Interactive narratives are frequently designed for learning and training applications, such as social training. In these contexts, designers may be inexperienced in storytelling and interaction design, and it may be difficult to quickly build an effective experience, even for experienced designers. Designers often approach this problem through iterative design. To augment and reduce iteration, we argue for the utility of employing models to reason about, evaluate, and improve designs. While there has been much previous work on interactive narrative models, none of them capture aspects of the interaction design necessary for testing and evaluation. In this paper we propose a new computational model called Progression Maps, which abstracts interaction design elements of the narrative's structure and visualizes its interaction properties. We report on the model, its implementation, and two studies evaluating its use. Our results demonstrate Progression Maps' effectiveness in communicating the underlying design through an easily understandable visualization.
https://doi.org/10.1145/3313831.3376527
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)