One of the challenges of interdisciplinary education is how to engage learners with the wide range of research methods available from across the disciplines. Complex projects with multiple opportunities and demands can reach their full potential if the right methods are selected and practised with confidence and creativity. At the start of a new project, it can be difficult to know what to prioritise, which processes to invest in, and who to reach out to:

How can we understand the community’s view on this problem?

What forms of documentation could we use to capture this work?

Do we need to appoint an arts facilitator?

What can a statistician bring to this project?

How could we use coding to streamline this process?

This section explores some of the options available to interdisciplinary learners who might be considering questions like these. It provides a selection of research methods that can be used for a variety of interdisciplinary projects. And it considers how some of these methods can be brought together effectively to address a range of challenges.

The conviction underpinning this section is that there is great value in developing a foundational understanding of a wide range of research methods. The intention is not towards expertise in all of these approaches (although researchers may well specialise in multiple methods). Rather, in order to prepare ourselves to work in interdisciplinary teams on complex problems, we need to become familiar with how different researchers and practitioners work. Interdisciplinary enquiry begins with shared reference points and an understanding of alternative approaches.

The approach taken by the MA(hons) Interdisciplinary Futures at The University of Edinburgh is to introduce a series of challenge questions, each of which is addressed from multiple methodological perspectives. Students take part in a collection of workshops, each of which offers a different approach to the same problem. The four workstations are: Data Collection, Data Analysis, Cultural Analysis and Creative Practice. On the methods courses, Researching Global Challenges (RGC1 and RGC2), learning takes place in a large teaching space, with students visiting each of the four workstations in turn. Looking around the room, they can see other groups who are working on the same question with very different activities. This video introduces methods training on these courses.

Introducing interdisciplinary learners to a wide range of methodological approaches means that communication and collaboration will happen more easily and efficiently. If we take time to engage with working processes that are unlike those with which we are most familiar, then we are likely to see the value in them and consider incorporating them into our projects.

This approach sets out to expand the ‘toolkit’ that is available for interdisciplinary projects. However, engaging with multiple methods does not guarantee interdisciplinarity. As Catherine Lyall and her co-authors point out, ‘interdisciplinary research does not occur automatically’ (2015, p. 1), but requires strategies for synthesis and collaboration. The methods in this section are therefore presented as potential components of an interdisciplinary enquiry, which can emerge within the wider context of interdisciplinary learning and teaching, informed by a holistic approach to collaboration, assessment strategies and ethical practice.

Some of the methods introduced in this section are particularly suited to an interdisciplinary approach, as they require a combination of diverse practices that are brought together in response to a specific challenge. Celia Lury introduces such compound methods, understood in the Routledge Handbook of Interdisciplinary Research Methods as combined research activities, which incorporate ‘a variety of practices’ (2018, p. 7). Thematic coding, ethnography, decolonising methods, and deep mapping are all examples of compound methods, which could be adopted as potentially, if not inherently, interdisciplinary activities.

Each of the following four categories of research methods includes a brief introduction, some suggested activities or lesson plans, and a list of resources. It is important to note that these are not discrete categories: they blend into each other and overlap, and their potential as interdisciplinary methods emerges in their combination as a ‘methodological bundle’. If interdisciplinarity is to be given a chance to develop in these contexts, a confident grounding in these categories may be the best place to start.

Data Collection is the process of gathering information, using various methods and for a specific purpose (Creswell 2022). Data can be qualitative (qualities, characteristics, words) (Ritchie et al. 2014; Silverman 2002), or quantitative (numbers) (Chivers & Chivers 2022). While collected data will also be analysed, the emphasis here is on methods for building new datasets.

Data collection training might include:

• Surveys – collecting information about a group of people by asking them questions (often about opinions, beliefs, characteristics, preferences etc.) and then analysing the results. Used in both cross-sectional studies (collect data just once), and in longitudinal studies (survey the same sample several times over an extended period).
• Interviews – Based on verbal communication and spoken narratives, interviews recognise that participants actively construct their social world and can verbalise their insights. The process is relational and used to explore complex issues and processes, private and sensitive subjects.
• Big data – working with large datasets, which might be changing and growing at the point of encounter. Used in a variety of areas including machine learning.
• Social media – Collection of social media content and metadata, which ‘contain useful information for understanding human-nature interactions in space and time’ (Toivonen et al., 2019).

