The Student as Creator – Making Patterns, Not Just Following Patterns
Posted: May 10, 2012 Filed under: Education | Tags: design, education, higher education, maze, modes of thinking, teaching, teaching approaches, thinking Leave a commentWe talk a lot about what we want students to achieve. Sometimes the students hear the details and sometimes they hear “Do your work, pass your courses, get your degree, wave paper in air, throw hat, profit.” Now, of course, sometimes they hear that because that’s what we say – or that’s what their environment, the people around them, even the employers say.
The image above is a Chinese-inspired maze pattern. Composed of simple elements, it can become complex quickly. If you built a hedge maze along these lines you could probably keep a lot of people lost for some time, simply because they wouldn’t necessarily be able to decompose the maze to the simple patterns, work out the composition and then solve the problem.
I can teach someone to follow a maze easily. In fact, this is probably done by the time they’ve finished school. Jump on the track, do your work, stay inside the lines, keep walking until you find the goal. Teaching someone to be able to step back, observe the patterns and then arrive at the goal more efficiently can also be taught, or it can arrive with experience. But, going further, being able to look at the maze and construct a brand new maze, potentially with new patterns or composition techniques, requires inspiration. You can reach this point with a fantastic brain and a lifetime of experience (we must have been able to do this) but, these days, we can also teach students abstraction, thinking, the right way to go about a problem so that they move beyond following the hedges or being able to build exactly the same kind of maze again.
This brings the student into a new mode of thinking: as a creator, rather than a pattern matcher or a follower. It is, by far, the hardest things to teach as it requires you to concentrate on providing an environment that supports and encourages creativity, as well as making sure that no-one is trying to build mazes that defy gravity, or where you can walk through concrete walls. (I note that these initial grounding constraints may relax later on – once people have a good grasp of the basics, creativity can take them to places where you can walk through walls.)
Of course, focussing on the mechanics of getting the piece of paper at the end of the degree, as if this was the objective, doesn’t lead to the right way of thinking. Getting into the right space requires us to focus on what should really be happening: the successful transfer of knowledge, the building of frameworks for knowledge development and a robust basis for creative and critical thought. This can, and does, occur spontaneously – but trying to make it happen more often results in a much larger group of people who can, potentially, change the world.
Deadlines and Decisions – an Introduction to Time Banking
Posted: May 9, 2012 Filed under: Education | Tags: education, higher education, learning, measurement, perry, reflection, resources, teaching, teaching approaches, time banking, time management, tools 3 CommentsI’m working on a new project, as part of my educational research, to change the way that students think about deadlines and time estimation. The concept’s called Time Banking and it’s pretty simple. Some schools already give students some ‘slack time’, free extension time that the students manage to allow them to manage their own deadlines. Stanford offers 2 days up front so, at any time in the course, you can claim some extra time and give yourself an extension.
The idea behind Time Banking is that you get extra hours if you hand up your work (to a certain standard) early. These hours can be used later as free extensions for assignment, up to some maximum number of days. This makes deadlines flexible and personalised per student.
Now I know that some of you already have your “Time is Money, Jones!” hats on and may even be waggling a finger. Here’s a picture of what that looks like, if you’re not a-waggling.
“Deadlines are fixed for a reason!”
“We use deadlines to teach professional conduct!”
“This is going to make marking impossible.”
“That’s not the right way to tie a bow tie!”
“It’s the end of civilisation as we know it!” (Sorry, that’s a little hyperbolic)
Of course, some deadlines are fixed. However, looking back over my own activities during the past quarter, I have far more negotiable and mutable deadlines than I do fixed ones. Knowing how to assess my own use of time in the face of a combination of fixed and mutable deadlines is a skill that I refine every year.
If I had up late, telling me to hand up on time or start earlier doesn’t really involve me in the process that’s required: making a decision as to how I’m going to manage all of my commitments over time, rather than panicking when I run into a deadline.
I can’t help thinking that forcing students to treat every assignment deadline as fixed, whether it needs to be or not, doesn’t deal with the student in the way that we try to in every other sphere. It makes them depend upon the deadline from an authority, rather than forcing them to look at their assignment work across a whole semester and plan inside that larger context. How can we produce students who are able to work at the multiplicity or commitment level, sorry, Perry again, if we force them to be authority-dependent dualists in their time management?
Now, before you think I’ve gone mad, there are some guidelines for all of this, as well as the requirement to have a good basis in evidence.
- We must be addressing an existing behavioural problem. (More on this later.)
- Some deadlines are immutable. This includes weekly dependencies, assignments where the solutions are revealed post submission, and ‘end of semester’ close-off dates.
- The assessment of ‘early and satisfactory’ must be low effort for the teacher. We don’t want to encourage handing up empty assignments a week ahead. We want to encourage meeting a certain standard, preferably automatically assessed, to bring student activity forward.
