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This article examines underdetermination as a key theoretical assumption in an emerging body of educational research. Underdetermination is described as a broad philosophical position that assumes that social, scientific and technological phenomena cannot be reduced to linear relationships between antecedents and consequences, for instance through the canonical progression from scientific hypotheses to experimentation and then empirical truths. Rather, phenomena are underdetermined by constellations of social and material influences that make the choice of univocal explanations problematic. The principle of underdetermination is implicit in a recent strand of educational research that critiques orthodox interpretations of scientific practices, innovation processes and policy dynamics, recasting them as social, material and political "assemblages". In the article, I analyse the philosophical and epistemological tenets of underdetermination, in order to clarify its nature as a "first principle" in this emerging body of research. By doing so, the article brings into view a broader theoretical debate that has great bearing on future research efforts. The article critically considers the continued theoretical relevance of underdetermination, whilst acknowledging critical arguments mounted against it, namely ontological relativism and political weakness. Some supplementing theoretical ideas are explored in the conclusion.

Teachers are increasingly required to enact assessment policies in digitalised spaces, raising ethical issues of privacy and surveillance in the process. Yet, while "policy enactment" has been examined extensively, there remains research uncertainty around the ethical dimensions associated with assessment policy in digitalised settings. Drawing upon Ball et al.'s Typology of Policy Positions, and utilising Australian teachers' interviews, we illustrate how the policy positions of the latter were shaped by "critical ethical incidents" in digitalised conditions. We describe how teachers struggled to reconcile their ethical obligation to provide valid assessment outcomes with their "duty of care, procedural institutional commitments," and the need to protect "student privacy." To ensure 'ethical assessment' practices that best fulfil their obligations, the educators were not confined to one policy position, rather they moved across roles, also framed as moral recuperation mechanisms. Regulations to help facilitate policy enactments of 'ethical assessment' in digitalised contexts are suggested.

This article proposes a pragmatic approach to data justice in education that draws upon Nancy Fraser's theory. The main argument is premised on the theoretical and practical superiority of a deontological framework for addressing algorithmic bias and harms, compared to ethical guidelines. The purpose of a deontological framework is to enable the evaluation of justice claims, not as a burden for individuals or groups, but as part of an ongoing public dialogue about the disparate impacts of algorithmic decisions. In a deontological framework, scrutiny is not limited to differences in treatment but is broader and more demanding, involving the evaluation of design approaches and a wider-ranging political discussion about who might be harmed.

In this analytical essay, part of Harvard Educational Review's symposium on Platform Studies in Education, Ben Williamson, Kalervo N. Gulson, Carlo Perrotta, and Kevin Witzenberger argue that global technology companies have begun acting as governance organizations in education. Their analysis focuses on the global technology company Amazon, which has begun penetrating education through a connective architecture of digital infrastructure and platform services. Looking at Amazon technical documentation and publicly available materials, the authors identify and examine five interlocking governance operations and their effects: inscribing commercial business models on the education sector, habituating educational users to Amazon technologies, creating new interfaces with educational institutions, platforming third-party education providers on the cloud, and seeking market dominance over provision and control of key information infrastructures of education. In showing how Amazon is potentially developing infrastructural dominance in the education sector as part of its transformation into a statelike corporation with significant social, technical, economic, and political power to govern and control state and public services, this article highlights the broader implications of increasing technological governance in education.

This article offers a case study of how platforms and predictive infrastructures are emerging in higher education. It examines a Learning Analytics Application Programming Interface (API) from a popular Learning Management System. The API is treated firstly as an artefact based on the computational abstraction of educational principles, and secondly as an empirical entry point to investigate the emergence of a Learning Analytics infrastructure in a large Australian university. Through in-depth ethnographic interviews and the interpretative analysis of software development workflows, the paper describes an API-mediated platformisation process involving a range of actors and systems: computational experts, algorithms, data-savvy administrative staff and large corporate actors inserting themselves through back-ends and various other dependencies. In the conclusion, the article argues that the platformisation of higher education is part of a broader project that mobilises programmability and computation to re-engineer educational institutions in the interest of efficiency and prediction. However, the social-scientific study of this project cannot ignore the practical and compromised dimension where human actors and technical systems interact and, in the process, generate meaning.

