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Startup schools, fast policies, and full-stack education
companies: digitizing education reform in Silicon Valley
Ben Williamson, Faculty of Social Science, University of Stirling, UK
[Chapter forthcoming in Means, A. & Saltman, K. Handbook of Global Education
Reform. Wiley-Blackwell.]
Silicon Valley technology companies, entrepreneurs, investors and philanthropists
are currently engaging in education with considerable enthusiasm. Global
technology companies including Facebook and Google have launched major
technology platforms for education, and begun investing financial resources in
other startup firms. More specifically, Silicon Valley has become the centre for a
‘startup school’ movement which has seen entrepreneurs associated with social
media and web companies creating their own private schools as competitive
alternatives to state schooling and models for the reinvention of public education
at massive scale. Investment initiatives from venture capital firms and
philanthropists based in the Valley have helped raise venture capital for these
initiatives, while new educational technology ‘incubators’ have begun to provide
technical, legal and financial support for startup projects from apps to new
institutions.
In this chapter I analyse the role of Silicon Valley as a major centre of technology-
driven global education reform. I utilize the concepts of ‘fast policy’ and ‘policy
mobilities’ (Peck & Theodore 2015) to advance the argument, and focus
specifically on ‘startup school’ projects as exemplars of digitized fast policy
solutions in action. AltSchool, Summit Public Schools, Khan Lab School, and XQ
Super School Project—as well as many other initiatives with which they are
networked—exemplify how Silicon Valley’s approach to speeding up education
policy involves sprawling networks of technology companies and entrepreneurs,
venture capital sources, incubator programs, technology philanthropy, digital apps
and platforms, technology evangelists, policy entrepreneurs, and new educational
‘experts’. These actors are creating relational networks of institutions, practices,
technologies, money, and marketing, which together function as paradigmatic
models of the future of public schooling.
Startup school projects are prototypical of Silicon Valley’s ambitions to become
the techno-political centre of global education reform, and exemplify techniques of
educational fast policy in motion. In the next section, I situate Silicon Valley as a
social, technical, economic and political zone of innovation with particular
aspirations to reform public education in its own image. I then identify and map a
particular ‘fast policy’ network of Silicon Valley projects, funders and practices
associated with startup schooling, before proceeding to interrogate three distinctive
practices of this network. The first is the financial dependence of startup schooling
on philanthropic and venture capital funding; the second is the centrality of digital
data to the vision of high-tech ‘personalized education’ characterized by startup
schools; and third, the ‘experimental’ approach to treating startup school
classrooms as ‘learning laboratories’ where new scientific theories of learning based
on psychological and neuroscientific forms of expertise are to be trialled and tested
upon students. Together, these financial techniques, data practices, and learning
science theories constitute a blueprint for the future of education that Silicon
Valley is prototyping and beta-testing through a number of startup school
initiatives, and which it aspires to scale-up across the public schooling sector.
Situating Silicon Valley
Silicon Valley is both a topographical zone that can be defined geographically, and
a social, technical and political zone of activity. Geographically delineated, Silicon
Valley stretches from the east Bay Area of San Francisco and runs south through
Santa Clara valley to include San Jose, Stanford, Mountain View, Cupertino and
Palo Alto, plus parts of San Mateo, Alameda and Santa Cruz counties. As a social
and technical zone of activity, however, the origins of Silicon Valley lie in the
1950s establishment of the Stanford Industrial Park by Stanford University and its
centrality to silicon chip innovation. In his seminal work on the ‘information age,’
Castells (1996: 54, 57) described Silicon Valley as a ‘milieu of innovation’ and a
‘social, cultural and spatial pattern of innovation’ that could be characterized by the
continuous creation of startup firms, rapid knowledge diffusion and ideas-
exchange, spatial concentration of research centres, business networks of venture
capital and finance startups, as well as loose social clubs where software developers
and designers could share ideas and information. Rather than a purely
topographical zone, then, Silicon Valley can be understood as the topological
outcome of networks of relations that have sedimented into specific technical,
economic and cultural patterns of innovation and production.
More recently, Duff (2016: 14) has claimed Silicon Valley presents itself as a
‘technopolis,’ simultaneously the headquarters of the ‘information revolution,’ an
identifiable social and cultural community, a physical space with borders, and ‘a
peculiar “state of mind” too.’ Silicon Valley’s high-tech companies, technology
philanthropists, startup companies and culture of venture capital are ‘the centre of
a techno-economic revolution’ that is ‘now spreading outwards across the world,
with major societal effects and implications’ (Duff 2016: 5). Silicon Valley has,
then, positioned itself as the centre of a technical revolution to be ‘executed with
bits, algorithms, code, telecoms, expert systems, [and] AI,’ but also an economic
revolution in ‘information capitalism’, a seemingly contradictory mixture of
standard capitalist practice, characterized by its extreme work ethic, profit-seeking
and efficiency, with libertarian individualism, hippie radicalism, and the idealism of
sharing and community values (Duff 2016, 13).
Although Silicon Valley’s culture of technology and economic innovation is well-
known, it also projects an idiosyncratic political outlook. Ferenstein (2015) has
described Silicon Valley as a socio-demographic zone characterized more by the
liberal politics of the technology sector than its geography. Silicon Valley liberals
mix libertarianism with Democratic political convictions, he argues, leading to
extreme idealism about human nature, society, and the future, as well as a rejection
of the idea there are inherent conflicts of interests between citizens, the
government, corporations or other nations. Ferenstein (2015) terms the new
Silicon Valley liberals ‘civicrats,’ or ‘tech-Democrats,’ whose goal is to make
everyone innovative, healthy, civic and educated, and see government’s role as an
investor in maximizing people’s contribution to the economy and society.
Education itself is therefore integral to a so-called ‘Silicon Valley ideology’ which is
centred on the belief ‘that the solution to nearly every problem is more innovation,
conversation or education,’ and therefore demands ‘massive investments in
education because they see it as a panacea for nearly all problems in society’
(Ferenstein 2015).
