Learning Analytics, Ethics, and Dutch Uncles

“There is an old expression, ‘a Dutch uncle,’ which refers to a person who gives you honest feedback.
Pausch (2008)

There was an interesting discussion about learning analytics today. Should you do it in an academic context? For example, track students progress with the aim to improve courses, but also to provide students with individual feedback or even more direct interventions?

It raises the specter of the always watching policemen, checking whether students actually do their job (after all, studying is their job). But on the other hand, it might provide students with a necessary reality check.

For me, it’s a no-brainer: Of course you should. I agree with the second position in this overview on Analytics:

«On one hand, institutions might be vulnerable to charges of “profling” students when they draw conclusions from student data; on the other, they could be seen as irresponsible if they don’t take action when data suggest a student is having difficulty.»

Thing is, technology is value neutral:

Scientific and technological progress themselves are value-neutral. They are just very good at doing what they do. If you want to do selfish, greedy, intolerant and violent things, scientific technology will provide you with by far the most efficient way of doing so. But if you want to do good, to solve the world’s problems, to progress in the best value-laden sense, once again, there is no better means to those ends than the scientific way.
Richard Dawkins

Or to put it differently, an Adolf Eichmann would have been very happy with Excel. The people in the cells — not so much. But that’s no reason to stop developing spreadsheet software.

And yeah, what we do with technology does matter. The application is not value neutral. Or as Isaiah Berlin put it when talking about moral relativism:

«I am not a relativist; I do not say ‹I like my coffee with milk and you like it without; I am in favor of kindness and you prefer concentration camps› — each of us with his own values, which cannot be overcome or integrated. This I believe to be false.»

To use a current example, there really is a difference between gays hanging out in bars, or from cranes. We do have a responsibility for what happens.

The question is: where are the lines? And, for the thankfully less grave subject we’re talking about, what do we think university administrators will do with the data? Or the PhDs and Profs?

There are applications for misuse. Need to do more with less resources? Invest heavily in the students whose profiles suggest study success — and ditch the rest. The risk to waste precious resources is too great. Want to do mostly hassle free advisory? Check the grades of the students and reject any students with less than stellar grades. It’s very easy to use the findings as a filter of whom to keep and invest in, instead of finding out who needs support — usually different kinds of support.

Frankly, I think university departments need a “Dutch Uncle” for the students. Someone who gives them honest feedback — based on actual data. And yeah, attendance (even if not mandatory) and grades do provide a pretty clear picture. Bad grades do not mean the student isn’t suited for university, but it usually strongly indicates that current methods to learn and perform aren’t working well.

And these things can be improved — if you know about them.

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