Wrapping up Grand Challenges

We had the final ‘farewell’ function for the end of my Grand Challenges course on Friday. While I would normally see most of these students again, as this is a first year course, one of them was a US exchange student who is flying home this morning to return to his own college system. I wanted to bring everyone together, in an informal setting, to say well done and farewell. It has been a remarkable semester. For me, now, digging through the student comments and feedback will drive a lot of my thinking for the next version of the course and the comments are very, very interesting. Students reflecting on the fact that they didn’t quite understand why they learned about the grand challenges in the first place, until we were knee deep in questionable ethics and the misapplication of Science, and then *bang* it all settled into place. Yes, this is what I intended but, frankly, it’s a little bit of a high risk strategy to construct scaffolding in that way and I had to carefully monitor the group dynamics, as well as making sure that the group had enough elements in it that we could achieve a good environment in which to reflect and develop. I, by myself, cannot be a full member of the group and I’m always going to be the outsider because, well, I have to be in order to function in the course coordinator and marker role.

Next year, we already have a lot of interest in the new course and this is very exciting. I’m not sure how many will roll up but I do know that I cannot handle a group larger than 8 with the current approach – hence, as I’ve said before, I now need to take all of the comments and work on scaling it up. Sitting around the table on Friday night, talking to all of the students, it really sank in that we (as a group) had achieved something pretty special. I couldn’t have done it without them and (I suspect) a lot of them weren’t quite ready to do it without me. What I saw around the table was passion, confidence, enthusiasm and curiosity. There was also some well-deserved pride when the final poster prints were handed out. I had their first projects professionally printed on Tyvek, a plastic material that is waterproof, hard to tear and really tough, so that their posters will go anywhere and hang up, without risking becoming sad and daggy old faded relics with tears and dog ears. The posters were the result of 6 weeks of work, hence some respect was due to their construction.

I’m not a very reserved person, which will come as no surprise to any of you, and people generally know what I’m feeling (with the usual caveat that I can appear delighted by the questionable musical practices of children and fascinated in meetings). My students will therefore know that I am pleased by what they have achieved and what, by their enthusiasm and willingness to go with a non-traditional structure, we have managed to achieve together. Was it perfect? No. I need to cater for students who are in transition more and remember that just because students can perform well academically, it does not magically grant them the associated maturity or ability to handle the unforeseen. It could certainly have been better organised and that was really down to the experimental nature of the course combined with my schedule. I was too busy, sometimes, to be as forward looking as I should have been (I was looking weeks out, rather than months). That will not happen next year. What’s really interesting is what my colleagues assume about these students. “Oh, they’re smart so they must have done all this maths or love maths or something.” No, they don’t. They come in with the usual range of courses you’d expect from students and have the usual range of likes and dislikes. They are, in a nutshell, students who happen to have worked out how to perform well under assessment. As it turns out, a GPA or ATAR (SAT) mark does not summarise a student, nor does achieving the same grade make you the same person. Shocking, I know.

But, snark aside, what a great experience and, from early indications, I am pretty confident that some of these students now have a completely different set of lenses through which to view the world. Now, of course, it is up to them. You might think that my posturing on an apolitical stance is just that, a posturing facade, but I am deadly serious about not imposing my political beliefs on my students. Yes, I firmly believe that there are a set of ethical standards that people in my discipline (Computer Science) and my calling (Education) should adhere to, but how you vote? None of my business. Next year, I hope to bring in more people from industry, more entrepreneurs, possibly even some more ‘challenging’ viewpoints. The world is complicated and the intellectual challenges are many. Me training students in dogma does nothing. Me training students in how they can think for themselves and then genuinely standing back to say “That was the toolkit, it’s up to you what you build” will truly test me and them.

Far too many times I’ve held forth on silly little points where I was wrong, or misinterpreting, and it didn’t help anything. I’ve always learned more from discussion than argument, and from informed disagreement rather than blind agreement. That’s the fine print on the PhD, as I read it, “be prepared to be wrong and then work out how to be right.”

If I were ever to work myself almost to collapse again, taking on too much, striving to develop an entirely new course for a new type of student that we haven’t really catered to before, while doing everything else – I would hope that at the end of the year, I could look back on something like Grand Challenges and nod, with satisfaction, because it worked. I’m looking forward to bouncing ideas off the course members over the next 6 months to get their feedback on the new direction, possibly using these students as mentors and tutors (good idea, MH) to help me run the course and to keep building the community. That’s what it was always about, after all. Yes, it was a course for students who could handle the academics but it was always about the biggest Grand Challenge of them all: getting people to work together to solve problems.

Turn on the news and you’ll see lot of problems at the moment. Running up to (yet another) end of the world, we are once again taking the crazy pills and, bluntly, it scares me. We have a lot of problems to solve and that will take people, working together, sharing, talking and using available resources to try and deal with things that could potentially destroy our species. If you have the opportunity to tun any kind of program that could assist with this – problem solving, community building, team formation, outreach to other schools, or whatever – please consider doing so. I’ll tell you, honestly, it’s one of the most rewarding things that I’ve ever done and I’ve been privileged to be able to do a lot of cool things.

Ethics and Opinion: Please Stop Confusing My Students

One of the sadly rather expected side benefits of the recent re-election of President Obama has been the predictable outpouring of racist sentiment. Of course, to listen to the people uttering racial slurs and unpleasant requests, they are not actually racists, they are just expressing their opinion. You know?

They’re just sayin’.

