AI-Based Personalized Learning Recommendation System

Computer Science - Artificial Intelligence

Traditional e-learning platforms usually provide the same learning materials to all students, regardless of their individual characteristics and needs. This approach, however, makes learning less personalized and less efficient. A personalized learning system, on the other hand, is capable of addressing the students’ diverse needs and learning patterns by providing recommendations based on their interests, skills, and learning outcomes. This research aims to design an AI-Based Personalized Learning Recommendation System that would be able to analyze student’s personal information, learning outcomes, learning preferences, and skill level to provide individualized suggestions about their learning materials. The proposed system will utilize machine learning algorithms to recommend appropriate courses and address the learners’ needs and skill-level requirements. The recommendation system will also be able to prioritize the suggested learning materials, based on individual skills, utilizing recommendation techniques. The performance of the designed system will be evaluated and validated through experiments using different performance metrics. The experiments’ results are expected to show the effectiveness of the proposed system in meeting students’ needs and enhancing their learning outcomes.

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