However, Silicon Valley’s vision of an education that can serve these ideals is one
which, in its view, bureaucratic government education departments are failing to
deliver. Technology entrepreneurs instead particularly advocate performance-based
funding systems like charter schools as educational alternatives that can operate
free of centralized government regulation and teachers’ unions, and want state
education to be run like a business and a competitive marketplace:
This helps explain why tech elites, including Bill Gates and Mark Zuckerberg, have given
hundreds of millions of dollars to charter schools. Charters are often highly experimental,
union-less public schools that are managed by performance-based metrics. Indeed, the
federal education law, itself, Race to the Top, is basically a giant prize competition, which
awards a greater share of federal dollars to schools and districts that outperform their
peers. (Ferenstein 2015)
A particular politics therefore underpins Silicon Valley’s approach to education,
one which emphasizes the centrality of education to innovation and to the creation
of ‘awesome,’ entrepreneurial individuals, and the establishment and support for
competitive models of education that can be measured and rewarded based on
performance toward these goals. The combination of commercial Silicon Valley
technology companies with education is part, therefore, of a broader ‘restructuring
of public education by economic and political elites’ which have ‘succeeded in
strategically advancing privatization and market-based school “reforms” to
transform public education into a private industry while also hijacking public
governance over educational policy’ (Saltman 2016, 107).
At least in part, the interests of Silicon Valley in education can also be understood
instrumentally as a commercial opportunity. As the ‘epicenter of technological
optimism’ (Cuban 2016a), Silicon Valley-based technology companies and venture
capital firms have invested in education technology development with
unprecedented enthusiasm in recent years. In 2012, Global Silicon Valley, a
merchant bank that has advised, invested in and accelerated many technology
companies, published a report entitled American Revolution 2.0 that described key
technical catalysts for educational transformation and reform—such as cloud
computing, wired classrooms, low-cost hardware and software—and estimated the
K-12 education market to be worth over US$2.2 trillion (Bulger et al 2017). An
estimated US$2.3billion of venture capital was invested in education technology
companies in the K-12 space in the US between 2010 and 2015 (EdSurge 2016),
although investment appeared to decline in 2016 (Watters 2016).
Venture capital funding tends to be awarded as seed funding for new startups, early
stage investment, or expansion investment, and by 2015 was consolidating around
expansion stage funding in a direct challenge to the existing monopoly over
educational technology by big publishers such as Pearson, Houghton Mifflin
Harcourt, and McGraw-Hill. One venture capitalist quoted in a magazine article on
Silicon Valley’s educational ambitions has noted that education ‘is an industry that
is measured in the trillions of dollars, not billions; it’s multiple percentage points of
gross domestic product’ (Kuchler 2017). Silicon Valley even has its own
educational technology news and media source, EdSurge, ‘to connect the emerging
community of edtech entrepreneurs and educators’ and help ‘entrepreneurs who
build new products and businesses, educators who use these tools, and investors
and others who support companies and schools’ (http://about.edsurge.com/).
The growth of entrepreneurial and venture capital support for education via Silicon
Valley makes financial revenue generation, measurable returns on investment, and
path to profitability into decisive factors shaping education reform. Although
Silicon Valley philanthropists such as Bill Gates have long sought to interfere in
public education through charter schools (Reckhow 2013), Silicon Valley is now
seeking more overtly computational models of education reform which utilize the
technical expertise of Silicon Valley itself to design new software systems and
technological fixes for insertion into the institutions of education. The distinctive
‘Silicon Valley ideology,’ or ‘Californian capitalism’ being applied to education
(Watters 2015) privileges a ‘programmer mindset’ toward solving computational
problems, entrepreneurialism, and ‘making a difference’ while making a profit, all
of it driven by similarly ‘computer-savvy venture capitalists and “angel investors”’
(Selwyn 2016: 114-115). As a result, Silicon Valley companies are becoming
‘shadow education ministries’ (Selwyn 2016: 131) with the entrepreneurial
capacities, technical expertise, economic capital and political aspirations alike to set
reformatory agendas for contemporary education.
Fast startup networks
Many of Silicon Valley’s most successful companies have positioned themselves to
support education. Although major technology corporations like Microsoft, Apple
and IBM have long-established educational aims and programs, more recently web
and social media companies like Google and Facebook have begun to concentrate
financial and technical resource on educational technology development. A lively
startup scene, supported by massive increases in venture capital funding for ed-
tech products noted above, has also emerged. Events such as HackingEdu, where
thousands of ed-tech software engineers compete for funding and entrepreneurial
support to develop their ideas into products, twinned with ‘incubator’ and
‘accelerator’ schemes to consolidate and grow startup teams into profitable
companies, have transformed the educational technology sector into a dynamic,
fast-moving and lucrative marketplace of ideas and technical expertise.
A notable aspect of Silicon Valley’s recent focus on education is the establishment
since 2013 of a number of ‘startup schools,’ recently described in the Financial
Times magazine as ‘Silicon Valley’s classrooms of the future’ (Kuchler 2017). These
are specifically school-centred initiatives, led by some of Silicon Valley’s most
successful technology entrepreneurs and engineers, that focus on a ‘reinvention of
learning’ based on the ideal of ‘personalized, digital tutoring,’ and which their
promoters aim to scale up from being startup companies to state education
solutions (Kuchler 2017). Though startup schools have been the subject of little
critical academic scrutiny (see Cuban 2016a, b; Williamson 2016), they have been
the focus of extensive commentary in the technology and business media.
AltSchool alone has featured in Wired, TechCrunch, EdSurge, Fast Company, Financial
Times, Bloomberg Business, Business Insider, Forbes and Business Week. Though these
sources note that personalization may be pedagogically innovative, their emphasis
is on business model innovation and technical invention as the model for future
schooling.
The fast pace with which the startup school movement has developed is
symptomatic of how education policy work has, in recent years, become
increasingly accelerated and distributed. Although, as Peck and Theodore (2015: 3)
note, the ‘modern policymaking process may still be focused on centers of political
authority,’ it is dispersed among ‘networks of policy advocacy and activism,’ and
sources, channels and sites of policy advice encompass sprawling networks of
human and nonhuman actors.’ Their conceptualization of ‘fast policy’ captures
how new generations of ‘best practice and paradigmatic models,’ twinned with
‘enlarged roles for intermediaries as advocates of specific policy routines and
technologies,’ have led to a significant shortening of policy development processes,
fast-tracked decision-making, continuous experimentation, rapid rollout, and a
privileging of particular participants in the policy process (Peck & Theodore 2015:
4). Fast policy and ‘policy mobility’ is evident in education specifically in the ways
that ‘a diverse cast of new actors and organizations’ is participating in
contemporary modes of educational policymaking and governance particularly
those actors that lie outside of government, such as edu-businesses, think tanks,
philanthropic and venture capital funders, technical experts, entrepreneurs and
lobbyists (Gulson et al 2017: 1).
