Implementing Affect Parameters in Personalized Web-Based Design
Researchers used to believe that emotional processes are beyond the scope of a scientific study. Recent advances in cognitive science and artificial intelligence, however, suggest that there is nothing mystical about emotional processes. Affective neuroscience and psychology have reported that human affect and emotional experience play a significant, and useful, role in human learning and decision making. Emotions are considered to play a central role in guiding and regulating learning, performance, behaviour and decision making, by modulating numerous cognitive and physiological activities. Our purpose is to improve learning performance and, most importantly, to personalize web-content to users’ needs and preferences, eradicating known difficulties that occur in traditional approaches. Affect parameters are implemented, by constructing a theory that addresses emotion and is feasible in Web-learning environments.
Keywordsaffect emotions mood disposition regulation personalization decision-making learning
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