The Impact of Sociomaterials on Architectural Learning Processes in Virtual and Physical Design Studios

Abstract

Since architectural education has been integrated into academic campuses, the design studio has become its most prominent pedagogical approach. However, in the last three decades, advances in computer-aided design (CAD) and online communication led to the development of virtual design studio (VDS) formats, which gained prominence during the COVID-19 pandemic. VDS and physical design studio (PDS) are characterized by different sociomaterial environments, each offering unique learning opportunities. This study examines how these environments influence learning processes, analyzing two desk critique sessions—one conducted in a VDS and the other in a PDS. Our data, comprising video recordings and on-site observations, were analyzed and interpreted through a sociomaterial lens. The findings indicate that PDS facilitates more spontaneous interactions, allowing for the communication of complex ideas and better addressing misunderstandings compared to VDS, which is constrained by the limitations of digital communication platforms. This research provides both theoretical and pedagogical contributions. Theoretically, it demonstrates how architectural concepts emerge through sociomaterial interactions, framing architectural learning as material practice. In addition, it illustrates the role of sociomaterials in communicating complex ideas and shaping collaborative learning processes. Pedagogically, the findings emphasize the importance of creating rich sociomaterial environments that effectively support intended learning processes.

1. Introduction

Leveraging advancements in online communication technologies, the demand for online education has witnessed continuous growth (Martin et al., 2020). In the architectural education field, these technologies led to the development of online variants of the design studio, termed by William J Mitchell, “virtual design studio” (VDS) (Wojtowicz, 1995). Unlike traditional physical design studios (PDSs), where teachers and students meet in person in the same physical space, VDS involves participants located remotely and who communicate using online platforms (Kvan, 2001).

Since the 1990s, VDSs have proliferated in architectural education programs (Broadfoot & Bennett, 2003) and have become a “new normal” during the 2019–2022 COVID-19 pandemic (Iranmanesh & Onur, 2021). Considering other profound crises affecting mobility, such as climate change, political instability, and future pandemics (Bayne et al., 2020), we can assume that VDS and blended modalities of VDS and PDS will remain dominant (Peimani & Kamalipour, 2022).

VDS and PDS are characterized by different sociomaterial environments (Bridges et al., 2020; Orlikowski, 2009) and encompass different learning opportunities (Pelman & Zoran, 2022). The present study explores how the sociomaterial environment of VDSs and PDSs affects learning processes in architectural education. More specifically, this study addresses the following research questions (RQs):

RQ1: How does the sociomaterial environment influence the structure of desk critique sessions in architectural education?

RQ2: How are sociomaterials utilized to facilitate the communication of complex ideas in VDS and PDS?

The present study employs a sociomaterial approach (Fenwick, 2011; Orlikowski, 2007; Seitamaa-Hakkarainen et al., 2023) to analyze two “desk critique” sessions of an architectural project: The first was within a PDS setting, and the second was within a VDS setting. The two sessions had the same students and tutor and the same themes and took place on two consecutive days. Our data comprise 20-min video recordings of each session; these video recordings were part of an extensive ethnographic study on architectural education published previously by the authors (Pelman & Zoran, 2023). While the former study employed a macro-level inductive methodology and suggested general theoretical dimensions for informal learning processes, the current study employs a micro-analysis approach to examine the dynamics of material interactions, utterances, and body gestures in the learning process involved in architectural education.

2. Physical and Virtual Design Studios

The design studio is a signature pedagogy (Shulman, 2005) commonly used in formal academic architectural programs. Originally acquired on site in a master–apprentice model of education and later entered into academic campuses (Mewburn, 2011), architectural education has traditionally taken place in shared physical spaces, applying various methods of active learning (Robertson, 2018). Studio pedagogy employs project-based-learning (PBL), where students learn through engaging with architectural projects, addressing open-ended and “wicked” problems (Buchanan, 1992; Rittel & Webber, 1974). It also incorporates constructionism (Harel & Papert, 1991) and experiential learning (Kolb, 1984), where students learn by making tangible artifacts and engaging with the physical and social environments to construct knowledge (Corazzo, 2019; Dunn, 2007; Schön, 1987). Additionally, collaborative learning plays a significant role (Kvan, 2000) as students construct meaning through reflection in and on their actions with peers and tutors (Schön, 1987; Priya et al., 2020).

While traditional architectural studios exist in physical spaces, the virtual design studio (VDS) operates in virtual learning environments (VLEs). In this setting, physical spaces are replaced by collaborative whiteboards and social media, which include digital drawings, graphics, images, text, and hyperlinks. Instead of physical architectural models and drawings, virtual representations are used on these digital platforms. Face-to-face social interactions are substituted with synchronized online communication tools such as video conferencing and messaging platforms.