Startup schools are typically mobile fast-policy models. They originate not in
political centres but from networks of entrepreneurs and advocates, with new
paradigmatic models of ‘personalized’ education that they aspire to market and
mobilize across public education; they are seeking to build ‘best practice’ sites that
can act as models for rapid rollout and expansion to other sites and spaces; they
are interlinked with policy actors, intermediaries and advisors from government
departments as well as commercial businesses; they are funded both through
sources of venture capital and philanthropic giving; they are staffed by in-house
technical experts capable of continuous forms of experimentation, product
development and evaluation; and they mobilize web-based communication
platforms and social media, as well as traditional media channels, to maximize
exposure and catalyse uptake of their school models and products. The mode of
fast-policy work being undertaken by startup school entrepreneurs is therefore part
of a ‘degovernmentalization’ of education policy and governance (Olmedo 2014)
and a rapid escalation in the influence of Silicon Valley and its webs of business-
backed charitable foundations, wealthy elites, venture capital sources, business
models and technical practices within the schools sector.
In what follows I concentrate on a selection of key startup school actors that
exemplify how the participation of commercial Silicon Valley technology
companies in education is part of a broader ‘restructuring of public education by
economic and political elites’ which have ‘succeeded in strategically advancing
privatization and market-based school “reforms” to transform public education
into a private industry while also hijacking public governance over educational
policy’ (Saltman 2016: 107). AltSchool (https://www.altschool.com/) is a private
chain of high-tech schools based around Silicon Valley, originating from the vision
of a former Google executive and supported by a philanthropic donation from
Mark Zuckerberg from Facebook. Summit Public Schools (http://summitps.org/)
is another charter school chain, also extensively supported by funding and
technical support from Facebook’s Mark Zuckerberg, via his philanthropic
program dedicated to ‘personalized learning.’ Zuckerberg has also established his
own startup school, The Primary School (https://www.theprimaryschool.org/), in
the Palo Alto area. The Khan Lab School (http://khanlabschool.org/) is the
product of the entrepreneur Salman Khan, formerly best known for launching the
Khan Academy platform for online learning based on shareable video content.
Finally, the XQ Super School Project (https://xqsuperschool.org/) has funded 10
high school redesign projects across the US; it too is philanthropically funded via
wealthy tech sector donors, emphasizes the role of digital technology and data
analytics in school improvement, and is extensively linked with networks of
venture capital, entrepreneurship and policy expertise.
Some startup schools are public, some private, and others funded by non-profits.
As a private school, AltSchool charges fees of US$27,000 per year; Khan Lab
School charges between US$27,000 for lower-school entrants and $32,000 for
upper-school students, plus enrolment fees. Summit Public Schools is a tuition-free
charter school chain, while the XQ Super School Project has supported public and
charter schools with funding from its non-profit philanthropic sources. In addition
to these specific sites of innovation, startup schooling is also supported by a range
of organizations and actors from across the business and government sectors.
Mark Zuckerberg of Facebook is one of the most high-profile supporters of
startup schools, though others include the Silicon Schools Fund, the venture
capitalists Andreessen Horowitz and First Round Capital, and the Founders Fund,
the venture capital company of Peter Thiel—the founder of PayPal, long-time
Facebook board member and, in 2016, a technology advisor to then President-elect
Donald Trump.
Startup schools, their entrepreneurial founders, and their venture capitalist and
philanthropic funders constitute new and mobile fast-policy networks of
educational development, innovation and reform that explicitly challenge existing
policymaking approaches and the established pedagogic and curriculum practices
of state schooling. In particular, they are experimenting with reformatory
innovations in three ways: through combining venture capital with technology
philanthropy, by applying data analytics to generate real-time insights into
classrooms and pedagogic processes, and by experimenting with new psychological
and neuroscientific theories of learning.
Venture PhilTech
Startup schools are supported financially through sources of venture capital and
technology sector philanthropy. ‘Venture philanthropy,’ or ‘philanthrocapitalism’
are terms used to describe the distinctive nature of how philanthropic giving has
combined with venture capital practices of for-profit investment. As Saltman
(2010: 33) has demonstrated, Silicon Valley entrepreneurs such as Bill Gates have
actively sought to intervene in public education through venture philanthropies
such as the Bill and Melinda Gates Foundation, ‘the largest player in a fundamental
transformation of education philanthropy: it is setting the agenda for modelling
public education in the United States on venture capital.’ Philanthropies such as
the Gates Foundation have sought to replace public education with privatized
educational provision, mobilizing techniques of goodwill, care and generosity to
‘redistribute control from teachers, parents, students and communities to private
foundations, for-profit and non-profit organizations, business groups, and
investors’ (Saltman 2010: 35). Venture philanthropy in American education has
been characterized by the participation of wealthy business-backed foundations in
charter school networks particularly, both on the ‘demand side’ by sponsoring
advocacy coalitions and on the ‘supply side’ by directly funding and supporting
new brand-name charter networks (Reckhow 2013; Saltman 2010). Charter school
policies have enabled privately owned philanthropic organizations to penetrate the
publicly funded education sector, govern institutions directly, and advocate for
more deregulated, competitive models of public education, thereby ‘serving as a
vehicle for privatizing public policy—diminishing the public while enhancing the
position and influence of private interests and organizations in public
policymaking’ (Lubienski 2013: 498).
