Truth, Lies and Enlightenment: how AI can help us to build knowledge and understanding in the echo chambers of life

AI is both a cause and a solution to the problem of a world where there is far more information than any one person can possibly effectively process to construct their own understanding about what they believe and what they don’t. AI can amplify the echo chamber by promoting the most believed over the most evidenced. BUT it can also help us to recognize valid information from noise, IF we know the right questions to ask and IF WE KNOW HOW TO WORK WITH OUR AI we can develop deep understanding and escape from the maze of invention…

Early in my career I was advised that if I wanted to get a point across when teaching, during an interview, as part of a presentation or when debating, I must repeat the point I wanted to make three times. There is an empirical basis for this advice: something eloquently explained my Malcolm Gladwell and the motivation for my blog identity: The Knowledge Illusion. Put simply, when people are provided with more information about X, they believe that they know more about X, when in fact they often know less about X. I wrote about this many blogs ago (transcribed below for ease of reference) to draw attention to the essential need to help people decipher the huge volume of information that comes their way so that they can discern what is genuine from what is fake.

I still follow the “say things three times” advice in my endeavour to communicate what I consider to be valid, some might say truthful, information. My objective is to persuade people that my perspective, opinion, or information presentation is the stuff to be believed. However, I accept that it is entirely up to my audience to decide whether or not they are won over. The importance of this subjective experience and the belief that an audience are actively analysing the information that comes their way is ever more important. In a world of echo-chambers and deluge of social media, we need people to be able to look at a stream of data and information and make intelligent decisions about what they believe to be the stuff of knowledge.

The problem is not new. It was JFK who once observed that “No matter how big the lie; repeat it often enough and the masses will regard it as the truth.” This is an enormous insult to the intelligence of the “masses”, but unless we pay attention to helping these “masses” to navigate through the morass of mediocracy that social media precipitates, proliferates and perpetuates then we will return to the pre-enlightenment era when the world was flat and knowledge was the privilege of those who knew how to decipher the written word and who acted as the mouth-piece for and the collective intellect of their communities: the “masses”.

The word “masses” is no longer widely used so let’s just refer to the “masses” as the people: the global human race whom education is intended to equip with the skills and abilities to think and make sense of the world and the information others produce about it. To consider what it is we need to do to help people to make sense of the world it is worth travelling even further back in time to the views of Roman Emperor Marcus Aurelius that: “Everything we hear is an opinion, not a fact. Everything we see is a perspective, not the truth.” We need to encourage a nuanced belief system where people are provided with the skills, confidence and resources to construct their own understanding from the tidal wave of data and information that threatens to engulf them.

Again, history can help to inform us. The scientific revolution set the stage for the age of enlightenment that transformed the human race and promoted the importance of reason. Influential thinkers like Bacon, Locke and Descartes paved the way for the likes of Voltaire, Kant and Smith. Life was so much simpler then of course, but the huge increase in what it is possible for an individual to try to understand and know does not discount the important role that influential thinkers can play.

The birth of the www and social media represent a new generation of publications that play the role of the encyclopedias and dictionaries in the age of enlightenment. BUT who are the key philosophers and scientists who can catalyze the popular debates in the way that the philosophers of the enlightenment did? Stephen Hawking would probably be high on the list of influential thinkers who many people (the “masses”) might be able to name. Who else?

Whilst the volume of information and data about the world has ballooned, the number of influential thinkers who can help people find their way to knowledge and understanding has may not have kept pace. Technologies that harvest the ‘wisdom’ of the crowd often promote the loudest shouters and the most-followed, rather than the considered and grounded reasoning of the real intellectuals. The demise of expertise has exacerbated the problem as professional predictions have failed to materialize…. Let’s just stop there for a moment.

Could the real problem be that we, the people, don’t know how to interpret expertise? We want simple answers when there are none to be had. In schools we still encourage the belief that rote learning and subject specific information of the type that can be reproduced by a single person when challenged with a standardized test sufficient. This outdated approach gives the impression that knowledge and understanding are way more simple than they really are. They encourage people to believe that there is a body of stuff that they need to learn and reproduce, and that if they can do this they will be knowledgeable. However, what we should be doing is ALSO encouraging people to constantly probe, prod, compare and conclude for themselves their understanding of the world so that they can apply this knowledge to solve the problems they encounter every day.

