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ESRC Doctoral Training Partnership for Social Sciences

 
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NCRM is a Hub-Node network of research groups, each conducting research and training in an area of social science research methods, coordinated by the Hub at the University of Southampton.
Updated: 1 hour 5 min ago

Using UK data portals to find and evaluate data for social science research (27/01/21)

Fri, 23/10/2020 - 01:00

Data are a key resource for research and datasets are increasingly being shared for reuse by others as secondary data. However, as more secondary data are made available online finding the most relevant data for your research can be difficult.

This event will guide participants through the benefits of using web-based data portals to discover secondary datasets relevant to their research project. As an example of how to do this we will introduce the WISERD DataPortal – a free tool to help researchers discover data related to Wales.

Data portals are web-based applications created with the intention of helping researchers discover secondary datasets. They provide detailed information about a dataset’s subject matter, geographic extent and timeframe, allowing a researcher to ascertain whether that data would be useful for their project. Portals either offer access to the data themselves or inform the researcher of how to gain access to the data.

The event will be split into two parts:

  1. We will consider the benefits of using data portals as data discovery tools. We will then review some of the key data portals available in the UK, including those provided by public sector organisations (such as the ONS), data repositories (such as the UK Data Archive) and academic institutions (such as the UK Collaborative Centre for Housing Evidence (CaCHE)).

 

  1. We will offer a detailed walk-through of how a data portal could be used as a data discovery tool for a research project using WISERD’s DataPortal as an example. WISERD’s DataPortal is focused on Wales, enabling users to discover government, academic and third sector data from a wide variety of social science related disciplines, including health, education, language, employment, socio-economic and demographic data.

In this event you will learn:

  1. About the benefits of using data portals as secondary data discovery tools;
  2. About the key data portals which are useful for discovering data available for the UK;
  3. How to use a data portal, using WISERD’s DataPortal as an example, to discover data for your project.

Programme

Part 1: Using data portals as data discovery tools for research

  1. The benefits of using data portals to discover secondary datasets.
  2. An overview of the key data portals providing data for the UK.

Part 2: How to use a data portal to discover data for a research project

  1. Overview of the WISERD DataPortal project
  2. Introduction and demonstration of the WISERD DataPortal’s key functions
  3. Case study example of how the DataPortal’s functions can be used to discover research data.

 

Subjective Expectations: Measurement and Analysis - Online (09/03/21)

Wed, 21/10/2020 - 01:00

When making decisions under uncertainty, economists typically assume that individuals form probabilistic expectations for unknown quantities and maximize expected utility. Probabilistic measurement of expectations in surveys and experimental settings has become a very active area of economic research. The online course (which will be taught over two mornings) will introduce you to recent developments in the measurement and use of data on subjective expectations.

The course will cover different methods for the elicitation of subjective expectations through probabilistic questions in surveys or experimental settings, using examples drawn from recent work in this area. The course discusses the different methods used for eliciting such information in both high and low income-countries contexts, the key methodological issues involved, and the open research questions. Several hands-on exercises will be proposed, where students could explore different ways of collecting the data through standard survey software, such as Qualtrics.

The second part of the course will focus on the value of subjective expectations data in the analysis of economic behaviour. Here we will show the way in which expectation data can be used in choice models to understand economic behaviour. Several examples will be discussed from the recent literature in economics, focusing on educational choices and choice related to risky behaviours.

The course covers:

  • Methods for eliciting subjective expectations in surveys or field experiments in high and low-income countries
  • How subjective expectations data is used to understand individual’s choices using econometric models
  • Recent applications to the analysis of educational choices or risky behaviours

By the end of the course participants will:

  • Have an understanding of why subjective expectations data are valuable for the study of several types of economic decisions
  • Be familiar with recent papers in economics which have used subjective expectations data to model economic behaviour in different contexts
  • Acquire some basic experience of eliciting subjective expectations using standard survey software

This course is aimed at PhD students, researchers and analysts interested in understanding recent developments in the collection and use of data on subjective expectations. Researchers who design surveys might be particularly interested in the different ways in which subjective expectations can be measured.

Pre-requisites

Some prior knowledge of discrete choice models is advisable.  The course will make use of Qualtrics, no prior knowledge of this software is required.

Preparatory Reading

Armantier, Olivier and Bruine de Bruin, Wändi and Potter, Simon and van der Klaauw, H. Wilbert and Topa, Giorgio and Zafar, Basit, 2013 “Measuring Inflation Expectations”, Annual Review of Economics, 5, 273-301

Delavande, Adeline, 2011:  “Measuring Subjective Expectations in Developing Countries: A Critical Review and New Evidence” with Xavier Gine and David McKenzie, Journal of Development Economics, 94, 151–163

Manski, Charles, 2004: “Measuring Expectations”. Econometrica, 72, 1329–1376

Models for Cause and Effect: Causal inference for social scientists - Online (23/03/21)

Fri, 16/10/2020 - 01:00

This is a two day course which will be taught over four mornings.