A woman is currently being investigated by the Secret Service for Tweeting a heavily charged racial epithet against the President, wrapped up in a paraphrased death threat, and appears puzzled about all of the fuss. After all, it’s just what she thinks and she’s not a racist. Australian former cricketer Greg Ritchie recently uttered some serious racial slurs that are highly inflammatory towards South Africans and can’t see what the big deal is either. He also managed to get in a joke about Muslims. When asked, however, Ritchie had this to say:

“If they take offence that’s their choice.”

His joke, involving Muslims, is in his own words “just a little humourous joke to indicate that they’re not my favourite people of my choice.” Hey, Greg, guess what, when you’re trying to defend yourself against charges of discrimination, perhaps it’s best to do so in a way that is not actually discriminatory? Of course, we’ve been tolerating Ritchie’s antics for years, so it’s not surprising that he is now confused that we don’t find him funny. He, in blackface as pseudo-Indian Mahatma Coate, was a regular on the Australian Rules Football sports variety show “The Footy Show” for years. And, thus we crawl, inexorably, towards my point.

If you’re opinion is actually racism, then it’s a racist opinion. I can completely understand why people don’t want to be labelled as racists because we all know that’s bad but, and here’s the tricky thing, racists are people who believe and say racist things or act in a manner than discriminates against people based on their race. Calling someone a racial epithet because of the race that they belong to counts here and, before we get all ‘classification theory’ about this, there is a world of difference between any classifications of ethnicity that are scientific in nature and slurs. There is also a great deal of difference in how we use this information. The moment that you start saying things like “they’re not my favourite people of choice”, you are saying that you don’t like an entire group that is defined by a given characteristic and, wow, it’s not hard to see where that leads. (Now, no doubt, there is someone who is itching to leap and tell me that ‘aha – Muslims are not a race’. Spare me the sophistry, especially where the Muslims that appear to catch the most problems here are (surprise!) not Caucasian.)

Whenever anyone leaps in and says “statement – I’m just sayin'” or “statement that challenges movements that are egalitarian – playing devil’s advocate” then I really must wonder ‘why?’ I have heard a number of people trying to sneak in sexist comments based on poor evidence or by playing the “Devil’s Advocate” card. “Wow, but what if women aren’t as good at X as men, playing Devil’s advocate/just sayin’/just askin’.” You know, that’s a good question. But it’s not the one that you’re asking. The question that I’m hearing (and I apologise because I have weird ears) is “How can I make a sexist statement with plausible deniability because I am not yet convinced that women are equal?”

This is about fundamental human rights, not an opinion on whether Picard or Kirk would win in a jello-wrestling competition. The questions that we ask, however they are framed, reveal what it is that we believe to be true. And right. And, by extension, what we consider false or wrong.

My real problem with all of this is that my students are like big mobile sponges. They hear a whole heap of stuff before they come to me and, if most of it is opinionated nonsense that magically escapes classification, they will learn that this is how the world works and come to me with a head full of garbage. They’ll recite rubbish at me that they’ve picked up from the world, politics, media, television and their own families that has no place in a University environment. I don’t give a hoot how entitled you feel to have a racist, sexist or discriminatory opinion, it’s going to get called as one and you can argue until you’re blue in the face that saying discriminatory things doesn’t make you discriminatory but, important point, you are almost never as ironically funny as you think you are. (And, yes, we all have to be aware of that. To my shame, I have occasionally gone too far in trying to mock discrimination and I apologetically confess that I have on occasion been less than funny and just plain dumb.) The important thing to ask is why are you trying to set up the situation in the first place?

My students have to think about these things all the time. They cannot guess how people will react to their dumb jokes and supposed ‘irony’. Worse, as people who have had the benefits of more education, other people will look to them (explicitly or not) as thought leaders and the best of my students will have a very wide-ranging impact. I can’t stop people saying silly and hurtful things, but let’s stop the pretence that there are special “get out of jail free” textual containers that allow people to utter the phrasings of discrimination and, yet, mysteriously escape being labelled as such.

(And, for the record, the Internet indicates that Picard would most likely take the match, given that he has mud wrestling experience.)

The Hips Don’t Lie – Assuming That By Hips You Mean Numbers

For those who missed it, the United States went to the polls to elect a new President. Some people were surprised by the outcome.

Even Benedict Cumberbatch, seen here between takes on Sherlock Series 3.

Some people were not, including the new King of Quants, Nate Silver. Silver studied economics at the University of Chicago but really came to prominence in his predictions of baseball outcomes, based on his analysis of the associated statistics and sabermetrics. He correctly predicted, back in 2008, what would happen between Obama and Clinton, and he predicted, to the state, what the outcome would be in this year’s election, even in the notoriously fickle swing states. Silver’s approach isn’t secret. He looks at all of the polls and then generates a weighted average of them (very, very simplified) in order to value certain polls over others. You rerun some of the models, change some parameters, look at it all again and work out what the most likely scenario is. Nate’s been publishing this regularly on his FiveThirtyEight blog (that’s the number of electors in the electoral college, by the way, and I had to look that up because I am not an American) which is now a feature of the New York Times.

So, throughout the entire election, as journalists and the official voices have been ranting and railing, predicting victory for this candidate or that candidate, Nate’s been looking at the polls, adjusting his model and publishing his predictions. Understandably, when someone is predicting a Democratic victory, the opposing party is going to jump up and down a bit and accusing Nate of some pretty serious bias and poll fixing. However, unless young Mr Silver has powers beyond those of mortal men, fixing all 538 electors in order to ensure an exact match to his predictions does seem to be taking fixing to a new level – and, of course, we’re joking because Nate Silver was right. Why was he right? Because he worked out a correct mathematical model and  method that took into account how accurate each poll was likely to be in predicting the final voter behaviour and that reliable, scientific and analytic approach allowed him to make a pretty conclusive set of predictions.

