Yes, and…

A great deal of what I understand about learning I know because I practised improvisation for many years and with a great deal of personal commitment. One of the principles of improvisation is to accept whatever is happening and build on it. That principle is often explained in theatrical/dramatic improvisation as the ‘Yes, and’ principle. Applying this principle in practice means that when creating a scene, if an actor makes a statement, a gesture, an expression- does anything really (the generic term used is to ‘make an offer’), other actors in the scene agree with that offer and then express something else which in some way references the offer. This principle can be applied in teaching (not easily!) and some teachers are actively promoting this.  

What makes using  ‘Yes, and’ difficult in teaching is firstly that the learners need to be prepared to use it just as much (if not more so) than teachers. The other big obstacle is the extent to which various subjects are based around the idea of correct and incorrect statements. Mathematics is probably the most polarising subject in terms of correct vs incorrect. If ‘Yes, and’ can work in mathematics it can work in anything. So, how can that polarisation be circumvented in mathematics teaching?

To sincerely attempt to apply ‘Yes, and’ in mathematics, a teacher would have to be prepared to accept the challenging of the most axiomatic aspects of the mathematical content that they were trying to teach. For example-

Learner: Does 5 + 1 = 7?

Teacher (For who saying ‘No’ is not option) : It can do, yes- and 5 + 2 can equal 7 as well. Why do you think most people choose that 5 + 2 = 7 instead 5 + 1 = 7? 

Learner (Being deliberately awkward): I don’t accept that 5 + 2 = 7, only 5 + 1 = 7.

Teacher: Yes, and you can define numbers to mean whatever you want them to mean. Everyone who has done mathematics so far uses meanings that make different mathematical statements consistent with each other.

Learner (Seeing how far they can push being awkward- maybe even thinking about it):  5 + 2 = 7 is consistent with 5 + 1 = 7  

Teacher: Yes, and it could be, depending on what ‘=’ means. Can you explain what ‘=’ means?

Two obvious difficulties with this are that some learners are likely to decide to use up a lot of teacher time on this sort of dialogue as a proxy for some kind of status jostling with teachers (and/or with each other), and that while ‘Yes, and’ may be suitable for discussing learning content it may not be suitable for managing conduct. If a learner asks if they are allowed to hit another learner and if a teacher says ‘Yes, and there will be disciplinary consequences’, then the learner may just respond impulsively to the ‘Yes’, and hit someone and say that the teacher said that they could; there is no neat and practical way to completely separate discussion of conduct from discussion of learning content. What this implies is that the learning of one thing is at a deep level inseparable from the learning many other things (which is one of the main insights that I gained from practising improvisation).

‘Yes, and’ based teaching appears to have numerous underlying similarities to Socratic teaching, which I discussed in this post and in doing so alluded to the idea of a Socratic chatbot (which would address the time-wasting and conduct management issues associated with human teaching). Unfortunately, some sort of ‘Yes, and’ chatbot would presumably be incredibly difficult to program. It might well be fun to try and program it though. Seeing a team of machine learning experts attempt to make some algorithms  based on observations of improvisation groups in action could be bizarrely joyful.


Riser run wiser

After decades of bludgeoning British schools for not meeting various standards, OFSTED (the schools inspectorate) has rather suddenly changed tack; The new chief inspector of OFSTED (Amanda Spielman) is now seriously unhappy that schools are preoccupied with teaching to the test. Spielman is concerned about schools that are gaming the system (the very same system that OFSTED has done so much to help maintain) and about the lack of a broad curriculum in schools (see this article). 

This change of heart by OFSTED is epically belated and it shows a staggering insensitivity in its failure to acknowledge that what OFSTED is saying now is an echoing of what the voice of the teaching profession has been saying for decades (speaking out against the tone of the inspectorate throughout that time). What ought to have been an apology to educators by OFSTED has been expressed as a fresh criticism of them. 

The inspectorate’s admission of failure is to be welcomed regardless of its dismally poor handling however. The important question is how educational institutions can now best address the recognised atrophy of broad based curriculum and erosion of defining purposes beyond the merely bureaucratic. Readers of this blog will likely know that I have a generally skeptical outlook on educational institutions and might not expect me to muster much enthusiasm for their potential renewal. In all fairness, what I have written in this blog is critical not of educational institutions across the board but specifically of educational institutions that are designed to operate along lines that are significantly based on Taylorist ‘scientific’ management principles (which the great majority of educational institutions unfortunately are).  

