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Higher education has invested in online course delivery for years, and the investment is increasing. Many colleges, universities, and state legislatures are well on their way to responding to enrollment problems with MOOCs. Given the pressure to leverage this solution, it is vital to understand who is actually taking MOOCs, identifying their motivations, participation, location and behavior, and sorting out the factors contributing to and discouraging their productive participation.
Because official statistics are not yet published for every MOOC, data is developmental. Phil Hill, an education technology consultant, and Katy Jordan, a Ph.D. student at Open University, have been actively researching, compiling, and publishing this data. Hill identifies five categories of MOOC participants and provides information on their behavior and activities:
- No-Shows, who register but never log in to a course while it is active, appear to be the largest group of those registering for Coursera-style MOOCs.
- Observers, who log in and may read content or browse discussions but do not take any form of assessment beyond pop-up quizzes embedded in videos.
- Drop-Ins, who perform some activity (watch videos, browse, or participate in a discussion forum) for a select topic within the course, but do not attempt to complete the entire course. Some of these students are focused participants who use MOOCs informally to find content that help them meet course goals elsewhere.
- Passive Participants, who view a course as content to consume. They may watch videos, take quizzes, read discussion forums, but generally do not engage with the assignments.
- Active Participants, who fully participate in the MOOC and take part in discussion forums, the majority of assignments and all quizzes and assessments.
Figure 3-1: Enrollment patterns
One hallmark of the discourse on MOOCs is the emphasis on numbers. Massive MOOC enrollment figures are reminiscent of the eyeballs-on-web-pages “metrics” of the 1990s dot.com boom in the way they are used to stir imagination and controversy, and raise money and expectations.
An impressive enrollment figure of one hundred eighty thousand is often cited as the largest MOOC ever. But an initial enrollment of fifty thousand is typical, as is a ninety percent dropout rate.
As Hill notes, most enrolled individuals do not participate beyond watching a video or two before abandoning the course by its second week. Jordan compiled a sampling of data from twenty-four MOOCs—nineteen from Coursera, three from edX, one from Udacity and one from MITx (precursor to edX)—concluding that a completion rate of less than ten percent is typical. The average completion rate of Coursera-style xMOOCs is 7.6 percent, with a minimum of 0.67 percent and a maximum of 19.2 percent.
While comparing enrollment numbers to completion rates is eye-catching, the dramatic discrepancy between the two does not provide useful decision-making data for colleges and universities. It is not the best measure of MOOC engagement in the context of higher education, for one simple reason: MOOCs in their current iteration are not “college courses” in the traditional model, with prerequisites, tuition, textbook fees, and grades that lead to credit and credentials. Rather, MOOCs are open to the world and attract a variety of participants with different objectives: ambitious high school students, students in traditional classes using MOOCs as reference sources for coursework elsewhere, and curious citizens using MOOCs like a public library. It is not enough simply to find the difference between enrollments and completions. It will be far more interesting and strategically valuable to better understand who takes MOOCs, what their relationship is to traditional education systems, and what motivates them to register for and complete online education programs.
 Phil Hill, “Emerging Student Patterns in MOOCs: A Graphical View,” e-Literate, March 6, 2013, http://mfeldstein.com/emerging_student_patterns_in_moocs_graphical_view/.