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Record W2581539930 · doi:10.1558/cj.29527

Encouraging Free Play: Extramural Digital Game-Based Language Learning as a Complex Adaptive System

2017· article· en· W2581539930 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

VenueCALICO Journal · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceEntertainmentMultimediaInteractivityLanguage acquisitionGermanContext (archaeology)Game mechanicsMathematics educationHuman–computer interactionPsychologyLinguistics

Abstract

fetched live from OpenAlex

Massively multiplayer online role-playing games like World of Warcraft are ideally suited to encourage and facilitate second language development (SLD) in the extramural setting, but to what extent do the language learners’ actual trajectories of gameplay contribute to SLD? With the current propensity to focus research in digital game-based language learning on vernacular games, or commercially-available games that are designed with entertainment in mind, it is vital to focus on the extramural setting in which these games are designed to be played, while still being subject to rigorous and empirical analysis. This paper examines the extramural gameplay and language learning trajectories of four university German language learners as they play World of Warcraft with native German speakers. Positioning learners’ experiences within a complex adaptive systems framework (Larsen-Freeman & Cameron, 2008;

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 categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.314
Threshold uncertainty score0.999

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 studies0.0030.000
Scholarly communication0.0040.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.259
Teacher spread0.221 · 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