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Record W2030426323 · doi:10.5959/eimj.v4i2.3

Investigating the applications of team-based learning in medical education

2012· article· en· W2030426323 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEducation in Medicine Journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicProblem and Project Based Learning
Canadian institutionsUniversity of Ottawa
FundersDivision of Undergraduate EducationUniversity of Ottawa
KeywordsMedical educationPsychologyComputer scienceMedicine

Abstract

fetched live from OpenAlex

The purpose of this study is to perform a review to account for currently published studies on team-based learning (TBL) in medical education by accredited researchers. In doing so, our two goals included seeking information and critical appraisal. First, the literature was scanned by means of manual and computerized methods to identify pertinent documents. Selected works were then critically appraised to identify the most prevalent themes in the applications and effects of TBL in medical education. After considerable data reduction strategies, six major themes are discussed; 1) experimental TBL approaches; 2) student experiences and perceptions of TBL; 3) student examination performance; 4) faculty impressions; 5) peer evaluations in TBL; 6) TBL in gross anatomy. Although TBL is just beginning to be implemented in medicine, usage of this teaching method is thriving. Students and faculty appear to view TBL favourably and to be highly satisfied with it.

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)0.008
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.630
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.006
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 head0.025
GPT teacher head0.399
Teacher spread0.374 · 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