Dropout Rates of Massive Open Online Courses: Behavioural Patterns

Massive open online courses (MOOCs) have received wide publicity and many institutions have invested considerable effort in developing, promoting and delivering such courses. However, there are still many unresolved questions relating to MOOCs and their effectiveness. One of the major recurring issues raised in both academic literature and the popular press is the consistently high dropout rate of MOOC learners. Although many thousands of participants enrol on these courses, the completion rate for most courses is below 13%. This paper investigates MOOC attrition from several different perspectives. Firstly, we review existing literature relating to MOOC dropout rates, bringing together existing findings on completion rates and analyses of several specific courses, which identify factors that correlate to likelihood of dropout. We provide a meta-analysis of the basic figures on overall dropout rates previously collected to identify relationships between course factors and dropout rates. In addition, the literature is reviewed from a qualitative perspective drawing together findings on the reasons for dropout and methods suggested for resolving or reducing the dropout rate. Secondly, using themes emerging from the initial investigation, we provide a preliminary analysis of data gathered from a Computing MOOC run by the University of Warwick, UK and presented using a Moodle platform. Different aspects of students’ demographic data are examined to see if relationships to persistence exist. An important feature of this course is that it has been run in two different parallel modes (“traditional” MOOC mode with peer support, and “supported” mode with real time, tutored programming labs). This allows direct comparison between the dropout figures for the two different modes. Qualitative information from student evaluations is also considered. Finally, we discuss our findings relating MOOC dropout rates, considering what factors are within the control of a MOOC provider and suggesting the most promising avenues for improvement. Our results indicate that many participants who may be classed as dropouts (for example, because they do not complete the necessary components to gain a certificate) are still participating in the course in their own preferred way (either at a slower pace or with selective engagement). This suggests that the structure of “a course” may not be helpful to all participants and supporting different patterns of engagement and presentation of material may be beneficial.