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Record W2027383486 · doi:10.3138/jvme.35.3.382

Objective Structured Clinical Examinations (OSCEs) as a Summative Evaluation Tool in a Ruminant Health Management Rotation for Final-Year DVM Students

2008· article· en· W2027383486 on OpenAlexaffvenueabout
K G Bateman, Paula Menzies, D. Sandals, T.F. Duffield, S.J. LeBlanc, Ken Leslie, K. Lissemore, Rob Swackhammer

Bibliographic record

VenueJournal of Veterinary Medical Education · 2008
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSummative assessmentFormative assessmentObjective structured clinical examinationMedical educationMedicinePsychologyPedagogy

Abstract

fetched live from OpenAlex

The objective structured clinical examination (OSCE) has been used for 10 years at the Ontario Veterinary College, University of Guelph, to evaluate the clinical competencies in ruminant health management of final-year DVM students. The performance of these students in the summative assessment, which includes the use of OSCEs, was compared to their formative assessment, given at the end of the rotation. Specifically, classification of students' performance as poor (bottom 10% of the grade range versus "serious deficits") or superior ("A grade" versus "exceeds expectations") was compared. Agreement between the two types of assessment is slight, regardless of whether assessing diagnostic process skills or technical skills--and regardless of whether all students were assessed or only those enrolled in food-animal or mixed streams in their final year--which suggests that the two assess different types of skills. OSCEs are a useful and viable tool for objectively assessing clinical skills in ruminant health management.

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)0.008
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.590
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.572
GPT teacher head0.650
Teacher spread0.079 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2008
Admission routes3
Has abstractyes

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