Fostering Social Interaction Variability in the Metaverse: A Case Study of the Museum of L’Avesnois in Fourmies

Abstract

This study explores the transformative potential of the metaverse in redefining cultural heritage engagement, with a specific focus on the digital metamorphosis of the Museum of L’Avesnois in Fourmies. By leveraging advanced 3D scanning technologies and immersive virtual environments, select artifacts have been meticulously digitized, creating an unprecedented interactive platform that bridges accessibility gaps and invites global audiences to engage with cultural heritage. Variability in user experience, reflecting the diverse interactions, emotions, and cognitive responses of participants, serves as a critical analytical axis in this research. While diversity can yield invaluable insights into user preferences, excessive discrepancies risk fragmenting the coherence of engagement. This study demonstrates how strategic design interventions can mitigate such variability, fostering uniform yet personalized experiences. Through the integration of real-time social dynamics, enabled by customizable avatars and communication tools, the metaverse is established as a pioneering medium for collaborative cultural exploration. Employing a robust mixed-methods approach, this research synthesizes quantitative metrics with qualitative insights from in-depth interviews to critically evaluate the metaverse’s capacity to deliver authentic, emotionally resonant, and pedagogically impactful engagements. While challenges persist in replicating the emotive depth of physical exhibits and sustaining user attention, findings underscore the metaverse’s unparalleled efficacy in democratizing access to cultural artifacts and enabling transboundary social interactions. Furthermore, the seamless incorporation of previously inaccessible artifacts into these virtual domains significantly enhances both user engagement and educational outcomes. This work advances the discourse on digital heritage by presenting actionable insights into the design of virtual environments that uphold cultural authenticity, foster socially immersive interactions, and align with the broader paradigm of digital transformation.

1. Introduction

In the contemporary digital era, cultural heritage institutions are undergoing a profound transformation as they increasingly adopt advanced technological frameworks to redefine accessibility [1], engagement, and the visitor experience.

1.1. Metaverse Definitions and Applications in Museum Contexts

The metaverse is a network of immersive virtual environments enabling real-time interaction with 3D artifacts and users [2]. It democratizes museum collections, transcends physical and geographic barriers, and fosters social, collaborative engagement by embedding digital artifacts in interactive spaces, thereby redefining heritage dissemination and preservation [3]. However, it raises epistemological and experiential concerns: Walter Benjamin’s “aura”, the unique presence of artifacts, is diminished when the sensory, material, and spatial dimensions are altered by digitization [4,5]. While avatars and real-time communication tools enhance social presence, they may lack the emotive and contextual depth of physical exhibits, risking fragmented engagement or cognitive overload [6,7,8]. Nonetheless, the metaverse enables institutions to display expansive, otherwise inaccessible collections with detailed 3D models [9], and supports global connections, collective experiences, and the co-creation of cultural narratives [10], positioning it as a transformative medium for cultural preservation and collective memory [11].

1.2. Contemporary Metaverse Technologies in Museums: An Overview of Best Practices

Over the past decade, museums have embraced metaverse platforms to increase access, engagement, and artifact preservation via virtual exhibitions, AR tours, and social VR with interactive storytelling and 3D manipulation [12,13,14,15]. Major institutions like the Smithsonian and British Museum provide photorealistic 3D galleries, AI tours, and XR narratives [15,16,17,18], while regional venues use photogrammetry for immersive historical scenes [19,20,21]. User-centered design and sustainability reduce costs and broaden reach [13,14,15,16,19,21,22,23].

Taken collectively, these case studies underscore emerging best practices:

• Narrative-centric immersion—embedding layered storytelling and emotional context can substantially heighten user engagement.
• Social and collaborative tools—proximity-based voice interaction, shared events, and AI avatar guides strongly correlate with visitor satisfaction.
• Adaptive and inclusive design—offering multiple navigation or engagement pathways helps cater to varying levels of digital literacy and interest.
• Cost benefits and sustainability—though potentially resource-intensive at the outset, well-structured metaverse platforms often yield broadened accessibility and resilience, positioning museums as agile, future-focused institutions [15,21].

Contemporary metaverse technologies enable museums not only to replicate physical exhibits but also to innovate new forms of cultural engagement and communal learning. As these platforms evolve, the interplay between technical robustness, user-centered design, and museum-led pedagogy will continue to shape how cultural heritage is experienced, shared, and preserved for a digitally connected global audience [12,13,22].

