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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.

As we write, England and Denmark have celebrated ‘freedom days’, yet parts of Australia are in their sixth lockdown, and families in Argentina still can’t bury their loved ones as they would like t...

The rapid shift to online teaching and learning during the COVID-19 pandemic has accelerated the penetration of an algorithmic world view into education systems around the world. Promoted by a burgeoning educational technology industry, platforms that use algorithms to structure and monitor teaching and learning have been presented as technical solutions to systemic problems. But they have also created new problems and reinforced existing inequities, stirring up public and political backlashes. Beyond its immediate effects during the pandemic in 2020, the expanded use of algorithm-driven learning management systems backed by major corporations has major implications for the future of global education.

Digital platforms have become central to interaction and participation in contemporary societies. New forms of ‘platformized education’ are rapidly proliferating across education systems, bringing ...

Scientific advances in genetic analysis have been made possible in recent years by technical developments in computational biology, or bioinformatics. Bioinformatics has opened up the human genome to diverse analyses involving automated laboratory hardware and machine learning algorithms and software. As part of an emerging field of social genomics, recent educational genetics studies using big data have begun to raise challenging findings linking DNA to predicted life outcomes. Bioinformatic technologies and techniques including ‘genome-wide association’ and ‘polygenic scoring’ are producing new kinds of genetic biodata and expert knowledge for rethinking the upbringing and education of children. This article takes as an empirical opening a recent epistemic and ethical controversy over the use of biodata to make genetic predictions about educational, socio-economic and life outcomes, detailing the forms of expert knowledge and technologies involved these predictions, and exploring the social and ethical implications of data-intensive bioinformatics.

Artificial intelligence has become a routine presence in everyday life. Accessing information over the Web, consuming news and entertainment, the performance of financial markets, the ways surveill...

Contemporary culture is increasingly defined by data, indicators and metrics. Measures of quantitative assessment, evaluation, performance, and comparison infuse public services, commercial compani...

‘Platform capitalism’ and ‘surveillance capitalism’ describe the new business model and market form of the web. These forms of digital capitalism have begun to infuse the higher education landscape by merging with existing political demands for universities to become more data-driven, competitive, and market-focused. This article presents a case study of the education business Pearson and its expansion of the digital platform as a model for global higher education reform. A key ‘edu-business’ in the ‘global education industry’, Pearson has pivoted to online program management platforms, on-demand digital learning platforms, and intensive mobilization of data analytics to enact its strategic business priorities. These developments position Pearson as an authoritative source for both the evaluation and valuation of HE as a market. The analysis foregrounds the micro-processes involved as Pearson has sought to make, exploit, and maintain market opportunities in HE, demonstrating how the market form of digital capitalism is being reproduced by commercial power-players in the global higher education industry. As an actor in the sociotechnical arrangement of markets, the digital platform is a key participant in HE reforms that are intended to align the public mission of universities with the private interests of digital capitalism.

Women with fish tails are among the oldest and still most popular of mythological creatures, possessing a powerful allure and compelling ambiguity. They dwell right in the uncanniest valley of the sea: so similar to humans, yet profoundly other. Mermaids: Art, Symbolism and Mythology presents a comprehensive, interdisciplinary and beautifully illustrated study of mermaids and their influence on Western culture. The roots of mermaid mythology and its metamorphosis through the centuries are discussed with examples from visual art, literature, music and architecture—from 600 BCE right up to the present day. Our story starts in Mesopotamia, source of the earliest preserved illustrations of half-human, half-fish creatures. The myths and legends of the Mesopotamians were incorporated and adopted by ancient Greek, Etruscan and Roman cultures. Then, during the early medieval period, ancient mythological creatures such as mermaids were confused, transformed and reinterpreted by Christian tradition to begin a new strand in mermaid lore. Along the way, all manner of stunning—and sometimes bizarre or unsettling—depictions of mermaids emerged. Written in an accessible and entertaining style, this book challenges conventional views of mermaid mythology, discusses mermaids in the light of evolutionary theory and aims to inspire future studies of these most curious of imaginary creatures.

