Dewey’s Pedagogic Creed

As I’ve noted, the space I’m in is not new, although some of the places I hope to go with it are, and we have records of approaches to education that I think fit well into an aesthetic framing.

As a reminder, I’m moving beyond ‘sensually pleasing’ in the usual sense and extending this to the wider definition of aesthetics: characteristics that define an approach or movement. However, we can still see a Cubist working as both traditionally aesthetically pleasing and also beautiful because of its adherence to the Cubist aesthetic. To draw on this, where many art viewers find a large distance between them and an art work, it is often attributable to a conflict over how beauty is defined in this context. As Hegel noted, beauty is not objective, it is our perspective and our understanding of its effect upon us (after Kant) that contributes greatly to the experience.

A black and white chest and head portrait of John C. Dewey, an older man with centre-parted white hair, a trimmed mostly dark haired moustache and oval wire-framed glasses.

John C. Dewey. Psychologist, philosopher, educator, activist and social critic. Also, inspiration.

Dewey’s Pedagogic Creed was published in 1897 and he sought to share his beliefs on what education was, what schools were, what he considered the essential subject-matter of education, the methods employed, and the essential role of the school in social progress. I use the word ‘beliefs’ deliberately as this is what Dewey published: line after line of “I believe…” (As a note, this is what a creed is, or should be, as a set of beliefs or aims to guide action. The word ‘creed’ comes to us from the Latin credo, which means “I believe”.) Dewey is not, for the most part, making a religious statement in his Creed although his personal faith is expressed in a single line at the end.

To my reading, and you know that I seek characteristics that I can use to form some sort of object to guide me in defining beautiful education, many of Dewey’s points easily transfer to characteristics of beauty. For example, here are three lines from the work:

  1. I believe that education thus conceived marks the most perfect and intimate union of science and art conceivable in human experience.
  2. I believe that with the growth of psychological science, giving added insight into individual structure and laws of growth; and with growth of social science, adding to our knowledge of the right organization of individuals, all scientific resources can be utilized for the purposes of education.
  3. I believe that under existing conditions far too much of the stimulus and control proceeds from the teacher, because of neglect of the idea of the school as a form of social life.

Dewey was very open about what he thought the role of school was, he saw it as the “fundamental method of social progress and reform“. I believe that he saw education, when carried out correctly, as being a thing that was beautiful, good and true and his displeasure with what he encountered in the schools and colleges of the late 19th/early 20th Century is manifest in his writings. He writes in reaction to an ugly, unfair, industrialised and mechanistic system and he wants something that conforms to his aesthetics. From the three lines above, he seeks education that is grounded in the arts and science, he wants to use technology in a positive way and he wants schools to be a vibrant and social community.

And this is exactly what the evidence tells us works. The fact that Dewey arrived at this through a focus on equity, opportunity, his work in psychology and his own observations is a testament to his vision. Dewey was rebelling against the things he could see were making children hate education.

I believe that next to deadness and dullness, formalism and routine, our education is threatened with no greater evil than sentimentalism.

John Dewey, School Journal vol. 54 (January 1897), pp. 77-80

Here, sentimentalism is where we try to evoke emotions without associating them with an appropriate action: Dewey seeks authenticity and a genuine expression. But look at the rest of that list: dead, dull, formal and routine. Dewey would go on to talk about schools as if they were prisons and over a hundred years later, we continue to line students up into ranks and bore them.

I have a lot of work to do as I study Dewey and his writings again with my aesthetic lens in place but, while I do so, it might be worth reading the creed. Some things are dated. Some ideas have been improved upon with more research, including his own and we will return to these issues. But I find it hard to argue with this:

I believe that the community’s duty to education is, therefore, its paramount moral duty. By law and punishment, by social agitation and discussion, society can regulate and form itself in a more or less haphazard and chance way. But through education society can formulate its own purposes, can organize its own means and resources, and thus shape itself with definiteness and economy in the direction in which it wishes to move.

ibid.


Exploring beauty and aesthetics

One of the first steps I took on this path occurred when I read Hegel’s lectures in aesthetics, and related writings, as he strove to understand the role of fine art. It’s worth noting that what I am referring to as Hegel’s views are reconstructed from what he wrote, what he was recorded to have said, and the interpretation of what he meant, and we must accept that this is not guaranteed to be what he actually thought. With that caveat aside, I can make some statements about Hegelian aesthetics, as they relate to beauty, truth and art.
A portrait of Hegel, staring at the reader. He has intense blue eyes and wispy grey hair.

“Nothing great in the world has ever been accomplished without passion.” Hegel

Hegel saw a clear relationship between fine art, beauty and truth building upon Kant’s reflection that even the declaration of an object’s beauty is an admission of the effect that the object is having upon us. Hegel took this into the realm of the senses, more precisely in my opinion, and sought to find the ideal beauty that was being represented by real art. Because Hegel saw art itself as an expression of spiritual freedom, his view of art was as in the figurative mode, depicting people and real scenes, and thus classical Greek form was particularly pleasing to him. As I’ve noted before, we can extract resonating phrases from the pragmatic situations of philosophers, and I will do so here.
For Hegel, ideal beauty is one where we see the sensuous expression of spiritual freedom; where our senses are engaged, they are consumed by their perception of an aesthetic ‘rightness’ and we see things are they are. Given the Platonic trinity of beauty, truth and goodness, it is not a surprise that classical Greek forms are so immediately pleasing to him! Hegel is rather dismissive of symbolic art, seeing it as a step on the way to real art and requiring both physical intervention and a movement forward to the figurative form.
At this point, I’d like to leave Hegel’s fixed point in time, given the changing opinion of the role and importance of symbolic forms in art, and because Hegel sets up a tension between the natural and the spiritual that is key to him arriving back at his fixation on the perfection of Greek art. It’s fascinating (and Hegel’s lectures on aesthetics are delightful) but it’s not my focus.
The sensuous expression of spiritual freedom can be interpreted in many ways. Sensuous, as a word, often has sexual overtones but it is not what is meant here. It simply means something that relates to or affects the senses rather than the intellect. This leads us immediately to aesthetics, whether as the appreciation of beauty or as the set of principles that we often use to describe art. Now, through aesthetics, we link the sensuous back to the intellect and we can see, more clearly, the way that beauty can drive us towards certain thoughts, as Plato espoused. Hegel’s idea of what constituted ideal sensuous expression began and ended with Greek gods, sculptures and all of those forms. His aesthetics could probably not have accommodated something such as Cubism, except as a step towards ‘real art’. He could appreciate it having some aesthetically pleasing characteristics but it was not really art. There is a lesson for us here in determining what constitutes “beautiful education”.
Hegel had no doubt that his aesthetics were sound, despite his views obliterating the value of almost any art in the previous millennium. Many of us feel equally strongly about the way that we teach and I have begun to believe that this conflict of principle is what often causes us to put aside even the strongest evidence, where it would lead us to abandon what we see as being beautiful, for something that we suspect or fear will be ‘ugly’. We also see a similar “shock of the new” in education as we did in art. Let us not forget that it was only 1905 when wild brush strokes and brash colour palettes saw a group of artists labelled as “Wild Beasts!” (Fauvism). But, as I noted earlier, the “fear of the old” is as contaminating a world view as the “shock of the new”. We should not confuse our personal comfort with a form of expression with it being the best that can be achieved. We should not assume that personal discomfort is a reliable indication of positive progress.
I gave a talk recently, which I will record and make available shortly, where I argued that many of our problems in education stem from what is, ultimately, an aesthetic distinction over which characteristics make up good teaching. It is entirely possible for two people with different, or even conflicting, views of the characteristics of good teaching to both be rightly convinced of their status of “good teachers”. I reduced good educational practice to three elements, after a model employed by Suits in “The Grasshopper”:
  1. the ability to state the goal of any educational activity as separate from the activity,
  2. the awareness of evidence-based practice and its use in everyday teaching, and
  3. a willingness to accept that it is correct goal setting and using  techniques that work, and can be shown to work, that will lead to better outcomes.
(Suits’ motivation was the refutation of Wittgenstein’s thoughts on the inability to define what a game is. The Grasshopper is a delightful book, whether you are convinced by the argument or not.)
This is a very short summary and I’ll write more on this but I mention it because these guidelines are effectively devoid of aesthetics, yet they are meaningless without having some aesthetically guided practice to act upon. They were chosen specifically because they were hard to argue against, as they are really a summary of how we conduct many actions as humans.
Is there an ideal form for education? Can it be, as Hegel did, put to one side while we discuss the vessels that carry it into the sensual realm? Are we capable of agreeing on that before we start ranking the characteristics that we can come up with?
I think it’s going to be an interesting year while we discuss it!

