Computer adaptive testing, big data and algorithmic approaches to education

Abstract

This article critically considers the promise of computer adaptive testing (CAT) and digital data to provide better and quicker data that will improve the quality, efficiency and effectiveness of schooling. In particular, it uses the case of the Australian NAPLAN test that will become an online, adaptive test from 2016. The article argues that CATs are specific examples of technological ensembles which are producing, and working through, new subjectivities. In particular, CATs leverage opportunities for big data and algorithmic approaches to education that are symptomatic of what Deleuze saw as the shift from disciplinary to control institutions and societies.

Keywords:

• Computer adaptive testing
• Big data
• assessment
• data infrastructure
• datafication