Like many other sci-fi fans, I was looking forward to the anticipated release of Isaac Asimov’s Foundation adaptation into a TV series. One of the key characters, Hari Seldon, is played by Jared Harris (a memorable Moriarty in Sherlock Holmes: A Game of Shadows); although - spoiler alert - he dies early in the series, his influence is all-encompassing. A mathematics professor, he has developed the (fictional) science of psychohistory, which, given a large enough population, makes general predictions about future behaviour. Yes, the Moriarty chess master is linked with the psychohistorian Seldon.
Still from the “Foundation” series. (Credit: Apple TV) Via BigThink
Why am I starting this post, after a long (too long, I admit) hiatus with these references? Because at UWCD we have been looking at how to use data more effectively in order to allow us to support our students better. I am a confessed geek, but by no means a data scientist, so I hope that any data scientist that may come across this blogpost will forgive me for any blunders here.
The Theory of Knowledge teacher in me is very aware that human sciences are different from natural sciences because of the human dimension. Apart from the ethical considerations that prevent us from some experiments, the fact that we are dealing with humans studying humans means that there is always an additional layer. I have greatly enjoyed Kahneman’s recent Noise: A Flaw in Human Judgment, which explores this in detail, focusing on the issues of noise and bias. According to Kahneman, in order to “improve the quality of our judgments, we need to overcome noise as well as bias”, for which he recommends what he calls “decision hygiene” (Kahneman 2021:7, 9).
Applied to education, this means that we need to have solid data to check our natural biases and to reduce the amount of noise present in any human organisation so that we do our best not to fall into the temptation of thinking that our instincts are honed in and that we always know what is going on.
At UWCD we are exploring both collecting better data and connecting it in order to develop a better understanding of each of the students entrusted to us. This goes from academic baseline testing to monitoring engagement in our learning programme to monitoring wellbeing. As of now, we are already using:
Komodo, a dedicated wellbeing monitoring tool that students can access via a dedicated app to complete surveys and, when needed, request help;
REACH, a boarding school software platform that we are using not only for check ins and leave permissions, but also to manage trips;
Finally, we are developing our own tools to capture some of the qualitative data that cannot be collected via these tools, for example, to provide mentors with updated information that they can use during the upcoming parent-mentor meetings
For those of us working in education, it is clear that there is a realisation that “big data” will have an impact on education. At the same time, the Facebook saga shows us clearly that data is a tool that can be used for different purposes, like a hammer or a knife.