Why Talk About Data (in Education)?

 

An Online Colloquium

12th-19th November 2020

What does data do in education? What does it become? Why does data visualisation matter? What might teachers do with data?

This online colloquium will generate debate about the role and purpose of data in education. It brings together researchers whose work, in different ways, raises issues about data use in schools, coinciding with the launch of a virtual exhibition produced through a British Academy funded project, Doing Data Differently, which showcases teachers’ data drawings about their everyday experiences of literacy teaching.

A series of short video think pieces will be released daily between 12th and 17th November 2020 from Helen Kennedy, Neil Selwyn, Luci Pangrazio, Gemma Moss, Lyndsay Grant, Alice Bradbury, Cathy Burnett and Guy Merchant. These can be accessed via the virtual exhibition – you will find more details on the Exhibition Events page.

Issues and questions arising from the think pieces will be discussed at a live panel   on 19th November 4.30-5.30 (GMT) chaired by Marjorie Siegel from Teachers College, New York. Panel members will include Alice Bradbury, Lyndsay Grant, Cathy Burnett, Guy Merchant and Stefanie Posavec, co-author of Dear Data . Please register for the panel on Eventbrite.

Think pieces include:

Data harms and inequalities

Prof Helen Kennedy, Professor of Digital Society, University of Sheffield

Data-driven technologies, automated and algorithmic systems, machine learning and AI are transforming society. They’re having wide-ranging effects, including numerous benefits, but they’re far from straightforward, and their use can result in harms as well as benefits. So we need to question claims that datafication will simply lead to a better society. In fact, it feeds into and is fed into by inequalities. Whether we talk about harms, inequalities, discrimination, bias, injustice or unfairness, the negative effects of data-related change and data-driven systems are not experienced equally by all. This is why we need to talk about data in education.

 

Deconstructing data traps: Where to draw the line?

Prof Gemma Moss, Professor of Literacy, and Director of the International Literacy Centre, University College London

This think piece sets out some of the issues a team of researchers at UCL have faced in documenting how English primary schools have dealt with the stresses and strains that COVID-19 has produced in our data-driven system. I will consider how and in what ways our research project findings might be able to disrupt the dominant narratives about system gaps and the urgent need to close them that the crisis has provoked.

 

The surprising non-appearance of the datafied school?

Prof Neil Selwyn, Professor of Maths Science & Technology, Monash University
Dr Luci Pangrazio, Research Fellow in Digital Literacies, Deakin University

This presentation considers an unexpected finding from our ongoing research into digital data use in Australian high schools – why is it that critical concerns over the steady ‘datafication’ of education are not readily reflected in current school data practices? We first identify apparent tensions between: (i) established ‘teacherly’ logics of ‘data-driven’ schooling; and (ii) emerging ‘datafied’ practices associated with digital systems, platforms and devices. In particular, we consider how promises/threats of digital dataism appear to be largely subsumed into prevailing institutional logics of state bureaucracy and professionalism. We then consider the extent to which these ‘school data’ logics can endure amid the increased digitisation of K-12 education and commercial pushes for personalised learning. Alternately, what scope might there be to encourage more resistant appropriations of digital data by otherwise marginalised groups within school communities?

 

Anticipating fair futures through educational data practices

Dr Lyndsay Grant, School of Education, University of Bristol

In this talk, I will draw on ethnographic research in a secondary school to explore how data came to play a role in shaping educational practices through defining what could be known about pupils, teachers and learning, and through determining the future outcomes that were made possible. This research raised questions about the role of data practices in shaping ‘fair’ future outcomes for pupils and limiting the possibilities of more open-ended educational futures. These questions can help us explore how claims of ‘unfair’ educational algorithmic decisions might reveal contested notions of how fairness is produced through data, and the limits of transparency as a response to questions of fairness.

 

The Five Ps of Datafication in Schools

Dr Alice Bradbury, Associate Professor in Sociology of Education, UCL Institute of Education

In this short film, I use a schema to discuss the impact of datafication which is based on five Ps: pedagogy, practice, priorities, people and power. This draws on my forthcoming book Ability, Inequality and Post-pandemic Schools (Policy Press, 2021), which examines the relationship between data and discourses of ability. In this talk, I give examples of how we can use these five categories to broaden out how we conceptualise datafication to include teacher subjectivities and relations of power, as well as what teachers do and care about.

 

Destabilising data: Creative data visualisation and professional dialogue

Prof Cathy Burnett & Prof Guy Merchant, Sheffield Hallam University

In this think piece we consider what data may do – and what may be done with data- when inserted differently into professional dialogue in education. We draw on a project that set out to ‘do data differently’ by inviting primary teachers to create, visualise and share their own data on what mattered to them in everyday literacy teaching using a postcard format. We argue that shifting the focus, visualisation and sharing of data can have ‘complicating effects’ which – through foregrounding data’s instability and partiality – can produce generative spaces for teachers’ professional dialogue.