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Record W4413998341 · doi:10.1111/jcal.70108

Gamification for Wildfire Education and Safety Training: A Systematic Literature Review and Meta‐Analysis

2025· article· en· W4413998341 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

VenueJournal of Computer Assisted Learning · 2025
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsNational Research Council Canada
FundersNational Institute of Standards and TechnologyU.S. Department of Commerce
KeywordsMeta-analysisTraining (meteorology)Systematic reviewPsychologyMedical educationMEDLINEGeographyMedicinePolitical science

Abstract

fetched live from OpenAlex

ABSTRACT Background Wildfires have become increasingly frequent and destructive, highlighting the need for more effective public education on safety and preparedness. Gamification, the use of game design elements in non‐game contexts, offers a promising strategy to enhance learner engagement and educational effectiveness compared to traditional methods. Objective This study aims to investigate the application of gamification in wildfire education and training, evaluating its effectiveness and highlighting key benefits and challenges. Methods A systematic literature review was conducted using the PRISMA 2020 framework. The review includes 38 articles selected from the Web of Science (WoS) and Scopus databases, which were published from 2007 to 2025, pertinent to the integration of gamification in wildfire simulation or education applications. This review examined gamification in wildfire education through planning, conducting and reporting stages, and included a meta‐analysis to assess the effect size of immersive versus non‐immersive applications. Eligible studies were quality assessed using predefined criteria and analysed to extract key characteristics. VOSviewer was used to conduct a keyword co‐occurrence analysis, identifying major research themes. SPSS was used to calculate the effect size for the meta‐analysis. Results and Conclusions The findings reveal that different gamification strategies distinctly influence user engagement, motivation, learning effectiveness and overall user experience within wildfire education contexts. Through keyword co‐occurrence analysis, the study maps the intellectual landscape of the field, identifying key thematic clusters and emerging trends. Moreover, the meta‐analysis provides empirical evidence of the impact of immersive gamification, showing a small but statistically significant effect in learning outcomes (Hedges' g = 0.18, p = 0.04). This review identifies five critical research gaps: the underrepresentation of safety behaviour outcomes, limited theoretical integration, lack of community‐level and prevention‐oriented educational interventions and insufficient attention to implementation barriers. These insights offer a targeted research agenda and practical guidance for advancing the design and deployment of gamified wildfire education initiatives. The novelty and contribution of this study lie in the comprehensive synthesis on the functional roles of gamification in shaping learning outcomes in the wildfire education context.

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)0.001
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: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.358
Teacher spread0.321 · 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