The “dot-com bubble” on either side of 2000 solidified personal computing and the internet as important components of modern Western economies. Increasingly capable computers permeated segments of society, enabling businesses and organizations new ways to connect, trade, and explore. Post-secondary institutions, with their deep expertise in computer science, carried-on the tradition of “spinning-off” private enterprises to capitalize on business opportunities, and played a significant role in the founding and meteoric rise of the worlds most valuable companies; today, only one in the top ten is not a technology company (“Companies ranked by market cap”, n.d). It is no surprise that economics has played an outsized role in the world’s collective adoption of information technology (IT).
The journey from amber monochrome screens to pinging pocket phones has several .well-known milestones: the aural beeps and burps of dial-up modems; the entry of “Google” into popular vernacular; the adoption of HTML to express purple-border web pages; BlackBerry buttons; Hotmail and email by Google; Napster and Facebook and iPhones, oh my. Affluent consumers able to purchase an x86 connected to corporate servers that were typically physically colocated in or around a business’s headquarters. Higher education was no exception: massive mainframes dominated the basements of computer science buildings to provide nascent online course offerings to university communities around the world.
As usage for IT services surged, the demand for more storage, faster connections, and bigger processors drove up costs; and when expectations weren’t met, people’s satisfaction suffered (Cheng & Yuen, 2018); the stage was set for a takeover. Although “distributed”, “grid”, or “utility” computing had existed for decades (ARPANET, 2026), it suffered from an inability to shed its “dumb terminal” image. When this cyberinfrastructure was rebranded as “the cloud”, it began “eating the world” (Mell & Grance, 2011; Andreessen Horowitz, n.d.).
This lighthearted introduction is meant to contrast with what Greenhalgh et al. (2023) describe as a more serious, insidious, and worrisome trend in education, which is the misconstruing of platforms as merely tools, and students’ resignation to the inevitability of the overdatafication of their lives (Greenhalgh et al., 2023). Education’s changing role in the service of changing societies has put pressure on traditional models of delivery, and under the coercion of technology venture capitalists, is now “driven by processes of privatization”, with students and instructors alike being configured as “users”, measured not by whether they understand a solution or concept, but how much time they spend on a page (Ramiel, 2019; Grandinetti, 2022). It within this context that I examine the supplantation of disparate, on-premise computing hardware – the servers and systems historically physically colocated with an organization – by supranational cloud vendors, which has resulted in education’s common configuration, the techno-social commodification of learning, and the obfuscation of data privacy practices that result from the “platformization” of educational activity (Noteboom, 2025; Ramiel, 2019; Grandinetti, 2022; Greenhalgh et al., 2023; Dowell et al., 2025).
Cloud services arose from an industry of computing based on data centers that were largely owned and operated by organizations considered “non-tech”. Researchers from Northwestern University estimated that in 2010, 79% of computing occurred in traditional data centers, but that the rise of the cloud resulted in a tectonic shift, with 89% of computing occurring in cloud data centers by 2018 (Lohr, 2020). In education, cloud computing was touted as “a model for enabling ubiquitous, convenient on-demand network access to a shared pool of configurable computing resources … that can be rapidly provisioned and released with minimal management effort or service provider interaction” (Mell & Grance, 2009, p. 2). Erenben (2009) described how cloud computing would significantly transform education to increase quality, improve access to resources, and lower costs, while Wang et al. (2014), suggested that regular monthly fees, rather than high initial capital costs, would facilitate mobile cloud learning services. Educators such as Attaran et al., (2017) confirmed that “technology has the real potential to enable accuracy, reliability, service enhancement, and cost reduction” (p. 20), while Ercan (2010) and Behrend et al. (2011) explained how the elastic scalability and outsourcing of equipment could accelerate the adoption of technological innovations, ensuring students can access and run software regardless of their location or personal processing capability. Advocates consistently encouraged their institutions to “take advantage” of the trend to “enrich students’ technology-enabled education” (Ercan, 2010, p. 940), and with a little nudging from techno-solutionism, it’s no surprise that cloud’s allure entrapped education (Ramiel, 2019).
Studies that examined the Technology Acceptance Model may have also inadvertently fuelled adoption, as their investigations explored users’ behavioural intentions, perceived ease-of-use, and perceived usefulness (Venkatesh & Bala, 2008; Behrend et al., 2011). Researchers found that “…the role of marketing having a positive impact on a person’s behaviour [to adopt technologies] illustrates that information technology companies can focus on advertising to increase the adoption rates of cloud computing users” (Ratten, 2012, p. 161), and to the glee of private corporations, these scholarly articles were published publicly. As the industry sought to appeal to as wide an array of users and contexts as possible, it began offering learning management services (LMS) to educational institutions, configured especially for students and teachers (Woolgar, 1990). Open source platforms such as Angel, Sakai, and Moodle eked out an open-source existence despite the enormous resources of private competitors like WebCT, BlackBoard, and Desire2Learn. At the outset, companies offered on-premise options to attract investment and develop a clientele; integrations with existing Student Information Systems such as Banner or synchronous tools like Elluminate Live! provided workflow improvements and functionality that enhanced the student experience. But as these connectivity tools shifted from on-premise installations to the cloud, and the involved system updates and upgrades evolved into continuously deployed “evergreen” software, companies were relieved from the duty to maintain a constant connection with their customers; ensuring service reliability was much easier because cloud offerings constrained customers into a small number of service options. In addition, the risk of proprietary source code exposure was eliminated because customers were no longer provided with the binaries to run on their own infrastructure. This boundary definition enabled educational technology service providers the ability to create distance between themselves and their customers, which resulted in the objectification, standardization, and optimization of interactive behaviours (Woolgar, 1990; Issa & Isaias, 2015).
