National Centre for Research Methods

Critical Praxeological Analysis (CPA) is a new approach which provides a way of conducting critical qualitative research. 

Critical Praxeological Analysis (CPA) synthesises ideas from three key areas: Wittgensteinian philosophy, particularly the method of grammatical investigation; ethnomethodology and conversation analysis, with a focus on praxeological gestalts; and critical research, especially critical phenomenology. This synthesis provides a robust method for critical qualitative research. 

In this two day online advanced course, the authors of the approach, Khadijah Diskin and Phil Hutchinson, will help participants identify and plan a project of study, handle data, and make a start on developing a research article. 

This course will assume an understanding of the basics of CPA and spend minimal time on a brief recap of these (see NCRM's online course Introduction to CPA - 10-11 September 2025  if you feel you need an introductory course first). 

The idea is for participants to make significant progress on work towards a CPA article for publication, either individually or working with other participants on the course as co-authors. The convenors will provide advice on every stage of the process and offer follow-up 1:1 sessions to participants.

The course (22 October) will focus on supporting participants in designing and carrying out a project and writing a paper. Two weeks after the course (29 October) there will be a data session, where those who attended the course can bring their data for the group to analyse. 

By completion of the course:

• Participants will have made a start on a CPA project and in some cases a paper for publication.
• Participants will learn and understand the stages of CPA project design.
• Participants will have hands-on experience of handling and analysing data as a CPA researcher and participating in a data session.
• Participants will have tips on overcoming the hurdles which are commonly faced in a CPA project.
• Participants will have the opportunity to make use of subsequent support sessions, which will support them to the completion and submission of their paper over 8 months following the course.

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In this online course, run over two mornings, we will show you how to prepare and conduct spatial analysis on a variety of spatial data in R, including a range of spatial overlays and data processing techniques. We will also cover how to use GeoDa to perform exploratory spatial data analysis, including making use of linked displays and measures of spatial autocorrelation and clustering.

The course covers: 

• Understanding and being able to interpret Spatial Autocorrelation measure Moran's I
• Understanding Local Indicators of Spatial Association statistic
• Perform Spatial Decision Making in R
• Perform Point in Polygon analysis using different approaches
• Be aware of the advantages and disadvantages of using point based or polygon based data
• Using buffers as a part of spatial decision making

By the end of the course participants will:

• Be aware of some spatial statistics concepts and be able to apply them to their own data using GeoDa
• Be able to perform spatial decision making 
• Understand the limitations and benefits of working with data in this way

This course is aimed as PhD students, post-docs and lecturers who have some existing knowledge of using R as a GIS and want to develop their knowledge of spatial stats and spatial decision making in R. Some prior knowledge of both R and GIS is required. It is also appropriate for those in public sector and industry who wish to gain similar skills. 

Students will be using R, RStudio and GeoDa. 

Students need to have completed my Introduction to Spatial Data and Using R as a GIS (https://www.ncrm.ac.uk/training/show.php?article=13142) course, or have equivalent experience.

This includes:

• Using R to import, manage and process spatial data
• Design and creation of choropleth maps
• Use of scripts in R
• Working with loops in R to create multiple maps

For more information, please look at the link.

Students will need R (v > 4.0), and the sf, tmap, dplyr libraries. They will also need RStudio (v > 2023.01 or greater)

No prior knowledge of GeoDa is needed. It can be downloaded following the instructions at https://nickbearman.github.io/installing-software/geoda. Version 1.20 or greater is required. 

THIS COURSE WILL RUN OVER TWO MORNINGS (10AM TO 1PM) AND EQUATES TO ONE TEACHING DAY FOR PAYMENT PURPOSES.

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This five-day workshop introduces participants to the theory and practice of experimental methods in the Social Sciences. It provides an overview of prevalent approaches—specifically lab, field, and survey experiments—offering a solid introduction to experimental methodology and the practical skills needed to design, implement, analyse, and present experiments.

The course is designed for researchers, PhD students, professionals, and members of public institutions, particularly those new to experimental methods or those with experience in one method (survey, field, or lab) who wish to deepen their knowledge of the others. No prior knowledge of experimental design or statistics is required. The course is also suitable for those looking to commission an experiment through a survey company or other service provider.

The workshop aims to equip participants with the skills to design, implement, analyse, and report experiments, as well as to critically evaluate experimental literature.

Additionally, the workshop will provide a brief overview of service providers for marketing experiments (Facebook, Google), access panels and online marketplaces (Lucid, MTurk, Prolific), and survey providers that support experiments (YouGov, Ipsos). Participants will also be introduced to Qualtrics, Stata, R, and Excel as tools for experimental research with practical exercises.

An interdisciplinary team of faculty members from the Centre for Behavioural, Experimental, and Action Research (C-BEAR) will lead the workshop, drawing on examples from Politics, Economics, Business, and Psychology. Each day, two faculty members from different disciplines will co-teach, fostering a dynamic and dialogic learning environment. The workshop will be interactive and hands-on, incorporating group work and practical exercises.

The workshop will also cover responsible research conduct in experimental studies, including research ethics, pre-registration, and debriefing practices for deceptive research designs.

Course Content

Days 1 and 2  will provide the basic knowledge to design, analyse and present experiments such as randomised controlled trials (RCTs), while Days 3, 4, and 5 will focus on survey, field and laboratory experiments.

Participants need to bring their own device that can run basic office suites, and free versions of R and Stata. A tablet with a keyboard might also work.

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The aim of this two-day online training course is to introduce participants to the practice and ethics of ethnographic research.

Through a mix of plenary sessions, group and independent work, participants will learn the basic principles of participant observation and research design, as well as the foundations of ethical ethnographic research.

The course will also examine the ways in which other qualitative and creative methods of data collection may be productively integrated in ethnographic research.

