Data – very little changed
The idea that we are blinded by a ‘fog’ is to assume that there is a blind spot in our understanding as educators that can be ‘made clear’ by data. Such an assumption is itself a product of recent orientations towards ‘learning’ as a central concern, and a subsequent marginalisation of teacher expertise.
(Knox, J., Williamson, B. & Bayne, S. 2020. Machine behaviourism: future visions of ‘learnification’ and ‘datafication’ across humans and digital technologies, Learning, Media and Technology)
This is a short follow-up blog to my last one about how the judicious use of data helped turn around a school.
As I said, the use of data was hugely successful on many levels. Yet, very little actually changed in the classrooms. I want to briefly explore this fact.
Before we embarked on the introduction of data tracking systems, the school functioned on an individual level. Pupils succeeded and went on to secondary schools. Job done? Yet, there was a palpable feeling that this wasn’t enough. The school had no point of reference. We had an idea we were a good school, yet no proof apart from a handful of scholarships to secondary schools. What about the the middle ability children? What about the children who need learning support? Did we even have the right children on the list for learning support?
The data showed us that we had been on track all along, yet gave us the information and the confidence to make a few tweaks, that changed the good school into an outstanding one. Very little changed in the classroom; teachers were imaginative and creative in their lesson planning and execution. We avoided the marginalisation of teacher expertise, which can be a product of over-datafication. Classes had a great atmosphere of constructive learning and that didn’t improve or change with the introduction of data into the school life. The data was not merely ‘a technical fix’. (Eynon). Luckily, the school was already enabling the children to learn SOMETHING for a PURPOSE from SOMEONE (Biesta). We were not suffering from learnification and nor did the datafication of the school lead to learnification; we managed to avoid reducing the learning to merely good outcomes.
The data was used with judgement to support and justify decisions we made in the running of the curriculum, but it did not dirve the decision making. As a result, we managed to keep our educational purpose along the lines of Biesta’s theory that it should be about the develpment of the WHOLE child, not just as a system of learnification outcomes.
It is interesting that I am able to think back to what we managed to do with the data and see that inadvertently, we succeeded to achieve an educational scenario that is backed up and described in the papers I have read on the IDEL course.
Nice reflections pointing to the importance of teacher judgement – supported by data. But does this also suggest that the data approach only led to a better presentation of the school and hence a shift to ‘outstanding’ or did it change other educational practices – in admissions, in student support etc? I liked your comment about maintaining your educational purpose as a counter to the view (common in data science) that the ‘data will speak for itself’ as if there are no choices about which data to collect, how to analyse it and, as you emphasise across the two posts, how it will be used.