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Research through co-design

Published online by Cambridge University Press:  15 January 2024

Daniele Busciantella-Ricci*
Affiliation:
Innovation in Design & Engineering (IDEE) Laboratory, Department of Architecture (DIDA), University of Florence, Florence, Italy
Sofia Scataglini*
Affiliation:
Department of Product Development, Faculty of Design Sciences, University of Antwerp, Antwerp, Belgium
*
Corresponding authors D. Busciantella-Ricci [email protected] S. Scataglini [email protected]
Corresponding authors D. Busciantella-Ricci [email protected] S. Scataglini [email protected]
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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.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press

1. Introduction

This study tackles issues that come both from the Research Through Design (RTD) and co-design realms. Specifically, our interest is in understanding how it is possible to consider co-design within the knowledge related to RTD. This is because RTD is a contemporary challenge for design research. However, in this realm, co-design is poorly discussed and addressed as a crucial variable that may interfere with the multiple aspects of an RTD process. Because design is at the core of the RTD ontology, the typology of design practice may assume relevance in determining the validity of the RTD process. This is the reason why we underline that “co-design” needs specific attention as a peculiar design process that determines not only a variant of RTD but a perspective that needs a new reflection. Co-design is generally interpreted as designerly collaborations and as a practice to involve people, but it is still not considered a formal research practice, with a formal general model that produces new academic knowledge. We aim to advance this aspect by matching co-design with RTD, through the Control System Theory (CST).

Finally, this article also addresses the role of non-designers in co-design practices embedded in research processes. In this context, non-designers represent a variable that is impossible to tackle with predictable aspects. Non-designers, even if recognised as important for de-structuring and opening the creative design process, may also represent a risk for reaching the design (or research) objectives with innovative results. On the contrary, we provide theoretical reflections that potentially demonstrate how diversity in co-design embedded in RTD processes, is a resource to obtain a relevant research answer. To address these aspects, after the literature review, we propose a focus on Research Through Co-Design (RTC) as a concept that may clarify how to match the aforementioned issues. Indeed, based on RTD, CST and co-design, this article discusses RTC as a research strategy. Prior studies (Busciantella-Ricci & Scataglini Reference Busciantella-Ricci and Scataglini2020c) examined the possibility of conceptualising the RTC theory by outlining its underpinnings. On the one hand, there is a lack of clarity on the practical application models in RTD literature. On the other hand, the co-design peculiarities are rarely studied as variables that may change the concept of designing within RTD. In design thinking or research procedures that employ design as a strategy, co-design is becoming increasingly important. Therefore, a description of this position inside RTD, what adjustments have been made, and how they have affected RTD would be beneficial. Consequently, we suggest RTC that aligns with (i) the requirements of the RTD approach, (ii) the co-design as a participation strategy and (iii) a rigorous model to merge these aspects in a unique framework. This study includes an introduction of the main literature on RTD, co-design and RTC, as well as improvements in the RTC model and their implications for design research processes. Finally, this article considers the possibility of developing an RTC model that allows practitioners and researchers to design, develop, predict and compute the variables of a research process that must use co-design as the primary strategy for participation, co-creation and democracy in innovation.

1.1. RTD: an introduction

RTD is one of the types (Glanville Reference Glanville2005) or categories (Frayling Reference Frayling1993) of design research. As Glanville (Reference Glanville2005) suggests, RTD is “research that recognises its source in design, and which uses the insights and understandings of design in its pursuit.” Firstly, Frayling (Reference Frayling1993) introduces the differences between research about, for and through design. Archer (Reference Archer1995) proposes notions such as research about practice, research for the purposes of practitioner activity or research through practitioner activity by also indirectly underling a difference between a professional and a researcher. According to Archer’s perspective, the “research through practitioner” activity, where the medium of that practice is relevant for the systematic inquiry whose goal is “communicable knowledge,” can be compared with action research. Specifically, through Archer’s thinking, this kind of research mediated through the practitioner activity “can count as research if, and only if, it accords with the criteria of research. It must be knowledge-directed, systematically conducted, and unambiguously expressed. Its data and methods must be transparent and its knowledge outcome transmissible. But like all Action Research, research through practitioner action must be recognised as very probably non-objective and almost certainly situation-specific” (Archer Reference Archer1995). Often, the possibility of generalising RTD experiences, as well as providing rigour and academic credibility, has been the focus of the design research studies. In the last decades, several authors have widely amplified the RTD discourse (e.g. Frayling Reference Frayling1993; Glanville Reference Glanville2005; Findeli et al. Reference Findeli, Brouillet, Martin, Moineau and Tarrago2008; Chow Reference Chow2010; Jonas Reference Jonas2015) also taking into consideration the importance of combining research “about” and “for” design in RTD to make it relevant and rigorous (Findeli et al. Reference Findeli, Brouillet, Martin, Moineau and Tarrago2008; Jonas Reference Jonas2014, Reference Jonas2015). Indeed, by contrasting Frayling’s (Reference Frayling1993) framework, Findeli et al. (Reference Findeli, Brouillet, Martin, Moineau and Tarrago2008) highlight that RTD “could be defined as a kind of research about design [more] relevant for design, or as a kind of research for design that produces original knowledge with as rigorous [and demanding] standards as research about design.” This position leads Findeli to call this approach “project-grounded research” which is more significant for contributing to creating design knowledge, improving design practice and framing consequences for design education. On a similar pathway, Jonas (Reference Jonas2014) refers to RTD as research “in the medium of design, guided by the design process, aiming at transferable knowledge and innovation according to various internally determined criteria.” Effectively, RTD uses the design thinking process as the main medium to gain knowledge that is both related and relevant for the design knowledge and for the knowledge of those fields that benefit from the design within the RTD process. We mainly create this vision by interpreting the Jonas perspective of RTD (Jonas Reference Jonas2007, Reference Jonas2014, Reference Jonas2015). Also, in this discourse, Zimmerman, Stolterman & Forlizzi (Reference Zimmerman, Stolterman and Forlizzi2010) describe RTD as “the process of iteratively designing artifacts as a creative way of investigating what a potential future might be (…)” an approach that “allows designers to do what they do naturally (to design), and to create a stepping-stone to theory generation.”

In addition, during the last decade, the Research Through Design Biennial Conference fuelled the debate starting from its foundation in 2013 and as a dissemination platform (Durrant et al. Reference Durrant, Vines, Wallace and Yee2017). According to Durrant et al. (Reference Durrant, Vines, Wallace and Yee2015), this experience allows us to reflect on the knowledge production about design research that can be also generated by the interaction between people and artefacts as part of the conference experience. This aspect emphasises the relevance, for some authors, of the artefacts in producing knowledge through RTD, while Jonas (Reference Jonas2015) underlines the importance of considering the design process as a unique epistemological medium for gaining knowledge.

From a wide perspective, when design assumes a central role in the research objectives, that process can be defined as RTD. For instance, Sevaldson (Reference Sevaldson2010) synthesises RTD can be defined as any research where “the design practice is central in generating knowledge.” This suggests considering and understanding what we mean by the central role of the design practice. Usually, it is intended as the central role of the practice made by practitioners in design that, if supported by relevant and robust reflections, can produce research material (Archer Reference Archer1995; Cross Reference Cross1999; Swann Reference Swann2002). This may also open interpretations of the term “through” to understand the RTD practice (as proposed by Redström Reference Redström2021) or underline the inseparability of design components (i.e. process, designers/researchers, objects) (Isley & Rider Reference Isley, Rider, Storni, Leahy, McMahon, Bohemia and Lloyd2018). Similarly, Dixon (Reference Dixon2019, Reference Dixon2020) connects RTD with Dewey’s pragmatist framework which also helps to frame the relevance of the (design) practice for design research.

In general terms, according to Godin & Zahedi (Reference Godin, Zahedi, Lim, Niedderer, Redström, Stolterman and Valtonen2014), RTD “is very similar, in appearance, to a regular design project,” it is not predictable, and knowledge and understanding are the main goals rather than the artefacts. However, Herriott (Reference Herriott2019) underlines that, despite RTD seems to embed the idea of a “designerly way of knowing” (Cross Reference Cross1982, Reference Cross2001), it is not demonstrable the designer’s unique to gain knowledge and the fact that knowledge resides in process and artefact (Herriott Reference Herriott2023). These aspects may also influence ways future designers, design researchers, designers-researchers or simply researchers can decide to address or not the RTD approach, as well as the way we rethink design education (e.g. Galdon & Hall Reference Galdon and Hall2022).

In the meantime, despite the multiple variants, RTD is also explored in several disciplines and fields related to design (e.g. Lenzholzer, Duchhart & Koh Reference Lenzholzer, Duchhart and Koh2013; Maher et al. Reference Maher, Maher, Mann and McAlpine2018; Groeneveld et al. Reference Groeneveld, Melles, Vehmeijer, Mathijssen, Dekkers and Goossens2019; Shroyer & Turns Reference Shroyer and Turns2021; Bofylatos Reference Bofylatos2022; Cortesão & Lenzholzer Reference Cortesão and Lenzholzer2022) with multiple interpretations also (e.g. Suberi Reference Suberi2022) by evidencing an interest in finding formal models and frameworks for its application. RTD essentially produces knowledge for a discipline (not necessarily related to design) through the application of design knowledge of the contemporary design culture (Jonas Reference Jonas2015). By “design culture” we mean the cultural background that designers (or non-designers) should elaborate on and use for designing (Julier Reference Julier2006, Reference Julier2013; Manzini Reference Manzini2015, Reference Manzini2016). The debate on the nature of RTD spills over into various aspects that depend on how design culture is formed and interpreted. The RTD variety is also understandable by reading the multiple instruments and models that are possible to find in RTD literature, embodying the diverse perspectives on this concept.

1.1.1. RTD instruments and models

In the following paragraphs, we also focus on the numerous perspectives and theoretical instruments the research in RTD has produced over the last decades. For instance, among the different perspectives in interpreting RTD and similar terminologies, it is worth mentioning the work offered by Chow (Reference Chow2010) that compares three research models based on the belief that “designing is a way of knowing and this way of knowing ought to be used in and for research.” They are the Project-Grounded Research (PGR) (Findeli et al. Reference Findeli, Brouillet, Martin, Moineau and Tarrago2008), the Practice-Led Research (PLR) (Rust, Mottram & Till Reference Rust, Mottram and Till2007) and RTD based on Glanville (Reference Glanville1999) and Jonas (Reference Jonas2007) perspective. Chow (Reference Chow2010) concludes that RTD “is the most theoretically elaborate and most ambitious proposal among the three research models.” However, several perspectives emerge to enrich the debate to develop RTD between research and design. Indeed, Stappers (Reference Stappers and Michel2007) underlines that, rather than giving academic credibility with research to designers, we should take advantage of some design skills they have that are valuable ingredients for research, including skills such as (i) creating prototypes, (ii) fostering design research through studios and (iii) giving results through publications. Gaver (Reference Gaver2012) suggests considering discursivity and elaboration rather than only standardisation and convergence as models for RTD development. Jonas (Reference Jonas2015) writes that “RTD has the potential to act as the epistemological paradigm for transdisciplinary studies and transformation design” and in discussing RTD visualised the idea of this model of inquiry. It means that “RTD cannot exist as an isolated concept, but that it has to integrate the other modes of inquiry. Scientific input (about, for) is indispensable, but the nature of the design phenomena does not allow the reduction of design research to (applied) scientific research. On the contrary: scientific research has to be embedded in designerly models of inquiry. There are the all-embracing subject matters of aesthetics/products – logic/process – ethics/people, and the essential distinguishing purposes of understanding design-relevant phenomena, of improving the design process, and of improving the human condition. These purposes can be related to the epistemological attitudes of research about design, for design, and through design” (Jonas Reference Jonas2015). Markussen (Reference Markussen and Vaughan2017) also proposes three forms of theory construction in RTD; that is (i) “extending theories” where the design process expands kernel theories; (ii) “scaffolding theories” where theory is constructed out of separated theories and (iii) “blending theories” where the design work fuses more concepts to produce a new understanding.

The richness of the perspectives also comes from different backgrounds. For instance, Stappers & Giaccardi (Reference Stappers, Giaccardi, Soegaard and Friis-Dam2017) identify a map of RTD projects and articles that underline four “pockets of energy” from different fields and geographical collocations. The map underlines those contributions coming from the art and design community (UK and Scandinavia), technical universities and design academies (Netherlands) and the human–computer interaction community (US). In addition, Stappers & Giaccardi (Reference Stappers, Giaccardi, Soegaard and Friis-Dam2017) collected eleven examples of how different authors label RTD and research in design. Indeed, other similar meanings have been introduced such as “practice-based research” (PBR) (Candy Reference Candy2006; Biggs & Büchler Reference Biggs and Büchler2007; Mäkelä & Routarinne Reference Mäkelä and Routarinne2007), “constructive design research” (Koskinen et al. Reference Koskinen, Zimmerman, Binder, Redström and Wensveen2011), “programmatic design research” (Löwgren, Svarrer Larsen & Hobye Reference Löwgren, Svarrer Larsen and Hobye2013; Bang & Eriksen Reference Bang and Eriksen2014), “empirical research through design” (Keyson & Bruns Reference Keyson and Bruns2009) just to name a few relevant for this article. Often differences are related to the role assumed by the artefact or the design process. For instance, according to Menichinelli (Reference Menichinelli2020), the difference between RTD and PBR is that the first has the goal of exploring a phenomenon with an artefact as a side effect, while the second has the artefact as the goal and insight as a spin-off.

Over the years, design researchers also stressed that RTD has to find ways of approaching research qualities such as “reliability, repeatability, and validity through ways that are trustworthy while true to the approach” (Zimmerman et al. Reference Zimmerman, Stolterman and Forlizzi2010). In this direction, Prochner & Godin (Reference Prochner and Godin2022) propose a framework for quality indicators of RTD projects made by categories (i.e. Traceability, Interconnectivity, Applicability, Impartiality, Reasonableness) and specific indicators (i.e. Replicability, Recoverability and Transparency, Internal validity, Credibility, Contextualisation, External validity, Transferability, Impact, Objectivity, Confirmability, Contextualisation in theory and research, Reliability, Dependability, Soundness of research methods and research norms).

In terms of process, Zimmerman & Forlizzi (Reference Zimmerman and Forlizzi2008) underline that RTD is an approach that “employs methods and processes from design practice” and “design researchers follow a typical design process” that can be described in six phases, that is Define, Discover, Synthesize, Generate, Refine, Reflect. In this perspective, the artefact serves as a “specific instantiation of a model – a theory – linking the current state to the proposed, preferred state” (Zimmerman & Forlizzi Reference Zimmerman and Forlizzi2008). In terms of dynamics, Basballe & Halskov (Reference Basballe and Halskov2012) underline that RTD has three types: (i) “Coupling” that establishes frameworks and constraints by uniting design and research interests; (ii) “Interweaving” in which “one activity or material informs both design and research interests” and (iii) “Decoupling” that “modifies the focus, by turning either design or research interests into the salient focus of the process.”

In terms of models that may inspire the embedding of co-design in RTD, Stapleton (Reference Stapleton2005) presents the RADDAR methodology to understand how the research and theory area can create reflection and differences (and vice versa) with the design and practice area. The RADDAR methodology creates a dialectic among the two areas. This dialectic is the core of the discussion in RTD and, even if Stapleton (Reference Stapleton2005) focussed on game design practices, this methodology may inspire reflections by also thinking about all those design activities that recall the concept of “practice” for finding research answers. Also, one of the most quoted in design literature is the contribution offered by Zimmerman, Forlizzi & Evenson (Reference Zimmerman, Forlizzi and Evenson2007) that essentially proposes an RTD model for Interaction Design Researchers (IDR). Through this model, it is visualised that the IDRs may integrate knowledge from several fields such as engineering, anthropology and behavioural science to concretely frame problems through a process of ideating, iterating and critiquing potential solutions, until obtaining the preferred state, and a series of artefacts, and also models, prototypes, products and documentation of the design process. In this model, it is still possible to feel a conceptual divide between those who intervene in HCI as researchers, and those as practitioners. Instead, in many other contributions this diversity is even discussed with overlapping systems that justify the nature of RTD.

In parallel, Jonas (Reference Jonas2007) introduces a generic hypercyclic design process model that can represent a basic design process for RTD and it can be operationalised linearly (Chow & Jonas Reference Chow, Jonas, Durling, Rust, Chen, Ashton and Friedman2008). The hypercycle model of the design process contributes to sustaining the designerly production of knowledge by providing a cybernetic foundation for design, which also “serves as a framework for design and design research practice” (Jonas Reference Jonas2007). Jonas’s (Reference Jonas2014, Reference Jonas2015) discourse underlines RTD as a cybernetic mode of inquiry (Jonas Reference Jonas2014). We follow this part of the RTD discourse as a foundation for this article. Indeed, Jonas (Reference Jonas2015), by referring to Archer (Reference Archer1995), Owen’s model (Owen Reference Owen1998) and Findeli’s (Findeli et al. Reference Findeli, Brouillet, Martin, Moineau and Tarrago2008) perspective, insists that RTD is “an embodied/situated/intentional observer inside a design/inquiring system, generating knowledge and change through active participation in the design/inquiring process” where design is seen as a “projective process, human-centered process, innovation process, emancipatory process, political/social process” (Jonas Reference Jonas2015).