The course covers:

• Research design
• Qualitative methods in ethnographic research
• Access and power
• Research ethics in participant observation

By the end of the course participants will:

• Understand the epistemological foundations of ethnographic research
• Have a solid understanding of ethnographic research in action
• Be able to design and conduct research integrating qualitative and ethnographic research methods
• Be able to conduct ethical ethnographic research

The course is suitable for any professional researchers interested in learning more about using ethnographic methods – whether within or outside academia (private sector, government researchers, etc.).

The course is likewise suitable for postgraduate students in any social science (human geography, sociology, business school, political sciences, area studies, education, etc.) with prior knowledge of any qualitative research methods, but not necessarily of ethnography.

Some prior training in qualitative research methods, broadly defined – regardless of whether that includes ethnographic methods specifically.

Programme

Day 1

Morning session:

• 09:30-09:45  Introduction to the course
• 09:45-10:45  Plenary – The Practice of Ethnography
• 10:45-11:00  Break
• 11:00-12:00  Group work followed by class discussion

Afternoon session:

• 12:45-13:45  Plenary - Qualitative methods in ethnographic practice
• 13:45-14:00  Break
• 14:00-15:15  Practical exercise followed by class discussion

Day 2

Morning session:

• 09:30-10:45  Plenary - Research ethics in ethnography
• 10:45-11:00  Break
• 11:00-12:00  Group work followed by class discussion

Afternoon session:

• 12:45-1:345  Plenary – Writing ethnography
• 13:45-14:00  Break
• 14:00-15:00  Practical exercise, followed by class discussion         
• 15:00-15:15  Conclusions and Evaluations

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This in-person three day course will provide participants with an understanding of the complex intervention research process. Presentations and activities will relate to the main concepts of developing/identifying and evaluating complex interventions and support participants to apply the principles to their own research. It will focus on the overarching considerations required to develop complex intervention research projects, rather than the details of study design, and enable researchers to develop and conduct research that will provide the most useful evidence for decision making. The course will be structured around the MRC/NIHR Framework for Developing and Evaluating Complex Interventions. There will be a mix of lectures and small group activities to put learning into practice. 

It is for anyone interested in developing, evaluating and implementing interventions with the intention of positive health and/or social change. This could be academic or other researchers, practitioners, or others interested in implementing the best process for their intervention development or evaluation. Participants should have some familiarity with the framework for developing and evaluating interventions, and some experience of working with complex interventions. 

The course covers: 

• Introduction to using the Framework
• Developing and identifying interventions
• Feasibility research
• Evaluation research
• Implementation & round up

Course timetable:

The course runs across three days on 6th, 7th & 8th May 2025 between 10am - 4pm each day.

By the end of day 1 participants will:

• Have an overview of the journey through complex intervention research.
• Have an awareness of the challenges and limitations of complex intervention research. 
• Understand how to approach complex intervention research & the key overarching considerations.
• Begin to see how you can apply the framework to your own complex intervention research. 
• Understand what resources/steps to use in developing a complex intervention
• Know how to take forward an ‘identified’ intervention
• Know how to develop a programme theory and make use of it throughout the research process
• Be aware of key issues to consider for the implementation of complex interventions

By the end of day 2, participants will: 

• Understand what feasibility studies are and why they are important ​
• Have learned how to approach designing a feasibility study​
• Have learned how the core elements can be applied at this stage ​
• Understand how feasibility study findings can inform decision about next steps​
• Be able to consider what complexity means for the evaluation of interventions
• Understand that a focus on usefulness of evidence requires methodological pluralism
• Have some understanding of how to choose between evaluation approaches
• Have an understanding of the six key considerations (core elements of the framework) at the evaluation stage
• Have an understanding of what economic evaluation is and why we do it
• Have an understanding of key methods/different types of economic evaluation

By the end of day 3, participants will: 

• Be aware of framework checklist and how it can be applied
• Understand the importance of considering Implementation throughout the phases of the framework and specifically at the Implementation Phase 
• Review and reinforce the key motivations and innovations of the new framework
• Be aware of research questions and methods particularly relevant to a systems perspective
• Have the opportunity to raise questions to reinforce learning and fill gaps.

Pre-requisites:

Participants should be familiar with the process of intervention development and evaluation, with some experience in intervention research.

No software or sign up required.

Essential reading: 

Skivington, Matthews, Simpson et al (2021). A new framework for developing and evaluating complex interventions: update of Medical Research Council guidance BMJ 2021; 374 doi: https://doi.org/10.1136/bmj.n2061 (Published 30 September 2021).

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How does ideological positioning, such as identifying as right-wing in the UK, compare across countries like Germany or Sweden? How can a single question in a cross-national survey account for contextual differences (where they exist)? Who should we ask to ensure nationally representative results, and how should we analyse and interpret the data across different countries?

This two-day online workshop equips participants with the tools to design, analyse, and interpret cross-national surveys, tackling key challenges such as measurement equivalence, sampling techniques, data harmonization, and weighting adjustments. Participants will explore how the Total Survey Error (TSE) Framework can help identify and address measurement error, nonresponse error, and sampling error—key factors that influence data quality and comparability.

The course will focus on practical issues like the impact of question wording on survey results, the influence of social desirability bias across cultures, and the role of cultural and demographic variability in shaping responses. Participants will be introduced to Multi-group Confirmatory Factor Analysis (MG-CFA) as a method for assessing measurement equivalence in diverse contexts. We will also cover essential sampling methods in cross-cultural survey research, as well as weighting techniques designed to make survey results nationally representative, while addressing the challenges of weighting in cross-national surveys.

The course covers: 

• Introduction to Measurement in Comparative Surveys

• Testing for Equivalence in Comparative Data

• Data harmonisation in Comparative Surveys

• Comparative Sampling Fundamentals

• Weighting Adjustments in Comparative Surveys

• Advanced sampling techniques and Ethical Considerations

By the end of the course participants will:

• Learn how to identify and apply the right strategies to ensure survey data comparability.
• Have an introductory understanding of key statistical tools such as Multi Group Confirmatory Factor Analysis to test for measurement equivalence in cross-national survey data.
• Understand the principles and implications of using different sampling methods.
• Learn about types of weights and the importance of weighting in comparative research.
• Learn to autonomously address common data quality issues (eg. nonresponse bias, social desirability bias).
• Enhance the ability to analyse and interpret cross-national survey data. 