Resources:

This Data Collection and Analysis activity plan includes suggestions for workshop activities:

• Exploring the use of data analysis
• Exploring the research question
• Exploring terms and concepts encountered in introductory data analysis texts
• Interpreting data in a research paper or report

Further reading:

• Creswell, J. W., (2022). Research design: qualitative, quantitative, and mixed methods approaches, 6^th Thousand Oaks, Sage, 2022
• Chivers, T., and Chivers,, (2022) How to Read Numbers: A Guide to Statistics in the News (And Knowing When to Trust Them.) London, Weidenfeld & Nicolson.
• Ritchie, J., Lewis, J., McNaughton Nicholls, C., and Ormston, R. (2014) Qualitative Research Practice: A Guide for Social Science Students and Researchers (eds.), 2nd edition., Los Angeles, SAGE.
• Silverman, D (2002). Doing Qualitative Research, 6th Edition, Washington D.C., SAGE.

Data Analysis is what happens after a dataset has been created or located. The aim of data analysis is to interpret, describe, or model information that has been purposefully collected to draw insights and conclusions about a particular question under investigation. These insights should be linked to higher order concepts and theories. Depending on the type of data, various systems, tools and programmes are available to clean, store, organise, interpret and communicate complex information.

Data analysis training might include:

• Descriptive statistics – exploratory analysis used to understand frequencies, averages and correlations. It is about summarising, or describing, the data numerically or visually, rather than making decisions based on causation. The process often involves creating tables, charts and summary statistics, such as percentages, from raw data.
• Thematic coding/analysis – for use with qualitative datasets, this analysis aims to identify, analyse, and interpret patterns or themes, and relate them to the research questions and higher order concepts. The most common analysis method is known as ‘thematic coding’ and it is useful for interdisciplinary research due to its flexibility (Braun & Clarke, 2006).
• Data visualisation – translation of raw data into aesthetically appealing visual formats, for example, graphs, tables or graphics. The purpose is to make it easier for an audience to process information faster and more efficiently. Data visualisation should help others identify patterns, trends, and correlations in the data; it should tell a story that can help in informed decision-making.
• NVivo – popular qualitative data analysis software for storing, organising, transcribing and thematically coding qualitative and mixed methods datasets. Its latest edition uses AI to drive sentiment categorisation and preliminary thematic analysis.
• Mapping interactional dynamics – analysis rooted in principles of interactional sociolinguistics (IS) which ‘studies the language use of people in face-to-face interaction’ (Jaspers, 2023), focuses on the relationality of speech and types of speech to make sense of participants’ evolving dynamic. With the use of tools like IDLab, interactional discourse analysis can help make sense of a team’s dynamic, encouraging self-awareness and responsiveness.

Further reading:

• Braun, V., and Clarke, V. (2006) Using thematic analysis in psychology. Qualitative Research in Psychology, 3 (2), 77-101.
• Clarke V., Braun V. (2013). Teaching thematic analysis: Overcoming challenges and developing strategies for effective learning. The Psychologist, 26(2), 120–123.
• Finlay, L. (2021). Thematic Analysis: The ‘Good’, the ‘Bad’ and the ‘Ugly’. European Journal for Qualitative Research in Psychotherapy, 11, 103–116.
• Jaspers, J. (2023). Interactional sociolinguistics and discourse analysis. In The Routledge handbook of discourse analysis (pp. 85-97). Routledge.

Cultural Analysis uses a range of methods to understand and interpret the meanings of various types of cultural texts, including art, literature, performance, film and images. It is multidimensional and ‘seeks to make sense of the ontological complexity of cultural phenomena’ (McGuigan 2010, p. 1). The emphasis here is on examining artefacts that have already been created.

