Well, first off, there was the fact that the "whiteboard" consisted of them writing on notebook paper. Had this been the only shortcoming, it would have been fine, but seriously, there are so many better ways to present something on a computer screen than writing in a notebook under a camera.
But what really got under my skin and ultimately caused me to give up on the program were the errors in the videos, and how they were dealt with – namely, by putting some correction text underneath the video on the website. This was annoying and frustrating to try to learn with even for simple errors. But it was ridiculous when the error was a single character change within three lines packed with newly introduced notation. The minimal correct way to handle this would have been simply to overlay a YouTube annotation over the incorrect text. Those would have shown up in full screen mode, and they wouldn't have required students to simultaneously mentally amend what they were watching while juggling new concepts in their heads.
I was also not thrilled when newly introduced terminology got thrown around imprecisely in some of the videos, leaving the viewer wondering what these terms actually mean, and what the teacher was actually trying to say.
I have no doubt that Thrun and Norvig are great computer scientists. But a great scientist and a good teacher are not often found in the same person. For that person to also be a good video director would have to be a miracle.
Sebastian is using one of those electronic pens to write in this course. I'm not sure how exactly this works, but his hand is transparent in such a way that it never blocks the text (I didn't notice this immediately, it all seemed very natural). I watched the first few videos of the Fall AI class--this is far better than that approach.
I'm not sure how they'll deal with errors--too soon to tell.
So far Sebastian has been very good about not using jargon without introducing it--in fact he's been extremely empathetic in this regard. Moreover, so far the format of the course has changed to focusing on solving the specific problem (like robot localization) and then afterwards introducing the formal ideas, like Bayes' theorem. Its much better than the videos I saw from the first AI course.
I think you're right that sometimes doers are not great teachers, but I am convinced that you should give Thrun another shot.
I took ai-class as well and was actually really disappointed in Norvig's teaching style (considering I generally love what he writes). I thought Thrun on the other hand was great, so I have a lot of hope for the udacity courses. My suspicion is that each instructor had different levels of commitment to the project, and since both are extremely busy this affected the presentation.
My biggest issue with ai-class was that in almost all the exams and homework there were quite a few very poorly phrased questions. In a human-graded exam/hw this isn't so bad since the ability to "show your work" usually allows you to misunderstand a question and demonstrate that you do understand the material. In general I though very little effort was put into creating assignments that worked well for an online environment (ml-class did this perfectly).
> Well, first off, there was the fact that the "whiteboard" consisted of them writing on notebook paper.
What's wrong with this? Handwriting looks way better on notebook paper than on a tablet or on an actual whiteboard.
The only problem with the AI courses was lack of official programming exercises and, yes, some imprecisions here and there that were not hard to resolve by checking the forums, where they were inevitably brought up and fixed.
But what really got under my skin and ultimately caused me to give up on the program were the errors in the videos, and how they were dealt with – namely, by putting some correction text underneath the video on the website. This was annoying and frustrating to try to learn with even for simple errors. But it was ridiculous when the error was a single character change within three lines packed with newly introduced notation. The minimal correct way to handle this would have been simply to overlay a YouTube annotation over the incorrect text. Those would have shown up in full screen mode, and they wouldn't have required students to simultaneously mentally amend what they were watching while juggling new concepts in their heads.
I was also not thrilled when newly introduced terminology got thrown around imprecisely in some of the videos, leaving the viewer wondering what these terms actually mean, and what the teacher was actually trying to say.
I have no doubt that Thrun and Norvig are great computer scientists. But a great scientist and a good teacher are not often found in the same person. For that person to also be a good video director would have to be a miracle.