There are notorious examples of what happens when you listen to the wrong set of polls, or poll in the wrong areas, or carry out a phone poll at a time when (a) only rich people have phones or (b) only older people have landlines. Any information you get from such biased polls has to be taken with a grain of salt and weighted to reduce a skewing impact, but you have to be smart in how you weight things. Plain averaging most definitely does not work because this assumes equal sized populations or that (mysteriously) each poll should be treated as having equal weight. Here’s the other thing, though, ignoring the numbers is not going to help you if those same numbers are going to count against you.

Example: You’re a student and you do a mock exam. You get 30% because you didn’t study. You assume that the main exam will be really different. You go along. It’s not. In fact, it’s the same exam. You get 35%. You ignored the feedback that you should have used to predict what your final numbers were going to be. The big difference here is that a student can change their destiny through their own efforts. Changing the mind of the American people from June to November (Nate published his first predictions in June) is going to be nearly impossible so you’re left with one option, apparently, and that’s to pretend that it’s not happening.

I can pretend that my car isn’t running out of gas but, if the gauge is even vaguely accurate, somewhere along the way the car is going to stop. Ignoring Nate’s indications of what the final result would be was only ever going to work if his model was absolutely terrible but, of course, it was based on the polling data and the people being polled were voters. Assuming that there was any accuracy to the polls, then it’s the combination of the polls that was very clever and that’s all down to careful thought and good modelling. There is no doubt that a vast amount of work has gone into producing such a good model because you have to carefully work out how much each vote is worth in which context. Someone in a blue-skewed poll votes blue? Not as important as an increasing number of blue voters in a red-skewed polling area. One hundred people polled in a group to be weighted differently from three thousand people in another – and the absence of certain outliers possibly just down to having too small a sample population. Then, just to make it more difficult, you have to work out how these voting patterns are going to turn into electoral college votes. Now you have one vote that doesn’t mean the difference between having Idaho and not having Idaho, you have a vote that means the difference between “Hail to the Chief” and “Former Presidential Candidate and Your Host Tonight”.

Nate Silver’s work has brought a very important issue to light. The numbers, when you are thorough, don’t lie. He didn’t create the President’s re-election, he merely told everyone that, according to the American people, this was what was going to happen. What is astounding to me, and really shouldn’t be, is how many commentators and politicians seemed to take Silver’s predictions personally, as if he was trying to change reality by lying about the numbers. Well, someone was trying to change public perception of reality by talking about numbers, but I don’t think it was Nate Silver.

This is, fundamentally, a victory for science, thinking and solid statistics. Nate put up his predictions in a public space and said “Well, let’s see” and, with a small margin for error in terms of the final percentages, he got it right. That’s how science is supposed to work. Look at stuff, work out what’s going on, make predictions, see if you’re right, modify model as required and repeat until you have worked out how it really works. There is no shortage of Monday morning quarterbacks who can tell you in great detail why something happened a certain way when the game is over. Thanks, Nate, for giving me something to show my students to say “This is what it looks like when you get data science right.”

Remind me, however, never to bet against you at a sporting event!

Road to Intensive Teaching: Post 1

I’m back on the road for intensive teaching mode again and, as always, the challenge lies in delivering 16 hours of content in a way that will stick and that will allow the students to develop and apply their understanding of the core knowledge. Make no mistake, these are keen students who have committed to being here, but it’s both warm and humid where I am and, after a long weekend of working, we’re all going to be a bit punch-drunk by Sunday.

That’s why there is going to be a heap of collaborative working, questioning, voting, discussion. That’s why there are going to be collaborative discussions of connecting machines and security. Computer Networking is a strange beast at the best of times because it’s often presented as a set of competing models and protocols, with very few actual axioms beyond “never early adopt anything because of a vendor promise” and “the only way to merge two standards is by developing another standard. Now you have three standards.”

There is a lot of serious Computer Science lurking in networking. Algorithmic efficiency is regularly considered in things like routing convergence and the nature of distributed routing protocols. Proofs of correctness abound (or at least are known about) in a variety of protocols that , every day, keep the Internet humming despite all of the dumb things that humans do. It’s good that it keeps going because the Internet is important. You, as a connected being, are probably smarter than you, disconnected. A great reach for your connectivity is almost always a good thing. (Nyancat and hate groups notwithstanding. Libraries have always contained strange and unpleasant things.)

“If I have seen further, it is by standing on the shoulders of giants” (Newton, quoting Bernard of Chartres) – the Internet brings the giants to you at a speed and a range that dwarfs anything we have achieved previously in terms of knowledge sharing. It’s not just about the connections, of course, because we are also interested in how we connect, to whom we connect and who can read what we’re sharing.

There’s a vast amount of effort going into making the networks more secure and, before you think “Great, encrypted cat pictures”, let me reassure you that every single thing that comes out of your computer could, right now, be secretly and invisibly rerouted to a malicious third party and you would never, ever know unless you were keeping a really close eye (including historical records) on your connection latency. I have colleagues who are striving to make sure that we have security protocols that will make it harder for any country to accidentally divert all of the world’s traffic through itself. That will stop one typing error on a line somewhere from bringing down the US network.

