Our demo showcases a choice-based interactive narrative game created to teach responsible conduct of research and research ethics. It re-imagines the experience of a game previously published in the literature, using a content-selection system that dynamically constructs dialogue choices during play. Our goal is to provide players with more opportunities to experience agency than they would have with the original game’s hand-authored branching narrative structure. Primarily, our system implements a conversation thread-switching mechanic that allows players to fluidly enter/exit conversation topics as one would in a real-life conversation.

Visual novels are a popular game genre for educational games. However, they often feature pre-authored plot structures that cannot dynamically adjust to the player’s progression through learning objectives. Employing procedural storytelling techniques boosts plot dynamism, but this comes at the cost of needing a larger repository of content (dialogue and images) to support different learning progressions and objectives. In this paper, we present postmortem-style case studies describing the lessons we learned from attempting to integrate large-language models (LLMs) and text-to-image models into the development of an educational visual novel about responsible conduct of research. Specifically, we discuss our experiences employing generative AI in our dialogue, character sprite, and background image creation processes.