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Record W4385987671 · doi:10.4018/ijthi.328578

The Virtual Community of Practice Facilitation Model

2023· article· en· W4385987671 on OpenAlex
Hugh Kellam, Clare Cook, Deborah L. Smith, Pam Haight

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Technology and Human Interaction · 2023
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsNOSM UniversityUniversity of Ottawa
Fundersnot available
KeywordsAsynchronous communicationMedical educationAsynchronous learningComputer scienceFacilitationKnowledge managementPsychologyMedicinePedagogyTeaching methodCooperative learningSynchronous learning

Abstract

fetched live from OpenAlex

This study examines the instructional design, learning experiences, and outcomes of a virtual community of practice (VCoP). In 2019, the Northern Ontario School of Medicine launched a continuing professional development program consisting of an asynchronous online module followed by an optional series of facilitated case-based videoconference workshops, designed as a VCoP. This program evaluation study employed a convergent parallel mixed methods design and combined data sources from participant pre- and post-program surveys and reflections with a content analysis of semi-structured interviews. The paper reports key enablers that contributed to the following outcomes: the value of an online module as a baseline of knowledge; the impact of the shared case studies, experiences, and peer support on reflection and modifications to medical practice; and skill development and patient-centered care as a result of module and VCoP participation. A model for the effective design and delivery of VcoPs is proposed that results in acquisition of new knowledge and skills and promotes patient-centred practice.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.626
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.055
GPT teacher head0.508
Teacher spread0.453 · 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