Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 1
Decoding identity: Reprogramming pedagogic
identities through algorithmic governance
Ben Williamson, School of Education, University of Stirling
Paper presented at British Educational Research Association
conference, University of Sussex, Brighton, 3 September 2013
Abstract: Recently there has been an accumulation of discourses around computer code,
algorithms, programming and software in public education. This article identifies new forms
of ‘governing by code’ in education: a particular approach to digital-era governance
facilitated by network-based communications technologies and database-driven information
processing devices. These new forms of network-based and database-led governance are
being promoted by third sector organisations including NESTA, RSA, Innovation Unit and
Nominet Trust that increasingly participate in educational governance in the UK. I explore
the style of ‘governing by code’ or ‘algorithmic governance’ endorsed by them and how this
feeds into new competence-based curriculum programmes, pedagogies of computer
programming, and the deployment of automated database-led ‘learning analytics’ software.
These computer-coded technologies and discourses have the potential to activate new
pedagogic identities for an imagined network-based and database-driven future.
Keywords: algorithm, computer code, database, governance, learning analytics, networks, third sector
Code acts in education
Computer code has become interwoven with the contemporary world. As software
travels out of the domain of computation, instructed by code and the algorithmic
procedures scripted by programmers, it has the capacity to influence everything it
touches (Fuller 2008). Moreover, a steady accumulation of discourses around code
works to persuade people to think and act in relation to software. Code discursively
‘transforms and reconfigures the world in relation to its own systems of thought’
(Kitchin and Dodge 2011: 43). Consequently, the contemporary world is increasingly
ordered and arranged by ‘algorithmic power’ (Beer 2009) and regulated by the
‘governing algorithms’ (Barocas, Hood & Ziewitz 2013) that are written in computer
code. The productivity of code to act on social forms, the power of governing code,
and its diffusion into everyday systems of thought are all evidence of how code—
including the algorithms it enables and the software it instructs—has now become a
significant social actor. The power of code is not just in its technical instructions but
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 2
in how it sinks into collective discourse, thought, action and identity formation
(Mackenzie 2006).
Taking up arguments about code, algorithmic processes and software as a system of
thought with the power to act and govern, this article is focused on an accumulation
of discourses and thinking around computer code, programming, algorithms and
software in public education. Discourses delimit what and how education can be
thought, spoken and done, and code has been justified and naturalised discursively
as a seemingly common sense solution to a whole range of educational problems.
From the use of electronic attendance registers, the growth of educational
technologies and the use of commercial management and administration tools, to the
collection and analysis of learners’ performance data, code can now be seen to be
mediating, augmenting, and ultimately co-producing pedagogies, curricula, policies
and modes of governance.
The central argument I make is that techniques and discourses of ‘governing by
numbers’ (Grek 2009) are being augmented with techniques and discourses of
‘governing by code.’ Where governing by numbers utilises statistical instruments,
measurement techniques, and the discourse of comparison, governing by code
depends on the deployment of sophisticated software instruments (especially
networks and databases) which, instructed by code and legitimised through related
discourses, have the ‘algorithmic power’ to participate as policy actors in public
education, and to activate the capacities of the individual learner.
In particular, I focus on the participation of ‘third sector’ organisations in promoting
new forms of governing by code, notably organisations such as the Innovation Unit,
Royal Society of Arts, Manufactures & Commerce (RSA) , Nominet Trust and the
National Endowment for Science, Technology and the Arts (NESTA). I have written
about these organisations in terms of their ideological positioning and their
contribution to new forms of cross-sectoral ‘network governance’ before (Williamson
2012, 2013); now I focus specifically on how these organisations take a current
preoccupation with computer code, algorithms and programming as discourses for
reimagining public education. From a Foucauldian perspective, the educational
technology researcher Selwyn (2013) reminds us that discourse is the historical and
cultural production of systems of knowledge and beliefs that are both shaped by,
and shape, our behaviour, and that all aspects of technology use in education are
ultimately constructed in political, professional, academic and commercial discursive
arenas. This article is concerned with how third sector discourses associated with
computer code are making the future of education thinkable, practicable and
governable in terms of network architectures and the algorithmic logic of databases.
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 3
Two key questions run through the analysis. How are the discourses and techniques
of ‘governing by code’ in education being generated and circulated? Following from
that, what pedagogic practices and identities are being discursively constructed and
promoted in relation to code, and what ways of thinking and doing are being
conferred upon these pedagogic identities? Adopting methods of policy text and
discourse analysis (Ball 2008), I focus on the reports, pamphlets, websites and other
documents which articulate third sector ideas and aspirations, and which make the
future of education intelligible, thinkable, and practicable through discourses and
activities related to computer code.
