Teaching child development to medical students
Bibliographic record
Abstract
PURPOSE: Several published strategies on teaching the screening of normal child development were integrated into a small group learning experience for second-year medical students to address practical and logistical problems of approaches used individually. This study examines the effectiveness of this integrated approach using student evaluations. METHOD: A total of 191 second-year university medical and dental students were invited to participate. Well-described learning objectives, the Ages and Stages Questionnaire (ASQ), live parent-child dyads and video backup were used. Students rotated through three small group stations. Feedback was provided using a Likert scale (from 1, low, to 5, high) and written comments. Consent was obtained. Live parent-child dyads versus video clip groups were analysed by averaging overall scores. Generalised estimating equation (GEE) analysis in stata (Stata Corporation, College Station, Texas) was used for comparing the two groups. RESULTS: A total of 178 students (93%) agreed to participate and filled out the evaluation forms. The overall score on the Likert scale was 4.6 (range 4-5). On two occasions video clips were substituted for live parent-child dyad presentations in one of the three stations. These students (n=43, rating 4.61/5) rated their experience as comparable with those who had three live family stations (n=135, rating 4.56/5). Student comments were grouped into broad themes, with most being positive about their learning experience. CONCLUSIONS: This integrated approach is highly acceptable. Video clip usage, live dyads, clear written objectives and use of a standardised screening tool preserved the interaction and immediacy of a clinical encounter, while maintaining consistency in content.
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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 | 0.012 | 0.013 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".