Digital platforms have become central to interaction and participation in contemporary societies. New forms of 'platformized education' are rapidly proliferating across education systems, bringing logics of datafication, automation, surveillance, and interoperability into digitally mediated pedagogies. This article presents a conceptual framework and an original analysis of Google Classroom as an infrastructure for pedagogy. Its aim is to establish how Google configures new forms of pedagogic participation according to platform logics, concentrating on the cross-platform interoperability made possible by application programming interfaces (APIs). The analysis focuses on three components of the Google Classroom infrastructure and its configuration of pedagogic dynamics: Google as platform proprietor, setting the 'rules' of participation; the API which permits third-party integrations and data interoperability, thereby introducing automation and surveillance into pedagogic practices; and the emergence of new 'divisions of labour', as the working practices of school system administrators, teachers and guardians are shaped by the integrated infrastructure, while automated AI processes undertake the 'reverse pedagogy' of learning insights from the extraction of digital data. The article concludes with critical legal and practical ramifications of platform operators such as Google participating in education.

The emergence of personalised data technologies such as learning analytics is framed as a solution to manage the needs of higher education student populations that are growing ever more diverse and larger in size. However, the current approach to learning analytics presents tensions between increasing student agency in making learning-related decisions and 'datafying' students in the process of collecting, analysing and interpreting data. This article presents a study that explores staff and student experience of agency, equity and transparency in existing data practices and expectations towards learning analytics in a UK university. The results show a number of intertwined factors that have contributed to the tensions between enhancing a learner's control of their studies and, at the same time, diminishing their autonomy as an active agent in the process of learning analytics. This article argues that learner empowerment should not be automatically assumed to have taken place as part of the adoption of learning analytics. Instead, the interwoven power relationships in a complex educational system and the interactions between humans and machines need to be taken into consideration when presenting learning analytics as an equitable process to enhance student agency and educational equity.

This article addresses the deliberately speculative question of 'What might the school of 2030 be like?', with a specific focus on the influences of digital technologies. The article adopts the methodological approach of 'social science fiction' to explore the ways in which digital technologies might be used in one Australian high school in 2030 (Lakeside), and what this might mean for the people whose lives are enmeshed with these technologies. Through the co-construction of five social science fiction 'vignettes' about life within Lakeside, the article considers the increasing prevalence of dataveillance, digital deskilling and the de-territorialization of schooling. The article then goes on to consider changing relationships between time/place, material and coded structures, as well as the increasingly platformized and data-driven nature of schooling in the 2020s. The article ends by considering the ways in which critical scholars can continue to use the methodological approach of social science fiction writing with regard to unpacking the politics of digital education futures.

In Applied AI, or 'machine learning', methods such as neural networks are used to train computers to perform tasks without human intervention. In this article, we question the applicability of these methods to education. In particular, we consider a case of recent attempts from data scientists to add AI elements to a handful of online learning environments, such as Khan Academy and the ASSISTments intelligent tutoring system. Drawing on Science and Technology Studies (STS), we provide a detailed examination of the scholarly work carried out by several data scientists around the use of 'deep learning' to predict aspects of educational performance. This approach draws attention to relations between various (problematic) units of analysis: flawed data, partially incomprehensible computational methods, narrow forms of 'educational' knowledge baked into the online environments, and a reductionist discourse of data science with evident economic ramifications. These relations can be framed ethnographically as a 'controversy' that casts doubts on AI as an objective scientific endeavour, whilst illuminating the confusions, the disagreements and the economic interests that surround its implementations.