Analytically, I draw on two key clusters of concepts. The first cluster of ideas
concerns governance, particularly the idea of ‘governing by code’ and related ideas
about ‘digital-era governance’ (Margetts & Dunleavy 2013) now circulating in the
governance literature in public policy and political science (Cairney 2012). The
second cluster concerns identity and draws on Bernstein’s (2000) concept of
‘prospective pedagogic identities’ that are constructed and promoted to learners as
sources of identification in order to stabilise preferred visions of the future. This is
interwoven with Hacking’s (2007) understanding that identifications of people
interact with and affect the people identified. Following this approach to identity, the
focus is not on what learners’ identities ‘really are’ but in what governing authorities
(from whatever sector) want them to be, as future persons to come for futures still in
the making. Specifically, the article queries what potential identity formations are
promoted through the pedagogic practices and discourses made possible by new
forms of network-based and database-driven digital governance being endorsed in
education.
Code and curriculum
Computer code is commonly understood as the machine-readable language
programmed to instruct computer software. A growing recognition of the power of
code is reflected in popular science publications like 9 Algorithms that Changed the
Future (MacCormick 2013). Yet as code is wired out into the world in software
products, it is now understood among many social scientists as more than just the
written script that instructs and controls computing devices. Albeit unevenly and
often invisibly, code is woven into the substrate of contemporary societies as a mass-
produced set of instructions with the power to shape how people think, act, and
conduct themselves (Thrift 2005). Through ‘software-sorting’ processes (Graham
2005) it organises, disrupts and participates in contemporary social, economic,
political and cultural activities and practices. Sociotechnically understood as both a
product of the world and a relational producer of the world, code acts: it interpolates,
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 4
mixes with and ultimately produces collective political, economic and cultural life
(Kitchin & Dodge 2011).
Given its sociotechnical reach, code ‘has been associated with processes of identity
formation, new modes of production, commodification and consumption (in the
digital economy), and sometimes as a reinvented public sphere,’ all
conceptualisations which ‘carry with them notions of agency, either in relation to
what software does as a technology or what people do with software as they make
use of it’ (Mackenzie 2006: 172). In everyday life this raises the issue of the
‘technological challenges to human agency offered by the decision-making powers of
established and emergent software algorithms’ and the extent to which ‘algorithmic
power’ may be ‘becoming a part of how we live, a part of our being, a part of how
we do things, the way we are treated, the things we encounter, our way of life’ (Beer
2009: 987). Institutionally, code makes possible the techniques of data collection,
collation and calculation without which, Chun (20011) argues, there would be no
government, no corporations, no global marketplace, and no schools. It may even be
‘reassembling social science’ itself (Ruppert, Law & Savage 2013) as new digital
methods and search algorithms influence academic practice and make possible new
analyses, configurations and visualisations of the social.
Moreover, people view and understand code through the deployment of powerful
and consistent discourses that promote, justify and naturalise software across a
whole array of domains (Kitchin & Dodge 2011). All of these things add up to a
pervasive system of thought within which the rule-based logic of algorithms (the
procedures and processes written in code) may be taken as a new set of rules and
mundane routines to live by. The power of code is not just in its technical operations
but in how it sinks into everyday cultural, economic and political thought.
In the field of education, ‘algorithmic power’ is shaping processes of governing as
well as pedagogic spaces, practices and identities. Specifically in relation to
pedagogy, there has been a recent explosion of interest in children learning the skills
of computer programming (Naughton 2012). This trend is reflected in the
proliferation of after-school ‘Code Clubs,’ volunteer-run programming classes
increasingly being sponsored by computing corporations like Google (Lamden 2013;
Sweeney 2013). In education policy, commercial internet companies such as Google
and Facebook have made high-profile media presentations criticising the UK for
producing too few skilled graduates in programming that have made it directly into
the discursive repertoire of policymaking at the Department for Education in
England (DfE 2012).
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 5
Third sector organisations have been important actors in this policy shift, and in a
wider reimagining of education through the promotion of techniques and discourses
associated with code. In what follows, I now want to examine how computer code,
algorithmic routines, and programming have been deployed by third sector
organisations as discourses and techniques for reimagining and reconfiguring public
education. I term this governing by code. Ultimately, through reshaping educational
governance, pedagogies and curricula, these organisations are participating in the
reassembling of learners’ potential pedagogic identities.
Algorithmic governance
Why are code, algorithmic processes, and programming important to third sector
organisations? NESTA, Nominet Trust, RSA and Innovation Unit documents all talk
of computational forms as models for reinventing educational governance. NESTA
chief executive Geoff Mulgan (2005), for example, writes of the ‘co-evolution’ of
computational technologies with decentralised ‘matrix models’ of ‘e.governance’ that
involve civil society organisations participating in all public services facilitated by
software. And Charles Leadbeater (2011), who has worked in a variety of roles across
the third sector, endorses the potential for ‘government by algorithm,’ an approach
to governance involving systems to mine and analyse ‘big data’ and algorithmic
methods to create ‘more effective and intelligent public systems’ (Leadbeater 2011:
18). NESTA was established by the New Labour government in 1998 and, though it is
now fully independent of government, it participates in many debates about public
sector reform. Many of its documents, projects and web pages specifically mobilise
technological discourses to reimagine future public services, with network and
database technologies dominant among these.
