but also prefer it to more traditional formats and indicate enthusiasm for the development of further online teaching resources in dermatology.
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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) | 0.001 | 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".