The Boolean Dilemma: Representing Gender as Data Type

Autor: Benedikt Pfülb, Natalie Kiesler
Rok vydání: 2021
Předmět:
Zdroj: Koli Calling
Popis: Unfortunately, the Boolean data type is still used in teaching and learning scenarios as default for the distinction of male or female gender. This paper focuses on the identification of the challenges associated with assigning binary gender identities as part of programming exercises. Due to an increasingly diverse society and computer science community, the authors advocate for new approaches, such as including aspects of diversity into the curriculum, exercises, educators’ mindsets and students’ socialisation in higher education. We also encourage the use of other data structures than the Boolean data type when referring or assigning gender identity, as both students and educators can benefit from an adequate and gender-sensitive CS education.
Databáze: OpenAIRE