Software code, algorithms, data analytics and infrastructures have become inseparable from policy processes and modes of governance. This article introduces ‘digital policy sociology’ as a way of studying the role and influence of digital technologies in education policy. Building on existing ‘policy sociology’ approaches combined with emerging insights rom ‘digital sociology’, digital policy sociology extends the analytical gaze to new technical actors – nonhuman software and hardware, as well as human experts, technology companies, and promotional organizations. As a case study exemplar, the analysis focuses on an emerging domain of data-intensive science and technology with significant implications for education policy in the future. ‘Precision education’ is an emerging combination of psychological, neuroscientific and genetic expertise, with a particular emphasis on using advanced computational technologies to produce ‘intimate data’ about students’ bodies and biological associations with learning. These intimate data have potential to become new sources of biological policy knowledge, raising significant methodological and analytical challenges for policy sociology.

The figure of the network has featured prominently in research on education, media and technology in recent years. In movements like ‘networked learning’ and ‘connected learning’, the network opens...

Reviewed by Bob Lingard and Ben WilliamsonBiosocial Education is a challenging, indeed demanding, yet very informative book, co-authored collaboratively by critical sociologist of education Deborah...

This paper examines visions of ‘learning’ across humans and machines in a near-future of intensive data analytics. Building upon the concept of ‘learnification’, practices of ‘learning’ in emerging big data-driven environments are discussed in two significant ways: the training of machines, and the nudging of human decisions through digital choice architectures. Firstly, ‘machine learning’ is discussed as an important example of how data-driven technologies are beginning to influence educational activity, both through sophisticated technical expertise and a grounding in behavioural psychology. Secondly, we explore how educational software design informed by behavioural economics is increasingly intended to frame learner choices to influence and ‘nudge’ decisions towards optimal outcomes. Through the growing influence of ‘data science’ on education, behaviourist psychology is increasingly and powerfully invested in future educational practices. Finally, it is argued that future education may tend toward very specific forms of behavioural governance – a ‘machine behaviourism’ – entailing combinations of radical behaviourist theories and machine learning systems, that appear to work against notions of student autonomy and participation, seeking to intervene in educational conduct and shaping learner behaviour towards predefined aims.

Sakurajima, located on the southern rim of Aira caldera, is one of the most active volcanoes in Japan. From long term deformation trends, the volcano is showing an increased risk of large-scale eruption, emphasizing the need to better understand the magmatic system.Deformation modelling, primarily using the Mogi method, has dominated the geodetic assessment history of Sakurajima. These methods, however, contain limitations, such as the assumption of a homogeneous crust, and have therefore not accurately depicted the magmatic system. Numerical modelling techniques have reduced this limitation by accounting for subsurface heterogeneity.Analytical modelling studies have suggested multiple magmatic sources beneath Aira caldera and Sakurajima volcano, whilst the only numerical study undertaken so far indicated a single source. Here, we test the multiple deformation source hypothesis, whilst also incorporating subsurface heterogeneity and topography, using Finite Element (FE) numerical modelling, and geodetic data from Sakurajima.Using a full 3D model geometry for Sakurajima and Aira caldera, preliminary forward modelling suggests a second deformation source produces our best fit to the measured geodetic data. Optimum results indicate a shallow prolate source 7-10 km below sea level (bsl), in addition to a deeper oblate source at ~13 km bsl. These preliminary findings produce greater shallow storage depths than the previous analytical models (3-6 km) and ties in with the trans-crustal magmatic system hypothesis.Increasing our understanding of the Sakurajima magmatic system will enable improved interpretations of geodetic data prior to eruptions and will inform models for a range of similar volcanoes world-wide.