If there is a way to breath life back into educational institutions as they predominantly exist currently (rather than as the decentralised, spontaneously self-ordering, scale-free, complex networks that EdTech can potentially transform them into) then I am inclined to believe that the way that this could be done would be if the curriculum of such institutions took to its heart the study and practice of philosophy.

Why philosophy?

For a start, it appears to be effective. A study conducted by Durham University found that (as reported by The Independent)-

Teaching philosophy to primary school children can improve their English and maths skills, according to a pilot study highlighting the value of training pupils to have inquiring minds.

Children from deprived backgrounds benefited the most from philosophical debates about topics such as truth, fairness and knowledge, researchers from Durham University found.

The 3,159 primary school pupils from 48 schools who took part in the trial saw their maths and reading scores improve by an average of two months. But the benefits were even more pronounced for pupils from disadvantaged backgrounds, whose reading skills improved by four months, their maths results by three months and their writing ability by two months.

The Durham study was one of a number of international studies showing similar results. The costs associated with introducing a few hours a week of philosophy teaching are pretty low by the standards of educational interventions in general. Good philosophy teachers are probably not going to be easy to come by in large numbers any time soon though so this approach would not be as easy to rapidly scale as technology based interventions, unless… It occurred to me a while ago (and not only to me, although to few others it would seem) that there was a particular nugget of philosophical practice which seemed to overlap rather neatly with a current EdTech trend.

Imagine the philosopher Socrates as a chatbot. Someone already has (and I am not referring to the ‘Socrative’ app). The Socratic method of teaching can be (very) simplistically explained as teaching which offers no instructions to learners other than that they attempt to supply an answer to an initial question and thereafter for each answer that a learner supplies they must additionally answer the question ‘How do you know that (answer) is true?’ 

Obviously there is more to the Socratic method than that. What I have stated above is merely how a software developer might sketch out the basic idea of how to start making a chatbot designed to emulate Socrates. A human teacher using the Socratic method to instruct learners would have in mind certain conclusions that they would hope that learners might arrive at (although they would not acknowledge this to their learners) and would embellish their responses to learners’ answers beyond ‘How do you know that (answer) is true?’ so as to more effectively guide learners towards approaching those conclusions. A simple Socratic chatbot that knew no more than its learners did about what conclusions to reach (much less probably- which might though be useful in helping it to avoid false positive conclusions) would be much less likely to direct its learners to discovering anything significantly true than it would be towards directing them to discover their own fixations. This can be understood visually.


A learner’s fixation corresponds to some local optimum in a conceptual landscape of understanding where the higher up one is the more one understands. The peak of a local optimum is a point from which it is not possible to rise any higher without first descending some distance in order to move closer to a bigger optimum (or even the biggest optimum- the global). Someone trying to at all times increase their understanding would be trapped on a local optimum as to move away from it they would have to decrease their understanding. A human Socratic teacher understands what makes the global optimum different from local optima and so steers learners away from local optima that block progress towards the global optimum. A simple Socratic chatbot that just asks ‘How do you know?’ is not equipped to steer learners away from local optima other than by the brute force approach of repeating ‘How do you know?’ until a learner becomes frustrated enough to admit ‘I don’t know!’- assuming that such frustration has not long since disengaged the learner entirely. 

An appealing feature of the conceptual landscape of understanding model of learning is that recognises the importance of paths taken rather than just points occupied. Understanding something need not mean occupying a particular point in the understanding landscape so much as recognising the influence of that point on other points around it. Such a point might in fact be a local (even a global) minimum rather than a maximum of understanding. This puts me in mind of strange attractors in the phase diagrams of chaotic systems in which the phase space path of a system irregularly orbits a point which represents a state that the system never actually visits.


Such are the places that thinking on philosophy (and mathematics) can take us. In my opinion it is in a large part this sense of mental freedom engendered by philosophy that schools ought to be incorporating in their new broad based curricula. Mental freedom is not the entire basis of curriculum of course. Mental freedom which remains entirely mental remains basically inconsequential. Curriculum needs to engage with the issues around how mental freedom can be maintained in a social context where actions have consequences that place restrictions on free actions. Social and political and ethical philosophy are as key to curricula as the parts of philosophy more concerned with the worlds that a mind partaking of an isolated freedom can explore. Philosophy does not necessarily have a great track record in this department.

