Summer School 2024
Our popular programme of research-methods courses will take place between 24 June and 5 July 2024.
What we offer
The selection includes a variety of in-person and online courses focusing on software training, qualitative and quantitative analysis, data collection techniques and much more! The course content is based on approaches from across the various schools within The University of Manchester.
Purchases for our Summer School have now closed. If you have any questions, please get in touch with methods@manchester.ac.uk.
Dates
The Summer School will take place on 24 June - 5 July 2024.
Course details
In-person courses
In-person courses will adopt the following approximate timetable, but you will be advised of precise starting and finishing times for your selected course:
Morning: 9.00am - 12.30pm (with refreshment break)
Lunch: 12.30pm - 1.30pm
Afternoon: 1.30pm - 5.00pm (with refreshment break)
Arrival on Day 1: There will be registration followed by a methods@manchester welcome talk at 1pm, with courses starting at 1.30pm.
For any questions, please get in touch at methods@manchester.ac.uk and a member of our team will respond as soon as possible.
Online courses
Online courses will each follow their own timetables set by the course leads.
Courses on offer this year
Date: 1 July – 5 July 2024
Course leads: Dr Haleema Sadia and Dr Pauline Prevett
This in-person course provides a comprehensive introduction to using NVivo to manage the data and analyse a qualitative or mixed methods research project.
For full details about this course and to book your place, please visit the course webpage.
Date: 1 July – 5 July 2024
Course leads: Sam Hind, Luca Scholz, Lukasz Szulc, Joanna Taylor and Shuaishuai Wang
Key digital developments, such as increasing volumes of available data, the automation of data collection, and the critical adoption of digital and computational methods across the humanities and social sciences have had profound effects not only on academic research but also on what qualifies as knowledge.
This course offers an introduction to digital methods and practical experience of how to use a range of digital tools, techniques, and software to study culture and society.
Participants will explore how digital methods and methodologies have shifted and changed over time, including their affordances and limitations. They will be introduced to state-of-the-art approaches (e.g. geospatial methods, mobile methods, operational methods, text mining, data visualisation and algorithmic ethnography) and have a chance to apply them to create, analyse and question data.
For full details about this course and to book your place, please visit the course webpage.
Date: 1 July – 4 July 2024
Course lead: Dr Gail Hebson
This in-person course introduces a critical but friendly approach to qualitative interviewing.
Participants will be encouraged to think about the role of qualitative interviews in their research, their own role in data collection and the nature of the data generated in interviews. Participants will position their own approach in relation to the different philosophical debates in qualitative research which will help them think critically about what type of data they can access using interviews.
Ultimately the course is a celebration of the interview – with all its’ flaws – and an opportunity to engage with the what, how and why of qualitative interviewing approach and a more ‘critical’ understanding of what interview data represents.
Since Atkinson and Silverman (2007) identified an ‘interview society’ and questioned why interviews seemed to be the ‘go-to’ method for qualitative researchers, little has changed and interviews have become even more ubiquitous. Celebrity ‘tell all’ interviews and podcasts all use the interview as a medium to access the interviewee’s real ‘authentic self’ and ‘their truth’
Methodological debates in the social sciences recognise that this is problematic and in fact interviews rarely give privileged access to the interior subjectivity and experiences of participants. Yet as noted by Silverman (2017), these methodological debates are in a silo and as social science researchers we continue to use interview data uncritically, focusing on the ‘what’ is said rather than the ‘why’ or the ‘how’ of what is said. On this course we will focus on all of these aspects.
For full details about this course and to book your place, please visit the course webpage.
Date: 2 July – 3 July 2024
Course lead: Dr Nicole Brown
This online course seeks to support qualitative researchers in dealing with the key concepts of positionality and reflexivity.
During the course attendees will explore the role of the researcher at the insider/outsider divide as well as experience and practise practical strategies and exercises to learn how to "do" reflexivity.
Drawing on embodied and creative techniques we practise conscious noticing, we discuss our being, assumptions and beliefs and how they impact research.
