The World, Storytelling, and Interactivity

Optimal human learning occurs when we engage with narratives, as our cognition inherently processes events as stories (Baldassano et al. 2017). Furthermore, a proper narrative does not merely explain but engages its audience (McCormack, Martin, and Williams 2021; Bellini 2022). Enhancing the strengths of narratives with interactivity, interactive digital narratives (IDNs) are potentially the ultimate learning medium. However, no model of IDN systems exists that supports human learning and is sufficiently general for various use contexts. Thus, we propose such a model. Learning comprises cognitive, affective, and sensorimotor domains (Dettmer 2005), which must be equally mobilized. Feelings like intrigue and boredom strongly influence our mental processes (Mangaroska et al. 2022). Moreover, we can learn through sensorimotor activities (Abrahamson and Mechsner 2022), such as using hand movements to better understand mathematical concepts (Abrahamson 2021). Sensory signals enter our senses to update our understanding of the world, while our brain commands our body to modify the world (Andersen et al. 2023). Additionally, a significantly positive emotion toward something allows us to comprehend it more deeply (Sarasso et al. 2020), while a piece of knowledge that excites or terrifies us is much more likely to trigger our actions (Ransom et al. 2020). The domains and their interactions align with the information, narrative, and interactivity aspects of IDNs (Atmaja and Sugiarto 2022), the former two corresponding with the story world and storytelling, respectively (Kybartas and Bidarra 2017). Currently, IDN models covering these aspects are only found in specific contexts, such as data storytelling (El Outa et al. 2020). Therefore, there remains a lack of general-purpose learning-minded IDN models. Figure 1 shows our IDN system model consisting of three subsystems. The world subsystem consists of a world model, a cognitive model, and a source system, the latter storing “raw data” from the real world. The cognitive model, which represents the audience’s cognitive needs, instructs the translation of the source system, such as by reducing its complexity, into the world model. The world model is taken into the next subsystem, which may change the world model’s structure following a model of the audience’s affective needs. The overall event sequence may undergo a reshuffle; some entities in each event may stand out more or be less pronounced; and non-diegetic elements may even come into play. Afterward, the storytelling model transforms further into the sub-subsystem of interactivity mechanics with the help of the audience’s sensorimotor model. Such a transformation may simplify the storytelling, such as turning real-time events discrete to make them less chaotic. Finally, the sensory-appropriate story is presented as sensory-appropriate assets through a sensorimotor-appropriate UI. We will describe a hypothetical IDN design as an instance of our model. We will also discuss synergies between our model and three prominent IDN-related models: the SPP model (Koenitz 2023), the MDA model (Hunicke, Leblanc, and Zubek 2004), and the GFI model (Cardona-Rivera, Zagal, and Debus 2023).

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