Datafication Of Education Research Articles

Data infrastructuring in schools: New forms of professional edu-data expertise and agency

The digitalisation and datafication of education has raised profound questions about the changing role of teachers’ educational expertise and agency, as automated processes, data-driven analytics and accountability regimes produce new forms of knowledge and governance. Increasingly, research is paying greater attention to the significant role of digital intermediaries, ‘in-between’ edtech or State authorities and the classroom itself, in educational transformations. School data infrastructures, understood as comprising diverse sociomaterial elements including teachers, data, software, standards and pedagogical practices, is one such intermediary through which teacher expertise and agency is reconfigured. In this paper, I focus on teachers’ involvement in processes of data infrastructuring in which people, platforms, systems and tools come together to create, enable and maintain data flows. Drawing on a sociomaterial ethnography of a secondary school in England, I analyse the work of a school data office in the behind-the-scenes work of data infrastructuring. The findings detail the significant labour and expertise involved in data infrastructuring, the dynamic, expanding and bespoke nature of the school data infrastructures that emerged, and processes of decontextualising and recontextualising numbers. The paper argues that the work of data infrastructuring undertaken by and through the school data office was an intermediary process which worked to both de-professionalise and re-professionalise teachers in new ways. In the process, this created new kinds of educational data experts and expertise, who gained significant influence and power within and beyond the school, both challenging and reinforcing existing organisational and governing power flows.

Researching In/Visibilities and Data Practices in Education

What is made in/visible in datafied educational settings? How are in/visibilities entangled with data practices in schooling? In this contribution, we provide an overview of recent literature on digital technologies and datafication of education and consider four kinds of interrelations between in/visibilities and data practices: decontextualisation, in/visibilising of data work, black-boxing, and fore- or backgrounding. Scoping some examples of research that capture aspects of invisibility and visibility, we reflect on conceptual and methodological underpinnings of how to study in/visibilities and data practices in education.

Does learning how to use data mean being motivated to use it? Effects of a data use intervention on data literacy and motivational beliefs of pre-service teachers

BackgroundIn times of expanding datafication in education, data-based decision making (DBDM) has become a crucial part of teaching and data literacy and motivational beliefs about data use are important preconditions of teachers’ data use. However, data use is not yet part of most teacher education programs. AimsThe present study investigated the effects of a short and easily implementable online intervention on pre-service teachers’ data literacy and their motivational beliefs about data use. SamplesWe conducted two studies with pre-service teachers: in the pilot (Study 1), the structure of motivational beliefs about DBDM was investigated (N = 34). In Study 2 (the main study), the effects of the intervention were examined (N = 136). MethodsThe study was designed as a randomized controlled trial with a wait list control group. The intervention focused on building the basic concept of data literacy with emphasis on data analysis and different types of data, such as assessment and self-evaluation data. ResultsStudy 1 revealed a three-factor structure of motivational beliefs about DBDM. The intervention in study 2 showed a strong positive effect on data literacy test scores and self-efficacy. On average, pre-service teachers reported positive motivational beliefs about DBDM. However, we found evidence for null effects regarding changes in motivational beliefs in the value components cost and enjoyment. ConclusionsThe intervention has the potential to foster aspects of data literacy and self-efficacy about DBDM but not value components of beliefs about DBDM in general.

One thing can be more than one thing: a comparative study of the teacher professionalization app ‘TeacherTapp’

ABSTRACT This article analyses the smartphone application TeacherTapp that is used to collect and disseminate information on teachers’ views on education and their classroom practices. The research takes as its object of analysis the use of TeacherTapp in England and Flanders. We analyze what TeacherTapp is, how it relates to a given localized community in its form and function, as well as how it impacts education by re-shaping discourse on teaching. We find that this technology is a ‘multiple enactment’ that is articulated, used, and viewed differently between England and Flanders as well as in different contexts of use. We furthermore find that this multiple enactment centers on the complexities of the participatory data streams’ flowing from, and generated by, the app. We conclude that TeacherTapp enables new forms of participatory datafication in education that constitutes new modes of enacting teachers’ professional voice as a teacher professionalization app.

Technical agonism: embracing democratic dissensus in the datafication of education

ABSTRACT This paper interrogates whether technical democracy is well-suited to contend with possible technical controversies, including the increasing prevalence of EdTech in public schooling. Drawing across Habermasian ‘deliberative democracy’ that seeks consensus-derived resolution, as well as more agonistic approaches that embrace conflict as the means for pursuing pluralistic values, we use this paper to problematise technical democracy for its potential to produce agonistic and pluralistic im/possibilities. Drawing on case studies developed from our previous research into digital platforms and infrastructures, we consider what an alternative to technical democracy might offer towards realising democratic ideals through what we call technical agonism. Using these thinking tools, we argue that a move towards technical agonism would centre dissension and scepticism as fundamental features of liberal democratic institutions, while also providing opportunities for schooling to be reimagined in ways that are more democratic and ethical.

The Politics of Inequalities in Education: Exploring Epistemic Orders and Educational Arrangements of Durable Disadvantaging

The durability of educational inequalities marks a key problem for research and politics alike. Why do unwanted patterns of social sorting and disadvantaging in education prove so persistent, despite decades of research, debates, and reforms? This thematic issue of Social Inclusion aims to further our understanding of the factors and mechanisms underlying this persistence by putting the manifold entanglements of politics, inequalities, and social research centre stage. The collected articles inquire into various facets of this interplay, from the history and politics of the statistical quantification of educational inequalities to the political embedding of everyday pedagogical practices. The contributions cover a wide range of fields and topics, from non‐formal education to school and higher education, from social selectivity in gifted education to subject formation in vocational education. Two strategic anchor points emerge from the collected articles for exploring and analyzing current arrangements of educational inequalities: (1) political and pedagogical epistemic orders and (2) educational arrangements that structure educational processes and situations. Ongoing social and political transformations—including the digitization and datafication of education and changing forms of governance—underline the pressing need for further research along these lines.

An Early Warning System to Detect At-Risk Students in Online Higher Education

Artificial intelligence has impacted education in recent years. Datafication of education has allowed developing automated methods to detect patterns in extensive collections of educational data to estimate unknown information and behavior about the students. This research has focused on finding accurate predictive models to identify at-risk students. This challenge may reduce the students’ risk of failure or disengage by decreasing the time lag between identification and the real at-risk state. The contribution of this paper is threefold. First, an in-depth analysis of a predictive model to detect at-risk students is performed. This model has been tested using data available in an institutional data mart where curated data from six semesters are available, and a method to obtain the best classifier and training set is proposed. Second, a method to determine a threshold for evaluating the quality of the predictive model is established. Third, an early warning system has been developed and tested in a real educational setting being accurate and useful for its purpose to detect at-risk students in online higher education. The stakeholders (i.e., students and teachers) can analyze the information through different dashboards, and teachers can also send early feedback as an intervention mechanism to mitigate at-risk situations. The system has been evaluated on two undergraduate courses where results shown a high accuracy to correctly detect at-risk students.

The datafication of higher education: discussing the promises and problems

ABSTRACT A common recommendation in critiques of datafication in education is for greater conversation between the two sides of the (critical) divide – what might be characterised as sceptical social scientists and (supposedly) more technically-minded and enthusiastic data scientists. This article takes the form of a dialogue between two academics representing these different perspectives – Dragan Gasevic (a data scientist who is one of the founders of the ‘learning analytics’ field) and Neil Selwyn (a social scientist and long-time critic of educational technology). Over the course of a six-month email exchange, we explore various arguments for and against the datafication of higher education. Thus, we are able to add a computational dimension to well-worn social criticisms of data representativeness, reductionism and injustice, as well as exploring social tensions inherent in technical claims to data-based precision, clarity and predictability. Crucially, these exchanges allow us to explore ways in which our two viewpoints converge, and therefore highlight opportunities for productive inter-disciplinary exchange and collaboration.

Centering complexity in ‘educators’ data literacy’ to support future practices in faculty development: a systematic review of the literature

ABSTRACT As algorithmic decision-making and data collection become pervasive in higher education, how can educators make sense of the systems that shape life and learning in the twenty-first century? This paper outlines a systematic literature review that investigated gaps in the current framing of data and faculty development, and explores how these gaps prevent the formulation of potential pathways and principles for fostering educators’ data literacy. The analysis of 137 papers through classification by relevant categories and key word mapping shows that there is little attention on higher education teachers. It also makes clear that most approaches to educators’ data literacy address management and technical abilities, with less emphasis on critical, ethical and personal approaches to datafication in education. The authors conceptualize this situation as a ‘complicated’ approach to data literacy in the academic profession, as opposed to a complex vision which would bundle management and technical skills together with a critical, systemic approach to professional learning and data.

Editorial: the datafication of education

The increasing datafication, in particular the availability of data and corresponding algorithms introduces new means to measure, capture, describe and represent social life in numbers. The educati...

Cruel optimism in edtech: when the digital data practices of educational technology providers inadvertently hinder educational equity

ABSTRACTAs digital data become increasingly central to education, hopes for educational equity are pinned more strongly on educational technology providers. This paper examines the data practices of edtech providers who are not simply making token gestures towards justice and equality. Drawing on ethnographic interviews and Berlant’s notion of cruel optimism, it presents three data stories. The paper suggests that datafication in education provides a showcase of cruel optimism, i.e., when the object of desire is blocking one’s flourishing. The conclusion considers the constitutive paradoxes of datafied education, and implications for the current phase of edu-technical transformation.

The Datafication of Learning: Data Technologies as Reflection Issue in the System of Education

Like other parts of the social system, education is becoming an information-driven venture: data technologies pervade all levels of the system. This datafication of education seems to take place alongside a general turn to learning that Gert Biesta has called learnification: a progressively singular focus on the manipulable features of individual learning in education. Given rapidly rising levels of datafication, it seems timely to take up Luhmann and Schorr’s contention that education entails a technology deficit and discuss datafication as reflection issue in the system of education. Against their argument that human learning is not amenable to a technology, I develop the counter-argument that data technologies are replacing human learning outright with data at the level of organisation. Data thus present a concretely digital form of what Raf Vanderstraeten has called education as an ersatz order. In a data-driven form of organising education, human dimensions of learning become secondary to a systemic dimension: making learning visible as data and so susceptible to databased manipulation. The text treats school-wide positive behaviour support interventions as an evidence-based exemplar of this trend towards datafication in the system of education.

Contributors

Contributors

Education policy, globalization, commercialization: An interview with Bob Lingard by David Hursh

In this interview with David Hursh, Bob Lingard comments on his current and/or recently completed research projects in respect to new modes of global governance in schooling and the complementarity between international large scale assessments and national testing. He also looks at a project that, in conjunction with school leaders, teachers, students, and community, developed an alternative mode of educational accountability to the currently dominant, simple, top-down, test-based mode. Here schools and their communities would be enabled to give an account of their multiple achievements of various kinds and draw on qualitative, as well as quantitative data. Another project has focused on the ways in which datafication in education opens up spaces for profit-motivated edu-businesses. Here data infrastructures are seen to actually structure schooling systems in particular ways and also work in networked governance across edtech companies and state actors. The final project considered is funded by a teacher union and documents the extent and nature of commercialisation of public schooling in Australia, what enables this, and teachers' and school leaders' attitudes to commercialisation.