Postmodern philosophy is loved by some and hated by others. I see both good and bad things in it. Conveniently, the conceptual landscape of understanding model of learning can illustrate this. 


Defining optima depends on the existence of an agreed definition of a flat grid representing some baseline of understanding. For much of its history, philosophy can be thought of as representing a set of discussions about the characteristics and qualities of the features of a landscape and speculations about what features might exist that had not been observed (perhaps because they were too small, changed too quickly, or were too distant). The onset of postmodern philosophy represents the beginning of discussions about the assumptions made regarding the definition of a flat grid which was necessary to make all other discussions possible. Postmodern philosophical arguments led to situations whereby any point in the landscape could be defined as the global optimum just by redefining what a flat grid is. While these arguments were very clever and indicative of a great deal of mental freedom, accepting these arguments fatally undermines the motivation for actually leaving any particular occupied point and exploring the landscape around it. Any point in the landscape can be at any height if ‘height’ can be redefined arbitrarily. Why go looking for greater heights? Why learn when anything can be correct just by appropriately defining it so (perhaps by critically analyzing the perspective of the teacher who argues that learners are supposed to supply correct answers)? 

I have admittedly rather heavily ‘put the boot in’ to postmodern philosophy here. I do acknowledge that there are good aspects of it despite the problems I’ve described but I really don’t think that it can form a very good basis for a broader curriculum for learners other than those who have already been fairly extensively educated. Postmodernism is very much a critical-analytical set of (loose) methods that can be useful in overturning limiting assumptions that have somehow or other remained under-scrutinized. This is something like an antidote to false knowledge rather than a means of approaching true knowledge. Those who have not yet gone very far on their life’s learning path are more in need of what might inspire them to continued exploration than what could make them question what the point of exploring is at all.   


Today I watched a news story about the XPRIZE. The XPRIZE website explains what XPRIZE does in clear and simple terms.


The Global Learning XPRIZE challenges teams from around the world to develop open source and scalable software that will enable children in developing countries to teach themselves basic reading, writing and arithmetic within 15 months. Once the 15-month field-testing phase concludes, the prize purse will be objectively awarded to the team that generates the best international standardized test scores within the group of participating children. Our goal is an empowered generation that will positively impact their communities, countries and the world.

Teams will compete in a multi-stage competition that test for specific criteria:

Ability to measurably increase the learning of children, with limited access to schooling, within the 15-month field-testing period.

Creation of a design that is easy to use and engaging for children, so they can operate it alone and/or in self-organized groups.

Creation of open source software that makes marked improvements to existing technology.


Many excellent ideas there- empowered learners, independent and self-organised groups of learners, and open source software (shame about the standardised testing part).

A similarly inspiring project is the One Laptop per Child project, which states that-

We aim to provide each child with a rugged, low-cost, low-power, connected laptop. To this end, we have designed hardware, content and software for collaborative, joyful, and self-empowered learning. With access to this type of tool, children are engaged in their own education, and learn, share, and create together. They become connected to each other, to the world and to a brighter future.

These projects have been devised specifically for developing world socioeconomic conditions. The learning that these projects intend to deliver are extensively mobile learning based in order to compensate for a lack of physical school infrastructure. These projects are designed to operate without teachers for the same reason.

Readers of this blog will probably not be surprised that I consider the design aspects of these projects that attempt to dispense with the necessity for schools and teachers not merely to be make-do substitutions for school and teacher oriented education but potentially as features that could make these projects a model for a more effective form of education than a school and teacher oriented model could provide. I noticed that the XPRIZE story was mentioned in Hack Education Weekly News, where it was described as an example “ed tech imperialism”. If XPRIZE and the like are examples of imperialism then it seems to me that they are no more so imperialist than if schools were built instead. Such schools would no doubt be run along the lines of twentieth century educational institutional traditions. The end of this post discusses the idea that the growth of m-learning in the developing world could give rise to a kind of post-colonial educational methodology feedback that would involve a reversal of the established flow of practices from developed to developing world (Ivan Illych discussed this possibility in Deschooling Society). Such a reversal leads me to think of the arguments made by Alison Gopnik. A review in Nature of ‘Child development: A cognitive case for un-parenting’ mentions that