A distinctive form of technology philanthropy has emerged from Silicon Valley:
abbreviated to ‘philtech’ it articulates a strongly utopian vision of social progress
through software, and is part of the ‘solutionism’ of Silicon Valley that focuses on
solving all social, cultural, economic and political problems with the application of
code and algorithms (Morozov 2013). This form of Silicon Valley solutionism is
increasingly being applied to education (Selwyn 2016) to propose very specific
kinds of educational intervention and reinvention. Silicon Valley philtech advocates
emphasize new approaches to ‘personalized learning’ and propose to become
supply side creators of new institutions, practices and products that are modelled
on the business plans, technical practices, and distinctive political outlook of
Silicon Valley ‘startup’ culture. An illustrative example of the emerging venture
philtech movement for education in Silicon Valley is the Silicon Schools Fund
(http://www.siliconschools.com/). It is supported by a range of philanthropic
foundations and wealthy individuals from business and technology, and is staffed
by a board of directors from influential foundations, think tanks, and charter
school networks with a focus on innovation in education. The organization
‘provides seed funding for new blended learning schools that use innovative
education models and technology to personalize learning,’ focusing on the creation
of new schools in the Bay Area as ‘laboratories of innovation and proof points for
personalized learning’—a ‘national demonstration hub of high quality learning’:
Schools that give each student a highly-personalized education, by combining the
best of traditional education with the transformative power of technology
Students gaining more control over the path and pace of their learning, creating
better schools and better outcomes
Software and online courses that provide engaging curriculum, combined with real-
time student data, giving teachers the information they need to support each student
Teachers developing flexibility to do what they do best—inspire, facilitate
conversations, and encourage critical thinking
The schools that Silicon Schools Fund supports include Khan Lab School and
Summit Public Schools, the charter chain also funded directly by Mark Zuckerberg,
the founder of Facebook, through his own philtech organization.
The Chan Zuckerberg Initiative (CZI) set up by Mark Zuckerberg and his wife
Priscilla Chan is one of the wealthiest and most influential philanthropic donors to
startup schooling (https://chanzuckerberg.com/initiatives/). CZI was established
as ‘a limited liability corporation … free to make philanthropic donations, invest in
for-profit companies, and engage in political lobbying and policy advocacy’
(Herold 2016), after Zuckerberg and Chan announced in 2015 their intention to
give away 99% of their Facebook stock, valued at around US$45bn, to a variety of
causes, particularly technology-enabled personalized learning in K-12 education.
The head of the educational arm of the initiative is James Shelton, former US
Deputy Secretary of Education; Shelton has previously worked as a program
director at the Bill & Melinda Gates Foundation and as a partner at the
NewSchools Venture Fund, both of which have donated and invested heavily in
education technology, charter schools and other new school models.
Zuckerberg and Chan have also established a series of for-profit and non-profit
organizations as part of ‘a new, multi-pronged effort to use their massive fortune
to reshape public education with technology’ (Education Week 2016), including a
partnership with Summit Public Schools, which has metamorphosed from a single
school in Silicon Valley to a Summit Personalized Learning Platform used by
20,000 students across 27 US states (Kuchler 2017). Mark Zuckerberg has
additionally established a nonprofit organization known as Startup:Education to
channel $120 million for Bay Area schools and millions more to support charter-
school growth, as well as the Silicon Valley Community Foundation, which has
funded his own startup school The Primary School.
AltSchool, set up in 2013 by Max Ventilla, a technology entrepreneur and former
Google executive, has been the recipient of substantial philtech funding. Originally
set up in San Francisco in 2013 as a ‘collaborative community of micro-schools,’
AltSchool later expanded to Brooklyn, Chicago and Palo Alto, with further long-
term plans for new schools and partnerships across the US. In 2016 it announced
that schools could apply to join to become part of the AltSchool Open partner
network, and plans to market its emerging software platform to traditional public
schools from 2019 (Herold 2017). AltSchool has hired executives from Google,
Uber, Airbnb, and other successful Silicon Valley startups, as well as senior
executives from a number of charter school networks, and in 2017 announced
recruitment of one of California’s top district superintendents.
Financially, on its establishment AltSchool originally raised $33 million in venture
capital funding, with another $100 million investment in 2015, including donations
from Mark Zuckerberg’s Silicon Valley Community Foundation, the venture
capital firms Andreeson Horowitz and First Round, as well as from LearnCapital
(an education technology investor of which the global education business Pearson
is the largest limited partner) and Peter Thiel’s Founders Fund. It is seeking to
generate revenue through both the AltSchool Open partner program and its
platform, with each school partner ‘paying AltSchool an undisclosed sum of
money’ and, in the future, any school using its platform required to ‘pay some sort
of recurring fee’ (Madda 2016).
AltSchool’s plan for educational reinvention is ultimately symmetrical with the
Silicon Valley business model of gradually escalating a small-scale startup through
expanding its team and its networks, while beta-testing and fine-tuning its product,
in order to become viable as a massively scaled-up platform for public
consumption.
AltSchool has also received substantial philanthropic support from the
philanthropic organization of Laurene Powell Jobs (the widow of Steve Jobs,
former head of Apple). In 2015, Laurene Powell Jobs granted a $50million
philanthropic donation to a crowdsourced school redesign project. The XQ Super
School Project is a competition to redesign the ‘dangerously broken’ social
institution of the American high school. Its founder and president, Powell Jobs is
the world’s ninth wealthiest woman and one of the richest women in Silicon
Valley. The XQ Super School Project is managed by the XQ Institute, itself an
incubated product of the Emerson Collective
(http://www.emersoncollective.com/). Also chaired by Powell Jobs, the Emerson
Collective is a philanthropic organization that claims to ‘invest in ideas and fuel
innovation’ through partnering with entrepreneurs, and is a key partner of the
Silicon Schools Fund and source of AltSchool funding. It is directed by Russlynn
Ali, a former assistant secretary in the US Department of Education. In practice,
the XQ Super School Project is conceived as a massive ‘democratic and
crowdsourced’ experiment ‘to reimagine and design the next American high
school’ in order to ‘deeply prepare our students for the rigorous challenges of
college, jobs and life.’ The project began soliciting proposals in late 2015, with the
objective of partnering with winning teams to provide them with expert support,
including the allocation of $50million funding for the winning proposals to turn
them into ‘real Super Schools.’ In autumn 2016, ten winning schools were
announced. The winners included Summit Elevate, a high school in Oakland,
California and one of the Summit Public Schools network. At Summit Elevate,
announced the XQ Super School Project website, ‘students will truly be “in the
driver’s seat” of their own educations, whether selecting their own network of
personal advisors and mentors from education and industry, or using the Summit
Personalized Learning Platform to ensure college and career readiness’
(http://xqsuperschool.org/abouttheproject).