- We have limits on the amount you can bank or spend, to keep assessment of the submitted materials inside the realm of possibility and, again, to reduce unnecessary load on the staff,
- We don’t tolerate bad behaviour. Cheating or system fiddling immediately removes the system from the scheme.
- We provide up-front hours to give all students a base line of extension.
- We integrate this with our existing ‘system problem’ and ‘medical/compassionate problem’ extension systems.
Now, if students don’t have a problem, there’s nothing to fix. If our existing fixed deadline system encouraged students to start their work at the right time and finish in a timely fashion, then by final year, we wouldn’t need anything like this. However, my data from our web submission system clearly indicates the existence of ‘persistently’ late students and, in fact, rather than getting better, we actually start to see some students getting later in second, third and honours years. So, while this isn’t concrete, we’re not seeing the “Nope, no problem here” behaviour that we’d like. So that’s point 1 dealt with – it looks like we have a problem.
Most of the points are technical issues or components of an economic model, but 6 and 7 address a more important issue: equity. Right now, if your on-line submission systems crash the day before the assignment is due, what happens? Everyone who handed in their work has done the right thing but, because you have to grant a one day extension, they actually prioritised their work too early. Not a huge deal in many ways, because students who get their work in early probably march to a different drum anyway, but it makes a mockery of the whole fixed deadline thing. Either the deadline is fixed or it isn’t – by allowing extension on a broad scale for any reason, you’re admitting that your deadline was arbitrary.
We’re trying to make them think harder than that.
How about, instead, you hand out 24 hours of time in the bank. Now the students who handed up early have 24 hours to spend later on and the students who didn’t get it in before the crash have a fair chance to get their work in on time. Student gets sick, your medical extensions are now just managed as time in the bank, reflecting the fact that knock on effects can be far greater than just getting an extension for a single assignment.
But we don’t go crazy. My current thoughts are that we’d limit the students to only starting to count early about 2 days before the assignment is due, and allow a maximum of 3 days extension (greater for medical or compassionate). This keeps it in our marking boundary and also, assuming that you’ve placed your assignments in the context of the appropriate knowledge delivery, keeps the assignments roughly in the same location as the work – not doing the assignment at the beginning of the term and then forgetting the knowledge.
So, cards on the table, I’m writing a paper on this, identifying exactly what I need to look at in order to demonstrate if this is a problem, the literature that supports my approach, the objections to it and the obstacles. I also have to spec the technical system that would support it and , yes, identify the range of assignments for which it would work. It won’t work for everything/everyone or every course. But I suspect it might work very well for some areas.
Could we allow team banking? Course banking? Social sharing? Community involvement (donation to charity for so many hours in the bank at the end of the course)? What could we do by involving students in the elastic management of their own time?
There’s a lot more but I’d love to hear some thoughts on it. I look forward to the discussion!
Spot the Computer Science Student and Win!
Posted: May 8, 2012 Filed under: Education | Tags: advocacy, computer science, computer science student, education, higher education, learning, measurement, resources, stereotype, student, teaching approaches 1 CommentCS Students get a pretty bad rap on that whole “stereotype” thing. Given that I’m an evidence-based researcher, let’s do some tests to find out if we can, in fact, spot the CS student. Here’s a quick game for you. Hidden in this image are 3 Computer Science students.
Which ones are they? (You can click on the image to enlarge it.)
I’ll make it easy for you to reference them – we’ll number the rows from the top (A) to the bottom (H) and the images from left to right as 1 to … well, whatever, because the rows aren’t the same length. So the picture with the cactus is A2, ok? Got it? Go!
Who did you pick? Got the details? Now scroll down.
Of course, if you know me at all, you probably know the answer to this already.
They’re ALL Computer Science students – well, they’re found in an image search for “I am a Computer Science student” and, while this is not guaranteed, it means that most of these students are in CS. Now, knowing that, go back and look at the ones you thought were music majors, physicists, business students, economics people. Yes, one or two of them probably look more likely than most but – wait for it – they don’t all look the same. Yeah, you know that, and I know that, but we just have to keep plugging away to make sure that everyone ELSE gets that. Heck, the pictures above are showing less pairs of glasses per person than you would expect from the average and there’s not even one light sabre! WON’T SOMEONE THINK OF THE STEREOTYPES???
This is only page 2 of the Image Search and I picked it because I liked the idea of some inanimate objects being labelled as CS students as well. Oh, that’s right, I said that you’d win something. You know never to trust me with statements unless I’m explicit in my use of terminology now. Sounds like a win to me!
(Of course, the guy with red hair is giving the strong impression that he now knows that you were looking at him on the Internet. I don’t know if you wanted that but that’s just how it is.)
Heroes
Posted: May 7, 2012 Filed under: Education | Tags: advocacy, alan turing, Arland D Williams, Arland Williams, bruno schulz, education, heroes, higher education, inspiring students, learning, reflection, teaching, teaching approaches, turing, work/life balance 1 CommentI know that I learn best when I’m inspired and engaged, so I regularly look for things around me that I can bring into the classroom that go beyond “program this” or “design that”. Our students are surrounded by the real world and, unfortunately, it’s easy to understand why they might be influenced by things that are less than inspirational. I don’t want to be negative, but there are so many examples of bad behaviour on the national and international stage that, sometimes, you really wonder why you bother.
