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Record W6920516972 · doi:10.60692/2xpc9-1jx83

Educational games created by medical students in a cultural safety training game jam: a qualitative descriptive study

2022· article· en· W6920516972 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2022
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsMcGill University
Fundersnot available
KeywordsThematic analysisContext (archaeology)Serious gameQualitative researchSituated learningEducational gameGame designSituatedGame Developer

Abstract

fetched live from OpenAlex

Cultural safety training, whereby health professionals learn to reflect on their own culture and to respect the cultural identity of patients, could address intercultural tensions in health care. Given the context of their medical education, however, medical students might perceive such training to be dull or even unnecessary. Game jams, collaborative workshops to create and play games, are a potentially engaging learning environment for medical students today. How medical students learn while making games is poorly documented. This study describes the characteristics of educational games created by participants in a cultural safety game jam and the concepts they used to create games.As part of a trial, 268 Colombian medical students divided into 48 groups participated in an eight-hour game jam to create a prototype of an educational game on cultural safety. In this qualitative descriptive study, we reviewed the description of the games uploaded by participants, including the name, objective, game narrative, rules, rewards, penalties, and pictures. An inductive thematic analysis collated their descriptions.The game descriptions illustrated the characteristics of the educational games and the aspects of the cultural safety concept that the students used to create games. Medical students situated cultural safety within a continuum with culturally unsafe actions at one end and cultural safety at the other end. Although not familiar with game design, the students designed prototypes of basic educational games including game dynamics, game scenarios, learning objectives, and pedagogical strategies.The findings of this study could help researchers and educators to understand how medical students learn from game design and the kind of games that game jam participants can create without previous game design skills.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

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

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 head0.037
GPT teacher head0.275
Teacher spread0.238 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2022
Admission routes1
Has abstractyes

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