Perception to Virtual Design Studio in the Initiation, Realization and Reflection Phase: The Faculties and Students Perspective

ABSTRACT

The study examines virtual design studio pedagogy in regional settings, providing a comprehensive understanding of the experiences of faculty members and students as they adapted to the virtual design studio due to the COVID-19 pandemic. The research focused on B.Arch., an undergraduate program affiliated with the University of Calicut, Malappuram, Kerala, India. A survey-based cluster sampling approach was made use of. The survey questionnaire collected information from faculties and students on various aspects of the virtual discourse, and SPSS software was used to analyze the data. The Mann-Whitney U test (non-parametric test) was employed to compare adaptation and acceptance levels of virtual design studios between faculties and students. The results indicated differences in adaptation and acceptance levels between the two groups. The research also outlines the various stage-wise phases of the virtual design studio model. Further explores the future of architecture studio pedagogy in a post-Covid scenario, with emphasis on hybrid mode, which could be an area for future research.

KEYWORDS:

• Architecture studio pedagogy
• virtual design studio
• survey-based research
• hybrid pedagogy
• AI process schema

1. Introduction

The design studio is considered the integral core of architecture pedagogy. It is the epicenter of design discourse and facilitates inventive exploration and innovation. The domain of architecture education is deeply rooted in educational principles that advocate design studio-based pedagogical approaches for knowledge and skill development. Collaborative and situated learning studio culture further facilitates experiential learning discourse. This has led to the development and encouragement of a collaborative process that involves a participatory approach. This empowers students to interrelate, connect, communicate, and deliberate in design studios with their peers and their instructors. Collaborative learning establishes its superiority over individualistic and competitive modes of learning. Isolated students do not learn as much or as well as students who are embedded in a network of informal social relations (Rau and Heyl 1990). The instructional strategies in the design studios are based on educational theories which enable students to construct and develop requisite knowledge and skills. The practice of architecture requires knowledge of a variety of fields on the part of its practitioner and involves their integration into a composite whole (Mehta 1978). Compared to typical classroom scenarios, studios are active sites where students are engaged intellectually and socially, shifting between analytic, synthetic, and evaluative models of thinking in different sets of activities (drawing, conversing, model-making) (Dutton 1987). This type of pedagogical approach supports active learning over passive learning. Moreover, it can be described as learner-centric, rather than teacher-centric one. Instructors foster the learning experience by encouraging exploration, critical thinking, innovation, and problem-solving. The pedagogical setting often replicates a situated learning context that emulates the settings of a professional architectural studio. Such settings are fundamental in defining the contextual framework in which learning takes place. It promotes learning outcomes that focus on process, involving both individuals and groups, alongside the application of skills (Grant and Manuelif 1995). Such approaches endow architecture students with the requisite know-how for meeting the highly knowledge-based and skill-based requirements of the practice of architecture. Progressive developments in the field of architecture education have revolutionized the nature and structure of the design studio pedagogy. The advancements in the field of information and communication technology have enabled institutions to use educational technology as part of the design pedagogy to accomplish learning objectives extensively. This paradigm shift over time has paved the way for the emergence of digital pedagogies; use of contemporary digital technologies in teaching and learning (Croxall 2013). broadly defines digital pedagogy as the use of electronic elements to enhance or change the experience of education.

In recent times the practice of architecture has become more collaborative necessitating aspirants to be more informed. From the perspective of the commercial practice of architecture, the need for a competitive upper hand between firms has created a vibrant drive for coupling architecture expertise at a scale never seen before. As a result, the outlook of the practice of architecture has taken a new dimension. This coupled with the development of Building Information Modelling (BIM) and increasingly distant professional collaborations in the Architecture, Engineering, and Construction (AEC) industry, necessitates the need to prepare students with the essential skills of online collaboration (Jonesand Dewberry 2013). Thereby recasting the nature of competency levels desired from fresh graduates. Education is a training of the future professional – a strictly positivistic educational approach. The student has to acquire the objective knowledge and skills that are required by the profession. Computing education here is a linear cause-effect acquisition of skills with digital tools that are required by the market (Jakimowicz 2018). The virtual design studio-based training is seen as a means to empower students to develop collaboration, networking, and design management skills. Thereby bestowing them with the fundamentals to work on a building design, simultaneously together (synchronously) or separately (asynchronously), while the latest state of the design would always be available to all team members virtually.

As a result, the conservative design studio pedagogy is being gradually replaced by the virtual design studio in the virtual ecosystem for effective mentoring. In general virtual design studio (VDS) refers to a format of teaching and learning where participants’ communication and collaboration are mediated mainly through asynchronous digital tools, thus, overcoming geographical or spatial barriers (Rodriguez, Hudson, and Niblock 2018). The virtual design studio offers bidirectional association thereby enhancing possibilities for online discourse and dialogue, encourages peer interactions, meaningful knowledge and skill development, and encourages self-directed learning, efficient time management, and flexibility to name a few enriching associative factors. Since 2020 in light of the societal impact of COVID-19, not only do online collaboration capabilities appear to be essential for future architects, but online studio education is also needed by most architectural schools (Yu et al. 2021a).

2. Theoretical background

The passive shift related to the perception of the learning environment and the rising need to empower learners with virtual collaboration requirements in the profession has brought about pioneering changes in the outlook of architecture pedagogy. The most noticeable and relevant shift is the promotional and explorative drive in favor of the transition from direct face-to-face interaction to the virtual discourse format of the studio. Virtual has not yet been referred to as an immersive Virtual Environment (VE) per se. Instead, students used quasi-virtual environments by the choice of design and communication media (Schnabel et al. 2001). Since the mid-1990s, virtual design studios (Kolarevic et al. 1998; Kvan et al. 2000; Wojtowicz 1995) have been established in the architecture and design domain internationally. A virtual design studio can be defined generally as a type of studio that investigates possibilities offered by digital media and virtual environments to expand studio space beyond physical and time limits (Pektaş 2015). There by enabling the realization of cross-cultural and cross-disciplinary collaboration via virtual space. With the advancement of global communication facilities and the user-friendliness of online web-based technology, the virtual design was used for collaborative pedagogical pursuits involving several architecture schools globally.

In such a studio, students from geographically separated educational institutions work together using a computer-mediated environment as if they were part of one design studio in one physical space. The location of the users becomes irrelevant because the VDS is an electronically distributed workplace, and users can enter this virtual place by being connected to the world wide web (Salama and Wilkinson 2007). However, it is observed that such experimentations have not altered the fundamental settings the material space of the design studio offers (Corazzo 2019) identified six key themes that the material space of the design studio enabled: a place to make artifacts; a bridge between academic and professional contexts; to provide meaning to educational activities; to enable or constrain experience and interaction; to provide the background to learning; and to shape disciplinary identities. Broadly we can perceive the virtual design studio structure to be similar to that of a conventional design studio extrinsically, made up of the following three phases namely the Initiation Phase, Realization Phase, and Reflection Phase (Table 1). However the major diversifying aspect is that the design studio is hosted in a virtual ecosystem and all the participants access the studio remotely using virtual connectivity. All the stages of the design development process are conducted virtually making use of Information Communication Technology (ICT) based aids. This makes the actual implementation of the virtual instruction system different from that of a physical design studio.

Table 1. Comparision physical design studio versus virtual design studio.