Recently writing together in a NESTA publication, Mulgan and Leadbeater (2013)
both advocate ‘systems innovation,’ based on the idea of networks of interconnected
innovations, which specifies the form of the network as a model for reforming,
adapting and creating better systems:
We have embraced vast new system for creating, sharing, processing and analysing
information from the Internet and the world wide web, through to new generations of mobile
phones, and social media to the possibilities of cloud computing, the semantic web, and the
Internet of Things. These digital platforms could allow us to create more distributed,
networked systems to achieve feats of coordination previously associated with large
hierarchical organizations. (Mulgan & Leadbeater 2013: 30).
The publication is illustrated with ‘systems maps’ and ‘diagrams’ of the various
feedback loops and feed-forward mechanisms, causal links and levers which
underpin network dynamics. The authors embrace the notion of using ‘big data’
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 6
sources to track and trace individuals as they go about their daily lives online. These
data include transactional data, such as that generated through online shopping,
using transport, and making entertainment choices; and personal and behavioural
data shared on blogs and social networks like Facebook. As political scientists
Margetts & Sutcliffe (2013: 139) point out, this big data not only offers scope for
understanding human behaviour, social structure, and citizens’ civic engagement; it
can ‘also be used for algorithmic and probabilistic policymaking’ and ‘for more
coercive modes of governance, whether by introducing conditionality into public
policy and services or simply exerting “nudges.”’
This is what Ruppert (2012: 117-118) calls ‘database government,’ a ‘science-in-the-
making’ which has shifted the focus of government from the ‘qualitative’ governance
of the social to the ‘quantitative’ governance of the ‘informational.’ As she further
argues, ‘database government’ signals:
a changing relation to data as well as relation to quantification in social, commercial and
governmental domains. It is a relation that is part of a technocratic infrastructure for knowing
subjects and populations, not so much in relation to pre-defined categories of identity but in
relation to what people do, their interactions, transactions, performance, activities and
movements in relation to government. (Ruppert 2012: 119)
From this perspective, database government does not merely ‘add up data’ on
subjects and what they do, but ‘materialises’ them in fluctuating and distributed
ways, a point taken up again later in relation to database-driven learning analytics.
The arguments of Mulgan, Leadbeater, and the approaches that the organisations to
which they are attached appear to endorse, represent a form of ‘digital-era
governance,’ which Margetts and Dunleavy (2013: 6) describe as ‘the adaptation of
the public sector to completely embrace and imbed electronic delivery at the heart of
the government business model.’ Digital-era governance, they argue, is a response to
technological developments such as analysing big data from transactional processes,
peer production, network effects, and to new popular ideas of ‘crowdsourcing,’
‘cognitive surplus,’ ‘wikinomics,’ and the ‘Internet of Things.’ In their model the key
features of digital-era governance can be summarised as:
Automated ‘zero-touch’ technologies Digital by default public service
transactions and interactions
Behavioural policy & persuasive ‘nudge’
technologies Government cloud
Big data analysis Intelligent centre—real-time government
data-pooling
Co-production or co-creation of services
Isocratic DIY administration
Database-led information processing
Joined-up governance
Decentralised delivery design
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 7
Networks-based communications Reprocessing data for public
consumption
Open book government & citizen-
auditors Social web development within online
government
Open data initiatives—freeing public
information for reuse, mashups etc.
(Margetts & Dunleavy (2013)
Significantly, digital-era governance is enabled by the coupling of network-based
communications technologies and database-led information processing technologies.
On the one hand, networks allow for forms of governance through communication
with individuals—governance with a voice maybe. On the other hand, database
technologies allow for forms of governance through gathering information about
individuals—governance with a brain. Combining these technologies, digital styles
of governance, then, are to be managed by an ‘intelligent centre’ but facilitated
through ‘decentralised delivery.’
Networks and databases are thus the dominant technological forms facilitating the
reinvention of governance. However, neither networks nor databases are neutral
devices, but are entangled in normative imaginings of the future. In relation to the
former, ‘networks provide a diagram on the basis of which reality might be
refashioned and reimagined: they are models of the political future’ (Barry 2001: 87).
Likewise, a ‘database way of thinking’ about governing seeks to intervene, through
‘personalised packages of public services,’ in ‘both who people are and who they are
possibly becoming’ (Ruppert 2012: 128, 130).
According to Margetts and Dunleavy (2013) central government is lagging behind
both the private sector and civil society in the digitization of governance. This is a
key point for my argument that through their deployment of discourses concerning
networks and databases in digital-era governance, third sector organisations such as
NESTA, RSA, Innovation Unit and Nominet Trust are seeking to make education a
particular target for reform.
