Social Sciences Research Methods Programme course timetable

This intensive course on structural equation modelling will provide an introduction to SEM using the statistical software Stata. The aim of the course is to introduce structural equation modelling as an analytical framework and to familiarize participants with the applications of the technique in the social sciences.

The application of the structural equation modelling framework to a variety of social science research questions will be illustrated through examples of published papers. The examples used are drawn from recent papers as well as from publications from the early days of the technique; some use path analysis using cross-national data, others confirmatory factor analysis, and other still full structural models, to test particular hypotheses. Some example papers may be found below, though they should not be treated as the gold standard, rather as an illustration of the variety of approaches and reporting techniques within SEM.

• Duff, A., Boyle, E., Dunleavy, K., & Ferguson, J. (2004). The relationship between personality, approach to learning and academic performance. Personality and individual differences, 36(8), 1907-1920.
  
• Garnier, M., & Hout, M. (1976). Inequality of educational opportunity in France and the United States. Social Science Research, 5(3), 225-246.
  
• Helm, F., Müller-Kalthoff, H., Mukowski, R., & Möller, J. (2018). Teacher judgment accuracy regarding students' self-concepts: Affected by social and dimensional comparisons?. Learning and Instruction, 55, 1-12.
  
• Parker, P. D., Jerrim, J., Schoon, I., & Marsh, H. W. (2016). A multination study of socioeconomic inequality in expectations for progression to higher education: The role of between-school tracking and ability stratification. American Educational Research Journal, 53(1), 6-32.
  

Students will engage in a critique of such examples, with the aim of gaining a better understanding of the SEM framework, as well as its application to real-life data. To further facilitate this application focus, the theoretical introduction will be accompanied by practical examples based on real, publicly-available data.

The module explores Good Data Visualisation (GDV) and graph creation using Python.

In this module we demystify the principles of data visualisation, using Python software, to help researchers to better understand and reflect how the “5 Principles” of GDV can be achieved. We also examine how we can develop Python’s application in data visualisation beyond analysis. Students will have the opportunity to apply GDV knowledge and skills to data using Python in an online Zoom, self-paced, practical workshop. In addition there will be post-class exercises and a 1-hour asynchronous Q&A forum on Moodle Forum.

This intensive course on structural equation modelling will provide an introduction to SEM using the statistical software Stata. The aim of the course is to introduce structural equation modelling as an analytical framework and to familiarize participants with the applications of the technique in the social sciences.

The application of the structural equation modelling framework to a variety of social science research questions will be illustrated through examples of published papers. The examples used are drawn from recent papers as well as from publications from the early days of the technique; some use path analysis using cross-national data, others confirmatory factor analysis, and other still full structural models, to test particular hypotheses. Some example papers may be found below, though they should not be treated as the gold standard, rather as an illustration of the variety of approaches and reporting techniques within SEM.

• Duff, A., Boyle, E., Dunleavy, K., & Ferguson, J. (2004). The relationship between personality, approach to learning and academic performance. Personality and individual differences, 36(8), 1907-1920.
  
• Garnier, M., & Hout, M. (1976). Inequality of educational opportunity in France and the United States. Social Science Research, 5(3), 225-246.
  
• Helm, F., Müller-Kalthoff, H., Mukowski, R., & Möller, J. (2018). Teacher judgment accuracy regarding students' self-concepts: Affected by social and dimensional comparisons?. Learning and Instruction, 55, 1-12.
  
• Parker, P. D., Jerrim, J., Schoon, I., & Marsh, H. W. (2016). A multination study of socioeconomic inequality in expectations for progression to higher education: The role of between-school tracking and ability stratification. American Educational Research Journal, 53(1), 6-32.
  

Students will engage in a critique of such examples, with the aim of gaining a better understanding of the SEM framework, as well as its application to real-life data. To further facilitate this application focus, the theoretical introduction will be accompanied by practical examples based on real, publicly-available data.

This is the first in a series of three workshops, which extend last term's teaching on 'Decoloniality in Research Methods'. In each session, participants will be presented with a range of theoretical concepts as well as case studies from a variety of scholars who mobilise these concepts to shape their methodologies. At least half of each session will be dedicated to practical application – participants will be encouraged to engage in a range of individual and group reflections, discussions and exercises.

Participants will be encouraged to reflect on how decolonial thought affects each stage of their research project. Beginning with initial research design and literature reviews, and ending with dissemination and research impact, each session focuses on a different stage in the research cycle, bringing a range of decolonial thought and scholar-activism into conversation with our research methods.

Please note: Participants can choose whether to attend a single session or multiple sessions, as each will be a 'stand alone' workshop. However, each workshop must be booked sepaarately.