Teaching/Learning Activity	Conventional Design Studio (Physical Design Studio)	Innovative Design Studio (Virtual Design Studio) Relevant Parameters
Studio Project Initiation and Interactions	Face To Face Interactions	Online Interactions	Initiation Phase Access to Essential Facilities &Technology Individual Profile Status Design: Teaching & Learning: Process and Resources Realization Phase Pedagogical Settings Teaching and Learning Effectiveness Level Nature of Interactions Reflection Phase Assessments/Appraisal Levels Peer Learning and Related Matters Studio Culture Skills & Behaviour
Site Study	Field Trips	Virtual Site Visits
Case Studies	Study Trips Interaction In Person With Project Architects/Consultants	Virtual Tour Interaction Online With Project Architects/Consultants
Design Studio	Institutional Studio Settings	Virtual Eco-System Based
Project Work Framework	Brief Specification Based - Individual Or Group Activity In Physical Design Studio Settings	Brief Specification Based - Individual Or Group Activity In Virtual Eco System
Collaborations And Peer Interactions/Learning	Physical Live Contact Level	Remote Virtual Contact Interaction
Reviews	In-Person Project Presentations	Remote Project Presentations
Studio Pedagogue Interventions	Expert Tutorials/Studio Mentorship/In-Person Review And Feedback	Expert Tutorials Online/Studio Mentorship/Review and Feedback - Virtually
Portfolio	In-Person Submissions and Presentations	Virtual Submissions and Presentations
Prototypes	Physical Prototypes	Virtual Prototypes

The studio instructors are at the helm of the pedagogical discourse in a studio, but with the transition to virtual design discourse, the onus of facilitating and coordinating the online exchange has also become their responsibility. Advancing technology alone will not create better student outcomes; developing fully online architectural design learning experiences requires a lot of effort from the instructor, who is not always well prepared for this task. Most instructors as well as students need time to adapt and adjust when they are confronted with new technological tools and teaching methods (Fleischmann 2020). This necessitates approaching pedagogical practices in the virtual ecosystem from innovative and divergent perspectives. Aided by systematic and grounded theory-based research about architecture design cognition and development, rather than perceiving the virtual design pedagogy as another platform for discourse using conservative approaches in the virtual realm.

3. The new normal

The COVID-19 pandemic has led to a significant transformation in architecture education, with a shift to virtual platforms. This has created a need to examine virtual design studios from a broader perspective and integrate them locally. The integration of virtual learning into architecture pedagogy is essential for effective pedagogical discourse in the current context of computer-based distance education. This shift presents both challenges and opportunities for the field of architecture. Therefore, a comprehensive review of pedagogical approaches concerning the implementation of virtual design studios is necessary. In concurrence to gain a thorough understanding of virtual design studio pedagogy, a comprehensive review was conducted of recent research publications and reports spanning from 2020 to 2022. These studies are categorized and summarised to provide insights into various aspects associated with the shift to online teaching, including the experiences, challenges, and potential benefits faced by both students and educators. Additionally, a few of these publications also highlight novel pedagogical concepts and ideas in the emerging field.

A study was conducted to examine the impact of COVID-19 on studio teaching in architectural institutions in the United Kingdom. The research involved 798 students and 120 teaching staff from 29 schools of architecture. The findings emphasized the challenges faced by schools of architecture during the pandemic, such as the negative impact of remote learning on peer networks and support, compromised quality of interactions, and the necessity of resource accessibility for successful remote learning. However, the study also highlighted the practical advantages of remote teaching and the potential for new teaching opportunities (Wright and Grover 2020). Another auxiliary study involved educators in India to assess the transition process to online teaching. The research revealed low satisfaction among educators regarding the effectiveness of online teaching, particularly in design studios. The findings emphasized the importance of increased engagement with digital tools and representational software on integrated platforms. Participants also expressed consensus about the future potential of blended learning, suggesting the development of an integrated framework and curriculum for architecture education in India (Varma and Jafri 2020).

A supplementary study featuring an online survey of architecture students in Jordan examined the perceptions of online design studios. The findings indicated that students had uncertainties and concerns about their online learning experience, including a desire for more guidance and support. Technical factors and personal situations during the pandemic were identified as significant challenges, impacting students’ engagement in online design studios. The tutors’ lack of expertise in online teaching and the limitations of peer interaction were identified as additional challenges. Collectively, these factors contributed to a more challenging experience in the online design studio for the students (Al Maani, Alnusairat, and Al-Jokhadar 2021). Another study gathered students’ opinions on online design studio education in Turkey. The study revealed that students identified the use of digital tools as a significant advantage of online studios. With the necessary tools and opportunities for self-expression, students demonstrated the ability to work efficiently even in a distance education setting (Ceylan et al. 2020). Furthermore, a study among students in consecutive virtual design studios associated with major universities in Cyprus highlighted that students showed improvement in independent research and learning new software through VDS. However, there was a decrease in informal peer learning, underlining the need for a more immersive social experience in VDS (Iranmanesh and Onur 2021).

Assessment of the effectiveness of online teaching in architecture courses in three Australian Universities through surveys and interviews conveyed that students generally had positive learning experiences in online courses, primarily due to their flexibility. However, improvements were needed in online teaching methods and tools for architecture studio courses to enhance student engagement (Yu et al. 2021 b). A different study assessed the performance of design students in the UAE who were engaged in online distance learning during the COVID-19 lockdown. The focus was on their negative emotions and how these emotions impacted their creativity and design performance. An online survey was conducted with the students, and focus group interviews were held with the instructors. The findings revealed that first-year students, with limited design experience, experienced higher levels of anxiety, which impacted their design practice and learning performance. However, despite the challenges, first-year students still displayed creativity in their projects. Fourth-year students also experienced high anxiety levels but expressed greater satisfaction with their performance compared to first-year students (Amro 2021). A supplementary comparison survey-based study made use of feedback from students of the Department of Architecture at Turkish and Spanish universities, the comparative results were evaluated using the path analysis method. The study generated two path analysis diagrams, one for each university, and presented a comparative analysis to elucidate the relationships among the selected architecture design competence components (Kavakoğlu et al. 2022).

Another study from Iran investigated the challenges faced by architecture students during distance learning and explored their perceptions of virtual learning experiences. The study recognized a multitude of factors that influenced students’ perspectives, encompassing aspects such as the design process and communication skills, self-directed learning, digital sketching, drafting, modeling, and presentation, personal connections and experiences, technical equipment, and resources, as well as tutorials and assessments. The research proposed a model for redefining education based on a sustainable design pedagogy framework. An e-studio was suggested as an activity-oriented space to foster interaction, connection, and creativity. The proposed model necessitates the adoption of new learning strategies and tactics (Asadpour 2021). Along similar lines, a study in India investigated the impact of the abrupt shift from conventional methods to virtual learning in the realm of architectural education in India. Utilizing a multidisciplinary approach, the research aimed to gain a comprehensive understanding of diverse aspects within a pedagogical framework. The study proposed the confluence approach as a theoretical concept for organizing virtual studio pedagogy in architecture, particularly in times of uncertainty (Khan and Thilagam 2021).

Research in Egyptian universities employed various approaches, such as an online survey, semi-structured interviews, observations, and literature reviews. In light of the COVID-19 pandemic, the study introduced a theoretical framework for examining blended learning (BL) approaches in architectural education. This framework is based on the continuum of blended teaching and learning, the increasing use of online delivery methods and technology integration, and the evolving response to the pandemic (Megahed and Hassan 2021a). Another auxiliary study employed a mixed-methods approach, collecting qualitative and quantitative data through a questionnaire-based survey involving 245 students. The survey focused on assessing students’ learning experiences across five dimensions, considering both positive aspects and challenges. The findings revealed that students’ overall experiences were generally neutral but tended toward the positive side. Three key factors were identified as influencing students’ learning experiences: their reliance on educational technologies, the stage of architectural education they were in during the lockdown, and the quality and timing of feedback they received. Although challenges were present during the transition to online learning, these difficulties may have motivated students to take greater responsibility for their knowledge construction (Bakir and Alsaadani 2022).