Although early studies on VDS typically focused on technological issues, more recent studies have put forward the effect of VDS on the social aspect of architectural learning processes (Dreamson, 2020). Researchers found that virtual communication platforms made it easy to engage with outside human actors, such as experts, consultants, and international students, enabling multicultural and professional exchange (Salama, 2015). Other research found that sharing teaching resources is made easier through online platforms; however, platform limitations can hinder communication between students and teachers (Mao & Queiroz, 2024). Other studies have found that VDS can expose social and economic inequalities among students, challenge the integrity of the student community, and sever the sense of belonging and emotional attachment to the studio framework and culture (Baloglu & Sezgin, 2021). In addition, a VDS was associated with students’ sense of isolation (Bakir & Alsaadani, 2021) and difficulties in identifying and addressing indicative signs of student’s needs and stress by teachers (Bernardo & Duarte, 2020; Fleischmann, 2019).

Less empirical research has been conducted on how moving to VDS has affected the material aspects of architectural learning processes. Disney et al. found that moving to digital learning environments led students to produce more digital outcomes (Disney et al., 2024). However, this shift may have drawbacks. For example, another study showed that 3D-printed models enhance students’ spatial cognition more effectively than their virtual versions, allowing learners to better understand materiality and spatial depth (Boumaraf & İnceoğlu, 2020). When comparing 3D printing with traditional and physical modeling techniques, Columbano and Dring noted that, although digital prototyping enables the representation of complex geometries, it can sometimes oversimplify material considerations. In contrast, traditional hands-on modeling methods provide students with a more profound comprehension of structural integrity and spatial relationships, fostering critical thinking in design (Columbano & Dring, 2010). Sinnamon and Miller further reinforced this by utilizing neuroscience and architectural theory to show that, unlike digital interactions, physical engagement can enhance cognitive clarity, creativity, and emotional engagement in architectural design (Sinnamon & Miller, 2022). However, Bernardo and Duarte pointed out that, even when students physically constructed architectural models, online communication made it challenging for teachers to assess material work and models, hindering meaningful reflection and feedback (Bernardo & Duarte, 2020).

Most prior research in design education has predominantly focused on either the social or material aspects, often treating them as separate dimensions. However, there has been a significant lack of studies that examine the combined impact of material and social interactions on learning processes, particularly in the context of VDS and PDS. Addressing this gap requires a micro-level analysis and a theoretical framework that treats social and material interactions as equally integral, avoiding the prioritization of one over the other in the study of architectural learning processes.

3. The Sociomaterial Approach to Education Research

Initially introduced in organizational studies, the concept of sociomateriality (Orlikowski, 2007) suggests that materials possess social and cultural meanings and, therefore, have both material and social affordances. Thus, the interaction with materials involves both their material properties and their social dimensions. For Orlikowski, no materiality exists independently of the social dimension: the two are intertwined and entangled. Therefore, materials are best described as sociomaterials (Orlikowski, 2007). The sociomaterial concept widens the view of materiality from the physical domain to the virtual one. The concept includes virtual models, virtual spaces, and digital interfaces, such as search engines and instant messaging protocols.

When sociomateriality was adopted in education research, it became an umbrella term for various theories. Fenwick (2011) encompassed four theories under this term: ANT (Latour, 2005), spatial theory (Lefebvre, 1991; Tuan, 1977), complexity theory (Byrne, 2002; Davis & Sumara, 2006), and cultural–historical activity theory (CHAT) (Leont’ev, 1978; Roth & Lee, 2007). Although deriving from different roots, these theories share some commonalities: (1) they all take whole systems into account and explore the web of entangled human and nonhuman action in knowledge creation; (2) they all trace interactions among humans and nonhumans while focusing on relations and mediations; and (3) they share a standpoint where learning is viewed as an “effect” of multiple interactions within sociomaterial assemblages incorporating human and nonhuman agents (Fenwick, 2011, pp. 6–10).

The sociomaterial approach aligns closely with the situated perspective in learning and cognition studies, as both shift the focus from individual cognition to broader systems encompassing interactions among different agents and their environments (Greeno, 1998). In design studies, the situated perspective has been widely employed to explore how meaning is constructed in specific situations and how social and material contexts regulate behavior (Craig, 2001). When focusing on meaning production, situated studies emphasize that meaning emerges through interactions with others and the environment rather than being intrinsic to symbols. Meanwhile, studies examining how social and material contexts afford specific behaviors stress the importance of learners engaging with or adapting these affordances to suit task-specific objectives.

