• Om Murhekar
• Smit Joshi
• Snehal Yadav
• Piyush Shinde
• Prof. R. T. Waghmode

This research explores the implementation and effectiveness of artificial intelligence systems in creating personalized student learning experiences. By analyzing individual learning patterns, preferences, and performance metrics, AI-powered Instructive stages can powerfully alter substance conveyance, pacing, and appraisal strategies to meet each student's special needs. This paper presents a framework for deploying adaptive learning technologies in educational settings, examines current implementations, and discusses the potential impact on learning outcomes, student engagement, and educational equity. Results from our experimental deployment demonstrate significant improvements in comprehension, retention, and student satisfaction compared to traditional one-size-fits-all approaches.

Artificial Intelligence (AI), Personalized Learning, Learning Path Optimization, Educational Equity, Bayesian Knowledge Tracing, Reinforcement Learning

"Enhancing Personalized Learning Paths Using AI: Experimental Insights", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.d922-d927, May-2025, Available :http://www.jetir.org/papers/JETIR2505454.pdf

"Enhancing Personalized Learning Paths Using AI: Experimental Insights", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppd922-d927, May-2025, Available at : http://www.jetir.org/papers/JETIR2505454.pdf