How is statistical study design and statistical analysis taught in the life sciences? A survey of undergraduate programmes across the UK

School:  Edinburgh Medical School  [Biomedical Sciences]

Team Members: Crispin Jordan, Nicola Romanò, Nick Colegrave, Kasia Banas

Abstract

Research in the life sciences is becoming increasingly data-driven. With this comes a need for high-quality teaching of study design and data analysis methods in undergraduate programmes. The University of Edinburgh has responded to this need in recent years by expanding the curriculum around study design and statistical analysis across disciplines (e.g. psychology, medicine, biomedical sciences). This also fits well with the positioning of both the University and City of Edinburgh as global leaders in data science. But how are other universities across the UK tackling the challenge of incorporating more statistical study design and statistical analysis content into life science curricula? What content and tools are taught? What approach is taken? How is study design and analysis content integrated with other topics within a discipline?

In this study, we propose a survey of how experimental design and data analysis is taught in undergraduate life science programmes throughout the UK. We will do this using a two-pronged approach, while leading a collaboration with several universities: First, a survey sent to all (around 300) programmes will allow a broad horizon scan to map out general trends. Second, a series of interviews with programmes selected for their diversity of circumstances will allow an in-depth understanding of how study design and data analysis teaching can be approached. Results will be used to reflect on and improve teaching practices in Edinburgh and UK-wide, with clear application to current curriculum transformation, but will also be published and disseminated to help higher education practitioners everywhere.