The surge of tweets that give the impression that meaningful things can be said in 140 characters is not always helpful either. There is certainly something to be said for trying to distil understanding into a short text — it is difficult and can test how much we really understand. However, the believe that a tweet can be the whole story in and of itself is misguiding. Knowledge and wisdom need to be worked at, by questioning, analyzing, aggregating and synthesizing to reach our own evidence-based beliefs about what we know and what we understand. Someone else’s tweet might start this process, but we have to finish it for ourselves.

Ai can help us to do the work here. AI can analyze and visualize complex data and information in order to literally help us see the ‘wood from the trees’. AI can be built to model human understanding and to justify the decisions and predictions that it makes. AI can explain to us how to complete complex activities, such as solving mathematical equations or managing a complex power plant. BUT Artificial and Human Intelligence must work together to help people extract the truth from the lies. We as humans must ensure that we know enough about what AI is capable of doing to ensure that we ask the right questions. We must learn to be discerning enough to challenge the AI when we are not convinced by what it is telling us.

This means that now more than ever we must educate the educators. Because educators must instill in us, the people, the investigative skills that we need to ask the right questions so that we can differentiate evidence from falsehood. Educators must encourage the confidence and self-efficacy in us that will help us believe our own minds. Educators must engender the perspective taking and integrative thinking that will enable us to work together to solve problems and to develop the influential thinkers we need now more than ever to enlighten us.

More relevant than ever…Information plenty, but knowledge famine: are we succumbing to an illusion?

I am curious about knowledge, not in philosophical sense, but in a practical one. I worry about what it means to know something in a world that is increasingly complex, ill defined and interconnected: a world that demands that we develop, and that we ensure that our children develop, the knowledge capacity to solve the problems it manifests and those that we create.

The first recollections that I have of my own curiosity about knowledge date back to 1966 when I was eight years old and growing up in Manfred Mann’s semi-detached suburbia: dad, mum, older brother and me. My father was an aircraft engineer and my mother taught typing and shorthand to women whose working lives were about to be dramatically changed by the word processing power of the digital computer. My brother was 3 years older than me, and his lack of interest in formal education was causing my parents some concern. Their reaction was to invest in ‘knowledge books’, or at least that’s how they saw the children’s book of knowledge and the encyclopedia that now filled up the bureau bookshelf. To keep us up to date, there was also the weekly general knowledge magazine that plopped on the doormat with a reassuring thud: the weight of its knowledge there for all to hear.

I suspect that my parent’s reaction to their son’s educational malaise was not an unusual one amongst the aspiring middle class families of our neighbourhood. My brother’s reaction to the new literary arrivals was cool; he was far more concerned with exploring the world of the woodland around our housing estate, than with sitting at home and reading about it. My father however, became quite addicted to the weekly general knowledge magazine. He did not have a great deal of time to read, but each evening when he went to bed he would sit in his paisley pyjamas and thumb through the pages. The stock of copies soon grew on the nightstand as his pace of reading failed to match the frequency of their arrival. The corners became slightly curled as the months and years passed and the dust gathered in and around the pile that now extended from the nightstand to the floor. His interest never waned and I do believe there were a pile of old issues by his bedside when he died many years later.

Forty years on and it’s a sunny day and I’m walking along the Euston Road in London. I pass the entrance to the British Library and a sign catches my eye, the sign says: “Step inside – Knowledge freely available”. I dislike the suggestion that one can walk into the British Library and just pick up some knowledge like going into Tesco and buying some bananas. I can relatively quickly formulate an explanation for myself about why the sign irritates me, because I have a clear idea about what I believe knowledge to be. I have moved on from the conception of knowledge loved by my father and represented by the pages of his books and articles. I know that I have to construct knowledge from the evidence available to me, that it is not handed to me by others, though they can certainly help me along the way, and that I can aspire to continually increase my knowledge by weaving together the information resources distributed throughout my world.

This is not the case for many of the youngsters who attend our schools and colleges. For them knowledge is still to be found in the dusty concepts in the out of date magazines on my father’s nightstand or on the shelves of a library they never visit.

“But what of the internet and world wide web?” I hear you wonder. These technological masterpieces offer information resources wherever we are and whenever we need them. These must surely pave the way for us to become more knowledgeable, both personally and as a human community?

The sheer abundance of this information has thrown into sharp relief our understanding of the relationship between information and knowledge. It makes my modest collection of childhood encyclopedias and my father’s overflowing magazine collection look like a speck of dust on the library shelf. I fear however that our understanding of what knowledge is and what it means to know something has not progressed in tandem with this technological progress. This puts us at risk of succumbing to the illusion that we know more than we actually do, because the more information we have the more we become certain that we know something.

