Wanted: British social scientists with better quantitative skills

The British Academy has long believed that the quantitative skills taught in the social sciences (other than economics and psychology) in the UK are far too basic.

To try and help put this right, it commissioned a team from the University of Edinburgh to look at what is happening at 16 leading international universities. The results have now been published as Measuring Up: International Case Studies on the Teaching of Quantitative Methods in the Social Sciences.

The central conclusions are stark.

“Undergraduate social science students in many universities in Europe, North America and Australasia reach much higher levels of achievement in quantitative skills than even their best UK counterparts,” argue the authors of the report.

This is most obviously because “their degree programmes devote a much larger share of curriculum time to the study of methods”, but a substantial contributory issue is the fact that “university teaching staff [in other countries] are much more likely to have advanced quantitative skills than in the UK”.

The case studies corroborate this general picture.

Motivated by the fact that “the universe of data, big and otherwise, is growing explosively”, the University of Auckland, for example, offers “a non-mathematical, conceptual introduction to statistics, and particularly data analysis” to about 4,500 students a year, reaching about two-thirds of the overall undergraduate intake.

First-year students of sociology and politics at the University of Mannheim “study a range of statistical methods, up to linear and logistic regression, in generic lecture classes”, so that when they embark on more substantive courses they “would be surprised to be asked to read material that did not rely to some extent on the application of advanced statistical methods”.

At Yale University, students undertaking a BA in sociology are required to take two methods classes, including “an introductory overview of research design, including the ethical implications of doing social research, sampling and the measurement and interpretation of data”.

In Britain, by contrast, says Measuring Up, social science “students not only [generally] arrive at university with little exposure to statistics or quantitative methods, but typically are given little encouragement, opportunity or requirement to develop these skills in their undergraduate programmes”.

Given that “the range of high-quality quantitative [data] available to social scientists is increasing exponentially”, there are “practical economic reasons” why this is worrying. Yet since many students find quantitative skills modules difficult or “only come to appreciate their value in the graduate labour market later on”, there is also a danger that student satisfaction surveys and the teaching excellence framework may act as a disincentive to their development.

But although the authors believe that “UK universities set their expectations far too low”, the case histories provide crucial lessons about the need for “suitably qualified staff, good teaching and adequate curriculum time”.

In doing so, they could draw on a number of valuable assets and precedents, such as “the world-class data infrastructure available in the UK through the UK Data Service”; a “wealth of teaching support resources” developed, for example, under the Economic and Social Research Council’s Quantitative Methods Initiative; and the way that the country has “already successfully tackle[d] the challenges of students’ math competence or anxiety around number work in the STEM subjects”.

matthew.reisz@tesglobal.com