Teaching statistics to the reluctant is hard work. We report here on an innovative approach to learning statistics in applied social research settings, by placing social science undergraduates into the workplace. We have collected data since 2014 based on our students' experiences of undertaking 8-week long paid internships in organizations ranging from university research centres, charities, social enterprises and think-tanks, local and national government departments, polling firms and data consultancies, and media companies, to international statistical organisations (The World Bank). This paper will report on (i) the level of statistical training that forms the foundation for this work (ii) the methods and data analysis skills that our students develop whilst in the workplace (iii) examples of outputs that they produce for their host organisations and (iv) the ways in which we nurture this skill-set for returning students in order to support our undergraduates to become future data analysts.

The paper is based on experiences at The University of Manchester, UK. The internship programme has been developed through our 'Q-Step Centre’ which is funded nationally (along with 14 others) to develop a step-change in quantitative methods teaching in the social sciences. The context for Q-Step is the long-standing quantitative skills deficit for UK social science and humanities graduates, as captured in numerous reports from research bodies and higher education funding councils dating back at least two-decades (ESRC (1987), MacInnes (2009)), Carter et al, 2011; Nind et al, 2015; Buckley et al, 2015; Scott and Goldring, 2015).

The University of Manchester Q-Step Centre has two strands to our approach to develop quantitative skills in the undergraduate population. First, by increasing the exposure to numerical data for all social science and humanities students from the start of their degrees, and second to train future quantitative social researchers by providing quantitative pathways through their social science degree.

To date 120 students have been hosted in 60 organisations across the public, private and community and voluntary sectors. This paper will share lessons learned from these experiences and highlight how we are now turning out attention to working with employers to ensure the university social science curriculum at Manchester aligns with labour market needs in a time of increasing volumes of data and a growing need for analytical skills to make use and sense of these.

Biography

Professor Jackie Carter is Co-director of the Manchester Q-Step Centre and Director for Engagement with Research Methods Training. Jackie has extensive project experience as an expert in the provision and use of data in learning and teaching, undertaking a one year Teaching Fellowship on statistical literacy in 2011-12. She previously taught high school maths, and undertook a PhD as a mature student in geostatistics. Jackie is based in Social Statistics for the Q-Step Centre role.