Without helping young people to develop an understanding of what knowledge is in a digital age they cannot progress beyond the well meaning, but limited conception of knowledge promoted by the books and magazines that appealed to my parents. Those of us who understand what we mean by knowledge can indulge ourselves, as my father did with his magazines. But, without actively engaging people in the excitement of connecting the knowledge construction process to their own particular context, we merely encourage them to pass the opportunity by in the same way as my brother did all those years ago.

In a time of information plenty we are at risk of a knowledge famine.

I wrote thsi piece originally for  Learning to Live – Creativity, Money and Love

‘Theresa Maybe’, but Colin definitely is an aide for greater educational equality

I was struck yesterday by the juxtaposition of the Economist’s dubbing of Theresa May as “Theresa Maybe“and the Telegraph article authored by the PM about her desire for a shared society that will tackle “everyday injustices”. How exactly will the shared society work, and in particular in what ways will education be changed in order to achieve the worthy goal of a fairer society for all? I feel there is already a lack of decisiveness in the lack of detail about what kinds of policy will deliver this solution to the everyday injustices faced by many learners across all ages and sectors of education. (From an interesting article in the Huffington Post)

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Education can change lives for the better, but sadly it often does not and those who are privileged are able to benefit from better opportunities for learning. So here is a suggestion for unlocking some of this inequality.

 

 

My colleague, Wayne Holmes and I were asked to write an article for ‘How we get to next‘ and we used this article to pitch the benefits of an AI classroom assistant to help and motivate teachers to ensure that all learners are involved in activities that meet their needs. We tell the story of Jude, a teacher in the year 2027.

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“And at Jude’s side, there’s her AI Teaching Assistant, Colin, whom she’s named after a childhood friend. In fact, so many aspects of how Jude understands her students’ learning are different now, thanks to her machine aide.

Through working with Colin, she has become somewhat of a metaphorical judo master, harnessing the data and analytical power of AI to tailor a new kind of education to each of her students. Her role at the helm of the classroom, however, is fundamentally unchanged.

….

Since Colin makes ongoing assessments based on daily student performance and engagement in the classroom, there is simply no longer any need for what were often inaccurate and stressful evaluations. The AI aide’s primary task is to build and maintain learner models for each child based on a combination of data gathered over time with things like voice recognition (which identifies who is doing and saying what in a team activity) and eye tracking (to note engagement and focus). The profiles are updated continuously, monitoring students’ progress against analysis of their emotional and motivational state.”

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I know that well designed AI can help us build a much fairer education system in which all learners benefit and prosper, and that we have the technical and human capacity to create the right type of AI. A better educated population would then surely help us to tackle some of the other major challenges that a shared society agenda might face, such as inequalities in the health system and problems related to immigration.

We can radically redesign the 11 plus exam to make it fairer, so what is stopping us?

AI assessment systems could provide a fairer eleven plus selection, it could also start to address the vexed question of assessing potential rather than just current ability. We know that well designed AI systems that assess learning, are accurate in their assessment. AI assessment can tackle more than subject specific knowledge and reasoning, it can also evaluate skills such as planning and knowing what we know. AI assessment would also provide a fairer assessment system that would evaluate students across a longer period of time and from an evidence-based, value added perspective. We also know how to prevent people from gaming AI assessments, in addition to which AI Assessment systems would also offer tutoring for everyone and support and formative feedback to help students learn and improve. If there is to be a revamp of the grammar school system then we must explore these possibilities.

Theresa May’s plans for new or expanded grammar schools in England have brought a torrent of comment, debate, criticism and rhetoric since these plans were inadvertently revealed last week. Most of the discussions seem to have focused on whether or not grammar schools are the right mechanism to aid social mobility. This is an extremely important issue, but let’s put the rights and wrongs of selection and grammar schools to one side for a moment and look at the eleven-plus examination itself.

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The eleven-plus examination is the key to the door of one of the 164 grammar schools in England, or one of the 69 grammar schools in Northern Ireland. The examination is sat by children in their last year of primary school and it varies depending upon where in the country it is taken. In fact, the situation is very complicated with a wide range of approaches even within the same county.  For example, in Yorkshire there are three Local Authorities with Grammar Schools: Calderdale has 2, Kirklees has 1 and North Yorkshire has 3. The 2 grammar schools in Calderdale use Verbal Reasoning tests, and Maths and English examinations using GL Assessment, University of Edinburgh and the school themselves as their examiners. However, the 1 school in Kirklees uses tests in Verbal Reasoning and Non-Verbal Reasoning, plus an English examination and a Numerical Reasoning test. These are all examined by University of Durham. The situation in North Yorkshire is different yet again, with 2 schools using Verbal Reasoning and Non-verbal Reasoning tests examined by NFER and the 1 remaining school administering and examining its own selection tests.

