Educational Digital Sovereignty and EdTech Platform Capitalism: Rethinking Innovation, Data Governance and Artificial Intelligence in Public Education

1. Introduction

The digital transformation of education has become one of the most significant structural developments shaping contemporary societies. Over the last decade, and particularly since the COVID-19 pandemic, digital platforms, artificial intelligence (AI) systems, learning analytics, cloud infrastructures, and data-driven educational technologies have become deeply embedded within educational systems worldwide. These technologies have transformed teaching and learning practices, institutional management processes, communication networks, and policy-making mechanisms across all educational levels. As a result, digitalization is no longer a peripheral component of educational reform but a central element in the reconfiguration of educational governance and innovation.

However, the digital transformation of education cannot be understood merely as a technological or pedagogical phenomenon. It is also a political, economic, and social process closely connected to the expansion of digital capitalism and the growing influence of technology corporations in public institutions. While digital technologies are frequently presented as neutral tools capable of improving efficiency, personalization, and educational outcomes, critical scholarship has demonstrated that their implementation is embedded within broader power structures that shape how knowledge is produced, governed, and distributed (Williamson, 2017; Selwyn, 2019; Knox et al., 2020).

The rise of platform capitalism has fundamentally altered the ways in which economic value is generated in digital societies. As Srnicek (2018) argues, digital platforms operate as infrastructures that extract, process, and monetize data generated through everyday activities. Data have become a strategic resource for contemporary capitalism, enabling new forms of economic accumulation based on prediction, surveillance, and behavioral modification. Within this context, educational institutions have emerged as particularly valuable sites for data extraction because they continuously generate extensive information about students, teachers, families, learning processes, and institutional operations.

Large technology corporations such as Google, Microsoft, Amazon, and Meta have significantly expanded their presence within educational systems through the provision of cloud services, communication infrastructures, learning management systems, productivity software, and increasingly sophisticated AI tools. This expansion has transformed schools and universities into strategic environments for data collection and algorithmic experimentation. Educational activities, interactions, assessments, communication patterns, and learning trajectories are increasingly translated into quantifiable data that can be processed and analyzed through digital infrastructures controlled by private corporations.

This process has been described as the datafication of education, referring to the transformation of educational practices, relationships, and experiences into machine-readable data suitable for algorithmic analysis and prediction (Jarke & Breiter, 2019; Selwyn et al., 2021). Datafication is not merely a technical development but a profound epistemological transformation. It privileges measurable indicators, predictive models, and computational forms of knowledge while potentially marginalizing ethical, social, cultural, and democratic dimensions of education. Consequently, educational technologies do not simply support existing educational practices; they actively shape what counts as learning, achievement, participation, and success.

The COVID-19 pandemic accelerated these developments dramatically. During periods of school closure and emergency remote teaching, digital platforms became indispensable infrastructures for educational continuity. Governments, educational institutions, and teachers adopted platform-based solutions at unprecedented speed, frequently relying on services provided by major technology corporations. While these platforms enabled continuity of instruction under exceptional circumstances, research has shown that the pandemic also intensified processes of privatization, platform dependency, and corporate influence within public education (Williamson et al., 2020; Saura, 2020). What emerged during the pandemic was not simply a temporary technological response but the consolidation of longer-term transformations in educational governance.

These developments have generated growing concerns regarding technological dependency, surveillance, privacy, democratic accountability, and the concentration of digital power. Educational institutions increasingly rely on proprietary infrastructures that they neither control nor fully understand. Decisions regarding data management, algorithmic processes, interoperability standards, and technological development are often made by private actors whose priorities may not align with educational values or public interests. As a result, schools and universities risk becoming dependent on technological ecosystems governed by corporate logics rather than democratic principles.

From a critical perspective, these transformations reflect broader processes of platformization. Platformization refers to the penetration of digital platforms into social sectors traditionally organized through public institutions, resulting in the restructuring of governance mechanisms, professional practices, and social relations according to platform logics (Kerssens & van Dijck, 2021; Komljenovic et al., 2023). In education, platformization involves more than the adoption of digital tools. It entails a reconfiguration of institutional authority, pedagogical practices, data governance arrangements, and educational infrastructures. Educational platforms increasingly mediate communication, assessment, curriculum delivery, professional development, and decision-making processes, thereby influencing the fundamental conditions under which education takes place.

The growing influence of Big Tech corporations in education has also raised concerns regarding digital colonialism and technological sovereignty. Educational technologies developed primarily within the economic, cultural, and political contexts of the Global North are increasingly exported and adopted worldwide. These technologies frequently embed specific assumptions about knowledge, learning, innovation, and governance that may not correspond to local educational priorities or cultural contexts. Consequently, educational systems can become dependent on infrastructures, standards, and technological frameworks designed externally, limiting their capacity to determine their own educational futures (Couldry & Mejias, 2019; Kwet, 2025).

Within this context, the concept of educational digital sovereignty has emerged as a critical framework for analyzing the relationship between digital technologies, democracy, and public education. Digital sovereignty generally refers to the capacity of societies, institutions, and communities to exercise meaningful control over technological infrastructures, data, digital resources, and governance processes (Lemos et al., 2024). Applied to education, educational digital sovereignty concerns the ability of educational communities and public authorities to govern digital ecosystems according to democratic values, public interests, and educational objectives rather than corporate imperatives.

Educational digital sovereignty does not imply technological isolationism or opposition to innovation. Rather, it seeks to ensure that technological innovation remains accountable to democratic principles, public interests, and educational goals. It involves questions regarding ownership, governance, transparency, accountability, participation, and control over digital infrastructures and data. It also encompasses broader concerns related to social justice, cognitive diversity, epistemic pluralism, and the protection of educational institutions for the public good.

Against this background, this article critically examines the expansion of EdTech platform capitalism and explores the possibilities for constructing educational digital sovereignty as an alternative framework for educational innovation. Drawing upon a critical review of recent literature indexed in Web of Science (WoS) and Scopus, the study integrates perspectives from digital sociology, political economy, critical data studies, educational technology research, and platform studies.

The article pursues three main objectives. First, it analyzes the processes through which platform capitalism has become embedded within educational systems, emphasizing the role of datafication, platformization, and corporate governance. Second, it examines the principal risks associated with educational technological dependency, including surveillance, algorithmic governance, digital inequalities, and technological colonialism. Third, it proposes educational digital sovereignty as a multidimensional framework capable of supporting more democratic, equitable, and publicly accountable forms of educational innovation.

The argument developed throughout the article is that the current digital transformation of education should not be interpreted as a neutral process of modernization. Rather, it represents a struggle over the governance of educational infrastructures, data, knowledge, and democratic institutions. Consequently, debates about educational technology are inseparable from broader questions concerning power, sovereignty, democracy, and the future of public education in increasingly digital societies.

2. Digital Capitalism, Platformization and Educational Datafication

The digital transformation of education is inseparable from the broader restructuring of contemporary capitalism. Over the last two decades, digital technologies have not merely introduced new tools into educational environments; they have contributed to the emergence of new economic models, governance arrangements, and forms of social organization. Understanding current developments in educational technology therefore requires situating them within the wider context of digital capitalism, where data, algorithms, and digital infrastructures have become central mechanisms of economic accumulation and political power.

The concept of digital capitalism refers to the increasing reliance of contemporary economies on digital technologies, data extraction, computational infrastructures, and networked platforms as sources of value creation and capital accumulation. Unlike earlier industrial models, digital capitalism operates through the continuous collection, processing, and monetization of information generated through social, economic, and cultural activities. Data have become a strategic asset capable of generating economic value, predictive knowledge, and forms of behavioral influence across multiple sectors, including education, healthcare, communication, finance, and public administration.

Within this context, digital platforms have emerged as the dominant organizational form of contemporary capitalism. According to Srnicek (2018), platforms function as digital infrastructures that facilitate interactions among users while simultaneously collecting vast quantities of data generated through those interactions. Their economic power derives not only from the services they provide but also from their capacity to centralize information flows, establish standards, control access to digital ecosystems, and create network effects that reinforce market concentration.

