Exploring the Complex Social Spaces of Higher Education: On the Uses and Challenges of Geometric Data Analysis and Topological Approaches

Abstract

Relational thinking and spatial analyses have become highly relevant for higher education research. However, choices of research methods and specifically of statistical procedures do not often correspond to the epistemological underpinnings implied by relational perspectives. Against this background, this chapter illustrates the uses and challenges of geometric data analysis (GDA) for studying the complexities and dynamics of current spaces of higher education. GDA can be described as a set of statistical techniques that allow the identification, assessment and visualisation of complex relations in social science data. Using an investigation into the social topologies of first-year students as an example, we discuss the mathematical foundations, the step-by-step procedures of data analysis, the interpretation of results and strategies for integrating GDA into multimethod research designs. In sum, we argue that GDA does not only entail a comprehensive set of statistical instruments that permit visual analysis of relational structures, but also enables the systematic integration of qualitative and quantitative methods, hence supporting the development of innovative and coherent research designs and analytical strategies.

Citation

Mundt, F. and Horvath, K. (2018), "Exploring the Complex Social Spaces of Higher Education: On the Uses and Challenges of Geometric Data Analysis and Topological Approaches", Theory and Method in Higher Education Research (Theory and Method in Higher Education Research, Vol. 4), Emerald Publishing Limited, Leeds, pp. 103-123. https://doi.org/10.1108/S2056-375220180000004008