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Record W2020510510 · doi:10.3138/jvme.35.2.318

Development and Evaluation of an Online Computer-Aided Learning (CAL) Package to Promote Small-Animal Welfare

2008· article· en· W2020510510 on OpenAlexvenueno aff
Matthew Denwood, Vicki Dale, Philippa S. Yam

Bibliographic record

VenueJournal of Veterinary Medical Education · 2008
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAnimal welfareWelfareMedical educationComputer sciencePsychologyMedicineEconomicsBiology

Abstract

fetched live from OpenAlex

RATIONALE FOR THE STUDY: The aims of the study, conducted as a student research project in the 2004-5 session, were to develop an interactive, online computer-aided learning (CAL) package on the topic of small-animal husbandry; to validate the resource as a suitable lecture replacement for first-year veterinary students; and to raise awareness of current guidelines and legislation relating to small-animal housing among local catteries and kennels and in the wider community. METHODOLOGY: Quantitative feedback was collected from student and teaching staff using paper-based questionnaires. Qualitative feedback was gathered from open questionnaire responses and through focus-group discussions with students. Student examination marks were compared for 2004 and 2005, allowing a comparison of student performance before and after the replacement of the traditional lecture with the CAL package. Ethical approval for the study was granted by the faculty's Ethics Committee. RESULTS AND CONCLUSIONS: The CAL package on small-animal housing was well received by teaching staff and students; student performance in examinations improved after the introduction of the CAL program, suggesting that it provides a suitable alternative to didactic teaching. The creation and distribution of the CAL package on CD-ROM and its availability via the Internet are intended to contribute to small-animal welfare education in local catteries and kennels and further afield. The package sets a precedent for the development of more Internet-based, student-authored CAL packages in the future, providing additional resources for independent learning.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.855
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
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 head0.520
GPT teacher head0.538
Teacher spread0.019 · 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 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

Citations5
Published2008
Admission routes1
Has abstractyes

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