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Globalisation, Societies and Education
ISSN: 1476-7724 (Print) 1476-7732 (Online) Journal homepage: http://tandfonline.com/loi/cgse20
Towards a topological re-assemblage of education
policy? Observing the implementation of
performance data infrastructures and ‘centers of
calculation’ in Germany
Sigrid Hartong
To cite this article: Sigrid Hartong (2018) Towards a topological re-assemblage of education
policy? Observing the implementation of performance data infrastructures and ‘centers
of calculation’ in Germany, Globalisation, Societies and Education, 16:1, 134-150, DOI:
10.1080/14767724.2017.1390665
To link to this article: https://doi.org/10.1080/14767724.2017.1390665
© 2017 The Author(s). Published by Informa
UK Limited, trading as Taylor & Francis
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Towards a topological re-assemblage of education policy?
Observing the implementation of performance data
infrastructures and ‘centers of calculation’in Germany
Sigrid Hartong
Department of Education, Faculty of Humanities and Social Sciences, Helmut-Schmidt-University, Hamburg,
Germany
ABSTRACT
The ongoing trend towards educational globalisation has brought about
various dynamics of education policy ‘rescaling’, resulting in a growing
number of governmental arrangements, which are operating across
traditional scales, levels or sectors of policy. This contribution takes up
the conceptual frameworks of topological spatialisation and assemblage
theory to better understand the pivotal role of new information
technologies, data infrastructures and also the increasing power of
‘centers of calculation’within education policy reforms that have been
implemented in Germany after the launch of the Programme for
International Student Assessment.
ARTICLE HISTORY
Received 19 December 2016
Accepted 7 October 2017
KEYWORDS
Data infrastructures; German
education policy;
globalisation; assemblage
theory; topological
governance; information and
communication technologies
Introduction
The past decades have witnessed a progressive increase of research in the field of education policy
globalisation, including a growing awareness for what has been described as ‘fast policy mobilities’
between countries, regions or cities (Peck and Theodore 2015; Steiner-Khamsi and Waldow 2012).
Such policy mobilities also include the expansion of standardisation instruments, new monitoring
and assessment strategies, or the enhancement of competition and (quasi) market structures (Verger,
Lubienski, and Steiner-Khamsi 2016).
At the same time, an essential marker for the heterogeneous and also contradictory transforma-
tions related to globalisation has been found in a constantly rising level of governance complexity,
which particularly results from higher numbers of intergovernmental and interagency relationships
and powers (Savage 2016) and also from an increasing amount of involved actors and stakeholders
between global to local policy contexts. In other words, globalisation articulates in a diversification of
actors forming a ‘social infrastructure’(Künkel 2015b, 8) of transfer agents, who
[…] sprung up around ‘best practices’codification, practitioner conferences, learning exchanges, knowledge
transfer, and communities of practice. (Peck and Theodore 2015, xv; see also Hartong 2016a)
This rising involvement of such ‘intermediary’actors has been fuelled by a broad policy ‘turn’
towards (digital) data and numbers (Grek 2009;Ozga2009), which includes a growing influence
of large-scale and longitudinal educational data production, data mediation or technology-related
consultancy practices (Hartong 2016b). Hence, in many education-related contexts, the implemen-
tation of new information and communication technologies (ICT) has been forming both an object
© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://
creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the
original work is properly cited, and is not altered, transformed, or built upon in any way.
CONTACT Sigrid Hartong hartongs@hsu-hh.de
GLOBALISATION, SOCIETIES AND EDUCATION, 2018
VOL. 16, NO. 1, 134–150
https://doi.org/10.1080/14767724.2017.1390665
and subject of (globalising) policy mobilities and reform (Clarke 2015, 129; Mok and Leung 2012;
Ruppert 2012; Stambach and Malekela 2006): while ICT have become translated into the field of edu-
cation, they simultaneously act as a core medium through which new actors have become authorised
as key players to shape output- and accountability-based policy and practice.
Particularly within orthodox neo-institutionalist trajectories of research, education policy globa-
lisation has often been focused on the question of policy convergence between nation-states (Lingard
and Grek 2007, 11), triggered by increasing coercion, normative pressure or imitation (often named
policy ‘learning’), which altogether produce ‘isomorphism’(DiMaggio and Powell 1983) towards a
common ‘world polity’(Meyer et al. 1997; Meyer, Krücken, and Kuchler 2005). One particular
strength of the world polity approach certainly lies in its emphasis on rational principles as construc-
tivist moments of globalisation, which form new ‘globalised’frames of reference for national or local
policy-making. Moreover, the approach has excited fervent debates on new supra-national ‘arenas of
standardisation and educational governance’(Leuze, Rusconi, and Martens 2007), particularly inter-
national organisations or transnational networks, who have been increasingly operating as ‘teachers
of norms’(Finnemore 1993), ultimately fuelling worldwide policy alignment.
Still, over the past decade, the world polity’s emphasis of top-down transformation, its identifi-
cation of fixed policy ‘objects’or ‘indicators’of policy transfer as well as its narrowed focus on results
(convergence) has evoked an increasing number of critics (for a summary see Adick 2009). Such cri-
tique saw too little attention paid to the influence of local ‘path-dependencies’(Levin 1997; Pierson
2000), to policy mobility processes beyond national systems or state actors (Dale and Robertson
2012; Künkel 2015b, 11; Steiner-Khamsi 2012), while it simultaneously began to question classical,
often taken-for-granted geographic images of scale and territory (one early example is Latour 1996).
Consequently, considerable efforts have been made in recent years to examine policy mobilities as
more complex, distinct and also continuously changing relations between the global and the local
(e.g., Brenner 2004; Carney 2009; DeLanda 2006; Hartong and Nikolai 2017; Herod and Wright
2002; Howitt 2002; Peck and Theodore 2015; Robertson and Dale 2015). While policy scales are
more ‘critically considered as a narrative device, a measure of distance and a technique of govern-
mentalities’(Legg 2009, 235), such approaches also more strongly accentuate ambivalences and
dynamics of simultaneously deterritorialised and ‘re-bordered’/territorialised policy mobilities
(Milana 2016, 207).
