RESEARCH STRATEGY AND DESIGN

SCHOOL OF HISTORY, PHILOSOPHY AND SOCIAL SCIENCES
2020/21
Module Title: RESEARCH STRATEGY AND DESIGN
Module number: SXU-4004
Semester: 1 (20 credits)

Module leader: Dr Miyoung Ahn, email: m.ahn@bangor.ac.uk
Other teaching staff: Dr Alison Orrell, email: a.orrell@bangor.ac.uk
Description:
The aim of the module is to provide postgraduate level research methods training in the main
varieties of quantitative and mixed methods research in the social sciences, including basic
statistical literacy. The module begins by locating the research process in the context of
different ‘ways of knowing’ (epistemology), to show how research design is grounded in
assumptions about the nature of the phenomena to be investigated. An appreciation of this
connection will enable students to evaluate research and make informed choices about the
selection of an appropriate research methodology for their own research.
The module is then organized in terms of (a) principles of research design (b) issues of data
collection and (c) data analysis. Topics covered include the definition and formulation of
research problems and hypotheses, the relationships between and the rationale for using
particular research methods, the relationships between empirical research and theory
generation and theory testing, different forms of sampling, sampling error and potential bias
in the interpretation of research findings, and the concepts of generalisability, validity,
reliability and replicability. Students are taught how to access and use secondary data,
construct and critique questionnaires, how to interpret measurement error and missing data,
and how to record data from experimental and quasi-experimental research.
Training in the use of SPSS is an integral part of the module and takes place alongside the
sessions dealing with surveys, questionnaire design, structured interviews and data analysis.
This module is co-requisite with SXU-4005 Research Process and Meaning (Semester 2) for
students studying for taught MAs in Social Sciences.
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Learning outcomes
At the end of this module, we expect students to have developed the following skills and to
be able to apply them:
1. Demonstrate the capacity to manage the research process, including managing
numerical data, and conducting and presenting research in a way that is consistent
with professional practice and research ethics.
2. Display critical understanding of the significance of epistemological positions that
provide the context for theory construction, research design, and the selection of
appropriate analytical techniques in quantitative research.
3. Show competence in recognising, evaluating and applying a wide range of
quantitative data sources and tools of analysis.
4. Manifest the ability to apply the essential principles of research design and strategy,
based on a clear grasp of how to formulate researchable problems and critical
discernment of alternative approaches to social research.
Key skills taught
1. Decision Making
Ability to make informed choices between a range of research techniques, e.g.
design and administering of questionnaires; using survey data; or statistical data
analysis.
2. Research Skills
‘Hands on’ experience of using research techniques and software.
3. Group Skills
Group work skills in applying research techniques within a classroom setting.
4. Research Skills
Competence in data handling and data analysis.
5. Communication – Verbal
Oral competence in explaining and interpreting the research process.
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Outline of topics (by University teaching calendar weeks)
SXU-4004 Semester 1 2020/21 TOPICS & DATES