“The network” is amazing. It’s empowering. It is changing the way that people think and live, mostly for the better in my opinion. It is harder to ignore the rest of the world or the people who are not like you, when you can see them, talk to them and hear their stories all day, every day. The Internet is a small but exploding universe of the products of people and, increasingly, the products of the products of people.

This is one of the representations of what the Internet looks like, graphically.

Computer Networking is really, really important for us in the 21st Century. Regrettably, the basics can be a bit dull, which is why I’m looking to restructure this course to look at interesting problems, which drives the need for comprehensive solutions. In the classroom, we talk about protocols and can experiment with them, but even when we have full labs to practise this, we don’t see the cosmos above, we see the reality below.

Maybe a green light will come on!

Nobody is interested in the compaction issues of mud until they need to build a bridge or a road. That’s actually very sensible because we can’t know everything – even Sherlock Holmes had his blind spots because he had to focus on what he considered to be important. If I give the students good reasons, a grand framing, a grand challenge if you will, then all of the clicking, prodding, thinking and protocol examination suddenly has a purpose. If I get it really right, then I’ll have difficulty getting them out of the classroom on Sunday afternoon.

Fingers crossed!

(Who am I kidding? My fingers have an in-built crossover!)

Another semester over – what have I learned?

Monday the 29th marks the last official teaching activities, barring the exam and associated marking, for my grand challenges in Computer Science course. It’s been a very busy time and I’ve worked very hard on it but my students have worked even harder. Their final projects are certainly up where I wanted them to be and I believe that the majority of the course has gone well.

However, I’m running some feedback activities this week and I’ll find out how I can make it better for next year. At this stage we look like we’re going to have a reasonably large group for next year’s intake – somewhere in the region of 10-20 – and this is going to change how I run the course. Certain things just won’t work at that scale unless I start to take better advantage of group structure. I’ve already learnt a lot about how hard it is to connect students and data and, in our last meeting, I commented that I was thinking about making more data available in advance. Well, maybe, was the reply from students but we learned so much about how the data in the world is actually stored and treated.

Hmm. Back to the drawing board maybe – but also I’m going to wait for all of the final feedback.

Do I have students who I would happily put out in front of a class to run it for a while, doubly so for a community involvement project, with the confidence that they’ll communicate confidently, competently and with passion? Well, yes, actually – although there’ll be a small range. (And now I’ve just made at least three people paranoid – that’s what you get for reading my blog.)

There is so much going on that the next two months are going to be pretty frantic. Next year is already shaping up to be a real make-or-break year for my career and that means I need to sit down with a list of things that I want to achieve and a list of things that I am and am not prepared to do in order to achieve things. The achievement list is going to be a while coming, as goal lists always are, but the will/won’t/want list is forming. Here’s a rough draft.

  1. I still want to teach and be pretty involved in teaching. That’s easy as I’m not senior or research-loaded enough to get out of teaching. (I don’t really have a choice.
  2. I need to have more time to work on my non-work projects. I’ve just spent all of a Sunday working and the only reason I stopped was that I couldn’t spell constructivist reliably any more. (Yes, that just took three tries.)
  3. I want to have enough time to spend time with my students and not looked rushed or feel guilty about the time.
  4. I want to have the time to be able to help out any colleagues who could use my assistance AND I want to have the time to be able to seek help from my colleagues!
  5. I don’t want to take on anything that I have to give up on, or push to the sidelines for next year.

So, obviously, it all boils down to time, planning and allocation of priorities. With that in mind, I’ll wish you a happy Monday or good weekend. I’m going to have some dinner.

Recursive Tutorial: A tutorial on writing a tutorial

I assigned the Grand Challenge students a slightly strange problem for yesterday’s tutorial: “How would you write an R tutorial for Year 11 High School Students?” R is an open source statistics package that is incredibly powerful and versatile but it is nowhere near as friendly to use or accessible as traditional GUI tools such as Microsoft Excel. R has some menus and buttons on it but most of these are used to control the environment, rather than applying the statistical and mathematical functions. R Studio is an associated Integrated Development Environment (IDE) that makes working with R easier but, at its core, R relies upon you knowing enough R to type the right commands.

Discussing this with students, we compared Excel and R to find out what the core differences were and some of them are not important early on but become more important later. Excel, for example, allows you to quickly paste and move around data, apply some functions, draw some graphs and come to a result quickly, mostly by pushing buttons and using on-line help with a little typing. But, and it’s an important but, unless you write a program in Excel (and not that many people do), re-applying all of that manipulation to a new data source requires you to click and push and move across the screen all over again. You have to recreate a long and complicated combination of mechanical and cognitive functions. R, by contrast, requires you to type commands to get things to happen but it remembers them by default and you can easily extract them. Because of how R works, you drag in data (from a file, say) and then execute a set of manipulation steps. If you’re familiar with R then this is straight-forward. If not, then steep learning curve. However, re-using these instructions and manipulations on a new data source is trivial. You change the file and re-run all of the steps.

Why am I talking about new data sources? Because it’s often the case that you want to do the same thing with new data OR you realise that the data you were working with was incomplete or in error. Unless you write a lot of Visual Basic in Excel (and that no longer works on Macs so it’s not a transferable option), your Excel spreadsheet with changed data requires you to potentially reapply or check the application of everything in the spreadsheet, especially if there is any sorting of data, creation of new columns or summary data – and let’s not even start talking about pivot tables! But, for single run, for finance, for counting stuff, Excel is almost always going to be more easy to teach people to use than R. For scientists, however, R is better to use for two very important reasons: it is less likely to do something that is irreversible to your data and the vast majority of its default choices are sensible.