This does not mean, however, that scales such as the transnational, national or subnational have
become obsolete (Legg 2009), but rather that they are understood as parts of multiple scalar and (also
de-)territorial transformations, in which governmental power is constantly created or (de-)stablised.
At the same time, such an understanding is not limited to the distinct influence of human agents, but
instead more strongly takes into account the various relations between humans and non-human
agents, which, through their ongoing interaction, are equally co-producing policy mobility. As
this article seeks to demonstrate, such approaches are particularly useful when observing the
implementation of ICT within new governmental complexes in education policy, which are increas-
ingly reaching beyond and across traditional policy ‘entities’, scales and geographies, while simul-
taneously transforming those entities (and also the individuals within) when being enacted.
In that context, this contribution will take up the conceptual framework of policy assemblages (as
applied i.a. by Clarke et al. 2015; Peck and Theodore 2015 or DeLanda 2006) and, within that con-
ceptual framework, draw upon the idea of topological spatialisation (as used by Allen and Cochrane
2010; Ruppert 2012; Lewis and Lingard 2015; Allen 2011 or Ball 2016) to better understand how new
data infrastructures of educational performance monitoring (as part of ICT) have recently affected
global–local policy mobilities (Anagnostopoulos, Rutledge, and Jacobsen 2013). The term ‘data’
hereby stands for quantified and digitalised educational information, which is stored and processed
by computers, and which is enacted by software and algorithmic code.
1
‘Data infrastructures’then
means networks of objects (the data itself, hard- and software, but also policy ‘fragments’, such as
educational standards or funding formulas) and subjects (technicians, administrators, school actors,
intermediary agents, etc.) assembled around these data and around its socio-technical de- and
GLOBALISATION, SOCIETIES AND EDUCATION 135
recontextualisation practices. In other words, data infrastructures are understood as (the transform-
ation of) governmental constellations constituted by (digital) data flows that, however, are more than
computer-based hard- and software, but networks of people, technologies and policies (Anagnosto-
poulos, Rutledge, and Jacobsen 2013, 8). Whilst such data infrastructures seem increasingly essential
for ‘soft governance’by producing, transferring and mediating governing as topological knowledge
(see also Lawn 2013), they still appear as a ‘hidden’, underexplored facet of policy rescaling in edu-
cation. Following Anagnostopoulos, Rutledge, and Jacobsen (2013, 3),
[…] the contours and consequences of […] [data] infrastructure[s] remain only vaguely understood. Questions
of how it is being built, the new technologies and actors it gives rise to, how it redistributes power and influence
across and beyond the formal educational system, and how it shapes what and who counts […] have not been
addressed in a comprehensive way.
This is particularly true for the German case, where hardly any (performance) monitoring infrastruc-
tures had been in place in the field of education until Germany participated in the Programme for
International Student Assessment (PISA) in the year 2000. Then, within a decade, Germany under-
went a radical shift towards ‘output-orientation’, assessments and monitoring infrastructures across
all scales of the education system (which, however, is still in its initial stage). Despite this tremendous
policy change, which has been flanked by most controversial political and public debates, the shifting
geographies of power through these new ‘data infrastructuralisation’, at least so far, have been poorly
examined.
In fact, as this contribution indicates, the German case clearly demonstrates how the turn towards
assessments and monitoring has given rise to new intermediary actors who are programming,
collecting, visualising or mediating data into politics, research, administration or school practice
(Hartong 2016b; Koyama 2011; Mayer-Schönberger and Cukier 2013; Williamson 2015b). Such
actors not only support a more effective or efficient use of data, but simultaneously, and together
with the data, co-create new policy assemblages, including new visibilities, geographies and modes
of (topological) governmentality.
Conceptual framework
A growing number of research in the field of education policy mobility has identified complex and
dynamic interactions between policy levels, sectors, actors or policy ‘fragments’when approaching
globalisation processes, rather than unilateral policy transfer or binary zero-sum games (Peck and
Theodore 2015, 6). Consequently, over the past years, increasing attention has been devoted to
more relational approaches of ‘local globalism’and ‘global localism’(de Sousa Santos 2006), to geo-
political ambivalences, to the role of (path-dependent) institutional settings (e.g., Powell, Edelstein,
and Blanck 2016), to the ongoing fragmentation of policy ‘objects’and also to implicit power
relations within structures of policy learning or policy transfer (e.g., Peck and Theodore 2015,
22ff.).
A concept, which has become increasingly used in policy mobility research, is Carney’s(2009)
approach of ‘global policy scapes’, which addresses national reforms and their subnational manifes-
tations as the result of complex and disjunctive global–local policy flows (see also Savage and O’Con-
nor 2015, 613). Similar to this idea, Robertson and Dale (2015) use the term ‘education ensembles’to
describe globalised policy spaces, which are made up ‘[…] of various layers of structures and gen-
erative mechanisms’(Robertson and Dale 2015, 150). Sheppard (2002), in turn, introduces the
term ‘positionality’as a power-oriented, relational construct of global policy rescaling through per-
ception and sense-making, which he traces back historically to Captain James Cook’s exploration of
Hawai’i in 1778, as a radical restructuring of ‘[…] the space/time vectors connecting Hawai’i with
London’(Sheppard 2002, 307). In that regard, Sheppard understands positionality as being
[…] continually enacted in ways that both reproduce and challenge its preexisting configuration. (Sheppard
2002, 318)
136 S. HARTONG
Others have introduced more ‘vertical case study’-approaches (e.g., Bartlett and Vavrus 2014) as well
as policy field approaches derived directly or more indirectly from Bourdieu’s critical sociology (e.g.,
Fligstein and McAdam 2012; Hartong and Nikolai 2017; Fourcade 2006 or Mangez and Hilgers
2012).