Indeed, Jonas takes distances from “Frayling’s understanding of the artifacts,” follows Findeli & Bousbaci’s (Reference Findeli and Bousbaci2005) perspective and affirms that “RTD is not primarily about conceiving artifacts/products as carriers or representation of knowledge, but about conceiving the design process as a unique epistemological and methodological medium/device for knowledge generation, different from other disciplines’ instruments” (Jonas Reference Jonas2015). This is a fundamental perspective for this article. It lets us think about differences in designing processes for using design as an epistemological process and how they impact RTD. Therefore, there should be a substantial difference between considering design and co-design in the RTD process. This is also why we suggest considering co-design as different in RTD through this article.

Jonas’ (Reference Jonas2015) visualisation of RTD is one of the most structured among the models offered in the literature. We adopted this model as our starting point for reflecting on how to provide an application model that embeds the ontological and epistemological factors we have discussed so far. This article mainly follows the position offered by Jonas’s discussion on RTD and design as research. In these instances, we found the foundations for the openness of similar issues in introducing co-design within the ontological and epistemological issues of RTD.

To continue the overview, Faste & Faste (Reference Faste and Faste2012) underline that all research is a subset of design practice at large and propose a 2 × 2 matrix for describing known categories of design research. In this framework, RTD is described as “embedded design research” which is “design activity that operates as research” and “the knowledge generated is contained in the cognitive processes and artifacts of the design activity performed” (Faste & Faste Reference Faste and Faste2012). Bang & Eriksen (Reference Bang and Eriksen2014) propose a diagram that interprets how different experiments in RTD interplay with research questions about the research program framed within and with the answer as a response to the overall challenges or matters of concern. Stappers & Giaccardi (Reference Stappers, Giaccardi, Soegaard and Friis-Dam2017) visualise the designerly ways of contributing to research and the designerly ways of doing research. It helps to understand how the design activities play a formative role in the generation of knowledge. Rodríguez Ramírez (Reference Rodríguez Ramírez2017) suggests a criteria-based design research model targeted to conduct practice-based research such as RTD. The stages of the model are (i) situating the research within the body of knowledge of the discipline (e.g. literature reviewing); (ii) free experimenting around the topic of research through making (e.g. sketching, rapid prototyping); (iii) designing to address and fulfil the developed criteria (it renders the designing a systematic enquiry) and (iv) assessing the final designs through the criteria by also describing the design and its explicit contribution to knowledge.

Also, Herriott (Reference Herriott2019) describes a simplified RTD process with the main steps of (i) defining the state of the art and the research question, (ii) creating the object, (iii) analysing qualitative and quantitative data produced by the object and (iv) formulating a new theory or modification of the theory. However, Herriott (Reference Herriott2019) claims RTD is analogous to experimental research/science and “unless tacit knowledge is elevated to the same level as explicit or communicable knowledge, the idea that there is a designerly way of knowing is either an unsupported or a weak claim” (Herriott Reference Herriott2019).

In parallel, Krogh & Koskinen (Reference Krogh and Koskinen2020) explore “ways of drifting” in “constructive design research” and discuss the Knowledge-Relevance (K-R) Model. It is a model that presents the design experiments at the core and it “enables researchers to continuously map and re-map their research activities as a conversation between hypothesis construction, experimentation and evaluation, assessed in relation to both knowledge theory and impact, in the ambition of being relevant and producing knowledge” (Krogh & Koskinen Reference Krogh and Koskinen2020).

Finally, it is not new that discourses around RTD and practice-based research activities refer to concepts such as the “reflection-in-action” (Schön Reference Schön1983), the action research model (Archer Reference Archer1995; Swann Reference Swann2002) and the related comparisons with RTD (Stewart Reference Stewart, Coghlan and Brydon-Miller2014). We do not introduce a general action research model here because we will introduce the “participatory action research” (PAR) model by discussing RTC in the next paragraphs.

As described so far, the literature offers several general and not homogeneous perspectives and models of RTD that do not necessarily describe the same theoretical, conceptual and practical aspects for discussing and applying RTD. This is partially what Boon et al. (Reference Boon, Baha, Singh, Wegener, Rozendaal and Stappers2020) describe as “diversity” in RTD.

1.1.2. Considerations for the purpose of RTC

In search of a reference model for building an RTC foundation, literature seems to provide the basis for the conceptual framework. At the same time, the literature does not provide a homogeneous perspective for RTD, as well as a unique model to easily make RTD applicable in several design research activities through principles, methods, processes and tools to be systematically applied. Several authors propose their own model and perspective in addressing RTD both from a theoretical and practical point of view, and the number of coined terms around the meanings of RTD makes evidence of this aspect. On the one hand, the need to discuss the validity and rigour of this kind of design research created the need for searching theoretical foundations and philosophical aspects to base on the practice and the development of RTD. On the other hand, it is possible to observe distinct approaches to RTD, that is (i) considering the tangible “object” as the medium for understanding new knowledge, and (ii) using the values, the attitudes and the design processes, as the epistemological medium for gaining knowledge outside the very concept of “artefact.” In any case, there is no consensus on (i) how to relate research questions with the design questions in an RTD process, (ii) how to design stages for applying RTD and (iii) how to consider the multiverse and wide possibilities offered by design in terms of approaches, methods and tools, including those related to co-design. The perspective that design methods are RTD methods is promising but not convincing, especially if, with those instruments, we pretend to gain knowledge about complex problems or global issues, through participative design processes, and with non-designers. At the same time, it is not clear from the literature why and how co-designing rather than designing should or should not be considered the same in an RTD process. All these aspects represent gaps or unclear topics we try to discuss by introducing co-design as one of the most challenging aspects of RTD. Our purpose is not to standard RTD through co-design but to enrich the debate by focussing on co-design as a useful explorative and speculative resource for diversifying the attitudes in the contemporary design culture.

1.2. Co-design: an overview

The reason why we focus on co-design as the main determinant of the RTC system is the shift we are observing from “designing” to systematic “co-designing.” This can be more understandable not only for ethical and philosophical reasons but also for practical reasons. As Manzini (Reference Manzini2014) wrote, in the world of networks “all design is co-design.” Nowadays, we cannot escape from interacting in a (co-)design process. “Being influenced by different actors, every design process is, de-facto, a co-design activity” (Manzini Reference Manzini2014). Indeed, co-design is based on several kinds of conversations which themselves are analogous processes of designing (Pangaro Reference Pangaro and Luppicini2008 in Jachna Reference Jachna, Fischer and Herr2019); therefore, once again, “there is thus no designing that is not co-designing” (Jachna Reference Jachna, Fischer and Herr2019). However, the “co” opens interesting perspectives about designing. Even if collaboration, cooperation, connection and coordination cannot be considered synonymous (Kozar Reference Kozar2010), in terms of collective design all four terms “are possible expressions of co-design practices, distinguished on the basis of how strongly they focus on shared goals and working practices” (Zamenopoulos & Alexiou Reference Zamenopoulos and Alexiou2020). In this article, we talk about co-design only concerning the term collaboration, with consideration to people who work together towards a common interest, project and goal (Zamenopoulos & Alexiou Reference Zamenopoulos and Alexiou2018, Reference Zamenopoulos and Alexiou2020). At the same time, we recognise co-design as a process that follows the principles of participatory design. In this view, based on democratic principles, co-design is manifested only if people actively participate in the whole design process, otherwise if people with contextual knowledge and lived experience “are not actively involved in the design process, but emphasis is put on their views and experiences, the process could be described as user-centred or human-centred design” (Blomkamp Reference Blomkamp2018). Indeed, collaboration and collaborative (design) approaches change how we research, what we research and who researches (Sanders & Stappers Reference Sanders and Stappers2008). From this perspective, we can also understand one of the main issues in co-design that is related to the roles and relationships the different people assume in the participatory process of designing. This also recalls the connection between design and participation where according to Lee (Reference Lee2008) is possible to map three (designers) roles, i.e. (i) “Design Developers” that work with the design community “to transform design processes for participation”; (ii) “Design Facilitators” that design with people “to transfer design knowledge to emancipate people to improve their lives” and (iii) “Design Generators” that collaborate with professionals “to explore design thinking to different implications.”

By assuming participatory design as the main comprehensive term for co-design, we understand that participatory design projects are always grappling with the understanding of how to involve people, with which means and tools, and how to make the design process democratic and inclusive for everybody – including non-designers. This is the reason why there is a continuous methodological evolution in participatory design, also through processes and tools that define a new way of conducting co-design (Robertson & Simonsen Reference Robertson and Simonsen2012). This also takes into consideration that co-design is a disagreement space based on possible language misalignment. It is a process where different people interact by converging (or not) on common results emerging from different perspectives and languages. These results “can be particularly interesting, resilient and rich in cultural qualities” (Manzini Reference Manzini2014). At the same time, co-design is a space for conflict, that, through the values of participatory design we can define as constructive and creative conflict. Despite these complexities, contemporary society is pushing for using creativity and collaborative practices as collective resources for sharing knowledge, activating co-creation processes and provoking systems changes (Jones Reference Jones2018; Eckhardt et al. Reference Eckhardt, Kaletka, Krüger, Maldonado-Mariscal and Schulz2021). Indeed, co-design in systemic design processes is a synonym for “co-creation” for addressing social transformation with system stakeholders (Jones Reference Jones2018). In general terms, co-design is a way to apply collective creativity in the whole span of a design process (Sanders & Stappers Reference Sanders and Stappers2008). It is a “mechanism for empowering people, namely a mechanism for taking control over their own futures by developing their own ideas, knowledge and skills” (Zamenopoulos & Alexiou Reference Zamenopoulos and Alexiou2018). Perhaps, this is the reason why emerging design approaches such as Transition Design (Irwin Reference Irwin2015), Design for social innovation (Manzini Reference Manzini2015) and Design for Policy (Bason Reference Bason2016) mostly recognise design as, basically, a collaborative design process. Literature often addresses the co-design discourse through its role or application within social innovation practices (Manzini Reference Manzini2015), participatory and democratic processes (Ehn Reference Ehn, Schuler and Namioka1993), knowledge co-creation processes (Garcia et al. Reference Garcia, Barberà, Gros, Escofet, Fuertes, Noguera, López, Meritxell Cortada and Marimón2014), as well as for citizen engagement and public policies making (Siodmok Reference Siodmok and Bason2016; Blomkamp Reference Blomkamp2018; Deserti, Rizzo & Smallman Reference Deserti, Rizzo and Smallman2020). Canonically, co-design is a participatory process where people learn from each other (Ehn Reference Ehn, Schuler and Namioka1993). For the purpose and perspective of this article, co-design is recognised as an activity that “produces new knowledge as people develop and experiment with (new) ideas” (Zamenopoulos & Alexiou Reference Zamenopoulos and Alexiou2018). In addition, we also assume that co-designing is not easy, it is a “complex, contradictory, antagonistic process in which different stakeholders, design experts included, participate in different ways, bring their specific skills and their culture” (Manzini Reference Manzini2014). These issues are also why user tests or marginal people’s participation (e.g. only interviews) is often confused or promoted as co-design processes. However, co-design “contributes to democratisation and empowerment because it can facilitate the closing of the gap between people who have the power to shape important aspects of their life, such as health, welfare or built environment, and those who do not” (Zamenopoulos & Alexiou Reference Zamenopoulos and Alexiou2018).

In the co-design discourse, the co-designer role is a matter of discussion. One of the most cited papers about co-design describes a basic co-design process as made by the role of designers, researchers and users (Sanders & Stappers Reference Sanders and Stappers2008); essentially a process among experts in design and people that participate to produce knowledge through the co-design process. However, the role of the expert co-designers recalls the role of designers in the participatory ecosystem and in building collective design intelligence (Manzini Reference Manzini2019); and it is not solved yet. However, labels such as experts and non-experts, trained or not trained in (co-)design (e.g. Manzini Reference Manzini2015, Reference Manzini2019; Meyer & Norman Reference Meyer and Norman2020) are a concern under discussion. It also evolves as design skills are demanded in different societal contexts. For instance, in bottom-up social innovation participatory processes, the role of the expert designer is closer to a non-design-expert who acts as a designer (Manzini & Rizzo Reference Manzini and Rizzo2011). Indeed, demarking boundaries of experience and training, as well as skills in co-design processes is difficult and probably useless (Busciantella-Ricci & Scataglini Reference Busciantella-Ricci and Scataglini2020c) and adds no real value as in the case of “design demarcation” (Whiting Reference Whiting2021). However, for understanding how designers, people or design experts (as we want to call them) roles in co-design, the proposal of the Collaborative Design Framework (Meroni, Selloni & Rossi Reference Meroni, Selloni and Rossi2018) may help. It works as a guide for helping infrastructure collaboration in those the authors defined as “massive” processes (Meroni et al. Reference Meroni, Selloni and Rossi2018). It can be also useful to understand determinant people’s roles in collaboratively designing and the relative skill. The quadrants of the framework are described according to the intersection between the designerly “style of guidance” – facilitation/steering – and the subject matter behind the design – conceptually described by the tension created by a linear design process – with the poles “concept driven/topic driven.” The quadrants help to understand how to co-design, through which roles and how to consider the relationship between designers and non-designers. This also lets us frame some future perspectives on co-design. Indeed, as needs for participation will change for new challenges, roles techniques, methods and tools will change. According to Sanders & Stappers’s (Reference Sanders and Stappers2014) speculation, “the people who are today’s designers and design researchers are the facilitators and shapers of the collective dreams of the people in 2044.” It is a way to say that we will shift from co-designing to taking care of collective creativity through co-design in future.

1.2.1. Challenges and benefits of embedding co-design

Co-design is also a widely used practice in several disciplines engaged with different types of research such as health and clinical research (e.g. Dimopoulos-Bick et al. Reference Dimopoulos-Bick, O’Connor, Montgomery, Szanto, Fisher, Sutherland, Baines, Orcher, Stubbs, Maher, Verma and Palmer2019; Bird et al. Reference Bird, McGillion, Chambers, Dix, Fajardo, Gilmour, Levesque, Lim, Mierdel, Ouellette, Polanski, Reaume, Whitmore and Carter2021; Bolster et al. Reference Bolster, Gessel, Welten, Hermsen, Lugt, Kotte, van Essen and Bloemen2021), education studies (Mäkelä et al. Reference Mäkelä, Helfenstein, Lerkkanen and Poikkeus2018), public management (Trischler, Dietrich & Rundle-Thiele Reference Trischler, Dietrich and Rundle-Thiele2019), public policies research (Blomkamp Reference Blomkamp2018) and social marketing research (Dietrich et al. Reference Dietrich, Rundle-Thiele, Schuster and Connor2016) just to name a few. Every experience with co-design sounds different and is still difficult to find a formal and unique model to apply co-design in formal research. However, we can explore this issue by emphasising a few challenges and benefits of adopting co-design in formal research frameworks. They are both challenges for design research activities and for those scientific disciplines that are adopting co-design.

Firstly, co-design implies collaboration, communication activities, as well as the use of terminologies that often encompass technical or scientific terms. At the same time, a co-design process is an encounter among experts (including designers), non-experts and people with, sometimes very different backgrounds. All of them have a role in co-designing, even if there are key participants with multiple roles (Barcellini, Prost & Cerf Reference Barcellini, Prost and Cerf2015). By observing general frameworks on collaborative research, as transposed in co-design for research, the lack of a common language and shared terms, and the communication issues among the actors of a co-design process can be a set of challenges (Camden et al. Reference Camden, Shikako-Thomas, Nguyen, Graham, Thomas, Sprung, Morris and Russell2015; Drahota et al. Reference Drahota, Meza, Brikho, Naaf, Estabillo, Gomez, Vejnoska, Dufek, Stahmer and Aarons2016; Moser Reference Moser2016; Slattery, Saeri & Bragge Reference Slattery, Saeri and Bragge2020). This is also discussed in design research studies where different languages and vocabulary create a barrier (Pirinen Reference Pirinen2016), and where the terminology for defining who the user, the participant, the co-creator, the expert or non-expert of a co-design process is fuzzy (Antonini Reference Antonini2021). Therefore, terminology is a challenge in co-design from two perspectives. The first is about the terms and knowledge to be managed within the co-design process for addressing a research objective as we discussed so far. And we argue this can be a common topic with general interdisciplinarity and transdisciplinary research challenges and/or barriers (Domino, Smith & Johnson Reference Domino, Smith and Johnson2007; Axelsson Reference Axelsson2010; Arnold Reference Arnold and Carayannis2020; Daniel et al. Reference Daniel, McConnell, Schuchardt and Peffer2022). The second is about the terminology for defining the co-design. On this second aspect converge discussions such as defining a common framework for terms such as co-creation, co-production and co-designing (Vargas et al. Reference Vargas, Whelan, Brimblecombe and Allender2022) where the first is generally adopted as the broader term to contain the co-design activities and values (Sanders & Stappers Reference Sanders and Stappers2008; Jones Reference Jones2018; Vargas et al. Reference Vargas, Whelan, Brimblecombe and Allender2022). However, they can be defined as co-approaches for which it is necessary to understand how they produce improved research outcomes (Grindell et al. Reference Grindell, Coates, Croot and O’Cathain2022).

