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Record W2088639469 · doi:10.3148/66.3.2005.187

<i>Distance Delivery</i> of Nutrition Education

2005· article· en· W2088639469 on OpenAlexaffvenue
Vera C. Mazurak, Ellen Whybrow, Stanley Varnhagen, Catherine J. Field

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsAlberta Ministry of Agriculture and ForestryUniversity of Alberta
Fundersnot available
KeywordsAsynchronous communicationDistance educationPerceptionMedical educationQuality (philosophy)Focus groupComputer scienceAsynchronous learningPsychologyProfessional developmentMathematics educationPedagogyMultimediaTeaching methodMedicineSynchronous learningSociologyCooperative learning

Abstract

fetched live from OpenAlex

Questions often arise about the quality of an educational experience in a distance format. Debate exists as to whether the relatively new format of on-line education can offer an equivalent learning experience for students, and the perception remains that virtual learning is impersonal. We examined students' experience in an introductory undergraduate nutrition course that had been remodelled as an asynchronous, active-learning, student-centred model. The investigation used the framework of instructional message design, a concept based on cognitive science principles, to highlight themes in student survey and focus group data. Results indicate that a motivating and accessible quality educational experience is possible in an on-line format through a student-centred model. Such a model provides a means to offer education to a diverse and larger audience. Further investigation is needed to determine faculty professional development needs and cost-effective ways to expand the model. Such a model provides alternatives to expand delivery to encourage interest in the field, and to provide continuing education for allied professionals and the general public.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0190.004

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 head0.099
GPT teacher head0.479
Teacher spread0.380 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2005
Admission routes2
Has abstractyes

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