Since my goal as a MOOC student is to enhance my knowledge of Computer Science, CS101 at Coursera was my first MOOC. Actually, that isn’t strictly true; earlier in the year, I had signed up for the Learning Analytics MOOC, although I did not stick to it and only dropped in to selected online sessions during the course. I think this was due to a combination of factors, mainly that I was very busy at the time in my ‘real life’ course, and the assessments in CS101 really helped me to keep up and stay focused along the way. CS101 was certainly the my first MOOC in the sense that I was the first I completed!
The course started on 23rd April 2012 and ran for six weeks. As a first taste of the Coursera platform, I was impressed; the course was well structured and organised, and the teaching materials were well thought through and engaging. I was slightly disappointed that the videos were not reusable (the lectures on computer networking would have been nice to incorporate in my online notes on Web Science, for example); to me, a crucial part of the concept of Open Educational Resources (OER) is reusability and remixability. Generally, the course materials were published under a Creative Commons Attribution-ShareAlike 3.0 license, however the video lectures were exempted from this and remained copyright Stanford University. So while the course is free, and anyone can study on it, whether it is OER is debatable.
I would guess that being an introductory-level course and one of the first courses offered by Coursera, this was for many of the participants their first experience of using a MOOC, and the Coursera platform. As a result, students were keen to introduce themselves and find out a bit about their classmates, and several forum threads sprang up for introductions. For me, with my background in e-learning research, this provided a fascinating insight into the reasons why people would choose to study a MOOC, and the students’ backgrounds. This is an interesting topic because while there have been suggestions that courses like this are mainly taken by students who are already educationally priveleged (e.g. Anya Kamenetz, Who can learn online, and how?), I don’t think that there is a lot of real data being used to explore this.
I had intended to analyse one of the forum threads in order to address this; however, it quickly became apparent that even taking just one thread, this is a hell of a lot of data! I’m still hoping to do this analysis at some point in the future. In the meantime, I don’t agree with the idea that MOOCs such as this serve just to make the elite even smarter; while I did see highly motivated high school students and undergraduates supplementing their formal education with the CS101 course, this is too much of a generalisation in my opinion. I also saw the more senior students whose last formal study was 30+ years ago, looking to get up-to-date with modern programming languages; and stay-at-home mothers taking the course, sometimes with their young children. Let’s not forget too that the ‘mainstream MOOCs’ such as Coursera, Udacity and EdX are very new, and the early-adopters of a technology (I use adopter to mean students here) may be more tech-savvy and inclined to experiment (see the ‘technology adoption lifecycle’; as it’s early days, mainstream MOOCs are probably in the ‘innovators’ phase right now). I would expect the demographic to shift a bit as the platforms become more well-known and more widely adopted across society.
It would be really interesting to catch-up with students across a range of backgrounds (not just those looking to enter formal higher education, but not excluding them either) say a year after the course to see if the course enabled them to achieve their broader goals, and how what they learned during the course had been used in practice. It’s an exciting time for figuring out what the mainstream MOOCs mean, for opening-up learning, and reconfiguring the relationship with higher education. What is needed though is more data about the phenomenon; the MOOC platforms are sitting on a goldmine in terms of data to answer questions such as who can learn online.