1.3. Study Motivation and Research Questions

This article focuses on the Museum of L’Avesnois in Fourmies (France) as a case study to examine how a metaverse-based virtual museum affects users’ behaviors and perceptions. Specifically, it addresses three research questions:

• User engagement—which platform features or design decisions most influence user engagement and how can engagement be measured consistently?
• Perceived authenticity—what factors increase or decrease a sense of authenticity among different demographic groups, and to what extent does storytelling mitigate potential authenticity gaps?
• Social interaction—how do users experience social presence in a metaverse environment? Does avatar-based or AI-based interaction augment or detract from their overall sense of immersion?

These issues are rooted in long-standing debates surrounding the nature of cultural objects, the role of museums, and the transformative impact of digital technologies on cultural preservation and dissemination. By employing a mixed-methods approach that integrates quantitative user data with qualitative insights from in-depth interviews, this study seeks to elucidate the opportunities and challenges of integrating cultural heritage into digital spaces [24]. By situating the investigation within these theoretical frameworks, this study aims to provide a comprehensive understanding of how the metaverse redefines the preservation, dissemination, and experience of cultural heritage. The findings contribute to the growing discourse on digital heritage by offering actionable frameworks for designing virtual environments that reconcile technological innovation with cultural integrity. Furthermore, this research advances our understanding of how immersive technologies can reshape the cultural landscape in the digital age, fostering new paradigms of engagement and interaction [25,26].

2. Materials and Methods

2.1. Case Study Site: Museum of L’Avesnois in Fourmies

The Museum of L’Avesnois houses industrial-era artifacts, notably a “Reconstructed Street” displaying 19th century scenes, looms, cobblestone roads, workers’ houses, and digitally integrated historical imagery (e.g., the 1891 labor protest). This virtual reconstruction at the Avesnois Ecomuseum exemplifies advanced digital heritage methods, preserving the tangible and intangible cultural heritage of Hauts-de-France, a key industrial revolution region (Figure 1) [26,27]. Detailed models of homes, streets, and workshops, enriched with authentic tools and furniture, vividly depict Fourmies’ working-class life. The project also illustrates Second Industrial Revolution socio-economic dynamics, showing how industrialization reshaped urban development and community experiences [28,29].

Hauts-de-France became a pivotal industrial hub through advances in textile production and metalworking. By the mid-19th century, Fourmies’ mechanized spinning mills and weaving workshops transformed textile manufacturing and raised the region’s profile in the global industrial landscape, though working-class districts grew dense around factories [30,31]. The reconstructed street (Figure 2) also embeds the May Day 1891 labor protests in Fourmies, which ended in violence. Integrating these events, the Eco-museum balances technological innovation with social struggle, offering a reflective educational experience [32,33].

Immersive digital tools at the virtual Museum of L’Avesnois broaden informed access to historical narratives and engagement. Its reconstructed street blends authenticity with innovation, modeling industrial heritage documentation and dissemination [33,34].

2.2. Scanning Technologies

Three-dimensional scanning evolution has transformed cultural heritage preservation through multi-scale digital reconstruction using handheld LiDAR on consumer devices like the iPhone and large-scale FARO laser systems. Handheld LiDAR offers portability and affordability; FARO systems deliver high-resolution precision across extensive sites.

By combining these strengths, heritage professionals overcome the challenges of accessibility, precision, and scalability, documenting objects, from small artifacts to entire heritage sites, with considerable detail. Consumer LiDAR employs time-of-flight algorithms to calculate depth from light pulse return times, generating low-resolution point clouds processed in real time on a device (Figure 3) [35]. Handheld LiDAR excels in portability and ease of use, capturing the fine details of small objects, interior spaces, and localized architectural elements, such as sculptures or inscriptions, for visualization, AR, or virtual exhibits, though its ~5 m range and lower resolution limit large-scale applications [36].

In contrast, FARO laser scanners employ phase-shift or ToF technologies (Figure 4) to generate high-density point clouds with sub-millimeter accuracy over distances beyond 350 m. Integrated with FARO SCENE for registration, segmentation, and texture mapping, they produce metrically precise, photorealistic 3D models of complex environments, but demand structured fieldwork and substantial computational resources [37,38].

