The proposed presentation draws on a rising number of so-called Critical Data Studies, which seek to understand the worldwide datafication of schooling and, more specifically, the role and impact of digital data infrastructures as powerful new tools of relation-making in education policy and practice (e.g. Williamson 2017, Gulson et al., 2017; Landri 2018). We contribute to this body of research by providing analytical insights into school monitoring systems in German and US state education agencies, focusing, in particular, on the translation of social/educational inequality into these systems as well as on the power of these systems to transform (the construction of) educational inequality. It is hereby argued that sociology of education should take a leading role in discussing the ongoing, powerful changes in the spatial and temporal framing of education - e.g. through datafication and digitalization -, which includes expanding its thinking “[…] beyond fixed and nation-state categories in which sociology of education had traditionally understood education, policy and society” (Landi/Neu­mann 2014: 1). In other words, we argue that an important way of “re-tuning“ sociology of education lies in its contribution to better understand “[…] how various forms of digital data are set to work within educational [governance] contexts, including what data is used, what the uses and [social] consequences are, and how data has become embedded within different organizational cultures“ (Selwyn 2014: 13-14).

As an example, over the past decade, the increasing digitalization of monitoring and leadership tools in state education agencies across countries worldwide has evoked new entangle­ments of actors and digital technologies around “[…] practices of sorting, naming, numbering, comparing, listing, and calculating” (Lury et al. 2012: 3) education, resulting in new forms of (topological) relation-making through commensuration (Espeland/Stevens 1998, Gulson et al. 2017, Landri 2018, Hartong 2018). Hence, while data infrastructures on the one hand introduce “new [topologi­cal] continuities into a discontinuous world by establishing equivalences or simili­tudes” (Lury et al. 2012: 3), on the other hand they also introduce new dis­continuities and differences fabricated through the managing, analyzing, ordering and visualizing of (digital) data, and crucially affected by algorithms and modeling.

Building on this line of argumentation, we argue that for a sociology of education in digital times, it is crucial to actively trace how the educational world becomes mediated into and simultaneously transformed by data infrastructures as the selected ‘forma­tion’ of data, information and knowledge (Thompson/Sellar 2018), including (the perception of) social/educa­tional inequality. Consequently, the goal of this contribution is to open up at least some features of what has widely remained a black box for most (sociology of) education researchers. We hereby address the following questions:

1. How is social/educational inequality (e.g. among schools, students etc.) translated into digital state monitoring and leadership systems, how is it processed into digital data infrastructures?

2. How do topological and territorial relations interact in monitoring and leadership tools used by state education agencies to make educational inequality visible and governable?

3. Do these digital monitoring tools transform (the perception of) educational inequa­lity, and if yes, how?

4. What important similarities and differences can be observed between different monitoring and leadership systems, both within and between Germany and the US, and why?

In that regard, our examination not only offers an empirical contribution to a growing body of critical data studies, but also discusses methodological questions of how to approach data infrastructures from a relational (and international comparative) sociology of education perspective.

The goal of our qualitative, small-n study is to better understand how datafication, in particular the relation-making of (digital) data for school monitoring and leadership (e.g. through data fabrication, processing, modelling, managing, visualization etc.), has become “enacted” in state education agencies, with a particular emphasis on the mediation and transformation of educational inequality. To approach these complex assemblages our study firstly draws on material collected through extensive online research and document analysis, including organization charts, policy papers, documentation on the development and usage of data instruments in state education agencies, as well as online data dashboards. Building on this initial research, we conducted more than 40 semi-structured interviews in four different Länder/states (Hamburg and North Rhine-Westphalia in Germany, Massachusetts and Georgia in the US), ranging between 60-90 minutes each. We hereby focused on the most relevant institutions conducting state-level data work related to school monitoring. Within these institutions, we then talked to individuals responsible for very different aspects of data formation, collection, validation, (re)coding, storage, processing and distribution, covering statistical as well as various kinds of assessment data. We used the method of qualitative content analysis to trace the “doing of data” in state education agencies, including a mapping of data infrastructures and also a deconstruction of topological and territorial relation-making within different monitoring tools. We hereby analyzed the material in a non-linear way, moving back and forth between contextualization and decontextualization (within and across “cases”, both intra- and cross-nationally). In doing so, context was transformed from a matter of fact (operating as a predetermined explanatory lens in comparative research) into a matter of concern (Sobe/Kowalszyk 2018: 198), while shifting attention towards the questions of how context is (re)produced, transformed (‘de/re-assembled’) and also how it attains meaning in social organization and scholarly interpretation.

As our findings illustrate, the implementation of data-based school monitoring and leadership in state education agencies appears as a complex entanglement of very different logics, practices and problems (see also Hartong/Förschler 2019). Within that entanglement, educational inequality becomes translated multiple times, including the selection of data (formats) collected from schools and districts, the production of algorithms to analyze that data, the application of statistical modelling, weighting and probability calculations, as well as the processing and visualization of data into dashboards or digital platforms. At the same time, we find topological and (re-) territorialized relation-making as (sometimes even contradictory) interacting. We illustrate this complex process of translation using the example of the Early Warning Indicator Systems in the US, as well as the Social Index used for ‘fair comparisons’ in Germany. As these examples illustrate, the problem of fabricating commensuration hereby equally concerns software/coding activities and the embedding of these kind of activities into wider institutional practices (e.g. school support, accountability or reporting), which, to a large extent, means linking numbers to norms and values and vice versa – for example by deciding which indicators are used to count it, which targets schools are expected to meet and, consequently, when to intervene as a state. In fact, we hereby observe what Diesner (2015) stated some time ago: small decisions can produce a big (governmental) impact, ultimately resulting in what could be described as an inequality of dataveillance. Finally, while our overall findings indicate a surprising similarity in the US and Germany, we still observe some significant differences between both countries, which particularly refer to the intensity of accountability which is much stronger in the US than in Germany.

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