A Year of Beauty

Plato: Unifying key cosmic values of Greek culture to a useful conceptual trinity.

Plato: Unifying key cosmic values of Greek culture to a useful conceptual trinity.

Ever since education became something we discussed, teachers and learners alike have had strong opinions regarding the quality of education and how it can be improved. What is surprising, as you look at these discussions over time, is how often we seem to come back to the same ideas. We read Dewey and we hear echoes of Rousseau. So many echoes and so much careful thought, found as we built new modern frames with Vygotsky, Piaget, Montessori, Papert and so many more. But little of this should really be a surprise because we can go back to the writings of Marcus Fabius Quintilianus (Quinitilian) and his twelve books of The Orator’s Education and we find discussion of small class sizes, constructive student-focused discussions, and that more people were capable of thought and far-reaching intellectual pursuits than was popularly believed.

… as birds are born for flying, horses for speed, beasts of prey for ferocity, so are [humans] for mental activity and resourcefulness.” Quintilian, Book I, page 65.

I used to say that it was stunning how contemporary education seems to be slow in moving in directions first suggested by Dewey a hundred years ago, then I discovered that Rousseau had said it 150 years before that. Now I find that Quntilian wrote things such as this nearly 2,000 years ago. And Marcus Aurelius, among other stoics, made much of approaches to thinking that, somehow, were put to one side as we industrialised education much as we had industrialised everything else.

This year I have accepted that we have had 2,000 years of thinking (and as much evidence when we are bold enough to experiment) and yet we just have not seen enough change. Dewey’s critique of the University is still valid. Rousseau’s lament on attaining true mastery of knowledge stands. Quintilian’s distrust of mere imitation would not be quieted when looking at much of repetitive modern examination practice.

What stops us from changing? We have more than enough evidence of discussion and thought, from some of the greatest philosophers we have seen. When we start looking at education, in varying forms, we wander across Plato, Hypatia, Hegel, Kant, Nietzsche, in addition to all of those I have already mentioned. But evidence, as it stands, does not appear to be enough, especially in the face of personal perception of achievement, contribution and outcomes, whether supported by facts or not.

Evidence of uncertainty is not enough. Evidence of the lack of efficacy of techniques, now that we can and do measure them, is not enough. Evidence that students fail who then, under other tutors or approaches, mysteriously flourish elsewhere, is not enough.

Authority, by itself, is not enough. We can be told to do more or to do things differently but the research we have suggests that an externally applied control mechanism just doesn’t work very well for areas where thinking is required. And thinking is, most definitely, required for education.

I have already commented elsewhere on Mark Guzdial’s post that attracted so much attention and, yet, all he was saying was what we have seen repeated throughout history and is now supported in this ‘gilt age’ of measurement of efficacy. It still took local authority to stop people piling onto him (even under the rather shabby cloak of ‘scientific enquiry’ that masks so much negative activity). Mark is repeating the words of educators throughout the ages who have stepped back and asked “Is what we are doing the best thing we could be doing?” It is human to say “But, if I know that this is the evidence, why am I acting as if it were not true?” But it is quite clear that this is still challenging and, amazingly, heretical to an extent, despite these (apparently controversial) ideas pre-dating most of what we know as the trappings and establishments of education. Here is our evidence that evidence is not enough. This experience is the authority that, while authority can halt a debate, authority cannot force people to alter such a deeply complex and cognitive practice in a useful manner. Nobody is necessarily agreeing with Mark, they’re just no longer arguing. That’s not helpful.

So, where to from here?

We should not throw out everything old simply because it is old, as that is meaningless without evidence to do so and it is wrong as autocratically rejecting everything new because it is new.

The challenge is to find a way of explaining how things could change without forcing conflict between evidence and personal experience and without having to resort to an argument by authority, whether moral or experiential. And this is a massive challenge.

This year, I looked back to find other ways forward. I looked back to the three values of Ancient Greece, brought together as a trinity through Socrates and Plato.

These three values are: beauty, goodness and truth. Here, truth means seeing things as they are (non-concealment). Goodness denotes the excellence of something and often refers to a purpose of meaning for existence, in the sense of a good life. Beauty? Beauty is an aesthetic delight; pleasing to those senses that value certain criteria. It does not merely mean pretty, as we can have many ways that something is aesthetically pleasing. For Dewey, equality of access was an essential criterion of education; education could only be beautiful to Dewey if it was free and easily available. For Plato, the revelation of knowledge was good and beauty could arose a love for this knowledge that would lead to such a good. By revealing good, reality, to our selves and our world, we are ultimately seeking truth: seeing the world as it really is.

In the Platonic ideal, a beautiful education leads us to fall in love with learning and gives us momentum to strive for good, which will lead us to truth. Is there any better expression of what we all would really want to see in our classrooms?

I can speak of efficiencies of education, of retention rates and average grades. Or I can ask you if something is beautiful. We may not all agree on details of constructivist theory but if we can discuss those characteristics that we can maximise to lead towards a beautiful outcome, aesthetics, perhaps we can understand where we differ and, even more optimistically, move towards agreement. Towards beautiful educational practice. Towards a system and methodology that makes our students as excited about learning as we are about teaching. Let me illustrate.

A teacher stands in front of a class, delivering the same lecture that has been delivered for the last ten years. From the same book. The classroom is half-empty. There’s an assignment due tomorrow morning. Same assignment as the last three years. The teacher knows roughly how many people will ask for an extension an hour beforehand, how many will hand up and how many will cheat.

I can talk about evidence, about pedagogy, about political and class theory, about all forms of authority, or I can ask you, in the privacy of your head, to think about these questions.

  • Is this beautiful? Which of the aesthetics of education are really being satisfied here?
  • Is it good? Is this going to lead to the outcomes that you want for all of the students in the class?
  • Is it true? Is this really the way that your students will be applying this knowledge, developing it, exploring it and taking it further, to hand on to other people?
  • And now, having thought about yourself, what do you think your students would say? Would they think this was beautiful, once you explained what you meant?

Over the coming year, I will be writing a lot more on this. I know that this idea is not unique (Dewey wrote on this, to an extent, and, more recently, several books in the dramatic arts have taken up the case of beauty and education) but it is one that we do not often address in science and engineering.

My challenge, for 2016, is to try to provide a year of beautiful education. Succeed or fail, I will document it here.


Learning Analytics: Far away, so close.

I’ve been thinking about learning analytics and, while some Unis have managed to solve parts of the problem, I think that we need to confront the complexity of the problem, to explain why it’s so challenging. I break it into five key problems.

  1. Data. We don’t currently collect enough of it to analyse, what we do collect is of questionable value and isn’t clearly tied to mechanisms, and we have not confronted the spectre of what we do with this data when we get it.
  2. Mechanisms linking learning and what is produced. The mechanisms are complex. Students could be failing for any number of reasons, not the least of which is crap staff.  Trying to work out what has happened by looking at outputs is unlikely to help.
  3. Focus. Generally, we measure things to evaluate people. This means that students do tests to get marked and, even where we mix this up with formative work, they tend to focus on the things that get them marks. That’s because it’s how we’ve trained them. This focus warps measurement into an enforcement and judgment mechanism, rather than a supportive and constructive mechanism.
  4. Community. We often mandate or apply analytics as an extension of the evaluation focus above. This means that we don’t have a community who are supported by analytics, we have a community of evaluators and the evaluated. This is what we would usually label as a Panopticon, because of the asymmetrical application of this kind of visibility. And it’s not a great environment for education. Without a strong community, why should staff go to the extra effort to produce the things required to generate more data if they can’t see a need for it? This is a terribly destructive loop as it requires learning analytics to work and be seen as effective before you have the data to make learning analytics work!
  5. Support. When we actually have the data, understand the mechanism, have the right focus and are linked in to the community, we still need the money, time and other resources to provide remediation, to encourage development, to pay for the technology, to send people to places where they can learn. For students and staff. We just don’t have that.

