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Record W1966547699 · doi:10.3138/jvme.32.1.51

“Blended” Online Technology: Maximizing Instructor Reach

2005· article· en· W1966547699 on OpenAlexvenueno aff
Geneva Keene Acor

Bibliographic record

VenueJournal of Veterinary Medical Education · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAsynchronous communicationThe InternetComputer scienceDistance educationProcess (computing)Blended learningMultimediaAsynchronous learningComputer-mediated communicationMedical educationTeaching methodEngineering managementEducational technologyWorld Wide WebSynchronous learningEngineeringMathematics educationPsychologyTelecommunicationsMedicineCooperative learning

Abstract

fetched live from OpenAlex

This article describes the development and implementation of a small animal nutrition course for veterinary technicians using ''blended'' online technology and delivery at multiple sites. Student contact was accomplished through both synchronous and asynchronous Internet platforms. A summary of student evaluations is provided. Application of the process described here may be appropriate where specific content expertise is available in one location and desired in multiple locations. Unique features of the course include (a) course and instructor provided by industry partner, (b) synchronous and asynchronous blended online elements, and (c) multiple schools engaged in merged, simultaneous sessions.

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)0.001
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 score0.969
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.081
GPT teacher head0.346
Teacher spread0.265 · 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

Citations5
Published2005
Admission routes1
Has abstractyes

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