Smart Learning Paths: Enhancing Education with Machine Learning Sentiment Analysis


  • Milind Rane, Bilal A. Ozturk, Hemant Nipse, Mahmoud Jamil Salem, Hrutik Shinde


Academic Courses, Machine learning, Sentimental Analysis


The post-COVID surge in E-learning led to the need for a robust recommendation system due to the overwhelming number of online courses. Our proposed solution integrates Smart learning paths with advanced web scraping, machine learning, and sentiment analysis to extract comprehensive information from diverse platforms. Smart Learning paths adapts to the dynamic E-learning landscape, offering nuanced insights through quantitative metrics and qualitative sentiment analysis. Rigorous real-world experiments validate its effectiveness, making it a beacon of innovation in reshaping how users navigate and select personalized pathways in online education. The integration of web scraping, machine learning, and sentiment analysis ensures adaptability to evolving needs, transcending traditional metrics and prioritizing user experience.


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How to Cite

Milind Rane. (2024). Smart Learning Paths: Enhancing Education with Machine Learning Sentiment Analysis. International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 3472 –. Retrieved from



Research Article