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This paper offers a framework for equitable instruction that emerged while designing a computer science course for students entering the sixth grade. Leveraging research from a range of fields, including sociology, mathematics education, and the learning sciences, we argue that in addition to material resources, such as rich course content and quality instruction, equity also depends on students' access to non-material resources, such as productive domain identities and peer relationships. We illustrate each dimension of the framework by describing in detail a core set of pedagogical practices implemented during a summer course.

Stereotypes of computer scientists are relevant to students' performance and feelings of belonging. While e↵orts exist to change these stereotypes, we argue that it may be possible to challenge a student's belief that stereotypes of computer scientists are relevant to whether they can become a computer scientist. In our previous work, we presented a model of five factors that influence students' decisions to major in computer science (CS). Data were collected from interviews with 31 students enrolled in introductory CS courses at two public universities in the United States. Here we elaborate on our grounded theory of one of these factors: how students assess their fit with CS. We describe how students measure their fit with CS in terms of the amount they see themselves as expressing the traits of singular focus, asocialness, competition, and maleness and how students make interpretations and decisions based upon these measurements. We found that students' interpretations were influenced by their attitudes toward the nature of stereotypes.

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