Enhancing Landscape Architecture Construction Learning with Extended Reality (XR): Comparing Interactive Virtual Reality (VR) with Traditional Learning Methods

Abstract

The application of extended reality (XR) in design education has grown substantially; however, empirical evidence on its educational benefits remains limited. This two-year study examines the impact of incorporating a virtual reality (VR) learning module into undergraduate landscape architecture (LA) construction courses, focusing on brick masonry instruction. A conventional learning sequence—lecture, sketching, CAD, and 3D modeling—was supplemented with an immersive VR experience developed using Unreal Engine 5 and deployed on Meta Quest devices. In Year 1, we piloted a preliminary version of the module with landscape architecture students (n = 15), and data on implementation feasibility and student perception were collected. In Year 2, we refined the learning module and implemented it with a new cohort (n = 16) using standardized VR evaluation metrics, knowledge retention tests, and self-efficacy surveys. The findings suggest that when sequenced after a theoretical introduction, VR serves as a pedagogical bridge between abstract construction principles and physical implementation. Moreover, the VR module enhanced student engagement and self-efficacy by offering experiential learning with immediate feedback. The findings highlight the need for intentional design, institutional support, and the continued development of tactile, collaborative simulations.

1. Introduction

Landscape architecture as a discipline requires an understanding of complex abstract concepts and their practical implementations. It merges an array of different subject topics, such as design, construction, understanding of environmental parameters, and overall, a mix of creativity and technological learning, for its students (Holden & Liversedge, 2014). Despite the interdisciplinary nature of the field, traditional pedagogical approaches—primarily based on two-dimensional hand and computer-aided drawings, class lectures, and infrequent site visits—often fall short in preparing students for the practical challenges encountered in professional practice (Barbarash, 2016). Without integrating technological advancement for improving teaching methodologies, students often struggle to transition from abstract design concepts to pragmatic design processes, potentially leading to errors in practical applications (Doyle & Senske, 2017). This challenge is becoming increasingly pronounced due to the rapid integration of complex technologies and shifting expectations in professional practice (Schön, 2017). As a result, fresh graduates may encounter difficulties in their transition from academia to practice, where implementation errors lead to reduced confidence (Hejazi, 2020). Utilizing extended reality (XR) in the learning process may aid students’ understanding by creating a bridge between abstract design and construction processes (Anifowose et al., 2022).

1.1. Research Background

1.1.1. Challenges in LA Education

Translating abstract concepts into practical applications is a challenge for most design disciplines. This issue is compounded in landscape architecture (LA) education by distinct pedagogical challenges. Topics such as understanding living systems, dynamic processes, and site-specific complexities can often exceed the efficacy of conventional learning methods. One of the fundamental challenges in the discipline lies in the comprehension and representation of complex and dynamic ecological systems and processes (Jørgensen et al., 2019; Nassauer & Opdam, 2008). Demonstrating how hydrology, soil conditions, plant ecology, and microclimates interact across a specific site through time and how that affects the design is difficult to convey with static diagrams or occasional site visits (Deming & Swaffield, 2011). The temporal dimension of the LA design adds to this pedagogical complexity (Sheppard, 2005; Thompson & Steiner, 1997), as simulating long-term transformations such as weathering and long-term design performance is difficult with traditional tools of learning LA (Ode et al., 2008).

For LA construction learning, a common challenge occurs when students attempt to visualize the manipulation of three-dimensional assemblies from two-dimensional construction documents (Kuliga et al., 2015). Learners often struggle to translate standard construction documentation, such as plans, sections, and detail drawings, into LA construction features such as retaining walls, water features, or paving patterns, especially when the task involves the sequential assembly of these features onto a varied terrain condition (W. Wu et al., 2019; Arranz-Paraíso & Arranz-Paraíso, 2023). This also relates to the hurdle of effectively bridging the gap between theory and the application of construction knowledge (Mills & Treagust, 2003), as traditional teaching methods offer limited hands-on problem-solving opportunities. Alongside this, materiality and the connection of different materials in LA construction also pose significant challenges, as landscape architects work with a broad palette of living and hard materials that require nuanced technical specifications, assembly logic, and sustainability implications (Brown & Corry, 2011).

Digital tools such as CAD and 3D modeling software have become indispensable for landscape architecture design and construction, but their usage does not translate directly to an intuitive understanding of constructability or the physical assembly process (Bishop & Lange, 2005; Sawyer & Lindsay, 2022). Students can be proficient in digital representation methods without fully grasping the implications of their design elements (Kuliga et al., 2015). This underscores the need for innovative tools and approaches that can offer immersive and interactive avenues for students to engage with construction principles and processes, setting the stage for exploring the potential of technologies like XR.

1.1.2. XR in Education

The Cognitive Affective Model of Immersive Learning (CAMIL) posits that immersive learning environments allow for enhanced educational outcomes by fostering agency, presence, and emotional engagement (Kloeppel, 2025). With the present state of XR technology, the tools for immersive learning exhibit the potential to enhance learning experiences (H.-K. Wu et al., 2013). XR has four key themes that enhance its educational value: immersion, visualization, interactivity, and spatial thinking (Che Man et al., 2024). With these key aspects, augmented reality (AR), virtual reality (VR), and mixed reality (MR) can have an effective impact on the learning process and enable educators to provide students with an enhanced learning environment, yielding greater student engagement and motivation (Dede, 2009; Mikropoulos & Natsis, 2011; Radu, 2014). This, as a result, has the potential to improve learning outcomes. XR technology has proven to be effective for new generations of learners, specifically Generation Y and Z students who prefer interactivity and connectivity within their learning environments provided by technology rather than traditional learning methods (Kuleto et al., 2021). By enabling experiential learning, XR creates increased accessibility and motivation for the learning content, with the potential to add new levels of improved cognition (Idrees et al., 2022; Pal et al., 2024; Pregowska et al., 2024).

XR’s ability to simulate true-to-world scale and interactivity aligns with constructivist learning theories, allowing students to create their own knowledge through experiential learning. Research has demonstrated that XR serves as a practical learning tool across various educational levels and disciplines, including the fields of science, medicine, art, and architecture (Garzón & Acevedo, 2019; Moro et al., 2021). Empirical evidence within the medical and science fields shows that the integration of XR technologies into the learning process enhances the understanding of complex topics, leading to improved knowledge retention and comprehension (Moro et al., 2021).

Although XR demonstrates substantial advantages when incorporated into educational environments, reported obstacles such as motion sickness and financial limitations associated with implementing the technology present challenges to its scalability (Jensen & Konradsen, 2018). Potential limitations also include a lack of faculty expertise for incorporating the technology in classroom settings (Kıdık & Asiliskender, 2024; Zhang & Huang, 2024), infrastructure limitations such as computational power and lack of high-speed internet access, as well as limited availability of high-quality educational content (Dimitrov, 2024).

1.1.3. XR in Landscape Architecture and Construction Education

Research indicates that the connection between design and construction in design education is weak. The underrepresentation of construction courses can cause a lack of the necessary skills to translate design into practical design solutions (Shareef et al., 2024). XR has the potential to solve this issue by providing immersive and realistic construction scenarios, enhancing students’ practical skills and safety awareness as a result (Wang et al., 2018). XR also has the potential to significantly improve hazard recognition and risk assessment skills among construction professionals and students, leading to increased readiness for real-world problem-solving (Li et al., 2018; Pedro et al., 2016). Where traditional modes of construction learning, such as sketching, 2D CAD drawing, or 3D modeling, may fall short in conveying complex concepts to the students, XR, with its immersive capabilities, facilitates a deeper understanding of the construction process (Sampaio & Martins, 2014). Gamification is becoming more common, and the use of game engines in creating the immersive learning experience is gaining traction for their enhanced real-time visualization capabilities (W. Wu & Issa, 2015). Advancements in emerging technologies, such as photogrammetry, drone mapping, and platforms for XR environment creation, have enabled immersive technologies to enter earlier design phases along with design conception and ideation rather than its conventional use as a visualization tool. In landscape architecture, VR is known to allow students to enhance their understanding of terrain, vegetation, watershed dynamics, and overall site analysis by placing students in spatially accurate 3D models (Johnson et al., 2019). The four key themes underpinning the educational values of XR enable students to interactively manipulate site grading, drainage, and planting design, with the results of their manipulation presented, allowing for a visual representation of complex abstract landscape topics (Che Man et al., 2024).

While data indicates that carefully crafted XR modules may enhance landscape architectural construction learning (Andalib & Monsur, 2024), it is essential to note the lack of research focused on integrating XR within different stages of landscape architecture learning.

1.1.4. Research Gaps

a. 

Limited Research Conducted on XR Applications in Landscape Architecture Compared to Other Fields

Most XR applications aimed at design disciplines focus on architecture, urban design, and engineering, but limited data is available on how XR can support landscape architecture (LA) (Che Man et al., 2024). Studies have reported that XR improves design visualization and simulation (Wang et al., 2018) along with creativity (Aydin & Aktaş, 2020), but its adoption in LA remains absent in these studies. Another aspect of this gap is the fact that XR is commonly used for the final stages of design visualization and as a presentation tool. Limited research has been conducted on its role in the early phases of the design process, such as concept development, site inventory, and analysis (Che Man et al., 2024). Although different studies have suggested that XR has the potential to foster early-stage creativity and design communication (Portman et al., 2015), the prominent use of XR rests in the later stages of design presentation (Johnson et al., 2019).

b. 

Limited Comparative Studies

Several studies report positive outcomes, such as reduced frustration and enhanced enthusiasm from implementing XR in the learning environment. However, a limited number of studies compare it to conventional teaching methods within a structured framework. (Ayer et al., 2016; Fonseca et al., 2016; Kidik & Asiliskender, 2024). Studies reporting positive outcomes of digital methods rarely compare learning outcomes objectively with conventional modes of teaching design, such as studio teaching (Sun et al., 2017). This limitation highlights a gap in comparative assessments necessary to determine whether XR genuinely improves learning outcomes or if its role is limited to effective student engagement. Rigorous experimental research with robust experimental design is required to fill this gap (Hamilton et al., 2021).

c. 

Limited Theoretical Integration

XR use in landscape-architecture construction still lacks a firm theoretical framework. Although Technological Pedagogical Content Knowledge (TPCK) by Mishra and Koehler and the six-level landscape analysis by Carl Steinitz have been proposed as foundational theoretical frameworks for XR integration, their adaptation in the curricula is yet to be established (Zhang & Huang, 2024). This gap keeps students in a mainly passive role and prevents them from gaining the kinesthetic learning benefits that XR can provide (Morphew et al., 2023). XR developers likewise favor technical novelty over pedagogical intentionality, heightening cognitive load without deepening conceptual understanding (Kıdık & Asiliskender, 2024).