All these contributions share a notion to go beyond the question how global trends impact on
nation-states, and instead explore how global and national forces continuously interact with subna-
tional or local processes, institutions, actors, objects (or fragments of objects) and polities, often caus-
ing unevenness, frictions, or different timelines of policy adaptation as well as particular possibilities
for reform (Ball 2016, 550; Clarke et al. 2015, 35; Dale 2005; Ozga et al. 2011; Savage and O’Connor
2015, 611).
Within this trajectory of research, this contribution takes up two concepts, which are seen as par-
ticularly powerful for understanding global–local mobilities enacted through the implementation
and expansion of performance data infrastructures in education. These are the concept of policy
assemblages (as used by Clarke et al. 2015; Peck and Theodore 2015 or DeLanda 2006) and, within
that conceptual framework, the idea of topological spatialisation (as used by Allen and Cochrane
2010; Ruppert 2012; Lewis and Lingard 2015; Allen 2011 or Ball 2016).
Observing data infrastructures through the lens of topological assemblages
Roots of assemblage theory go back to the work of the French philosophers Deleuze and Guattari,
who defined assemblages as
number[s] of disparate and heterogeneous elements convoked together into a single discernible formation that
displays some form of consistency and regularity while it remains open to transformative change through the
addition or subtraction of elements or reorganization of the relations between them. (Bureš2015, 14)
In other words, assemblage theory focuses on simultaneities, tensions and heterogeneities, but also
on the fixity of social constellations (Mattissek and Wiertz 2014, 3; Peck and Theodore 2015, xvii),
which are observed as historically and structurally contingent. In that view, single parts of particular
assemblages (in this contribution: particular data, technologies or data-mediating actors) can always
play different roles within different assemblages (DeLanda 2006, 18ff.), while assemblages themselves
are composed by a heterogeneity of human and non-human elements that ‘go into making policy’
(Clarke et al. 2015, 31).
Among others, Ong and Collier (2005) used assemblage theory to explicitly trace the ‘global
shape’of particular policy subjects. For them,
‘global assemblages’integrate ‘global [which] implies broadly encompassing, seamless, and mobile, [and]
assemblage [which] implies heterogeneous, contingent, unstable, partial, and situated’. (Ong and Collier
2005, 12, italics by author)
Hence, following Clarke et al. (2015, 49), the core question of assemblage research in the context of
global–local policy mobility focuses on different ways in which specific assemblages may, or may not,
become (temporarily and territorially) stabilised.
Within the conceptual framework of assemblage theory, different scholars then have developed
new perspectives on relational rescaling by applying a more topological notion of power and govern-
mentality. Instead of observing horizontal or vertical forms of power distribution, such topological
perspectives mainly focus on the reach and proximity of influence, which however are not simply
spatial, territorial extension, but rather
[…] play across one another in a variety of intensive ways to bridge the gap erected by the physical barriers of
distance. (Allen and Cochrane 2010, 1075; see also Ruppert 2012, 121)
In education policy, such topological understandings of globalisation have been applied, among
others, by Ball (2016), Savage and Lewis (2016) or Lewis and Lingard (2015). Lewis and Lingard’s
GLOBALISATION, SOCIETIES AND EDUCATION 137
(2015) contribution is of particular interest here, because they use the concept of topological globa-
lisation to describe the influence of the Organisation of Economic Co-operation and Development
(OECD) on nations, states, cities and schools through PISA-based data governance. As they show,
the OECD has successfully established topological spaces of data-related practices (such as particular
narratives, but also instruments such as rankings and reports), which enable the OECD to be phys-
ically absent and yet still (locally) present in terms of policy reach and influence (Lewis and Lingard
2015, 625).
While there has been a growing body of research focusing on the ‘governance by numbers’exer-
cised by international organisations (Leuze, Rusconi, and Martens 2007; Milana 2016), such research
often led to an understanding of education being increasingly ‘governed at a distance’(Rose 1999),
which, however, mainly referred to the geographical distance of international actors. Topological
understandings of governmentality see such a geographically based diagnosis as potentially misguid-
ing (Clarke et al. 2015, 26), given that
topographical distance between actors can be elided by the global being topologically ‘folded’into local spaces.
In effect, territorial distance –as measured in kilometres or miles –becomes less reflective of near and far, of
place and space, than does the topological notion of ‘closeness’as expressed through relationality and connect-
edness. (Lewis and Lingard 2015, 623; building on Allen 2011)
Building on these ideas, I argue that the worldwide mobilisation of educational performance moni-
toring can be identified as an effect of international assessments such as PISA, which triggered a
‘turn’towards comparative ‘what works’-knowledge, and, as a consequence, towards a topological
(re-)assemblage of education policy through performance data infrastructures. Hereby, objects
(data, technology and other policy ‘fragments’) and subjects (technicians, administrators, school
actors or intermediary agents) become ‘(re-)assembled together’(Koyama 2011, 706) around new
governmental constellations that are constituted by (digital) data flows and that create various
new linkages and spaces between the global and the local (also Sassen 2002, 365).
Within such new policy assemblages, data mediators and also data managers have become power-
ful change agents, because they transfer data between digital spheres, territories and traditional gov-
ernmental spaces in education, which in turn increasingly rely on successful data mediation
(Hartong 2016b). For instance, data mediators and data managers apply practices of data visualisa-
tion or data services around the production and usage of assessment results or information plat-
forms, ultimately operating at the heart of data de- and recontextualisation. One example is the
complex network of institutional partnerships and data service contractors assembled around the
OECD, who collaboratively produce and process PISA data (Bloem 2016), exemplarily for the online
platform Education GPS (http://gpseducation.oecd.org, 24 July 2017),
2
but who have rarely been the
subject of in-depth analysis (see also Hartong 2016b, 524).
