Conference Agenda

Dashboards, progression curves, benchmarks, and traffic lights. All are examples of data visualizations used to mobilize data about educational institutions and their students. Data visualizations are graphic representations of digital data which summazise large amounts of data to patterns and trends within data sets. Data visualizations signpost the emergence of educational institutions and students as data objects, which can be observed and compared on a computer screen. They are thus shaping educational administrators’ and teachers’ socio-technical ways of ‘seeing’ educational quality and learning (Selwyn et al., 2022), and it is crucial to investigate their world making capacities and their ‘social life’ in educational worlds. As the main ‘interface’ through which educational administrators and educators access data, they are an underlooked but central aspect of the datafication of education.

This symposium investigates the role of data visualizations as a distinct way of making ‘education’ or ‘learning’ tangible and knowable. Although praised for making data accessible and interpretable, data visualizations also imply a distancing from data. Issues relating to how data is categorized in a database and how statistical techniques are performed on data are not included in visualizations (Ratner & Ruppert, 2019). The software developers of data visualizations make numerous design choices rendering some things absent and others present (Greller & Drachsler, 2012). While visualizations may appear factual and transparent, data visualizations provide neither direct nor neutral access to the object they are deemed to represent. Rather, they may be seen as persuasive and value-laden devices that privilege certain viewpoints (Latour, 1990).

This symposium examines data visualizations as entry point for discussing issues related to power, governance and automation. Dashboards visualizing the performance of educational institutions are today mundane artifacts in educational governance and require actors at different levels of governance hierarchies to turn performance gaps into improved outcomes (Decuypere & Landri, 2021; Ratner & Gad, 2018). Here, visualizations may have an affective dimension with e.g. rankings encouraging a dynamics of faming and shaming (Brøgger, 2016; Sellar, 2015), which, in turn, may situate education in a wider political context of competition and accountability. We may also examine questions of automation through data visualizations. With data visualizations increasingly presenting pre-fabricated interpretations of data, they now conduct some of the professional judgment formerly done by teachers (e.g. identifying low performing students). This may naturalize new forms of knowledge such as ‘at risk students’. It also maps out new responsibilities for teachers, such as ‘acting on’ visualizations to improve student learning. It is thus likely that visualizations both shape what counts as educational quality and signal to administrators and educators what they should prioritize. This raises important questions about how data visualizations reconfigure human judgment and decision-making in a digital and datafied age. While powerful, however, data visualizations can never fully determine the social contexts they are part of. Users may take them up in unanticipated ways. Thus, it is equally important to examine how educators and administrators make sense of data visualizations, ignore them, resist them or put them to other uses than those anticipated by the designers.

This conference symposium will explore the role of data visualizations in education across Europe and beyond. It does so by comparing different European and international cases of how data visualizations are used in education, including historical and contemporary examples. The symposium includes contributions examining both the production and consumption of data visualizations. Across the different contributions, it will also discuss conceptual and methodological questions arising from the study of educational data visualizations.

Due to the expanding use of visualisations in the digital sphere, our sensemaking of the world increasingly depends on how information and data is assembled for display (Kennedy et al., 2016), also in the field of education. Over the past years, growing critical attention has consequently been put on practices of design, which lie behind these visualisations and consist of a multi-layered process, reaching from strategic decisions and the involvement of various actors over the development of data-architectures to the creation of visual experiences that effectuate the behaviour of educational actors (Decuypere, 2021). Taking this crucial role of design for visualisations as a starting point, our contribution focuses on how three different schools in Hamburg, Germany, (re-)designed the interface of a Moodle-based learning management system (LMS) according to their pedagogical and organisational ideas. The case of Hamburg’s LMS is particularly interesting since the system´s original design on the one hand gives a lot of freedom to schools to visualise their individual ideas due to its open-source structure. On the other hand, the LMS design was deliberately pre-limited by the educational agency, thus inscribing particular ideas of schooling and its potential visualisation into the product. Assuming that platforms are no self-contained units, but rather constantly (re)enacted through interaction with their specific environment (Karasti & Blomberg, 2018), we worked with the three schools and media educators, following a Participatory as well as Critical Design approach (Brandau & Alirezabeigi, 2022), to design individual and context-related LMS interfaces.1 Integrating teachers and students as future users into the design process, the central idea was to empower them to understand the technology and, consequently, to develop a reflected and creative engagement with what it displays (Cumbo & Selwyn, 2021). Combining ethnographic insights from these co-design processes (Pink et al., 2022) with platform walkthroughs (Light et al., 2018), this contribution shows how oftentimes invisible design practices substantially influence the visual manifestations of LMS and, thus, the resulting data-based enactment of ‘the school’. Still, those practices can be partially made visible using a critical co-design approach and, in doing so, empower schools to constructively deal with datafication.