One more aspect to be discussed as a challenge for co-design is engaging and managing participants and their roles (Barcellini et al. Reference Barcellini, Prost and Cerf2015; Pirinen Reference Pirinen2016; Kirk et al. Reference Kirk, Bandholm, Andersen, Husted, Tjørnhøj-Thomsen, Nilsen and Pedersen2021). In general terms, the typologies of participants and their roles also depend on what the design or research project’s focus is. However, this aspect recalls significant discussions about the role of designers. As a few authors point out, it is possible to observe a shift from the problem-solving designer to the designer who facilitates processes (Antonini Reference Antonini2021) in co-design. Similarly, some studies underline challenges in identifying a new role for the researcher within co-design processes by favouring a more empathic relationship with the other participants (Kirk et al. Reference Kirk, Bandholm, Andersen, Husted, Tjørnhøj-Thomsen, Nilsen and Pedersen2021). In a similar vein, there is the reflection that among the researchers and the other participants, tensions in decision-making can occur in the design process (Slattery et al. Reference Slattery, Saeri and Bragge2020).

Some challenges also emerge from the relationship among the participants in terms of hierarchies (e.g. different working roles in the same table) (Moser Reference Moser2016) that also are barriers in terms of distribution of powers in a context where a common ground for co-design is needed (Pirinen Reference Pirinen2016; Antonini Reference Antonini2021).

Co-design is also envisioned as a strategy for addressing research waste caused by a mismatch between research objectives and real benefits for people, such as patients in health research (Slattery et al. Reference Slattery, Saeri and Bragge2020). Indeed, it is recognised that the application of co-design can create benefits (Steen, Manschot & De Koning Reference Steen, Manschot and De Koning2011; Steen Reference Steen2013) such as (i) improving the processes of idea generation for designing a specific design output; (ii) improving the decision-making process and (iii) promoting cooperative activities and creativity, to improve the users’ satisfaction and loyalty over the long term. Over the design or specific design output such as products and services, for instance, in co-designing research, the stakeholder’s engagement creates benefits such as favouring the identification of the relevant research materials (e.g. research questions) and the credibility of the knowledge produced, as well as the outcome resulted easier and more acceptable for the application in a context (Camden et al. Reference Camden, Shikako-Thomas, Nguyen, Graham, Thomas, Sprung, Morris and Russell2015; Slattery et al. Reference Slattery, Saeri and Bragge2020).

Engaging stakeholders, users and contextual participants in co-design, which in most cases are non-designers, produces benefits both for the research team and for the participants (Moser Reference Moser2016). The latter generally experience positive emotions and a sense of increased skills and knowledge (Slattery et al. Reference Slattery, Saeri and Bragge2020) that also simplify the engagement of the involved people (Pirinen Reference Pirinen2016). For the research team, involving non-experts (including non-designers) creates benefits such as (i) increasing the possibility of finding novel ideas and increasing creativity (Moser Reference Moser2016; Pirinen Reference Pirinen2016; Blomkamp Reference Blomkamp2018; Antonini Reference Antonini2021), (ii) creating a better connection between the contextual user needs and the research outputs (Camden et al. Reference Camden, Shikako-Thomas, Nguyen, Graham, Thomas, Sprung, Morris and Russell2015; Moser Reference Moser2016; Pirinen Reference Pirinen2016; Blomkamp Reference Blomkamp2018; Slattery et al. Reference Slattery, Saeri and Bragge2020) and (iii) establishing commitment for the consequential cooperation in organisations or communities (Pirinen Reference Pirinen2016). Consequently, a challenge for embedding co-design in formal research frameworks is ensuring benefits with a singular formal model. However, as Slattery et al. (Reference Slattery, Saeri and Bragge2020) point out “the lack of a singular consistent conceptualisation of ‘co-design’ made it much more difficult to retrieve and understand the relevant literature.” This makes the identification of a singular model to apply co-design in research a challenge.

In addition, co-design processes are preferred to give value to the stakeholder’s voices and preferences. Therefore, as a critical point of co-design applications, some studies underline that in co-design there may occur a scientific rigour sacrifice for end-user preferences (Slattery et al. Reference Slattery, Saeri and Bragge2020). This is a relevant tension in co-design that underlines the need for finding a balance between multiple aspects concerning scientific rigour and an open, bottom-up design, as well as the urgent actors’ needs and the long-term focus of a specific research project (Moser Reference Moser2016).

In addition, the co-design impact can be considered an additional challenge due to a series of reasons such as the lack of data (Slattery et al. Reference Slattery, Saeri and Bragge2020; Wang et al. Reference Wang, Jiang, Huang, Tai and Trapani2022). Indeed, Slattery et al. (Reference Slattery, Saeri and Bragge2020) emphasise the importance of addressing a pressing challenge for co-design, which is creating models and evidence for evaluating the real-world impact of co-design. The impact of what co-design produces in a context, for example for designing services, is a recurrent topic in the Pirinen (Reference Pirinen2016) study on barriers and enablers of co-design for services. In this work, despite it can be considered a transversal topic, the author discusses this aspect by underlying that a lack of impact is determined by barriers such as (i) poor ability to utilise the outcomes, (ii) reliance on the implementation on a few insiders and (iii) systemic barriers to dissemination. On the same issue, Wang et al. (Reference Wang, Jiang, Huang, Tai and Trapani2022) identify a five-step evaluation framework for co-design, that is (i) considering evaluation from the beginning of the co-design process; (ii) co-defining key performance indicators and the evaluation criteria; (iii) selecting methods and techniques for the assessment; (iv) critically interpreting the results and (v) gaining additional feedback and increasing the validity. While, Ostrowski, Breazeal & Park (Reference Ostrowski, Breazeal and Park2021) use Zimmerman et al.’s (Reference Zimmerman, Forlizzi and Evenson2007) four lenses for RTD evaluation (i.e. “process,” “invention,” “relevance” and “extensibility”) to evaluate co-design in an RTD process.

For his uncontrollable nature, co-design can increase the application of resources and time (Moser Reference Moser2016; Kirk et al. Reference Kirk, Bandholm, Andersen, Husted, Tjørnhøj-Thomsen, Nilsen and Pedersen2021). This can be seen as a critical point (Slattery et al. Reference Slattery, Saeri and Bragge2020) or as a requirement for adopting co-design. However, this also opens a discussion on an additional challenge. Co-designing requires involving people who may not have a direct interest in the research. Involving them, finding the right strategy of engagement, instigating collaboration and communication with a common language and preserving their interest along the process of the co-design activities is a time- and resource-consuming set of efforts (Moser Reference Moser2016; Slattery et al. Reference Slattery, Saeri and Bragge2020; Kirk et al. Reference Kirk, Bandholm, Andersen, Husted, Tjørnhøj-Thomsen, Nilsen and Pedersen2021). In addition, this kind of collaboration is often regulated by conflicts and heated debates (Manzini Reference Manzini2014; Pirinen Reference Pirinen2016; Andersen & Mosleh Reference Andersen and Mosleh2021) that are challenging aspects for applying co-design that require conflict mitigation skills (Slimani et al. Reference Slimani, Da Silva, Médini and Ghodous2006; Zamenopoulos & Alexiou Reference Zamenopoulos and Alexiou2018).

There is a consensus that co-design potentially produces knowledge collaboratively by mixing different fields of knowledge from the co-designers (including non-experts). However, how this knowledge is formally generated and how co-design is formally relevant for and embedded in the research process are unclear. If RTD is a kind of research that exploits the designerly ways of knowing, and by taking it for granted that this approach is used by designers (design experts), how we consider knowledge produced in the boundless context of co-design is unclear. If that knowledge is also produced by non-designers or non-design-experts, clarification is needed on how we can consider this aspect in RTD. At the same time, as one more issue addressed in this article, we highlight co-design that does not explicitly consider a generalised, formal and robust model that ensures the embedding of participative design practices within formally recognised research.

1.3. RTC: an introduction

From the first structuring of RTC (Busciantella-Ricci & Scataglini Reference Busciantella-Ricci and Scataglini2020a), new publications emerged on the connections between RTD and co-design. Indeed, RTC appears in literature as a way to use co-design projects for introducing the values of co-design, such as participation and dialogue, within a practice-based research experience (Jørgensen, Skovbjerg & Eriksen Reference Jørgensen, Skovbjerg and Eriksen2021). Also, when co-design in an RTD process is used as the main vehicle to conduct research (Aslam, Van Dijk & Dertien Reference Aslam, Van Dijk and Dertien2019), its role as an RTC process is clearer. In parallel, RTC has been used as a methodology to conduct RTC activities with older adults in a doctoral research process engaged with the topic of Eudaemonic Design (Mikus Reference Mikus2023). In this case, RTC is used “as a reflexive form of inquiry to foster participant engagement while collaboratively considering the research questions” (Mikus Reference Mikus2023). Also, Bakırlıoğlu & Doğan (Reference Bakırlıoğlu and Doğan2020) propose a “research through co-designing” process as an adaptation of the steps for “research through designing” which in turn is based on Schön’s (Reference Schön1983) reflexive practice framework to accommodate the co-design processes. Walsh et al. (Reference Walsh, Druin, Guha, Bonsignore, Foss, Yip, Golub, Clegg, Brown, Brewer, Joshi and Brown2012) claim to use RTC as they claim to use a co-design approach in their RTD “because participants were part of a culture that values partnership […]” among different users. It is the case where “design partners do more than just inform the direction for the future, they are active participants in the next design.” However, in some cases (e.g. Taylor Reference Taylor2017; Ostrowski et al. Reference Ostrowski, Breazeal and Park2021), even if the usage of co-design is an integral part of an RTD approach, the process itself is presented as “through design” without any mentioned change concerning the mental model for managing the collaborative process in the RTD process. Similar relationships and challenges emerge from those works (e.g. Kerr et al. Reference Kerr, Whelan, Zelenko, Harper-Hill and Villalba2022) where RTD is used as a research method, and a reflective process for discovering knowledge through a design work, that embeds co-design as an approach to plan the incorporation of the multiple stakeholder groups and the related needed applications.

Recent contributions introduce “participatory research through design” (Wilde Reference Wilde2020, Reference Wilde2022). It is presented as a methodology for embedding participatory values into the RTD process. Even if a specific model is not presented, what is considered highly relevant for this article is the perspective that they offer about the roles of designers in participatory RTD. Every designerly approach to conducting research, if struggling with collaboration and participation, creates tensions in the traditional designer position’s meanings, values and roles. For instance, in participatory RTD “the designer is not the expert” (Wilde Reference Wilde2020). Rather this role collaborates with the other stakeholders and recognises their (non-designers) designerly contribution. Also, Wilde (Reference Wilde2020) underlines that participatory RTD “brings differing perspectives to bear on creative decision-making; and enables researchers to navigate tensions of difference, articulate more precisely and realistically what might be meaningful for stakeholders with divergent values, and identify which benefits to aim for.” Diversity in design research is a core concept. And it lets us recall the direct relationship between RTD – action research, and co-design – Participatory Action Research (PAR). According to Stewart (Reference Stewart, Coghlan and Brydon-Miller2014), “co-design can be seen as a type of Participatory Action Research and often explicitly draws upon an action research methodology. The important contribution of design to collaborative action contexts is its generative mode of inquiry.” In parallel, some explorative approaches are emerging by embedding similar topics such as the “action research through design” (ARtD) methodological approach (Cruz et al. Reference Cruz, Ersoy, Czischke and van Bueren2022). It allowed researchers to develop a framework for co‐design processes to conceptualise and analyse design in collaboration. This framework provides three design circle phases through which people move from “Informative” to “Consultive,” “Participative” or “Collaborative” levels of collaboration.

Both design and action research – as well as PAR – are engaged in changes. In general terms, design and action research are different even if aspects such as the design process and the action research process present similarities and differences (Swann Reference Swann2002; Stewart Reference Stewart, Coghlan and Brydon-Miller2014). Similar to RTC, PAR is “an approach characterised by the active participation of researchers and participants in the coconstruction of knowledge” (McIntyre Reference McIntyre2008). RTC considers co-designers all the members of the RTC process. The PAR process may help the understanding of the RTC fundamentals. Specifically, PAR describes a “recursive process that involves a spiral of adaptable steps that include” (McIntyre Reference McIntyre2008) (i) questioning, (ii) reflecting, (iii) developing and (iv) implementing and refining. PAR is therefore “a research paradigm within the social sciences which emphasises collaborative participation of trained researchers as well as local communities in producing knowledge directly relevant to the stakeholder community” (Pant Reference Pant, Coghlan and Brydon-Miller2014). This knowledge intends to contribute to the theoretical corpus of the social sciences, and it also contains a social change agenda (Pant Reference Pant, Coghlan and Brydon-Miller2014). PAR and RTC present differences such as different purposes, but they present a common connection with the participatory paradigm (Heron & Reason Reference Heron and Reason1997; Lincoln, Lynham & Guba Reference Lincoln, Lynham, Guba, Denzin and Lincoln2018). In terms of process, PAR may inspire RTC even if the goal is different.

Finally, a recurrent term that can be connected with RTC is the “co-production of knowledge.” It is used as a terminology to understand how participatory processes allow communities and target groups to produce new knowledge for a discipline (e.g. Heaton, Day & Britten Reference Heaton, Day and Britten2015; Rycroft-Malone et al. Reference Rycroft-Malone, Burton, Bucknall, Graham, Hutchinson and Stacey2016; Djenontin & Meadow Reference Djenontin and Meadow2018; Redman et al. Reference Redman, Greenhalgh, Adedokun, Staniszewska and Denegri2021; Gerlak et al. Reference Gerlak, Guido, Owen, McGoffin, Louder, Davies, Smith, Zimmer, Murveit, Meadow, Shrestha and Joshi2023). And this may have a connection with the production of knowledge through co-design. For instance, Schwoerer et al. (Reference Schwoerer, Keppeler, Mussagulova and Puello2022) propose the CO‐DESIGN framework with eight elements each representing a salient process or product in public administration research and/or practice. The eight elements are (C) co-production of knowledge; (O) open science; (D) developmental and comparative perspectives; (E) equity and diversity; (S) social innovation; (I) inclusive participation; (G) goal-oriented research; (N) new possibilities (for research).

In general terms, the frameworks emerging from research in the co-production of knowledge can affect the formalisation of a model to use the RTC theory.

1.4. CST for RTC

Why is the CST here reported as a relevant aspect of RTC? And, how is the CST conceptually connected with RTD and co-design? We provide a discourse to address these questions. Firstly, in CST it is essential to define the meaning of the word “control.” This concept stands for two meanings, that is controlling in terms of (i) testing a system, and (ii) preventing a specific behaviour of the system (Neculai Reference Neculai2005). Essentially, controlling is the main activity of this system where there is a subject that assumes the role of the controller (that executing the action of control), and an object (a process, a system or a device) – technically a control plant – which is the object the control is acted upon (Bubnicki Reference Bubnicki2005). If we consider the relationships between the controller and control plant, we can consider around four cases that Bubnicki (Reference Bubnicki2005) describes as (i) open-loop system without the measurement of disturbances; (ii) open-loop system with the measurement of disturbances; (iii) closed-loop system and (iv) mixed (combined) system. Essentially, the difference is determined by the role of system output. In an open loop, it does not affect the control action of the system. In the closed loop, the output depends on the input and the system allows the creation of the desired output through a feedback system. This is the reason why the closed loop is considered a feedback control system. The feedback loop can be positive or negative. In the first case, positive feedback increases the status of a system. In negative feedback, the system tends to be stable, in a sort of system equilibrium (Levine Reference Levine1996; Bubnicki Reference Bubnicki2005; Iglesias & Ingalls Reference Iglesias and Ingalls2009; King Reference King2021).

A lot of biological systems can be explained with the CST (Iglesias & Ingalls Reference Iglesias and Ingalls2009). For instance, fruit ripening is an example of positive feedback, while homeostasis in the human body is a traditional example of negative feedback in a closed system (Michal & Klein Reference Michal and Klein2015). Negative feedback is also discussed in public policy studies (Baumgartner & Jones Reference Baumgartner, Jones, Baumgartner and Jones2002; Bardach Reference Bardach and Goodin2006; Zahariadis Reference Zahariadis2008; Howlett Reference Howlett2009) to understand how the self-correcting mechanisms can reinforce the stability of a system (Baekgaard, Larsen & Mortensen Reference Baekgaard, Larsen and Mortensen2019).

Indeed, CST is widely known in the application of engineering (King Reference King2021), systems biology (Iglesias & Ingalls Reference Iglesias and Ingalls2009) and automation (Levine Reference Levine1996). It is also a mechanism that can embed mathematical theory on how to approach co-design (e.g. Censi Reference Censi2015). However, why connect CST to RTD? Specifically, we previously referred to the second-order cybernetic as one of the most influential RTD models (Jonas Reference Jonas2015) for applying co-design variables to it. At the same time, we know that “Cybernetic or control theory is a general approach to the understanding of self-regulating systems” (Carver & Scheier Reference Carver and Scheier1982) where “the basic unit of cybernetic control is the feedback loop” (Carver & Scheier Reference Carver, Scheier and Ryan2012). Indeed, cybernetics is essentially the control theory as it is applied to complex systems (Britannica 2023). RTD which assumes co-design as the main system to be controlled is a complex system. At the same time, RTD has been discussed in the logic of cybernetics (Glanville Reference Glanville, Glanville and de Zeeuw1997, Reference Glanville2005; Jonas Reference Jonas2007, Reference Jonas2015; Sweeting Reference Sweeting2017). Therefore, If we assume that RTD is a typology of design research, and the latter is a cybernetic process of experiential learning (Jonas Reference Jonas2015), we can use the CST as the basic theory to create a practical model for understanding RTD and the related role of the co-design process on it. This is also in line with research studies that tend to suggest that design research is a variety of second-order cybernetic (Sweeting Reference Sweeting2017). According to this view, RTD determines the whole system based on the negative feedback of the closed loop, and co-design is the open-loop system made by the controller and the control plant. If we assume that the co-design is the open-loop gain, and RTD is the whole system, we may assume that there is a feedback loop that allows us to make the system stable by using co-design. Consequently, we may measure and control the transfer function of the control system. Quantifying and measuring the whole system is an objective of this work for also finding rigorousness and robustness to the system behind the RTC conceptual model.

