Factors affecting High Attrition Rate of MOOCs and its Prediction using Machine Learning Techniques

The realm of education is undergoing a profound transformation, catalyzed by the rapid advancements in technology and the growing needs of learners. In this dynamic landscape, Massive Open Online Courses (MOOCs) have emerged as a transformative force, redefining traditional educational paradigms and democratizing access to knowledge. MOOCs offer a promising avenue for learners across the globe to engage with high-quality educational content, transcending geographical and socio-economic barriers. As a result, they have garnered widespread attention for their potential to revolutionize the way education is delivered and consumed. However, alongside the remarkable promise of MOOCs, there also exists a critical challenge that has garnered attention from researchers, educators, and policy makers alike - the issue of high attrition rates within these online learning platforms. The allure of open access and flexibility that MOOCs offer is often accompanied by the concern of learners not completing the courses they enroll in. This challenge poses questions about the effectiveness of MOOCs in engaging learners and delivering meaningful learning expenences. This chapter serves as the gateway to an in-depth exploration of the multifaceted landscape of MOOCs and their challenges. It provides an overarching framework for understanding the research that follows, offering a comprehensive view of the issues, opportunities, and complexities inherent to the realm of online education and MOOCs. By navigating through the historical development of MOOCs, exploring the intricate factors contributing to attrition, and delving into the possibilities offered by artificial intelligence and machine learning, this chapter lays the foundation for unravelling the tapestry of MOOC attrition.