Enhanced Emotional Intelligence and Decision Making with Generative Artificial Intelligence, Fuzzy Sets, and Intelligent Tutoring Systems

ITSs have achieved significant developments in personalized learning; however, most of the systems are largely focused on cognitive learning and do not consider the emotions of the learners. Such factors as stress, motivation, and frustration are emotional factors, which are strong in terms of the effects on the learning outcomes and decision making. The paper outlines a better emotionally intelligent tutoring system integrating Generative Artificial Intelligence (GenAI), fuzzy set theory and ITS architectures in facilitating the situation aware affect aware decision making. Generative AI is implemented to solve the contextual and implicit emotional hints of the interaction between the learner, and fuzzy logic is implemented to solve the confusion and ambiguity in the emotional states via linguistic reasoning. The adaptive pedagogical interventions are translated into adaptive pedagogy systems based on a fuzzy inference-based decision (adaptive pedagogy) engine that takes emotional insights. The proposed hybrid framework is experimentally evaluated to be superior to the traditional, GenAI-based, and fuzzy-based ITS models regarding the accuracy of emotion intelligence detection and effectiveness of decision-making. The results stress the increased learner active involvement and emotional well-being and flexibility of instructions in favor of the suitability of the offered method in the digital-based learning classrooms of the next generation.

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