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Motivation is an important factor underlying successful learning. Previous research has demonstrated the positive effects that static interactive narrative games can have on motivation. Concurrently, advances in AI have made dynamic and adaptive approaches to interactive narrative increasingly accessible. However, limited work has explored the impact that dynamic narratives can have on learner motivation. In this paper, we compare two versions of Academical, a choice-based educational interactive narrative game about research ethics. One version employs a traditional hand-authored branching plot (i.e., static narrative) while the other dynamically sequences plots during play (i.e., dynamic narrative). Results highlight the importance of responsive content and a variety of choices for player engagement, while also illustrating the challenge of balancing pedagogical goals with the dynamic aspects of narrative. We also discuss design implications that arise from these findings. Ultimately, this work provides initial steps to illuminate the emerging potential of AI-driven dynamic narrative in educational games. 

Simulationist interactive narrative systems allow game makers to craft reactive stories driven by simulated characters and their social dynamics. These systems produce narrative experiences that feel more emergent but may lack a coherent plot structure. We explored how to combine the emergent possibilities of social simulation with a procedural narrative system that affords writers strong authorial control over the plot. We did this by developing a Unity extension called Anansi that helps people create social simulation-driven visual novels. It enables users to inject simulation data into their story dialogue using logical queries and parameterized storylets written using Ink. The paper describes an overview of our extension and how we empower writers to drive narrative progression using cascading social effects from player choices. 

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. 

Choice poetics is a formalist framework that seeks to concretely describe the impacts choices have on player experiences within narrative games. Developed in part to support algorithmic generation of narrative choices, the theory includes a detailed analytical framework for understanding the impressions choice structures make by analyzing the relationships among options, outcomes, and player goals. The theory also emphasizes the need to account for players’ various modes of engagement, which vary both during play and between players. In this work, we illustrate the non-computational application of choice poetics to the analysis of two different games to further develop the theory and make it more accessible to others. We focus first on using choice poetics to examine the central repeated choice in “Undertale,” and show how it can be used to contrast two different player types that will approach a choice differently. Finally, we give an example of fine-grained analysis using a choice from the game “Papers, Please,” which breaks down options and their outcomes to illustrate exactly how the choice pushes players towards complicity via the introduction of uncertainty. Through all of these examples, we hope to show the usefulness of choice poetics as a framework for understanding narrative choices, and to demonstrate concretely how one could productively apply it to choices “in the wild.”