Taking up Clarke’s(2015) analysis of what he calls the global management assemblage, which
over the past years has been entering and transforming universities, I consequently argue that
data management itself can be described as a global phenomenon, which forms both an object of
translation and a core medium of catalysing re-assembling processes. In other words, data manage-
ment in many fields of education has become a hidden transcript, which is pushing actors towards
‘finding things [here: data] to manage’(Clarke 2015, 118, 130), to engage with codes and software
(Manovich 2013; Williamson 2016b) and to focus on translating ‘things’into data and back.
Against this backdrop, observing performance data infrastructures in education through the lens
of topological assemblages seems promising for several reasons:
(1) Assemblage theory understands itself as a rather open heuristic for explorative empirical
research, which seems particularly appropriate for the analysis of the still very opaque, distinct
shapes of datafication (meaning the quantification of things) and digitalisation (meaning the
conversion of analogue information into a binary computer code) in education (Mayer-Schön-
berger and Cukier 2013, 78). In understanding objects of analysis as constantly processing and
138 S. HARTONG
changing (Künkel 2015b, 9), the approach provokes dense empirical descriptions, a more eth-
nographic gaze, and also a stronger awareness for details, rather than taking them for granted
(Bureš2015; DeLanda 2006).
(2) While assemblage theory has often been applied in ethnographic single-case studies, it also
offers multiple options for international, comparative research. For instance, understanding
the path-dependent recontextualisation of global trends as different assemblage-‘landscapes’,
might shed new light on current policy transformations within particular geographical(ly con-
structed) settings, such as nation-states. Within the empirical focus of this contribution on
Germany, the same seems true for transformations within multi-level, federal systems, that
reveal additional dynamics, repercussions or subnational varieties of reform when responding
to global trends.
(3) Many scholars have pointed out the close relation between assemblage theory and concepts of
governmentality, which pay particular attention to asymmetries of power within processes of
(re-)assemblage and policy mobility (Legg 2009, 239; Mattissek and Wiertz 2014, 2). Such
power relations are contingent in the sense of ongoing (potential) struggle and power, which
determine what may, or may not, be translated in a particular way (Clarke et al. 2015, 40ff.).
Related to data infrastructures and data mobility, such power asymmetries are not only reflected
in the crucial stages of software programming, data selection/data processing, data distribution
or data visualisation, but also in the growing emergence of infrastructural ‘centers of calculation’
(Ruppert 2012; Sheppard 2002, 316). Within such technical zones of human-data interaction,
material infrastructures are co-created with specific rules, norms and values, ultimately bringing
about a new ‘digital economy of scale’within ‘cybergeographies’(Goodchild 2004; Ong and
Collier 2005, 11).
(4) Consequently, topological assemblage thinking takes up various ideas of Actor Network Theory,
as substantiated by Latour, Woolgar or Callon (Bousquet 2013; Bureš2015, 15; Färber 2014, 95;
Piattoeva 2016). In particular, assemblages are not understood as solely ‘including’individuals,
but rather, through the establishment of particular topologies and visibilities, as ‘creating’them.
In line with that idea, Ruppert (2012) showed how the recent expansion of database devices by
the new UK Labour government has brought about new topologies, which materialise and
advance new, distinctly defined individualities of subjects, ultimately resulting in a ‘technocratic
infrastructure for knowing subjects and populations’(Ruppert 2012, 119).
(5) Topological assemblages address the emergence of new spatialities, but also transformations of
temporalities (Peck and Theodore 2015, xxii), thus pointing to a still underexplored facet in pol-
icy mobility research (Clarke et al. 2015, 20; DeLanda 2006, 40; Sassen 2002), which, however,
seems the more important when observing datafication and digitalisation. While the infrastruc-
turalisation of data is commonly associated with an overall acceleration of knowledge mobility, I
argue that particular assemblages around programming, (human) data processing and data
mediation have created entirely new regimes of temporality. As an example, the ‘fixed’schedule
of long-term performance assessments (such as PISA, which must be published within three-
year cycles) has brought about new temporal forces (Bloem 2016), which are constantly guiding
potential data-human interaction, while, at particular points in time (which is the publication of
new results), continuously opening up possibilities for policy re-assemblage.
(6) Understanding parts and their functioning in a different manner within different assemblages
can facilitate the classification of data/data management in education, which in one context
might serve as an automated learning or teaching device, in a second as information for admin-
istrative requirement planning, in a third as accountability measure, and in a fourth as a (global)
market product. In other words, datafication in education evokes numerous (re-)assemblage
processes, including distinct ‘things’that are actually moving (Künkel 2015a, 82), e.g., codes
or algorithms, programmes, data mediators or visualised data products (such as monitoring
reports or rankings). Consequently, what assemblage theory describes as an ongoing interplay
between deterritorialisation and re-bordering/territorialisation (DeLanda 2006, 12), might
GLOBALISATION, SOCIETIES AND EDUCATION 139
also inform a broader and also more critical observation of data de- and recontextualisation
processes.
Despite this illustrated strengths of the topological assemblage approach for observing data infra-
structures in education, scholars have also pointed to particular weaknesses of the concept. Such
weaknesses are mainly related to the empirical challenge of simultaneously embracing local depth
and transnational reach of assemblage processes (Künkel 2015a, 77; Peck and Theodore 2015, 37)
without ending up in endless deconstruction. Similarly, understanding assemblages as being in con-
stant motion also complicates an actual ‘mapping out’of relations (Bureš2015, 19). Considering
these concerns, this contribution understands assemblage theory primarily as a new way to approach
the globalisation (here: datafication and digitalisation) of knowledge, power and politics (Clarke et al.
2015, 52) and, consequently, as a flexible, yet broad guideline for empirical research (Bureš2015, 20).
