Cloud computing underpins the contemporary digital landscape of online services and platforms. In education, cloud systems make it possible for many educational technologies to function and scale, and are increasingly present in institutions as back-end infrastructure for running digital services and managing data. While research on the ‘platformization’, ‘datafication’, and ‘automation’ of education has been growing in recent years, ‘the cloud’ has received less attention, despite underpinning many of those transformations.
The cloud promises, of course, many benefits. But like the platforms and data systems that cloud operators support, we also need to better understand its social, technical, political and economic dimensions as a route to considering the implications of the cloud in education. Wary of prematurely claiming the ‘cloudification’ of education, in this post I want to think through possible priorities for research along four lines:
- corporate cloud enclosure of public education
- enhanced extraction of economic and data ‘rent’ from the education sector by cloud operators
- expanding infrastructural power over the edtech ecosystem
- extension of capacities of automation and anticipation in education practice, policy and governance
Rather than taking up an advocacy position against cloud infrastructures or platforms, future research could take up analytical positions to understand more fully the kinds of social, economic, technical and institutional transformations that the cloud enables within education systems. Drawing from other recent relevant research, this (longish) work-in-progress provides a sketch towards such studies of the cloud in education.
In technical terms, the cloud is a particular configuration of computing, networking, and data storage and analytics technologies, delivered over the internet without requiring management by the cloud-user. The cloud consists of hardware and software that are available on-demand and on a ‘pay-as-you-go’, ‘plug-and-play’ basis, offering customers the benefit of outsourcing management, maintenance, scaling and upgrading of critical systems, as well as saving on IT infrastructure costs. The cloud operates an ‘as-a-service’ model, providing Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS) depending on clients’ needs.
The cloud is also highly commercialized and privatized. The main players in the cloud infrastructure and platform services market are multinational US-based technology companies, such as Amazon Web Services (AWS), Google Cloud, Microsoft Azure, IBM Cloud, Oracle Cloud Infrastructure, and Salesforce Cloud, as well as Alibaba Cloud and Tencent Cloud in China. With material locations in massive data centres distributed around the world, many of these serve a range of organizations across enterprise and industry sectors, with some increasingly pushing into government and public sector areas such as health, policing and justice, welfare, and education.
The entry of proprietorial clouds into public services is raising significant concerns over governance, regulation, and the concentration of techno-political power. As Jose van Dijck has recently argued, clouds are both highly privatized and deeply penetrating public infrastructures, with little public control.
The architecture of cloud services forms a blueprint for data storage, analytics, and distribution; control over cloud architecture increasingly informs the governance of societal functions and sectors. Amazon Web Services, Google Cloud, and Microsoft Azure dominate this layer, and while states and civil society actors become increasingly dependent on them, public control over their governance is dwindling.
Notably, in Europe there is considerable political resistance to corporate cloud operators on the basis of concerns over digital sovereignty. The French government has announced investment in national cloud operators to ‘regain our technological sovereignty in the Cloud’, while in Denmark Google cloud-based services for schools have been effectively banned due to data transfer and security concerns.
Building on the above characteristics and controversies of cloud computing, the first priority around the cloud in education is to understand it as a significant shift in underlying computing arrangements, which may affect a vast range of educational practices. Cloud services appear in education in two main forms. First, the cloud operates as computing and data infrastructure for education platforms to operate upon. Many existing edtech firms are pivoting to the cloud, and corporate clouds underlie many other third-party education platforms and software.
AWS is the major player in this approach, as many other education platforms rely on AWS for computing and data services, such as server space, data storage, and analytics. Global edu-businesses and big edtech platforms including Pearson, the Coursera online learning platform, the 2U online program manager, the language learning app Duolingo, the home tutoring app Byju’s, the school app ClassDojo, and many more, all sit on AWS. AWS also hosts its own cloud-based education service, the AWS Educate online learning program, and actively supports third party edtech startups with AWS training, facilities and discounts. Google’s cloud-based Classroom also integrates with a vast Marketplace of thousands of third-party education platforms, as the cloud facilitates elasticity, connectivity, and interoperability between different platform operators.
Second, the cloud operates in education as institutional infrastructure. Rather than running their own in-house IT systems, educational institutions including schools, colleges and universities increasingly outsource infrastructure services and management to cloud operators. Whole school districts have migrated to cloud systems to enable greater collaboration, access and data flow.