So, today, I’m going to talk about four people. Regrettably, three of them some of you won’t be able to talk about because of personal convictions, political considerations or the ages of your class, but I hope that most of you will either have learned something new or remembered something important by the time I’m finished. Are these people actually heroes, given the title of my post? Well, one is a professional inspiration to me, one is an artistic inspiration to me (and reminder of the importance of what I’m doing), one is generally inspiring in the area of democracy and dedication, and the other… well, the other, I can barely look at his picture without wondering if I could ever approach the level of selflessness and heroism that he demonstrated. But I’ll talk about him last.
This is Alan Turing, the most likely candidate for the term “Father of Computer Science”. Witty, well-educated, highly intelligent and thoughtful, he was leader in cryptanalysis at Bletchley Park, providing statistical and mathematical genius to breaking codes including the design of the bombe, the machine that attacked Enigma. Importantly, for me as a Computer Scientist, he developed Turing Machines, effectively providing the foundations of studies in the theory of computation. He provided the first detailed design of a computer that used a stored program, very different from the electrical calculators of the day. He defined some of the key terms that we still use in Artificial Intelligence. (There’s so much more but it wouldn’t mean much to you outside the discipline, but he’s well worth looking up.)
Of course, some of you can’t mention Turing to your students, because he was a known homosexual, with a conviction for gross indecency in 1952 after admitting to a consensual homosexual relationship. He had a choice between imprisonment or chemical castration (he chose the latter) and his security clearance was revoked and he was barred from continuing with his security work. He was found dead in 1954, having (most likely) committed suicide.
There is no doubt that the field I am in is the better (or even exists) for Turing having lived and worked in this field. We are poorer for his early loss and, personally, I’m ashamed that persecution based on his sexual orientation may have led to the premature self-administered death of a genius.
Meet Bruno Schulz, author, artist and critic. Schulz wrote some incredible works, contributed murals and was, despite his somewhat hermitic nature, an influential contributor to the arts. Schulz was born and lived, for most of his life, in Drohobych, Galicia. His contributions, although limited by his early death, include the highly influential works “Sanatorium Under the Sign of the Hourglass” and “The Street of Crocodiles”. In 1938, he was awarded the Polish Academy’s Golden Laurel award for his works and translations.
I am currently writing a series of stories that were inspired, in part, by the “Sanatorium” with its dreamlike qualities, stories interweaving with unreliable narration and innate and unexpected metamorphoses. Schulz is a fascinating counterpoint to Borges for me, woven with the immersion in Jewish culture I would expect from Singer, but with a different tone that comes from through, even in the English translations I have to read.
We have no more works from Schulz, not even the fragments of the book he was working on at the time of his death “The Messiah”. Why was Schulz killed? After the German invasion of the Soviet Union in the Second World War, Drohobych was occupied and, for a time, Schulz (who was Jewish) was protected by a Gestapo officer who admired his artistic work. Unfortunately, another Gestapo officer, a rival of the first, decided to kill this “personal Jew” and shot Schulz on the way home. You will excuse me for being confusing by referring to neither officer by name.
This person you may have heard of. Fang Lizhi died very recently, a Chinese Astrophysicist who lived in exile for over 22 years, after a life spent trying to pursue science despite being politically persona non grata and, for many years, not being able to publish under his own name. He survived hard labour during his re-education by the worker class during the cultural revolution but continued to fight against what he saw as severe obstacles to the pursuit of his scientific aims, including proscriptive ideological opposition to some of the key ideas required to be a successful astrophysicist or cosmologist.
In 1989, he was highly instrumental in the movement that occupied Tiananmen Square, despite not being directly involved in the protest and, once those protests had been dealt with, he decided that, with his wife, his safety was no longer ensured and he sought refuge at the US Embassy. He remained in the embassy for over a year, while diplomatic negotiations continued. Eventually he was allowed to leave and had an international career in his discipline, as well as speaking regularly on human rights and social responsibility. Of all the people on this list, Professor Fang died of old age, at 76, having managed to escape from the situation in which he found himself.
We talk a lot about academic freedom, or the entitlement to academic freedom, but we often forget that there is a harsh and heavy price imposed for it, depending upon the laws and the governments in which we find ourselves. That is a hard and heavy lesson.
Some of you will not be able to talk about Alan Turing, because he was gay. Some of you may have difficulty discussing Bruno Schulz, because of the involvement of Nazis or because he was a Jew. Some of you have may have stopped reading the moment you saw the picture of Fang Lizhi, because you didn’t want to get into trouble. Please keep reading.
