Advancement: Process Visualizations to Enhance Self-Regulated Learning in Complex Games

Erica Kleinman
Computational Media PhD Student
Virtual Event
Dr. Magy Seif El-Nasr

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Description:  Complex games, those with multiple correct strategies and unpredictable outcomes, are seeing increased popularity and integration into high-impact domains such as health, education, and training. Further, even in entertainment contexts, these games have proven benefits for players. The steep learning curves, however, make the games inaccessible to many players and risk rendering them ineffective in serious domains. To address this, we need better ways to support players' ability to learn on their own. In this dissertation research, I investigate learning in complex gameplay from the perspective of the cyclical phase model of self-regulated learning. Based on the results of my prior research, I propose using process-visualizations during self-reflection to support learning of complex gameplay. In this advancement, I first present my prior and ongoing research on how players learn and master gameplay and how computational tools support these processes. I follow this with a proposal to examine how process-visualizations can enhance self-reflection and learning in complex gameplay.