There is currently a conference taking place at Queensland University of Technology (QUT) Australia called the “National Summit on Student Engagement, Learning and Behaviour.” A lot of the folks in my Twitter timeline seem to be in attendance. The conference website makes it clear that it has been set up in reaction to calls for more traditional discipline in the classroom. So the conference is on a mission.
Whether as a result of this mission or not, people have been tweeting some pretty dodgy claims. During one session about school exclusion, the claim was made that, “Schools with higher suspension rates have poorer climates, higher drop out, lower achievement, more time on discipline.” This is clearly meant to imply that high suspension rates cause these other problems but it is a classic example of attributing a cause to what is actually a correlation. For example, it is quite possible that the poor climate (however that is measured) causes the high suspension rate or, alternatively, there may be some unmeasured or unmeasurable factor that causes all of these issues. A high level of social deprivation in the local community could plausibly cause all of these issues, so too could an inadequate behaviour management policy.
In another tweet the claim was made that being excluded once increases the likelihood of further exclusions. I hardly find this surprising. What is the point of this claim? It certainly doesn’t prove that exclusions cause exclusions because, again, there is likely to be a latent factor – e.g. propensity towards violence – that causes particular students to be repeatedly excluded. Perhaps the argument is that exclusions don’t cure bad behaviour. Is that the purpose of exclusion? I had assumed that it was primarily to keep other students safe and allow them to learn.
What if we control for all other factors and find that exclusion is the greatest ‘predictor’ of poor school climate and so on. Have we now proved cause? Well the language is seductive but all that it essentially means is that of the things we’ve measured, exclusion and school climate have the greatest correlation. This still does not tell us which way around this interaction works or whether there might be a factor that we haven’t measured that causes both; either of which scenario seems far more plausible that attributing cause to exclusions.
I am not making an argument for exclusion here. I am just pointing out that you can’t really argue against it with these correlations. If you think exclusion is morally wrong then make that case.
As a student in the 1980s and 1990s, I took part in many classroom debates. As a form tutor in England, I used to have to orchestrate the occasional debate as part of the school’s citizenship programme. Largely ignorant of the relevant facts, students would nonetheless be encouraged to take a position – which was usually that of their parents – on a hot-button social issues such as hunting with dogs or whether beauty contests are bad. The debate was unedifying and I always sensed that perhaps there was a better way.
Yet there is one positive comment that we can make about such classroom activities: they reflect real life. We have just seen precisely such a debate take place prior to the UK referendum on whether to leave the European Union.
I did not vote in this referendum. My future is in Australia and it didn’t seem right to cancel-out the vote of someone whose future is in the UK. If I had chosen to vote then I would have reluctantly voted to remain in the EU. It’s worth briefly exploring why.
I have no love for the European Union. It is undemocractic and absurd. The fact that the European Parliament has to pack-up once a month and move everything from Brussels to Strasbourg, that this is to please the French, that everyone else thinks it’s mad and that nothing can seemingly be done about it tells you much about the organisation and how it operates. I also think that the common agricultural policy needs to go or be radically reformed as well as the common fisheries policy. I don’t see these as operating in Britain’s interest.
So why would I have voted to stay? I would have worried about the economic uncertainty of leaving, especially at a time when the UK has such a low balance sheet due to the bank robberies of 2008 and when much of the country is still feeling the effects of austerity: that mechanism by which the poor bail-out the rich. I would also have been concerned about the consequences for the English regions who are likely to suffer most from any downturn. Admittedly, many of those in the most deprived economic groups might wonder what they had to lose.
Much of this wasn’t captured by the public debate and the proponents on either side. The leave campaign made absurd claims about extra funding for public services and banged on about immigration. The remain side did address the economic arguments but in a silly, pantomime kind of way which insulted everyone’s intelligence. As I now scan social media, I see people blaming the leave vote on ignorant racists. No doubt, there are plenty of those about. But I also think there are also many who voted remain in an ignorant way – they just wanted to signal how cosmopolitan and virtuous (not racist) they were.
