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Record W3025402807 · doi:10.1097/nne.0000000000000832

The Simulation Games

2020· article· en· W3025402807 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNurse Educator · 2020
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsLethbridge College
Fundersnot available
KeywordsDebriefingCapstoneCritical thinkingFeelingCurriculumMedical educationPsychologyExperiential learningAnxietyNurse educationMedicinePedagogyComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Although nursing students practice skills in labs as part of the curriculum, many report feeling anxious and unprepared for their first clinical experience. PURPOSE: A capstone lab, integrating gaming with simulation, was implemented to assimilate previous learning and promote critical thinking before beginning clinical experiences. METHODS: Second-year baccalaureate nursing students participated in a gamified lab with simulated scenarios working in teams in various roles to manage patient situations. Remediation opportunities throughout the lab and formal structured debriefing further maximized their learning. RESULTS: Students reported the lab was beneficial. Most students found the lab "stressful, but in a good way," which challenged them to apply previous learning. Most students cited reduced anxiety and increased confidence for practice after the labs. CONCLUSIONS: Integrating gaming with simulated scenarios maintained student engagement while encouraging critical thinking and knowledge synthesis to better prepare them for clinical experiences.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.050
GPT teacher head0.395
Teacher spread0.345 · 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