Pity the Young Learner

As naturally selected creatures we humans are unable now to compete computationally with the best of the learned "machines". Does this mean that in education we should seek to awaken the human awareness in our children, that quality of understanding that may just be beyond Artificially Intelligence in the coming century?

The children of today face (amongst others) two uniquely human (existential) threats to their mental well-being:

1- that they will not be the computationally dominant entities on the planet
2- that they will survive long beyond their best before date.

How best then to draw out durable attributes that will differentiate them from (the) routine performers and enrich them when their utility is no longer called upon?

Further we foster the erroneous notion that there is only one truth with reward for delivering it precisely according to a prescription that only us, the educated classes are party to. Mostly we are cornered reinforcing "get it right to get a reward". It is all very Pavlovian, habituating in the learner "I will only do that which I can do (and little or no more)." 

That the measuring process moulds our teaching pedagogy in an unfavourable way is pretty well acknowledged. We know assessment fails to reflect the abilities of children fairly, more often eliciting only what they don't know. As such we ought to be minimising summative measuring until it is absolutely necessary. Learning as a means to be measured is merely a behaviour management tool doing a poor job of engendering any curiosity, the student dispirited rails against the process perversely reinforcing our need to shackle them with it.

This format does not model how they will be rewarded in their working lives.  How to prepare for the discombobulation of being in the workplace when everyone is pretty much making it up as they go along? We need to create argumentation in the classroom and be happily drawn off-course, because having such skills will, even if not making them leaders will make them questioning followers. 

Perhaps then we should consider spending the first years after primary education breaking down the (necessarily acquired?) dependence on delivering recipes of clear instructions, fulfilling tasks with known outcomes. 

How often do we hear:

"Shall I do it like this? Shall I write here not there, like this or that? or "What should I do now that I have finished this? ", "But we learnt it this way.", "But I do it this way using this (algorithm /recipe/Ansatz)?"

These are more the questions of machine learning, not a human being! What about:

"I got the answer right so what does it matter how I got to it?" 

Machine or human? Interesting at least. We ought to be harnessing and emphasising their human qualities, that will put them ahead of their principle competition this century, the machine. 

Promote Creativity and nurture Talent:

1-their innate ability to recognise patterns (even when they aren't there- to always err on type 1 statistical errors of false positives which is an evolutionary survivorship trait that may be difficult to embed in machines!)

2-an emotionally reaction to something that resonates with them, be it something they can empathise through experience or the realisation that they (think) they may have understood something for the first time. 

3-an awareness of what that sensation of an awakening of an understanding might feel like. (Some self-awareness of how they might just of acquired that awakening)

4-a feeling that it is more rewarding to come up with the question themselves rather than just a possible answer; to be able to generate questions from a body of understanding and to build on their knowledge database, one that is not merely Google searchable.

We need to be doing a better job of cultivating:

1-curiosity, debating argumentation social skills, 

2-respect for differences of opinion, openness to new ideas, 

3-risk taking so as to not be afraid to err on the wrong side of right,

4-a sense of being humble within ones knowledge; to know that knowing more reveals how little they know

Argumentation points can develop into philosophical debates in which cross curricular content can be made mutually more relevant for the learner (even by pure association). More obtuse and abstract content can be made more tractable or at least accessible. Ultimately the young student can at least have been asked to ponder, (if not resolve) some of the great imponderables that the rigidity of  examinable content-laden middle and higher level courses deem too difficult to differentially measure. By loosening the didactic constraints that linearised modularising syllabuses create we as teachers should anticipate more rewarding interactions, through debate, context-oriented open-ended classes.

It is more than anecdotal that content-led learning is not as durable in the child memory as context-led learning. How best to learn a language after all? Surely not through learning the rote rules of grammar? That students may have come across material three or four times before and may have no recollection of doing so, may well reflect genuinely in that moment an honest recall of no memory of a memory of doing something previously for the sake of it (and perhaps for the promise that it may be of use in the future). In Mathematics for example a student can be taught power (index) laws, graphing of functions in a sterilised answer led environment  from age 11 to 16 and not know to (let alone even How or When to) to deploy any of these ideas in the context of the messiness of high school sciences.

In promoting longer term cross-curricular project theme-based learning the student would be empowered to emphasise what most strikes a chord with them that may stretch across multiple school subjects. They would be introduced to similar ideas from multiple perspectives and teachers.

