This study was prompted by my suspicion that spatial design undergraduates’ production of paper-based freehand sketches during design ideation was in decline. Seeking to find out why, I conducted video-recorded focused interviews with undergraduates from a range of UK spatial design degrees, during which we examined their sketchbook material and discussed their ideational activities (termed ‘ideational moves’). I subjected the data to a form of content analysis, but the outcomes appeared to contradict my initial premise whilst revealing that the interactions during the interviews between myself, the respondents and the sketchbook material (termed ‘discursive moves’) warranted examination. This persuaded me that the study’s focus should emerge through ‘evolved’ grounded theory rather than being stated a priori, which highlighted my presence in, and impact on, the data and prompted me to adopt a constructivist grounded theorising approach in combination with actor-network theory’s concepts of translation and circulating references. This study has thus been qualitative, relativist, iterative and multi-modal. Grounded theorising led to the identification of a number of categories and sub-categories of ideational move across the sample, and indicated that the respondents had used a ‘core’ of each. ‘Core’ categories comprised: making paper-based ideational moves, carrying out research and using photographic material. Several respondents also evidenced producing digital imagery and physical models. ‘Core’ sub-categories comprised using paper-based freehand perspective sketches, sketch diagrams and word-based approaches, plus supporting visuo-spatial research. Several respondents also evidenced producing paper-based freehand plan, section and elevation sketches, plus collage. Grounded theorising also revealed that each respondent had utilised a different combination of sub-categories, with different degrees of connectedness. I did not set out to evaluate the design outcomes showcased, but, as a spatial design academic and practitioner, I felt compelled to. This led to the tentative conclusion that respondents who added to the ‘core’ of categories and sub-categories and worked with greater connectedness appeared to produce more thoroughly-considered work, whilst those who forsook the ‘core’ and worked with less connectedness appeared to produce more unexpected results by allowing ‘ ... room for chaos ... ’: periods of confusion and surprise. Regarding the discursive moves, grounded theorising indicated that the sketchbook material tabled by each respondent during the study was not one fixed thing, but an abstraction using placing-for and directing-to techniques to focus attention on certain ideational moves and away from others. This made the sketchbook material a performance within the network of human and non-human actors who, in effect, co-constructed it as a temporary reality without necessarily realising this. Research into sketchbook material appears to regard it, once shared with others, as having the candour of a secret diary, and as eligible for formative and summative assessment because it documents design process authentically. My study, whilst not claiming generalisability, suggests that this view should be challenged. The new knowledge is now informing my future teaching practice and will, I hope, prompt other academics to investigate whether their own students manifest similar outcomes and, through this, contribute to wider discussions on the formative and summative assessment of undergraduate spatial design development activity.

Advancements in creative artificial intelligence (AI) are leading to systems that can actively work together with designers in tasks such as ideation, i.e. the creation, development, and communication of ideas. In human group work, making suggestions and explaining the reasoning behind them as well as comprehending other group member’s explanations aids reflection, trust, alignment of goals and inspiration through diverse perspectives. Despite their ability to inspire through independent suggestions, state-of-the-art creative AI systems do not leverage these advantages of group work due to missing or one-sided explanations. For other use cases, AI systems that explain their reasoning are already gathering wide research interest. However, there is a knowledge gap on the effects of explanations on creativity. Furthermore, it is unknown whether a user can benefit from also explaining their contributions to an AI system. This thesis investigates whether reciprocal explanations, a novel technique which combines explanations from and to an AI system, improve the designers’ and AI’s joint exploration of ideas. I integrated reciprocal explanations into an AI aided tool for mood board design, a common method for ideation. In our implementation, the AI system uses text to explain which features of its suggestions match or complement the current mood board. Occasionally, it asks for user explanations providing several options for answers that it reacts to by aligning its strategy. A study was conducted with 16 professional designers who used the tool to create mood boards followed by presentations and semi-structured interviews. The study emphasized a need for explanations that make the principles of the system transparent and showed that alignment of goals motivated participants to provide explanations to the system. Also, enabling users to explain their contributions to the AI system facilitated reflection on their own reasons. / Framsteg inom kreativ artificiell intelligens (AI) har lett till system som aktivt kan samarbeta med designers under idéutformningsprocessen, dvs vid skapande, utveckling och kommunikation av idéer. I grupparbete är det viktigt att kunna göra förslag och förklara resonemanget bakom dem, samt förstå de andra gruppmedlemmarnas resonemang. Detta ökar reflektionsförmågan och förtroende hos medlemmarna, samt underlättar sammanjämkning av mål och ger inspiration genom att höra olika perspektiv. Trots att system, baserade på kreativ artificiell intelligens, har förmågan att inspirera genom sina oberoende förslag, utnyttjar de allra senaste kreativa AI-systemen inte dessa fördelar för att facilitera grupparbete. Detta är på grund av AI-systemens bristfälliga förmåga att resonera över sina förslag. Resonemangen är ofta ensidiga, eller saknas totalt. AI-system som kan förklara sina resonemang är redan ett stort forskningsintresse inom många användningsområden. Dock finns det brist på kunskap om AI-systemens påverkan på den kreativa processen. Dessutom är det okänt om en användare verkligen kan dra nytta av möjligheten att kunna förklara sina designbeslut till ett AI-system. Denna avhandling undersöker om ömsesidiga förklaringar, en ny teknik som kombinerar förklaringar från och till ett AI system, kan förbättra designerns och AI:s samarbete under utforskningen av idéer. Jag integrerade ömsesidiga förklaringar i ett AI-hjälpmedel som underlättar skapandet av stämningsplank (eng. mood board), som är en vanlig metod för konceptutveckling. I vår implementering använder AI-systemet textbeskrivningar för att förklara vilka delar av dess förslag som matchar eller kompletterar det nuvarande stämningsplanket. Ibland ber den användaren ge förklaringar, så den kan anpassa sin förslagsstrategi efter användarens önskemål. Vi genomförde en studie med 16 professionella designers som använde verktyget för att skapa stämningsplank. Feedback samlades genom presentationer och semistrukturerade intervjuer. Studien betonade behovet av förklaringar och resonemang som gör principerna bakom AI-systemet transparenta för användaren. Höjd sammanjämkning mellan användarens och systemets mål motiverade deltagarna att ge förklaringar till systemet. Genom att göra det möjligt för användare att förklara sina designbeslut för AI-systemet, förbättrades också användarens reflektionsförmåga över sina val.