By combining the iPhone’s real-time, portable scanning with FARO’s precision and range, practitioners achieve a multi-scale digital reconstruction that captures both intricate details and broader spatial relationships, marking a significant advance in heritage documentation [29,39,40].

2.3. The VECOS Platform: Informatics Perspective

Mainstream metaverse platforms like Roblox and VRChat excel at social engagement and user-generated experiences but lack built-in tools for historically accurate reconstructions, guided narratives, and advanced data logging, forcing educators to rely on complex scripting or external plugins. Blockchain-centric worlds such as Decentraland introduce digital ownership and virtual real estate but omit curated multimedia options and user behavior analytics that are vital for controlled, in-depth cultural heritage research. In contrast, VECOS (Virtual Education Collaborative System) is a purpose-built, multi-user immersive platform offering a no-code framework for importing 3D artifacts, AI-assisted tour creation, real-time event tracking, and cross-device accessibility. Its in-house architecture supports the seamless addition of pedagogical modules and interactive features, enabling rigorous academic inquiry into visitor engagement, authenticity perceptions, and social interaction within a fully customizable metaverse.

• No-Code/Low-Code Editors: Users can import scanned 3D assets (e.g., building exteriors, interior furniture, historical objects) without direct programming.
• Advanced Avatar Systems: Each participant has a customizable avatar with real-time movement, proximity-based voice chat, and body gesture animations.
• AI Avatars (“BAYA”): These NPC-like guides respond to text or voice queries, providing historical context or directing visitors to specific exhibits. By default, the avatar can trigger interactions when a user’s avatar is within a defined proximity, though visitors can also summon the AI with a text command.
• Interaction Framework: Users can manipulate 3D objects, view additional media (videos, text, and audio), and attend “live” events with multiple participants.
• Analytics and Data Logging: Real-time user tracking is integrated, enabling the collection of participant metrics (e.g., dwell times and object interactions).
• Cross-Platform Compatibility: Content is accessible via VR headsets, desktop software, or mobile devices.

Using VECOS, the team imported complex 3D assets, buildings, cobblestones, and artifacts directly into the virtual space without extensive programming expertise (Figure 5). The platform’s real-time rendering and support for high-resolution models ensured spatial fidelity, preserving every detail down to the smallest artifact and allowing on-the-fly alignment of FARO-scanned architecture with iPhone LiDAR captures. Moreover, VECOS’s cloud-based, multi-user environment enabled researchers to collaborate simultaneously on infrastructure, artifact placement, and interactive features, with all changes updated in real time. This seamless, distributed workflow maintained consistency across historical signage, period-specific buildings, and interactive elements throughout the virtual reconstruction.

2.3.1. Social Interaction: AI, Avatar Systems, and Real-Time Collaboration

VECOS’s avatar system enabled fully customizable, gesture-driven avatars and proximity-based voice chat to foster immersion and natural social interaction in the reconstructed street. Its synchronous multiplayer and group management tools supported collaborative tours, peer discussions, and structured activities. Additionally, AI avatars “BAYA” (Figure 6) acted as context-aware, NLP-powered guides, unlike scripted NPCs, dynamically answering questions and leading personalized educational tours.

• Functionality and creation: BAYA is developed through a combination of scripted dialogue and AI-driven algorithms. The system is fed curated historical data, including detailed artifact descriptions, contextual narratives, and interpretative insights about the reconstructed street and industrial heritage. This content is maintained via an integrated content management system that allows for updates and expansions as needed.
• BAYA operates in dual modes: Automatic Activation, when a visitor’s avatar approaches a designated exhibit or point of interest, BAYA is triggered automatically to provide a brief, contextual overview, and On-Demand Interaction, where visitors can also actively engage by sending a written message or using voice commands, prompting BAYA to deliver more detailed information or answer specific questions.
• This approach ensures that our AI avatars not only guide visitors effectively but also adapt to varying user preferences and interaction styles within the virtual museum.
• Follow-Me option: A key enhancement in our system is the “follow-me” feature. Visitors can request BAYA to take them on a personalized tour using the follow-me button. In this mode, BAYA actively leads the visitor through the virtual museum, highlighting key exhibits and providing narrative context along the way. This feature not only streamlines the tour experience but also allows for adaptive guidance based on the visitor’s pace and interests.

The combination of user-controlled avatars and AI avatars in Vecos enabled both social exchanges between participants and meaningful interactions with the virtual museum’s AI guides. The AI avatars also supported the overall educational goals of the study by providing real-time, contextual explanations of historical artifacts and fostering deep engagement with the museum’s content.

