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Record W4414561215 · doi:10.34190/ecgbl.19.1.4175

Trust, Pedagogy and Play

2025· article· en· W4414561215 on OpenAlexafffundabout
Suzanne de Castell, Jennifer Jenson

Bibliographic record

VenueEuropean Conference on Games Based Learning · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBridge (graph theory)Set (abstract data type)Focus (optics)Focus groupSocial learning

Abstract

fetched live from OpenAlex

This paper reports selected findings from a set of classroom studies across several elementary school grades that involved a program of “just playing”, where videogame play was the focus of positive pedagogical attention. The focus here is on observations and analysis of gameplay in two middle school Canadian classrooms. The paper argues that, and illustrates how, playing video games engaged participating students, and their teachers, in overlooked, but educationally impactful, pedagogical practices—pecifically those engendering social relationships of mutual trust. Trust forms an overlooked bridge connecting play and pedagogy. Indispensable to both, trust is a central, indeed a necessary, condition of learning and play: you have to trust to play; you have to trust to learn. Building on observations and analyses of a 10-week videogame study with 2 middle school classes, this paper highlights the important role trust plays in learning generally, and in learning from video games in particular.

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)0.005
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.021
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0070.024
Scholarly communication0.0100.006
Open science0.0010.009
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.038
GPT teacher head0.400
Teacher spread0.362 · 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 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
Published2025
Admission routes3
Has abstractyes

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