So let me give you the story of the first man on this page. Let me tell you about a man who was a bank investigator. Recently divorced, with a youngest child of 17. I want to tell you about him because his story is the simplest and the most complex. He has no giant academic backstory, no grand contribution to literature, no oppression to fight. He just choose to be good.
In 1982, Arland D. Williams, Jr, was a passenger on board a plane from Washington DC to Florida, Air Florida Flight 90, that took off in freezing weather, iced up, failed to gain altitude and slammed into the 14th Street Bridge across the Potomac. The crash killed four motorists and the plane slid forward, down into the Potomac, with the tail breaking off as it did so. There were 79 people on board. Only 6 made it up and onto the tail, which was still floating.
When the rescue helicopter got there, they started recovering people from the tail section, dropping rescue ropes. Williams caught the rescue ropes multiple times and, instead of using them for himself, he handed them to the other passengers.
Life vests were dropped. Rescue balls. He handed them on.
The helicopter, overloaded and struggling with the conditions, got every other survivor back to shore, sometimes having to pick up the weak survivors multiple times. But Williams made sure that everyone else got helped before he did.
Sadly, tragically, by the time the helicopter came back for him, the tail section had shifted and sank, taking him with it. As it happened, Williams had made so little fuss about himself during his actions that his identity had to be determined after the fact.
It would be easy, and cynical, to describe human beings in terms of animals, given some of the awful things we do. Taking away a man’s livelihood (maybe even killing him) because of who he’s in love with? Killing someone because you have an argument with someone else? Persecuting someone for trying to pursue science or democracy?
Yet their stories survive, and we learn. Slowly, sometimes, but we learn.
It would be easy to assume that everyone, when desperate enough, would scrabble like rats to survive. (Except, of course, that not even rats do that. We just tell ourselves they do because we can’t sometimes recognise that this is just a paltry excuse for human evil.)
Here is your counter example – Arland Williams. Here is your existential proof that revokes the “WE ARE ALL LIKE THIS” Myth. There are so many more. Go back to the top of the page and look at that ordinary, middle-aged man. Look at someone who looked down at the freezing water around him and decided to do something great, something amazing, something heroic.
100 Killer Words (Pleas Reed Allowed)
Posted: May 6, 2012 Filed under: Education, Opinion | Tags: authenticity, blogging, education, higher education, identity, ivory tower, killer words, learning, lighthouse, reflection, teaching Leave a commentWriting over 100,000 words in a year has an impact on a lot of things. It affects the way that you think about whatever it is that you’re writing on. It affects the way that you manage your time, because you have to put aside 30-60 minutes a day. It affects the way that you think about your contact with the world because, when you have a daily deadline, you have to find something interesting every single day.
I have always read a lot. I read quickly and I enjoy it a great deal. But, until recently, apart from technical writing, my reading wasn’t important enough to keep track of. I surfed some pages over there? Oh, that’s nice. But now? Now, if I read something and there’s a germ of an idea, I have to keep track of it because I will need that to put together a post, most often late at night or on weekends. My gadgets and browsers are full of half-ideas, links, open pages, sketches. It changes you, writing and thinking this much in such a short time.
Let me, briefly, tell you how I’ve changed this year. I don’t know what to call this year because it’s most certainly not “The Year of Living Dangerously” or “The Year My Voice Broke” and it’s most certainly not “The Year of Living Biblically”. But let’s leave that for the moment. Let me tell you how I’ve changed.
- I have never used my brain so much, for such an extended period. My day is now full of stories and influences, connections and images, thinking, analysing, preparing and presenting. This is changing me as a person – giving me depth, making me more able to discuss issues, drawing out a lot of the frustration and anger I’ve wrestled with for years.
- I now try to construct working solutions from what I have, rather than excise non-working components. If reading and thinking this much about education has taught me anything, it’s that there is no perfect system and there are no perfect people. Saying that your system would work if only people were better is not achieving anything. You have to build with what you’ve got. People are building amazing systems from ordinary people, inspiration and not much else. No matter how you draw up your standards, setting a perfection bar, which is very different from a quality bar, will just lead to failure, frustration and negativity.
- I can see the possibility of improvement. People, governments, companies, systems – they often disappoint me. I have had the luxury of reading across the world and writing a small fraction of it. For every cruel, vicious, and stupid person, there are so many more other people out there. I have long wondered whether our world will outlast me by much. Am I sure that it will? No. Am I more optimistic that it will? Yes.
But it’s not all beer and skittles. I also work far too much. Along the way, my workaholism has been severely re-engaged. I worked a full (long) week last week and yet, here I am, 5 hours work on Saturday and somewhere along the lines of 8-10 hours on Sunday. That’s not a good change and I have to work out how I can keep all the positive aspects – because the positives are magnificent – without getting drawn down into the maelstrom.
I would like to describe this year as “The Year of Living” because, in many ways, I’ve never felt so alive, so aware, so informed and so capable of changing things in a constructive way. But, until I nail the overwork thing, it doesn’t get that title.