1.5. Aim

The goal of the research we are presenting in this article is to develop a cognitive model for RTC. Indeed, as co-design practices and requests increase among the design community and society, more knowledge is needed about collaborative design processes. In contemporary society, designing means co-designing. It implicates differences in RTD. Literature provides discussions, comparisons, instruments and examples that very rarely distinguish if knowledge is produced by designers or co-designers in RTD. Generally, RTD considers designers/researchers as the producers of knowledge. It means design experts (Manzini Reference Manzini2015). However, in a typical co-design process professional design experts collaborate with researchers, citizens and several different people non-experts in design. This variety is a resource for the co-design process. However, rarely literature provides a discussion on what happens if they are the “non-design-experts” in strongly affecting the production of (design) knowledge rather than specific roles of the design research area, such as the designers-researchers (Cross Reference Cross2006). Co-design literature provides interesting contributions to learning, and conversational processes aimed at underlying the value of the contribution from “non-design-experts” along the participative design processes. Rarely discussions on how these aspects may modify the essential design research foundations are provided. In other words, we do not know what happens to RTD if the process is entirely operated with collaborative and participative dynamics. Since the design literature debate on the foundational and epistemological issues of RTD started, we know that this kind of design research deals with creating a consistent concept to create its academic standards and reputation, as well as to prove that research answers obtained by designerly procedures are of equal quality respect to answers provided by other disciplines (e.g. Jonas Reference Jonas2015). If we assume that design knowledge resides in people, products and processes (Cross Reference Cross1999, Reference Cross2006), then it is possible to affirm that forms of design research – as a practice for producing design knowledge (Manzini Reference Manzini2009) – such as RTD are influenced by people, products and processes. Indeed, several contributions in design literature on RTD address the “product” of design as an artefact that embeds knowledge for finding research answers. In parallel, the process of making those artefacts is also the subject of the investigation to understand how designers excogitate manners to produce new knowledge with a designerly approach. The literature review presented in the previous paragraphs mainly describes an overview of these aspects and the mentioned contributions mainly consider how “designers” as “design experts” and the related processes can represent a robust body of knowledge for considering RTD as an academic and formal type of research. However, what happens to RTD robustness when design experts with non-experts collaborate in a design process – by creating a co-design process – or better, what happens when non-experts collaborate in a designerly process for finding a research answer – is not clear. At the basis of this article, there is the assumption that a co-design process, where potentially everybody can participate, is different to a traditional design process driven by the dynamics of an expert designer. For instance, the co-design process needs to consider aspects such as dealing with conflicts among the participants; or it constitutes a basic perspective for the co-creation processes in adopting citizen science perspectives (see e.g. Eckhardt et al. Reference Eckhardt, Kaletka, Krüger, Maldonado-Mariscal and Schulz2021). It means that co-design needs to consider variables that make the RTD process more complex to an RTD process where a trained designer tries to find a research answer (mainly by herself or himself). A traditional perspective on RTD assumes the designer is the core person of the RTD process. Its RTC variant assumes groups of multiple people – experts and non-experts, or only non-experts – as the core persons of the whole designerly-research process. This aspect is less debated in design literature that addresses RTD issues. Also, as Boon et al. (Reference Boon, Baha, Singh, Wegener, Rozendaal and Stappers2020) discuss by talking about the participation concept among RTD themes, “while many participatory design projects can be considered as a form of RtD, such work is not often discussed in RtD-related papers.” At the same time, participatory design projects do not discuss how co-design may represent a new frontier of RTD, or it can go beyond, or it could question the dynamics of RTD. Therefore, opening the discussion on these aspects is the overall goal of this article. And introducing a cognitive model for doing RTC is the objective. It is an alternative model for applying RTD in the case of co-design and according to the participative paradigm (Lincoln et al. Reference Lincoln, Lynham, Guba, Denzin and Lincoln2018).

1.6. Significance

We argue providing a robust discussion on co-design at the core of the RTD process is needed. Firstly, it is important to understand more specific aspects of RTC because it enables consideration of the co-design as an integral part of the research process. Consequently, it gives robustness to RTD processes that assume co-design at the core. Co-design is becoming a pervasive process adopted transversely through a lot of diverse research even from different disciplines. Therefore, it is even more important to understand how to integrate a specific instance of co-creation through design within a research process, that is clarifying the role of co-design in RTD processes. Indeed, while RTD has been discussed in design literature, RTD that assumes co-design has been poorly considered as a perspective to be theoretically defined. However, co-design implies several dynamics and processes that make the design process different from a traditional non-collaborative/participative design process. Co-design implies aspects such as empathy with other participants (Smeenk, Sturm & Eggen Reference Smeenk, Sturm and Eggen2019), (constructive) conflicts (Manzini Reference Manzini2014; Zamenopoulos & Alexiou Reference Zamenopoulos and Alexiou2018; Andersen & Mosleh Reference Andersen and Mosleh2021), tools and techniques (Brandt, Binder & Sanders Reference Brandt, Binder and Sanders2012) that substantially differ from a traditional design process mostly regulated by designer-alone processes. Consequently, it is needed to make a distinction between what is defined as RTD and what can be defined as RTC. Also, this article underlines why and how a new model that better describes what can be defined as RTC should be framed and discussed. In fact, from a certain perspective, RTC is RTD that assumes co-design at the core of the process. However, a formal, unique and robust RTD operative process is still difficult to generalise. Therefore, RTC may contribute to both integrating co-design in RTD and at the same time, giving a reference and robust model to RTD thanks to the adoption of the CST. In addition, co-design is largely adopted in several research processes, but it is still considered a collaboration process where design is detached from pure research. This perspective risks distancing co-design from the design research debate that discusses RTD and “design as research” frontiers (Frayling Reference Frayling1993; Jonas Reference Jonas2015). Finally, the RTC model proposed in this article attempts to contribute to robustness by using co-design as the main process for finding a research answer, independently from the research discipline.

All these aspects indicate the need for more work on the subjects presented in this contribution because RTC, in summary, leveraging on (i) augmenting the discussion on co-design in RTD that is poorly considered as a determinant of RTD variables; (ii) clarifying how co-design applied in different research processes can be a consistent part of the research as it happens in RTD and (iii) investigating the possibility of providing a formal, unique and robust model for conducting research through the medium of co-design. Finally, none of the models presented in the literature allow us to measure specific variables, not in RTD, RTC and co-design contributions. Firstly, it is because design processes are almost impossible to compute both in terms of planning and creating a prediction of how it can be conducted. Designing a model to simplify the design, development and computation of specific variables is needed to give robustness and generalisation to all the diverse models and practices that are engaged in both RTD and co-design. Therefore, by introducing the RTC model it will be possible to (i) understand how gaining knowledge in an RTD process by enabling design collaborations of a wide variety of diverse people and resources; (ii) simulate an RTC process by also taking advantage of the opportunity to use the computational features of the model; (iii) measure and validate research processes that adopt co-design; (iv) enhance the possibility to adopt co-design in society by decreasing the efforts for designing and managing participatory processes; (v) improve design research opportunities by giving a theoretical model for future research activities (e.g. through doctoral thesis) and (vi) develop additional computation model (e.g. based on artificial intelligence) to understand how to foresight co-design processes for doing research.

2. Methodological approach

We assumed to design the RTC model by adopting a speculative design approach (Raby Reference Raby, Erlhoff and Marshall2008) and by adopting a “what if” question (Dunne & Raby Reference Dunne and Raby2013) specifically related to “what if exploring the idea of RTC by assuming CST with negative feedback as the main cognitive model?” Consequently, we used an RTD approach for designing the RTC model assigning variables to a control feedback-loop system to control the state. We combined a general feedback-loop model (Figure 1) with variables that can represent, on the one hand, a general RTD approach, and on the other hand the basic elements of a co-design process. We followed the general process of goal-seeking (Figure 2) of the CST for activating a loop cycle according to an RTD approach and introducing co-design variables in the design of the model (Figure 3). The control theory has been used as a strategy to select the appropriate input (as a research question for RTC) giving an output (or research answer in RTC) (Figure 2). The control theory presents two types of control loops: open loops and closed loop (feedback control) (Levine Reference Levine1996; Iglesias & Ingalls Reference Iglesias and Ingalls2009; Carver & Scheier Reference Carver, Scheier and Ryan2012). Open-loop systems are systems where the output of the system does not affect the input. A closed-loop control system has a retro-feedback to generate a control action to bring the controlled process variable to the same value as the set point in input. Closed-loop systems are designed to automatically achieve and maintain the desired output condition by comparing it with the actual condition. It does this by generating an error signal which is the difference between the output and the reference input. The difference between the actual and desired value of the process variable called the error signal is applied as feedback to generate a control action to bring the controlled process variable to the same value as the set point. Stability is an important characteristic of a control system. For the bounded input signal, the output must be bounded, and if the input is zero, then the output must be zero, then such a control system is said to be a stable system.

Figure 1. A general feedback-loop system.

Figure 2. The goal-seeking process. Left (system structure), right (pattern structure).

Figure 3. A graphical summary of the loops for designing the model.

As a method, we applied the CST according to a basic closed-loop control system (Figure 1) according to the transfer function of the positive feedback control system (Levine Reference Levine1996). We used the process of designing the model as the epistemological medium to gain knowledge about RTC inspired by Jonas (Reference Jonas2015). Essentially, the process for designing the model is the iterative loop of the same mechanism where, after assigning a research question, we managed it according to the following steps; (i) we assigned the variables to the model to first connect RTD and co-design principles with the CST; (ii) we designed the prototype of the model; (iii) we verified the balance of the system through the transfer function and (iv) we finally compared the results with the gaps of the literature that we previously identified. In the second and third loops, we followed the same process steps by firstly refining the variables and the model prototype for each loop, as well as verifying the reliability of the obtained results through mathematical applications and comparison with the existing literature on RTD. Regarding the development of the model prototypes during the loops, we conceptualised their simulation in different backgrounds by presenting our RTC theory and its possible application in the field of applied ergonomics and human factors (Busciantella-Ricci & Scataglini Reference Busciantella-Ricci and Scataglini2020a); its application as a logical aid to prepare for a shared scenario of a research process (Scataglini & Busciantella-Ricci Reference Scataglini and Busciantella-Ricci2020); as a model able to visualise the nature of places such as maker-spaces and FabLabs (Scataglini & Busciantella-Ricci Reference Scataglini and Busciantella-Ricci2021a); as a model to reflect on the future of design education (Busciantella-Ricci & Scataglini Reference Busciantella-Ricci and Scataglini2020c); for connecting RTC with ergonomics principles (Scataglini & Busciantella-Ricci Reference Scataglini, Busciantella-Ricci and Rebelo2021b) and policy-making (Busciantella-Ricci & Scataglini Reference Busciantella-Ricci and Scataglini2020b), and for reflection on the connection between RTC, Design for All and Policy Ergonomics (Busciantella-Ricci & Scataglini Reference Busciantella-Ricci and Scataglini2021). We used the designed model as a speculative design proposal (Raby Reference Raby, Erlhoff and Marshall2008) adopting a speculative research approach (Wilkie, Savransky & Rosengarten Reference Wilkie, Savransky and Rosengarten2017) to discuss theoretical aspects within seven peer-reviewed papers in three international conferences and one journal. We used the RTC model as a “model for” that is “purposive and therefore essentially cybernetic, intended to allow us to act on that world, to find something out, to see what would happen if” (Glanville Reference Glanville2005). We also positioned the RTC model by considering a paradigm shift towards the participatory ones (Lincoln et al. Reference Lincoln, Lynham, Guba, Denzin and Lincoln2018) also for its “subjective-objective ontology”; an epistemology with a “critical subjectivity” and four ways of knowing, i.e. experiential, presentational, propositional and practical; and a “methodology based on co-operative relations between co-researchers” (Heron & Reason Reference Heron and Reason1997). In terms of referencing the synthesis of our idea of the RTC model, we considered:

  • Jonas’s (Reference Jonas2015) perspective on RTD as a synthesis of how design works as an epistemological medium in research;

  • Owen’s (Reference Owen1998) model for using and accumulating knowledge; we created a synthesis by merging the two realms in the model and by assigning at the realm of the practice the principles and the processes of the co-design;

  • the Knowledge-Relevance (K-R) Model (Krogh & Koskinen Reference Krogh and Koskinen2020; based on Bang et al. Reference Bang, Krogh, Ludvigsen and Markussen2012) by specifically taking the concept of “relevance” as related to the gap generated between the research question and the research answer, and the “design experiment” concept as an element that, in our idea of the RTC model, embodies the meanings of doing co-design in the RTC theory;

  • Bakırlıoğlu & Doğan (Reference Bakırlıoğlu and Doğan2020) model that accommodates the co-design process within the RTD influenced by Schön’s (Reference Schön1983) reflexive practice framework; it represents a first-stage reflection on how embedding co-design in a structured research process based on RTD; however, we argue it needs to be integrated with a more robust reflection of what are the variables determined by the concept of “research”;

  • a general basis of the feedback-loop system (Figure 1) to create a robust basis to generate a new synthesis of the aforementioned concepts.

3. Results

The most advanced model to address RTC in simulation settings is presented in this study as the major outcome. We offer an overview of the work in creating the RTC model based on our RTC theory.

3.1. The basic RTC model

In all our speculative work, we used the same basic model for each situated emulative application context. It is the RTC co-model (Figure 4) that we integrated loop by loop with additional knowledge acquired during the speculative works. As a result, after attributing variables to the RTC process based on the closed-loop CST, it was possible to compute the research answer, C(s) of a research question in R(s) minimising the error E(s) expressed as the difference between actual (research answer obtained) and desired value (pre-fixed research answer).

Figure 4. A co-model based on a closed-loop system in RTC.

This can be expressed as

(1) $$ E(s)=R(s)-C(s)H(s). $$

The error signal E(s) is applied as feedback to generate a control action to bring the controlled process variable to the same value as the set point.

The goal of the RTC system is the transfer function representing the co-design process G(s) of the system that is represented as the ratio between the research answer C(s) and the input of the research question R(s), as expressed in equation (2) below

(2) $$ G(s)=\frac{C(s)}{R(s)}, $$

where

(3) $$ {\displaystyle \begin{array}{c}\hskip4pt C(s)=G(s){R}_1(s)=G(s)\left[C(s)-{C}_2(s)\right]=G(s)\left[R(s)-H(s){R}_2(s)\right]\\ {}=G(s)\left[R(s)-H(s)C(s)\right]=G(s)R(s)-G(s)H(s)C(s).\end{array}} $$

Putting this equation (3) into the previous equation (2), we can express

(4) $$ G(s)=\frac{C(s)}{R(s)}=\frac{G(s)}{1+G(s)H(s)}, $$

where G(s)H(s) is the transfer function of the loop that is the product between the co-design process and the co-testing. Therefore, in the co-design process G(s) the team of co-designers Co (assuming that is necessary to have coi and coj > or equal to 2) is expressed by equation (5). Ideally, it is a cross/multidisciplinary team where each co-designer is a person from different fields, experiences and backgrounds that can take a fundamental role into the co-design process due to their diversity. By observing this system, we identified a possible insight. We observed that co-designers, as single key elements of G(s), are variables that should establish a connection to correctly work. As we know, communication and interactions among the participants are some of the challenges and characteristics of co-design (Moser Reference Moser2016; Pirinen Reference Pirinen2016; Blomkamp Reference Blomkamp2018; Slattery et al. Reference Slattery, Saeri and Bragge2020; Antonini Reference Antonini2021). Consequently, the co-designers are connected like a network that communicates with the language of co-design, or through the language facilitated by the co-design tools. If the co-designers can be seen as nodes of a network, we may assume they are in a “network” of neural mechanisms (Tang, Tan & Yi Reference Tang, Tan and Yi2007). They can act and communicate as computing systems of biological mechanisms that can be used to train and simulate a research answer to gain the fabrication of the knowledge.

(5) $$ \mathrm{C}\mathrm{o}=\sum \limits_{i,j=1}^n{\mathrm{co}}_i\times {co}_j. $$

As a consequence, giving a design question R 1(s), the co-designer should use the design tools T in the co-design process G(s) to solve the design answer C 1(s) such as equation (6):

(6) $$ G(s)=\frac{\mathrm{Co}\times T}{R_1(s)}. $$

A design tool (T) is a context-related set of actions, thoughts or objects that makes possible other actions, thoughts or objects for the accomplishment of design-related tasks.

