In October 2012 I gave several talks on my experiences with using MOOCs (or simply using material from MOOCs) in my regular Vanderbilt courses (e.g., http://vimeo.com/53361649, with my presentation starting at about 26:40, speaking from slides at https://my.vanderbilt.edu/douglasfisher/files/2012/02/ITHAKA-Presentation-10-16-12.pdf); a text summary of my experience up to that time can be found on the Chronicle of Higher Education's ProfHacker blog at http://chronicle.com/blogs/profhacker/warming-up-to-moocs/44022.
As part of each of these presentations (ITHAKA S+R, UNCC, CUMU-12), I illustrated the breadth of computer science course offerings online with 4 slides (https://my.vanderbilt.edu/douglasfisher/files/2012/02/CSMajorOnline.pdf ), showing that one could come close to fulfilling the course requirements of a typical CS major online and free. I was also presenting this material from the perspective of an instructor, so my focus was on how instructors could add to online content, allowing others still to customize, drawing from expanding online content.
Since these presentations and the ProfHacker post, my graduate "Individual Studies" course (CS 390) in Fall 2012 on Machine Learning has finished; this course was a "wrapper" around Andrew Ng's COURSERA (Stanford) course. The requirements of the CS 390 included the requirements (quizzes, homeworks) of the COURSERA course. There were 10 graduate students who completed the CS 390 course. You can look at the details of the course organization, roughly a cross between a more structured upper division undergrad class (the COURSERA component) and a graduate seminar course (the face-to-face component), at https://my.vanderbilt.edu/cs390fall2012/, should you wish. Rather than feeling more like a TA (it has been suggested by some that faculty roles might morph into glorified TAs under a blended model), I felt LESS like a TA, and more like an "old-school" prof (I suppose as portrayed in 1940s and 50s movies :-), interacting closely with students in class. But there are models of blended learning besides the one that I used, and probably better fits to different preferences.
The CS 390 OVERALL RATINGs (as coded on Vanderbilt's forms, each on a 1...5 range, 5 being "best") for the instructor/course (4.16/4.16) were comparable to the "regular" Spring 2012 Machine Learning (CS 362) offering (4.33/4.22) and my other Fall 2012 courses of CS 360 (4.50/4.25) and CS 260 (4.25/4.00 ). Derek Bruff and others at Vanderbilt/s Center for Teaching did a mid semester evaluation, we have identified ways to improve, and we are working on further evaluation. On the whole it seems that the wrapper was a well appreciated course.
Despite this CS 390's more structured (COURSERA) component, the CS 390 required no more than 1/4 the time as my upper-division AI course (CS 260), probably considerably less than that, because the COURSERA platform was doing work of lectures and grading. A very specific consequence of my CS 390 experience is that I may advocate offering CS 362 (Machine Learning) yearly (instead of every other year), if it can be done as a wrapper (all or some of the time). Coincidentally, there is at least one other ML MOOC coming online soon, enabling more customization across the two MOOCs, to say nothing of the material that I will put up (e.g., on YouTube), as I have done for CS 260; in fact, I have a couple of "best sellers", which resulted from students of yet another AI MOOC looking for clarification on a couple of algorithms (i.e., generalized arc consistency and iterative deepening): https://www.youtube.com/channel/UCWOFdpEfNuQP3O_JUiwhT8A.
More generally, most commentaries point out that reduced faculty workload per course (nonetheless, regarded by students and faculty as strong courses!!!) would enable more high-quality electives for a fixed staff level, and it would allow a finer granularity in assessing faculty workload; finer granularity in characterizing course workload could translate into finer granularity in course buyouts, enabling even a heavily committed research faculty member to lead a (blended) course, etc. I haven't seen the increased flexibility of faculty buyouts mentioned in previous commentaries, but I suspect that some of the most grant-committed faculty would like to get in front of a class of undergrads if it just didn't take so much time, and of course, I'm sure undergrads would love this too.
A GRADUATE-LEVEL INDIVIDUAL STUDIES course, such as my CS 390, seemed like the most conservative next step into formal blended learning courses, but the online CS offerings through COURSERA particularly (but EdX and Udacity too, and to include "opensource" initiatives), are large, giving lots of opportunities for blended courses -- again, recalling the "CS major online" (https://my.vanderbilt.edu/douglasfisher/files/2012/02/CSMajorOnline.pdf ). And because CS enrollments are busting at the seams, CS is perhaps an ideal program to be designing and vetting blended learning courses.
My initial thoughts are that "standard format" ("the way" we have always done it) might remain ideal for core classes (we don't want our faculty's skills to atrophy!!!), as well as for electives that correspond to the primary expertise of instructors, but offering electives that blended courses, for which there is limited existing faculty expertise, but for which there would be student (and faculty) interest. My limited experience is that students would like and appreciate this stretch; and I, for one, would love to learn with a group of students in an area that I was not expert in; faculty member as "lead learner" is only one blended model, albeit much different than the CS390 model I have experience with.