AI-Powered Recommendation System for Personalized Course and Mentor Selection

Harividhya S; Angelinrosy M

doi:10.36948/ijfmr.2025.v07i03.47639

AI-Powered Recommendation System for Personalized Course and Mentor Selection

Author(s)	Harividhya S, Angelinrosy M
Country	India
Abstract	Online courses have revolutionized the education landscape, providing students with the flexibility to learn at their own pace and access a wide range of topics from anywhere in the world. However, traditional online course and mentor recommendation systems face several challenges. These systems typically rely on basic factors such as course descriptions, ratings, and reviews, but fail to offer personalized or contextually relevant suggestions. As a result, students may find it difficult to navigate through a plethora of courses, and mentors, who are crucial to a student’s learning journey, are often not appropriately matched. This leads to inefficiencies in the course selection process and poor student engagement due to irrelevant or generic recommendations. To overcome these issues, this project proposes an innovative recommendation system for both online courses and mentors, incorporating Natural Language Processing (NLP) and deep learning techniques, particularly Lexicon-Enhanced Long ShortTerm Memory (LSTM). The system is designed to analyze large datasets of course and mentor reviews, as well as course content, to provide more accurate, personalized recommendations. By applying sentiment analysis, the system processes nuanced feedback from students to identify specific course attributes and mentor qualities that align with a learner’s needs, preferences, and academic goals. This not only enhances the matching process for courses but also recommends mentors whose expertise and teaching styles complement the student’s learning preferences. The model considers factors like student goals, learning styles, and past performance to suggest courses and mentors who can provide a tailored educational experience. This personalized approach ensures that students receive relevant course and mentor suggestions, fostering a more effective and satisfying learning experience.
Field	Computer Applications
Published In	Volume 7, Issue 3, May-June 2025
Published On	2025-06-14
DOI	https://doi.org/10.36948/ijfmr.2025.v07i03.47639
Short DOI	https://doi.org/g9qp39

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AI-Powered Recommendation System for Personalized Course and Mentor Selection

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