Abstract: In the rapidly evolving environment of online education, personalized learning experiences have become the cornerstone for improving student engagement and performance. However, the abundance of educational resources available on online learning platforms presents a significant challenge to students in identifying and using content that meets their individual needs and preferences.
To address this challenge, this project proposes to develop a new machine learning-based recommendation system specifically adapted for e-learning platforms. Using advanced algorithms and user data, the system aims to provide personalized recommendations that match individual learning goals, skill levels and preferences. By analyzing user interactions and behavior patterns, the system identifies and reveals the most relevant and useful resources for each learner, facilitating more effective and engaging learning. This project represents a pioneering effort to harness the power of machine learning to revolutionize the world of online education, enabling learners to reach their full potential in a dynamic and adaptive learning environment.
Cite:
Ms.R.ARTHI, SHIYAM GANESH.S,"PERSONALIZED ONLINE LEARNING PLATFORM RECOMMENDATION USING MACHINE LEARNING", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 13, no. 3, 2024, Crossref https://doi.org/10.17148/IJARCCE.2024.133149.
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DOI:
10.17148/IJARCCE.2024.133149