We will further examine the use of a research journal in relation to doing reflexivity and exploring one's positionality. We will experiment with form and formats of recording journal entries, consider how to make choices of what to record when and trial strategies for recording information we may have missed. Finally, we will deal with the practicalities of moving from the personal, private practice of doing reflexivity to the formal, public statement of positionality that is often asked for in theses and publications.
In line with the pedagogical principles of social constructivism the course is delivered as a mixture of interactive group tasks, discussions and lectures to enable active and experiential learning.
For full details about this course and to book your place, please visit the course webpage.
Date: 24 – 28 June 2024
Course lead: Dr Helen Kara
Academic writing is always creative: putting words together to make sentences, sentences to make paragraphs, and so on, as nobody has ever done before. However, in any discipline, some academics write more creatively than others.
This online course will raise your awareness of the scope for creativity in academic writing, and provide you with the skills you need to use creative techniques in ways that will make your academic writing more engaging and accessible for your readers.
This course will support you in reaching an understanding of:
- The role of fiction and fiction writing techniques in academic writing
- The role of poetry and poetic techniques in academic writing
- The role of play and screenplay writing in academic work
- The blurred boundary between writing and drawing
- Writing as a resource as well as a task to complete
By the end of this course you should know how to find time to write creatively, and how to use that time well. You should also be able to draft a piece of creative academic writing: for example a blog post, journal article, thesis chapter or section.
For full details about this course and to book your place, please visit the course webpage.
Date: 1 - 5 July
Course leads: Martin Everett, Nick Crossley, Nikita Basov, Tomáš Diviák
This is an introductory course, covering the concepts, methods and data analysis techniques of social network analysis. This course can be attended in-person or online.
This is a hands on course largely based around the use of UCINET software, and will give participants experience of analyzing real social network data using the techniques covered in the workshop.
This course will support you in reaching an understanding of:
- Introduce the assumptions and main ideas underlying Social Network Analysis
- Explain how to describe and visualise networks using specialist software (UCINET)
- Explain and apply key concepts of Social Network Analysis (e.g. cohesion, brokerage)
- Provide hands-on training to use software to investigate social network structure
For full details about this course and to book your place, please visit the course webpage.
Date: 4 - 5 July
Course leads: Elisa Bellotti
This in-person course teaches how mixed methods can be used in egonets as well as whole network analysis.
This course will introduce you to ontological and epistemological foundations of SNA and how they call for a mixed method approach.
This course will support you in reaching an understanding of:
- To understand the ontological, epistemological and methodological foundations of Social Network Analysis.
- To learn how to use qualitative methods to collect, analyse and interpret social network data.
- To learn how to mix qualitative methods with quantiative analysis of social networks.
- To critically evaluate social network studies and their methodological framework.
For full details about this course and to book your place, please visit the course webpage.
Date: 1 - 5 July
Course leads: Martin Everett, Nick Crossley, Nikita Basov, Tomáš Diviák, Elisa Bellotti
This in-person course is designed for those who would like to gain an introductory knowledge of social network analysis (e.g. learn how to compute SNA measures) before developing understanding of the use of SNA for mixed methods research.
You will join other in-person attendees on the ‘Introduction to SNA’ course Monday - Wednesday (1st - 3rd July) before joining attendees on the ‘mixed methods in SNA’ course on the Thursday morning (4th July) for the remaining 1.5 days.
This course will support you in reaching an understanding of:
- Introduce the assumptions and main ideas underlying Social Network Analysis
- Explain how to describe and visualise networks using specialist software (UCINET)
- Explain and apply key concepts of Social Network Analysis (e.g. cohesion, brokerage)
- Provide hands-on training to use software to investigate social network structure Understand the ontological, epistemological and methodological foundations of Social Network Analysis
- Learn how to use qualitative methods to collect, analyse and interpret social network data
- Learn how to mix qualitative methods with quantiative analysis of social networks
- Critically evaluate social network studies and their methodological framework
For full details about this course and to book your place, please visit the course webpage.