Scoping the Skills Needs in the Social Sciences to Support Data Driven Research

Ferrie, J. , Wain, M., Gallacher, S., Brown, E. , Allinson, R., Kolarz, P., MacInnes, J., Sutinen, L. and Cimatti, R. (2022) Scoping the Skills Needs in the Social Sciences to Support Data Driven Research. Project Report. Economic and Social Research Council (ESRC).

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This study, commissioned by the Economic and Social Research Council (ESRC), aims to help identify the skills needs of UK social science researchers to carry-out data-driven research and fully exploit the increasing volume of large and complex data available for research purposes. Data-driven research is defined inclusively, covering all forms of data production and/or data analysis that informs and/or is used by social science researchers from archives to zines, inclusive of qualitative and quantitative approaches. Data-driven research produces a robust and rigorous evidence-base that can be opened to scrutiny, and that the researcher is confident in defending. Data-driven research has sufficient rigour to inform decisions within academia and beyond. The study focusses on doctoral training and will be complemented by broader work, led by the ESRC, which considers skills needs at later career stages. It assesses core and advanced skills needs among social scientists, gaps in current provision, the structural barriers impacting the teaching or learning of data-driven skills and interventions and changes required in doctoral training, to address them. Our methodology used five phases of inquiry. A scoping literature and landscape review have delivered a foundation for primary data collection. This report is informed by 38 interviews with researchers at different career stages, a survey to Doctoral Training Partnership (DTPs) training leads and sense-checking workshops involving 14 ‘experts’ in data-driven skills and/or data-driven skill teaching plus 11 ESRC-funded doctoral candidates. Core training is defined as the teaching provided at Master’s level and which is a prerequisite for ESRC funded doctoral candidates. Advanced training is defined in two ways: specialised training which advances a researcher’s capabilities towards being an expert user; and training that researchers’ need at an advanced stage in their doctoral research projects. ‘Gaps’ are identified where there is: i) a lack of access to training in a particular skill, method or field, and ii) lack of knowledge to evaluate what skill, method, field or provider would best fill the gap identified. The findings of this research are organised into two stages: a stage 1 ‘needs analysis’, and stage 2 ‘doctoral intervention analysis’. For each stage, we present a summary of key findings, followed by a presentation of ideas on how to address relevant structural factors and barriers to data-driven skills learning (i.e. to ‘close the gap’).

Item Type:Research Reports or Papers (Project Report)
Keywords:Methods, research methods, post-graduate teaching, learning methods, pedagogy of research methods, social science research skills, data-driven skills.
Glasgow Author(s) Enlighten ID:Ferrie, Professor Jo and Brown, Dr Eleanor
Authors: Ferrie, J., Wain, M., Gallacher, S., Brown, E., Allinson, R., Kolarz, P., MacInnes, J., Sutinen, L., and Cimatti, R.
Subjects:H Social Sciences > H Social Sciences (General)
H Social Sciences > HA Statistics
L Education > LB Theory and practice of education > LB2300 Higher Education
College/School:College of Social Sciences > School of Social and Political Sciences > Sociology Anthropology and Applied Social Sciences
College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > MRC/CSO SPHSU
Publisher:Economic and Social Research Council (ESRC)
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