Sgoil Cheumnaichean Saidheans Sòisealta na h-Alba
With a wide variety of interesting and useful workshops over six days across two weeks, plus opportunities to socialise, join a pub quiz and learn about social science research happening throughout Scotland, our SGSSS Summer School is an exciting way to learn advanced skills, meet other PhD students, and be inspired by ideas and stories.
Queen Margaret University has a modern, beautiful and eco-friendly campus just outside Edinburgh, with its own bus stop, and is right beside Musselburgh Railway Station which is just a few minutes’ journey from Waverley. Musselburgh itself is a historic fishing town with a still-active harbour and two sandy beaches – look out for the silver mussel sculpture!
Accommodation is available for students who are based more than 30 miles away from the venue, and can be requested on our registration form which will open in due course. Travel expenses will be reimbursed in accordance with our expenses policy.
Our Deputy Director for Training, Dr Katy Keenan, has recorded a video to talk you through the Summer School schedule – have a look now:
Check out our schedule below to configure your ideal pathway through the Summer School, and then register via Eventbrite using the button at the top of the page. We look forward to seeing you in June!
led by the SGSSS Research Impact Team
Join the SGSSS Research Impact Team and the Scottish Government to find out more about the opportunities of the SGSSS internship scheme. This session will draw on the real world experiences of hosts and former interns to share the experience of completing an internship as a PhD student. The session will include tips on preparing for an internship, getting the most out of your time on internship and using the experience to enhance your career planning post placement. This will be a participatory session, with lots of opportunities to ask questions to former interns and SGSSS internship hosts including Scottish Government hosts. More details and bios of the hosts and former interns attending on the day will follow closer to the time.
led by Professor John H. McKendrick and Mandy McConville, Glasgow Caledonian University
We will use the example of the work of the Scottish Poverty and Inequality Research Unit to reflect on the ways in which we can use social science research to shape Scottish (and beyond) society for the common good. We will draw on other examples of impactful social science and think critically about the way in which 'impact' is conceptualised and appraised in the REF.
There are no prerequisites for this session - it is open to all who are interested in research impact. The session will comprise traditional lecture sections and interactive activities.
led by Dr Juliane Kloess, University of Edinburgh
As you get started on your PhD journey, this session will introduce you to some strategies and techniques for managing your research project, which will ultimately support your wellbeing. The session will cover the relationship with the supervisory team, time management, and how to keep motivated, all of which will help you stay organised and be productive.
There are no prerequisites for this event.
led by Neha Okhandiar, Emma Devine and Sophie McCall from Research Data Scotland
Research Data Scotland is a not-for-profit charity, established to ensure research in Scotland provides timely public policy insights that can improve lives.
In the first half of this session, you will have the chance to hear about the Researcher Access Service, a new service which was launched in April 2024 and provides a streamlined approvals process for accessing certain datasets for research.
This section will be delivered by Suhail Iqbal our Service Owner and will include:
We will then have a short break, during which we will have an interactive activity for attendees to gain more insights into the datasets we have available through the Researcher Access Service, and how these might be linked for research in the public good.
After the break we will have a presentation from Sophie McCall our Senior Data Analyst, about how Research Data Scotland are making synthetic datasets available for research.
There will also be opportunities throughout for attendees to ask presenters any questions they might have.
led by Dr Roxanne Connelly, University of Edinburgh
[Quantitative data]
As social scientists we aim to influence social policy, to improve people's lives and to build better societies, but we are increasingly recognising that the way we do social science research may have unintended consequences, and a negative influence on research quality. This workshop will introduce you to the arguments for why we need to improve our research practices in quantitative social science research, and you will learn skills which will help you to promote the transparency and reproducibility of your statistical research. Take this workshop to find out why our politicians started standing strangely, if eating potatoes is bad for teenagers, and how you can open black boxes to improve the quality of your research.
Attendees should have some understanding of inferential statistics.
led by Dr Malaka Shwaikh, University of St Andrews
This is a reflective session on navigating ethics, and dealing with trauma, vulnerability and emotions in research. It will build on my research working with and researching prisons and prisoners in multiple global contexts. We will discuss the following topics: reflexive research, navigating vulnerability and emotions, and resilience expectations. No prior learning is required. This would be of value to students conducting research that has elements of vulnerability. I will also encourage students to share overview of their research and relevant experiences then relate it to the topics we discuss.
led by Dr Kiril Sharapov, Edinburgh Napier University
This session provides a practical guide for PhD researchers planning overseas fieldwork, focusing on preparation, logistics, and ethical responsibilities. It highlights the importance of having clear research goals, securing ethical approvals, and understanding the local context before departure. Researchers are encouraged to plan for key practicalities, including visas, funding, healthcare, safety, and IT security, while also being aware of cultural differences, power dynamics, and potential ethical challenges such as corruption or working with local collaborators.
A key theme is adaptability - things will not always go as planned, and researchers must be ready to problem-solve and adjust their approach in the field. The session also emphasises the transition back home, encouraging researchers to shift from data collection to writing without getting stuck in a cycle of chasing more information. Through real-world examples and group discussions, participants are encouraged to think critically about their own fieldwork plans and develop strategies to navigate challenges with confidence and responsibility.
led by Dr Yasaman Sarabi, Heriot-Watt University
[Quantitative Data]
In this workshop, we provide an introduction to Social Network Analysis. Social Network Analysis (SNA) investigates the relations among a certain group of entities. In this session, we will introduce the core concepts and metrics, including centrality measures, network level metrics (i.e. density, centralisation), and sub-group metrics. We explore these in a number of real-world applications. Additionally, we will touch on network data and collection instruments, to give an overview of how to start conducting research with SNA as a method.
