It begins, as it often does, in the course design meeting. A colleague sketches out a new module idea: collaborative, inquiry-based, and dialogic. But the excitement begins to fade when the discussion turns to implementation. “Can we do that in Canvas?” someone asks. Another suggests, “Maybe we can use the quiz function or the discussion board?” Soon the question is no longer what kind of pedagogy we want to design, but what the platform allows. The tool, not the teaching, has taken the lead.

This is a familiar scene for many educators navigating contemporary digital learning environments. What once were means to support pedagogy have become the architecture within which pedagogy must fit. Learning Management Systems (LMSs), educational apps, virtual proctoring tools, and AI-powered feedback systems increasingly define the boundaries of what is possible in our teaching. As Jesse Stommel observes, “if the tool is making the pedagogical decisions, then we’ve lost sight of what teaching is for” (Stommel, 2014).

This inversion - where technology precedes and constrains pedagogy - is not accidental. It has been institutionalised through procurement processes, platform standardisation, and a managerial logic that prioritises efficiency, scale, and surveillance over dialogue, care, and relationality (Selwyn, 2022; Macgilchrist, 2019). Universities increasingly adopt digital platforms based on cost-effectiveness and data metrics, rather than on the pedagogical possibilities they afford. These systems become ’invisible infrastructure’ - shaping how learning happens while appearing neutral or inevitable (Star, 1999; Williamson, 2017).

But what happens when our tools start to shape our teaching, rather than support it? This question is not merely technical; it is pedagogical and political. It asks us to consider how the affordances and constraints of platforms contour our assumptions about knowledge, authority, time, and learning itself. It demands that we interrogate how educational technologies are embedded in broader institutional, economic, and epistemic structures.

The work of reclaiming pedagogy, then, must begin by resisting the quiet encroachment of platform logic into our everyday teaching decisions. It requires us to ask not what does the platform enable?, but what kind of education do we want - and what tools do we need to support it?

In many contemporary universities, digital decisions often begin not with pedagogy but with platforms. Learning Management Systems (LMSs), online proctoring tools, AI writing detectors, lecture capture systems, and data dashboards are adopted to meet needs of scalability, standardisation, and institutional oversight. These decisions are frequently made at a senior management level, with input from procurement, IT services, and legal departments - but often without sufficient pedagogical consultation.

This logic of platform-first thinking reflects what Williamson (2017) calls the “datafication” of education: the growing reliance on systems that frame learning in terms of metrics, compliance, and content management. Teaching becomes less about dialogue, discovery, or transformation, and more about what can be tracked, measured, and reported. Similarly, Selwyn and Jandrić (2020) argue that in the wake of rapid digitalisation - particularly during moments of crisis such as the COVID-19 pandemic - there has been an acceleration of “technocratic” responses that prioritise functionality over meaningful pedagogy.

Proctoring software is introduced not because it enhances learning, but because it scales exam surveillance. AI detectors are implemented to enforce academic integrity policies, often without considering the pedagogical causes of misconduct or the human cost of false positives. These tools do not emerge from teaching dilemmas but from institutional anxieties. As Macgilchrist (2019) observes, educational technologies are increasingly embedded with “cruel optimism” - promising fairness, efficiency, and inclusion, but often entrenching inequities and standardisation.

Ultimately, the widespread adoption of such tools without critical scrutiny reshapes the very grammar of teaching. Assessment becomes less an act of professional judgement and more a matter of algorithmic verification. Teaching is reframed as “content delivery” to be uploaded, accessed, and tracked asynchronously. The question is no longer how best to support student learning, but how to ensure it fits into the architecture of the platform.

The widespread adoption of digital platforms in higher education—LMSs, AI-assisted grading tools, content repositories—has not only reshaped administrative workflows, but also profoundly altered the pedagogical landscape. When the affordances and constraints of platforms precede and define the logic of teaching, the result is a subtle but powerful recalibration of educational values.

One of the most immediate casualties is educator autonomy. Teachers increasingly find themselves working within rigid templates that privilege efficiency and scalability over responsiveness and creativity. Learning designs become boxed into what the system allows: dropdown rubrics, timed quizzes, templated discussions. As Biesta (2012) notes, this instrumental turn in education diminishes the space for judgement and professional discretion, reducing teaching to an act of delivery rather than a relational and interpretive practice.

At the same time, this platform-led orientation reinforces transmissive and linear models of learning. Systems are optimised to measure activity—clicks, completions, submissions—not engagement, reflection, or transformation. As Castañeda and Selwyn (2018) argue, the digitisation of higher education has largely followed managerial logics, reinforcing quantifiable outputs at the expense of more dialogic and exploratory pedagogies. This push toward data-friendly instruction reflects what Biesta (2010) calls the “learnification” of education: a shift in which pedagogical relationships are de-centred in favour of depersonalised “learning outcomes” abstracted from context.

The implications for student agency are significant. When digital platforms serve as the primary interface for education, students are often positioned as passive recipients rather than active participants. The structured navigation flows, automated feedback, and surveillance-oriented proctoring tools teach students that their role is to comply, complete, and consume. This is not a neutral development. As Watters (2021) demonstrates in her critical history of “teaching machines,” such patterns echo a long lineage of education technologies designed to condition student behaviour rather than support critical thought or emancipatory learning.

