Block 2: ‘Teaching’ with data / Week 7
This week, I was very tired. I drew the ebb and flow of my energy over three days. Those are the lines you see below.
The icons were added after I drew the lines. They were an attempt to reflect upon and codify the circumstances around my wavering energy levels. Activities like eating or travelling were easy to classify and see links to changes in energy level. Yet by attempting to codify what was happening, I felt like I simplified the complexities of the circumstances. Especially the attempt to codify what was happening “in head” – I immediately regretted reproducing this superficial CBT-style classification of thoughts and emotions. The assumption that you could read this data and make connections between my activities, thoughts and energy levels over three days reproduces an intrumentalised approach to human psychology that I personally only find occasionally useful.
This activity made me think about the assumptions and norms that inform the datafication of education, and the instrumentalised forms of behavioural and educational psychology that these can draw from. I agree with Raffaghelli & Stewart (2020) that approaches to ‘data literacy’ for teachers should interrogate these assumptions and norms and what they reinforce and represent. What data can ‘show’ you about your students is not just a partial or simplified view, it is a view that might reinforce harmful or misrepresentative views of your students, based on particular pedagogical and psychological assumptions.
References
Raffaghelli, J.E. & Stewart, B. 2020. Centering complexity in ‘educators’ data literacy’ to support future practices in faculty development: a systematic review of the literature, Teaching in Higher Education, 25(4), 435-455.
Jeremy Knox says:
‘I drew the ebb and flow of my energy over three days.’
Really like this idea. For me this connects really well to the critique of the drive for efficiency that is often bound up with the promotion of data-driven tech. In the endless drive for efficiency (and the ‘home working’, everything-will-be-ok-with-tech kind of rhetoric is part of this), we so often seem to overlook that fact that bodies get fatigued. Where we might want to correlate the time a student has spent with a particular resource with the outcome of their assessment, why wouldn’t fatigue be factored in? This seems to be another useful way of acknowledging the embodied practices of education that you’ve explored previously – excellent work.
As you suggest, codifying fatigue is less straightforward than it sounds, and would then seem to further envelope the student in pervasive surveillance.
‘The assumption that you could read this data and make connections between my activities, thoughts and energy levels over three days reproduces an intrumentalised approach’
The emotion classification certainly does this. I suppose one could link this more directly with ‘thinking’ in relation to a specific course and its themes, although that might produce equally questionable correlations with energy levels. I suppose, as a teacher, it would be interesting to have a sense of what ideas ‘energised’ students, but I expect that measure might end up being a bit superficial.
‘What data can ‘show’ you about your students is not just a partial or simplified view, it is a view that might reinforce harmful or misrepresentative views of your students, based on particular pedagogical and psychological assumptions.’
Good point, and this picks up on what I think is a shift in thinking in recent years, following what are increasingly powerful data-driven technologies. I think there has always been an awareness of data providing a partial view, but the shift to seeing that incompleteness as damaging is still a message that, some people at least, feel is not acknowledged enough. And I think that idea of harm is being construed from the ways that data, perhaps now more than ever, can powerfully intervene in our lives.
March 2, 2021 — 3:54 pm