Workshop 1: Research design and the impact of (de)coloniality on our research projects

In this session we’ll place our disciplines in the historic context of their emergence and ask what implications this historicization has on our research in the present. We’ll then discuss a number of scholars who propose decoloniality and/or decolonisation as theoretical frames through which we can approach our research. In terms of practical skills, we’ll look to the emerging field of citational justice, asking how who and what we cite impacts the work we produce. We’ll also examine our research questions and explore their potential contributions to the reproduction of or resistance to deeper structures of power.

This SSRMP module introduces solicited diaries as a qualitative data collection method. Diary methodology is a flexible and versatile tool which has been used across a variety of disciplines (e.g. public health, nursing, psychology, media studies, education, sociology).

Solicited diaries are particularly powerful in combination with qualitative interviews, enabling the remote collection of rich data on intimate or unobservable topic areas over a longer period of time. This multi-method approach, also known as the ‘diary-interview method’ (DIM), has been originally developed as an alternative to participant observation (see: Zimmerman, D. H., & Wieder, D. L. (1977). The Diary: Diary-Interview Method. Urban Life, 5(4), 479–498.), which makes it an especially attractive qualitative data collection method in Covid-19 times.

In addition to the engagement with pre-recorded videos on Moodle (covering diary methodology basics), you will get hands-on experience with designing your own qualitative diary (3 hours live workshop via Zoom) and trying out the role of a researcher as well as research participant over a 5-day period (teaming up with a module colleague and filling out each other’s diaries). We will reflect on these experiences and answer remaining questions in a final 1-hour live session via Zoom.

The module is suitable for anybody interested in learning more about the method and/or using solicited qualitative diaries in their own research projects.

The neurodiversity module is designed for researchers and academics who wish to expand their knowledge of neurodiversity-friendly practices in research. The module centres around 5 key themes and covers the following:

• What is neurodiversity?

• How does neurodiversity impact research?

• What are specific learning difficulties (SpLD)?

• How do they impact your participants, and the positionality of the researcher?

• Delivering useful approaches and resources

Highlighting the difference between 'integration' and 'inclusion', the content will equip researchers to design the most effective research methods to increase inclusion and lessen the need for 'bolton' practices. The course will also discuss the difference between research design and delivery at the individual level versus the strategic level to be develop universal methods. The course will be practically useful for those wishing to learn about equipment, tools, and techniques additionally available to support researchers and participants alike, and how these can be funded through the University and/or other funding providers.

This is the third and last in a series of three workshops, which extend last term's teaching on 'Decoloniality in Research Methods'. In each session, participants will be presented with a range of theoretical concepts as well as case studies from a variety of scholars who mobilise these concepts to shape their methodologies. At least half of each session will be dedicated to practical application – participants will be encouraged to engage in a range of individual and group reflections, discussions and exercises.

Participants will be encouraged to reflect on how decolonial thought affects each stage of their research project. Beginning with initial research design and literature reviews, and ending with dissemination and research impact, each session focuses on a different stage in the research cycle, bringing a range of decolonial thought and scholar-activism into conversation with our research methods.

Please note: Participants can choose whether to attend a single session or multiple sessions, as each will be a 'stand alone' workshop. However, each workshop must be booked separately.

Session 3: From data collection to analysis to dissemination

In this session, we’ll begin with Linda Tuhiwai Smith’s (2012:226) claim that researchers ‘must get the story right as well as tell the story well’. We’ll think about what it means to analyse our data and create a product (a dissertation, research paper) which exists within the wider context of the academy. We’ll examine six different ways in which different researchers have oriented themselves towards their research, and their research towards the future (including an ‘ethics of care’, ‘rage anger and complaint’, ‘love, empathy, solidarity and desire’ and ‘action, speculation and movement’).

In terms of practical skills, we’ll think about our research outputs, the potential impacts of their design and dissemination and how these considerations might impact the earlier stages of our research projects, such as in the way we collect and store our data. Participants will also be encouraged to think about their own research orientation and place their project into a wider speculative context.

Qualitative research methods are often used in the social sciences to learn more about the world and are often considered to be particularly appropriate for people who might be considered vulnerable. The goal of this course is to encourage students to think critically about the concept of 'vulnerability'; to offer a practical guide to conducting qualitative research that responds to the vulnerabilities of participants and researchers; and to explore ways of challenging and resisting research practices that could be extractive or harmful. It will be highly discursive and will draw throughout on ‘real life’ research examples. The course will be of interest to students who are conducting, or planning to conduct, research with a group considered vulnerable, and will also be of interest to students who want to critically engage with such research in their field.

For a more detailed outline of each session please see the 'Learning Outcomes' section below.