This course is aimed at all researchers interested in using cross-national survey data, mainly from social sciences and related disciplines would benefit from the course. 

Participants should have a basic understanding of linear regression analysis.

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In this one-day online training workshop you will be introduced to four qualitative research methods to better understand diverse lives - Photo Go-Alongs, Collage, Life History Interviews and Participant Packs.

When researching social groups, researchers may focus on categories such as age, gender, sexuality and so on. These categories can turn catch-all terms into catch-all agendas. Treating groups of people with one shared characteristic as homogenous risks a cookie-cutter approach which overlooks diverse lives and needs. Given the complexity of what it means to be a person, a one-size fits all approach to engagement cannot suffice.

The methods introduced in this training workshop are beneficial in exploring diverse lives and can be used when researching with any group. 

The session is aimed at PhD students and academics of all career stages across the UK who want to better understand: 

• The specific place-based needs of people 
• The everyday practices of people
• The world from participants’ perspectives
• How to work with people in an inclusive and accessible way

This online training workshop will be structured as follows:  

• Introductions
• Origins and Approach 
• Methods deep dive: 
• Photo Go-Alongs
• Participant packs
• Collage 
• Life Histories 
• Workshops 
• Learnings and close 

By the end of the course participants will:

• Be able to think critically about how creative, participatory methods might be incorporated into their research and/ or teaching. 
• Have broadened their understanding of research methods from tools of data collection to techniques for capacity building.
• Have workshopped four qualitative methods for creatively engaging with people (Photo Go-Alongs, Collage, Life Histories and Participant packs).

This online training workshop will take place over the course of one day between 10:00 and 16:00, with 1 hour for lunch between 12:30 and 13:30.

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This online workshop aims to give participants a range of practical approaches they can adopt when writing about methodology in the social sciences.

Using a range of exercises throughout, the course focuses on 20 or so writing strategies and thought experiments designed to provide more clarity and power to the often-difficult challenge of writing about methods.

The course also looks at common mistakes and how to avoid them when writing about methods. The focus throughout is on building confidence and increasing our repertoire of writing strategies and skills.

The course covers:

• A range of practical writing strategies for handling methodology
• The challenges of writing a PhD methodology chapter or a methods section in a research paper
• Writing for qualitative and quantitative research approaches
• Understanding different audiences and the needs of different academic markets

By the end of the course participants will:

• Better understand who and what ‘methodology writing’ is for
• Know the differences and similarities between PhD methods chapters, research paper methods sections and methods books
• Understand and reflect on 21 principles (or starting points) of best practice in methodology writing
• Focus writing on audience needs and expectations
• Be aware of common mistakes and misunderstandings and so avoid them
• Reflect on the relationship between methodology writing and other parts of your manuscript
• To develop learning and best practice through exercises and examples

Target Audience:

PhD students, post-docs and junior researchers in the social sciences working on their doctoral theses or supervising doctoral students.

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This one-day online, interactive course will provide a practical introduction to qualitative longitudinal enquiry. The morning session will explore key design features of this methodology, including how to build time into a study, how to sample through time, how to generate temporal data, the ethics of longitudinal enquiry, and the potential to create real-time impact in policy processes. The afternoon session will focus on the intricate nature of QL analysis. The course will comprise two lectures and two interactive workshops (see below and attached programme for further details). The course will be delivered by Anna Tarrant and Kahryn Hughes, specialists in QL research and authors of multiple books and papers on this methodology.

The course will run from 10am to 5pm and covers the following: 

• In the first presentation of the day, delegates will be introduced to the principles and design features of qualitative longitudinal (QL) research. The unique power of this methodology – the combination of its real-time operation and its interactive, real-world engagement - will be explored, and its application in policy/practice settings and processes will be introduced.   

• In the morning workshop, delegates will work individually and in pairs to generate temporal data. They will be introduced to life mapping techniques and will have the opportunity to construct a life map and use this as the basis for life journey interviewing. 

• In the second presentation of the day, delegates will be introduced to the principles and practice of QL analysis (QLA): including the tripartite logic of working across cases, themes and processes, and the abductive reasoning that underpins this strategy.

• In the afternoon workshop, delegates will brainstorm the analysis of data from the Following Young Fathers Study. They will have an opportunity to build a longitudinal case history for a young father, drawn from several waves of interviews; and to engage in cross-case comparative analysis of contrasting cases. 

 By the end of the course participants will:

• Have an appreciation of the key design features of Qualitative Longitudinal Research,
• Have gained insights into working with and through time to generate temporal data about unfolding lives,
• Have a greater understanding of the principles of QL analysis, and some experience in working analytically with data and collectively brainstorming new insights. 

The course is suitable for doctoral and established researchers who are either new to this methodology or wish to refresh or enhance their research practice. Delegates will receive a course pack, comprising powerpoint slides and data files from the Following Young Fathers Study. 

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This one-day online, interactive course will provide a practical introduction to Qualitative Secondary Analysis. The morning session will explore key debates and histories characterising the beginnings of this methodology, including how and why we might use existing qualitative data, how to sample from and across datasets and repositories, the unique ethical considerations of using existing qualitative data, and the potential of Qualitative Secondary Analysis to produce new and relevant research findings. The afternoon session will focus on the practicalities of analysing existing data, exploring the possibilities for these methods for delegates’ own research and the diversity of research designs made possible through data reuse. The course will comprise two lectures and two interactive workshops (see below for further details). The course will be delivered by Kahryn Hughes and Anna Tarrant, both specialists in QSA, and the authors of numerous books and papers based on research innovating in this methodology. 

