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Record W1991282656 · doi:10.3138/jvme.34.4.497

Interactive Computerized Learning Program Exposes Veterinary Students to Challenging International Animal-Health Problems

2007· article· en· W1991282656 on OpenAlexvenueno aff
Patricia A. Conrad, D. W. Hird, Jonathan Arzt, Rick H. Hayes, Dave Magliano, Janine Kasper, Saul Morfin, Stephen J. Pinney

Bibliographic record

VenueJournal of Veterinary Medical Education · 2007
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsProblem-based learningExperiential learningThe InternetCLIPSComputer scienceMedical educationMedicineMultimediaWorld Wide WebPsychologyMathematics educationArtificial intelligence

Abstract

fetched live from OpenAlex

This article describes a computerized case-based CD-ROM (CD) on international animal health that was developed to give veterinary students an opportunity to "virtually" work alongside veterinarians and other veterinary students as they try to solve challenging disease problems relating to tuberculosis in South African wildlife, bovine abortion in Mexico, and neurologic disease in horses in Rapa Nui, Chile. Each of the three case modules presents, in a highly interactive format, a problem or mystery that must be solved by the learner. As well as acquiring information via video clips and text about the specific health problem, learners obtain information about the different countries, animal-management practices, diagnostic methods, related disease-control issues, economic factors, and the opinions of local experts. After assimilating this information, the learner must define the problem and formulate an action plan or make a recommendation or diagnosis. The computerized program invokes three principles of adult education: active learning, learner-centered education, and experiential learning. A medium that invokes these principles is a potentially efficient learning tool and template for developing other case-based problem-solving computerized programs. The program is accessible on the World Wide Web at <http://www.calf.vetmed.ucdavis.edu/html/International_web/international_menu.html>. A broadband Internet connection is recommended, since the modules make extensive use of embedded video and audio clips. Information on how to obtain the CD is also provided.

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)0.005
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 score0.810
Threshold uncertainty score0.914

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.375
GPT teacher head0.611
Teacher spread0.236 · 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

Citations7
Published2007
Admission routes1
Has abstractyes

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