The fact that correlation does not equate to causation is so well known that it has become a popular saying in itself. Yet the way that quantitative analysis is discussed in much popular and political discourse, as well as interpreted by many social scientists, fails to take issues surrounding causality fully into account. This may be because randomized control experiments, widely understood as the most defensible method of establishing causality, are frequently impossible or unethical to conduct in social science settings.

Analysts thus have to work with observational data, which often miss information crucial for making causal interpretations of statistical associations. However, under some circumstances and subject to specific assumptions, one can interpret estimated associations as casual with substantially higher confidence. This course deals with methods that can be used under such circumstances and subject to the specific assumptions. The course offers practical skills in implementing these methods and the theoretical skills needed to understand and discuss evidence from them.

The course covers:

  • An introduction to conceptual issues around causal analysis and counterfactual research design
  • A review of “classic” regression and covariate adjustment techniques
  • Instrumental variables
  • Regression discontinuity
  • Difference in difference

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

  • Understand the motivation for and theoretical underpinnings of common counterfactual designs
  • Discuss strengths and weaknesses of different designs for specific research questions
  • Use and interpret output from counterfactual models
  • Discuss critically issues of internal and external validity of different designs

Pre-requisites

Participants should have had an introduction to quantitative research methods at undergraduate or postgraduate level and be familiar with basic concepts in probability theory and statistical inference.

Participants should be familiar with basic elements of coding for a statistical software package such as R, SPSS or Stata (preferred).

Preparatory Reading

The course will draw on the following textbooks:

Morgan, S. L., & Winship, C. (2015). Counterfactuals and causal inference. Cambridge University Press.

Angrist, J. D., & Pischke, J. S. (2014). Mastering'metrics: The path from cause to effect. Princeton University Press.

Programme

Day One

9-11                 Introduction to causal inference and potential outcomes framework, mix of video and online discussion, interactive exercises

11-12               Regression/covariate adjustment, video and online discussion

12-13               Lunch

13-15               Regression / covariate adjustment, Guided lab with chat and video discussion

Day Two

9-10                 Instrumental variables, video and online discussion

10-10:30          Half Hour Break

10:30 – 12:30  Instrumental variables, guided lab with chat and video discussion

Day Three

9-10                 Regression discontinuity, video and online discussion

10-10:30          Half Hour Break

10:30-12:30     Regression discontinuity, guided lab with chat and video discussion           

Day Four

9-10                 Differences in Differences, video and online discussion

10-10:30          Half Hour Break

10:30-12:30     Differences in Differences, guided lab and online discussion

12:30-1:30       Wrap Up

Introduction to dealing with Missing Data (07/12/20)

Thu, 15/10/2020 - 01:00

This course looks at the problem of missing data in research studies in detail. Reasons and different types of missing data are discussed as well as bad and good methods of dealing with them.

Introduction to Meta-Analysis (14/12/20)

Thu, 15/10/2020 - 01:00

This course provides an overview of meta-analysis from a statistician's point of view, with an optional half day workshop in R.

Introduction to Stata (26/10/20)

Wed, 14/10/2020 - 01:00

Introduction to Stata

26 October 2020–27 October 2020, 9:30 am–1:00 pm

This course offers an introduction to the uses and functions of the statistical software Stata including data entry and manipulation, do-files, and the basics of analyses and graphs.

Introduction to Regression (16/11/20)

Wed, 14/10/2020 - 01:00

This course provides an overview of different regression types and details the application of multiple linear regression. The main course focuses on the theory behind regression analysis, in particular linear regression, and covers the formulation, interpretation and validation of linear regression models. A second, optional session allows delegates hands-on use of a statistical package (SPSS) to see how the theory can be applied to answer a specific research question.

Sample Size Estimation and Power Calculations with Excel (24/11/20)

Wed, 14/10/2020 - 01:00

This course gives the basics of sample size estimation. It will be of use to those embarking on a research project and who are perhaps trying to complete ethics and grant application forms. Both precision and power estimation approaches are covered.

Introduction to Logistic Regression (26/11/20)

Wed, 14/10/2020 - 01:00

This one day course focuses on understanding the principles of logistic regression via the notions of odds/odds ratios and transformations. How good the given model is will be discussed and ways of improving it.

Further Topics in R (30/11/20)

Wed, 14/10/2020 - 01:00

This course introduces a number of topics for R for those already familiar with the basics of the programming language, including some of the more advanced R code structures such as conditional commands and loops.

Introduction to Multilevel Modelling Using MLwiN, 26-28 January 2021, Online Webinar via Zoom ...

Mon, 12/10/2020 - 01:00

Introduction to Multilevel Modelling Using MLwiN, 26-28 January 2021, Online Webinar via Zoom 

 

Instructors 

Professor George Leckie and Professor William Browne 

Summary 

This three-day course provides an introduction to multilevel modelling and includes software practicals using the MLwiN software. We focus on multilevel modelling for continuous and binary responses (dependent or outcome variables) when the data are clustered (nested or hierarchical). These models can be viewed as an extension of conventional linear and logistic regression models to account for and learn from the clustering in the data. Such models are appropriate when, for example, analysing exam scores of students nested within schools, or health outcomes of patients nested within hospitals. Special interest lies in disentangling social processes operating at different levels of analysis by decomposing the within- from the between-cluster effects of covariates (explanatory variables). Longitudinal data are also clustered, with repeated measurements on individuals or multiple panel waves per survey respondent. Throughout the course we emphasize how to interpret the models and to decide on what kinds of research question they can be used to explore. 

