Sentient schools?
Education in the smart city
Ben Williamson
University of Stirling
@BenPatrickWill
Image: Upgrade Studio, http://www.archello.com/en/project/digital-university#
The old city of concrete, glass and steel now conceals a vast
underworld of computers and software. Linked up via the
internet, these devices are being stitched together into a
nervous system that supports the daily lives of billions in a
world of huge and growing cities. Machines now run the world
on our behalf. This digital upgrade to our built legacy is giving
rise to a new kind of citya ‘smart’ city Anthony Townsend 2013
 Sentient cities that ‘think of us’ Mike Crang & Steve Graham 2007
 As computational objects have developed, cities are able
to take on new forms of vitality, but only gradually, line
by line, algorithm by algorithm, program by program.
Cities are full of a whole new layer of emergent entities
which, because they are underpinned by code using data
as fuel, might be thought of as akin to sentient beings
Nigel Thrift 2014
Image: Mark Dorf, http://dismagazine.com/issues/73066/rob-kitchin-spatial-big-data-and-geosurveillance/
 The programming of environmentsurban processes, citizen
engagements, and governance unfold through networks of
sensors, algorithms, databases and mobile platforms that
constitute the environments of smart cities. These technologies
are generative of political techniques for governing everyday
ways of life
Jennifer Gabrys 2013
 ‘Smartmentality’the production & circulation of knowledge,
rationalities, subjectivities & moralities suited to the
management of the smart city
Alberto Vanolo 2014
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While many cities are already well on their way toward modernizing
their technology infrastructures, they also need to respond to
today’s most important education trends. … To thrive, cities need to
provide access to powerful learning devices, tools, & apps that
empower education…. Microsoft CityNext solutions transform
education to create more innovative schools and teaching practices
Microsoft CityNext 2014
Digital technologies and education:
almost all our work in this area has a
smart cities aspect (though oddly
education has tended to be excluded from
the SC field), and we’re spreading out into
new ways of promoting digital making of
all kinds in cities
Geoff Mulgan 2014
Sociotechnical imaginaries
 Smart cities as a social imaginary, often
idealized & unrealized, vs. ‘actually existing
smart cities’
Taylor Shelton et al. 2014
 Sociotechnical imaginariescollectively
imagined forms of social life and order,
reflected in technological projects, that
describe attainable futures & prescribe futures
that states believe ought to be attained
Sheila Jasanoff & Sang-Hyuan Kim 2009
Image: Robert Cameron, http://www.byronlast.com/2014/02/robert-cameron-guide-to-living-in.html
Fabricated spaces
 Governing cities as ‘laboratories of conduct’
the city as a way of diagramming human
existence, human conduct, human subjectivity,
human life itself Thomas Osborne & Nikolas Rose 1999
 Fabricated spaces are models, diagrams &
distillations of practices for shaping of conduct,
with aspiration that reality can be made to
conform with themtechnologies for
visualizing & governing urban lifeMargo Huxley 2001
Image: Robert Cameron, http://www.byronlast.com/2014/02/robert-cameron-guide-to-living-in.html
Technologies of schooling
Q What is the ‘technology of schooling’ in smart cities?
Pedagogic knowledges, civilizing aspirations, techniques of
discipline and organization, professional standards and
obligations, schoolrooms of a certain design, mental
exercises, material and technical infrastructures, textbooks
and other discursive products, all infused with the aim of
shaping and inculcating particular forms of conductto act
upon action
Nikolas Rose 1999
Image: Emely Jensen, http://emelyjensen.deviantart.com/art/Art-Classroom-Concept-Blackboard-430049099
Built pedagogy
Q What is the ‘built pedagogy’ of the smart school?
 Built pedagogy describes how spaces teach individuals what
should and should not be done
 Built pedagogies of ‘technological spaces’ embody politics &
values, catalyze and foreclose particular actions &
experiences
Torin Monahan 2005
Image: Emely Jensen, http://emelyjensen.deviantart.com/art/Art-Classroom-Concept-Blackboard-430049099
Fabricating smart schools
 Smart schools as sociotechnical imaginaries & fabricated spaces
Technicaldevices, information, data, code, & algorithms
Socialactors, groups & organizations e.g. software producers,
commercial companies, designers, government
Discursivetexts, documents, images, infographics, visualizations
A ‘technology of schooling’ infused with aim to shape student
behaviour through coded built pedagogies
Image: Upgrade Studio: http://www.archello.com/en/project/digital-university#
1 Schools as data platforms
Schools, universities & classrooms as ‘data
platforms’ in a ‘big data ecosystem’
Image: Tomas Saraceno, http://www.tomassaraceno.com/Projects/OntheRoof/
To be competitive, cities need to ensure that their citizens have
access to twenty-first century productivity tools. All schools,
including higher-education institutions, can benefit from
complementary, world-class apps and online services that make it
easier to interact and collaborate. Microsoft CityNext offers
students and educators solutions built on technology they’re
already using, including cloud, Big Data, mobile and social
Microsoft Educated Cities 2014
The rise of the ‘smart classroom’: The rapid digitization of the
education industry and the emergence of cognitive systems is
already happening in parallel. Digital education creates a
tremendous amount of data about all aspects of teaching and
learning—test scores, information about student behavior on
digital learning platforms, attendance, and more. IBM envisions
educational institutions adopting cloud-based cognitive systems
to collect and analyze all of this data over a long period of time
IBM 2013
Schools and universities have always recorded and stored data as
they tracked grades, attendance, test scores and demographics.