The students came up with a list of things that Excel does (good and bad): it’s strongly visual, lay-user friendly, tells you what you can do, does what it damn well wants to, data changes may require manual reapplication. There’s a corresponding list for R: steep learning curve, visual display for R environment but command-line interface for commands, does what you tell it to do (except when it’s too smart). I surveyed the class to find out who was using R rather than Excel and the majority of students were using R for their analysis but, and again it’s an important but, only because they had to. In situations where Excel was enough (simple manipulation, straight forward analysis), then Excel got used because Excel is far easier to use and far friendlier.

The big question for the students was “How do I start doing something?” In Excel, you type numbers into the spreadsheet and then can just start selecting things using a relatively good on-line help system. In R you are faced with a blinking prompt and you have to know enough to type streams of commands like this:

newtab <-read.csv("~/days.txt",header=FALSE)

And, with a whole set of other commands, you can get graphs like this. (I realise that this is not a box plot!)

Once you’re used to it, this is meaningful, powerful and re-applicable. I can update the data and re-run this to my heart’s content, analysing vast quantities of data without having to keep mouse clicking into cells. But let’s remember our context. I’m not talking about higher education students, I’m talking about school students and it’s important to remember that teaching people something before they’re ready to use it or before they have an opportunity to use it is potentially not the best use of effort.

My students pointed out that the school students of today are all learning how to use graphing calculators, with giant user manuals, and (in some cases) the students switch on their calculators to see a menu rather than the traditional calculator single line. But the syntax and input modes for calculators vary widely. Some use ( ) for operations like sin, so a student will see sin(30) when they start doing trig, whereas some don’t. This means that some of the students I might want to teach R to have not necessarily got their head around the fact that functions exist, except as something that Excel requires them to do. Let’s go to the why here, because it’s important. Why are students learning how to use these graphing calculators? So they can pass their exams, where the competent and efficient use of these things will help them. Yes, it appears that students may be carrying out the kind of operations I would like them to put into a more powerful tool, but why should they?

If a teach a high school student about Excel then there are many places that they might use this kind of software: micro-budgeting, keeping track of things, the ‘simple’ approximation of a database storing books or things like that. However, the general practice of using Excel is familiarisation with a GUI interface that is very, very common and that most students need experience with. If I teach them R then I might be extending their knowledge but (a) the majority are probably not yet ready for it and (b) they are highly unlikely to need to use it for anything in the near future.

The conclusion that my students reached was that, if we really wanted to provide exposure to an industry-like scientific or engineering tool at the earlier stage, then why not use one that was friendlier, more helpful but still had a more scientific focus. They suggested Matlab (as a number of them had been exposed) or Mathematica. Now this whole exercise was designed to get them to practice their thinking about outreach, community, communication and sharing knowledge, so I wasn’t ever actually planning to run an R tutorial at Year 11. But these students thought through and asked the very important questions:

  • Who is this aimed at?
  • What do they already know?
  • What do they need to know?
  • Why are we doing this?

Of course, I have also learned a great deal from this as well – I had no idea that the calculators had quite got to this point, nor that there were schools were students would have to select through a graphical menu to get to the simple “3+3 EXE” section of the calculator! Don’t tell my Grand Challenge students but I think I’m learning roughly as much as they are!

Industry Speaks! (May The Better Idea Win)

Alan Noble, Director of Engineering for Google Australia and an Adjunct Professor with my Uni, generously gave up a day today to give a two hour lecture of distributed systems and scale to our third-year Distributed Systems course, and another two-hour lecture on entrepreneurship to my Grand Challenge students. Industry contact is crucial for my students because the world inside the Uni and the world outside the Uni can be very, very different. While we try to keep industry contact high in later years, and we’re very keen on authentic assignments that tackle real-world problems, we really need the people who are working for the bigger companies to come in and tell our students what life would be like working for Google, Microsoft, Saab, IBM…

My GC students have had a weird mix of lectures that have been designed to advance their maturity in the community and as scientists, rather than their programming skills (although that’s an indirect requirement), but I’ve been talking from a position of social benefit and community-focused ethics. It is essential that they be exposed to companies, commercialisation and entrepreneurship as it is not my job to tell them who to be. I can give them skills and knowledge but the places that they take those are part of an intensely personal journey and so it’s great to have an opportunity for Alan, a man with well-established industry and research credentials, to talk to them about how to make things happen in business terms.

The students I spoke to afterwards were very excited and definitely saw the value of it. (Alan, if they all leave at the end of this year and go to Google, you’re off the Christmas Card list.) Alan focused on three things: problems, users and people.

Problems: Most great companies find a problem and solve it but, first, you have to recognise that there is a problem. This sometimes just requires putting the right people in front of something to find out what these new users see as a problem. You have to be attentive to the world around you but being inventive can be just as important. Something Alan said really resonated with me in that people in the engineering (and CS) world tend to solve the problems that they encounter (do it once manually and then set things up so it’s automatic thereafter) and don’t necessarily think “Oh, I could solve this for everyone”. There are problems everywhere but, unless we’re looking for them, we may just adapt and move on, instead of fixing the problem.

Users: Users don’t always know what they want yet (the classic Steve Jobs approach), they may not ask for it or, if they do ask for something, what they want may not yet be available for them. We talked here about a lot of current solutions to problems but there are so many problems to fix that would help users. Simultaneous translation, for example, over telephone. 100% accurate OCR (while we’re at it). The risk is always that when you offer the users the idea of a car, all they ask for is a faster horse (after Henry Ford). The best thing for you is a happy user because they’re the best form of marketing – but they’re also fickle. So it’s a balancing act between genuine user focus and telling them what they need.

