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Record W4289786562 · doi:10.1097/acm.0000000000004897

Enculturating a Community of Action: Health Professions Educators’ Perspectives on Teaching With Wikipedia

2022· article· en· W4289786562 on OpenAlexaff
Paolo C. Martin, Lauren A. Maggio, Heather Murray, John Willinsky

Bibliographic record

VenueAcademic Medicine · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicWikis in Education and Collaboration
Canadian institutionsQueen's University
Fundersnot available
KeywordsCurriculumThematic analysisContext (archaeology)Medical educationResource (disambiguation)Constructivist teaching methodsPedagogyPsychologyComputer scienceTeaching methodQualitative researchMedicineSociology

Abstract

fetched live from OpenAlex

PURPOSE: Health professions educators are increasingly called on to engage learners in more meaningful instruction. Many have used Wikipedia to offer an applied approach to engage learners, particularly learning related to evidence-based medicine (EBM). However, little is known about the benefits and challenges of using Wikipedia as a pedagogic tool from the collective experience of educators who have sought to improve their instructional practice with it. This study aims to synthesize the perspectives of health professions education (HPE) instructors on the incorporation of Wikipedia editing into their HPE courses. METHOD: Applying a constructivist approach, the authors conducted semistructured interviews from July to December 2020, with 17 participating HPE instructors who had substantively integrated Wikipedia into their curriculum at 13 institutions. Participants were interviewed about their experiences of integrating Wikipedia editing into their courses. Thematic analysis was conducted on resulting transcripts. RESULTS: The authors observed 2 broad themes among participants' expressed benefits of teaching with Wikipedia. First, Wikipedia provides a meaningful instructional alternative that also helps society and develops learners' information literacy and EBM skills. Second, Wikipedia supports learners' careers and professional identity formation. Identified challenges included high effort and time, restrictive Wikipedia sourcing guidelines, and difficult interactions with stakeholders. CONCLUSIONS: Findings build on known benefits, such as providing a real-world collaborative project that contextualizes students' learning experiences. They also echo known challenges, such as the resource-intensive nature of teaching with Wikipedia. The findings of this study reveal the potential of Wikipedia to enculturate HPE students within a situated learning context. They also present implications for HPE programs that are considering implementing Wikipedia and faculty development needed to help instructors harness crowd-sourced information tools' pedagogic opportunities as well as anticipate their challenges.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.026
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0240.031
Scholarly communication0.0140.012
Open science0.0020.015
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.092
GPT teacher head0.465
Teacher spread0.373 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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