Like the Silicon Schools Fund, the XQ Super School Project is prototypical of
Silicon Valley efforts to invest and intervene directly in schools through venture
philanthropic means, the role of wealthy tech-entrepreneurial individuals in the
attempt to ‘fix’ schools and the ‘failed system’ of schooling, and the increasing
blurring of lines between Silicon Valley entrepreneurship and education policy
activism and advocacy. These declarations of ‘failure’ represent an assault on the
public sector and its ‘failed systems,’ and thus ‘naturalize private enterprise as the
cure to public schools “failings”’ (Saltman 2010: 37), as well as proposing new
solutionist ‘technical fixes’ for intractable social problems. As solutions to the
failures of state education, startup schools are positioned by their investors as high-
risk and high-growth companies that are required to guarantee profitable return on
investment while solving social problems. AltSchool, for example, has a legally
defined special type of corporate structure, ‘where the goal is not only to be a
profitable entity, but also to have a positive impact on society’ (Cutler 2015).
Venture-based philtech is the business model of the startup school that its
investors hope to make profitable, all while using these schools as private beta-
testing sites for new digital personalized learning platforms that might be scaled up
and marketed competitively within the public schooling sector.
Algorithmic progressivism
The use of data as a source for performance measurement has a lengthy history in
American education. Over recent decades, a vast infrastructure of test-based
systems for monitoring US schools, teachers and students has been developed as
the product of interrelated policies and technical developments. The consequence
of the quantification of performance has been an increasing intensification of
standardization in schools as ‘students’ standardized test scores and the
standardized quantitative measures of teacher and school performance derived
from them … enable students, teachers, and schools to be sorted into performance
categories to which incentives and sanctions can be attached’ (Anagnostopoulos et
al 2013: 14). The collection and analysis of data as a means of calculating school
effectiveness has been advanced and intensified further through the involvement
of technology businesses and philanthropic foundations in charter schools
networks (Reckhow 2013).
The standardization of schooling associated with the infrastructure of test-based
accountability is viewed by startup school advocates, however, as one of the core
problems with state education. According to a profile of Silicon Valley’s emerging
educational entrepreneurs in Wired magazine, ‘they believe that the very
philosophical underpinnings of modern education are flawed. … Problems arise,
the thinking goes, when kids are pushed into an educational model that treats
everyone the same—gives them the same lessons and homework, sets the same
expectations, and covers the same subjects’ (Tanz 2015a). By contrast to
standardized, test-centred schooling, the dominant discourse supporting startup
schooling is of ‘personalized learning’ enabled by adaptive learning technologies.
Personalization has become a significant concept for schools such as AltSchool,
Khan Lab School, and Summit Public Schools, which merge a progressivist
emphasis on student-centred learning with the social media technique of
customizing digital experiences to individual users based on data analytics
(Corcoran & Gomes 2016). The Chan Zuckerberg Initiative, for example, has a
stated aim to develop both ‘products and practices’ as ‘personalized learning
solutions’:
We focus on developing breakthrough products and practices that address the needs of
each student, bringing together the best teachers, researchers, advocates and engineers to
tackle pressing problems and growing a movement to support the development and broad
adoption of powerful personalized learning solutions. … Many philanthropic organizations
give away money, but the Chan Zuckerberg Initiative is uniquely positioned to design,
build and scale software systems … to help teachers bring personalized learning tools into
hundreds of schools. (https://chanzuckerberg.com/initiatives/)
To this end, CZI is the main philtech supporter of Summit Public Schools, the
charter schools network headquartered in Silicon Valley and also a beneficiary of
XQ Super School funding. Not only has CZI dedicated significant funding to
Summit; it has also seconded a dedicated engineering team from Facebook to build
a software platform for the chain.
At the core of the Summit Personalized Learning Platform is a powerful suite of
learning analytics techniques and applications, complemented by built-in courses
made up of projects and focus areas vetted by Stanford University’s centre for
assessment and learning. By tracking students’ engagement and progress on each
of the courses, the system automatically adapts to allow students to ‘work through
playlists of content at their own pace and take assessments on demand’ and enable
teachers to ‘use that data to personalize instruction and provide additional support
through mentoring and coaching.’ Available for free online, the Summit
Personalized Learning Platform is available to schools outside of the official
Summit Schools Network, which can join as part of a Summit Base Camp program
designed to provide ‘teachers and schools across the US with the resources they
need to bring personalized learning into the classroom’
(http://summitbasecamp.org/explore-basecamp/)
AltSchool has likewise developed its own personalized learning technology
platform. Notably, AltSchool founder Max Ventilla was previously the head of
‘personalization’ at Google, with responsibility for the Google+ social network
platform. A recent profile claimed that ‘when Ventilla quit Google to start
AltSchool, in the spring of 2013, he had no experience as a teacher or an
educational administrator. But he did have extensive knowledge of networks, and
he understood the kinds of insights that can be gleaned from big data’ (Mead
2016). Self-described as a ‘full-stack education company,’ AltSchool is staffed
equally by engineers, educators and business managers, with some of its staff
development time dedicated to ‘hackathons’ where they collaborate to delegate
‘robot tasks’ such as routine data entry to software.
The software platform, which it describes as a new ‘central operating system for
schools’, consists of two main applications—the ‘Playlist’ tool for students and the
‘Progression’ tool for teachers—as well as a parent communication application
called ‘Stream.’ ‘A Playlist is a customized to-do list for students to manage their
work,’ claims the AltSchool website. ‘Educators curate a Playlist for each student.
Within the Playlist, students can view their assignments, communicate with their
teacher, and submit their work. Educators can then provide feedback and assess
student work.’ In addition, the teacher tool Progression ‘provides a comprehensive
portrait of a student's progress in math, language arts, and social-emotional
development. It tracks a student’s practice and trajectory … and gives educators a
rich view of past learning experiences, patterns, successes, and areas that need
support. Insights from Progression inform how an educator plans future learning
experiences and sets goals.’ These tools, AltSchool’s founder has claimed, are part
of ‘a revised conception of what a teacher might be: “We are really shifting the role
of an educator to someone who is more of a data-enabled detective”’ (Mead 2016).
In autumn 2016, AltSchool announced it was to begin distributing its software
platform to other schools, with ambitions to ‘apply the company’s formula to a
network of private, public, and charter schools across the US’ (Alba 2016).
Another profile piece noted that AltSchool’s founders and investors hoped it could
‘help “reinvent” American education: first, by innovating in its micro-schools; next,
by providing software to educators who want to start up their own schools; and,
finally, by offering its software for use in public schools across the nation, a goal
that the company hopes to achieve in three to five years’ (Mead 2016). Recent
media coverage of AltSchool’s plans estimate a target date of 2019-2020 (Herold
2017) ‘to scale a massive network of schools around personalized learning’ (Madda
2016).
