Algorithmic governmentality and student subjectivities: a critical examination of learning analytics in higher education
Article / Journal
Author(s) / editor(s):
Hannes Hautz & Silvia Lipp
Year: 2026
Language(s): English
Abstract:
This mixed qualitative study uses "algorithmic governmentality" to examine how learning analytics shape student subjectivities among 103 master's students in Austria. Findings show ambivalent responses—enthusiasm, resignation, anxiety—where analytics encourage self-regulation, reduce reflexivity, align behavior with data-driven norms, and risk reproducing educational inequalities. Yet students’ critical engagement also offers possibilities for disruption and reflexive inquiry.
https://doi.org/10.1080/17439884.2026.2618762
Post created by: Virginia Signorini