International Journal of Science, Engineering and TechnologyAuthors: Triveni Rathod, Dr. S. T. Khandare
Abstract: Traditional educational systems employ standardized pedagogical frameworks that exhibit significant limitations in accommodating the diverse cognitive capabilities and learning preferences of modern learners. This paper presents an extensive survey exploring the integration of Generative Artificial Intelligence (GenAI) and Adaptive Artificial Intelligence (Adaptive AI) techniques for developing personalized learning environments. The study systematically reviews existing methodologies leveraging Machine Learning (ML) and Reinforcement Learning (RL) approaches—particularly Markov Decision Process (MDP) and Q-learning algorithms—for adaptive content delivery, learner modeling, and sequential learning optimization. It also examines recent advancements in Generative AI that facilitate dynamic content generation and individualized feedback in real time. By analyzing multiple frameworks, models, and pedagogical applications, this survey identifies emerging trends, key challenges, and potential research directions in adaptive and generative AI-driven education. The findings underscore that the synergy of adaptive and generative intelligence can transform conventional instruction into an intelligent, learner centered, and continuously evolving educational paradigm.
DOI: http://doi.org/10.5281/zenodo.17617669