This platform-based model has enabled a small number of technology corporations to acquire unprecedented influence over social and institutional life. Companies such as Google, Microsoft, Amazon, Meta, and Apple increasingly operate not simply as service providers but as infrastructural actors whose technologies underpin communication systems, information networks, administrative processes, and educational environments. Their growing dominance has contributed to what several scholars describe as a new phase of digital monopoly capitalism characterized by the concentration of technological resources, computational capacity, and data ownership in the hands of a limited number of global actors (Leclercq & Bertin, 2024).

The educational sector has become a particularly attractive field for platform expansion. Educational institutions generate vast amounts of information regarding learning processes, academic performance, communication patterns, behavioral interactions, and institutional management. From the perspective of digital capitalism, these data represent valuable resources that can be analyzed, aggregated, and transformed into economic and strategic assets. Consequently, schools and universities have become increasingly integrated into platform ecosystems designed and controlled by private corporations.

The incorporation of digital platforms into education has given rise to what scholars describe as the platformization of education. Platformization refers to the process through which educational activities, institutional operations, and pedagogical practices become mediated by digital platforms that increasingly shape the conditions under which education is organized and experienced (Kerssens & van Dijck, 2021; Komljenovic et al., 2023). This transformation extends far beyond the adoption of technological tools. It involves the reconfiguration of educational governance, communication structures, assessment systems, professional practices, and knowledge production processes according to platform logics.

Educational platforms increasingly function as infrastructures through which teaching, learning, assessment, administration, and communication are coordinated. Learning management systems, cloud services, videoconferencing platforms, productivity applications, and AI-powered educational tools have become embedded in everyday educational activities. As a result, educational institutions are progressively incorporated into broader digital ecosystems governed by private actors whose operational logics are often shaped by commercial objectives rather than educational values.

The platformization of education is closely linked to the process of educational datafication. Datafication refers to the transformation of educational activities, interactions, and experiences into quantifiable digital data that can be stored, analyzed, and utilized for decision-making purposes (Jarke & Breiter, 2019; Selwyn et al., 2021). Through datafication, learning is increasingly represented through metrics, indicators, dashboards, predictive models, and algorithmic classifications that seek to render educational processes visible, measurable, and manageable.

This transformation has important epistemological implications. Datafication promotes a particular understanding of education in which complex social, cognitive, and relational processes become translated into computationally manageable variables. Educational success, engagement, participation, and achievement are increasingly defined through measurable indicators rather than through broader pedagogical, ethical, or democratic considerations. Consequently, digital technologies do not simply record educational activities; they actively shape how educational realities are understood and governed.

Several scholars have argued that datafication contributes to the emergence of new forms of algorithmic governance within education. Algorithmic governance refers to the growing use of computational systems to monitor, classify, predict, and influence educational processes and behaviors. Learning analytics, predictive assessment systems, recommendation engines, adaptive learning technologies, and AI-driven educational platforms increasingly participate in decision-making processes that were traditionally governed by professional judgment and pedagogical expertise (Knox et al., 2020; Williamson et al., 2023).

These developments are closely connected to broader transformations associated with surveillance capitalism. Zuboff (2019) argues that contemporary digital corporations generate profits through the extraction and analysis of behavioral data, which are subsequently used to predict and influence future actions. Within educational contexts, this logic manifests through the continuous collection of information regarding students’ learning behaviors, online activities, communication patterns, emotional responses, and academic trajectories. Educational data are not merely used to improve learning processes; they increasingly become resources within wider circuits of economic valorization and behavioral prediction.

The growing integration of platform infrastructures into education also alters traditional relationships between public institutions and private actors. Historically, schools and universities exercised substantial control over educational resources, curricula, assessment practices, and institutional governance. However, platformization introduces new intermediaries that increasingly mediate these functions. Educational institutions become dependent upon proprietary technologies whose design, maintenance, and development remain largely outside democratic control. This shift raises important questions concerning accountability, transparency, and institutional autonomy.

Moreover, platformization contributes to the expansion of corporate influence over educational agendas and policy development. As Williamson (2017) notes, technology corporations increasingly position themselves as providers of educational solutions capable of addressing challenges related to efficiency, quality, personalization, and innovation. Through partnerships with governments, philanthropic initiatives, certification programs, research funding, and professional development networks, technology companies actively participate in shaping educational discourses and policy priorities. This phenomenon reflects a broader trend in which technological innovation becomes closely intertwined with governance processes and public sector reform.

The expansion of artificial intelligence further intensifies these dynamics. AI systems increasingly depend upon large-scale data infrastructures, computational resources, and proprietary models controlled by a limited number of corporations. As educational institutions adopt AI-powered tools for assessment, feedback, tutoring, content generation, and administrative decision-making, they become further integrated into platform ecosystems characterized by asymmetrical distributions of technological power. Consequently, debates surrounding AI in education cannot be separated from broader questions concerning data ownership, infrastructure control, democratic governance, and digital sovereignty.

From a critical political economy perspective, educational platformization should therefore be understood not as a neutral process of technological modernization but as a restructuring of power relations within education. Digital platforms function simultaneously as technological infrastructures, economic actors, governance mechanisms, and epistemological frameworks. They influence not only how education is delivered but also how educational problems are defined, how solutions are imagined, and how educational futures are governed.

For these reasons, analyzing the relationship between digital capitalism, platformization, and educational datafication is essential for understanding the contemporary transformation of education. These processes are reshaping the governance of educational systems, redistributing authority among public and private actors, and redefining the conditions under which educational innovation occurs. The central challenge is therefore not whether digital technologies should be used in education, but rather who controls these technologies, whose interests they serve, and under what democratic conditions they are developed, implemented, and governed.

3. The Expansion of Big Tech in Education: Corporate Power, Dependency and the Reconfiguration of Educational Governance

The increasing integration of digital technologies into educational systems has been accompanied by the growing presence of large technology corporations as central actors in educational governance. Over the past decade, companies such as Google, Microsoft, Amazon, Meta, and, more recently, AI developers including OpenAI and Anthropic, have expanded their influence far beyond the provision of technological services. Through digital infrastructures, cloud computing, educational platforms, artificial intelligence systems, certification programs, and strategic partnerships with public institutions, these corporations have become deeply embedded in the everyday functioning of schools and universities.

This transformation reflects a broader shift in the governance of education. Historically, educational systems were primarily organized through public institutions operating under democratic accountability mechanisms. Although private actors have always played some role in educational provision, the expansion of digital platforms has enabled technology corporations to occupy increasingly strategic positions within educational ecosystems. As a result, educational governance is progressively being reconfigured through relationships between public institutions and private technological infrastructures that shape communication, administration, teaching, assessment, and decision-making processes.

The growing influence of Big Tech corporations in education cannot be explained solely by technological innovation. Rather, it is closely connected to broader political and economic transformations associated with neoliberal governance, public sector restructuring, and the marketization of educational services. Since the early 2000s, governments across many countries have promoted digital modernization agendas aimed at increasing efficiency, accountability, and competitiveness within educational systems. Technology corporations have successfully positioned themselves as indispensable partners in these transformation processes, presenting their products and services as solutions to complex educational challenges.

The global financial crisis of 2008 created favorable conditions for this expansion. As public budgets contracted and educational institutions faced increasing pressure to reduce costs while expanding digital provision, technology companies promoted scalable online solutions as cost-effective alternatives to traditional infrastructures. Massive open online courses (MOOCs), cloud-based services, and platform-mediated learning environments were increasingly presented as innovative responses to financial constraints affecting public education.

The COVID-19 pandemic accelerated these trends dramatically. During periods of school closure, digital platforms became essential infrastructures for maintaining educational continuity. Governments and educational institutions rapidly adopted corporate platforms to support remote teaching, communication, and assessment. While these technologies undoubtedly played a significant role in sustaining educational activities during the crisis, their widespread adoption also reinforced long-term dependencies on proprietary digital ecosystems (Williamson et al., 2020). What emerged during the pandemic was not merely a temporary emergency response but a substantial consolidation of corporate influence within educational systems worldwide.

