Online education – bane or boon? A quantitative plus text mining approach

Purpose The COVID-19 pandemic and its aftermath sent the entire educational system across the globe topsy-turvy. Virtual classrooms, online lectures and online evaluations became the order of the day, replacing traditional face to face classroom interactions and examinations conducted physically. While it may be possible to reach out to a larger audience in remote places via online platforms, the new medium lacks personal touch of the past, and is known to cause physical and psychological problems for participants. This study collects primary data from a representative sample of students from emerging economies to study the factors that influence intention to pursue online education. Design/methodology/approach ANOVA, Kruskal–Wallis test, exploratory factor analysis (EFA) and multiple linear regression (MLR) have been used to test our hypothesis. We have also used text mining to corroborate statistical test results and ascertain the sentiment of students towards online learning. Findings This study not only confirms findings in extant literature that “benefits” is an important factor. It also identifies new factors such as “health”, “evaluation”, “class duration” and “student qualification”, that influence student intention to pursue online education. Sentiment analysis shows that students have positive sentiment coupled with trust towards online education. Text mining shows that “mode of class”, “time or duration of class” and “quality of learning” are important features that students consider. Originality/value This is one of the few studies to use quantitative plus text mining method of research to understand intention to pursue online education.