The (global) expansion of performance data infrastructures in education and the
particular case of Germany
Over the past two decades, an increasing global fabrication of educational data through new ICT can
be observed, designed to improve and to accelerate the application of educational knowledge through
numbers and statistics (see also Lingard, Creagh, and Vass 2012). Central in this development are
international organisations such as the OECD, who have implemented complex global–local infra-
structures of data production, databases, data-related policy products, data experts and mediators, as
well as data-related norms, values and ideas.
Particularly over the last decade, the OECD (but also actors such as the European Union or the
World Bank) have increasingly focused on becoming data experts, by using survey data for policy
consultancy and services, by expanding the scope of their instruments (e.g., PISA for schools) to
‘reach into’nations, cities or schools (Bloem 2016; Lewis and Lingard 2015; Sellar and Lingard
2013), and by promoting the digitalisation of educational governance. Promoters of data infrastruc-
turalisation hereby regularly pointed to an ‘intolerable’situation for policy-makers, teachers and
parents who were supposedly forced to make meaningful decisions on the basis of either poor
(e.g., fragmented) data or ‘opinion’(as Andreas Schleicher, head of the OECD’s PISA division,
recently stated). Consequently, through triggering a growing orientation towards large-scale,
small-scale, ‘big’and ‘thick’data (Boyd and Crawford 2012; Mayer-Schönberger and Cukier
2013), such actors prompted governments, but also a growing number of private firms or philan-
thropies, to invest in the creation and expansion of data infrastructures, educational monitoring
and e-learning/e-governance.
In many parts of the world, yet in varied extent and scope, this turn towards (better) data stands in
close relation to standards-based reform initiatives as well as to a growing orientation towards edu-
cational output and accountability (Hartong 2015). Applying the idea of topological assemblages,
while there occurs an overall rise of new assemblages and topologies through the implementation
of performance data infrastructures and new ‘centers of calculation’, the shape of these assemblages,
the functionality of single pieces within (e.g., the role and scope of PISA), and also the internal
relation between pieces may look very different. Reasons certainly lie in varying legal regulations
within the politically constructed boundaries of nation-states, but also in path-dependent options
for data mediators’influence, as well as in the cultural ‘likeliness’to trust in numbers (e.g., rather
than in judgements of the teaching profession).
Against this backdrop and in contrast to other countries, Germany is still in its initial stage of
turning to datafication and especially to digitalisation in terms of educational performance monitor-
ing. In this regard, it crucially differs from countries which have already created extensive (centra-
lised) data infrastructures and systems of e-governance, such as the United Kingdom (Ruppert
2012), but also federations such as the United States or Australia (Hogan, Sellar, and Lingard
2016; Koyama 2011; Williamson 2015b,2016a,2016b).
140 S. HARTONG
For example, in Australia, a national school reform agenda after 2008 led to the implementation
of a centralised Australian Curriculum, Assessment and Reporting Authority (ACARA), a national
census testing of literacy and numeracy (NAPLAN), and a new national online platform, which pub-
licly and interactively compares school performance data (the MySchool website).
The United States appear as even further developed in terms of top-down, test- and accountabil-
ity-driven data infrastructuralisation (see also Lingard and Lewis 2016). Here, key driving forces
included the federal No Child Left Behind (NCLB)- and Race to the Top (RttT)-resolutions, estab-
lished between 2001 and 2010, but also the extensive involvement of non-governmental, often
for-profit actors, who early created a powerful market for data, digitalisation, and ‘smart’education
governance products. Simultaneously, problems of data (policy) fragmentation between the Ameri-
can states and districts were addressed with nation-wide initiatives such as the Data Quality Cam-
paign, which recommended the states to adopt common standards, to implement (centralised,
standardised) performance data management structures, and to build on (automated) ICT.
But also many non-western countries, such as the Russian Federation, have radically intensified
the datafication and digitalisation of education policy, which in the case of Russia led to a complex
surveillance regime, including an intensified production of ‘data on data production’(Piattoeva
2016).
Interestingly, some of today’s most developed ‘smart’educational monitoring and assessment sys-
tems are located in Estonia and Cambodia.
3
The Estonian Education Information System (EEIS,
www.eeis.ee) not only automatically collects, processes and evaluates individual educational data,
but at the same time links that data to international surveys such as PISA, to various research sur-
veys, and also to (constantly adjusted) assessment-building processes. Data access is hereby moni-
tored via individual ID-cards. In Cambodia, the Ministry of Education, Youth, and Sport
(MoEYS) tremendously reformed the educational system with the support of the non-profit organi-
sation World Education, Inc.(http://www.worlded.org, 9 December 2016), which not only fostered a
turn towards learning apps and digital classroom environments, but also towards continuous cross-
level assessment and evaluation. Therefore, World Education developed the TEST app assessment,
which automatically collects student performance data in a nationally/globally accessible cloud sys-
tem (https://wecambodia.exposure.co/learning-to-read, 9 December 2016), which can then be used
for administrative, accountability or teacher training purposes.
The German ‘turn’towards data infrastructuralisation after PISA
4
Germany as a system where the different states (Länder) hold almost all responsibility for edu-
cational governance (and more or less only for that policy field) is a good example of how the global
trend of performance data infrastructuralisation in education evoked very ambivalent policy
(re-)assemblage processes. In Germany, a combination of different factors in the past resulted in
a strong resistance against large-scale reform, particularly against supra-state control or incisive
(performance, data-based) accountability measures (Hartong 2015). One factor is a fairly high
level of teacher professionalism/autonomy within a state-controlled input system, which exerted
[…] weak control and evaluation of the processes and almost no external control of the outcomes [such as per-
formance data] of schooling. (Hopmann 2003, 472)
Another is a school structure which segregates different school tracks (Powell, Edelstein, and Blanck
2016), while the actual composition of that segregation again varies a lot between the states and the
different political constellations, ultimately resulting in a juxtaposition of very heterogeneous subna-
tional ‘path-dependencies’(Pierson 2000) (and policy assemblages).
