Fortnightly Mailing

New from ICTP: an app that compiles images and audio into video-like recording

The International Centre for Theoretical Physics (ICTP) in Trieste plays a key role in training physicists from developing countries. Some readers will remember Enrique Canessa and Marco Zennaro's terrific presentation in London in May 2011 about ICTP's elegant low-tech automated lecture capture system, which allows archiving and sharing traditional lectures and talks carried out using, for example, very large chalkboards found in classrooms and/or using more modern presentations systems. ICTP has just released EyApp which is an iPhone app that applies the same principals. From the media release:

EyApp enables your iPhone, iPad or iPod Touch to make a video composed of a series of captured images along with simultaneous audio recording. With just the press of a button, the App automatically captures images at intervals ranging from 5 to 20 seconds (or manually by the user) and then synchronizes the images with a continuous audio signal.

The resulting recording is a smaller size compared with traditional video (HD or standard resolution) because the still frames can be processed by the highly-efficient compression algorithms used by the H264 movie format found in modern mobile i devices.

The film is then ready to be shared immediately or, when saved on a device's photo/movie gallery, can be further edited with other Apps, shared by email and rich-media messaging systems or via social networking Apps, or transferred to a computer. EyApp makes it easy to create personal recording archives as well as to share them via YouTube.

An Android version is follow, and EyApp is available now for download from the iPhone App Store. My feeling is that combined with a Swivl to hold the recording device, EyApp would have specially good potential for low-cost systematic capture of workshops and speaker sessions.

The need to try lots of MOOCish things at the same time

I think Stephen Downes (picking up on analysis by Michael Feldstein) hits the nail on the head in this comprehensive well-linked commentary on developments in Californian HE relating to online learning, MOOCs etc. Specifically:

The problem, to my mind, is that the aristocrats - the professors - fundamentally don't care whether the sysem is accessable or affordable. Tha's what has to change. Feldstein proposes:

• aggressive program of experimentation and evaluation
• a data-driven and public conversation about the cost and sustainability models
• personas and use cases that help the stakeholder groups have focused and productive conversations

I think the initiatives have to reach beyond mere planning (there's always the clarion call from  professors for "more research" and a "coordinated program" and an "emphasis on quality", but at a certain point it becomes more important to do than to plan, to try a bunch of things on a larger scale and take notes about what worked and what didn't).

Worthwhile also reading Donald Clark's MOOCs: ‘dropout’ a category mistake, look at ‘uptake’? which concludes:

We need to look at uptake, not dropout. It’s astonishing that MOOCs exist at all, never mind the millions, and shortly many millions, who have given them a go. Dropout is a highly pejorative term that comes from ‘schooling’. The ‘high school dropout’. He’s ‘dropped out of ‘University’. It's this pathological view of education that has got us into this mess in the first place. MOOCs are NOT school, they eschew the lecture hall and are more about learning than teaching. MOOCs, like BOOKs, need to be seen as widely available opportunities, not compulsory attendance schooling. They need to be encouraged, not disparaged.

Douglas Adams via Donald Clark. This stuff is "alright really".

Donald Clark ends his recent talk at TEDxGlasgow with a nice quote from Douglas Adams's 1999 How to Stop Worrying and Learn to Love the Internet:

1. Everything that’s already in the world when you’re born is just normal.
2. Anything that gets invented between then and before you turn thirty is incredibly exciting and creative and with any luck you can make a career out of it.
3. Anything that gets invented after you’re thirty is against the natural order of things and the beginning of the end of civilisation as we know it until it’s been around for about ten years when it gradually turns out to be alright really.

[Source]

The talk is a nicely condensed and developed version of Donald's "Don't Lecture Me" from the 2010 ALT conference, here presented alongside its associated Twitter-stream:

Disclosure. I (still, but not for much longer) work part time for ALT.

