Education 4.0: Classification of Student Adaptability Level in E-Education

In India, online education is an important part of the educational system, but it grew even more popular during the Covid 19 epidemic since schools and universities were closed after March 2020. Students benefit from online instructions since they may record lectures and watch them as many times as necessary to grasp the material. However, the application of this technology in the sphere of education presents obstacles and ethical issues. Artificial Intelligence's prospects, advantages, and problems in education is be examined in this research. Several researches have shown that pupils might be hindered by online education, despite its widespread appeal and effectiveness. This study examines whether or not students are accepting of technology in the classroom. This article uses machine learning algorithms to classify the adaptability level of pupils. To predict the amount of student adoption of Industry 4.0 capabilities, we used a variety of machine learning techniques. With 93% classification accuracy, neural network and random forest techniques were shown to be the most effective.