‘I’m not a natural mathematician’
| Date | 01 October 2017 |
| Published date | 01 October 2017 |
| DOI | 10.1177/0144739417711219 |
| Author | Liam Foster,Tom Clark |
| Subject Matter | Articles |
Article
Teaching Public Administration
‘I’m not a natural
2017, Vol. 35(3) 260–279
ª The Author(s) 2017
mathematician’: Inquiry-
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DOI: 10.1177/0144739417711219
based learning, constructive
journals.sagepub.com/home/tpa
alignment and introductory
quantitative social science
Tom Clark
Department of Sociological Studies, University of Sheffield, Sheffield, UK
Liam Foster
Department of Sociological Studies, University of Sheffield, Sheffield, UK
Abstract
There is continuing concern about the paucity of social science graduates who have the
quantitative skills required by academia and industry. Not only do students often lack the
confidence to explore, and use, statistical techniques, the dominance of qualitative
research in many disciplines has also often constrained programme-level integration of
more quantitative material. However, whilst the topic of statistical literacy is relatively
well researched within the more general educational literature, the evidence-base with
respect to the effectiveness of teaching and learning of quantitative research methods in
the social science remains somewhat limited. This paper describes the development,
integration and evaluation of a series of student-led inquiry-based quantitative work-
books within a sociology/social policy undergraduate degree. It outlines how the
workbooks were constructively aligned within a ‘methods spine’ and offers some insight
into quantitative teaching and learning generally. The paper also discusses some of the
opportunities and challenges of taking both an aligned and IBL approach to the teaching
of quantitative methods. In doing so it adds to growing evidence that ‘problem-based
pedagogies’ tend to increase educational gain over and above more didactic approaches
to learning and teaching. It highlights three key findings: programme-level approaches to
curriculum design can be crucial in improving quantitative skills, particularly where they
Corresponding author:
Liam Foster, Department of Sociological Studies, University of Sheffield, Elmfield Building, Northumberland
Road, Sheffield, S10 2TU, UK; Telephone: 01142226434
Email: l.foster@sheffield.ac.uk
Clark and Foster
261
are tailored to student needs; a general indifference to quantitative methods is likely to
be due to a process of disenfranchisement that happens before and during students’
engagement with university; and, meaningfully engaging students as partners in the
process of designing, integrating and evaluating curricula can help to overcome some of
the barriers associated with the learning and teaching of quantitative skills.
Keywords
Constructive alignment, inquiry-based learning, quantitative methods, social sciences,
student engagement
Introduction
Recent calls to establish an underlying pedagogy for the learning and teaching of
quantitative techniques in the social sciences have highlighted the paucity of the
evidence-base in the area, particularly with respect to the experiences of contemporary
undergraduates themselves (MacInnes, 2012). Whilst the challenges of teaching quan-
titative methods in the social sciences are relatively well rehearsed (see, for instance,
Payne and Williams, 2011), providing evidence of effective solutions to these difficulties
has proved much more elusive.
The topic of statistical literacy is, of course, very well developed within more
mathematically-inclined arenas such as science and/or engineering. However, the entry
requirements, the expectations of students, and the epistemological frameworks that
shape the social sciences, are not necessarily the same as they are in disciplines such as
physics and robotics. Simply transferring pedagogical techniques and experiences from
one to the other is not necessarily a straightforward task. Many students entering degree
courses in the social sciences, and sociology and social policy in particular, have little
knowledge of maths and statistics beyond the rudimentary requirements of GCSE level
study (Byrne, 2012; Foster and Clark, 2013). This is significant, as Parker et al. (2008:
11) noted: ‘the lack of sustained and widespread mathematics training among secondary
school students and their fear and suspicion of taking up maths or statistics once in
university creates a substantial impediment to quantitative methods training’. Indeed, in
our experience there is a general expectation amongst sociology/social policy students
that there will be an emphasis on substantive ideas and issues. Furthermore, there is a
tendency for qualitative approaches, including interviews and focus groups, to be
favoured by social science entrants (Williams et al., 2008). It is these interests that attract
them to study for their social science degree, not statistical equations.
