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This design case explores how an AI-supported, narrative-centered science learning game (SciStory: Pollinators) was designed over multiple iterations to support middle schoolers’ socioscientific learning, engagement, and persuasive writing. The case highlights how AI-driven conversational agents were designed to support student-led socioscientific inquiry, and the tensions our team explored as we integrated agents into a story game about community food systems, pollinators, and neighborhood land use. 

This study investigates the implementation of a classroom response system in STEM education in a higher education context. The study used ExplainIt, a web-based classroom response system designed to support students’ self-explanations and provide instant feedback. Data were collected from 32 undergraduate students using four instruments including demographic information, self-efficacy, engagement, and system evaluation. The results showed that students reported positive learning experiences, demonstrated increased self-efficacy in STEM content, and indicated high levels of engagement following their use of ExplainIt. 

Interactive narrative in games utilize a combination of dynamic adaptability and predefined story elements to support player agency and enhance player engagement. However, crafting such narratives requires significant manual authoring and coding effort to translate scripts to playable game levels. Advances in pretrained large language models (LLMs) have introduced the opportunity to procedurally generate narratives. This paper presents NarrativeGenie, a framework to generate narrative beats as a cohesive, partially ordered sequence of events that shapes narrative progressions from brief natural language instructions. By leveraging LLMs for reasoning and generation, NarrativeGenie, translates a designer’s story overview into a partially ordered event graph to enable player-driven narrative beat sequencing. Our findings indicate that NarrativeGenie can provide an easy and effective way for designers to generate an interactive game episode with narrative events that align with the intended story arc while at the same time granting players agency in their game experience. We extend our framework to dynamically direct the narrative flow by adapting real-time narrative interactions based on the current game state and player actions. Results demonstrate that NarrativeGenie generates narratives that are coherent and aligned with the designer’s vision.