Abstract

This presentation draws on evidence of how an experimental intervention programme in UK higher education, which involved experiential learning, resulted in improved opportunities for women to enter careers in data science. The case study used is from The University of Manchester where a Data Fellows programme was pioneered. Building on the teaching of statistics in undergraduate curricular in social science and humanities subjects, students were given the opportunity to apply to undertake experiential learning in the workplace. The programme required them to be on eligible social science and humanities degrees and to have taken statistical classes which were applied, rather than theoretical, in design. Working with real world data – from polling data to official statistics – teaches students how empirical data can be used to examine complex social research questions. All classes are taught through the lens of the substantive social science subject being studied (e.g. sociology, politics, criminology). Combining these taught statistical skills with applied learning in the workplace through a paid data fellowship programme enabled students to out their statistical skills into practice and create connections, skills and knowledge that they bring back to their studies. Of the 373 students who have undertaken data fellowships, 75% have been female and 25% from historically underrepresented groups. The presentation will focus on the women who have taken up careers in data science, eliciting some of their reflections on what helped them navigate into these careers. A personal reflection from the presenter on why this programme has won her personal awards from Higher Education and industry will also be included.