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 - 12-13 February 2025  if you feel you need an introductory course first). 

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.

Ethnographic methods are increasingly popular with researchers across the social sciences, but the full potential and possible pitfalls of this complex practice are often overlooked in favour of catch-phrase definitions.

This course moves beyond standard understandings of ethnography that depict it as a generic qualitative method founded on ‘participant observation’ to provide learners with a sophisticated, state-of-the-art approach based on cutting-edge academic research.

The course will blend theorical and practical considerations. On the one hand, the course examines the theoretical scaffolding of ethnography, recognising that a thorough understanding of the epistemological foundations of the methods we use is essential to conducting rigorous and ethical research.

On the other, the spirit of the course is inherently practical and pragmatic, as it aims at preparing researchers to design and conduct ethnographic fieldwork, as well as writing it up for academic and non-academic audiences.

The course covers:

• Epistemology, method, and research design: ethnography beyond participant observation
• Preparing for fieldwork: a pragmatic approach to designing research projects
• Ethics and power: access, collaboration, co-production, and the possibility of decolonising research
• Writing ethnography: from the practical to the political

By the end of the course participants will:

• Grasp the practice of ethnographic research beyond participant observation
• Understand the potential of ethnography beyond the traditional ‘study of culture’
• Have a sophisticated understanding of ethnographic research, from the design stage to its execution and writing up, including an overview of sensorial considerations and visual methods
• Be able to appreciate the ethical and power dimensions of ethnographic research
• Understand the ethics and politics of writing, publishing, and representing ethnographically

This advanced course is suitable for any researchers equipped with some prior knowledge/experience using both standard qualitative methods (interviews, focus groups, life histories, etc.) as well as ethnographic methods but is interested in advancing their understanding of ethnographic research to a professional level.

Researchers working within and outside academia (private sector, government, charitable institutions, etc.) are equally welcome to apply. The course is likewise suitable for postgraduate students in any social science (human geography, sociology, business school, political sciences, area studies, education, etc.), particularly if enrolled or intending to enrol in a research degree (e.g., PhD, Masters by Research, Masters in Research Methods).

Please note that this course is also suitable for postgraduate researchers with an UG background in anthropology, as the course if pitched to an advanced level.

Pre-requisites

Experience using ethnographic research methods and qualitative research methods.

Preparatory Reading

Demetriou, O. (2023), ‘Reconsidering the vignette as method. Art, ethnography, and refugee studies’, American Ethnologist, 50(2): 208-222.

Hage, G. (2005), ‘A not so multi-sited ethnography of a not so imagined community’, Anthropological Theory 5, no.4: 463-475.

Ingold, T. (2014), ‘That’s enough about ethnography!’, HAU Journal of Ethnographic Theory 4, no 1: 383–395

Stefanelli, A. (forthcoming 2024) ‘Reading ethnography in the classroom: complementary strategies to develop students’ ethnographic imagination.’ Learning and Teaching in the Social Sciences.

The course will run from 09:30 to 15:15 both days.

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.

This is a six-week course covering creative research methods and ethics in theory and in practice.

The course runs for 1.5 hours online each week, from 2-3.30 pm on Wednesdays, with associated readings, videos, exercises and online discussions in between the online sessions. 

• Session 1: creative methods and ethics in a pandemic
• Session 2: enhanced and mobile interviews
• Session 3: using comics and animation in research
• Session 4: using video in research
• Session 5: poetic inquiry
• Session 6: metaphor collection and analysis 

The course will focus on gathering and analysing data. Exercises will offer hands-on experience and an online space will be available for discussions and feedback in between the Wednesday sessions.

The online introduction space and preparatory reading will be available from the 8th of January, weekly sessions will begin on the 15th of January. 

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. 

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. 

This course is run as a collaboration between the National Centre for Research Methods and Administrative Data Research UK and is part of a series on short courses on administrative data.

The aim of the course is to provide an introduction to the Growing Up in England (GUiE) dataset. GUiE is a flagship ADR dataset and provides a link between 2011 Census data and longitudinal administrative data from the education and children’s social care systems.

The course provides an introduction and overview of GUiE including:

• The different component datasets that are brought together in GUiE
• Waves and linkage methods
• Coverage, years and gaps
• Strengths and limitations
• Exemplar analysis
• The application process, documentation and support

By the end of the course participants will:

• Be familiar with the structure of GUiE
• Understand the content, coverage and years of the GUiE Waves 1-3 data
• Be aware of the strengths and limitations of the data available
• Be aware of existing studies and analysis using GUiE
• Have knowledge of GUiE documentation 
• Understand the application process, conditions of use and where to go for further information and support

Knowledge of administrative data research datasets and SDC processes would be helpful but are not essential. This is an introductory course and prior knowledge of or experience using GUiE is not required. 

PLEASE NOTE THIS COURSE IS BEING TAUGHT OVER TWO MORNINGS (10:00-13:00) AND EQUATES TO ONE TEACHING DAY FOR PAYMENT PURPOSES.

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.

