A Data-People-Theory Approach to Enhancing Student Advising: Findings from a Multi-institution Project

Student advising is gaining prominence with senior university staff in UK Higher Education, driven by the need to retain students and support successful outcomes across diverse groups. Drawing on initial findings from a cross-institutional experiential project, the paper explores institutional enhancement activities related to student advising through a data-people-theory model. Using purposive sampling, participants were invited to join the research because the first and second authors were aware that their institutions were in the process of or about to undergo, institution-wide projects to enhance advising. The project initially sought to explore whether McVitty and Maxwell’s (2024) data-people-theory model could provide a consistent framework for better understanding varied approaches to advising activity. An in-depth overview of the model and its constituent parts is provided, enabling readers to consider how they might use this same lens at their own institutions. Typical use cases include benchmarking existing advising systems and practices to better understand how their input components interact. Gaps in provision can be surfaced through an intentional consideration of the components and their interplay. The model can also be used to articulate a future desired state for advising that enhances student success. Project findings offer institutions a flexible framework for reviewing and enhancing student advising, drawing conclusions that can help other institutions consider how to proceed. A revised version of the data-people-theory model is also presented.