The RTC model works as a mechanism for producing, understanding, evaluating and iterating knowledge acquired with systematic feedback loops of cycles. Every loop of the RTC process is a chance to gain knowledge for understanding the research question R(s) and advancing the chance to reach the research answer C(s) by exploiting creativity, collaborations, processes, approaches, empathies and all the values that can be expressed in the co-design process G(s). The entering of the co-design process is itself determined by an input R 1, the design question, and an output C 1, the design answer as an effective outcome of the co-design process. This outcome can be tested within the H(s) variable to verify if the outcomes of the co-design process answer the research question R(s). In this process, diversity, in terms of different people (with diverse skills, backgrounds, needs, capabilities, cultural, political, economic status, etc.), is the real resource of the whole process. The greater the diversity of people in the co-design process, the greater the possibility of feeding the system with new loops will be. More loops mean increasing the possibility of gaining more knowledge. And, as a direct implication of this mechanism, more possibilities to gain knowledge means a greater chance to reach a clearer answer C(s). The clearness of the answer is therefore proven by the E(s). If it does not produce an error, it means the system recognises the answer of the co-design process (i.e. C 1) as valuable to answer the whole system (i.e. C(s)). H(s) tests that C 1 produces or does not an error of the system reported through E(s). It essentially describes a self-validation process of the RTC system. In other words, the loops produce and stabilise the turbulence that the co-design process in G(s) determined through the multiple creative activities, and through the diversity of the people. However, this turbulence is a resource the whole system may use to stabilise a research answer through the loops guaranteed through the mechanism that describes the negative feedback in the CST mechanism. In summary, more loops (i.e. more possibility to gain knowledge) give a more accurate answer by reducing the error answer of the system. It is how an intelligent system works.

3.2. RTC as a learning system

G(s) can be represented as a neural network in which each co-designer is a node that communicates with one or more co-designers. This co-designing neural network mechanism is a computational neural model used to train and simulate the elaboration of a research response through a co-design process while minimising the error between the acquired research answer C(s) and the predetermined research query R(s). As a result, the nodes function similar to neurons in biological systems, augmenting consciousness through learning and knowledge creation. Human intelligence is defined as the capacity to do difficult tasks that require judgement, creativity, empathy, interaction and multi-domain knowledge. This is distinguishable likewise based on subjective experience. Each co-designer in RTC displays his or her unique consciousness. In G(s), the co-designers are nodes, as neurons of a brain (Figure 5), with different backgrounds, knowledge, competencies and relational intelligence concerning designing.

Figure 5. Graphical representation, variables and transfer function of the RTC model.

In the RTC co-design process, G(s) is seen as a perceptron (Rosenblatt Reference Rosenblatt1957) where to the inputs we are attributing the nodes that are the co-designers (co) characterised by weights $ {w}_i $ (experiences). Therefore, it is possible to describe the transfer function inside G(s) as equation (7):

(7) $$ G(s)=\sum \limits_{i=1}^n{w}_i{x}_i. $$

The perceptron produces output that is the exit of a design process that can be 0 or 1. If it is 1, we obtain the response C 1(s) to G(s). Otherwise, in the case of 0, we are not obtaining a response C 1(s). In RTC, weights $ {w}_i $ are variables that determine the understanding of diversity in terms of those factors that can describe the differences among the people participating in the co-design process.

3.3. Diversity and inclusion variables

In designing the RTC model, we also reflected on the meaning and the value of diversity and thus inclusion in the co-design that substantially influences the whole research process. We started from the assumption that, even if some peculiarities are similar, every person is essentially unique from every point of view. This is a resource to be considered in the co-design process that determines the systematic inquiry through RTC. Therefore, from Figure 5, we designed a polynomial to understand how to consider diversity in G(s). Diversity is a core feature in co-design and needs an interpretation in RTC. Consequently, we designed the polynomial of diversity (PoD) because it considers exclusion factors and some elements that can describe how diversity can be addressed. Addressing exclusion factors is a way of considering the concept of inclusion through multidimensional levels of inclusion/exclusion (Taket et al. Reference Taket, Crisp, Graham, Hanna, Goldingay and Wilson2013). Therefore, we adopted a framework of five inclusion/exclusion factors (Busciantella-Ricci et al. Reference Busciantella-Ricci, Dong, Rinaldi and Tosi2017; Busciantella-Ricci & Scataglini Reference Busciantella-Ricci and Scataglini2021) which allow us to consider physical and cognitive (a), cultural (b), political (c), economic (d) and social (e) factors among the diversity domains of the people. We assigned the five exclusion factors (a, b, c, d, e) as values to be multiplied by the elements (x, y, z) that guarantee the diversity in the RTC system. Specifically, these elements are the participation (x) of the different people/actors in the RTC process; the context (y) in terms of a significant interaction of the design beneficiaries with the context; the personalisation (z) as an intrinsic attitude of the self/auto-regulation feature of the RTC system in favour of the different people/actor’s needs. The multiplication of these elements with the five exclusion factors defines the PoD as a P or polynomial in the RTC process. It is described by equation (8).

(8) $$ P=\left(a+b+c+d+e\right)\left(x+y+z\right). $$

The polynomial describes the weight as we discussed in the previous paragraph where we introduced equation (7) and the variable weights $ {w}_i $ . P describes the weight that is learning of the perceptron. It categorises the diversity of each co-designer in the co-design process G(s); they are nodes of that brain. The sum of the products of the weight and the input in each node are computed at perceptron function G(s) that need to pass a threshold that fires. The firing represents the capability or not of the success to determine the research answer through a co-design process G(s). The diversity’s variables – accordingly, exclusion factors and the assigned elements of diversity – can describe how diversity collaborates in G(s) and RTC. The RTC model is a neuronal network where all the diversities collaborate. The threshold to exit G(s) is crossed or not if this diversity is respected. If the answer (C 1) is representative of the different weights within the co-design process, there will be more chances to cross the threshold.

4. Discussion

As a tentative formal definition, RTC is a mathematical model of cognitive control for understanding how co-creating knowledge through a co-design process in a wider research process. In the real world, RTC may work as a strategy for those who adopt co-design processes, experiences and knowledge as a medium to give answers to their research questions. If supported by the related model, RTC is useful to be adopted not only by designers-researchers but also by citizens, policy-makers and social innovators. RTC is exploitable in a wide range of contexts by improving the possibility of collaborating through co-design thinking in complex systems and contexts. Indeed, control theory and the feedback loop allow stability and self-regulation to the research system without losing relevant properties such as creativity, participation and conflict in the co-design process. Specifically, RTC is an application of the CST that includes a research problem (assigned or related) to a co-design process in RTD. This reinforces “co-design” and RTD and merges them into a unique discussion. RTC is an opportunity to make RTD and co-design evolve.

4.1. RTC and RTD

The RTC model supports rigorousness and relevance as one of the most common concerns in the RTD debate (e.g. Findeli et al. Reference Findeli, Brouillet, Martin, Moineau and Tarrago2008; Chow Reference Chow2010; Jonas Reference Jonas2015). Indeed, CST as the behind model supports the interpretation of the variety of possible RTD processes as described in the literature. Specifically, while G(s) gives space to the designerly ways of addressing research problems and challenges, the outcomes of that process can be tested in H(s) by directly referring to the research question R(s) and by simulating and measuring it iteratively. Also, RTC introduces some features and topics within the RTD discussion. By considering co-design as the main focus of the research process, the RTC model introduces the auto/self-regulation feature. It is a property of the feedback loop that may be relevant to be deeply studied in systematic RTC or RTD experiments. Conceptually, it confers to the research system the possibility of being an autopoietic system (Maturana & Varela Reference Maturana and Varela1980). The RTC model, as an auto/self-regulated system, generates design knowledge by the same entities that learn via the system – through the collaborative processes in G(s). This system may be thought of as an autopoietic learning design system. It embeds instructional processes in the same processes that the model’s variables describe. The more consistent and diverse the cooperation in the co-design process G(s) is, the more the system may expand via the diversity of the same players in G(s). The RTC model encourages variety while also supporting equality.

Secondly, concerning the RTD discussion, RTC recalls the attention on the concept of “materiality,” “object” and “artefacts” and their related meanings. What emerges from an RTC process does not necessarily have a tangibility to be observed. It is unclear how RTD can consider the intangibility of design as an “artefact” to be observed and through which to gain new knowledge. We argue that RTC reinforces the Findeli and Jonas perspective on RTD following the hypothesis of the “eclipse of the object” (Findeli & Bousbaci Reference Findeli and Bousbaci2005).

Third, and probably the most important, RTC introduces the concern of co-design and participation; and this begins to be recognised as one of the topics to be addressed in the RTD discussion (e.g. Boon et al. Reference Boon, Baha, Singh, Wegener, Rozendaal and Stappers2020). Co-designing potentially changes the paradigm we think about the word “design.” Collaborating within a design process introduces significant changes in the approach, methods, tools, processes and the general conditions of the design context. RTD is different from RTC as designing is different from co-designing with a collaborative and participative mindset and attitude. This aspect also opens a discussion on the role of those we generally call “designers” or “designers-researchers” or researchers engaged in design research or reflective designers. In any case, access in G(s) with real participation and a collaborative mindset means being part of the system with no labels.

4.2. RTC and co-design

Who is the co-designer within the RTC process? According to the RTC perspective, the co-designer in the RTC process is a person who takes part in the research process without any distinction on experience, background, capabilities, cultural, economic, social or political status. In our idea of RTC, potentially, anybody could apply an RTC process. Are those considered “designers-experts” useful for the RTC process to take positions, facilitate, stimulate discussions and conflicts and do any other kind of designerly activity? From the RTC perspective, the right answer is “not necessarily.” Let us try to explain this. Entering the RTC process means that the RTC system enables the training as the people enter the system. Conceptually, as the system takes the input (R(s)), it finds a balance with its own resources, including human resources. This aspect would be clearer by thinking about the entering process in G(s). We described the “weight” as the variable that contributes to making every person valuable because it is different to any other person in the same system. The more the diversity is represented in terms of different weights, the more the system can find the output of the system. It means that RTC values and favours diversity as a favourable condition for the whole research process. This is a determinant aspect of co-design because diversity can also favour creativity and innovation by increasing the possibility of finding the answers to the research questions. Technically, the PoD is the description of those variables that guarantee the system takes into consideration diversity, inclusion and thus a real co-design experience. Therefore, the designer, as a role, will be determinant as it will be determinant in any other representative role in the co-design process. We argue that changing the perspective on the role of “designers” may also help the design community to evolve in new forms within a constantly changing society. We argue that RTC helps to reflect on these aspects. In other words, RTC makes tangible and computable the roles of the co-design actors through their weights and their position within the system. It emphasises a relevant aspect for designing co-design processes; i.e. planning criteria to involve participants in a co-design process. This aspect is one of the most relevant to make the co-design process participative and representative within specific research processes. This aspect may increase the potential of co-design to be not only a way to participate and democratise the design and research process but also a robust way for conducting research. The citizen sciences approach is a potential example. It can potentially benefit from adopting RTC as a robust modality to embed co-design for conducting formal research. In this context, RTC may help to increase the introduction of systematic co-design activities in scientific research.

Also, RTC formally helps the co-design culture to evolve in terms of knowledge production. As an instrument, RTC serves the participatory and collaborative design-based processes to gain a new kind of knowledge from the values and the process of co-designing and co-creating. Co-design is G(s) in the RTC system. Therefore, it is the set of variables that determine the trend of the whole system, that through retro-feedback properties is also able to control the instability of the process and allow the iteration; again, with co-design, loop by loop. Potentially, this helps to systematically adopt co-design in a wide variety of situations and conditions increasing the possibility to adopt collaborative practices in complex contexts and by systematically gaining new verifiable knowledge.

Moreover, the whole RTC system can be simulated. It means solving a series of latent problems for co-design. Traditionally, co-design processes are not predictable. Indeed, they are subject to several factors, field conditions and uncontrollable variables that make the simulation difficult or impossible; or, if possible, really expensive, as it is expensive in terms of work and human resources designing the co-design and the collaborative research processes. Also, in this case, simulating all the variables is even impossible. RTC allows the simulation of the co-design and the entire collaborative research process. We do not yet have sufficient data to say that RTC is a model that allows us to make predictions on co-design, but we can affirm it is a starting point. For instance, through the RTC variables and the PoD, it is possible to consider new ways of understanding how to build the set of co-design processes according to the diversity of the people that should be involved. Also, ideally, these variables may help in simulating what kind of outcomes can be expected according to the kind of diversity in the process; or what kind of people should contribute to the co-design process for reaching a specific research answer. RTC may be useful to build a computational model for simulating these difficult aspects of the process, increasing the level of quality, creativity and inclusiveness of the whole research process. Artificial intelligence (AI) fields of study may also benefit from this starting point on RTC. And through RTC, it can be easier to connect co-design with advancement in AI. However, our intention was not to close in a set of rules on the discussion of RTD and co-design. Instead, we felt the need to create an interpretation of the RTC idea by discussing its genesis in an established theoretical framework. We do not exclude changing our perspectives in the future, especially after doing simulations and in-field experiments which is one of the limitations of this research. Another limitation is the lack of testing examples or cases that can support or drastically change our perspective on the RTC concept.

Also, the RTC model facilitates the pursuit of the co-design challenges presented in the introduction paragraphs of this article. Frequently, co-design processes are challenging because of different languages, terminologies, power balances, hierarchies and situations that also require conflict negotiation (e.g. Moser Reference Moser2016; Pirinen Reference Pirinen2016; Antonini Reference Antonini2021; Kirk et al. Reference Kirk, Bandholm, Andersen, Husted, Tjørnhøj-Thomsen, Nilsen and Pedersen2021). All these aspects are related to the concept of human diversity and they also produce benefits for co-design to improve creativity and widen the borders of the research process. At the same time, they increase the time and resources needed to be adopted in a research process. The RTC model potentially creates the condition to prevent, compute and rigorously plan these challenging aspects for co-design. And it does it by taking into consideration how they may impact the whole circle of the research process. In practical terms, through the G(s) variables, it is possible to create in advance an overview of how these challenges can affect the whole system. Consequently, it improves the decision-making on what kind of participants can create the best conditions for both gaining the benefits of diversity and reducing the risk of transforming these challenges into barriers. Weights (w) and design tools (T) are the variables that allow us to compute and plan the previously discussed aspects of the RTC process. Through these variables, it is possible to have a quantified preview for addressing the aforementioned challenges by reducing the time consumed and resources, as well as the risks of creating uncontrollable conflicts and/or co-design contexts where the differences are transformed into barriers that block the creative process. Consequently, this is a relevant novelty to also contribute to advancing co-design.

In addition, we also discussed that challenges for co-design in research processes are (i) evaluating the real impact of co-design (e.g. Slattery et al. Reference Slattery, Saeri and Bragge2020); and (ii) creating a balance between the scientific rigour and what is produced by the participants through open, bottom-up design that often reflects the urgent needs of a context (e.g.Moser Reference Moser2016; Slattery et al. Reference Slattery, Saeri and Bragge2020). RTC offers a system approach to embed the discussion of the co-design outcome within a feedback loop that allows testing if the co-design output is effectively responding to the research question. In practical terms, the whole control mechanism serves as a system (i) to evaluate the real impact of co-design for the research needs and objectives; and (ii) to give space and time to the researchers to understand if the co-design output effectively contributes to the creation of scientific evidence. These aspects need to be investigated with in-depth and empirical research to create specific evidence for a systematic application of RTC. However, RTC creates a structured and supported model where co-design as a systematic research approach can address and improve these challenges. In other words, co-design can benefit from the RTC system for addressing common co-design challenges.

Finally, in canonical research, co-design-based processes are discussed as time- and resource-consuming (e.g. Kirk et al. Reference Kirk, Bandholm, Andersen, Husted, Tjørnhøj-Thomsen, Nilsen and Pedersen2021). Often the aforementioned challenges become barriers that effectively increase these factors. RTC may help by providing a cognitive and computational model to understand how to optimise the management of those aspects that can increase time and resources in co-design.

4.3. RTC, beneficiaries, actors and non-designers

This paragraph discusses how the RTC model can be used and by whom. Firstly, the RTC model can be used as a strategy for planning how to conduct research that uses co-design with the robustness of the CST variables. The variables of the model simplify the embedding of design thinking – through co-design practices – within a research process. At the same time, the RTC model gives stability and equilibrium to a research process that is driven “through” co-design. Also, the RTC model works as an operating model for doing research in several fields by using co-design as the main engine to balance the research question and the desired answer. In parallel, RTC is a cognitive model of how people may address RTD – with its specific variant of co-design – for research purposes. More specifically, how does RTC work? Each variable of the RTC model is a variable of the research process. Therefore, the variables of the model represent the minimum requirements a research process should cover to adopt an RTC approach. The main beneficiaries of this model are designers and the design researchers – or “designers-researchers” by using Cross’ (Reference Cross1999, Reference Cross2006) terms – that do research by adopting a design thinking approach based on co-design. With this model, they may plan a robust research process with the core of co-design as a creative and open medium of the whole process. Specifically, the main beneficiaries are designers-researchers who have the aim to adopt a research process with co-design practices with a consistent group of non-designers. We argue this model can be useful when the group of co-designers is made up of people with very different backgrounds. Potentially, co-design can be made by all non-designers who use design skills, tools and approaches. How this kind of design knowledge by non-designers may influence the whole research process is the core of the RTC model. It is not uncommon to find groups of co-designers without those people who formally define themselves as designers within a specific design discipline background.

4.3.1. A process for non-designers at the core

By framing RTC, both as a model and as a strategy, we expect to simplify the usage of co-design within research processes that need the contribution of the design culture. Traditionally, co-design allows the creation of a design space that lets expert and non-expert designers collaborate. Also, it describes collaborative design processes between researchers from different disciplines, citizens and other individuals who may potentially contribute to the project, and to find research answers. Consequently, co-design deals with the relationship between experts and non-experts, as well as non-designers.