Many of the major cloud companies offer specific cloud-based packages to the education sector, ultimately providing the ‘full stack’ of back-end infrastructure and education platform products. Salesforce, for example, offers full migration of institutions’ legacy systems to its Education Cloud, and as part of that provides the cloud-based ‘Education Data Architecture’ for a ‘360 degree view’ of the student. MS Azure for Education includes ‘virtual desktop’ and ‘app virtualization that runs in the cloud’ to support online and remote teaching and learning, and ‘flexible migration’ to ‘the cloud with managed service’.
Likewise, Google Cloud for education provides ‘scalable infrastructure’ for educational institutions, including its Workspace suite for digital learning, its Classroom online learning platform, ‘virtual desktop infrastructure’, ‘data warehouse optimization’, ‘serverless apps for edtech’, ‘smart analytics and AI’ and ‘intelligent learning tutors powered by AI’ to support ‘personalized learning’. AWS for Education also offers ‘Desktop-as-a-Service’ solutions and ‘personal cloud desktops’ for distance learning, ‘no-cost online learning modules on cloud computing’, and ‘virtualized app streaming’ for ‘anytime access’, as well as full institutional migration to the AWS cloud.
For some commentators, the ‘as-a-service’ model of the cloud should be applied to education. ‘Education-as-a-Service’ is likened to the flexible pricing and on-demand delivery of the cloud. In this sense, the technical and economic model of the cloud has become a template for reimagining education as ‘unbundled’ into modularized ‘plug-and-play’ components. More prosaically, AWS describes the ‘big idea that all schools will move to the cloud’ as ‘absolutely right and proper’, part of its attempt to secure widespread institutional migration to cloud infrastructure.
But this marketing discourse glosses over major issues concerning the penetration of public education by proprietary clouds and the platforms with which they are vertically integrated. Commenting on Google cloud-based platforms for schools, Jose van Dijck notes that ‘the dependence of schools on proprietary information systems effectively funnels pupils’ data, generated in a public context, into a proprietary data flow controlled by one corporation’s platforms’.
In these ways, cloud operators have taken up powerful infrastructural positions in the sector: they host and enable digital education companies, services and platforms, as well as underlying and empowering institutions’ digital services, all while inspiring imaginaries of a cloud-like reorganization of education itself and enclosing or ‘locking-in’ public education in privatized infrastructure systems. This reflects how cloud operators have expanded across industries and sectors, and the transformations cloud computing has wrought on the global digital economy.
The cloud is not simply a technical accomplishment. Understanding the cloud in public service areas such as education also means situating it in the shifting dynamics of the digital economy. Education platforms themselves could not operate as they do without the cloud and its distinctive business models.
Many contemporary tech business models are ‘based on turning all social interactions and economic transactions into “services” that are mediated by corporate platforms’, Jathan Sadowski has argued, thereby ‘concentrating control over infrastructure and economic value in a small number of large hands’. He adds,
… tech companies increasingly describe themselves as providing “X as a service.” But what this business model really means is that they enjoy all the rights of owning an asset while you pay for the limited privilege of access. In other words, we are now forced to deal with an explosion of landlords in our daily life — constantly paying rent, both in terms of money and data, for all of the different tools and services we use.
In the platform economy, value is generated from organizations paying on-demand fees and subscriptions for services, which Sadowski defines as ‘economic rent’, and is also amassed from the extraction of ‘data rent’ in the shape of valuable user information that can be monetized, for example by creating derivative products or upgrades.
The cloud is the techno-economic infrastructure underpinning this colossal concentration of tech power. In a recent article on cloud infrastructure, Devika Narayan argues that transformations in underlying computing arrangements are shaping the growth of platform-based companies—specifically that cloud computing arrangements are ‘setting the foundational sociotechnical infrastructure’ for ‘platform capitalism’. Noting the intense competition for cloud market share between big tech companies including Amazon, Microsoft and Google, as well as those companies building on top of their cloud services, she calls the cloud an ‘infrastructural force of 21st-century corporate expansion’.
So, the second priority is to address how the dynamics of corporate cloud expansion apply to education. There are clear issues with the commercialization and privatization of education to consider here. Public education systems are increasingly underpinned by private infrastructures, bringing about concerns over the erosion of public values by private interests and profit-seeking motives. As cloud computing arrangements have become constitutive of the platform economy, education is now thoroughly enmeshed in those new economic shifts, including the vast concentration of power by big tech firms and their new modes of value acquisition. Institutional users of cloud services are paying both economic and data rents for cloud-based services. So too are other third-party edtech platforms.