There are no prerequisites for attending this session. This workshop aims to be the starting point for researchers interested in employing SNA in their research.
led by Professor Les Back, University of Glasgow
[Qualitative Data]
The most basic task of a researcher is to ask questions. However, this challenge is far from simple, easy or basic. In this session we will explore how to ask questions in a way that enable the people we are listening to. We will focus on the dangers of asking questions in a way that is laden with values or where the researcher runs the risk of presuming that they already know the answers. We will also think about the risk of being fascinated with the dramatic or the spectacular aspects of society and how this might limit what we are listening for. In this session we want to use films called Fieldwork Fables which dramatize social research in action. These scenarios are developed from things that actually happened in the course doing sociological work. We want you to use the films to imagine yourself in the role of a researcher and think about what is done well or poorly. Ellie has been asked to conduct an interview for her social research method class. Her flatmate Sara is a dancer and Ellie is fascinated by Sara’s experience of one particular job she had working in a nightclub in central London.
In the session we will watch together the ‘It’s Not What You Think’ Fieldwork fable film. The questions we will ask are as follows:
This session is most useful for social scientists from sociology, anthropology or media and cultural studies.
Key Reading:
Back, L. (2010) Broken devices and new opportunities: Re-imagining the tools of qualitative research ESRC National Centre for Research Methods Working Paper Series 08/10. [Available electronically at http://bit.ly/15uShQE]
Media Links on formulating questions:
Janis Prince-Inniss Asking Sociological Questions, Everyday Sociology https://www.everydaysociologyblog.com/2011/06/asking-sociological-questions.html
Strategies for Qualitative, Harvard University Dept of Sociology Interviews https://sociology.fas.harvard.edu/files/sociology/files/interview_strategies.pdf
Robin Rogers-Dillon Writing in Sociology – Formulating a Question, Queen College online resources
http://qcpages.qc.cuny.edu/writing/sociology/question.html
Further Reading:
Gunaratnam, Y. (2003) Researching ‘Race’ and Ethnicity: Methods, Knowledge and Power London: SAGE. Chapter 4. Messy Work: Qualitative Interviewing Across Difference
Oakley, A. (1981) Interviewing women: a contradiction in terms, in Roberts, H. (ed.) Doing Feminist Research. London: Routledge. pp. 30-61.
Edwards, R. and Holland, J. (2013) What is qualitative interviewing? London: Bloomsbury.
Fielding, N and Thomas, H (2016) ‘Qualitative Interviewing’, Chapter 15 in N Gilbert and P Stoneman (eds) Researching Social Life, pp.281-300. London: Sage.
Finch, J. (1984) '”It's great to have someone to talk to”: ethics and politics of interviewing women’, in Bell, C. and Roberts, H. (eds) Social Researching: Politics, Problems, Practice. London: Routledge. Reprinted in Hammersley, M. (ed) (1993) Social Research: Philosophy, Politics and Practice. London: Sage.
Gray, D (2018) ‘Interviewing’, Chapter 15, in Doing Research in the Real World, pp.377-404. London: Sage.
Holstein, J. and Gubrium, J. (2011) The active interview, in Silverman, D. (ed.) Qualitative research: issues of theory, method and practice. London: SAGE, pp. 140-161.
Holt, A. (2010) ‘Using the telephone for narrative interviewing: a research note’, Qualitative Research, 10(1), pp. 113-121.
King, N and Horrocks, C (2010) Interviews in Qualitative Research. London: SAGE.
Kvale, S., and Brinkmann, S., (2008) InterViews: Learning The Craft Of Qualitative Research Interviewing. London: SAGE.
Marvasti, A., Holstein, J. and Gubrium, J. (2012) The handbook of interview research. London: SAGE
led by Dr Diarmuid McDonnell and Dr Roxanne Connelly, Associate Directors, SGSSS
You've prepared your manuscript for publication, now what? In this workshop, students will learn to navigate the submission and review stage of the academic publication process, including how to interact with journal editors and reviewers. In the first half of the session, we will consider and workshop some strategies for writing effective cover letters and response to reviewers' comments. The second half of the session will be a panel discussion and Q&A featuring current editors of leading social science journals: Prof Jamie Pearce, current Senior Editor (Medical Geography) of Social Science & Medicine and co Editor-in-Chief of Wellbeing, Space & Society; Dr Roxanne Connelly, Associate Editor of European Societies, and some current students to share their experiences, tips and suggestions.
led by Professor Andrew Smith, University of Glasgow
[Qualitative Data]
This session is intended for anyone who might be considering the use of focus groups as part of their research project. It will introduce and consider the use of focus group and reading group as a distinctive method of qualitative research. It will reflect on what focus groups are good for – what they can help us better understand or explore – as well as recognizing the limitations and challenges of this kind of research. We will also reflect on the practicalities of recruiting for, organizing and running, these kinds of session.
The session will involve a mixture of mini-lectures and small-group work intended to give you a chance to try out, and to reflect on, the running of focus group type discussions.
led by Professor Alan Marshall, University of Edinburgh
[Quantitative Data]
This workshop will teach you how natural experiments can be used in the social sciences as a tool to provide stronger evidence for causal connections between variables than in observational studies.
The workshop covers:
By the end of the workshop participants will:
Requirements
Participants should be competent in the use of statistical software such as Stata, and in running analyses using code. Participants should be confident in the use of inferential statistics including regression. You will need to bring your laptop to the workshop to participate in the computer lab elements. You should ensure Stata is installed on your laptop before attending the workshop.
led by Professor Jo Edson Ferrie, University of Glasgow
The course draws on recent work around research integrity, notably from the Economic and Social Research Council but also from experts working in the forefront of the field. As well as explaining what we mean by research integrity, we will explore why it is important by thinking about the consequences where integrity standards are not met. By assessing what 'bad' research looks like, we can reach an acceptance of what 'good' research looks like. In this session we will explore this threshold of 'good' research as an 'industry standard' but also consider personal standpoint and disciplinary traditions.
