Beyond Stop Disasters 2.0: Video Games as Tools to Foster Participation in Learning about Disasters and Disaster Risk Reduction
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».