Gopnik reveals how the parenting model can affect how children explore. She describes a wide range of experiments showing that children learn less through “conscious and deliberate teaching” than through watching, listening and imitating. Among the K’iche’ Maya people of Guatemala, even very young children with little formal schooling can master difficult and dangerous adult skills — such as using a machete — by watching adults engaging in these tasks in slow and exaggerated fashion. In one of Gopnik’s own experiments using a “blicket detector” (a box that lights up and plays music when a certain combination of blocks is placed on it) four- and five-year-olds worked out that unusual combinations rather than individual blocks did the trick — and younger kids were more skilled than older ones at finding unlikely options.

Gopnik makes many references to pre-industrial educational practices of various cultures and argues for their effectiveness due to their deep compatibility with human developmental processes. My personal enthusiasm for EdTech derives from its potential to provide means of cheaply providing widely accessible learning opportunities more in tune with the rhythms of human growth than industrial educational models permit.  

How much though projects like XPRIZE are actually likely to represent improvements on more traditional educational programmes will be partly influenced by these programmes’ curricula. Basic literacy and numeracy are plausibly utilitarian content- unquestionably so in the developed world. In the developing world there may be other more utilitarian study options available. I have posted here before on the possible educational value of maker culture. In one such post I stated that “Amateur manufacturing is not (currently anyway) a realistic basis for meeting the material needs of the people of the world…”- at that point I perhaps should have specified that I was referring to the developed world rather than to places in the world where manufacturing (and various other forms of economic activity) are at most only semi-industrialised. In such places, education concerned with practical techniques for a range of locally relevant production and maintenance activities might be extremely valuable (as contexts for the teaching of literacy and numeracy if nothing else).   

It has occurred to me (as I alluded to earlier) that areas of the developing world with limited educational and industrial infrastructure could be in a position to leapfrog the twentieth century stage of development in education (and perhaps also in manufacturing), similarly to the way that the wire and cable based stage of telecommunications infrastructure was bypassed in some of the developing world, whereby most people that acquired mobile telephones had not done so to replace a landline telephone but simply to have a telephone at all in a place which lacked landline infrastructure. Interestingly, novel uses came to be made of mobile phones in such places to compensate for inadequate banking infrastructure by using prepaid phone cards as currency for remote transfers and it is not hard to imagine m-learning practices catching on easily in these places.

It might be that in the fairly near future the developed world could end up having lessons to learn on education from the developing world. 




All in all, you’re just a- nother node in the network (guitar solo)

What learners today seem to find so difficult is to combine different pieces of information that they are given with some kind of integrating purpose. Give typical contemporary learners an ensemble of information and a task that does not explicitly specify how it should be achieved (here, not explicitly defined task means tasks that exceeds the scope of an acyclic series of single-step processes for which no crucial information must be remembered or taken note of without having been instructed to take note of it) and the typical learner response tends to be ‘I see what the task says, but what do I do?’. What the learner is supposed to do is interpret the task. This is precisely what they struggle with.

What superficially seems to be the case is that learners lack a combinatorial fluency in some way that might plausibly be associated with inadequacy of attention span, as well as exhibiting a similar lack of efficacious fluency associated with depleted autonomy.

This diagnosis is questionable however when the capacity of contemporary learners to integrate information sources in informal learning is considered. The world now is tremendously complex and rich (and requiring of interpretation), to the point that simply navigating it at all requires a great deal of integration of information streams. Young people are highly active informal information stream integrators. Equally, young people now typically take great interest in their own autonomy and preferences and tend to be skeptical of authorities generally. 

These qualities of young people often fail to be at all evident when considering them as individuals, where the diagnosis of ‘poor attention span and weak autonomy’ is apparently the last word on the matter. Learners’ individual limitations should not be surprising however when it is understood that acting individually and unilaterally is an extremely alien mode of operation for today’s young person. This generation’s learners’ worldview is that of the network node, not of the self-sufficient individual.

