MétaCan
Menu
Back to cohort
Record W2806229007 · doi:10.1080/19415257.2018.1474490

A pilot study on interprofessional education: how prepared are faculty to teach?

2018· article· en· W2806229007 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.

Bibliographic record

VenueProfessional Development in Education · 2018
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of British ColumbiaThompson Rivers University
Fundersnot available
KeywordsPreparednessFaculty developmentMedical educationInterprofessional educationProfessional developmentPsychologyTeaching methodQualitative researchMedicinePedagogyHealth careSociology

Abstract

fetched live from OpenAlex

Faculty development for interprofessional (IP) teaching and learning is a complex and evolving part of educators’ preparation for IP teaching and learning. A review of the literature highlighted a gap of rigorous research in the area of faculty development for interprofessional education (IPE). This pilot study used a mixed-methods approach to explore how faculty development affected educators’ preparedness for IP teaching and looked at the possible effects of IP and teaching experiences. Pre- and post-faculty development evaluations were captured using validated instruments and helped to explore the impact faculty development had on educators’ preparedness for IPE. The qualitative data offered insights using participants’ perspectives about IPE where the quantitative method could not. This pilot study offers findings that explored important characteristics that may have a role in faculty preparation for IPE teach and learning and could possibly be used in future research.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.311
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.071
GPT teacher head0.479
Teacher spread0.408 · 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