1.2. Research Questions

This study seeks to quantitatively and qualitatively assess the effectiveness of VR-based learning for construction education by addressing the following research questions.

RQ1: How does VR-aided instruction impact students’ self-efficacy in performing construction-related tasks?

Rationale: This question aims to address the limited theoretical integration (Gap C) of XR in LA education by examining self-efficacy. Changes in self-efficacy can provide insights into how experiential VR environments might influence students’ confidence and perceived competence in construction tasks. Furthermore, by focusing on a psychological outcome beyond basic usability, this inquiry also begins to explore the deeper pedagogical benefits of VR, contributing to the need for more nuanced evaluations identified in Gap A (Limited XR in LA) and Gap B (Limited Comparative Studies).

RQ2: How does VR-aided learning affect knowledge retention?

Rationale: A central concern highlighted by the limited comparative studies (Gap B) is whether XR genuinely improves learning outcomes or merely enhances engagement. This question directly addresses this issue by seeking to measure objective knowledge retention. Assessing retention aims to provide crucial empirical evidence regarding the effectiveness of VR as a pedagogical tool for LA construction, moving beyond anecdotal reports of student enthusiasm due to the novelty of tools and technology.

RQ3: How does cognitive load in VR-aided learning environments influence construction education outcomes?

Rationale: Limited theoretical integration (Gap C) has often led to XR tools that inadvertently cause cognitive overload. This question explores the critical aspects of cognitive load within the VR environment designed for this study. By investigating how students experience and manage cognitive demands while learning complex construction tasks in VR, meaningful insights into designing pedagogically effective XR experiences can be achieved.

RQ4: What role does user engagement play in the effectiveness of VR-based construction learning?

Rationale: While increased engagement is often cited as a benefit of XR, Gap B (Limited Comparative Studies) calls for analyzing whether this engagement translates to actual learning. This question aims to quantify user engagement and explore its relationship with other learning outcomes (e.g., knowledge retention and self-efficacy). Understanding the correlation between these variables is vital for discerning whether the impact of VR is primarily motivational or whether engagement actively contributes to deeper learning in LA construction.

RQ5: How do students’ qualitative experiences (perceptions, usability, preferences) and perceived usefulness of the technology shape their learning in VR?

Rationale: To complement quantitative measures and address the need for more LA-specific insights (Gap A), this qualitative question explores the richness of student experiences when utilizing VR modules. Understanding student perceptions of usability, their preferences when comparing VR to traditional methods, and the perceived usefulness of technology provides a critical context for interpreting quantitative findings. It also offers practical insights for refining VR tools and pedagogical approaches for LA construction education, ensuring that they are learner-centric and effectively address the identified limited theoretical integration (Gap C).

1.3. Significance of the Study

This study aims to contribute to disciplines such as educational technology, construction education, and VR learning methodologies. We attempted to address the existing research gaps by evaluating empirical evidence on VR’s pedagogical effectiveness. This research also incorporates several existing learning theories, such as self-efficacy theory, cognitive load theory, experiential learning theory, and user engagement theory. Insights from these theories enable a structured and multi-level analysis of VR’s effectiveness in construction learning, evaluating engagement, cognitive load, self-efficacy in understanding and application, and knowledge retention.

This research has both pragmatic implications and academic contributions. It provides evidence-based guidelines for educators in landscape architecture and related fields, interdisciplinary scholars, XR developers, and educational policymakers. By highlighting the potential benefits and constraints of VR in LA construction learning, it supports the development of intuitive and effective VR tools.

2. Materials and Methods

2.1. Theoretical Framework for This Study

To investigate the impact of virtual reality (VR) on landscape architecture (LA) construction learning, this study is grounded in a theoretical framework. This framework integrates four key learning theories: self-efficacy theory, experiential learning theory, cognitive load theory, and user engagement theory. These theories provide different lenses to understand how students interact with the VR learning environments, process information, develop confidence, and achieve learning outcomes. Here, we discuss the relevance of each study and how they have contributed to the research design.

2.1.1. Self-Efficacy Theory

Bandura’s self-efficacy theory (Bandura, 1977, 1997) posits that learners’ confidence in their abilities drives motivation, persistence, and performance. Students who perceive themselves as capable engage more, overcome challenges, and master complex concepts (Schunk & Pajares, 2002).

VR can reinforce these beliefs in construction instruction by supplying realistic, low-risk practice (Birt et al., 2017). Repeated practice of construction techniques in a virtual setting builds competence without real-world consequences, promoting confidence in the application of knowledge in the real-world setting.

VR-based learning can facilitate self-efficacy growth through the four mechanisms identified by Bandura (Bandura, 1997). This research aims to leverage two of these: mastery experiences and affective states. Completing VR tasks provides concrete mastery cues, and the immersive environment can lower anxiety, sustaining effort. These principles inform RQ1 and underpin the self-efficacy measures adopted in Year 2.

2.1.2. Experiential Learning Theory

Experiential learning theory (Kolb, 1984/2014) states that knowledge is acquired through a cyclical process involving four key stages: concrete experience, reflective observation, abstract conceptualization, and active experimentation. The VR module follows this sequence: students build virtual brick walls (concrete experience), inspect their work from multiple angles and watch misplaced bricks fall (reflective observation), refine mental models of bonding patterns (abstract conceptualization), and tackle “challenge” levels that require applying those models in new contexts without guidance (active experimentation). VR’s inherent alignment with experiential learning principles is a core premise of this study. By providing realistic simulations of construction tasks, VR aims to deepen understanding beyond the usually employed passive methods like lectures or textbook diagrams (Lee et al., 2023). Unlike traditional classroom or workshop settings where material costs and time can limit iteration, VR supports repeated practice, allowing students to experiment, make mistakes, learn from them, and refine their approach in a consequence-free virtual setting (Radianti et al., 2020). This theoretical lens directly informed the design of the VR learning activities and underpins the investigation of RQ2 and RQ5.

2.1.3. Cognitive Load Theory

Sweller’s cognitive load theory (CLT) (Sweller, 1988) posits that learning is most effective when cognitive resources are optimally allocated between three types of cognitive load: intrinsic, extraneous, and germane.

VR presents both opportunities and challenges regarding cognitive load in construction education. Hands-on learning can reduce extraneous load and enhance germane load, but overly complex or poorly structured VR interfaces can increase extraneous load, leading to cognitive overload, even with enhanced user engagement (Makransky & Lilleholt, 2018). The RQ3 of this study is informed by CLT and aims to examine whether the VR learning environment effectively balances the cognitive load to optimize construction education outcomes compared to traditional instructional methods.

2.1.4. User Engagement Theory

User engagement theory (O’Brien & Toms, 2008) highlights the role of attention, interest, and motivation in sustaining interaction with digital systems. In educational contexts, engagement influences retention, motivation, and the overall learning experience (Hamari et al., 2014).

Studies on VR report stronger engagement than conventional media because immersive interaction holds attention and fosters interest (Merchant et al., 2014). Yet, novelty effects, motion sickness, or technical faults can break immersion and impair learning (Weech et al., 2019).

The RQ4 and RQ5 of this study examine how facets of VR engagement (or lack thereof), including perceived enjoyment, interest, and focused attention, relate to self-efficacy, knowledge retention, and overall user experience in landscape-construction training.

2.1.5. Drawing Insights from Theories for Research Design

These four theories work together to present a framework for this study to make the VR learning experience meaningful to the learners. Experiential learning theory provides the pedagogical blueprint by linking active practice and reflection to durable understanding. Cognitive load theory guides the VR design, ensuring that tasks challenge students without overwhelming them, thereby enabling mastery experiences. Self-efficacy theory explains how repeated success in these tasks can strengthen learners’ confidence and persistence. At the same time, user engagement theory emphasizes the motivational conditions that sustain attention long enough for learning to occur.

This integrated lens shaped the different stages of the investigation. It guided the design of the brick-masonry VR module, the formulation of the research questions, and the selection of research instruments. Surveys captured self-efficacy, engagement, cognitive load (including VRISE symptoms and perceived task difficulty), knowledge retention, and open-ended responses gathered qualitative insights. The framework also supports the analysis of interactions among variables—for example, whether high engagement mitigates elevated load or effective experiential cycles enhance self-efficacy.

Two iterations were conducted in LARC 2332: LA Construction and Administration II, a third-year LA undergraduate course on construction materials and techniques (Figure 1). Students who had taken one prior construction course and possessed minimal VR experience used the VR brick-masonry learning module as supplemental instruction. Its impact was then assessed using the different survey outcomes described above.

2.2. Research Design

This study employed an explanatory–sequential mixed-methods design (Creswell & Clark, 2017). The quantitative phase attempted to address the research questions by measuring self-efficacy, knowledge retention, user engagement, usability, and user preferences, while the qualitative phase provided elucidations of the theoretical foundations. The methodology was aimed to be comprehensive and was informed by four synergistic frameworks: self-efficacy theory, cognitive theory of multimedia learning (Mayer & Moreno, 2003), media richness theory (Daft & Lengel, 1986), and user engagement theory (O’Brien & Toms, 2008).

• Phase 1 (Year 1): A pilot study was conducted with a cohort of landscape architecture students (n = 15). The primary objectives during this phase were to evaluate the feasibility of integrating VR into the curriculum, identify technical and pedagogical challenges, and gather preliminary data on learning outcomes and user experience.
• Phase 2 (Year 2): Based on the findings and refinements made after the pilot study, one additional VR module was added and deployed with another cohort (n = 16). In this phase, a more comprehensive assessment framework was implemented to capture detailed quantitative measures (e.g., knowledge retention tests, self-efficacy scales, and validated tools to assess VR experience quality by measuring the intensity of VR-induced symptoms and effects (VRISE)) along with qualitative feedback.

The reason behind the apparently small number of participants is the usual cohort group of landscape architecture programs—typically at 15–30 students per cohort—to satisfy accreditation requirements for instructor-to-student ratio, desk critiques, and access to specialized laboratories (Landscape Architectural Accreditation Board [LAAB], 2021).

2.3. Participants and Research Setting

The participants were third-year undergraduate students enrolled in the Bachelor of Landscape Architecture (BLA) program at Texas Tech University. The course this study was conducted on was LARC 2332 Landscape Architecture Construction and Administration II. The VR modules designed for this study were introduced after standard lectures, and class materials were provided to the participants.

The participants were recruited through program announcements and provided informed consent prior to participation. No personal identifier was collected for this study, and all the responses by the participants were anonymous. Participation in this research was voluntary, and the study received approval from the Texas Tech University Institutional Review Board (IRB #: IRB2021-720). Written informed consent was obtained from all the participants before the survey.