The course will run from 10am to 4pm. 

In the first presentation of the day, delegates will be introduced to the key debates and challenges characterising the histories of Qualitative Secondary Analysis (QSA). They will  be introduced to early debates interrogating the particularities of reusing qualitative data and the evolution of questions from whether we should reuse qualitative data to how we might do it. 

In the second presentation of the day, delegates will be introduced to methods and ethics of QSA, sources of qualitative data and the practicalities of sampling within and across datasets and repositories

In afternoon workshops, delegates will get more ‘hands on’ with existing data with an opportunity to analyse short excerpts from real world research, and engage in guided reflection on the possibilities and limitations of this methodological approach.  A second practical session will offer delegates the opportunity to consider possible research designs incorporating QSA in their own research.

The course is suitable for doctoral and established researchers who are either new to this methodology or wish to refresh or enhance their research practice. Delegates will receive a course pack, comprising powerpoint slides and data files from the Timescapes Archive.

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ArcGIS Online (AGOL) is Esri’s cloud-based GIS platform that allows users to create maps and other web applications for data sharing, collaboration and analysis.

This practical, one-day hands-on course provides a guided introduction to AGOL. You will learn how to publish existing vector data to AGOL, set sharing and group privileges and create a web map that drives field-based data collection. You will use Experience Builder to create a web application that is used for sharing and visualising spatial data. The course comprises hands-on exercises each introduced with a short presentation and a live demonstration.

The course covers: 

• An introduction to ArcGIS Online (AGOL).
• Sharing your vector data from ArcGIS Pro to AGOL.
• Controlling access (settings, groups and views).
• Create a web map from your shared data.
• Build a web map application in Experience Builder.
• Configure layers for data capture.
• Accessing data in AGOL directly within ArcGIS Pro.

By the end of the course participants will be able to:

• Prepare and upload vector data from desktop ArcGIS Pro to ArcGIS Online.
• Create views, groups and set access privileges for hosted feature layers.
• Create a web map, set layer symbology and configure pop-ups.
• Configure data for data capture.
• Create an Experience Builder application from the web map to share and visualise data.
• Access layers in AGOL directly within ArcGIS Pro for data analysis.

This course is intended for users of ESRI’s ArcGIS Pro software who wish to improve their technical knowledge and understanding in ArcGIS Online (AGOL), the cloud-based counterpart, to traditional desktop GIS. Delegates should be familiar with the basics of using ArcGIS Pro and spatial data (e.g. using spatial layers, working with an attribute table, setting symbology, vector data).

Delegates should be familiar with the basics of using ArcGIS Pro and spatial data (e.g. using spatial layers, working with an attribute table, setting symbology, vector data).

This is a 1-day online course starting from 9:30 and completing at 17:00, with a mid-morning break (10 mins), a 30 minute lunch and an optional mid-afternoon break (10 mins).

Delegates are provided with the data used to take part in the course and electronic copies of the course materials (presentations and exercises). The course comprises of 7 modules. Each module has a short introduction presentation, followed by a live demonstration to reinforce what was discussed in the presentation.

Delegates will then work through an exercise on that topic for around 15 to 45 minutes. The trainer will be present to answer any queries. The course is delivered online using Zoom desktop. The trainer will be present throughout the course and additional trainers will support if required.

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Critical Praxeological Analysis (CPA) is a new approach which provides a way of conducting critical qualitative research.

Critical Praxeological Analysis (CPA) synthesises ideas from three key areas: Wittgensteinian philosophy, particularly the method of grammatical investigation; ethnomethodology and conversation analysis, with a focus on praxeological gestalts; and critical research, especially critical phenomenology. This synthesis provides a robust method for critical qualitative research. 

In this online introductory course, the authors of the approach, Khadijah Diskin and Phil Hutchinson, will provide newcomers with a foundation in CPA, by laying out the philosophical background, outlining the stages of project development and analysis, and then ending the day by facilitating a CPA data session on some recent data that might serve as a topic for CPA studies.

This course will assume no prior knowledge of either CPA, Critical Phenomenology or Ethnomethodology and Conversation Analysis and so works as perfect introduction for those who are looking for a method of critical qualitative research.

The course will cover the following:

CPA – Respecifying Critical Research. 

We explain how the purpose of CPA is to provide a procedure for conducting critical qualitative research. Where much critical research is based in theoretical or formal analyses, CPA provides a process for conducting qualitative praxeological analyses which are designed to recover the experiences of members of society.

CPA – The philosophical resources of CPA. 

We introduce the resources that feed into CPA. These are the grammatical investigations of Wittgensteinian philosophy, the praxeological Gestalts of ethnomethodology and CPA’s concept of discordant Gestalts and the extending of the unique adequacy requirement. Each of these will be explained in easy-to-grasp ways with the use of examples.

CPA – Selecting a topic and designing a project. 

We take you through a step-by-step process of selecting a topic, designing, and executing a CPA project.

CPA – Data Session

We end the course by conducting a group data session on some recently acquired data. This will help participants become familiar with how a CPA researcher handles data and what it is to be attuned to aspects of the material as a CPA researcher. The data will be audio or video data gathered in the ‘wild’ and will be from recent events (i.e. 2024).

Learning Outcomes:

• Participants will have a good understanding of the purpose of conducting a CPA, understand the philosophical building blocks of CPA, and have a working understanding of what it is to be a CPA researcher.
• Participants will learn and understand the stages of CPA project design.
• Participants will have hands-on experience of handling and analysing data as a CPA researcher.

Schedule:

10th September: 9am - 4:30pm

11th September: 9am - 2pm

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This course provides an introduction to National Pupil Database (NPD), an administrative data resource covering the education system in England.