This online workshop will introduce Institutional Ethnography (IE), an interdisciplinary feminist approach to social research that focuses on how texts and language organise our everyday lives. IE is not just a methodology, but an entire approach to research with a specific ontology of how the social world works and the organising role of texts and language.

In IE, the researcher ‘takes sides’ using a specific version of standpoint to explore how institutions work in practice rooted in peoples’ experiences. This often involves researching as, with, or alongside marginalised groups and making visible how institutions exclude or make invisible certain groups of people and experiences. 

The overall aim of the workshop is to provide attendees with a comprehensive overview of institutional ethnography as an approach and the opportunity to translate their own research ideas and projects into an IE research proposal and do a small piece of text-focused analysis. This hands-on workshop is suitable for students, academics, and anyone else interested in feminist methodologies, text and discourse analysis, and institutional or organisational ethnographies. No prior training in, or knowledge of, IE is required. 

The course covers: 

• An overview of Institutional Ethnography and the work of feminist sociologist, Dorothy Smith, who developed Institutional Ethnography 
• Case studies of Institutional Ethnography research projects to show how it works in practice in different disciplines
• How to translate your research into an Institutional Ethnography project using a research proposal framework
• Practical explanation of how to do text and discourse analysis within Institutional Ethnography through a short text analysis activity 

By the end of the course participants will:

• understand of the origin and development of Institutional Ethnography
• know how to use Institutional Ethnography to analyse texts, processes, and discourses
• have an outline of how their research ideas could become an Institutional Ethnography project 

This course is aimed at academics, students, any other qualitative researchers, including policymakers, organisers, and activists interested in analysing organisational processes.  Participants must have at least some experience in qualitative research methods, but no experience of Institutional Ethnography is required.

Preparatory Reading

Required:

• 1 hour lecture by Dorothy Smith summarising Institutional Ethnography - https://www.youtube.com/watch?v=1RI2KEy9NDw
• Murray, Ó.M., 2020. Text, Process, Discourse: Doing feminist text analysis in institutional ethnography, Available at: https://doi.org/10.1080/13645579.2020.1839162

Desirable:

• Earles, J., & Crawley, S. L. 2020. Institutional ethnography. In P. Atkinson, S. Delamont, A. Cernat, J. W. Sakshaug, & R. A. Williams (Eds.), Foundation: SAGE research methods. Retrieved July 17, 2020, from: http://dx.doi.org/10.4135/9781526421036759274
• Smith, D.E. & Griffith, A.I., 2022. Simply Institutional Ethnography: Creating a Sociology for People. Toronto: University of Toronto Press.

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.

The purpose of this course is to familiarise students with the basic concepts of Bayesian theory. It is designed to provide an introduction to the principles, methods, and applications of Bayesian statistics. Bayesian statistics offers a powerful framework for data analysis and inference, allowing for the incorporation of prior knowledge and uncertainty in a coherent and systematic manner.

Throughout this course, we will cover key concepts such as Bayes' theorem, prior and posterior distributions, likelihood functions, and the fundamental differences between Bayesian and frequentist approaches. You will learn to formulate and estimate statistical models, update beliefs using new data, and make informed decisions based on the posterior probabilities generated through Bayesian inference.

By the end of this course, you will possess the necessary skills to perform Bayesian data analysis, interpret results, and apply Bayesian methods in various contexts.

The course covers: 

• The Basics of Probability
• Bayes’ Theorem and Bayesian inference
• Probability Functions
• Bayesian Conjugates
• Markov Chain Monte Carlo
• Applications

By the end of the course participants will:

• Be able to understand the basics of Bayesian analysis
• Perform simple Bayesian analyses
• Apply simple models to their own work

The course will be delivered over two days, with a two-hour live session on each day  (26/03/2025 and 02/04/2025 at 2pm).  Participants will be given access to a two-hour pre-recorded lecture one week prior to each live session, which they are expected to work through in preparation.  The live sessions will provide an opportunity to apply concepts from the lectures, and participants are encouraged to come with questions.

This course will be taught using STATA - Some basic knowledge of STATA will be required. 

The course leader will prepare the basics of probability refresher which can be used as part of the preparatory work for this course. It will be available 2 weeks before the course start date.  Students who are not as confident with using probability or haven’t worked with it recently are encouraged to complete this. 

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 online one day course (which will be taught over two mornings) will introduce you to various empirical, quantitative methods that can be used to estimate the impact of a specific policy intervention.

These methods can be referred to as “programme evaluation”, “impact assessment”, “causal estimation” or “impact evaluation”. The course assumes basic statistical concepts (mean, median, correlation, expected value, statistical significance and confidence intervals), and algebra is optional.

It does not teach participants how to implement any of these methods using statistical software.

The course covers:

• The evaluation problem, and how randomized experiments solve the problem
• An intuitive explanation of the advantages and disadvantages of matching, including propensity score matching; quasi-experimental methods such as instrumental variables; and difference-in-differences
• It does not teach participants how to implement any of these methods using statistical software

By the end of the course participants will:

• Be able to think about evaluation in terms of “counterfactuals” and “informative contrasts” (or comparisons)
• Be able to explain intuitively the conditions under which propensity score matching, instrumental variables and difference-in-differences are likely to produce unbiased estimates of the impact of an intervention
• Be able to assess whether an actual or proposed design for an impact evaluation is likely to give reliable results, given the nature of the policy under consideration

This course is aimed at Government researchers and analysts interested in quantitative methods for impact evaluation, Third sector researchers and analysts interested in quantitative methods for impact evaluation and PhD students and junior researchers.

Longitudinal data is essential in a number of research fields as it enables analysts to concurrently understand aggregate and individual level change in time, the occurrence of events and improves our understanding of causality in the social sciences. 

In this course, you will learn both how to clean longitudinal data as well as the main statistical models used to analyse it. The course will cover three fundamental frameworks for analysing longitudinal data: multilevel modelling, structural equation modelling and event history analysis. 

The course is organised as a mixture of lectures and hands-on practicals using real-world data. During the course, there will also be opportunities to discuss also how to apply these models in your own research.

Objectives:

• To gain competence in the concepts, designs and terms of longitudinal research;
• To be able to apply a range of different methods for longitudinal data analysis;  
• To have a general understanding of how each method represents different kinds of longitudinal processes;
• To be able to choose a design, a plausible model and an appropriate method of analysis for a range of research questions.

IMPORTANT: Please note that this course includes computer workshops. Before registering please check that you will be able to access the software noted below. Please bear in mind minimum system requirements to run software and administration restrictions imposed by your institution or employer with may block the installation of software.

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.

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.

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. 

In this two day course (which will be taught online over 4 mornings), you will learn what GIS is, how it works and how you can use it to create maps and perform spatial analysis.

We assume no prior knowledge of GIS and you will learn how to get data into the GIS, how to produce maps using your own data and what you can and cannot do with spatial data. You will also learn how to work with a variety of different data sources and types (including XY coordinate data and address or postcode data) and using spatial overlays, point in polygon analysis and spatial joins.

The course covers:

• What is GIS and spatial data?
• How to classify data for a choropleth map
• How to create a publication ready map
• How to work with different data sources including XY coordinate and postcode data
• Using attribute and spatial joins
• Using spatial overlays and spatial analysis
• How to apply these skills to your own data

By the end of the course participants will:

• Be able to set up QGIS and add data
• Know how to classify data for a choropleth map
• Be able to join tabular data to spatial data
• Designing and producing a publication ready map in QGIS
• Understand how to import a range of data types into QGIS
• Be able to locate and open a range of GIS data sets
• Know how to apply GIS analysis tools including spatial overlays and point in polygon.
• Be confident at applying the skills to their own data

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.

In this live online course, learn about questionnaire design in the context of different modes of data collection. Explore question wording issues, the questionnaire as a whole and visual concerns when moving from interviewer-administered to web survey, when creating a web survey in general and when facing the questionnaire design challenges in creating mobile-friendly web surveys. Mirroring in-person training this will be an interactive course and will also have workshops throughout.

The course covers:

• The push towards mixed mode, web and mobile web surveys
• Questionnaire design revision - Getting started, trade-offs, general guidelines, beware of certain question formats
• Question design solutions for comprehension issues - Appendix for memory and sensitivity issues
• Don't rely on survey templates
• Mixing modes of data collection, some overall mode differences, mode effects by question content and format
• From interview survey to web survey
• Web survey questionnaire requirements and options, web surveys can include . . . but should we?, importance of visual layout, unexpected issues with HTML formats
• Push to web
• Questionnaires for mobile web surveys - earlier evidence, later findings, current thinking on making a questionnaire mobile-friendly

By the end of the course participants will:

• Have better knowledge about questionnaire-related mode differences and effects
• Have the skill to change an existing interviewer-administered questionnaire to a web survey
• Have the ability to create effective web survey questionnaires as well as mobile-friendly ones
• Have greater questionnaire design skills in general and the ability to critique existing survey templates

This course is for anyone involved in mixed-mode, web and/or mobile web surveys.  Participants need familiarity with surveys and questionnaire design.

Ethical research is better quality research. This online course (one day, taught over two mornings) is designed to raise your awareness of why and how you need to think and act ethically in practice throughout your research work.

The current system of ethical review by committee can lead to the misleading sense of having ‘done ethics’. This course shows you how to conduct research which is truly ethical. It also provides the opportunity for discussion of your own ethical dilemmas, if you wish.

The course covers:

• Research ethics in context – ethical breaches past and present, ethics dumping, ethics activism
• Potential ethical pitfalls at each stage of the research process, from question setting to aftercare
• How to think and act ethically throughout research

By the end of the course participants will:

• Recognise the importance of context for ethical decision-making
• Understand why they need to think and act ethically throughout research work
• Be clearer about potential ethical pitfalls at different stages of the research process
• Know how to approach ethical thought and action at any point in their research

This course is aimed at Doctoral students, early career researchers (any discipline). Also practice-based/applied researchers. Possibly government researchers too, and independent researchers.

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.

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.