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Record W2048702081 · doi:10.4018/jgcms.2010040103

Effects of Playing a History-Simulation Game

2010· article· en· W2048702081 on OpenAlex
Shiang‐Kwei Wang

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

VenueInternational Journal of Gaming and Computer-Mediated Simulations · 2010
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsNew York Institute of Technology
Fundersnot available
KeywordsTest (biology)PsychologyGame based learningPeriod (music)Game playKingdomMathematics educationComputer scienceMultimedia

Abstract

fetched live from OpenAlex

Studies on game-based learning usually investigate at least one of three subjects: the effects of gaming on learning performance, the effects of gaming on cognitive skills and attitudes, and learners’ game-design experiences. Whether gaming relates positively to learning outcomes is still under investigation. This study examines the components contributing to the development of a literate game player and how players could cognitively grasp the design of a game scenario based on real history (namely, the game Romance of the Three Kingdoms). This study surveyed 497 participants in Taiwan on their knowledge of Chinese history (the Three Kingdoms period). The participants constituted two groups: participants who had years of gaming experience and participants who did not. The study examined test performance by using an independent sample t-test and one-way ANOVA and Pearson-correlation methods. The results revealed that the game players were more knowledgeable about the history of the Three Kingdoms period, had greater motivation to learn history, and were more motivated to learn history by playing the game than was the case with the non-game players.

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 score0.524
Threshold uncertainty score0.445

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)0.0000.000

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 head0.015
GPT teacher head0.311
Teacher spread0.296 · 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