Networks of competence
Digital governance is constituted by network communication technologies and
database-driven information processing. In this section I examine how the form of
the network has been deployed by third sector organisations as a model for
reinventing the school curriculum, with a particular emphasis on the RSA Opening
Minds programme and the Learning Futures programme run by the Innovation
Unit. Technically, networks are understood as a complex ‘algorithmic mosaic of
calculations carried out to allow communication to occur in the presence of many
others’ (Mackenzie 2010: 68). Networks are thus constituted by the processes coded
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 8
and expressed in algorithms. Through Opening Minds and Learning Futures, the
algorithmic structuring of networks is positioned as co-evolving with the
reimagining of education.
Opening Minds was initiated by the Royal Society for Arts, Manufactures and
Commerce (RSA) as a ‘competence-based curriculum which aims to equip young
people with the skills they will need for life and work in the knowledge-intensive
and new media-rich 21st century.’ Initially trialed for three years from 1999 in a small
cluster of secondary schools, by 2012 Opening Minds had become an independent
charitable organisation, the competencies curriculum had extended to a network of
200 schools nationwide, and the RSA had established its own flagship school in
Manchester. In 2013 it announced plans to launch a training centre, a CPD
programme entitled ‘Grand Curriculum Designs,’ and an ‘OM online toolkit’ for use
by schools (RSA 2013). Rather than focusing on academic ‘performance,’ the
specialisation of subjects, skills and procedures, and the selection, sequencing and
pacing of pedagogy by teachers, Opening Minds emphasizes competences including
many related to computer technologies and related discourses. These include
handling ICT and understanding its underlying processes; understanding the social
implications of technology; team work and communication; being entrepreneurial
and initiative-taking, managing risk and uncertainty; and managing, accessing,
evaluating, differentiating, analysing, synthesizing and applying information.
In a report prepared for the RSA, Ormerod (2010: 10) argues from a highly
normative position that networks should be considered as an ‘intellectual
framework’ and a ‘mindset’ for understanding how societies and economies
function, and thus to inform how policies are devised and planned. Ormerod’s essay
refers to networks in terms of ‘social networks’ and ‘social learning’—learning
through observation and interaction with others—and to networks in general as the
‘patterns of connections between individuals,’ as well as to large-scale ‘networked
systems’ such as crowds, stock markets, and ‘scale free networks’ such as the World
Wide Web (Ormerod 2010: 14-15, 29-30). All of these approaches to the
understanding of networks—social and technical—are reflected in the Opening
Minds curriculum. Just as the network has become prevalent as a metaphor for
individual and collective life, economics and politics, it has also been mobilised, as
Opening Minds demonstrates, as a diagram for reimagining public education.
Further evidence of the prevalence of the idea of networks among third sector
organisations comes from the Innovation Unit. The Innovation Unit is a social
enterprise first formed within the Department for Education and Skills in 2002 and
spun-out as an independent not-for-profit organization in 2006 with a mission to
innovate in public services. In line with RSA’s networks mindset and NESTA’s
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 9
emphasis on networked systems innovation, the Innovation Unit endorses the idea
of an ‘innovation ecosystem’ for education. In such an educational ecosystem school
is imagined as a ‘base camp for enquiry’ that is supported beyond school by the
internet, mobile technologies, and a ‘vastly increased number of education
providers,’ many accessed virtually. The Learning Futures curriculum vision is based
on a model of a network of ‘extended learning relationships’ including teachers,
tutors, experts, mentors, coaches, peers, and families as well as industry, local
businesses, cultural institutions, community organizations, and the internet
(Learning Futures 2012: 11).
In this innovation ecosystem, education is reimagined through the imagery of the
use of social networking sites to encourage peer-to-peer learning and collaborative
research; online chat, instant messaging and email to help to strengthen the student-
teacher relationship; digital portfolios as a continuous performative record of
assessment; the use of Twitter hashtags to collate research sources (Hampson, Patton
& Shanks 2012). Learning Futures constructs pedagogic identities that can be
characterised as networked learners participating in a connected ecosystem of
learning at home, at school and online—for a prospective future in which the
internet itself is presupposed as a new learning institution. Finally, Learning Futures
suggests the use of performance technologies which can collect data in order to
‘know’ learners, sort and aggregate them on the basis of personal and behavioural
data, and respond with an algorithmically generated ‘playlist’ of appropriate
personalized pedagogy (Hampson, Patton & Shanks 2012).
The main message system of both Opening Minds and Learning Futures is that more
competence and skills-based curricula and pedagogies are required to equip young
people with the skills they will require for life and work in an increasingly
networked, knowledge-intensive and media-rich future. Through the discourse they
deploy they make the school curriculum appear to be an outdated relic of an era of
enclosures that is at odds with the emergent possibilities of open networks,
interconnected systems, interactivity and participation facilitated by the internet.