The course covers:

• The population coverage of NPD
• The component modules of NPD and how they link together
• How to create a longitudinal picture of pupils’ lives in schools
• Key data cleaning routines
• Accessing NPD

By the end of the course participants will:

•  Be familiar with the structure of NPD
•  Understand the strengths and limitations of the data available
•  Know where to go to find more detailed information
•  Know how to apply for access

This course is suitable for anyone intending to undertake quantitative research on the school system in England. No prior knowledge of the NPD or statistical code is required to access the course.

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Over the two days of this in-person course, you will gain valuable skills that you can market to employers, gain confidence in your ability to work with data, and create a knowledge base that you can build on for years to come.

Topics to be covered:

• How to navigate the R-Studio environment
• Reading data into R
• Tidyverse programming and Base R, including packages such as ggplot
• Data wrangling, including cleaning data and creating variables
• Data visualisation, including how to create the right graphs for your data
• Data analysis, both descriptive and inferential, including t-tests and an introduction to regression modelling

By the end of the course participants will:

• Be able to use R-Studio to analyse data
• Have improved their understanding of programming in R-Studio

Course Outline:

Day 1:

• RStudio principles and key terms
• Reading data into RStudio
• Creating variables
• Visualising data with ggplot

Day 2:

• Subsetting and grouping data
• Analysing survey data
• Analysing experiment data
• Performing a regression analysis

Software:

Students are able to use the computers in the lab during the course. If they are using their own laptops, they will need to install R and R-Studio, available free from https://cran.rstudio.com/ 

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To prevent obesity or smoking initiation among teenagers, who should be targeted in an intervention? How can we contain the spread of an infectious disease under limited resources? Who should be vaccinated first in order to be most effective during vaccination shortages? How can we dismantle a terrorist organization, a drug distribution network or disrupt the communication flow of a criminal gang?

Social network analysis offers the theoretical framework and the appropriate methodology to answer questions like these by focusing on the relationships between and among social entities. Unlike transitional research methods, we shift the object of study from the individual as the unit of analysis, to the social relations that connect these individuals. A network is therefore a structure composed of units and the relationships that connect them. Network analysis is about the position of these units, the overall structure and how these affect the flow of information.

The focus of this two day online course is not so much on how to express these concepts formally through mathematics, but rather on how to use appropriate software to acquire measurements for these concepts in the data and use them rigorously in empirical hypothesis testing. The majority of the course will focus on descriptive methods of network analysis, but we will also discuss network-specific models and inferential methods for network analysis.

The course covers:

• Foundations social networks data: relational structures and data collection;
• Manipulation of network data (matrix algebra and graph theory);
• Node-level measurements;
• Graph-level measurements;
• Network visualization.

Learning outcomes:

• Navigate the key areas of research in social networks;
• Acquire knowledge of data collection and suitable data structures for analysing social networks;
• Develop an understanding of social phenomena through the lenses of the social networks theory;
• Learn how to operate software package for the analysis of social network data;
• Learn how to use and interpret graph-theoretic and matrix algebra concepts with real-world data;
• Acquire the ability and comprehension to independently read scientific literature using social network analysis methodology;
• Learn the fundamentals of social network analysis to acquire the necessary proficiency to explore more advanced topics autonomously.

Basic knowledge of Excel and data matrices will be required.

This course will run from 9.00am - 5.30pm each day.

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In this one day course (online over two mornings) we will explore how to use R to import, manage and process spatial data. We will also cover the process of making choropleth maps, as well as some basic spatial analysis.

Finally, we will cover the use of loops to make multiple maps quickly and easily, one of the major benefits of using a scripting language to make maps, rather than traditional graphic point-and-click interface.

The course covers:

• Using R to import, manage and process spatial data
• Design and creation of choropleth maps
• Basic spatial analysis
• Working with loops in R to create multiple maps

 By the end of the course participants will:

• Use R to read in CSV data & spatial data
• Know how to plot spatial data using R
• Join spatial data to attribute data
• Customize colour and classification methods
• Understand how to use loops to make multiple maps
• Know how to reproject spatial data
• Be able to perform point in polygon operations
• Know how to write shapefiles

This course is ideal for anyone who wishes to use spatial data in their role. This includes government & other public sector researchers who have data with some spatial information (e.g. address, postcode, etc.) which they wish to show on a map.

This course is also suitable for those who wish to have an overview of what spatial data can be used for. Although no previous experience of spatial data is required it would be beneficial (eg Google Maps).

This course will be taught over two mornings (10:00 – 13:00, including a mid morning break) and equates to one teaching day for payment purposes.

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The problem: Your team collected thousands of words of data. You try a traditional thematic analysis of the text. Soon, colour coding, close reading, writing ad hoc reflections about the text become too onerous a task. You doubt the validity of your observations. You wish there was another way to streamline the process, that would extract key themes in data in a faster and empirically-valid way.

Solution: Join us for a session in which we showcase empirical methods for the extraction and analysis of meaning, concepts, and themes in texts. The session will provide training in corpus linguistics and mixed-method tools that enable the analysis of texts in an empirical, bottom-up fashion. Through a range of case-studies, you will be guided to extract meaning and other thematic patterns from texts to gain insight into thoughts and behaviours of authors of those texts. We will share best practises on the thematic analysis of various data types, such as diaries, interview transcripts, data scraped from the web, and outputs of both new and traditional media. We also demonstrate ways of building the results of such analyses into answering research questions, developing business strategy, or a public policy.

This session will be run by researchers from the University of Sussex’s Concept Analytics Lab (https://conceptanalytics.org.uk/). We will demonstrate solutions developed for a variety of problems and text types coming from our work with medical sciences, psychology, economics, and the energy industry. We will also show how linguistic patterns within or between texts (e.g. those that differ demographically or diachronically) can be explored, particularly through the use of new visualisation techniques. The workshop will conclude with a showcase of next-generation textual analysis tools that have been developed at Concept Analytics Lab.