I moved into a house in the dodgy end of Watford in 2004. When I left for Australia in 2010 the area had already started to change through Eastern European immigration. When I returned for a visit in 2014 we decided to drive past the old house. It was 11.00 am and a group of about five white guys were stood at the end of the street drinking beer. It’s not illegal to do this – in many ways Britain is still a remarkably free country. But you can imagine how the elderly, white, working class residents of that street might have felt. I have a friend who still works in a local school where she claims that the majority of students are now from Eastern Europe.
I understand that such areas largely voted to remain but it is not racist to coolly discuss the impacts of large-scale migration. In fact, it is necessary. The working class people living in these districts are unlikely to make use of the benefits of free movement. They, their children and grandchildren are unlikely to move to Spain any time soon. That’s a middle class perk. And yet they are the ones who are being asked to make the greatest accommodations to change.
In education, we are starting to move away from ignorant classroom debates. Some are starting to recognise that before you can think critically about a subject, you need to know something about it and so systematically explaining concepts has become a priority. I think that a new politics needs to do the same. We need less name-calling and more discussion of the way that the common agricultural policy works. Facts won’t tell us what is moral but they will certainly enrich and improve our moral decision making.
As a traditional educator, I don’t consign people to categories or assume that everything comes from within. I believe that people can be taught, that ideas can be transmitted and that minds can grow and change. This is an optimistic ideology of self advancement through informed choice. I believe in people and that if we give them a better standard of public debate then they might just surprise us.
These slides will not mean much if you didn’t see my presentation on explicit teaching. However, for those who did see it, they contain all the references that I drew upon.
In the early 1980s, my parents bought my sister and me a big Christmas present – a Sinclair ZX Spectrum 48K with a portable black-and-white television to connect it to. From the outset, I made more use of it than my sister and it spent much of its time connected to the colour television in our lounge. It was a colour computer, after all: the successor to the black-and-white Sinclair ZX81.
I did two things with it. I tried playing games. This was the early 80s computer game boom and lots of little shops had appeared to take advantage of this. There was a dingy place under the council offices in Dudley where I bought Manic Miner and Atic Atac on cassette tape. I rapidly decided that there was nothing more pointless and frustrating than Atic Atac but Manic Miner had a certain surreal charm. I enjoyed progressing past the first few levels but then I ground to a rapid halt at Eugene’s Lair. This was a level where Eugene – a kind of humpty-dumpty character – went slowly up and down as toilets with flapping lids chased Miner Willy. I just couldn’t do it. It was too hard.
My mum had a good friend who had a son my age. We would meet up a few times a year. He also had a Spectrum and told me that he had completed Manic Miner ages ago. He took charge of my machine and flew past Eugene and his toilets as easily as I might smash a watermelon with a mallet, which was something that I now felt like doing. I had already become aware that I was not ‘sporty’ because I was never picked first when we were choosing teams in the playground for football. I carved out a role as a brick-wall of a defender but I saw this as consistent with my general lack of hand-eye coordination, a factor which also explained my computer gaming failure.
So I focused on programming. I didn’t know anyone else who program computers. My Dad bought a few books and ‘INPUT’ magazine and I copied out the programs. It was largely discovery learning with the aid of a little instruction from ‘INPUT’. I would change a line in a program to see what happened. Usually the program stopped working but sometimes I figured out something useful. Programming gives you this kind of instant feedback and so makes for a relatively good discovery learning environment. You can write a story full of errors and nonsensical sentences and be completely unaware of this unless someone read it and gave you detailed advice. But if you write a dodgy program it just won’t work.
