Personalizing Learning Pathways Through Deep Learning Models and Educational Data Analytics

The aim of this research is to investigate the role of deep learning and educational data analysis in personalizing learning paths. Relying on the capacity of deep learning models to identify behavioral patterns and predict learner performance, it is possible to design learning paths that meet individual needs. In this context, educational data analysis not only helps to improve the quality of education, but also paves the way for the development of adaptive and intelligent learning systems. The research also addresses the technical challenges, ethical considerations, and implementation limitations of this approach and offers solutions for the responsible use of new technologies in education.