Themes

• ‘Big Data’ has become a contested term that is used diversely by different groups. The simple technical definition is that big data consists of information collected in huge volume, of highly diverse variety, which is collected at extreme velocity. 

• Rather than working with a strict technical definition of big data, big data can be better understood as an emerging social phenomenon and as a powerful concept that has attained critical importance in recent years. Big data is also inseparable from the software programs, algorithms and analytics required to collect and manage it, all of which requires diverse forms of specialist expert practice to be performed (Williamson, 2017).

• Over the last decade, school-level education across the world has seen the growing involvement of a small number of large technology firms prevalent across all sectors of the global economy. Three of the biggest are Google, Apple, and Microsoft. All have a vertically integrated business model, meaning that they produce interlinked hardware, operating systems, a range of cloud services, and educational platforms. Their educational platforms – including Google Classroom, Apple Classroom and Schoolwork and Microsoft Teams and OneNote for Education – are tied in varying constellations to their well-known general-purpose hardware (e.g., Chromebook, iPad, Surface) and operating systems (ChromeOS, iOS/MacOS, Windows). (Veale, 2022)

• Postdigital theory posits that technology and education are entangled. "As Bayne argued, the digital is not a special or separate domain from embodied, co-present spaces that we inhabit day to day – instead, the two kinds of spaces are inextricably linked with each other" (Bayne & Jandrić 2017, p. 14–15, as cited by Fawns, 2019)

• "Entangled pedagogy is collective, and agency is negotiated between teachers, students and other stakeholders" (Fawns, 2022).

• "It begins with a summary of two general interpretations of the postdigital: firstly, to understand the ‘post’ as meaning simply ‘posterior to’ the digital, suggesting a different stage in the perception and use of technology; and secondly, to consider the ‘post’ as signalling a critical appraisal of the assumptions" (Knox, 2019)

Fawns (2019) Postdigital Design and Practice, & An Entangled Pedagogy: Looking Beyond  the Pedagogy—Technology Dichotomy (2022) 

Knox, J. (2019) What Does the “Postdigital” Mean for Education? Three Critical Perspectives on the Digital, with Implications for Educational Research and Practice

• "More information is now gathered, collected, sorted, and stored about the everyday activities of individuals in the world than at any other point in human history."

• Digital systems extract, accumulate, and collate. These digital systems are pervasive, governing registration, financial services, research, communications and credentialing, as well as teaching. Even keystrokes and actions we believe we have deleted may be tracked or collected as part of a platform’s data profile. 

• The datafication of schools is witnessed through numerous software applications, devices, and platforms that have become ubiquitous in education. The multitude of computer based applicaations is collectively referred to as Education Technology or “EdTech” within the school communities and research. EdTech is an industry with a worldwide market exceeding $250 billion annually. This exponential growth is made possible by data. Algorithms, data mining, analytics, machine learning and AI have become some of the most significant technical developments and concepts of recent years. 

• The EdTech industry attracts substantial investment and facilitates development in the United States, promising cost savings and productivity efficiency. EdTech companies offer educators big data analysis by collecting and providing access to student information, assessment results, and business intelligence tools. (Rhoades, 2020)

• "Social, pedagogical, and administrative actions that may previously have been unseen or untraceable are now transformed into data that can be monitored, tracked, analysed, and optimised"

• "As Andrejevic notes in his interview piece (Andrejevic and Selwyn 2022), the logic of behavioural economics and ‘nudging’ inherent in automated media suppose that people’s behaviours can be internalised in ways that conform to a bounded model of the algorithmically rendered classroom. In this sense, automated technologies are concerned with exercising power over the actions and activities of the teacher, rather than the complete replacement of the teacher." 

Making sense of the digital automation of education, (Selwyn et al., 2022). 

Educators’ understandings of digital classroom tools and datafication: perceptions from higher education faculty, (Szcyrek et al., 2024).

• “As a preliminary definition, we can say that the digital economy refers to those businesses that increasingly rely upon information technology, data, and the internet for their business models” (Srnicek, 2016). 

