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.

References

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Andreessen Horowitz. (n.d.). Software is eating the world. Retrieved March 16, 2026, from https://a16z.com/

Arpaci, I., Kilicer, K., & Bardakci, S. (2015). Effects of security and privacy concerns on educational use of cloud services. Computers in Human Behavior, 45, 93–98. https://doi.org/10.1016/j.chb.2014.11.075

ARPANET. (2026). In Wikipedia. https://en.wikipedia.org/wiki/ARPANET

Attaran, M., Attaran, S., & Celik, B. G. (2017). Promises and challenges of cloud computing in higher education: A practical guide for implementation. Journal of Higher Education Theory and Practice, 17(6), 20–38.

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.

Bandura, A. (2001). Social cognitive theory of mass communication. Media Psychology, 3(3), 265–299. https://doi.org/10.1207/S1532785XMEP0303_03

Behrend, T. S., Wiebe, E. N., London, J. E., & Johnson, E. C. (2011). Cloud computing adoption and usage in community colleges. Behaviour & Information Technology, 30(2), 231–240. https://doi.org/10.1080/0144929X.2010.489118

Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351–370. https://doi.org/10.2307/3250921

Cheng, M., & Yuen, A. H. K. (2018). Student continuance of learning management system use: A longitudinal exploration. Computers & Education, 120, 241–253. https://doi.org/10.1016/j.compedu.2018.02.004

Cheng, Y.-M. (2020). Students’ satisfaction and continuance intention of the cloud-based e-learning system: Roles of interactivity and course quality factors. Education + Training, 62(9), 1037–1059. https://doi.org/10.1108/ET-10-2019-0245

Chowdhury, G., McLeod, J., Gillet, V., & Willett, P. (Eds.). (2018). Transforming digital worlds. Springer.

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Demoulin, M., Bushey, J., & McLelland, R. (2018). How to assess cloud service contracts? In G. Chowdhury et al. (Eds.), Transforming digital worlds (pp. 175–184). Springer.

Dowell, M. L., & Greenhalgh, S. P. (2025). Information flow solipsism in Canvas: An exploration of student privacy awareness. The Internet and Higher Education, 65, 100989. https://doi.org/10.1016/j.iheduc.2024.100989

Ekuase-Anwansedo, A., & Smith, A. (2019). Effect of cloud-based learning management system on the learning management system implementation process. In Proceedings of the 2019 ACM SIGUCCS annual conference (pp. 176–179). ACM.

Ercan, T. (2010). Effective use of cloud computing in educational institutions. Procedia – Social and Behavioral Sciences, 2(2), 938–942. https://doi.org/10.1016/j.sbspro.2010.03.130

Grandinetti, J. (2022). From the classroom to the cloud: Zoom and the platformization of higher education. First Monday. https://doi.org/10.5210/fm.v27i2.11655

Greenhalgh, S. P., DiGiacomo, D. K., & Barriage, S. (2023). Platforms, perceptions, and privacy: Ethical implications of student conflation of educational technologies. Information and Learning Sciences, 124(9–10), 247–265. https://doi.org/10.1108/ILS-03-2023-0030

Hirsch, B., & Ng, J. W. P. (2011). Education beyond the cloud: Anytime-anywhere learning in a smart campus environment. In Proceedings of the International Conference for Internet Technology and Secured Transactions (pp. 718–723).

Ibert, O., Oechslen, A., Repenning, A., & Schmidt, S. (2022). Platform ecology: A user-centric and relational conceptualization of online platforms. Global Networks, 22(3), 564–579. https://doi.org/10.1111/glob.12355.

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Noteboom, J. (2025). The student as user: Mapping student experiences of platformisation in higher education. Learning, Media and Technology, 50(1), 29–43. https://doi.org/10.1080/17439884.2024.2414055

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Sefton-Green, J., & Pangrazio, L. (2022). The Death of the Educative Subject? The Limits of Criticality under Datafication. Educational Philosophy and Theory 54(12):2072–81. https://doi.org:10.1080/00131857.2021.1978072.