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The complexity in the selection process is not helpful to poorer parents, who do not have the time, and possibly not the capability, to navigate the process. In addition to which the examination approach is traditional and outdated. The need to look deeper than the selection process to the eleven plus examination itself was highlighted in an interesting discussion on the Radio 4 Today programme last week. The discussion was between Laura McInerney, the editor of Schools Week, and Sean Worth, from Policy Exchange. Sean pointed out that the current mechanism for selecting children for grammar schools can be gamed and that we therefore need to change the examination if we are to ensure that the poorest children are not disadvantaged. Laura McInerney also pointed out the major problem for poorer children accessing grammar schools is that we “put a test in the way”, especially divisive when the parents of poorer children can’t pay for tutoring to get their offspring through the eleven plus examination.

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The Guardian published a depressing article on the problems inherent in the eleven plus test ‘‘Tutor-proof’ 11-plus professor admits grammar school test doesn’t work’. The article reports the failure of a ‘coaching resistant’ test developed by CEM at the University of Durham for use in Buckinghamshire. CEM has now withdrawn the claim that the test could assess “natural” ability. Prof Coe director of CEM is reported as saying: “Whatever system you use it is imprecise, there are false positives and negatives and probably more of those than people realise.” He goes on to reflect that whilst he does not agree with creating if we are to have more then we need to try and make the system fairer. I couldn’t agree more – and the need for a radical rethink is echoed in what the IOE’s Tina Isaacs says about the problems of coming up with any test that can assess future potential.

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So, let’s take the test away and develop a radically different, socially equal eleven plus. We are lucky enough to be in a very different situation today from that which existed when the original eleven plus was introduced in 1944. There is now a realistic and economically attractive alternative at our fingertips. We have the Artificial Intelligence (AI) technology to build a superior assessment system should the proposed reforms become a reality. AI provides a powerful tool to open up the ‘black box of learning,’ to provide a deep, fine-grained understanding of when and how learning actually happens. Intelligent algorithms can process information about each learner and reach a view about their progress, knowledge and understanding of a subject or skill over a ‘period of time’. Unlike the eleven plus examination, this ‘period of time’ could be a whole school semester, a year, several years and beyond.

Of course there are serious ethical questions around AI being used in education and these must be explored. But the over-riding and uncontested fact in this debate is that education is the key to changing people’s lives. We trust AI with our personal, medical and financial data without a thought, so let’s trust it with the assessment of our children’s knowledge and understanding. Let’s open our minds and explore the challenges to build a new generation of eleven plus assessment that genuinely irons out the inequalities and gives all children a chance to shine.

[3] Hill, P. & Barber, M. (2014). Preparing for a renaissance in assessment. London:  Pearson., DiCerbo, K. E. & Behrens, J. T. (2014). Impacts of the digital  ocean  on  education.  London: Pearson.

To appear on the IOE blog

https://ioelondonblog.wordpress.com

Calling education: wake up and smell the coffAI, don’t miss a great opportunity to drive prosperity for all

A recent article in the THES got me thinking. David Matthews reported under the title: The robots are coming for the professionals, and asked if universities need to rethink what they do and how they do it now that artificial intelligence is beginning to take over graduate-level roles? This motivated me to write a blog post for THES that was published on 9 August: Four ways that artificial intelligence can benefit universities, in which I suggested that HE needs to embrace the positives of AI, not just look at the negatives.

 

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These issues are not limited to HE, in fact this is a wake up call for all of Education. We must engage with these technologies and those who are developing them NOW in order to ensure that the AI that we end up with in classrooms, homes and the workplace is informed by what we know about learning and NOT what we know about what the technology can do.

7fba0586036d8b0f2cdf47df1d037557There is a huge and growing interest among those who invest in new technology ventures, specifically Artificial Intelligence (AI) techniques and methods. For example, between 2011 and 16 May 2016 Sentient Technologies received over 143 million USD in funding (Data from CB Insights) Much of the excitement about AI has focused on general purpose AI i.e. intelligence that is applicable across a variety of industries and activities. This is being promoted for technology businesses as a force for good. For example, Antoine Blondeau, the CEO of Sentient, has stated that: “From healthcare to finance to e-commerce, we’re focused on changing people’s lives.” Sentient is reported to be working on financial platforms and on an AI nurse to diagnose patients with sepsis.It is a business that like many who are adopting AI methods has no problem in attracting funding.

