Development of Machine Learning Based Framework for Classification and Prediction of Students in Virtual Classroom Environment
B. Loganathan, Indrajit Patra, Vipul Garchar, Harikumar Pallathadka, Mohd Naved, Sanjeev Gour
Abstract
MOOCs provide a new way to train students, reshape the way students learn, and attract students from all over the world to participate in their courses. Machine learning is a key component of artificial intelligence. Machine learning may be used to classify and predict outcomes. In order to aid the underachieving or average student, educational institutions need to know how much work they need to put in. The importance of EDM models can't be overstated, since they make use of past student performance data to forecast future student success. Educational institutions utilize a variety of methods to collect data on the characteristics of students who are actively involved in the learning process in order to help them and their pupils improve their performance. In a virtual classroom, pupils may be classified and predicted using the methodology presented in this article.