The expansion of Big Tech in education has been facilitated by strategies that extend beyond the provision of technological tools. One important mechanism involves the construction of educational legitimacy. Technology corporations increasingly invest in teacher certification programs, professional development initiatives, educational communities, and research partnerships designed to position their platforms as pedagogically valuable and professionally desirable (Zomer & Kerssens, 2026). Through these initiatives, corporations cultivate networks of educators who become both users and promoters of their technological ecosystems.

Educational legitimacy is further reinforced through narratives of innovation, modernization, and digital transformation. Corporate discourse frequently presents technological adoption as a necessary condition for educational progress, competitiveness, and future readiness. Within these narratives, digital technologies are portrayed as neutral instruments capable of improving learning outcomes, enhancing personalization, and preparing students for participation in knowledge-based economies. However, critical scholars have argued that such narratives often obscure the political and economic interests underlying technological adoption while marginalizing alternative visions of educational development (Williamson, 2017; Selwyn, 2019).

This process is closely related to what Saura (2020) describes as digital philanthrocapitalism. Technology corporations frequently frame their educational initiatives as contributions to social progress, equity, and innovation. Through philanthropic foundations, educational grants, public-private partnerships, and corporate social responsibility programs, they position themselves as benevolent actors committed to improving educational opportunities. Yet these initiatives frequently generate strategic advantages that strengthen corporate influence, expand market penetration, enhance brand legitimacy, and facilitate access to valuable educational data and institutional networks.

The role of philanthrocapitalism illustrates how contemporary educational governance increasingly operates through hybrid arrangements that blur traditional distinctions between public and private interests. Corporate actors are no longer external providers of educational products; they actively participate in shaping educational agendas, policy discussions, research priorities, and institutional practices. Consequently, educational governance is becoming increasingly dependent upon actors whose accountability mechanisms are primarily oriented toward shareholders, investors, and corporate objectives rather than democratic public interests

The growing influence of Big Tech is also connected to the financialization of educational technology. Recent research demonstrates that the expansion of EdTech industries is increasingly driven by venture capital, private equity investment, and financial speculation (Komljenovic et al., 2023; Komljenovic & Williamson, 2025). Educational technologies are no longer viewed simply as pedagogical tools; they are increasingly treated as assets capable of generating future revenues through subscription models, data extraction, user acquisition, and platform expansion.

From this perspective, educational innovation becomes integrated into broader processes of assetization. Educational platforms derive value not only from the services they provide but also from their capacity to capture users, accumulate data, establish infrastructural dependencies, and create long-term market opportunities. Students, teachers, educational institutions, and learning processes increasingly become incorporated into digital ecosystems designed to generate economic value through continuous engagement and data production.

The consequences of these developments extend beyond economic considerations. As educational institutions become dependent upon proprietary digital infrastructures, they experience significant reductions in technological autonomy. Dependence emerges at multiple levels. Technical dependence arises when schools and universities rely on corporate platforms for communication, storage, assessment, administration, and learning management. Economic dependence develops through subscription models, licensing agreements, and technological upgrades that create ongoing financial commitments. Epistemic dependence occurs when educational practices become increasingly shaped by technological architectures designed according to assumptions embedded within corporate systems.

This multidimensional dependency has important implications for educational sovereignty. When core educational functions depend upon infrastructures controlled by private actors, educational institutions lose significant capacity to determine how technologies operate, how data are managed, and how digital environments evolve. Decisions regarding interoperability, privacy, algorithmic design, platform governance, and technological development are frequently made outside democratic oversight and beyond the influence of educational communities.

Furthermore, platform dependency generates powerful lock-in effects. Students and educators become accustomed to specific technological ecosystems through everyday use, making transitions to alternative platforms increasingly difficult. Skills, routines, communication practices, and institutional workflows become aligned with particular corporate infrastructures, reinforcing long-term dependence. As a result, platform adoption frequently establishes durable relationships that extend far beyond initial implementation decisions.

The emergence of artificial intelligence intensifies these dynamics. Contemporary AI systems require extensive computational infrastructures, large-scale datasets, and significant financial resources that are concentrated within a small number of global corporations. As educational institutions adopt AI-powered tools for tutoring, assessment, content generation, analytics, and administrative decision-making, they become further integrated into technological ecosystems characterized by asymmetrical distributions of power and resources. This concentration raises important concerns regarding transparency, accountability, autonomy, and democratic control.

From a political economy perspective, the expansion of Big Tech in education represents a broader transformation in the governance of public institutions. Technology corporations increasingly function not merely as suppliers of digital services but as infrastructural actors capable of shaping educational practices, influencing policy agendas, and mediating access to knowledge. Their growing presence contributes to the emergence of new governance arrangements in which educational authority is distributed across networks of public institutions, private corporations, digital infrastructures, and algorithmic systems.

These developments challenge conventional understandings of educational innovation. Rather than representing a neutral process of technological modernization, the expansion of Big Tech reflects a reconfiguration of power relations within education. Innovation becomes intertwined with questions of ownership, governance, accountability, and democratic participation. Consequently, debates about educational technology must address not only the effectiveness of digital tools but also the broader political and institutional structures through which technological transformation is organized.

Understanding these dynamics is essential for evaluating the future of educational systems in increasingly digital societies. The central issue is not whether digital technologies should be integrated into education, but whether educational institutions will retain the capacity to govern these technologies according to democratic principles and public interests. This question becomes particularly urgent in light of the growing dependence of educational systems on corporate infrastructures and the increasing concentration of technological power in the hands of a small number of global actors.

4. Risks of Educational Technological Dependence

The increasing integration of digital platforms into educational systems has generated significant opportunities for communication, resource sharing, administrative efficiency, and pedagogical innovation. However, these developments have also produced new forms of dependency that extend beyond technical considerations. Educational institutions are becoming progressively embedded within digital ecosystems governed by corporate actors whose interests, governance structures, and economic objectives often differ from those traditionally associated with public education.

Technological dependence in education should therefore be understood as a multidimensional phenomenon encompassing surveillance practices, algorithmic governance, infrastructural lock-in, economic dependency, and epistemic influence. These dynamics acquire particular relevance within a context characterized by the growing concentration of digital power among a limited number of global technology corporations. As educational systems increasingly rely on privately controlled infrastructures, concerns emerge regarding democratic accountability, institutional autonomy, social justice, and the capacity of educational communities to govern their own technological futures.

This section examines three interconnected risks associated with educational technological dependence: educational surveillance and data extraction, algorithmic governance and the erosion of pedagogical autonomy, and the reinforcement of digital inequalities through technological colonialism and cognitive dependency.

4.1. Educational Surveillance and Data Extraction

One of the most significant consequences of educational platformization is the expansion of digital surveillance within educational environments. Contemporary educational platforms continuously collect, store, process, and analyze vast quantities of information regarding students, teachers, and institutional activities. These data include attendance records, assessment results, communication patterns, learning behaviors, engagement metrics, navigation histories, time spent on tasks, and increasingly sophisticated forms of behavioral and emotional data.

While platform providers frequently justify data collection in terms of personalization, efficiency, and educational improvement, critical scholarship has highlighted the emergence of new surveillance infrastructures embedded within everyday educational practices (Parcerisa et al., 2022; Raffaghelli et al., 2024). Educational activities that were previously ephemeral or confined to specific institutional contexts are increasingly transformed into permanent digital records subject to continuous monitoring and analysis.

The implications of this transformation are particularly significant because education occupies a unique position within democratic societies. Schools and universities are not merely service providers; they are institutions responsible for intellectual development, critical citizenship, and social participation. The expansion of surveillance practices within educational environments therefore raises questions that extend beyond privacy and data protection. It concerns the conditions under which learning takes place and the broader relationship between education, autonomy, and democratic life.

