Research Methods: Surveys as a Mixed-Data Tool
To evaluate the Digital Journeys prototype, I am using short, structured questionnaires for two participant groups: students and staff. Although surveys are sometimes associated with quantitative research, Gray and Malins emphasise that in art and design research, questionnaires can generate both qualitative and quantitative insights, particularly when combined with reflective interpretation. They note that questionnaires can be used “not simply to collect facts, but to reveal attitudes, perceptions and experiences” (Gray and Malins, 2004, p. 143).
The student survey is designed to capture:
- Quantitative data (e.g. Likert-scale questions measuring clarity, usefulness, and confidence).
- Qualitative data (open-ended questions inviting comments on what worked, what was confusing, and what could be improved).
The staff survey focuses more strongly on qualitative feedback, exploring how the resource might support teaching, clarify expectations around software use, and integrate into unit delivery.
This approach aligns with Doing Your Research Project, which argues that combining question types allows researchers to balance breadth and depth, noting that “open questions can provide insights that the researcher may not have anticipated” (Bell, 2014, p. 157). In my project, this is particularly important because I want students to articulate in their own words how the resource affects their workflow, rather than forcing their experience into predefined categories.
Thematic Analysis as an Analytical Strategy
Given the qualitative nature of much of the survey data, I am using thematic analysis as my primary method of analysis. Braun and Clarke describe thematic analysis as “a method for systematically identifying, organising, and offering insight into patterns of meaning (themes) across a dataset” (Braun and Clarke, 2021, p. 4). This flexibility makes it particularly suitable for practitioner research, where data may be relatively small-scale but rich in meaning.
Rather than treating thematic analysis as a purely technical process, Braun and Clarke emphasise that it is an interpretive act. They argue that themes do not simply “emerge” from data, but are actively constructed by the researcher through engagement with theory, context, and research questions (Braun and Clarke, 2021). This perspective is important for my project, as my analysis is shaped by my professional experience supporting students with creative software. Braun and Clarke argue that transparency strengthens qualitative research, noting that “good thematic analysis makes the researcher’s analytic process visible” (Braun and Clarke, 2021, p. 35). In practice, this means clearly linking themes to data extracts and explaining how design decisions are informed by participant feedback.
I am following Braun and Clarke’s six-phase approach:
- Familiarisation: Reading survey responses multiple times to gain an overview of student and staff perceptions.
- Coding: Identifying meaningful features of the data, such as references to confusion, confidence, efficiency, or visual clarity.
- Generating themes: Grouping codes into broader themes, for example software confusion, value of visual guidance, or independent learning support.
- Reviewing themes: Checking themes against the dataset to ensure they are coherent and representative.
- Defining and naming themes: Refining each theme to clearly articulate what it captures about the data.
- Writing up: Integrating themes with theory and reflecting on their implications for practice.
Braun and Clarke stress that thematic analysis is particularly valuable for applied research, as it allows researchers to connect individual experiences to broader patterns. As they note, it enables researchers to “move beyond describing data to interpreting and making sense of it” (Braun and Clarke, 2021, p. 22). In my project, this means linking student comments about confusion or confidence directly to design decisions within Digital Journeys.
Visual Analysis and Designerly Ways of Thinking
As this project sits within art and design education, analysis is not limited to text. Gray and Malins argue that designers often think through visual means, suggesting that analysis can involve “mapping, diagramming and visual structuring of ideas” as much as written interpretation (Gray and Malins, 2004, p. 172). This has directly informed how I plan to analyse and present my findings.
For example, emerging themes from the surveys may be translated into visual diagrams or infographics that mirror the structure of the Digital Journeys resource itself. This approach reflects Gray and Malins’ assertion that visual methods help researchers “see relationships, gaps and patterns that might remain hidden in linear text” (Gray and Malins, 2004, p. 176).
This visual mode of analysis also reinforces alignment between method and output: a project about visual learning pathways is analysed and communicated using visual strategies.
Visual analysis and iterative interpretation
Gray and Malins frame analysis in art and design as an iterative, practice-led process that moves between “gathering material, reflecting on it, making something, evaluating it, and adjusting and continuing” (Gray and Malins, 2004). This perspective is directly applicable to Digital Journeys, where visual mapping operates not only as an outcome but as an analytical tool. In this project, diagrams and clustered visual maps are used to identify patterns in survey feedback such as recurring references to clarity, confidence and workflow supporting Gray and Malins’ argument that designers should not analyse “only with words” but through visual organisation and pattern recognition. Their emphasis on defining evaluation criteria in relation to the research question also informs how the prototype is assessed, ensuring that interpretation remains systematic and aligned with the project’s aim of improving accessibility and digital literacy for students.
Conclusion
In summary, this project combines action research, survey-based data collection, and thematic analysis to investigate how a visual digital learning resource can improve students’ creative software workflows. Drawing on McNiff and Whitehead, Gray and Malins, and Braun and Clarke, the research design foregrounds practitioner knowledge, visual ways of thinking, and reflexive qualitative analysis. Rather than treating theory as separate from practice, the methodologies used are embedded within the real constraints, values, and challenges of teaching creative software in higher education.
The next stage of the project will involve applying the findings from the thematic analysis to refine Digital Journeys, closing the action research loop by translating insight into improved educational practice.
Bibliography
Braun, V. and Clarke, V. (2021) Thematic Analysis: A Practical Guide. London: SAGE.
Gray, C. and Malins, J. (2004) Visualizing Research: A Guide to the Research Process in Art and Design. Farnham: Ashgate.
McNiff, J. and Whitehead, J. (2011) You and Your Action Research Project. 3rd edn. London: Routledge.
Bell, J., Bryman, A. and Harley, B. (2018) Doing Your Research Project: A Guide for First-Time Researchers. 7th edn. Maidenhead: Open University Press.
British Educational Research Association (BERA) (2024) Ethical Guidelines for Educational Research. 5th edn. London: BERA. Available at: https://www.bera.ac.uk/publication/ethical-guidelines-for-educational-research-fifth-edition-2024-online (Accessed: 12 December 2025).
University of the Arts London (UAL) (n.d.) Inclusive Teaching and Learning Framework. Available at: https://www.arts.ac.uk/about-ual/learning-and-teaching/teaching-and-learning-exchange/inclusive-teaching-and-learning (Accessed: 7 December 2025).