For now, because I’ve written 100,000 words or, 100 kiloWords, I’m going to call it “The Year of Killer Words” and hope that, homophones aside, that there’s some truth to that – that some of my words have brought light into the shadows and killed some monsters. Rather idealistically, that’s how I think of the job that we do – we bring light into dark places. Yes, a University can look like an ivory tower sometimes, and sometimes it is, but lighthouses look much the same – it’s the intention and the function that makes one an elitist nightmare and gives the other its worth and nobility.
That image, up the top? That’s what I think we’re doing when we do it right.
Whoops, I Seem To Have Written a Book. (A trip through Python and R Towards Truth)
Posted: May 6, 2012 Filed under: Education | Tags: blogging, curriculum, data visualisation, design, education, higher education, Python, R, reflection, teaching, teaching approaches, tools 3 CommentsMark’s 1000th post (congratulations again!) and my own data analysis reminded me of something that I’ve been meaning to do for some time, which is work out how much I’ve written over the 151 published posts that I’ve managed this year. Now, foolish me, given that I can see the per-post word count, I started looking around to see how I could get an entire blog count.
And, while I’m sure it’s obvious to someone else who will immediately write in and say “Click here, Nick, sheesh!”, I couldn’t find anything that actually did what I wanted to do. So, being me, I decided to do it ye olde fashioned way – exporting the blog and analysing it manually. (Seriously, I know that it must be here somewhere but my brain decided that this would be a good time to try some analysis practice.)
Now, before I go on, here are the figures (not including this post!):
- Since January 1st, I have published 151 posts. (Eek!)
- The total number of words, including typed hyperlinks and image tags, is 102,136. (See previous eek.)
- That’s an average of just over 676 words per post.
Is there a pattern to this? Have I increased the length of my posts over time as I gained confidence? Have they decreased over time as I got busier? Can I learn from this to make my posting more efficient?
The process was, unsurprisingly, not that simple because I took it as an opportunity to work on the design of an assignment for my Grand Challenges students. I deliberately started from scratch and assumed no installed software or programming knowledge above fundamentals on my part (this is harder than it sounds). Here are the steps:
- Double check for mechanisms to do this automatically.
- Realise that scraping 150 page counts by hand would be slow so I needed an alternative.
- Dump my WordPress site to an Export XML file.
- Stare at XML and slowly shake head. This would be hard to extract from without a good knowledge of Regular Expressions (which I was pretending not to have) or Python/Perl-fu (which I can pretend that I have to then not have but my Fu is weak these days).
- Drag Nathan Yau’s Visualize This down from the shelf of Design and Visualisation books in my study.
- Read Chapter 2, Handling Data.
- Download and install Beautiful Soup, an HTML and XML parsing package that does most of the hard word for you. (Instructions in Visualize This)
- Start Python
- Read the XML file into Python.
- Load up the Beautiful Soup package. (The version mentioned in the book is loaded up in a different way to mine so I had to re-enage my full programming brain to find the solution and make notes.)
- Mucked around until I extracted what I wanted to while using Python in interpreter mode (very, very cool and one of my favourite Python features).
- Wrote an 11 line program to do the extraction of the words, counting them and adding them (First year programming level, nothing fancy).
A number of you seasoned coders and educators out there will be staring at points 11 and 12, with a wavering finger, about to say “Hang on… have you just smoothed over about an hour plus of student activity?” Yes, I did. What took me a couple of minutes could easily be a 1-2 hour job for a student. Which is, of course, why it’s useful to do this because you find things like Beautiful Soup is called bs4 when it’s a locally installed module on OS X – which has obviously changed since Nathan wrote his book.
Now, a good play with data would be incomplete without a side trip into the tasty world of R. I dumped out the values that I obtained from word counting into a Comma Separated Value (CSV) file and, digging around in the R manual, Visualize This, and Data Analysis with Open Source Tools by Philipp Janert (O’Reilly), I did some really simple plotting. I wanted to see if there was any rhyme or reason to my posting, as a first cut. Here’s the first graph of words per post. The vertical axis is the number of words and the horizontal axis is the post number. So, reading left to right, you’ll see my development over time.
Sadly, there’s no pattern there at all – not only can’t we see one by eye, the correlation tests of R also give a big fat NO CORRELATION.
Now, here’s a graph of the moving average over a 5 day window, to see if there is another trend we can see. Maybe I do have trends, but they occur over a larger time?
Uh, no. In fact, this one is worse for overall correlation. So there’s no real pattern here at all but there might be something lurking in the fine detail, because you can just about make out some peaks and troughs. (In fact, mucking around with the moving average window does show a pattern that I’ll talk about later.)
