Thursday, December 15, 2011
Stanford classes -- what I'd do next
Now that the ML and AI courses are at an end, here are some of the things I would do moving forward.
Both courses already have a basic track where students just watch the lectures and do the in lecture quizzes and an advanced track where students also complete weekly assignments. I think we can be certain that there were students who just watched a few lectures, many who completed every assignment, and those who fell at all points in between.
On top of this, there were students who made use of the on line discussion groups and those who didn't.
This means there ware a wide range of experiences to be had.
With this in mind, here's what I would do.
Suggestions dealing with basic site content:
More practice problems, particularly in AI
While there were in video quizzes each week that provided practice, it would have been nice if there was a link to additional optional problems (preferably with solutions available). This would be easy to implement. The ML class would also benefit from this, but since you could retake the weekly assignments and get some variation on the questions, it would be as necessary.
Better reference materials
Reference sections would be nice as well. The AI staff posted related sections from the text, but there were a number of great on line resources I discovered by reading the discussion groups. Perhaps some of these could be linked to from the main site.
Grading
I'm pretty sure that having weekly assignments that were actually graded helped keep me honest. The fact that the ML course was submit as many times as you want and the AI course was one shot didn't matter. I put the same effort into both classes. In a way I preferred the ML course. I was frustrated a few times when I mis-entered something on a homework or forgot to convert units and got a lower grade than I thought I should have (I know, the grade doesn't really count).
I'd actually kind of like the AI course to move more towards the ML class model. The grades don't really count for anything anyway, and if they did, there are so many X-factors.
For example, if some one has to do the weekly assignment early due to obligations later in the week, he or she can't make use of clarifications. Likewise, students probably had widely varying amounts of time to dedicate towards the course. Contrast that to the traditional undergrad student probably has a similar workload to the other people in their classes. In the ML class, it all really didn't matter.
Office Hours:
I wasn't a huge fan of the office hour questions in the AI class but I very much liked the idea of seeing the profs directly answering weekly questions, it helped connect the instructors and the class. This was lacking in the ML class and should be added.
On running the class in the future:
What made these classes different from other on line lectures was that these were "live" with a staff releasing new content, opening and closing assignments, and adjusting as the course progressed. Each class also had a large number of people taking the class at the same time. Far different than say someone arbitrarily to watch videos from an Open Class Ware course.
I'd like to believe that the live staff, real deadlines, and large cohorts had a significant psychological effect. I've started on line courses in the past but rarely finished them. I think the weekly deadlines and "live" aspect of the course got me to start early each week and forced me to stay up to date.
With this in mind, Stanford could just run the courses again in a similar manner, possibly with some one else acting as "instructor" to field office hours and oversee the course.
In addition I'd allow people to take the courses in the following ways:
Solo:
Since many people probably didn't avail themselves of the discussion groups, there's no reason not to allow someone to start at any time. All that would be needed is the ability to have them submit projects, quizes, etc. If the system could do that, Anyone could take the course at any time, albeit without interaction with others.
Cohort:
People could sign up with a start date or number of students in mind. When that's reached, a cohort group can start the class. The discussion pages could be modified so that a cohort can go to it's own discussion page and the system can dole out lectures and assignments on a pre-determined schedule. This would allow the course to start at a range of times while making sure that students had a community of learners to support each other via discussion groups.
Facilitated:
Similar to Cohort but someone would sign up as a facilitator. They would moderate the discussion group and control the flow of lectures and assignments. There could even be a way of "licensing" facilitators so they could run official versions of the classes. This way, a local group or school could run the class on their schedule.
So, there you have it. How I'd modify Stanford's great educational experiment. Next time, I'll share my thoughts on on-line education and how it's (mis) used in our high schools.
Labels:
AI,
ai-class,
artificial intelligence,
computer science,
education,
machine learning,
ML,
ml-class,
Stanford
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The grades do matter as the top 1000 scorers in the AI class were sent an email by Dr Thrun offering to facilitate a job interview with a well known search company in silicon valley.
ReplyDeleteMaybe but no one entered the course with any expectations of such a reference (or at least they shouldn't have).
ReplyDeleteNow, for people like me -- I'm 44, not seeking other employment and if I were, I have a sufficient network of contacts to arrange interviews, the reference isn't much of a draw. I'd imagine the same would be true of other experienced people taking the course.
For the younger crowd taking the course, I'd imagine a real hotshot who is acing everything would be able to open the doors anyway.
In any event, it's just the possibility for an opportunity for an interview.