Discursively framed by the RSA and the Innovation Unit in this way, the idea of the
network ‘seems easily and routinely to criss-cross the distinction between the
technical and the social,’ though the idea that the social world can be ‘imagined and
acted upon as if it were a system of networks and flows’ is a ‘typically modern
political fantasy’ (Barry 2001: 14, 16):
A key part of the attractiveness of the network model is the way it can simultaneously serve as
a response to two intersecting problematisations of the present. On the one hand, networks,
conceived as technologies, are thought of as solutions to a whole series of problems
concerning the fragmentation of communities, the problem of empowerment, the decline in
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 10
democratic participation, the crisis in scientific and technical literacy, and the need to foster
new forms of entrepreneurial activity and freedom. On the other hand, networks, conceived
of as social and political relations, are reckoned to be solutions to many of the economic
problems of society such as fostering a culture of invention and innovation and meeting the
challenges of globalisation. (Barry 2001: 87)
Opening Minds and Learning Futures are similarly positioned in relation to these
problematisations of the present, from issues of community-building, student
empowerment, and participation, to technical literacy, entrepreneurship and
innovation. These programmes turn on the idea of the network for the reinvention
of the curriculum, and are fashioned on the network as a diagram for solving a
whole series of social, political and economic problems.
Moreover, Opening Minds and Learning Futures anticipate learners’ entry into a
network-based digital economy which is premised on notions of flexibility, speed,
virtuality, just-in-time-production, teamwork, and other aspects of ‘immaterial
labour’ –all activities epitomised in the work of computer programmers (Mackenzie
2006). Thus an emphasis on immaterial digital skills is part of what Barry (2001)
describes as the contemporary political preoccupation with sculpting a mind and
body with the technical skills, knowledge and capacity to meet the demands of new
flexible work routines: making up a subject with the appropriate conduct and
mentality for contemporary regimes of political and economic governance. These
activities ‘govern by activating the capacities of the individual’ to contribute to the
digital economy (Ozga, Segerholm & Simola 2011: 88).
The individual activated by Opening Minds and Learning Futures is a flexible
subject who educational sociologist Bernstein (2000) would describe as a ‘prospective
pedagogic identity’ constructed and promoted in educational institutions in order to
‘deal with cultural, economic and technological change’ and ‘stabilise the future’
(Bernstein 2000: 68 original emphases). With prospective identities what is important
is the construction of appropriate attitudes, dispositions and performances for
preferred futures. Bernstein charted the emergence of a particular kind of
prospective learning identity, one which possesses ‘flexible transferable potential,’
the capacity to be ‘appropriately formed and re-formed according to technological,
organisational and market contingencies,’ and the ability to be taught, continuously
and lifelong, in order to project him- or herself meaningfully into a ‘pedagogised
future’ (Bernstein 2000: 59). The flexible subject being activated for immaterial labour
by Opening Minds and Learning Futures, then, is anticipated by Bernstein’s notion
of a flexible prospective pedagogic identity which is epitomised by the work of
computer programmers. It should come as little surprise, then, that computer
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 11
programming has itself become the focus for new pedagogic and curricular
interventions by third sector organisations.
Programming pedagogies
Today there is a growing interest in promoting computer programming to young
people. The evidence for this is in the fast growth of ‘Code Club’, a volunteer-based
initiative that places computer programmers in after-school clubs in primary schools
to teach young children basic programming and coding, and in the proliferation of
activities around the Raspberry Pi device. Code Club is sponsored and promoted by
NESTA and the Nominet Trust with funding from the Department for Education,
and it is marketed simultaneously in terms of the educational benefits and the
economic benefits of upskilling children as computer programmers. According to the
organisers of Code Club:
Learning to code is an important skill now we’re living in a digital age. It’s not just enough for
children to know how to use technology. They should know how it works too.
Learning to code doesn’t just mean you can become a developer, it strengthens problem
solving skills and logical thinking and supports key academic subjects such as science, maths
and technology.
Code Club is about fun, creativity and learning through exploring. … They should
understand that they’re in charge of the computer, and can (and should) make it do what they
want, not the other way around.
Other benefits of Code Club, such as learning about computational thinking, or developing
expertise in coding, are secondary to these two objectives. Having said that, children will
absorb all these wonderful skills as they work through the projects rather than through
didactic teaching. (Code Club 2013)
NESTA’s Next Gen report is a key policy text in this area, while the RSA ran a
‘FutureMaker’ workshop event in June 2013, hosted a seminar on ‘Coding and
Creativity: Programming, Computational Thinking and the Arts in Schools’ in July
2013, and is supporting the use of the Raspberry Pi device for programming in
schools. These third sector organisations are all closely interwoven through efforts to
establish the pedagogic legitimacy of coding and programming.