The challenges faced by traditional education in architecture and urbanism due to the COVID-19 pandemic were further critically explored by a renowned academician. By providing an evolutionary account of how design education in these fields has evolved, examining the current challenges, and exploring opportunities to address them in light of the pandemic. The analysis followed a chronological approach, studying design pedagogy from historical schools to alternative approaches in different decades. The research discussed the legacy model, its influences, and resistance, as well as groundbreaking alternative pedagogies. It also highlighted the strengths of process-based, learning-by-making, and social construction-based pedagogies. By scrutinizing the consequences of the COVID-19 condition and the transitional emergency model, the analysis identifies persisting challenges and current adaptations. It concludes by outlining the potential opportunities for a responsive design pedagogy in architecture and urbanism in a post-pandemic world (Salama and Burton 2022).

These publications offered valuable insights into various aspects of virtual design discourse in real-world settings. Moreover, they provided relevant information about the research methodologies employed by distinguished academics to examine virtual design studio discourse in their specific context, including research design, survey methods, and data collection and analysis. The research findings reveal the existence of complexities at various stages (initiation, realization, and reflection) of the virtual design model. Therefore, this study proposes that to address these complexities, it is necessary to theoretically break down the virtual design studio model into its probable constituent phases and associated components for analyzing the virtual design studio at different stages of implementation for further examination. The virtual design studio discourse constituents illustration (Figure 1) provides a schematic representation of the sequentially linked activity phases of a virtual design studio setup, which is made up of hosting, approach and contents framework, and progress appraisal. Each phase is constituted by associated domains, which can be further linked to analyzable instructional aspects to bring about effective comprehension of the pedagogical process.

Figure 1. Virtual design studio discourse constituents.

3.1. Initiation phase (hosting)

To establish successful virtual discourse, educators need to understand the essentials of the virtual learning ecosystem, including the virtual learning environment and instructional design principles. This will enable them to develop and deliver engaging and effective virtual learning experiences that are aligned with learning objectives.

3.1.1. Virtual learning environment

The evolution of instructional environments from physical settings to digital platforms and virtual design studio environments has revolutionized the domain of architecture pedagogy. Advancements in information and educational technology have given rise to e-learning, which is facilitated by a learning management system (LMS) (Pina 2010). LMSes are web-based applications used to manage the e-learning process, including course catalogs, contents, profiles, sharing sections, assessments, feedback, and progress indicators. The virtual design studio is an example of technology-mediated pedagogies, which is further facilitated by asynchronous and synchronous techniques in remote design collaboration. Despite the innovations, a conscious effort is required in the virtual ecosystem to ensure student participation and accessibility.

3.1.2. Instructional design

In the current virtual context, faculties need to act as instructional designers to deliver relevant educational content and ensure continuity of learning (Sampson, Ifenthaler, and Isaias 2020). The stages of instructional design include conception, preparation, development, refinement, management, and delivery of resources. Effective integration of knowledge fundamentals within an e-learning architecture framework is crucial, as is imbuing students with knowledge traits such as information acquisition, development of procedural knowledge and skills, and action learning. The notion of domain-specific knowledge, or “designerly ways of knowing” (Cross 2006), is important in design, and both explicit and implicit knowledge (Khan and Thilagam 2019) should be explored. A proper understanding of these fundamentals would enable students to identify issues, understand user requirements, and develop logical solutions concerning given spatial issues.

3.2. Realization phase (approach & contents framework)

Once the basics of a virtual learning ecosystem are comprehended, it is crucial to understand about the implementation process, which includes the methods and processes of teaching and learning. This knowledge is necessary to effectively structure and realize a virtual design studio discourse, which requires exploring instructional systems and pedagogical structures.

3.2.1. Instructional systems

To ensure effective course delivery, it is important to match teaching style and content to the needs of learners. Pedagogy and educational psychology are two domains that can provide valuable insights for educators. Pedagogy is concerned with teaching methods and how educational goals can be achieved, while educational psychology is concerned with optimizing learning through scientific study. With the shift to virtual learning environments due to the COVID-19 crisis, it is important to choose suitable teaching models that can improve learning outcomes. Bruce Joyce, Marsha Weil, and Emily Calhoun (Joyce, Weil, and Calhoun 2014) have classified teaching models into four families based on their focus directives: social, information-processing, personal, and behavioral systems. In the case of architecture education, the virtual design studio has become the new teaching and learning environment, and it is important to integrate information-processing teaching models with e-learning architecture to ensure better results. These models focus on intellectual capacity, including the ability to observe, organize data, understand information, form concepts, employ verbal and nonverbal symbols and solve problems. Their primary purposes are the mastery of methods of inquiry, academic concepts and facts, and the development of general intellectual skills.

3.2.2. Pedagogical structures

Different approaches to learning have been adopted by pedagogues to meet their course objectives. The behaviorist approach emphasizes training with a focus on desired outcomes, while the cognitive approach is concerned with how people acquire and apply information to enhance understanding and generate solutions. The constructivist approach regards learning as an active process where learners construct knowledge based on their present and past experiences. An explicit integrative approach that blends ideas from multiple learning theories to construct a better learning experience is effective (Guey, Cheng, and Shibata 2010; Honebein and Sink 2012).

Advancements in information technology have influenced the pedagogical domain, leading to the increasing relevance of connectivism (Siemens 2017). According to this approach, learning is creating networks where nodes, which can be people, organizations, libraries, websites, or any other source of information, are connected to form a network (Huang, Spector and Yang 2019). In the current scenario of virtual learning imposed by the COVID-19 crisis, connectivism gains more relevance, making it possible to create a virtual learning studio culture. However, successful implementation of the connectivism-based approach necessitates the need for proper feedback mechanisms to be in place. The notion of self-regulated learning becomes more crucial than conservative progress appraisal systems, especially in virtual settings where faculties and students are separated in either time or place.

3.3. Reflection phase (progress appraisal)

The degree of accomplishment of course objectives and goals is the key factor in determining the effectiveness of an academic program. A precise assessment can be made by examining the students’ learning outcomes, which is typically done through formal appraisal systems employed by faculty members. However, with the emergence of virtual design studios that employ flexible delivery systems and online participation, traditional appraisal methods face new challenges. Consequently, there is a need to investigate the realm of self-regulated learning.

3.3.1. Appraisal systems

The adoption of virtual pedagogical practices has given rise to new perspectives on the design studio. Despite being conducted in a physical or virtual setting, the design studio remains central to pedagogical activities. It is a space where students can address spatial issues, learn to create spatial solutions, and present and defend their work. The importance of positive feedback mechanisms in architecture pedagogy is underscored by the fact that good design is iterative and iterations can only be improved with feedback. Two types of feedback, formative and summative assessments, are used to measure student learning goals effectively. Historically, the main aim of measuring students’ educational progress was to identify differences among students to rank order them by achievement. This type of measurement model makes heavy use of summative assessment, which is useful for accountability purposes but only marginally useful for guiding day-to-day instruction and supporting student learning. In contrast, student-centered measurement models rely mostly on formative assessment, which is associated with meaningful feedback that can be very useful in guiding instruction and supporting student learning (Shute and Kim 2014). Because there are no standardized criteria for assessments in the subjective and creative domain of architecture, discussions and criticism in design studios tend to focus on clarity and reliability. These appraisal sessions can be stressful for students, so faculties aim to promote thoughtful debate and considerate dialogue. In the virtual mode of learning, where students are remotely located, the responsibility for achieving educational objectives falls heavily on their shoulders. Faculties need to encourage self-regulated learning in addition to consistent reviews to ensure that teaching and learning are mutually productive. Self-regulated learning is an inherent activity individuals undertake to achieve positive academic outcomes. It involves meta-cognitive, motivational, and behavioral processes, such as goal-setting and learning strategies (Zimmerman 2015). In the design studio, self-regulated learning enhances learning outcomes by guiding and regulating individual actions.

