MétaCan
Menu
Back to cohort
Record W4391566347 · doi:10.5334/pme.962

Evaluating Competence by Design as a Large System Change Initiative: Readiness, Fidelity, and Outcomes

2024· article· en· W4391566347 on OpenAlexafffundabout
Andrew K. Hall, Anna Oswald, Jason R. Frank, Timothy R. Dalseg, Warren J. Cheung, Lara Cooke, Lisa Gorman, Stacey Brzezina, Sinthiya Selvaratnam, Natalie Wagner, Stanley J. Hamstra, Elaine Van Melle

Bibliographic record

VenuePerspectives on Medical Education · 2024
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsQueen's UniversityUniversity of TorontoUniversity of CalgaryUniversity of AlbertaRoyal College of Physicians and Surgeons of CanadaUniversity of Ottawa
FundersRoyal College of Physicians and Surgeons of Canada
KeywordsCompetence (human resources)Transformational leadershipFidelityProgram Design LanguageComputer scienceProcess managementProgram evaluationMedical educationKnowledge managementMedicinePsychologyEngineeringSoftware engineering

Abstract

fetched live from OpenAlex

Program evaluation is an essential, but often neglected, activity in any transformational educational change. Competence by Design was a large-scale change initiative to implement a competency-based time-variable educational system in Canadian postgraduate medical education. A program evaluation strategy was an integral part of the build and implementation plan for CBD from the beginning, providing insights into implementation progress, challenges, unexpected outcomes, and impact. The Competence by Design program evaluation strategy was built upon a logic model and three pillars of evaluation: readiness to implement, fidelity and integrity of implementation, and outcomes of implementation. The program evaluation strategy harvested from both internally driven studies and those performed by partners and invested others. A dashboard for the program evaluation strategy was created to transparently display a real-time view of Competence by Design implementation and facilitate continuous adaptation and improvement. The findings of the program evaluation for Competence by Design drove changes to all aspects of the Competence by Design implementation, aided engagement of partners, supported change management, and deepened our understanding of the journey required for transformational educational change in a complex national postgraduate medical education system. The program evaluation strategy for Competence by Design provides a framework for program evaluation for any large-scale change in health professions education.

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 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)0.002
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.073
GPT teacher head0.457
Teacher spread0.385 · 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 teacher head, not a consensus.

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

Citations21
Published2024
Admission routes3
Has abstractyes

Explore more

Same venuePerspectives on Medical EducationSame topicInnovations in Medical EducationFrench-language works237,207