To preserve academic equity, every student in the cohort received identical instructional content and assessments, a practice consistent with recommendations for educational technology research (Li et al., 2018). Although this approach promotes fairness, it also limits causal inference because no control group was used, a constraint acknowledged in the study’s limitations and targeted for future work.

2.4. VR Module Development

The VR modules were designed to provide a hands-on, fully immersive, and fully interactive experience to learn steps in brick masonry construction. The development process involved the following stages:

2.4.1. Conceptualization and Instructional Design

The instructional design of the VR modules was guided by the principles of experiential learning theory (Kolb, 1984/2014), structured to provide a complete cycle of concrete experience, reflective observation, abstract conceptualization, and active experimentation. To accurately represent the brick masonry details, including brick terms and types, along with different brick bond patterns, references were taken from the referred course textbook (Allen & Iano, 2019).

The present stage of VR development consists of two VR modules for brick masonry learning:

Module A: Bond Terminology and Pattern Construction (lesson + challenge levels) covers fundamental brick types and four standard bonds (Running, English, Flemish, Common) and was delivered in both Year 1 and Year 2.

Module B: Corner Conditions and Wall Junctions extends Module A by focusing on corner construction for the same bond set and was introduced in Year 2 following pilot feedback.

Each student cohort may engage with both modules during a single semester, ideally in Weeks 5–6 of the construction course. The self-paced design allows these experiences to be scheduled in any semester, since the content is compatible with both Meta Quest 2 and 3 headsets. Once added to the institutional headset library, the modules remain available for review or independent study throughout the academic year.

2.4.2. Technical Development

VR content was developed using Unreal Engine 5 to ensure high-fidelity graphics and interactive realism. The modules were optimized for deployment on Meta Quest devices, allowing full-scale, immersive experiences (Figure 2 and Figure 3).

The technical development included

a. 

3D Modeling: Consisted of creating detailed virtual environments, construction elements such as brick walls and corners with a specific bond type, and reference frames for students to place the interactive bricks onto. Rhinoceros 3D software (version 7) and Unreal Engine 5 were used in this process.

b. 

Interactive Programming: The interaction system was constructed using the blueprint system of the game engine Unreal Engine 5 and employed physics-based manipulation with six degrees of freedom, allowing natural movements for picking, placing, rotating, and stacking bricks (Müller et al., 2007). The module adhered to established construction-simulation principles by allowing students to grasp objects using Unreal Engine’s grab-physics system, experience realistic gravity and collision responses, and receive reinforcing haptic feedback through controller vibration.

c. 

Level Design: The first VR module that was used for both Year 1 and Year 2 data collection consisted of the following sections:

• Brick Terminology and Types: Interactive exploration of brick nomenclature, standard dimensions, and common variations.
• Running Bond: This level introduces the basic stretcher bond pattern, including proper overlap and alignment principles. It establishes foundational concepts before introducing more complex patterns.
• English Bond: Exploration of alternating courses of headers and stretchers, including corner conditions and wall thickness considerations.
• Flemish Bond: Instruction on the alternating header–stretcher pattern within each course, including dimensional relationships and alignment requirements.
• Common Bond: Introduction to the hybrid pattern with periodic header courses, including structural implications and course counting conventions.

The second VR module, which was only added to the second-year data collection, included brick wall corner construction sections for the aforementioned bonds.

Each section had a lesson level and a test level.

(a)

The lesson (tutorial) levels consisted of

-

Completed example wall demonstrating the target bond pattern

-

Interactive reference frame for brick placement practice

-

Physical simulation allowing natural brick manipulation and stacking

-

Spatial audio instructions providing contextual and theoretical guidance.

-

Visual reference guides and terminology overlays

(b)

The test (challenge) levels consisted of

-

Assorted interactive bricks

-

Empty construction area for pattern replication

-

No visual references to completed examples

-

Audio instruction to clearly delineate the task requirements for the students.

d. 

Open-Platform Workflow and Reproducibility: All VR modules were prototyped and compiled in Unreal Engine 5, an open-source game engine distributed under a permissive license that allows free academic redistribution. The modules run on Meta Quest 2 (Year 1) and 3 (Year 2) headsets without additional licensing costs. To support replication, the complete Blueprint graphs, Level Blueprints, walk-through documentation, and asset dependencies will be shared with interested educators and researchers upon request. Developing an open platform mitigates proprietary bindings and answers broader calls for computational reproducibility in educational technology research (Stodden et al., 2013). It is essential to note that the visual-scripting environment provided by Blueprints also enables non-programmers to customize interaction logic, assessment triggers, and feedback channels, facilitating the adaptation of the modules to other masonry topics or construction methods. This open-access strategy ensures that the broader community of design educators and researchers can audit, extend, and re-contextualize the XR materials to their unique lesson requirements.

2.5. Data Collection Methods

A combination of quantitative and qualitative data was collected to evaluate the impact of VR-enhanced instruction through online surveys powered by Qualtrics. The surveys were distributed immediately after the participants experienced the VR modules (Figure 4 showing participants experiencing the learning modules in VR).

2.5.1. Year 1 Data Collection

(a)

Likeability Survey: In year 1, the survey (Appendix A) consisted of comparing the VR module to conventional teaching methods, students’ perceived usefulness of the VR module, and basic questions on user engagement and user experience.

(b)

Qualitative Responses: The survey also included an open-ended response from the students, asking which aspects of the VR module they liked and what could be improved about the overall experience.

2.5.2. Year 2 Data Collection

With the learnings from Year 1, the data collection method was refined in Year 2, considering different theoretical frameworks and established measures to understand user experience. This helped with a deeper understanding of both the positive and negative impacts of incorporating VR into the conventional educational framework. The data collection consisted of

(a)

Likeability Survey: Similar to Year 1, the likeability survey consisted of questions on comparing VR-aided and conventional lesson delivery methods and assessing the perceived usefulness and effectiveness of the VR module.

(b)

Self-Efficacy Survey: Grounded in Self-Efficacy Theory (Bandura, 1997), this survey assessed users’ confidence in their knowledge and ability to implement different components delivered through the VR learning modules.

(c)

Knowledge Retention Survey: Drawing on Cognitive Load Theory (Sweller, 1988) and Experiential Learning Theory (Kolb, 1984/2014), this survey was designed to assess the impact of VR on the retention of educational content. It employed multiple-choice questions targeting various learning components—such as brick terminology, typology, and bonding methods—to objectively evaluate participants’ understanding and long-term retention of key concepts.

(d)

User Engagement Survey: Based on User Engagement Theory (O’Brien & Toms, 2008), this survey quantified the degree of involvement, attention, and interest experienced by users during their interaction with the VR system. Drawing on the research of Parong and Mayer (Parong & Mayer, 2018), the survey items were meticulously developed to capture the dynamic engagement levels essential for immersive learning environments.

(e)

Qualitative Responses: In addition to the quantitative instruments, open-ended questions were included to gather qualitative feedback.

(f)

VRNQ Survey: The Virtual Reality Neuroscience Questionnaire (VRNQ) was employed to assess specific VR-related experiences, such as presence, immersion, and system quality (Kourtesis et al., 2019). This tool complements the other surveys by focusing on the distinct experiential aspects of VR, thereby offering a comprehensive perspective on the technology’s impact.

The survey instruments were administered in two separate parts: components (a) through (e) were combined and distributed as a single questionnaire (Appendix B), while the VRNQ survey (f), focusing on VR-specific experiential dimensions, was administered independently in a separate survey form (Appendix C).

Data from all instruments were collected digitally and stored securely in compliance with ethical standards. Quantitative data were analyzed using descriptive statistics. Qualitative responses were coded manually using MaxQDA software (version 24), and the active theming facilitated the identification of key themes and the systematic categorization of responses. This data analysis process ensured that the conclusions drawn from the study were based on multiple converging sources of evidence.

To summarize the data collection process, the pilot phase in Year 1 provided baseline data on feasibility, user experience, and technical challenges. This initial feedback drove the refinements implemented in Year 2, which were designed to capture measures of learning outcomes, self-efficacy, user engagement, and knowledge retention. The combination of quantitative surveys, standardized testing, and qualitative feedback allowed for an analysis of the VR module’s impact on the instructional process.

Each methodological component aligned with a specific research question, enabling a systematic evaluation of VR integration. The sequential design, combined focus on technical and pedagogical factors, and use of both quantitative and qualitative measures offer a reproducible framework for future educational technology studies.

3. Results

3.1. Year 1 Results

3.1.1. Year 1 Quantitative Results

The likeability survey aimed to assess students’ perceptions of the VR module’s effectiveness in aiding their understanding of the content (e.g., brick masonry construction), its usability, and its role in the learning process. In Figure 5, the findings are summarized through stacked bar chart visualizations and statistical distributions of student responses.

a. 

Student Perception of VR’s Contribution to Understanding Brick Masonry Construction

The likeability survey indicated that 86.67% of the participants either “Strongly Agreed” or “Somewhat Agreed” that the VR game improved their understanding of the brick masonry layout; 6.67% “Somewhat Disagreed,” none “Strongly Disagreed,” and the remaining 6.66% selected a neutral option. When the statement was inverted—“The VR module did not help me understand brick masonry organization”—80% “Strongly Disagreed” or “Somewhat Disagreed,” 6.67% “Somewhat Agreed,” and 13.33% chose a neutral response. Together, these distributions suggest that most students viewed the module as pedagogically valuable, though a small minority perceived limited benefit.

b. 

Integration of VR in the Learning Process

The students assessed whether the VR module should accompany lectures and assigned readings. In total, 80% of the participants “Strongly Agreed” or “Somewhat Agreed” that it could “supplement traditional learning methods effectively,” demonstrating broad support for integrating interactive digital tools into construction instruction. When the module was framed as “merely a fun experience without meaningful learning value,” 73.33% “Strongly Disagreed” or “Somewhat Disagreed,” whereas 6.67% “Strongly Agreed.” These results confirm that most participants perceived clear pedagogical benefits, though a small subset viewed the experience as chiefly recreational.

c. 

Enhancement of Scale, Processes, and Material Understanding

A key learning objective of the VR module was to improve students’ comprehension of construction scale, materiality, and process sequencing. Survey results indicate that 80% of the students “Strongly Agreed” or “Somewhat Agreed” that the VR game enhanced their understanding of brick masonry elements, suggesting a positive outcome in achieving this goal. The minority who remained neutral or disagreed with this statement (20%) highlighted the need for further refinement of the instructional content or usability aspects of the VR experience.

d. 

Student Engagement and Enjoyment

The level of engagement and enjoyment in an educational tool has a significant impact on its adoption and effectiveness. In assessing whether students found the VR experience enjoyable, 86.67% of the students “Strongly Disagreed” or “Somewhat Disagreed” with the statement that the VR game was neither enjoyable nor educational. This indicates that the majority found the experience engaging, suggesting that well-designed VR environments can enhance student motivation and willingness to engage with the material.

e. 