Life as a network node is based around asynchronous collaboration with other network nodes. Asynchronous collaboration involves multiple agents working remotely to informally decide amongst themselves what actions to undertake, and doing so in a fashion that adapts to emergent network properties. This way of life represents a rational recognition of the efficiency gains of division of labour as well as the effectiveness gains that decentralised decision making can provide. These forms of behaviour are though almost the exact opposite of the forms appropriate for adapting to a setup in which individual agents are physically situated together but required to act individually and in isolation from each other, in response to an agenda that they had no significant part in selecting or influencing- the setup upon which twentieth century education is modelled. 

Trying to educate today’s learners in accordance with twentieth century educational systems and procedures and then being surprised at the ineffectiveness of the learners’ performance is to do something comparable with taking completely offline a computer that is running almost exclusively cloud based applications and then being surprised at how limited its functionality has become. Additionally, imagine that the computer is capable of allocating resources to the end of attempting to reconnect itself to its cloud networks- and indeed does everything it can to do just that (to the detriment of its capacity to do very much of anything else that it could conceivably do without cloud support).    

Educational institutions of today have two main options in responding to the problem of having a teaching model that does not fit its learners. The first response is to alter the model to better fit the learners by transforming the model into something essentially network based. The second response is to find ways to obscure the negative effects of the model-learner mismatch by modifying the model used so as to as far as is practically possible eliminate situations involving learners being required to genuinely interpret tasks (this being where the most noticeable symptoms of the model-learner mismatch are evident).

For the most part, educational institutions seem to have preferred the second option. Given the choice of implementing a complete paradigm change versus retaining the current paradigm but eliminating interpretation, the latter option is clearly the easier one to take. In a competitive educational environment, it is very risky for individual educational institutions to unilaterally and openly acknowledge the existence of major problems within themselves lest this simply mark them out as failing institutions. Bitterly ironically, the educational provision system tend to very much have a fixed mindset rather than a growth mindset; a school acknowledging its mistakes is not seen an opportunity for that school’s growth but as evidence of that school not being viable and hence of the need to replace its management and/or staff, or even to close it down.  

Competitiveness incentivises schools to disguise rather than address structural problems in the short-term interests of schools. The effect of such occlusion is to pass on the schools’ structural problems to the learners that graduate from problem affected schools. Learners whose education evaded the difficulties of equipping them to interpret complex tasks proceed after graduation to face the challenge of finding employment opportunities that are highly likely to be dependent on applicants’ abilities to interpret complex tasks (this problem is elaborated on in this article in Inc).

What seems to be taking a long time for educational policy makers to recognise is that what is in the short-term interests of schools is basically unsustainable; the prevalence of network-orientation in learners that drives the educational model/learner mismatch is not a short-term phenomenon and it is only going to intensify in the future. Helping schools to protect their short-term interests at the cost of the long-term interests of their graduates cannot continue arbitrarily without incurring seriously damaging economic consequences in terms of unemployment, under-employment and the prevalence of low-skill/low-pay employment (in other words, general job insecurity). The prospect of increasing workplace automation rising to substantial levels in the near future threatens to greatly exacerbate this damage.

If you can’t say it and you can’t show it then you don’t know it

This was one of the two stock phrases that I used in teaching (the other one was ‘No one ever looked good making someone else look bad’, used in behaviour management). The point of ‘If you can’t say it and you can’t show it then you don’t know it’, was that I encountered a fair few learners who insisted that they knew one thing or another, despite being unable to answer questions or perform actions that demonstrated that knowledge. The knowledge that they had was some sort of private revelation that was not amenable to external scrutiny.

I have chanced to learn some intriguing things since my time in the classroom that make me think that there could after all be some truth to learners’ claims of private knowledge (although I think that the claim of such knowledge is generally an empty one). 

As an educator, my specialism is physics. Physics offers a variety of interesting ways to think about things, including about thinking.

The particular example of this that I am discussing here is quantum cognition.

Quantum cognition is the phenomenon of human decision making that is inconsistent with classical logic but is consistent with quantum mechanics. A well known example of this phenomenon involved asking students whether they would buy a ticket for a Hawaiian holiday, depending on whether

  • they had passed a big test.
  • they had failed the test.
  • they didn’t yet know whether they had passed or failed.

More than half said they would buy the ticket if they had passed. Even more than that said they would buy the ticket if they failed. Strangely though, 30 percent said they wouldn’t buy a ticket until they found out whether they had passed or failed.

