Bridging Social Science with Artificial Intelligence Fuzzy Framework Smart Pedagogy for bright minds in Decision Making Process
Аннотация
The growing sophistication of social, economical, and behavioral problems requires pedagogical frameworks with the capacity to strengthen analytical thinking and decision-making skills. Conventional social science education costs frequently depend on a linear and deterministic approach to evaluation which is not responsive to uncertainty, subjectivity and cognitive diversity of human learning. In this research, it is proposed to use empirical machine learning-based fuzzy artificial intelligence structure to assist smart pedagogy in social science teaching. The architecture combines monitored ML algorithms with the fuzzy logic to capture learner thinking, interaction, and reasoning behaviors, therefore, facilitating instructive decision support. Data collected among the students of undergraduate social sciences were experimentally evaluated based on classification and prediction models with a fuzzy inference system. Findings show that the suggested ML-fuzzy smart pedagogy provides much more efficient solutions in decision making, critical thinking, and application of concepts when compared to traditional pedagogical methods. The research also initiates a new field of interdisciplinary research between social science and artificial intelligence, which is explainable and human-based learning systems.