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“Things that can’t last don’t. This is why MOOCs matter. Not because distance learning is some big new thing or because online lectures are a solution to all our problems, but because they’ve come along at a time when students and parents are willing to ask themselves, ‘Isn’t there some other way to do this?'”
~ Clay Shirkey, “How to Save College”
Ultimately, students are not concerned with the distinctions we make about online learning platforms. They look to those of us in higher education to provide an accessible environment in which they can excel and attain their academic objectives. MOOCs must be discussed, planned for, and implemented as an additive component in a broader online learning environment that provides flexibility and choice to students trying to navigate a higher education system in transition.
The 2013 Babson Survey, Changing Course: Ten Years of Tracking Online Education in the United States, confirmed that enrollments in online education are increasing (although retention and completion rates remain low) in the face of declining enrollment in higher education overall. This suggests that MOOCs can develop, even thrive, in the current environment.
An overview of current online learning helps contextualize MOOCs. Over 6.7 million—roughly one third—of all higher education students took at least one online course during the fall 2011 term. This was an increase of 570,000 students over the previous year and a noteworthy increase over 2002’s 1.6 million. Thirty-two percent of higher education students now take at least one course online. More than 70 percent of public and for-profit colleges now offer online academic programs (as opposed to single courses). Roughly half of private nonprofit colleges now offer online programs—nearly double the number doing so in 2002. Other key findings from the report:
- 77 percent of academic leaders rate the learning outcomes in online education as the same or superior to those in face-to-face courses.
- Low completion rates are an obstacle for the growth of online learning.
- 88.8 percent of academic leaders surveyed believe that student discipline in online courses is a barrier to growth, and just over 40 percent believe the same is true regarding acceptance of online degrees by potential employers.
Online learning in all forms is expanding for several reasons, including the growing number of students unable to gain access to classrooms. Campuses are struggling to accommodate the needs of matriculated students unable to register for required classes, transfer to four-year colleges, or maintain eligibility for financial aid. As a result, more college and university systems across the country are considering MOOCs. In addition to hoping to alleviate enrollment issues, many are betting on MOOCs to generate new revenue, reduce the cost of education, decrease time to graduation, and maximize return on investment.
The following is a brief overview of how some state systems are integrating MOOCs into their online portfolios.
New York. In March 2013, the State University of New York’s Board of Trustees announced support of a plan to use MOOCs, prior-learning assessment, and competency-based programs to increase enrollment, shorten time to completion for degrees, and reduce the cost of education. The SUNY board intends to leverage expansion of the current prior-learning assessment program of the system’s Empire State College and will encourage more faculty to teach MOOCs so as to maximize return on that investment. There are one hundred fifty online degree programs offered across the system, developed, delivered, and administered by each individual campus. As part of an effort to reduce costs, create a three-year degree program, streamline administration, and expand curricular offerings to non-traditional students, SUNY Chancellor Nancy Zimpher intends to consolidate these online offerings. SUNY aims to increase enrollment by one hundred thousand students in three years.
Florida. Where the Chancellor’s office is taking the lead in the New York system, Florida lawmakers tentatively plan to place a single university—likely the University of Florida—in charge of expanding online efforts while simultaneously streamlining administrative overhead and oversight. Florida’s online offerings and administration currently are scattered across the system, with nearly three hundred ninety online degree programs offered by ten of its twelve schools. Each campus administers its own design, development, and delivery of online courses. If the proposed legislation passes, Florida’s university system will offer two new undergraduate degree programs by January 2014 and four more in the following year, while consolidating authority and eliminating redundancies. Florida, like New York, intends to leverage existing programs and take advantage of MOOCs to reduce the cost of education and increase enrollment.
California. In California, where cutbacks in state support led to decrease in the number of available course sections just as student demand increased, the legislature is reviewing a bill to use MOOCs and online learning to solve their higher education woes. [As of this writing] Senate Bill 520, sponsored by State Senator Darrell Steinberg, calls for a system enabling students experiencing trouble registering for lower-level, high-demand classes to take approved online courses offered by commercial providers outside the state’s higher-education system. If the bill is passed and signed into law by Governor Jerry Brown (in the face of strong opposition from faculty in all three California college systems), state colleges and universities may soon be accepting credits earned by students enrolled in MOOCs.
Enrollment and completion data. 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.
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.
While demographic data about MOOC participation is still difficult to find, there are some sample profiles with numbers. Steve Kolowich provides a glimpse in “Early demographic data hints at what type of student takes a MOOC,” in Inside Higher Ed. The article reviewed survey results from one Coursera MOOC.