This article is about 'making' in education. Often associated with software programming (as in 'digital making'), making can also involve creating or modifying physical technological artefacts. In this paper, making is examined as a phenomenon that occurs at the intersection of culture, the economy, technology and education. The focus is not on the effects on cognitive gains or motivations, but on locating making in a social, historical and economic context. Making is also described as a form of 'material connotation', where connotation refers to the process through which the technical structure of artefacts is altered by culture and society. In the second part of the paper, the theoretical discussion is complemented by a case study in which making is described as a networked phenomenon where technology companies, consultants, volunteers, schools, and students were all implicated in turning a nebulous set of practices and discourses into an educational reality.

This paper argues that methods used for the classification and measurement of online education are not neutral and objective, but involved in the creation of the educational realities they claim to measure. In particular, the paper draws on material semiotics to examine cluster analysis as a 'performative device' that, to a significant extent, creates the educational entities it claims to objectively represent through the emerging body of knowledge of Learning Analytics (LA). It also offers a more critical and political reading of the algorithmic assemblages of LA, of which cluster analysis is a part. Our argument is that if we want to understand how algorithmic processes and techniques like cluster analysis function as performative devices, then we need methodological sensibilities that consider critically both their political dimensions and their technical-mathematical mechanisms. The implications for critical research in educational technology are discussed.

Interest in artificial intelligence (AI) language models has grown considerably following the release of 'generative pre-trained transformer' (GPT). Framing AI as an extractive technology, this article details how GPT harnesses human labour and sensemaking at two stages: (1) during training when the algorithm 'learns' biased communicative patterns extracted from the Internet and (2) during usage when humans write alongside the AI. This second phase is framed critically as a form of unequal 'affective labour' where the AI imposes narrow and biased conditions for the interaction to unfold, and then exploits the resulting affective turbulence to sustain its simulation of autonomous performance. Empirically, this article draws on an in-depth case study where a human engaged with an AI writing tool, while the researchers recorded the interactions and collected qualitative data about perceptions, frictions and emotions. [ABSTRACT FROM AUTHOR]

This paper focuses on the relationship between rational beliefs, culture and agency in formal school settings. This relationship is analysed in the context of the adoption of technological innovations. Interviews and focus groups with 39 secondary teachers from England and other European countries were carried out. The analysis highlights a number of cultural differences between English teachers and their continental colleagues. The paper argues against a linear and simplistic appropriation of rational choice theory in educational research, whereby individual behaviour is examined from the perspective of individualist psychology and micro-economic theory without considering models of culturally informed agency beyond self-interest and calculation. In the conclusion, the paper argues that explanations of teacher agency in relation to technology must take into account the role of rationality and emotionality--not as a binary opposition that reflects actual psychological qualities that teachers may or may not possess, but as phenomena to be unpacked: competing (and culturally shaped) discursive strategies enacted to make sense of the world.

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This paper draws on actor-network theory and on the sociology of cultural consumption to examine the phenomenon of corporate Massive Open Online Courses. Through an analysis of texts available in the public domain, the paper argues that over a short period (between 2012 and 2013) digitisation technology became associated with the emergence of a hybrid "actor": the digital video-recorder teacher. A parallel is drawn between the "interactive affordances" of digital instruction and the playback and cataloguing options that have contributed to shifts in television viewing habits. The digital video-recorder teacher is described as an artefact in the service of a postmodern project of self-improvement through cultural consumption, which recruits digitisation to meet a growing demand for "upgrades to the self". In the conclusion, the paper explores how the study of digital education could benefit from an interface between sociomaterial studies and the sociology of culture.

This paper uses methods derived from the field of futures studies to explore the future of technology-enhanced assessment. Drawing on interviews and consultation activities with experts, the paper aims to discuss the conditions that can impede or foster "innovation" in assessment and education more broadly. Through a review of relevant research, the paper suggests an interpretive model of the factors sustaining the conservatism of educational assessment: the utilitarian view of education, dominant beliefs about academic excellence, and market or quasi-market dynamics. In the central section of the paper, three scenarios of innovation in assessment are described, developed through an iterative process involving researchers, representatives from the e-assessment industry, and experts from British awarding organisations. In the final section, a critical discussion draws attention to the implications that data pervasiveness and computer-generated predictive models may have for the future of education.

