I plan to post occasional reflections on ST101 and Power Searching with Google here as they progress.The first thing to say this week is that these online courses are not really MOOCs, but MOTS. However, I'm going to continue to use the term MOOC for these courses as that is now established, although not technically accurate.
I struggled so badly on probability last week that I spent some time on Khan Academy. Hated it - videos poorly produced c.f. the Udacity screen captures, non-interactive (no questioning), boring, couldn't follow most of it. Having said that, I was unhappy with ST101 Unit 2: "Processes that generate data", as I felt it did not cover the title of the unit well (in contrast to Unit 1: Visualizing relationships in data, which was a very good overview of the first topic).
Back on familiar ground this week with Unit 3: normal distributions and the central limit theorem. I enjoyed the Laplace probability generations at the start of the unit though - well explained (but don't they belong in the previous Unit?). I didn't like all the complex algebra around the standard deviation - an unwelcome distraction based on the unnecessary "optional" python programming element of the course, which is increasing distracting me from the key statistics messages.
While I like the formative questions integrated with the video (which is really the strength of the Uadacity approach), it's starting to get irritating - too many itty bitty pieces. The format, which I initially liked, is starting to grate. There's also no way the bottom-end-of-Bloom's-pyramid approach translates into other disciplines with non-numercial answers.
And I'm annoyed with Udacity's mis-selling of this computer science course as a statistics course. It's not, and that's not what I signed up for. Under other circumstances, I'd be asking for my money back. For me, this is the week the cracks started to show in the Udacity model. Would I sign up for another Udactity course after this one? No, not now I've seen how their model works.
Second concurrent MOOC I started this week is Power Searching with Google. This feels very different from ST101, and, surprisingly from Google, far less slick. The course site has a homebrew feel about it, and there is no progress bar. The content consists entirely of well-produced but conventional YouTube videos interspersed with javascript-driven formative questions. For me, the videos are slightly too long, slightly too slow, but that reflects personal choice. The pace gives a non-pressured, relaxed feel to the proceedings. The summative assessment consists of a midway and a terminal quiz, completion of which (inside fairly tight deadlines of a few days) results in an electronic certificate of completion for participants. There is a Google Groups forum which I haven't bothered to join, partly because I'm allergic to Google Groups, partly because I haven't felt the need. This has had the effect of making me feel far more distanced from and less involved with this course that with ST101. There has also been one live Hangout so far that I wasn't able to join because of the timing and haven't yet watched the recording of.
It's a bit PR-orientated and Google is clearly using it to gather user data. No change there then. Hard to complain when you're not paying. I'm now halfway through this course and it feels like a worthwhile exercise. I've picked up some really nice tips related to image searching, e.g. image search for:
[scientist curriculum vitae]
Would I sign up for another course in this format, e.g. on Photoshop, Chrome or Blackboard? Yes I would, which is a very interesting contrast with Udacity.
Update: Here's the Hangout:
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