No prior learning is needed. The session will be lecture-based with opportunities to reflect on our individual views about the themes addressed.
Professor Sarah Skerratt, Chief Executive of the Royal Society of Edinburgh discusses research impact in our 2025 Summer School Keynote Speech.
Doing research gives each one of us the opportunity to benefit others through our work. But how can we do that? And how do we know if we’re doing that? Through some examples, I’ll try to illustrate the challenges of, and pathways to, ensuring we can have impact. This includes: asking ourselves why we are researching a particular topic; who we need to work with to get the best understanding; how we plan for impact from the beginning, including via evaluation; how listening and dialogue are as important as speaking; and how learning about each other’s “inner worlds” is crucial to making a difference in policy and in practice. Some of my reflections will be based on research I have carried out in rural mental health and rural poverty; I’ll also be looking back on my early days as a PhD student and my journey since then. I really look forward to talking with you about bringing research to life for ourselves and others.
Join the SGSSS team and your fellow students for an informal drinks reception to celebrate the first day of Summer School.
led by Dr Diarmuid McDonnell, University of the West of Scotland
[Qualitative and Quantitative Data]
Computational methods are transforming research practice across the disciplines. For social scientists these methods offer a number of valuable opportunities, including creating new datasets from digital sources; unearthing new insights and avenues for research from existing data sources; and improving the accuracy and efficiency of fundamental research activities.
In this one-day course you will learn how to apply computational methods for the processing and analysis of textual data. Using Python and R, you will develop skills in preparing textual data for computational analysis; and core methods of text data analysis (e.g., sentiment analysis, topic modelling).
Attendees should bring their own devices with the ability to access a Web browser (WiFi is available at the venue).
led by Emma Davidson and Helen Berry, Binks Hub, University of Edinburgh
[Qualitative Data]
This workshop offers a creative and hands-on guide to participatory research approaches and methods. By sharing our own research experiences, we will reflect on the different forms that participatory research can take. We will consider the practicalities of setting up your project, as well as offering ‘hands-on’ experience using a range of creative tools that can be employed at different cycles of the research. Students will work together to identify and discuss the limitations and challenges of participatory research approaches, including issues related to process, ethics, engagement, analysis, and impact.
Attendees will be sent a video and a reading to review in advance of the session.
led by Dr Thees Spreckelsen, University of Glasgow
Data drives decisions, discoveries, and public discussion. Data visualisations can act as an easily accessible support of these. They are analysis tools as the key means to communicate insights from data. This course will enable you to generate impactful visualisations, to plan and assess graphs that provide analyses, and to report on quantitative data in a systematic, accessible and trustworthy way.
We will explore the process of planning visualizations and the wide range of possibilities they offer. Additionally, we will discuss how to create and present these visualizations in a trustworthy and accessible manner.
You will receive an introduction to using the R software to generate graphs. This will include basic data preparation and an in-depth training session on the 'ggplot2' graphics package. You will also learn how to use the reporting tool 'RMarkdown,' which enables transparent and highly versatile presentations of visualizations and any accompanying media (e.g., presentations, documents, webpages, or dashboards). Together, these tools will equip you to produce and report a variety of commonly used visualizations.
The session will combine presentations, reflective exercises, and hands-on programming training, allowing you to work directly on your own computer.
Learners will need their own device (preferably a laptop). A series of introductory recordings will be made available to learners one week prior to the course. These will contain a 1) step-by-step guide to installing the free software beforehand; 2) Warm-up materials on how to use R, and 3) a first glimpse at the overall course content.
led by Dr Faical Akaichi and Chen Ai, Scotland's Rural College
[Quantitative Data]
This all day course is designed to be gentle introduction to the basics of bivariate analysis and regression analysis in the open-source software RStudio.
We will cover these topics:
Some preparatory work is required: All students will receive a tutorial booklet prepared by the lecturer to read before the in-person session and will provide a theoretical overview of these topics. The in-person session will be dedicated to practical work conducting the bivariate and regression analyses in RStudio. The students will be provided with the data and the R code and will be guided through the analysis process. The lecture will also teach the students how to interpret the results and use them in prediction and policy analysis.
Students should bring their own devices and need to ensure they have R and RStudio installed.
led by Professor Paul Lambert, University of Stirling
[Quantitative Data]
In this session we introduce and reflect upon the role of multilevel models in applied social research, and provide practical training materials which demonstrate ways of running multilevel models in survey data analysis scenarios.
Multilevel models are popular in the social sciences as statistical analytical devices which can be useful in a variety of scenarios where data has a complex or 'clustered' structure. The most popular formats for running multilevel models are outlined in session materials and illustrated in multiple software environments (using Stata, SPSS and R). There remain plenty of situations, however, when the added value of using a multilevel model is ambiguous, and there are different views on the best strategies to use activities such as specifying, estimating, and interpreting suitable models. As well as giving introductory accounts, lecture and workshop materials also provide critical reflections on the place of multilevel models as statistical analytical procedures in applied social research, and describe and explore enduring debates about these methods.
The session activities will comprise approximately 3 hours' worth of lecture-based materials and approximately 2 hours of practical workshop activities. Lectures are likely to comprise four talks each in sessions of around 45 minutes, and two practical workshops, each around 60 minutes. Lectures will introduce and reflect upon multilevel models in social research, with opportunities for questions and answers and discussion. Workshops will involve computer-based exercises which open existing datasets and run multilevel models on them, guided by software example files that are provided to participants.