The supposed benefits of teachers' use of information and communications technology (digital technology) are well reported throughout the academic literature--most often involving issues of enhanced learning outcomes, increased pupil engagement and more efficient management and organisation of learning. This paper uses survey data from 683 teachers in 24 secondary schools across the UK to analyse the factors influencing how these benefits are being experienced. In particular, the paper explores the complex relationships between teachers' perceptions of technology-related benefits and a range of individual, classroom, school and system-level issues. A number of mediating issues and influences are identified and discussed throughout these analyses. In particular, it is suggested that teachers' perceptions of the benefits of using technology are influenced more by institutional rather than individual characteristics. A number of possible reasons are discussed, highlighting the importance of social and cultural contexts of digital technology use in education. (Contains 4 tables and 1 figure.)

This paper contends that powerful techniques to manipulate data, enabled by technological and economic developments, can be easily co-opted to serve the restrictive frameworks of hyper-controlling, managerial accountability that characterise current cultures of summative assessment in education. In response to these challenges, research is urgently needed to increase our understanding of the impact that assessments have on individuals and society. The paper concludes that social research ought to contribute to the identification of responses--educational, technological and political--that can minimise inequalities and potential abuses through the encouragement of data literacy across society. (Contains 2 notes.)

This article proposes a pragmatic approach to data justice in education that draws upon Nancy Fraser's theory. The main argument is premised on the theoretical and practical superiority of a deontological framework for addressing algorithmic bias and harms, compared to ethical guidelines. The purpose of a deontological framework is to enable the evaluation of justice claims, not as a burden for individuals or groups, but as part of an ongoing public dialogue about the disparate impacts of algorithmic decisions. In a deontological framework, scrutiny is not limited to differences in treatment but is broader and more demanding, involving the evaluation of design approaches and a wider-ranging political discussion about who might be harmed. [ABSTRACT FROM AUTHOR]

Teachers are increasingly required to enact assessment policies in digitalised spaces, raising ethical issues of privacy and surveillance in the process. Yet, while policy enactment has been examined extensively, there remains research uncertainty around the ethical dimensions associated with assessment policy in digitalised settings. Drawing upon Ball et al.'s Typology of Policy Positions, and utilising Australian teachers' interviews, we illustrate how the policy positions of the latter were shaped by critical ethical incidents in digitalised conditions. We describe how teachers struggled to reconcile their ethical obligation to provide valid assessment outcomes with their duty of care, procedural institutional commitments, and the need to protect student privacy. To ensure 'ethical assessment' practices that best fulfil their obligations, the educators were not confined to one policy position, rather they moved across roles, also framed as moral recuperation mechanisms. Regulations to help facilitate policy enactments of 'ethical assessment' in digitalised contexts are suggested. [ABSTRACT FROM AUTHOR]

This article offers a case study of how platforms and predictive infrastructures are emerging in higher education. It examines a Learning Analytics Application Programming Interface (API) from a popular Learning Management System. The API is treated firstly as an artefact based on the computational abstraction of educational principles, and secondly as an empirical entry point to investigate the emergence of a Learning Analytics infrastructure in a large Australian university. Through in-depth ethnographic interviews and the interpretative analysis of software development workflows, the paper describes an API-mediated platformisation process involving a range of actors and systems: computational experts, algorithms, data-savvy administrative staff and large corporate actors inserting themselves through back-ends and various other dependencies. In the conclusion, the article argues that the platformisation of higher education is part of a broader project that mobilises programmability and computation to re-engineer educational institutions in the interest of efficiency and prediction. However, the social-scientific study of this project cannot ignore the practical and compromised dimension where human actors and technical systems interact and, in the process, generate meaning. [ABSTRACT FROM AUTHOR]

