Digital classrooms

This is Part 5 in my series of posts on the future of learning and technology. A few years ago Peter John and I wrote a book entitled 'The Digital Classroom'. It was published by Routledge in 2008 and is now also available as a Kindle reader version. It wasn't the first published under that title, and it probably won't be the last. The idea of a 'classroom' (regardless of how anachronistic that may sound) is appealing when it is 'digitised'. It's the old, comfortably familiar territory embellished with the new. Everyone in the world of education it seems, has an interest in how technology is going to influence what we do in the classroom. The book was received well, and we received some positive comments and feedback. Although the book is probably a little dated now, with technology advancing at rapid pace, it still set a benchmark for some of the things we could expect to see in the coming years. We talked for instance about how technology would streamline assessment, and how the curriculum might be impacted by new technologies. There were sections on digital literacies and mobile learning, both of which we considered to be important for the success of education and learning in the future. Blogs and wikis and other social media made an appearance, even though at the time they were still fairly nascent in compulsory education. We even mentioned the Semantic Web (or Web 3.0) as a potential horizon technology for learning. We spent a lot of time talking about digital cameras and interactive whiteboards, both of which have had dubious success in the school classroom.

Ultimately though, we could not have predicted the new tools and technologies that will become very much a part of normal school life in the recent and coming years. We did not foresee the touch tablets and their rapid success in schools, nor did we predict the rapid rise of smart phones and apps, or the potential of augmented reality. The non-touch motion sensing gestural interfaces now emerging (for example the Xbox 360 Kinect) and the voice activation applications were still just a gleam in the eye for many of us. Perhaps we should not have titled the book The Digital Classroom, but simply Digital Classrooms, because now we know that there are many possibilities, and that classrooms that have digital capabilities are many and varied. If I was to take a risk and suggest possibilities for the next 5 years of development, I might be right on some of my predictions, and hopelessly wrong on others, but here we go...

The signs are there that in the coming years, more gestural interface technology will be available for learners, and that advances in manufacture and design will enable the installation of screens on walls, desktop, in fact on any flat surface. The screens will be resilient and high resolution, but as thin as a sheet of card. The mouse, and keyboards such as the one in the image above, may disappear completely in favour of voice and gesture activated tools. For students with mobility issues in particular, this may turn out to be an important leveler. Smart touch devices will continue to develop too, so that every student will have the means to access all their learning resources right there in their hand, wherever they are, and whenever they need them.

Much more learning will be done outside of the classroom. Digital classrooms will become the place where learning is performed, celebrated and assessed - on large wall screens for all to enjoy. For many teachers, learner analytics will become an indispensable tool for tracking student progress and intervening when necessary. Many governments will probably insist on it and legislate accordingly when they realise just how much data can be mined from personal activities across the web. Eye tracking and attention tracking will also emerge as useful behaviour management tools for teachers in the next few years. Gamification and games based learning will establish a stronger foothold in classrooms as teachers realise just how powerful self-paced, self-assessed task oriented and problem based learning can be.

Probably the most important development I foresee though, is the emergence of student developed applications. As technology increasingly takes its hold on the school classroom, so students will become increasingly adept at coding. There is more scope than ever for children to experiment with computers. The Raspberry Pi is just the first of many tools to support this. The result will be the creation of a vast array of student games, mobile apps and eventually new forms of hardware (See this TED talk by 12-year old app developer Thomas Suarez). Many of the new apps and games will be made commercially available. Schools working in partnership with commercial companies will ensure it happens. We may even see some children achieve millionaire status before they leave school, and it will become commonplace for young people to be entrepreneurs before they reach higher education age. Now there's incentive.

A lot of learning comes from doing, making and problem solving. One of the most important contributions technology has made to education over the last decade can be found in its provisionality - that with digital, nothing is necessarily graven in stone, anything can be changed, upgraded, edited, revised, deleted. Learning in digital classrooms will be much more exciting, because learning through failure and experimentation will engage learners thoroughly in the right conditions.

Finally, a word of warning. We don't know how long these developments will take, nor do we know for sure  if they will materialise, because it is very hard to predict the future accurately, and schools are conservative places where change can be very difficult to achieve. What we do know is that the future will be very different from anything we can imagine right now. As ever, your comments and views on this article are very welcome.

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Digital classrooms by Steve Wheeler is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.