In craft sciences, a branch of teaching education developed in Finland, Sweden, and Norway (Kokko et al., 2020), the concept of sociomateriality has been employed in studies of collaborative making to describe learning as an epistemic activity that involves both material and social entities (e.g., Seitamaa-Hakkarainen et al., 2023; Latour, 2005; Lefebvre, 1991). As a field of inquiry looking into knowledge creation through the process of materializing artifacts (Vega, 2018; Vega et al., 2021), scholars of craft sciences drew from such theories as pragmatism (Dewey, 1938) and constructionism (Harel & Papert, 1991). Learning is understood not as merely an outcome of reading cultural signs from objects, such as in iconographic studies or early studies in material culture (Hicks & Beaudry, 2010), but as an outcome of engaging with materials through workmanship.

In summary, sociomateriality is a theoretical approach that sees the social and material aspects as intricately intertwined, conceptualizing learning as the effect of multiple interactions between human and nonhuman agents. This approach has been effectively used in fields such as organizational studies, education, and craft sciences. However, very little research has been conducted on its application in design studies and architectural education.

4. Materials and Methods

The current study follows Hindmarsh and Llewellyn’s recommendation to integrate video analysis with field notes in sociomaterial research (Hindmarsh & Llewellyn, 2018). While many empirical sociomaterial studies rely on in-depth interviews that provide rich and insightful data, some scholars argue that these interviews often fail to capture the complexities of how materials are entangled in social practices (Feldman & Orlikowski, 2011; Leonardi & Barley, 2008; Jarzabkowski & Pinch, 2013). This limitation arises from the interviewees’ difficulties in recalling and fully describing intricate interactions. To address this issue, Hindmarsh and Llewellyn suggest combining video recordings and field notes, as the two data collection methods effectively complement each other. Field notes and real-time observations offer contextualized, on-the-spot insights, while video recordings enable a detailed analysis of how social and material elements interact in specific contexts.

4.1. Data Collection

The data for the current study were extracted from larger ethnographic research conducted between 17 December 2021 and 31 August 2022, in a master’s level architectural program situated on a forest campus near Barcelona. During this study, the first author actively participated in all formal and informal learning activities and gained access to digital and physical design process outcomes. The complete dataset includes 146 h of participant observations, 78 short video clips, 163 min of recorded interviews with various participants, and 70 gigabits of digital media, which encompasses syllabi, design briefs, presentations, and digital models.

This dataset was analyzed in a previous study (Pelman & Zoran, 2023) following Ash’s approach to macro-level analysis (Ash, 2007). In the current study, we further refine our analysis into intermediate and micro levels. At the intermediate level, we identified two critical events (Powell et al., 2003, p. 413), which were particularly relevant to our RQs. These events were virtual and physical desk critiques and were chosen due to their significant role in architectural design pedagogy (El-Latif et al., 2020; Goldschmidt et al., 2010; Olweny, 2020). During this event, a tutor visits the students’ desks to discuss their design ideas and how they were executed before then providing feedback. The tutor collaborates with the students to reframe their ideas, identify new directions, reflect on the consequences of these ideas, and sketch new design briefs and learning trajectories (Schön, 1987; Goldschmidt et al., 2010). The events occurred during a structural design module over two consecutive days with the same students and tutor. The students had already gained a strong understanding of the architectural project’s layout, massing, programmatic organization, and bioclimatic design strategy. The first event was conducted online on 15 February 2022, while the second was conducted in person on 16 February 2022.

Our primary data for the intermediate level of analysis consist of two 20 min video recordings (referred to hereafter as “full videos”) and field notes from both in-person and online desk critiques. To further support the analysis, the dataset also includes presentation files and still images. At the micro level, we adopted the deductive approach outlined by Derry et al. (Derry et al., 2010) to identify two video clips relevant to our second RQ. These clips are one-minute excerpts from the full videos, one drawn from the in-person session and the other from the online session.

4.2. Context and Layout

The desk critiques focused on an architectural project developed collaboratively by three students, who will be introduced by their nicknames: Suzan (F) and Bernard (M), both of whom hold bachelor’s degrees in architecture from the same university in Asia, and Alice (F), who comes from South America and also has a bachelor’s degree in architecture. The tutor, Eli (F), is a practicing architect with a strong interest and expertise in mass timber structural design. It is important to note that English was not the first language for all participants involved.

The first event represents a VDS scenario of an online desk critique session. It occurred on 15 February and was conducted remotely using the Zoom platform (see Figure 1). During the session, the students communicated with a tutor who was in a remote location while sitting together in a studio space. There were two conceptual rough models made from thin white cardboard and a more detailed small structural model representing the building’s structural cures and trusses (hereafter referred to as the small structural model). Additionally, a residential unit model made from wood sticks was also placed on the table.