In the introduction paragraphs, we also emphasised that involving non-experts can create a few challenges for applying co-design in formal research frameworks. In summary, we underlined that involving participants from different backgrounds, especially in the case of non-experts, can (i) increase difficulties in creating communication before, during and after the co-design process, with a lack of a common language (Camden et al. Reference Camden, Shikako-Thomas, Nguyen, Graham, Thomas, Sprung, Morris and Russell2015; Drahota et al. Reference Drahota, Meza, Brikho, Naaf, Estabillo, Gomez, Vejnoska, Dufek, Stahmer and Aarons2016; Moser Reference Moser2016; Slattery et al. Reference Slattery, Saeri and Bragge2020; Antonini Reference Antonini2021; Vargas et al. Reference Vargas, Whelan, Brimblecombe and Allender2022); (ii) increase the time and effort for involving, effectively engaging and maintaining the interest of the participants (Moser Reference Moser2016; Slattery et al. Reference Slattery, Saeri and Bragge2020; Kirk et al. Reference Kirk, Bandholm, Andersen, Husted, Tjørnhøj-Thomsen, Nilsen and Pedersen2021); (iii) require the prevention and mitigation of conflicts that generally occur in co-design activities (Slimani et al. Reference Slimani, Da Silva, Médini and Ghodous2006; Manzini Reference Manzini2014; Pirinen Reference Pirinen2016; Zamenopoulos & Alexiou Reference Zamenopoulos and Alexiou2018; Andersen & Mosleh Reference Andersen and Mosleh2021) and (iv) create tensions between the scientific rigour and the end-user preferences (Moser Reference Moser2016; Slattery et al. Reference Slattery, Saeri and Bragge2020).

These aspects are also risks to successfully using co-design as the main engine for the knowledge production mechanism. Some reflections can be described to mitigate these risks. For instance, regarding communication and language, Pirinen (Reference Pirinen2016) suggests that designers should adjust their communication according to the organisation where the co-design is applied. And, where the context requires a more formal, scientific approach, the option for “hard” communication should be adopted. Regarding time- and resource-consuming activities, Slattery et al. (Reference Slattery, Saeri and Bragge2020) suggest investing in the right way in co-design by allocating sufficient time and resources, providing pay/reward for participants’ time and providing training, if needed. More specifically, for what concern strategies for engaging and maintaining the interest of the participants, Slattery et al. (Reference Slattery, Saeri and Bragge2020) suggest drawing on behavioural insights by considering models such the Fogg’s work (Fogg Reference Fogg2019) and the COM-B model (Michie, Van Stralen & West Reference Michie, Van Stralen and West2011). Regarding conflicts and their mitigation, Andersen & Mosleh (Reference Andersen and Mosleh2021) suggest the use of specific tangible artefacts designed to conduct co-design workshops to legitimise conflicts and tensions among stakeholders and consequently create the condition for negotiation. About the balance between the scientific rigour and the open bottom-up design that may merge the urgent actors’ needs (Moser Reference Moser2016), we argue the researcher plays a crucial role. For instance, Blomkamp (Reference Blomkamp2018) by referring to Roggema (Reference Roggema and Roggema2014) and Durose & Richardson (Reference Durose and Richardson2016) depicts the policy-maker in co-design as a figure that shifts from a “prima donna” role to a facilitating role without losing the scope of gaining scientific evidences from the process. On the contrary, the co-design process creates an addition of knowledge with the contribution of the participants. Similarly, changing the role from director to facilitator and catalyst (Cornwall & Jewkes Reference Cornwall and Jewkes1995; Tay et al. Reference Tay, Cox, Brinkworth, Davis, Edney, Gwilt and Ryan2021) by also supporting the participant’s expression of creativity (Kirk et al. Reference Kirk, Bandholm, Andersen, Husted, Tjørnhøj-Thomsen, Nilsen and Pedersen2021) does not harm the possibility of adopting a scientific approach. Through the researcher in the co-design process, data can be maximised for creating scientific evidence. However, there is a lack of a single model for maximising these data and assessing the co-design impact (Slattery et al. Reference Slattery, Saeri and Bragge2020) on the whole research process. We suggest taking into account the RTC model. It can grasp the participant’s needs, through the co-design process and output, without sacrificing the scientific rigour. Indeed, if we interpret preferences, turbulence and participants’ needs as conditions of the system to be controlled, we may assume that the RTC control system allows us to manage these turbulences by creating an equilibrium with the research question.

Also, RTC can help in maximising co-design output produced in the collaboration between contextual non-experts, stakeholders and researchers. Indeed, the RTC system allows us to assess if the co-design outputs are consistent, and relevant and do not produce errors for the research question. On the contrary, it will use additional loops to iterate the process and improve the output. Although some authors discussed possible strategies, we noted a fragmented scenario in the literature for addressing these aspects with a single conceptual framework for co-design. The RTC model simplifies this complexity by creating a space where the divergence among people, and their turbulent process significantly contribute to the research process. The RTC theory tries to describe how the complex relationship among all the individuals participating in the design process can contribute to finding a balanced research answer. From a certain perspective, non-designers are the core figure of the RTC model. Indeed, the presence of non-designers in G(s) gives the chance to find unexpected design answers. Through the RTC process, these design answers can be tested, verified and eventually validated, but, if they produce an error (the E(s) variable), they create a loop that is a benefit both for the whole system and for the actors participating in the process. Therefore, loop by loop the RTC model potentially mitigates the risks that present the co-design process G(s) by facilitating the management of the whole research system. In addition, because the RTC model presents computable variables, all these aspects including the unpredictability of the non-designers can be planned. Substantially, the RTC model creates a predictable scenario where the impact of non-designers can be balanced within a computable system according to the RTC system where the research question and answer are assumed as variables that create the expected balance of the whole system.

4.4. Towards co-design as research

RTC, through its model and variables, presents the potential to be visualised and operative. It means to make tangible the process of formalising and developing a research question to find a relevant research answer through co-design, which is a collaborative representation of the contemporary design culture. RTC as a strategy can be applied through the variables, and they are made usable to all those who are engaged in co-design as a way of conducting research. It means formalising the co-design as research. This follows the debate in design research towards the “design as research” perspective. More specifically, the RTC model is intrinsically proposing the “co-design as research,” in terms of giving this type of design research the rigours, robustness and practicability as it happened for traditional academic and scientific research disciplines. We argue that just the practice of co-design is not enough to be considered within the “co-design as research” paradigm. At the same time, RTD is not sufficiently representative of the whole complexity of applying participative practices through design as, itself, “design as research.” Similarly, the literature debated “research as design” (Jonas Reference Jonas2015 based on Glanville Reference Glanville, Glanville and de Zeeuw1997) as “probably the essential mental and social ‘mechanism’ of generating new ideas, the location of abductive reasoning.” We thought about this mechanism as more representative of collaborative designing where the collaboration is itself a social mechanism. In the contemporary era, co-design is everywhere and it is largely requested in most of the research processes that need to find innovations. Making these opportunities tangible for every researcher, designer, decision-maker and citizen is what stimulates the research we presented in this article. We feel that RTC is a more empathic model for conducting research through the principles and values of co-design. RTC is research that approaches people’s needs and makes them participate, even if not designers, even if not experts. RTC is a tentative theory and model to make even more tangible the concept of doing “co-design as research.”

4.4.1. RTC implications, new insight and future research and practices

RTC took robustness through the CST. It is something that was searched in previous RTD models, as well as in the pure co-design practice. At the same time, through the basis of the feedback-loop system, we merged RTD and co-design in a unique model that can present a process itself to plan and conduct RTC. It gives RTD a model to refer to, even if peculiarly based on co-design. However, co-design is the real new frontier for design. How is it possible to address complex problems such as those related to climate change and social issues without providing participation sessions and co-design practices? For instance, involving people in research and development, or innovation actions, is becoming a requirement for every programme funded by the European Commission. RTC can support this societal approach by combining science and citizens. Indeed, we suggest RTC as a research practice to be adopted in processes related to citizen science, more largely recognised as an example of open science (Robinson et al. Reference Robinson, Cawthray, West, Bonn, Ansine, Hecker, Haklay, Bowser, Makuch, Vogel and Bonn2018). This potentially opens a new area to investigate where co-design, as well as the explorative pragmatism of RTD, plays a crucial, useful and performative role in the research process.

In addition, RTC uses a collaborative model quantifying in an empirical way a co-design research process demonstrating that given a research question, it is possible to calculate the research answer and the relative error between the research question obtained and the prefixed. This allows measuring the error in this control closed-loop system of RTC assuring that the obtained research question is near to the prefixed. This supports optimisations in an empirical way of a co-design process.

This model also can be used to quantify a co-design process that nowadays is not quantifiable (e.g. collaborative action or collaborative co-design task or process). Similarly, the process demonstrates the collaboration of co-design actors who come from different backgrounds in a multidisciplinary approach that empirically demonstrates inclusiveness (e.g. CoiCoj>2). The predictable features of the RTC model through its specific variables may open new research works, as well as new areas to be investigated, related to the application of this model with AI frameworks. Computing the variables of RTC is something we theorised about in this article. It can be the next step for additional research on the topic. Predicting or controlling through computational help the variables of co-design has a double value (as implications) for future RTD and future design and research practices. The first is reducing the possibility of making errors with participative models based on co-design. As a consequence, it improves the possibility of making the funding for research to apply co-design safer by reducing the risk related to the co-design variables. The second is reducing the gap between science and citizen needs. It is in terms of improving the possibility of engaging more and more citizens because the RTC process ensures having a tool to plan, manage and control the multiple variables of these kinds of processes. These two aspects simplify the involvement of non-designers in research processes based on participatory design processes.

Indirectly, this will open new discussions on the role of what are considered as “expert designers.” We do not know who will, and if, be considered design-experts, and in which terms. If RTC is applied, future designers will be the ones most likely to adopt and manage this model. In conferences we presented the RTC model as a preview of our original idea, designers were the most responsive to understanding the model and its variable as a research process that lacked their specific design research knowledge. We expect they will use it, reinforcing their research and professional skills and conferring to the related practice the right relevance to make it more academically robust.

5. Conclusion

In conclusion, RTC is a mathematical model of cognitive control for understanding how to co-create knowledge by applying the CST and merging RTD and co-design. RTC may serve as a strategy for those who adopt co-design processes, experiences and knowledge as a medium to gain new ((co)design) knowledge. RTC embeds the participatory paradigm through collaborative design practice and makes the research a collaborative process for learning from all the participants. We argue that RTC can contribute both to the discussion of RTD and co-design by strengthening (co-)design as an independent field of research and offering cybernetically informed methods of inquiry with its form of rigour.

This work tries to contribute to wide aspects of co-design and RTD such as the co-creation of knowledge, research-oriented co-design, diversity and inclusion in co-designing as well as diversity and inclusion in research processes that systematically adopt co-design. Specifically, we designed a model for transforming the RTC idea into an entity to be observed and criticised. Therefore, observing the RTC model we frame contributions both in RTD and co-design field of studies. Specifically, RTC may contribute to confer rigorousness and relevance to RTD processes by introducing the RTC model and its variables. At the same time, by introducing co-design within the RTD discourse, the meanings of “artefacts” and “designers/co-designers” we suggest need a revision. Indeed, co-design and RTC offer different challenges where labels and boundaries may result in insignificant and without providing any real value. RTC may help in reconsidering diversity and inclusion in co-design and collaborative research processes, by introducing variables (such as the PoD) that make the process more careful on these aspects. We described how the RTC model can improve the quality of the whole process by increasing the diversity in the co-design process. The greater the diversity level is, the greater will be the chance to reach the research answer through creative and innovative solutions. RTC is also an auto/self-regulation process where people (co-designers – including non-designers) can learn from each other and improve the quality of the whole system loop by loop. This is the reason why we described RTC as an autopoietic learning design system. In parallel, we also open a discussion on some implications the RTC process may offer for envisioning co-design as research. The offered model can simplify these aspects by merging in a unique framework issue such as those concerning open science and citizen science processes.

Finally, the RTC model is described through variables that make it possible to simulate an RTC process. This could bring significant advantages in designing the RTC process by facilitating the identification of expected activities, resources and outcomes, and reducing the general efforts for using co-design. In addition, the possibility of simulating the RTC process is a starting point for identifying AI tools for exploiting co-design in research in multiple ways we have yet to imagine.

Financial support

This research received no specific grant from any funding agency, commercial or not-for-profit sectors.

