Comparison of Pre and Post Covid Education System and Evaluation of Student Performance

ABSTRACT

India is one of the best countries which follows the conventional education system and forces the student to learn the subjects by attending the classes directly. The normal education system in the country has changed at the starting of February 2020, when the government confirmed the first case of coronavirus infection in India. The schools were suspended suddenly and the situation continued for a few months. But the government found a solution that the students who are not permitted to go to class can pick an online training framework. This research is mainly for comparing the pre and post covid education system and evaluation of the student performance using machine learning techniques such as Artificial Neural Network (ANN), Logistic Regression, and Naïve Bayes. The prediction algorithms are focus on the attributes such as understandability of subject topics, internal assessment, level of concentration, language proficiency, and percentage of marks in the main exam during regular class and online class. The prediction model compares the attributes and predicts either the regular class or the online class increases the student’s performance. The dataset for research is collected mainly from graduation and post-graduation students through Google form due to the pandemic. ANN is the model that gave a higher accuracy rate of 0.95. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.