My visualisation for Block 2 ‘Teaching with Data’ stems from Raffaghelli and Stewart’s (2020) recommendation to expand data literacy to include critical, ethical and personal dimensions as well as technical proficiency. Raffaghelli and Stewart explain that most of the focus in education so far has been on training teachers to be more data literate, and to make more use of abundance of data available to them. Taking this concept on face-value, I chose to experiment with an uncritical acceptance of digital data for 24 hours. For one day, I enabled every available push notification on my smartphone and recorded what I received. Within this visualisation, I also attempted to categorise the notifications into those that were purely information based, those that were attempts to pull me back into the app, and those that were direct targeted ads. The result was a very disruptive and frustrating day, as I frequently dismissed notifications that were largely irrelevant.

While this 24 hour experiment is a tenuous and somewhat crude analogy of how teachers are affected by datafication, it allowed me to surface contentious discussion points often raised by educators. Through experience and training, teachers continually strive to develop and improve their practice. They will often draw upon the softer skills of teaching such as humour, empathy, and personal judgement to engage students in learning. However, in a world where decisions are increasingly informed by big data sets, these autonomous teaching practices can be seen as ineffective and inefficient. As stated by (Van Dijk, Poell & de Waal, 2018), “Datafication and personalization are pushed as the mantras of a new educational paradigm where human judgment is increasingly replaced by a product of predictive analytics”.

The use of digital technology in education seems to have gone well beyond our supplementary ideals. Driven by rose-tinted views of the potential of big data, educational infrastructure has largely been moved into the cloud and teaching and learning practices are increasingly being shaped by the feature sets of the technology available. As summarised by  Harrison et al., (2020: 402) “It seems we cannot now think or experience education without thinking or experiencing data”.

So how does my visualisation relate to the teaching with data? While as an individual, I have a lot of autonomy over what data I choose to use and engage with, this isn’t quite the same in education. The way that schools operate – and in turn teachers teach – is increasingly becoming a reactive process in response to metrics such as university league tables and student feedback. This is referred to by the term ‘performativity’ by Harrison et al., (2020). Whilst not direct measures of teaching, these learner focussed metrics are then frequently used as proxies of effective teaching. So in the case of my notifications dashboard, dismissing or turning off these notifications could be seen as bad practice, or at least not using data to its potential. More desirable action would be to look at the notifications through an essentialist perspective, believing that there’s lots of potential there that I should be able to utilise if I invest more time in the ecosystem.

There is a danger that in order to respond to these metrics in a way that scales, teachers will be put under pressure by their institutions to change their pedagogies to ensure everything fits on the digital platforms that are required to generate the data demanded to assess learning. (Williamson, Bayne & Shay, 2020). It appears that the argument against teacher autonomy is not only compromised at an institutional level, but also at a national level as governments are also endorsing platformisation whilst ignoring academic autonomy (Van Dijk, Poell & de Waal, 2018).

What is needed is a more critical view of datafication, where teachers are encouraged to challenge assumptions made by predictive analytics and learning dashboards. This should include more transparency over big data practices and the risks and implications associated with it, which can in turn empower more responsible use of technology in future (Sander, 2020).

Throughout my education, some of the most influential teachers were those who had strong personal values, used humour, and at times probably used unorthodox pedagogies to engage students. However, it now seems that these personal values are being lost to as they don’t easily reduce down to data entities or scale up to repeatable practices that can be enacted through digital platforms. It now seems that the ‘good teacher’ is defined as one that is familiar with their data and responsive to it. Harrison et al., (2020: 405).

Bibliography

Harrison, M.J., Davies, C., Bell, H., Goodley, C., Fox, S & Downing, B. 2020. (Un)teaching the ‘datafied student subject’: perspectives from an education-based masters in an English university, Teaching in Higher Education, 25:4, 401-417, DOI: 10.1080/13562517.2019.1698541

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, DOI: 10.1080/13562517.2019.1696301

Sander, I. 2020. What is critical big data literacy and how can it be implemented? Internet Policy Review. 9(2) DOI: 10.14763/2020.2.1479

van Dijck, J., Poell, T., & de Waal, M. 2018. Chapter 6: Education, In The Platform Society, Oxford University Press

Williamson, B. Bayne, S. Shay, S. 2020. The datafication of teaching in Higher Education: critical issues and perspectives. Teaching in Higher Education. 25(4), pp. 351-365.