Time to re-load? Computational Thinking and Computer Science in Schools

April 26, 2012 — Prof. Rose Luckin

Snapshot—April 5th, 2012 In Chicago today the Obama re-election campaign is set to be the most technically sophisticated ever seen with voters being wooed via Twitter and Facebook, and digital technology along with those who understand how to build and use it set to play a key role in influencing people’s decision making. Across the Atlantic in the UK we face an abundance of choices about how to exploit and use technology, and this poses an enormous challenge for both the current and future education of our children. The realisation that we need people who can produce as well as consume technology has brought a new energy and excitement about computer science and computational thinking, which is being heralded by some as the new literacy of the 21st century. The technology revolution has changed the way many of us work and interact, it has generated new industries and new
businesses, and it is natural that we now look to schools, teachers and the education system to help us to understand how we might best prepare our children to live, work and make best use of what computer technology offers.

But how best can we do this?

A mess? 2012 has seen the Secretary of State for Education state that “ICT in schools is a mess” and he has called for a new approach with the hope that technology can be used creatively to develop curricular content: the ‘wiki’ curriculum. What is happening with ICT and computer science education in schools has also been the subject of a 2011 Naace report entitled “The Importance of Technology”, an Ofsted report on ICT in schools, and the importance of providing young people with the skills required by the new workplace is captured by Nesta’s Next Gen report. Clearly there is growing concern and government commitment to change, so what change should we make and why?

Is Computer Science the answer? Computer science is an important element of the debate. The Royal Society’s 2012 ‘Shut down or restart?’ report suggested that a sound understanding of computer science concepts enables people to get the best from the systems they use, and to solve problems when things go wrong. However, computer science is evolving rapidly and its interdisciplinarity means that its evolution touches on many domains and every day life. There are significant challenges for those interested in how best to include it in the curriculum.

Are we sure we know what we want to change? There is already some excellent teaching of ICT and computer science in some schools within the current curriculum and programme of study, so not everything is wrong. Care needs to be taken that the changes we make do lead to a better learning experience at school: an experience that inspires and educates. But, are we clear about what is wrong with computer science and ICT in schools now? Can we be precise about the rationale for what learners at different stages need to be taught? What do we want learners to be able to achieve as a result of studying computer science? Where do ICT and computer science fit in the structure of the school curriculum: media, design, science, cross-curricular?

How can learners tap into the power of computational thinking? The skills of computational thinking can be taught with or without computers, by exploring how processes work, looking for problems in everyday systems, examining patterns in data, and questioning evidence. With a computer, learners can put their computational thinking into action. Could a focus on computational thinking better equip learners to use their understanding effectively and to learn how to apply a range of computing tools? Writing the code that makes a computer behave in a particular way is a creative pursuit: reflecting on what you have constructed is a key part of learning. We may therefore valuably ask: How can we develop good computational thinking for children?

Are we looking in all the right places? Are there less obvious areas of research that might help us answer some of these questions? For example, many people encounter the experience of Flow and are all too familiar with the experience of losing themselves in a task. Might the idea of Flow itself help us understand the learning process in computational thinking and computer science? Researchers in the psychology of programming have spent decades exploring how people learn to code, surely their expertise needs to be drawn into the debate?

There are no short cuts to answering these questions. The process of addressing them requires an interdisciplinary and participatory approach that involves groups from across the sectors that is inclusive in nature and powerful in design. This will require an approach that is new to society, schools, teachers and learners: a process that must be both flexible in its thinking and realistic in its understanding of the role of schools.

Tomorrow we will be having a debate about some of these issues at the London Knowledge Lab and I’ll report back on how that goes.

Read our briefing paper (from which the above text is taken)

Follow the event through illuminate – go to http://link.lkl.ac.uk/e-meeting for access to the live stream.

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Let’s talk about what the research says: Industry, Academia, Learning: 7 days to go

March 23, 2012 — Prof. Rose Luckin

Vanessa Pittard DfE, Richard Noss TEL Research Programme Director, BESA, Intellect, ALT, and Demos about research inspired technology enhanced learning to tackle challenges from teenagers’ energy consumption to social communication in a multimodal virtual environment for youngsters with Autism Spectrum Disorders. What the research says event at LKL now has a waiting list for places! Clearly people do want to talk.

Speak to Me

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Squares in a round world: has research about technology and learning passed its sell by date?

February 20, 2012 — Prof. Rose Luckin

I really enjoyed my trip to see the David Shrigley Brain Activity exhibition at the Hayward. And was amused by the endearing hand drawn animation about new friends in which a square enters a round world and … well I won’t spoil it for you. But it made me wonder if researchers run the risk of being squares in a round world. This was prompted by the comment I mentioned in my last post that asked if technological pace was “making traditional research models and institutions look a little archaic?”So has research passed its sell by date in this fast-moving technological space and do we need to re-fashion ourselves out of our squareness, or help squareness to be better appreciated? What do us squares have to offer? Four sorts of research come readily to mind and I am sure there are more.