2.3.2. Interactive Object Management and Immersive Content

The interactive nature of the virtual reconstructed street was made possible by Vecos’ ability to manage and integrate interactive objects and multimedia content within the digital environment. Using Vecos’ content management system (CMS), the research team was able to embed a range of interactive elements throughout the virtual street, such as historical objects, informational panels, and multimedia exhibits. Participants could interact with 3D models of artifacts, triggering additional layers of information such as videos, historical facts, or audio descriptions that provided context for the objects they encountered. The interactive objects deployed within the street were not merely static representations but dynamic elements that reacted to user engagement. For example, participants could manipulate digital artifacts, such as spinning wheels or artisan tools, which activated corresponding educational content. This hands-on interaction enhanced the learning experience, transforming users from passive observers to active participants in the exploration of industrial heritage.

2.3.3. Experimentation and Real-Time Data Collection

VECOS relies on its built-in tools for real-time analytics and data collection, which were instrumental in measuring participants’ behaviors, engagement, and social interactions during the experiment (Figure 7). Vecos’ analytics engine was used to track user activity, providing a granular view of how participants navigated the virtual space, interacted with objects, and engaged with one another.

The data logging capabilities of Vecos captured key metrics such as movement patterns, interaction hotspots, and user dwell times at specific locations within the street. This information was visualized through heatmaps, enabling the research team to identify areas of the virtual street that garnered the most user interest and engagement. These data were crucial in understanding how participants interacted with different artifacts and sections of the street, as well as how the design of the environment influenced user behaviors.

Furthermore, Vecos supports detailed event tracking, allowing the research team to monitor specific interactions, such as when participants engaged with interactive exhibits, communicated with other avatars, or completed guided tours. These data allowed for a quantitative analysis of social interaction patterns, helping to assess the effectiveness of the virtual environment in fostering authenticity and engagement.

2.3.4. Cross-Platform Accessibility and Scalability

VECOS’s cross-platform support (VR headsets, desktops, and mobile devices) and cloud-based infrastructure ensured synchronized access and updates, broadening participation across varied devices. Its scalable design allowed the seamless addition of interactive elements, educational modules, and multiplayer features over time. As the study’s backbone, VECOS facilitated real-time construction, social interaction, and analytics within the reconstructed street, leveraging avatar systems, content management, and data tracking for an in-depth exploration of user behaviors. The following Methodology section outlines explain how we structured experiments, managed participant interactions, and collected data to assess both the digital reconstruction’s effectiveness and the immersive user experience.

2.4. Methodology Overview and Study Design

2.4.1. Procedure

• Participant Recruitment: The event is part of a series of actions carried out as part of EUNICE Weeks 2022, taking place from October 20 to November 24, an initiative of the European University EUNICE and offering numerous cultural, sporting and educational activities. A total of 75 participants were recruited through the EUNICE (European University Network for Excellence), an academic consortium that promotes interdisciplinary exchange and excellence among universities across Europe (Figure 8). These participants were specifically selected from a diverse range of countries and academic disciplines within the network, ensuring a heterogeneous group in terms of cultural backgrounds and fields of study. This diversity provided a robust sample to examine how varying user demographics engage with digital heritage content within a metaverse environment. The recruitment process was initiated through an open call within the EUNICE program (Figure 8), wherein students were invited to subscribe to participate in an immersive exploration of the virtual Museum of L’Avesnois using the VECOS platform. This approach allowed for a transnational, interdisciplinary sample that could provide insights into the cross-cultural dynamics of social interaction, authenticity perception, and user engagement in digital heritage settings.
  Participant Details: Most participants joined remotely from personal devices (e.g., desktop/laptop, VR headsets, or mobile phones), a smaller subset accessed the experience through on-campus facilities. The final sample reflected primarily undergraduate and master’s-level students, aligning with the younger demographic typically present in EUNICE institutions, yet still encompassed participants aged over 30.

  Table 1. Demographic distribution, participation modality, and device usage.

