MétaCan
Menu
Back to cohort

Fostering education scholarship: the mentored research group

2009· article· en· W2099907521 on OpenAlexaff
Mark Goldszmidt, Elaine Zibrowski, Christopher Watling

Bibliographic record

VenueMedical Education · 2009
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsWestern University
Fundersnot available
KeywordsMentorshipScholarshipMedical educationContext (archaeology)Qualitative researchFocus groupInstitutionHigher educationFaculty developmentPsychologySociologyPedagogyMedicineProfessional developmentPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Context and setting Increasingly, clinical faculty members are being encouraged to participate in education scholarship, but for those without a pre-existing track record of such work, a number of barriers exist. Neither traditional faculty development programmes nor advanced education training, including that provided by Master’s level programmes, may adequately address these barriers. Why the idea was necessary Although many medical school faculty members possess a personal interest in research and some have also undertaken advanced education training, few have successfully transitioned to a stage of actively pursuing education research. In our institution, we found a trend for faculty members interested in education to choose leadership over research career paths. A local needs assessment identified a gap in the area of education research mentorship, which we surmised might be a contributor to these problems. The purpose of this project was to assess the feasibility and effectiveness of using an external mentor to support a research group that would in turn promote the development of a cadre of medical education researchers. What was done In the fall of 2005, we arranged that a mid-career education scientist from a nearby medical school, with expertise in qualitative research, would serve as a research mentor. The opportunity to participate in a group mentored by the expert was advertised via e-mail. The project had six phases: (i) initial group formation and introduction to qualitative methods (three monthly meetings with readings); (ii) identification of a research question and determination of appropriate methodology for its exploration (four bi-monthly meetings); (iii) delegation of a principal investigator and preparation of an ethics application and grant proposal (four to six meetings over 2 months); (iv) data collection and analysis (1 year); (v) dissemination of results (1 year), and (vi) development of follow-up projects (ongoing – into its second year post-project). During each phase, an attempt was made to include all members of the group and to allow different members to participate to greater and lesser extents depending on the tasks and their availability. As the group progressed into phases 4–6, the mentor personally attended meetings at key time-points, but was continually available for advice by phone and e-mail. Evaluation of results and impact Ten individuals indicated an initial interest in participating and nine committed to joining after the first meeting. One dropped out by phase 2. Two others subsequently dropped out because of time constraints by phase 3. The remaining six individuals have collaboratively published two papers and have another currently under review. Six peer-reviewed presentations have been given at international meetings and five at local education conferences. All members co-authored the papers and all but one have presented. The group has remained together and has received two additional grants for follow-up projects. In a post-project anonymous survey, all members who continued their participation rated their experiences very highly. One group member said: ‘It was one of the highlights of my working career.’ Lastly, our mentor also rated the experience highly and has agreed to continue mentoring the group during its ongoing projects.

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)0.004
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.803
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.069
GPT teacher head0.477
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
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

Citations7
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueMedical EducationSame topicInnovations in Medical EducationFrench-language works237,207