Content warning: Throughout, the course will cover the experience and effects of different forms of trauma. The first session will touch on the lecturer's research with people affected by criminal exploitation.

Content warnings for other sessions will be raised at the end of the preceding session and emailed, where necessary. If you have any concerns you would like to raise with me regarding these matters, please do email the lecturer.

Using secondary data (that is, data collected by someone else, usually a government agency or large research organisation) has a number of advantages in social science research: sample sizes are usually larger than can be achieved by primary data collection, samples are more nearly representative of the populations they are drawn from, and using secondary data for a research project often represents significant savings in time and money. This short course, taught by Dr Deborah Wiltshire of the UK Data Archive, will discuss the advantages and limitations of using secondary data for research in the social sciences, and will introduce students to the wide range of available secondary data sources. Students will learn how to search online for suitable secondary data by browsing the database of the UK Data Archive.

Face-to-face interviews are used to collect a wide range of information in the social sciences. They are appropriate for the gathering of information on individual and institutional patterns of behaviour; complex histories or processes; identities and cultural meanings; routines that are not written down; and life-history events. Face-to-face interviews thus comprise an appropriate method to generate information on individual behaviour, the reasons for certain patterns of acting and talking, and the type of connection people have with each other.

The first session provides an overview of interviewing as a social research method, then focuses on the processes of organising and conducting qualitative interviews. The second session explores the ethics and practical constraints of interviews as a research method, particularly relevant when attempting to engage with marginalised or stigmatised communities. The third session focuses on organisation and analysis after interviews, including interpretation through coding and close reading.

In Lent Term, the course is entirely virtual, comprising the online resources, supported by 3 x zoom Q&A sessions.

Qualitative research methods are often used in the social sciences to learn more about the world and are often considered to be particularly appropriate for people who might be considered vulnerable. The goal of this course is to encourage students to think critically about the concept of 'vulnerability'; to offer a practical guide to conducting qualitative research that responds to the vulnerabilities of participants and researchers; and to explore ways of challenging and resisting research practices that could be extractive or harmful. It will be highly discursive and will draw throughout on ‘real life’ research examples. The course will be of interest to students who are conducting, or planning to conduct, research with a group considered vulnerable, and will also be of interest to students who want to critically engage with such research in their field.

For a more detailed outline of each session please see the 'Learning Outcomes' section below.

Content warning: Throughout, the course will cover the experience and effects of different forms of trauma. The first session will touch on the lecturer's research with people affected by criminal exploitation.

Content warnings for other sessions will be raised at the end of the preceding session and emailed, where necessary. If you have any concerns you would like to raise with me regarding these matters, please do email the lecturer.

The module will introduce students to the study of language use as a distinctive type of social practice. Attention will be focused primarily on the methodological and analytic principles of conversation analysis. (CA). However, it will explore the debates between CA and Critical Discourse Analysis (CDA), as a means of addressing the relationship between the study of language use and the study of other aspects of social life. It will also consider the roots of conversation analysis in the research initiatives of ethnomethodology, and the analysis of ordinary and institutional talk. It will finally consider the interface between CA and CDA.

Open Source Investigation for Academics is methodology course run by Cambridge’s Digital Verification Corps, in partnership with Cambridge’s Centre of Governance and Human Rights, Social Sciences Research Methods Programme and Cambridge Digital Humanities, as well as with the Citizen Evidence Lab at Amnesty International.

NB. Places on this module are extremely limited, so please only make a booking if you are able to attend all of the sessions.

This course will provide a detailed critique of the methods and philosophy of the Null Hypothesis Significance Testing (NHST) approach to statistics which is currently dominant in social and biomedical science. We will briefly contrast NHST with alternatives, especially with Bayesian methods. We will use some computer code (Matlab and R) to demonstrate some issues. However, we will focus on the big picture rather on the implementation of specific procedures.

The module explores Good Data Visualisation (GDV) and graph creation using Python.

In this module we demystify the principles of data visualisation, using Python software, to help researchers to better understand and reflect how the “5 Principles” of GDV can be achieved. We also examine how we can develop Python’s application in data visualisation beyond analysis. Students will have the opportunity to apply GDV knowledge and skills to data using Python in an online Zoom, self-paced, practical workshop. In addition there will be post-class exercises and a 1-hour asynchronous Q&A forum on Moodle Forum.

Ethics is becoming an increasingly important issue for all researchers, particularly in the covid-19 era. The aim of this session is twofold: (I) to demonstrate the practical value of thinking seriously and systematically about what constitutes ethical conduct in social science research; (II) to discuss the new valences of research in the pandemic era and develop new practices to tackle the insecurity it has created.

Two new sessions have been scheduled to replace previous ones which were cancelled.