The Dataveillance and Care in Teachers’ Work with Early Warning Systems

Abstract

It has now become a widespread practice in both public and private organisations to analyse data collected through digital systems and tools. Datafication in schools has resulted in additional work tasks for teachers and an increased level of accountability on their part. One of these data-work-related tasks of teachers is to proactively recognize students who may be at risk of dropping out of school and help them. Machine learning holds significant promise in the creation of advanced early warning systems (EWS) for predicting such student dropouts. Such systems are in line with a positive discourse supporting teachers’ effective decision making and a deeper understanding of student behaviour. In contrast, critical scholars raise concerns about the impact of data-driven practices in education on the teaching profession. This study adds to this body of literature by exploring how teachers are regulated by and regulating EWS as part of their work practice.
In this study as part of a larger working life funded project, we focus on one digital tool used in Swedish upper secondary schools called StudyBee, integrated with Google Classroom and connected to the Swedish National Agency for Education. We conducted a combination of ethnographic methods such as desktop research of application’s website and social media posts to gain a deeper knowledge on the StudyBee’s Graphical User Interface, interviews with teachers and principals, as well as go-alongs with teachers to understand their interactions with EWSs. Based on Decuypere’s (2021) topological framework, we analyse what is happening on, with, behind, and beyond EWS.
To argue that teacher work is shaped by accountability mechanisms, we use a critical perspective on teacher work within the digital platform/accountability discourse, aiming to reveal underlying power dynamics. We apply the concept of dataveillance (datafied surveillance, Clarke in Lyon, 2022) to illustrate how power operates, encouraging teachers to self-regulate in alignment with school accountability. Furthermore, we utilize the concept of care (Zakharova & Jarke, 2022) to understand technology-related aspects and care for students.