Abstract:

Science, Technology, Engineering and Maths (STEM) continues to discriminate against certain groups including women, disabled, those from low socioeconomic backgrounds and the racially minoritized both educationally and in employment (Science, Innovation and Technology Committee, 2022). In education, ethnically minoritized staff and students, for example, consistently demonstrate poorer outcomes than white staff and students (Science, Innovation and Technology Committee, 2022). Computing and computer science in the UK mirrors these disparities and the complexities in the causes of the gaps. Structural and social barriers, access to the subject, cost of study and the discipline only being for certain groups deters already minoritized groups from studying the subject (Oxford University, 2019-20). One major barrier reported by students relates to their experiences of belonging (Mejias, Pierre, et al, 2019). Stereotypes and student perceptions of what ‘traditional’ computer scientists ‘should be’ fuels these feelings (Barker, Hovey, and Thompson, 2014). Research shows a connection between a sense of belonging in a learning environment and a student’s concentration and ability to retain information. This session explores how the School of Computing and Communications at the Open University have been challenging narratives about who belongs in STEM learning and careers by destabilising stereotypes of what makes a STEM student/scholar to improving the student experience and outcomes. Participants will have the opportunity to discuss successful and unsuccessful strategies used to create inclusion including presenting positive role models, inclusive curriculum reviews, supported inductions and specialist workshops. They will be able to evaluate the strategies against their own providing a developmental critique whilst sharing best practice, exchanging ideas and exploring opportunities for collaboration.

This session is appropriate for practitioners of any discipline who are responsible for supporting student learning and who want to improve outcomes for students from minoritized backgrounds.

Keywords:

Inclusive practice, STEM, student outcomes, equality, diversity, inclusion, role models, induction, sense of belonging.