People: Surround yourself with people who are equally passionate! Strive of a culture of innovation and getting things done. Treasure your agility as a company and foster it if you get too big. Keep your units of work (teams) smaller if you can and match work to the team size. Use structures that encourage a short distance from top to bottom of the hierarchy, which allows for ideas to move up, down and sideways. Be meritocratic and encourage people to contest ideas, using facts and articulating their ideas well. May the Better Idea Win! Motivating people is easier when you’re open and transparent about what they’re doing and what you want.

Alan then went on to speak a lot about execution, the crucial step in taking an idea and having a successful outcome. Alan had two key tips.

Experiment: Experiment, experiment, experiment. Measure, measure, measure. Analyse. Take it into account. Change what you’re doing if you need to. It’s ok to fail but it’s better to fail earlier. Learn to recognise when your experiment is failing – and don’t guess, experiment! Here’s a quote that I really liked:

When you fail a little every day, it’s not failing, it’s learning.

Risk goes hand-in-hand with failure and success. Entrepreneurs have to learn when to call an experiment and change direction (pivot). Pivot too soon, you might miss out on something good. Pivot too late, you’re in trouble. Learning how to be agile is crucial.

Data: Collect and scrutinise all of the data that you get – your data will keep you honest if you measure the right things. Be smart about your data and never copy it when you can analyse it in situ.

(Alan said a lot more than this over 2 hours but I’m trying to give you the core.)

Alan finished by summarising all of this as his Three As of Entrepreneurship, then why we seem to be hitting an entrepreneurship growth spurt in Australia at the moment. The Three As are:

  • Audit your data
  • Having Audited, Admit when things aren’t working
  • Once admitted, you can Adapt (or pivot)

As to why we’re seeing a growth of entrepreneurship, Australia has a population who are some of the highest early adopters on the planet. We have a high technical penetration, over 20,000,000 potential users, a high GDP and we love tech. 52% of Australians have smart phones and we had so many mobile phones, pre-smart, that it was just plain crazy. Get the tech right and we will buy it. Good tech, however, is hardware+software+user requirement+getting it all right.

It’s always a pleasure to host Alan because he communicates his passion for the area well but he also puts a passionate and committed face onto industry, which is what my students need to see in order to understand where they could sit in their soon-to-be professional community.

Fragile Relationships: Networks and Support

I’ve been working with a large professional and technical network organisation for the past couple of days and, while I’m not going to go into too much detail, it’s an organisation that has been around for 28 years and, because of a major change in funding, is now having to look at what the future holds. What’s interesting about this organisation is that it doesn’t have a silo problem in terms of its membership across Australia and New Zealand, which makes it almost unique in terms of technology networks in this neck of the woods. There’s no division between academic and professional staff, there are representatives from both. Same for tech and non-tech, traditional and new Unis, big and small players. It’s a bizarrely egalitarian and functional organisation that has been developing for 28 pretty good years.

Now, for some quite understandable reasons, the original funds provider is withdrawing and we have to look at the future and decide what we’re going to do. I’ve been out talking to possible organisation sponsors or affiliates but, until we decide what form we’re going to take, I’m trying to sell a beast behind a curtain by offering a dowry. This is not a great foundation for a future direction. As it turns out, trying to find a parent organisation that will be a good host is challenging because there’s nothing quite like us in the region. So, we’re looking at other alternatives. I have, however, just moved on to the executive of the organisation to try and help steer it through the next couple of years and, with any luck, into a form that will be self-sustaining and continue to give the valuable contribution to the ANZ community that it has been making for so many years.

The problem is that it takes 28 years to produce a network this strong and, if we get it wrong, relationships are inherently fragile and the disintegration of a group is far easier (and requires zero effort) than the formation. I have one of those composite stone benches in my house and I often ponder the amount of work it took to produce it and get that particular shape up on my bench top.

And how easily it could be broken, irrevocably, with one strike of a sledgehammer.

Knock knock!

(This is why my wife won’t let me use the sledgehammer to cook with.)

Human networks don’t need a sledgehammer strike to fall apart, they just need neglect. There are many examples of good low-cost networks that manage to keep people linked up, regardless of their level of resource, and I often think of the computing education community in the US, made of the regional committees, the overarching groups like SIGCSE and how the regional groups provide sustenance and a focus point, with the large conference coming into town every so often to bring everyone together.

2012 is an interesting year in so many ways and, every time I turn around, there seems to be a new challenge, something to look at, something to review to see if it’s worth keeping and, in many cases, something new to steward or assist. But I suppose that it’s important to remember that all of these things take energy and, at some stage, I’m going to have to sit down and organise how all of these tasks will go together in a way that I can make this work effectively for 2013.

The Complex Roles Of Universities In The Period Of Globalization – Altbach – Part 2

Continuing from my previous post, Altbach deals with the University as a focus of the international community. We host other people, share interests, cross-populate each other with PhD students and professors – sometimes it’s a wonder that we don’t get spontaneous germination of new Universities just from all of the swapping! Because of our mission, we tend to have a much greater ability to look, think and act on the international level. This is an interesting contrast to the role of the Uni as a national stabiliser, as the more one travels and looks outward, the more one realises that your country is just one of many. I travel a fair bit for work and I can tell you that, right now, I haven’t run across a single issue that is not being felt by at least two (or more) Universities at an equal level of pain, yet most people who don’t travel or share their world view feel isolated and that “no one else would understand.” The realisation that all countries are really very similar (yes, with one or two exceptions) and that Unis are the same all over the world sets the academic even further away from the people outside and again increases the obligation to communicate with people outside of academia. Hoarding knowledge or sneering at the uninformed do not come with the territory – Universities have traditionally been the centres of connectivity, even before the internet, and now that most Unis end up being the default Internet distribution point in many regions, this is becoming even more important.