I think almost all Unis are suffering from the same problems. This is a terribly complex problem and it cannot be solved by technology alone.

It’s certainly not as easy as driving car. You know that you make the car go faster by pushing on one pedal and you make it go slower by pushing on another.  You look at your speedometer. This measures how often your wheels are rotating and, by simple arithmetic, gives you your speed across the road. Now you can work out the speed you want to travel at, taking into account signs, conditions and things like that. Simple. But this simple, everyday, action and its outcomes are the result of many, many technological, social and personal systems interacting.

The speedometer in the car is giving you continuously available, and reasonably reliable, data on your performance. You know how to influence that performance through the use of simple and direct controls (mechanism). There exists a culture of driver training, road signage and engineering, and car design that provides you with information that ties your personal performance to external achievement (These are all part of support, focus and community). Finally, there are extrinsic mechanisms that function as checks and balances but, importantly, they are not directly tied to what you are doing in the car, although there are strong causative connections to certain outcomes (And we can see elements of support and community in this as we all want to drive on safe roads, hence state support for this is essential).

We are nowhere near the car scenario with learning analytics right now. We have some measurements of learning in the classroom because we grade assignments and mark exams. But these are not continuous feedback, to be consulted wherever possible, and the mechanisms to cause positive change in these are not necessarily clear and direct. I would argue that most of what we currently do is much closer to police enforcement of speed. We ask students to drive a track and, periodically, we check to see if they’re doing the correct speed. We then, often irrevocably from a grading sense, assign a mark to how well they are driving the track and settle back to measure them again later.

Learning analytics faces huge problems before it reaches this stage. We need vast quantities of data that we are not currently generating. Many University courses lack opportunities to demonstrate prowess early on. Many courses offer only two or three measurements of performance to determine the final grade. This trying to guess our speed when the speedo only lights up every three to four weeks after we have pressed a combination of pedals.

The mechanisms for improvement and performance control in University education are not just murky, they’re opaque. If we identify a problem, what happens? In the case of detecting that we are speeding, most of us will slow down. If the police detect you are speeding, they may stop you or (more likely) issue you a fine and eventually you’ll use up your licence and have to stop driving. We just give people low marks or fail them. But, combine this with mechanism issues, and suddenly we need to ask if we’re even ready to try to take action if we had the analytics.

Let’s say we get all the data and it’s reliable and pedagogically sensible. We work out how to link things together. We build  community support and we focus it correctly. You run analytics over your data. After some digging, you discover that 70% of your teaching staff simply don’t know how to do their jobs. And, as far as you can see, have been performing at this standard for 20 years.

What do you do?

Until we are ready to listen to what analytics tell us, until we have had the discussion of how we deal with students (and staff) who may wish to opt out, and until we have looked at this as the monstrous, resource-hungry, incredibly complex problem that it is, we really have to ask if we’re ready to take learning analytics seriously. And, given how much money can be spent on this, it’s probably better to work out if we’re going to listen before we invest money into a solution that won’t work because it cannot work.


Educator’s Statement: Nick Falkner

An artist’s educator’s statement (or artist educator statement) is an artist’s educator’s written description of their work. The brief verbal representation is for, and in support of, his or her own work to give the viewer the student/a peer/an observer/questioning parents/unconvinced politicians/citizens/history understanding. As such it aims to inform, connect with artistic/scientific/educational/societal/intellectual/political contexts, and present the basis for the work; it is therefore didactic, descriptive, or reflective in nature. (Wikipedia + Nick Falkner)

Fear thrives in conditions of ignorance and deprivation. Ignorance is defeated by knowledge. Deprivation is defeated by fairness, equality and equity.

Education shares knowledge and provides the basis for more knowledge. Education attacks ignorance, fights fear, champions equality and saves the world.

If I am always learning then I can model learning for my students and adapt my practice to reflect changes in education as my knowledge increases. Who are my students? What do they need to know? How can I teach them? When will I know if they have the knowledge that they need? What do I need to do today, tomorrow and the day after that?

I have made mistakes but I will try not to make the same mistakes again. The essence of education is that we pass on what we have learned and keep developing knowledge so that we do not have to make the same mistakes again.

That is why I am an educator.


Musings of an Amateur Mythographer I: Islands of Certainty in a Sea of Confusion

If that's the sea of confusion, I'll be floating in it for a while. (Wikipedia - Mokoli'i)

If that’s the sea of confusion, I’ll be floating in it for a while. (Wikipedia – Mokoli’i)

I’ve been doing a lot of reading recently on the classification of knowledge, the development of scientific thinking, the ways different cultures approach learning, and the relationship between myths and science. Now, some of you are probably wondering why I can’t watch “Agents of S.H.I.E.L.D.” like a normal person but others of you have already started to shift uneasily because I’ve talked about a relationship between myths and science, as if we do not consider science to be the natural successor to preceding myths. Well, let me go further. I’m about to start drawing on thinking on myths and science and even how the myths that teach us about the importance of evidence, the foundation of science, but for their own purposes.

Why?

Because much of what we face as opposition in educational research are pre-existing stereotypes and misconceptions that people employ, where there’s a lack of (and sometimes in the face of) evidence. Yet this collection of beliefs is powerful because it prevents people from adopting verified and validated approaches to learning and teaching. What can we call these? Are these myths? What do I even mean by that term?

It’s important to realise that the use of the term myth has evolved from earlier, rather condescending, classifications of any culture’s pre-scientific thinking as being dismissively primitive and unworthy of contemporary thought. This is a rich topic by itself but let me refer to Claude Lévi-Strauss and his identification of myth as being a form of thinking and classification, rather than simple story-telling, and thus proto-scientific, rather than anti-scientific. I note that I have done the study of mythology a grave disservice with such an abbreviated telling. Further reading here to understand precisely what Lévi-Strauss was refuting could involve Tylor, Malinowski, and Lévy-Bruhl. This includes rejecting a knee-jerk classification of a less scientifically advanced people as being emotional and practical, rather than (even being capable of) being intellectual. By moving myth forms to an intellectual footing, Lévi-Strauss allows a non-pejorative assessment of the potential value of myth forms.

In many situations, we consider myth and folklore as the same thing, from a Western post-Enlightenment viewpoint, only accepting those elements that we can validate. Thus, we choose not to believe that Olympus holds the Greek Pantheon as we cannot locate the Gods reliably, but the pre-scientific chewing of willow bark to relieve pain was validated once we constructed aspirin (and willow bark tea). It’s worth noting that the early location of willow bark as part of its scientific ‘discovery’ was inspired by an (effectively random) approach called the doctrine of signatures, which assumed that the cause and the cure of diseases would be located near each other. The folkloric doctrine of signatures led the explorers to a plant that tasted like another one but had a different use.

Myth, folklore and science, dancing uneasily together. Does this mean that what we choose to call myth now may or may not be myth in the future? We know that when to use it, to recommend it, in our endorsed and academic context is usually to require it to become science. But what is science?

Karl Popper’s (heavily summarised) view is that we have a set of hypotheses that we test to destruction and this is the foundation of our contemporary view of science. If the evidence we have doesn’t fit the hypothesis then we must reject the hypothesis. When we have enough evidence, and enough hypotheses, we have a supported theory. However, this has a natural knock-on effect in that we cannot actually prove anything, we just have enough evidence to support the hypothesis. Kuhn (again, heavily summarised) has a model of “normal science” where there is a large amount of science as in Popper’s model, incrementing a body of existing work, but there are times when this continuity gives way to a revolutionary change. At these times, we see an accumulation of contradictory evidence that illustrates that it’s time to think very differently about the world. Ultimately, we discover the need for a new coherency, where we need new exemplars to make the world make sense. (And, yes, there’s still a lot of controversy over this.)

