Millions of people have signed up for Massive Open Online Courses, known as MOOCs. Early studies show that the majority of those who have signed up already have a college degree, and most do not opt to pay for a certificate to prove they passed the class. Put simply, they’re not looking to get college credit in any way. So I’m curious to dig deeper into what motivates these online “students.”
I am late to post because I’ve been digging around for a killer data set on this. I’ve made requests to HarvardX and to some researchers who have a large MOOC dataset, but so far no one has been willing to share their raw numbers. But HarvardX has published some demographic and survey data (not much). My sense, though, is that their data does not answer the question very well (most MOOC surveys only offer a few multiple choices on motivation).
So for the assignment, I’m focusing on playing around with fuzzier “data” – the student postings to forums in a MOOC. In many MOOCs, students post short introductions in the forums at the beginning of the term, usually saying why they are taking the course. I’ll analyze the intro discussion postings in one MOOC and group them into broad categories (my categories won’t capture everything, but there are definitely clear patterns in the responses).
My plan is to pick an astronomy course on edX that just started. https://courses.edx.org/courses/ANUx/ANU-ASTRO1x/1T2014/discussion/forum/i4x-edx-templates-course-Empty/threads/533080e801772bb02e00087f
There are only about 200 intro posts, so it should be do-able in the short time frame.
I plan to pull out one student post that is the best example of each category I create. So the interface will be a simple pie chart with the percentages of each reason for taking a MOOC, but then when you click on a specific group/color, you’ll be taken to that person’s intro post so you viewers can “meet” them.
I’m certainly open to suggestions on tools, critique, etc.