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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]

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]

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 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. [ABSTRACT FROM PUBLISHER]

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]

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]