The growing datafication of educational activities has created unprecedented opportunities for the extraction and commodification of educational data. Information generated through learning processes increasingly functions as a valuable economic resource within digital markets. Educational data can be used to develop predictive models, improve platform services, train artificial intelligence systems, generate commercial insights, and strengthen competitive advantages within technology sectors.

This process reflects broader dynamics associated with surveillance capitalism (Zuboff, 2019). From this perspective, educational data are not collected solely to support pedagogical objectives. They also contribute to systems of economic accumulation based on the continuous extraction and analysis of human behavior. Students and teachers become producers of data that can be transformed into strategic assets within broader digital economies.

The situation is particularly sensitive in relation to children and young people. Educational institutions increasingly rely on digital tools that collect information from minors who often have limited understanding of how their data are used, stored, shared, or monetized. Moreover, educational participation frequently requires engagement with digital platforms, reducing the possibility of meaningful consent and creating asymmetrical relationships between users and technology providers.

The central issue is therefore not only who owns educational data but also who possesses the capacity to transform those data into systems of knowledge, prediction, and governance. Data extraction increasingly enables forms of intervention that extend beyond observation, allowing digital systems to influence behaviors, shape choices, and structure educational experiences. Consequently, educational surveillance should be understood not merely as a technical practice but as a political issue closely connected to questions of power, autonomy, and democratic accountability.

4.2. Algorithmic Governance and the Erosion of Pedagogical Autonomy

A second major risk associated with educational technological dependence concerns the growing role of algorithmic systems in educational decision-making. Artificial intelligence, learning analytics, predictive technologies, recommendation systems, and automated assessment tools are increasingly incorporated into educational environments. These technologies are frequently promoted as mechanisms for improving efficiency, personalizing learning, optimizing resource allocation, and supporting evidence-based decision-making.

The expansion of algorithmic systems reflects a broader shift toward forms of governance based on data-driven prediction and automated decision-making. In educational contexts, algorithms increasingly participate in activities such as performance evaluation, student monitoring, early-warning systems, curriculum recommendations, admissions procedures, and institutional planning. While these systems may provide valuable forms of support, they also redistribute authority within educational processes.

Traditionally, educational decisions have relied heavily upon professional judgment, contextual understanding, and pedagogical expertise. Teachers, school leaders, and educational communities have exercised discretion in evaluating students, interpreting learning needs, and designing educational interventions. Algorithmic systems introduce alternative forms of authority based on computational models that often operate according to criteria inaccessible to those affected by their decisions.

This development raises concerns regarding transparency and accountability. Many contemporary AI systems function as opaque “black boxes” whose internal operations remain difficult to understand, evaluate, or challenge (Giró-Gracia & Sancho-Gil, 2022). Educational stakeholders frequently lack access to information regarding how algorithmic recommendations are generated, what variables are prioritized, or how predictive outcomes are calculated. As a result, significant educational decisions may increasingly depend upon systems that cannot be meaningfully scrutinized through democratic processes.

The expansion of algorithmic governance also affects pedagogical autonomy. As educational institutions adopt data-driven management systems, there is a risk that professional judgment becomes subordinated to metrics, indicators, and algorithmic recommendations. Teachers may experience pressure to align their practices with data outputs generated by digital systems, even when those outputs fail to capture the complexity of educational realities.

Moreover, algorithmic systems are not neutral technologies. They are shaped by the assumptions, values, objectives, and datasets embedded within their design processes. Consequently, they may reproduce or amplify existing social inequalities and forms of discrimination. Numerous studies have demonstrated that algorithmic systems can inherit biases related to socioeconomic status, race, ethnicity, gender, language, disability, and geographical location when such inequalities are reflected within training data or decision-making frameworks.

In an educational context, these biases may have profound consequences. Automated classification systems can influence access to educational opportunities, shape expectations regarding student performance, and reinforce patterns of exclusion affecting historically marginalized groups. The risk is not merely that algorithms make mistakes but that they institutionalize particular forms of knowledge and authority while obscuring the political choices embedded within their operations.

The increasing reliance on algorithmic governance therefore raises a fundamental question: who governs educational technologies, and according to what values? The challenge is not whether artificial intelligence can contribute to educational improvement but whether democratic societies retain the capacity to determine the purpose, limits, and conditions under which such technologies are deployed.

4.3. Digital Inequalities, Technological Colonialism and Cognitive Dependency

A third major risk associated with educational technological dependence concerns the reproduction and intensification of social inequalities. Although digital technologies are often presented as instruments of inclusion and democratization, research consistently demonstrates that their benefits are unevenly distributed across different social groups and geographical contexts.

Digital inequalities extend beyond access to devices and internet connectivity. Contemporary scholarship increasingly distinguishes between multiple dimensions of digital inequality, including access gaps, differences in digital skills, disparities in patterns of use, and inequalities in the outcomes generated through technological engagement. These dimensions interact with existing social structures, frequently reinforcing rather than reducing pre-existing forms of disadvantage (Jacovkis & Tarabini, 2021).

Educational platformization can amplify these dynamics. Students from socially advantaged backgrounds generally possess greater access to technological resources, stronger digital literacy skills, and more supportive learning environments. Consequently, they are often better positioned to benefit from digital educational opportunities. Conversely, students facing socioeconomic disadvantages frequently encounter barriers related to connectivity, digital competencies, institutional support, and access to alternative learning resources.

However, the implications of technological dependence extend beyond social inequality. The global expansion of educational platforms has also generated growing concerns regarding technological colonialism and digital dependency. Most dominant educational technologies are designed, developed, and controlled by corporations headquartered in a small number of countries within the Global North. These platforms frequently embody particular assumptions regarding knowledge, learning, assessment, innovation, and governance that reflect specific cultural, political, and economic contexts.

As educational institutions worldwide adopt these technologies, they may become dependent on infrastructures, standards, and epistemological frameworks developed elsewhere. This dependence can reduce local capacity to define educational priorities, design alternative technological models, and preserve cultural and linguistic diversity. Consequently, educational technologies increasingly function not only as technical infrastructures but also as vehicles for the global circulation of particular forms of knowledge and social organization.

Scholars have described these dynamics as manifestations of digital colonialism and data colonialism (Couldry & Mejias, 2019; Kwet, 2025). Unlike historical forms of colonial domination based primarily on territorial control, contemporary technological colonialism operates through the governance of digital infrastructures, information flows, and data resources. Educational institutions contribute valuable information, labor, and participation to global technological ecosystems while possessing limited influence over how these systems are governed.

These processes can also generate forms of cognitive dependency. Educational platforms increasingly mediate access to knowledge, structure learning experiences, organize information flows, and influence how educational problems are conceptualized. Over time, dependence on externally designed technological systems may limit the capacity of educational communities to develop alternative pedagogical approaches, technological infrastructures, and epistemological frameworks.

The challenge, therefore, extends beyond questions of technological access or institutional efficiency. It concerns the capacity of societies to exercise meaningful control over the infrastructures through which knowledge is produced, circulated, and governed. Educational technological dependence ultimately raises questions about democratic self-determination, cultural autonomy, and the ability of communities to shape their own educational futures.

Taken together, educational surveillance, algorithmic governance, and technological colonialism reveal that platformization is not simply a process of technological modernization. It represents a profound reconfiguration of power relations within education. Understanding these risks is essential for developing alternative approaches capable of protecting democratic governance, pedagogical autonomy, social justice, and public control over educational infrastructures. It is within this context that the concept of educational digital sovereignty emerges as a critical framework for rethinking the relationship between technology, innovation, and democracy in education.

Education ceases to be an emancipatory project and becomes a laboratory of social engineering. aimed at producing competent consumers, obedient users, and flexible workers for the platform economy. On behalf of. modernization, the school is stripped of its transformative potential and its mission is rewritten under the imperatives of profitability and control. What is advertised as digital emancipation is merely a sophisticated form of. subjection: a colonization of the pedagogical imagination that empties the act of educating of its political content.

