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Record W3046536248 · doi:10.3138/jvme.2019-0136

Comparison of Graphic Organizers Versus Online Flash Cards as Study Aids in an Elective Veterinary Cardiology Course

2020· article· en· W3046536248 on OpenAlexvenueno aff
Jessica Ward, Courtney A. Vengrin

Bibliographic record

VenueJournal of Veterinary Medical Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)PreferenceMedicineCrossover studyMedical educationPsychologyAlternative medicineMathematicsPathology

Abstract

fetched live from OpenAlex

The ideal study aid format for veterinary students remains unknown. Both graphic organizers (GOs) and flash cards (FCs) have shown utility for enhancing learning in specific contexts. A mixed-methods prospective randomized crossover trial was undertaken with veterinary students ( n = 59) in an elective cardiology course. All students received identical content presented via weekly in-class lectures and were given study aids in either GO or FC format. One week later, students completed quizzes of content knowledge for each lesson and indicated amount of time spent studying. Crossover occurred such that groups of students alternated between receiving GOs and FCs. Quantitative and qualitative data were collected in the form of in-depth pre- and post-course surveys. Overall, there was no significant difference in quiz scores ( p = .26) or time spent studying ( p = .33) based on study aid type. Time spent studying for each quiz, as well as other measures of study habits, decreased significantly throughout the semester. Post-course survey responses showed overall higher student satisfaction for GOs compared to FCs ( p = .022), as well as a shift in preference away from FCs throughout the semester ( p = .03). Free-text survey responses revealed that individual students had strong preferences either for or against FCs in the context of their particular study habits. In an elective veterinary cardiology course, use of GO format compared to FC format study aids resulted in equivalent short-term learning outcomes and time spent studying, with each study aid format appealing to specific learning preferences of individual students.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.996
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.244
GPT teacher head0.563
Teacher spread0.319 · 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.

Study designNon-randomized trial
DomainMethods
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

Citations1
Published2020
Admission routes1
Has abstractyes

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