Brandau, N., & Alirezabeigi, S. (2022). Critical and participatory design in-between the tensions of daily schooling: working towards sustainable and reflective digital school development. Learning, Media and Technology, Special Issue: Instituting socio-technical education futures: Encounters for technical democracy, data justice, and post-automation, 1–13. DOI: 10.1080/17439884.2022.2156538. Cumbo, B., & Selwyn, N. (2021). Using Participatory Design Approaches in Educational Research. International Journal of Research & Method in Education, 45 (1), 1–13. https://doi.org/10.1080/1743727X.2021.1902981. Decuypere, M. (2021). The Topologies of Data Practices: A Methodological Introduction. Journal of New Approaches in Educational Research, 10 (1), 67-84. https://doi.org/10.7821/naer.2021.1.650. Karasti, H., & Blomberg, J. (2018). Studying Infrastructuring Ethnographically. Computer Supported Cooperative Work, 27 (2), 233–65. https://doi.org/10.1007/s10606-017-9296-7. Kennedy, H., Hill, R. L., Aiello, G., & Allen, W. (2016). The Work That Visualisation Conventions Do. Information, Communication & Society, 19 (6), 715–35. https://doi.org/10.1080/1369118X.2016.1153126. Light, B., Burgess, J., & Duguay, S. (2018). The Walkthrough Method: An Approach to the Study of Apps. New Media & Society, 20 (3), 881–900. https://doi.org/10.1177/1461444816675438. Pink, S., Fors, V., Lanzeni, D., Duque, M., Strengers, Y., & Sumartojo, S. (2022). Design Ethnography: Research, Responsibility, and Futures. Routledge. https://www.taylorfrancis.com/books/9781003083665.

This article explores how data visualizations come to matter, and how different types of data visualizations are ascribed different modes of existence. Data and visualizations of data are widespread within education (Decuypere & Landri, 2021; Williamson, 2016; Wyatt-Smith et al., 2021), however different types of data and their visualizations take different forms, meanings and have different journeys. In this article I pay attention to the data visualizations found in digital learning materials in the Danish primary and lower secondary school system. For the oldest students in the Danish primary and lower secondary schools, digital learnings materials have largely replaced analogue learnings materials and books. Some of these digital learning materials offer teachers graphic overviews about student performance during and/or after lessons. Through ethnographic fieldwork in Danish schools and among Danish teachers, I have studied how teachers interact with, make sense of, and how they use these visualizations. Data visualizations in digital learning materials vary from other types of data visualizations, e.g., from national tests, and international large-scale assessments. They typically do not travel as far as the abovementioned types of data (and their visualizations) but are engaged more intimately by individual teachers. Yet, they are entangled in wider eco-systems or assemblages beyond the teachers that interact with them including both humans and nonhumans (like school leadership, technologies, local municipalities, and policies). In order to explore how the data visualizations come to matter, I build on and draw inspiration from feminist new materialist work (Barad, 2007; Braidotti, 2022; Haraway, 2008, 2016). I build on the conceptualization of data (and their visualizations) as more-than-human phenomena invested with diverse forms of vitality (Lupton, 2020). Data are performative (Staunæs et al., 2021), they are local and inextricably entangled (Loukissas, 2019). By paying attention to the situated, local, and embodies experiences of teachers engaging data visualizations (in digital learning materials), I explore how teachers make and enact data (and their visualizations) and how the data make and enact teachers (Lupton, 2020). I argue that data visualizations come to matter in different ways and that they are ascribed different modes of existence. Some visualizations become ‘comatose’ – abandoned and almost dead, while others become ‘vibrant’ – full of life and influence. At the same time, I look at how (some) visualizations also contribute to teacher becomings.