I look back and I reflect that I improved at programming because I spent a lot of time doing it. I realise now that my friend probably spent a great deal of time playing Manic Miner or similar platform games, even if he wasn’t letting on. He also seemed to be quite eloquent with his tips and dodges whenever I asked him about the games and I therefore suspect that he was supplementing his discovery learning with a little instruction from his friends and from magazines. The fact that I had poor hand-eye coordination was my reality in the 1980s and, in truth, I’m probably not optimised as a human being for playing computer games but this seems like less of a factor now than perhaps it once was.
There are two messages that I would draw from this and that seem quite consistent with the research. Firstly, we can convince ourselves that we are not an X person, whatever X might be. This could well be based upon some underlying genetic propensity but it is far from the destiny that it might seem. This is the fixed mindset that we might bring to a particular subject or area of learning and I think it has been underappreciated just how much this can vary within one individual: I had a fixed mindset about computer games but a growth mindset about computer programming.
Secondly, we need to be careful about frustration because it can kill learning. I became so frustrated with Eugene’s lair that I declared a plague not only on Manic Miner but on computer games in general. When we introduce students to complex areas we need to be careful to strategically sequence wins. Students need to have some success in order to believe that success is possible. We can fetishise being stuck and preach about how marvelous this is but it is only those students who already back themselves – like I did with programming – who will readily persist. Those who have little affinity for the subject are just as likely to declare it stupid, pointless and not something that they will need in their future lives.
I still hate Eugene and his stupid toilets and I don’t play computer games.
On July 2nd, Australians will go to the polls for a general election. At the time of writing, the two major parties are tied in opinion polling with a hint that the incumbent Liberal-National Coalition (roughly equivalent to Britain’s Conservative Party) still have an advantage in key marginals.
Continues here at the UK Labour Teachers site
A while back, I found myself visiting my sister-in-law who had just moved to a new town. I decided to drive to the local supermarket and this seemed like a good chance to test out an idea that I had heard from David Didau and others. There is a debate about when feedback should be provided to students: should it be immediate or delayed? Feedback is a complicated issue in education and this is probably due to the fact that we are lumping together very different things under the one heading and so the answer to the question on timing is likely to be, ‘it depends.’
Didau had used the example of a car satellite navigation system or GPS in order to make a point against immediate feedback. GPS systems provide such feedback and it was Didau’s contention that this is why we don’t learn routes very well if we rely on them. Didau discussed using GPS to navigate a new city and not learning any of the routes.
So I decided to try and use GPS to learn the route to the supermarket. I paid attention to it on the way there and then tried to drive back without it. I learnt the route just fine and was even able to complete the same trip the next day from memory. I was using Google Maps on my iPhone – this shows a live map of the surrounding area and not only gives an indication of the next turn but the turn after that, something I find useful for ensuring that I turn into the correct lane if there are multiple lanes. I never suggested that this was the best way to learn a route – I was simply testing whether it was possible with GPS.
Dan Meyer picked up on my post about this and decided to relate GPS to explicit instruction in mathematics. He had found a study from 2006 where participants were given various different ways of navigating around a German zoo. Three conditions involved using handheld Personal Digital Assistants (PDAs) that gave various visual and auditory information (such as a picture of the intersection, an animation of the pathway and verbal instructions to ‘turn left’) when a participant reached an intersection. The fourth condition involved giving participants map ‘fragments’ i.e. maps of routes rather than of the whole zoo with photographs of the intersections in numbered order.
Participants were not told in advance that they would be tested on route and survey knowledge. When these tests were later carried out, all conditions showed learning but the map fragment condition demonstrated a statistically significant advantage over the others. Meyer then states:
“So your GPS does an excellent job transporting you efficiently from one point to another, but a poor job helping you acquire the survey knowledge to understand the terrain and adapt to changes.
Similarly, our step-by-step instructions do an excellent job transporting students efficiently from a question to its answer, but a poor job helping them acquire the domain knowledge to understand the deep structure in a problem set and adapt old methods to new questions.”