Sketch drawings, tracing paper, markers, two laptops, and one tablet were also present. The first laptop was used to communicate with the tutor via Zoom and had a slide presentation open, which contained images of a larger model of a building segment (hereafter referred to as the large structural model; see Figure 2) and a virtual detailed model representing structural and architectural ideas (hereafter referred to as the virtual developed model). Drawings of typical floors and images of case studies addressing structural issues were also included in the presentation. The tablet had the same presentation open but with presenter notes available for the students. The second laptop remained closed during the session. The tutor sat near a table in her studio and communicated with the students using a tablet and digital pen.

The second event represents a PDS scenario of an in-person desk critique session. It took place on 16 February, one day after the online session, and focused on the same themes. The students and tutor met in person in a workshop space.

Before the session, the students arranged a table with four small conceptual models made from thin white cardboard. These models included the small structural model from the online session, now with added floor segments, and a new conceptual model representing a concept for building envelop design (see the envelop model in Figure 2). Additionally, the students presented a sizable physical model of a building segment at a 1:50 scale (hereafter referred to as the large structural model). Along with the physical models, two laptops were open. One had the virtual model presented, and the other had the slide presentation previously shown to the tutor in the online session.

4.3. Analysis

Each desk critique session was transcribed and broken down into units of analysis at the scale of an “interaction”. Interaction was defined as an event that involved spoken output from either the students or the tutor (interpersonal interaction), as well as any interaction with physical or virtual material in a physical or virtual space (material and technologically mediated interaction) (Mao & Queiroz, 2024). In instances of verbal interaction, the size of the unit could range from a few words to several sentences (Goldschmidt et al., 2010). When spoken outputs were accompanied by physical interactions with objects, the size of the analysis unit was determined by the length of the spoken sentences. However, in cases where interactions with objects occurred without accompanying spoken words, such as silent thoughts, the analysis unit was defined by the beginning and end of physical contact with the object.

However, while sociomaterial approaches view the world as a complex web of relations between similarly important entities (Hultin, 2019), a key challenge lies in determining which materials to include in the analysis and which to exclude (Fenwick & Edwards, 2010, p. 151). To address this, we adopted Hindmarsh and Llewellyn’s action-oriented approach to identify the materials most relevant to our analysis (Hindmarsh & Llewellyn, 2018).

Table 1. Materials relevant to the analysis following Hindmarsh and Llewellyn’s approach.

In-Person Session	Online Session
Large structural model	Images of the large structural model
Small structural model	Images of the small structural model
Envelope model	Images of the envelope model
Virtual model (through laptop 1)	Virtual model
Virtual plans (through tablet)	Virtual plans
Digital pen	Digital pen

provides an overview of the relevant materials for each session. In the online session, students interacted with virtual materials and images using computer screens and a mouse, while the tutor engaged with these materials on a computer screen and annotated them using a digital pen on a tablet.

The analysis was conducted in two phases, each addressing a different RQ. The first phase focused on RQ1 and aimed to reveal session dynamics and structural differences without delving into the specific types of interactions and their effects. To achieve this, we utilized an intermediate analysis level (Ash, 2007). We recorded each interaction in a spreadsheet, including its duration, the associated text (if relevant), visible actors involved, and themes discussed. We created a graphical timeline chart to visualize the structure of the conversations (see Figure 3). The online desk critique is shown at the top, while the in-person session is positioned at the bottom. Each session is divided into stages, which are labeled with letters and titles (from A1/2 to F1 or G2). The color scheme indicates who is leading the conversation at each point on the timeline.

The first analysis also served as a context for the second phase, which was focused on RQ2. In the second phase, we adapted Ash’s dialogic analysis (Ash, 2007), extending it beyond spoken utterances to include the material aspects of interactions, such as body gestures, tool use, and engagement with models, interpreting their roles within the conversation. We called this version of dialogic analysis “sociomaterial interaction analysis”. In both phases, we included screenshots from video recordings representing the analyzed moments to provide a clearer view of the material interactions and sociomaterial context.

Although the differences between macro-, intermediate-, and micro-level analyses were presented here in a chronological manner, the actual analysis oscillated between various perspectives and levels of detail. This approach allowed us to continuously contextualize and triangulate our findings for better verification.

5. Results

5.1. Phase 1: Sessions’ Structure

The online session started with a welcome and a sound and image connectivity check. Eli appreciated the hard work carried out by the students (stage A1). Then, the students presented their structural and architectural ideas through presentation slides (stage B1). During the presentation, the students or tutor occasionally stopped to ask and address questions. This was followed by four discussion stages (stages C1 to E1), each focused on a different aspect presented in the presentation. In the last stage (F1), the tutor reflected on the structural ideas discussed and offered other ideas. The tutor used a digital pen to draw ideas and structural suggestions on the shared screen using the annotation tool in Zoom.