Let me attempt to bring this all together, finally. We, as humans, live in a world full of information and some of it, even in our post-scientific world, we incorporate into our lives without evidence and some we need evidence to accept. Do you want some evidence that we live our lives without, or even in spite of, evidence? The median length for a marriage in the United States is 11 years and 40-50% of marriages will end in divorce yet many still swear ‘until death do us part’ or ‘all of my days’. But the myth of ‘marriage forever’ is still powerful. People have children, move, buy houses and totally change their lives based on this myth. The actions that people take here will have a significant impact on the world around them and yet it seems at odd with the evidence. (Such examples are not uncommon and, in a post-scientific revolution world, must force us to consider earlier suggestions that myth-based societies move seamlessly to a science-based intellectual utopia. This is why Lévi-Strauss is interesting to read. Our evidence is that our evidence is not sufficient evidence, so we must seek to better understand ourselves.) Even those components of our shared history and knowledge that are constructed to be based on faith, such as religion, understand how important evidence is to us. Let me give an example.

In the fourth book of the New Testament of the Christian Bible, the Gospel of John, we find the story of the Resurrection of Lazarus. Lazarus is sick and Jesus Christ waits until he dies to go to where he is buried and raise him. Jesus deliberately delays because the glory to the Christian God will be far greater and more will believe, if Lazarus is raised from the dead, rather than just healed from illness. Ultimately, and I do not speak for any religious figure or God here, anyone can get better from an illness but to be raised from the dead (currently) requires a miracle. Evidence, even in a book written for the faithful and to build faith, is important to humans.

We also know that there is a very large amount of knowledge that is accepted as being supported by evidence but the evidence is really anecdotal, based on bias and stereotype, and can even be distorted through repetition. This is the sea of confusion that we all live in. The scientific method (Popper) is one way that we can try to find firm ground to stand on but, if Kuhn is to be believed, there is the risk that one day we stand on the islands and realise that the truth was the sea all along. Even with Popper, we risk standing on solid ground that turns out to be meringue. How many of these changes can one human endure and still be malleable and welcoming in the face of further change?

Our problem with myth is when it forces us to reject something that we can demonstrate to be both valuable and scientifically valid because, right now, the world that we live in is constructed on scientific foundations and coherence is maintained by adding to those foundations. Personally, I don’t believe that myth and science have to be at odds (many disagree with me, including Richard Dawkins of course), and that this is an acceptable view as they are already co-existing in ways that actively shape society, for both good and ill.

Recently I made a comment on MOOCs that contradicted something someone said and I was (quite rightly) asked to provide evidence to support my assertions. That is the post before this one and what you will notice is that I do not have a great deal of what we would usually call evidence: no double-blind tests, no large-n trials with well-formed datasets. I had some early evidence of benefit, mostly qualitative and relatively soft, but, and this is important to me, what I didn’t have was evidence of harm. There are many myths around MOOCs and education in general. Some of them fall into the realm of harmful myths, those that cause people to reject good approaches to adhere to old and destructive practices. Some of them are harmful because they cause us to reject approaches that might work because we cannot find the evidence we need.

I am unsurprised that so many people adhere to folk pedagogy, given the vast amounts of information out there and the natural resistance to rejecting something that you think works, especially when someone sails in and tells you’ve been wrong for years. The fact that we are still discussing the nature of myth and science gives insight into how complicated this issue is.

I think that the path I’m on could most reasonably be called that of the mythographer, but the cataloguing of the edges of myth and the intersections of science is not in order to condemn one or the other but to find out what the truth is to the best of our knowledge. I think that understanding why people believe what they believe allows us to understand what they will need in order to believe something that is actually, well, true. There are many articles written on this, on the difficulty of replacing one piece of learning with another and the dangers of repetition in reinforcing previously-held beliefs, but there is hope in that we can construct new elements to replace old information if we are careful and we understand how people think.

We need to understand the delicate relationships between myth, folklore and science, our history as separate and joined peoples, if only to understand when we have achieved new forms of knowing. But we also need to be more upfront about when we believe we have moved on, including actively identifying areas that we have labelled as “in need of much more evidence” (such as learning styles, for example) to assist people in doing valuable work if they wish to pursue research.

I’ll go further. If we have areas where we cannot easily gain evidence, yet we have competing myths in that space, what should we do? How do we choose the best approach to achieve the most effective educational outcomes? I’ll let everyone argue in the comments for a while and then write that as the next piece.


Designing a MOOC: how far did it reach? #csed

Mark Guzdial posted over on his blog on “Moving Beyond MOOCS: Could we move to understanding learning and teaching?” and discusses aspects (that still linger) of MOOC hype. (I’ve spoken about MOOCs done badly before, as well as recording the thoughts of people like Hugh Davis from Southampton.) One of Mark’s paragraphs reads:

“The value of being in the front row of a class is that you talk with the teacher.  Getting physically closer to the lecturer doesn’t improve learning.  Engagement improves learning.  A MOOC puts everyone at the back of the class, listening only and doing the homework”

My reply to this was:

“You can probably guess that I have two responses here, the first is that the front row is not available to many in the real world in the first place, with the second being that, for far too many people, any seat in the classroom is better than none.

But I am involved in a, for us, large MOOC so my responses have to be regarded in that light. Thanks for the post!”

Mark, of course, called my bluff and responded with:

“Nick, I know that you know the literature in this space, and care about design and assessment. Can you say something about how you designed your MOOC to reach those who would not otherwise get access to formal educational opportunities? And since your MOOC has started, do you know yet if you achieved that goal — are you reaching people who would not otherwise get access?”

So here is that response. Thanks for the nudge, Mark! The answer is a bit long but please bear with me. We will be posting a longer summary after the course is completed, in a month or so. Consider this the unedited taster. I’m putting this here, early, prior to the detailed statistical work, so you can see where we are. All the numbers below are fresh off the system, to drive discussion and answering Mark’s question at, pretty much, a conceptual level.

First up, as some background for everyone, the MOOC team I’m working with is the University of Adelaide‘s Computer Science Education Research group, led by A/Prof Katrina Falkner, with me (Dr Nick Falkner), Dr Rebecca Vivian, and Dr Claudia Szabo.

I’ll start by noting that we’ve been working to solve the inherent scaling issues in the front of the classroom for some time. If I had a class of 12 then there’s no problem in engaging with everyone but I keep finding myself in rooms of 100+, which forces some people to sit away from me and also limits the number of meaningful interactions I can make to individuals in one setting. While I take Mark’s point about the front of the classroom, and the associated research is pretty solid on this, we encountered an inherent problem when we identified that students were better off down the front… and yet we kept teaching to rooms with more student than front. I’ll go out on a limb and say that this is actually a moral issue that we, as a sector, have had to look at and ignore in the face of constrained resources. The nature of large spaces and people, coupled with our inability to hover, means that we can either choose to have a row of students effectively in a semi-circle facing us, or we accept that after a relatively small number of students or number of rows, we have constructed a space that is inherently divided by privilege and will lead to disengagement.

So, Katrina’s and my first foray into this space was dealing with the problem in the physical lecture spaces that we had, with the 100+ classes that we had.

Katrina and I published a paper on “contributing student pedagogy” in Computer Science Education 22 (4), 2012, to identify ways for forming valued small collaboration groups as a way to promote engagement and drive skill development. Ultimately, by reducing the class to a smaller number of clusters and making those clusters pedagogically useful, I can then bring the ‘front of the class’-like experience to every group I speak to. We have given talks and applied sessions on this, including a special session at SIGCSE, because we think it’s a useful technique that reduces the amount of ‘front privilege’ while extending the amount of ‘front benefit’. (Read the paper for actual detail – I am skimping on summary here.)