References

Andersen, P. V. K. & Mosleh, W. S. 2021 Conflicts in co-design: engaging with tangible artefacts in multi-stakeholder collaboration. CoDesign 17 (4), 473492.10.1080/15710882.2020.1740279CrossRefGoogle Scholar
Antonini, M. 2021 An overview of co-design: advantages, challenges and perspectives of users’ involvement in the design process. Journal of Design Thinking 2 (1), 4560.Google Scholar
Archer, B. 1995 The nature of research. Co-Design Journal 2 (11), 613.Google Scholar
Arnold, M. 2020 Transdisciplinary research (Transdisciplinarity). In Encyclopedia of Creativity, Invention, Innovation and Entrepreneurship (ed. Carayannis, E. G.), pp. 18191828. Springer International Publishing.Google Scholar
Aslam, S., Van Dijk, J. & Dertien, E. 2019 CoCoCo: co-designing a co-design toolkit for co-bots to empower autistic adults. In Proceedings of the 4th Biennial Research Through Design Conference, 19-22 March 2019 (Vol. 13), pp. 116. University of Twente; doi:10.6084/m9.figshare.7855904.v1.Google Scholar
Axelsson, R. 2010 Integrative research and transdisciplinary knowledge production: a review of barriers and bridges. Journal of Landscape Ecology 3 (2), 1440.10.2478/v10285-012-0025-0CrossRefGoogle Scholar
Baekgaard, M., Larsen, S. K. & Mortensen, P. B. 2019 Negative feedback, political attention, and public policy. Public Administration 97 (1), 210225.10.1111/padm.12569CrossRefGoogle Scholar
Bakırlıoğlu, Y. & Doğan, Ç. 2020 Exploring product/part longevity in open design of small kitchen appliances. The Design Journal 23 (6), 885905; doi:10.1080/14606925.2020.1826635.CrossRefGoogle Scholar
Bang, A. L. & Eriksen, M. A. 2014 Experiments all the way in programmatic design research. Art 6 (1), 4.14.20; doi:10.1386/art_00004_1.Google Scholar
Bang, A. L., Krogh, P., Ludvigsen, M. & Markussen, T. 2012 The role of hypothesis in constructive design research. In Proceedings of the Art of Research IV. Aalto University School of Arts, Design and Architecture.Google Scholar
Barcellini, F., Prost, L. & Cerf, M. 2015 Designers’ and users’ roles in participatory design: what is actually co-designed by participants? Applied Ergonomics 50, 3140.10.1016/j.apergo.2015.02.005CrossRefGoogle ScholarPubMed
Bardach, E. 2006 Policy dynamics. In The Oxford Handbook of Political Science (ed. Goodin, R. E.). Oxford University Press.Google Scholar
Basballe, D. A. & Halskov, K. 2012 Dynamics of research through design. In Proceedings of the Designing Interactive Systems Conference on – DIS ’12. ACM; doi:10.1145/2317956.2317967.Google Scholar
Bason, C. 2016 Design for Policy. Routledge; doi:10.4324/9781315576640.CrossRefGoogle Scholar
Baumgartner, F. R. & Jones, B. D. 2002 Positive and negative feedback in politics. In Policy Dynamics (ed. Baumgartner, F. R. & Jones, B. D.), pp. 328. University of Chicago Press.Google Scholar
Biggs, M. A. R. & Büchler, D. 2007 Rigor and practice-based research. Design Issues 23 (3), 6269; doi:10.1162/desi.2007.23.3.62.CrossRefGoogle Scholar
Bird, M., McGillion, M., Chambers, E. M., Dix, J., Fajardo, C. J., Gilmour, M., Levesque, K., Lim, A., Mierdel, S., Ouellette, C., Polanski, A. N., Reaume, S. V., Whitmore, C. & Carter, N. 2021 A generative co-design framework for healthcare innovation: development and application of an end-user engagement framework. Research Involvement and Engagement 7, 112.10.1186/s40900-021-00252-7CrossRefGoogle ScholarPubMed
Blomkamp, E. 2018 The promise of co-design for public policy. Australian Journal of Public Administration 77 (4), 729743; doi:10.1111/1467-8500.12310.CrossRefGoogle Scholar
Bofylatos, S. 2022 Upcycling systems design, developing a methodology through design. Sustainability 14 (2), 600.10.3390/su14020600CrossRefGoogle Scholar
Bolster, E. A., Gessel, C. V., Welten, M., Hermsen, S., Lugt, R. V. D., Kotte, E., van Essen, A. & Bloemen, M. A. T. 2021 Using a co-design approach to create tools to facilitate physical activity in children with physical disabilities. Frontiers in Rehabilitation Sciences 2, 707612.10.3389/fresc.2021.707612CrossRefGoogle ScholarPubMed
Boon, B., Baha, S. E., Singh, A., Wegener, F. E., Rozendaal, M. C. & Stappers, P. J. 2020 Grappling with diversity in research through design. In DRS 2020 International Conference, Held online: Synergy, pp. 139151. Design Research Society.Google Scholar
Brandt, E., Binder, T. & Sanders, E. B. N. 2012 Tools and techniques: ways to engage telling, making and enacting. In Routledge International Handbook of Participatory Design, pp. 145181. Routledge.Google Scholar
Britannica 2023 Cybernetics. Encyclopædia Britannica. https://www.britannica.com/science/cybernetics.Google Scholar
Bubnicki, Z. 2005 Modern Control Theory. Springer.Google Scholar
Busciantella-Ricci, D., Dong, H., Rinaldi, A. & Tosi, F. 2017 Discussing about “inclusion in sharing-based services”. A design workshop using an analytic tool. The Design Journal 20 (sup1), S4671S4677.10.1080/14606925.2017.1352964CrossRefGoogle Scholar
Busciantella-Ricci, D. & Scataglini, S. 2020a A Co-model for Research Through Co-design. In Advances in Additive Manufacturing, Modeling Systems and 3D Prototyping, pp. 595602. Springer; doi:10.1007/978-3-030-20216-3_55.CrossRefGoogle Scholar
Busciantella-Ricci, D. & Scataglini, S. 2020b Discussing research through co-design in policy-making. In Advances in Intelligent Systems and Computing, pp.39. Springer; doi:10.1007/978-3-030-51038-1_1.Google Scholar
Busciantella-Ricci, D. & Scataglini, S. 2020c Making design knowledge democracy happen. Disegno Industriale - Industrial Design (DIID) 71, 8087.Google Scholar
Busciantella-Ricci, D. & Scataglini, S. 2021 Research through co-design for connecting design for all and policy ergonomics. In Lecture Notes in Networks and Systems, pp.163171. Springer; doi:10.1007/978-3-030-74605-6_20.Google Scholar
Camden, C., Shikako-Thomas, K., Nguyen, T., Graham, E., Thomas, A., Sprung, J., Morris, C. & Russell, D. J. 2015 Engaging stakeholders in rehabilitation research: a scoping review of strategies used in partnerships and evaluation of impacts. Disability and Rehabilitation 37 (15), 13901400.10.3109/09638288.2014.963705CrossRefGoogle ScholarPubMed
Candy, L. 2006 Practice based research: a guide. CCS Report 1 (2), 119.Google Scholar
Carver, C. S. & Scheier, M. F. 1982 Control theory: a useful conceptual framework for personality–social, clinical, and health psychology. Psychological Bulletin 92, 111.10.1037/0033-2909.92.1.111CrossRefGoogle ScholarPubMed
Carver, C. S. & Scheier, M. F. 2012 Cybernetic control processes and the self-regulation of behavior. In The Oxford Handbook of Human Motivation (ed. Ryan, R. M.), pp. 2742. Oxford University Press; doi:10.1093/oxfordhb/9780195399820.013.0003.Google Scholar
Censi, A. 2015 A mathematical theory of co-design. arXiv preprint. arXiv:1512.08055.Google Scholar
Chow, R. 2010 What Should be Done with the Different Versions of Research-Through-Design? Entwerfen - Wissen - Produzieren, pp. 145158. Transcript Verlag; doi:10.1515/transcript.9783839414637.145.Google Scholar
Chow, R. & Jonas, W. 2008 Beyond dualisms in methodology: an integrative design research medium “maps” and some reflections. In Undisciplined! – DRS International Conference 2008, 16–19 July, Sheffield, United Kingdom (ed. Durling, D., Rust, C., Chen, L., Ashton, P. and Friedman, K.). https://dl.designresearchsociety.org/drs-conference-papers/drs2008/researchpapers/29.Google Scholar
Cornwall, A. & Jewkes, R. 1995 What is participatory research? Social Science & Medicine 41 (12), 16671676.10.1016/0277-9536(95)00127-SCrossRefGoogle ScholarPubMed
Cortesão, J. & Lenzholzer, S. 2022 Research through design in urban and landscape design practice. Journal of Urban Design 27 (6), 617633.10.1080/13574809.2022.2062313CrossRefGoogle Scholar
Cross, N. 1982 Designerly ways of knowing. Design Studies 3 (4), 221227; doi:10.1016/0142-694x(82)90040-0.CrossRefGoogle Scholar
Cross, N. 1999 Design research: a disciplined conversation. Design Issues 15 (2), 510.10.2307/1511837CrossRefGoogle Scholar
Cross, N. 2001 Designerly ways of knowing: design discipline versus design science. Design Issues 17 (3), 4955.10.1162/074793601750357196CrossRefGoogle Scholar
Cross, N. 2006 Designerly Ways of Knowing. Springer.Google Scholar
Cruz, M. G., Ersoy, A., Czischke, D. & van Bueren, E. 2022 A framework for co-design processes and visual collaborative methods: an action research through design in Chile. Urban Planning 7 (3), 363378.Google Scholar
Daniel, K. L., McConnell, M., Schuchardt, A. & Peffer, M. E. 2022 Challenges facing interdisciplinary researchers: findings from a professional development workshop. PLoS One 17 (4), e0267234.10.1371/journal.pone.0267234CrossRefGoogle ScholarPubMed
Deserti, A., Rizzo, F. & Smallman, M. 2020 Experimenting with co-design in STI policy making. Policy Design and Practice 3 (2), 135149.10.1080/25741292.2020.1764692CrossRefGoogle Scholar
Dietrich, T., Rundle-Thiele, S., Schuster, L. & Connor, J. 2016 Co-designing social marketing programs. Journal of Social Marketing 6 (1), 4161; doi:10.1108/JSOCM-01-2015-0004.CrossRefGoogle Scholar
Dimopoulos-Bick, T. L., O’Connor, C., Montgomery, J., Szanto, T., Fisher, M., Sutherland, V., Baines, H., Orcher, P., Stubbs, J., Maher, L., Verma, R. & Palmer, V. 2019 Anyone can co-design?: a case study synthesis of six experience-based co-design (EBCD) projects for healthcare systems improvement in New South Wales, Australia. Patient Experience Journal 6 (2), 93104.10.35680/2372-0247.1365CrossRefGoogle Scholar
Dixon, B. 2019 Experiments in experience: towards an alignment of research through design and John Dewey’s pragmatism. Design Issues 35 (2), 516; doi:10.1162/desi_a_00531.CrossRefGoogle Scholar
Dixon, B. S. 2020 Dewey and Design. Springer International Publishing.10.1007/978-3-030-47471-3CrossRefGoogle Scholar
Djenontin, I. N. S. & Meadow, A. M. 2018 The art of co-production of knowledge in environmental sciences and management: lessons from international practice. Environmental Management 61 (6), 885903.10.1007/s00267-018-1028-3CrossRefGoogle ScholarPubMed
Domino, S. E., Smith, Y. R. & Johnson, T. R. 2007 Opportunities and challenges of interdisciplinary research career development: implementation of a women’s health research training program. Journal of Women’s Health 16 (2), 256261.10.1089/jwh.2006.0129CrossRefGoogle ScholarPubMed
Drahota, A. M. Y., Meza, R. D., Brikho, B., Naaf, M., Estabillo, J. A., Gomez, E. D., Vejnoska, S. F., Dufek, S., Stahmer, A. C. & Aarons, G. A. 2016 Community‐academic partnerships: a systematic review of the state of the literature and recommendations for future research. The Milbank Quarterly 94 (1), 163214.10.1111/1468-0009.12184CrossRefGoogle ScholarPubMed
Dunne, A. & Raby, F. 2013 Speculative Everything: Design, Fiction, and Social Dreaming. MIT Press.Google Scholar
Durose, C. & Richardson, L. 2016 Designing Public Policy for co-Production: Theory, Practice and Change. Policy Press.Google Scholar
Durrant, A., Vines, J., Wallace, J. & Yee, J. 2015 Developing a dialogical platform for disseminating research through design. Constructivist Foundations 11 (1), 821.Google Scholar
Durrant, A. C., Vines, J., Wallace, J. & Yee, J. S. 2017 Research through design: twenty-first century makers and materialities. Design Issues 33 (3), 310.10.1162/DESI_a_00447CrossRefGoogle Scholar
Eckhardt, J., Kaletka, C., Krüger, D., Maldonado-Mariscal, K. & Schulz, A. C. 2021 Ecosystems of co-creation. Frontiers in Sociology 6, 642289; doi:10.3389/fsoc.2021.642289.CrossRefGoogle ScholarPubMed
Ehn, P. 1993 Scandinavian design: on participation and skill. In Participatory design (ed. Schuler, D. & Namioka, A.), pp. 4177. L. Erlbaum Associates, Inc.Google Scholar
Faste, T. & Faste, H. 2012 Demystifying “design research”: design is not research, research is design. IDSA Education Symposium 2012, 15.Google Scholar
Findeli, A. & Bousbaci, R. 2005 L’éclipse de l’objet dans les théories du projet en design. The Design Journal 8 (3), 3549.10.2752/146069205789331574CrossRefGoogle Scholar
Findeli, A., Brouillet, D., Martin, S., Moineau, C. & Tarrago, R. 2008 Research through design and transdisciplinarity: a tentative contribution to the methodology of design research. In «Focused» Current Design Research Projects and Methods. Symposium Conducted at the Meeting of Swiss Design Network 2008, pp. 6791. Swiss Design Network.Google Scholar
Fogg, B. J. 2019 Tiny Habits: The Small Changes that Change Everything. Eamon Dolan Books.Google Scholar
Frayling, C. 1993 Research in art and design. Royal College of Art Research Papers 1 (1), 15.Google Scholar
Galdon, F. & Hall, A. 2022 (Un) Frayling design research in design education for the 21st century. The Design Journal 25 (6), 915933.10.1080/14606925.2022.2112861CrossRefGoogle Scholar
Garcia, I., Barberà, E., Gros, B., Escofet, A., Fuertes, M., Noguera, I., López, M., Meritxell Cortada, M. & Marimón, M. 2014 Analysing and supporting the process of co-designing inquiry-based and technology-enhanced learning scenarios in higher education. In Proceedings of the 9th International Conference on Networked Learning 2014, pp. 493501. University of Edinburgh.Google Scholar
Gaver, W. 2012 What should we expect from research through design?. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM; doi:10.1145/2207676.2208538.Google Scholar
Gerlak, A. K., Guido, Z., Owen, G., McGoffin, M. S. R., Louder, E., Davies, J., Smith, K., Zimmer, A., Murveit, A., Meadow, A., Shrestha, P. & Joshi, N. 2023 Stakeholder engagement in the co-production of knowledge for environmental decision-making. World Development 170, 106336.10.1016/j.worlddev.2023.106336CrossRefGoogle Scholar
Glanville, R. 1997 A ship without a rudder. In Problems of Excavating Cybernetics and Systems (ed. Glanville, R. & de Zeeuw, G.), pp. 110. BKS+.Google Scholar
Glanville, R. 1999 Researching design and designing research. Design Issues 13 (25), 112.Google Scholar
Glanville, R. 2005 A (cybernetic) musing: certain propositions concerning prepositions. Cybernetics & Human Knowing 12 (3), 87.Google Scholar
Godin, D. & Zahedi, M. 2014 Aspects of research through design: a literature review. In Design’s Big Debates - DRS International Conference 2014, 16–19 June, Umeå, Sweden (ed. Lim, Y., Niedderer, K., Redström, J., Stolterman, E. and Valtonen, A.). https://dl.designresearchsociety.org/drs-conference-papers/drs2014/researchpapers/85.Google Scholar
Grindell, C., Coates, E., Croot, L. & O’Cathain, A. 2022 The use of co-production, co-design and co-creation to mobilise knowledge in the management of health conditions: a systematic review. BMC Health Services Research 22 (1), 877.10.1186/s12913-022-08079-yCrossRefGoogle ScholarPubMed
Groeneveld, B., Melles, M., Vehmeijer, S., Mathijssen, N., Dekkers, T. & Goossens, 2019 Developing digital applications for tailored communication in orthopaedics using a research through design approach. Digital Health 5, 2055207618824919.10.1177/2055207618824919CrossRefGoogle ScholarPubMed
Heaton, J., Day, J. & Britten, N. 2015 Collaborative research and the co-production of knowledge for practice: an illustrative case study. Implementation Science 11, 110.10.1186/s13012-016-0383-9CrossRefGoogle Scholar
Heron, J. & Reason, P. 1997 A participatory inquiry paradigm, Qualitative Inquiry, 3 (3), 274294; doi:10.1177/107780049700300302.CrossRefGoogle Scholar
Herriott, R. 2019 What kind of research is research through design, IASDR 2019 Conference Proceedings. International Association of Societies of Design Research, Manchester 11, 111.Google Scholar
Herriott, R. 2023 Delightful phrase: are there really designerly ways of knowing? Design Issues 39 (3), 7282.10.1162/desi_a_00727CrossRefGoogle Scholar
Howlett, M. 2009 Process sequencing policy dynamics: Beyond homeostasis and path dependency. Journal of Public Policy 29 (3), 241262.10.1017/S0143814X09990158CrossRefGoogle Scholar
Iglesias, P. A. & Ingalls, B. P. 2009 Control Theory and Systems Biology. MIT Press.10.7551/mitpress/9780262013345.001.0001CrossRefGoogle Scholar
Irwin, T. 2015 Transition design: a proposal for a new area of design practice, study, and research. Design and Culture 7 (2), 229246; doi:10.1080/17547075.2015.1051829.CrossRefGoogle Scholar
Isley, C. G. & Rider, T. 2018 Research-through-design: exploring a design-based research paradigm through its ontology, epistemology, and methodology. In Proceedings of DRS 2018: Catalyst (Vol. 1 ) (ed. Storni, C., Leahy, K., McMahon, M., Bohemia, E. and Lloyd, P.), pp. 357367; doi:10.21606/drs.2018.263.Google Scholar
Jachna, T. 2019 Designing, together and apart. In Design Cybernetics: Navigating the New (ed. Fischer, T. & Herr, C. M.), pp. 219232; doi:10.1007/978-3-030-18557-2_12.CrossRefGoogle Scholar
Jonas, W. 2007 Research through DESIGN through research: a cybernetic model of designing design foundations. Kybernetes 36, 13621380; doi:10.1108/03684920710827355.CrossRefGoogle Scholar
Jonas, W. 2014 A cybernetic model of design research. In The Routledge Companion to Design Research, pp. 2337. Routledge; doi:10.4324/9781315758466-4.CrossRefGoogle Scholar
Jonas, W. 2015 Research through design is more than just a new form of disseminating design outcomes. Constructivist Foundations 11 (1), 3236.Google Scholar
Jones, P. 2018 Contexts of co-creation: designing with system stakeholders. In Translational Systems Sciences, pp. 352. Springer; doi:10.1007/978-4-431-55639-8_1.Google Scholar
Jørgensen, H. H., Skovbjerg, H. M. & Eriksen, M. A. 2021 Appropriating a DBR model for a ‘research through codesign’ project on play in schools-to frame participation In Nordes Nordic Design Research Conference: Matters of Scale, pp. 434443. UC Vieden.Google Scholar
