This paper examines visions of 'learning' across humans and machines in a near-future of intensive data analytics. Building upon the concept of 'learnification', practices of 'learning' in emerging big data-driven environments are discussed in two significant ways: the "training" of machines, and the "nudging" of human…

This paper argues that methods used for the classification and measurement of online education are not neutral and objective, but involved in the creation of the educational realities they claim to measure. In particular, the paper draws on material semiotics to examine cluster analysis as a 'performative device' that, to a significant extent,…

The generation and processing of data through digital technologies is an integral element of contemporary society, as reflected in recent debates over online data privacy, "Big Data" and the rise of data mining and analytics in business, science and government. This paper outlines the significance of digital data within education,…

The analysis of classroom observation data is seen as increasingly important in research on the impact of high-stakes language tests or new foreign-language programmes on students, teachers and other stakeholders. Video-recordings of language teaching and learning in classrooms impacted by such tests or programmes can provide revealing data,…