During the in-person session, the tutor began by interacting with the physical models on the table, paying particular attention to the sizable structural model before moving on to the others. She used her hands and fingers to test the stability and measure the dimensions of the models to fully comprehend their properties (stage A2). At the end of this stage, the tutor said, “There is so much knowledge to gain from these models. They really help you to understand”. Later, the students presented their structural ideas and connected them to the discussion from the online session (stage B2); they did not follow their presentation slides but used them when needed for clarification. The tutor took on a more prominent role as the session progressed, with the students gradually decreasing their participation. The discussion mainly focused on topics raised by the tutor (stages C2–G2).

Upon comparing the two sessions, it was noted that the conversation in the virtual session was primarily dictated and structured by the sequence of slides in the presentation. In contrast, the conversation during the in-person session was influenced by the arrangement of materials in the physical space. As a result, the in-person session was less directed, encompassed a broader range of topics, and exhibited transitions between topics.

5.2. Phase 2: Sociomaterial Interaction Analysis

In this section, we have selected two excerpts: one from an in-person session and the other from an online session. We aimed to examine how sociomaterials were integrated into the discussions to foster a shared understanding of the architectural project. We selected one extract from the in-person session and another from the online session. In both instances, the tutor identified a potential design issue and collaborated with the students and sociomaterials to develop a shared understanding of the problem.

5.2.1. Extract 1: Online Session

In this extract (see Figure 4), Eli, the tutor, attempts to focus the students’ attention on a structural issue she has identified (line 43). She uses her digital pen to draw on the screen to indicate the places that need more structural support. However, she realizes that the virtual model image she uses does not provide a good context for her drawing and, therefore, requests that the students locate a suitable 2D plan for her. While searching for that plan in other slides, the students need to remove the sketches drawn by Eli (line 44) because they derive their meaning from the virtual model image that served as the background for Eli’s drawings. Suzan searches for the slide she believes would assist and asks Eli to verify that it has the necessary information (Line 45). Eli confirms that this slide includes the required plan, marks the plan with her digital pen to draw the student’s attention to the correct location on the slide, and then marks the area where she identifies the problem. Then, she marks new pillars on the plan, stating, “So you can have pillars, these, here, under the trusses. Yeah, you can have some pillar there” (Line 46).

Before the session, the students designed a slide presentation to convey certain structural and spatial ideas. However, the presentation’s design does not provide an appropriate context to support Eli’s communication requirements. This shortfall obstructs her ability to instruct the students on a potential solution to a structural issue.

Eli suggests adding extra pillars to reinforce the building’s structural stability. However, to communicate the location of the added pillars, Eli needs a contextualizing object-specific 2D plan that would help identify the exact location of the pillars in relation to other building elements. This highlights the limitations of using only words to communicate spatial ideas and to effectively support the cognitive processes related to them.

In this meaning-making process, words and objects are interconnected, and both undergo changes. As Eli adds new marks to the plan, it evolves and changes shape, leading to new spatial and structural scenarios and design affordances. The evolving plan also gives new meanings to the words. Adverbs like “here”, “it”, and “there” are redefined based on the developing situation in the plan. Similarly, words like “problem” acquire new meanings as the structural and spatial ideas in the conversation evolve.

The described dynamics between words and objects are made possible in virtual meetings through digital applications, such as screen sharing and digital annotations. What appears to be unique to the virtual session is how materials are sought, identified, and reshaped to cater to Eli’s need for the correct context. These processes are influenced by the design and characterization of the software, as well as the nature of online communication. Because Eli lacks control over the presentation, she can only verbally guide the students toward what she is seeking rather than actively participating in the search for the proper contextual object she needs. Constrained by the presentation and communication software limitations, the students frequently ask questions such as, “This one, can you see it?” (line 45) or “Can you hear me properly?” (line 46). This makes the activity less effective.

5.2.2. Extract 2: In-Person Session

In the second excerpt (see Figure 5), Alice indicates a specific area on a virtual model to discuss a structural issue. However, Eli concentrates on the larger structural model and suddenly realizes that the layout of the residential units she sees differs from what she understood from the virtual session (lines 44–45). This new understanding is because of the 3D physical model’s superior ability to represent spatial characteristics compared with the 2D images shown in the virtual session.

Once the students became aware of the confusion, they collaborated to rectify the error (line 46). They reorganize the available materials for Eli and use verbal explanations and physical gestures to clear up the misunderstanding (lines 47). Bernard looks for the correct blueprint on the tablet and shows it to Eli. Suzan switches the slide on the laptop to a virtual 3D model, while Alice points out locations on the virtual model that provide context to Bernard’s explanations.