Topics 

  1. Overview of multilevel modelling 
  2. Introduction to MLwiN 
  3. Variance-components models 
  4. Random-intercept models with covariates 
  5. Between- and within-effects of level-1 covariates 
  6. Random-coefficient models 
  7. Growth-curve models 
  8. Three-level models 
  9. Review of single-level logistic regression 
  10. Two-level logistic regression 

Format 
The course will consist of a 2:1 mix of lectures and hands-on practical sessions applying the taught methods to real datasets. The instructors alternate the lecturing. Each lecture is immediately followed by a practical giving participants the chance to replicate the presented analyses and to consolidate their knowledge. The lectures are software independent. The practicals are self-directed and use MLwiN: participants complete them at their own pace. In both the lectures and practicals participants have opportunities to interact with the instructors. 

Zoom 
The course will be delivered online via the freely accessible Zoom platform. The lectures will be delivered live. Participants can ask questions via Zoom’s text-based Q&A facility that will be monitored and answered by one of the instructors not presenting or relayed to the instructor presenting to answer live.  

Participants are encouraged to join the lectures live, but recordings of the lectures will be made available shortly afterwards for two weeks following the course if participants are unable to attend at the scheduled time. After two weeks, video access will end and can’t be extended. 

During the practicals, participants can speak 1:1 with the instructors in short Zoom meetings. Participants can use these opportunities to ask specific questions about the course material or about multilevel modelling related to their own research. 

Materials 
Participants will be emailed in advance with comprehensive PDF copies of the lecture slides and practical handouts. They will also be provided with the teaching version of MLwiN and the MLwiN worksheets (datasets) to replicate the course materials. Participants are encouraged to view the lecture slides and practical handouts on a second screen (or tablet etc.) during the live lectures and self-directed practicals, else print copies out to have in front of them. 

MLwiN 
MLwiN is dedicated multilevel modelling software developed by our research team over the last 25 years. On this course we will be using the free teaching version of MLwiN. This version works with all the datasets used on the course and a wide range of other teaching datasets which come with the software. We will email you the teaching version prior to the start of the course. 

Should you wish to use MLwiN after the course with your own data, you will need to use the regular version of MLwiN. This is free to UK academics (but without user support) reflecting long periods of funding from the UK’s Economic and Social science Research Council (ESRC). For all other users there is a 30-day trial version, but after that you will have to purchase MLwiN if you wish to continue using it to analyse your own data. There are various price options available. 

http://www.bristol.ac.uk/cmm/software/mlwin/

MLwiN is Windows software, but can be run on Mac via the Wine software or through a virtual machine. Note that Wine will only work on versions of MacOS prior to Catalina.

http://www.bristol.ac.uk/cmm/software/mlwin/features/sysreq.html#unix

Pre-requisites 
We assume no prior knowledge of multilevel modelling or MLwiN. However, participants should be familiar with estimating and interpreting linear regression models, including the writing and interpretation of model equations, hypothesis testing and model selection, and the use and interpretation of dummy variables and interaction terms. 

In order for participants to start to become familiar with MLwiN, we will email in advance a video lecture which provides an introduction to the software in terms of fitting linear regression models. We will also provide a practical with step-by-step instructions to allow you to replicate the presented analyses. Youshould run through this to confirm that MLwiN is working correctly on your computer and to further familiarise yourself with using MLwiN. 

Some participants may wish to further refresh themselves of linear regression by reading module 3 of our LEMMA online course. 

https://www.bristol.ac.uk/cmm/learning/online-course/course-topics.html

Timings 
The course starts and ends each day at 09:30 and 16:00 with a 15-minute morning break and a one-hour break for lunch from 13:00 to 14:00. 

Fees 

  • For UK-registered MSc and PhD students - £180 
  • For UK university academics, UK public sector staff, and staff at UK registered charity organisations - £360 
  • For all other participants - £660 
     

Please note, in order to be eligible for the reduced pricing brackets please submit your application using your UK academic/organisational email address. 
 

Cancellation/refunds 
A full refund will be given if cancellation occurs three weeks prior to the event. No refund is given after this date. By completing the application form, you are accepting these cancellation terms. 

Applications 
Our workshops are now regularly over-subscribed so we have had to introduce an application and selection process. If you would like to attend the workshop, please complete and submit the online application form (see below). Please note the closing date for applications is 29th November 2020. 

Submission of the form and its acknowledgement does not guarantee a place on the workshop. We will email you by 7th December to tell you whether or not your application has been successful. If you are offered a place on the workshop, it will not be confirmed until you have accepted and paid the relevant fee. 