With the increasing availability of technology in the instructional
process, educational institutions now collect, in real time, data
about what their students learn and how they progress. Using big
data and analytics, everything from attendance to a campus
building’s energy usage has a place in identifying targets for
improvement…
Today’s students expect their learning environments to mirror the
environments in which they live ― punctuated by always-on,
available-anywhere information & personalized, multichannel
learning
IBM Smarter Education 2014
Just as in other sectors of the economy and government, ‘Big Data’
and its potential for personalized learning holds the key to
significant increases in student achievement. Everything students
do in digital environmentsfrom completing online lessons to
playing gamesgenerates massive amounts of data about their
activities and learning. Researchers in the Center for Digital Data,
Analytics & Adaptive Learning are making progress in harnessing
the power of that data to assess, enable, and personalize learning
without the disruption of traditional tests
Pearson 2014
 ‘Datafying the learning
process’
 Feedback
 Online courses enabling
logging & tracking of learners
through clickstream data
 ‘Knowing’ e-textbooks that
can ‘learn’ from use and ‘talk
back’ to the teacher
 Personalization
 Algorithmically personalized
pedagogic ‘playlists’
 Probabilistic prediction
 Predictive learning analytics
to optimize student learning
Viktor Mayer-Schonberger & Kenneth
Cukier 2014
Big data are being used in the
development of smarter cities,
smarter governments, and a
smarter planet. So why not
smarter colleges or universities?
The Big Data movement could
help build smarter universities
institutions that can use the
huge amounts of data they
generate to improve the student
learning experience, enhance the
research enterprise, support
effective community outreach,
and advance the campus’s
infrastructure Jason E. Lane 2014
Sqord gives you an
administrative reporting tool
with quantifiable metrics on
the physical activity, levels, &
participation of each of your
players. No more guesswork or
gray areas in measuring
physical activity. Sqord puts
the numbers in plain view, &
allows your teachers &
coaches to see exactly what’s
what in real-time Sqord 2014
Biosensors & biometrics in the classroom
Gates Foundation ‘student sensor bracelets’ to detect
excitement, stress, fear, engagement, boredom & relaxation
through the skin
EngageSense‘face-cams’ & computer vision algorithms
produce automated metrics of student engagement
 ‘Quantified self-city’ hybridscities are rethought as organisms
and human bodies quantified as systemsMatthew Wilson 2015
 Quantified student-school hybridssmart learners in smart
schools, whose behaviours can be nudged, tweaked & changed
through interaction with flows of data
Image: John A Rogers, http://news.illinois.edu/news/14/0403microfluidics_JohnRogers.html
2 Digital policy instruments
Policy instruments make policy agendas operational
devices that enact particular policies, & that constitute
a condensed form of knowledge about exercising
social control
Pierre Lascoumes & Patrick le Gales 2007
 Transparency, open data, comparison, marketization
 Making school data more visual, publicly intelligible & persuasive
 Display &
visualization of
school data
replacing expert
judgment of the
inspector
Jenny Ozga 2014
MoneySupermarket for school choice
configuring parents as educational
comparative analysts
‘Public social statistics’ enable ‘media-assisted government
from afar’ whereby authorities are enabled to act upon
schools through indirect forms of control, by guiding users to
make rational evidence-informed decisions Nelli Piattoeva 2014
 A ‘virtual world of educational data’ that displaces a
focus on the ‘real world of education’
 Makes different ‘school realities’ visible & actionable
 A ‘realist epistemology’ of ‘visualized facts’
Rob Kitchin et al 2015
Smart schools as nodes in global data networks
A web of data, feedback & prediction required to
coordinate & control the system Jenny Ozga 2009
Software and data companies are the ‘hidden’
new managers of the ‘virtual educational
landscape.’ The management of education
systems is increasingly connected to the capacity
of data servers, software developments, & the
use of data-mining tools
Martin Lawn 2013
3 Learning analytics
 Intelligent software devices that facilitate unobtrusive
classroom data collection in real time
 Track learning & teaching at the individual student and lesson
level every day in order to personalise & optimise learning
 Application of data analytics and the adoption of new metrics
to generate deeper insights into & richer information on
learning & teaching
 Online intelligent learning systems, data analytics & automated
artificial intelligence systems to provide ongoing feedback to
personalise instruction & improve learning and teaching
Pearson 2014
Educators already have plenty of administrative and economic
data—the challenge is gaining insights from it … for improved
tracking and evaluation. Microsoft education analytics solutions
help students perform better and can be adapted to meet
individual needs. The analytics tools improve administration as well
with a 360-degree view of performance and operations. Easy-to-use
reporting tools simplify access to data for everyone, and make it
easier to share information with stakeholdersMicrosoft Educated Cities 2014
Analytics translates volumes of data into insights for policy
makers, administrators and educators alike so they can identify
which academic practices and programs work best and where
investments should be directed. By turning masses of data into
useful intelligence, educational institutions can create smarter
schools for now and for the future IBM Smarter Education 2014
 P-TECH as test bed for the next plank in IBM’s Smarter
Cities effort, which is to build for schools what its
operations center is for cities: a single system for collecting,
aggregating and analyzing data from students and teachers
alike, then writing algorithms to prescribe how to cope
 a software ‘infrastructure layer’ for schools, running behind
the scenes to manage students’ digital textbooks & analyze
their performance
 a research project for gleaning best practices that can be
codified into software
Greg Lindsay 2013
 The IBM ‘smarter classroom’ is a ‘classroom that will learn you’
through ‘cognitive-based learning systems’
 Predictive tools: based on what’s already happened, what’s
going to happen next?