Coursera began when co-founder Andrew Ng taught a course called Machine Learning to 104,000 online students. According to Kolowich, half of the 14,045 respondents to a demographic survey were full-time professionals employed in technology. Forty-one percent of those identified themselves as “professionals currently working in the software industry” and nine percent as professionals working in other areas of the information technology industry. Nearly twenty percent were graduate students in traditional post-secondary education programs and another 11.6 percent identified themselves as undergraduates. Of the remaining respondents, 3.5 percent were unemployed or employed outside of the technology industry; one percent were enrolled in a K-12 school program, and 11.5 percent identified themselves as “other.” When a subset of 11,686 participants was asked why they chose to take the course, thirty-nine percent responded that they were “curious about the topic,” another 30.5 percent said they were interested in the potential to “sharpen the skills” used in their current position and eighteen percent were interested in the course as a means to “position [themselves] for a better job.”
Kolowich also reviewed data on an electrical engineering course, Circuits and Electronics, offered by edX. Like the data from the Coursera sample, the numbers are by no means comprehensive, but they do provide a basic view into the demographics of the participants who completed the course. Of 155,000 who registered, 9,300 passed the midterm exam, 8,200 made it as far as the final exam, and just over 7,000 passed the final with the option to receive an informal certificate of completion from edX. Kolowich notes that the age distribution of participants who made it to the end lean towards what we in higher education would call “nontraditional” students (although Clay Shirkey would argue that the nontraditional is increasingly the norm). Half of the participants were twenty-six or older while about forty-five percent were traditional college-aged students. Five percent identified as current high school students. The oldest was seventy-four, the youngest fourteen. Roughly thirty percent said they did not have a bachelor’s degree while thirty-seven percent said they did. Twenty-eight percent claimed to have a master’s degree and six percent a doctorate.
Yvonne Belanger, who leads assessment and program evaluation at the Center for Instructional Technology at Duke University, recently published a summary of enrollment in Duke’s first Coursera MOOC, Bioelectricity: A Quantitative Approach. Only about three hundred fifty of the approximately 12,700 registrants took the final exam—a dropout rate of ninety-seven percent.
Noting that “Student motivation in the MOOC environment is a significant area of interest to stakeholders at Duke and elsewhere,” Belanger surveyed the participants with both pre- and post-course questions about their reasons for enrolling and completing the course. As part of a Coursera-supplied, pre-course survey instrument, “fun and enjoyment” were identified as important reasons for enrolling by a large majority of students, and Belanger included that data in her report:
On her post-course survey, students responded to a broader range of questions in which Belanger separated motivations for enrolling from initial intentions once enrolled. Respondents had the option to select all applicable choices. Regarding initial intentions and objectives, the following graphic summarizes student motivations for enrolling:
Mining information in user-supplied comments from both the survey and course discussion forums, Belanger identified four categories of participant motivation including:
- Lifelong learning.
- Social experience.
- Exploration of online learning.
Writing on the Center for Instructional Technology blog, Belanger notes that motivations for MOOC participants vary, and she cautions against comparing MOOC demographics and completion rates to traditional campus courses. She identifies five reasons that may help us understand why individuals sign up for MOOCs but fail to complete them:
- A significant number (1/3 to 1/2) of those who registered for the course never actually started it. As Belanger says “Based on data about Duke’s Coursera courses, anywhere from 1/3 to 1/2 of students who enroll in our MOOCs never come back and log in after the course begins.”
- A majority of those who registered for the course never intended to finish it. According to the statistics gathered by Belanger, “earning the Statement of Accomplishment . . . was very important to only about 10% of them.”
- The course was open to anyone without restriction. Several factors and requirements contribute to limiting class sizes and participation in traditional courses including “a secondary school education, the admissions office, the bursar’s office, whether or not they’ve passed the prerequisites as defined on our campus, and the number of seats in the classroom.” These requirements are absent in MOOCs and this contributes to the inflated registration numbers.
- For many, perhaps most, there is no concrete value in completing the course. Qualifying for a “Statement of Accomplishment” that currently carries little if any credibility beyond individual satisfaction fails to motivate most registrants.
- The course simply was not a priority for most of those who registered. Despite curiosity and interest in the potential of the course, most have more pressing things to attend to: “In our largest course, about 2/3 say they work either full or part time, with full time outnumbering part time 2:1. About 1/3 are currently students (including pre-college, undergrad and grad). And quite a few are students who work.”