This is changing the economic landscape of education, with major multinational computing companies now acting as infrastructural forces in education systems in multiple different ways. The ‘network effect’ of increasing educational subscriptions to clouds, by institutions and platforms alike, means education is entangled in what Devika Narayan calls ‘new modes and strategies of accumulation and corporate expansion’, as well as being a key target of ‘the aggressive market-making activities of the cloud computing heavyweights—Amazon, Google, and Microsoft’.
A third area of research on the cloud in education might focus on its connective architectures—the way specific programs and protocols connect various platforms and services together into networked ecosystems, facilitated by cloud infrastructures. Devika Narayan, for example, talks of ‘modularized architectures’ of different software applications that are connected together by application programming interfaces (APIs). She refers to APIs as ‘boundary resources’ that integrate different software applications in cloud systems, ‘resulting in a do-it-yourself approach to computing infrastructure’.
Technically, APIs are a mundane instance of software code allowing applications to connect, interoperate, and exchange data and functionalities. But in a new article, Fernando van der Vlist, Anne Helmond, Marcus Burkhardt and Tatjana Seitz argue APIs have a much more significant role. ‘APIs have become the core elements of digital infrastructure, underpinning today’s platform economy and society’, they argue, suggesting research and regulation should ‘not only focus on the market dominance of platform companies but also on their “data dominance”—specifically, how platform companies use APIs to share data or integrate their services with third parties’. API specifications ‘govern and control the possibilities for the exchange of data and services between software systems and organizations’, they add, and are a ‘major source of infrastructural power’.
Cloud operators therefore rely on API specifications to enable platform developers to build on and interoperate with the cloud infrastructure. In that sense the design of APIs sets the rules by which other third party platforms can integrate into, communicate, and exchange data with cloud operators, ‘in exchange for infrastructural control’ as van der Vlist and colleagues put it.
Moreover, as Kean Birch and Kelly Bronson argue, APIs may not only function as boundary resources in modularized ‘digital ecosystems’ of interconnected platforms and infrastructures. They also function as ‘boundary assets’ with calculable techno-economic value for their owners and controllers. These boundary assets, they argue, ‘not only enable integration across boundaries’, but ‘the modular relations they constitute end up having significant value for Big Tech firms whose valuation is based on the capitalization of future earnings derived from the users in and of their ecosystems’. Understood as assets that generate value from constructing modular relations across platform ecosystems, cloud APIs thus reinforce the dominant techno-economic business model and cloud economics of big tech firms.
APIs play a significant function in the contemporary educational ecosystem of cloud-based digital education platforms. Cloud operators such as Google and AWS, which are highly active in education, are mobilizing APIs to integrate an array of education platforms into their cloud infrastructures. The cloud-based Google Classroom, for example, integrates with a huge variety of third party educational platforms through a specific Classroom API and single-sign-on access, facilitating significant cross-platform interoperability across the edtech landscape and making Classroom itself a central gatekeeper to other education platforms.
Similarly, AWS has deployed APIs to enable other third party developers to integrate its voice and face recognition technologies. These include an API to permit other developers to integrate Alexa-based voice interfaces into educational applications, such as learning management systems, student information systems, classroom management tools and online course platforms. AWS also provides an Amazon Rekognition API enabling developers to add image and video analysis to their applications, including facial recognition and facial analysis, which has been integrated into exam proctoring software.
As van der Vlist and coauthors argue, APIs govern the development of third party services and platforms. Beyond being technical objects, API design sets kinds of policies that ‘directly influence, often in subtle ways, what can and cannot be built, sustained, or thrive in the ecosystem’, and ‘provide centralized and unidirectional hierarchical control over large numbers of apps and services—and the developers who build and maintain them’. And as Birch and Bronson put it, ‘big tech’ proprietors ‘can set the terms of engagement through contractual arrangements…, representing privately-made rules and standards’ that function as ‘gatekeeping’ devices for modular integrations and relations.
Yet very little is known about the ways APIs govern the development, functionalities and relations of third party education platforms with cloud arrangements, or about the exchanges of data that occur once a platform integrates into and interoperates with a cloud infrastructure via an API.