However, those of who you are used to reading graphs will have noticed something about the axis label for the x-axis. It’s labelled as wp$day. This would imply that I was plotting post day versus average or count and, of course, I’m not. There have not been 151 days since January the 1st, but there have been days when I have posted multiple times. At the moment, for a number of reasons, this isn’t clear to the reader. More importantly, the day on which I post is probably going to have a greater influence on me as I will have different access to the Internet and time available. During SIGCSE, I think I posted up to 6 times a day. Somewhere, this is lost in the structure of the data that considers each post as an independent entity. They consume time and, as a result, a longer post on the same day will reduce the chances of another long post on the same day – unless something unusual is going on.
There is a lot more analysis left to do here and it will take more time than I have today, unfortunately. But I’ll finish it off next week and get back to you, in case you’re interested.
What do I need to do next?
- Relabel my graphs so that it is much clearer what I am doing.
- If I am looking for structure, then I need to start looking at more obvious influences and, in this case, given there’s no other structure we can see, this probably means time-based grouping.
- I need to think what else I should include in determining a pattern to my posts. Weekday/weekend? Maybe my own calendar will tell me if I was travelling or really busy?
- Establish if there’s any reason for a pattern at all!
As a final note, novels ‘officially start at a count of 40,000 words, although they tend to fall into the 80-100,000 range. So, not only have I written a novel in the past 4 months, I am most likely on track to write two more by the end of the year, because I will produce roughly 160-180,000 more words this year. This is not the year of blogging, this is the year of a trilogy!
Next year, my blog posts will all be part of a rich saga involving a family of boy wizards who live on the wrong side on an Ice Wall next to a land that you just don’t walk into. On Mars. Look for it on Amazon. Thanks for reading!
Stats, stats and more stats: The Half Life of Fame
Posted: May 5, 2012 Filed under: Education | Tags: abelson, education, feedback, half-life of fame, higher education, Korzybski, learning, measurement, MIKE, reflection 4 CommentsSo, here are the stats for my blog, at time of writing. You can see a steady increase in hits over the last few weeks. What does this mean? Have I somehow hit a sweet spot in my L&T discussions? Has my secret advertising campaign paid off (no, not seriously). Well, there are a couple of things in there that are both informative… and humbling.
Firstly, two of the most popular searches that find my blog are “London 2012 tube” and “alone in a crowd”. These hits have probably accounted for about 16% of my traffic for the past three weeks. What does that tell me? Well, firstly, the Olympics aren’t too far away and people are looking for how convenient their hotels are. The second is a bit sadder.
The second search “alone in a crowd” is coming in across two languages – English and Russian. I have picked up a reasonable presence in Russia and Ukraine, mostly from that search term. It seems to contribute a lot to my (Australian) Monday morning feed, which means that a lot of people seem to search for this on Sundays.
But let me show you another graph, and talk about the half life of fame:
That’s since the beginning my blogging activities. That spike at Week 9? That’s when I started blogging SIGCSE and also includes the day when over 100 people jumped on my blog because of a referral from Mark Guzdial. That was also the conference at which Hal Abelson referred to a concept of the Half Life of fame – the inevitable drop away after succeeding at something, if you don’t contribute more. And you can see that pretty clearly in the data. After SIGCSE, I was happily on my way back to being read by about 20-30 people a day, tops, most of whom I knew, because I wasn’t providing much more information to the people who scanned me at SIGCSE.
Without consciously doing it, I’ve managed to put out some articles that appear to have wider appeal and that are now showing up elsewhere. But these stats, showing improvement, are meaningless unless I really know what people are looking at. So, right now I’m pulling apart all of my log data to see what people are actually reading – whether I have an increasing L&T presence and readership, or a lot of sad Russian speakers or lost people on the London Underground system. I’m expecting to see another fall-away very soon now and drop down to the comfortable zone of my little corner of the Internet. I’m not interested in widespread distribution – I’m interesting in getting an inspiring or helpful message to the people who need it. Only one person needs to read this blog for it to be useful. It just has to the right one person. 🙂
One of the most interesting things about doing this, every day, is that you start wondering about whether your effort is worth it. Are people seeking it out? Are people taking the time to read it or just clicking through? Are there a growing number of frustrated Tube travellers thinking “To heck with Korzybski!” Time to go into the data and look. I’m going to keep writing regardless but I’d like to get an idea of where all of this is going.
Grand Challenges – A New Course and a New Program
Posted: May 4, 2012 Filed under: Education | Tags: advocacy, challenge, curriculum, design, education, educational problem, equality, grand challenges, higher education, learning, reflection, teaching, universal principles of design Leave a commentOh, the poor students that I spoke to today. We have a new degree program starting, the Bachelor of Computer Science (Advanced), and it’s been given to me to coordinate and set up the first course: Grand Challenges in Computer Science, a first-year offering. This program (and all of its unique components) are aimed at students who have already demonstrated that they have got their academics sorted – a current GPA of 6 or higher (out of 7, that’s A equivalent or Distinctions for those who speak Australian), or an ATAR (Australian Tertiary Admission Rank) of 95+ out of 100. We identified some students who met the criteria and might want to be in the degree, and also sent out a general advertisement as some people were close and might make the criteria with a nudge.
