Beyond the Gender Binary in Computing Education Research

Abstract

Mathematician Eugenia Cheng offers a fresh framework for thinking about the problem of the under-representation of women in STEM. Cheng's approach is grounded in her research field, category theory, which leads to her proposal that instead of focusing on a gender binary, we instead consider each person as being on a continuum from "congressive"(that is, focused on interdependence) to "ingressive"(focused on independence). The purpose of this poster is to consider the application of Cheng's framework to computing education by focusing on three main questions: If we base computing education research on this framework, what might that look like? What might we gain, and what might we lose? Cheng's framework applied to computing education research would change the methodology used in interventions that consider the participants' gender. Gains from Cheng's framework therefore include a way to research, analyze, and implement interventions in computer science education to improve representation that do not reify the gender binary and (further) marginalize non-cis-gendered students. However, adopting Cheng's framework would create several hurdles, including the need for a valid instrument to assess placement on the continuum. And the framework may well fail to rectify the problem of under-representation. Nonetheless, Cheng's framework, particularly in its ability to include all students, regardless of gender identity, is worth considering as a tool in computing education, not the least because it suggests a possible contrast to the status quo.