This will be a practical session, enabling attendees to develop hands-on experience with using corpus analysis tools. The course will consist of six hours of training over the course of one day [9.30am - 5pm] and will be delivered online. 

The course covers: 

• How to extract meaning from large textual data
• How to build a corpus using textual data 
• How to engage with existing corpora, such as multi-billion word corpora scraped from the web
• How to use corpus methods for bottom-up and top-down research
• Techniques for the visualisation of unstructured language data
• An introduction to discourse analysis and its application to corpora (corpus-assisted discourse analysis)

By the end of the course participants will:

• Know how to engage a suite of mixed-method corpus linguistic tools to extract meaning from a corpus
• Be able to use corpora to answer a variety of research questions
• Be able to build their own corpora
• Conduct comparative corpus analysis (e.g. between texts that differ demographically or diachronically)

Programme:

9:30: Welcome and introduction to corpus linguistics

10:00: Interrogating existing corpora - quantitative analysis

12:00: Lunch

13:00: Interrogating existing corpora - qualitative analysis

15:00: Break

15:15: Building your own corpus

16:15: The Concept Cruncher: The next generation of text analysis

16:45: Final remarks

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This course is designed to familiarize students and researchers with various facets of qualitative research, particularly focusing on challenging fieldwork environments involving complex and intimate inquiries, expansive research scopes and diverse participant types. We will draw on our personal experience of undertaking ethnographic work and collecting semi-structured interviews with adults and children, presenting examples from the field to illustrate key challenges. The course will particularly benefit researchers engaging in qualitative research with vulnerable communities for short-term periods and in international contexts.

This course will discuss:

• Making sense of the field: As researchers working on sensitive issues and with families living in precarious conditions, how can one effectively understand and document the field (space, participants, communities and surroundings)? How can we make decisions about community engagement in research while recognizing that our participants are part of existing networks and communities? How can our research ensure that voices are heard without causing harm or disruption to people’s daily lives and social structures? How does our definition of the boundaries of a ‘community’ influence how we define and include community/peer researchers? Further, do we concentrate on noticeable elements that define the field for us, or should we pay attention to aspects that may not be prominent to us but hold significance for the participants? What leads us to make these decisions? Likewise, in informal discussions when new subthemes of our primary research objective emerge, what strategies can we employ to capture the evolving field effectively. 

• Working with ‘vulnerable’ participants: How can we define vulnerability in a way that respects participants’ right to participate and be heard but also attends to situated realities? How do you interact with participants who are traditionally seen as vulnerable, considering both the environment they live in and the potential vulnerability their involvement in the research might entail?

  • Research with children

  • Researching daily wage labourers in factory settings

  • Navigating the complexities of posing tough questions in qualitative research

• Locating researcher and participant vulnerabilities in qualitative research: While participants may be structurally vulnerable and situated in precarious circumstances, it is likely that both researchers and participants will encounter additional vulnerabilities during the research process. How should these challenges be managed and navigated as the research progresses?

  • Managing unanticipated challenges during fieldwork

  • Understanding and iteratively addressing multi-layered power dynamics in working with community/peer researchers

• Ethics as an ongoing process in qualitative research: How does one navigate ethical dilemmas in the field while collecting data and later representing participants’ and their experiences in academic writing? How does one continue to maintain ethical rigour throughout the research and beyond the application process?

  • Navigating positionality constraints in short-term field research

  • Adopting inclusive research practices

  • Praxis-oriented reflexive research

  • Adopting more collaborative methods, including working with community/peer researchers

By the end of the course participants will:

• Understand key challenges and ethical considerations in qualitative research
• Be able to articulate their own positionality and why it might matter during fieldwork
• Have a nuanced view of how to define a ‘vulnerable’ group and understand the methodological and ethical challenges while working with such groups
• Understand what a praxis-oriented, reflexive approach entails
• Understand how local contexts might shape participants’ understandings
• Be able to identify non-disruptive community engagement strategies
• Identify benefits and challenges of working with community/peer researchers
• Be able to identify some of the unique considerations involved in international research
• Acquire essential insights into the challenges and experiences of working with children

This course is aimed at students, researchers and academics in the social sciences with little or no training in qualitative methods.

The course will run from 11:00-16:00 and equates to one teaching day for payment purposes.

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This online course will provide participants with an understanding of how Hospital Episode Statistics (HES) data are collected and coded, their structure, and how to clean and analyse HES data.

A key focus will be on developing an understanding of the strengths and weaknesses of HES, how inconsistencies arise, and approaches to deal with these. Participants will also learn how to ensure individuals’ anonymity and confidentiality when carrying out analyses and publishing results based on HES.

The course consists of a mixture of lectures and practicals for which participants will use Stata software to clean and analyse HES data.

The course covers:

• HES data collection and coding
• HES data structure
• How to clean and manage HES data
• How to ensure anonymity and confidentiality
• How to carry out basic analyses using HES data
• Sources of variation in HES data
• How to apply for HES data

By the end of the course participants will:

• understand how and why HES data are collected
• become aware of the strength and weaknesses of using HES data for research
• know how to carry out basic cleaning, management and analysis tasks using HES data
• know how to ensure anonymity and confidentiality when using HES

The course is for researchers and data analysts in academia, government and private sector at all levels who are using or planning to use HES for their work.

There are no pre-requisites for the lectures. Computer practicals will involve analysis of simulated data therefore previous experience of programming in Stata, R or SAS will be helpful. 

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Qualitative Diary Methods (QDMs) are increasingly recognised as a valuable and important method in social science research, due to concern across disciplines with an overreliance on cross-sectional research, a lack of focus on temporality, and the need to capture evolving processes and the daily dynamics of phenomena.

QDMs offer a range of innovative approaches and tools for social science researchers that enable us to capture and subsequently begin to understand, how phenomena are experienced in the moment, as well as how they evolve over time. However, they remain a methodological blindspot in much postgraduate research training.

