HCC-Small: Modeling Student Affect in Game-Based Learning Environments

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Because of the growing recognition of the role that emotion and motivation play in learning, affective computing has become the subject of increasing attention in research on interactive learning environments. Narrative-centered learning environments, which are game-based learning environments where learning activities play out in dynamically generated interactive narratives, afford great opportunity for exploring computational models of student affect. The project will explore student affect modeling through the design, implementation, and evaluation of affect models for game-based learning environments. It will develop 1) affect recognition technologies to predict students' affect states, recognize engagement and flow, and detect frustration, and 2) affect expression technologies to customize pedagogical activities and dynamically plan the empathetic responses of the virtual agents in the learning environment. All design, implementation, and evaluation activities will be carried out in Crystal Island, a narrative-centered game-based learning environment for biology.The project will determine precisely which affect modeling techniques best close the 'affective loop' and contribute most effectively to student learning effectiveness and motivation. It is expected that the project will have a significant impact on the theory and practice of educational technology. Because of the multidisciplinary nature of the research objectives, the project will produce significant advances in computational models of affect recognition and affect expression. It is anticipated that the resulting computational models of student affect and the cognitive account of affect-informed interaction in game-based learning environments will create new learning environment technologies that promote high levels of achievement and find broad application in science education.