MétaCan
Menu
Back to cohort
Record W2009819107 · doi:10.3138/jvme.0113-014r

Using Educational Games to Engage Students in Veterinary Basic Sciences

2013· article· en· W2009819107 on OpenAlexvenueno aff
Jennifer L. Buur, Peggy L. Schmidt, Margaret C. Barr

Bibliographic record

VenueJournal of Veterinary Medical Education · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicProblem and Project Based Learning
Canadian institutionsnot available
Fundersnot available
KeywordsDebriefingSession (web analytics)Set (abstract data type)Mathematics educationEducational gamePsychologyMedical educationComputer scienceMedicine

Abstract

fetched live from OpenAlex

Educational games are an example of an active learning teaching technique based on Kolb's learning cycle. We have designed multiple games to provide concrete experiences for social groups of learners in the basic sciences. "Antimicrobial Set" is a card game that illustrates global patterns in antimicrobial therapy. "SHOCK!" is a card game designed to enhance student understanding of the four types of hypersensitivity reactions. After each game is played, students undergo a structured debriefing session with faculty members to further enhance their self-reflective skills. "Foodborne Outbreak Clue" utilizes the famous Parker Brothers® board game as a means to practice skills associated with outbreak investigation and risk assessment. This game is used as a review activity and fun application of epidemiologic concepts. Anecdotal feedback from students suggests that they enjoyed the activities. Games such as these can be easily implemented in large- or small-group settings and can be adapted to other disciplines as needed.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.004

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 head0.154
GPT teacher head0.487
Teacher spread0.333 · 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 designObservational
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

Citations28
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Veterinary Medical EducationSame topicProblem and Project Based LearningFrench-language works237,207