This level of preparedness and interest can create a barrier between students and lec-
turers, with many ‘stats’ modules requiring substantial mathematical skill on one hand, and
knowledge of dry technical literature on the other. This means that students are often
anxious about undertaking quantitative methods modules, have a tendency to approach
them with poor attitudes and misconceptions as to what they entail, and fail to see
their significance to the rest of their degree programme (see Earley, 2014). Such barriers
not only constrain the enthusiasm necessary to use quantitative data for sociological
purpose, but also can lead to a (lifelong) lack of interest in quantitative methods generally.
262
Teaching Public Administration 35(3)
The challenge for dedicated lecturers of research methods is, therefore, to help to develop
their students’ confidence in using quantitative techniques in more engaging and mean-
ingful ways.
The difficulties of teaching and learning these techniques are reflected in the apparent
paucity of social science graduates who have the quantitative skills required by academia
and industry (see, for example, Irvine et al., 1979; and Wiles et al., 2009). These con-
cerns typically detail the relative shortage of quantitative research within a UK context
‘but also a shortage of the quantitative research skills required . . . to understand, and
critically review, quantitative research’ (Gorard et al., 2003: 19). If quantitative data are
to be useful, not only do they need to be used by skilled social scientists, but also any
presentation of those data needs to be understood and interpreted with critical awareness.
Indeed, the need to promote statistical skills among social scientists is perhaps more
prominent than ever. The commencement of the five-year Nuffield-funded Q-Step
Centres in 2013 – a £19.5 million programme designed to promote a step-change in
quantitative social science training – once again underlined the need to establish
quantitative skills as a cornerstone of the social science degree experience. Elsewhere,
and as a part of their strategic plan for 2012–2016 to encourage ‘reflection and inno-
vation’ in teaching, the challenges of teaching research methods have also been a key
concern for the Higher Education Academy (HEA), with teaching research methods one
of its three Social Science Strategic Priorities for 2013–2014. Within the priority there is
recognition of the need to share good practice in the area and focus on ‘the use of open
educational resources (OER) in research methods teaching’ (HEA, 2014a).
It is as a result of these initiatives that greater interest is being directed toward the
underlying pedagogy of the field. However, exploring how social science students
understand statistics in practice is likely to be crucial in developing more effective ped-
agogies. This paper details the development and evaluation of a project funded under the
HEA’s Social Science Strategic Priorities for 2013–2014. The aim was to enable sociol-
ogy/social policy students having no prior statistical knowledge to develop the confidence
and skills necessary for quantitative research. More specifically, the project involved the
design, implementation and evaluation of a series of inquiry-based workbooks to provide
undergraduate sociology and social policy students with ‘hands on’ experience of working
with quantitative data extracted from the teaching datasets held by Economic and Social
Data Service (ESDS).1 The paper outlines a rationale for the development of ‘student-led’
inquiry-based quantitative workbooks, followed by a description of how the workbooks
were implemented within a whole curriculum approach that emphasised the constructive
alignment of a ‘methods spine’. Offering some student-led insight into quantitative
teaching and learning generally – and the evaluation of these initiatives specifically – the
paper continues with a discussion of some of the opportunities and challenges of adopting
an aligned inquiry-based learning approach to the teaching of quantitative methods.
Inquiry-based learning
Inquiry-based learning (IBL) – sometimes also referred to as ‘active learning methods’ –
can come in a variety of forms and under many different headings. These include:
Clark and Foster
263
‘collaborative learning’, ‘problem-based learning’, ‘performance learning’ and even
‘service-based learning’. What all these methods stress, however, is a research-led and
student-orientated approach to teaching and learning. IBL ‘describes a cluster of strongly
student-centred approaches to learning and teaching that are driven by inquiry or
research’ (Levy et al., 2010).
IBL promotes theoretically-informed practice-based learning. Often this means
involving ‘ . . ....
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