In the 2021 publication, 'The Ontology of Design Research', Miguel Angel Herrera Batista argues that the ongoing development of postgraduate programmes in design has led to a growing focus on establishing the field of inquiry as an independent and differentiated research area. For design research to contribute to disciplinary development, researchers need to focus not only on procedural rigour but also on ensuring that the philosophical foundations of selected methodological approaches align with the ontological reality of design. It is, therefore, necessary to encourage postgraduate students to investigate both familiar and novel research methodologies in the search for appropriate approaches to design research projects.

Appreciative Inquiry (AI) is a research methodology developed in the late 1980s to reveal often overlooked, positive aspects of experience. AI is grounded in the theory of social constructionism. It focuses on understanding processes and experiences, and on creating alternative opportunities and ways of viewing situations and problems. AI typically follows a four-stage approach: 1) Discovery (appreciating and determining the best of what is); 2) Dream (identifying what might be and envisioning results); 3) Design (determining what should be and co-constructing change); and 4) Destiny (developing ways to achieve the vision). AI is commonly used as a research tool in fields such as management studies, education, healthcare, and social work, to study and improve the effectiveness of interventions and programmes.

The paper presents an MA Design (with a specialisation in Interior Design) research project as a case study to investigate the application of AI as a methodology in design research. The case study illustrates that, although AI has not been used extensively in design research, it offers opportunities to investigate under-researched topics in the design disciplines. AI is especially valuable in areas where processes and strategic thinking may be implicit and not yet formally described. In addition, the method's future-focused, collaborative approach aligns well with the speculative nature of design thinking (ideation & prototyping) and the anticipatory mindset encouraged during the design process. The paper makes recommendations for future applications of AI in design research. The paper postulates that by encouraging students at the master’s level to explore novel methodologies, design researchers, and by extension design practitioners, can gain deeper insight into design processes and build on the experiential knowledge of professionals to expand the theoretical base of the design disciplines.