The reinvention of American education protoyped by AltSchool and Summit is
one that hybridizes learner-centred approaches to personalized learning with social
media techniques of personalizing user experiences online. As Lapowsky (2015)
characterizes it in a recent profile of AltSchool in Wired magazine:
AltSchool is a decidedly Bay Area experiment with an educational philosophy known as
student-centered learning. … To that, however, AltSchool mixes in loads of technology to
manage the chaos, and tops it all off with a staff of forward-thinking teachers set free to
custom-teach to each student. … This puts AltSchool at the intersection of two rapidly
growing movements in education. Along one axis are the dozens of edtech startups
building apps for schools; along the other are the dozens of progressive schools rallying
around the increasingly popular concept of personalized education.
According to a study of technology-enhanced personalized learning in Silicon
Valley schools by Cuban (2016a), however, the Silicon Valley brand of
progressivism is closer to that of efficiency-minded, ‘administrative progressives,’
whose approaches seek to emulate the practices of corporate leaders of large
organizations committed to both efficiency and effectiveness, than to Dewey’s
progressive form of democratic education.
This reflects a long history of competing forms of progressivism in education.
While ‘one wing of these early progressives were pedagogical pioneers advocating
project-based learning, student-centered activities, and connections to the world
outside of the classroom,’ the administrative progressives ‘counted and measured
everything in schools and classrooms under the flag of “scientific management”’:
They reduced complex skills and knowledge to small chunks that students could learn and
practice. They wanted to make teachers efficient in delivering lessons to 40-plus students
with the newest technologies of the time: testing, film, radio. They created checklists for
teachers to follow in getting students to learn and behave. They created checklists for
principals to evaluate teachers and checklists for superintendents to gauge district
performance including where every penny was spent. … What exists now is a re-
emergence of the efficiency-minded ‘administrative progressives’ from a century ago who
now, as entrepreneurs and practical reformers want public schools to be more market-like
where supply and demand reign, and more realistic in preparing students for a competitive
job market. (Cuban 2016a)
What differentiates AltSchool, Summit and their networks from administrative
progressivism, however, is their dependence upon, and advocacy for, digital data
analytics. Roberts-Mahoney et al (2016: 1-2), for example, argue that powerful
venture philanthropies, educational technology companies, and the US
Department of Education have combined to form ‘a growing movement to apply
“big data” through “learning analytics” to create “personalized learning” in K-12
education in the United States,’ which they argue reflects ‘narrow corporate-driven
educational policies and priorities such as privatization, standardization, high-
stakes assessment, and systems of corporate management and accountability.’
Moreover, the new forms of data analytics being developed and deployed at
AltSchool and Summit introduce new forms of algorithmic automation into school
administration and the pedagogic environment of the classroom itself. Their model
represents an evolution of forms of administrative progressivism into algorithmic
progressivism. In a rare empirical observation of AltSchool, Cuban (2016b), for
example, notes that AltSchool has adapted a form of progressive pedagogy
inspired by John Dewey, and hybridized it with the legacy of Edward Thorndike,
‘that early twentieth century “educational engineer” who thought everything could
be measured and analysing data could point the way to better managed and
efficient schools.’ With the emergence of big data, startup schools such as
AltSchool are increasingly applying algorithmic processes such as machine learning,
predictive analytics, and adaptive systems to engineer better-managed and more
efficient systems of personalized learning.
Algorithmic progressivism as a concept captures well the pedagogic uptake of big
data software within the personalized learning aspirations of Silicon Valley. Critical
studies of data and software in a variety of sectors have begun to detail how code
and algorithms have begun to intervene in diverse processes, practices and
institutions. Kitchin and Dodge (2011), for example, have articulated how software
and analytics have pervasively entered into everyday life through the production of
‘code/spaces’—environments that entirely depend on software systems for their
intended functioning, and that are recursively transformed by their presence. They
note in particular the emergence of a new form of governance they term
‘automated management’ where tasks are increasingly performed by autonomous
software systems that operate automatically, with limited human intervention. In
particular, data collection and analysis has become an increasingly automated task,
with algorithms designed to gather, store, sort out, and process information.
Startup schools are prototypical of classroom code/spaces, where the pedagogic
processes of the school are increasingly governed by algorithmic processes of
automated management and the constant collection and analysis of data from
learners and teachers. The discourse of personalization that accompanies and
justifies startup schools supports new hybrid data-driven forms of individualized
learning, a form of algorithmic progressivism that is managed via data analytics and
adaptive platforms, and that is rationalized simultaneously as a form of social good
and a source of revenue generation under an experimental regime of technology
philanthropy in public education.
Learning laboratories
As well as acting as new classroom code/spaces of algorithmic progressivism,
Silicon Valley’s startup schools are also positioned as laboratories where new
scientific theories of learning itself may be trialled in experimental fashion. Summit
Public Schools, Khan Lab School and AltSchool have been described as ‘mini-
research and development labs, where both teachers and engineers are diligently
developing the formula for a 21st century education, all in hopes of applying that
formula … to private, public, and charter schools across the country’ (Lapowsky
2015). In this sense, startup schools are setting themselves the highly normative
goal of defining the future of education and learning, informed by their own in-
house analyses from data about their own classrooms, curricula, teachers and
students. They also draw on academic expertise in the assessment of both the
cognitive and the non-cognitive aspects of learning developed in recent years by
psychologists at Stanford University within Silicon Valley.
The Facebook-supported Summit Learning Platform used across the Summit
Public Schools network, for example, has been engineered on an explicit model of
cognitive skills development developed at Stanford:
Summit developed the Cognitive Skills Rubric built into our Summit Learning Platform in
collaboration with the SCALE team at Stanford, whose mission is to improve instruction
and learning through the design and development of innovative, educative, state-of-the-art
performance assessments and by building the capacity of schools to use these assessments
in thoughtful ways, to promote student, teacher, and organizational learning.
(http://info.summitlearning.org/program/program-requirements/)
70% of each student’s grade on the Summit platform is criterion-referenced with
the cognitive skills rubric, with the remaining 30% assessed on content knowledge.
