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Netflixing Human Capital Development: Personalized Learning Technology and the Corporatization of K-12 Education

Authors :
Roberts-Mahoney, Heather
Means, Alexander J.
Garrison, Mark J.
Source :
Journal of Education Policy. 2016 31(4):405-420.
Publication Year :
2016

Abstract

Advanced by powerful venture philanthropies, educational technology companies, and the US Department of Education, a growing movement to apply "big data" through "learning analytics" to create "personalized learning" is currently underway in K-12 education in the United States. While scholars have offered various critiques of the corporate school reform agenda, the role of personalized learning technology in the corporatization of public education has not been extensively examined. Through a content analysis of United States Department of Education reports, personalized learning advocacy white papers, and published research monographs, this paper details how big data and adaptive learning systems are functioning to redefine educational policy, teaching, and learning in ways that transfer educational decisions from public school classrooms and teachers to private corporate spaces and authorities. The analysis shows that all three types of documents position education within a reductive set of economic rationalities that emphasize human capital development, the expansion of data-driven instruction and decision-making, and a narrow conception of learning as the acquisition of discrete skills and behavior modification detached from broader social contexts and culturally relevant forms of knowledge and inquiry. The paper concludes by drawing out the contradictions inherent to personalized learning technology and corporatization of schooling. It argues that these contradictions necessitate a broad rethinking of the value and purpose of new educational technology.

Details

Language :
English
ISSN :
0268-0939
Volume :
31
Issue :
4
Database :
ERIC
Journal :
Journal of Education Policy
Publication Type :
Academic Journal
Accession number :
EJ1101669
Document Type :
Journal Articles<br />Reports - Research<br />Information Analyses
Full Text :
https://doi.org/10.1080/02680939.2015.1132774