Barad, K. M. (2007). Meeting the universe halfway: Quantum physics and the entanglement of matter and meaning. Duke University Press. Braidotti, R. (2022). Posthuman feminism. Polity. Decuypere, M., & Landri, P. (2021). Governing by visual shapes: University rankings, digital education platforms and cosmologies of higher education. Critical Studies in Education, 62(1), 17–33. https://doi.org/10.1080/17508487.2020.1720760 Haraway, D. J. (2008). When species meet. University of Minnesota Press. Haraway, D. J. (2016). Staying with the trouble: Making kin in the Chthulucene. Duke University Press. Loukissas, Y. A. (2019). All data are local: Thinking critically in a data-driven society. The MIT Press. Lupton, D. (2020). Data selves: More-than-human perspectives. Polity. Staunæs, D., Juelskjær, Malou, Bjerg, Helle, & Olesen, Kristian Gylling. (2021). Datasans: Etisk skole- og uddannelsesledelse med data (1. udgave). Nyt fra Samfundsvidenskaberne. Williamson, B. (2016). Digital education governance: Data visualization, predictive analytics, and ‘real-time’ policy instruments. Journal of Education Policy, 31(2), 123–141. https://doi.org/10.1080/02680939.2015.1035758 Wyatt-Smith, C., Lingard, B., & Heck, E. (Eds.). (2021). Digital disruption in teaching and testing: Assessments, big data, and the transformation of schooling. Routledge.

Sub-paper had to be withdrawn.

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The desire to optimize and control education by predicting the future plays an increasing role in contemporary educational governance. Today, economic forecasts of future labor market needs constitute one type of governance technology of importance for educational governance, and a technology of future-making (Wenzel, 2022). Through websites and reports, visual images of forecasted futures stage higher education in relation to a desired future and furthermore imply particular policy decisions to be rational and timely in order to achieve this future. In these visual images, the uncertainty of the future is often masked, as visual shapes of intervals and areas are replaced by lines and bars. Whereas lines and bars indicate an exact prediction, intervals and areas indicate a range of more or less probable future outcomes, which is more in line with the statistical forecasting methods developed by economics (Elliott & Timmermann, 2016). Based on two case studies, including a Danish and a Norwegian economic forecasting of labor market needs, and the methodological and analytical concept of topology (Allen, 2016; Decuypere, 2021; Decuypere, Hartong, & van de Oudeweetering, 2022), this paper explores different visual approaches to future-making in such technologies and the implications of these for the promotion of particular policy-driven concepts of the future of education and rational and timely policy decisions. The cases include forecasts of the future educational profiles of Norwegian graduates, produced by Statistisk Sentralbyrå in Norway (Statistisk Sentralbyrå, 2020), and forecasts of the future educational profiles of Danish graduates combined with forecasts of the labor market needs of the public sector in Denmark, produced by the Danish Ministry of Higher Education and Research (Committee on Better University Programs, 2018). These technologies are conceptualized as topological forms that via their ways of visually connecting data points describing the past with data points describing the future have particular temporalizing effects. They will be studied in terms of their architecture (Decuypere 2021), including how the different data points in each technology are generated, how they relate to each other, and how they are extended into the future, combined with studies of their interface (Decuypere 2021), including how this is visualized differently in forecasts disseminated in foreground policy texts and in background methodology texts. The analysis will furthermore draw on interviews with experts who have been involved in producing the forecasts. The findings will be analyzed in light of the higher education policy circumstances characterizing Denmark and Norway respectively.

Allen, J. (2016). Topologies of Power: Beyond territory and networks. London: Routledge. Committee on Better University Programs. (2018). University Programs for the Future [Universitetsuddannelser til fremtiden]. Retrieved from https://ufm.dk/publikationer/2018/filer/rapport-universitetsuddannelser-til-fremtiden.pdf Decuypere, M. (2021). The Topologies of Data Practices: A Methodological Introduction. Journal of new approaches in educational research, 10(1), 67-84. doi:10.7821/naer.2021.1.650 Decuypere, M., Hartong, S., & van de Oudeweetering, K. (2022). Introduction―Space-and time-making in education: Towards a topological lens. European educational research journal EERJ, 147490412210763. doi:10.1177/14749041221076306 Statistisk Sentralbyrå. (2020). Framskrivinger av arbeidsstyrken og sysselsettingen etter utdanning mot 2040. Retrieved from Oslo–Kongsvinger: Wenzel, M. (2022). Taking the Future More Seriously: From Corporate Foresight to “Future-Making”. Academy of Management perspectives, 36(2), 845-850. doi:10.5465/amp.2020.0126 Elliott, G., & Timmermann, A. (2016). Economic Forecasting. Princeton, New Jersey: Princeton Univ Press.