Digital platforms have become central to interaction and participation in contemporary societies. New forms of 'platformized education' are rapidly proliferating across education systems, bringing logics of datafication, automation, surveillance, and interoperability into digitally mediated pedagogies. This article presents a conceptual framework and an original analysis of Google Classroom as an infrastructure for pedagogy. Its aim is to establish how Google configures new forms of pedagogic participation according to platform logics, concentrating on the cross-platform interoperability made possible by application programming interfaces (APIs). The analysis focuses on three components of the Google Classroom infrastructure and its configuration of pedagogic dynamics: Google as platform proprietor, setting the 'rules' of participation; the API which permits third-party integrations and data interoperability, thereby introducing automation and surveillance into pedagogic practices; and the emergence of new 'divisions of labour', as the working practices of school system administrators, teachers and guardians are shaped by the integrated infrastructure, while automated AI processes undertake the 'reverse pedagogy' of learning insights from the extraction of digital data. The article concludes with critical legal and practical ramifications of platform operators such as Google participating in education. [ABSTRACT FROM AUTHOR]

This article presents a critical examination of European policy in relation to gamification. We begin by describing how gamification "traveled" as an idea, evolving from controversial yet persuasive buzzword to legitimate policy priority. We then focus on how gamification was represented in Horizon 2020: the flagship European Research & Development program from 2014 to 2020, worth nearly €80 billion of funding. The article argues that the ethically problematic aspects of gamification were removed through a process of policy capture that involved its assimilation in an established European network of research and small and medium enterprise (SME) actors. This process of "ethical neutering" is also observable in the actual funding calls, where the problematic assumptions of gamification around agency and manipulation are made invisible through a superficial commitment to vague and illdefined criteria of responsible research and innovation. [ABSTRACT FROM AUTHOR]

In Applied AI, or 'machine learning', methods such as neural networks are used to train computers to perform tasks without human intervention. In this article, we question the applicability of these methods to education. In particular, we consider a case of recent attempts from data scientists to add AI elements to a handful of online learning environments, such as Khan Academy and the ASSISTments intelligent tutoring system. Drawing on Science and Technology Studies (STS), we provide a detailed examination of the scholarly work carried out by several data scientists around the use of 'deep learning' to predict aspects of educational performance. This approach draws attention to relations between various (problematic) units of analysis: flawed data, partially incomprehensible computational methods, narrow forms of educational' knowledge baked into the online environments, and a reductionist discourse of data science with evident economic ramifications. These relations can be framed ethnographically as a 'controversy' that casts doubts on AI as an objective scientific endeavour, whilst illuminating the confusions, the disagreements and the economic interests that surround its implementations. [ABSTRACT FROM AUTHOR]

The emergence of personalised data technologies such as learning analytics is framed as a solution to manage the needs of higher education student populations that are growing ever more diverse and larger in size. However, the current approach to learning analytics presents tensions between increasing student agency in making learning-related decisions and 'datafying' students in the process of collecting, analysing and interpreting data. This article presents a study that explores staff and student experience of agency, equity and transparency in existing data practices and expectations towards learning analytics in a UK university. The results show a number of intertwined factors that have contributed to the tensions between enhancing a learner's control of their studies and, at the same time, diminishing their autonomy as an active agent in the process of learning analytics. This article argues that learner empowerment should not be automatically assumed to have taken place as part of the adoption of learning analytics. Instead, the interwoven power relationships in a complex educational system and the interactions between humans and machines need to be taken into consideration when presenting learning analytics as an equitable process to enhance student agency and educational equity. [ABSTRACT FROM AUTHOR]

