Devi Dhivya, S. and Balakrishna, R. and Selva Banu Priya, T. and Thilagam, T. and Sathya, V. and Anto Gracious, L.A. and Siva Subramanian, R. (2025) Artificial Intelligence in Personalized Education: Revolutionizing Learning Paths and Student Engagement. In: AI, Personalization, Equity, and the Future of Learning. IGI Global, pp. 453-468.
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S. Devi Dhivya SRM Institute of Science and Technology, India R. Balakrishna Vels Institute of Science Technology and Advanced Studies, India T. Selva Banu Priya Panimalar Engineering College, India T. Thilagam Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India https://orcid.org/0000-0002-7657-0726 V. Sathya Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India L.A. Anto Gracious R.M.K. College of Engineering and Technology, India https://orcid.org/0000-0003-2386-9182 R. Siva Subramanian SRM Institute of Science and Technology, Tiruchirappalli, India https://orcid.org/0000-0002-7509-9223 Artificial Intelligence in Personalized Education Revolutionizing Learning Paths and Student Engagement
Education is changing with AI, and the intelligent tutoring, adaptive learning, and recommendation systems are transforming the education based on personalization. This chapter surveys current trends, recent technologies and use cases for what is to come in the future of education. It is using AI driven system to analyze student behavior and provide real time content, quizzes and feedback. Recommendation systems, intelligent tutors, and learning paths take shape due to machine learning; natural language processing enters the picture with intelligent tutors; and reinforcement learning also improves the learning paths. Even with benefits, there are concerns about data privacy, bias, and technical difficulties. That is, advanced AI models, multilinear data and AR/VR may unite to improve personalisation in future. This chapter examines the impact and potential, and even challenges of AI about revolutionizing learning.
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Item Type: | Book Section |
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Subjects: | Computer Science Engineering > Artificial Intelligence |
Domains: | Computer Science Engineering |
Depositing User: | Mr IR Admin |
Date Deposited: | 31 Aug 2025 07:21 |
Last Modified: | 31 Aug 2025 07:21 |
URI: | https://ir.vistas.ac.in/id/eprint/10757 |