The past, present and future of q-step – a programme creating a step-change in quantitative social science skills

Abstract

This article provides an outline of the conception and implementation to date of Q-Step, a national programme to make high-level quantitative skills an essential element of teaching and learning in social sciences across the UK. Q-Step has supported the development and delivery of specialist undergraduate programmes (including new courses, work placements, and pathways to postgraduate study) in order to increase the number of quantitatively trained social scientists in the UK. There are 17 UK universities currently participating in the programme which has been funded by the Nuffield Foundation, the Economic and Social Research Council (ESRC), and the former Higher Education Funding Council for England (HEFCE). The Nuffield Foundation funds research, analysis, and student programmes that advance educational opportunity and social well-being across the United Kingdom. The Q-Step programme provides opportunities for students to develop skills and confidence in quantitative methods. This is in keeping with the Nuffield Foundation’s interest in promoting digital skills and data literacy more generally. The Nuffield Foundation believes that these skills are essential for people to participate fully in a digital knowledge economy. This article provides the background and rationale leading to Q-Step’s inception, some detail on the wider context in which the programme operates, an insight into the progress made by Q-Step so far, and also looks toward the future of the programme and the wider agenda it operates within. This article provides a snapshot of one particular model for building quantitative methods capacity in the UK higher education sector and a useful reference point for understanding the background and context of further studies and articles which might follow from Q-Step universities sharing some of their pedagogical expertise and their experience of teaching social sciences with quantitative methodology.