‘Our grading policy reflects our values,’ it states, ‘which is why we emphasize
cognitive skills over content knowledge.’ Similarly, the Khan Lab School has been
established as an experimental R&D lab for testing different educational
approaches and technologies, and aspires to contribute to the production of new
theories of learning itself. As an educational R&D laboratory, Khan Lab School
has been profiled in Wired, which noted that its
goal isn’t just to build one fancy school but to develop and test a new model of learning
that can be exported to other schools around the country and the world. [Its] team is
diligently recording and tracking every student’s progress and sharing the findings with
their parents and the staff, an open source approach to educational innovation. In this
view, the Lab School kids are guinea pigs … willingly subjecting themselves to new ideas
that have never been tried before, then adapting and adjusting and trying again. ‘This is a
lab for establishing new theories that could affect the rest of the planet,’ Khan says. ‘The
whole point is to catalyse change.’ (Tanz, 2015b)
Lab School’s ‘touchy-feely surface’ of character education, well-being and
mindfulness, however, ‘masks a rigorous fealty to tracking data about every
dimension of a student’s scholastic and social progress’ (Tanz, 2015b).
At Altschool, likewise, ‘parents pay fees, hoping their kids will get a better
education as guinea pigs, while venture capitalists fund the R&D, hoping for
financial returns from the technologies it develops’ (Kuchler 2017). Notably,
AltSchool has ambitious technical and methodological aspirations to subject its
students to data analytics, not just through academic tracking and monitoring of
cognitive skills, but also through wearable biometrics, facial vision analysis and
motion detection that can capture the non-cognitive aspects of learning. This
includes fitting cameras that run constantly in the classroom, capturing each child’s
every facial expression, fidget, and social interaction, as well as documenting the
objects that every student touches throughout the day; microphones to record
every word that each person utters; and wearable devices to track children’s
movements and moods through skin sensors. This is so its in-house data scientists
‘can then search for patterns in each student’s engagement level, moods, use of
classroom resources, social habits, language and vocabulary use, attention span,
and academic performance, and more’ (Herold 2016).
An emphasis on the non-cognitive, social and emotional aspects of learning has
emerged strongly in US education in recent years. Startup schools are seeking new
experimental ways of capturing, quantifying and acting upon such qualities. The US
Office of Educational Technology in the Department of Education published its
report ‘Promoting Grit, Tenacity and Perseverance’ in 2013, noting these were
‘critical factors for success’ in the 21st century (Schechtman et al 2013). The report
sought to encourage a shift in educational priorities to promote not only content
knowledge and cognitive skills, but also grit, tenacity, and perseverance, and
proposed the use of technical systems to measure non-cognitive factors and
student dispositions such as levels of frustration, motivation, confidence, boredom,
and fatigue. One of the influential psychological advisors to the report, Carol
Dweck of Stanford University, has turned her theory of ‘growth mindset’ into
practical techniques that she has successful marketed not only to the education
sector but also to technology management in Silicon Valley, while California state
has become the emerging testbed for a range of techniques to measure the non-
cognitive, social-emotional and personal qualities of education (Zernike 2016).
Beyond its symmetries with emerging policy regimes, AltSchool’s aspirations to
monitor not only students’ academic progress but also track their social and
emotional learning through data is an exemplar of what McStay (2016) has
designated ‘empathic media.’ Empathic media consist of ‘technologies that track
bodies and react to emotions and intentions,’ or a combination of online behaviour
tracking and the commercial application of neuroscience-based understandings of
the involuntary nature of human emotions and affects (McStay 2016: 1). These
technologies include biometrics that can detect emotional arousal through the skin,
and affective computing systems. Affective computing relies on the development
of systems that can collect physiological data from the user, often through facial
recognition software and algorithms. The user’s emotion can then be classified
using psychological theories of how emotions express themselves physiologically,
with training sets of data used to teach an algorithm to identify particular emotions,
thus allowing the system to respond appropriately and even simulate human
emotions in a way recognizable to humans, and in some cases deliberately generate
a particular emotional response in the user (Rose, Aicardi & Reinsborough 2016).
A recent summary of ‘emotive computing in the classroom’ produced by Silicon
Valley’s ed-tech industry magazine EdSurge has identified a number of relevant
ongoing technical innovations:
Transdermal Optical Imaging, with a camera that is able to measure facial blood flow
information and determine student emotions where visual face cues are not obvious
Electroencephalogram (EEG) electrical brain activity tests to measure students’
emotional arousal, task performance and provide computer mediation to individuals
Wearable social-emotional intelligence prosthetic which uses a small camera and
analyzes facial expressions and head movements to detect affects in children in real-
time
A glove-like device that maps students’ physiological arousal an measures the
wearer’s skin conductivity to deduce excitement, engagement or fatigue and stress
(Spreeuwenberg 2017)
As these examples indicate, AltSchool’s ambitions to utilize affective computing
and wearable biometric technologies are prototypical of wider Silicon Valley
aspirations to treat the body of the student as a source of psychological and
neuroscientific data collection and analysis. Students are treated by Silicon Valley
not just as active, enquiring agents, but as transparent and machine-readable bodies
of data that can be tracked and traced through their unconscious physiological
signals or even brain activity.
XQ Super School Project takes neuroscience expertise even further in its vision of
the future of US high schooling. A paper on the ‘science of learning’ provided on
its website—and intended as guidance for entrants to the competition—refers to
‘understanding and applying the fundamentals of brain science’ to ‘empower young
people to become agents of their own learning journeys.’ It draws on
neuroscientific claims about the malleability and ‘neuroplasticity’ of the ‘adolescent
brain’ and about the brain-based nature of students’ ‘mindsets.’ In this sense, XQ
Super School Project is an instantiation of the recent interest in ‘neuroeducation’
and the proliferating discourse and practices of neuroscience in education, which
tends to treat the functional architecture of the brain in explicitly determinist
terms, and even ‘to reduce learning to an algorithmic or computational process’
(Pykett 2015: 97).
Another Super School guidance document for competition entrants further
emphasizes the skills students require in the 21st century. It dismisses the so-called
‘old paradigm’ (of following orders, being product-driven, 9-5 lifelong employment
and domain specialization), and replaces it with the ‘knowledge economy’ paradigm
of co-creation, distributed leadership, flexibility, domain agility and creativity.