This is a non-sequitur. It is not clear that we can make any inferences from such a study and apply them to maths teaching. Even if we were able to, why does Meyer think the PDA conditions are more like explicit instruction than the map fragment one? In classic studies on the worked example effect the experimenters often made use of example-problem pairs. This is where a student is shown a whole worked example and then has to complete a similar problem themselves. You might argue that this has more structural similarity to the map fragment condition than the PDA conditions. I won’t be making such an argument because the link between German zoos and maths teaching seems tenuous and any conclusions we might draw about maths seem a little eccentric.
Many of those commenting on Meyer’s post made similar points to this and he added a coda in a comment of his own:
“The question that’s useless to us is “should we use [x] in helping students learn?” The answer for most values of x including worked examples is “yes.” The more interesting question to me is, “What kind of knowledge is easy and difficult to learn by way of worked examples?” And, “Under what preconditions are worked examples most helpful?”
The answer to those questions for some of the traditionalists whose blogs I tune into now and then seems to be “all knowledge for all novices” and “no preconditions are necessary.” That kind of maximalism is pretty easy to falsify. (See Greg Davies‘ comment for an example: “Surface structure always comes first.”) Even one datum falsifies a universal claim.” [sic]
I am not sure whether Meyer is referring to me here but I have certainly never claimed that “no preconditions are necessary” for learning from worked examples. To learn from a worked example you would need to understand a whole lot of prerequisite maths. If you don’t know multiplication tables, for instance, then algebra can be tricky – try factorising quadratics. This is a point I’ve made many times and actually sounds like a viewpoint that you might label as ‘traditional’.
I have also written about the expertise reversal effect where the usefulness of worked examples fades as students become more expert. This is why explicit instruction gradually moves from explicit examples, through guided examples to independent practice. Rosenshine provides an excellent explanation of this process which is one that also makes objectives clear and is highly interactive. It is odd that Meyer links to Rosenshine but then insists on such a weird interpretation of explicit teaching.
The idea – dismissed by Meyer – that surface structure comes first is pretty well known in the field of cognitive psychology. I note that Meyer has recently become a fan of Dan Willingham and so he should perhaps return to this piece that Willingham wrote about the subject. Sadly, there are no pedagogical magic beans that we can buy that will helps us accelerate students towards apprehending deep structure. I am deeply sceptical that problem-based learning (PBL) can do this. I note that Meyer links to some Bransford and Schwartz pieces to support his view. I haven’t had chance to read these yet because I’ve been focused on the GPS study but I would be surprised if they draw upon well-controlled experiments that test strong explicit approaches against strong PBL ones.
We all want students to apprehend the deep structure of problems but we must recognise that this is hard work. The methods used by explicit educators might be to highlight non-examples to prevent students overgeneralising principles – a key source of many maths misconceptions – and providing deep explanations. Some have even tried to turn this into a science. Indeed, I find it surprising that those who are so eager to promote problem-based approaches to mathematics are also keen to see explicit instruction as simply a set of step-by-step directions, ignoring the role of explanations altogether: “Do this. Now do that. Don’t ask why.”
Actually, it’s not that surprising because it is much easier to knock-out a straw man than a heavyweight boxer.
For some time now, here at the Extraordinary Learning Foundation™, we have been working on Actionizing Thinkiness. This is why we developed the Think-it-out™ toolkit. We have been working with teachers to help engage more thinking in their otherwise thought-free lessons.
However, we have encountered a problem. Teachers typically use the toolkit to direct questions to students in class. In other words, the teacher maintains complete control over the learning episode. This is self-evidently undesirable so we wondered whether we could develop a model of co-deliveracy that was authentic, engaging and allowed learners to take control of the thinkiness.
This is the thinking behind the thinking that led to us thinking-up the idea of Thinkiballs™.
Mace Jakins is a fifth grade social studies teacher at Benington International School, UA. His chestnut hair shines as he describes the process of working with one of our Extraordinary Learning Foundation™ Associates on…
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