Developing a Scenario-Based Video Game Generation Framework: Preliminary Results

Date

2019-11-01

Author

Sürer, Elif
Erkayaoğlu, Mustafa
Öztürk, Zeynep Nur
Yücel, Furkan
Bıyık, Emin Alp
Altan, Burak
Şenderin, Büşra
Oğuz, Zeliha
Gürer, Servet
Düzgün, H. Şebnem

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Emergency training and planning provide structured curricula, rule-based action items, and interdisciplinary collaborative entities to imitate and teach real-life tasks. This rule-based structure enables the curricula to be transferred into other systematic learning platforms such as serious games ---games that have additional purposes rather than only entertainment. Serious games aim to educate, cure, and plan several real-life tasks and circumstances in an interactive, efficient, and user-friendly way. Although emergency training includes these highly structured and repetitive action responses, a general framework to map the training scenarios' actions, roles, and collaborative structures to game mechanics and game dialogues, is still not available. To address this issue, in this study, a scenario-based game generator, which maps domain-oriented tasks to game rules and game mechanics, was developed. Also, two serious games (i.e., Hospital game and BioGarden game) addressing the training mechanisms of Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNe) domain, were developed by both the game developers and the scenario-based game generator for comparative analysis. The results show that although the game generator uses higher CPU time, memory usage, and rendering time, it highly outperforms the game development pipeline performance of the developers. Thus, this study is an initial attempt of a game generator which bridges the CBRNe practitioners and game developers to transform real-life training scenarios into video games efficiently and quickly.

URI

https://arxiv.org/abs/1911.07380
https://hdl.handle.net/11511/70584

Collections

Graduate School of Informatics, Article

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Citation Formats

E. Sürer et al., “Developing a Scenario-Based Video Game Generation Framework: Preliminary Results,” 2019, Accessed: 00, 2021. [Online]. Available: https://arxiv.org/abs/1911.07380.