This workshop will provide researchers with a new range of methods to add to their methodological toolkit, as well as support and guidance in managing some of the challenges associated with these methods, including insights into qualitative diary (longitudinal) analysis approaches.

The course covers:

• Intro to Qualitative Diary Methods (QDMs)
• When and why to use different qualitative diary methods
• Addressing challenges associated with QDMs
• Ethical considerations when using QDMs
• Designing pen and paper diaries
• Designing audio and video diaries
• Designing photo-elicitation diaries
• Designing qualitative ‘App’ diaries
• Analysing data from QDMs: Moving beyond thematic analysis

By the end of the course participants will:

• Have a comprehensive understanding of the benefits and challenges of QDMs, and how to manage these challenges
• Be able to evaluate when different QDMs should be used and why
• Be able to design appropriate QDM research projects to address particular research questions
• Have a critical awareness of particular ethical issues associated with the use of QDMs
• Have a comprehensive understanding of analytical approaches suited to data gathered using QDMs

Programme Outline:

Welcome & Introductions 10:30 am

Session 1: 10:45 – 12:45

• An introduction to diary methods
• When and why to use different qualitative diary methods
• Collecting qualitative diary data: challenges and practical considerations
• Ethical considerations and participant reflexivity
• Sampling approaches for qualitative diary studies
• Pre- and post-diary interviews
• Audience Q&A and Task: Design a diary for your own research project/ interest – Justify design choices in line with sample, data needs and research questions.

Lunch Break 12:45 – 1:45

• Opportunity for informal discussions and networking

Session 2: 2:00 – 4:30

• Designing pen and paper diaries: Tips & Examples
• Designing audio and video diaries: Tips & Examples
• Designing photo-elicitation diaries: Tips & Examples
• Designing qualitative ‘App’ diaries: Some Examples
• Analysing data from qualitative (longitudinal) diary projects: Moving beyond thematic analysis - Thematic Trajectory Analysis (TTA)
• Audience Q&A & Group Task; Group discussions around proposed diary projects, including analytical approaches. Feedback from participants and presenters.

4:30 pm Conclusion & Finish

The event runs from 10:30am-4:30pm

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Queering data introduces participants to issues surrounding the ways that sex, gender and sexuality are represented in UK data. The course focuses on the production of data via surveys, helping participants design survey questions in an inclusive, transparent and reflexive manner. It takes place over four half days (10th & 11th and 17th & 18th June), with each session on a specific theme. The first two sessions engage with critical theories surrounding how populations are categorised and counted and dives into the UK data context. The final two sessions provide participants with insights and tools for designing their own survey questions and engaging with data in an informed and reflexive manner. The recommendations provided in this course are based on a mixed method research project that directly engaged with people with relationships to sex, gender and sexuality overlooked in UK survey data. 

The course covers: 

• Introduction to critical queer and feminist theories on data collection 
• Introduction to the UK census and the controversies around them 
• The pros and cons of data visibility for LGBTI+ people 
• Being a reflexive data collector 
• Being transparent data collector 
• Ways to design sex, gender and sexuality survey questions based on research with overlooked populations 

By the end of the course participants will:

• Be able to summarise the pros and cons of LGBTI+ data collection as seen by queer theorists 
• Be able to summarise feminist critiques of quantification 
• Know what the UK census are, what they are for, how they are designed and the latest debates surrounding how they represent sex, gender and sexuality 

Course format:

• Four half days over two weeks - 10th & 11th and 17th & 18th June 2025
• All sessions running from 10:00-13:00 with two 15 minute comfort breaks
• A mix of lectures and group discussion based activities.
• Some short post session activities, should take no more than 15 minutes.
• Additional reading which the participants can choose to do if they wish.

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The measurement of health in surveys involves collecting data from individuals about their health status, health-related behaviours, and experiences, often as part of multi-purpose surveys. These surveys may include both subjective self-reports (e.g., self-assessed health measures) and objectively measured health data (e.g., physical health assessments, blood-based biomarkers, or DNA data).

Survey measurement of health plays a vital role in advancing social science research on health. It is essential for the analysis of health inequalities, for informing policy decisions, and evaluating the effect of interventions. By capturing individual health behaviours alongside the social, economic, and environmental contexts influencing health outcomes, surveys offer a nuanced understanding of the complex interplay between society and health.

However, measurement error in health data can significantly affect and compromise the quality of social science research in health. Importantly, such errors are not confined to self-reported data. While self-reports are often susceptible to certain types of inaccuracies, other sources of error can arise, including those associated with nurse-administered health assessments or blood-based biomarker data.

Survey mode – e.g. face-to-face interview, telephone interview, online questionnaire - is also well known to affect the distribution of the survey variables so is a special case of measurement error.  Mode effects are hypothesised to be driven by well-known sources of survey bias such as social desirability, positivity and satisficing and the presence (or not) of an interviewer. Mode effects can be defined in the same way as causal or treatment effects and estimated from mixed-mode surveys, and estimated using the same methods.

We provide an overview of methods for understanding measurement error and mode effects. We will also provide practical sessions and illustrative examples demonstrating the impact of measurement error and mode effects in the social and health sciences.

The course covers: 

• Collection of health data in multi-purpose social science surveys

• Measurement errors in health data, including both self-reports and objective measures

• Implications of measurement errors in health data for existing social science research in health

• The nature of mode effects and the connection with classical measurement error

• The definition and identification of different kinds of mode effect from mixed-mode surveys and a case study based on Wave 8 of Understanding Society.

• Practical sessions with illustrative examples of measurement error and mode effects

By the end of the course participants will be able:

• Understand the basis on the process of survey measurement of health, including the collection of both self-reported and nurse-collected health data.
• Explain the role of survey measurement in advancing social science research, particularly in understanding health inequalities, guiding policy, and tracking interventions.
• Recognize the impact of measurement error in health data, including errors in self-reported, nurse-administered, and biomarker data.
• To understand the potential impact of survey mode on survey data, learn how to estimate different kinds of mode effects from mixed-mode surveys, and how to do so robustly using instrumental variable estimation.
• Apply practical knowledge of how measurement error in survey health data can affect the accuracy and interpretation of social science research.