• From the notion of surveillance capitalism. "Surveillance capitalism unilaterally claims human experience as free raw material for translation into behavioral data. Although some of these data are applied to product or service improvement, the rest are declared as a proprietary behavioral surplus, fed into advanced manufacturing processes known as “machine intelligence,” and fabricated into prediction products that anticipate what you will do now, soon, and later" (Zuboff, 2019)

• "we need to give careful thought to how firms such as Amazon, Microsoft, and Google act as powerful ‘gatekeepers’—both in economic terms and in terms of shaping the digitization of public services such as education" (Selywn et al., 2022)

• "These forms of technology—and the logics that underpin them—are now a significant aspect of the digitization of education, and therefore require our sustained attention. As with most aspects of the algorithmic landscape of everyday life, these are technologies that are quickly becoming woven into the digital infrastructure of education—and therefore increasingly ‘invisible and forgettable’ (Knott 2022), only revealing themselves when they impact on our lives in notably unfair, harmful, and obtrusive ways" (Selwyn et al., 2022)

Making sense of the digital automation of education, (Selwyn et al., 2022). 

Platform Capitalism, by Nick Srnicek (2016) 

The age of surveillance capitalism: The fight for a human future at the new frontier of power, by Shoshana Zuboff (2019)

"Since the 1990s, around the time political and social scientists turned their attention to documenting and explaining the technological, economic and cultural effects of globalisation (Bauman; Beck; Giddens), the term governance has been rearticulated within/across various academic disciplines to make possible new kinds of analyses and interpretations of a wide range of political, social and economic changes. This has in turn giving rise to a wide range of compounds:  

technocratic governance, financial governance, transnational governance, soft governance, hard governance, network governance, democratic governance, corporate governance, education governance, school governance, educational governance, therapeutic governance, global governance, international governance, intrastructural governance, multi-level governance, pluri-scalar governance, hierarchical governance, heterarchical governance, market governance, neoliberal governance, digital governance, philanthropic governance, meta-governance, governance by numbers, public governance, private governance, good governance, effective governance, community governance, stakeholder governance, self-governance, European governance, neurogovernance, local governance, psychological governance, pedagogic governance, collegial governance, higher education governance, epistemic governance, metrics governance, competitive governance, cooperative governance, collaborative governance, precision governance, research governance, centralised governance, decentralised governance, curriculum governance, mediatised governance, platform governance, welfare governance, mediative governance, regulative governance, participative governance, indigenous governance, bureaucratic governance, affective governance, academic governance, modernised governance, therapeutic governance, palliative governance, epistemological governance, inquisitive governance, urban governance, rural governance, neighbourhood governance, dialogic governance, discursive governance, competition governance, algorithmic governance, university governance, policy governance, comparative governance, state governance, syncretic governance, regulatory governance, and modern governance 

"Governance is also used to represent or stand in for various complex processes and relations where it has been described as an ‘art’ (Pataki, 57), a ‘mode’ (Milner, Browes, and Murphy, 228), a ‘technology’ (Papanastasiou, 415), and a ‘discourse’ (Sifakakis et al., 37). Moreover, governance is typically imagined through various organisational and geographical typologies, such as:

• levels (direct, midway, at a distance);

• sites (federal, state, regional, local, institutional, individual);

• tiers (regional schools commissioner, school governing body, board of trustees, local government);

• scales (hierarchy, market, network); and

• spaces/places (schools, hospitals, prisons)."

–What is governance? Projects, objects and analytics in education (Wilkins & Mifsud, 2024) 

Algorithmic Rights and Protections for Children

The MIT Press | DOI: https://doi.org/10.7551/mitpress/13654.001.0001

Publication date: 2023

"Essays on the challenges and risks of designing algorithms and platforms for children, with an emphasis on algorithmic justice, learning, and equity.

One in three Internet users worldwide is a child, and what children see and experience online is increasingly shaped by algorithms. Though children's rights and protections are at the center of debates on digital privacy, safety, and Internet governance, the dominant online platforms have not been constructed with the needs and interests of children in mind. The editors of this volume, Mizuko Ito, Remy Cross, Karthik Dinakar, and Candice Odgers, focus on understanding diverse children's evolving relationships with algorithms, digital data, and platforms and offer guidance on how stakeholders can shape these relationships in ways that support children's agency and protect them from harm. 

This book includes essays reporting original research on educational programs in AI relational robots and Scratch programming, on children's views on digital privacy and artificial intelligence, and on discourses around educational technologies. Shorter opinion pieces add the perspectives of an instructional designer, a social worker, and parents. The contributing social, behavioral, and computer scientists represent perspectives and contexts that span education, commercial tech platforms, and home settings. They analyze problems and offer solutions that elevate the voices and agency of parents and children. Their essays also build on recent research examining how social media, digital games, and learning technologies reflect and reinforce unequal childhoods."