5. Educational Digital Sovereignty: Conceptual Foundations and Strategic Dimensions

The risks associated with educational platformization, technological dependency, algorithmic governance, and digital colonialism have stimulated growing interest in the concept of digital sovereignty across academic, political, and policy debates. Originally developed in discussions concerning cybersecurity, data governance, and technological autonomy, the notion of digital sovereignty has increasingly been extended to broader questions regarding democratic control over digital infrastructures, information systems, and technological development (Lemos et al., 2024; Fratini et al., 2024).

Within educational contexts, digital sovereignty represents a critical framework for rethinking the relationship between technology, democracy, and public education. Rather than focusing exclusively on technological innovation or digital adoption, educational digital sovereignty emphasizes the capacity of educational communities and public institutions to govern technological ecosystems according to collective interests, democratic principles, and educational values.

Educational digital sovereignty does not imply technological isolation, technological nationalism, or rejection of innovation. Nor does it advocate the abandonment of digital technologies. Instead, it seeks to ensure that digital transformation remains accountable to public interests and democratic governance. The central question is not whether educational institutions should use digital technologies, but whether they retain meaningful control over the infrastructures, data, algorithms, and governance arrangements through which educational activities are increasingly organized.

From this perspective, educational digital sovereignty may be defined as the collective capacity of educational communities, public institutions, and democratic societies to determine how digital technologies are designed, adopted, governed, and utilized within educational systems. It involves both technological autonomy and democratic self-determination, encompassing issues of infrastructure ownership, data governance, algorithmic accountability, cognitive diversity, and participatory decision-making.

Building upon recent scholarship on digital sovereignty, digital commons, educational governance, and critical technology studies, this article proposes five interconnected dimensions that constitute the foundation of educational digital sovereignty: public digital infrastructures, open-source technologies, democratic data governance, cognitive justice and epistemic decolonization, and community participation.

5.1. Public Digital Infrastructures

The first and most fundamental dimension of educational digital sovereignty concerns the development of public digital infrastructures. Contemporary educational systems increasingly depend upon technological infrastructures controlled by private corporations, including cloud services, communication platforms, storage systems, learning management environments, and artificial intelligence applications. This dependency limits institutional autonomy and reduces the capacity of public authorities to govern educational technologies according to democratic priorities.

Digital infrastructures should be understood as strategic public resources comparable to transportation systems, energy networks, or public communication infrastructures. They constitute the material foundations upon which educational activities increasingly depend. Consequently, questions concerning ownership, governance, and accessibility become critical political concerns rather than merely technical issues.

Recent research has demonstrated that educational platformization has transferred essential functions of communication, administration, teaching, assessment, and institutional management to corporate actors (Nichols & Dixon-Román, 2024; Moreno-González et al., 2026). This transfer creates structural vulnerabilities because educational institutions become dependent upon external providers for functions that are increasingly essential to their operation.

Educational digital sovereignty therefore requires the development of publicly governed digital infrastructures capable of supporting educational activities while ensuring transparency, interoperability, security, and democratic accountability. These infrastructures may include public cloud services, educational data repositories, open learning environments, publicly managed communication systems, and federated digital ecosystems designed according to principles of public governance.

Experiences such as Germany’s HPI Schul-Cloud demonstrate that alternative models are both technically feasible and politically viable (Meinel et al., 2023). Such initiatives illustrate how digital infrastructures can be developed within public frameworks that prioritize educational objectives, privacy protection, and democratic oversight rather than commercial interests.

More broadly, the development of public digital infrastructures represents a strategic investment in educational autonomy. By reducing dependence on proprietary ecosystems, educational institutions can strengthen their capacity to determine technological priorities, protect public values, and ensure that digital transformation remains aligned with democratic objectives.

5.2. Open-Source Technologies and Technological Autonomy

A second pillar of educational digital sovereignty is the adoption and development of open-source technologies. Open-source software provides access to source code, enabling users to examine, modify, adapt, and redistribute technological tools according to local needs and priorities. This openness contrasts sharply with proprietary systems whose internal operations remain inaccessible to educational communities.

The significance of open-source technologies extends beyond economic considerations. While reducing licensing costs and limiting vendor lock-in are important benefits, open-source ecosystems also contribute to transparency, innovation, technological literacy, and institutional autonomy (Schubert & Annen, 2024; UNESCO, 2025).

Educational institutions that rely exclusively on proprietary technologies often become dependent on external providers for maintenance, updates, security, interoperability, and future development. By contrast, open-source ecosystems foster local capacities for technological adaptation and collective innovation. Universities, schools, public administrations, and civil society organizations can collaborate in developing technologies that respond to specific educational needs rather than adapting educational practices to the requirements of commercial platforms.

Open-source technologies also facilitate public scrutiny and democratic accountability. Because source code can be independently audited, educational communities are better positioned to identify vulnerabilities, algorithmic biases, privacy risks, and governance issues. This transparency becomes particularly important in contexts where artificial intelligence systems increasingly influence educational decisions and institutional processes.

Furthermore, open-source ecosystems contribute to the creation of digital commons. Knowledge, software, and technological innovations become shared resources that can be collectively improved and adapted rather than proprietary assets controlled by individual corporations. Such collaborative approaches align closely with the democratic principles underpinning educational digital sovereignty.

Technological autonomy should therefore be understood not merely as technical independence but as the capacity to shape technological development according to collective educational goals. Open-source technologies constitute an essential mechanism for achieving this objective.

5.3. Democratic Data Governance

Data have become one of the most valuable strategic resources in contemporary societies. Within educational systems, processes of datafication have generated vast quantities of information concerning students, teachers, institutions, learning trajectories, and educational practices. As discussed in previous sections, these developments create opportunities for educational improvement but also generate significant risks related to surveillance, commodification, and loss of institutional control.

Educational digital sovereignty requires a fundamental rethinking of how educational data are governed. Rather than treating data as assets available for extraction and commercialization, democratic approaches conceptualize educational data as collective resources whose use must be guided by public values, transparency, and accountability.

Democratic data governance involves ensuring that educational communities retain meaningful control over the collection, storage, processing, and use of educational information. Such governance frameworks should include clear mechanisms for public oversight, independent auditing, algorithmic transparency, citizen participation, and legal protections against misuse or commercialization.

The principle of data sovereignty implies that educational institutions and communities possess the authority to determine how data generated through educational activities are managed and for what purposes they may be used (Rana & Azeez, 2025). This principle challenges business models based on the extraction and monetization of educational information while promoting alternative governance arrangements oriented toward public benefit.

Democratic data governance also requires transparency regarding algorithmic systems that rely on educational data. Educational stakeholders should be able to understand how data are transformed into recommendations, classifications, predictions, and decisions. Without such transparency, algorithmic governance risks undermining democratic accountability and weakening public trust.

Ultimately, educational data should serve educational purposes rather than commercial interests. Democratic governance seeks to ensure that the benefits generated through data-driven innovation contribute to educational improvement, social inclusion, and public knowledge rather than primarily supporting private accumulation.

5.4. Cognitive Justice and the Decolonization of Digital Knowledge

Technological sovereignty cannot be reduced to infrastructure, software, or data governance alone. Educational digital sovereignty also involves questions concerning knowledge production, epistemological diversity, and cultural autonomy. Contemporary digital technologies are not neutral tools; they embody particular assumptions regarding knowledge, learning, communication, and social organization.

Most educational technologies currently used worldwide are designed within specific cultural, economic, and linguistic contexts, predominantly located in the Global North. Consequently, these technologies frequently reproduce dominant epistemological frameworks while marginalizing alternative forms of knowledge, local traditions, indigenous perspectives, and non-hegemonic educational practices.

This phenomenon has been described as technological colonialism and digital colonialism (Couldry & Mejias, 2019; Aparici-Marino et al., 2024). Digital technologies increasingly influence not only how people access information but also how knowledge is categorized, validated, circulated, and prioritized. Algorithms, recommendation systems, educational platforms, and AI models participate in shaping what becomes visible, relevant, and legitimate within digital learning environments.

