Do online courses provide an equal educational value compared to in-person classroom teaching? Evidence from U.S. survey data using quantile regression

Authors

DOI:

https://doi.org/10.14507/epaa.29.5919

Keywords:

Binary outcomes, COVID-19, online education, Gibbs sampling, public opinion, Pew Research Center

Abstract

Education has traditionally been classroom-oriented with a gradual growth of online courses in recent times. However, the outbreak of the COVID-19 pandemic has dramatically accelerated the shift to online classes. Associated with this learning format is the question: what do people think about the educational value of an online course compared to a course taken in-person in a classroom? We address this question and present a Bayesian quantile analysis of public opinion using a nationally representative survey data from the United States. We find that previous participation in online courses and full-time employment status favor the educational value of online courses. We also find that the older demographic and females have a greater propensity for online education. In contrast, highly educated individuals have a lower willingness towards online education vis-à-vis traditional classes. Regional variations in the propensity to value online classes also exist. Besides, covariate effects show heterogeneity across quantiles which cannot be captured using probit or logit models.

Downloads

Download data is not yet available.

Author Biographies

Manini Ojha, O. P. Jindal Global University

Manini Ojha is an Assistant Professor at the Jindal School of Government and Public Policy, O. P. Jindal Global University. She did her Ph.D. in Economics (2018) from Southern Methodist University, Dallas, USA. Her areas of research are Applied Microeconometrics, Empirical Development Economics, Economics of Education, Economics of the Households, Economics of Gender and Labour Economics. She has taught courses in Microeconomics, Macroeconomics, Public Economics, Econometrics, and Statistics in the United States, and India. 

Mohammad Arshad Rahman, Zayed University, UAE and Indian Institute of Technology Kanpur, India

Mohammad Arshad Rahman is an Associate Professor of Finance in the College of Business at Zayed University (Abu Dhabi Campus) and a tenured Associate Professor in the Department of Economic Sciences at the Indian Institute of Technology, Kanpur, India. He did his Ph.D. in Economics (2013) from the University of California, Irvine, USA, and has research interest in Bayesian Econometrics, Quantile Regression, Markov chain Monte Carlo Techniques, and Applied Econometrics. Professor Rahman has taught courses in Economics, Econometrics, Statistics, and Finance in the United States, India, and the United Arab Emirates.

Downloads

Published

2021-06-21

How to Cite

Ojha, M., & Rahman, M. A. (2021). Do online courses provide an equal educational value compared to in-person classroom teaching? Evidence from U.S. survey data using quantile regression. Education Policy Analysis Archives, 29(January - July), 85. https://doi.org/10.14507/epaa.29.5919