This ties in with the next topic that Altbach mentions, our role in social mobility. Education transforms people. While you have to the son of the King to (most likely) become King, anyone can become an engineer (with a few caveats, to keep my colleagues in Eng happy!) with access to education. Expanding Universities from a small and elite focussed approach to a larger scale, massified, model has brought access and equity to a much larger group of people. This is not a given, of course, as the first-in-family do face a lot of challenges but, where the right attention is given to support and scholarships, great things can be achieved.

We are also engines for economic development, in that our knowledge can be commercialised, spun-off, licensed and re-used, through adjacent Science and Technology Parks or through relationships with industry. There are entire twins in the US that would shrivel up overnight without their co-located University. Academic research is still a key driver in innovation both directly and indirectly, through the production of research staff who then go to corporate research facilities.

But a number of these are fairly recent developments. International focus requires knowing about the world and having a method of travel, as well as not being at war with the place you’re trying to visit! The change from small and elite to large and massive requires vast amounts of money and resources and the changes have taken place with staggered effects across most of the second half of the 20th Century, into this new century. It’s not just the number of students, Altbach emphasises, it’s the range of post-secondary options that have sprung up to meet technical and industrial demand. These new institutions have new charters, new focus areas, different lengths and types of degree and we suddenly find that, much as oranges are not the only fruit, training at a University that can grant PhDs may not be the best preparation for working at an institution that is post-secondary yet nothing much like the places that its teachers have come from. The ‘pinnacle’ research institutions, prestigious and few in number, serve a smaller group and are probably the most complex institutions in the spectrum, training the most professionals and receiving the lion’s share of research funding. This introduces tension, between the doctoral graduates of the pinnacle who may transfer to other institutions and find themselves at odds with a very different mission, and because any system where an entrenched elite receive advantages that allow them to stay elite is always going to cause tension. Massification has led to greater disparity. Yes, almost anyone can go to college, but it appears that achieving that has meant that we have now risked devaluing the term ‘college’ along the way. In Australia, students say they’re going to ‘Uni’ when that could mean TAFE (Technical and Further Education), adult education, or actual University. (We had a comprehensive shake-up some time ago that turned all of the institutes of technology into Universities, or we would have that distinction as well. The previous separation of degrees and ‘applied’ degrees had actually worked quite well, at least in my reading and opinion, but government initiatives are what they are, and we will talk more about this in the discussion of public and private good.) Should it matter what one does when the word ‘college’ is mentioned? No, it shouldn’t. The problem is when the issue becomes confusing or we provide a service that we call ‘college’ to all of our citizens, yet some citizens get a better version than others for reasons that are not transferable or equitable. To quote Altbach:

Massification inevitably creates more variations and diversity in academic systems. It creates opportunities for access that are unprecedented in world history, but at the same time it creates systems that are less equal and more difficult to support financially.

This brings us squarely into Altbach’s next point, the issue of public versus private good, a debate that rages unabated today. Changes in Australian University funding have very much been under the presumption that the greatest good is being enjoyed by the private citizen who receives the education, rather than the society to which they contribute, hence the citizen should bear more of the load for their own education. (My response is ‘piffle’, the benefit to our society of the educated is hard to overestimate,  but I’ve already discussed this in an earlier post.) As noted in the article, whether the state can or cannot support public education is moot as many states are just shifting the burden to the citizen and their families. This inevitably creates a two-speed system, where some go to college and some do not, because of influences and decisions that may have had an impact on the grandparents and parents of the student, rather than any personal merit. Given that, even in a meritocratic system, training programs and preparation schools can make all the difference, and these are usually private and expensive, any meritocratic system risks quickly falling into the same two-speed divide. Even if a place is available at the correct type of institution, the costs of relocating, leaving a secure community and moving from a more socialised and low-cash environment to an isolated, pay-up-front and distant location to attend a college may place another bar in the way of the prospective student from a less advantaged area. Mass higher education is supposed to be for the masses but solving the issues of nomenclature, access and preparation do nothing if no-one can actually attend unless they’re rich. Many of our activities are linked, in one way or another, to the public good and we are well aware that feeling that you are an active and contributing member of your society is usually associated with greater motivation to participate and be involved with this good. Any restrictive mechanisms driven by forcing the burden back on to the citizen, defended by the notion of personal benefit dominates any public benefit, undermine the ability of people to join and contribute to greater society: this undermines the public good, as well as setting the stage for disenfranchisement and a disengagement from society. Every time we do this, we risk casting another generation out of the circle of those who will go to college.

I’ll finish this tomorrow, with a discussion of the contemporary issues, from the report, and my own thoughts overall.

The Complex Roles Of Universities In The Period Of Globalization – Altbach – Part 1

One of the most handy things about having a new member in a research group, especially one who is just finishing or has just finished submitting a PhD, is that they come in with an entirely new subset of the possible papers in the given discipline, which they have used to construct their theses and inform their thinking. While you will have the standard overlap of the key papers in the field, there will often be waterways that run away from the main river and it is in these diverse streams that we find new ways of thinking, even leading to these stream becoming tributaries that feed back into our main body, strengthening the overall work.

