Moulding student emotions through computational psychology: affective learning technologies and algorithmic governance

Citation

Williamson B (2017) Moulding student emotions through computational psychology: affective learning technologies and algorithmic governance. Educational Media International, 54 (4), pp. 267-288. https://doi.org/10.1080/09523987.2017.1407080

Abstract
Recently psychology has begun to amalgamate with computer science approaches to big data analysis as a new field of ‘computational psychology’ or ‘psycho-informatics,’ as well as with new ‘psycho-policy’ approaches associated with behaviour change science, in ways that propose new ways of measuring, administering and managing individuals and populations. In particular, ‘social-emotional learning’ has become a new focus within education. Supporters of social-emotional learning foresee technical systems being employed to quantify and govern learners’ affective lives, and to modify their behaviours in the direction of ‘positive’ feelings. In this article I identify the core aspirations of computational psychology in education, along with the technical systems it proposes to enact its vision, and argue that a new form of ‘psycho-informatic power’ is emerging as a source of authority and control over education.

Keywords
affective computing; big data; biometrics; computational psychology; psycho-informatics; social-emotional learning

Journal
Educational Media International: Volume 54, Issue 4

• WilliamsonB_Moulding student emotions_postprint_2017.pdf