Modern Computer Science and Electrical Engineering curricula emphasise the importance of teamwork. Gender-composition of such teams is known to influence biases towards women in gender-mixed teams. Aiming in the long-term at reducing gender biases in engineering, in this proposal we focus on identification and validation of best-practices in gender composition of student teams. Moreover, given the significant share of international students in ICT programs in the Netherlands, as well as the interaction between nationality and gender we also study composition of student teams with respect to nationality. To address (potentially different) cultures and needs of engineering disciplines we consider both Computer Science (CS) and Electrical Engineering (EE). In this way we (a) will create awareness of teachers of the ways team composition affects performance and attitudes of students, and (b) reduce gender biases of future generations of students.
- A. Serebrenik (Full Professor, TU/e, CS)
- X. Long (Assistant Professor, TU/e, EE)
- G. Catolino (postdoc, TUD, CS)
- A. Zaidman (Full professor, TUD, CS)
- T. van Dijk (Assistant Professor, UT, EEMCS).
- 4TU CEE recognises the importance of the project proposed and has kindly agreed to assist with building the community and disseminating the results.