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Record W2166627776 · doi:10.3109/0142159x.2012.670328

The Academic Support Process (ASP) website: Helping preceptors develop resident learning plans and track progress

2012· article· en· W2166627776 on OpenAlexaff
Emma J. Stodel, Madeleine Montpetit, Alison Eyre, Michelle Prentice, Mary M. Johnston

Bibliographic record

VenueMedical Teacher · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsÉlisabeth Bruyère HospitalMedical Council of CanadaUniversity of OttawaLearning PartnershipOnex (Canada)College of Family Physicians of CanadaCARE Canada
Fundersnot available
KeywordsTrack (disk drive)Process (computing)Medical educationPsychologyComputer scienceMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: At times, preceptors struggle with aspects of resident education. Many are looking for more support and faculty development in this area. AIMS: To address preceptors' needs for resources and provide a proactive framework for their teaching, the Academic Support Process (ASP) website was developed and evaluated. Preceptors' (N = 35) experiences using the ASP website, as well as their perceptions of its usefulness in supporting resident education, were identified. METHODS: The research comprised two phases: a self-directed workshop involving the creation of a web-based learning plan for a standardised scenario of a resident in difficulty followed by 3 months use of the ASP website with residents in their practice. Information on their experiences was solicited via surveys and focus group interviews. RESULTS: Findings revealed the ASP website enabled preceptors to find words for their concerns around resident competency, gave them a proactive teaching framework, expanded their arsenal of teaching strategies, and supported a customised approach for all learners along the performance spectrum. However, there were a number of challenges encountered by the preceptors that affected site use and buy in. CONCLUSIONS: Results are promising. Next steps involve developing a clear strategy for adoption.

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)0.010
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.837
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.042
GPT teacher head0.434
Teacher spread0.392 · 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 designObservational
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

Citations2
Published2012
Admission routes1
Has abstractyes

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