This research examines the role of virtual identities in students' learning core computational principles. Women and many ethnic minority groups are underrepresented in science, technology, engineering, and mathematics (STEM) professions in the United States. Increasingly, computational skills are required for entry into any of the STEM fields. Identifying effective and innovative means of teaching computational skills is a critical contribution to this national challenge. This research builds on the evidence that stereotype threats can undermine the learning process for women and ethnic minorities. Using computer science learning software developed at MIT with previous NSF funding, this work examines the role that virtual identities can play in improving student learning in computer science specifically and broadening participation in the field generally.

This project uses computational and qualitative methods to study the roles that virtual identities, avatars, can play in students' learning computer science. It centers on three core operational pillars: 1) deployment of a computer science learning intervention for diverse middle and high school students that draws on students' sociocultural identities and generative themes to agitate awareness of core concepts, problem solving and thinking in topics including critical sections of Exploring Computer Science; 2) characterization of the relationship between students' virtual identities and their actual sociocultural identities to develop a taxonomy of virtual identity types and a rubric for describing how students use and relate to their virtual identities; and 3) identification of the impacts of different avatar types on students' performance.