Empowering Rural India with Machine Learning: The Impact of Personalized Learning on English Education

This review article explores the impact of machine learning and personalized learning on English education in rural India. With limited access to quality education, rural India is facing several challenges such as a shortage of quality teachers, limited access to resources, and low enrollment rates. The use of technology, specifically machine learning and personalized learning, has the potential to address some of these challenges and improve the quality of education in rural India. This survey focusses on the existing methods, such as the Digital India program and mobile-based learning, and discuss their limitations in terms of personalization and adaptability to individual learning needs. The authors then discuss different techniques that can be used to empower English education in rural India, such as personalized learning plans, analysis of student data, and adaptive learning. While machine learning and personalized learning have the potential to revolutionize education in rural India, there are several challenges that need to be addressed, such as the need for infrastructure, teacher training, and access to technology. In the future, it is important to focus on developing scalable and sustainable models for machine learning and personalized learning in education. Ultimately, the goal should be to provide quality education to all individuals in rural India, irrespective of their socio-economic background, and empower them to achieve their full potential.