If you have any queries, please email info-cmm@bristol.ac.uk

Go to booking form >> 

Terms and conditions 
Please click here to read the booking terms and conditions before completing the booking form. Note that it is the participant’s responsibility to ensure that the Zoom and MLwiN software work on their computer in advance of the course, as the Centre for Multilevel Modelling is unable to provide technical support. 

Conducting Online Focus Groups (16/11/20)

Thu, 08/10/2020 - 01:00


This live online course explores the principles and benefits of online focus groups (Foundation level). 


Introduction/Overview


This course provides participants with an in-depth introduction to successfully conducting and facilitating online focus groups. Traditionally, online focus groups have tended to be viewed as inferior to the traditional physical ‘face-to-face’ focus group. However, online focus groups can vary in form and offer us a valuable means by which to conduct social research with a range of diverse groups via various information and communication technologies. The course covers the principles and benefits of online focus groups, and the challenges which online communication poses when conducting focus groups virtually. We cover how to design, conduct and facilitate a synchronous online focus group using voice and video technologies. Participants are provided with guidance and the opportunity to practice running an online focus group, including strategies for participation and ethical considerations.

 
Learning outcomes
 

To have knowledge of the original principles of traditional face-to-face focus groups.
To understand how these principles change in the context of online communication and online data collection.

  • To be aware of the pros and cons of running an online focus group.
  • To be aware of the different types of online focus groups including synchronous and asynchronous and be able to select the most appropriate in various scenarios.
  • To be able to design and facilitate an online focus group via a practical activity.
  • Sensitivity to the ethics of online data collection.

 
Topics
 

  • The principles and benefits of online focus groups
  • The nature of online communication
  • Challenges of conducting online focus groups
  • Synchronous online focus groups and voice and video technologies
  • Designing and running your online focus groups
  • Strategies for encouraging participation
  • Ethics of online data collection
  • Other types of online focus groups: discussion forums, email distribution lists

 
Who will benefit
 

This introductory course will benefit researchers who are new to qualitative research methods and those who already have a basic understanding of qualitative research methods but are new to conducting focus groups in online settings.

 
Course tutor
 

Dr Karen Lumsden is currently Assistant Professor in Criminology at the University of Nottingham and has a PhD in Sociology from the University of Aberdeen. She has over 15 years experience teaching qualitative research methods at postgraduate level and to academics and practitioners. This includes courses at the University of Aberdeen, University of Glasgow, University of Essex and Kingston University, and for the Social Research Association.

Karen has also designed and delivered social research methods training for police officers and staff via the East Midlands Policing Academic Collaboration (EMPAC) and for research consultancies. She has authored a number of academic books and journal articles in the areas of sociology and criminology, and on qualitative research methods. Karen is also Chair of the Editorial Board of Sociological Research Online.

Narratives and Storytelling in Qualitative Research (17/11/20)

Thu, 08/10/2020 - 01:00

This live online course explores narrative analysis and storytelling in qualitative research. This course uses Zoom software.
 

Summary / Overview

Narrative inquiry is a valuable investigative technique in qualitative research. Narrative inquiry and storytelling offer us a different way of knowing, of investigating the lived experiences of individuals, and of exploring subjectivity. Narrative knowledge is created and constructed through the stories of lived experience and sense-making, the meanings people afford to them, and therefore offers valuable insight into the complexity of human lives, cultures, and behaviours. It allows us to capture the rich data within stories, including for example giving insight into feelings, beliefs, images and time. It also takes account of the relationship between individual experience and the wider social and cultural contexts. Crucially, it also involves collaborative inquiry and co-construction of meaning between participants and the researcher. Examples of narrative inquiry in qualitative research include for instance: stories, interviews, life histories, journals, photographs and other artifacts.

 
Objectives
 

By the end of the workshop, participants will:

  • Have knowledge of narrative inquiry as a qualitative research technique.
  • Understand the benefits which narrative inquiry and stories offer for understanding people’s lived experience and meanings.
  • Be able to demonstrate knowledge of the theories of narrative analysis.
  • Have an awareness of the different types of narrative analysis that can be employed in practice.
  • Have conducted their own narrative inquiry using a variety of texts and/or images.
  • Understand the additional benefits offered through the use of self-narratives (i.e. auto-ethnography).
  • Be aware of the practical and ethical issues which must be considered when conducting narrative inquiry.

 
Learning outcomes
 

  • Understand the various ways in which narrative analysis is employed in qualitative research.
  • Understand the theories underpinning narrative analysis.
  • Gain knowledge of the various forms of narrative analysis which can be employed in qualitative research.
  • Be able to undertake a narrative analysis as evidenced in practical activities.
  • Understand the role that collaboration plays between researcher and participant in narrative inquiry.
  • Demonstrate awareness of the ethical and practical issues which must be considered when conducting narrative analysis.

 
Topics
 

During the course we will cover:

  • What is narrative inquiry?
  • Why use stories in research?
  • Theories of narrative analysis.
  • Different forms of narrative analysis.
  • The importance of collaboration between researcher and participant.
  • How to conduct narrative inquiry including various examples such as: stories, interviews, life histories, journals, photography, and artifacts.
  • Self-narratives i.e. autoethnography.
  • Ethical and practical issues to consider.

