Monthly Archives: December 2012

Networked Life, Social Network Analysis, & a new appreciation for feedback

Two key Coursera courses which did not fall by the wayside for me this Autumn were ‘Networked Life‘ (Michael Kearns, University of Pennsylvania) and ‘Social Network Analysis‘ (Lada Adamic, University of Michigan).

Both courses held a particular significance for me. Whereas the MOOCs I had taken up until this point had been ‘just for fun’, these courses were directly related to my PhD, which I started this Autumn. The courses were incredibly helpful as introductory social network analysis courses, giving me a head start methodologically, and saving me probably a couple of hundred pounds in face-to-face training courses. The courses were also the first MOOCs which I’ve found to be challenging; graph theory gave my brain the best mathematical workout since I did A-level maths (and I really do mean that as a compliment!).

Although the courses were ostensibly very similar, in terms of the subject matter and scope, they each provided very different MOOC experiences, and I ended up with very different marks – 98.8% for Networked Life, compared to 80.3% for Social Network Analysis (just scraping a certificate)! Here I’m going to try to explore the reasons behind this.

‘Networked Life’ (NL) had a simpler course structure than ‘Social Network Analysis’ (SNA). NL was slightly short, at 6 weeks, compared to SNA’s 8 weeks. In NL, the material was taught via video lectures (including simulations), and assessed by multiple-choice questions. Assessments were quite strict in that you could only attempt quizzes a maximum of twice. In contrast to the other Coursera courses I’ve taken in the past, all of the NL lectures and quizzes were available right from the start of the course, i.e. there was no weekly release of material (which was nice – I enjoyed being able to get further ahead when I had spare time, but still having weekly deadlines for the quizzes kept me from falling behind when time was tighter). The quizzes were tough, but the feedback on the first attempt was helpful and constructive, which really helped in learning from mistakes.

The main mode of material delivery in SNA was also video lectures including simulations. There were however two different ‘modes’ to the course; a basic certificate could be earned by gaining a mark of over 80% via the weekly multiple choice quizzes and final exam, while a certificate with distinction could be earned by completing this plus additional programming assignments (usually multiple choice questions relating to interrogating a network data set in a social network analysis package, plus a peer-assessed project). The multiple choice questions in SNA were the hardest I have encountered in a MOOC yet, mainly because it did not give any feedback after each attempt – not even an indication of which questions were right or wrong! This was very frustrating, and has given me a whole new level of appreciation of feedback! Because of this, I could generally do quite well on the assignments, but remember that the pass mark was set at 80% right from the start of the course; I found it really hard to get really good marks on the assignments due to the lack of feedback, and kept bumping along right on the pass mark.

I think it helped that I had chosen to do the optional programming assignments, as I had been doing a bit better on these (getting more like 90-100%). It was a bit of a surprise when I realised that I need to complete a project though – I’d thought that the optional programming assignments were a sort of ‘extra credit’ affair, and didn’t realise ’til a week before the project was due that doing the programming assignments kind of put me on the programming ‘track’ and I would fail if I did not submit a project. If you are interested, here is the project that I submitted – if you refer to it anywhere, please use the suggested citation at the top of the PDF file. I got a bit carried away and marked 25 peer assessments! It was compelling to see what other students had chosen for their project. I think this was the advantage of the SNA course over NL; NL was better for covering the basic concepts, but SNA offered the benefit of the opportunity to think about and apply what you had learned, which was invaluable for me.

It was a bit of a mystery to me as to whether I would actually get a certificate or not (my calculations put me right on the grade boundary), and was genuinely pretty surprised when I did. The following statistics were released at the end of the course:

“Some participation stats: 61,285 students registered, 25,151 watched at least one video, 15,391 tried at least one in-video quiz, 6,919 submitted at least one assignment, 2,417 took the final exam. 1303 earned the regular certificate. Of the 145 students submitting a final project, 107 earned the programming (i.e. ‘with distinction’) version of the certificate.”

The most surprising statistic here for me though is that out of the 2,417 students who took the final exam, I’m assuming having completed all the weekly assignments and made it through the course to the end, only 1,410 actually got a certificate. I think that there could not have been a bit more leniency in terms of the pass mark – 80% seemed quite arbitrary and was fixed at the start of the course, which had not run on Coursera before. Also, it turns out that with only 145 students submitting a project, I had actually personally marked 17% of the projects submitted! Which made me think … is this really massive?



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The MOOCs that got away: A brief roundup & reflection on my drop outs this Autumn

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!

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