In this instance, two processes occur concurrently. The first process is understanding the layout of the residential units, while the second is identifying and organizing the necessary materials to aid the first process. Compared with the online session, these processes are executed more swiftly and effectively because the students and Eli work in tandem and simultaneously utilize multiple resources to convey their ideas. They employ their bodies using physical gestures to draw attention to specific locations and demonstrate size and relationships. They reposition both physical and virtual objects to make new spatial information readily available and contextual. Interestingly, this complex reorganization of the sociomaterial environment is carried out intuitively, without any verbal planning or negotiation.

5.3. Summary of Results

The results emphasize the critical role of sociomaterial interactions in architectural learning processes and how they shape collaborative design efforts. In Phase 1, online discussions were structured around slide presentations, which were limited by the capabilities of digital tools. In contrast, in-person sessions benefited from the physical arrangement of materials, fostering broader and less linear conversations.

In Phase 2, the analysis of online sessions highlighted the limitations of virtual environments in conveying complex spatial ideas. On the other hand, the analysis of in-person sessions demonstrated the effectiveness of physical models and gestures in resolving misunderstandings and enhancing spatial cognition. The physical presence of participants allowed for the intuitive reorganization of materials and communication through embodied practices, leading to more efficient and contextualized problem-solving.

Overall, the findings underscore the significance of sociomaterial environments in shaping cognitive and collaborative processes in architectural education. They reveal that while digital tools can support certain aspects of design discussions, physical and embodied interactions offer richer affordances for understanding and addressing complex design issues.

6. Discussion

The main goal of the desk critiques is to act as a framework for a collaborative reflection on the students’ work (Goldschmidt et al., 2010). To allow this, the students must first communicate their design ideas to the tutor and ensure a common understanding of their design proposals. Based on this understanding, the students and tutors can raise questions and concerns about design ideas and suggest possible directions for new design investigations.

During desk critique events, various actors are involved, including students, tutors, physical and digital objects, and the broader spatial environment. From a sociomaterial perspective, both the students and tutors are part of this environment and interact based on its affordance. The present study explores how the sociomaterial environment of VDS and PDS affects two aspects of the desk critique event: the first is the structure of the conversation (RQ1), and the second is the communication of complex ideas (RQ2).

6.1. RQ1

Our analysis revealed notable differences in how conversations progress during online versus in-person desk critique sessions, influenced by the sociomaterial environment. In online sessions, interactions were limited by the slide presentation format and the characteristics of the Zoom platform, which restricted engagement with materials. In contrast, in-person sessions allowed for fluid navigation between physical and virtual models and plans, promoting a better flow of ideas and information.

This finding aligns with earlier studies, such as those by Clayton and Al-Qawasmi, which noted that digital mediums often disrupt the natural flow of discussion and risk cognitive overload (Clayton & Al-Qawasmi, 2000). While this research dates back over two decades, our findings suggest these challenges persist with contemporary platforms. Moreover, while Clayton and Al-Qawasmi’s study focused mainly on social and technological interaction, the sociomaterial perspective allowed us to examine more closely how material interactions affect the discussion and the ability to communicate complex ideas. This aspect is explored further in RQ2.

6.2. RQ2

We have identified several ways in which sociomaterials are utilized to facilitate the communication of complex ideas. First, they store information by carrying graphical symbols and spatial relationships, such as the size, location, and proportions of their elements. Second, they can offer embodied experiences that contribute to theoretical understanding. For instance, during an in-person session, the tutor physically engaged with the models by testing them structurally, measuring their elements with her fingers, and observing them from different angles. Even though she had already seen the models’ representations in an online session, the physical interaction provided experiential knowledge that was not available when engaging with digital representations. Third, certain sociomaterials can support cognitive processes better than others by organizing and visualizing information to create new relationships that are otherwise difficult to analyze. For example, when the students needed to understand the spatial characteristics of the residential units rather than their structural properties, they changed the sociomaterial environment by incorporating objects that supported this process.

Recent developments in cognitive science support these observations by providing possible explanations for how interaction with materials is included in cognitive processes.

The concept of embodied cognition (Borghi & Pecher, 2011) posits that cognitive activities are deeply intertwined with sensory experiences, with each influencing and shaping the other. This idea is exemplified in Sennett’s seminal work, The Craftsman, where he demonstrates how physical interactions with materials foster the development of cognitive skills and open pathways for new learning opportunities (Sennett, 2009).

