The “governance by numbers” logic has become the dominant mode of governance in the education sector (Neumann, 2021), turning it into “one of the most noticeable domains affected by datafication” (Jarke & Breiter, 2019: 1). In the recent years, many scholars have further argued for the need to adopt a precision education approach (Luan & Tsai, 2021) that would allow to remedy obsolete and dysfunctional education systems (Davies, Eynon, & Salveson, 2021). In 2020, Estonia announced that it has started building AI-driven personalised learning path infrastructure in an effort to become the first country, where personalised education is enabled as a public system. The Estonian Education Strategy for 2021-2035 envisions that the personalised learning infrastructure would provide teachers with detailed diagnostics about their students, and provide students with an active role in crafting their futures by allowing them to choose what, when and with whom they learn. Considering that news media outlets act as governing actants of meaning, and play a prominent role in setting the agenda of any public discourse, the present study systematically maps dominant media discourses surrounding the national personalised learning pathways initiative. Our goal was to explore how different agents involved in the process – teachers, students, school officials, policy makers, representatives of the educational technology industry and governance of education – promote, justify or problematise this infrastructure initiative. In our analysis, we applied the critical discursive psychology approach (Locke & Budds, 2020) to news articles (N= 127) published in national media from 2019 to 2022. Our preliminary findings raise three main points of consideration. Firstly, the attitudinal shift towards what we call datatime reflects a speeding up of communication within the school ecosystem. This often discursively relegates central school agents – students and teachers – to secondary roles in comparison with their datafied representations. Secondly, whilst promoting a shift towards datatime, inadequate consideration is given to consequences from relevant school agents’ rapidly expanding dataspaces, i.e., the information about individuals to become available for mass-scale processing. Thirdly, the combination of promoting a shift towards datatime and the ensuing expansion of indviduals’ dataspaces, personal learning paths increase the extent to which the meta-agentic ‘school’ follows students around both outside and beyond the school itself. With this purview extension in mind, we conclude that, with respect to personalised learning paths, ‘the school goes to you’.

Davies, H. C., Eynon, R., & Salveson, C. (2021). The Mobilisation of AI in Education: A Bourdieusean Field Analysis. Sociology (Oxford), 55(3), 539-560. doi:10.1177/0038038520967888 Jarke, J., & Breiter, A. (2019). Editorial: the datafication of education. Learning, Media and Technology, 44(1), 1-6. doi:10.1080/17439884.2019.1573833 Locke, A., & Budds, K. (2020). Applying critical discursive psychology to health psychology research: a practical guide. Health psychology & behavioral medicine, 8(1), 234-247. doi:10.1080/21642850.2020.1792307 Luan, H., & Tsai, C.-C. (2021). A Review of Using Machine Learning Approaches for Precision Education. Educational technology & society, 24(1), 250-266. Neumann, E. (2021). Setting by numbers: datafication processes and ability grouping in an English secondary school. Journal of Education Policy, 36(1), 1-23. doi:10.1080/02680939.2019.1646322