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Vanessa Ratten. (2012). Entrepreneurial and ethical adoption behaviour of cloud computing. Journal of High Technology Management Research, 23(2), 155–164. https://doi.org/10.1016/j.hitech.2012.06.006

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Task preface: Formulate a conception of usability based on the ideas of Issa and Isaias (2015); what might be missing from this conception from an educational perspective? Discuss a couple of Woolgar’s (1990) examples of “usability gone wrong”, and compare to the following exerpts:

“…the usability evaluation stage is an effective method by which a software development team can establish the positive and negative aspects of its prototype releases, and make the required changes before the system is delivered to the target users”  (Issa & Isaias, 2015, p. 29).

“…the design and production of a new entity…amounts to a process of configuring its user, where ‘configuring’ includes defining the identity of putative users, and setting constraints upon their likely future actions” (Woolgar, 1990).

What could “usability” mean?

“Usability” has the intrinsic advantage of being a vague enough term to be welcoming of a variety of ideas based on the context of discussion. It can be associated with the form and function of physical objects like ball-point pens or airplane seats, and it can also refer to the use and utility of digital “things” like Facebook Marketplace or Doom 2. The common thread suggests an exploration of how humans engage with, employ, master, and ultimately derive value from a tool – whether it is virtual or not.

More recently, the term has become a reference for the experience people have when interacting with a digital service. Is the interface enticing to engage with? Is it easy to understand? Do specific actions lead to predictable outcomes? Did it drain your energy or generate frustration?! Did it help achieve a goal? Issa and Isaias (2015) reference Benyon et al. (2005) in ascribing usability to the “quality of the interaction… such as time taken to perform tasks, number of errors made, and the time to become a competent user” (Benyon et al. 2005 , p. 52), and by framing the concept within the bounds of digital interaction, it is reasonable to agree that the most important components of usability as a definition of the user’s experience, are 1) the design of the tool or system being used; 2) the characteristics of the tasks performed to achieve the objective; and 3) the user themselves, including their capabilities and motivations (Issa and Isaias, 2015, p. 31).

Listening to learners and teachers

Photo by Royhan Firdaus on Unsplash

These parameters reflect a generalized definition used by technologists to help explain purpose and corroborate justification, but in education, where profits are not the primary driver, usability requires a more nuanced articulation. Whether referring to a post-secondary context or one within the K-12 system, usability in education could arguably be called “userability” to reinforce the importance of the centrality of learner factors, with system and task parameters re-positioned clearly as dependent factors. In striking contrast to Woolgar’s (1990) proposal that a user is configured, and is “delimited” by a particular set of actions, Cazden, et al. (1996) reminds us that “…learning processes need to recruit, rather than attempt to ignore and erase, the different subjectivities – interests, intentions, commitments, and purposes – students bring to learning.” It is in fact this diversity which requires us to examine and adjust our digital interfaces in order to improve and optimize the user experience.

How not to…

Two examples of Woolgar’s (1990) humorous but problematic approach to usability involved the production of the Stratus machine. In recounting how user “trial” results were incorporated into subsequent iterations, Woolgar incredibly states that findings “…were never written up in any final form”, but were instead passed to members of the project team by word of mouth (Woolgar, 1990, p. 75-76)! In another example, the young Woolgar describes how the users to be tested were chosen: who did they think would be “…most likely to act as users” (Woolgar, 1990, p. 82-83)? Incredibly (again!), the trial group was comprised solely of members of the company (product secrecy really should have been addressed with non-disclosure agreements). If you are attempting to gauge real-world experience accurately, this is not the way to do it!

Optimizing the experience

While there is value in Woolgar’s (1990) assertion that the user should be defined (similar to a marketer’s tenet of knowing their audience), what is refreshing about Issa and Isaias’ (2015) reframing is that discovering optimal usability is a process – a process that has well understood stages and methods that put the user at the centre.

References

Benyon, D., Turner, P., Turner, S. (2005). Designing interactive systems: A comprehensive guide to HCI, UX and interaction design (2nd ed.). Pearson Education Limited, Edinburgh.

Cazden, C., Cope, B., Fairclough, N., Gee, J., Kalantzis, M., Kress, G., & Nakata, M. (1996). A pedagogy of multiliteracies: Designing social futures. Harvard educational review, 66(1), 60-92.

Issa, T., & Isaias, P. (2015) Usability and human computer interaction (HCI). In Sustainable Design (pp. 19-35). Springer.