4. Research methodology and material

With the stages-wise phases, domains, and analyzable activities in mind, a survey was devised to gather the necessary information from both faculty and students. The survey aims to understand the effectiveness of measures adopted for teaching and learning, improving communication, executing project work, assessing progress, evaluating portfolios, externalizing feedback, and the impact on studio culture in the virtual design studio format of discourse. To achieve this objective, a survey research design was utilized, which is a distinct type of research design. In survey research, a sample of a population is studied (questioned or observed) to determine its characteristics, and it is then inferred that the population has the same characteristics (Kothari 2014). Sampling, therefore, is the process of selecting a few (a sample) from a bigger group (the sampling population) to become the basis for estimating or predicting the prevalence of an unknown piece of information, situation, or outcome regarding the bigger group (Kumar 2011). The population or more explicitly the study population in the context of this research work is comprised of faculty members and students of architectural institutions affiliated with a regional university following the same syllabus and curriculum. There were fourteen (based on the chronology of inception) architectural institutions affiliated with this particular university, pursuing the same curriculum and syllabus.

The cluster sampling approach was given preference to identify the appropriate sample size. Cluster sampling is a probability sampling technique in which all population elements are categorized into mutually exclusive and exhaustive groups called clusters. Clusters are selected for sampling, and all or some elements from selected clusters comprise the sample (Wakar and Poznyak 2018). The focus is on institutions affiliated with the University of Calicut, Malappuram, Kerala, India. These institutions adhere to the same regulations, curriculum, and syllabus for the B.Arch. program. Faculties in service and students pursuing their 3^rd year of B.Arch., course from 7 Institutions out of 14 Institutions, who have experienced physical design studios as well as virtual design studios, were chosen. The sample size of respondents was derived as follows: faculties 78 and students 250 numbers presuming a confidence level of 95% and a margin of error of 5% as the baseline.

Survey research would allow for a more comprehensive understanding of the virtual design studio experience from both the perspective of tutors and students. An effectively structured questionnaire has been created to gather insightful responses and critical information on various aspects of the virtual discourse, with a focus on the virtual design studio’s different stage-wise phases of implementation: initiation, realization, and reflection phases. The queries in the questionnaire are linked to Likert scale-based response index. A Likert scale is a form of descriptive scale where respondents indicate their levels of agreement with statements. Typically, it offers five options, allowing individuals to express the strength of their positive-to-negative agreement towards the statement. The scale assumes a linear relationship between the strength or intensity of an attitude, ranging from strongly agree to strongly disagree, or similar verbal descriptivism, and is based on the assumption that characteristics can be measured along a continuum.

The initiation phase involves understanding the user experience from both the faculty’s and students’ viewpoints regarding the establishment of a virtual learning ecosystem. This includes evaluating the significance of the instructional content. To accomplish this, it is imperative to delve into the realms of virtual learning environments and instructional design. Specific questions are developed using indicators (Table 2) that are pertinent to the domain, such as the availability of essential resources and technologies, influence on individual profile status, and elements related to instructional methods and learning. The aim is to attain a clear and accurate comprehension.

Table 2. Initiation Phase (hosting): survey Questionnaire parameters.

Index		Faculty Survey Questionnaire Description	Student Survey Questionnaire Description
Initiation Phase (Hosting)	Access to Essential Facilities & Technology	The section focuses on the faculty members’ access to essential facilities and technology for hosting VDS, such as workstations, network connectivity, hardware, and software applications. It also explores whether the institution had resources to facilitate virtual learning via learning management systems and web-based portals.	The section focuses on students’ access to essential facilities and technology for VDS, including workstations, network connectivity, hardware, and software applications. Effectiveness of LMS provided by Institution. It also explores whether the institution provided orientation programs and web-based portals to facilitate VDS.
	Individual Profile Status	The section assesses the challenges faced by faculty members during the migration from conventional face-to-face studios to virtual design discourse. It explores changes in their responsibilities, teaching hours, and the need for skill upgradation in technology. Additionally, it delves into the necessity for research on instructional methodologies to facilitate VDS.	The second section assesses students’ profile status during VDS, including the challenges faced in migrating from conventional face-to-face studios to virtual design discourse. It explores changes in their commitment levels and learning hours/workload distribution. It also asks about their perception of faculty members’ preparedness and the need for skill upgradation in technology.
	Design: Teaching & Learning: Process and Resources	The section analyzes the nature of teaching and learning methods adopted in VDS, including the use of learning management systems, digital resources, online tutorials, and virtual exploration platforms. It also considers interactions with project architects/consultants and the use of CAD/BIM software applications and virtual meeting platforms.	The section reviews the nature of teaching and learning methods adopted in VDS, including the effectiveness of the course organization in virtual mode, access to learning management systems and digital resources, and the impact of online tutorials, discussions, and virtual exploration platforms on their learning experience.

The realization phase provides comprehension of progressive structuring and effective implementation of the virtual design studio discourse. To achieve this, exploration of the instructional system and pedagogical structure domains is necessary. Specific questions are developed using indicators (Table 3) that are pertinent to the domain, such as the availability of essential resources and technologies, influence on individual profile status, and elements related to pedagogical settings, teaching and learning effectiveness level, and nature of interactions. The aim is to achieve a precise and thorough understanding.

Table 3. Realization Phase (approach & contents framework): survey Questionnaire parameters.

Index		Faculty Survey Questionnaire Description	Student Survey Questionnaire Description
Realization Phase (Approach & Contents Framework)	Pedagogical Settings	The section examines the role of pedagogical models in VDS, exploring the adoption of learner-centric instructional approaches, the significance of Bloom’s taxonomy, and the relevance of learning theories like constructivism and experiential learning.	The section aims to assess students’ perspectives on the pedagogical approaches used by faculty members in VDS, including student-centric instructional approaches and the use of multi-disciplinary approaches.
	Teaching & Learning Experiential Level	The section focuses on the effectiveness perceived by faculty members in discharging teaching and related activities during VDS, including preparation time for tutorials, engagement levels, and student participation.	The section considers students’ experiential levels during VDS, covering the quality of tutorials, reviews, engagement levels, and self-appraisal of their work, including drawings, visualizations, and models.
	Nature of Interactions	The section evaluates the ease and quality of interactions within the VDS as perceived by faculty members. It encompasses project discussions, design exploration, feedback in crits, and mentoring interactions.	The section assesses the level of easiness and quality of interactions in VDS, including project discussions, interactions during design development, and feedback in crits from the perspective of students.

The reflection phase is essential for developing comprehension of the success and effective realization of course objectives and goals, which are typically evaluated through learning outcomes. To develop an understanding in terms of the effectiveness of virtual pedagogy from the perspective of the faculties as well as of the students. Queries are formulated based on domain-specific indicators (Table 4) such as appraisal formats, peer learning, studio culture, and profile development. Consequently, it is imperative to explore the domain of self-regulated learning in this phase.

Table 4. Reflection Phase (progress appraisal): survey Questionnaire parameters.

Index		Faculty Survey Questionnaire Description	Student Survey Questionnaire Description
Reflection Phase (Progress Appraisal)	Assessments/ Appraisal Levels	The section examines the effectiveness of feedback and assessment methods in the virtual design studio. This includes faculty members’ perspectives on verbal and written feedback during tutorials and crits, as well as their assessment of reports and portfolios. The appraisal is done through self-comparison to the experience in a physical design studio setting.	The section evaluates students’ contentment regarding assessment and appraisal levels within the VDS. This involves assessing their satisfaction with verbal and written feedback during tutorials and crits, as well as the assessment of reports and portfolios, in relation to their experiences in the physical design studio.
	Peer Learning	The section examines peer learning and its effectiveness, encompassing peer interactions, collaboration, and team spirit, as perceived by faculty members among students during virtual discourse.	This section explores students’ viewpoints, in terms of the effectiveness of peer learning and associated activities. This encompasses factors such as peer interaction, positive mutual interactions, and collaborative work.
	Studio Culture	The section evaluates the importance of studio culture components in VDS, including the studio community, mutual support, peer learning, and student involvement in extracurricular activities, from the viewpoint of faculty members.	The section delves into the significance of studio culture within VDS from the perspective of students. It addresses aspects like the relevance to the studio community, mutual support, peer learning, and student engagement in extracurricular activities.
	Skills & Behavior	The section investigates the enhancement of skills and behavior within the context of VDS. This encompasses areas such as time management, presentation skills, and the overall advancement of one’s profile as an academician.	The section examines individual skill and behavior development during VDS, including time management skills, design skills, presentation skills, and overall profile development as student architects.