First, there is basic research about how people learn and about the nature of learning itself that can be applied to education in a digital world, both in terms of how to develop technologies and in terms of how to use technologies for learning, both informally and formally. This research does not go out of date but gets better and better, for example John Bransford and others work on the nature of transfer is mature and well grounded, it is rigorous and has developed over several decades. Perhaps one the reasons that research like this is timelessly useful is that it has a focus upon an ever-present issue: the nature of learning, rather than a changing space: the nature of a particular technology, category of technologies, or indeed particular practices. It is also the case that all those who are doing this research and all those who want to use this research share a common need: to understand more about how people learn. However, there is perhaps a need to better communicate this research in a way that makes it accessible and relevant to technologies as they change.

Second, there is research conducted by those who want to see how the learning and/or teaching process might be better supported through the use of technology. This research can also maintain its value, for example, if it has a focus upon the interactions that are important for teaching and learning and the manner in which different technologies do or don’t support that, rather than how to use a particular technology. Good example here are example Diana Laurillard’s classic work in her book Re-thinking University Teaching and the community of researchers who consider the nature of Instructional Design.

Thirdly, is the work done by those within research labs both in universities and companies that involves developing a technology and using it with learners and teachers, usually in small numbers, to see if it helps them to learn or teach so that learners learn more, or feel more motivated, or collaborate with others in a more supportive manner, or in answer to many other varieties of question. It is harder to see from the usual outputs from this category of research how it can be easily applied within practice, either informal or formal. One of the main reasons for this is that such research is about generating new technologies that are not yet in classroom and may not ever make it outside of the research lab. I have seen hundreds of such research projects very few of which see the light of real application. Sometimes they are only ever intended as a proof of concept to motivate some further research activity, but sometimes they are fit for purpose, but it is not the role of the research lab to take them into a development phase. There is a huge gap here between research and practice that means that many valuable research projects never get tested outside of small scale studies, but that is the subject worthy of more space than I have here.

Fourth, and finally for now, there is research that has a focus upon a particular technology, Video, Integrated Learning Systems, or Learning Platforms, for example. The currency of this research is more limited to the particular technology in question and therefore much more likely to go out of date. Although it has to be said that such research can also provide more generalisable findings: such as that about Integrated Learning Systems, which highlighted the impact of a learner’s context upon the efficacy or not of the technology, in this instance Integrated Learning System.

Research may be square, but most of it is not archaic. Squareness is good, but its beauty is currently only appreciated by a small community and that community needs to find better ways to get the word out to the wider world. At the same time that wider world has something valuable to contribute in the form of innovative practice and communities of people who use technologies in innovative ways and record their experiences in blogs, tweets and forums. Us research squares could do well to pay more attention to what this research in action has to contribute.

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Heads in the Cloud

January 30, 2012 — Prof. Rose Luckin

At a quick glance one might think that the title of this post means that I am thinking about the 2004 romantic drama with  Charlize Theron and Penélope Cruz

…and I do love films, as anyone who knows me will be aware.

However this post is about ‘Heads in the Cloud’ as opposed to ‘Head in the Clouds‘ and refers to the technological cloud that lets us connect with resources, people and applications from almost anywhere, without having to lug loads of technology around with us. Not that long ago, the idea of being able to access sophisticated computation and almost limitless information without needing to know where all this stuff is would have been nothing more than a romantic glint in the eyes of computer scientists and engineers. Now it is a reality: an important reality for learning. The implications of the cloud were the subject of a panel organised by Brightwave at the Learning Technologies exhibition.

When thinking about the panel it struck me that there are some useful things that research can tell us about how people think and learn that might help us make the best use of the cloud.

Firstly, technology driving learning closer to the workplace means that we can help learners to transfer and apply what they learn to their work.  We know that learning through a variety of real world experiences can help people to use their learning flexibly and effectively. The cloud enables learning across a variety of these all important real world contexts.

Secondly, there are important generational differences in the way that people use technology in their everyday lives. Young people in particular are early adopters of new and emerging technologies. These technologies can increase engagement and empower people with a feeling of control. We can therefore use the cloud to recognise and benefit from the expectations and skills that younger people bring to learning and the workplace. The cloud can be used to support on demand learning for example.

And thirdly, theories of socially distributed cognition show us that people can learn effectively in groups and that people can offload some of their thinking through tools, such as technology, and through other people. The cloud can help us to bring people and technologies together to make the most of these collaborative learning opportunities that can help people to learn in this distributed manner.

The panel audience thought that cloud technologies could be used to create a knowledge environment that encourages sharing and that learning designers would need to focus upon continuous learning. However there were also concerns that it would be difficult to prove what knowledge had been acquired, which suggests that new forms of continuous assessment, and self-assessment, might also be needed.

So the cloud for learning is about multiple heads in the integrated and single cloud, working together to solve increasingly complex problems and learning whilst they do so, using the technology to capture evidence of that learning. This is not a romantic notion, rather it is an achievable and desirable vision.

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