Similarly, the extended mind concept (Clark, 2008) argues that materials can replace internal cognitive components and drive, shape, and restrain reasoning processes (Clark & Chalmers, 1998). For example, Latour highlights how various visualizations—such as drawings, diagrams, maps, graphs, and models—offer distinct cognitive affordances and limitations, shaping scientific understanding and development (Latour, 1986). An architectural model, for instance, organizes spatial information in a way that represents relationships between objects in space, a task that would require significant mental effort if conveyed solely through text. Hutchins underscores this point by explaining that well-designed objects reduce cognitive load by performing part of the necessary computational work for the cognitive process (Hutchins, 1996, p. 173).

However, reducing mental load is not the sole way materials enhance cognition. Materials can also evoke associations and contextualize information, eliciting new meanings that may redirect discussions or thinking processes in unexpected ways. These associations can emerge from cultural symbols embedded within the material (Tilley et al., 2000), connotation elicited by individuals (Karana, 2009), or meanings that evolve within new contexts.

In our study, we witnessed that even though the sociomaterial environment may be designed to support a particular cognitive process, such as evaluating the structural behavior of a particular design, engaging with sociomaterials can uncover alternative design features and lead to different thinking paths. This was shown when the tutor interacted with the structural model and suddenly realized that she and the students had different understandings of the layout of some apartments. This led to a discussion about the functional aspects of space.

Sociomaterials in architectural education are not static entities; they dynamically change their forms and affordances throughout the design and thinking processes. When students or tutors engage with models or drawings in exploratory ways, cognition evolves in tandem with these materials (Craig, 2001). For instance, when a tutor modifies a plan or adjusts an element in a 3D model, the change redefines the context in which other elements are understood, creating new affordances that inspire fresh ideas. Roth explained this co-evolution of material and cognition by introducing the concept of “becoming aware” (Roth, 2015). This concept was offered as an alternative to the constructivist explanation of learning, which assumes learners work toward predefined knowledge goals. Instead, Roth illustrated how manipulating materials can spark moments of insight and demonstrated the co-evolution principle through the work of Watson and Witkowski, who discovered the structure of DNA while building its physical model (Watson & Witkowski, 2012).

Lastly, interacting with sociomaterials elicits their social dimensions, which can also be used to facilitate communication. This can be explained by viewing architectural representations as metaphors, or, more accurately, “material metaphors” (Tilley, 1999). In linguistics, conceptual metaphors are cognitive mechanisms that help us understand abstract concepts by relating them to more concrete experiences. As proposed by Lakoff and Johnson (1980), they involve projecting meaning from one domain (source domain) to another (target domain), typically in our thought processes. Material metaphors (Malafouris, 2013) work similarly, but they use materials instead of words as containers for projected meanings. For instance, when Alice said, “This is like a mezzanine” (Figure 5, line 46), she indicated that the higher living units in the model include a mezzanine and, by extension, different living experiences than the lower living units. Here, the differing floor heights in the model (target domain) can be seen as representing distinct living conditions in the future project (source domain).

The concept of material metaphors can help us understand the mechanism by which material’s social dimension is communicated during material interaction. For example, when a small wooden stick (a target domain) was identified as a truss (source domain) (line 47), it represented not only its structural role but also the social and financial forces that influence its dimensions, transportation, and installation. This was also observed at 04:13 min into the online session when Bernard said, “So we try to use the strongest one and also consider how to transport it. Right now, we are still not sure”.

6.3. Learning as a Material Practice

Architectural education is deeply rooted in material practices, yet its learning processes are predominantly framed within socio-constructivist paradigms, often overlooking the critical role of materials and material practices in generating knowledge.

In socio-constructivism (Vygotskij & Cole, 1981), learning is understood as the development of concepts within a sociocultural context, where knowledge is treated as a set of discrete units that can be acquired, accumulated, and constructed. This perspective, often described as “learning as acquisition” (Sfard, 1998) was challenged by researchers who emphasized the situated nature of learning. For instance, Lave and Wenger (1991) studied communities of practitioners in non-academic settings, demonstrating that learners develop knowledge and skills through active participation in communities of practice (p. 29). More recently, Salama (2015) built on this perspective in his studies of architectural pedagogy, developing the trans-critical pedagogical model, which underscores the active and participatory nature of architectural learning. (p. 311).

While the above scholars primarily focus on social dynamics, other situated studies within design disciplines extend the discussion beyond the social realm to include material engagements. These studies argue that learning occurs within complex contexts that encompass both social interactions and material engagements (e.g., Dunn, 2007; Craig, 2001; Pons-Valladares et al., 2015; Sukkar et al., 2024). However, many of these studies still adhere to a dichotomous view, treating the social and material as separate entities.