 
Who will benefit
 

This course will benefit participants who wish to advance their knowledge of qualitative research methods by exploring the benefits that narratives and stories offer as a method of inquiry in a range of applied and policy settings and contexts. This one-day course is designed to help participants become aware of narrative analysis and storytelling in qualitative research, and to practice some of the techniques involved. As well as providing a grounding in the principles and theories of narrative analysis, participants will gain hands-on experience of using the techniques of narrative inquiry and of conducting narrative analysis. Some prior knowledge of qualitative research methods is advisable.

 
Course tutor
 

Dr Karen Lumsden is currently Assistant Professor in Criminology at the University of Nottingham and has a PhD in Sociology from the University of Aberdeen. She has over 15 years experience teaching qualitative research methods at postgraduate level and to academics and practitioners. This includes courses at the University of Aberdeen, University of Glasgow, University of Essex and Kingston University, and for the Social Research Association. Karen has also designed and delivered social research methods training for police officers and staff via the East Midlands Policing Academic Collaboration (EMPAC) and for research consultancies. She has authored a number of academic books and journal articles in the areas of sociology and criminology, and on qualitative research methods. Karen is also Chair of the Editorial Board of Sociological Research Online.

Introduction to Applied Behavioural Science Online (25/11/20)

Thu, 08/10/2020 - 01:00


This live online course is for anyone who is new to behavioural science and/or looking for a neutral, pragmatic perspective on the theory and practice in social research. * Price:  £165 for SRA members, £220 for non-members.  It runs over two mornings and uses Zoom software *


Introduction/Overview


Applied behavioural science should be natural territory for social researchers, but despite becoming much more prominent in recent years it is still not well understood or effectively integrated with practice. Applied behavioural science is a transdisciplinary activity that is problem and issue focused and draws on diverse disciplinary backgrounds; it is a way of both thinking and doing that provides an important complement to the social researcher’s toolbox. This course will introduce the theory and practice of applied behavioural science and demonstrate how to integrate it with social research to both better understand behaviour and how to approach changing behaviour whether that takes the form of more useful recommendation or intervention design and implementation.

 
Objectives:
 

By the end of the workshop, participants will:

  • Scope an applied behavioural insights project, identifying and prioritising behaviours effectively
  • Use behavioural frameworks to systematically investigate and analyse behaviours
  • Develop a behaviour change intervention using a behavioural analysis
  • Think through how a behaviour change intervention can be implemented effectively

 
Topics:
 

The course will cover:

  • Scoping applied behavioural insights projects
  • Selecting behaviours for understanding and change
  • Investigating and analysing behaviours systematically
  • Designing behaviour change interventions
  • Implementing behaviour change interventions

 
Who will benefit?
 

This course is for anyone who is new to behavioural science and/or looking for a neutral, pragmatic perspective on the theory and practice in social research. The primary intended audience for the course is practicing social researchers. The course may also be of interest to other researchers e.g. user or design researchers, or those who commission or use research such as policy-makers and service designers.

 
Learning outcomes:
 

After this course participants will be able to:

  • Understand what is meant by applied behavioural science, behavioural insights and behaviour change
  • Translate high level behavioural challenges i.e. problems that require behaviour change into tangible applied behavioural science projects
  • Recognise and use a range of applied behavioural science frameworks in social research
  • Better understand and conduct behavioural analysis and diagnosis
  • Better understand and translate behavioural analysis and diagnosis into intervention development and implementation

Note: This is not an evaluation course and does not cover experimental or quasi-experimental design
 
Course tutor:
 

Chris Perry is an independent researcher and consultant with over ten years’ experience and a background in social research, user and design research, evaluation and applied behavioural science. He set up and led the Behavioural Science practice at Ipsos MORI Social Research Institute for five years, working on a wide range of applied projects both in terms of method and subject area culminating in becoming a preferred supplier on the Cabinet Office Behavioural Insights Framework in 2018. Following this he led research at Ctrl Group, a digital health start-up to support the design and development of Fora, a technology enabled service to improve communication and conversation between patients and healthcare professionals.

 

Narrative Analysis (30/11/20)

Thu, 08/10/2020 - 01:00


This live online course provides qualitative data analysis techniques using narrative analysis. (Advanced level) This course uses Zoom software.


Introduction/Overview


Narrative analysis is a valuable data analysis technique in qualitative research. It is typically used in those studies which have already employed narrative inquiry as a qualitative method. Narrative knowledge is created and constructed through the stories of lived experience and sense-making, the meanings people afford to them, and therefore offers valuable insight into the complexity of human lives, cultures, and behaviours. Narrative analysis uses the ‘story’ as the unit of analysis, in contrast to thematic and other forms of qualitative analysis.

Narrative analysis is useful for practitioners and researchers who wish to focus on individual experiences, eg. via collected stories and unstructured interviews. Examples of possible applications include case studies; patients’ experiences of health care services or illness; life stories and experiences of social care clients; victims’ experiences of the criminal justice system.