(Source: Blogpost, “Participation And Completion Of Moocs,” Yvonne Belanger, March 1, 2013. http://cit.duke.edu/blog/2013/03/participation-and-completion-of-moocs/)
It is important also to note that MOOCs have successfully connected participants from across the globe. EdX speaks to this strategic motive on its website: “Along with offering online courses, the institutions will use edX to research how students learn and how technology can transform learning–both on-campus and worldwide” [emphasis added]. So where are MOOC participants located? What are the factors that contribute to or challenge the global reach of MOOCs?
The map below provides a glimpse into global demographics for the course Internet History, Technology, and Security, taught by Charles Severance, Associate Professor in the School of Information at the University of Michigan, through Coursera. Severance conducted his own survey to determine the geographic distribution of participants:
Severance describes his methodology, noting its limitations: “This data is from a survey conducted of the students enrolled (4701 responses) in the Internet, History, Technology and Security course taught on Coursera on July-September 2012. The data was open-ended responses to the question, ‘Where are you taking the course from (State / Country)?’ The open-ended user responses were submitted to the Google Maps geocoding API and as such likely to be imperfect and/or approximate. There was no cleaning of the data either before or after submitting it to the Google geocoding API. All data including location label displayed when you hover over a marker comes from the geocoding API and its approximation of the location – no end-user entered data is present on this page.” [NOTE: This map is Copyright CC]
Though a rough estimate of a sampling of data from one course, the map illustrates general views into the demographics of MOOC participation at the global scale. As expected, there is heavy representation from North America, Europe, and South Asia, specifically India. There is slightly less participation from South America and East Asia. Participation from African nations and Central Asia is sparse. This correlates with more general data provided by Coursera on the geographic representation of participation in its MOOCs:
Kris Olds, in “On the territorial dimensions of MOOCs,” notes the importance of using geospatial representations of MOOC usage and demographic data on access to Internet and telecommunications to understand regional and national capacity to participate in such courses. He believes forwarding a monolithic “notion of a singular ‘global’ or ‘international’ category” to MOOC participation is misguided. Internet access and telecommunications bandwidth is clearly increasing, but there are significant limitations even within wired countries. as these charts from a 2011 International Telecommunications Inion report illustrate:
Olds also points out that the disciplinary content of MOOCs is worth reviewing when examining geospatial demographics. For example, many of the first MOOCs were on information technology, specifically computer science and software development—topics with a global reach. Other topics may be of more regional or local interest. When Tucker Balch, a professor in the School of Interactive Computing at Georgia Tech, taught Computational Investing, Part I, via Coursera in Fall 2012, the overwhelming proportion of those completing the MOOC were from the United States. Balch surveyed participants and collected responses from 2,350 of his 53,205 students:
At this time, demographic data is inadequate. Effective decision-making by campuses will require much better metrics and data. The preliminary work of observers like Belanger, Hill, and Jordan is useful, however, and will influence the development of projects analyzing enrollment and completion rates.
Udacity and San Jose State University, for example, are currently at work on a project demonstrating the potential of building data gathering directly into the delivery of MOOCs. In January 2013, they announced the joint creation and delivery of three introductory mathematics classes. For Udacity, a stated objective of the pilot is to investigate strategies to bolster retention by requiring participating SJSU students to have more “skin in the game” by paying $150 per credit (standard per-credit fees in the California state university system range from $450-$750). By framing these “MOOCs” in the context of commitment and reward, SJSU and Udacity hope to create a laboratory for defining metrics, establishing baselines, and measuring success. Such projects will help develop successful and scalable online programs with defined retention strategies. As more data on MOOCs is generated and compiled, campus leaders will have better decision-making tools regarding them.
Whether or not you are part of a large state university system or affiliated with an elite campus with whom providers like Coursera are willing to work, you need to develop an assessment plan to help you consider MOOCs as potential solutions to enrollment problems.
- Update enrollment needs at your institution.
- Determine your institutional ability to develop and deliver MOOCs.
- Decide if you will work with external MOOC providers.
- Consider working with an outside agency to develop a critical review of providers.
- Work with faculty to define courses that are candidates for online teaching.
- Define an inclusive approval process that involves your faculty.
- Define financial aid eligibility as it applies to MOOCs.
- Determine whether you will charge for course enrollments.
- Determine how you will manage MOOC data in your student information systems.
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Balch, Tucker. “MOOC Student Demographics.” The Augmented Trader, January 27, 2013. http://augmentedtrader.wordpress.com/2013/01/27/mooc-student-demographics/.
Belanger, Yvonne. “Participation and Completion of MOOCs.” Center for Instructional Technology, Duke University, March 1, 2013. http://cit.duke.edu/blog/2013/03/participation-and-completion-of-moocs/.
Belanger, Yvonne, and Jessica Thornton. “Bioelectricity: A Quantitative Approach Duke University’s First MOOC” (2013). http://dukespace.lib.duke.edu/dspace/handle/10161/6216.