The high level of state-centralised school authority, however, not only limited federal influence on
school policy, but also the range of autonomy for districts and communities (Kommunen). Regularly,
this led to extended debates about a systematic ineffectiveness of the system, which –despite the het-
erogeneity of the states –was (too) often ‘governed from a distance’.
GLOBALISATION, SOCIETIES AND EDUCATION 141
Against this backdrop, the recent turn towards performance data and (digital) data infrastructures
in German education policy can only be understood as the result of complex interactions between
‘catalysing’events and power shifts among policy actors at transnational, national and subnational
scales around the turn to the twenty-first century (see for similar findings in the Australian standard-
isation movement Savage and Lewis 2016). Unsurprisingly, one of the most important ‘catalysers’
was the PISA-‘shock’in 2001, whose wide-ranging effects have been examined within a large
body of research (e.g., Hartong 2012; Niemann 2010; Tillmann et al. 2008). With regard to data
infrastructures, the PISA-shock reflected the growing topological influence of international large-
scale databases and comparative educational monitoring instruments, which, by that time, had
also been intensively promoted by the European Union (e.g., the European Qualification Framework
or the Europass). The emergence of PISA and other international large-scale monitoring system ulti-
mately provoked a substantial transformation within the German field of educational research
(Aljets 2015), which opened up a unique opportunity for particular empirical research institutions
(which also served as the German PISA-consortium) to become core leaders in the post-PISA policy
agenda (Hartong 2015), including the implementation and expansion of performance data
infrastructures.
At the centre of this data infrastructuralisation stood an output-oriented national education
monitoring strategy, which included the creation of nationally centralised standards and assessments
(Tillmann et al. 2008), and which was led by the Standing Conference of the Ministers of Education of
the German States (Kultusministerkonferenz, KMK 2006). However, by that time, the KMK, which
traditionally formed a rather slow-reacting national arena for the coordination of state policies, stood
under enormous pressure by the Federal Ministry of Education (BMBF) to accelerate reform activi-
ties, to improve the overall educational performance, to close student achievement gaps and to more
effectively govern districts and communities. Consequently, the national reform agenda, which
formed up between 2002 and 2008, also included a range of federal (BMBF-) programmes to foster
local autonomy-building and reform empowerment, also in the field of monitoring and accountabil-
ity (see below).
At the same time, the BMBF initiated large funding programmes to strengthen and to stabilise
empirical research networks in the field of large-scale data surveys. One example was the establish-
ment of the National Educational Panel Study (NEPS) in 2009, funded by the BMBF and nested
within a network of more than 20 large German research institutions. Different from PISA, NEPS
was designed as a longitudinal educational survey, which tracks individual competency development
from Kindergarten (pre-elementary sector) to adult education. Six starting cohorts of over 60,000
persons, who to date have been repeatedly interviewed, were sampled through the years 2009–
2012. Eventually, in 2013,
[…] NEPS turned from a temporary research project into an infrastructure facility permanently financed under
the funding agreement between the German Federal and State Governments. (www.neps-data.de, 14 December
2016)
Moreover, in 2003, the KMK passed a resolution, which for the first time in German history obliged
the states to record a defined amount of nationally standardised, individualised data (e.g., school,
student or teacher data, yet excluding test performance data) (KMK 2003). Over the following
years, the states, though in varying speed and extent, responded to that resolution by centralising
and standardising their monitoring and reporting practices (see below).
Simultaneously, the national agenda brought more attention to profound data from ‘the local
level’(districts/Kommunen). Particularly promoted by the BMBF’sLocal Learning-programme
(Wilkoszewski and Sundby 2014, 19), districts were addressed to become more strongly activated
in educational monitoring, including the regular production of locally adjusted monitoring reports
(Döbert and Weishaupt 2012; Ratermann and Stöbe-Blossey 2012). Hereby, the Local Learning-pro-
gramme funded the creation of partnerships between districts and philanthropies, who, as experts in
142 S. HARTONG
education reform, should guide the local policy transformation (e.g., towards data-based policy-mak-
ing) and enhance transparency between districts and cities (e.g., through data exchange).
In sum, tremendous re-assemblage processes became initiated in Germany after PISA, which
included the implementation, expansion, standardisation and centralisation of performance data
infrastructures and platforms, as well as a new influence of data mediators. Such infrastructures
and actors became assembled together with (or around) governmental actors (such as the KMK,
the state or district departments), including the creation of new ‘centers of calculation’. Two
examples of such infrastructural ‘centers of calculation’will be closer illustrated in the following
sections.
The Institute for Educational Quality Improvement
In 2004, the KMK founded the Institute for Educational Quality Improvement (IQB) to support,
coordinate and to inform the implementation of educational standards and also the development
of standards-aligned assessments/tests on the national and state level.
In Germany, the PISA-study was from the beginning managed by a consortia of empirical
research institutions (now integrated in the ZIB, the Centre for International Student Assessment),
which, between 2000 and 2006, conducted an additional survey (PISA-E) for generating a significant
PISA-sample of the German states. After 2006, this additional survey became transformed into
‘PISA-BS’and re-designed to monitor the states’achievement of the national education standards
(BS), which had been developed by the KMK between 2002 and 2006 for both primary (fourth
grade) and secondary education (year of graduation, either ninth, tenth or 12/13th grade, depending
on the school track). The IQB became assigned with further processing PISA-BS into a state com-
parison study at ‘national’scale, including the development and supervision of assessment frame-
works, test items and reporting instruments, for both primary (fourth grade) and secondary
(ninth grade) education. Hence, after 2008, the IQB-test circle gradually developed an own self-
dynamic and infrastructure, which was officially decoupled from PISA and instead (re)assembled
around the development and monitoring of the national education standards.