Critical Digital Pedagogy offers a vital counterpoint. As Stommel (2014) insists, teaching must remain a site of resistance against the flattening tendencies of educational technologies. The goal is not to reject digital tools wholesale, but to remain vigilant about how they frame pedagogical possibilities—and to reclaim space for conversation, risk, and ambiguity. Stommel’s provocation reminds us that platforms are never just platforms; they are carriers of ideology, shaping how we imagine what education can be.

At its core, this critique is not nostalgic—it is ethical. As Ball (2012) argues, the performative pressures of the neoliberal university increasingly recast pedagogy as a mechanism of accountability and branding. In such a climate, the cost of letting platforms determine teaching is not just poor design. It is the erosion of education as a human, democratic, and hopeful practice.

The idea that technology is a neutral backdrop to pedagogy - merely a means to deliver content or facilitate interaction - is both persistent and dangerous. In reality, every platform, protocol, and interface in digital education encodes a particular set of assumptions about what learning is, who controls it, and how it should be measured. To engage with digital infrastructure uncritically is to risk embedding forms of pedagogy that may be at odds with our educational values.

As Macgilchrist (2019) argues, the logics embedded in educational technology often reflect “cruel optimism”: the promise of equitable, personalised learning through data-driven tools obscures the reproduction of inequalities and exclusions. This is not accidental. It is a result of how platforms are designed - with incentives that prioritise scale, surveillance, and efficiency over care, dialogue, and agency.

Selwyn (2016) warns that these platforms represent “a narrowing of educational possibilities,” driven less by pedagogical insight and more by institutional imperatives for control and quantification. This narrowing is not simply technical - it is ideological. When a university chooses an LMS or assessment system, it is making a decision about what counts as teaching, how students should behave, and what kinds of data matter. These decisions shape not only practice, but also the imaginative possibilities of pedagogy itself.

The result is a shift in the locus of pedagogical authority - from educators to platforms, from professional judgement to pre-configured defaults. As Stommel (2014) notes, “technology is not value-neutral, and the systems we use to deliver education have deep pedagogical implications.” The infrastructural choices institutions make - often without meaningful input from educators or students - thus become acts of educational governance.

To reclaim pedagogy, we must first confront the infrastructure. That means refusing to see platforms as background tools and recognising them instead as central agents in the shaping of learning. It means asking not only “does this work?” but “who does this serve?” and “what does this make possible or impossible?” A truly critical digital pedagogy begins by treating infrastructure as a site of ideological struggle - and as a space for ethical imagination.

Proposing a shift: pedagogy must guide technology, not vice versa. This means starting with teaching aims and designing or adopting tools to serve them - not shaping teaching to fit a platform.

Open Source and Pedagogical Values Moodle offers a strong example. Originally created by educators for educators, it was built to support constructivist, dialogic learning environments. Costello (2013) documents how universities selected Moodle not simply for cost but for its flexibility, community ownership, and alignment with social-learning pedagogies. The choice was rooted in educator agency and intentional design - not top-down administrative convenience.

Participatory and Values-Driven Design Similarly, Quinn et al. (2022) argue that platforms built with practitioners and learners - not merely for them - better reflect educational values like inclusion and dialogue. These participatory design processes - where teaching teams influence feature development - reclaim tech as a site of pedagogical agency, not institutional compliance.

Critical Reflection in Procurement and Policy It is vital that procurement processes, platform selection, and edtech deployment involve educators in weighing not just costs but also values: transparency, sovereignty, equity. As Watters (2021) demonstrates, critique of edtech myths - efficiency, scalability, data promise - must ground policy in ethical, teaching-centred priorities.

By flipping the question from What can the platform do? to What do we want learners to learn - and how can technology help?, institutions centre pedagogy as the guiding force. Technology becomes tool, not teacher. Procurement becomes deliberative, not declarative.

This orientation - where teaching defines tooling - drives not only healthier classroom environments, but more democratic institutions: ones where professionals shape not only practice, but also infrastructure, governance, and futures.

The pedagogical reversal proposed in this post - placing pedagogy before platform - is not an endpoint but an opening gesture. The landscape of digital education is vast and uneven, shaped by infrastructural decisions, ideological defaults, and powerful actors whose priorities do not always align with humanistic or democratic values.

Future posts in this series will chart key sites of contestation and possibility. We will begin by unearthing the hidden curriculum embedded in the very design of Learning Management Systems, drawing attention to how these tools inscribe assumptions about sequencing, authority, and learner passivity into the architecture of education. As Selwyn (2016) observes, “there is a politics to every click” - a reminder that even mundane platform features can carry deep pedagogical consequences.

The series will then turn to AI and the automation of assessment, interrogating how generative and evaluative technologies threaten to reduce complex human judgement to calculable outcomes. As Knox (2020) argues, such developments risk reconfiguring pedagogy around prediction and performance, rather than inquiry and relational learning.