Ground deformation offers vital insight into the activity of volcanoes, as well as the characteristics of the magmatic systems that feed them. The extended eruption of the Soufrière Hills Volcano (SHV) has allowed for the development of a comprehensive multi-disciplinary monitoring network, which has aided extensive research into the magmatic system underlying the volcano. The modern network comprises GPS, strainmeters, and cheaper Electronic Distance Measurement (EDM). However, the island’s EDM network has to date only being used for monitoring the SHV. Here, for the first time, we co-analyse the EDM dataset from 2010-19 with the GPS data from the same period. This study aims to delineate the modern magmatic system conditions by building 3D Finite Element Models, as well as assessing the best use of EDM data in modelling the SHV.The island-wide deformation recorded over the past decade at the GPS network is broadly radial relative to the SHV dome, with a decreasing deformation rate. The EDM data shows line lengthening on the west and east flanks of the volcano, but minor line length shortening on the northern flank. We utilise Finite Element Modelling to model the SHV magmatic system as a single elongated prolate with 3D topography incorporated. We systematically test a wide range of parameters to explore how both EDM and GPS record perturbations to the magmatic system. Our preliminary results show that variations of certain parameters to the deeper magmatic system have an impact on both EDM and GPS timeseries, while some parameters (e.g., source pressure, source depth, and source location) have a more significant effect on EDM measurements than others (e.g., source shape).

Understanding the physical properties of magma reservoirs and their fluid/mechanical behaviour is crucial for improving geophysical models. New evidence suggests that large bodies of magma are difficult to maintain for an extended time period and that melts may instead reside within crystal-mush reservoirs which consist of variably packed frameworks of crystals and interstitial melt. Most existing volcano deformation models assume a pressurized cavity embedded in a homogeneous or heterogenous elastic half-space and therefore ignore the presence of crystals and the possible poroelastic mechanical response to melt intrusion or withdrawal. Here, we consider the magma reservoir to be entirely porous, comprising melt distributed between solid crystals. We investigate the influence of poroelastic mechanical behaviour on reservoir pressure development and resultant spatio-temporal surface deformation. We examine the post-intrusion and post-eruption time-dependent pressure evolution in the magma reservoir due to melt diffusion in the porous domain. Unlike the classic (cavity) models for volcanic surface deformation, an observable post-eruptive or post-intrusion time-dependent inflation can occur without an additional mass change if the reservoir is sufficiently permeable. Post-intrusion and post-eruption timescales vary depending on the porosity of the mush (melt fraction), permeability and magma viscosity. Our study confirms that reservoir inflation and surface deformation can occur without an intrusion or withdrawal of melt but are instead controlled by the mush's poroelastic behaviour.

If financial markets are taken as the main measure of the impact of the Covid-19 pandemic on education since early 2020, then education technology (‘edtech’) has finally arrived with disruptive and...

Education has long been a space of in which knowledge was created through data practices. But the ongoing datafication and digitalisation has made new forms of datafied knowledge production within educational research possible. This new form of datafied knowledge creation has shifted the sites of expertise and the authority to create educational knowledge to a more-than-human network. This panel conceptually and empirically examines the possibilities and implications that arise from the entanglement of education with advanced media such as ubiquitous sensory environments, APIs, machine learning, and codes. The panel shows how the idea of measurable and re-configurable bodies of students is being performed and stabilized through trade shows and academic conferences; it moves towards a critical analysis of different applications of facial recognition in education and the role of doubt in machine learning methods; it shows the complex involvement of advanced learning analytics through a critical examination of interrelated studies in behavioural genetics and genoeconomics looking for associations between genes and educational outcomes through bioinformatic methods; and, it examines learning and living spaces that create a situation of ubiquitous sensation and explores interventions to disrupt the technical milieu. What connects these papers is more than the spaces, ideas and practices that surround education. All contributions look at datafied knowledge about human life – whether in behavioural, physiological, emotional, or genetic form. The panel aims to show what critical education research has adopted from other disciplines, but also show how it can contribute to the wider discourse around science, technology and society.

Education data scientists, learning engineers and precision education specialists are new experts in knowledge production in educational research. By bringing together data science methodologies and advanced artificial intelligence (AI) systems with disciplinary expertise from the psychological, biological and brain sciences, they are building a new field of AI-based learning science. This article presents an examination of how education research is being remade as an experimental data-intensive science. AI is combining with learning science in new ‘digital laboratories’ where ownership over data, and power and authority over educational knowledge production, are being redistributed to research assemblages of computational machines and scientific expertise.

The first special issue of Learning, Media and Technology of 2020, entitled ‘Education and technology into the 2020s: speculative futures’, presented a series of papers looking to the future of cri...