INTELLIGENT ADAPTIVE SYSTEMS FOR PERSONALIZED EDUCATION: A NEURO-FUZZY APPROACH

Neuro-fuzzy models, integrating the adaptive learning capabilities of neural networks with the interpretability of fuzzy logic systems, have emerged as powerful tools in educational data mining. This research explores the application of neuro-fuzzy models in education, focusing on their role in predicting student performance, classifying academic outcomes, and enhancing personalized learning experiences. By analyzing various case studies and methodologies, this study highlights the effectiveness of neuro-fuzzy systems in handling the inherent uncertainties and complexities of educational data.