Building on the work of Selwyn (2013a) and Biesta (2004), Ramiel (2017), outlines how educational technology production is reframed:
“Teaching, educational goals and skills are described through certain learning concepts: capabilities, opportunities, choices and experiences that come from industrial product design cultures… This learnification (as Biesta (2009) called it) cuts the educational process off from social contexts and from cultural and political issues and values” (p. 488).
Through this techno-social transformation and the associated normalization of “ideologically invisible” platforms, educational technologies are critically assessed less, and unfortunately accepted as objective (Ramiel, 2019). Greenhalgh et al. (2023) and van Dijck (2013) remind us that:
“…a platform is not truly neutral – rather, it “shapes the performance of social acts instead of merely facilitating them” (van Dijck, 2013, p. 29). This shaping becomes increasingly important as “neither neutral nor value-free” platforms play a growing role in public life (van Dijck et al., 2018, p. 3)” (Greenhalgh et al., 2023, p. 248).
Within this context we begin to understand the depth, complexity, and seriousness of the problem: if, students – those members of society who are undertaking the development of critical analysis skills – become habituated to the uncritical acceptance of platforms as they are, it emboldens technology capitalists to carry-on reshaping information flows to their benefit and deepening our dependence on their services.
Noteboom (2025) draws our attention to “platformatization” as educational institutions “…increasingly rely on proprietary platforms for their teaching, research and operational functions” (p. 29). Start-up methodologies like lean, and six-sigma emphasize the focus on the collection of data, algorithmic analysis, and the quantification of behaviours that ultimately serve to monetize the service (Noteboom, 2025; Ramiel, 2019). Online learning activity, as with most cloud services, is recast as ‘retention’ (success), or ‘churn’ (bounce rate, failure) (Ramiel, 2019), which leads scholars like Greenhalgh to question whether the analytics accurately represent the true value of learning as we understand it (Greenhalgh et al., 2023). And with Noteboom’s (2025) research uncovering that students’ perception of the systems they use as simply tools, rather than what van Dijck and Poell (2018) describe as a “complex interplay between technical architectures, business models, and mass user activity” (p. 579), it’s not surprising that students, teachers and parents might not be as concerned about their activity being surveilled (Greenhalgh et al., 2023). A corollary to this apparent apathy is Pangrazio and Sefton-Green’s (2022) reference to data resignation, a circumstance where individuals are aware that their activity is being tracked, but consider the benefits of online participation to be too great to pass up (Pangrazio & Sefton-Green, 2022; Greenhalgh et al., 2023).
A less discouraging perspective by Proferes (2017) attributes students’ attitudes and behaviours to their general lack of understanding of how their data is collected and used:
“Information flow solipsism [is] the subjective position of the user who is familiar with the facets of a platform for which the interface provides informational feedback mechanisms, but who remains unaware of how the technology operates at a broader techno-cultural or socioeconomic level” (p. 10)
This naivety does not recuse the numerous questions about the ethical implications of student privacy (Dowell & Greenhalgh, 2024), but it certainly should spur educational organizations to reflect on their approach to data literacy. This is especially salient for institutions where participation in educational technology platforms is effectively mandatory, and both confusing and challenging to students who value privacy (Dowell & Greenhalgh, 2024). Grandinetti (2022) is particularly critical of Zoom’s meteoric rise as a result of the COVID-19 pandemic:
“…capitalist transformations are imbricated in the greater reliance on third-party big tech platforms by higher education generally and the rise of Zoom as go-to videoconferencing platform specifically, the intertwining of crisis, capitalism, and platformization serve to historicize, in part, how Zoom has been able to rapidly gain an integral place in university life” (p. 3).
Ample literature exists in support of this critical perspective, but Noteboom (2025) reminds us that “affordances cannot be seen as universal properties of platforms but are always ‘enacted’ in a specific context by specific users for particular purposes” (p. 32). It follows that students are not unidirectionally configured; they exercise a degree of agency within a ‘sociotechnical infrastructure’ that entangles education providers within the larger construct of platformatization (Noteboom, 2024; Ibert et al., 2022).
Cloud based educational systems have indeed supplanted traditional on-premise infrastructure – data centres that overwhelmingly chrooted students’ online activity to the providing institution. This cloud shift has enabled the development of improved service reliability, increased access and mobility, and widespread systems integration. It has also resulted in the configuration of students, instructors, institutions, and the education sector as a whole through the commodification of learning and the platformatization and datafication of educational activity. The complicated, intertwined relationship between cloud services and educational technologies has important implications for society’s future, and reflecting on Education’s changing nature today can help ensure our children’s children can thrive in the future to come.
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