Furthermore, NESTA and the Nominet Trust, in partnership with the internet
company Mozilla, are running an initiative called Make Things Do Stuff that
promotes various forms of programming and ‘digital making’:
Make Things Do Stuff aims to mobilise the next generation of digital makers. We want to help
people to make the shift from consuming digital technologies, to making and building their
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 12
own. Because when all kinds of different people start hacking, re-mixing and making things
with technology, the possibilities get really interesting. Make Things Do Stuff will enable
people to … navigate a path that will take them from being a digital consumer, to being a
digital maker. (Make Things Do Stuff 2013a)
The initiative is described as an ‘open movement’ and is partnered with a range of
technology companies, education businesses, third sector organisations, and
government. These include Facebook, Microsoft, O2, Mozilla, and Virgin Media;
Codecademy, Coding for Kids, Decoded; and HM Government, the Scottish
Government and the Teacher Development Trust. The government Chancellor of the
Exchequer, George Osborne MP, launched the initiative in May claiming that ‘this
campaign is backing the entrepreneurs of the future and helping ensure that Britain
is equipped to succeed in the global race’ (HM Treasury 2013).
The Nominet Trust has perhaps taken the intellectual lead in the area of digital
making and computer programming, with a series of reports, events, projects and
blogs dedicated to the topic. The organisation itself was established in 2008 by
Nominet, the internet registry which maintains the .uk register of domain names.
The Nominet Trust invests in projects and programmes ‘using the internet to address
big social challenges.’ The trust describes itself through the discourse of social
investment, social innovation, and social technology entrepreneurship. The chief
executive of Nominet Trust was formerly the chief executive of the NESTA initiative
Futurelab, while several key members of staff have also moved from Futurelab to the
trust, and both Geoff Mulgan and Charles Leadbeater perform Trustee duties for it.
Nominet Trust chief executive Annika Small claims there is a ‘serious and economic
imperative’ besides the ‘fun and learning that digital making offers young people,’
namely that the ‘UK and global jobs market are crying out for digital skills and we
need to make sure that the next generation can meet this need’ (Nominet Trust 2013).
These activities are justified through a combination of discourses about the growing
role of computational code in the contemporary world and the need of commercial
computer companies. The Make Things Do Stuff website states that: ‘In a world
where everything from fridges to cars, bank accounts to medical diagnoses are
becoming powered by computing, understanding how digital technologies are made
(and how to make your own) is vital to full participation in society’ (Make Things Do
Stuff 2013b). Furthermore, it juxtaposes a constructivist understanding of ‘making
something, sharing it and getting feedback’ as ‘ a powerful way to learn,’ with how
‘digital technologies are developed in the real world: get something made, get it out
there, get feedback, learn, and make it better’ (Make Things Do Stuff 2013b).
What to make of the emphasis on digital making and programming code in terms of
its promotion of prospective pedagogic identities? One way to think about this is to
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 13
view the programming of code as promoting practices of ‘co-production,’
‘crowdsourcing’ and ‘prosumption’ in new social media practices. Beer & Burrows
(2013: 49) argue that network-based social media—Facebook, Twitter, YouTube,
Wikipedia, and so on—have facilitated the increasing participation of people in the
formation of media content, leading to the ‘significant phenomena of the growing
amount of “labouring” people are undertaking as they “play” with these new
technologies: creating profiles, making status updates; distributing information;
sharing files; uploading images; blogging, tweeting; and the rest.’ Ideas associated
with participation in the networked cultures of social media, such as co-production,
prosumption, crowdsourcing, user-centred design, and so on, have long been
attractive within the third sector, which has put such practices at the centre of its
reformatory ambitions for government, public services, and innovation (e.g. Coyle
2009; Gillinson, Horne & Baeck 2010).
Learning to programme is a logical outgrowth of this proliferation of technologies of
co-construction, crowdsourcing and prosumption, a kind of training for new
practices of media production in a highly networked social media culture. These
algorithmically mediated practices promote the idea of the learner as a ‘self-
programming’ individual with the capacity to script a unique identity through new
‘technologies of the self,’ for example by updating social network site profiles,
editing wikis, writing blogs, and other social media practices which shape ‘how
individuals think, act, interact, and identify themselves’ (Loveless & Williamson
2013: 68). This is a self-programming pedagogic identity akin to Castells’ (1996)
notion of technically advanced ‘self-programmable’ workers in the ‘network society.’
However, network-based activities of programming, prosumption and so on are also
interweaving individuals more and more densely into new database architectures:
This type of media engagement, premised on participation of various types, is creating vast
and new forms of data about us … [and ] creating new forms of social data—data generated
as a by-product of new forms of cultural engagement. We are concerned with how this by-
product data also comes to constitute and reshape cultural forms and practices as they occur.
(Beer & Burrows 2013: 49)
Database pedagogies
In recent years there has been an explosion of interest in database-led technologies of
‘big data,’ ‘data mining,’ and ‘data analytics,’ all of which have been taken up
enthusiastically by third sector organisations such as NESTA (e.g. Davies 2013).