Taking the red pill: Sebastian Thrun's candid reflection on the AI course

After a horribly embarrassing introduction, this 25 minute talk yesterday by Sebastian Thrun gives Thrun's own candid and personal reflection on last Autumn's AI course, which had 160,000 sign-ups (nearly 100,000 of whom were on the advanced track), 46,000 submitters of the first homework, 23,000 submitters of the mid-term exam, and 20,000 who completed the final exam.

Highlights of the talk:

• the large drop-out rate from the lectures on the same course at Stanford, with students preferring to use the free video-based version;
• a volunteer army of ~2000 translators;
• individual feedback from students in terrible places in the world or under big social pressure who completed the course;
• Thrun's own epiphany concerning the wrongness of "weeder" classes;
• Thrun's decision not to teach by lecture at Stanford again and instead to concentrate his efforts on a private venture-capital funded initiative called Udacity, whose online courses will be free.

Udacity aims to enrol 500,000 students on its first two courses: CS101- Building a search engine; CS373 - Programming a robotic car.

My own and others' reports from the AI course.

Interviews about "remote learning" with Dan Cardinali, Paul Mitiguy, and Peter Norvig

Here are links to three November 2011 "canteen" interviews (audio and, in two cases helpful text transcripts) with Peter Norvig (Director of Research at Google), Dan Cardinali (President of Communities in Schools) and Paul Mitiguy (Senior Consulting Professor of Mechanical Engineering at Stanford University). The interviews form part of the resources of an undergraduate project by Deniz Kahramaner, Jon Rodriguez and Ben Kallman about "the challenges and ethical implications of implementing large-scale distance education platforms". 

The interview with Peter Norvig draws on his contemporaneous experience with the Stanford/KnowLabs Introduction to Artificial Intelligence course [November 2011 article in ALT News Online; my weekly reports from the course] and contains several perceptive and diverse insights, ranging over:

• course design (and the advantages of combining the deadline driven "discipline" of face-to-face learning with the "anytime anyplace" nature of asynchronous learning);
• the advantages (from a learner's point of view) of video, and challenges (from a course design point of view) of using it;
• the need for design/production environments for teachers and for experimentation/exploration environments for learners;
• the value, from a learning point of view, of ambiguity in presentations and open-endedness in questions;
• recruitment (and a possible business model for providers of free remote education);
• the possible motivations for teachers to contribute to the production of free courses;
• the need for collegiality and collaboration between the start-ups that are getting involved in online education.

Unexpected - how an open course's conventional exam can prompt subsequent learning

Graph by automagic using code by pedrosorio.
Other posts tagged ai-course.

The AI course finished this week. Here is a link to a discussion thread involving some very mathematically able people discussing, after the exam results were in, a "disputed" mark concerning an exam question about a statistical technique called Laplace smoothing.

I'm not making a point about the substance of the discussion (a lot of which is over my head), or about the underlying investigation (which is even more so).

But the interesting thing is the way that this open course, with its underlying conventional, assessed structure, has resulted in a great deal of very high level collaborative research, investigation, and discussion, which has gone far beyond its (first year US undergraduate) boundaries.

Even if the subject matter of the post is outside your ken, it is worth taking in the kinds of reflections that contributors are making, for example:

"This is really the sort of thing and the sort of thinking and exploring that I believe professors really want to see result from efforts to teach stuff in class (whether in K-12 or undergraduate or graduate school). This one little question has generated more serious inquiry than anything else I have seen so far from our class...... But THANK YOU for all of the serious and thoughtful responses to this question which it has been a pleasure to read."

 

Sitting in a bar with a really smart friend. The ai-class: Notes from a Lab Rat

Guest Contribution by Rob Rambusch

Picture by Ressaure (CC licensed)

Me: Test Subject

Rob Rambusch is a Project Manager for software development and implementation based in New York City. This was his first exposure to any class on Artificial Intelligence. He can be contacted at robrambusch [AT] gmail.com, or through Google+.