We then got involved in the support of the national Digital Technologies curriculum for primary and middle school teachers across Australia, after being invited to produce a support MOOC (really a SPOC, small, private, on-line course) by Google. The target learners were teachers who were about to teach or who were teaching into, initially, Foundation to Year 6 and thus had degrees but potentially no experience in this area. (I’ve written about this before and you can find more detail on this here, where I also thanked my previous teachers!)

The motivation of this group of learners was different from a traditional MOOC because (a) everyone had both a degree and probable employment in the sector which reduced opportunistic registration to a large extent and (b) Australian teachers are required to have a certain number of professional development (PD) hours a year. Through a number of discussions across the key groups, we had our course recognised as PD and this meant that doing our course was considered to be valuable although almost all of the teachers we spoke to were furiously keen for this information anyway and my belief is that the PD was very much ‘icing’ rather than ‘cake’. (Thank you again to all of the teachers who have spent time taking our course – we really hope it’s been useful.)

To discuss access and reach, we can measure teachers who’ve taken the course (somewhere in the low thousands) and then estimate the number of students potentially assisted and that’s when it gets a little crazy, because that’s somewhere around 30-40,000.

In his talk at CSEDU 2014, Hugh Davis identified the student groups who get involved in MOOCs as follows. The majority of people undertaking MOOCs were life-long learners (older, degreed, M/F 50/50), people seeking skills via PD, and those with poor access to Higher Ed. There is also a small group who are Uni ‘tasters’ but very, very small. (I think we can agree that tasting a MOOC is not tasting a campus-based Uni experience. Less ivy, for starters.) The three approaches to the course once inside were auditing, completing and sampling, and it’s this final one that I want to emphasise because this brings us to one of the differences of MOOCs. We are not in control of when people decide that they are satisfied with the free education that they are accessing, unlike our strong gatekeeping on traditional courses.

I am in total agreement that a MOOC is not the same as a classroom but, also, that it is not the same as a traditional course, where we define how the student will achieve their goals and how they will know when they have completed. MOOCs function far more like many people’s experience of web browsing: they hunt for what they want and stop when they have it, thus the sampling engagement pattern above.

(As an aside, does this mean that a course that is perceived as ‘all back of class’ will rapidly be abandoned because it is distasteful? This makes the student-consumer a much more powerful player in their own educational market and is potentially worth remembering.)

Knowing these different approaches, we designed the individual subjects and overall program so that it was very much up to the participant how much they chose to take and individual modules were designed to be relatively self-contained, while fitting into a well-designed overall flow that built in terms of complexity and towards more abstract concepts. Thus, we supported auditing, completing and sampling, whereas our usual face-to-face (f2f) courses only support the first two in a way that we can measure.

As Hugh notes, and we agree through growing experience, marking/progress measures at scale are very difficult, especially when automated marking is not enough or not feasible. Based on our earlier work in contributing collaboration in the class room, for the F-6 Teacher MOOC we used a strong peer-assessment model where contributions and discussions were heavily linked. Because of the nature of the cohort, geographical and year-level groups formed who then conducted additional sessions and produced shared material at a slightly terrifying rate. We took the approach that we were not telling teachers how to teach but we were helping them to develop and share materials that would assist in their teaching. This reduced potential divisions and allows us to establish a mutually respectful relationship that facilitated openness.

(It’s worth noting that the courseware is creative commons, open and free. There are people reassembling the course for their specific take on the school system as we speak. We have a national curriculum but a state-focused approach to education, with public and many independent systems. Nobody makes any money out of providing this course to teachers and the material will always be free. Thank you again to Google for their ongoing support and funding!)

Overall, in this first F-6 MOOC, we had higher than usual retention of students and higher than usual participation, for the reasons I’ve outlined above. But this material was for curriculum support for teachers of young students, all of whom were pre-programming, and it could be contained in videos and on-line sharing of materials and discussion. We were also in the MOOC sweet-spot: existing degreed learners, PD driver, and their PD requirement depended on progressive demonstration on goal achievement, which we recognised post-course with a pre-approved certificate form. (Important note: if you are doing this, clear up how the PD requirements are met and how they need to be reported back, as early on as you can. It meant that we could give people something valuable in a short time.)

The programming MOOC, Think. Create. Code on EdX, was more challenging in many regards. We knew we were in a more difficult space and would be more in what I shall refer to as ‘the land of the average MOOC consumer’. No strong focus, no PD driver, no geographically guaranteed communities. We had to think carefully about what we considered to be useful interaction with the course material. What counted as success?

To start with, we took an image-based approach (I don’t think I need to provide supporting arguments for media-driven computing!) where students would produce images and, over time, refine their coding skills to produce and understand how to produce more complex images, building towards animation. People who have not had good access to education may not understand why we would use programming in more complex systems but our goal was to make images and that is a fairly universally understood idea, with a short production timeline and very clear indication of achievement: “Does it look like a face yet?”

In terms of useful interaction, if someone wrote a single program that drew a face, for the first time – then that’s valuable. If someone looked at someone else’s code and spotted a bug (however we wish to frame this), then that’s valuable. I think that someone writing a single line of correct code, where they understand everything that they write, is something that we can all consider to be valuable. Will it get you a degree? No. Will it be useful to you in later life? Well… maybe? (I would say ‘yes’ but that is a fervent hope rather than a fact.)

So our design brief was that it should be very easy to get into programming immediately, with an active and engaged approach, and that we have the same “mostly self-contained week” approach, with lots of good peer interaction and mutual evaluation to identify areas that needed work to allow us to build our knowledge together. (You know I may as well have ‘social constructivist’ tattooed on my head so this is strongly in keeping with my principles.) We wrote all of the materials from scratch, based on a 6-week program that we debated for some time. Materials consisted of short videos, additional material as short notes, participatory activities, quizzes and (we planned for) peer assessment (more on that later). You didn’t have to have been exposed to “the lecture” or even the advanced classroom to take the course. Any exposure to short videos or a web browser would be enough familiarity to go on with.

Our goal was to encourage as much engagement as possible, taking into account the fact that any number of students over 1,000 would be very hard to support individually, even with the 5-6 staff we had to help out. But we wanted students to be able to develop quickly, share quickly and, ultimately, comment back on each other’s work quickly. From a cognitive load perspective, it was crucial to keep the number of things that weren’t relevant to the task to a minimum, as we couldn’t assume any prior familiarity. This meant no installers, no linking, no loaders, no shenanigans. Write program, press play, get picture, share to gallery, winning.

As part of this, our support team (thanks, Jill!) developed a browser-based environment for Processing.js that integrated with a course gallery. Students could save their own work easily and share it trivially. Our early indications show that a lot of students jumped in and tried to do something straight away. (Processing is really good for getting something up, fast, as we know.) We spent a lot of time testing browsers, testing software, and writing code. All of the recorded materials used that development environment (this was important as Processing.js and Processing have some differences) and all of our videos show the environment in action. Again, as little extra cognitive load as possible – no implicit requirement for abstraction or skills transfer. (The AdelaideX team worked so hard to get us over the line – I think we may have eaten some of their brains to save those of our students. Thank you again to the University for selecting us and to Katy and the amazing team.)

The actual student group, about 20,000 people over 176 countries, did not have the “built-in” motivation of the previous group although they would all have their own levels of motivation. We used ‘meet and greet’ activities to drive some group formation (which worked to a degree) and we also had a very high level of staff monitoring of key question areas (which was noted by participants as being very high for EdX courses they’d taken), everyone putting in 30-60 minutes a day on rotation. But, as noted before, the biggest trick to getting everyone engaged at the large scale is to get everyone into groups where they have someone to talk to. This was supposed to be provided by a peer evaluation system that was initially part of the assessment package.

Sadly, the peer assessment system didn’t work as we wanted it to and we were worried that it would form a disincentive, rather than a supporting community, so we switched to a forum-based discussion of the works on the EdX discussion forum. At this point, a lack of integration between our own UoA programming system and gallery and the EdX discussion system allowed too much distance – the close binding we had in the R-6 MOOC wasn’t there. We’re still working on this because everything we know and all evidence we’ve collected before tells us that this is a vital part of the puzzle.