Database-driven technologies are today significant since ‘the sociotechnical
instantiation of many aspects of the contemporary world depend on database
architectures and database management techniques’ and the technical processes of
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 14
‘ordering, sorting, counting, and calculating’ that they involve (Mackenzie 2012: 335,
338).
A specific development related to these database-led technologies in the field of
education has been the growth of ‘learning analytics.’ NESTA has advocated
‘adaptive learning technologies’ which use student data, algorithmic learning
analytics and feedback mechanisms to adapt and personalise learning:
Adaptive learning technologies use student data to adapt the way information is delivered to
a student on an individual level. This data can range from online test scores to session time
(how long users spend on a single exercise) to records of where a user has clicked or touched
while figuring out a problem. Based on this feedback, the programme will understand which
content to point the user at next—planning a personalised learning journey. (Nesta 2013a)
An accompanying NESTA document claims these adaptive technologies provide ‘the
means to shift away from a one-to-many model of teaching, so that every child has a
'digital tutor' that is responsive to their interests, their prior-conceptions and
achievement’; and the potential for ‘intelligent online platforms that can use data
gathered from learners to become smart enough to predict, and then appropriately
assist and assess, that learner's progression to mastering the concept being taught’
(Nesta 2013b). Buckingham-Shum (2012) has described learning analytics as a
‘digital nervous system’ for education, an artificial ‘brain or collective intelligence’
that can measure and interpret a learner’s activity, provide real-time feedback and
adapt the learner’s future behaviour accordingly. The applications of learning
analytics include tailored course offerings, predictive modelling, learner profiling,
and the design of ‘intelligent curriculum.’ The aim of some learning analytics
developments is to create automated pedagogic systems, or what might be termed
database pedagogies. These database pedagogies can include automated messages
which provide brief and simple nudges or fully automated intelligent tutoring
systems: the automatic production of personalised pedagogies.
NESTA has specifically supported and promoted Beluga Learning, a learning system
based on the application of data-based learning analytics, adaptive software and
artificial intelligence technologies. The Chief Executive of Beluga has also spoken at
a major NESTA event launching a ‘decoding learning’ report. The Beluga system
makes use of two types of learner data. It collects ‘intelligent data’ such as
curriculum data, semantic data and linked data that is often collected by educational
institutions. It also collects ‘off-put data’ from students’ own social media
programmes and conducts ‘smart analysis’ on both of these sources of data in order
to create a profile of each individual user which can be compared and matched with
an entire population of user profiles:
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 15
The data is allowing the software to make a real-time prediction about the learner and
changes the environment, … the pedagogy and the social experience. … This process occurs
continually and in realtime, so that with every new piece of data collected on the student,
their profile changes and the analytical software re-searches the population to compare once
more. … The content and environment then adapt continually to meet the needs of the
learner. (Beluga Learning 5-6)
Beluga Learning utilises advances in artificial intelligence, combined with learning
analytics and adaptive learning, to develop a ‘smart system’ that is able to ‘behave
with an intelligence’ and circumvent the role of the teacher.
Database-led learning analytics and adaptive software systems such as Beluga
exemplify what Kitchin and Dodge (2011: 85) have termed ‘automated management.’
This term captures how new software systems can be coded to collect and process
information about people and things in ways that are increasingly automated
(technologically enacted), automatic (the technology performs without prompting or
direction) and autonomous (making judgements and enacting outcomes
algorithmically without human intervention). Automated management is a form of
governance that uses surveillance data to target and reshape behaviour:
Unlike traditional forms of surveillance that seek to self-discipline, new forms of surveillance
seek to produce objectified individuals where the vast amount of [data] harvested about them
is used to classify, sort, and differentially treat them, and actively shapes their behaviour. …
Software … makes possible a fundamental shift in how information is gathered, by whom, for
what purposes, and how it is applied to anticipate individuals’ future lives. (Kitchin & Dodge
2011: 86)
The codes and algorithms of databases work by collecting , compiling and
calculating transactional data about people, and creating profiles and classifications
in order to sort and sift them for a variety of (sometimes political) purposes (Ruppert
& Savage 2012). This constructs algorithmically a digital shadow-profile, or a kind of
data-based doppelganger, that can precede individuals wherever they go (shopping,
travelling, working, learning) and may be used to modify how each person is
treated. Thus, educationally speaking, transactional data is now being utilised as a
governing resource for classifying, sorting and ordering learners, and for
anticipating and activating their future behaviour (Williamson 2014).
A key issue emerging from these developments of automated, automatic and
autonomous database technologies concerns the assumptions about the learner that
are programmed into the system. For Facer (2013: 715), educational databases
‘reconstruct’ the learner as a ‘cybernetic system’ made up of inputs and outputs
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 16
rather than an ‘embodied person.’ As Ruppert (2012: 125) has argued in relation to
government education databases:
database devices are based on the logic that the subject is made up of unique combinations of
distributed transactional metrics that reveal who they are and their capacities, problems and
needs. An individual is not simply a child or youth, but rather a combination of needs and
services.
