Embedding historical and contextual sensitivity in QuantCrit approaches to STEM identity research: implications for data collection and analysis techniques

Abstract

In this review, we build on accelerating interest in measuring and supporting ‘STEM identity’ in research, policy, and practice to consider how approaches to measurement and analysis could disrupt or perpetuate established marginalizing expectations of identifying as a STEM person. We discuss how guidance such as QuantCrit can inform conscious deviations from well-worn methodological paths. We contrast this approach with traditional outcome comparisons between those subjected to racist, sexist, classist, nativist, and ableist marginalization and those supported by the same structures. By situating this discussion in STEM identity, we explore what it means to critically measure and model a construct that ostensibly can broaden participation in STEM but which also offers a theoretical explanation for why marginalization persists. We offer recommendations, particularly encouraging STEM identity researchers such as ourselves to reconsider approaches to survey design.