On the one hand, the KMK explicitly accentuated this dissociation (here: dis-assemblage) of the
national performance monitoring from the OECD and PISA, which was justified by referring to
‘necessary cultural adjustments’. On the other hand, since the development of both the national stan-
dards and the national comparison study had gradually emerged (also) from PISA (also Waldow
2012, 169), the KMK, by that time, had already opted for a close alignment of the assessment designs,
which was also repeatedly manifested within the KMK monitoring resolutions (latest KMK 2015,5,
11). In other words, while different institutions became assigned with separately coordinating inter-
national (ZIB), and national (IQB) assessments as well as longitudinal monitoring (NEPS), the KMK
and also the BMBF still fostered a close alignment and maximal exchange of data, exemplarily
regarding the performance indicators, surveyed student/teacher background information (KMK
2015, 11), and also integrated databases within the IQB’s data centre (see below, see also http://
zib.education/en/about-zib.html, 24 July 2017).
A similar ambivalence between official assessment structure dissociation and simultaneous pro-
cesses of standardisation/integration can be observed in terms of the internal state comparison tests
(Vergleichsarbeiten, VERA), which are not sample-based but ‘[…] determine achievement levels of
all students at a certain grade’(IQB 2016), thus providing much more detailed information about the
[…] strengths and weaknesses of [individual] […] students[ classes and schools] with regard to the educational
standards. (IQB 2016)
VERA initially started as a subnational assessment harmonisation of seven German states in 2004,
coordinated by a university in southern Germany. Each of the states then used VERA data indivi-
dually (there was no comparison between the states) to monitor student performance and to use
that data for teaching improvement.
GLOBALISATION, SOCIETIES AND EDUCATION 143
Triggered by the national reform agenda and the monitoring strategy of the KMK, however, the
number of states participating in VERA gradually expanded after 2004, until the IQB once again took
over the meta-governance and coordination of test development and piloting for all VERA tests.
Again, the purpose was to better align VERA with the national standards. Consequently, the IQB
started to develop standards-aligned learning tasks for teachers to support test preparation and
test-related skill achievement. The tasks are accessible through a digital platform, which simul-
taneously collects and distributes particularly ‘framed’(standards-aligned) data, ultimately linking
the IQB directly to classroom practice.
At the same time, the states have remained responsible for administering VERA and for mediat-
ing the test data between schools and administration individually (while they are legally prohibited to
use the test results for school or student rankings, KMK 2012). Indeed, at least to date, the admin-
istration of VERA in the states (e.g., the distribution of responsibilities, the degree of test obligation,
the usage of test results either for school support or accountability purposes), and also the role VERA
plays compared to other state-level evaluation processes, varies a lot.
In other words, on the one hand the states officially retain the authority for all total educational
performance surveys, which has also been repeatedly clarified in the KMK monitoring strategies (see
latest KMK 2015). On the other hand, the IQB as a new, cross-scale data-mediating agency is
increasingly designing these tests and hereby produces detailed datapools, which link local, state-
related, national and also international data within new topological spatialisation. Consequently,
while public rankings of schools or individuals have remained prohibited (for now), the data and
infrastructure for such rankings is increasingly existent (see Figure 1).
Similar to the OECD, the IQB has not only acquired an enormous database for student perform-
ance data and background information through its own assessments, but simultaneously integrates
these database with other (e.g., the PISA-) datasets within an IQB in-house research data centre (For-
schungsdatenzentrum, FDZ), which documents the data and then makes it available for re- and sec-
ondary analysis.
[…] The FDZ also offers a broad variety of training seminars, such as workshops on specific data sets and their
appropriate analysis. Moreover, the FDZ organizes academies on advanced methodological issues in edu-
cational research and aims to promote the general infrastructure of research data in the field of education.
(IQB 2016)
Figure 1. Standardised performance assessments in Germany.
144 S. HARTONG
In sum, the establishment of the IQB appears as a significant catalyser within monitoring-oriented
re-assemblage processes in German education policy. The IQB (yet together with other research
institutions) has contributed to the implementation of large-scale performance data infrastructures,
which, particularly through the activities of the FDZ, are gradually integrating international (e.g.,
PISA), national (the state comparison study) and state-level data (e.g., VERA), while simultaneously
mediating large parts of that data back into research for further (aligned) data production. In other
words, even though the IQB was itself officially de-coupled from PISA (which was instead trans-
ferred to the ZIB), the PISA data is still part of the IQB- (and particularly ZIB-) practices.
At the same time, from the beginning, the IQB data production has been coupled to (here:
assembled together with) national standardisation policies, particularly to the evaluation and pro-
motion of the national education standards, which mark a core element of all IQB-assessments. Con-
sequently, with the recent ‘takeover’of the VERA test development, state-level monitoring activities
became partly dis-assembled from decentralised state authority, while the test administration and
also the disaggregated test results have, at least so far, remained with the states.
Still, the IQB has been fostering national and subnational standardisation processes, which are
increasingly ‘reaching into’the states, into classroom activities and also into educational research
practices. In other words, even though the states’educational authority (so far) still brings a large
amount of fragmentation into the assessment of educational performance, the IQB exercises increas-
ing topological power (Hartong 2014) by operating as a main supervisor for (further) standards
development, as a coordinator for standards-aligned data infrastructuralisation, and as a key host
for performance data, ultimately creating new visibilities for knowing subjects (Ruppert 2012).
New digital monitoring systems at the state and local level
Before PISA, the German states widely governed education by centrally providing input ‘resources’
(such as learning material or teachers) to the schools, and by distributing these resources based on
long-term requirement planning. The very broad data basis (school statistics) was delivered regularly
by the schools, which, however, often used different systems, and sometimes only provided fragmen-
ted data. At the same time, school (let alone student or teacher) performance data had been excluded
from those statistics.
As described above, the national monitoring strategy then categorically shifted the focus towards
the performance output of the German education system, which also demanded more detailed
reporting of what was happening/achieved inside the different states, districts and schools.
