2 Years Impact Factor:
2.85
5 Years Impact Factor: 1.53
Author: Rachith Reddy. K, Prakash . P, G.Gowthmi
Abstract:
E-learning has evolved significantly since the early 2000s, transitioning from static web-based courses to interactive, multimedia-rich platforms. Traditional online learning systems primarily relied on linear content delivery without adapting to individual learner needs. Recent advancements in technology have paved the way for more adaptive and intelligent learning environments. The title "Harnessing Machine Learning for Comprehensive Evaluation of Next-Generation E-Learning Systems" signifies the integration of advanced machine learning techniques to assess and optimize modern e-learning platforms. It highlights the focus on using data analysis to refine teaching methods and enhance student engagement and performance. The objective of this project is to evaluate the effectiveness of next generation e-learning systems using machine learning techniques. It aims to enhance personalized learning experiences and improve educational outcomes through data-driven insights. Tra
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