In terms of visible output, the amount of novel and amazing art work that has been generated has blown us all away. The degree of difference is huge: armed with approximately 5 statements, the number of different pieces you can produce is surprisingly large. Add in control statements and reputation? BOOM. Every student can write something that speaks to her or him and show it to other people, encouraging creativity and facilitating engagement.

From the stats side, I don’t have access to the raw stats, so it’s hard for me to give you a statistically sound answer as to who we have or have not reached. This is one of the things with working with a pre-existing platform and, yes, it bugs me a little because I can’t plot this against that unless someone has built it into the platform. But I think I can tell you some things.

I can tell you that roughly 2,000 students attempted quiz problems in the first week of the course and that over 4,000 watched a video in the first week – no real surprises, registrations are an indicator of interest, not a commitment. During that time, 7,000 students were active in the course in some way – including just writing code, discussing it and having fun in the gallery environment. (As it happens, we appear to be plateauing at about 3,000 active students but time will tell. We have a lot of post-course analysis to do.)

It’s a mistake to focus on the “drop” rates because the MOOC model is different. We have no idea if the people who left got what they wanted or not, or why they didn’t do anything. We may never know but we’ll dig into that later.

I can also tell you that only 57% of the students currently enrolled have declared themselves explicitly to be male and that is the most likely indicator that we are reaching students who might not usually be in a programming course, because that 43% of others, of whom 33% have self-identified as women, is far higher than we ever see in classes locally. If you want evidence of reach then it begins here, as part of the provision of an environment that is, apparently, more welcoming to ‘non-men’.

We have had a number of student comments that reflect positive reach and, while these are not statistically significant, I think that this also gives you support for the idea of additional reach. Students have been asking how they can save their code beyond the course and this is a good indicator: ownership and a desire to preserve something valuable.

For student comments, however, this is my favourite.

I’m no artist. I’m no computer programmer. But with this class, I see I can be both. #processingjs (Link to student’s work) #code101x .

That’s someone for whom this course had them in the right place in the classroom. After all of this is done, we’ll go looking to see how many more we can find.

I know this is long but I hope it answered your questions. We’re looking forward to doing a detailed write-up of everything after the course closes and we can look at everything.


EduTech AU 2015, Day 2, Higher Ed Leaders, “Change and innovation in the Digital Age: the future is social, mobile and personalised.” #edutechau @timbuckteeth

And heeere’s Steve Wheeler (@timbuckteeth)! Steve is an A/Prof of Learning Technologies at Plymouth in the UK. He and I have been at the same event before (CSEDU, Barcelona) and we seem to agree on a lot. Today’s cognitive bias warning is that I will probably agree with Steve a lot, again. I’ve already quizzed him on his talk because it looked like he was about to try and, as I understand it, what he wants to talk about is how our students can have altered expectations without necessarily becoming some sort of different species. (There are no Digital Natives. No, Prensky was wrong. Check out Helsper, 2010, from the LSE.) So, on to the talk and enough of my nonsense!

Steve claims he’s going to recap the previous speaker, but in an English accent. Ah, the Mayflower steps on the quayside in Plymouth, except that they’re not, because the real Mayflower steps are in a ladies’ loo in a pub, 100m back from the quay. The moral? What you expect to be getting is not always what you get. (Tourists think they have the real thing, locals know the truth.)

“Any sufficiently advanced technology is indistinguishable from magic” – Arthur C. Clarke.

Educational institutions are riddled with bad technology purchases where we buy something, don’t understand it, don’t support it and yet we’re stuck with it or, worse, try to teach with it when it doesn’t work.

Predicting the future is hard but, for educators, we can do it better if we look at:

  • Pedagogy first
  • Technology next (that fits the technology)

Steve then plugs his own book with a quote on technology not being a silver bullet.

But who will be our students? What are their expectations for the future? Common answers include: collaboration (student and staff), and more making and doing. They don’t like being talked at. Students today do not have a clear memory of the previous century, their expectations are based on the world that they are living in now, not the world that we grew up in.

Meet Student 2.0!

The average digital birth of children happens at about six months – but they can be on the Internet before they are born, via ultrasound photos. (Anyone who has tried to swipe or pinch-zoom a magazine knows why kids take to it so easily.) Students of today have tools and technology and this is what allows them to create, mash up, and reinvent materials.

What about Game Based Learning? What do children learn from playing games

Three biggest fears of teachers using technology

  • How do I make this work?
  • How do I avoid looking like an idiot?
  • They will know more about it than I do.

Three biggest fears of students

  • Bad wifi
  • Spinning wheel of death
  • Low battery

The laptops and devices you see in lectures are personal windows on the world, ongoing conversations and learning activities – it’s not purely inattention or anti-learning. Student questions on Twitter can be answered by people all around the world and that’s extending the learning dialogue out a long way beyond the classroom.

One of these is Voltaire, one is Steve Wheeler.

One of these is Voltaire, one is Steve Wheeler.

Voltaire said that we were products of our age. Walrick asks how we can prepare students for a future? Steve showed us a picture of him as a young boy, who had been turned off asking questions by a mocking teacher. But the last two years of his schooling were in Holland he went to the Philips flying saucer, which was a technology museum. There, he saw an early video conferencing system and that inspired him with a vision of the future.

Steve wanted to be an astronaut but his career advisor suggested he aim lower, because he wasn’t an American. The point is not that Steve wanted to be an astronaut but that he wanted to be an explorer, the role that he occupies now in education.

Steve shared a quote that education is “about teaching students not subjects” and he shared the awesome picture of ‘named quadrilaterals’. My favourite is ‘Bob. We have a very definite idea of what we want students to write as answer but we suppress creative answers and we don’t necessarily drive the approach to learning that we want.

Ignorance spreads happily by itself, we shouldn’t be helping it. Our visions of the future are too often our memories of what our time was, transferred into modern systems. Our solution spaces are restricted by our fixations on a specific way of thinking. This prevents us from breaking out of our current mindset and doing something useful.

What will the future be? It was multi-media, it was web, but where is it going? Mobile devices because the most likely web browser platform in 2013 and their share is growing.

What will our new technologies be? Thinks get smaller, faster, lighter as they mature. We have to think about solving problems in new ways.

Here’s a fire hose sip of technologies: artificial intelligence is on the way up, touch surfaces are getting better, wearables are getting smarter, we’re looking at remote presence, immersive environments, 3D printers are changing manufacturing and teaching, gestural computing, mind control of devices, actual physical implants into the body…

From Nova Spivak, we can plot information connectivity against social connectivity and we want is growth on both axes – a giant arrow point up to the top right. We don’t yet have a Web form that connects information, knowledge and people – i.e. linking intelligence and people. We’re already seeing some of this with recommenders, intelligent filtering, and sentiment tracking. (I’m still waiting for the Semantic Web to deliver, I started doing work on it in my PhD, mumble years ago.)

A possible topology is: infrastructure is distributed and virtualised, our interfaces are 3D and interactive, built onto mobile technology and using ‘intelligent’ systems underneath.

But you cannot assume that your students are all at the same level or have all of the same devices: the digital divide is as real and as damaging as any social divide. Steve alluded to the Personal Learning Networking, which you can read about in my previous blog on him.

How will teaching change? It has to move away from cutting down students into cloned templates. We want students to be self-directed, self-starting, equipped to capture information, collaborative, and oriented towards producing their own things.

Let’s get back to our roots:

  1. We learn by doing (Piaget, 1950)
  2. We learn by making (Papert, 1960)

Just because technology is making some of this doing and making easier doesn’t mean we’re making it worthless, it means that we have time to do other things. Flip the roles, not just the classroom. Let students’ be the teacher – we do learn by teaching. (Couldn’t agree more.)

Back to Papert, “The best learning takes place when students take control.” Students can reflect in blogging as they present their information a hidden audience that they are actually writing for. These physical and virtual networks grow, building their personal learning networks as they connect to more people who are connected to more people. (Steve’s a huge fan of Twitter. I’m not quite as connected as he is but that’s like saying this puddle is smaller than the North Sea.)

Some of our students are strongly connected and they do store their knowledge in groups and friendships, which really reflects how they find things out. This rolls into digital cultural capital and who our groups are.

