Research Through Design (RTD) needs to reconsider the meaning of “designing” in the research process of “through design.” We propose Research Through Co-design (RTC) as a new application of Control System Theory (CST) that includes a research problem assigned to a co-design process in RTD. It embeds the participatory paradigm through collaborative design practice and makes the research a collaborative process for learning from all the participants. To sustain the RTC theory, we present a cognitive model of RTC. It is a “model for” – rather than a “model of” – describing how the co-design, as a neural network process, works through its nodes’ collaboration to find co-designed solutions and the research answer. Diversity increases as non-experts and non-designers with different backgrounds participate. This is valuable for the RTC learning system. The discussions highlight the possibility of considering (i) the RTC model as useful for describing a robust RTD process through CST; (ii) RTC as a cognitive model for explaining the value of co-design in research processes; and (iii) RTC as a strategy for applying the participative paradigm in formal research. Finally, new insights and implications are highlighted, including using RTC as a predictive tool through artificial intelligence.

Research through co-design / Busciantella-Ricci, Daniele; Scataglini, Sofia. - In: DESIGN SCIENCE. - ISSN 2053-4701. - ELETTRONICO. - 10:(2024), pp. 1-43. [10.1017/dsj.2023.35]

Research through co-design

Busciantella-Ricci, Daniele
;
2024

Abstract

Research Through Design (RTD) needs to reconsider the meaning of “designing” in the research process of “through design.” We propose Research Through Co-design (RTC) as a new application of Control System Theory (CST) that includes a research problem assigned to a co-design process in RTD. It embeds the participatory paradigm through collaborative design practice and makes the research a collaborative process for learning from all the participants. To sustain the RTC theory, we present a cognitive model of RTC. It is a “model for” – rather than a “model of” – describing how the co-design, as a neural network process, works through its nodes’ collaboration to find co-designed solutions and the research answer. Diversity increases as non-experts and non-designers with different backgrounds participate. This is valuable for the RTC learning system. The discussions highlight the possibility of considering (i) the RTC model as useful for describing a robust RTD process through CST; (ii) RTC as a cognitive model for explaining the value of co-design in research processes; and (iii) RTC as a strategy for applying the participative paradigm in formal research. Finally, new insights and implications are highlighted, including using RTC as a predictive tool through artificial intelligence.
2024
10
1
43
Busciantella-Ricci, Daniele; Scataglini, Sofia
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1348351
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