Julier, G. 2006 From visual culture to design culture. Design Issues 22 (1), 6476.10.1162/074793606775247817CrossRefGoogle Scholar
Julier, G. 2013 From design culture to design activism. Design and Culture 5 (2), 215236.10.2752/175470813X13638640370814CrossRefGoogle Scholar
Kerr, J., Whelan, M., Zelenko, O., Harper-Hill, K. & Villalba, C. 2022 Integrated co-design: a model for co-designing with multiple stakeholder groups from the ‘fuzzy’ front-end to beyond project delivery. International Journal of Design 16 (2), 7590.Google Scholar
Keyson, D. V. & Bruns, M. 2009 Empirical research through design. In Proceedings of the International Association of Societies of Design Research Conference (IASDR’09), 18–22 October 2009, Seoul, Korea, pp. 45484557. Eindhoven University of Technology.Google Scholar
King, P. H. 2021 Control theory in biomedical engineering: Applications in physiology and medical robotics. IEEE Pulse 12 (1), 3738; doi:10.1109/mpuls.2021.3052597.Google Scholar
Kirk, J., Bandholm, T., Andersen, O., Husted, R. S., Tjørnhøj-Thomsen, T., Nilsen, P. & Pedersen, M. M. 2021 Challenges in co-designing an intervention to increase mobility in older patients: a qualitative study. Journal of Health Organization and Management 35 (9), 140162.10.1108/JHOM-02-2020-0049CrossRefGoogle ScholarPubMed
Koskinen, I., Zimmerman, J., Binder, T., Redström, J. & Wensveen, S. 2011 Design Research through Practice: From the Lab, Field, and Showroom. Morgan Kaufmann.Google Scholar
Kozar, O. 2010 Towards better group work: Seeing the difference between cooperation and collaboration. English Teaching Forum 48(2), 1623, online document (downloadable on November 2nd 2023) https://americanenglish.state.gov/files/ae/resource_files/48_2-etf-towards-better-group-work-seeing-the-difference-between-cooperation-and-collaboration.pdf.Google Scholar
Krogh, P. G. & Koskinen, I. 2020 Drifting by Intention: Four Epistemic Traditions from within Constructive Design Research. Springer.10.1007/978-3-030-37896-7CrossRefGoogle Scholar
Lee, Y. 2008 Design participation tactics: The challenges and new roles for designers in the co-design process. Co-design 4 (1), 3150.Google Scholar
Lenzholzer, S., Duchhart, I. & Koh, J. 2013 ‘Research through designing’ in landscape architecture. Landscape and Urban Planning 113, 120127; doi:10.1016/j.landurbplan.2013.02.003.CrossRefGoogle Scholar
Levine, W. S. 1996 The Control Handbook. CRC Press.Google Scholar
Lincoln, Y. S., Lynham, S. A. & Guba, E. G. 2018 Paradigmatic controversies, contradictions, and emerging confluences, revisited’. In The Sage Handbook of Qualitative Research, 5th Edn (ed. Denzin, N. K. & Lincoln, Y. S.), pp. 213263. Sage.Google Scholar
Löwgren, J., Svarrer Larsen, H. & Hobye, M. 2013 Towards programmatic design research. Designs for Learning 6 (1–2), 80; doi:10.2478/dfl-2014-0017.CrossRefGoogle Scholar
Maher, R., Maher, M., Mann, S. & McAlpine, C. A. 2018 Integrating design thinking with sustainability science: a research through design approach. Sustainability Science 13, 15651587.10.1007/s11625-018-0618-6CrossRefGoogle ScholarPubMed
Mäkelä, T., Helfenstein, S., Lerkkanen, M. K. & Poikkeus, A. M. 2018 Student participation in learning environment improvement: analysis of a co-design project in a Finnish upper secondary school. Learning Environments Research 21 (1), 1941; doi:10.1007/s10984-017-9242-0.CrossRefGoogle Scholar
Mäkelä, M. & Routarinne, S. 2007 The Art of Research: Research Practices in Art and Design. University of Art and Design Helsinki UIAH.Google Scholar
Manzini, E. 2009 New design knowledge. Design Studies 30 (1), 412.10.1016/j.destud.2008.10.001CrossRefGoogle Scholar
Manzini, E. 2014 Design in a changing, connected world’. Strategic Design Research Journal 7 (2), 9599.Google Scholar
Manzini, E. 2015 Design, when Everybody Designs: An Introduction to Design for Social Innovation. MIT Press; doi:10.7551/mitpress/9873.001.0001.CrossRefGoogle Scholar
Manzini, E. 2016 Design culture and dialogic design. Design Issues 32 (1), 5259.10.1162/DESI_a_00364CrossRefGoogle Scholar
Manzini, E. 2019 Politics of the Everyday. Bloomsbury; doi:10.5040/9781350053687.CrossRefGoogle Scholar
Manzini, E. & Rizzo, F. 2011 Small projects/large changes: participatory design as an open participated process. CoDesign 7 (3–4), 199215; doi:10.1080/15710882.2011.630472.CrossRefGoogle Scholar
Markussen, T. 2017 Building theory through design. In Practice-Based Design Research (ed. Vaughan, L.). Bloomsbury.Google Scholar
Maturana, H. R. & Varela, F. 1980 Autopoiesis and cognition: the realization of the living. In Boston Studies in the Philosophy of Science (Vol. 42 ). Reidel Publishing Company.Google Scholar
McIntyre, A. 2008 Participatory Action Research. Sage.10.4135/9781483385679CrossRefGoogle Scholar
Menichinelli, M. 2020 Exploring the impact of maker initiatives on cities and regions with a research through design approach. Strategic Design Research Journal 13 (1), 92109; doi:10.4013/sdrj.2020.131.07.CrossRefGoogle Scholar
Meroni, A., Selloni, D. & Rossi, M. 2018 Massive Codesign. A Proposal for a Collaborative Design Framework. Franco Angeli.Google Scholar
Meyer, M. W. & Norman, D. 2020 Changing design education for the 21st century, she Ji. The Journal of Design, Economics, and Innovation 6 (1), 1349; doi:10.1016/j.sheji.2019.12.002.Google Scholar
Michal, Z. İ. O. N. & Klein, S. 2015 Conceptual understanding of homeostasis. International Journal of Biology Education 4 (1), 127.Google Scholar
Michie, S., Van Stralen, M. M. & West, R. 2011 The behaviour change wheel: A new method for characterising and designing behaviour change interventions. Implementation Science 6 (1), 112.10.1186/1748-5908-6-42CrossRefGoogle ScholarPubMed
Mikus, J. 2023 Eudaemonic design as an approach to co-creating health and well-being in the built environment: an exemplar case of older adults at home. PhD Thesis, Queensland University of Technology (downloadable on November 2nd 2023) https://eprints.qut.edu.au/239357/.Google Scholar
Moser, S. C. 2016 Can science on transformation transform science? Lessons from co-design. Current Opinion in Environmental Sustainability 20, 106115.10.1016/j.cosust.2016.10.007CrossRefGoogle Scholar
Neculai, A. 2005 Modern control theory: a historical perspective. Scrieri Matematice 1, 112.Google Scholar
Ostrowski, A. K., Breazeal, C. & Park, H. W. 2021 Research through (co)-Design: engaging older adults in the design of social robots. In Virtual ’21, March 08–11, 2021, Virtual (downloadable on November 2nd 2023) https://robots.media.mit.edu/wp-content/uploads/sites/7/2021/04/Ostrowskietal_HRI_2021_RtD_Workshop_Position_Paper_CameraReady.pdf.Google Scholar
Owen, C. L. 1998 Design research: building the knowledge base. Design Studies 19 (1), 920; doi:10.1016/S0142-694X(97)00030-6.CrossRefGoogle Scholar
Pangaro, P. 2008 Instructions for design and designs for conversation. In Handbook of Conversation Design for Instructional Applications (ed. Luppicini, R.), pp. 3548. ICI Global Publishers.10.4018/978-1-59904-597-9.ch003CrossRefGoogle Scholar
Pant, M. 2014 Participatory action research. In The SAGE Encyclopaedia of Action Research (ed. Coghlan, D. & Brydon-Miller, M.), pp. 583587. Sage.Google Scholar
Pirinen, A. 2016 The barriers and enablers of co-design for services. International Journal of Design 10 (3), 2742.Google Scholar
Prochner, I. & Godin, D. 2022 Quality in research through design projects: recommendations for evaluation and enhancement. Design Studies 78, 101061; doi:10.1016/j.destud.2021.101061.CrossRefGoogle Scholar
Raby, F. 2008 Critical design. In Design Dictionary: Perspectives on Design Terminology (ed. Erlhoff, M. & Marshall, T.), pp. 9496. Birkhäuser.10.1007/978-3-7643-8140-0_64CrossRefGoogle Scholar
Redman, S., Greenhalgh, T., Adedokun, L., Staniszewska, S., Denegri, S. & Co-production of Knowledge Collection Steering Committee 2021 Co-production of knowledge: The future. BMJ 372, n434.10.1136/bmj.n434CrossRefGoogle ScholarPubMed
Redström, J. 2021 Research through and through design. Artifact: Journal of Design Practice 8 (1–2), 16.CrossRefGoogle Scholar
Robertson, T. & Simonsen, J. 2012 Challenges and opportunities in contemporary participatory design. Design Issues 28 (3), 39.10.1162/DESI_a_00157CrossRefGoogle Scholar
Robinson, L. D., Cawthray, J. L., West, S. E., Bonn, A. & Ansine, J. 2018 Ten principles of citizen science. In Citizen Science: Innovation in Open Science, Society and Policy, 1st Edn. (ed. Hecker, S., Haklay, M., Bowser, A., Makuch, Z., Vogel, J. & Bonn, A.), pp. 2740. UCL Press; doi:10.14324/111.9781787352339.CrossRefGoogle Scholar
Rodríguez Ramírez, E. 2017 A postgraduate thesis model for research through design based on design criteria. The International Journal of Designed Objects 11(4), 1127; doi:10.18848/2325-1379/cgp/v11i04/11-27.CrossRefGoogle Scholar
Roggema, R. 2014 The design charrette. In The Design Charrette: Ways to Envision Sustainable Futures (ed. Roggema, R.), pp. 1534. Springer.10.1007/978-94-007-7031-7_2CrossRefGoogle Scholar
Rosenblatt, F. 1957 The Perceptron: A Perceiving and Recognizing Automaton, Report 85-460-1. Cornell Aeronautical Laboratory.Google Scholar
Rust, C., Mottram, J. & Till, J. 2007 AHRC Research Review: Practice-Led Research in Art, Design and Architecture. Arts and Humanities Research Council.Google Scholar
Rycroft-Malone, J., Burton, C. R., Bucknall, T., Graham, I. D., Hutchinson, A. M. & Stacey, D. 2016 Collaboration and co-production of knowledge in healthcare: Opportunities and challenges. International Journal of Health Policy and Management 5 (4), 221.10.15171/ijhpm.2016.08CrossRefGoogle ScholarPubMed
Sanders, E. B. N. & Stappers, P. J. 2008 Co-creation and the new landscapes of design. CoDesign 4 (1), 518; doi:10.1080/15710880701875068.CrossRefGoogle Scholar
Sanders, E. B. N. & Stappers, P. J. 2014 From designing to co-designing to collective dreaming. Interactions 21 (6), 2433; doi:10.1145/2670616.CrossRefGoogle Scholar
Scataglini, S. & Busciantella-Ricci, D. 2020 Toward a co-logical aid for research through co-design. In Advances in Additive Manufacturing, Modeling Systems and 3D Prototyping. AHFE 2019. Advances in Intelligent Systems and Computing (Vol. 975). Springer; doi:10.1007/978-3-030-20216-3_58.Google Scholar
Scataglini, S. & Busciantella-Ricci, D. 2021a Fab the knowledge. In Lecture Notes in Networks and Systems, pp. 119124. Springer; doi:10.1007/978-3-030-77040-2_16.Google Scholar
Scataglini, S. & Busciantella-Ricci, D. 2021b Research through co-design (RTC) and ergonomics. In Advances in Ergonomics in Design. AHFE 2021. Lecture Notes in Networks and Systems (Vol. 261) (ed. Rebelo, F.). Springer. https://doi.org/10.1007/978-3-030-79760-7_7.Google Scholar
Schön, D. 1983 The Reflective Practitioner: How Professionals Think in Action. Temple Smith.Google Scholar
Schwoerer, K., Keppeler, F., Mussagulova, A. & Puello, S. 2022 CO‐DESIGN‐ing a more context‐based, pluralistic, and participatory future for public administration. Public Administration 100 (1), 7297.CrossRefGoogle Scholar
Sevaldson, B. 2010 Discussions & movements in design research. FORMakademisk 3 (1), 835.10.7577/formakademisk.137CrossRefGoogle Scholar
Shroyer, K. E. & Turns, J. A. 2021 Research through design: a promising methodology for engineering education. In 2021 ASEE Virtual Annual Conference Content Access. ASEE.Google Scholar
Siodmok, A. 2016 Tools for insight: design research for policymaking, In Design for Policy (ed. Bason, ), pp. 221230; doi:10.4324/9781315576640-31.Google Scholar
Slattery, P., Saeri, A. K. & Bragge, P. 2020 Research co-design in health: a rapid overview of reviews. Health Research Policy and Systems 18 (1), 113.10.1186/s12961-020-0528-9CrossRefGoogle ScholarPubMed
Slimani, K., Da Silva, C. F., Médini, L. & Ghodous, P. 2006 Conflict mitigation in collaborative design. International Journal of Production Research 44 (09), 16811702.10.1080/00207540500445198CrossRefGoogle Scholar
Smeenk, W., Sturm, J. & Eggen, B. 2019 A comparison of existing frameworks leading to an empathic formation compass for co-design. International Journal of Design 13 (3), 5368.Google Scholar
Stapleton, A. 2005 Research as design-design as research. In DiGRA 2005: Changing Views: Worlds in Play, 2005 International Conference. DiGRA.Google Scholar
Stappers, P. J. 2007 Doing design as a part of doing research. In Design Research Now (ed. Michel, R.), pp. 8191. Birkhäuser.CrossRefGoogle Scholar
Stappers, P. J. & Giaccardi, E. 2017 Research through design. In The Encyclopedia of Human-Computer Interaction (2nd Edn.) (ed. Soegaard, M. & Friis-Dam, R.), pp. 194. The Interaction Design Foundation.Google Scholar
Steen, M. 2013 Co-design as a process of joint inquiry and imagination. Design Issues 29 (2), 1628.10.1162/DESI_a_00207CrossRefGoogle Scholar
Steen, M., Manschot, M. & De Koning, N. 2011 Benefits of co-design in service design projects. International Journal of Design 5 (2), 5360.Google Scholar
Stewart, S. 2014 Design research. In The SAGE Encyclopedia of Action Research (ed. Coghlan, D. & Brydon-Miller, M.). Sage.Google Scholar
Suberi, H. K. 2022 Research analysis of built environment as a system: implementing research through design methodology. Frontiers in Built Environment 7, 649903.10.3389/fbuil.2021.649903CrossRefGoogle Scholar
Swann, C. 2002 Action research and the practice of design. Design Issues 18 (1), 4961; doi:10.1162/07479360252756287.CrossRefGoogle Scholar
Sweeting, B. 2017 Design research as a variety of second-order cybernetic practice. In New Horizons for Second-Order Cybernetics, pp. 227238. World Scientific.10.1142/9789813226265_0035CrossRefGoogle Scholar
Taket, A., Crisp, B. R., Graham, M., Hanna, L., Goldingay, S. & Wilson, L. 2013 Practising Social Inclusion. Routledge.CrossRefGoogle Scholar
Tang, H., Tan, K. C. & Yi, Z. 2007 Neural Networks: Computational Models and Applications (Vol. 53). Springer Science & Business Media.10.1007/978-3-540-69226-3CrossRefGoogle Scholar
Tay, B. S., Cox, D. N., Brinkworth, G. D., Davis, A., Edney, S. M., Gwilt, I. & Ryan, J. C. 2021 Co-design practices in diet and nutrition research: an integrative review. Nutrients 13 (10), 3593.10.3390/nu13103593CrossRefGoogle ScholarPubMed
Taylor, R. 2017 Reflecting on RTD 2015: making connections to doing research through design. Design Issues 33 (3), 7992; doi:10.1162/desi_a_00453.CrossRefGoogle Scholar
Trischler, J., Dietrich, T. & Rundle-Thiele, S. 2019 Co-design: From expert- to user-driven ideas in public service design. Public Management Review 21 (11), 15951619.10.1080/14719037.2019.1619810CrossRefGoogle Scholar
Vargas, C., Whelan, J., Brimblecombe, J. & Allender, S. 2022 Co-creation, co-design, co-production for public health: a perspective on definition and distinctions. Public Health Research & Practice 32 (2), e3222211.CrossRefGoogle ScholarPubMed
Walsh, G., Druin, A., Guha, M. L., Bonsignore, E., Foss, E., Yip, J. C., Golub, E., Clegg, T., Brown, Q., Brewer, R., Joshi, A. & Brown, R. 2012 DisCo: a co-design online tool for asynchronous distributed child and adult design partners. In Proceedings of the 11th International Conference on Interaction Design and Children. ACM.Google Scholar
Wang, Z., Jiang, T., Huang, J., Tai, Y. & Trapani, P. M. 2022 How might we evaluate co-design? a literature review on existing practices. In DRS2022: Bilbao, 25 June–3 July, Bilbao, Spain (ed. D. Lockton, S. Lenzi, P. Hekkert, A. Oak, J. Sádaba, P. Lloyd); doi:10.21606/drs.2022.774.Google Scholar
Whiting, P. G. 2021 Design demarcation—A pointless and fruitless task…, she Ji. The Journal of Design, Economics, and Innovation 7 (1), 95103.Google Scholar
Wilde, D. 2020 Design research education and global concerns. She Ji: The Journal of Design, Economics, and Innovation 6 (2), 170212.Google Scholar
Wilde, D. 2022 Shitty food-based world-making: recasting human microbiome relationships beyond shame and taboo. Futures, 136, 102853.10.1016/j.futures.2021.102853CrossRefGoogle Scholar
Wilkie, A., Savransky, M. & Rosengarten, M. 2017 Speculative Research. Routledge; doi:10.4324/9781315541860.CrossRefGoogle Scholar
Zahariadis, N. 2008 Ambiguity and choice in European public policy. Journal of European Public Policy 15 (4), 514530.10.1080/13501760801996717CrossRefGoogle Scholar
Zamenopoulos, T. & Alexiou, K. 2018 Co-design as collaborative research. Bristol University/AHRC Connected Communities Programme. Open Research Online-ORO (downloadable on November 2nd 2023) http://oro.open.ac.uk/58301/.Google Scholar
Zamenopoulos, T. & Alexiou, K. 2020 Collective design anticipation. Futures 120, 102563; doi:10.1016/j.futures.2020.102563.CrossRefGoogle Scholar
Zimmerman, J. & Forlizzi, J. 2008 The role of design artifacts in design theory construction. Art 2 (1), 4145; doi:10.1080/17493460802276893.Google Scholar
Zimmerman, J., Forlizzi, J. & Evenson, S. 2007 Research through design as a method for interaction design research in HCI. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 493502. ACM.10.1145/1240624.1240704CrossRefGoogle Scholar
Zimmerman, J., Stolterman, E. & Forlizzi, J. 2010 An analysis and critique of research through design. In Proceedings of the 8th ACM Conference on Designing Interactive Systems - DIS ’10. ACM; doi:10.1145/1858171.1858228.Google Scholar
Figure 0

Figure 1. A general feedback-loop system.

Figure 1

Figure 2. The goal-seeking process. Left (system structure), right (pattern structure).

Figure 2

Figure 3. A graphical summary of the loops for designing the model.

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Figure 4. A co-model based on a closed-loop system in RTC.

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Figure 5. Graphical representation, variables and transfer function of the RTC model.