These students know how to do their work and pass their courses. Because of this, we can assume some things and then build to a more advanced level.
Now, Nick, you might be saying, we all know that you’re (not so secretly) all about equality and accessibility. Why are you running this course that seems so… stratified?
Ah, well. Remember when I said you should probably feel sorry for them? I talked to these students about the current NSF Grand Challenges in CS, as I’ve already discussed, and pointed out that, given that the students in question had already displayed a degree of academic mastery, they could go further. In fact, they should be looking to go further. I told them that the course would be hard and that I would expect them to go further, challenge themselves and, as a reward, they’d do amazing things that they could add to their portfolios and their experience bucket.
I showed them that Cholera map and told them how smart data use saved lives. I showed them We Feel Fine and, after a slightly dud demo where everyone I clicked on had drug issues, I got them thinking about the sheer volume of data that is out there, waiting to be analysed, waiting to tell us important stories that will change the world. I pretty much asked them what they wanted to be, given that they’d already shown us what they were capable of. Did they want to go further?
There are so many things that we need, so many problems to solve, so much work to do. If I can get some good students interested in these problems early and provide a coursework system to help them to develop their solutions, then I can help them to make a difference. Do they have to? No, course entry is optional. But it’s so tempting. Small classes with a project-based assessment focus based on data visualisation: analysis, summarisation and visualisation in both static and dynamic areas. Introduction to relevant philosophy, cognitive fallacies, useful front-line analytics, and display languages like R and Processing (and maybe Julia). A chance to present to their colleagues, work with research groups, do student outreach – a chance to be creative and productive.
I, of course, will take as much of the course as I can, having worked on it with these students, and feed parts of it into outreach into schools, send other parts in different levels of our other degrees. Next year, I’ll write a brand new grand challenges course and do it all again. So this course is part of forming a new community core, a group of creative and accomplished leaders, to an extent, but it is also about making this infectious knowledge, a striving point for someone who now knows that a good mark will get them into a fascinating program. But I want all of it to be useful elsewhere, because if it’s good here, then (with enough scaffolding) it will be good elsewhere. Yes, I may have to slow it down elsewhere but that means that the work done here can help many courses in many ways.
I hope to get a good core of students and I’m really looking forward to seeing what they do. Are they up for the challenge? I guess we’ll find out at the end of second semester.
But, so you know, I think that they might be. Am I up for it?
I certainly hope so! 🙂
No More Page 3 Girls
Posted: May 3, 2012 Filed under: Education | Tags: education, higher education, news, reflection, teaching, teaching approaches Leave a commentYou are probably wondering where today’s post is going. (If you’re not from certain parts of the world you’re probably wondering what I’m talking about!) So let me briefly explain, first, what a Page 3 girl is and, secondly, what I’m talking about.
Back in 1969, Rubert Murdoch relaunched the Sun newspaper in the UK and put “glamour models” on Page 3. They were clothed, with a degree of suggestive reveal. Why Page 3? Because it’s the first page you see AFTER you open the newspaper. When it’s sitting on the shelf, you can’t see what’s on Page 3 – but, once you do pick it up, you can get to the glamour models pretty quickly.
(Yes, you’ve probably worked out what kind of newspaper the Sun was. If you haven’t run into the word tabloid yet, now is a good time to check it out.)
In late 1970, to celebrate the newspaper’s first anniversary, the Sun ran its first ‘nude’ model with a topless girl. And, forty years later, they’re still at it. So, that’s a Page 3 girl – but why am I talking about it?
Because our way of reading news has changed.
Newspapers, while still around, are in the process of moving to alternative delivery mechanisms. It will probably be relatively soon that we won’t have a page 3 because we have exclusively hyperlinked sources – a front page, decided by editorial committee but strongly influenced by click monitoring and how the users explore the space. Before the Internet, stories that were to be buried could be put on page 32, between boring sports and public notices. Now, you have to saturate your users in stories and hope that they won’t find it – or be accused that you’re not reporting all stories. Of course, once people find it, they can now link directly, share, restructure and construct your own stories.
On the Internet, there are no page numbers, only connections – and the connections are mutable.
So, no more Page 3, although there will not be an end to unfortunate pop-up images of women and questionable content, and there will be no end to people trying to hide stories or manipulate links in a way that achieves the same aims as burying. But we have entered a time when we can bypass all of this and then share the information on how to get the information, without all of that getting in the way.
(And, of course, we enter a time of clickjacking, misleading searches, commercial redirection and other nonsense. Hey, I never said that the time after Page 3 girls was going to solve everything! Come back in 10 years and we’ll talk about the new possibilities.)