4.1. Non –parametric analysis

Comparing two samples using a parametric test would have led us to use an independent sample t-test. It is used to compare the location of two means from two samples. Where the samples are assumed to have normal distribution values. However, here we use a non-parametric equivalent (Mann Whitney U) for conducting a test. Mann-Whitney U-test allows us to compare two populations where the underlying distributions are not normal but have similar shapes. Therefore we use the ranks of the observations and not the underlying value. The Mann-Whitney U-test uses the principle of ranking to determine if the sample is from the same distribution. The two samples are combined and ranked ordered together. The strategy is to determine if the values from the two samples are randomly mixed in the rank ordering or if they are clustered at opposite ends when combined. A random rank order would mean that the two samples are not different, while a cluster of one sample’s values would indicate a difference between them.

$\mathit{Ui}=n_1{n}_2+\frac{n_i\left(n_i+1\right)}{2}-{\sum }^{R_i}$

Where Ui is the test statistic for the sample of interest,$n_i$ is the number of values from the sample of interest, $n_1$ is the number of values from the first sample, $n_2$is the number of values from the second sample, and ${\sum }^{R_i}$is the sum of the ranks from the sample of interest. After the U statistic is computed, it must be examined for significance (Corder and Foreman 2009).

Further, the p-value or probability value helps to determine the significance of the results concerning the null hypothesis. The null hypothesis states that there is no relationship between the two variables being studied. It states that the results are due to chance and are not significant in terms of supporting the idea being investigated. The alternative hypothesis states that the independent variable did affect the dependent variable, and the results are significant. A p-value less than 0.05 (typically ≤0.05) is statistically significant. It indicates strong evidence against the null hypothesis, as there is less than a 5% probability that the null hypothesis is correct (and results are random). Therefore, the alternative hypothesis can be accepted and the null hypothesis can be rejected (McLeod 2019). The scenario is vice versa when the p-value is greater than 0.05 (typically >0.05) and validates the null hypothesis.

Let’s illustrate as follows:

• Null hypothesis H0: indicates the nonexistence of differences in adaptation and acceptance levels with respect to virtual design studio between the faculties and the students.

• Alternative hypothesis Ha: infers about the existence of differences in adaptation and acceptance levels with respect to virtual design studio between the faculties and the students.

5. Results

Statistical Package for the Social Sciences (SPSS) is the software used by researchers for complex statistical data analysis. IBM SPSS V23 was used to process the data collected during the survey. IBM® SPSS® Statistics is a powerful statistical software platform. It offers a user-friendly interface and a robust set of features that aids in quickly extracting actionable insights from data (IBM. n.d.). Mann Whitney U test was the specific analysis technique used to analyze and interpret the data. Analysis and interpretation of data would help achieve the objectives concerning gathering effective insights on the virtual design studio from the perspective of faculties as well as students.

5.1. Initiation phase: access to essential facilities & technology

The Mann – Whitney test was conducted for all the parameters under access to essential facilities and technology fields. Five out of the eight parameters showed significant variations in responses between faculty and students (Table 5). Both teachers and students were able to access a suitable basic teaching and learning environment in the virtual setting. The institutions were able to provide appropriate Learning Management System (LMS) platforms, and both teachers and students had access to basic computers and internet connectivity to access the virtual system. However, analysis of responses indicates that the faculty members had better access as well as availability to aspects like workstation, network connectivity, software, orientation programs and web-based portals, cloud computing, etc. so they were able to engage effectively, whereas the relatively lower accessibility or availability of these resources impeded students’ ability to engage consistently in general.

Table 5. Analysis insights: access to essential facilities & technology.

Stage 1	Initiation Phase: Access to Essential Facilities & Technology
Index	Indicators	Category	N	Mean Rank	Mann Whitney U	P Value	Assessment
1	Access to workstation	Faculty	78	196.35	7266.00	<0.001	Significant
		Students	250	154.56
2	Workstation settings & working environment	Faculty	78	173.78	9026.00	0.309	Not Significant
		Students	250	161.60
3	Access to network connectivity	Faculty	78	189.81	7775.50	0.005	Significant
		Students	250	156.60
4	Virtual learning; delivery via the learning management system	Faculty	78	180.56	8497.00	0.059	Not Significant
		Students	250	159.49
5	Access to hardware	Faculty	78	169.96	9324.50	0.550	Not Significant
		Students	250	162.80
6	Access to software	Faculty	78	195.40	7340.00	<0.001	Significant
		Students	250	154.86
7	Access to orientation programs	Faculty	78	182.35	8357.5	0.047	Significant
		Students	250	158.93
8	Access to web-based portals/cloud computing	Faculty	78	186.22	8056.0	0.018	Significant
		Students	250	157.72

5.2. Initiation phase: individual profile status

Analysis to review the change associated with individual profile status scenario was performed. Three out of the five parameters showed significant variations in responses between faculty and students (Table 6). In terms of general migration from PDS to VDS the transition was not burdensome. Also, the nature of the workload in terms of coursework was relatively similar to the conventional format. However, it was felt that more resources and time were required to be made use of to teach and learn remotely. Concerning the nature of responsibilities the faculties were able to manage relatively well to adjust to their responsibilities, however, the students encountered difficulties to adapt themselves and becoming self-accountable for their overall learning experience. As they were remotely participating in the educational process which was overwhelmingly a new format. Appraisal-based feedback from the faculties indicates that there was a critical need to upgrade proficiency levels to adapt to the new normal. Furthermore in the virtual format of teaching and learning skill up gradation was crucial to maintain continuity as well as consistency.

Table 6. Analysis insights: individual profile status.

Stage 1	Initiation Phase: Individual Profile Status
Index	Indicators	Category	N	Mean Rank	Mann Whitney U	P Value	Assessment
1	Ease of migration to VDS	Faculty	78	168.60	9430.00	0.645	Not Significant
		Students	250	163.22
2	Nature of responsibilities	Faculty	78	142.74	8053.00	0.013	Significant
		Students	250	171.29
3	Nature of workload	Faculty	78	173.32	9062.00	0.321	Not Significant
		Students	250	161.75
4	Nature of proficiency status	Faculty	78	188.96	7842.00	0.006	Significant
		Students	250	156.87
5	Role of skill up gradation	Faculty	78	198.71	7081.50	<0.001	Significant
		Students	250	153.83