The session is suitable for people who have at least some previous statistical analysis training and experience, and at a minimum are used to reading descriptive statistical results (tables and graphs), and have seen at least some examples of popular types of regression model (such as multiple regression models or logistic regression models). The session ought to be helpful for participants who have only a little statistical background, as it will use an introductory style to describe the features of multilevel models, and improve participants' confidence in this approach. The session should also be useful to people who already have a more extensive statistical methodology background, as materials also provide critical reflections on strengths and limitations of the approach and explore selected advanced issues.
led by Professor Jo Edson Ferrie, University of Glasgow
[Qualitative Data]
Though well established as a methodology, discourse analysis (DA) can be an elusive methodology when learning. This session will map the socio-historical context of DA, from its roots in semiology and through the ethnomethodology that characterized much 1970s social research. Theory will be explored, particularly contributions from Foucault around power. We will draw explicitly too on two frameworks including Fairclough and Potter and Wetherall. Throughout this session students will have the opportunity for hands-on qualitative work as they practice with real-world data. The session will build towards an understanding of how discourse analysis becomes critical as we explore the purpose of social research, not just as a means to know, but as a tool for change.
led by Sidonie Ecochard, PhD student at the University of Strathclyde
This session offers a space to reflect on the doctoral journey and explore the PhD as an emotional and embodied process, unique and personal to each student. Through gentle movements, mindfulness practices and reflection exercises, the attendees will be invited to consider their academic journey beyond notions of output, career trajectory and destination. This session will approach the PhD as a process, journey, and stage of life. The attendees will be invited to reflect on how the PhD may fit within the context of one’s broader life, sometimes bringing complications but also enriching experiences and relationships.
The session is accessible and inclusive to all, and no experience of mindfulness is required to participate.
Directed by Dr Itandehui Jansen, Screen Academy Scotland at Edinburgh Napier University
We are excited to host a special screening of Itu Ninu (2023), an environmental sci-fi film.
Running time 72 mins.
In the not-so-distant future of 2084, Ángel finds himself trapped as a climate migrant in an undisclosed city, where surveillance reigns supreme. Amidst a bleak and oppressive existence, Ángel makes a living by cultivating plants, preserving the fading wisdom of seeds. Within this desolate landscape he crosses paths with Sofia, another climate migrant toiling away at a recycling facility. Fate intertwines their lives when a chance encounter reveals an unexpected connection: a shared language. Fueling Ángel’s longing for human connection and a glimmer of hope, he reaches out to Sofia. Aware of the omnipresent digital monitoring, Ángel decides to communicate with her through the timeless medium of pen and paper, fostering an intimate, clandestine bond. As their secret correspondence unfolds, a friendship grows between Ángel and Sofia as does their desire for liberation from excessive control.
This film will be of interest to all social science PhD students, especially those researching environment, migration, and linguistics. See the trailer here: https://ituninu.com/
led by Dr Dely Elliot, University of Glasgow
In this workshop, I will explore in more depth the concept of the ‘hidden curriculum’, what it is, what it entails in practice and why it is inherent in the doctoral journey. I will discuss the shift from its previous negative connotation towards a new conceptualisation that is more positive, relevant and useful for doctoral scholars. This will lead to discussing the necessity to make the hidden curriculum visible. If harnessed well, I argue that the hidden curriculum can complement existing formal institutional provision to support doctoral progression, well-being and eventual completion. In this workshop, I also aim to highlight an expanded model of 'the hidden curriculum' and its three domains, i.e. 'Structured pedagogies (required); 'Informal pedagogies (optional); and 'Not yet existing pedagogies' (intentional) – offering exemplars in terms of its aims, sample activities, approaches, tools, hidden curricular learning, added benefits, etc.. The concept of the hidden curriculum will then be explored further in relation to Development Needs Analysis (DNA). Examining the link between these two crucial concepts is intended to assist doctoral scholars to plan more effectively their personal and professional journeys of growth and development not only to achieve a successful, meaningful and timely PhD completion, but also in preparation for a dynamic post-PhD career.
This session will be a combination of presentation, Q&A and workshop activity.
References/pre reading:
Now well established as a part of Summer School, the wonderful Beirhope Alpacas will be joining us again in 2025.
Come along to this drop-in session to meet Lynne and her herd of alpacas - feed them snacks, take them for a walk around the green, and learn more about their lives on a smallholding in the Scottish Borders. Direct interaction with the alpacas is not a requirement and you are welcome to look from afar if you prefer!
Please note that there will be students participating in a Multi-Species Ethnography training session at the same time. They may be observing, and asking questions of attendees who are willing to contribute.
You can read more about Beirhope's environmental responsibility policy here: https://www.beirhope.co.uk/ourresponsibilities
led by Professor Nicholas Jenkins, University of the West of Scotland
[Qualitative Data]
Could you analyse a play by only observing half of the cast? It seems impossible - yet this is exactly what happens when we undertake social research and ignore the roles animals play in our social world. In this short session, we will critically explore how incorporating ‘more-than-human’ viewpoints and experiences into social research can yield richer accounts of social life and open up new possibilities for addressing contemporary social challenges. We will experiment with multi-species research techniques through hands-on exercises, interactive discussions, and real-world observations—some of which may take place outdoors (so bring suitable clothing and footwear). No prior knowledge is required, but familiarity with ethnography and symbolic interactionism may be helpful. By the end of the session, you will have conceptual and practical tools you can use to bring multi-species perspectives into your own research—whether that means rethinking your fieldwork, expanding your theoretical framework, or challenging human-centric assumptions in your discipline.
This session is suitable for anyone with an interest in the topic, but students with backgrounds in social anthropology and sociology may find it particularly relevant, as would students 'crossing over' from the natural sciences (e.g. veterinary and zoological sciences).