 
Objectives
 

By the end of the workshop participants will:

  • Have knowledge of narrative analysis as a qualitative data analysis technique.
  • Be aware of the relationship between narrative inquiry in qualitative research and narrative analysis.
  • Be aware of the different models of narrative analysis.
  • Understand the benefits which narrative analysis offers for interpreting and making sense of ‘whole’ stories.
  • Have conducted their own narrative analysis using a selection of the various models covered in the workshop.
  • Be aware of the research contexts in which narrative analysis is potentially valuable and effective.

 
Topics
 

During the course we will cover:

  • What is narrative analysis?
  • Models of narrative analysis
  • Codes, patterns, themes and categories
  • ‘Narrative meaning’ and ‘narrative smoothing’ (Etherington, 2004)
  • Interpretations of ‘faith’ and ‘suspicion’
  • Narrative analysis in narrative genres and arts-based inquiry
  • Practicing conducting your own narrative analysis

 
Who will benefit?
 

This advanced training course is relevant for those who have undertaken the SRA foundation course on Narratives and Storytelling (or similar course), or who have already completed their own narrative inquiry. It will benefit participants who wish to advance their knowledge of qualitative research methods by exploring the benefits that narrative analysis offers in a range of applied and policy settings and contexts.

**Prior knowledge of qualitative research methods and storytelling and narrative inquiry is advisable.

 
Learning outcomes
 

  • Understand what we mean by narrative analysis and interpretation.
  • Have knowledge of different models of narrative analysis.
  • Understand the relationship between qualitative research, narrative inquiry, and narrative analysis and how this informs selection of model of narrative analysis.
  • Be able to undertake a narrative analysis as evidenced in practical activities.

 
Course Tutor
 

Dr Karen Lumsden is currently Assistant Professor in Criminology at the University of Nottingham and has a PhD in Sociology from the University of Aberdeen. She has over 15 years experience teaching qualitative research methods at postgraduate level and to academics and practitioners. This includes courses at the University of Aberdeen, University of Glasgow, University of Essex and Kingston University, and for the Social Research Association. Karen has also designed and delivered social research methods training for police officers and staff via the East Midlands Policing Academic Collaboration (EMPAC) and for research consultancies. She has authored a number of academic books and journal articles in the areas of sociology and criminology, and on qualitative research methods. Karen is also Chair of the Editorial Board of Sociological Research Online.

 

Research with Children and Young People (01/12/20)

Thu, 08/10/2020 - 01:00


This live online course explores a range of issues in conducting research with children and young people, both in person and remotely. * Price:  £165 for SRA members, £220 for non-members.  It runs over two mornings and uses Zoom software *


Introduction/Overview


Capturing the views and experiences of children and young people directly, rather than by proxy (through parents or professionals), is increasingly recognised as essential for research, evaluation and policy development. Drawing on the tutors’ extensive experience and expertise in this field, this long-running, and highly interactive, training has now been developed into an online course which, over two half days, provides an opportunity for participants to explore the ethical, methodological and practical considerations of doing research and evaluation with children and young people, both face-to-face and remotely, and consider how to apply this learning to their own work.
 
Course objectives
 

By the end of the workshop, participants will:

  • Understand the policy, theoretical underpinnings and advantages of conducting primary research with children and young people
  • Understand the key ethical and methodological considerations
  • Be able to apply this learning to their own work and plan ethically and methodologically sound projects with children and young people
  • Be more aware of, and equipped to meet, common challenges

 
Topics
 

  • Common enablers and challenges likely to be encountered
  • Additional ethical considerations when conducting research or evaluation with children and young people and applying these in real world situations
  • Developing appropriate methods and tools, including creative, remote and participative* methods

(*Participative methods are only touched on briefly in this course, but are covered in much more depth in the ‘Public involvement in social research’ course by the same tutors.)

 
Who will benefit?
 

This course is designed for people with prior practical research/ evaluation experience, although not necessarily with children and young people, and who expect to manage and/or directly work on research or evaluation projects with children and young people.

 
Course tutors
 

The course will be delivered jointly by Berni Graham and Dr Louca Mai Brady, both senior researchers with extensive experience of conducting research and evaluation with children and young people. They have delivered this and other courses for the SRA since 2010. They are joint authors of Social Research with Children and Young People (2018). Both previously worked together as researchers at the National Children’s Bureau (NCB) Research Centre and in recent years have collaborated on research and evaluation projects for the NSPCC, Action for Children and NCB.

Dr Louca-Mai Brady is a Senior Research Fellow at UCL and independent researcher, trainer and facilitator with particular interests in participative and inclusive research methods, health research, and the involvement of children and young people in research. She is editor and co-author of: Embedding Young People's Participation in Health Services: New Approaches (2020), which is based on her doctoral research. (https://policy.bristoluniversitypress.co.uk/embedding-young-peoples-participation-in-health-services)

Twitter: @Dr_Loucamai

Berni Graham is an independent researcher, Evaluator and trainer, bringing 20 years’ experience of research and evaluation with children, young people and families, and typically exploring issues such as poverty, disability, the care system, school exclusions and child sexual abuse and exploitation. She is currently evaluating a Mencap Cymru project, which aims to raise awareness of the importance of relationships and friendships for people with learning disabilities, and recently evaluated an innovative early intervention programme to minimise behaviour that challenges among children with severe learning disabilities.

