In the past couple of months, I’ve been spoiled for choice at Coursera, as many more universities have joined the platform. After finishing the Internet History, Technology and Security course, there were several which caught my eye . I initially thought ‘hey, why not, let’s push this and see how many I can do simultaneously’, but there was a another factor involved – needing to move house and starting my PhD! So compromises had to be made. Here is a whirlwind summary:
Networks: Friends, Money, and Bytes: I had signed up to this course quite a while in advance as it seemed very interesting, and if I hadn’t had two ‘essential’ courses at the same time (Networked Life and Social Network Analysis – blog post on these to follow soon), I imagine I would have stuck with it. Additional factors which led me to drop the course were: (i) it seemed very long, at 14 weeks; (ii) despite seeming like quite a lot of work, it did not offer a certificate (I’m slightly ashamed to say that this did contribute to putting me off – I know getting a certificate is not really the point!); and (iii), the course content had recently been published as a book, so I could potentially read this at some point in the future instead.
Web Intelligence and Big Data: I completed the first week of this course, before dropping out in the second. Again, had it been running at a time when I did not have higher priority MOOCs underway, I would probably have persevered. The course included programming assignments, which I don’t think I would have been able to do without further study (other students on the forum helpfully suggested that the Udacity CS101 course is a good introduction to Python, so I will aim to take this course in preparation for the next offering of Web Intelligence and Big Data).
Securing Digital Democracy: A bit of a detour from my main interests (I set out with MOOCs to learn about Computer Science), I took this course because I thought it may fit with my broader interest in Web Science. It was relatively short (5 months) – small, but perfectly formed. The professor, J. Alex Halderman, had an excellent presentation style and the lectures were nicely finished. The course was assessed by multiple choice question sets, and a final peer reviewed essay (although due to time pressures, the course topic not being a high priority for me at the moment, and safe in the knowledge that I had scored well enough on the quizzes to gain a certificate, I did not submit an essay).
Learn to Program: The Fundamentals: Completed the first weeks’ material, but then it slipped and missed deadlines. Think it would have been manageable otherwise – and useful as my lack of programming knowledge is proving a stumbling block with some other courses (such as Big Data). It was a victim of purely bad timing for me. Hoping it will prove popular and run again soon!
Reflecting on these hits and misses, I think it raises an interesting question about how you join together multiple MOOCs into a broader learning pathway. I’ve gone on a bit of a detour from my original aim of studying computer science, which is not a bad thing – the detours have been enjoyable and I don’t really have any kind of deadline I’m aiming for – but as a beginner, it is a bit tricky to tell where I ought to go next. There is also an issue about starting to need prerequisites for courses, such as programming, which creates a progression between courses, but this kind of progression is not explicit. On a related note, Coursera have recently introduced profile pages for students, which show which courses students are taking; it would be interesting to map the network of co-studied MOOCs to see if students’ choices cluster into traditional disciplines or emergent interdisciplinary areas. As for my next MOOC, I am planning on going back to Computer Science and taking either CS101 at Udacity, or EdXs’ CS50 – watch this space!