(Then there was a steam of images at too high a speed for me to capture – go and download the slides, they’re creative commons and a lot of fun.)

Learners will need new competencies and literacies.

Always nice to hear Steve speak and, of course, I still agree with a lot of what he said. I won’t prod him for questions, though.


EduTech AU 2015, Day 2, Higher Ed Leaders, “Assessment: The Silent Killer of Learning”, #edutechau @eric_mazur

No surprise that I’m very excited about this talk as well. Eric is a world renowned educator and physicist, having developed Peer Instruction in 1990 for his classes at Harvard as a way to deal with students not developing a working physicist’s approach to the content of his course. I should note that Eric also gave this talk yesterday and the inimitable Steve Wheeler blogged that one, so you should read Steve as well. But after me. (Sorry, Steve.)

I’m not an enormous fan of most of the assessment we use as most grades are meaningless, assessment becomes part of a carrot-and-stick approach and it’s all based on artificial timelines that stifle creativity. (But apart from that, it’s fine. Ho ho.) My pithy statement on this is that if you build an adversarial educational system, you’ll get adversaries, but if you bother to build a learning environment, you’ll get learning. One of the natural outcomes of an adversarial system is activities like cheating and gaming the system, because people start to treat beating the system as the goal itself, which is highly undesirable. You can read a lot more about my views on plagiarism here, if you like. (Warning: that post links to several others and is a bit of a wormhole.)

Now, let’s hear what Eric has to say on this! (My comments from this point on will attempt to contain themselves in parentheses. You can find the slides for his talk – all 62MB of them – from this link on his website. ) It’s important to remember that one of the reasons that Eric’s work is so interesting is that he is looking for evidence-based approaches to education.

Eric discussed the use of flashcards. A week after Flashcard study, students retain 35%. After two weeks, it’s almost gone. He tried to communicate this to someone who was launching a cloud-based flashcard app. Her response was “we only guarantee they’ll pass the test”.

*low, despairing chuckle from the audience*

Of course most students study to pass the test, not to learn, and they are not the same thing. For years, Eric has been bashing the lecture (yes, he noted the irony) but now he wants to focus on changing assessment and getting it away from rote learning and regurgitation. The assessment practices we use now are not 21st century focused, they are used for ranking and classifying but, even then, doing it badly.

So why are we assessing? What are the problems that are rampant in our assessment procedure? What are the improvements we can make?

How many different purposes of assessment can you think of? Eric gave us 90s to come up with a list. Katrina and I came up with about 10, most of which were serious, but it was an interesting question to reflect upon. (Eric snuck

  1. Rate and rank students
  2. Rate professor and course
  3. Motivate students to keep up with work
  4. Provide feedback on learning to students
  5. Provide feedback to instructor
  6. Provide instructional accountability
  7. Improve the teaching and learning.

Ah, but look at the verbs – they are multi-purpose and in conflict. How can one thing do so much?

So what are the problems? Many tests are fundamentally inauthentic – regurgitation in useless and inappropriate ways. Many problem-solving approaches are inauthentic as well (a big problem for computing, we keep writing “Hello, World”). What does a real problem look like? It’s an interruption in our pathway to our desired outcome – it’s not the outcome that’s important, it’s the pathway and the solution to reach it that are important. Typical student problem? Open the book to chapter X to apply known procedure Y to determine an unknown answer.

Shout out to Bloom’s! Here’s Eric’s slide to remind you.

Rights reside with Eric Mazur.

Rights reside with Eric Mazur.

Eric doesn’t think that many of us, including Harvard, even reach the Applying stage. He referred to a colleague in physics who used baseball problems throughout the course in assignments, until he reached the final exam where he ran out of baseball problems and used football problems. “Professor! We’ve never done football problems!” Eric noted that, while the audience were laughing, we should really be crying. If we can’t apply what we’ve learned then we haven’t actually learned i.

Eric sneakily put more audience participation into the talk with an open ended question that appeared to not have enough information to come up with a solution, as it required assumptions and modelling. From a Bloom’s perspective, this is right up the top.

Students loathe assumptions? Why? Mostly because we’ll give them bad marks if they get it wrong. But isn’t the ability to make assumptions a really important skill? Isn’t this fundamental to success?

Eric demonstrated how to tame the problem by adding in more constraints but this came at the cost of the creating stage of Bloom’s and then the evaluating and analysing(Check out his slides, pages 31 to 40, for details of this.) If you add in the memorisation of the equation, we have taken all of the guts out of the problem, dropping down to the lowest level of Bloom’s.

But, of course, computers can do most of the hard work for that is mechanistic. Problems at the bottom layer of Bloom’s are going to be solved by machines – this is not something we should train 21st Century students for.

But… real problem solving is erratic. Riddled with fuzziness. Failure prone. Not guaranteed to succeed. Most definitely not guaranteed to be optimal. The road to success is littered with failures.

But, if you make mistakes, you lose marks. But if you’re not making mistakes, you’re very unlikely to be creative and innovative and this is the problem with our assessment practices.

Eric showed us a stress of a traditional exam room: stressful, isolated, deprived of calculators and devices. Eric’s joke was that we are going to have to take exams naked to ensure we’re not wearing smart devices. We are in a time and place where we can look up whatever we want, whenever we want. But it’s how you use that information that makes a difference. Why are we testing and assessing students under such a set of conditions? Why do we imagine that the result we get here is going to be any indicator at all of the likely future success of the student with that knowledge?

Cramming for exams? Great, we store the information in short-term memory. A few days later, it’s all gone.

Assessment produces a conflict, which Eric noticed when he started teaching a team and project based course. He was coaching for most of the course, switching to a judging role for the monthly fair. He found it difficult to judge them because he had a coach/judge conflict. Why do we combine it in education when it would be unfair or unpleasant in every other area of human endeavour? We hide between the veil of objectivity and fairness. It’s not a matter of feelings.

But… we go back to Bloom’s. The only thinking skill that can be evaluated truly objectively is remembering, at the bottom again.

But let’s talk about grade inflation and cheating. Why do people cheat at education when they don’t generally cheat at learning? But educational systems often conspire to rob us of our ownership and love of learning. Our systems set up situations where students cheat in order to succeed.

  • Mimic real life in assessment practices!

Open-book exams. Information sticks when you need it and use it a lot. So use it. Produce problems that need it. Eric’s thought is you can bring anything you want except for another living person. But what about assessment on laptops? Oh no, Google access! But is that actually a problem? Any question to which the answer can be Googled is not an authentic question to determine learning!

Eric showed a video of excited students doing a statistic tests as a team-based learning activity. After an initial pass at the test, the individual response is collected (for up to 50% of the grade), and then students work as a group to confirm the questions against an IF AT scratchy card for the rest of the marks. Discussion, conversation, and the students do their own grading for you. They’ve also had the “A-ha!” moment. Assessment becomes a learning opportunity.

Eric’s not a fan of multiple choice so his Learning Catalytics software allows similar comparison of group answers without having to use multiple choice. Again, the team based activities are social, interactive and must less stressful.

  • Focus on feedback, not ranking.

Objective ranking is a myth. The amount of, and success with, advanced education is no indicator of overall success in many regards. So why do we rank? Eric showed some graphs of his students (in earlier courses) plotting final grades in physics against the conceptual understanding of force. Some people still got top grades without understanding force as it was redefined by Newton. (For those who don’t know, Aristotle was wrong on this one.) Worse still is the student who mastered the concept of force and got a C, when a student who didn’t master force got an A. Objectivity? Injustice?

  • Focus on skills, not content

Eric referred to Wiggins and McTighe, “Understanding by Design.”  Traditional approach is course content drives assessment design. Wiggins advocates identifying what the outcomes are, formulate these as action verbs, ‘doing’ x rather than ‘understanding’ x. You use this to identify what you think the acceptable evidence is for these outcomes and then you develop the instructional approach. This is totally outcomes based.

