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Record W2528494184 · doi:10.22456/1679-1916.67347

State of the Art in Educational Games Virtualization

2016· article· en· W2528494184 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

VenueRENOTE · 2016
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsVirtualizationComputer scienceState (computer science)Field (mathematics)Process (computing)MultimediaGame mechanicsGame designMathematics educationPsychologyMathematics

Abstract

fetched live from OpenAlex

Game Virtualization is a process of digital versions creation for traditional/ physical games. In education, this process aims to create digital versions for traditional/ physical educational games, keeping psychological and pedagogical concepts from traditional version, as well as associate these concepts to contemporary game design elements. In the last years, a series of studies and efforts have been done in this field, making room to important discussions regarding the results obtained and perspectives to future works. In this sense, this paper presents a state of the art in Educational Game Virtualization, as well as some discussions, challenges and directions to new studies in this field.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
Threshold uncertainty score0.912

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 head0.019
GPT teacher head0.318
Teacher spread0.299 · 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