The fourth area of research on the cloud in education could focus on the specific new capacities that the cloud affords for other education platforms and services. In the book Cloud Ethics, Louise Amoore approaches cloud computing in terms of its algorithmic powers of perception. The cloud, she argues, ‘is a bundle of experimental algorithmic techniques acting in and through data’, and ‘contemporary cloud computing is about rendering perceptible and actionable (almost seeing) that which would be beyond the threshold of human vision’.
The promise of the cloud is that masses of heterogeneous data processed using machine learning algorithms can generate unprecedented insights and predictions to be acted upon by reducing vast complexity to single outputs, often by automated means. The cloud, Amoore argues, generates objects of ‘attention’ from the combination and analysis of massive datasets; objects of attention that might then become targets of intervention.
In this sense, the cloud needs to be considered as the active infrastructure that makes possible applications of machine learning, predictive analytics, and the bundle of technologies known as artificial intelligence. The cloud enables new kinds of ‘AIOps’ (Artificial Intelligence for IT Operations, as tech consultancy Gartner describes it) to be built into industries and sectors such as education.
Indicatively, AWS is actively seeking to embed its machine learning facilities in other edtech platforms, inciting customers to ‘add Amazon API-driven ML services to your education software’, such as image and video analysis, text-to-speech, speech-to-text, translation, and natural language processing. Google has recently begun adding AI functionality to Google Classroom, supported by its cloud facilities, and proposed applying its large language model LaMDA as a conversational agent within the Workspace suite of platforms widely used in education too.
Educational institutions subscribing to the cloud may also be transformed by these new AIOps capacities. Cloud prioprietors propose that institutions using their cloud facilities can access enhanced data functionality, machine learning and AI for ‘digital transformation’. As part of its ‘Student Success Services’, Google has launched a ‘new Google Cloud artificial intelligence powered learning platform’. The platform is described as ‘a suite of applications and APIs that can be integrated into an institution’s existing infrastructure’, including ‘auto-generated and personalized recommendations for courses based on their prior learning’, and an ‘interactive tutor’ that ‘uses APIs to present a chat-based experience for students, incorporating AI-generated learning activities’.
AWS similarly claims its institutional cloud users can ‘Share data seamlessly across platforms to get a comprehensive view of student performance and uncover insights’, and ‘enhance learning with powerful tools including, artificial intelligence (AI), machine learning (ML), and voice-recognition’. It has published an entire guide on becoming ‘a data-informed institution’ focused on ‘how institutions are using data and cloud technology to inform digital transformation’. Oracle, too, has launched Oracle Student Cloud, which it claims is ‘powered by artificial intelligence (AI)’ and ‘consumer-market design elements’ to ‘dramatically change the student experience at every stage of the lifecycle’.
As these examples indicate, the cloud can power education platforms with new capacities for datafication, prediction, automation, and other AIOps. It is a sociotechnical foundation for what Kalervo Gulson and Kevin Witzenberger have termed ‘automated anticipatory governance’, whereby AI enacts forms of prediction and pre-emption, particularly through integrating AI in edtech platforms via APIs. The cloud and platform APIs may therefore function to govern a widening array of processes and practices in education by introducing new capacities of corporate AIOps into edtech platforms and institutional information systems.
The cloud is a largely invisible, background presence in education, despite playing an increasingly significant role in many technical and institutional processes and practices. As recent relevant scholarship on the cloud has indicated, cloud computing arrangements are significantly affecting and reshaping a range of industries and sectors. The cloud represents an expansion of corporate big tech power into sectors like education, introducing new economic models, platform ecosystem arrangements, and AIOps capacities of automated governance.
At its most extreme the cloud will even underpin plans to build out new virtual reality educational experiences and institutions in the ‘metaverse’, which (if realized) will both be a huge economic bonus for cloud operators and for cloud-based metaverse platform providers.
Much more significant are the more mundane instances of cloud computing in education, which promise many benefits, but also pose important questions for research. Areas of investigation include institutional autonomy and control over data and infrastructure, challenges to student consent and ‘opt-out’ of cloud storage, potential for breaches and leaks, the possibility of long-term lock-ins, automation of educational processes, and the redirection of educational funds from in-house systems to outsourced cloud provision and maintenance.
It may be too soon to claim the cloudification of education, but it’s clear many aspects of education are now being enclouded to a significant degree, with longer-term effects which remain to be seen. While remaining sceptical of cloud-inspired imaginaries of Education-as-a-Service or cloud-based ‘metaversities’, education research should nonetheless consider what powers the cloud and its operators could exert on the sector, and how to respond.