Our research stream into Belonging Analytics has been putting a new platform through its paces in a pilot study…
We’re delighted to share a new development in our Belonging Analytics research program, after piloting the SenseMaker® platform.
- We design a SenseMaker framework grounded in theories of belonging, to identify key dimensions, indicators, and factors of belonging.
- Story prompts invite students to share a story or an experience that made them feel that they belong or do not belong to the university (anonymous)
- Students then use SenseMaker’s innovative visual triads, dragging the dot in the triangle to the position that feels right to them. This is in effect coding their story quantitatively, producing aggregate analytics.
Lim, L.-A. and Buckingham Shum, S. Degrees of Belonging: Gaining insights into university students’ belonging through theory-informed learning analytics. In Companion Proceedings, 15th Int. Conf. Learning Analytics & Knowledge (Dublin, IRE, 2025)
Poster PDF: Degrees of Belonging: Gaining insights into university students’ belonging through theory-informed learning analytics
This poster reports ongoing work to leverage learning analytics for enhancing students’ sense of belonging in higher education. Despite the importance of belonging for student engagement, there is a significant research gap in how to monitor and support students’ belonging throughout their degree programs. Using an innovative, theory-informed learning analytics approach, we conduct a study to gather and analyze both quantitative and qualitative data on students’ belonging at scale via the SenseMaker® tool. This platform allows respondents to share narratives (referred to as ‘stories’) and then code these using signifiers grounded in theories of belonging. Currently conducted at an institution in Australia, we invited in-degree students across the university to share their stories of belonging (or alienation). The poster presents preliminary findings from the collected data and discusses possible interpretations and future directions, contributing to the emerging subfield of Belonging Analytics.