Educational digital sovereignty therefore requires a commitment to cognitive justice. Cognitive justice refers to the recognition that multiple knowledge systems possess legitimacy and that diverse epistemological traditions should be able to coexist and contribute to educational processes. It challenges the assumption that technological innovation necessarily entails cultural homogenization or epistemological standardization.

From this perspective, educational institutions should promote the development of open educational resources, multilingual digital environments, locally developed technologies, and community-based knowledge networks. Educational technologies should support cultural diversity rather than erode it. Likewise, digital innovation should be evaluated not only according to technical efficiency but also according to its capacity to foster pluralism, inclusion, and epistemic diversity.

Decolonizing digital knowledge involves creating conditions under which communities can participate actively in shaping the technological systems that mediate learning, communication, and knowledge production. Educational sovereignty therefore includes the right to imagine and construct alternative technological futures rooted in local contexts and democratic aspirations.

5.5. Community Participation and Democratic Governance

The final dimension of educational digital sovereignty concerns democratic participation. Decisions regarding technological adoption, platform selection, artificial intelligence deployment, and data governance are often concentrated in governmental agencies, corporate organizations, or technical experts. While expertise remains important, educational digital sovereignty requires broader forms of participation involving teachers, students, families, researchers, and civil society organizations.

Digital transformation should not be understood as a purely technical process. It is fundamentally a political process involving choices about values, priorities, governance arrangements, and social objectives. Consequently, those affected by technological decisions should possess meaningful opportunities to participate in shaping them.

Participatory governance contributes to educational digital sovereignty in several ways. First, it enhances democratic legitimacy by ensuring that technological decisions reflect collective interests rather than exclusively institutional or commercial priorities. Second, it incorporates situated knowledge and practical experience into decision-making processes, improving the relevance and effectiveness of technological initiatives. Third, it promotes critical digital literacy by encouraging educational communities to engage actively with questions concerning technology, power, privacy, and governance.

Research has demonstrated that participatory approaches can strengthen institutional trust, facilitate technological adoption, and support more equitable forms of innovation (Erlangga et al., 2026). Moreover, participation enables educational communities to develop the capacities necessary for exercising democratic control over increasingly complex technological systems.

Educational digital sovereignty therefore requires moving beyond models of technological governance based solely on expert authority or corporate influence. Instead, it calls for collaborative governance arrangements in which diverse stakeholders share responsibility for shaping educational futures.

Taken together, these five dimensions provide a comprehensive framework for understanding educational digital sovereignty as both a democratic project and a strategy for educational innovation. Public digital infrastructures, open-source technologies, democratic data governance, cognitive justice, and community participation are mutually reinforcing components of an alternative model of digital transformation. Rather than rejecting technological innovation, educational digital sovereignty seeks to align innovation with democratic values, social justice, and the public mission of education. In this sense, it offers a pathway toward more equitable, accountable, and sustainable forms of educational development in the digital age.

6. Cooperative Artificial Intelligence and Democratic Alternatives

The rapid expansion of artificial intelligence (AI) constitutes one of the most significant technological transformations currently affecting educational systems. Generative AI models, large language models, learning analytics platforms, automated assessment systems, and predictive algorithms are increasingly integrated into teaching, learning, administration, and educational governance. These developments have generated considerable expectations regarding the potential of AI to improve educational efficiency, personalize learning experiences, support teachers, and expand access to knowledge.

At the same time, however, the growing incorporation of AI into education raises fundamental questions concerning power, governance, accountability, and democratic control. Contemporary AI infrastructures are characterized by a high degree of concentration. The computational resources, data repositories, cloud infrastructures, and technical expertise required to develop advanced AI systems are largely controlled by a small number of global technology corporations. As a result, educational institutions increasingly depend upon technological ecosystems whose design, governance, and strategic priorities remain outside public control.

This concentration of technological power reinforces broader dynamics associated with platform capitalism and digital dependency. The development of contemporary AI systems requires access to massive datasets, high-performance computing infrastructures, and substantial financial investment. Consequently, the production of AI increasingly becomes concentrated among a limited group of corporations capable of mobilizing the resources necessary to train and deploy large-scale models. This concentration creates asymmetries that extend beyond economic competition and affect the capacity of societies to govern technological innovation according to democratic principles.

Within educational contexts, these developments have particular significance. Artificial intelligence does not merely provide new tools for teaching and learning; it increasingly participates in the production of knowledge, the organization of educational experiences, the generation of learning recommendations, and the mediation of communication processes. AI systems are therefore becoming influential actors within educational ecosystems, shaping how information is accessed, interpreted, and utilized.

The challenge is not simply technological but also epistemological and political. AI systems incorporate assumptions, values, classifications, and priorities embedded within training datasets, algorithmic architectures, and design processes. Consequently, the growing adoption of AI may contribute to the diffusion of particular cultural, linguistic, and epistemological frameworks while marginalizing alternative perspectives and forms of knowledge. In this sense, concerns regarding algorithmic dependency overlap with broader debates surrounding digital sovereignty, technological colonialism, and cognitive justice.

The emergence of generative AI intensifies these concerns. Large language models increasingly mediate access to information, influence knowledge production, and shape educational interactions. Yet the governance of these systems remains highly centralized. Educational institutions frequently adopt AI tools without meaningful influence over how models are trained, what datasets are used, how biases are addressed, or how outputs are generated. This situation creates new forms of dependency in which educational actors rely on infrastructures they neither control nor fully understand.

For these reasons, growing attention has been directed toward alternative approaches capable of reconciling technological innovation with democratic governance. One of the most promising frameworks emerging from recent debates is the concept of cooperative artificial intelligence. Cooperative AI refers to the development and governance of AI systems according to principles of collective ownership, democratic accountability, transparency, social participation, and public benefit rather than exclusively commercial objectives.

The concept draws inspiration from broader traditions associated with digital commons, platform cooperativism, open-source development, and democratic innovation. Rather than concentrating technological resources within a small number of corporations, cooperative approaches seek to distribute control among public institutions, educational organizations, civil society actors, and local communities. In this model, AI becomes a shared social infrastructure rather than a proprietary asset governed primarily by market imperatives.

Recent scholarship has highlighted the potential of digital commons as alternative models for technological governance (Kostakis, 2019; Muldoon et al., 2024; Open Future Foundation, 2024). Digital commons involve collectively governed resources that remain accessible, transparent, and accountable to the communities that use them. Applied to artificial intelligence, this perspective encourages the development of shared datasets, open models, collaborative infrastructures, and public repositories designed to support educational and social objectives.

Within education, cooperative AI could take multiple forms. Publicly funded language models trained on educational resources could provide alternatives to proprietary systems. Federated infrastructures could allow educational institutions to collaborate in developing AI tools while maintaining control over their own data. Cooperative data trusts could enable collective governance of educational information. Open-source AI ecosystems could facilitate transparency, auditability, and adaptation to local educational contexts.

Such approaches would contribute to reducing technological dependency while strengthening institutional autonomy. Educational institutions would be better positioned to influence the design and governance of AI systems according to pedagogical priorities rather than adapting educational practices to technologies developed elsewhere. Such a move would represent a significant step toward educational digital sovereignty.

Transparency constitutes another central principle of cooperative AI. Democratic governance requires that educational stakeholders understand how AI systems operate, what data they use, how decisions are generated, and what limitations characterize their outputs. Transparency cannot be reduced to technical documentation alone; it must include meaningful opportunities for public scrutiny, independent auditing, and democratic oversight.

Equally important is the principle of algorithmic accountability. AI systems deployed in educational contexts should be subject to mechanisms capable of identifying errors, biases, discriminatory effects, and unintended consequences. Because educational decisions often have profound implications for students' opportunities and trajectories, AI systems must remain accountable to the communities affected by their operation.

