Integrating Wikipedia editing into health professions education: A curricular inventory and review of the literature
Bibliographic record
Abstract
Abstract Introduction Wikipedia is an online encyclopedia read by millions seeking medical information. To provide health professions students with skills to critically assess, edit, and improve Wikipedia’s medical content, a skillset aligned with evidence-based medicine (EBM), Wikipedia courses have been integrated into health professions schools’ curriculum. This study describes a literature review and curricular inventory of Wikipedia educational initiatives to provide an overview of current approaches and identify directions for future initiatives and research. Methods Five databases were searched for articles describing educational interventions to train health professional students to edit Wikipedia. Course dashboards, maintained by Wiki Education (WikiEdu), were searched for curricular materials. From these sources, key details were extracted and synthesized, including student and instructor type, course content, educational methods, and student outcomes. Results Six articles and 27 dashboards reported on courses offered between 2015-2019. Courses were predominantly offered to medical and nursing students. Instructors delivered content via videos, live lectures, and online interactive modules. Course content included logistics of Wikipedia editing, EBM skills, and health literacy. All courses included assignments requiring students to edit Wikipedia independently or in groups. Limited details of student evaluation were available. Discussion A small but growing number of schools are training HPE students to improve Wikipedia’s medical content. Course details are available on WikiEdu dashboards and, to a lesser extent, in peer-reviewed publications. There is limited evidence of the initiatives’ impacts on student learning, however, integrating Wikipedia into health professions education has potential to facilitate learning of EBM and communication skills, improve Wikipedia’s online content, and engage students with an autonomous environment while learning. Future considerations should include a thorough assessment of student learning and practices, a final review of student edits to ensure they follow Wikipedia’s Guidelines and are written in clear language, and improved sharing of teaching resources by instructors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".