 

Public Involvement in Social Research (09/12/20)

Thu, 08/10/2020 - 01:00


This live online course explores the principles and practice of involving the public in research and evaluation, including using online methods. *Price:  £165 for SRA members, £220 for non-members. It runs over two mornings and uses  Zoom software*


Introduction/Overview


Involving the public in research and evaluation means that research design and delivery is carried out ‘with’ and ‘by’ members of the public rather than ‘for’ or ‘about’ them, e.g. as research ‘subjects’. Involving those who are the focus of research has a positive impact on what is researched, how research is conducted and the impact of findings. This can help policies and services to better reflect the priorities and concerns of those most directly affected by them, and is increasingly expected by research commissioners.

Drawing on the tutors’ extensive experience and expertise in this field, this popular SRA course is now available online. Using a mixture of slides, breakout groups and exercises, it combines theory with practical examples of public involvement and participatory methods, and explores online methods, and other alternatives to face-to-face involvement. It provides an opportunity for participants to develop an understanding of the choices and processes involved and how they can apply these to their own work.

 
Course objectives
 

By the end of the course participants will have a better understanding of:

  • What is meant by ‘public involvement’ in research and evaluation and the common language and terms used;
  • The theories and principles underpinning involvement;
  • Practical considerations, such as when and how to involve people and helpful models and approaches;
  • How to apply the principles & practice ideas to your own work, ensure quality and assess impact.

 
Topics
 

  • Benefits, rationale and the theoretical background for public involvement in the design and delivery of research and evaluation
  • Different models and approaches to face-to-face and online/remote involvement, co-production and user-led research
  • The main methodological and ethical considerations involved, and how participative and inclusive research methods can support public involvement
  • Challenges to meaningful public involvement including issues of diversity and representativeness, as well as when and how best to involve who

 
Who will benefit?
 

This course is suitable for people with practical experience of research and/or evaluation (qualitative or quantitative), who want to learn more about public involvement and why and how they might involve the public in their own research and evaluation projects.

 
Course tutors
 

Both tutors are senior researchers with extensive experience of applied social research and evaluation, supporting public involvement in research and considerable expertise in supporting the involvement of children and young people and other less frequently heard groups.

Dr Louca-Mai Brady is a Senior Research Fellow in Public Involvement at UCL and independent researcher, trainer and facilitator with particular expertise in qualitative and participative methods and public involvement in health and social care research, which was also the topic of her PhD. She has supported and written about young people’s involvement in research and evaluation for many years and is editor of Embedding Young People's Participation in Health Services: New Approaches (2020): Over 2007-2019 Louca-Mai was a longstanding advisory member of INVOLVE, the National Institute for Health Research advisory group. In 2020 she helped run an online young people’s research advisory group and co-hosted a series of online meetings on ‘Coproduction and involvement in COVID and beyond’ (#CoProCOVID).

Twitter: @Dr_Louca-Mai

Berni Graham is an independent senior researcher, evaluator and trainer with extensive experience of research and evaluation in health, education, social care, early years, welfare, disability, community development and the environment. She has often collaborated with groups of the public to jointly develop research or evaluation methods and questions and, conversely, has also evaluated many public engagement projects. Berni regularly trains and supports both adults and young people as peer / community researchers in different settings.

 

Introduction to QGIS: Spatial Data and Spatial Analysis - Online (20/04/21)

Wed, 07/10/2020 - 01:00

In this online two day course (taught over four 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

This course is ideal for anyone who wishes to use spatial data in their role. This includes students, academic, 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 GIS and spatial data can be used for, and how you can better represent your data with maps. No previous experience of spatial data is required. 

Please note this course is two days but will be taught over four mornings on the 20th, 21st, 27th and 28th April from 10am-1pm.

Working with large amounts of secondary or primary qualitative data: Breadth-and-Depth Method ...

Tue, 06/10/2020 - 01:00

This exciting and flexible online course will develop your knowledge and skills for working with qualitative data at scale: ‘big qual’.  It provides the methodological foundations for identifying, merging and analysing multiple sets of data from different sources, and working with large amounts of secondary or primary qualitative data.  Big qual data enables qualitative researchers to scope out new research questions that allow comparison and claims to generalisability while still retaining the distinctive order of knowledge about social processes that is the hallmark of rigorous qualitative research, with its integrity of attention to nuanced context and detail.