While in the initial years of reform, the states and districts mainly developed fragmented pilot
initiatives and sporadic reporting, the amount of cross-state and cross-district coordination regard-
ing reform exchange, and also the amount of standardisation, grew significantly after 2006. Crucial
here were the aforementioned funding and framework-setting initiatives from the federal ministry
(BMBF), but also the increasing involvement of intermediary actors (such as consultants, philan-
thropies or research institutions), who successfully ‘transferred’knowledge and built reform infra-
structures between the states and districts.
One example of such transfer activities has been the integration of reports or ‘extracted’data (e.g.,
particular graphs or distribution curves) into new digital platforms. One of many examples is the
website bildungsbericht.de, hosted by the German Institute for International Educational Research
(DIPF), which is also the producer of the national educational monitoring report, and which has
served as a member of the former PISA-consortia (now the ZIB). The website collects information
on the educational monitoring reports of all German states and (where available) districts. Some
states (such as Bavaria or North Rhine-Westphalia) also started to centralise district data into com-
mon formats (e.g., standardised data forms or particular types of visualisation), which, as ‘data pro-
files’are now quickly available online.
However, while the monitoring reports and data profiles may include aggregated student per-
formance data (such as generated through the IQB-assessments), such data has so far been
GLOBALISATION, SOCIETIES AND EDUCATION 145
widely limited, given the aforementioned legal prohibition to publicly compare school-based
performance or individual test results. Instead, the data mainly include school statistics, such
as number of schools/teachers/students, distribution of minority groups, graduation or drop-
out rates, which more indirectly provide information about (comparable) performance. This
fairly high level of data protection is also reflected in extensive restrictions of public access
to the databases.
Apart from the massive expansion of monitoring reports and their gradual integration into public
data platforms, a range of private firms has responded to the rising demand of data management by
developing new IT-solutions for the states and districts to better harmonise different data infrastruc-
tures. In many states, these new system solutions explicitly go beyond requirement planning pur-
poses, but (so far very vaguely) promise to effectively use both disaggregated and comparative
performance data for output-based decision-making (e.g., http://www.svp-rlp.de/projektinform
ationen/hintergrund.html, 23 June 2016). It remains to be seen how this rising market will be devel-
oping in the upcoming years.
Conclusion and outlook
In Germany, the ongoing expansion of data infrastructures for performance monitoring has particu-
larly been triggered by the PISA-study and the following national reform agenda. While this agenda
was led by the governmental body of the KMK, the resulting performance data infrastructures are
constituted by a complex assemblage, in which particular data mediators have turned into cross-sca-
lar ‘centers of calculation’. Such actors increasingly exert what has been conceptualised as ‘govern-
ance by numbers’or topological spatialisation, and which is currently ‘working through’the multi-
level policy architectures and institutional structures of the German federal system. At the same time,
such topological spatialisation increasingly works as a mode of ‘close’governmentality, which is sim-
ultaneously (meta-)governed from the physical absent (e.g., by IT-providers or global/national net-
works of data analysts).
In other words, while the KMK’s national monitoring strategy in the beginning evoked a hotch-
potch of fragmented data production and reporting, it was soon followed by a period of infrastruc-
turalisation and topologisation. In that regard, digital technologies triggered the expansion of
interface-development and data dashboarding (e.g., ‘data sheets’), which are simultaneously
embedded within transforming legal regulations of the KMK, the BMBF and the states. Hereby,
new policy assemblages have been created around objects and subjects, which are increasingly con-
stituted by (digital) data flows, resulting in new topological spatialisations and temporalities (such as
survey/assessment schedules) between the global and the local (also Sassen 2002, 365). New data
mediators (such as the IQB or the state-system providers) hereby link (digital) technologies and
data with different policy ‘levels’(international, national, state, district) and sectors (politics,
research, school practice, for-profit market), while continuously making decisions regarding assess-
ment design, ways of data processing or institutional network-building. Particularly because such
actors and digital platforms are usually operating in the background of policy-making or are
taken for granted, it seems the more important to pay more attention to their role and influence
within new policy assemblages.
While this contribution mainly presented initial findings from the German case, the worldwide
implementation and fast expansion of highly mobile, but still very opaque data infrastructures
offers new challenges also for international/comparative research. Assemblage theory and the con-
cept of topological spatialisation might offer new ways of comparatively rethinking the globalisa-
tion of path-dependent localities, and to more closely observe (power-related) mechanisms of
assemblage creation, stabilisation, or (de)territorialisation. Such comparisons might not only
map out varying scopes of databases, data mediators or assessments, but also their actual relation
(to each other or to governmental bodies) as well as their centrality within the different sectors of
education policy.
146 S. HARTONG
Notes
1. For an elaborated description and also critical reflection on what is commonly understood as ‘big data’, see
Boyd and Crawford (2012).
2. Education GPS operates through interactive data processing, which offers users a flexible, individual and auto-
mated combination and visualisation of data generated from large databases such as PISA (Williamson 2015a).
While Education GPS is officially hosted by the OECD, the visualisation technology as the core service of the
platform has been developed and is operated by the companies NComVA and TTangs.
3. I would like to thank Sam Sellar for calling my attention to this.
4. The following insights are related to an ongoing project, funded by the German Research Foundation (DFG,
project number HA 7367/2-1), which seeks to improve the understanding of digital-era governance and the
role of data management in education within the German federal context and also from an international com-
parative perspective (using the United States as a contrasting case). The project includes analyses of (1) policy
material, such as monitoring regulations, resolutions or digitalisation/datafication programmes (ongoing), (2)
the actors and institutions involved in performance data management at national and state level (ongoing), (3)
the performance data infrastructures and their modes of operation in three selected states per country (sched-
uled for 2018), as well as (4) interviews with national and state-level policy actors, technicians, administrators
and data system companies (scheduled for 2018). This article presents findings from an initial round of policy
material/actor analysis for the German case, complemented by secondary literature.
Disclosure statement
No potential conflict of interest was reported by the author.
Funding
The presented research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) –
project number HA 7367/2-1.
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