Some rough thematic ideas to consider:

A) English Literature, Ethics, AI, Mary Shelley's Frankenstein:

1. what is a "life-force", what gives us our energy?  
2. the scientific history of the origins of Electricity, through Galvini's experiment. 
3. how the notion of a monster has shaped our ethics on AI, has corrupted the idea that a man-made machine will inevitably be used for bad?
4. what is that conscious feeling? that conversion of light, sounds into electrical impulses?

B) Mathematics in science:

1. hereditary, genetics, gene therapy?, eugenics, Dalton good or bad?
2. sequences, golden ratio, aesthetics (projective geometry-the only useful bit of trig they will never know about!) log spirals, hurricanes, Galaxy formation, fractals, chaos theory, dynamical systems.
3. logical deduction and induction, logic gates, coding, cellular automatons, game of life, 
4. fooled by randomness- evolution as a filter delivering magic numbers: the Cicada beatle's prime number mating frequencies, the investment management industry as the story telling of the lucky winner. 
5. awareness of bias, survivorship, Confirmatory bias. What other bias are they subject to: last thing I was told is most true bias?

C) Geography and Mathematical Statistics:

Discover questions or results that show highly suggestive correlations but without a mechanism: 

1. the radius of the earth increases and contracts by 2mm every five or so years (it is a spinning oblate sphere of cold crust floating on a warm fluid sculpted along the magnetic field lines of the earth and by the slow dissemination of its geothermal heat) 
2. we see spikes in magnitude 7 earthquakes every 5 years -spurious correlation? 
3. that the increase in the radius of the Earth is 2mm, that is 12mm on a circumference change of 2pi x6300 km (as a percentage?...) sound like a feasible mechanism?
4. that if I told you that tectonic plates are moving less than the annual growth of your fingernails and that that 12mm in a year is enough movement generally to causes earthquakes? Any more plausible? earthquake-predictions

D)  History and the Machine (from Ethics to levers and pivots)

1. How did the Pharoes build the pyramids? 
2. History of enslavement- Filipino building of Qatari olympic stadium?
3. levers, pulleys, Rube Goldberg machines.
4. nature's structures: the beehive hexagon as a solution to an optimisation problem, packing problems, (Pascal) triangle numbers. 

E) the Art of seeing, perspective and distance from Science:

1. optical illusions
2. what is an image, seeing is believing?
3. what is it that makes that makes a lemon appear yellow? Why a leaf is green not black? why o brown on decay?
4. casting shadows, orthographic drawings?
5. perspective-representing 3d image on 2d surfaces - projective geometry, mapping
6. standard candles of the cosmic ladder distance measurment

F) What makes belief a plausible explanation? (Belief or ceding to the expert)

1. Do we believe we have the instrumentation to measure with a precision down to billionth of second? Gravitational wave detection? 
2. Global warming even with these nasty cold snaps? Why believe or otherwise?
3. Do you believe in other people's belief? How do they know that they don't know (better?) 
4. When are you satisfied by an argument or an answer. Because someone of authority has offered it? what makes an explanation a good one or plausible?

G) What thinking skills do you need to be responsible citizens: 

1. discern fact from fiction; be sceptical, does something sound reasonable? 
2. be aware of how big data is being gathered and will be used (against them perhaps e.g. health, lifestyle insurance), 
3. be aware of their footprint on the Internet. Will there future self thank them for their efforts?
4. how best to find something on the Internet? Can you ask a question whose answer can just as well be Googled? What type of questions are not so easily Googable?
5. what is the usefulness of knowledge given that it is all there out there anyhow? What are the implications of never looking at answers beyond the first page of Google? Never using another search algorithm? Same question, different engine? What do websites do in order to promote themselves in search algorithms? What is the/a algorithm?!
6. be aware of how advertising effects their news feeds, their version of the truth, that AI is already influencing their lives. Happy having their world-view being being sculpted by advertising and led by machines? 
7. would you prefer to be marked by a machine? Judged by a machine, diagnosed by a machine? No chemistry, no emotions, no human bias?

The goal would be to be engendering student-centred self ownership of their education. For us teachers to be flexible enough to be drawn off topic, to let the students guide us or at least give us cues as to where they are interested. To remove the burden of delivering thorough contrived premature content across all age groups. To create debate, cultivate reflection and maintain some of that early curiosity (that we have beaten out of them) for the world.

We should look to encourage such broader context-led learning at least when in principle we can expect to be less pressurised by a parent's need for measurable feedback. Perversely it is in the early middle years that the most iterative futile metric laden feedback is generated.