We will also explore how digital policy - from procurement frameworks to institutional guidelines - often functions as a form of pedagogical governance. As Williamson (2017) contends, education is increasingly “steered by data,” with metrics and compliance eclipsing critical deliberation.

From here, we move to possibilities: what might it look like to reimagine infrastructure in ways that align with values of care, participation, and justice? Drawing on examples from open-source platforms and community-owned systems, we’ll ask how institutions can build alternatives that foreground transparency and user agency.

Finally, the series will culminate in a manifesto for critical digital pedagogy - a set of provocations and principles grounded in the recognition that education is not a product to be delivered, but a relationship to be nurtured. It is through reclaiming pedagogy as a democratic, ethical, and humanising practice that we can resist the deterministic futures imagined by platforms and propose more just, more dialogic alternatives.

As the terrain ahead will show, the struggle for critical digital pedagogy is not about rejecting technology, but about reasserting the values that ought to guide it.

• Ball, S.J. (2012) Performativity, commodification and commitment: An I-spy guide to the neoliberal university, British Journal of Educational Studies, 60(1), pp. 17–28. Available at https://doi.org/10.1080/00071005.2011.650940 (Accessed: 26 May 2025).
• Biesta, G.J.J. (2010) Good education in an age of measurement: Ethics, politics, democracy. 1st edn. Abingdon: Routledge. Available at https://doi.org/10.4324/9781315634319 (Accessed: 26 May 2025).
• Biesta, G.J.J. (2012) ‘Giving teaching back to education: Responding to the disappearance of the teacher’, Phenomenology & Practice, 6(2), pp. 35–49. Available at https://doi.org/10.29173/pandpr19860 (Accessed: 26 May 2025).
• Castañeda, L. and Selwyn, N. (2018) ‘More than tools? Making sense of the ongoing digitizations of higher education’, International Journal of Educational Technology in Higher Education, 15(22). Available at https://doi.org/10.1186/s41239-018-0109-y (Accessed: 26 May 2025).
• Costello, E. (2013) ’Opening up to open source: Looking at how Moodle was adopted in higher education’, Open Learning: The Journal of Open, Distance and e‑Learning, 28(3), pp. 187–200. https://doi.org/10.1080/02680513.2013.856289
• Knox, J. (2020) Artificial intelligence and education in China. [online] Learning, Media and Technology, 45(3), pp. 298–311. Available at https://doi.org/10.1080/17439884.2020.1754236 (Accessed: 3 June 2025).
• Macgilchrist, F. (2019). Cruel optimism in edtech: When the digital data practices of educational‑technology providers inadvertently hinder educational equity. Learning, Media and Technology, 44(1), pp.77–86. Available at https://doi.org/10.1080/17439884.2018.1556217 (Accessed: 3 June 2025).
• Macgilchrist, F. (2019). Cruel optimism in edtech: When the digital data practices of educational‑technology providers inadvertently hinder educational equity. Learning, Media and Technology, 44(1), pp.77–86. https://doi.org/10.1080/17439884.2018.1556217
• Macgilchrist, F., 2019. Cruel optimism in edtech: When the digital data practices of educational‑technology providers inadvertently hinder educational equity. Learning, Media and Technology, 44(1), pp.77–86. https://doi.org/10.1080/17439884.2018.1556217
• Quinn, J., Burtis, M.F. and Jhangiani, R.S. (2022) Toward a Critical Instructional Design. Hybrid Pedagogy Inc. Available at https://pressbooks.pub/criticalinstructionaldesign/ (Accessed: 4 June 2025)
• Selwyn, N. (2016). Is technology good for education? Cambridge: Polity Press. Available at https://ebookcentral-proquest-com.manchester.idm.oclc.org/lib/manchester/detail.action?docID=4547494
• Selwyn, N. (2022). Education and Technology: Key Issues and Debates. London: Bloomsbury Academic. Available at http://dx.doi.org/10.5040/9781350145573 (Accessed: 26 May 2025).
• Selwyn, N. and Jandrić, P. (2020). Postdigital Living in the Age of Covid-19: Unsettling What We See as Possible. Postdigital science and education, 2(3), pp.989–1005. https://doi.org/10.1007/s42438-020-00166-9
• Star, S.L., 1999. The ethnography of infrastructure. American Behavioral Scientist, 43(3), pp.377–391. https://doi.org/10.1177/00027649921955326
• Stommel, J., 2014. Critical digital pedagogy: a definition. Hybrid Pedagogy. Available at https://hybridpedagogy.org/critical-digital-pedagogy-definition/ [Accessed 4 Jun. 2025].
• Watters, A. (2021). Teaching Machines: The History of Personalized Learning. Cambridge, MA: MIT Press. https://doi.org/10.7551/mitpress/12262.001.0001 (Accessed: 26 May 2025).
• Williamson, B. (2017). Big Data in Education: The Digital Future of Learning, Policy and Practice. London: SAGE Publications. Available at https://ebookcentral.proquest.com/lib/manchester/detail.action?docID=4923811 (Accessed: 26 May 2025).