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Hill, Phil. “Emerging Student Patterns in MOOCs: A Graphical View.” e-Literate, March 6, 2013. http://mfeldstein.com/emerging_student_patterns_in_moocs_graphical_view/.
———. “The Most Thorough Summary (to Date) of MOOC Completion Rates.” e-Literate, February 26, 2013. http://mfeldstein.com/the-most-thorough-summary-to-date-of-mooc-completion-rates/.
Jordan, Katy. “MOOC Completion Rates.” Accessed March 18, 2013. http://www.katyjordan.com/MOOCproject.html.
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———. “edX Explores Demographics of Most Persistent MOOC Students.” Inside Higher Ed, September 12, 2012. http://www.insidehighered.com/news/2012/09/12/edx-explores-demographics-most-persistent-mooc-students.
———. “SUNY Signals Major Push Toward MOOCs and Other New Educational Models.” The Chronicle of Higher Education. The Wired Campus, March 20, 2013. http://chronicle.com/blogs/wiredcampus/suny-signals-major-push-toward-moocs-and-other-new-educational-models/43079?cid=wc&utm_source=wc&utm_medium=en.
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Regalado, Antonio. “Massive Open Online Courses in the Developing World.” MIT Technology Review, November 12, 2012. http://www.technologyreview.com/news/506336/online-courses-put-pressure-on-universities-in-poorer-nations/.
Rivard, Ry. “California Academic Leaders Oppose Outsourcing Plan.” Inside Higher Ed, March 28, 2013. http://www.insidehighered.com/news/2013/03/28/california-academic-leaders-oppose-outsourcing-plan.
———. “Florida and New York Look to Centralize and Expand Online Education.” Inside Higher Ed, March 27, 2013. http://www.insidehighered.com/news/2013/03/27/florida-and-new-york-look-centralize-and-expand-online-education.
———. “Researchers Explore Who Is Taking MOOCs and Why so Many Drop Out.” Inside Higher Ed, March 8, 2013. http://www.insidehighered.com/news/2013/03/08/researchers-explore-who-taking-moocs-and-why-so-many-drop-out.
Severance, Charles. “Visualizing the Geographic Distribution of My Coursera Course,” September 30, 2012. http://www.dr-chuck.com/csev-blog/2012/09/geographic-distribution-of-my-coursera-course/.
Shirky, Clay. “How to Save College.” The Awl, February 7, 2013. http://www.theawl.com/2013/02/how-to-save-college.
“The Big Three MOOC Providers.” The New York Times, November 2, 2012, sec. Education / Education Life. http://www.nytimes.com/2012/11/04/education/edlife/the-big-three-mooc-providers.html.
Watters, Audrey. “Top Ed-Tech Trends of 2012: Data and Learning Analytics.” Inside Higher Ed, December 20, 2012. http://www.insidehighered.com/blogs/hack-higher-education/top-ed-tech-trends-2012-data-and-learning-analytics.
———. “Top Ed-Tech Trends of 2012: MOOCs.” Inside Higher Ed, December 18, 2012. http://www.insidehighered.com/blogs/hack-higher-education/top-ed-tech-trends-2012-moocs.
Young, Jeffrey R. “California State U. Will Experiment With Offering Credit for MOOCs.” The Chronicle of Higher Education, January 15, 2013, sec. Technology. http://chronicle.com/article/California-State-U-Will/136677/?cid=wc&utm_source=wc&utm_medium=en.
 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/.
 Steve Kolowich, “Early Demographic Data Hints at What Type of Student Takes a MOOC,” Inside Higher Ed, accessed March 6, 2013, http://www.insidehighered.com/news/2012/06/05/early-demographic-data-hints-what-type-student-takes-mooc.
 Yvonne Belanger and Jessica Thornton, “Bioelectricity: A Quantitative Approach Duke University’s First MOOC” (2013), http://dukespace.lib.duke.edu/dspace/handle/10161/6216.
 Charles Severance, “Visualizing the Geographic Distribution of My Coursera Course,” September 30, 2012, http://www.dr-chuck.com/csev-blog/2012/09/geographic-distribution-of-my-coursera-course/.
 Kris Olds, “On the Territorial Dimensions of MOOCs,” Inside Higher Ed, December 3, 2012, http://www.insidehighered.com/blogs/globalhighered/territorial-dimensions-moocs.
 Tucker Balch, “MOOC Student Demographics,” The Augmented Trader, January 27, 2013, http://augmentedtrader.wordpress.com/2013/01/27/mooc-student-demographics/.