5.3. Initiation phase: design: teaching & learning: process and resources

In general, both faculties, as well as students, expressed shortcomings like strategies, course packages, etc. owing to a lack of proper awareness of e-learning architecture frameworks and directives. E-learning, a computer-based alternative approach to education, has made notable progress and found success in diverse fields. Nonetheless, in architecture, where design studio-based settings are predominant, the application of e-learning frameworks has been confined to introductory foundation-level courses. The systematic organization of course requirements and the creation of databases within studio-based contexts have received limited attention. Therefore the awareness of assumptions on which e-learning architecture is developed: receptive architecture based on an information acquisition view, a directive architecture based on a response strengthening view, and guided discovery architecture based on a knowledge construction view, would not be well known in general (Clark, 2016). Further analysis to review design: teaching and learning with regard to process and resources was performed. Eight out of the twelve parameters showed significant variations in responses between faculty and students (Table 7). The transition from PDS to VDS didn’t seem to interfere with the basic interaction levels between faculties and students, as they were mutually in contact using virtual utilities. Along similar lines, the use of virtual exploration portals, virtual site visits, and presentation portals allowed basic progression and continuity of discourse. However, the students encountered the following difficulties and expressed certain concerns, the students felt that lack of high speed and consistent network connectivity at times hampered their access to LMS and digital resources. Although the faculties thought that the course contents and aiding hand-outs were effective for virtual discourse, the students often desired more input. The faculties expressed the relevance of the world wide web/portals etc. but the students seem to have had issues accessing the same consistently. The faculties felt that virtual tours and explorative activities to an extent could recreate the physical experience; however, the students deferred to agree. The students were positive about the need for the utilization of CADD/BIM applications for design development and communication. However, they felt that they weren’t able to express themselves effectively during reviews, receipt of feedback, etc. by making use of the virtual platforms. In concurrence, they also felt the need for faculties to give more consideration to the diverse learning preferences of different learners in a studio. On the contrary, the faculties conveyed that due regard and attention were being given at the individual level. It was observed that the effectiveness of teaching and learning utilizing digital platforms can only be ensured based on acclimatization to the new normal with time.

Table 7 Analysis Insights: Design: Teaching & Learning: Process and Resources

Stage 1	Initiation Phase: Design: Teaching & Learning: Process and Resources
Index	Indicators	Category	N	Mean Rank	Mann Whitney U	P Value	Assessment
1	Access to LMS	Students	250
		Faculty	78	198.71	7082.00	<0.001	Significant
		Students	250	153.83
2	Access to digital resources	Faculty	78	201.82	6849.00	<0.001	Significant
		Students	250	152.86
3	Quality of online tutorials	Faculty	78	207.88	6366.00	<0.001	Significant
		Students	250	150.96
4	Dependence on world wide web/portals	Faculty	78	204.06	6664.00	<0.001	Significant
		Students	250	152.16
5	Effectiveness of virtual interactions	Faculty	78	160.77	9459.00	0.670	Not Significant
		Students	250	165.66
6	Usage of virtual exploration portals	Faculty	78	168.87	9409.00	0.623	Not Significant
		Students	250	163.14
7	Effectiveness of virtual tours	Faculty	78	214.71	5833.5	<0.001	Significant
		Students	250	148.83
8	Effectiveness of virtual site visits	Faculty	78	168.87	9409.00	0.623	Not Significant
		Students	250	163.14
9	Use of CADD/BIM applications	Faculty	78	146.45	8342.00	0.044	Significant
		Students	250	170.13
10	Use of virtual meeting platforms	Faculty	78	250.35	3054.00	<0.001	Significant
		Students	250	137.72
11	Use of virtual presentation platforms	Faculty	78	167.38	9525.00	0.746	Not Significant
		Students	250	163.60
12	Consideration of learning preferences	Faculty	78	201.24	6884.00	<0.001	Significant
		Students	250	153.04
Index	Faculty: Were you aware of E-Learning Architecture Framework directives while preparing the teaching strategy and course contents?			Students: Was the course organized effectively in virtual mode incorporating various digital tools and techniques?
				Strongly Disagree		2.8%
				Disagree		27.6%
1	Yes	29.5%		Neutral		46.4%
	Neutral	0		Agree		22.4%
	No	70.5%		Strongly Agree		.8%

5.4. Realization phase: pedagogical settings

Broadly 83% of the students expressed low levels of satisfaction regarding the virtual learning pedagogical settings in the realization phase. Four out of the five parameters showed significant variations in responses between faculty and students (Table 8). The faculty’s feedback indicated their recognition of the importance of aligning course content and teaching style with the learners’ needs, considering the diverse categories of students and the use of student-centric approaches. However, student feedback, in general, suggests that faculties have not been successful in garnering appreciation for their approaches from the student community. This lack of recognition may be due to an inadequate understanding of instructional systems, pedagogical structures, and learning theories, thereby hindering the utilization of insights from various disciplines to enrich architectural discourse. Therefore, it is crucial to raise awareness among both parties about the significance of these factors, as it will greatly contribute to the achievement of the studio’s objectives in future discussions.

Table 8. Analysis insights: design: pedagogical settings.

Stage 2	Realization Phase: Pedagogical Settings
Index	Indicators	Category	N	Mean Rank	Mann Whitney U	P Value		Assessment
1	Characteristics of teaching style	Faculty	78	240.47	3824.00	<0.001		Significant
		Students	250	140.80
2	Nature of learners	Faculty	78	162.36	9583.00	0.590		Not Significant
		Students	250	165.17
3	Student-centric instructional approaches adopted by the faculty members	Faculty	78	231.41	4531.00	<0.001		Significant
		Students	250	143.62
4	Multi-disciplinary approaches used in teaching and learning. (Students Response)				Yes	40%
					No	60%
5	Satisfaction levels with the overall instructional methods adopted by the faculties. (Students Response)				Never	8.8%
					Seldom	20%
					Sometimes	54.4%
					Often	16%
					Almost always	0.8%
Faculties’ Response to Pedagogical Aspects
1	Can teaching and learning be emphasized by stressing learning theories?				Yes		59%
					No		41%
2	Learning by making use of experiential and value-based approaches helps students to co-construct information and knowledge. Such an approach is always better than passive learning.				Strongly Disagree		Nil
					Disagree		1.3%
					Neutral		12.8%
					Agree		42.3%
					Strongly Agree		43.6%
3	Awareness of Constructivist theory				Yes		57.7%
					No		42.3%
4	Experiential learning is critical in design discourse (teaching and learning)				Strongly Disagree		Nil
					Disagree		Nil
					Neutral		12.8 %
					Agree		43.6 %
					Strongly Agree		43.6 %
5	Awareness of Kolb’s Experiential Learning Theory				Yes		12.8 %
					No		87.2%
6	Need for a learning network linked via online connectivity; constituted by learners, faculties, expert personals, and other digital resources spread across time and space.				Strongly Disagree		2.6 %
					Disagree		20.5%
					Neutral		46.2 %
					Agree		30.8 %
					Strongly Agree		2.6 %
7	Awareness of Connectivism Theory				Yes		16.7 %
					No		83.3%

5.5. Realization phase: teaching and learning effectiveness level

Analysis to review the teaching and learning effectiveness level during the studio discourse brought about mixed and contradicting responses. Seven out of the eight parameters showed significant variations in responses between faculty and students (Table 9). The faculties conveyed that they had acknowledged the challenges bestowed by the virtual format and had extensively worked to ensure a positive learning scenario. This is seen in the analysis of their responses collectively concerning the preparation time and commitment levels put forward for tutorials, reviews, and crits for ensuring the effectiveness of the design discourse. However, they felt that participation levels from students for various sessions and effective engagement were less when compared to the physical design studio settings. On the contrary, the students felt that they spend more time developing know-how about digital platforms and software skills through learning and exploring on their own to adapt to the virtual mode. To ensure that they were able to prepare and present design studio prerequisites digitally at various stages of the design studio project, without the need to depend on physical drawings and models. Faculties and students thought that virtual interactions and crits ensured the continuity of design development and related activities at various stages of the studio activities. However, lack of face-to-face contact in the accustomed mode and consistent personnel-level feedback seemed to have affected the quality levels of drawings, and models produced as part of the submissions.

Table 9. Analysis insights: teaching and learning effectiveness level.

