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Record W2166850456 · doi:10.1080/01421590701663295

Games as teaching tools in a surgical residency

2007· article· en· W2166850456 on OpenAlexaff
Sarkis Meterissian, Moïshe Liberman, Peter J. McLeod

Bibliographic record

VenueMedical Teacher · 2007
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsMontreal General HospitalMcGill University
Fundersnot available
KeywordsPreferenceMedical educationSet (abstract data type)Quality (philosophy)Face (sociological concept)MedicinePsychologyMathematics educationComputer scienceSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Didactic lectures have been the mainstay of core teaching in the surgical residency program at our school. Our concerns about the educational impact of these passive activities led us to consider more interactive teaching approaches. METHODS: We developed an interactive games-based approach to learning. One set of games was labeled "Who wants to be a Surgeon" (WS) and the other was called "Senior Face-off" (SF). We evaluated the impact of this innovation using an end-of-year questionnaire. RESULTS: Enjoyment, teaching quality and preference over lectures were high for both games. However, the WS sparked interest significantly more in junior residents (4.3 +/- 0.21 vs 3.3 +/- 0.31, p = 0.015) and senior residents found both games more stressful than did junior residents (WS: 2.88 +/- 0.32 vs 2.00 +/- 0.21, p = 0.038, and SF: 3.54 +/- 0.29 vs 1.80 +/- 0.33, p = 0.001). CONCLUSIONS: This innovative teaching technique promoted learner interest and was regarded as a worthwhile educational activity. Games with a competitive emphasis may unduly stress senior residents.

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)0.003
metaresearch head score (Gemma)0.005
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.736
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0150.000

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 head0.056
GPT teacher head0.391
Teacher spread0.335 · 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 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

Citations40
Published2007
Admission routes1
Has abstractyes

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