Learning to Live with Datafication

Educational Case Studies and Initiatives from Across the World

Luci Pangrazio, Julian Sefton-Green, Luci Pangrazio, Julian Sefton-Green

• Publisher: Routledge
• Year: 2022
• ISBN:
  9781000541663
• Edition: 1
• Topic: Education
• Subtopic: Research in Education

As digital technologies play a key role across all aspects of our societies and in everyday life, teaching students about data is becoming increasingly important in schools and universities around the world. Bringing together international case studies of innovative responses to datafication, this book sets an agenda for how teachers, students and policy makers can best understand what kind of educational intervention works and why.

Learning to Live with Datafication is unique in its focus on educational responses to datafication as well as critical analysis. Through case studies grounded in empirical research and practice, the book explores the dimensions of datafication from diverse perspectives that bring in a range of cultural aspects. It examines how educators conceptualise the social implications of datafication and what is at stake for learners and citizens as educational institutions try to define what datafication will mean for the next generation.

Written by international leaders in this emerging field, this book will be of interest to teacher educators, researchers and post graduate students in education who have an interest in datafication and data literacies.

1 Learning to live well with data Concepts and challenges

Luci Pangrazio and Julian Sefton-Green

DOI: 10.4324/9781003136842-1

Introduction

Digital technologies infuse virtually every aspect of life. From health tracking apps, social media and learning management systems, to the Internet of Things, traffic surveillance, government services, dating, work and education – many of our routines and practices are recorded and analysed somewhere in the world. Scholars and technology experts call this “datafication”. Datafication refers to the process in which actions and behaviours are translated into data that can be recorded, sorted or indeed commodified by governments and private companies. The consequences and implications of datafication are immense, extraordinary and unprecedented.

Governments have responded to these challenges in various ways. The European Union has enforced the General Data Protection Regulation (GDPR) to increase data protection and privacy and regulate public competition, while in Singapore the government is addressing “fake news” by taking control of the media. The use of data to manipulate democratic processes has come under scrutiny, most notably around the Cambridge Analytica “scandal” of 2016. While there has been intense concern over the integrity of democratic systems and public information, there has been equal scrutiny of privacy rights especially where they impinge on the security and safety of young people. In many countries around the world there are laws and agencies designed to protect young people, especially from the threats implicit to being online.

Educational responses to the magnitude and range of these challenges have differed around the world. In many respects datafication should be understood as a global phenomenon – not only because of the transnational nature of many of the private companies at work across the countries of the world (i.e., Google), but also because there are extraordinary similarities to the digitisation of everyday life despite different national cultures. In some countries, nationally sanctioned advisory agencies, such as Australia’s eSafety Commission, mix information, advice, and, where possible, regulation and scrutiny of digital activities to protect and uphold rights, safety and education.

However, at the level of school management, curriculum design and/or pedagogy there has not been the same degree of investment or classroom innovation. Some countries have attempted to support the development of online learning systems, while others have introduced social norms, such as the banning of mobile phones. Other individual schools or districts have used digital or other means of communicating with parents and the community to engage interest and support for initiatives that teach young people about the risks and opportunities posed by datafication.

This book collects approaches to teaching and learning about data and datafication from countries around the world. Each chapter explains an aspect of datafication and conceptualises the problem for educational purposes. The authors explore the pedagogic challenges in understanding how students might learn about the problems of data and living in a datafied society and how we might construct curriculum progressions to support deeper engagement. The focus is on methods, approaches, models and theories that conceptualise and implement ways of learning to live well with data. Although all sections of the population are engaged in these forms of learning, the attention in this book is on young people and especially on forms of school-aged education.

The datafication of everyday life

Attending school, joining sporting groups and socialising with friends now typically requires some kind of engagement with digital platforms, and this engagement generates personal data that can be used to profile, track and trace. Personal data refers to any information that can be directly attributed to an individual. Personal data can be drawn from a huge array of sources – from the seemingly insignificant mouse click through to the more expected information of date of birth, address and social security number. It can also take a variety of modes, including numbers, characters, symbols, images, electromagnetic waves, sensor information and sounds (Kitchin, 2014). Indeed, part of the problem in supporting people to understand and engage with digital data is that it is a rather nebulous concept that refers to so many seemingly different pieces of information. As Golumbia (2018, n.p.) explains, personal data is a “much larger and even more invasive class of information than the straightforward items we might like to think”. It includes not only what individuals voluntarily share with the platform, but also what can be inferred from this data through probability analytics. Indeed, personal data now drives a multibillion-dollar data broker industry (Couldry and Mejias, 2019; Zuboff, 2019).

