[Decided to remove image of scratch pad shortly after publishing this.]
In September 2007 I had a personally revelatory moment concerning how AI (as I now know it to be) might be used to provide formative feedback for learners. It stemmed from being involved in running the 2007 ALT conference at which Dylan Wiliam and Peter Norvig each gave keynote speeches. With Richard Noss (who now directs the ESRC/EPSRC funded TEL programme) we set up a Google Doc "scratch pad" to gather a shortlist of issues that could be worth examining. Not a lot (well, nothing!) came from it, as is often the way.
Here are the playlists for videos of keynote and invited speaker sessions from the 2011, 2010, and 2009 Association for Learning Technology conferences. Below is a selection from the 2011 conference. Hat tip to Darren Moon and Danny Blandy for the snazzy ALT-branded opening and closing "indents". At the time of writing, less than five days after publication, John Naughton's talk had been viewed over 7,000 times . [Disclosure: I work half time for ALT.]
12 1 - "The educational and social impacts of Plan Ceibal -- a new approach to the use of technology in education" by Miguel Brechner 2 - "The elusive technological future" by John Naughton
34 3 - "I Have a Blind Student in My Maths/Science Class, Should I panic? How to promote inclusion for blind students" by Dónal Fitzpatrick 4 - "On being public...how social media reshapes professional identity" by Anne-Marie Cunningham
Last week's attempt to run an "office hours" session in real time did not work. In substitution for it, two short videos have been published with Peter Norvig and Sebastian Thrun responding informally to the most voted on questions submitted by students prior to the session. More such recordings will follow. I've embedded the videos below because they:
give a lay person some sense of why the AI field is important and interesting;
contain pointers to what may be coming next from Norvig and Thrun by way of further online courses.
Note the explicit references to the course team's intention to:
develop a course at a more introductory level than the current one;
get to grips with extracting meaning from the data that is being collected about, for example, learners' use of the materials and, I am assuming, the relationships between things like use and progress.
(The two sessions - do not be deceived by their very similar "thumbnails" - are respectively 13 and 8.5 minutes long.)
The paths of blindfolded walkers trying to walk in a straight line in overcast (blue) and sunlit (yellow) conditions. From Unit 8.2 of Introduction to Artificial Intelligence course.
1. I'd finished the work before I noticed that, unannounced, the order of the course had been changed from that shown in the originally published outline. Thus units on Representation with Logic, and Planning, taught by Peter Norvig, have come before the originally scheduled units on Hidden Markov Models and Bayes Filters.
2. This change of order probably explains why this week's study felt somewhat disconnected from last week's, a fact emphasised by a change of teacher from Sebastian Thrun to Peter Norvig. Thrun, it has to be said has a less austere and more down-to-earth presence than Norvig, whose delivery style is dry and very concentrated. Underlying this, I think Norvig's material on propositional logic and on mathematical representations of plans is by its nature relatively abstract: and for me this spells trouble, being someone who has always tended to struggle with the abstract.
3. The advice I'd give from a course design point of view is to further strengthen the illustrations as to why these kinds of abstraction matter. The video from which the picture above is taken a good example of this:
4. Secondly this kind of more abstract content needs more rather than less use of "dialogic" check questions, as has been the case in other units of the course. To illustrate this point here are the contents-lists of Units 4 and Units 8. Check-questions are indicated by ?. 12 sets of check questions out of 21 sections is a much more promising ratio than 3 out of 22.
5. During the last week Sebastian Thrun and Peter Norvig ran an online "office hours" session using a Google Plus "Hangout". I was not around to try to join this, but from Thrun's "We apologize for the large number of people who were denied participation in the online office hours via youtube. We had a lively discussion which was recorded on video - mostly on topics beyond this course (e.g., what are great research topics). We will soon post the video on this site. Apologies again. Technical problems with the Hangout-Youtube link." it looks as if this was a partial success. I think this is a "forgivable" issue, given the very large number of people who will have attempted to take part in it.
6. Next week I hope to find out whether and if yes by how much the participation rate has changed, as measured by the submission of homework for weeks 3 and 4.
This is a shorter report than #1-3, mainly because the course has got into a rhythm and because there've been no substantial changes in delivery methods.
1. Despite the work that has been done to the web systems that sit behind the site, it looks as if there were again overload issues at and around the week 2 homework submission deadline, and this despite the probability the number submitting homework may have dropped quite a bit dropping by nearly 20% to ~37,000 from the ~46,000 reported after the week 1 homework deadline.
2. The course continues to fascinate. For example it is nice to gain a practical understanding of how things like spam filters actually work.
For more than half my working life I have been engrossed by on-line distance learning (yes - since 1992). I've been unable to resist giving the course organisers a piece of my mind about aspects of the underlying course design, having been given active encouragement to do so. I've pasted at A below an excerpt from some feedback provided to Know It!'s David Stavens earlier this week.
The rest of this report concerns my experience of the course as a learner over the last week.
Final paragraph updated 18/10/2011, and 23/11/2011
Here is my second participant's report from the Stanford Introduction to Artificial Intelligence course.
1. Over the last week I worked through the second section of the course - Problem Solving - consisting of nearly 40 short, low-tech videos. I described the pleasing, quirky, design of these in the first report.
2. Here you can review the Problem Solving materials, without being logged into the course. If you click on "cc" in the video-control bar you will see how the videos have been captioned and translated in multiple languages (by volunteers, using the dotSUB platform).
Yesterday evening I worked through the introduction to the course.
Here is a key point report.
1. There have been the usual start-up hiccups [snapshot at 08.00 UK time 10/10/2011) about which I am not complaining.
2. The content consists of 1-6 minute "Khan-style" videos of diagrams being written and talked about by Peter Norvig or Sebastian Thrun. And there has been some clever/wise truncation in the videos so that they run at the speed of the presenter's voice rather than taking the time it took to write the diagrams.
Marsden's piece is wide-ranging, and it draws on the knowhow of several people in UK HE, including Nial Sclater and Susanah Quinsee.
But it was filed some time ago1: if Rhodri had done a bit more digging at the time, the possibility that Stanford or an associated business might be looking to pilot a delivery method for future commercial or revenue-generating use might not have escaped him.
Using AI in formative and summative assessment
[Decided to remove image of scratch pad shortly after publishing this.]
In September 2007 I had a personally revelatory moment concerning how AI (as I now know it to be) might be used to provide formative feedback for learners. It stemmed from being involved in running the 2007 ALT conference at which Dylan Wiliam and Peter Norvig each gave keynote speeches. With Richard Noss (who now directs the ESRC/EPSRC funded TEL programme) we set up a Google Doc "scratch pad" to gather a shortlist of issues that could be worth examining. Not a lot (well, nothing!) came from it, as is often the way.
Doing the Stanford AI course (see also my piece in ALT News Online) has sensitised me to current work on the same thing.
Here are some examples. If you know of others, please post them as comments and I will collate them.
Posted on 19/11/2011 in ai-course, Lightweight learning, News and comment | Permalink | Comments (0)
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