This course is aimed at Post-graduate researchers and analysts, including (but not limited to): Academics, Government Researchers, Third sector organisations, (Health) Consultancy analysts and Survey methodologists. Participants will need a basic knowledge of STATA.

This three-day workshop introduces participants to the theory and practice of experimental methods in application to scholarship research in higher education (HE). It delivers an overview of prevalent approaches, specifically using survey experiments, mixed methods and randomised control trials (RCT) providing a solid introduction to key experimental methodology. The course will focus on the practical skills needed to design, implement, and analyse scholarship in HE. Instructors include Caroline Elliott (Warwick) Fabio Arico (UEA), Paolo Spada (Southampton), Douglas McKee (Cornell), Jadrian Wooten (Virginia Tech), Annika Johnson (Bristol), Thomas Gall (Southampton), Christian Spielmann (Bristol) and Jana Sadeh (Southampton).

The course covers: 

Day 1: Introduction to Scholarship Research in HE, choosing appropriate methods, and ethics of research in HE.

Day 2: Survey and mixed methods: design, implementation and analysis

Day 3: RCT: design, application and analysis.

By the end of the course participants will:

• Understand the breadth of methods available for scholarship research in HE.
• Be able to design a research project using survey, mixed or RCT methods
• Be able to implement a research project using survey, mixed or RCT methods
• Be able to analyse data generated from a research project using survey, mixed or RCT methods 
• Understand the ethical frameworks and challenges surrounding scholarship research

This course is aimed at Teaching Fellows and Senior Teaching Fellows embarking on scholarship research in the higher education (HE) sector for the first time or who are interested in trialling new methodologies in their research. Non-teaching faculty members interested in doing scholarship research in HE.

This workshop is designed by trainers from the field of Economics but will be relevant to other Social Sciences staff with some quantitative background. Participants should have relatively sound knowledge of basic statistics.

This will course run from 09:00-18:00 each day.

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In recent years, there has been an upsurge in calls to decolonise academia. This has involved discussion about the need to decolonise curricula, pedagogy, campus spaces, and relationships within universities.

It has also been suggested that research methods and methodologies need to be decolonised too. This course will offer an in-depth exploration of this area by asking: What are the possibilities when it comes to decolonial research? This one-day course will be split into four sections, as follows. 

Firstly, the course will examine the decolonial critique of academia. This will involve exploring some of the main themes found within decolonial scholarship and activism with a specific focus on the decolonial critique of social science research. 

Secondly, the course will explore some of the key predecessors of decolonial research which have had a significant impact on current thinking about decolonial research. More specifically, consideration will be given to the relationship between feminist research, Indigenous research, and decolonial research. 

Thirdly, the course will consider various strategies which have been suggested to decolonise research. This will involve discussing some of the practical strategies that may be used when trying to produce decolonial research.

Fourthly, the course will offer a critique of decolonial research. This will involve recognising the limitations of decolonial research which make it an imperfect approach to conducting research. The course will be delivered in an interactive workshop format which will involve a mixture of lecture-style teaching, interactive large-group discussions, and small-group conversations. Researchers from all disciplines, expertise, and backgrounds are welcome to attend.

The course covers: 

• Theoretical and practical insights into what decolonial research is and how it can be conducted.
• Robust exposition of decolonial theory and its critique of contemporary academia.
• Examination of the significant influence that feminist research and Indigenous research has had on decolonial research.
• Consideration of various strategies which have been adopted in the pursuit of decolonial research.
• Exploration of the limitations of decolonial research

By the end of the course participants will:

• Be well-versed in the decolonial critique of academia, particularly in relation to social science research.
• Be able to identify the core principles and strategies which constitute decolonial research.
• Be prepared to offer a lucid critique of decolonial research.

This is an in-person course, taking place in Cardiff on the 9th of May from 10am to 5pm. 

The course is suitable for all levels. It is structured in such a way so as to ensure that it progresses from entry-level, to intermediate-level, to advanced-level. 

This course is designed for doctoral researchers within social science disciplines and anyone else who would like to further explore decolonial research methods and methodologies.

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This two day course will outline creative research methods and show you how to use them appropriately throughout the research process.

The course assumes that you have a good working knowledge of conventional research methods, and builds on that knowledge by introducing arts-based methods, embodied methods, research using technology, multi-modal research, and transformative research frameworks such as participatory and activist research.

Any or all of these techniques can be used alongside conventional research methods and are often particularly useful when addressing more complex research questions. You will have several opportunities to try applying these methods in practice. Attention will be paid to ethical issues throughout.

The course will include plenty of practical advice and tips on using creative methods in research.

The course covers:

• Arts-based methods
• Embodied methods
• Research using technology
• Multi-modal research

By the end of the course participants will:

• Have a good level of knowledge of creative research methods
• Understand how to use creative methods alongside conventional methods
• Understand when to use creative methods in research
• Have more resources to counter any opposition to the use of creative methods
• Know how creative methods can add value to funding bids

This course will be relevant for researchers from the third sector, public services (e.g. health, criminal justice, social care, education, local or national government), and those who work in independent research organisations or academia. It is an intermediate level course and attendees will need a good working knowledge of conventional research methods.

The course will run from 10.30-17.30 on Day One and  9:00-16:00 on Day Two at the University of Liverpool. Please note refreshments will be provided, but lunch will not (there are various outlets nearby to purchase something, or bring your own).

Preparatory Reading

Although not required participants may wish to purchase the book on which the course is based: Creative Research Methods: A Practical Guide (2nd edn), by the trainer, published by Policy Press. NB: if participants sign up for the monthly e-newsletter produced by Policy Press, they will receive a substantial discount on the book.

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