Predictors of Massive Open Online Courses (MOOC) Learning Satisfaction: A Recipe for Success

Abstract

Massive Open Online Courses (MOOCs) have recently gained great attention. However, the biggest challenge to the success of MOOCs is their low completion rate. During the lockdown of the COVID-19 pandemic, MOOCs were in high demand by many higher education institutions to replace their face-to-face lessons. MOOCs have great potential to grow and reinvent the way of learning in the 21st century. This study uses the Virtual Learning Environment (VLE) effectiveness model to understand how the five key factors (learner, instructor, course, technology system, and interactivity) influence student learning satisfaction from a holistic approach and determine the best predictor of student learning satisfaction in the MOOC learning environment. A set of online data based on a 5-point Likert scale was collected from 333 undergraduate students from the top five public universities in Malaysia whose students are actively using MOOCs in their learning. The Partial Least Squares Structural Equation Modelling (PLS-SEM) technique was used to analyse the data. The empirical results revealed that all factors significantly influence student learning satisfaction positively. Learner and interactivity factors were the strongest predictors in determining student learning satisfaction in MOOCs. These findings provide an empirically justified framework for developing successful online courses such as MOOCs in higher education.