These ‘21st century skills’ are reflected in numerous other initiatives led by the
Silicon Valley technology companies, most notably the influential Partnership for
21st Century Learning, which are concerned with cultivating the skills associated
with STEM subjects (science, technology, engineering and maths) and accord
closely with the workforce priorities of the tech sector itself. As XQ Super School
Project illustrates, theories of brain plasticity from neuroscience wedded to
economic rationalities are becoming the dominant ways of thinking about
processes of learning, linked to ‘a manic plasticity demanded in the global
marketplace’ (Pitts-Taylor 2016: 18):
There is clearly an ‘elective affinity’ … between this emphasis on plastic, flexible brains
and more general sociopolitical changes that prioritize individual flexibility across the life
span to accommodate to rapidly changing economic demands, cultural shifts, and
technological advances. (Rose and Abi-Rached 2013: 223)
Indeed, concerns about ‘training a twenty-first century workforce’ have been taken
up in neuroscientifically-based training programs designed to mould the plasticity
of the brain, which represent strategies of ‘preemptive neurogovernance’ that are
intended to promote the economic and political optimization of the population
(Pitts-Taylor 2016: 40).
As an institutionalized realization of pre-emptive neurogovernance, XQ Super
School Project makes young people’s STEM mindsets into characteristics that can
be activated through the brain. Its aspiration is to activate human capital through
brain-targeted pedagogies that are intended to produce malleable minds, future-
proofed for the demands of the global marketplace and technology-centred jobs.
Roberts-Mahoney et al (2016: 1) have recently articulated how many educational
data analytics systems are based on categories that measure skills reductively in
terms of ‘human capital’:
Big data and adaptive learning systems are functioning to redefine educational policy,
teaching, and learning in ways that transfer educational decisions from public school
classrooms and teachers to private corporate spaces and authorities. [They] position
education within a reductive set of economic rationalities that emphasize human capital
development, the expansion of data-driven instruction and decision-making, and a narrow
conception of learning as the acquisition of discrete skills and behavior modification
detached from broader social contexts and culturally relevant forms of knowledge and
inquiry.
The student of a silicon startup school is therefore addressed through pedagogies
and technologies inspired by neuroscientific, psychological and economic
categories. In this context, the student of a silicon startup school becomes the
subject of a kind of R&D process where human cognition, emotions and
behaviour itself are seen as targets for techniques of governance, improvement and
optimization.
Conclusion
The new educational models that Silicon Valley is beta-testing on itself and seeking
to roll out and scale up represent the next step in the ‘corporatization of public
schools’—not just the ‘transformation of the school on the model of the
corporation’ (Saltman 2010: 13), but more specifically the transformation of the
school on the technical, economic, cultural and scientific model of Silicon Valley
itself. Silicon Valley’s startup schools exemplify the growing influence of venture
capital and philtech in shaping and mobilizing new paradigmatic fast-policy models
of best practices in education. They are actively prototyping new kinds of
code/space classrooms where pedagogic routines are increasingly semi-automated
through the use of sophisticated analytics and adaptive systems that can help
educators define ‘personalized learning playlists’ based on student data. The
hybridization of personalized learning software and data analytics with
progressivist educational aspirations is leading to a new form of algorithmic
progressivism which combines student-centred pedagogic ideals with social media
logics of user customization. And startup schools are acting as learning laboratories
for new psychological and neuroscientific theories, in ways which make cognitive
skills, non-cognitive social-emotional learning, and even the plasticity of the brain
itself the targets for intervention, management and optimization.
Lewis-Krause (2016) claims that the ‘most important thing happening in Silicon
Valley right now is … institution-building—and the consolidation of power—on a
scale and at a pace that are both probably unprecedented in human history.’
Increasingly, Silicon Valley is seeking to de-governmentalize public education by
governing educational institutions such as schools directly from its own offices and
studios. Through this strategy, it is seeking to consolidate its position as a techno-
political centre of global education reform by enacting fast-policy processes such as
rapid roll-out, policy experimentation and diffusion of best practices. It has created
startup schools as competitive alternatives to state schooling, and built these
schools as the physical infrastructure that overlays its digital infrastructure of data
analytics and adaptive systems. In this way, entrepreneurs such as Max Ventilla,
Mark Zuckerberg, Laurene Powell Jobs and Salman Khan have become architects
of a new model of the ‘full-stack education company’—a supply-side provider of a
school service that also includes commercial, for-profit in-house software
engineering and product development—but also high-profile and persuasive
corporate education reformers. Their aspiration is to govern education
entrepreneurially and digitally from the offices of philanthropic foundations and
the engineering studios of software development startups.
Most notably, these Silicon Valley entrepreneurs are constructing a new digital
infrastructure of personalized learning technologies as a direct counter to the
sociotechnical infrastructure of test-based accountability that has driven processes
of quantification and standardization in US education particularly
(Anagnostopoulos et al 2013). Startup schools such as AltSchool may be
understood, then, as both R&D labs and marketing devices for the digital systems
and infrastructural networks being developed by their engineers, analysts and
entrepreneurial founders and boards of directors and investors. These digital
systems are imprinted with the values and business plans of their originators, and
act as sociotechnical diffusers of their aspirations and priorities to reinvent public
education in the image of Silicon Valley itself. If, as it plans, AltSchool successfully
launches its platform across state education in 2019/2020, for example, then any
school paying the required recurring fee will be transformed into a mini-AltSchool
outpost, with its administrative and pedagogic processes running on Silicon
Valley’s encoded models of teaching, learning and schooling. Instead of an
infrastructure of test-based accountability, it is creating a digital infrastructure of
data-based algorithmic progressivism, from which it aims to profit while making a
positive social and public impact.
Just as Silicon Valley itself may be best understood as a topological array of
relationships between business, money, technologies, entrepreneurship and coding
practices—rather than just as a topographically defined geographical zone—startup
schools are seeking to extend their founders’ and funders’ influence and power
topologically by linking public schools via a networked digital infrastructure to
headquarters in Silicon Valley. In other words, Silicon Valley is seeking to
reproduce the model of the startup school across public education by implanting
its software platforms in classrooms at massive scale, and stitching the entire
system together as a vast digitally connected network of pedagogic management
and data analytics software platforms. The reformatory policy model favoured by
startup school founders and funders is exactly the same as its business model and
its technical plan: to mobilize and scale innovation at speed through digital
networks. It is digitizing education reform itself.
Through these techniques, actors and relations, Silicon Valley is involving itself in a
major program of institution-building and the consolidation of power within
education itself. As the leading site of global digital education reform, it is treating
education as a marketplace within which successful startup companies might scale-
up to public education at large, as long as they can secure the right investment,
build the right software, tune the right algorithms, secure the required customers
and users, and guarantee return on investment.
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