Self-Explanatory Nature of the VR Experience

A critical usability factor for educational VR tools is navigation intuitiveness. When asked whether they found the VR module to be self-explanatory, 53.33% of the students “Strongly Agreed” or “Somewhat Agreed,” indicating that most participants were able to use the module without needing extensive external guidance. However, 40% of the students expressed disagreement, suggesting that improvements should be made in either the onboarding process or in the clarity of instructions provided within the VR environment.

f. 

Technical and Physical Difficulties Encountered

While VR offers a promising avenue for immersive learning, technical difficulties and physical discomfort can be limiting factors. Concerning navigation, 46.67% “Somewhat Agreed” or “Strongly Agreed” that they ran into technical difficulties, whereas 40% “Somewhat Disagreed” or “Strongly Disagreed,” revealing that a sizable minority struggled while many progressed with few problems. Physical discomfort proved more common: 64.29% “Strongly Agreed” or “Somewhat Agreed” that they experienced visual strain, auditory issues, or related sensations, highlighting the need for adjustable comfort features and ergonomic refinements. Even so, 66.67% “Somewhat Agreed” or “Strongly Agreed” that they had “minimal technical difficulties” and found the module easy to navigate, implying that most students still regarded the interface favorably.

g. 

Perceived Suitability of VR for Landscape Architecture Construction Education

The final survey question assessed whether VR is suitable for teaching landscape architecture construction, materials, and details. In total, 80% “Strongly Agreed” or “Somewhat Agreed” that VR “could enhance the learning process for brick masonry construction,” signaling broad confidence in its capacity to convey spatial and structural concepts. When the reverse statement—“VR is unsuitable for construction education”—was posed, 66.67% “Strongly Disagreed” or “Somewhat Disagreed,” whereas 13.33% “Somewhat Agreed.” Thus, most participants endorsed VR’s instructional value, although a small minority remained cautious about its wider applicability.

3.1.2. Year 1 Qualitative Results

This section presents the findings from the qualitative responses collected in Year 1 of the study. The participants provided open-ended feedback regarding their experiences with the VR module, specifically focusing on aspects they found beneficial and areas they believed could be improved. Thematic analysis was used to categorize the responses into major themes.

a. 

Positive Aspects of the VR Module

The participants were asked to describe which aspects of the VR module they liked the most. The responses were analyzed and categorized into the following themes:

• Interactivity and Hands-On Experience:

Some students highlighted the interactive nature of the VR module as a key advantage. The ability to actively build brick walls, manipulate individual bricks, and engage with different bond patterns was frequently cited as an enjoyable and engaging feature. For example, one participant stated,

“I enjoyed having the opportunity to build and construct the walls myself, which made me feel more engaged compared to just reading about it.”

• Spatial and Scale Awareness:

Several students appreciated how the VR experience helped them understand the spatial relationships between the construction elements. The immersive environment allowed them to see brick bonds from different perspectives, reinforcing their understanding of construction sequencing and material arrangement. A participant noted,

“The ability to move around the models and see the structure from multiple angles really helped me grasp the relationships between different brick courses.”

• Novelty and Engagement of VR Technology:

Some students emphasized that the VR module provided an exciting and novel way to learn about brick masonry. Participants who had never used VR before found the experience intriguing and engaging, making learning more enjoyable. One response mentioned,

“I have never used VR before, so once I figured out the controls, it became a fun and unique way to learn about construction.”

• Realistic Construction Application:

Another recurring theme was that the VR module simulated close-to-real-world construction scenarios, allowing students to practice bricklaying techniques in a virtual environment. One student commented,

“The application of usable brick objects made it feel like I was actually constructing something rather than just watching a video or looking at diagrams.”

b. 

Areas for Improvement

The participants were also asked to describe aspects of the VR module that they felt could be improved. Their responses were analyzed and grouped into key themes:

• Brick Alignment and Stability Issues:

A common concern was the difficulty in placing bricks, as some students reported that the bricks would bounce off each other or fall off the placement platform too easily. One participant expressed,

“The bricks bounce off each other, so it made it hard to make them align properly, which was frustrating.”

Another student mentioned that the lack of a snapping function made it difficult to place bricks, stating accurately,

“If there was a way to make the bricks snap in place when they are correctly aligned, it would make the experience much smoother.”

• Movement and Navigation Challenges:

Some participants found the navigation controls within the VR environment difficult to use. Movement types and locomotion methods were highlighted as potential areas for improvement. One participant wrote,

“Movement types need to be improved. There’s a version where pushing a button makes you move instead of teleporting—it would be more intuitive.”

• Weight and Physical Behavior of Bricks:

Students commented on the inaccurate physics properties of virtual bricks. The bricks were perceived as too light or lacking realistic physics constraints, making the stacking process less natural. One student noted,

“Bricks were too light, and it didn’t feel like they had weight. They should be harder to move, like real bricks.”

• Need for Background Audio:

Some suggested adding background audio or guided instructions to enhance the learning experience. They felt that additional audio cues could improve engagement and clarify task objectives. One participant mentioned,

“Needs background music. The silence made the experience feel incomplete.”

• Technical and Usability Improvements:

Some students noted minor technical issues that impacted their overall experience. These included difficulties keeping blocks on the placement platform and occasional glitches in object manipulation. One participant remarked,

“I had trouble keeping the blocks on the platform—they kept sliding off, which made it frustrating to complete the exercise.”

3.1.3. Summary of Year 1 Results

The Year 1 findings provided initial insights into the effectiveness of the VR module in facilitating student learning in brick masonry construction. The likeability survey results demonstrated mostly positive reception, with participants reporting that the VR experience contributed to their understanding of brick bonds, material scale, and construction techniques. The participants also expressed that the module complemented traditional lectures and reading materials, highlighting the potential of VR as an instructional supplement. However, some students encountered technical difficulties and usability issues, such as object manipulation and navigation challenges. This finding indicates that onboarding learners is a potential challenge, as a portion of the participants required additional time and support to familiarize themselves with the VR interface and controls before fully engaging with the learning content.

The qualitative responses further supported these findings, highlighting key advantages of the VR module, such as its hands-on interactivity, immersive visualization of construction concepts, and novel approach to learning. However, the students also identified areas for improvement, including better brick alignment mechanics, enhanced movement controls, and more intuitive interface elements. Some participants also mentioned the need for additional guidance, such as background audio or more apparent visual cues, to support independent learning.

Year 1 delivered useful baseline data, but also revealed gaps in understanding VR’s broader educational impact. Key dimensions—user engagement, self-efficacy, knowledge retention, and VR-specific usability—remained under-examined. These factors are crucial for determining whether VR genuinely enhances student confidence, fosters lasting learning, and operates effectively in the classroom environment. The Year 2 iteration, therefore, adopted a more structured evaluation to close these gaps and provide a fuller account of VR’s contribution to construction education.

3.2. Year 2 Results

3.2.1. Year 2 Quantitative Results

Upon understanding the user discomfort and engagement parameters from Year 1, the quantitative data collection for Year 2 was elaborated. It consisted of likeability data, user engagement data, self-efficacy data, knowledge retention data, and user experience data.

Year 2 Likeability Survey Results

This portion of the Year 2 quantitative data collection was aimed at comparing the VR experience with traditional teaching methods (Figure 6).

a. 

Effectiveness of VR in Understanding Masonry Bonds

Similar to Year 1, the students compared the VR module with traditional lectures to clarify the concepts of masonry bonds. In total, 30.77% “Somewhat Agreed” that VR offered a clearer understanding, while an identical 30.77% selected “Neither Agree nor Disagree,” implying that many saw the module as useful, yet not markedly better than lectures.

When asked whether 2D drawings were easier for visualizing bonding patterns than the VR experience, 30.77% again remained neutral, 30.77% “Disagreed,” and 30.77% “Agreed.” Perceptions were therefore evenly split, indicating that conventional drawings still served as a preferred aid for a substantial portion of the cohort.

A similar division appeared when the students judged VR against 3D modeling software for teaching bond corners: 30.77% were neutral, 23.08% “Agreed,” and 15.38% “Strongly Agreed,” suggesting that while some valued the immersive approach, others rated existing 3D tools as equally or more effective for representing complex bond patterns.

b. 

VR Compared to Traditional Learning Methods

When asked to compare the effectiveness of VR with textbooks and static images, 38.46% of students agreed that traditional methods were more helpful than VR, while another 30.77% remained neutral. This indicates that while some students preferred VR for its interactive and immersive elements, a substantial number still found conventional learning materials to be more reliable for grasping brick bonding concepts.

Additionally, when comparing VR with class lectures and discussions, 30.77% agreed that lectures were more effective, while another 30.77% remained neutral. This reinforces the idea that VR alone may not be sufficient for understanding construction techniques, but can be helpful when integrated alongside traditional teaching methods.

c. 

Engagement and Interactive Learning

Interactivity proved central to engagement, as 53.85% of the students agreed or strongly agreed that the module’s interactive features enhanced learning compared to non-interactive materials, indicating a broad appreciation for hands-on virtual practice. Yet the absence of tactile feedback remained a concern; 30.77% agreed, and another 30.77% were neutral that the lack of physical bricks and mortar limited the modules’ effectiveness. These results underscore a persistent gap between virtual simulation and sensory demands, such as material texture, weight, and object handling of real-world construction.

d. 

Preferences for Learning Methods

A new aspect introduced in Year 2 was assessing whether students preferred the flexibility of VR-based learning over the structured classroom environment. The results showed that 30.77% of the students preferred the flexibility of VR, while another 30.77% remained neutral. This suggests that while some students appreciated the ability to learn at their own pace in VR, others did not find it to be a decisive advantage over traditional learning structures.

Summary of Year 2 Likeability Findings

The Year 2 likeability survey clarifies students’ engagement with the virtual reality module in relation to RQ4 and RQ5. A clear majority—53.85%—agreed or strongly agreed that the interactive checkpoints and immediate feedback sharpened their understanding, in line with user engagement theory, which links sustained attention to learning value (O’Brien & Toms, 2008). At the same time, evaluations of comparative clarity revealed that only 30.77% somewhat agreed that VR provided a clearer explanation of masonry bonds than lectures, 30.77% remained neutral, and the remaining 38.46% did not share that view, underscoring the value of lectures, textbooks, and 2-D drawings. Experiential learning theory helps explain this stance: without tactile contact with bricks and mortar, the virtual tasks cannot complete Kolb’s cycle of concrete experience, reflection, abstraction, and active experimentation. Indeed, 30.77% agreed and another 30.77% remained neutral that the absence of tactile feedback limited the training’s effectiveness, highlighting a gap that physical workshops could fill to consolidate mastery experiences and strengthen self-efficacy (Bandura, 1997).