There will be some introductory readings shared in advance to help prepare students, and there may be a pre-course practical activity.
After an exciting day of learning new things and meeting your fellow PhD students, why not come and win some prizes at our legendary SGSSS Summer School Quiz Night? There are goodies and glory to play for, and snacks provided.
Taking place in Maggie's, the student union bar at Queen Margaret University just a short walk from the Summer School sessions, this is a great way to round off your day two of Summer School.
More details will be provided to Summer School attendees closer to the time.
led by Dr Helen Packwood, University of Edinburgh, and Professor Nissa Finney, University of St Andrews
[Qualitative and Quantitative Data]
This workshop will examine how we integrate different forms of knowledge in social science research, with particular emphasis on the integration of small and large scale (qualitative and quantitative) approaches and data. It will begin by asking fundamental questions such as: What is mixed methods research? Why undertake mixed methods research? What are the opportunities and challenges with integrating different forms of data? Where should I begin? How do I write up mixed methods work? After consideration of the theory and foundations of mixed methods research, we will reflect on real-world case study examples in discussion groups.
This workshop is designed to support doctoral students who are undertaking a mixed methods project but is open to anyone interested in an introduction to mixed methods research.
This interactive workshop will introduce the theory and practice of mixed methods research using discussion, group work and input from the front.
led by Professor Georgios Leontidis and Matthew Beddows, University of Aberdeen. This session is run in partnership with SUSTAIN CDT, which is a UKRI AI Centre for Doctoral Training in Sustainable Understandable agri-food Systems Transformed by Artificial INtelligence.
[Qualitative and Quantitative Data]
This course will introduce core machine learning concepts, including the practical use of large language models for coding, with an emphasis on hands-on practice using relatable examples and discussing ethical implications.
The session will cover key aspects of data generation—primarily using synthetic data—while addressing a subset of tasks such as mental health survey data, personality survey data, sentiment analysis, time-series analysis, fairness audits, and psychometrics, among others. Participants will explore how machine learning can be applied to real-life tasks.
The session will blend theory and practice, covering topics and concepts related to supervised and unsupervised learning, data processing, model evaluation, privacy concerns, and ethical implications. Hands-on activities will be included, and participants will actively use large language models such as DeepSeek, ChatGPT, and Claude to understand their applications in coding exercises and visualisations.
By the end of the session, participants will have gained a basic understanding of machine learning models, their applications and evaluation, and the implications and limitations of using them for data analysis and predictive modelling.
No prior knowledge is required to follow the session. However, it would be beneficial to explore Google Colab in advance, particularly by setting up a Gmail account to access it and reviewing some of Colab’s tutorials that use Python. That said, there is no expectation that participants will have any prior experience with Python.
led by Dr Katy Keenan, University of St Andrews and Dr Alasdair Stewart, University of Glasgow
[Qualitative Data]
This one-day in person workshop will introduce the basics of using NVivo for qualitative research projects. This is ideal for those who are new to NVivo, or would like a refresher. Students will be introduced to the NVivo software and learn how to do some fundamental tasks.
In the morning session we will cover:
In the afternoon we will show you some more advanced analysis features:
We will use some curated open access qualitative data (the Qualitative Election Study of Britain). However, there is an opportunity to discuss how to use NVivo to manage your own project.
The session will be taught using computer terminals using the Windows version of Nvivo (version 14). You do not need to provide your own device.
led by Dr Natalie Bennett, University of Sheffield. This session is run in partnership with White Rose DTP.
[Quantitative Data]
Multilevel models allow researchers to analyse data with a clustered structure—for example, pupils nested within schools or individuals within neighbourhoods. Recently, a variation of multilevel modelling has been developed to study intersectional inequalities in individual outcomes. The Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) approach nests individuals within their intersectional strata—that is, their unique combination of sociodemographic identity categories, such as gender, age, ethnicity, and social class. This method holds great potential for uncovering and understanding intersectional inequalities, where multiple social identities interact in complex ways to shape societal (dis)advantages.
This one-day training course will provide a brief introduction to multilevel modelling, followed by an overview of the intersectional MAIHDA approach. The course will cover the basics of two-level random-intercept multilevel models, how to apply this model within the MAIHDA framework, key statistics generated by the approach, examples from the literature, and guidance on visualizing the results.
Topics
1. Overview of multilevel modelling
2. The two-level random-intercept model
3. Intersectionality: theory and practice
4. Ways of statistically identifying intersectional inequalities: dummy variables and interactions
5. The MAIHDA approach
6. Visualising results from MAIHDA
7. Conceptual and practical challenges with MAIHDA
8. Extensions of MAIHDA
Format
The course will consist of a mix of lectures and hands-on practical sessions applying the taught methods to real datasets (the lectures are software independent). Practical sessions will follow lectures, giving participants the chance to replicate the presented analyses and to consolidate their knowledge. The practicals are offered in participants’ choice of R or Stata and are self-directed: participants complete the practicals at their own pace. At the end of each practical session the instructors demo the different software.
Pre-requisites
We assume no prior knowledge of multilevel modelling. However, participants should be familiar with estimating and interpreting linear regression models, including the writing and interpretation of model equations, hypothesis testing and model selection, and the use and interpretation of dummy variables and interaction terms. We assume you are already users of R or Stata and so have these softwares already installed and know the basics. Participants may wish to have a look at this published MAIHDA tutorial paper prior to attending, although it is not required: Evans, Leckie, Subramanian, Bell, Merlo (2024) A tutorial for conducting intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA). SSM-Population Health, online.
You will need a laptop with up-to-date versions of R or Stata installed, depending on your preference.