Woolgar, S. (1990). Configuring the user: The case of usability trials. The Sociological Review, 38(1, Suppl.), S58-S99.

Task preface: Using a historical-educational work as a canvas, carry-out a search of terms – similar to those employed in the course’s example of a search of Lord’s (1991) records – that demonstrates how Indigenous peoples have been represented historically, and how this has impacted education, educational government policy, and socio-cultural attitudes towards education.

Inside the BC Telephone Company Museum.

My exploration for “educational history-related” documents began with a search of a museum my family and I visited this past spring – the BC Telephone Company Museum in Aldergrove, BC. This hidden gem houses a variety of tactile and informational artifacts about how telephone communication developed in BC, and it was my first thought after pondering the kinds of historical records that I might reference for this assignment. Unfortunately, very few of the records have been digitized, so my search led me to the Internet Archive, where I perused artifacts on military education and books on educational policy over the twentieth century, as well as collections about BC’s education history at the Royal BC Museum Archives. I settled on Cowan’s (2018) Postsecondary education in British Columbia: public policy and structural development, 1960-2015, because it appeared to span a relevant timeframe: a range that includes the attitudes and sentiments of those who may have supported repressive government policies (sixties scoop), as well as the zeitgeist of more recent times, particularly since the release of the report and recommendations of the Truth and Reconciliation Commission (2015). This text was published just as BC’s Ministry of Education’s redeveloped provincial curriculum was introduced, so it certainly could have had the potential to supplement teacher education programs throughout the province.

Although this text focuses on the post secondary context, I’m curious to know more about the articulation between the K-12 system and post-secondary education with respect to the more holistic and lived-experience re-telling of First People’s history reflected in BC’s new K-12 curriculum. How did post-secondary public policy and structural development impact teacher education programs as society’s perception towards Indigenous people change?

In addition to the terms identified in the assignment example, I’ve added the words “traditional”, “reserve”, “reservation”, and “ancestral” to my search because they may illuminate passages that are associated with relevant text, and they are they are often used in land acknowledgements as a way of attempting to correct perceptions by describing the depth, richness, and importance of the history of the First Nations peoples.

A new question worth considering might be something along the lines of “What structural development or policy changes were made – with specific reference to indigenizing the curriculum – to better respect the knowledge, history, and culture of Indigenous peoples?”

A simple search of these terms generated the following results:

• indigenous: 17
• native: 4
• indian: 1
• aboriginal: 30
• first nations: 3
• traditional: 12
• ancestral: 0
• reserve: 1
• reservation: 1

In reading the sections containing the search terms, Cowin (2018) takes an objective view when describing Indigenous education:

“…in the 1990s, programming for Aboriginal students began to build momentum, as reflected in the creation of the province’s Aboriginal Post-Secondary Education and Training Policy
Framework in 1995…” (Cowin, 2018, p. 95).

“The Indigenous Adult and Higher Learning Association formed in 2003, the third generation of a consortium of Aboriginal-governed institutions. The original consortium had been established partly due to a perception in the Aboriginal community that the public institutions with which Aboriginal-governed institutions were partnering were charging excessive amounts for programming.” (Cowin, 2018, p. 130).

“…although calls to increase the number of apprentices may have resulted in better educational opportunity for individuals and groups – most recently, a concerted effort to make apprenticeship more appealing to Aboriginal people – the precipitating motivation was
often a desire to avoid future labour shortages rather than a desire to allow more individuals to enjoy a certain way of life. (Cowin, 2018, p. 169).

These excerpts highlight Cowin’s tendency to describe the development of our education system in a way that distances responsibility and justifies decisions; this demonstrates that we continue to struggle with the use of a coherent narrative that stresses the need for collective internalization of our past, and our duty to continuously strive for true reconciliation.

References:

Cowin, R. (2018). Postsecondary education in British Columbia: public policy and structural development, 1960-2015. UBC Press.

Lord, A. R. (1991). Alex Lord’s British Columbia: Recollections of a rural school inspector, 1915-36 (Vol. 9). UBC Press.

What does the new curriculum look like: An overview of BC’s redesigned learning. (n.d.). Retrieved January 12, 2026, from https://www.vsb.bc.ca/what-does-the-new-curriculum-look-like-an-overview-of-bc-s-redesigned-learning.16848.