Elements of Social Science Research

This module is for anyone considering studying on an SSRMP module but not sure which one/s to choose. It provides an overview of the research process and issues in research design. Through reflection on a broad overview of empirical research, the module aims to encourage students to consider where they may wish to develop their research skills and knowledge. The module will signpost the different modules, both quantitative and qualitative, offered by SSRMP and encourage students to consider what modules might be appropriate for their research and career development.

Topics covered

• The research process and the different stages it might consist of
• Issues related to research design
• To consider what data you will need to address your research aims
• To consider the best methods to collect and analyse your data
• What modules are offered by SSRMP and how they might be appropriate to your needs

Prerequisites

• No prior knowledge is required.
• You may wish to prepare for this module by considering your research project, the aims and objectives, and your research and training needs to complete the project

Format

Lecture

Session dates

This modules in run in Michaelmas Term and then repeated in Lent Term. You only need to book on ONE of these iterations, EITHER in Michaelmas OR in Lent. Please note that in the Michaelmas iteration the session is in-person but during Lent takes place online.

How to Book

Bookings can be made via the Modules List where you will also find the module dates. Click on the module you want and you will be taken to a booking screen. As soon as you book, you will receive an automated email confirming your place. Please note, some modules (though not all) have multiple iterations in the Michaelmas and Lent Term.

The analysis of policy depends on many disciplines and techniques and so is difficult for many researchers to access. This module provides a mixed perspective on policy analysis, taking both an academic and a practitioner perspective. This is because the same tools and techniques can be used in academic research on policy options and change as those used in practice in a policy environment. This course is provided as three 2 hour sessions delivered as a mix of lectures and seminars. No direct analysis work will be done in the sessions themselves, but some sample data and questions will be provided for students who wish to take the material into practice.

Topics covered

Session 1
How do we analyse policy development and change over time? The policy cycle and models of policy change In studying how policies are developed and chosen there are two different timescales to consider- the immediate process of policy development (the policy cycle) and the evolution of a policy over long periods of time (models of policy change). This session will outline both timescales and discuss how these models can be applied to study policy change, highlighting the contested nature of most models of policy.

Session 2
What tools do we use to analyse policy options (I)? – CBA and MCDA in policy analysis. Policy analysis is a distinct practice that is forward looking, taking an issue and trying to both develop options and to provide a decision framework for making a policy choice. This first of two sessions provides a brief overview of cost-benefit analysis (CBA) and multi-criteria decision analysis (MCDA), gives examples of their use in policy decision making, and discusses the role of political considerations in the use of these tools.

Session 3
What tools do we use to analyse policy options (II)? – assessing the (likely) effects of policies. A key challenge in policy analysis and practice is how to assess and predict the effect of particular policy decisions. Examples of widely used tools for this are regression analysis (as much of the information that policymakers need is provided through the outputs of regression analysis of varying complexity) and randomised controlled trials. This session will focus on some of tools, discussing their main features and using examples of their use in policy analysis and policy making.

Assessment

The SSRMP does not assess students at the end of this module, although individual degree programmes may set their own assessment using the content in it.

Session dates

How to Book

Bookings can be made via the Modules List where you will also find the module dates. Click on the module you want and you will be taken to a booking screen. As soon as you book, you will receive an automated email confirming your place. Please note, some modules (though not all) have multiple iterations in the Michaelmas and Lent Term.

Social Network Analysis (SNA) is “a distinct research perspective in the behavioural and social sciences” because it elevates relationships as the primary unit of analysis when attempting to understand and explain social phenomena (Wasserman and Faust, 1994, p. 4). This methods module will introduce you to network research tools used to explore the social constructs that surround all of us, continuously facilitating and frustrating our individual ambitions. Each of our three sessions will focus on a primary component of modern SNA: relational data collection, network visualisation, and descriptive network statistics and modelling. We will use real relational datasets from historical network studies. Participants will also be encouraged to develop their own relational data and complete a basic descriptive analysis and network visualisation of their data. This module will make use of web-based tools and open-source options in the R environment. However, no previous training in SNA methods or R will be assumed by the instructor.

Session dates

How to Book

Bookings can be made via the Modules List where you will also find the module dates. Click on the module you want and you will be taken to a booking screen. As soon as you book, you will receive an automated email confirming your place. Please note, some modules (though not all) have multiple iterations in the Michaelmas and Lent Term.

