The Use of Learning Analytics in STEM over 4 years

Project leader(s): Tom OlneyCarlton Wood
Theme: Technologies for STEM learning
Faculty: STEM
Status: Archived
Dates: May 2022 to August 2024

Learning analytics is a rapidly expanding area of interest for many higher education institutions. Over the last decade the focus in this field has largely been on the technical challenges associated with collecting, storing and refining data in order for it to be presented to users in actionable visualisations. Much of this work has been accompanied by an underlying assumption that once presented learning analytics will lead to improvements that are not yet clearly defined. However, the practice of educators in using learning analytics has not been well studied. This study has used the Theory of Practice Architectures (TPA) as a methodology in order to describe the situated practice of learning analytics (what it means to ‘do’ learning analytics), and to explore the contextual arrangements that serve to enable or constrain that practice. Based on two sets of semi-structured interviews - separated by six years - of academics and academic-related staff from STEM this study provides insights into the evolution of learning analytics practice. The findings suggest that the establishment of reliable and trustworthy data, and its presentation, is only the first step in a long and ongoing process that requires serious and substantial support at the institutional level. To illustrate this, learning analytics is discussed in terms of the actions that it prompts, the language that characterizes practice, and the time and resources that are required to embed it into meaningful practice.