The development of cooperative AI also requires reconsidering the relationship between innovation and public value. Contemporary technological discourse frequently assumes that innovation is inherently beneficial and that rapid technological adoption constitutes an objective in itself. However, critical scholarship has demonstrated that innovation is never neutral. Technological developments always embody particular assumptions regarding social priorities, governance arrangements, and the distribution of power.

From the perspective of educational digital sovereignty, innovation should be evaluated according to its contribution to democratic participation, social justice, pedagogical autonomy, and public well-being. The objective is not simply to accelerate technological adoption but to ensure that technological development remains aligned with educational values and collective interests.

This perspective also challenges forms of technological solutionism that reduce complex educational challenges to technical problems susceptible to algorithmic optimization (Morozov, 2015). Education is not merely an information-processing system. It is a social, ethical, cultural, and political process involving human relationships, collective meaning-making, democratic participation, and the cultivation of critical capacities. Artificial intelligence may support certain educational functions, but it cannot substitute the relational, deliberative, and emancipatory dimensions that define education as a public good.

Consequently, educational institutions should approach AI not as an autonomous force driving inevitable transformation but as a set of technologies whose purposes, limits, and governance arrangements remain open to democratic deliberation. The key question is not whether AI will shape the future of education, but under what conditions, according to whose interests, and through what forms of accountability this transformation will occur.

Cooperative artificial intelligence offers a framework for addressing these challenges. By combining technological innovation with democratic governance, public infrastructures, collective ownership, and participatory decision-making, it provides an alternative to increasingly concentrated models of AI development. More importantly, it aligns technological transformation with the broader objectives of educational digital sovereignty: protecting democratic control over educational infrastructures, strengthening pedagogical autonomy, fostering cognitive justice, and ensuring that digital innovation contributes to the public mission of education.

In this sense, cooperative AI should not be understood simply as a technological alternative but as part of a broader democratic project aimed at reclaiming collective agency over the digital futures of education.

7. Discussion

The analysis presented in this article suggests that the contemporary digital transformation of education cannot be adequately understood through narratives of technological progress, innovation adoption, or pedagogical modernization alone. Rather, the expansion of digital platforms, data infrastructures, and artificial intelligence systems must be situated within broader processes of economic restructuring, platform capitalism, and the concentration of technological power. From this perspective, educational digitalization emerges not merely as a technical transition but as a contested political process involving competing visions of governance, democracy, public value, and educational futures.

The concept of educational digital sovereignty developed throughout this article offers a framework for critically examining these transformations while simultaneously identifying pathways toward more democratic forms of educational innovation. Unlike approaches that focus primarily on technological adoption or digital competence, educational digital sovereignty foregrounds questions of ownership, governance, accountability, participation, and collective control. It shifts attention from what technologies can do to who governs them, whose interests they serve, and how their benefits and risks are distributed across society.

7.1. Educational Digital Sovereignty as a Framework for Democratic Innovation

A central contribution of this article is the proposition that educational digital sovereignty should be understood as a framework for democratic innovation. Contemporary policy discourse frequently equates innovation with technological adoption, efficiency gains, automation, or the deployment of increasingly sophisticated digital tools. However, such perspectives often neglect the institutional and political conditions under which innovation occurs.

The findings presented here suggest that innovation cannot be evaluated solely in terms of technical performance or organizational efficiency. Educational innovation also involves normative questions concerning democratic participation, social justice, institutional autonomy, and public accountability. Technological developments that increase efficiency while simultaneously reducing democratic control or intensifying dependency may be innovative in technical terms but problematic from the perspective of educational governance.

Educational digital sovereignty provides an alternative conception of innovation grounded in democratic principles. Within this framework, innovation is not defined primarily by the introduction of new technologies but by the capacity of educational systems to shape technological development according to collectively determined goals. Public digital infrastructures, open-source technologies, democratic data governance, cognitive justice, and participatory decision-making become not obstacles to innovation but essential conditions for ensuring that innovation contributes to public value.

This perspective aligns with emerging debates concerning digital public good, digital commons, and democratic technological governance. It suggests that educational innovation should be assessed not only according to effectiveness or scalability but also according to its contribution to autonomy, inclusion, transparency, and democratic capacity-building.

7.2. The Structural Tension between Platform Capitalism and Public Education

A second major finding concerns the growing tension between platform capitalism and the normative foundations of public education. Throughout the article, it has been argued that the increasing presence of Big Tech corporations in educational systems is not simply the result of technological superiority or institutional necessity. Rather, it reflects broader transformations in which educational infrastructures are progressively incorporated into economic models based on data extraction, platform dependency, and assetization.

This development creates a structural contradiction. Public education is traditionally organized around principles of universal access, democratic accountability, social inclusion, and collective benefit. Platform capitalism, by contrast, operates according to logics of market expansion, data accumulation, competitive advantage, and value extraction. While these logics may occasionally converge, they are not inherently compatible.

The platformization of education illustrates this tension clearly. Educational platforms provide valuable services and often address genuine institutional needs. However, they simultaneously create new dependencies, redistribute authority toward private actors, and transform educational activities into sources of economic value. Consequently, educational institutions increasingly operate within technological environments whose governance mechanisms remain largely outside democratic control.

This tension becomes even more pronounced with the expansion of artificial intelligence. AI systems require extensive data resources, computational infrastructures, and technical expertise concentrated among a limited number of corporations. As educational systems adopt AI-powered technologies, they risk becoming further integrated into ecosystems characterized by asymmetrical distributions of power and limited public oversight.

The concept of educational digital sovereignty offers a response to this tension by emphasizing the need to strengthen public capacities for technological governance. Rather than rejecting technological innovation, it seeks to rebalance relationships between educational institutions and technological actors, ensuring that public values and concerns remain central to digital transformation processes.

7.3. Implications for Educational Policy and Governance

The arguments developed in this article have important implications for educational policy. First, they suggest that digital transformation should be treated as a strategic governance issue rather than merely a matter of technological procurement. Decisions concerning platforms, data infrastructures, and AI systems shape the future capacities of educational institutions and therefore require democratic scrutiny comparable to that applied to other forms of public infrastructure.

Second, policymakers should move beyond narrow approaches focused on digital skills and technological adoption. While digital literacy remains important, educational digital sovereignty requires broader investments in institutional capacity, public infrastructures, technological expertise, and democratic governance mechanisms. Without such investments, educational systems may become increasingly dependent on external providers for functions that are central to their operation.

Third, regulatory frameworks should address questions of data ownership, algorithmic transparency, interoperability, and public accountability. Existing approaches often focus on privacy protection while neglecting broader issues related to governance, dependency, and institutional autonomy. A sovereignty-oriented perspective highlights the need for more comprehensive regulatory frameworks capable of ensuring that educational technologies remain aligned with public interests.

Fourth, educational policy should support the development of alternative technological ecosystems, including open-source initiatives, public digital infrastructures, cooperative AI projects, and digital commons. Such investments can contribute to diversifying technological options and reducing structural dependencies on proprietary platforms.

Finally, educational institutions themselves must be recognized as active participants in technological governance rather than passive consumers of digital products. Universities, schools, educators, and students possess valuable expertise regarding the educational implications of technological systems and should therefore play a meaningful role in shaping digital transformation strategies.

7.4. Future Research Directions

The concept of educational digital sovereignty also opens several promising avenues for future research. Although the notion is gaining visibility within policy and academic debates, its application to educational contexts remains relatively underdeveloped and requires further theoretical and empirical investigation.

Future studies could examine how different countries and educational systems conceptualize and implement digital sovereignty strategies. Comparative research would be particularly valuable for understanding how political traditions, institutional arrangements, and technological capacities influence approaches to educational governance.

Additional research is also needed regarding the practical implementation of public digital infrastructures, open-source educational ecosystems, and cooperative AI models. While these alternatives are increasingly discussed within policy debates, empirical evidence concerning their effectiveness, scalability, governance structures, and long-term sustainability remains limited.