Please note that this session finishes at 4.30pm rather than 3pm.
led by Professor Paul Flowers, University of Strathclyde
[Qualitative Data]
This one-day workshop will involve presentation on the background and development of the IPA approach, training and practice in IPA interviewing skills, training and practice with IPA analysis (circa 2021 approach with a particular focus on the development of personal experiential themes) and some discussion of writing and publishing of IPA studies.
The workshop will be as interactive as possible - with minimal listening and maximum engagement from the participants. The actual content on the days will be tailored to the participants and their learning needs. We will mix plenary discussions (with everyone in the room) with small group discussions (four or five participants) and feedback (giving and receiving it from peers and facilitators). Throughout, participants are encouraged to ask questions.
led by Louise Scott, Joe Rennie Taylor and Breda Cullen, Scottish Government
The workshop will introduce students to applied social research in the Scottish Government. You will stand in the shoes of a government social researcher for the first part of the day and will work on a series of scenarios to develop an applied research proposal. This will help you draw out the practical application of methodologies to real world policy scenarios and focus on deliverability of research in a business context. The facilitators will share with you some case studies of where and how evidence informs policy making and delivery, highlighting opportunities for you to share your academic research with policy makers. The day will conclude with a brief outline of career gateways to research roles in government.
led by Professor Adina Dudau, University of Glasgow
This is an interactive session designed to help doctoral candidates navigate and make the most of their supervision experience. No prior knowledge is required—just a willingness to reflect on and engage with strategies for fostering an effective supervisory relationship. Participants will explore key aspects of PhD supervision, including how to seek and use feedback effectively, maintain research progress, and communicate expectations with their supervisor. The session will also cover strategies for personal, professional, and career development, preparing for final examination, and disseminating research. Through a mix of content, discussion, case studies, and practical toolkits, attendees will develop actionable approaches to strengthen their supervision experience and take greater ownership of their PhD journey.
led by Dr Dely Elliot, University of Glasgow, and Dr Rui He, University of Manchester
We will discuss in this workshop what makes international PGR journeys distinct from other PGR journeys and how international PGRs can optimise their own unique journeys. Cross-cultural studies often carry a certain mystique about what lies ahead resulting from the mixed experiences of deliberate and serendipitous cultural interactions during the sojourn. With a view to cultivating holistic development of doctoral scholars, we offer a new model for understanding what could underpin the quality of international scholars’ experience. Drawing from Psychology, we are using metacognition and Self-Determination Theory to elucidate the inherent potential, challenges and uncertainties embedded in the international sojourn. During the workshop, we will collectively examine how the concepts and principles in this model can be applied by participants to make the most of their doctoral experience abroad. While the focus of this presentation is on the international PhD experience, we argue that it also has importance for other doctoral scholars, the doctoral community and the wider institutional community.
This session will be a combination of presentation, Q&A and workshop activity.
Reference:
Elliot, D. L. (2023) Navigating Your International Doctoral Experience (and Beyond). Series: Insider guides to success in academia. Routledge. ISBN 9781032220505 (https://doi.org/10.4324/9781003271000)
led by Professor Anna Morgan-Thomas, University of Glasgow
Generative AI holds the potential to significantly transform academic publishing by enhancing the writing process, optimizing peer review, and broadening research dissemination. However, this promise is accompanied by notable risks related to accountability, integrity, and bias (Májovský et al. 2023). To date, the dialogue surrounding the potential and perils of AI has predominantly been spearheaded by the natural sciences, particularly medicine (Misra et al., 2023). This Professional Development Workshop (PDW) seeks to extend the conversation to explore the specific implications of generative AI in the realm of social science (Budhwar et al., 2023).
The session will commence by exploring the advantages offered by AI tools, such as aiding non-native English speakers in manuscript preparation (Kacena et al., 2024), delivering instantaneous feedback (Lund et al., 2023), and automating the initial screening of manuscripts (Lund et al., 2023). The ability of AI to democratize access to scientific knowledge is contrasted with urgent ethical considerations like the question of authorship (Lee et al., 2023), concerns of plagiarism, and preserving the integrity of scientific communication (Májovský et al., 2023), intellectual property rights (Inam et al., 2024), as well as the potential for ingrained biases (Lund et al., 2023).
This workshop will delve into these complex issues, aiming to provide attendees with a comprehensive understanding of the influence of AI on academic publishing and the ability to ethically navigate its use. Participants will examine the latest guidelines from academic publishers in the field of management and discuss the ethical integration of AI into scholarly communication, thereby ensuring the quality and integrity of academic outputs.
led by Dr Galina Oustinova-Stjepanovic, University of Glasgow
[Qualitative Data]
The session examines how archives are used and assembled to promote social and criminal justice. Starting with a theoretical discussion of non-representational and collaborative methodologies and their temporalities, the session challenges the privileged status of the archive in creating truth-claims about the past or now. Instead, the session looks into ways to harness archival authority to pursue fugitive justice, or difficult to envisage, let alone achieve, redress. The workshop moves away from documentary methodologies of reading, writing, and analysing historical materials to emancipatory, praxis-oriented methodologies of human rights activists, conflict archives, as well as community and indigenous production of archives.
There will be a required piece of pre-reading for this session.
led by Dr Dely Elliot, University of Glasgow, and Dr Dangeni, Anglia Ruskin University
[Qualitative Data]
This workshop provides an introduction to the visual method (i.e. River of Experience interviews) and the audio diary method. Participants will engage in the design and implementation of a study using these two creative methods and gaining practical experience through guided activities. The session will conclude with a discussion of key methodological, ethical and logistical considerations for researchers who want to apply creative methods in other research contexts or settings.
