GREEN RENOVATOR: A SERIOUS GAME FOR AWARENESS-RAISING IN SUSTAINABLE URBAN ENERGY MANAGEMENT AND BUILDING RETROFITS

Date

2025-8-28

Author

Ozan, Ali

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This thesis presents Green Renovator, a serious game designed to raise public awareness of city-scale energy management grounded in a real neighborhood dataset. Following a width-over-depth design philosophy, the game puts the player in the shoes of a local authority that is responsible for building retrofit investments, energy supply mix choices, technology adaptations, policy instruments, and public response. It integrates these into a single, comprehensible gameplay loop. Uncertainty and a higher replay value are introduced through a random-event system that models realistic shocks and frictions. At the same time, an in-game encyclopedia and an optional yearly quiz help with reflection and self-directed learning. The game was evaluated with N = 55 participants using a mixed-methods protocol: the System Usability Scale (SUS), a purpose-built awareness and perceived-learning questionnaire, and a complementary engagement/usability questionnaire, alongside open-ended prompts for qualitative insight. Results indicate acceptable-to-good usability and consistently positive outcomes across all three instruments, with many effects statistically meaningful. Thematic analysis of open-ended responses suggests that players recognized interdependencies among retrofit decisions, energy supply choices, governance tools, and citizen reaction, and highlighted opportunities for expanding event diversity and policy depth in future versions. Overall, the study offers a practical design for awareness-oriented, city-scale simulation and an evaluation showing educational promise. The findings support the claim that thoughtfully scoped, replayable simulations can make the complexity of urban energy decisions tangible for non-experts while remaining pedagogically effective.

Subject Keywords

Serious Games, Game-Based Learning, Urban Energy Efficiency, UN SDGs

URI

https://hdl.handle.net/11511/115604

Collections

Graduate School of Informatics, Thesis