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W5. Introduction: brief history of research in the social sciences
This session will describe the emergence of empirical social science, and its
relationship to theories and research methods used in social policy, sociology and
related disciplines. It will examine the view that social science can have practical
benefits for government and society.
Moses, J and Knutsen, T (2012) Ways of Knowing: Competing Methodologies in
Social and Political Research. 2nd edition. Palgrave Macmillan. Introduction.
W6. Experience, evidence, research and knowledge
This session will deal with the fundamental questions of what we know, and how we
know it. It will introduce students to the main strands of social science reasoning:
positivism, constructivism and realism. It will consider the ways in which users as well
as researchers understand, experience or shape the research process and the
applications of research. Do methods have a social life of their own?
Blaikie, N. (2010) Designing social research: the logic of anticipation, Cambridge:
Polity Press
Crotty, M. (1998) The Foundations of Social Research: Meaning and Perspective in
the Research Process. London: Sage
Gorard, S. (2013) Research Design: Creating Robust Approaches for the Social
Sciences, London: Sage
Hughes, J and Sharrock, W (1998) The Philosophy of Social Research, 3rd ed, London,
Longmans
Hughes, J and Sharrock, W (2007) Theory and Methods in Sociology, Palgrave
Macmillan
W7. Research questions and hypotheses
This session will use some classic and contemporary studies to illustrate how social
scientists set about formulating and managing researchable questions. Examples will
be drawn from a range of influential studies as well as studies carried out by social
researchers at Bangor University.
Blaikie, N. (2010) Designing social research: the logic of anticipation, Cambridge:
Polity Press. Ch.3 Research Questions and Purposes
W8. Principles of research design
The aim of this session is to provide an overview of the research design principles
including classic experimental research and methods for inferring causal relationships.
It explains the logic of social research using hypotheses, independent and dependent
variables, and deduction. It will also discuss design strategies which are suited to less
artificial and controlled environments than the classic experiment. It uses examples
of longitudinal, cross-sectional and case study designs to explain how research
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problems can be explored using quasi-experimental methods. The choice of design
should be theoretically informed and should lead to answers to specific research
questions.
de Vaus, D (2001) Research Design in Social Research, London: Sage. Parts I-V.
W9. Questionnaire design; design of questions
This session is concerned with the considerations that are involved in asking questions
that are used in structured interviews and questionnaires. Issues to be covered
include: open and closed questions; agree/disagree questions; satisfaction questions;
rules for designing questions and the importance of piloting questions.
The session will involve practical work in question design, which will be followed up
in the SPSS workshop session.
Dillman, D. A. (2007) Mail and Internet Surveys: The Tailored Design Method, John
Wiley & Sons
W10. Reading and assessment week
W11. Uses of official data
The collection and analysis of official UK data is undertaken by the Office of National
Statistics (ONS) as well as government departments and a number of nondepartmental public bodies. Official statistics are an essential source of data for social
scientists as well as a vital part of the policy-making process. Their accuracy and
trustworthiness are matters of central concern to the research community. This
session examines the construction and collection of official datasets such as the
Census, the Crime Survey for England and Wales and the British Household Survey.
Questions of access, control and bias are also considered in the light of recent
controversies about the interpretation of official data.
Census
http://www.ons.gov.uk/ons/guide-method/census/2011/index.html
Crime Survey for England and Wales
http://www.crimesurvey.co.uk/
UK Household Longitudinal Survey (UKHLS)
https://www.understandingsociety.ac.uk/
W12. Populations, measurement and survey sampling
This session aims to provide an understanding of the procedures involved in planning
and conducting social survey research and practical examples in how to apply these
procedures. It begins with the question: why carry out a survey? Assuming the method
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can be justified by the research question, issues of design are considered, from
problem definition to measurement and sampling. There is an overview of sampling
theory (both probability and non-probability), the sources of sampling error and ways
to minimize them.
Fink, A and Kosecoff, J (1998) How to conduct surveys: a step-by-step guide, 2nd
edition. London: Sage
Moser, C and Kalton, G (1971) Survey Methods in Social Investigation, 2nd edition.
London: Heinemann.
Sapsford, R (2007) Survey Research, 2nd edition, London: Sage.
W13. Structured interviews and standardization
The structured interview is a technique commonly employed in survey research. The
goal of the structured interview is for the interviewing of respondents to be
standardized so that differences between interviews in any research project are
minimized.
This session will explore: the importance of standardization; the different contexts of
interviewing; pre-requisites of structured interviewing, questionnaire testing and
problems with this form of research. Issues of practicality are considered, including
scale, resources and consent.
Dillman, D. A. (2007) Mail and Internet Surveys: The Tailored Design Method, John
Wiley & Sons
W14. Introduction to quantitative data analysis: frequencies, means distributions
This session will highlight the importance of considerations of data analysis from the
very earliest stages of research. Distinctions will be drawn between the different kinds
of variable that can be generated in quantitative research as this is crucial to an
appreciation of which methods of analysis can be applied when examining variables
and relationships between them. Practical examples of this will be explored in the
follow-up workshop session
Field, A (2009/2013) Discovering Statistics Using SPSS. London: Sage Publications.
W15. Simple statistical models: testing research questions
This session will explain the significance of ‘significance’ in the statistical sense,
including the t test which can be used to test whether the means of two groups are
statistically significantly different from each other.
Field, A (2009/2013) Discovering Statistics Using SPSS. London: Sage Publications.
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W16. Presenting your findings and report writing
This session will sum up the module and reflect on how to present data and research
findings in an accessible and clear manner. It will include discussions of visualising
data, different forms of presenting data, and writing styles. Examples of research
reports for different audiences will be used.
Preparing for the dissertation
Modules SXU-4004 and SXU-4005 provide essential support for students proceeding to a
Masters dissertation in social sciences. Formal sessions will take place in semester 2. In
semester 1, students should be thinking about their dissertation topic, formulating research
questions and identifying sources of data. Your proposed research and the eventual proposal
should take into account the research design and methodological issues covered in this
module.
Assessment
For this module students must complete the following assignments. Detailed instructions
and deadlines are provided on Blackboard.
1. Critically discuss the research design and method(s) in one example of quantitative
or mixed method social research, focusing on the relationship between
epistemology, theory and empirical procedures.
2. Critique and design a questionnaire.
3. Practical exercise using secondary data, SPSS, and conducting basic statistical
analyses.
USING SPSS
Training in the use of the SPSS (Statistical Package for the Social Sciences) for quantitative
data analysis is provided during the second half of Semester One. It consists of a series of 5
computer-based workshop sessions involving instruction and practical exercises. The
workshops take place broadly in parallel with the sessions in weeks 9, 12-15 dealing with
surveys, questionnaire design, structured interviews and data analysis.
SPSS is one of the most widely used applications in social research and the latest version is
supported by Information Services at Bangor University. Proficiency in using SPSS can easily
be transferred to other statistical software such as Minitab.
The main topics covered are:
– access to SPSS and familiarization with commands and instructions
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– data entry, including cleaning data, defining variables, measurements and coding
– statistical analysis with single variables
– statistical analysis of relationships between two variables
– multivariate analysis involving three or more variables
– inferential statistics and hypothesis testing
– data management techniques
Reading
Field, A P (2009) Discovering statistics using SPSS: and sex and drugs and rock ‘n’ roll (Third
Edition). London: Sage.
Field, A P (2013) Discovering statistics using SPSS: and sex and drugs and rock’ n’ roll (Fourth
Edition). London: Sage.
Field, A P (2018) Discovering statistics using IBM SPSS statistics (Fifth Edition). London: Sage
Fielding, J and Gilbert, N (2000) Understanding Social Statistics, London: Sage.
Pallant, J (2010) SPSS Survival Manual: a Step by Step Guide to Data Analysis Using SPSS for
Windows (up to version 18) Buckingham: Open University Press.
https://www.discoveringstatistics.com