  • resolve coach/judge conflict

In his project-based course, Eric brought in external evaluators, leaving his coach role unsullied. This also validates Eric’s approach in the eyes of his colleagues. Peer- and self-evaluation are also crucial here. Reflective time to work out how you are going is easier if you can see other people’s work (even anonymously). Calibrated peer review, cpr.molsci.ucla.edu, is another approach but Eric ran out of time on this one.

If we don’t rethink assessment, the result of our assessment procedures will never actually provide vital information to the learner or us as to who might or might not be successful.

I really enjoyed this talk. I agree with just about all of this. It’s always good when an ‘internationally respected educator’ says it as then I can quote him and get traction in change-driving arguments back home. Thanks for a great talk!

 


EduTech AU 2015, Day 2, Higher Ed Leaders, “Innovation + Technology = great change to higher education”, #edutechau

Big session today. We’re starting with Nicholas Negroponte, founder of the MIT Media Lab and the founder of One Laptop Per Child (OLPC), an initiative to create/provide affordable educational devices for children in the developing world. (Nicholas is coming to us via video conference, hooray, 21st Century, so this may or not work well in translation to blogging. Please bear with me if it’s a little disjointed.)

Nicholas would rather be here but he’s bravely working through his first presentation of this type! It’s going to be a presentation with some radical ideas so he’s hoping for conversation and debate. The presentation is broken into five parts:

  1. Learning learning. (Teaching and learning as separate entities.)
  2. What normal market forces will not do. (No real surprise that standard market forces won’t work well here.)
  3. Education without curricula. (Learning comes from many places and situations. Understanding and establishing credibility.)
  4. Where do new ideas come from? (How do we get them, how do we not get in the way.)
  5. Connectivity as a human right. (Is connectivity a human right or a means to rights such as education and healthcare? Human rights are free so that raises a lot of issues.

Nicholas then drilled down in “Learning learning”, starting with a reference to Seymour Papert, and Nicholas reflected on the sadness of the serious accident of Seymour’s health from a personal perspective. Nicholas referred to Papert’s and Minsky’s work on trying to understand how children and machines learned respectively. In 1968, Seymour started thinking about it and on April, 9, 1970, he gave a talk on his thoughts. Seymour realised that thinking about programs gave insight into thinking, relating to the deconstruction and stepwise solution building (algorithmic thinking) that novice programmers, such as children, had to go through.

These points were up on the screen as Nicholas spoke:

  1. Construction versus instruction
  2. Why reinventing the wheel is good
  3. Coding as thinking about thinking

How do we write code? Write it, see if it works, see which behaviours we have that aren’t considered working, change the code (in an informed way, with any luck) and try again. (It’s a little more complicated than that but that’s the core.) We’re now into the area of transferable skills – it appeared that children writing computer programs learned a skill that transferred over into their ability to spell, potentially from the methodical application of debugging techniques.

Nicholas talked about a spelling bee system where you would focus on the 8 out of 10 you got right and ignore the 2 you didn’t get. The ‘debugging’ kids would talk about the ones that they didn’t get right because they were analsysing their mistakes, as a peer group and as individual reflection.

Nicholas then moved on to the failure of market forces. Why does Finland do so well when they don’t have tests, homework and the shortest number of school hours per day and school days per year. One reason? No competition between children. No movement of core resources into the private sector (education as poorly functioning profit machine). Nicholas identified the core difference between the mission and the market, which beautifully summarises my thinking.

The OLPC program started in Cambodia for a variety of reasons, including someone associated with the lab being a friend of the King. OLPC laptops could go into areas where the government wasn’t providing schools for safety reasons, as it needed minesweepers and the like. Nicholas’ son came to Cambodia from Italy to connect up the school to the Internet. What would the normal market not do? Telecoms would come and get cheaper. Power would come and get cheaper. Laptops? Hmm. The software companies were pushing the hardware companies, so they were both caught in a spiral of increasing power consumption for utility. Where was the point where we could build a simple laptop, as a mission of learning, that could have a smaller energy footprint and bring laptops and connectivity to billions of people.

This is one of the reasons why OLPC is a non-profit – you don’t have to sell laptops to support the system, you’re supporting a mission. You didn’t need to sell or push to justify staying in a market, as the production volume was already at a good price. Why did this work well? You can make partnerships that weren’t possible otherwise. It derails the “ah, you need food and shelter first” argument because you can change the “why do we need a laptop” argument to “why do we need education?” at which point education leads to increased societal conditions. Why laptops? Tablets are more consumer-focused than construction-focused. (Certainly true of how I use my tech.)

(When we launched the first of the Digital Technologies MOOCs, the deal we agreed upon with Google was that it wasn’t a profit-making venture at all. It never will be. Neither we nor Google make money from the support of teachers across Australia so we can have all of the same advantages as they mention above: open partnerships, no profit motive, working for the common good as a mission of learning and collegial respect. Highly recommended approach, if someone is paying you enough to make your rent and eat. The secret truth of academia is that they give you money to keep you housed, clothed and fed while you think. )

Nicholas told a story of kids changing from being scared or bored of school to using an approach that brings kids flocking in. A great measure of success.

Now, onto Education without curricula, starting by talking public versus private. This is a sensitive subject for many people. The biggest problem for public education in many cases is the private educational system, dragging out caring educators to a closed system. Remember Finland? There are no public schools and their educational system is astoundingly good. Nicholas’ points were:

  1. Public versus private
  2. Age segregation
  3. Stop testing. (Yay!)

The public sector is losing the imperative of the civic responsibility for education. Nicholas thinks it doesn’t make sense that we still segregate by ages as a hard limit. He thinks we should get away from breaking it into age groups, as it doesn’t clearly reflect where students are at.

Oh, testing. Nicholas correctly labelled the parental complicity in the production of the testing pressure cooker. “You have to get good grades if you’re going to Princeton!” The testing mania is dominating institutions and we do a lot of testing to measure and rank children, rather than determining competency. Oh, so much here. Testing leads to destructive behaviour.

So where do new ideas come from? (A more positive note.) Nicholas is interested in Higher Ed as sources of new ideas. Why does HE exist, especially if we can do things remotely or off campus? What is the role of the Uni in the future? Ha! Apparently, when Nicholas started the MIT media lab, he was accused of starting a sissy lab with artists and soft science… oh dear, that’s about as wrong as someone can get. His use of creatives was seen as soft when, of course, using creative users addressed two issues to drive new ideas: a creative approach to thinking and consulting with the people who used the technology. Who really invented photography? Photographers. Three points from this section.

  1. Children: our most precious natural resource
  2. Incrementalism is the enemy of creativity
  3. Brain drain

On the brain drain, we lose many, many students to other places. Uni are a place to solve huge problems rather than small, profit-oriented problems. The entrepreneurial focus leads to small problem solution, which is sucking a lot of big thinking out of the system. The app model is leading to a human resource deficit because the start-up phenomenon is ripping away some of our best problem solvers.

Finally, to connectivity as a human right. This is something that Nicholas is very, very passionate about. Not content. Not laptops. Being connected.  Learning, education, and access to these, from early in life to the end of life – connectivity is the end of isolation. Isolation comes in many forms and can be physical, geographical and social. Here are Nicholas’ points:

  1. The end of isolation.
  2. Nationalism is a disease (oh, so much yes.) Nations are the wrong taxonomy for the world.
  3. Fried eggs and omelettes.

Fried eggs and omelettes? In general, the world had crisp boundaries, yolk versus white. At work/at home. At school/not at school. We are moving to a more blended, less dichotomous approach because we are mixing our lives together. This is both bad (you’re getting work in my homelife) and good (I’m getting learning in my day).

Can we drop kids into a reading environment and hope that they’ll learn to read? Reading is only 3,500 years old, versus our language skills, so it has to be learned. But do we have to do it the way that we did it? Hmm. Interesting questions. This is where the tablets were dropped into illiterate villages without any support. (Does this require a seed autodidact in the group? There’s a lot to unpack it.) Nicholas says he made a huge mistake in naming the village in Ethiopia which has corrupted the experiment but at least the kids are getting to give press conferences!

Another massive amount of interesting information – sadly, no question time!