MétaCan
Menu
Back to cohort
Record W4366583884 · doi:10.2147/amep.s399851

Exploring Perceptions of Competency-Based Medical Education in Undergraduate Medical Students and Faculty: A Program Evaluation

2023· article· en· W4366583884 on OpenAlexaff
Erica Ai Li, Claire A. Wilson, Jacob Davidson, Aaron Kwong, Amrit Kirpalani, Peter Wang

Bibliographic record

VenueAdvances in Medical Education and Practice · 2023
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedical educationCurriculumOptimismFaculty developmentPerceptionPsychologyProcess (computing)MedicineProfessional developmentPedagogyComputer science

Abstract

fetched live from OpenAlex

Background: There is limited work exploring competency-based medical education (CBME) in undergraduate medical education. We aimed to assess medical students' and faculty's perception of CBME in the undergraduate medicine setting after its implementation at our institution through a Content, Input, Process, Product (CIPP) program evaluation model. Methods: We explored the rationale for the transition to a CBME curriculum (Content), the changes to the curriculum and the teams involved in the transition (Input), medical students' and faculty's perception of the current CBME curriculum (Process), and benefits and challenges of implementing undergraduate CBME (Product). A cross-sectional online survey was delivered over 8-weeks in October 2021 to medical students and faculty as part of the Process and Product evaluation. Results: Medical students displayed greater optimism towards CBME, compared to faculty, in terms of its role in medical education (p<0.05). Faculty were less certain about how CBME was currently implemented (p<0.05), as well as how feedback to students should be delivered (p<0.05). Students and faculty agreed on perceived benefits to CBME implementation. Faculty time commitment to teaching and logistical concerns were reported as perceived challenges. Conclusion: Education leaders must prioritize faculty engagement and continued professional development of faculty to facilitate the transition. This program evaluation identified strategies to aid the transition to CBME in the undergraduate setting.

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)0.007
metaresearch head score (Gemma)0.075
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.930
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.075
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.095
GPT teacher head0.538
Teacher spread0.443 · 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 designOther design
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

Citations26
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueAdvances in Medical Education and PracticeSame topicInnovations in Medical EducationFrench-language works237,207