Potential for Game-based Assessment of Creativity using Biometric and Real-time Data
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This study explores the development of a game-based creativity assessment model usingbiometric and real-time data. By integrating game learning analytics (GLA) with neuroscienceapproaches such as functional near-infrared spectroscopy (fNIRS), the goal of this research isto provide a comprehensive, process-oriented approach to creativity. The study emphasizesthe importance of social and affective dimensions of creativity, moving beyond traditionalcognitive-focused models. By analyzing log data, social network interactions, and biometricfeedback, the study highlights how these dimensions influence creative outcomes. Theresults demonstrate the effectiveness of using GLA to provide personalized and adaptivefeedback, fostering a deeper understanding of creative processes and improving educationalpractices.
Abstract
This study explores the development of a game-based creativity assessment model usingbiometric and real-time data. By integrating game learning analytics (GLA) with neuroscienceapproaches such as functional near-infrared spectroscopy (fNIRS), the goal of this research isto provide a comprehensive, process-oriented approach to creativity. The study emphasizesthe importance of social and affective dimensions of creativity, moving beyond traditionalcognitive-focused models. By analyzing log data, social network interactions, and biometricfeedback, the study highlights how these dimensions influence creative outcomes. Theresults demonstrate the effectiveness of using GLA to provide personalized and adaptivefeedback, fostering a deeper understanding of creative processes and improving educationalpractices.
참고문헌 (42)
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