 

You will gain guided experience of the unique four-step Breadth and Depth Method to enable you to combine extensive coverage with intensive illumination, moving between the span of big qual analysis and the qualitative integrity of detailed context.  In your 7 hours or so of study across the three days, using a range of resources, including informative short videos and guided hands-on activities, the course will cover:

  • An introduction to the course, outlining its content and format
  • The potential gains of working with large amounts of qualitative data
  • An introduction to the Timescapes Archive, giving you a feel for accessing, searching, obtaining and organising large amounts of data
  • Working through the Breadth-and-Depth Method of working: 
    • Step 1:  Creating breadth - identifying and exploring datasets using contextual meta data
    • Step 2:  Investigating breadth – preliminary explorations of the big qual data set using basic text analysis software
    • Step 3:  Moving from breadth to depth – identification of themes and hotspots in the data using analytic software, to identify case studies for deeper analysis
    • Step 4:  Exploring depth – undertaking in-depth analysis of cases, and then relating depth to back to breadth
  • Closing the course:  discussion and reflections on the method and learning process

 

The course is suitable for early career as well as more experienced researchers.  You will need to be familiar with the purpose of qualitative research and qualitative methods of data collection and analysis.

 

  • The course is tailored so that you can dip-in-and-out of resources and activities, self-directing your study to fit in with your work and life commitments.
  • The course is guided by expert tutors in a way that allows you to tailor your 7 hours or so of participation across a 3-day period to fit in with your work and life commitments.
  • You will be able to access online guidance from the course tutors as you work your way through sets of resources and activities.
  • You will be introduced to the course by the tutors who will be available online for question and answer chat sessions in scheduled ‘office hours’ every morning and afternoon, culminating in a live online discussion session on the afternoon of the third day.
  • Informative ‘bite-size’ videos, annotated reading lists, and step-by-step activity explanations will provide you with knowledge foundations and hand-on experience, enabling you to work through the course in a flexible way, checking in to the chat facility to post any questions and receive answers.
  • Course participants will also be able to access peer support through scheduled open classroom sessions, where you can meet and chat with each other.

 

The course will be delivered by the ESRC National Centre for Research Methods team who developed the Breadth and Depth Method approach to analysing big qual:

  • Dr. Emma Davidson, University of Edinburgh
  • Professor Lynn Jamieson, University of Edinburgh
  • Dr. Susie Weller, University of Southampton
  • Professor Rosalind Edwards, University of Southampton

Working with large amounts of secondary or primary qualitative data: Breadth-and-Depth Method. ...

Fri, 02/10/2020 - 01:00

The exciting and flexible online course will develop your knowledge and skills for working with qualitative data at scale: ‘big qual’. It provides the methodological foundations for identifying, merging and analysing multiple sets of data from different sources, and working with large amounts of secondary or primary qualitative data. Big qual data enables qualitative researchers to scope out new research questions that allow comparison and claims to generalisability while still retaining the distinctive order of knowledge about social processes that is the hallmark of rigorous qualitative research, with its integrity of attention to nuanced context and detail.

You will gain guided experience of the unique four-step Breadth and Depth Method to enable you to combine extensive coverage with intensive illumination, moving between the span of big qual analysis and the qualitative integrity of detailed context.

In your 7 hours or so of study across the three days, using a range of resources, including informative short videos and guided hands-on activities, the course will cover: ·

An introduction to the course, outlining its content and format ·

The potential gains of working with large amounts of qualitative data ·

An introduction to the Timescapes Archive, giving you a feel for accessing, searching, obtaining and organising large amounts of data ·

Working through the Breadth-and-Depth Method of working: -

Step 1: Creating breadth - identifying and exploring datasets using contextual meta data -

Step 2: Investigating breadth – preliminary explorations of the big qual data set using basic text analysis software -

Step 3: Moving from breadth to depth – identification of themes and hotspots in the data using analytic software, to identify case studies for deeper analysis -

Step 4: Exploring depth – undertaking in-depth analysis of cases, and then relating depth to back to breadth ·

Closing the course: discussion and reflections on the method and learning process The course is tailored so that you can dip-in-and-out of resources and activities, self-directing your study to fit in with your work and life commitments. You will be able to access live online guidance from the course tutors as you go, culminating in a live online discussion session on the afternoon of the third day. ·

The course is guided by expert tutors in a way that allows you to tailor your 7 hours or so of participation across a 3-day period to fit in with your work and life commitments. · You will be able to access online guidance from the course tutors as you work your way through sets of resources and activities. · You will be introduced to the course by the tutors who will be available online for question and answer chat sessions in scheduled ‘office hours’ every morning and afternoon, culminating in a live online discussion session on the afternoon of the third day. · Informative ‘bite-size’ videos, annotated reading lists, and step-by-step activity explanations will provide you with knowledge foundations and hand-on experience, enabling you to work through the course in a flexible way, checking in to the chat facility to post any questions and receive answers. · Course participants will also be able to access peer support through scheduled open classroom sessions, where you can meet and chat with each other. The course will be delivered by the ESRC National Centre for Research Methods team who developed the Breadth-and-Depth Method approach to analysing big qual: ·

Dr. Emma Davidson, University of Edinburgh ·

Professor Rosalind Edwards, University of Southampton ·

Professor Lynn Jamieson, University of Edinburgh ·

Dr. Susie Weller, University of Southampton