DISHCODE: Design of an Educational Game for Computational Thinking Using the Game Development Life Cycle Model

Abstract

The low level of computational thinking (CT) ability among Grade X Vocational School students in branching material is the primary problem underlying this research. This study aims to design an educational game named DISHCODE that systematically develops CT skills through structured branching programming material. The game targets Grade X PPLG students at SMKN 1 Sumedang, West Java, Indonesia. DISHCODE is developed as an extension of Kitchen Chaos, an open-source educational game developed by CodeMonkey, by adapting its culinary world theme and integrating branching code input as the core mechanic. The research employs a Research and Development (R&D) approach using the Game Development Life Cycle (GDLC) model, limited to the pre-production phase. The GDLC process produced five primary design artefacts, namely game mechanics and learning mechanics mapping, a Game Design Document (GDD), use case and activity diagrams, level mapping aligned with CT indicators, and a storyboard. The game comprises four levels of progressively increasing difficulty that map branching sub-topics, starting from single IF, sequential if-then, if-else, and nested if, onto four CT indicators covering decomposition, pattern recognition, abstraction, and algorithm design. Each level employs a distinct input mechanism calibrated to the cognitive demands of its target indicator. The design results indicate that the GDLC framework provides a systematic structure for translating CT-based learning objectives into coherent game design artefacts, and that DISHCODE's mechanic-indicator alignment positions it as a prospective structured medium for developing and reflecting students CT competency through gameplay, pending empirical validation in future implementation stages. These findings suggest that DISHCODE has the potential to offer teachers a ready-to-use game-based learning instrument that maps branching sub-topics directly onto CT indicators, enabling more structured and measurable CT instruction within vocational programming classes, and to provide learners with a progressively scaffolded gameplay experience that trains decomposition, pattern recognition, abstraction, and algorithm design through contextual branching problem-solving.