In addition to projects focusing on specific departments and groups of students, there are several cross-College projects exploring students’ sense of belonging.
Research has identified multiple domains of belonging, including academic and social, which can operate independently of each other. Further areas include students’ belonging in their environment, including their living space, geographical and cultural location, as well as their personal and mental space, capturing their well-being, attitudes, identity and personal interests (Ahn & Davis 2020).
Large-scale research has identified variations in sense of belonging across different groups of students, in terms of gender, ethnicity, social class, nationality and the intersections of these multiple identities (Mountford-Zimdars et al 2015; Thomas et al 2017). There are also gaps in belonging for students across different courses, particularly for those on professional courses (Arulampalam et al 2007; Holmegaard et al 2014).
One strand of work at Imperial to measure, track and support students’ sense of belonging is through the development of an academic dashboard. This provides academics with information to support their personal tutees as they navigate their course. Data from multiple sources, such as Registry and Blackboard is drawn together to offer a personalised view on how students are engaging with their course. This offers the opportunity for tailored support, advice and guidance to students.
Another strand of work takes a macro approach, drawing on learning analytics to explore patterns of students’ engagement within and beyond their course. This work explores large-scale anonymised data on how students are experiencing their courses, how students navigate on-line learning spaces and how they stay connected to the institution. Analysis also explores how different groups of students engage with their courses and the institution and any differential outcomes that students face. This work aims to feed into ways to support individual students, redesign curricula and inform pedagogical practices, as well as to provide information to help students understand and enhance their own learning.
Further work explores linking localised and large-scale data, particularly how to understand and meet the needs of students who are not widely represented in the community and may get lost in the analysis of data and a focus on numbers. This work also explores intersectionality—how students as individuals exist across several groups and how this impacts on their experience and outcomes.