R has just sent me a reference from her thesis, a copy of Altbach’s 2011 publication in Higher Education in the World 3: New Challenges and Emerging Roles for Human and Social Development, entitled “The Complex Roles Of Universities In The Period Of Globalization”. The abstract is pithy but this quote stands out: “The academic drift of the 21st century raises concerns about the core functions of universities and how contemporary changes have affected academic missions.” This is a fascinating paper and one that I wish I turned up early because it has the same concerns as I do, and as Richard Hil did with his Whackademia book, in that we are all being asked to do more with less and it is how we do this that will decide our future, and the future of higher education. (Readers may recall that I did not agree with much of what Hil said – as I said, I wish I had read Altbach sooner because it would have made the rebuttal easier.) I’m going to cover this across a few posts because the paper has a fair bit of comment and I’d like to make some commentary!

Altbach looks at the different roles that Universities have had over time, including the different roles that they play in certain countries and how time, politics, religion, wealth and nationalism have all contributed to changing demands on the sector. There is no doubt that teaching and research make up our core functions but we can vary from country to country as to whether we are teaching technical skills, professional skills or general education at Universities. Over time, we have often been in conflict with our own societies, which can lead to great creativity but at the cost of additional load or difficult burdens. Research is equally difficult to pin down: are we talking ‘pure’ research or ‘applied’ research? Does research have to be discipline focused or can we perform research on teaching, or research on research? Does it matter where the research money comes from? Different areas inside the same university can have completely different answers to these questions so it’s little doubt that this question is still open!

Universities have been used to foster national development and identity, as Altbach mentions with German, Japanese and American examples, or as stabilising influences in the third world. We are also steadily evolving academic centres, adding courses as the ranks of the professions grow. My profession, Computer Scientist, wasn’t even a profession until the second half of the 20th century (that’s why we have so few cool awards – there is no Nobel prize in Applied Algorithmics). Immediately we see a conflict in the sense of stability and status quo required to be a national touchstone, while determining how we adapt to the changing demands of the workforce and the new professionals.

We have always been associated with knowledge as both the defenders and disseminators, ignoring secular and religious demand to not teach certain things or to state that red is black, with a focus on organisation to facilitate later retrieval. This access to knowledge also feeds in to one of our other key facets, or at least one of the most desirable, that of an intellectual centre. As academics, we have the freedom to express our ideas and, many would argue, the obligation to do so given that we have that freedom. The expertise that our staff have should be available to all in terms of interpretation and refinement of ideas and concepts but to do that we have to engage with the community. It is of little surprise that we often find ourselves involved in social and political movements, supporting other activists, providing resources and making an overall contribution to the intellectual life of our surroundings.

This is, for me, a very important point because it forces us to consider where the private individual ends and the public intellectual begins, if such a division even makes any sense. From a personal perspective, I would not raise my politics in a classroom but I would discuss issues of ethics and equality, some of which may or may not be in accord with prevailing government thought. Let me be more explicit. Yesterday, I attended a rally for Marriage Equality, as part of a reaction against the Australian Federal Government’s rejection of a bill to allow same sex marriage. I would most certainly not have advertised this event in my lectures or told my students about it because I think that there’s far too much capacity for me to influence my students to act through our relationship, which is not a discussion or political sharing but overt influence. I attended the rally as a private citizen but if my students asked me about it, because we did get photographed and videoed, then I feel that I could explain my actions within an ethical framework, which means that this is informing my role as public intellectual. My community, equality and ethical focus drives both the citizen and the academic and allows me to carry out two roles while attempting to minimise any exploitation of the power relationship that I have with my students. However, my capacity as a (notional) public intellectual requires me to have an explanation for what I did that is articulate and comprehensible. The private citizen is impassioned but the academic is both passionate and rationale, and can place the activity in a context that allows it to be shared.

But, as I always say, there is no point having a system that only works with perfect people. Altbach is talking about our institutions, which is the right focus for the paper, but the institutions are just buildings without the academics and students that fill them. I attempt to juggle my private and public self and, while sometimes I succeed more than others, I think I know what I should ‘look like’ to my institution, my peers, my students and my social groups. What will be interesting in the coming world of change for Universities is how we deal with the people who don’t work as well within the role of educator. I have no time, respect or tolerance for those of my colleagues who confuse intellectual freedom with a wanton disregard for reasonable behaviour in this privileged role. Just because we organise the knowledge doesn’t mean that we own it, nor does our mastery of intellectual pursuits (if we achieve that) make us any better than anyone else: we have merely had more opportunity but, for me, that comes with a corresponding level of responsibility. I have seen more than one academic, not at my own University I hasten to add, who has obviously been grooming a student through manipulation of the aura of competency that any decent academic can muster, where we appear wise, worldly and incredibly, staggeringly, deep on matters that are so very, very passionate and important. Altbach writes of what changes we have seen in Universities but you only have to read through the yellow press (or the FFFF00 press on the web) to see how many educators are abusing their relationship with their students and I’m not sure what this says about how the educators themselves are changing. I have heard dire tales of exploitative behaviour in the 70s and 80s in my country – “A for a lay” unpleasantness and similar. When we talk of our intellectual freedoms, our influence on the world as national stabilisers and centres of knowledge, it is important to remember that the components of these institutions are merely people. As we increase the stresses on the organisations, so too do we distribute this across people and, given that people are already failing some key moral and disciplinary requirements, any discussion of what our role should become will have to take into account the fact that we are building a system from people, to work with other people.