This research project investigated student experiences of AI-assisted coding (“vibe coding”) within the BA Fine Art: Computational Arts programme, using semi-structured interviews (Wilson, 2012). The study addresses a social justice issue within arts education: how uneven access to prior technical training, language proficiency, and confidence with coding can shape students’ ability to benefit from emerging AI tools. These disparities directly affect student experience, particularly in a programme that aims to be inclusive while supporting highly individualised artistic practices.
Semi-structured interviews were selected as an appropriate research design for exploring complex, subjective experiences that cannot be meaningfully reduced to quantitative data (Beck and Manuel, 2008). The interview questions provided a flexible structure that enabled participants to reflect on prior coding experience, first encounters with AI tools, and perceived impacts on learning and creative agency. However, the study revealed important methodological considerations. One participant requested access to the questions in advance due to English not being their first language, highlighting accessibility needs that were not fully anticipated. This participant ultimately chose to respond in writing rather than through an online interview, demonstrating how research methods may need to adapt to participants’ circumstances.
Rather than viewing this deviation as a failure, the project draws on Mike Michael’s concept of “idiotic methodology” (Michael, 2012; 2013), which encourages researchers to embrace unexpected methodological turns as productive. In retrospect, a more open-ended, creative instrument may have been better suited to an arts education context. Future iterations of the study would therefore adopt a cultural probe approach (Gaver and Dunne, 1999), reshaping the research questions into drawing, annotating, and reflective exercises that can be completed offline. Drawing on my prior experience contributing to probe-based research (Gaver, 2016), this approach would support more inclusive and imaginative forms of participation.
Findings from the interviews suggest that challenges surrounding vibe coding are less about the presence of AI itself and more about uneven starting points in coding education. Both participants emphasised the need for a clear foundational understanding of code in order to use AI tools critically and effectively. This highlights a gap in the course team’s awareness of students’ prior training, with implications for curriculum design and support structures.
Although the study was limited to two participants due to timing constraints, the inclusion of both a current first-year student and a recent graduate enabled a valuable cross-generational comparison. When situated alongside larger-scale studies of student–AI interaction (e.g. Geng et al., 2025), this project demonstrates the value of small-scale, qualitative inquiry while also identifying the need for broader participation and task-based methods in future research.
References
Beck, S. E., & Manuel, K. (2008). Practical research methods for librarians and information professionals. New York, NY: Neal-Schuman.
Gaver, B., Dunne, T. and Pacenti, E., 1999. Design: cultural probes. interactions, 6(1), pp.21-29.
Gaver, W., Ovalle, L. and Plummer-Fernandez, M., 2016. Tilly and the Myth of Energy Independence.
Geng, F., Shah, A., Li, H., Mulla, N., Swanson, S., Raj, G.S., Zingaro, D. and Porter, L., 2025. Exploring Student-AI Interactions in Vibe Coding. arXiv preprint arXiv:2507.22614.
Michael, M., 2012. De‐signing the object of sociology: Toward an ‘idiotic’methodology. The Sociological Review, 60, pp.166-183.
Michael, M., 2013. The idiot. Informática na educação: teoria & prática, 16(1).
Wilson, V., 2012. Research methods: interviews.
Wakeford, N. ed., 2012. Inventive methods. London: Routledge.