The economic consequences of MOOCs

tl;dr check out our new paper on the relationship between MOOC completion and economic outcomes!

Last Monday we launched our Chromebook Data Science Program so that anyone with an internet connection, a web browser, and the ability to read and follow instructions could become a data scientist.

Why did we launch another MOOC program? Aren’t MOOCs dead?

Well we didn’t think so :). We have been pretty excited about MOOCs for a while now and now run five different MOOC programs through the Johns Hopkins Data Science Lab. Our enthusiasm is motivated by our desire to make education available to everyone and help the world.

There has been a significant amount of research on attendance in MOOCs, on learner attrition, and how to keep students motivated. But there has been almost no research on whether MOOCs can actually help you improve your economic situation.

A postdoc in our group,Aboozar Hadavand, set out to study this in our main data science MOOC program, the JHU Data Science Specialization on Coursera. We wanted to know whether completing our program, with an average cost less than 1,000 dollars, would lead to any economic benefits in terms of increase in salary or job mobility.

We created a survey that we sent out to all students who had ever enrolled in the most popular course in the sequence - R programming. The survey asked questions about salary before and after the sequence, location, and job mobility (the number of times a person switched jobs). By emailing everyone who enrolled we surveyed both people who completed our sequence and people who did not complete.

We compared the respondents to our survey to the demographics we have from students who enrolled in our sequence and found them to be broadly similar.

Our survey population and Coursera's demographics match up broadly

Using this survey we wanted to know whether there are any significant differences between the people who enrolled and completed the program versus those who enrolled but never completed in both income and job mobility. We used propensity score weighting to match up the people who completed 0, 1-5, and 5 or more courses (left panel). Based on these propensity score weighted data it looks like there is an association between completion of the courses and post-completion income. For users who completed at least 5 courses (compared to those who completed none) we observe an increase of \$2,790 to \$7,820 depending on the choices we make about which countries to include in the analysis (middle panel). We then used generalized propensity score weighting to calculate the percent increase in income for each fraction of the Data Science Specialization that students completed (right panel). The majority of the increase occured after completing 25% of the Specialization with a relatively steady increase beyond that. While there are still a lot of challenges with MOOCs, we are very excited about the potential return on investment for learners. When you compare our MOOC program to other educational programs the potential ROI for these program is what has us so excited about doing things like Chromebook Data Science

Results of our survey

If you want to read more about how we did the survey and the other interesting analyses we did you should go check out Aboozar’s paper on SSRN.

COI Disclosure: Dr. Leek receives financial compensation through the Johns Hopkins Tech Transfer Program from revenue generated by the Johns Hopkins Data Science Specialization.

 
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