Monday, March 03, 2014

Horizon Scanning – bears really do shit in the wood

Horizon Scanning is a popular sport these days. Commission a report, by people who scan for the opinions of others on the web and out pops a report that is invariably a statement of the bleedin’ obvious. You too can read that the Pope is a Catholic and that bears do indeed shit in the woods – social, mobile, MOOCs, cloud, 3D printing, wearables – ho hum. How can we avoid this?
1. Focus on starting line
Let’s not start with a distant technological horizon but change focus and first up, have a good, hard look around and ask that age old question “To what problems are these emerging technologies a solution?’ Flip the issue and ask about the top ten learning problems to which technology is a solution. This will lead, not to a predictable list, of what technologies just appear, which any fourteen year old can tell you about, to a more relevant list of technologies that could solve problems in learning.
2. Ask what inhibits learning?
How about the Top Ten specific inhibitors to learning in, say, Higher Education? Take the lecture, long-form essay, poor formative feedback, agricultural calendar, low occupancy buildings, one intake per year, crisis of costs, crisis of relevance, poor teaching, poor CPD….. these are just some of the commonly debated weaknesses in the existing model. These should be our starting points, not treating technologies like ballista balls being fired over the walls at academe.
3. Don’t see technology as disruptive i.e. dystopian
When you read between the lines, these reports betray a view of technology as ‘disruptive’, which many in education read as dystopian. Technological advances are seen as an annoying nuisance that has to be ‘coped’ with, rather than just real progress in the real world. The future is the ‘other’, to be feared rather than embraced and welcomed. In truth, education barely uses the technology of today, never mind the technology of tomorrow. Don’t horizon scan, start with what’s your students currently have and do.
4. Abandon deep-rooted conceits
The reasons for this dystopian bias lie in several deep-rooted conceits in education and training. These conceits are, 1) teaching is always good and anything that threatens teaching is bad, 2) teachers are special and that anything that threatens teachers is bad, 3) teaching is a necessary condition for learning, and 4) face-to-face contact is a necessary condition for learning. None of these are true but all are deeply held, basic assumptions, if not prejudices, in education. We need to face up to the hard fact that technology changes some of these assumptions.
5. Think of technologies that will NOT work
Really smart prophets are those who know what technologies will NOT work in learning. I’m on the side of people like Steve Rayson at Kineo who consistently derides those who see mobile learning as some sort of inevitable pedagogic force. I’ve seen reports that have gone gaga on, say 3D printing, yet when it comes down to matching this with real learning, it all seems a little lame. Don’t just scan for everything that appears, be highly selective.
6. Don’t set up a quango
Whenever ‘institutions’, ‘quangos’ or ‘ centres of excellence for technology’ are put in charge of technology in learning, the whole business gets institutionalised and yet more committees and reports get produced, with yet more dilution. The virtual world of technology is not usually well served by physical buildings and organisations.
7. Keep it simple
What’s needed, rather than endless Horizon reports, are a few hard policy decisions around mandated, online solutions, so that the system can ‘plan’. A good example is the just announced 10% online in courses by 2015/16 rising to 50% online by 2017/18 in the FELTAG report for Further Education. We could mandate minimum levels of bandwidth in educational institutions. We could stop ‘banning’ and ‘blocking’ things. This is a hard-nosed catalyst or stimulus for action, something the Principal and CFO of a college can work with and plan to. The technology will fall into place if the planning is right.
Conclusion

It is this matching of problems with solutions that can lead to good predictive policy, rather than committees, chosen not on merit but on who knows who, in government – the usual suspects, some very suspicious indeed. Think in terms of solutions to problems and stop the endless stream of Horizon reports with endless streams of isolated recommendations that remain isolated and fragmented. It’s all about decision-making and action.

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