The becoming-statistic: Information ontologies and computerized adaptive testing in education

Sellar, Sam & Thompson, Greg (2016) The becoming-statistic: Information ontologies and computerized adaptive testing in education. Cultural Studies <=> Critical Methodologies. (In Press)

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Abstract

This article examines how computerized adaptive testing functions in relation to learning in control societies. We first document the transition from static and discrete forms of statistical work that characterized Foucault’s disciplinary societies into the continuous, predictive analytics that have emerged as the powerful form of statistical work in Deleuze’s control societies. We then explore the function of information science ontologies in adaptive testing and learning applications from the perspective of Deleuze’s philosophical ontology. Working between these two conceptions of ontology enables us to open a critical space in which to posit the need for an alternative ontology of number in education. Focusing on the case of Pearson, the world’s largest edu-business, we consider how the “datafication” of education is presenting opportunities to exploit information assemblages for profit. The primary focus of analysis is Pearson’s Next Generation Assessment agenda, which focuses on the development and implementation of computerized adaptive testing within a broader digital learning environment. Next Generation Assessment is theorized as an information assemblage that functions according to an axiomatic modeling of numerical data enabling the production and communication of information throughout proliferating data infrastructures in education. We argue that the shift from “becoming a statistic” in disciplinary society to “the becoming-statistic” in control society is facilitating the development of digital learning platforms that risk limiting the conditions for learning in the creative sense of this term.

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ID Code: 94073
Item Type: Journal Article
Refereed: Yes
Keywords: Computer ontologies, Interoperability standards, digital data, testing, HERN
DOI: 10.1177/1532708616655770
ISSN: 1552-356X
Divisions: Current > QUT Faculties and Divisions > Faculty of Education
Copyright Owner: Copyright 2016 SAGE Publications
Deposited On: 29 Jun 2016 22:30
Last Modified: 20 Jul 2016 04:21

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