This defies classical logic because if you would have some preference P if some condition C is true, and you have the same preference if C is false, then you should have the preference P whether C is true or false, whatever your current knowledge about the truth value of C. In quantum mechanics this does not lead to a contradiction however as quantum mechanics is based around operators that are non-commutative, meaning (A X B) ≠ (B X A); the order of these operations must be taken into account to find the result of them, so it is possible to have a situation where a preference can fail to exist because a question has not yet been asked where that preference would exist whatever the answer to the question was.

Quantum mechanics has been used to analyse the results of surveys where the order of pairs of ‘yes/no’ questions is reversed to see how switching the order of  the questions affects survey respondents’ answers to these questions. QM predicts not only that switching the order of question pairs should change what answers respondents give for them, but that the number of respondents who switch from answering both questions with ‘yes’ to answering both questions with ‘no’ when the order is switched should balance the number of respondents who do the opposite (switch from answering ‘no’ to both questions to answering ‘yes’ to both questions when the question order is reversed). Weirdly enough, this balancing is observed in survey results. No one yet understands why this is so.

What this implies (but falls far short of concluding) is that preferences are produced by the act of being asked questions about those preferences. The preferences apparently did not really exist before they were asked about. If we consider that preferences ought to be at least partly based on memories (we base our future expectations on our memories of the past) then the implication arises that memories are at least partially generated by the act of remembering!

To conjecture a bit further; preferences have dependencies with other preferences (the same is true of memories). Being asked a question that sets a preference/memory into a certain state therefore has knock on effects on other preferences/memories. If these dependencies also happen to work similarly to how QM does then some sets of preferences/memories could have complementary relationships with each other, meaning that determining the state of one of the complementary items would result in the state of the other complementary items becoming undetermined; knowing one thing clearly would mean that there would be something else that you couldn’t simultaneously know clearly.  

It seems to me that a complementarity principle of some sort (or something quantum-like at any rate) can be discerned in the process of learning. This phenomenon arises (I think) around the issue of the relationship between some knowledge (referred to for convenience as ‘k‘) that someone (referred to for convenience as ‘p‘) knows  and how it is known (by p or by someone else) that p knows whether or not they know k.

The basic idea is that whether or not p knows k is affected by asking p whether or not they know k. More specifically, asking p if they know k may reduce the extent to which they do know k. This may sound strange and far-fetched but I am arguing for this on the basis that asking p whether or not they knows k involves some sort of assessment process that the act of participation in alters how p perceives k. This argument rests on the principle (which I invoke here!) that just about any example of learning that a human can possess is decomposable in a variety of ways.

There are (in general) lots of different ways of knowing any particular thing, and the way that a learner knows a thing may be different to the way that someone assessing that learner’s knowledge knows that same thing (let’s call the knowledge again). If an assessor asks a learner questions (even indirectly) concerning k then those questions cannot help but influence the learner’s state of determination of some memories/preferences related to that k. If the assessor learned k in a different way than the learner did then the assessor’s questions could disrupt the learner’s state of determination of k.

QM terminology could be useful in explaining this situation. In QM, any measurement of the state of a system results in what is called the projection of the state of the measuring system onto the state of the measured system (this is a more technical way of stating the oft-repeated principle of QM that the act of observing a system changes that system). Using this sort of terminology, it would no longer be valid to speak of in itself but only of the projection of the assessor or learner on k. These projections can be denoted kassesor and klearner. When an assessor attempts to measure a learners knowledge of k, this results in a projection of kassesor onto klearner, which can be denoted kassesorklearner. This projection is different to klearner and may represent a less determined state of knowledge than klearner does.

Thinking in this sort of way, I speculate that two entities exist (they could be called variables, but that doesn’t do justice to how abstract and complex they are) that can have a complementary relationship to each other. These entities are ‘Whether learner knows k‘ and ‘What is’. Strange as it may sound, I am suggesting that it might be possible to say clearly whether a learner knew something but not be able to say clearly what it was they knew. Conversely, it might be possible to say clearly what a learner knew but not be able to say clearly whether or not they knew it. 

In practical terms, I would argue that these two entities need to be measured in distinctly different ways to try and minimise how complementary they are.