These results suggest that the module’s principal contribution lies in scaffolding early conceptual visualization while leaving traditional methods to reinforce materiality and craft. They also reveal a boundary condition: engagement alone, though necessary, may be insufficient to displace conventional learning practices unless complementary hands-on experiences are provided. Future research should therefore pair VR with live masonry labs and embed observational or performance-based measures to test whether blended sequences yield additive learning benefits without inflating cognitive load.

Year 2 User Engagement Survey Results

The User Engagement Survey aimed to evaluate students’ interest, motivation, and engagement while using the VR module to learn brick masonry construction. The survey included a Likert-scale questionnaire covering aspects such as mental effort, challenge, enjoyment, motivation, emotional responses, and perceived learning benefits. Additionally, correlation and significance tests were conducted to examine the relationships between different engagement factors.

a. 

Mental Effort and Perceived Challenge

The students were asked to indicate the extent to which they exerted mental effort while using the VR module. The responses were widely distributed (Figure 7), with a median response level of 5 (Agree) on a 7-point scale (1 = Strongly Disagree, 7 = Strongly Agree). This suggests that most students found the VR experience to be cognitively demanding, but within a manageable range.

Similarly, for perceived challenge, responses clustered around 4 (Neutral) to 5 (Agree), indicating that while the students found the module appropriately challenging, it did not create excessive difficulty.

b. 

Understanding and Learning Outcomes

Student responses to understanding reflected the likeability pattern and addressed RQ2—knowledge retention while intersecting with RQ4—user engagement. Median ratings of 6 on a seven-point scale for interest, perceived benefit, and motivation indicate that most participants felt they had “grasped the material well” after completing the virtual lesson. In user engagement terms, the module maintained both affective (interest) and cognitive (perceived usefulness) engagement—factors linked to deeper processing and longer-term recall (O’Brien & Toms, 2008). Experiential learning theory offers a complementary lens: interactive checkpoints and immediate visual feedback likely enabled rapid concrete–reflective cycles, helping students encode brick-bond concepts into durable schemas.

Cognitive load theory cautions, however, that high motivation alone cannot guarantee efficient learning if intrinsic and extraneous demands are misaligned. Performance data and delayed post-tests, absent from this survey, are still required to verify lasting retention. Even so, the convergence of strong engagement scores with students’ confidence in comprehension supports the module’s pedagogical value.

c. 

Enjoyment and Future Preference for VR Learning

Enjoyment ratings and future preference offer further insight into RQ4 (user engagement) and extend the qualitative dimension of RQ5. A median enjoyability score of 6 suggests that the immersive lesson was genuinely appreciated. User engagement theory links such positive affect to sustained attention and motivation, suggesting a foundation for continued integration (O’Brien & Toms, 2008). The same affective response translated into behavioral intention: most respondents marked “Agree” to “Strongly Agree” when asked whether they would like to learn additional topics through virtual reality, signaling broad support for the continued integration of VR into the construction curriculum.

Experiential learning theory implies that this willingness to re-engage reflects a desire to repeat the concrete–reflective cycle with new content, potentially accelerating skill acquisition as students tackle increasingly complex masonry lessons. Cognitive load theory, however, cautions that enthusiasm may decrease if future modules raise intrinsic complexity without parallel scaffolding or if novelty effects fade (Sweller, 1988). High enjoyment and a strong preference for future use, therefore, confirm the modules’ motivational appeal. At the same time, it underscores the need for iterative usability testing to keep cognitive demands balanced and ensure that engagement translates into measurable learning gains.

d. 

Negative Affective Responses: Uninterest, Confusion, and Frustration

The radar chart shows an overall positive emotional response from the participants, characterized by low levels of negative affect such as boredom, sadness, or fear. Moderate scores related to confusion indicate some cognitive challenge, but not enough to hinder engagement or cause disengagement from the learning experience (Figure 8).

Only one affective dimension reached 50%: confusion. In cognitive load terms, this suggests that the task imposed a manageable degree of intrinsic complexity—enough to stimulate problem-solving but not so high as to trigger disengagement (Sweller, 1988). This balance is important because excessive ease can erode engagement, whereas overload reduces motivation and retention. The moderate confusion score highlights an instructional design guideline: future iterations should introduce just-in-time hints or adaptive pacing to convert transient uncertainty into deeper reflection without inflating extraneous cognitive load. Low scores on frustration-related emotions further suggest that the VR interface achieved the desired equilibrium between challenge and support.

Overall, the emotional landscape portrayed in Figure 8 strengthens earlier evidence that VR can foster an engaging environment for construction learning. Positive emotions combined with a manageable challenge appear to promote self-efficacy gains and support durable knowledge retention.

e. 

Correlation Analysis: Relationships Between Engagement Variables

The interrelations among affective, cognitive, and motivational indicators were mapped in the correlation matrix (Figure 9), addressing RQ4 (user engagement) while informing RQ3’s concern with cognitive load. Enjoyability correlated strongly with both perceived benefit (r = 0.72) and interest capture (r = 0.68), implying that learners who found the simulation pleasurable simultaneously judged it pedagogically valuable. This pattern is supported by user engagement theory, which posits that positive affect amplifies perceptions of usefulness and hence sustains attention (O’Brien & Toms, 2008). Motivation, in turn, aligned closely with happiness (r = 0.81) and excitement (r = 0.69). These links suggest that positive emotions foster the persistence needed for deliberate practice, a critical route to mastery in self-efficacy theory.

Cognitive load theory clarifies the trade-off between effort and affect. Reported mental effort correlated moderately with perceived challenge (r = 0.37), but displayed a small negative association with enjoyment (r = −0.22). This pattern implies that a moderate level of difficulty stimulates germane processing, whereas excessive demand begins to diminish positive affect. Design refinements should therefore target extraneous load so that the inherent complexity of brick-bond sequencing translates into productive engagement rather than frustration.

f. 

Statistical Significance Analysis: p-Value Heatmap

The p-value heatmap (Figure 10) extends the correlation analysis by confirming which engagement links are unlikely to have arisen by chance, offering evidence through statistical significance for RQ4 (the role of user engagement in effectiveness) and, indirectly, for RQ2 (knowledge retention). Enjoyability correlated significantly with perceived comprehension (p < 0.05). This result supports user engagement theory’s argument that positive affect promotes deeper cognitive processing (O’Brien & Toms, 2008), resonating with the themes of experiential learning theory. In-session motivation showed an even stronger association with the students’ preference for future VR use (p < 0.01). The finding indicates that positive affect extends into behavioral intention, prompting learners to seek further immersive practice. Such voluntary repetition provides the mastery experiences central to self-efficacy theory.

Captured interest predicted willingness to explore additional VR topics (p < 0.01), underscoring sustained attention as a precursor to broader curricular adoption. The inverse correlation between “uninteresting” and “enjoyable” reached significance at p < 0.05, validating the scale’s polarity and confirming that the module effectively suppressed boredom, a known trigger for disengagement.

Not all relationships achieved significance. Mental effort failed to correlate with perceived benefit, and motivation showed no reliable link to sadness. From a cognitive load perspective, this suggests that the task demanded a moderate level of effort—neither trivial nor overwhelming—and that high motivation was not simply the absence of negative affect. These null findings caution against assuming that every facet of engagement uniformly predicts perceived value and highlight the multidimensionality of user experience in VR.

Two limitations temper these conclusions. The small sample limits statistical power and heightens the risk of Type I error, so replication with larger cohorts is essential. Moreover, the correlations cannot establish causality; it remains unclear whether enjoyment drives comprehension or vice versa. Even with these constraints, the converging evidence in Figure 9 and Figure 10 strengthens confidence that a blend of enjoyment, attentional capture, and balanced cognitive demand is critical for transforming immersive novelty into meaningful learning gains while avoiding cognitive overload.

Year 2 Self-Efficacy Results

The self-efficacy survey in Year 2 measured students’ confidence in understanding and applying various brick bonds after using the VR module. The responses were collected on a 5-point Likert scale (1 = Not Confident at All, 5 = Extremely Confident).

a. 

Confidence in Understanding Brick Bonds

Figure 11 shows that most students rated their understanding of Running and Common Bonds as Confident or Extremely Confident (median ≈ 4.5 on the 5-point scale). In contrast, English and Flemish patterns drew more “Neutral” ratings, and each corner variation scored lower than its corresponding straight bond. Self-efficacy theory (Bandura, 1997) suggests that the VR lesson delivered credible mastery experiences for the simpler bonds but achieved only partial mastery for the more intricate layouts. Experiential learning theory (Kolb, 1984/2014) offers a complementary view: the immersive setting supplied rich, concrete experiences and rapid reflection; yet, the lack of tactile feedback may have constrained abstract conceptualization of the complex patterns.

b. 

Confidence in Applying Brick Bonds in Real-World Construction

When asked about performing the same bonds on a real job site (Figure 12), the median scores were lower compared to the understanding of the construction method. Running Bond remained the most transferable, but Flemish Bond and all corner applications elicited noticeable uncertainty. Cognitive load theory helps explain the gap: as corner construction or other comparatively complex constructions, such as Flemish Bond, impose higher intrinsic load without physical cues, the virtual task may not have generated sufficient germane processing to support transfer.

c. 

Heatmap Analysis: Confidence Trends Across Bonds

A heatmap visualization was generated to compare confidence levels across all bonds (Figure 13), distinguishing between understanding and application confidence.

The “understanding” row is warmer than the corresponding “application” row, underscoring a persistent gap between conceptual grasp and perceived site competence. Running Bond again elicited the strongest confidence ratings. Flemish Bond and its corner variant showed the weakest, reflecting the pattern’s geometric complexity. Across all bonds, corner conditions scored lower than straight-wall segments, indicating that students view three-dimensional intersections as demanding aspects of brickwork. These findings point to a need for added scaffolding, such as guided demonstrations, extended VR challenges, or physical mock-ups, to deepen the mastery of corner construction.

d. 

Key Observations and Trends

Theoretical confidence surpassed practical confidence across every bond, exposing a gap between understanding and application. Running Bond ranked first, followed by Common, English, and Flemish Bonds, a progression that reflects increasing geometric complexity and signals the need for scaffolds proportional to intrinsic load. Although Figure 8, Figure 9 and Figure 10 record sustained enjoyment and motivation, engagement alone did not overcome spatial transfer challenges, reaffirming Bandura’s assertion that authentic mastery experiences are required to build self-efficacy.

