A Predictive Model for Analyzing Students’ Satisfaction in Online Education System

The outbreak of the COVID-19 pandemic triggered the biggest overnight shift in the mode of education in India from classroom teaching to online teaching. Around 250 million Indian students and their teachers were counting on online education for the continuation of their studies. Several studies have attempted to investigate the impact of online modes of learning on the student’s performance and well-being. Yet, there is a sparsity of empirical studies which deal with this area comprehensively. The theoretical framework and conceptual model explaining the interplay between the predictors are needed to study this domain. Adopting the Technology Acceptance Model, the study presents a predictive model to examine the impact of different factors associated with online education on students’ satisfaction. The study applies partial least squares structural equation modeling (PLS-SEM) with the help of SmartPLS (Version 3.3.3) owing to the nature of the constructs and complexity of the conceptual model. This model intends to guide future researchers in the area of online education and direct the policy and practice in devising technological and pedagogical solutions. However, this research paper studies the students’ perspective and other stakeholders’ perspectives remain unexplored.