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Record W1980426061 · doi:10.3138/jvme.31.2.146

Levels of Continuing Veterinary Medical Education Program Evaluation: Assessing a Course on Dairy Reproductive Management

2004· article· en· W1980426061 on OpenAlexvenueno aff
Dale A. Moore, R.O. Gilbert, W. Gregory Thatcher, J.E.P. Santos, M.W. Overton

Bibliographic record

VenueJournal of Veterinary Medical Education · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
FundersUniversity of Florida
KeywordsVeterinary educationCourse (navigation)Veterinary medicineContinuing educationMedical educationMedicineCurriculumPsychologyEngineeringPedagogy

Abstract

fetched live from OpenAlex

There are four different levels of continuing education program evaluation: participant perceptions of the program or course; participant competence with new skills, knowledge, and abilities; participant performance or change in behavior; and health care or client outcomes, such as resultant changes in patient care or herd/flock production performance. The purpose of this article is to describe different levels of evaluation and demonstrate some methods used in evaluating a continuing veterinary medical education (CVME) course in dairy reproductive management. Participants' learning needs were assessed using learning stage theory and a pre-test of knowledge. Post-program assessments included a test of knowledge, a satisfaction survey, a commitment to change, and self-reported behavior change. The results of the evaluation indicate that self-reports of learning needs do not necessarily reflect actual needs and that satisfaction with a course does not necessarily indicate behavior change. Providers of CVME must recognize the value of program evaluation, as well as the advantages and disadvantages of different evaluation methods.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.177
GPT teacher head0.443
Teacher spread0.266 · 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 designOther design
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

Citations8
Published2004
Admission routes1
Has abstractyes

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