Eliminating Gender Bias in Computer Science Education Materials

Abstract

Low female participation in Computer Science is a known problem. Studies reveal that female students are less confident in their CS skills and knowledge than their male counterparts, despite parallel academic performance indicators. While prior studies focus on limited, apparent factors causing this lack of confidence, our work is the first to demonstrate how, in CS, instructional materials may lead to the promotion of gender inequality. We use a multidisciplinary perspective to examine profound, but often subtle portrayals of gender bias within the course materials and reveal their underlying pedagogical causes. We examine three distinct samples of established CS teaching materials and explain how they may affect female students. These samples, while not a complete display of all gender inequalities in CS curriculum, serve as effective representations of the established trends of male-centered representation, imagery, and language that may promote gender inequality. Finally, we present easily implementable, alternative gender equitable approaches that maximize gender inclusion.

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