This article addresses the deliberately speculative question of 'What might the school of 2030 be like?', with a specific focus on the influences of digital technologies. The article adopts the methodological approach of 'social science fiction' to explore the ways in which digital technologies might be used in one Australian high school in 2030 (Lakeside), and what this might mean for the people whose lives are enmeshed with these technologies. Through the co-construction of five social science fiction 'vignettes' about life within Lakeside, the article considers the increasing prevalence of dataveillance, digital deskilling and the de-territorialization of schooling. The article then goes on to consider changing relationships between time/place, material and coded structures, as well as the increasingly platformized and data-driven nature of schooling in the 2020s. The article ends by considering the ways in which critical scholars can continue to use the methodological approach of social science fiction writing with regard to unpacking the politics of digital education futures. [ABSTRACT FROM AUTHOR]

This article is about ‘making’ in education. Often associated with software programming (as in ‘digital making’), making can also involve creating or modifying physical technological artefacts. In this paper, making is examined as a phenomenon that occurs at the intersection of culture, the economy, technology and education. The focus is not on the effects on cognitive gains or motivations, but on locating making in a social, historical and economic context. Making is also described as a form of ‘material connotation’, where connotation refers to the process through which the technical structure of artefacts is altered by culture and society. In the second part of the paper, the theoretical discussion is complemented by a case study in which making is described as a networked phenomenon where technology companies, consultants, volunteers, schools, and students were all implicated in turning a nebulous set of practices and discourses into an educational reality. [ABSTRACT FROM AUTHOR]

This paper argues that methods used for the classification and measurement of online education are not neutral and objective, but involved in the creation of the educational realities they claim to measure. In particular, the paper draws on material semiotics to examine cluster analysis as a 'performative device' that, to a significant extent, creates the educational entities it claims to objectively represent through the emerging body of knowledge of Learning Analytics (LA). It also offers a more critical and political reading of the algorithmic assemblages of LA, of which cluster analysis is a part. Our argument is that if we want to understand how algorithmic processes and techniques like cluster analysis function as performative devices, then we need methodological sensibilities that consider critically both their political dimensions and their technical-mathematical mechanisms. The implications for critical research in educational technology are discussed. [ABSTRACT FROM AUTHOR]

This paper uses methods derived from the field of futures studies to explore the future of technology-enhanced assessment. Drawing on interviews and consultation activities with experts, the paper aims to discuss the conditions that can impede or foster ‘innovation’ in assessment and education more broadly. Through a review of relevant research, the paper suggests an interpretive model of the factors sustaining the conservatism of educational assessment: the utilitarian view of education, dominant beliefs about academic excellence, and market or quasi-market dynamics. In the central section of the paper, three scenarios of innovation in assessment are described, developed through an iterative process involving researchers, representatives from the e-assessment industry, and experts from British awarding organisations. In the final section, a critical discussion draws attention to the implications that data pervasiveness and computer-generated predictive models may have for the future of education. [ABSTRACT FROM PUBLISHER]

