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Record W3040930531 · doi:10.3138/jvme-2019-0113

Institutional Experience with Curricular Renewal during the OIE Veterinary Education Twinning Program between the University of Peradeniya, Sri Lanka, and Massey University, New Zealand

2020· article· en· W3040930531 on OpenAlexvenueno aff
Nayana Wijayawardhane, Chanaka Rabel, Lachlan McIntyre, Tim Parkinson, Siril Ariyarathne, Harishchandra Abeygunawardena

Bibliographic record

VenueJournal of Veterinary Medical Education · 2020
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMandateCurriculumVeterinary medicineMedical educationSri lankaGeneral partnershipScope (computer science)Veterinary educationQuality (philosophy)Political scienceMedicinePedagogySociologySocioeconomics

Abstract

fetched live from OpenAlex

The Veterinary Education Twinning Program between the University of Peradeniya (UP) and Massey University (MU) was carried out within the mandate of the World Organisation for Animal Health (OIE) to create opportunities for developing countries to establish educational facilities and methods based on current and accepted international standards. This article describes how the twinning partnership between UP and MU enabled a strong flow of expertise that benefited Sri Lanka to develop a new veterinary undergraduate curriculum. The new curriculum was created to improve the relevance and quality of veterinary education, incorporating current international best practices, to strengthen national veterinary services. Adoption of an outcome-based educational framework has allowed the incorporation of tools such as problem-based learning and student-centered pedagogies and assessments. Extending the duration of the program from 4 academic years to 5 has expanded the scope for clinical learning, particularly in terms of student exposure to livestock veterinary services. This article documents the processes followed during the twinning program to highlight those factors that were critical for success or that were found surprising, difficult, or problematic.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.207
GPT teacher head0.449
Teacher spread0.242 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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