Summary of Year 2 Self-Efficacy Findings

The VR module raised students’ confidence in understanding brick-bond principles, notably for simpler patterns. Confidence in applying those principles remained lower, most noticeably for Flemish Bonds and all corner details. This pattern is theoretically consistent: positive affect heightened motivation (O’Brien & Toms, 2008), but the absence of kinesthetic cues such as weight and texture disrupted the experiential cycle and allowed intrinsic load to reduce practical confidence. Future iterations should pair headset sessions with tactile mock-ups or with guided overlays at corner stages to convert conceptual mastery into practical self-efficacy. Because the findings rely on self-reporting from a small cohort, later studies should include objective performance measures to verify that confidence gains translate into demonstrable skill.

Year 2 Knowledge Retention Results

The knowledge retention survey in Year 2 evaluated students’ ability to recall the lessons learned in the VR module. The assessment consisted of multiple-choice applied knowledge questions covering Running Bond, Flemish Bond, English Bond, Common Bond, and their respective corner conditions, along with basic brick terminology. The correctness of student responses was analyzed to determine retention rates across different masonry concepts (Figure 14).

a. 

Overall Knowledge Retention Trends

Around half of the cohort (53.8%) recalled the definitions of common brick terminologies, signaling partial consolidation of core vocabulary. Recall was strongest for Running Bond: 84.6% of students answered its characteristics correctly. Accuracy declined with rising geometric complexity: Flemish Bond and Common Bond yielded 53.8% and 30.8% correctness, whereas English Bond dropped to 15.4%, respectively. In cognitive load theory terms, the pattern illustrates how higher intrinsic complexity in the absence of additional scaffolds depresses retention (Sweller, 1988).

b. 

Retention of Corner Bond Patterns

Corner configurations sharply reduced retention. Correct answers for Running Bond fell from 84.6% to 30.8%. Flemish corners dropped to 23.1%, and English and Common corners reached only 30.8% and 15.4%, respectively. These figures show that the students struggled to extend planar schemes to three-dimensional junctions, mirroring the self-efficacy pattern noted in the “Year 2 Self-Efficacy Results” section. Experiential learning theory helps explain the gap: the VR lesson offered practice opportunities in straight courses but provided few opportunities for reflection or guided experimentation, limiting the formation of spatial-transfer schemas.

Summary of Year 2 Knowledge Retention Findings

The VR intervention improved basic terminology and the simplest bond pattern knowledge (Running Bond, 84.6%), but proved less effective for complex layouts and especially for corner applications. This outcome supports cognitive load theory: greater intrinsic complexity, unaccompanied by matching scaffolds, constrains learning. Similarly, experiential learning theory emphasizes that durable memory requires iterative, hands-on engagement. Future iterations should combine repeated VR exposure with corner-specific sessions or physical demonstrations to diminish the retention gap.

Year 2 User Experience Results from Virtual Reality Neuroscience Questionnaire (VRNQ) Survey

The VRNQ survey in Year 2 was designed to evaluate students’ overall experience with the VR module by assessing key usability and performance metrics. The questionnaire covered four primary categories: User Experience, Game Mechanics, In-Game Assistance, and VR-Induced Symptoms and Effects (VRISE). Responses were recorded on a 7-point Likert scale (1 = Poor Experience, 7 = Excellent Experience), allowing for an analysis of the VR system’s strengths and limitations (Figure 15).

a. 

User Experience and Game Mechanics

By averaging scores by category, levels of user experience were identified through different aspects of the VR learning modules (Figure 16).

User Experience earned a mean rating of 6.37/7, showing that students regarded the interface as intuitive, the visual immersion effective, and the lesson flow coherent—features that user engagement theory links to sustained attention and motivation (O’Brien & Toms, 2008). Game Mechanics followed at 6.08, indicating that brick manipulation and teleport navigation were deemed functionally sound. Open-ended comments recommended modest refinements, such as adding haptic cues and smoothing turn rates, to deepen interactivity without increasing extraneous cognitive load.

b. 

In-Game Assistance and Support Features

In-game assistance averaged 6.27/7, confirming that instructional scaffolds narrowed the knowledge gap during practice. From a cognitive load perspective (Sweller, 1988), VR aided in reducing extraneous load and redirected learners’ attention to germane processing. This result is also consistent with the high self-efficacy and retention scores for Running Bond.

c. 

VR-Induced Symptoms and Effects (VRISE)

The mean VRISE rating of 4.08 was above neutral, but comparatively lower than other categories. A subset of participants reported mild dizziness or eye strain, reflecting individual variability in vestibular and oculomotor sensitivity. While the discomfort did not reach levels likely to trigger disengagement, it signals an ergonomic boundary condition: prolonged exposure, lagging graphics, or faster camera motions could elevate symptoms and compromise engagement.

Key Observations and Trends Understood from VRNQ Findings

Overall, the ratings indicate that User Experience and In-Game Assistance were the module’s primary strengths. Together, they created an immersive and manageable learning environment consistent with experiential learning theory by facilitating rapid concrete–reflective cycles. Game Mechanics functioned effectively, but future iterations should increase kinesthetic realism to deepen mastery of complex tasks without adding effort. The moderate VRISE score also signals the need for ergonomic breaks and adjustable locomotion to keep students susceptible to simulator sickness engaged.

3.2.2. Year 2 Qualitative Results

The qualitative responses collected in Year 2 provide insights into the students’ experiences, perceptions, and challenges with the VR module. The responses were categorized into five main themes: Impact of VR on Learning, Perceived Benefits, Comparison to Traditional Methods, Positive Aspects of VR, and Areas for Improvement.

a. 

Impact of VR on Learning

When describing how the VR experience influenced their understanding of brick masonry construction, the students responded that VR provided a hands-on learning experience, improving their ability to visualize and conceptualize masonry techniques.

Several students emphasized that VR facilitated active learning by allowing them to engage with brick structures rather than passively observing them. One student noted,

“It was a sort of hands-on learning experience, which helped me understand better than just looking at diagrams.”

Others mentioned that VR helped them translate theoretical knowledge into spatial understanding, particularly regarding brick placements and bond patterns. A response stated,

“Helped me visualize the bricks in an almost real-world scenario, which made it easier to understand bond alignment and how walls are structured.”

VR increased the students’ engagement with complex construction concepts by converting abstract ideas into spatial representations. The module’s interactive design lets students manipulate brick bonds, which reinforces understanding through direct practice. These results suggest that VR can bridge the gap between classroom theory and on-site construction principles.

b. 

Perceived Benefits of VR Learning

When asked about the most beneficial aspects of the VR module, the students highlighted the ability to see walls and brick patterns in real time and the interactive nature of the experience.

Spatial perception was a significant benefit, as students found the 3D visualization of brick bonds more intuitive than traditional 2D drawings:

“Seeing the walls in real-time and in 3D made a huge difference. I could actually see the layers and how they stacked.”

The ability to interact with the bricks by picking them up and placing them in designated positions was frequently mentioned as a decisive advantage. One student noted,

“The hands-on aspect was great. Instead of just memorizing patterns, I actually got to build them.”

VR provided a spatial representation of masonry techniques that conventional instruction cannot replicate. Direct manipulation of virtual bricks gave the students control over the learning process and clarified complex patterns. The evidence indicates that VR enhances procedural understanding by simulating real-world interactions.

c. 

Comparison to Traditional Learning Methods

The students compared their learning experience in VR to traditional teaching methods such as lectures, textbooks, and 2D drawings.

Most students found VR to be more engaging than passive learning methods, stating that active participation helped them retain information better. One student explained,

“It’s a bit better because you’re actively doing something instead of just reading or watching slides.”

Some students noted that VR closely simulates real-world applications, making it feel like a practical training tool rather than a theoretical exercise. A participant stated,

“I like how it is as close to the real thing as possible. It makes learning brick bonds more practical.”

However, a few students preferred traditional methods for initial learning, mentioning that VR was better suited as a reinforcement tool rather than a primary instructional method. One response noted,

“I think VR is helpful, but I still prefer having diagrams and written explanations first before jumping into it.”

Most students preferred VR to conventional instruction, yet some wanted it to complement rather than replace traditional materials. They valued manipulating masonry patterns in real time, but deemed a blended sequence more effective than VR alone. These results suggest a course design in which diagrams and written explanations precede the immersive session, providing foundational scaffolding to support cognitive processing and enhance retention.

d. 

Positive Aspects of the VR Experience

The students highlighted three features as desirable: the module’s interactivity, its realistic simulation of masonry tasks, and the ease of manipulating bricks. They particularly valued being able to grasp and place virtual bricks through intuitive controller motions, reporting that this direct manipulation deepened engagement and clarified complex patterns.

“I liked the way you just grabbed the bricks and placed them—it felt very natural.”

Some students appreciated that the experience was well-structured, allowing them to progress through different bond types methodically. One response mentioned,

“The way the tasks were structured made it easy to follow along and build the bonds correctly.”

The structured learning design helped facilitate step-by-step understanding, making the experience more intuitive and guided. These findings reinforce the notion that VR can be an effective tool for experiential learning when designed with structured progression and interactive feedback.

e. 

Areas for Improvement

The students also identified aspects of the VR module that could be improved. The most commonly mentioned challenges included movement difficulties, object manipulation, and environmental adjustments.

Several students found movement controls restrictive, making it difficult to position themselves comfortably while building structures.

“The movement and ability to get closer to the bricks need improvement. Sometimes, I felt like I was too far away.”

Object placement was another concern, with some students suggesting that the bricks should have a snapping function to ensure alignment accuracy.

“Maybe have the bricks snap into place when they are aligned properly. It would make it less frustrating.”

A few students suggested that visual cues or an improved tutorial could enhance the learning experience. One participant stated,

“It would be helpful to have better instructions or a guide on how to complete each task.”

Although the students welcomed the VR module, they reported several usability issues. Movement precision and object-placement accuracy were the main weaknesses. Aligning bricks without a snapping aid was difficult, and restricted locomotion controls added frustration. Future versions should refine control mechanics and expand tutorial guidance to provide a smoother learning experience.

Summary of Year 2 Qualitative Findings

The qualitative responses highlight the substantial impact of VR on student engagement, spatial visualization, and interactive learning. The Students appreciated the hands-on nature of the experience and found it to be a more engaging and practical supplement to traditional methods. The ability to see and manipulate brick structures in real time was widely regarded as the most beneficial feature. However, students also identified challenges related to movement mechanics, object alignment, and the need for more explicit guidance. These findings suggest that while VR is an effective learning tool, refinements in usability and instructional design could further enhance its usefulness. These insights will be further examined in the discussion section to assess how VR technology can be optimized for construction education.