Consequently, children can be ‘discovered and made up by these technologies’ as a
‘potential future person yet to come’ (Amoore cited in Ruppert 2012: 131). Learning
analytics is perhaps the ideal pedagogic technology for ‘knowing capitalism’ (Thrift
2005) which mobilizes powerful data collecting and calculating technologies to know
and act upon individuals and populations. In education this is a process which
requires knowledge and information about learners to be ‘collated, monitored and
interpreted by service providers, and even used as the basis for forecasting future
needs’ (Grek & Ozga 2010: 285). The process involves defining ‘personalised
packages’ of pedagogies for learners that are ‘formulated from distributed data
about them and targeted to meet their needs but not seen by them’ (Ruppert 2012:
128).
What are the implications of learning analytics and similar database pedagogies for
the promotion of pedagogic identities? One way to conceive of learning analytics is
through the notion of recursive feedback. In an analysis of recursive data in
contemporary popular culture, Beer and Burrows (2013) argue that data
accumulation does not just ‘capture’ culture but is recombined through feedback
loops to actually shape, reconstitute and co-construct popular culture and everyday
practices. They offer examples such as automated recommendations services and
‘behavioural advertising’ in consumption practices. These services accumulate
personal and behavioural data from online transactions and run these data through
predictive analytics in order to generate personalised recommendations. These
systems work recursively by continually harvesting by-product data and feeding it
back into their predictive recommendations. There is undoubtedly algorithmic
power at work in such devices, ‘not of someone directly having power over someone
else,’ but the programmed power of ‘the software making choices and connections in
complex and unpredictable ways in order to shape the everyday experiences of the
user’ (Beer 2009: 997).
Shaped recursively through such feedback loops, the pedagogic identity formation
presupposed by database pedagogy is, as Cheney-Lippold (2011) has argued in
relation to databases generally, an ‘algorithmic identity,’ an effect of computational
processes which infer categories of identity on the basis of the collection and analysis
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 17
of personal information and behavioural data. An algorithmic pedagogic identity
associated with database pedagogies is algorithmically inferred from its transactions,
its generation of data, and its amenability to intervention through data-based
analytics technologies. These technologies work recursively and dynamically to
identify individuals based on patterns and regularities; on that basis to make
predictions and recommendations for learners; and through those algorithmic
processes, to shape and structure how they might think and act in the future.
The process follows Hacking’s (2007: 285) contention that technologies of
identification and classification ‘interact’ in the process of ‘making up’ new ‘kinds of
people.’ As Ruppert (2012: 128-29) explains in relation to government databases, the
distributed data used to produce personalised packages of services ‘may interact
with the people through governing interventions that reinforce the “identity” of a
person so discovered’; that is to say, the data ‘interact with people and change them
and since they are changed they are not quite the same kind of people as before.’ In
line with the notion that prospective pedagogic identities are not what learners’
identities ‘really are’ but what authorities want them to be, the pedagogic identity
inferred by learning analytics is not what learners ‘really are’ at all, but ‘made up’ as
a data doppelganger to be utilised recursively to predict future needs and
programme future pedagogic intervention, and consequently to make up the learner
anew. The coding undertaken to facilitate database-driven technologies in education
does not just work by identifying and categorising individuals, but is dynamically
co-constitutive of new kinds of learners—potential persons for futures yet to come.
In this sense, governing by code is an emerging mode of educational governance
which seeks to re-sculpt and reactivate learners directly through automated and
recursive database pedagogies.
Conclusion
This article has begun to explore how code acts in education, focusing particularly
on third sector reimaginings of education through discourses related to
computationally coded technologies. I have developed the idea of ‘governing by
code’ to express how computer code is increasingly interwoven with efforts to
govern public education. The style of governance endorsed and promoted
discursively by third sector organisations is a kind of digital-era governance which
employs network-based communications technologies and database-driven
information processing technologies both as discursive models and technological
methods for activating new forms of pedagogy and curriculum.
Three aspects of third sector pedagogy and curriculum development related to code
have been presented: a network-based model for new curricula, which promotes a
Williamson, B. 2013. Decoding identity: Reprogramming pedagogic identities through algorithmic governance. Paper
presented at British Educational Research Association conference, University of Sussex, Brighton, 3 September 2013 18
flexible pedagogic identity; a coding and making model which promotes learners to
be self-programming actors, co-producers and prosumers; and a data-based model
which, associated with the current growth of learning analytics and the recursivity
of data, assembles algorithmic learner identities through their digital data
doppelgangers. The coded technologies, techniques, and discourses of the third
sector have the potential to co-constitute, reactivate and ‘make up’ learners as future
persons yet to come in order to stabilise a particular imagining of a network-based
and database-driven future.
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