Stage 2	Realization Phase: Teaching and Learning Effectiveness Level
Index	Indicators	Category	N	Mean Rank	Mann Whitney U	P Value	Assessment
1	Preparation time/quality: tutorials	Faculty	78	233.20	4391.50	<0.001	Significant
		Students	250	143.07
2	Engagement level/Participation level during tutorials	Faculty	78	139.05	7765.00	0.005	Significant
		Students	250	172.44
3	Preparation time & quality: reviews/crits	Faculty	78	226.04	4950.00	<0.001	Significant
		Students	250	145.30
4	Engagement level/Participation level during reviews/crits	Faculty	78	118.51	6163.00	<0.001	Significant
		Students	250	178.85
5	Consistency Levels	Faculty	78	110.47	5535.50	<0.001	Significant
		Students	250	181.36
6	Quality of drawings	Faculty	78	121.94	6430.00	<0.001	Significant
		Students	250	177.78
7	Quality of visualizations	Faculty	78	158.12	9252.50	0.479	Not Significant
		Students	250	166.49
8	Quality of models	Faculty	78	135.41	7481.00	<0.001	Significant
		Students	250	173.58

5.6. Realization phase: nature of interactions

Further analyses to determine the influence of interactions on the outcome of the design studio portfolios were examined. Two out of the eight parameters showed significant variations in responses between faculty and students (Table 10). The faculties as well as the students did acknowledge the significance of face-to-face interactions and also the relevance of physical settings of a design studio. Feedback does show that they felt that it was achievable to an extent via online interactions and reviews in virtual settings. However, the lack of effectiveness is attributed to the absence of explorative efforts, successive interactions at progressive stages of the project development, and lack of punctuality levels.

Table 10. Analysis insights: nature of interactions.

Stage 2	Realization Phase: Nature of Interactions
Index	Indicators	Category	N	Mean Rank	Mann Whitney U	P Value	Assessment
1	Project discussions	Faculty	78	156.58	9132.00	0.376	Not Significant
		Students	250	166.97
2	Interactions at progressive stages	Faculty	78	146.61	8354.50	0.046	Significant
		Students	250	170.08
3	Design explorations & progressiveness	Faculty	78	147.76	8444.50	0.065	Not Significant
		Students	250	169.72
4	Feedback & consistency	Faculty	78	166.06	9628.00	0.861	Not Significant
		Students	250	164.01
5	Punctuality levels for discussions and review	Faculty	78	142.54	8037.50	0.016	Significant
		Students	250	171.35
6	Mentoring & well-being related interactions	Faculty	78	174.46	8973.00	0.266	Not Significant
		Students	250	161.39

5.7. Reflection phase: assessments/appraisal levels

Analysis to review the mode of assessments and nature of appraisal levels indicated differences of opinion. Five out of the six parameters showed significant variations in responses between faculty and students (Table 11). The faculty’s feedback conveyed that they have been systematically assessing with clarity as usual. However, the student’s feedback seems to have a difference of opinion. Probably a more inclusive format needs to be in place for appraisal.

Table 11. Analysis insights: assessments/appraisal levels.

Stage 3	Reflection Phase: Assessments/Appraisal Levels
Index	Indicators	Category	N	Mean Rank	Mann Whitney U	P Value	Assessment
1	Verbal feedback was given during tutorials VDS	Faculty	78	181.19	8448.50	0.061	Not Significant
		Students	250	159.29
2	Written feedback was given during tutorials VDS	Faculty	78	191.65	7632.00	0.003	Significant
		Students	250	156.03
3	Verbal feedback was given during crits VDS	Faculty	78	196.62	7245.00	<0.001	Significant
		Students	250	154.48
4	Written feedback was given during crits VDS	Faculty	78	190.30	7737.50	0.004	Significant
		Students	250	156.45
5	Assessment of reports VDS	Faculty	78	190.96	7686.50	0.003	Significant
		Students	250	156.25
6	Assessment of portfolios VDS	Faculty	78	183.41	8275.00	0.037	Significant
		Students	250	158.60

5.8. Reflection phase: peer learning and related matters

Analysis to review the peer learning and related matters didn’t convey many variations. One out of the four parameters showed significant variation in responses between faculty and students (Table 12). The student community seems to have adjusted to the shift from a conventional mode to a virtual mode of interactions and collaboration. It seems the only area that has been affected is concerning sharing of technical know-how and the use of physical infrastructure linked to various labs etc. for the upgradation of technical knowledge and skill development.

Table 12. Analysis insights: peer learning and related matters.

Stage 3	Reflection Phase: Peer Learning and Related Matters
Index	Indicators	Category	N	Mean Rank	Mann Whitney U	P Value	Assessment
1	Peer Interaction and exchange levels VDS	Faculty	78	173.03	9084.50	0.341	Not Significant
		Students	250	161.84
2	Positive mutual interactions related to sharing positive crits and being useful to others VDS	Faculty	78	167.67	9502.50	0.724	Not Significant
		Students	250	163.51
3	Positive mutual interactions and facilitation related to technical know-how sharing VDS	Faculty	78	183.50	8268.00	0.035	Significant
		Students	250	158.57
4	Collaborative work and team spirit VDS	Faculty	78	180.47	8504.50	0.076	Not Significant
		Students	250	159.52

5.9. Reflection phase: studio culture

Analysis to review the impact of virtual mode on studio culture and related matters didn’t convey significant variations (Table 13). Traits like mutual support, promotion of mutual growth, relationship maintenance, emotional wellness, etc. seemed to be still in place using virtual connectivity, live video chats, etc. Although the students felt that the sense of knowing each other beyond basic levels of acquaintanceship, brought about by actual presence and interactions in the physical studio was missing. Both faculties and students felt that aspects like tutor and student interactions, peer learning, and participation in extracurricular activities have been impacted to a certain level owing to the transition to a virtual mode of learning and interactions.

Table 13. Analysis insights: studio culture.

Stage 3	Reflection Phase: Studio Culture
Index	Indicators	Category	N	Mean Rank	Mann Whitney U	P Value	Assessment
1	Sense of belonging	Faculty	78	175.98	8854.50	0.195	Not Significant
		Students	250	160.92
2	Mutual support	Faculty	78	169.22	9382.00	0.594	Not Significant
		Students	250	163.03
3	Peer learning	Faculty	78	159.21	9256.00	0.595	Not Significant
		Students	250	165.47
4	Mutual growth	Faculty	78	165.78	9650.50	0.887	Not Significant
		Students	250	164.10
5	Relationships	Faculty	78	162.33	9581.00	0.811	Not Significant
		Students	250	165.18
6	Motivation Emotional Wellness	Faculty	78	162.02	9556.50	0.784	Not Significant
		Students	250	165.27
7	Extracurricular activities	Faculty	78	150.42	8652.00	0.117	Not Significant
		Students	250	168.89
8	Tutor & Students Interactions	Faculty	78	157.59	9211.00	0.444	Not Significant
		Students	250	166.66
9	End Semester Exhibitions	Faculty	78	163.99	9710.00	0.955	Not Significant
		Students	250	164.66

5.10. Reflection phase: skill & behaviour

Analysis to review aspects of skill and behavior development during a virtual design studio discourse scenario brought about very interesting insights. Four out of the four parameters showed significant variations in responses between faculty and students (Table 14). In major aspects like time management & punctuality, development of technical skills, development of presentation skills and overall development the feedback from the survey and further analysis it seems that the faculties had made major gains. They seem to have put in loads of effort and improved themselves to adapt to the new normal. Thereby enabling them to deliver virtual studio pedagogy. This directly empowered them with new knowledge and skills, paving the way for overall development. However feedback from the students conveys that they did evolve themselves positively by acquiring new knowledge and skills to adapt to the new normal, however, they require more facilitation and guidance to achieve a better outlook.

Table 14. Analysis insights: skill & Behaviour.

