Towards learning analytics for students’ sense of belonging (Zoom)

Research has well-documented the importance of students’ sense of belonging in fostering their transition to higher education, engagement and success even beyond the degree (Araújo et al., 2014; Meehan & Howells, 2019; Allen et al., 2022). However, research in belonging has tended to draw on students’ self-reports. While there are validated instruments such as the Psychological Sense of School Membership, PSSM (Goodenow, 1993) to measure students’ belonging, the challenge lies in getting students to respond to these surveys, in order to monitor, track, and support students with respect to their belonging. Learning analytics may be able to provide a solution, by harnessing students’ digital traces, and then providing technology-mediated, personalised support to students. However, to date, there is little research in learning analytics for belonging. In this presentation, I will discuss the possibilities of capturing students’ ongoing sense of belonging through learning analytics, as well as personalizing support to students with respect to belonging.

Learning analytics may be able to provide a solution, by harnessing students’ digital traces, and then providing technology-mediated, personalised support to students. However, to date, there is little research in learning analytics for belonging.

In this presentation, Dr Lisa Lim will discuss the possibilities of capturing students’ ongoing sense of belonging through learning analytics, as well as personalising support to students with respect to belonging.