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Record W2019646362 · doi:10.3138/jvme.35.4.589

Interactive Clinical Cases in Veterinary Education Used to Promote Independent Study

2008· article· en· W2019646362 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Veterinary Medical Education · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicProblem and Project Based Learning
Canadian institutionsnot available
Fundersnot available
KeywordsTUTORSet (abstract data type)Medical educationImplementationResource (disambiguation)Veterinary educationMathematics educationField (mathematics)PsychologyComputer scienceMedicinePedagogyCurriculumMathematics

Abstract

fetched live from OpenAlex

This study set out to encourage veterinary undergraduates to adopt independent and deep approaches to their study in a five-week third-year course on the alimentary system by incorporating problem solving and decision analysis. We were interested in exploring the effectiveness of two implementations of online interactive case scenarios and the amount of staff time required to develop, deploy, and support their use by students. The majority of students who responded to our questionnaire attempted all the cases available and were able to work with very little tutor input. Cases that prompted students to type an answer before allowing them to progress were rated by all students as making them think more. The realistic nature of the cases, the way they stimulated students' interest, and the need to apply existing knowledge gained in lectures were cited as three of the five characteristics that students most liked. These characteristics map to a range of learning processes that are considered to form a fully developed deep approach by research in this field over the past 40 years. While resource implications are still high, this use of these case scenarios did engage the vast majority of students in independent and deep approaches to their study.

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)0.004
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 score0.550
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.213
GPT teacher head0.517
Teacher spread0.304 · 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