Datafixation of education

Abstract

This article problematizes the datafication of education through the concept of datafixation—a wordplay that combines datafication and fixation. The article showcases how the datafication of education presents compelling arguments about the importance and usefulness of data, while remaining silent about the negative consequences of reducing students, learning, teaching, and education to superficial indicators. Such a one-sided view meets the criteria of fixation as an unhealthy attachment. I will also demonstrate that datafixation is not limited to any particular agents, technologies, or educational contexts but, like datafication, is a phenomenon that encompasses various fields and permeates different societal layers from global educational policies to classroom activities. Thus, throughout the article, I will provide examples from various sources, including edtech companies’ materials, policy documents, and scholarly articles, to illustrate that they share similar views and rhetoric. Diversity is also evident in the types of data technologies —such as facial recognition technology, learning management systems, and national continuing education platforms— that this paper concretizes datafixation with.