There is a growing body of critical scholarship that documents how the collection of personal data not only invades personal privacy, but also, through recommendations, prompts and design trains young people into new routines that increase data generation (Chun, 2016; Langlois et al., 2015). This intensifies a whole host of nascent issues to do with profiling, prediction as well as providing a ready-made way to judge and assess others – for example, social media metrics now shape the way young people think about themselves and others (Gangneux, 2018; Pangrazio, 2019), or in the school domain how teachers and administrations use automated data collection to help gauge the capabilities of their students.

Data and datafication

Datafication is the transformation of digital interactions into a record that can be collected, analysed and commodified (Mayer-Schoenberger and Cukier, 2013). It is made possible by the capacity to capture and translate social phenomena into data and is integral to the business model and functioning of many digital platforms. For students, personal data and metadata is generated through the school-based platforms and social media platforms that they use throughout their day. In some instances, student may be aware of data being generated and captured, like when creating a profile on the school’s learning management systems (LMS), but in many others, they are not. For example, while a young person may not even be a Facebook user, if they have visited a site that has a Facebook ‘like’ button embedded, this third-party cookie can be used to track their online movements. Data have long been used to monitor and regulate populations; however, digital technologies have greatly expanded what can be turned into a data point.

While datafication is a new process, it is also just the next step in the long-standing trajectory towards quantification. Hacking (1990) argues that the drive to quantification has been underway since ‘populations’ were introduced for statistical analysis in the 17^th century. The reliance on numbers was seen as a way of ‘taming chance’ and providing some form of stability and security in a world that was rapidly changing. This mindset is evident everywhere today. In schools, the use of data may be marketed around optimising performance and managing risk, however, the reality involves new school logics based upon the dataveillance of teachers and students. This creates new routines and regimes for staff and students to follow, which is often characterised by a high degree of manual labour and the emergence of new power dynamics (Selwyn et al., 2021). At the same time, it is easy to see why it might be appealing to the school for the reassurance it can give to teachers and parents.

However, the collection of data about people has implications. Statistics leads to the construct of a ‘norm’ and mathematical notions of deviance, as well as the ability to predict risk. It both reinforces and intensifies the reliance on data-driven epistemologies (Kitchin, 2014) based upon comparison, pattern recognition, prediction and analytics. Through artificial intelligence and automation, the more ‘human’ skills of interpretation, reflection and evaluation are displaced. Most digital systems automate feedback (i.e., metrics), as well as curate and personalise content (i.e., recommendations and search). As a consequence, individuals are directed towards particular behaviours and practices, as ‘the self is mobilised and activated in response to the calculation to which it is exposed’ (Beer, 2016, p. 139). An important purpose of datafication is to enable digital systems to provide an experience that will keep the individual user engaged with the platform longer. Zuboff (2019) argues that datafication is a key tool in enacting ‘instrumentarian power’ – a new form of power enacted by governments and corporations that can shape and manipulate people in subtle and incremental ways.

Yet big data clearly has benefits for many different sectors in society including education, medicine and science. For example, if used effectively and ethically, data can be used to provide detailed feedback on student performance and provide new and promising insights into the learning process through learning analytics (Gasevic et al., 2015). Data has also become an essential part of modern medicine, providing better health profiles and predictive models that can be used to diagnose and treat disease (Schadt, 2015). As Bhargava et al. (2015) argue, data can also improve civic life. The increasing availability of open data has increased the potential to engage citizens through ‘grass roots’ innovation. This is dependent, of course, on citizens having the knowledge and skills to access and analyse open data sets. In principle, data can be used for civic empowerment and positive social change. All in all, digital data facilitates many everyday experiences and opportunities, enabling people to build knowledge, swap and share objects, and of course, participate in society.

