Categorizing Research on Identity in Undergraduate Computing Education

Researchers in education have explored identity constructs to solve a variety of problems such as improving retention, ameliorating diversity and inclusion, fostering learning, and gauging decision-making. However, literature in social sciences describes identity research as often fragmented, with researchers often building their work on siloed factions in identity literature. This paper aims to build a categorization model for classifying types of papers on identity in computing education research (CER). We categorized 55 papers that either investigated identity formation of students in computing undergraduate degree programs or suggested relationships of other constructs to identity using a systematic literature review. We first explored trends in the types of papers with respect to their demographics and then categorized the papers based on semantics and contributions using inductive content analysis. We observed a growing interest in identity over the last five years. The types of papers on identity in CER fell into two themes: identity-centric studies and non-identity centric studies. These themes included six categories of papers that described identity, assessed identity formation, measured identity construct, studied the influence of identity on a factor, implied another construct as identity, and inferred relationships of other constructs to identity. We shed light on our categorization scheme, provide a framework for positioning future research, and discuss opportunities for future work on identity in computing. Our model can support researchers to position their work or find appropriate literature when investigating work related to identity in computing at the undergraduate level.