Getting lost at the crossing? Tips for Assessing intersectional experiences

Getting lost at the crossing? Tips for Assessing intersectional experiences

Allison BrckaLorenz—Faculty and administrators are often tasked with creating holistic experiences for students upon arrival at college, so it is important to understand ways to assess the whole student. NSSE and FSSE researchers presented to participants at the 2019 Assessment Institute with factors to consider when quantitatively examining intersecting aspects of students’ identities, student characteristics, and collegiate endeavors. Starting with an overview of the Model of Multiple Dimensions of Identity (Jones & McEwen, 2000), attendees discussed challenges and strategies that move our understanding of students from a since or binary lens to one where students and their experiences are represented by multiple, intersecting identities.

Case studies using NSSE and FSSE data showed different methods for starting intersectional investigations including analyzing dichotomized demographics (by examining the teaching environment for STEM or non-STEM faculty for tenure-track and non-tenure-track faculty) or holding one demographic constant while looking within (by looking at stress for women of different racial/ethnic identifications and then by looking at Black students with different gender identities). A more statistically rigorous analysis included an example of using interaction terms in regression analyses by looking at the experiences of students with different sexual orientations, students with various racial/ethnic identities, and the unique experiences of LGBQ+ students with varying racial/ethnic identities. A final example looked at different strategies for creating groupings based on complex measures such as socio-economic status measures.

Discussion during the session focused on which strategies work best in certain situations, challenges in collecting identity-based data in rigid institutional software, and difficulties with getting buy-in from various stakeholders when intersectional data results in small populations. Researchers presented a final challenge for participants to consider with an example using more person-centered approaches to analysis that group people based on their experiences versus their demographic identities.

See more details from this session here.


Jones, S. R., & McEwen, M. K. (2000). A conceptual model of multiple dimensions of identity. Journal of College Student Development, 41(4), 405-414.