INTELLIGENT MUSIC RECOMMENDATION FOR CLASSROOM LEARNING
DOI:
https://doi.org/10.29121/shodhkosh.v6.i1s.2025.6618Keywords:
Intelligent Music Recommendation, Classroom Learning, Machine Learning, Personalized Education, Cognitive EnhancementAbstract [English]
Enhancing the brain involvement, attention, and memory of students has been proven to be very feasible with the introduction of music for classroom learning environments. This research proposes for Intelligent Music Recommendation System (IMRS) which can be used to change the background music according to the state of the brain, tasks and tastes of trainee. A mixed method is used for the study, which consists of a combination of quantitative analysis of learning success measures and personal reviews of student experience. Machine learning and deep learning algorithms, Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), K-Nearest Neighbours (KNN) and Support Vector Machines (SVM) are adopted in the proposed system to look at the music features and guess the best soundscapes for different learning situations. Information about each student, such as age, subject, attention level and mood is combined with information about the environment to make personalised music suggestions. To ensure that they meet the needs for cognitive load, music files are processed for the purpose of emotional mapping, feature extraction and tag extraction. When compared to traditional background music methods that don't change, the IMRS framework is judged on how well it helps people to focus, relax and remember things. The consequences of the predicted results for the educational experience demonstrate the usefulness of AI-driven personalisation in educational contexts by showing how smart music selection can help students do better in school and be happier with their lives. This is a new combination of artificial intelligence, music psychology and educational technology, which has made learning more fun and more effective in the modern day world.
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Copyright (c) 2025 Navnath B. Pokale, Kanika Seth, Dikshit Sharma, Dr. M D Anto Praveena, Dr. Vineet Kumar, Mr. Sanjay Kumar Jena
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