The future of classrooms

This is Part 4 in my series on the future of learning and technology. What will be the future of school classrooms? It is unlikely that we will see the demise of the classroom in the next decade. Those who study the future of education often suggest that the demise of traditional classrooms is not only inevitable, but imminent. This is due to the rapid proliferation of mobile technology, the disintermediation of traditional teacher and student roles, new trends such as MOOCs and the upsurge of user generated content on social media sites -  all of which take learning away from previously familiar territory. The argument that these tools and trends are removing the need for classrooms and 'schools' in specific geographical locations is a strong one, but also has some flaws.

In a recent article, Larry Cuban attempts to gaze 10 years into the future, and makes the case that classrooms will stay very much the same during this period. Firstly, he argues, teachers tend to use new technology in much the same way they used old technology, and that as a result very little has changed in terms of pedagogy. Secondly, he suggests that technology is overhyped and is not future-proofed, especially against 'major unplanned events', although what these might be, he fails to elaborate. Anyone who is familiar with Cuban's work will think 'well he would say that, wouldn't he?', but is he right?

One of the future developments he is optimistic about, however, is the lightening of students' backpacks. Cuban believes that the digitisation of texts (books, encyclopedias and other paper based knowledge) will take hold and become an important trend. He predicts the obsolescence of the hard bound book, at least in the hands of school children. Automated assessment of learning through computer adaptive testing is another trend he predicts, where students are given grades based on their performance on multiple choice questions. Implicit within this scenario is learner analytics, where the data mining of all student scores, attendance levels, social media postings and discussion group contributions can be analysed to provide teachers with an overview of where the student is, and whether any intervention is required. Also implicit within this prediction is the need for teachers to adopt new roles, change their professional practice, and move from instructors to facilitators and moderators.  It also means that teachers would need to revisit their concepts of knowledge and learning, and begin to accept that often learning occurs without their direct input, both inside and outside the classroom. Many teachers would welcome such a shift in practice, whilst many others might feel very threatened by such a seismic shift in the profession.

Cuban is very sceptical of online courses, and presumably his sceptiscism also embraces MOOCs. He believes that online learning has repeatedly failed to deliver its promise. His argument here stems from the human need to socialise, to gather together face to face, and learn firsthand the cultural, moral and civic values we hold so important in today's society. Online course, he argues, fall very short of delivering this richness.

Cuban sees a place for technology in schools, but does not see it radically changing the face of the 'place for education', and says:

'...by 2023, uses of technologies will change some aspects of teaching and learning but schools and classrooms will be clearly recognizable to students’ parents and grandparents.'

Is he right? Will we see no radical change in schools in the next 10 years? Will it take longer for us to witness transformational changes in our education institutions, or are the changes above sufficient to revolutionise pedagogy? Are schools too conservative and resistant to change to be impacted by new technology? Is technology the only catalyst for change, or should we look elsewhere? As ever, your comments on this blog are welcome.

Photo by Paul Shreeve


The future of classrooms by Steve Wheeler is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.

Tracking sentiments

Last year I flew via Amsterdam into Cologne, Germany to give a keynote speech at a large international conference. I arrived at the airport and made my way through passport control into the baggage collection area. Along with my fellow passengers I dutifully stood, waiting at the carousel, watching as bags and cases of all sizes, shapes and colours processed slowly by. Passengers began to collect their luggage and leave. I continued to wait. Decreasing numbers of passenger waited with me as one by one, they spotted their bags, grabbed them and made off to find their transport. Soon I began to get the sneaking suspicion that my bag wasn't going to arrive. This is what I sometimes refer to as 'baggonising' and it's something I am becoming increasingly familiar with. After I had been left standing along like a spare lemon at a cocktail party for a while, I admitted defeat, and walked over to the KLM desk to ask why my bag had not appeared.

The woman behind the desk checked, and then with a straight face informed me that there had been 'technical difficulties' at Amsterdam Schipol, and that my bag would not now arrive until tomorrow evening. She asked for the name of my hotel and told me it would be delivered directly to my room. All fine and good, but there was me standing there in my jeans and sneakers, and my best suit and shirt were in my luggage. In Amsterdam. Worse, my keynote was scheduled for the following morning, which left me in something of a dilemma. To say I was furious with the airline would have been an understatement. The plane I disembarked at Amsterdam was exactly the same plane I got into again to fly onward to Cologne. I recognised the crew. I got off the plane, trotted a mile or more across Schipol Airport and then got back on to exactly the same plane, but in the meantime my bag had been removed and left who knew where.

