Count: Developing STEM skills in qualitative research methods teaching and learning

In June 2012 HEA Social Sciences held its first learning and teaching summit, which focused on teaching research methods in the Social Sciences. In December 2012 we commissioned 11 projects that were designed to explore further the issues identified at the summit.

Qualitative methods of social research are to do with the interpretation and meaning of texts, words, images and actions. They are often defined, in contrast to quantitative methods, as methods that do not use numbers. However, recent years have seen two developments that are beginning to break down this simple distinction. One is the availability of software to assist the analysis of qualitative data – the text, images and video that researchers collect. Such software often has quantitative data mining functions built in which can be used to assist with the interpretation and analysis of qualitative data. The second development has been the growth in interest in mixed methods, that is, approaches to social research that combine the use of both qualitative and quantitative methods.

Traditionally, there has been little reference to technology or number in the use of qualitative methods in social research and particularly in the teaching of qualitative methods at undergraduate level. The one exception to this is the discussion of the use of computer assisted qualitative data analysis programs in several textbooks aimed at undergraduate users. At the moment, although the use of such software is a standard part of most postgraduate training, it is not much used at undergraduate level. But there is clearly the potential to increase this level of usage, more in line with the almost ubiquitous use of software to support quantitative data analysis.

This project will look for examples of good practice in promoting STEM skills acquisition, “through the back door” so to speak, as part of teaching qualitative research methods. It will identify what barriers there are both to the use of software at undergraduate level and to the use of numerical techniques to assist qualitative analysis. One likely barrier is the lack of good educational resources and data sets that can be used in such teaching so the project will try to identify those that do exist.