An Automatic Deep Learning Model for Student Performance Grading System

Abstract

Academic Sector is providing higher education under public or private organizations to award and certify them based on their level of education. A student is a person who registered in an academic sector. Students in primary and elementary schools are called as pupils. In recent times, due to international collaboration studies, the number of students in all schools and universities is high. Students’ performance prediction becomes one of the most urgent needs in the majority of educational institutions. It is not so easy for all the schools and universities in extracting particular cases. So, it is essential to develop a computer-aided algorithm for the Student Performance Grading (SPG) system which can extract the student's list under different constraints. The main objective of this paper is to implement a deep learning algorithm for handling small to huge-sized student datasets for predicting student performance with high accuracy. The experimental results of the proposed SPG system have proved the efficiency of the deep learning algorithm in terms of training all sized datasets and providing efficient prediction accuracy and reliability test rates.