In contrast, the sociomaterial approach challenges this separation, enabling an exploration of how social and material interactions are deeply intertwined in situated learning practices (Orlikowski, 2007). Through the sociomaterial approach, this study demonstrates how architectural concepts arise and evolve through interaction with sociomaterials, rather than being discrete units of knowledge to be “gradually refined and combined” (Sfard, 1998, p. 5). During the development of architectural projects, cognition co-evolves with drawings and models, emphasizing their essential role in non-declarative knowledge processes. This dynamic is analogous to the role of writing—as a material practice— in shaping declarative knowledge (Barthes, 1977). Just as conceptual ideas are shaped through writing, spatial ideas, and material understanding are born through the practices of drawing and model making.

Sociomaterials evolve during the design process, continuously reshaping their affordances and influencing cognitive development. Interactions with sociomaterials generate new insights, reveal unexpected design features, and create metaphorical connections that link social and material meanings, deepening understanding beyond the immediate design context. Learning, therefore, emerges not as an abstract acquisition of knowledge but as a performance (Bekerman & Zembylas, 2023), as sociomaterial practice embedded within a community of practitioners (Wenger, 1998).

6.4. Limitations

This study provides valuable insights into the role of sociomaterials in architectural education. However, it is not without its limitations, which should be considered when interpreting the findings. The research focuses on two desk critique sessions within a single architectural design course, offering rich qualitative data but limiting its ability to capture the wider variety of sociomaterial interactions across different contexts, disciplines, or institutions. Moreover, the sessions occurred within a short timeframe, which constrained the observation of long-term learning dynamics and the cumulative effects of repeated interactions. While desk critiques are a significant element of architectural education, this focus does not encompass the full spectrum of pedagogical formats, such as group discussions, studio workshops, or final critiques. Additionally, the virtual session relied on specific online tools and platforms available at the time of the study. As digital communication technologies evolve rapidly, newer tools and features may offer different insights into sociomaterial interactions.

Finally, as with any ethnographic research, this study’s observations and interpretations are subject to the influence of the researchers’ presence and perspective. Despite employing a systematic and data-driven approach, inherent subjectivity exists in interpreting the interactions and deriving conclusions.

6.5. Future Research

Future research should adopt longitudinal designs to examine how sociomaterial interactions evolve and impact learning outcomes over time. Exploring diverse educational contexts, disciplines, and participant demographics would enhance generalizability and offer richer comparative insights. Additionally, studies should investigate other instructional formats, such as workshops and group discussions, to understand the role of sociomaterials across different educational settings.

Emerging technologies, like augmented reality (AR) and virtual reality (VR), should also be studied as they present promising avenues to bridge physical and digital environments, addressing VDS’s current limitations. Moreover, advancements in AI technologies present a transformative shift in the design landscape. AI can now replicate social actors, generate objects, and autonomously create new entities without human input. This evolution redefines digital entities, transitioning them from tools directed by humans to independent agents capable of generating new designs and systems. However, AI-generated entities raise fundamental questions about the sociomaterial concept itself, particularly whether AI-generated objects, devoid of direct human intervention, retain the social meaning described in traditional material culture and sociomaterial theories. Future research must address these challenges, reexamining foundational assumptions to adapt sociomaterial frameworks for an AI-influenced design environment.

6.6. In Summary

The present study investigated how sociomaterials influence architectural learning processes by comparing interactions during two desk critique sessions: one held in a VDS and the other in a PDS. It examines how sociomaterials influence each session’s structure and the communication of complex design ideas. We found that PDS offers a richer sociomaterial environment that enables spontaneous interactions and a more fluent flow of ideas compared with the VDS, which was limited by the digital communication platform and structured slide presentations. These limitations in a VDS result in fewer opportunities for experiential knowledge and less effective handling of misunderstandings.

The present study suggests that materials are active participants in the learning process, storing information, providing embodied experiences, and influencing cognitive pathways. Interactions with materials can generate new insights, reveal unexpected design features, and create metaphorical connections that expand understanding beyond the immediate design context. In addition, sociomaterials are not static; they evolve and change their affordances during the design-thinking process.

The research offers both theoretical and pedagogical insights. Theoretically, it frames learning as a material practice rather than the mere acquisition of abstract concepts, demonstrating how architectural ideas emerge through sociomaterial interactions and emphasizing the performative nature of learning. This perspective challenges traditional notions of conceptual knowledge as static and incrementally refined, proposing instead that design ideas are co-constructed through material engagement. Pedagogically, the findings highlight the importance of cultivating rich sociomaterial environments that align with intended learning outcomes. They also inform the development of innovative virtual learning environments (VLEs) that combine the strengths of PDS and VDS, fostering blended instructional modes to enhance learning experiences.

Future research should address emerging technologies, like augmented and virtual reality, for their potential to address the limitations of currently available online interfaces.

In addition, advances in AI technologies should be critically studied by re-examining foundational assumptions to adapt sociomaterial frameworks for an AI-influenced design environment.