However, datafication has political implications. Processing data is dependent on the creation of categories and norms, which are often based upon particular social and cultural assumptions. These are assumptions with long, problematic histories. For example, predictive analytics are used in the US to assist with child protection and support, with particular racial groups being unfairly targeted as a consequence (Eubanks, 2017). Without correction embedding digital tools in old systems of power and privilege intensifies social inequalities. For example, some families cannot afford high speed broadband, which means their children’s participation in school activities is constrained. Datafication therefore does not affect individuals equally with people of a particular race, religion, income, gender and social status unfairly targeted through data processing.

As data-driven epistemologies are seen as more objective and reliable, datafication changes how we understand social phenomena. It changes how we see ourselves and others shaping the kinds of behaviours and interactions that we engage in. Finally, it has become a new arena for long-standing social justice issues, with implications for decision-making, governance and power in civil society.

…and the responses to it

The challenges brought about by datafication have inspired a range of different responses. From ‘top-down’ government regulation of tech companies through to ‘bottom-up’ grass roots activism, all responses have a common focus on changing how data is being ‘done’ to individuals. More specifically, responses attempt to intercede at different points in the process of datafication – either by decreasing the amount of data that tech companies can collect through legal or technical means or coming up with alternative platforms that are not reliant on the commodification of personal data for their business model. What follows is a brief overview of three main responses to datafication: regulation; technical and tactical; and educational (see Pangrazio and Sefton-Green, 2020). We delineate between educational responses and educational research to explore not only what is being done in schools to support teachers and students develop their understandings of data, but also how the phenomenon is being researched and approached.

Regulation

The notion of rights – particularly digital rights – has been invoked in response to the challenges posed by datafication. In relation to data, the concept has two dimensions: first as individual human rights and second as property rights. In the first instance, a notion of human rights is unsettled by datafication because the rights an individual has in society – for example freedoms of movement, speech and so on – are not legally protected in the digital domain. Traditions from habeas corpus to Miranda rights in the US, therefore, do not govern our online interactions.

One response, which has been led by one of the authors in this collection, Sonia Livingstone, is to advocate for the digital rights of the child (Livingstone and Third, 2017). This response makes a strong case for bringing the 1989 UN Conventions on the Rights of the Child (UN CRC) to the digital context, arguing that the internet is typically thought of as a resource for adults and is reflected as such in policy, regulation and ideology. Drawing on key articles in the UN CRC, a special issue in the journal New Media & Society (2017), brought together researchers across different fields in the social sciences, to argue that the digital rights for children should cover both participation and provision, as well as protection. More recently, this has developed into the 5Rights Foundation, which seeks to make systemic changes to the digital world to ensure by ‘design and default…that children can thrive in a digital world’ (5RightsFoundation, 2020).

Regulatory responses seek to prevent unfair and unequal power relations that position the individual in a vulnerable relationship. In this way, they can be an effective reply to data justice issues, as well as encouraging a more interpretive and critical approach to datafied identities and interactions. The language of rights and regulation derives authority from being governed by principles of law that operate in the interests of th...

Table of contents

• Cover Page
• Half Title Page
• Title Page
• Copyright Page
• Dedication
• Contents
• List of illustrations
• List of Contributors
• 1 Learning to live well with data: Concepts and challenges
• 2 Datafication and the role of schooling Challenging the status quo
• 3 Turn off your camera and turn on your privacy: A case study about Zoom and digital education in South American countries
• 4 Data classes: An investigation of the people that ‘do data’ in schools
• 5 Educators’ data literacy: Understanding the bigger picture
• 6 Datafication, educational platforms and proceduralised ideologies
• 7 The tipping point in the platformisation of Dutch public education?: How to approach platformisation from a values-based perspective
• 8 “The Beatles with the lower score, it breaks my heart”: Framing a media education response to datafication and algorithmic recommendations in digital media infrastructures
• 9 Critical algorithm literacy education in the age of digital platforms: Teaching children to understand YouTube recommendation algorithms
• 10 Emerging from the shadows of datafication: A favourable turn for cultural studies
• 11 Children’s privacy and digital literacy across cultures: Implications for education and regulation
• 12 Conclusion: Learning to live better with data
• 13 Afterword: The future of datafication in education? Clouds, bodies and ethics
• Index