A Study on Personalized Learning Experience through AI-driven User Profiling in E-learning Platforms - Abdul Wahid, Mohd Yousuf Khan, Mohd Yousuf (International Journal of Intelligent Systems and Applications in Engineering, 2024)
This research delves how e-learning systems may use artificial intelligence (AI) methods to provide students with more tailored lessons. Less engagement and effectiveness are common outcomes of using traditional e-learning systems because of their inability to adapt to the demands of various learners. This project seeks to improve e-learning systems through the use of AI-driven user profile in order to provide personalised content, resources, and learning pathways to each user. The creation and deployment of an advanced AI system that can study user habits, tastes, and patterns of learning. The algorithm generates unique user profiles by collecting and analysing vast amounts of data; this allows the system to provide tailored suggestions and adaptive learning opportunities. Using measures for user engagement, learning results, and satisfaction surveys, the study assesses the efficacy of the AI-driven personalised learning strategy. When compared to more conventional, cookie-cutter methods, the results show that this one works far better in terms of student engagement, information retention, and happiness. The development of better e-learning tools by proving that user profile powered by AI can lead to more tailored and efficient education. Educators, instructional designers, and developers may use the findings to make online education more effective and accessible.