The challenge of training future cohorts of quantitative social science researchers to secure the ‘pipeline’ from school/undergraduate study through postgraduate to postdoctoral research, depends not only on resources but on effective pedagogy1. A successfully functioning pipeline would generate a stream of social scientists capable of engaging with quantitative data and evidence. This could be important to maintain the relevance of the social sciences in a world where the ability to process, manage and analyse large volumes of data both opens up new opportunities to enhance knowledge, whilst, at the same time, presenting methodological challenges2.
While there is research evidence on statistics teaching at school and university levels, most is USA-based and much of the literature is prescriptive, providing 'how to' recipes for classes3. There is little evidence-based work that addresses social science teaching specifically, where the challenge of poor maths skills and of a lack of confidence in applying them is often considered particularly acute. Indeed, although the current pedagogical literature is a useful resource, it is far from comprehensive and the pedagogical culture is limited4.
In the context of many current initiatives (Nuffield Foundation Q-Step, evolving ESRC Doctoral Training Centres, Applied Quantitative Methods Network training,the British Academy Count Us In data skills strategy) NCRM has a unique opportunity to work with quantitative methods trainers and students to learn more about ‘what works’ in pedagogical and career development terms. Our research focus is on learning modes and achievements, motivation, student recruitment and retention. To enable this we are in the process of reviewing literature, evaluating tools and conducting secondary analysis as a prelude to primary data collection. This project provides one step towards developing a pedagogical culture based on evidenced and peer reviewed literature, which could provide a foundation on which a pipeline producing QM literate graduates and post-graduates could be constructed.
One possibly fruitful theme of the data collection for this project may focus upon student anxiety. The belief that social science undergraduates are apprehensive about their studies related to maths, statistics and quantitative methods in general is often cited in the literature5,6. By contrast, other research suggests the concept to be overstated, showing that 40% of sociology students in a single institution in the USA who responded to a survey report no angst7 and only a slight majority report angst in a sample of students in England and Wales8. Tools such as the Statistical Anxiety Scale9 and the Maths Anxiety Rating Scale10,11 have been developed to measure the level of angst, with some comparisons between academic fields12. Our study could undertake a comprehensive comparison of anxiousness between social science disciplines and between social science and more numerate subjects, so that we might know whether social science students are significantly more ‘frightened’ of numbers than students in other disciplines or whether some social sciences are faring better than others in this respect.
References
1 Payne, G., Williams, M. (Eds.), 2011. Teaching Quantitative Methods: Getting the Basics Right. SAGE Publications Ltd, Los Angeles, Calif.
2 Savage, M., Burrows, R., 2007. The coming crisis of empirical sociology. Sociology 41, 885–899. doi:10.1177/0038038507080443
3 Gelman, A, Nolan, D., 2002. A probability model for golf putting. Teaching Statistics 24, 93-95.
4. Lewthwaite, S., Nind, M., 2015. Let’s talk about pedagogy. MethodsNews Spring 2015. http://eprints.ncrm.ac.uk/3754/
5 Bridges, G.S., Pershing, J.L., Gillmore, G.M., Bates, K.A., 1998. Teaching quantitative research methods: A quasi-experimental analysis. Teaching Sociology 26, 14–28.
6 Paxton, P., 2006. Dollars and sense: Convincing students that they can learn and want to learn statistics. Teaching Sociology 34, 65–70.
7 DeCesare, M., 2007. “Statistics anxiety” among sociology majors: A first diagnosis and some treatment options. Teaching Sociology 35, 360–367.
8 Williams, M., Payne, G., Hodgkinson, L., Poade, D., 2008. Does British sociology count? Sociology students’ attitudes toward quantitative methods. Sociology 42, 1003–1021.
9 Oliver, A., Sancho, P., Galiana, L., Cebria i Iranzo, M.A., 2014. New evidence on the Statistical Anxiety Scale (SAS). Anales de Psicologia 30, 151–157.
10 Bessant, K.C., 1995. Factors associated with types of mathematics anxiety in college students. Journal of Research in Mathematics Education 26, 327–345.
11 Suinn, R.M., Winston, E.H., 2003. The Mathematics Anxiety Rating Scale, a brief version: psychometric data. Psychological Reports 92, 167–173.
12 Hamza, E., Helal, A.M., 2013. Maths anxiety in college students across majors: A cross-cultural Study. Educationalfutures 5, 58-74.