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

TL;DR

This paper introduces a scenario-based game generator that automates mapping emergency training scenarios into serious games, demonstrating improved development efficiency despite higher resource usage.

Contribution

The study presents a novel framework for converting domain-specific emergency training scenarios into serious games, bridging practitioners and developers.

Findings

Game generator outperforms manual development in efficiency

Higher CPU, memory, and rendering times for the generator

Initial step towards automated scenario-to-game transformation

Abstract

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.