‘Whether learner knows k‘ should be measured in terms of some sort of minimally ambiguous outcome (perhaps a rather artificial one), and is more accurately expressed as ‘Whether learner can produce some outcome that has been assumed to be connected with knowledge of k‘. Only the outcome would be measured, the process by which the outcome was achieved would be a black-box to the assessor. Assessors could of course observe the process but their observations could not influence the determination of whether the outcome was or was not achieved.

‘What is’ would be measured not in terms of some outcome brought about by the learner but by how consistently successfully such outcomes were achieved by people other than that learner who were instructed by that learner in how to achieve the outcome. If a learner can consistently induce outcome achieving actions in others then some sort of shared construct must exist common to that learner and those whom they have instructed. Scrutinising different interpretations of this construct would go some way to establishing the characteristics of  k, especially in terms of how those constructs correlated with individuals’ ability to achieve outcomes. 

My speculations on this are, well, speculative. Intuitively I think that I am onto something and that learning will one day be understood to be more quantum than classical, and that what we learn is not our learning, but our learning exposed to our way of asking questions about what our learning is.


The curse of motivation

The curse of knowledge is a cognitive bias that educators are particularly vulnerable to. When you spend your working life explaining certain things, it becomes progressively harder to remember what it was like not to understand them. Your knowledge becomes ever more implicit and your learners’ failure to grasp what to you is simply ‘obvious’ becomes a barrier to effective communication of that knowledge.

The problems arising from the curse of knowledge are perhaps less severe than those arising from what should be called the ‘curse of motivation’.

Educators are inclined towards believing that formally learning things is desirable. If educators did not believe that formal learning was an inherently worthwhile undertaking then it would be hard to account for their choice to work as educators. This default attitude for educators is by no means necessarily closely related to the attitude of typical learners.

Design considerations pertaining to the learner engagement potential of learning content and learning objects are not likely to be appropriately handled if the designers’ have specific empathy deficits regarding learners’ motivation to engage with what is being designed.

A crucial factor involved in learners’ motivation to learn is their belief about whether of not they can learn.  A lot of awareness currently exists regarding fixed and growth mindsets. A fixed mindset is often described in mindset related literature to be associated with regarding intelligence as static rather than capable of development. Focusing mindset on attitudes towards intelligence is not necessarily very helpful for promoting the cause of the growth mindset. Intelligence in the sense of general intelligence g -as measured in IQ tests is not necessarily a highly mutable characteristic. What is far more clearly amenable to development is learners’ crystallised intelligence, which many learners might better recognise as experience.

Experience is something that is difficult to acquire quickly (other than by taking big risks). Anything that only occurs gradually has a precarious status in the minds of a lot of contemporary young learners, for whom ‘long‘ is a pejorative. Network technology has made very high speed communication so commonplace that anything that involves a significant degree of waiting carries with at a distinct whiff of obsolescence that relegates its perceived importance to near negligible levels. Furthermore, what is learned through experience can in many cases be learned fairly implicitly. When learners learn implicitly, they do not necessarily explicitly recognise that they have learned.

Learners tend to have unrepresentative views of what they do and do not know. This in turn affects what they tend to be curious about. People tend to be most curious about what is not too detached from what they already know. It follows from this that if learners were able to become more aware of what they did actually know, that should make them more curious about what else they might not have realised that they knew, or wanted to know. This has given me the idea for a learning tool that I would like to call a curiosity integrator (CI).

A CI works similarly to a decision engine (the part of a search engine that recommends things to you, such as when it auto-completes your search term inputs). The CI is an app that is synced to your social media and search engines to collect information about what you are interested in and hence what you probably know about. Either by data mining or by modelling human learners (or both), the CI can extrapolate from your interests (and the knowledge that this implies that you have) what you might know implicitly without knowing that you know. The CI also tracks what you have (probably) learned from experience.

The CI uses what it knows (and can infer) about you to deliver an unpredictably timed series of informal reflections on what you have learned and when, and how these things connect with each other in ways that probably had not occurred to you. The CI suggests what future activities that you might want to undertake could be facilitated by particular learning experiences and links you to appropriate resources for learning.

The point about the CI is that it has no agenda. It does not expect that you should or should not learn anything in particular, it merely attempts to help you to recognise that you know more than you think that you do, in the hope that you find that information encouraging.