Stage 3	Reflection Phase: Skill & Behaviour
Index	Indicators	Category	N	Mean Rank	Mann Whitney U	P Value	Assessment
1	Time management & punctuality	Faculty	78	215.74	5753.00	<0.001	Significant
		Students	250	148.51
2	Development of technical skills	Faculty	78	206.71	6457.50	<0.001	Significant
		Students	250	151.33
3	Development of presentation skills	Faculty	78	210.59	6155.00	<0.001	Significant
		Students	250	150.12
4	Overall Development	Faculty	78	197.31	7191.00	<0.001	Significant
		Students	250	154.26

6. Survey research conclusive summary

Data analysis and interpretation support the acceptance of the alternative hypothesis and the rejection of the null hypothesis. The alternative hypothesis (Ha) suggests that there are differences in adaptation and acceptance levels of the virtual design studio between faculties and students. The experiences of faculties and students during the various phases can be summarized as follows:

During the initiation phase, both faculties and students engaged in virtual design studio pedagogy. While faculties had better access to resources, students faced challenges in taking responsibility for their learning experiences. There were also shortcomings in e-learning strategies and course packages due to a lack of awareness of e-learning architecture frameworks and directives. Despite these challenges, the use of virtual utilities allowed for continued discourse and progression, although students faced difficulties with network connectivity and consistent resource access. Students expressed the need for more consideration of diverse learning preferences, while faculties showed commitment to providing individual attention. It is crucial for everyone to gradually adapt to the new normal and facilitate effective teaching and learning using digital platforms.

Further in the realization phase, faculty and student experiences in the virtual design studio varied. While faculties acknowledged the need for adapting teaching styles and content to cater to diverse learners and utilizing student-centered approaches, students reported low effectiveness. Though the faculties asserted that they made efforts to create a conducive virtual learning environment, they believed that student engagement and participation were lower than in physical studio settings. On the other hand, students reportedly spent more time improving their digital and software skills to adapt to virtual learning well. Both faculties and students recognized the importance of virtual interactions and critiques in sustaining design development, but they also acknowledged that the absence of in-person contact and consistent feedback may have impacted the quality of submissions. It seems that there is a need for developing more understanding of instructional systems, pedagogical structures, and learning theories by both faculties and students in the virtual e-learning framework-based ecosystem.

Finally, in the reflection phase, different opinions emerged regarding assessments and appraisal aspects. While faculty feedback indicated that assessments were being systematically conducted with clarity, student feedback suggested the need for a more inclusive format for appraisal. The analysis also indicated minimal differences in the student community’s adjustment to the shift from conventional to virtual interactions in terms of peer learning, except for the sharing of technical know-how and the use of physical infrastructure for technical skill development. The analysis of the impact of virtual mode on studio culture showed no significant changes in traits such as mutual support, relationship maintenance, and emotional wellness, although students missed the sense of knowing each other beyond basic levels due to the absence of physical interactions Both faculties and students acknowledged the impact of the virtual mode on aspects like tutor and student interactions, peer learning, and extracurricular activities. Analysis of skill and behavior development indicated faculties made significant gains in areas like time management, technical skills, and presentation skills as they adapted to the new normal. Nonetheless, student feedback indicated that they have indeed experienced personal growth through the acquisition of new knowledge and skills to navigate the changing circumstances. However, they also expressed the need for increased support and direction to attain a more favorable perspective.

7. New directions

The COVID-19 pandemic led to a rapid shift to virtual learning in architecture education. However, as we move towards a post-pandemic world, a hybrid pedagogical approach combining virtual and physical learning is expected to emerge. This approach would offer the flexibility of virtual learning and the essential hands-on experience of physical learning, providing a well-rounded education for architecture students. The blended learning model can be previewed as a primary method in this direction (Mahmoud Saleh, Abdelkader, and Hosny 2022; Megahed and Hassan 2021b). Blended learning combines virtual and physical teaching methods in architecture education, enhancing the learning experience. Virtual design studios connect students with professionals and foster collaboration. Additionally, students can interact with focus groups and peers from diverse campuses. At the same time, physical learning environments will continue to be essential, providing students with the opportunity to participate in offline lectures, tutorials, and studio sessions. Further, reconnect with the tangible aspects of architecture, such as the material library, building science labs, structural and construction yards. Also, enable the effective use of CADD and digital prototyping studios. Thereby paving the way for a comprehensive integrated learning experience.

In concurrence, when discussing novel possibilities of hybrid approaches, the HyFlex format and the role of AI (Artificial Intelligence) also require consideration as evolving domains. The HyFlex model is a relatively new approach to education that has gained popularity in recent times. While blended learning provides some flexibility to students, the implementation of the same is generally faculty or instruction driven. The HyFlex blended learning model is an alternative approach that places selection power in students’ hands (Malczyk and Mollenkopf 2019). In HyFlex courses, students can choose from one of three participation paths or combinations: participate in face-to-face synchronous class sessions in person, participate in face-to-face sessions via video conference, and participate fully asynchronously via coursework (Columbia/CTL Center for Teaching and Learning n.d.).

Artificial Intelligence is a booming technological domain capable of altering every aspect of our social interactions. In education, AI has begun producing new teaching and learning solutions that are now undergoing testing in different contexts (2019). The integration of AI in education has the power to transform the teaching and learning experience. By granting students access to advanced analytical and design tools, AI enables them to generate more intricate and innovative designs. Furthermore, AI can analyze vast volumes of data, offering students deeper insights into various aspects of architecture, such as design development, building performance, sustainability, services, and material properties. When combined with the HyFlex model, AI enhances flexibility and autonomy for students. Personalized feedback and guidance based on individual preferences can be provided through AI tools. Additionally, adaptive learning environments can be created, catering to the unique needs and preferences of each student, ensuring a customized learning experience. A novel and constructive methodological process schema, illustrated in (Figure 2), holds promise for further research and exploration in the field.

Figure 2. AI hybrid pedagogical process schema.

In conclusion, the HyFlex model and AI are both promising approaches to architecture pedagogy that have the potential to transform the way we teach and learn. By providing students with greater flexibility and autonomy, while also utilizing powerful analytical and design tools, we can create a more engaging and effective learning environment that prepares students for the complex and dynamic world of architecture.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Asif R. Khan

Asif R. Khan is pursuing his part-time Ph.D. program in Architecture at the School of Architecture, Kalasalingam Academy of Research and Education, Tamil Nadu, India. He acquired his B.Arch., degree from MES School of Architecture, Malappuram, University of Calicut, Kerala, India, and pursued his M.Arch., degree from Smt. Manoramabai Mundle College of Architecture, Nagpur University, Maharashtra, India. He is a recipient of the Netherlands Fellowship (NFP), to study the post graduate diploma course at the Institute for Housing and Urban Development Studies, Erasmus University, Rotterdam. Holds a Pg.Dip., in Developing Social Housing Projects (DSHP), from Institute for Housing and Urban Development Studies, Erasmus University, Rotterdam. He has been associated with AA School, London as a visiting teacher. He has been associated with the Centre for Environmental Planning and Technology (CEPT) University, Ahmedabad, Gujarat, India, as a research scholar. Is a registered architect with the Council of Architecture, India. Is a fellow member of the Indian Institute of Architects. Has professional exposure in the Middle East as well as in India on significant architectural projects. He has been associated with several architectural colleges in India. Has authored and presented numerous research papers at national and international forums. Presently officiating as Principal, Al Salama Institute of Architecture, University of Calicut, Kerala, India.

N. Lakshmi Thilagam

N. Lakshmi Thilagam is an Architect and Urban Designer. She acquired her B.Arch., degree from the National Institute of Technology, Tiruchirappalli, Tamil Nadu, India, and pursued her M.Arch., degree from the School of Planning and Architecture, New Delhi, India. Pursued her Ph.D. from the Indian Institute of Technology, Kharagpur, India. Her research interests are traditional urbanism, space syntax application for historic cities, heritage, and urban conservation. She is currently researching to analyze the principles of sustainability exhibited in the traditional urban patterns of the historic cities of Tamil Nadu. Is a passionate academician, involved in teaching activities for over twenty years. Also writes on the subject of Architectural Education.