 Prescriptive analytics: in light of what we believe is going to
happen, what is the best response?
 These two dimensions of smarter analytics enable educational
leaders to detect patterns that exist in masses of data, project
potential outcomes and make intelligent decisions based on
those projections
 Anticipatory governancefrom ‘real-time’ monitoring to
‘future-tense’ pre-emption
 Classrooms that learn you in ‘sentient cities that think of us’
Mike Crang & Stephen Graham 2007
Image: http://www.nesta.org.uk/blog/smart-cities-what-were-doing-and-why
4 Smart citizens
 Citizens learning to be participatory ‘computational operatives,’
‘human capital’ & ‘civic hackers’ of the smart city
 Mobilising the next generation of digital makersthe world is
becoming increasingly digitised & filled with products that
change the way we connect & interact. … We want to help
people shift from consuming digital technologies, to … hacking,
re-mixing and making things with technologyMake Things Do Stuff 2013
 Promoting digital making of all kinds in cities Geoff Mulgan 2014
 Learning to code as production of the smart people and
innovative human capital required by smart cities
 The urbanization of codeCalifornian coder culture infuses the
work of code & its coders
Adrian Mackenzie 2014
Making smart cities into ‘maker cities’makers
are starting to reimagine the systems that
surround them. They are bringing the ‘maker
mindset’ to the complex urban challenges of
health, education, food, & even citizenship.
Makers will make the future of their cities
Institute for the Future 2014
 AltSchools as ‘startup schools’$28million in venture capital
funding, set up by former Google engineering exec
 Hybrid maker-schoolspart ‘makerspace’, part school
 ‘Our world-class team of educators, entrepreneurs, and
technologists is working together to build a technology-driven
network of micro-schools that offers a new, radicallypersonalized experience’
AltSchool 2014
 Learning to ‘code for x’—merging ‘what is (technically) possible
and what is (politically) feasible’
Nesta 2014
 ‘Civic hackers’ in ‘civic laboratories’ coding solutions to smart
city problems … knowing how to code will be an important skill
for civic improvement
Anthony Townsend 2013
 Computationally skilled citizens who have learned to code to
facilitate ‘technocratic solutionism’ in the smart city
 Smart citizensactions of citizens have less to do with
individuals exercising rights & responsibilities, & more with
operationalizing the cybernetic functions of the smart city.
The citizen is a data point, both a generator of data & a
responsive node in a system of feedback Jennifer Gabrys 2014
 Smart citizens are very subtly asked to participate in the
construction of smart cities & implicitly considered
responsible for it, re-subjectified as active citizens
Alberto Vanolo 2014
Image: Mark Dorf, http://dismagazine.com/issues/73066/rob-kitchin-spatial-big-data-and-geosurveillance/
Fabricating smart schools
Emerging ‘technology of schooling’ in the ‘laboratory’
of the smart city:
1 Databases making schools more ‘known’ & ‘knowing’
2 Digital policy instruments & global policy networks
3 Analytics trained to self-adapt & learn the learner
4 Learning to code to interpolate students into the
computational systems of the city
Image: Tomas Saraceno, http://www.tomassaraceno.com/Projects/OntheRoof/
Conclusion
 Smart schools as smart cities’ laboratories of conduct where
‘the computer boys take over’ Nathan Ensmenger 2010
 The politics of programmers, their coder cultures, models of
the world, values, methods, ways of thinking & doing are builtin to the pedagogic spaces & practices of the classroom
 Schools more data-driven, smart, sentientwith a life of their
own…
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Further research
 Network analysis of smart schools promoters & programmers
tracing commercial, governmental, academic, entrepreneurial,
& third sector connections
 Tracing the genealogy of smart schools discoursesanalyzing
policy imaginaries, technology fantasies, & visualizations
 Software studies of smart schools technologiessocial &
cultural creation of tech; its programming, code & algorithms;
its underlying assumptions, values & models
 Ethnographies of ‘actually existing’ smart schoolsfollowing
‘live’ smart city education developments in-the-making
Image: Upgrade Studio: http://www.archello.com/en/project/digital-university#
http://codeactsineducation.wordpress.com
@BenPatrickWill
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