MétaCan
Menu
Back to cohort
Record W7055001884

Beyond Stop Disasters 2.0: Video Games as Tools to Foster Participation in Learning about Disasters and Disaster Risk Reduction

2020· dissertation· en· W7055001884 on OpenAlexaboutno aff

Bibliographic record

VenueResearchSpace (University of Auckland) · 2020
Typedissertation
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsDisaster risk reductionPopularityDisaster researchVideo gameMainstreamParticipatory action researchCitizen journalismDisaster recovery
DOInot available

Abstract

fetched live from OpenAlex

With the increasing popularity of video games over the last few decades, a significant research area for disaster studies has presented itself. Preliminary disaster video game research explored a multitude of disaster video games from various international organisations (e.g. United Nations Office for Disaster Risk Reduction [UNISDR], United Nations: Educational, Scientific and Cultural Organisation [UNESCO]), governments (e.g. Canada, Australia), non-government organisations (e.g. Save the Children, Christian Aid), researchers (e.g. Earth Observatory of Singapore) and mainstream disaster video games. This preliminary research demonstrated that video games have an ability to convey messages regarding disaster and disaster risk reduction (DRR), including portrayals of hazards, vulnerabilities, capacities and numerous disaster discourses. Yet, there is a paucity of studies on these games in the disaster research literature. Hence, a necessity exists for innovative research to explore how disaster video games could contribute to DRR learning strategies of the future. This thesis worked to link video games to disaster studies through the sphere of DRR education, participation and the learning theory of constructivism. Unlike conventional video game research approaches, this project conceptualised an innovative participatory methodological framework for video game research. This framework is based upon constructivist learning theory and active learner participation, to better foster the learning process and explore learning from the inside. Utilising this framework, this research considered how various ‘serious’ disaster video games (Quake Safe House, Earth Girl 2, Sai Fah – The Flood Fighter, Stop Disasters!) in educational environments like museums and schools, could foster player participation in learning about disaster and DRR. The perspectives of museum visitors (Te Papa in Wellington and Quake City in Christchurch), students (four Hawke’s Bay school) and teachers, indicate the strengths and challenges of such video games in regards to game content, game mechanics, skill-building, player motivations and social interactions. These findings indicate video games cannot be stand-alone tools for the purpose of building disaster awareness in players. Video games require greater integration into the teaching and learning processes to minimise the potential risk of such video games becoming tokenistic learning tools. The initial research findings were tested with academics, teachers, students and emergency management personnel in co-designing a teaching pedagogy, involving several group-based learning activities and a geo-referenced Minecraft world, to engage students in learning about disaster and DRR within their local area. Ultimately, the needs of the players and educators need to be factored in both the video game design and development process, and associated teaching and learning pedagogy, in order to foster meaningful player participation in learning about disaster and DRR. Therefore, this thesis puts forward the argument that video games need to be repositioned from being perceived by scholars, educators and DRR practitioners as simply tokenistic learning activities to fully integrating video games within teaching pedagogy and the broader learning process. In turn, the empirical evidence collected from three case studies, forming the basis of this research project, highlights how disaster video games can facilitate deeper engagement and understanding of disasters and DRR when social interactions, metagaming and gameplay, are taken into more serious consideration. Thereby, demonstrating how disaster video games could potentially contribute to DRR learning strategies of the future, becoming a new cadre to the existing DRR education tool kit.

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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score1.000

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 integrity0.0000.001
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 head0.017
GPT teacher head0.264
Teacher spread0.247 · 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 teacher head, not a consensus.

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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueResearchSpace (University of Auckland)Same topicLaser Design and ApplicationsFrench-language works237,207