A social cartography of analytics in education as performative politics

Abstract

Data—their collection, analysis and use—have always been part of education, used to inform policy, strategy, operations, resource allocation, and, in the past, teaching and learning. Recently, with the emergence of learning analytics, the collection, measurement, analysis and use of student data have become an increasingly important research focus and practice. With (higher) education having access to more student data, greater variety and nuanced/granularity of data, as well as collecting and using real‐time data, it is crucial to consider the data imaginary in higher education, and, specifically, analytics as performative politics. Data and data analyses are often presented as representing “reality” and, as such, are seminal in institutional “truth‐making,” whether in the context of operational or student learning data. In the broader context of critical data studies (CDS), this social cartography examines and maps the “data frontier” and the “data gaze” within the context of the dominant narrative of evidence‐based management and the data imaginary in higher education. Following an analysis of the main assumptions in evidence‐based management and the power of metrics, this paper presents a social cartography of data analytics not only as representational, but as actant, and as performative politics. What is already known about this topic Student data in higher education are increasingly used not only to inform operational and strategic planning, but to inform and shape curricula, pedagogy and student learning. The collection, measurement, analysis and use of student data are informed by a particular data imaginary in service of evidence‐based management. Data and analytics are seen as objective, neutral representations of reality and used as basis for informing policy, operational planning, resource allocation, and, increasingly, learning analytics and student facing dashboards. What this paper adds Critically examines data analytics in higher education as “truth‐making” and never neutral, and always as provisional snapshots of “reality” serving particular, often undeclared, assumptions and interests. Situates learning analytics as the collection, measurement, analysis and use of student data in the broader context of the data imaginary and student data as “data frontier”. Provides evidence that data analytics is not only representational, but, increasingly, performative and political. Implications for practice and/or policy Makes explicit some of the theoretical, political, epistemological and ontological assumptions underpinning and sustaining the data imaginary in higher education. Foregrounds the need for more critical approaches to our expectations, collections, analyses and use of student data. Argues the need for policy and practitioners to recognise the inherent political and performative nature of data and data analysis, and the need for transparency, accountability and care.

Supporting and challenging learners through pedagogical agents: Addressing ethical issues through designing for values

“…Dealing with these conflicts of interest and protection of the rights of vulnerable people such as children and the mentally disabled, will need carefully designed standards and legislation. Further discussion of data privacy will be left to other articles in this special issue whose focus is on learning analytics (Johanes & Thille,2019;Kitto & Knight, 2019;Prinsloo, 2019;Tsai, Poquet, Gaševid, Dawson, & Pardo, 2019;Williamson, 2019). Hudlicka (2016) identifies several ethical issues that go beyond the general concerns of data privacy and which are specific to virtual agents.…”

Learning analytics and AI: Politics, pedagogy and practices

“…Politics, Pedagogy and Practices cannot, of course, be neatly split into separate analytical threads: they are mutually constitutive. Building on the critical analyses of information infrastructures (Bowker & Star, ; Star & Ruhleder, ) and knowledge infrastructures (Edwards, ; Edwards et al , ), we may now be seeing the emergence of “educational knowledge infrastructures” (Buckingham Shum, )—these only exert political power through practices (in policy and design), which translate educational worldviews (whether implicitly or explicitly recognised: Knight, Buckingham Shum, & Littleton, ) into code (eg, in database schemas, algorithms and user interfaces), involving and excluding stakeholders, for instance, through the networks of institutions funding and building such infrastructure (Luckin & Cukurova, ; Prinsloo, ; Williamson, ), and the design methodologies employed to make design decisions (Buckingham Shum, Ferguson, & Martinez‐Maldonado, ; Richards & Dignum, ; Mavrikis, Geraniou, Gutierrez Santos, & Poulovassilis, ).…”

“…In “A social cartography of analytics in education as performative politics,” Prinsloo () critiques “the data imaginary” in higher education, arguing that this narrative ascribes too much trust and power in the potential of data analysis to represent the complex reality of student progress. Following an analysis of the main assumptions in evidence‐based management, and the increasing power of quantitative metrics, he presents a “social cartography” of data analytics, which should be thought of “not only as representational, but as actant, and as performative politics.”…”

“…Finally, within the theme of politics, our goal was to garner accounts that recognise the political significance and the potential for power and influence that the intelligence infrastructure constructed through the use of big data, AI and analytics brings to the world. Accounts that would help us to be appropriately vigilant and judiciously embracing with respect to these technologies and the quantifiable approaches they can bring to education (Kitto & Knight, ; Prinsloo, ; Richards & Dignum, ; Tsai et al , ; Williamson, ). We were also keen for clarifications of the way that the three elements of our theme: Politics, Pedagogy and Practices are deeply connected and inter‐related (cf.…”

“…Dialogue between multiple stakeholders is essential to ensure increased understanding as we venture into uncharted educational territory, although we should never underestimate the fact that higher education institutions are complex adaptive systems, as made clear by Tsai et al (). Prinsloo () echoes this, highlighting the need to pay attention to making visible and relevant the social, political, economic, legal, technological and environmental context that “entangles” all that we do. The key role to be played by multiple stakeholders, within school education as well as within HE, also arises for Mavrikis et al Their paper discusses the way in which teachers can be assisted by well‐designed information visualisations driven by sound LA, and how teachers need to be part of the conversation when it comes to the design and implementation of data driven approaches within education.…”