Regression Based Modelling to Predict the Undergraduate Students Performance After Pandemic in Educational Institutions

Authors

  • P. Ravi Prakash Assistant Professor, Department of Information Technology, PVP Siddhartha Institute of Technology, Vijayawada, Andhra Pradesh, India.
  • R.S.V. Rama Swathi Assistant Professor, Department of MBA, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India.
  • Naveenkumar Anbalagan Assistant Professor, Department of Information Technology, Sona College of Technology, Salem, Tamil Nadu, India.
  • Manjula Pattnaik Associate Professor, College of Business Administration, Princess Nourah Bint Abdulrahman University, Riyadh, KSA.
  • Alaparthi Maruthi Varaprasad Associate Professor, Department of Accounting and Finance, College of Business and Economics, Ambo University, Ambo, Ethiopia, East Africa.
  • Pavan Kumar Yadavalli Professor, Department of Special Needs and Inclusive Education, Institute of Education & Behavioral Sciences, Ambo University, Ambo, Ethiopia, East Africa.

Keywords:

Linear regression, machine learning, student performance, educational institutions

Abstract

The linear regression model was utilized as our major tool for doing forecasting. A regression model is a technique that is used in statistical analysis and may be used to make inferences about the trend of data. This technique can be used to create predictions about the data. The LR model is applicable and useful in a wide variety of contexts and circumstances. This model has seen widespread use due to the ease with which it can be implemented and the benefits it provides in terms of creating accurate projections of academic accomplishment. In this paper, regression-based modelling to predict the performance of undergraduate students after pandemic in educational institutions is developed. The model is conducted by the combination of various machine learning algorithm with regression model. The simulation shows an improved rate of accuracy in predicting the students’ performance in face-to-face mode than the existing online mode. The results further reveal an improved performance of students post pandemic era than during the pandemic.

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Published

05.12.2023

How to Cite

Prakash, P. R. ., Swathi, R. R. ., Anbalagan, N. ., Pattnaik, M. ., Varaprasad, A. M. ., & Yadavalli, P. K. . (2023). Regression Based Modelling to Predict the Undergraduate Students Performance After Pandemic in Educational Institutions. International Journal of Intelligent Systems and Applications in Engineering, 12(7s), 57–66. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4029

Issue

Vol. 12 No. 7s (2024)

Section

Research Article

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