THE PERCEPTION OF E-LEARNING QUALITY IN HIGHER EDUCATION: SEM-ANN APPROACH

Abstract

The pandemic resulted in lockdown measures worldwide, which forced humanity to seek online alternatives to almost every human activity, including the education system. This research aims to develop a new integrated model to determine the predictors of the quality of E-learning during the pandemic disruption. This paper provides the development of the traditional approach based on Structural Equation Modelling (SEM) into the prediction method based on the Artificial Neural Network (ANN). This research was conducted on a sample comprising 1,254 students of the University of Belgrade. The results show that Authority initiative had the most important influence and significance in predicting the perception of the Quality of E-learning during the pandemic. At the same time, the Information Security predictor had the most negligible impact. The findings contribute to the raising the academic community and policy-makers awareness to the necessity of dealing with quality in E-education to a greater extent, especially in emergencies such as pandemics. The suggested combination of constructs that predict the Quality of E-learning has never been analysed in previous research by applying SEM-ANN methodology, which represents the additional contribution of this study.