4. Discussion

Integrating VR LA construction education marks a complicated but promising shift from traditional pedagogy towards immersive experiential learning. The results from Year 1 and Year 2 highlight both the potential and the challenges of using VR for enhancing self-efficacy, engagement, knowledge retention, and usability. The discussion interprets these findings through four complementary frameworks: self-efficacy theory (Bandura, 1997), experiential learning theory (Kolb, 1984/2014), cognitive load theory (Sweller, 1988), and user engagement theory (O’Brien & Toms, 2008). These lenses shape guidance for VR instructional design. The analysis centers on four paired relationships—self-efficacy with knowledge retention, user engagement with usability, cognitive load with VR-induced symptoms, and experiential learning with skill acquisition—thereby linking the quantitative and qualitative results and delineating where VR instruction excels and where refinement is required.

4.1. Self-Efficacy and Knowledge Retention: Confidence vs. Performance

Self-efficacy is a critical factor in learning outcomes, as it influences how students approach and persist in mastering new skills (Bandura, 1997). The results (Figure 17) indicate that students reported high self-efficacy for basic brick bond understanding but significantly lower confidence in applying more complex masonry techniques. This aligns with the knowledge retention data, which showed high correctness rates for simpler patterns (e.g., 84.6% for Running Bond) but a sharp decline for complex bond types (e.g., 15.4% for English Bond).

The self-efficacy vs. knowledge retention scatterplot (Figure 17) highlights the mastery–experience gap described by self-efficacy theory: After guided VR practice, students felt highly competent, yet they overestimated their ability to transfer skills to new contexts. Confidence did not consistently convert into durable recall or accurate application of brick-bond techniques. According to cognitive load theory (Sweller, 1988), this discrepancy may be due to higher cognitive demands associated with more intricate bond structures.

Implications for VR-Based Learning:

These findings suggest that while VR can enhance self-efficacy, it should be supplemented with structured reinforcement strategies to support experiential learning, such as progressive skill-building, repeated exposure, and guided feedback. Future modules should also scale difficulty adaptively so challenges rise with proficiency and foster long-term retention.

4.2. User Engagement and Usability: The Impact of Interactive Learning

User engagement theory (O’Brien & Toms, 2008) emphasizes that an effective learning tool must capture attention and sustain motivation through interactivity and immersion. The user engagement survey results indicate that the students were motivated, found the VR module enjoyable, and preferred it over traditional methods. This engagement was further reflected in the VRNQ scores, which rated User Experience (6.37/7) and Game Mechanics (6.08/7) highly.

However, the correlation heatmap (Figure 18) between engagement variables and VR usability metrics suggests that while high engagement was reported, usability challenges, such as movement restrictions and object manipulation, may have introduced friction into the learning process. Some students found VR enjoyable, but noted difficulties with positioning themselves, aligning bricks, and experiencing minor discomfort. This illustrates how VR design impediments can act as the “gatekeeper” function of usability, as described by user engagement theory: positive affect can be undermined if behavioral goals are thwarted, limiting deep processing and flow.

Implications for VR-Based Learning

Cognitive load theory emphasizes that poorly designed interaction raises extraneous load, diverting resources for germane processing. Findings from this study mirror the theory and show that engagement alone is insufficient for an optimal learning experience. Usability and ergonomics should be prioritized in future iterations of VR modules, improving movement mechanics, intuitive object manipulation (e.g., snapping mechanics for brick placement), and customizable interaction settings to accommodate different user preferences.

4.3. Cognitive Load and VR-Induced Symptoms: Managing Complexity in Immersive Learning

Cognitive load theory (Sweller, 1988) states that excessive information processing demands can impede learning, particularly in immersive environments where multiple stimuli compete for attention. The knowledge retention data suggest an inverse relationship between complexity and retention. Similarly, the VRNQ results indicated that while students enjoyed the VR experience, some reported mild VR-induced discomfort (VRISE: 4.08/7).

The engagement vs. VRNQ correlation heatmap (Figure 18) highlights the relationship between mental effort, perceived challenge, and VR usability issues. While most students found VR intuitive, some experienced cognitive strain in tasks requiring complex spatial manipulation (e.g., corner bonds). This pattern implies that the students experienced cognitive overload rather than disengagement. Complex brick patterns generate a high intrinsic load, and technical difficulties add extraneous load. When both demands converge, they exceed working-memory capacity and depress performance, even if user engagement remains high, as Sweller’s cognitive load theory predicts. As seen from the VRNQ survey results (Figure 16), high scores in User Experience, Game Mechanics, and In-Game Assistance indicate that the VR module was deemed intuitive and well-structured by the users. At the same time, the correlation indicates that future iterations could benefit from enhanced onboarding and tutorial features. Improvements in “tutorialization”—such as interactive walkthroughs, adaptive prompts, or scaffolded guidance for complex tasks—may reduce confusion, enhance user confidence, and better support learners with limited prior exposure to VR environments or construction-based problem-solving.

Implications for VR-Based Learning

To reduce cognitive load and VR-induced strain, instructional designers should incorporate structured scaffolding techniques such as progressive task difficulty, embedded hints, and real-time guidance. Additionally, break intervals and adjustable comfort settings could mitigate VR-induced fatigue, ensuring that cognitive resources are effectively allocated to learning.

4.4. Experiential Learning and Skill Acquisition: Hands-On Learning in Virtual Spaces

Experiential learning theory (Kolb, 1984/2014) emphasizes the importance of active, hands-on engagement in knowledge acquisition. The qualitative word cloud (Figure 19) illustrates key terms frequently mentioned by students, such as “learning,” “experience,” and “understand,” reinforcing the idea that VR provides an immersive learning experience.

The students consistently highlighted the ability to physically interact with masonry elements as a significant advantage over traditional methods. However, some students also noted that VR should be used as a supplemental tool rather than as a standalone method, indicating the need for MR that could be used as a scaffolding for real-world masonry construction tasks. This need also echoes self-efficacy theory’s insistence on authentic mastery experiences.

Implications for VR-Based Learning

To fully integrate experiential learning principles, future VR applications should incorporate structured debriefing exercises, such as post-VR discussions, interactive assessments, and mixed-reality applications, where students can transition seamlessly between VR simulations and real-world practice.

4.5. Understanding

This study demonstrates that VR enhances engagement, confidence, and experiential learning in construction education; however, obstacles persist in usability, cognitive load control, and the retention of complex knowledge. Drawing on four learning theories, we outline guidelines for XR design that respect cognitive limits, preserve engagement without ergonomic strain, and link virtual mastery to practical competence.

Future work should test adaptive systems that scale task difficulty to each learner, apply real-time load metrics to balance immersion, and compare VR training with on-site practice in extended field studies. Although the present sample was small, the module’s open-source design and low-cost hardware favor scalable deployment. Multi-institution collaborations and data aggregation across cohorts will yield the larger samples required for generalization. Discipline-specific adaptations of this pipeline can broaden impact without altering the core interaction framework.

4.6. Recommendations for Integrating VR into Future Construction Courses

The mixed findings of this study suggest actionable guidelines for instructors and instructional designers who wish to integrate virtual reality modules into technical courses. Recommendations are grounded in the four theories that framed our analysis and in peer-reviewed evidence on XR pedagogy:

(a) 

Blend VR with physical practice to complete Kolb’s experiential cycle.

It is apparent from this study that XR cannot replace real-life brick masonry construction, as evident from the self-efficacy results. While learning, practical brick masonry installations should be accessible. Deploying the VR session before or between hands-on masonry labs would allow students to test virtual insights in real material contexts. Sequencing digital “concrete experience” with tangible experimentation reinforces mastery experiences and strengthens self-efficacy (Birt et al., 2017). MR could also play a crucial role in bridging this gap.

(b) 

Introduce complexity gradually to manage intrinsic load

Begin with linear bonds, such as Running Bond, add intermediate patterns (Common, Flemish), and culminate with corner assemblies. Progressive layering keeps cognitive demands within working-memory limits while still challenging learners to extend schemas.

(c) 

Embed adaptive guidance for instructional clarity

Provide optional slow-motion replays, ghosted placement cues, or context-sensitive hints that fade as proficiency grows. Such scaffolds convert confusion into germane load and furnish the mastery experiences critical to confidence growth (Bandura, 1997; Makransky & Lilleholt, 2018). In-game usage of AI could play a vital role in this type of adaptive gameplay and learning.

(d) 

Design for ergonomic comfort and brief, spaced sessions

Offer adjustable locomotion modes between teleportation or smooth locomotion, enforce short breaks after 15–20 min, and supply seated options for susceptible users. These steps curb VR-induced symptoms (Kourtesis et al., 2019) and preserve the positive affect that sustains engagement (O’Brien & Toms, 2008).

(e) 

Provide a structured onboarding tutorial

A brief sandbox session that covers controller mapping, object manipulation, and re-centering reduces extraneous load at the outset and allows subsequent instructional time to focus on domain content rather than interface navigation (Radianti et al., 2020).

(f) 

Align assessment with both confidence and performance.

Pair self-efficacy scales with objective tasks—e.g., timed brick-laying drills, in-VR quizzes, or delayed recall quizzes—to detect gaps between perceived and actual mastery and to guide targeted remediation.

5. Conclusions

This study explored the integration of virtual reality (VR) into brick masonry construction education, focusing on its impact on self-efficacy, user engagement, cognitive load, and knowledge retention. The findings provide actionable insights into the benefits and challenges of employing VR as an educational tool in the landscape architecture discipline, analyzed through the lenses of self-efficacy theory, experiential learning theory, Cognitive Load Theory, and user engagement theory.

5.1. Bridge Between Theory and Application

a. 

Enhancement of Self-Efficacy Through Immersive Learning

Self-efficacy is defined as an individual’s belief in their capacity to execute behaviors necessary to produce specific performance attainments (Bandura, 1997), a trait crucial in educational settings. The immersive nature of VR allows students to engage in realistic simulations, thereby enhancing their confidence in performing tasks. This study reports increased self-efficacy after participating in VR-based learning modules, in terms of both understanding and application. This aligns with previous research indicating that VR can serve as a source of self-efficacy in teacher training, enhancing educators’ confidence in their teaching abilities (Nissim & Weissblueth, 2017).

However, the study also revealed that while VR improved self-efficacy for fundamental tasks, this confidence did not always translate into improved performance. This discrepancy suggests that while VR can enhance perceived competence, additional instructional support may be necessary to ensure that this confidence aligns with actual skill proficiency.

b. 

User Engagement: A Catalyst for Active Learning

User engagement is a multifaceted construct encompassing cognitive, emotional, and behavioral dimensions, all of which are vital for effective learning (O’Brien & Toms, 2008). Interactive and immersive VR is known to significantly enhance student engagement. In this study, students exhibited heightened motivation and interest when learning through VR compared to traditional instructional methods. This finding is consistent with previous studies that demonstrate the potential of VR to improve student engagement and learning outcomes, particularly among students with learning disabilities (Lin et al., 2024).