The supposed benefits of teachers' use of information and communications technology (digital technology) are well reported throughout the academic literature-most often involving issues of enhanced learning outcomes, increased pupil engagement and more efficient management and organisation of learning. This paper uses survey data from 683 teachers in 24 secondary schools across the UK to analyse the factors influencing how these benefits are being experienced. In particular, the paper explores the complex relationships between teachers' perceptions of technology-related benefits and a range of individual, classroom, school and system-level issues. A number of mediating issues and influences are identified and discussed throughout these analyses. In particular, it is suggested that teachers' perceptions of the benefits of using technology are influenced more by institutional rather than individual characteristics. A number of possible reasons are discussed, highlighting the importance of social and cultural contexts of digital technology use in education. Practitioner Notes What is already known about this topic So far, research on teachers' perceptions of the benefits of information and communication technologies (ICTs) has shown that while some teachers effortlessly 'assimilate' and incorporate digital technologies into their teaching, and are more inclined to see the benefits of technology use in their classrooms, many others are often 'blamed' for failing to see the 'obvious' benefits of ICTs in the classroom., Descriptions and analyses currently available therefore position particular groups and 'types' of teachers as having rather uneasy relationships with technology, while at the same time representing technology use as the most rational and obvious choice for all teachers, irrespective of social and cultural differences., What this paper adds The paper argues that there is a need for more attention to be paid to how digital technologies are being used between different schools and, more problematically, to explore the relationship between teachers' perceptions and a range of individual and institutional factors., The paper attempts to move beyond the 'discourses of deficiency' that characterise some schoolteachers as lacking individual attributes, capabilities and the required rational mindset to appreciate the 'compelling potential' of ICTs., In particular, this paper explores in more detail the complex relationships between the benefits of technology use as perceived by schoolteachers and the various individual, classroom, school and system-level issues that may underlie these perceptions. The findings suggest that broader contextual and cultural dimensions may mediate and significantly alter individual perceptions., Implications for practice and/or policy This paper points to the need to develop a more rounded picture of the relationship(s) between the social contexts that surround schools, teachers and technology use. Indeed, there is arguably a need to move beyond 'blaming' certain groups of teachers for not making best use of technology (ie, those who are older, female and so on)., As such, the data presented in this paper support the emerging argument to move beyond placing 'dangerous moral imperatives' onto individual teachers to change their practices and processes in line with the assumed 'affordances' of digital technology., Individual teachers or whole schools could draw on the social shaping perspective and the findings presented in this paper to articulate a more critically minded set of responses in relation to digital technologies in their contexts, resisting individualising and blaming discourses that unfairly position them as the weak link in an otherwise linear, robust and unproblematic chain of deterministic assumptions. [ABSTRACT FROM AUTHOR]

This paper contends that powerful techniques to manipulate data, enabled by technological and economic developments, can be easily co-opted to serve the restrictive frameworks of hyper-controlling, managerial accountability that characterise current cultures of summative assessment in education. In response to these challenges, research is urgently needed to increase our understanding of the impact that assessments have on individuals and society. The paper concludes that social research ought to contribute to the identification of responses – educational, technological and political – that can minimise inequalities and potential abuses through the encouragement of data literacy across society. [ABSTRACT FROM AUTHOR]

In this analytical essay, part of Harvard Educational Review's symposium on Platform Studies in Education, Ben Williamson, Kalervo N. Gulson, Carlo Perrotta, and Kevin Witzenberger argue that global technology companies have begun acting as governance organizations in education. Their analysis focuses on the global technology company Amazon, which has begun penetrating education through a connective architecture of digital infrastructure and platform services. Looking at Amazon technical documentation and publicly available materials, the authors identify and examine five interlocking governance operations and their effects: inscribing commercial business models on the education sector, habituating educational users to Amazon technologies, creating new interfaces with educational institutions, platforming third-party education providers on the cloud, and seeking market dominance over provision and control of key information infrastructures of education. In showing how Amazon is potentially developing infrastructural dominance in the education sector as part of its transformation into a statelike corporation with significant social, technical, economic, and political power to govern and control state and public services, this article highlights the broader implications of increasing technological governance in education. [ABSTRACT FROM AUTHOR]

Focusing on the UK context, and drawing on freely available information about online learning and the underlying commercial agreements between institutions, Massively Open Online Course (MOOC) platforms and Online Program Management (OPM) companies, this article shows how digitization and universities' global expansion strategies are involved in forms of transnational marketization. In particular, the article shows that the online learning marketplace in the UK shows signs of segmentation, with 'premium' offerings in the high-to-middle tier targeting socially advantaged students-as-consumers, and a bottom region of low-ranking institutions drifting towards low-grade 'unbundled' provision that targets middle-to-low income groups. The article argues that the current global landscape of online education is a shifting, unequal market place, and that more research is needed on how different groups from a range of socio-economic backgrounds successfully or unsuccessfully navigate an increasingly fragmented and 'unbundled' educational terrain. [ABSTRACT FROM AUTHOR]