References:
Dangeni, Elliot, D. L. and MacDiarmid, C. (2021) Audio diaries: a creative research method for higher education studies in the digital age. In: Cao, X. and Henderson, E. F. (eds.) Exploring Diary Methods in Higher Education Research. Series: Research into Higher Education. Routledge: Abingdon. ISBN 9780367345211
Iantaffi, A. (2012). Travelling along ‘rivers of experience’: Personal construct psychology and visual metaphors in research. In P. Reavey (Ed.), Visual methods in psychology: Using and interpreting images in qualitative research (pp. 271‒283).
led by Louise Scott, Deputy Chief Social Researcher, and Breda Cullen, Principal Researcher, Scottish Government
Do you want your research to have policy impact but don't quite know how? Are you keen to learn more about how best to engage with the Scottish Government when conducting your research? In this online session, hear from officials from the Office of the Chief Researcher about a range of opportunities for engaging with the Scottish Government and creating the conditions for enhancing the policy relevance of your academic work.
led by Dr Katherine Auty, University of Cambridge
[Quantitative Data]
This course aims to introduce students to the fundamental concepts of Bayesian theory. It provides a foundational understanding of the principles, methods, and applications of Bayesian statistics, which offers a robust framework for data analysis and decision-making by incorporating prior knowledge and uncertainty in a structured way. The course will cover essential topics such as Bayes' theorem, prior and posterior distributions, likelihood functions, and the key distinctions between Bayesian and frequentist approaches. Students will learn how to build and estimate statistical models, update beliefs with new data, and make decisions based on the posterior probabilities derived through Bayesian inference. By the end of the course, students will have the skills to conduct Bayesian data analysis, interpret the results, and apply Bayesian methods in a range of practical situations.
Attendees should have basic statistical knowledge including regression analyses, and should have R downloaded and available on their devices. Video recordings will be available to review prior to the session.
Students are expected to attend both parts of this training.
led by Cristina Magder, UK Data Service
Join us for a three-hour interactive workshop focused on the best practices for managing social sciences research data, either primary or secondary. This session will help you handle your research data responsibly and ethically, regardless of your experience.
We will explore the entire data lifecycle, covering everything from planning and organising your data to sharing it appropriately and ensuring it is preserved for the long term. While prior knowledge of research data management isn’t required, having a basic understanding of research design and data collection could be helpful.
By the end of the workshop, you will:
- Gain a solid grasp of the key principles of research data management (RDM) for all types of research data.
- Understand the importance of, and learn how to write a Data Management Plan (DMP).
- Familiarise yourself with the ethical and legal requirements for managing research data.
- Discover best practices for organising, documenting, storing, and backing up your data.
- Understand the importance of data quality and metadata standards.
- Find out how to preserve and share your data responsibly.
- Learn about various semi-automated tools that can help streamline your data management processes.
We will keep things engaging with the following:
- Presentations covering key RDM concepts.
- Hands-on exercises using platforms like Padlet and Menti.
- Case studies that tackle real-world data management issues.
You will leave this workshop with practical strategies that you can easily apply to your research projects.
led by Dr Roxanne Connelly, University of Edinburgh
[Quantitative Data]
We often learn statistical data analysis skills using data which is assumed to arise from a simple random sample of the target population. However, most large-scale multi-purpose social survey data resources use complex sampling strategies. If you are analysing data with a complex sample design, you will need to take this into account in your statistical analyses. This workshop will explain why complex samples are used, the implications of complex samples for statistical data analysis, and approaches to analysing complex samples data. Whilst this workshop is primarily focussed on the analysis of social survey data resources, the principles can be more widely applied to other forms of made and found data. Examples will be provided in Stata and R.
This workshop assumes an understanding of inferential statistics including regression, and familiarity with Stata or R.
led by Dr Alasdair Stewart, University of Glasgow
This online session introduces "critical genAI literacies" to explore ethical, epistemic, and practical considerations in using generative artificial intelligence. It aims to provide an understanding of the strengths and limitations of genAI models to help inform decisions on whether, when, and how to use these tools in research and learning contexts.
This session will cover:
- How genAI models, such as ChatGPT, are made and actually work.
- Ethical and practical risks associated with genAI.
- Critical and pragmatic considerations for crafting prompts.
- Maintaining academic integrity when using genAI tools.
- Using genAI to support, rather than replace, learning.
The session includes time for discussion and practical experimentation with prompting techniques. Custom GPTs have also been setup for the session to illustrate ways to use genAI as sounding boards, learning aids, and tools for working with files and data.
No prior experience with generative AI is required. A free(!) ChatGPT account is required to use the custom GPTs setup for the session. However, it is also possible to copy/paste the instructions used for the custom GPTs - provided in the online materials accompanying the session - into other genAI tools.
led by Professor Jim Boyle, University of Strathclyde
Following this session students will be able to demonstrate an awareness of the advantages of systematic reviews over non-systematic reviews, and of the mechanics of conducting a systematic review.
The following steps will be considered: (i) formulating research questions; (ii) searching the literature (search strategies, databases, inclusion and exclusion criteria, search terms, reference management software, PRISMA flow diagram); (iii) data extraction; (iv) quality assessment (weight of evidence, critical appraisal checklists); (v) analysis and synthesis of systematic quantitative reviews, systematic qualitative reviews, systematic scoping reviews and umbrella reviews; and (vi) writing up the results. Toolkits for systematic reviews including generative AI tools will also be discussed.
led by Professor Norin Arshed, University of Strathclyde
This online workshop focuses on understanding impact and on how you could inform and influence government policy in your areas of research and expertise. In this session, we’ll dive into the crucial questions: What is impact, why is it important, and why should you start thinking about it now? Through a blend of lecture, discussions, and interactive exercises, you’ll explore the key aspects of impactful research, including how to align your work and methodology with broader policy, and stakeholder needs.