Cultural analysis training might include:

• Semiotics – the study of signs and their meaning, semiotics offers a useful structure for reading a wide range of cultural texts and decoding their meaning (Chandler 2022).
• Narrative analysis – understanding personal experience of research participants by interpreting story structure and identifying narrative devices.
• Visual analysis – a structured approach to decoding meaning in images and understanding the compositional choices of the image creator.
• Film analysis – the technical and compositional elements of film images are analysed with attention to sound, camera angles, editing and arrangement of the screen picture.
• Discourse analysis – attention is given to the linguistic content and socio-linguistic context of writing and speech, often in dialogue.
• Ethnography – analysis of human cultures and societies, including qualitative methods such as interviews and observations, often taking place in the field.
• Participant observation – joining a particular group or organisation as a researcher and taking part in the phenomena being studied.
• Decolonising methods – a recognition that research has often been exploitative and can be decolonised by a wide range of practices that are respectful, reciprocal and reflexive. Linda Tuhiwai Smith (2012) advocates strategies of: Claiming, Testimonies, Storytelling, Celebrating survival, Remembering, Indigenising, Intervening, Revitalising, Connecting, Reading, Writing. Representing, Gendering, Envisioning, Reframing, Restoring, Returning, Democratising, Networking, Naming, Protecting, Creating, Negotiating, Discovering and Sharing.

Resources:

1. Semiotics – This lesson plan is an Introduction to semiotics – the study of signs. It provides a valuable starting point for a series of workshops that explore how we read and interpret a variety of cultural texts (from books to videos, fashion and cities).
2. Visual analysis – The Writing Studio at Duke University provides a useful introduction to visual analysis in art history. The approach can easily be adapted to understand how a range of visual sources create meaning.
3. Decolonising methods – This worksheet for Methods of decolonisation provides a description of the 25 methods introduced by Linda Tuhiwai Smith. These can be used in a variety of projects that draw attention to the ways in which research can become more respectful, reciprocal and reflexive.

Further reading:

• Chandler, Daniel. 2002. Semiotics: The basics. Routledge.
• McGuigan, Jim. 2010. Cultural Analysis 1st ed. Sage.
• Smith, Linda Tuhiwai. 2012. Decolonizing Methodologies: Research and Indigenous peoples. 2nd edition ed. Zed Books.

Creative Practice is the use of artistic methods to generate new cultural texts. The process of creation is often just as important as the output and this section includes a range of collaborative and participatory methods that can be used in a variety of research contexts. In this context, creative practice is understood as a research methodology (Nelson 2022).

Creative practice training might include:

• Drawing – facilitating visual responses to a challenge question can indicate themes and trends; collaborative drawing can encourage creative approaches to team research.
• Zine making – quick, DIY magazines allow exploration of research topics through cutting, sticking, drawing and folding, focussing attention on creating, interpreting and visualising information.
• Photography – no longer reliant on specialist equipment, participants can use their own devices and consider visual storytelling as an important research tool.
• Film making – the stages of development, pre-production, production, post-production and distribution, can all inform a research process.
• Speculative fiction – creative writing can be used to imagine possible futures, inviting a close consideration of the impact of the choices that we make today (Fischer and Mehnert 2021).
• Creative engagements with place – mapping, participatory methods and art making can all be used to shift perceptions and modes of engagement with our communities and environments (Modeen and Biggs 2021).

Resources:

1. Collaborative drawing – This lesson plan for Collaborative drawing offers a way into creative methods, for groups of learners who may have a wide range of experience.
2. Zines – This lesson plan for Zine making offers another creative method: DIY magazines that can be created quickly during a learning session. See also Dan Swanton’s What’s a zine? zine, used in assessment of geography students at the University of Edinburgh.
3. Poetry – The Scottish Poetry Library and the Binks Hub have developed a series of Poetry for wellbeing workshops. Originally created with and for social workers, the tasks and lesson plans can be adapted to various contexts and can be embedded within a research methods course.

Further reading:

• Nelson, Robin. (2022). Practice as Research in the Arts (and Beyond): Principles, Processes, Contexts, Achievements. Springer.
• Fischer, Nele and Mehnert, Wenzel. (2021). ‘Building possible worlds: a speculation based framework to reflect on images of the future’, Journal of Futures Studies3. pp. 25-38.
• Modeen, Mary, and Iain Biggs. 2021. Creative Engagements with Ecologies of Place: Geopoetics, deep mapping and slow residencies. Oxon: Routledge. 

   

  A full list of references for the TILT site is available here.