And so I arrived at my hotel, checked in to my room and then proceeded to tweet my problem to anyone on Twitter who cared to read it. I named and shamed KLM, and then went off to find something to eat. An hour later, to my surprise, KLM responded to me on Twitter, apologising for the mix up and advising me that I should go and purchase whatever I needed, and they would foot the bill. Wonderful. Clutching my credit card, I went off and bought a new pair of shoes, two new shirts, underwear, socks, shaving kit and toiletries.  I stopped short of purchasing an expensive new suit. I was wearing a serviceable jacket and anyway, KLM would probably only increase the airfares to compensate if I blew another 1000 Euros on a Ted Baker original.

The keynote went well and my luggage duly arrived the following evening. But how did KLM know to respond to my tweet? Answer - they were scanning for mentions of KLM on Twitter and other social media. This is known as sentiment tracking, a method that may well come in useful in education in the future. I'll give you some examples of how it's used now and how it works...

The Twitter example above is a very primitive form of Sentiment Tracking and Analysis (also known as opinion mining). It simply involves a KLM staff member regularly scanning the popular social media channels to intervene if there is any bad publicity or complaint, before it blows up into something unmanageable. Several tools are available for sentiment tracking on Twitter and other social media channels. Sentiment tracking is becoming much more sophisticated. Many large business do this now, because they want to know what is being said about their brand. They know that a complaint in a public forum can have a highly negative impact on their business if it's not dealt with quicky. But sentiment tracking can also be harnessed positively by businesses. Recently I wanted to buy some black, Italian hand made slip on shoes. I visited one or two online stores, and then without purchasing, I went off to do other things. An hour later, I searched on Google for some e-learning blogs, and landed on my first page. There at the bottom of the Blogger website this advert was staring back at me:

How did the system know how to target me? The online store (Amazon) had logged my IP address, and my interest in that specific product, and the fact that I had not purchased. It had probably sent a cookie. It assumed from this that I must still be interested. At the next available opportunity, Amazon targeted me with an advert through Google Ads via Blogger. The same applies when you mention something on Facebook, or simply let slip your date of birth, location or other personal information such as hobbies and interests. Before you know it, Facebook is pushing targeted advertising to your page, and it's highly effective. Facebook logs dozens of different items of personal data from your actions every time you visit, tag a photo, post a new status update or 'like' someone's comment.

I noticed the following three adverts on my Facebook page just now: You will notice that Facebook knows I am in the UK. It knows a lot more about me than that though. The last advert is because Facebook knows I am a Manchester United fan - that little detail is there in my profile somewhere. The middle advert is because it knows I am a guitarist, again from information in my personal profile. The first advert? I'm not sure why the first is there, because I have never let it be known that I wish to illuminate something 200 metres away from me. Perhaps someone else can shed some light on this. It's not in my profile that I like to bother pilots as they land their jet airliners, or that I have aspirations to be a covert operative for MI6. Sometimes sentiment tracking gets it wrong, and sometimes it just takes a wild punt and hopes for the best, a bit like playing Internet Battleships. But it could be a lot worse. Facebook might decide to send me links to a mature women dating site, or a wholesale Viagra dealer, just for a laugh. That would be hard to explain. Sentiment tracking is usually quite accurate though, picking up on your emotional statements, likes and dislikes, conversations, as well as links you have previously clicked. Sometimes it seems to take a random guess, as with the torch. But sometimes that guess can be disturbingly accurate.

How does sentiment tracking work? At the simplest level, the system uses Natural Language Processing techniques (NLP) to mine the words you type into your status updates or query boxes. At a deeper level, artificial intelligence applications capture the NLP data and process them into clusters that have collective meaning. A lot of modeling can be done with those kinds of data. Essentially, sentiment tracking makes sense of what you do on the web, and then transforms it into recommendations, actions or in this case, advertising. There are many problems with this kind of computation, including questions over how machines can differentiate between various emotional intensities, differentiate between polarities of opinion, or detect subjectivity in a statement. However, refinements in systems will continue to improve their accuracy.