However, the same is not yet true of organisations who are adopting AI for education. Yes, there are things like Udacity, that claims it will change HE, and Knewton whose CEO Jose Ferreira, really does believe that his technology will replace human teachers. Such an outcome would make ‘driverless classrooms’ into a science reality. These commercial AI in Education ventures are well funded. BUT it is hard to find mass investment in the application of AI to education, despite the fact that the Educational Technology sector is predicted to grow from £45bn to £129bn by 2020. And to my mind much more significantly, despite the fact that education is the real key to changing people’s lives.maxresdefault.jpg

We need to take a fresh look at education if we are to ensure that the global population is able to reap the potential of the AI revolution that is sweeping across the workplace. AI is both a cause of the radical changes to the workplace that prompted David Matthews to write his piece in the THES and a provider of an answer to the problem of how we make the most of the workplace automation that AI is enabling. The purpose, methods and outcomes of education need re-thinking and AI can help us to tackle the challenge of this re-thinking if we invest in its development and build on the thirty years plus of research in AI for Education.

The importance of the social and economic significance of the developments in autonomous systems and AI was reflected at the annual meeting of the World Economic Forum 2016 in Davos, where the focus was on ‘The Fourth Industrial Revolution. This revolution “is characterized by a range of new technologies that are fusing the physical, digital and biological worlds, impacting all disciplines, economies and industries, and even challenging ideas about what it means to be human.” These radical changes do not however seem to manifest themselves in a concerted effort to use AI to revolutionize education. This oversight is shortsighted to say the least. The few exceptions that one can find where AI is being applied to education at some scale have a very narrow perspective and are a long way from changing people’s lives in the positive way that we want and need. For example: Knewton, is just one a a host of companies who believe that Subject Knowledge is the key to unlocking education for all. Through, for example, making artificially knowledgeable adaptive tutors who can personalize their content to meet an individual learner’s needs. This is all very well, but there is so much more to education than subject knowledge and so much more to AI than adaptive educational content

So what are the key attributes of AI for Education that will enable it to start attracting the sort of investment that Horizons Ventures and Tata Communications have made in Sentient Technologies? What are the attributes of AI that will persuade research funders that AI for education is a subject they must prioritize and that it must be a truly interdisciplinary enterprise that is not driven purely by technologist’s dreams. For a change let’s focus on disadvantaged learners’ dreams and see if we can work with technology to turn these dreams int o reality.

One key attribute of AI for Education is the ability that Educationally driven AI techniques and algorithms bring to the analysis of the vast amounts of data about learners that is routinely harvested by the increasing amount of technologies in the world around us from CCTV, to smartphones, wearable technologies and online courses, such as MOOCs. For example, we can

  • Conduct fine-grained analysis of learners’ skills and capabilities so that their development can be tracked at the student/employee, workplace, school, area, and country level;
  • Enable the collation of a dynamic catalogue of the best training and teaching practices across a range of environments and as a result enable us to educate and train the future workforce in an economically productive manner.

A second key attribute of Educationally driven AI is that it can help us to tackle the toughest educational challenges, including learner achievement gaps, teacher skill shortages, continuous professional development for educators. If we think about the business of education for a moment, imagine the AI teaching assistant that can be used to stretch the brightest pupils, while the human teacher devotes their expertise to giving the less able learners the sensitive human support that they need in order to progress. The teacher would train their personal assistant to work in the way that the teacher and their students need and would demand that the AI assistant explain the decisions it has made about students and the educational opportunities the assistant has provided.

But perhaps what we need to focus on first is using AI systems that go beyond the machine learning and neural network techniques that dominate the work of the main AI protagonists within and beyond education, from Knewton to Google DeepMind. The types shutterstock_260422808.jpgof AI we need within education is the AI that enables the technology it powers to explain its reasoning, to justify its decisions and to negotiate with its users. This is the sort of AI technology that could help us address one of the toughest challenges within the current workplace:  The lack of understanding about how humans can best work with AI systems so that the result is AI augmented human intelligence that is greater than the sum of its parts. We need workers who understand how to make the best use of the power that AI automation can bring to industry and commerce. Workers who understand enough about AI to know where and how human intelligence can work with AI to achieve a blended intelligence that can increase productivity. And what is beautiful about all this is that the appropriate type of AI can help us educate and train people to understand enough about their AI colleagues to work alongside them effectively.

