Problems with the fusion of  big data and education

Last Updated on December 27, 2017 by

The first problem is that it will be more difficult for us to forget and escape our past….

While we as individuals grow, evolve and change, comprehensive educational data collected through the years remains unchanged – there is a problem that as the amount of data collected on us through our formative years, we might be judged in the future by this historic data – creating a kind of ‘permanence of the past’.

Our historic data record might show a future employer that we were enrolled in a remedial math class in our first year of university, and this fact alone might put them off calling us for interview, even if our maths has evolved in the intervening years, which means we might get credit for how we have evolved in our later years.

The problem with data is that it is unlikely to tell anyone about the context in which it takes place – if test scores are low during particular years, for example, the data alone is unlikely to tell us what was going on more broadly in our lives at that time – unlike today, when we can effectively forget low-periods in our lives, in the forthcoming age of big data, they will always be on display for anyone to scrutinise, without access to the more in-depth context.

Employers already track Facebook posts, if there is more educational data, then they might well delve into that too.

A second problem is that our big data record might fix our future…

Today schools make predictions based on ‘small data’, yet students can argue against the paths suggested by such small data (GCSEs etc) because it is precisely that, small, collected at only a few points in time, clearly not telling the whole story.

In the Big data age, however, predictions based on more data may become so accurate that they lock students into educational tiers of particular programmes of study – some universities are already experimenting with ‘e-advisors’ – since the University of Arizona implemented such a system in 2007, the proportion of students moving on from one year to the next has increased from 77% to 84%…. In future these systems may evolve to advise, or prevent, students from undertaking particular courses of study deemed to be too difficult for them.

This may lock-in students to pre-determined study and career paths, which may have a detrimental effect on equality of opportunity.

A third problem, largely dismissed by Cukier, is that the fusion between big data and educational institutions will only work if students and parents consent to tech companies having access to their children’s private data. For some reason he cannot see the problems with this, which suggests more than anything else he’s an industry-insider.

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.

%d bloggers like this: