Knowing the (Datafied) Student: The Production of the Student Subject Through School Data

Selwyn, Neil; Pangrazio, Luci; Cumbo, Bronwyn

doi:10.1080/00071005.2021.1925085

Cited by 25 publications

(14 citation statements)

References 31 publications

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“…Yet, the idea that automation in education is a paradigm shift toward the better has been increasingly challenged within the social sciences (e.g., [12]). Researchers conducting situated research in schools have convincingly shown that schools are complex spaces and new apps, such as PGBL, sit within and interact with preexisting learning ecologies, infrastructures, and human networks that shape how PGBL is ultimately used and its emergent benefits [11], [13], [18].…”

Section: Reflections On Personalizedmentioning

confidence: 99%

Reflections on Personalized Games-Based Learning: How Automation Is Shaped Within Everyday School Practices

Vasalou

2022

IEEE Technol. Soc. Mag.

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Section: Reflections On Personalizedmentioning

confidence: 99%

Reflections on Personalized Games-Based Learning: How Automation Is Shaped Within Everyday School Practices

Vasalou

2022

IEEE Technol. Soc. Mag.

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“…', a question she has visited several times throughout her writing (e.g., Sachs, 2001Sachs, , 2003. Many critical scholars have similarly argued that cultures of performativity and accountability have had a profound influence on how teacher professionalism is defined, as well as what is required to either improve the professional judgment of teachers or protect teachers' professional autonomy (see Biesta et al, 2015;Mockler & Stacey, 2021;Selwyn et al, 2021). Within this broad coalition, the teacher is often positioned as an actor who is affected by, but who also has agency to interpret and respond to, policy in different ways.…”

Section: The De-/re-and New Professionalism Of Teachersmentioning

confidence: 99%

“…What is clear from the past decade of critical research is that 'good teaching' has become almost entirely defined by metrics that can be captured and reported via digital techniques (Lewis & Holloway, 2019;Selwyn et al, 2021;Taubman, 2010). What is less clear, however, is how various theoretical understandings of teachers and teaching have led to subtly and profoundly different claims about the effects of such quantified discourses and trends.…”

Section: Introductionmentioning

confidence: 99%

Teachers and teaching: (re)thinking professionalism, subjectivity and critical inquiry

Holloway

2021

Critical Studies in Education

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The collection of papers presented in this issue of Critical Studies in Education adds to the expansive body of work on teachers and teaching. Collectively, the papers draw our attention to new ways the field is problematising the emerging and evolving conditions that shape the work, lives and identities of teachers. With this editorial introduction to the issue, I not only summarise the various themes of the collection, but also offer a provocation that I hope will inspire new questions moving forward. As critical researchers, we have an obligation to challenge taken-for-granted assumptions -not only by looking outwards at the policymakers, edu-businesses, and intergovernmental agencies (e.g., the Organisation for Economic and Co-operation Development [OECD]), but also by looking inwards and challenging our own assumptions about power, discourse and subjectivity. The authors in the special issue take up both challenges in their geographically diverse accounts of 'the teacher' and 'teaching', demonstrating what it means to do critical research well.

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“…In this discourse, the limited capacity of teachers can be circumvented with advanced decision‐making algorithms. This assumption, however, is increasingly being questioned by researchers drawing from theoretical orientations and empirical approaches from science and technology studies (STS; e.g., Bayne, 2015; Eynon & Young, 2020; Selwyn et al, 2021; Wajcman, 2017). By challenging the idea of education technology as a neutral tool in the service of teachers and administrators, many of these studies reveal complex entanglements between social and material interactions and problematise causal relations and effects between technology on one side and behavioural outcomes on the other (e.g., Eynon & Young, 2020; Knox et al, 2020; Perrotta & Selwyn, 2019).…”

Section: Introductionmentioning

confidence: 99%

Still w(AI)ting for the automation of teaching: An exploration of machine learning in Swedish primary education using Actor‐Network Theory

Sperling

Stenliden

Nissen

et al. 2022

Euro J of Education

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Machine learning and other artificial intelligence (AI) technologies are predicted to play a transformative role in primary education, where these technologies for automation and personalization are now being introduced to classroom instruction. This article explores the rationales and practices by which machine learning and AI are emerging in schools. We report on ethnographic fieldwork in Sweden, where a machine learning teaching aid in mathematics, the AI Engine, was tried out by 22 teachers and more than 250 primary education students. By adopting an Actor-Network Theory approach, the analysis focuses on the interactions within the network of heterogeneous actors bound by the AI Engine as an obligatory passage point.The findings show how the actions and accounts emerging within the complex ecosystem of human actors compensate for the unexpected and undesirable algorithmic decisions of the AI Engine. We discuss expectations about AI in education, contradictions in how the AI Engine worked and uncertainties about how machine learning algorithms 'learn' and predict. These factors contribute to our understanding of the potential of automation and personalisation-a process that requires continued re-negotiations. | 585 SPERLING et al. 1 | INTRODUC TI ON VLADIMIR: A-. What are you insinuating? That we have come to the wrong place? ESTRAGON: He should be here. VLADIMIR: He did not say for sure he'd come. ESTRAGON: And if he does not come? VLADIMIR: We'll come back tomorrow. ESTRAGON: And then the day after tomorrow.

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Knowing the (Datafied) Student: The Production of the Student Subject Through School Data

Cited by 25 publications

References 31 publications

Reflections on Personalized Games-Based Learning: How Automation Is Shaped Within Everyday School Practices

Reflections on Personalized Games-Based Learning: How Automation Is Shaped Within Everyday School Practices

Teachers and teaching: (re)thinking professionalism, subjectivity and critical inquiry

Still w(AI)ting for the automation of teaching: An exploration of machine learning in Swedish primary education using Actor‐Network Theory

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