I have taken a couple of Coursera courses on R and Stats. They basically give you a brief outline of some topics you might want to pursue more in depth and they give you access to a discussion forum. I haven't found that this method of learning/teaching is very useful. There seems to me to be a huge opportunity waiting to be developed if someone can make a site like that but with more interactive elements AND where the learning/teaching is based on sound educational principles that can be demonstrated to effectively result in skills mastery. As it is now, Coursera is basically skimming cash off of the internet's insatiable google searching for information, like for example someone might google "Learn R" and then fall into the trap of paying $49 for a class that consists of nothing but videos really without having a clue about whether or not the videos really work to communicate knowledge or even whether the videos are touching on anything meaningful. If it hadn't been for the "Johns Hopkins Data Science Course" branding on the class I signed up for I wouldn't have fallen for it I am sure.
If it hadn't been for the "Johns Hopkins Data Science Course" branding on the class I signed up for I wouldn't have fallen for it I am sure.
Just to provide a counter-point.. I've taken 5 or 6 of the classes in that sequence, and have found them well worth every penny I've spent so far. Probably you could argue that the same information is available elsewhere for free, but the classes have worked for me, and the way I study and learn.
Obviously YMMV, but they've been a bargain from my perspective. I think because, if nothing else, they provide some structure, sequencing and a token measure of accountability... whereas if I just said "Hey, I'm going to teach myself R from this book" it would be a lot easier to loaf around, waste time reading HN instead of studying, etc.
That said, I don't argue against the idea that online learning could still be better. In fact, I don't think we've even come close to tapping the full potential of this stuff.
I agree with you, while they are far from the optimal to consume something there is always some need for alternative ways of learning, if only to address the variety of people who would like to learn. I find that I retain content better when I learn it in multiple ways (explore using MOOCs and podcasts about it, go deeper into it using books and practical work if applicable) and I'm sure it's the same for most people.
Yeah, same here. I'm doing the Johns Hopkins Data Science classes on Coursera, as well as the Duke "Statistics with R" series, but I've been supplementing that with both dead-tree books (R in Action among others) and other videos (like the Professor Leonard ones on Youtube), reading Wikipedia articles, etc., etc. Gaining a good understanding definitely involves attacking the problem from multiple angles in my approach. :-)
A complex field should be divided into multiple skills and each one should be learned in proper logical order. If a student has problems on some of those skills, appropriate videos and exercises should be presented. As it is now, there is no skill tracking and no adaptation to student needs. I'd especially like to see this done in ML, Stats, Probability and Information Theory. There are a lot of mini-skills there to be mastered, and every student has a different level of experience with each one.