Immersive VR allows students to explore and interact with virtual environments that are difficult to simulate in traditional classroom settings. This active participation fosters deeper cognitive processing and understanding of the subject matter. However, it is essential to balance engagement with instructional goals to prevent cognitive overload, which can impede learning.

c. 

Cognitive Load: Balancing Complexity and Comprehension

Cognitive load theory posits that the human cognitive system has limited capacity, and instructional methods should avoid overloading it to facilitate learning (Sweller, 1988). While VR offers immersivity and interactivity, it can also introduce additional cognitive demands due to navigational and usability difficulties, a trait that is present in this study. Students experienced increased cognitive load when dealing with complex tasks. This finding aligns with research indicating that VR might not be able to reduce cognitive load if it is not appropriately designed and optimized (Makransky & Lilleholt, 2018).

To mitigate cognitive overload, designing VR learning experiences that align with learners’ prior knowledge and cognitive abilities is crucial. Incorporating adaptive learning systems that adjust the complexity of tasks based on individual learner profiles can help manage cognitive load effectively, a task where the role of AI could be explored. Additionally, providing clear instructions and scaffolding within the VR environment can help learners navigate complex tasks without becoming overwhelmed.

d. 

Knowledge Retention: Translating Experience into Memory

One objective of incorporating VR into education is to enhance knowledge retention through experiential learning opportunities. Experiential learning theory emphasizes learning through experience, where knowledge is constructed through concrete experiences, reflective observation, abstract conceptualization, and active experimentation (Kolb, 1984/2014). This study found that VR-based learning improved knowledge retention of some of the easier construction methods (such as Running Bond), but not as much for the more complex types of brick bonds (such as Common Bond or Flemish Bond).

This outcome suggests that while VR can effectively introduce and reinforce concepts, additional strategies may be necessary to ensure better retention. These strategies could include integrating VR experiences with traditional teaching methods at regular intervals, providing opportunities for repeated practice, and encouraging reflective activities that promote deeper processing of the educational material. Additionally, the design of the VR module plays a crucial role in long-term retention, and incorporating effective audio and visual cues into the experience may lead to improved learning outcomes.

5.2. Implications for Instructional Design in VR-Aided Learning

The findings of this study have several implications for the design and implementation of educational VR environments that may help future instructional designers:

1. 

Alignment with Learning Theories: Effective VR educational tools should be designed in accordance with established learning theories. For instance, incorporating elements that enhance self-efficacy, such as achievable challenges and immediate feedback, can boost learners’ confidence and motivation. Additionally, applying cognitive load theory principles by user-friendly interfaces and adaptive information flow can prevent cognitive overload (Sulisworo et al., 2024).

2. 

Scaffolding and Support: Providing scaffolding within VR environments can assist learners in managing complex tasks. This support can take the form of guided tutorials, prompts, and cues that help learners focus on essential aspects of the task without becoming overwhelmed by extraneous information.

3. 

Hybrid Learning Approaches: Combining VR with traditional instructional methods can enhance learning outcomes. For example, using VR to simulate real-world scenarios allows students to apply theoretical knowledge in a practical context, thereby reinforcing learning and improving knowledge retention (Radianti et al., 2020).

4. 

User-Centered Design: Incorporating user feedback into the design of VR educational tools ensures meeting learner preferences. A user-centric iterative approach can enhance usability, reduce cognitive load, and increase overall satisfaction with the learning experience.

5. 

Continuous Evaluation: Implementing mechanisms for continuous assessment within VR environments can provide real-time feedback to learners and educators. This ongoing evaluation allows for the identification of areas where learners may struggle, enabling timely interventions to address knowledge gaps.

5.3. Limitations

While this study provides insights into the impact of VR on LA construction education, several limitations should be acknowledged to contextualize the findings and guide future research. These limitations include methodological constraints, data comparability issues, participant variability, and technological challenges inherent in VR-based learning environments.

a. 

Lack of Direct Comparability Between Year 1 and Year 2 Data

One of the primary limitations of this study is the inability to directly compare the Year 1 and Year 2 datasets due to differences in research design, survey instruments, and data collection methods. While Year 1 provided foundational insights into the feasibility and acceptability of VR in construction education, refinements in the study design for Year 2—including additional survey metrics and expanded assessment tools—prevented direct statistical comparison between the two cohorts. This limitation makes it difficult to determine whether observed improvements were due to VR module refinement, changes in student perception, or natural variability in learning outcomes.

b. 

Small Sample Size and Limited Generalizability

The study was conducted with third-year undergraduate landscape architecture students within a single academic institution, resulting in a relatively small sample size for both cohorts. While the findings provide important insights into VR’s effectiveness in construction education, they may not be fully generalizable to other student populations, disciplines, or educational settings. Future studies should incorporate larger and more diverse samples, including students from multiple institutions and varying levels of expertise, to enhance the external validity of the findings.

c. 

Short-Term Assessment of Learning Outcomes

The study primarily focused on short-term learning gains and self-reported perceptions of VR effectiveness rather than on long-term retention and skill application. While immediate post-VR assessments provided insights into engagement, self-efficacy, and usability, longitudinal studies tracking student performance over an extended period would be necessary to assess the long-term impact of VR-based learning on knowledge retention and practical skill development. Future research should incorporate delayed post-tests and real-world application assessments to determine whether VR learning experiences translate into sustained knowledge and competency in professional practice.

d. 

Potential Cognitive Load and Technological Barriers

Although the study identified high engagement levels and positive user experiences, it also highlighted instances of cognitive overload and usability challenges that may have impacted learning outcomes. Some students struggled with complex brick bond applications, suggesting that VR environments may introduce additional cognitive demands beyond those in traditional learning settings. A subset of participants reported motion sickness and VR-induced symptoms, which could have influenced their ability to remain fully engaged with the learning materials. Future research should explore ergonomic improvements in VR interaction mechanics and investigate how adjustable cognitive load features (e.g., guided prompts and gradual difficulty progression) can improve knowledge acquisition while minimizing learner fatigue.

e. 

No Control Group for Traditional Learning Comparisons

While the study effectively analyzed student engagement, self-efficacy, and knowledge retention within VR-based learning, it did not include a control group using traditional, non-VR instructional methods. As a result, it is difficult to determine whether VR provides a significant advantage over conventional approaches. Future studies should incorporate experimental control groups using traditional classroom instruction and hands-on training to quantitatively assess the relative efficacy of VR in comparison to traditional teaching methods.

f. 

Limited Customization and Personalization in VR Learning

The VR module used in this study was designed as a standardized instructional tool: all students experienced the same content and interaction mechanics, regardless of their prior knowledge, learning pace, or cognitive abilities. However, research suggests that personalized and adaptive learning systems can improve educational outcomes by tailoring content to individual learner needs (Bernacki et al., 2021). Future iterations of VR-based construction education should explore adaptive learning environments that adjust task difficulty, provide real-time feedback, and offer customized learning pathways to better support diverse learners.

5.4. Future Research Directions

From the understanding and limitations of this research, it is apparent that the present state of XR needs research-based iterative development to be further optimized for inclusion in design as well as LA educational frameworks. Some potential future research directions could be proposed from this research:

a. 

Longitudinal Studies: Examining the long-term effects of VR-based learning on knowledge retention and skill development can provide a more comprehensive understanding of its efficacy.

b. 

Integration with Real-World Applications: Future research should explore how VR training translates into real-world competency for construction education. Experimental studies comparing a treatment group (students who undergo VR training) with a control group (those who receive traditional instruction in actual construction environments) would provide insight into the practical transferability of VR-acquired skills. Different forms of XR technology, such as MR and AR, should also be incorporated in learning settings in this regard.

c. 

Adaptive Learning in VR: Investigating the use of other emerging technologies, such as AI-driven adaptive learning in VR environments, could help tailor instructional complexity to individual learner needs. By incorporating real-time assessments and dynamic task adjustments, VR learning modules can better accommodate students with varying levels of prior knowledge and cognitive capacity (González-Erena et al., 2025).

d. 

Comparisons Across Disciplines: While this study focuses on landscape architecture and construction education, future research could examine how VR impacts other fields requiring hands-on skill development, such as engineering, healthcare, and architecture. By analyzing VR’s effectiveness across disciplines, a broader understanding of its pedagogical value can be established.

e. 

Physical and Cognitive Ergonomics of VR Learning: The study identified minor VR-induced discomfort among some students, reinforcing the need for further exploration into ergonomic and optimized XR environment design to accommodate a larger user group. Research focusing on optimizing VR hardware, minimizing motion sickness, and designing user-friendly interaction mechanisms would enhance the overall XR learning experience.

f. 

The Role of Collaborative VR Learning: Collaborative VR learning has been shown to enhance peer interactions and problem-solving skills, warranting further investigation (Sulisworo et al., 2024). While this study evaluated the impact of VR on individual learners, future research could explore how collaborative VR environments, where multiple students interact within the same virtual space, influence engagement and knowledge retention.

5.5. Reflections on the Role of XR in Education

The findings from this study reinforce that VR is not a replacement for traditional education, but rather a complementary tool that has the potential to enhance learning outcomes when used strategically. Overall, VR and XR as a whole provide interactive, immersive, and experiential learning, which aligns well with the principles of experiential learning theory. This makes it a practical pedagogical approach for disciplines requiring spatial understanding and hands-on skill development.

However, the study highlights several limitations of the technology, especially regarding knowledge retention for complex skills, cognitive overload, and usability concerns. While students expressed high engagement and motivation, their ability to retain and apply more advanced construction knowledge remained a concern. These findings suggest that XR must be carefully designed to strike a balance between engagement, cognitive load, and skill transferability to be fully effective in educational contexts.

As XR technology continues to evolve, the potential for VR in education will expand, with advances in AI-driven adaptive learning, mixed-reality integration, and haptic feedback technologies further enhancing the realism and effectiveness of virtual simulations. The key takeaway from this study is that VR offers substantial benefits, but it requires pedagogical refinement to maximize its long-term impact. By adopting interdisciplinarity and integrating the best practices from educational psychology, cognitive science, and instructional design, VR can become an essential tool for training future professionals in disciplines requiring experiential learning, such as landscape architecture, construction, engineering, and environmental sciences.

VR integration in LA should be approached as a hybrid learning strategy. Interactive virtual experiences should be supplemented with real-world applications, structured reflection, and adaptive learning components. Future advancements in VR technology, AI-driven instructional scaffolding, and ergonomic usability improvements will likely enhance VR’s effectiveness in skill-based learning environments.

In conclusion, this study contributes to the growing body of research on adopting immersive learning technologies in design disciplines. It provides pragmatic insights for educators, instructional designers, XR developers, and researchers seeking to optimize VR-based learning experiences. The results underscore the need for continued innovation, evaluation, and refinement to ensure that VR is leveraged to its full potential in education.