 

 

Here is what ‘smart’ looks like in an AI tutor

 

So, what would a piece of education technology driven by AIEd look like? Here is a simplified picture of a typical model-based adaptive tutor.

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It is based on the three core models as described above: the learner model (knowledge of the individual learner), the pedagogy model (knowledge of teaching), and the domain model (knowledge of the subject being learned and the relationships between the different parts of that subject matter). AIEd algorithms (implemented in the system’s computer code) process that knowledge to select the most appropriate content to be delivered to the learner, according to their individual capabilities and needs.

While this content (which might take the form of text, sound, activity, video, or animation) is being delivered to the learner, continuous analysis of the learner’s interactions (for example, their current actions and answers, their past achievements, and their current affective state) informs the delivery of feedback (for example, hints and guidance), to help them progress through the content they are learning. Deep analysis of the student’s interactions is also used to update the learner model; more accurate estimates of the student’s current state (their understanding and motivation, for example) ensures that each student’s learning experience is tailored to their capabilities and needs, and effectively supports their learning.

Some systems include so-called Open Learner Models, which present the outcomes of the analysis back to the learners and teachers. These outcomes might include valuable information about the learner’s achievements, their affective state, or any misconceptions that they held. This can help teachers understand their students’ approach to learning, and allows them to shape future learning experiences appropriately. For the learners, Open Learner Models can help motivate them by enabling them to track their own progress, and can also encourage them to reflect on their learning.

One of the advantages of adaptive AIEd systems is that they typically gather large amounts of data, which, in a virtuous circle, can then be computed to dynamically improve the pedagogy and domain models. This process helps inform new ways to provide more efficient, personalised, and contextualised support, while also testing and refining our understanding of the processes of teaching and learning.

In addition to the learner, pedagogical, and domain models, AIEd researchers have also developed models that represent the social, emotional, and meta-cognitive aspects of learning. This allows AIEd systems to accommodate the full range of factors that influence learning. Taken together, this set of increasingly rich AIEd models might become the field’s greatest contribution to learning.

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This post is an adapted extract from Intelligence Unleashed published by Pearson.

A bit of Yackety Yak about the Hackety Hack

I am increasingly excited about Re-Designing our education and I have a song in my heart…

Get out those mobiles and that scratch
Or you won’t get to code and mash
If you don’t drum on that LKL door
You ain’t gonna teach and learn no more.
Hackety Hak (you won’t look back)

Re-Designing our Education – Education Hack – 7 days and counting

Re-Designing our Education – Education Hack 16-17 November, 2102 at The London Knowledge Lab

What a great weekend!  A new initiative from Nesta:  Digital Making initiative and the Mozilla Festival too. But even more exciting than all this is the final countdown to our Education Hack Event, which starts a week today where learners will be working with teachers, researchers and volunteers from the SME and StartUp community to ‘Hack their Education’ and show us all how technology really could make a difference to teaching and learning.

The Education Hack Event involves 50 students from 6 schools over 2 days at London Knowledge Lab working with volunteers to develop the future of education . It will enable secondary students to put into action their ideas about how technology could revolutionise their learning. Teachers get hands-on too, working with their students and experts from the LKL, industry and the media.

From e-diary systems to help them track their learning and homework to cyber bullying help networks, the students have the ideas and we will help them put them into action. This is ‘The real McCoy’ – kids hacking for good.

The technologies that are being used include MIT apps inventor, Java, HTML, digital film, web building using Thimble, Arduino kits, content mashups and  much, much more

Members of the public can also take part on the Saturday afternoon, see what the students have built and try their hand at a range of activities from making jewellery tagged with radio frequency detection devices to writing code.

Teaching children computer science, including programming, is at the heart of the policy shift in the current teaching of IT. Programming helps build understanding of and access to formal systems of thought that are essential in helping people to express their ideas about the world, and make sense of it. That’s why programming is important: not just to increase the supply of programmers (important) or to introduce to everyone what is under the bonnet of the systems that power our society (essential), but to introduce the power of computational thinking. Events like Education Hackday allow young people to develop their computational thinking and hack new ideas to revolutionise their learning environment, working with their peers, teachers and technology professionals.

As one of our participating teacher says:

“Education Hackday will provide our gifted and talented computing and IT students with a challenging “real life” opportunity. They will learn how to use new computing and programming tools, experience different design environments, and work with a range of other peers, agencies and experts. The benefits of such an experience have a long term impact on the pupils themselves, as well on as the staff of the school.”

Chris Betts, Blatchington Mill School: