This course will give you an overview of avant-garde and arts-based approaches of doing qualitative research and provide you with basic knowledge about creative methods in the social sciences. 

Led by Dr Alexandrina Vanke and contemporary artist Victoria Lomasko, we will cover a full-cycle qualitative study and explain how to incorporate arts-based strategies at all stages. We will discuss how to:
•    create research designs building on avant-garde, documentary and ethnographic approaches;
•    combine arts-based strategies of data collection, such as drawing and collage, with qualitative methods of observation, participation and interview;
•    use sketches and comics in the study of everyday lives, urban landscapes and material culture;
•    elaborate strategies of analysis of multisensory data;
•    employ the research assemblage and write research poems complemented by visual narratives;
•    apply arts-informed strategies of dissemination of research outputs.  

You will need to bring pencils, markers, paper, old magazines, scissors and glue, and some of your qualitative data as well.

Note:

Monday 21st March – Wednesday 23rd March and will run from 10:00-13:00 each day
(charged at 1.5 full days)

The aim of this two-day 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.

This 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 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 a comprehensive feminist ontology of how the social world works which advocates using a form of standpoint to explore from specific perspectives. IE research ‘takes sides’, often researching as, with, and/or for, marginalised groups who are often made invisible by, or excluded from, organisations and institutions. The focus on texts – conceptualised as replicable materials objects that carry messages – allows IE researchers to ethnographically explore the organising power of language and institutions, made material in institutional texts which act as bridges between different people and places.

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 or 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 the work of feminist sociologist, Dorothy Smith, who developed Institutional Ethnography
• Three Institutional Ethnography case studies from Sociology and Human Geography
• Three text and discourse analysis methods within the Institutional Ethnography approach
• How to translate your research ideas or projects into an Institutional Ethnography proposal/plan

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

The course is aimed at academics, students, any other qualitative researchers or policymakers 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
• Campbell, M. L., & Gregor, F. (2002). Mapping social relations: A primer in doing institutional ethnography. Garamond Press.

This short course is designed to give participants a practical introduction to data linkage and is aimed at both analysts intending to link data themselves and researchers who want to understand more about the linkage process and its implications for analysis of linked data—particularly the implications of linkage error. Day 1 will focus on the methods and practicalities of data linkage (including deterministic and probabilistic approaches) using worked examples. Day 2 will focus more on analysis of linked data, including concepts of linkage error, how to assess linkage quality and how to account for the resulting bias and uncertainty in analysis of linked data. Examples will be drawn predominantly from health data, but the concepts will apply to many other areas. This course includes a mixture of lectures and practical sessions that will enable participants to put theory into practice.

The course covers:

· Overview of data linkage (data linkage systems, benefits of data linkage, types of projects)

· Overview of linkage methods (deterministic and probabilistic, privacy-preserving)

· The linkage process (data preparation, blocking, classification)

· Classifying linkage designs

· Evaluating linkage quality and bias (types of error, analysis of linked data)

· Reporting analysis of linked data

· Practical sessions (no coding required; see below)

By the end of the course participants will:

· Understand the background and theory of data linkage methods

· Perform deterministic and probabilistic linkage

· Evaluate the success of data linkage

· Appropriately report analysis based on linked data

The course is aimed at analysts and researchers who need to gain an understanding of data linkage techniques and of how to analyse linked data. The course provides an introduction to data linkage theory and methods for those who might be implementing data linkage or using linked data in their own work. Participants may be academic researchers in the social and health sciences or may work in government, survey agencies, official statistics, for charities or the private sector. The course does not assume any prior knowledge of data linkage. Some experience of using Excel or other software will be useful for the practical sessions.

Preparatory Reading

Recommended (not required):

· Doidge JC, Christen P and Harron K (2020). Quality assessment in data linkage. In: Joined up data in government: the future of data linking methods. https://www.gov.uk/government/publications/joined-up-data-in-government-the-future-of-data-linking-methods/quality-assessment-in-data-linkage

· Harron K, Doidge JC & Goldstein H (2020) Assessing data linkage quality in cohort studies, Annals of Human Biology, 47:2, 218-226, DOI: 10.1080/03014460.2020.1742379

· Harron KL, Doidge JC, Knight HE, et al. A guide to evaluating linkage quality for the analysis of linked data. Int J Epidemiol. 2017;46(5):1699–1710. doi:10.1093/ije/dyx177

· Doidge JC, Harron K (2019). Reflections of modern methods: Linkage error bias. International Journal of Epidemiology. 48(6):2050-60. https://doi.org/10.1093/ije/dyz203

· Sayers A, Ben-Shlomo Y, Blom AW, Steele F. Probabilistic record linkage. Int J Epidemiol. 2016;45(3):954–964. doi:10.1093/ije/dyv322 · Doidge JC, Harron K. Demystifying probabilistic linkage: Common myths and misconceptions. Int J Popul Data Sci. 2018;3(1):410. doi:10.23889/ijpds.v3i1.410

Programme

Day 1

· Overview

· Deterministic linkage algorithms

· Linkage error

· Probabilistic linkage theory and practical demonstration

· Practical considerations (including variable selection, handling missing data and managing processing

requirements)

· Overview of advanced topics including privacy preservation, string comparators and linkage of multiple files

Day 2

· Recap: Common myths and misconceptions about probabilistic linkage

· Linkage error bias

· Linkage quality assessment

· Handling linkage error in analysis

· Reporting studies of linked data

· Software demonstration: Splink – open-source toolkit for probabilistic record linkage and deduplication at scale

Longitudinal data (data collected multiple times from the same cases) is becoming increasingly popular due to the important insights it can bring us.

Structural Equation Modelling (SEM) offers a flexible framework in which longitudinal data can be analysed.

The course will be delivered online and cover some of the basics and more advanced Latent Growth Models using lavaan package in R.

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.

Ideally, research is collaborative, well-documented, sharable, and can be reproduced by others (or by the original researchers at a later point in time). Not only does this make a researcher’s job MUCH easier, it makes their work more valuable, citable and extensible. This is increasingly important in light of the ‘crisis of reproducibility’ that risks undermining scientific research in so many fields.

This training series walks you through how to:
• make your research ready for open science,
• apply reproducibility to social science and other “tricky” topics, and
• collaborate, document and share research in diverse contexts.

Ludwig Wittgenstein is widely considered one of the greatest and most influential philosophers of the 20th century who in his later work produced a radical and distinctive approach to philosophical analysis, which had far-reaching ramifications for research in the social and human sciences. What does Wittgenstein and Witgensteinian philosophy have to say to Social Scientists and Psychologists in the 21st century?

Wittgenstein’s impact on the social sciences can be divided into a number of phases, some of which (2 & 3) spawned distinctive research programmes:

1. Via reception of the work of the Wittgensteinian philosopher Peter Winch and his influential book The Idea of a Social Science and its Relation to Philosophy, published in the mid-20th Century.

2. The combining of Wittgensteinian insights with Ethnomethodology and Conversation Analysis (EMCA) beginning in the early 1970s and found in the work of the ‘Manchester School’ of Ethnomethodology and Conversation Analysis in the work of authors such as Wes Sharrock, Rod Watson and Bob Anderson in addition to associated figures such as Mike Lynch (Cornell) and Jeff Coulter (Boston).

3. The combining of Wittgensteinian insights with Michael Billig’s Rhetorical Analysis, Ethnomethodology and Conversation Analysis to form Discursive Psychology, initiated by Johnathan Potter, Derek Edwards and Margaret Wetherell, beginning in the 1980s at Loughborough University and being developed by others in the decades that have followed.

Run across two afternoons, this course will revisit the philosophical sources that inform a Wittgensteinian approach to questions in the social and human sciences and explore these alongside the approach to interaction found in Ethnomethodology.