The relationship between educational digital sovereignty and cognitive justice also deserves further attention. Questions concerning linguistic diversity, indigenous knowledge systems, local innovation capacities, and epistemological pluralism are likely to become increasingly important as artificial intelligence systems exert greater influence over educational environments and knowledge production processes.

Finally, future scholarship should explore how educational communities themselves understand and negotiate questions of technological dependency, autonomy, and governance. Greater attention to the perspectives of teachers, students, families, and local communities would enrich current debates and contribute to more participatory approaches concerning digital transformation.

This article contributes to the emerging literature on educational digital sovereignty in three principal ways.

Firstly, it extends the concept of digital sovereignty to the educational field by developing a multidimensional analytical framework that integrates technological infrastructures, data governance, algorithmic accountability, cognitive justice, and democratic participation. While existing discussions on digital sovereignty have largely focused on cybersecurity, state capacity, or technological autonomy, this article demonstrates that educational systems constitute a strategic domain in which sovereignty concerns are increasingly relevant due to the expansion of educational platformization, artificial intelligence, and data-driven governance.

Secondly, it establishes a conceptual bridge between the literature on platform capitalism and debates on educational innovation. Rather than treating digital transformation as a neutral process of technological modernization, the analysis situates educational platformization within broader political-economic dynamics associated with data extraction, infrastructural dependency, and the concentration of digital power. In doing so, it reframes educational innovation as a question of governance, democratic accountability, and public control over technological infrastructures.

Thirdly, the article advances the concept of Cooperative Artificial Intelligence as a potential framework for reconciling technological innovation with democratic governance. By connecting debates on artificial intelligence, digital commons, public digital infrastructures, and educational digital sovereignty, the article identifies alternative pathways for developing AI systems that prioritize transparency, accountability, collective ownership, and public value. This perspective contributes to emerging discussions concerning democratic approaches to AI governance and highlights the importance of educational institutions as active participants in shaping technological futures.

Taken together, these contributions position Educational Digital Sovereignty not only as a critical analytical concept but also as a normative and strategic framework for guiding democratic digital transformation in education.

7.5 Toward a Democratic Future for Digital Education

Taken together, the findings of this article suggest that educational digital sovereignty represents more than a response to technological dependency. It constitutes a broader democratic project aimed at reclaiming collective agency over the infrastructures, data, algorithms, and knowledge systems that increasingly shape educational life.

The central challenge facing contemporary educational systems is not whether digital technologies should play a role in education. Their presence is already deeply embedded within institutional and pedagogical practices. Rather, the challenge concerns the governance of these technologies and the extent to which educational communities retain the capacity to influence their development and use.

Educational digital sovereignty provides a framework for addressing this challenge by connecting debates on innovation, democracy, public governance, and technological transformation. It invites policymakers, educators, researchers, and citizens to move beyond questions of technological adoption and toward broader discussions concerning the kind of digital future that democratic societies wish to build.

In this sense, the future of educational innovation is inseparable from the future of democratic governance itself. The struggle over digital infrastructures, data governance, and artificial intelligence is ultimately a struggle over who will shape the educational institutions, knowledge systems, and social relations of the twenty-first century.

8. Conclusions

The digital transformation of education has become one of the defining challenges of the twenty-first century. While digital technologies have created new opportunities for communication, knowledge sharing, pedagogical innovation, and educational access, they have also facilitated profound shifts in the governance of educational systems. These transformations cannot be understood solely as processes of technological modernization. Rather, they are embedded within broader dynamics of platform capitalism, datafication, algorithmic governance, and the increasing concentration of digital power in the hands of a small number of global technology corporations.

The analysis demonstrates that the expansion of digital platforms within education has generated new forms of technological dependency that extend beyond questions of infrastructure and service provision. Educational institutions increasingly rely on proprietary ecosystems that shape communication processes, learning environments, assessment practices, data management systems, and decision-making mechanisms. As a result, educational governance is progressively being reconfigured through technological architectures whose design, ownership, and strategic direction remain largely outside democratic control.

Three interrelated risks emerge from this transformation. First, the growing datafication of educational activities has intensified forms of surveillance and data extraction that transform educational experiences into valuable economic resources. Second, the expansion of artificial intelligence and algorithmic systems has introduced new forms of governance that may undermine transparency, accountability, and pedagogical autonomy. Third, the global diffusion of educational platforms has reinforced patterns of technological dependency, digital inequality, and epistemic asymmetry that resemble contemporary forms of technological and cognitive colonialism.

Against this backdrop, educational digital sovereignty is offered as a conceptual and political framework capable of addressing these challenges. Educational digital sovereignty shifts the focus from technological adoption to technological governance. It emphasizes the capacity of educational communities, public institutions, and democratic societies to exercise meaningful control over digital infrastructures, data ecosystems, algorithmic systems, and technological innovation processes. In doing so, it reconnects debates on educational technology with broader concerns regarding democracy, public value, social justice, and collective self-determination.

A central contribution of the article is the identification of five strategic dimensions that constitute the foundations of educational digital sovereignty: public digital infrastructures, open-source technologies, democratic data governance, cognitive justice and epistemic pluralism, and community participation in technological decision-making. Together, these dimensions provide a comprehensive framework for reimagining digital transformation beyond the limits of platform dependency and market-driven innovation.

What is more, the emergence of artificial intelligence intensifies the urgency of these debates. AI systems are rapidly becoming integrated in educational environments, influencing how knowledge is produced, distributed, and evaluated. Yet the infrastructures supporting contemporary AI remain highly concentrated, creating new dependencies and governance challenges. In response, the concept of cooperative artificial intelligence has been advanced as a democratic alternative capable of aligning technological innovation with principles of transparency, accountability, public ownership, and collective benefit.

More broadly, the findings suggest that educational innovation should not be equated with technological adoption alone. Innovation is fundamentally a political and social process that involves decisions about values, priorities, governance arrangements, and the distribution of power. Technologies can support educational improvement, but they cannot determine the purpose of education. This remains a matter of democratic deliberation and collective choice.

Consequently, the future of digital education depends not only on technological capabilities but also on the institutional and political frameworks through which those technologies are governed. Educational systems that rely exclusively on externally controlled infrastructures risk losing the capacity to define their own priorities and shape their own futures. Conversely, educational systems that invest in public infrastructures, democratic governance mechanisms, technological autonomy, and participatory innovation are better positioned to harness digital technologies in ways that strengthen rather than weaken democratic institutions.

The debate on educational digital sovereignty is therefore not a marginal or exclusively technological concern. It lies at the heart of contemporary discussions about the future of public education, democratic governance, and social justice in digital societies. As educational environments become increasingly mediated by platforms, algorithms, and artificial intelligence, questions of sovereignty become inseparable from questions of educational purpose, citizenship, and democracy itself.

Ultimately, educational digital sovereignty should be understood not as a defensive reaction against technological change but as a proactive project for shaping technological futures according to democratic values. It represents an effort to ensure that digital transformation serves the public mission of education rather than subordinating education to the imperatives of platform capitalism. In this sense, educational digital sovereignty emerges as a necessary condition for preserving pedagogical autonomy, protecting digital rights, promoting cognitive diversity, and strengthening democratic control over the infrastructures that increasingly organize educational life.

The future of education will undoubtedly be digital. The critical question is whether that future will be governed primarily by corporate interests and technological concentration or by democratic institutions committed to the public good. Educational digital sovereignty provides a framework for ensuring that digital innovation contributes to the latter. It offers a pathway toward more equitable, participatory, and democratically governed educational systems capable of responding to the challenges of the digital age while preserving the emancipatory promise of public education.

Ultimately, Educational Digital Sovereignty should be understood not merely as a response to technological dependency but as a comprehensive framework for governing digital transformation in education. By integrating public digital infrastructures, democratic data governance, cognitive justice, community participation, and Cooperative Artificial Intelligence, it offers a coherent approach for aligning technological innovation with democratic values and the public mission of education.