Monday 25 April 2016

Learning Analytics: What we have and what we need

It's an unfortunate tendency of educational technology to take a form which reinforces existing practices in education. So we have the 'giant photocopier' of the VLE, the 'giant classroom' of the MOOC, 'giant assessments' of MCQs, and increasingly 'giant marking' in the form of automatic essay assessment and plagiarism detection. As we've become beholden to the problems that technology is able to solve (and which it consequently creates), our institutions have been drawn into a 'production line' mindset where every student is cash, we have lost sight of what we actually need.

With the dismal application of computers in upholding ancient practices (and power structures), the greatest tragedy of all this is that we lost trust in computers: that they are forever tarnished with ramping up bureaucracy and surveillance and diminishing freedom.

Standing back to consider what we need in education means standing apart from the madness that has become education. When we look at the real problems, they are not expressed in terms of marketisation of institutions, or problems with retention. Rather they are expressed in terms of social alienation, inequality, lack of opportunity, fascism, terrorism and the collapse of trust in institutions. Somehow we have to look at these problems.

Then we should turn to our tools. What tools do we now have? The simple fact is that the technologies we have today are amazing: they are far more powerful than our parents had at their disposal when dealing with their complex problems. Moreover, they are cheap and ubiquitous. Whilst big data has its downsides (which Wikileaks can attest to), machine processing of data, whilst not intelligent, performs not far behind the dreams of science fiction.

The point is, if these technologies were applied to real problems, rather than upholding ancient institutional structures and vested interests, how much better could we make the world?

I think communication and teaching and learning would be top of the list if we were to get to the heart of where things currently go wrong. Communication is a more complex process than the sending of tweets or emails. The quality of intersubjective understanding and empathy which emerges when we engage face-to-face occurs under conditions which are poorly understood. The 'dance' of engagement between a teacher and a learner, as the teacher tries to work out where the learner's "blockages" are is something that is far more difficult to coordinate at a distance. Why? What might we do about it?

Are there not things we can do to amplify latent signals in communication which might give a teacher a better indication of where specific pedagogical blockages might be? Are there not things that we can do to help the teacher manage the diverse complexity of many learners with many different needs? The answers to these questions are not just technical. They require a rethinking of pedagogy too. But our technologies can give us deeper insight into each other if we let them.

Learning analytics today seems concerned to keep learners on courses, or to help the design of new courses where learners are less likely to drop off (or out). But just because learners stay on a course doesn't mean that good education is going on (the best educational action might be a decision to leave!). Analytics is post-hoc and market driven - and increasingly keeping learners on courses means keeping teachers in chains.

Education is relational. We could use our technologies to help us monitor (in real time) the health of our relations - much as ecologists now monitor the health of ecosystems. If we attempted this, we might start to question the ecological relations between students, institutions, markets and governments. 

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