When it comes down to group behaviour, sentiment tracking can be quite accurate. As we have demonstrated with our previous research into Technosocial Predictive Analytics (TPA), using a mashup of NLP, AI, GPS and geomapping, events such as flu epidemics and social movements can be tracked and even predicted quite accurately over geographical location and time. Have you ever shopped for a book on Amazon? You select your book and then Amazon displays a message saying something like '76 people who bought this book also bought...' and you suddenly realise that there's another book you didn't know about on a similar subject to your own purchase, and now you want that book too! It's a very effective marketing ploy, but there is also enormous educational potential. Amazon is using a form of crowd sourcing for its sentiment tracking, and is selling you a book you didn't know you wanted, based on the tacit approval of a cluster of people who are similar in their tastes, profiles or backgrounds to you. In effect, the individual acts of buying books, combined, create a desire line - a slime trail of social enzymes if you will -  that can be mapped and recommended to future purchasers of similar products.

Clearly there are opportunities to harness the power of these methods in education. Imagine students being directed to new and highly useful content they were previously unaware of. Imagine new content being created automatically on the basis of the actions of like minded scholars in dispersed locations. Imagine content being changed and updated automatically, based on the activities of a global community of practice. Finally, imagine being able to track the actions, content creation and decision making of your groups of learners, and mapping these onto information graphics to track their collective and individual progress, knowing when to intervene and when to let them alone. This kind of learner analytics (or educational data mining) will emerge from the collective intelligence of crowd sourcing and the sentiment tracking of individual actions and behaviour. The technology already exists. We now have to determine whether we want this capability in education, and if we do, we next have to ask what will be the ethical, pedagogical and social implications?

In the next blog post: How Google is refining your web search

Photo by David Sky
Other images by Steve Wheeler

  
Tracking sentiments by Steve Wheeler is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.

Uncertainty principles

It's extremely difficult to predict the future accurately, because as futurologist Ray Kurzweil once said, change isn't linear, it's exponential. I often consult The Horizon Report, which is published every year and attempts to predict what will be the widespread adoptions of technologies in education and training. The annual report is published after extensive consultation with an international panel of technology and pedagogy experts. Yet even this is problematic, because the farther you move away from the present, the more opportunity there will be for unforeseen and unpredictable events to occur. And experts are not infallible. You really have to turn to science fiction and read something like Isaac Asimov's Foundation Trilogy to appreciate some of the complexity associated with this kind of uncertainty. What does the future hold? We can't be certain, because right now it's imaginary. The Horizon Report is usually quite accurate in the 1 year cycle. When we examine the predictions in the 2-3 year cycle, it becomes a little hit and miss, and by the time we attempt to predict what will be widely available on the 5 year horizon, it becomes even more tricky to maintain accuracy. The farther out we move in projected time from the familiarity of 'here and now' the less accurate we are in our predictions.

I was invited to speak at the Learning and Performance Institute's annual conference - Learning Live - at St Paul's in London recently, on the subject of Learning Futures, and afterwards talked to Martin Couzins, who recorded the brief video interview below (yes, I know it says 'learning tends'... but perhaps that's a fortuitous error):



Uncertainty principles by Steve Wheeler is licensed under a Creative Commons Attribution 3.0 Unported License. Based on a work at steve-wheeler.blogspot.com.

Learner analytics

As was identified in the 2011 NMC Horizon Report ( I served on the advisory board of the UK JISC version), it seems that learner analytics is going to be a big thing for education over the next four to five years. Expect to see it emerging into mainstream practice in a number of versions, specifically aligned to the personalised learning agenda. From the report comes an explanation of learner analytics:

Learner analytics loosely joins a variety of data gathering tools and analytic techniques to study student engagement, performance, and progress in practice, with the goal of what is learned to revise curricula, assessment and teaching in real time. Building on the kinds of information generated by Google Analytics and other similar tools, learner analytics aims to mobilize the power of data-mining tools in the service of learning, and embracing the complexity, diversity and abundance of information that dynamic learning environments can generate.

Below is a very useful infographic developed by the Australian Open Colleges organisation. I think it explains just about everything you will need to know about learning analytics:

Image source 

Learner analytics by Steve Wheeler is licensed under a Creative Commons Attribution 3.0 Unported License. Based on a work at steve-wheeler.blogspot.com.