#### Data relating to MOOC activity has been trickling out for quite some time. For instance, the University of Edinburgh released this 42-page report detailing their analysis of statistics related to six courses they released via Coursera in 2013. And data related to edX’s popular Circuits and Electronics course has been making the rounds for quite some time.

But if you’re looking for an easy-to-understand, straight-to-the-point lesson on how to interpret data generated from a MOOC class, who better to provide it than someone who has been teaching a MOOC on the very subject of metadata?

Jeffrey Pomerantz from the University of North Carolina at Chapel Hill offered a Coursera MOOC entitled Metadata: Organizing and Discovering Information in 2013. And part of doing business with Coursera involved receiving weekly downloads of statistics related to activity in his class, data the professor shared with students (also on a weekly basis) so that the class could use their own behavior as a subject of study.

Pomerantz recently summarized some of his findings in a series of four blog entries which start here. And while even the author admits that his work so far represents a starting vs. an end point for discovery, there are some important lessons to be learned, even through what should be considered an early entry into a “Big Data” story sure to grow longer and more interesting.

To begin with, his stats help settle (or at least inform) one of the big issues hanging over the head of MOOC enthusiasts: high drop-out rates (sometimes as high as 95%). I’ve commented frequently about why using the number of people who just sign up for a MOOC in the denominator of our fractions when calculating MOOC attrition rates might be an error (given that signing up simply represents the number of people willing to register to get something of value for free).

Pomerantz puts it a bit differently, claiming that since there is no penalty for signing up for a MOOC and never attending that we should not be so hung up on what Coursera refers to as the number of “Total Registered Students.” But he shares my attitude that treating a student who supplies their name and e-mail address to Coursera (or some other MOOC web site) should not be considered the equivalent of a student who enrolls in a class at a brick-and-mortar university.

So if we’re not going to divide course completion numbers by total registrations to calculate a MOOC attrition rate, what statistic *would* make a better denominator? Pomerantz walks through a few candidates including Total Active Students (students who have logged onto the site at least once after registering, which increases the pass rate from 5% to 10%), unique students who have watched at least one video (which increases pass numbers to 15%), and students who have completed at least one assignment (which jacks up the pass rate to a far-more-respectable 48%).

This last figure jibes with one of Anant Agarwal’s key talking points when confronted with questions regarding MOOC attrition rates in which he claims pass rates climb towards 40% when you assume that only students who actually complete an assignment (even a light quiz given on Week 1) should be considered serious enrollees. And if you take into account that many of the students who might enroll in a course but not do any assignments might be auditing the class, then you begin to get a better picture of what people are *actually* doing when they take part in a MOOC (other than dropping out).

Now this more informed picture is a two-edged sword for MOOC boosters. On the one hand, it gives them strong evidence to counter critics who like to hammer on drop-out rates to “prove” MOOCs are educationally worthless. At the same time, it’s hard to continue using huge front-end MOOC enrollments to impress the media, public and investors and then turn around and minimize the significance of that number when it comes time to calculate “true” completion statistics.

I’ll be returning to the subject of statistics again, but I highly recommend you read through all four parts of Pomerantz’s analysis which takes a look at video-viewing and discussion-forum statistics as well as information related to overall rates of participation.

And as you do so, keep in mind the distinction the professor makes between descriptive statistics (i.e., data deriving from observing a phenomenon) vs. more powerful predictive results you would get from a controlled experiment. At this stage, descriptive data is probably all we have and, as Pomerantz’s series highlights, it can be powerfully informative. But I look forward to the time when MOOC classes are designed with the type of controls and variables that would help better demonstrate what they actually accomplish.

Thanks for the shoutout! I want to clarify one thing: Coursera’s instructor dashboard provides overview statistics on an ongoing basis. So it’s not that Coursera only sent us that data weekly, it’s that we chose to post it to the forums weekly. There’s also more data that Coursera doesn’t provide in the instructor dashboard, that’s available to me & the UNC team on request. Anyway, not to nitpick, but I want to be clear about what the data situation is from the instructor side.

I completely agree with you, I’d like to see some actual studies of instructional design & instructional effectiveness for MOOCs. And it would be totally feasible to set up a study like that on Coursera, since they have a mechanism to randomize assessments. Obviously I didn’t take full advantage of that for my course… maybe for the next offering.

Alternatively… Coursera will provide data from a course *only* to the institution that offers it (a reasonable position). So I personally believe that institutions should pool their MOOC data, which would allow them to compare across more types of students, subjects, & teaching styles.

Thanks for clarifying and I’d glad to know there are professors interested in looking at what the data can tell us about MOOCs in general, rather than just one course. The more that can be proven through data that is already being generated when people take a MOOC, the more credibility claims about them will be.

It’s kind of amazing how the kind of analysis you did can clarify one of the biggest arguments against MOOCs (alleged drop-out rates), although I guess you could also use that same data to prove that MOOCs are not really educating the kinds of numbers that made the press most of last year and this year. That said, I’m not sure why we aren’t celebrating courses that “merely” let gifted and dedicated teachers reach more people than they’ve taught their whole lives (and committed students at that).

Looking forward to reaching the Plateau of Enlightenment.

This all jibes quite well with figures and discussions from various sources; there seems to be a quite consistent 50% proportion of those who register who never start a course. It seems reasonable to assume that many of those use registration simply as a ‘bookmark’ to note courses in which they might have an interest–I have certainly done so myself. As I mentioned in an earlier comment, even Open2Study, where courses repeat on a five week carousel and most registrations are within a week of course start, see 50% of non-starters.

Something that I’ve not seen any feedback on are the outcomes of the surveys that are common at the start of courses. As they always ask about the student’s intentions, it would be interesting to see how intentions map to engagement. That is to say, what proportion of those intending to ‘complete’ a course go on to do so. This seems far more significant than simply looking at total registrations.

You make a good point here, Paul. I think one of the problems with the way MOOCs are portrayed in the press (even the higher ed press) is that students are treated as some kind of monolithic thing, like all students are the same. Hardly anyone discusses students’ motivations for taking a course. I took the Introduction to Astronomy MOOC, but I stopped doing the assignments after a few weeks because they were kicking my butt and I didn’t have the time to put in. But I watched all the videos & I got a lot out of the course anyway. So I’d count as a dropout, despite the fact that I was never in it for the certificate. My Teaching Assistant for the MOOC is doing her Masters thesis on student motivations in the MOOC. I’m personally really looking forward to seeing her findings.