It: Experiment

"A bold experiment in distributed education, "Introduction to Artificial Intelligence" will be offered free and online to students worldwide from October 10th to December 18th 2011. The course will include feedback on progress and a statement of accomplishment. Taught by Sebastian Thrun and Peter Norvig, the curriculum draws from that used in Stanford's introductory Artificial Intelligence course. The instructors will offer similar materials, assignments, and exams."

Them: Experimenters

"Peter Norvig is Director of Research at Google Inc.  He is also a Fellow of the American Association for Artificial Intelligence and the Association for Computing Machinery. Norvig is co-author of the popular textbook Artificial Intelligence: A Modern Approach. Prior to joining Google he was the head of the Computation Sciences Division at NASA Ames Research Center."

"Sebastian Thrun is a Research Professor of Computer Science at Stanford University, a Google Fellow, a member of the National Academy of Engineering and the German Academy of Sciences. Thrun is best known for his research in robotics and machine learning."

 One Month Before: Preparation

I started working on the prerequisites in the month before the course began. I prepared for the class by learning Probability and Linear Algebra from Salman Khan at the Khan Academy website. I followed up by watching lectures on Linear Algebra by Gilbert Strang at the MIT OCW website. So even before the class began I had exposure to two common online teaching styles, the filmed lecture and the video tutorial.

Final report from the Norvig/Thrun/Stanford/Know Labs Artificial Intelligence course

Word-cloud by Sea Otter

(Other posts tagged ai-course. Post originally published on 20/12/2011, with paragraph one updated to incorporate completion numbers kindly provided by David Stavens of Know Labs, and a new concluding sentence to the final paragraph.)

Along with just over 20,000 others (some 3,000 fewer than had taken the midterm exam) I completed the final examination for the free online Introduction to Artificial Intelligence course taught by Sebastian Thrun and Peter Norvig. Here is my final participant's  report from the course.

1. The final section of the course concerned Natural Language Processing. I've had an interest in machine translation for some years [e.g.]: and it was this interest that initially made me aware of Peter Norvig's work.) So for me this meant that the best part of the course came last, and if you want to gain an underlying appreciation of the science of natural language processing, it will take you a couple of hours to work through the courses 42 short videos about NLP, starting here. It is probably worth doing despite a certain amount of dependency on earlier sections of the AI course.

2. The course has been mercifully free from programming assignments: being capable of completion using pen and paper, a calculator (and on a couple of occasions a slide rule unused since 1973).  To conclude the NLP unit there were two optional programming problems, both of which could be tackled without programming. I did the second of the problems (recovering a message from a shredded version) using scissors and adhesive tape:

Food for thought. Video recording of Q&A session between Sal Khan, Peter Norvig and Sebastian Thrun

There is plenty of food for thought and a great deal to identify with - from a very diverse set of angles - in yesterday's 45 minute "Google+ Hangout" discussion between Sal Khan, Peter Norvig and Sebastian Thrun. Examples include:

• the authenticity and hence superiority of unscripted, tentative explanations, with "low" production values;
• how lectures empower lecturers not students;
• data analysis as an "underpinning process" for real personalisation;
• why their is such a mismatch between the value that a university thinks its courses provide what students think they provide;
• the challenge of combining individual study with group interaction.

 

Eighth report from the Norvig/Thrun/Stanford/Know Labs Artificial Intelligence course

(Other posts tagged ai-course.)

Here is my eighth participant's report from the Stanford Introduction to Artificial Intelligence course.

Last week's report focused mainly on the midterm exam, and on a conversation with Sebastian Thrun. This report conments on the midterm exam and reflects on the way the course has run this week.

First, some comments on the midterm exam

1. According to information just received from Sebastian Thrun, 23k students passed the midterm, with 85% currently falling into the B+ range.

2. There was a surprising amount of post-exam discussion between students about the substance of the exam. There was some whingeing, but not much given the very large numbers on the course.  The interesting discussion fell into three categories: