Eternagram: Probing Player Atitudes in Alternate Climate Scenarios Through a ChatGPT-Driven Text Adventure

Conventional methods of assessing attitudes towards climate change are limited in capturing authentic opinions, primarily stemming from a lack of context-specifc assessment strategies and an overreliance on simplistic surveys. Game-based Assessments (GBA) have demonstrated the ability to overcome these issues by immersing participants in engaging gameplay within carefully crafted, scenario-based environments. Concurrently, advancements in AI and Natural Language Processing (NLP) show promise in enhancing the gamifed testing environment, achieving this by generating context-aware, human-like dialogues that contribute to a more natural and efective assessment. Our study introduces a new technique for probing climate change attitudes by actualizing a GPT-driven chatbot system in harmony with a game design depicting a futuristic climate scenario. The correlation analysis reveals an assimilation efect, where players' post-game climate awareness tends to align with their in-game perceptions. Key predictors of pro-climate attitudes are identifed as traits like 'Openness' and 'Agreeableness', and a preference for democratic values.