You’ll also learn practical skills to conduct research that has a tangible impact by carefully considering your methodology and working closely with relevant stakeholders. We’ll explore case studies, including Professor Arshed’s own work on Enterprise Policy for informing and influencing the Scottish Government.
This workshop will be divided into interactive segments, including:
This session is open to all PhD students, regardless of year, who are interested in learning how to make their PhD impactful. Professor Arshed’s work focuses on enterprise policy – the formulation, implementation and exploitation of the policy itself. She has been exploring women’s enterprise policy, unconventional entrepreneurship, scale-ups, the entrepreneurial ecosystem and contextual entrepreneurship. Much of her work draws on institutional theory.
led by Dr Kendra Briken, University of Strathclyde
Overview of the session:
[Qualitative Data]
This workshop is aimed at people who are considering and/or actively designing a project that compares case studies. It is cross-disciplinary across the social sciences and focussed on the logics and underpinnings, or, first principles of comparative case studies. The workshop engages two logics of comparison: the probably most common compare and contrast; and a ‘tracing’ across sites or scales. We will reflect on three axes: horizontal, vertical, and transversal comparison, and how power relations need to be included. In doing so, the workshop will allow to engage actively with the foundations of comparative case study research, and for participants to situate their own approach in context. During the interactive workshop session, we will discuss challenges for case study research beyond practicalities. To start, we will use the example of an international comparative case study focussing on public sector employment regimes, and discuss underlying assumptions..
Collectively, we will challenge the method on three epistemological levels:
• What is captured by comparative case studies in different disciplines?
• What would interdisciplinary perspective add to our assumptions?
• Through the lens of feminist/intersectional perspectives, and considering attempts to decolonise research: How do our underlying assumptions reflect hegemonic power relations?
Prior learning required:
Participants are strongly encouraged to prepare for the workshop by reading a textbook chapter of their own choice. The pre-reading will be part of the reflection.
What will be learned?
Comparative Case Study research differs highly between discipline-specific approaches. This workshop will not cater towards disciplinary detail, but aims at shaping and sharpening individual approaches to unsee limitations and actively engage with these. The aim of the workshop is to establish a critical and collective understanding and to prepare for working in ever moire interdisicplinary teams, a globalised world, and in planetary crisis moments.
What kind of activities will be undertaken during the training?
The 4 hours online will include the necessary breaks to allow for inclusivity. Based on shared prompts, we will use Padlet as a collective learning space so that additional material can be made available to participants. The shared workspace will remain open for two weeks after the event to allow for continuing collective discussion. With consent sought from participants during the workshop, the results will be captured and shared within the group.
led by Dr Diarmuid McDonnell, University of the West of Scotland
[Quantitative Data]
Many interesting social phenomena follow processes of change that are not directly observable but can be inferred using statistical models. The classical example is the development trajectories of infants and children (e.g., height and weight) but many other outcomes are amenable to what are known as growth-curve analytical approaches e.g., career earnings trajectories, area-level change in business or charitable activity.
This short course will outline the fundamental concepts and approaches for estimating trajectories of change for social science phenomena, and includes practical examples and exercises using R and Stata.
led by Dr Emmanuel Olamijuwon, University of St Andrews
This workshop provides an introduction to the fundamental principles and practices of data visualisation using R. The workshop is targeted at beginners and will cover the essential concepts and techniques for transforming raw data into meaningful, visually appealing representations. Participants will learn how to leverage R’s powerful visualisation libraries to create various types of charts, graphs, and plots, enabling them to communicate data-driven insights effectively. By the end of the workshop, students will be able to explain key foundational concepts in human perception of data, describe practical approaches for data visualisation and understand how to create a range of impactful data visualisations in R.
Participants should have basic R programming skills.
led by Dr Juliane Kloess, University of Edinburgh
As you get started on your PhD journey, this session will introduce you to some strategies and techniques for managing your research project, which will ultimately support your wellbeing. The session will cover the relationship with the supervisory team, time management, and how to keep motivated, all of which will help you stay organised and be productive.
There are no prerequisites for this event.
led by Dr Katherine Auty, University of Cambridge
[Quantitative Data]
This course aims to introduce students to the fundamental concepts of Bayesian theory. It provides a foundational understanding of the principles, methods, and applications of Bayesian statistics, which offers a robust framework for data analysis and decision-making by incorporating prior knowledge and uncertainty in a structured way. The course will cover essential topics such as Bayes' theorem, prior and posterior distributions, likelihood functions, and the key distinctions between Bayesian and frequentist approaches. Students will learn how to build and estimate statistical models, update beliefs with new data, and make decisions based on the posterior probabilities derived through Bayesian inference. By the end of the course, students will have the skills to conduct Bayesian data analysis, interpret the results, and apply Bayesian methods in a range of practical situations.
Attendees should have basic statistical knowledge including regression analyses, and should have R downloaded and available on their devices. Video recordings will be available to review prior to the session.
Students are expected to attend both parts of this training.
led by Dr Emmanuel Olamijuwon, University of St Andrews
This workshop provides an introduction to the fundamental principles and practices of data visualisation using R. The workshop is targeted at beginners and will cover the essential concepts and techniques for transforming raw data into meaningful, visually appealing representations. Participants will learn how to leverage R’s powerful visualisation libraries to create various types of charts, graphs, and plots, enabling them to communicate data-driven insights effectively. By the end of the workshop, students will be able to explain key foundational concepts in human perception of data, describe practical approaches for data visualisation and understand how to create a range of impactful data visualisations in R.
Participants should have basic R programming skills. Students are expected to attend both parts of this training event.
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