The module provides a practical guide to designing and developing a research project based on quantitative dates.  It focuses on key aspects of research design, how to work with theory, identify key concepts and operationalise them with quantitative data.  It will explore the use of applied statistical methods for data analysis, their applications in academic research, and how to interpret statistical outputs. Although the illustrative examples are mainly drawn from education and policy research, the statistical and design knowledge and skills acquired via this module are also applicable to other social sciences research topics and areas.  

Outline  

The module consists of four lectures (two-hour per session) including:  

• Lecture 1: Introduction to quantitative research design 

• Lecture 2: Key statistical concepts and methods  

• Lecture 3: Applied social statistics in education research  

• Lecture 4: Education and social policy evaluation 

Contents  

Lecture 1 will focus on how to design quantitative studies, including formulating research questions, engaging with theoretical and empirical evidence, developing hypothesises, as well as preparing relevant data. Lecture 2 will cover some of the widely used statistical toolkits for data description and hypothesis testing, such as graphs, z-score, conference intervals, parametric and non-parametric tests, correlation and regression analyses. Lecture 3 applies the principles of research design and key statistical methods to examples drawn from education research. It will highlight regression analyses and the interpretation of statistical outputs. Lecture 4 will introduce a few causal inference methods, such as matching, instrumental variables, difference-in-differences, and regression discontinuity design, which are commonly used in social policy evaluations.  

Objectives  

By the end of the module, students will be able to:  

• Understand how to design quantitative studies   

• Understand key statistical theories and methods widely used in academic research  

• Analyse and interpret quantitative research papers and reports  

• Understand causal inference methods widely used in policy evaluations  

Software  

The module uses Stata software for practical examples. Basic knowledge of Stata is recommended to maximise the learning experience.  

Format  

Teaching will take place in person, with each session lasting for 2 hours. No specific lab sessions are planned; however, Stata codes will be provided whenever relevant to facilitate learning and practice.   

Session dates

How to Book

Bookings can be made via the Modules List where you will also find the module dates. Click on the module you want and you will be taken to a booking screen. As soon as you book, you will receive an automated email confirming your place. Please note, some modules (though not all) have multiple iterations in the Michaelmas and Lent Term.

Content analysis has been widely used to study different sources of data, such as interviews, conversations, speeches, and other texts. This module adopts an interactive approach, where students are introduced to the key elements of content analysis, how to conduct content analysis, and a range of examples of the use of content analysis. This module offers two practical workshops, where students have a hands-on opportunity to practice performing content analysis, followed by guided reflection.

Objectives

• To introduce content analysis as a research method
• To introduce students to how content analysis can be used in research
• To explore how content analysis is performed
• To highlight methodological considerations concerning content analysis
• To provide academic examples of content analysis used in research
• To provide experiential, collaborative, learning experiences for students in performing content analysis

Format

Lectures and practical workshops.

Sessions

In order to ensure workshops contain only small numbers of participants, three groups of workshops will be run. You only need to book on ONE group either Group 1, Group 2, or Group 3.

Group 1

Group 2

Group 3

Learning Outcomes

• Students will develop their understanding of how content analysis can be used in research
• Students will be able to describe theoretical and practical considerations regarding the use of content analysis
• Students will be able to describe how to perform content analysis
• Students will reflect on their performance of conducting content analysis in the workshops
• Students will consider whether and how content analysis may be used in their own research

Assessment

This module is not assessed.

How to Book

Bookings can be made via the Modules List where you will also find the module dates. Click on the module you want and you will be taken to a booking screen. As soon as you book, you will receive an automated email confirming your place. Please note, some modules (though not all) have multiple iterations in the Michaelmas and Lent Term.

This module is designed to help students who will need to use archives in their research, and consists of four sessions. The first session will deal with the large variety of material which can be found in archives, how it is organised, and how to use their various different catalogues and use of finding devices. The second session will look at how to plan an archive visit when it is necessary to consult stored documents. Increasingly more archives are making their material available online, and this session will examine how to find out what is available to view and can be download. The first session on overseas archives is given as part of the History Faculty general training.

Topics covered

• What is in an archive
• Planning your trip to an archive
• Online Resources
• Overseas Archives

Session dates

How to Book

Bookings can be made via the Modules List where you will also find the module dates. Click on the module you want and you will be taken to a booking screen. As soon as you book, you will receive an automated email confirming your place. Please note, some modules (though not all) have multiple iterations in the Michaelmas and Lent Term.