Developing pedagogy for 'Big Qual' methods: Teaching how to analyse large volumes of secondary qualitative data

The sharing and re-use of data is encouraged by major research funding bodies in the UK as a way of maximising its value and as vital to accountability and transparency. The creation of repositories, such as the UK Data Archive which houses over 1,000 qualitative and mixed methods datasets, offers qualitative researchers and students many opportunities to re-use data. However, the practice of moving beyond the reuse of one or two datasets to working across multiple small-scale archived qualitative studies remains under developed. This represents a challenge, both for researchers seeking to develop their skills and for methods teachers tasked with developing research capacity. This working paper describes the work of a unique collaboration between researchers of methods for analysing large volumes of qualitative data, ‘big qual’, and researchers of social science research methods pedagogy to develop big qual methods teaching and open educational resources. Using reflective and evaluative methods, the combined team completed three cycles of action and reflection based upon the teaching of big qual analysis using an innovative breath-and-depth method for working across multiple archived qualitative data sets. This paper reports key messages for teachers of big qual and related innovative methods, identifying the importance of teachers’ pedagogic reflection across their approaches, strategies, tactics and discrete in-class tasks, and other key pedagogic resources that are necessary to develop teaching and learning. These resources respond to particular challenges for interdisciplinary and innovative methods teaching. They include modes of teaching through data, the use of worked examples and metaphors for articulating and structuring the acquisition of new concepts and knowledge, and the use of peer-learning to enrich learning and manage diversity. Lastly the paper links to an extensive suite of Open Educational Resources for the teaching of big qual analysis at the ESRC National Centre for Research Methods