Saving Lives With Pictures: Seeing Your Data and Proving Your Case
Posted: May 2, 2012 Filed under: Education | Tags: advocacy, analytics, authenticity, cholera outbreak, data visualisation, design, education, higher education, learning, teaching, teaching approaches, voronoi 1 Comment
From Wikipedia, original map by John Snow showing the clusters of cholera cases in the London epidemic of 1854
This diagram is fascinating for two reasons: firstly, because we’re human, we wonder about the cluster of black dots and, secondly, because this diagram saved lives. I’m going to talk about the 1854 Broad Street Cholera outbreak in today’s post, but mainly in terms of how the way that you represent your data makes a big difference. There will be references to human waste in this post and it may not be for the squeamish. It’s a really important story, however, so please carry on! I have drawn heavily on the Wikipedia page, as it’s a very good resource in this case, but I hope I have added some good thoughts as well.
19th Century London had a terrible problem with increasing population and an overtaxed sewerage system. Underfloor cesspools were overfilling and the excess was being taken and dumped into the River Thames. Only one problem. Some water companies were taking their supply from the Thames. For those who don’t know, this is a textbook way to distribute cholera – contaminating drinking water with infected human waste. (As it happens, a lack of cesspool mapping meant that people often dug wells near foul ground. If you ever get a time machine, cover your nose and mouth and try not to breath if you go back before 1900.)
But here’s another problem – the idea that germs carried cholera was not the dominant theory at the time. People thought that it was foul air and bad smells (the miasma theory) that carried the bugs. Of course, from this century we can look back and think “Hmm, human waste everywhere, bugs everywhere, bad smells everywhere… ohhh… I see what you did there.” but this is from the benefit of early epidemiological studies such as those of John Snow, a London physician of the 19th Century.
John Snow recorded the locations of the households where cholera had broken out, on the map above. He did this by walking around and talking to people, with the help of a local assistant curate, the Reverend Whitehead, and, importantly, working out what they had in common with each other. This turned out to be a water pump on Broad Street, at the centre of this map. If people got their water from Broad Street then they were much more likely to get sick. (Funnily enough, monks who lived in a monastery adjacent to the pump didn’t get sick. Because they only drank beer. See? It’s good for you!) John Snow was a skeptic of the miasma theory but didn’t have much else to go on. So he went looking for a commonality, in the hope of finding a reason, or a vector. If foul air wasn’t the vector – then what was spreading the disease?
Snow divided the map up into separate compartments that showed the pump and compartment showed all of the people for whom this would be the pump that they used, because it was the closest. This is what we would now call a Voronoi diagram, and is widely used to show things like the neighbourhoods that are serviced by certain shops, or the impacts of roads on access to shops (using the Manhattan Distance).

A Voronoi diagram from Wikipedia showing 10 shops, in a flat city. The cells show the areas that contain all the customers who are closest to the shop in that cell.
What was interesting about the Broad Street cell was that its boundary contained most of the cholera cases. The Broad Street pump was the closest pump to most people who had contracted cholera and, for those who had another pump slightly closer, it was reported to have better tasting water (???) which meant that it was used in preference. (Seriously, the mind boggles on a flavour preference for a pump that was contaminated both by river water and an old cesspit some three feet away.)
Snow went to the authorities with sound statistics based on his plots, his interviews and his own analysis of the patterns. His microscopic analysis had turned up no conclusive evidence, but his patterns convinced the authorities and the handle was taken off the pump the next day. (As Snow himself later said, not many more lives may have been saved by this particular action but it gave credence to the germ theory that went on to displace the miasma theory.)
For those who don’t know, the stink of the Thames was so awful during Summer, and so feared, that people fled to the country where possible. Of course, this option only applied to those with country houses, which left a lot of poor Londoners sweltering in the stink and drinking foul water. The germ theory gave a sound public health reason to stop dumping raw sewage in the Thames because people could now get past the stench and down to the real cause of the problem – the sewage that was causing the stench.
So John Snow had encountered a problem. The current theory didn’t seem to hold up so he went back and analysed the data available. He constructed a survey, arranged the results, visualised them, analysed them statistically and summarised them to provide a convincing argument. Not only is this the start of epidemeology, it is the start of data science. We collect, analyse, summarise and visualise, and this allows us to convince people of our argument without forcing them to read 20 pages of numbers.
This also illustrates the difference between correlation and causation – bad smells were always found with sewage but, because the bad smell was more obvious, it was seen as causative of the diseases that followed the consumption of contaminated food and water. This wasn’t a “people got sick because they got this wrong” situation, this was “households died, with children dying at a rate of 160 per 1000 born, with a lifespan of 40 years for those who lived”. Within 40 years, the average lifespan had gone up 10 years and, while infant mortality didn’t really come down until the early 20th century, for a range of reasons, identifying the correct method of disease transmission has saved millions and millions of lives.
So the next time your students ask “What’s the use of maths/statistics/analysis?” you could do worse than talk to them briefly about a time when people thought that bad smells caused disease, people died because of this idea, and a physician and scientist named John Snow went out, asked some good questions, did some good thinking, saved lives and changed the world.