  Variable/Category	N = 75	Percentage
  Age Range
  18–24	40	53.3%
  25–29	25	33.3%
  30+	10	13.4%
  Country of Origin
  France	21	28.0%
  Germany	15	20.0%
  Spain	3	4.0%
  Italy	5	6.7%
  Belgium	8	10.7%
  Finland	7	9.3%
  Portugal	6	8.0%
  Poland	6	8.0%
  Greece	4	5.3%
  Participation Location
  Remote (Home)	68	90.7%
  On Campus (Lab)	7	9.3%
  Primary Device
  Desktop/Laptop	50	66.7%
  VR Headset	15	20.0%
  Mobile Phone	10	13.3%

  summarizes the key demographic and technological characteristics of the cohort, which are broadly consistent with a cross-institutional, multidisciplinary audience.
  Approximately 90.7% took part in the study remotely, while 9.3% participated on campus. In terms of device usage, 66.7% accessed the metaverse via desktops or laptops, 20.0% used VR headsets, and 13.3% relied on mobile phones. This distribution underscores both the platform’s cross-device capabilities and the participants’ varied technical backgrounds. All participants completed a guided tour before optionally exploring the virtual environment independently, and then provided feedback through surveys and focus group discussions. This arrangement offered a multifaceted perspective on how diverse learners in a European academic network engaged with and experienced an immersive metaverse-based cultural heritage setting.

• Activities and Interactions: The virtual museum serves as a vibrant gateway into the virtual Museum of L’Avesnois, transporting visitors to an early 20th century townscape where cobblestone alleys, artisan workshops, and brick façades evoke Fourmies’ industrial past. Visitors navigate the street as customizable avatars, encountering interactive stalls, shops, and domestic interiors where they can inspect scanned objects, trigger short historical narratives, and manipulate virtual tools in craft demonstrations (Figure 9).
  Beyond simple observation, the experience weaves in mini-games, quizzes, and guided storytelling features that prompt users to explore specific artifacts, discover hidden anecdotes, and compare historical recipes. In the schoolhouse, participants can attend simulated lessons and experiment with vintage lesson materials, while a market stall showcases regional produce linked to diaries and oral histories about day-to-day life in the Avesnois. These interwoven activities foster immersion and collaboration, allowing visitors to not only see history but to step into it, exchanging views, solving guessing games together, and forging emotional connections with the heritage that shaped this industrial community.

• Group Assignment: To simulate social interaction dynamics, the 75 participants were divided into virtual groups of 10–15 individuals. Each group was assigned a trained moderator, whose role was to facilitate the interaction between participants, guide them through the virtual exhibits, and ensure the effective use of Vecos’ advanced features. These moderators had undergone specialized training in the Vecos platform to ensure that they could efficiently support the participants in navigating the environment, engaging with interactive content, and making full use of the platform’s communication tools.
• Guided Tour Structure: The moderators also played a crucial role in observing group behaviors, noting key interaction points, and providing real-time support where necessary. By facilitating small group discussions and guided tours, the moderators ensured that each group experienced the reconstructed street in a way that fostered both collaborative exploration and individual discovery. These group dynamics were carefully orchestrated to reflect real-world social interactions in heritage spaces, providing a rich dataset for subsequent analysis.

The virtual Museum of L’Avesnois tour uses two phases: a moderator-led guided tour and an autonomous exploration with the AI avatar BAYA. In the guided phase, a trained moderator systematically introduces key exhibits, elucidating the historical context and technological processes underpinning the digital reconstruction, explains the 3D scanning integration and exhibit layout, highlights critical themes, facilitates group discussions, and answers queries in real time. In the free phase, visitors select exhibits at their own pace, and BAYA leverages its knowledge base and NLP to deliver on-demand information and detailed multimedia content, technical descriptions, historical narratives, and contextual data. This dual-phase model combines structured instruction with AI-supported self-directed learning to enhance cognitive assimilation and exploratory engagement.

2.4.2. Instruments

Quantitative and qualitative data were collected through a combination of embedded analytics, user surveys, and focus groups. This mixed-methods approach allowed for a holistic evaluation of how participants interacted with the digital heritage content and engaged with one another within the virtual environment.

• Embedded Analytics: The Vecos platform includes sophisticated real-time tracking of user behaviors, including navigation patterns, interaction points, and group communication dynamics. The platform’s analytics tools allowed the research team to capture detailed data on how participants moved through the virtual space, which exhibits attracted the most attention, and the nature and frequency of interactions between participants and the AI avatars. This interactional data were essential for understanding the degree to which participants engaged with both the digital content and their fellow users.
• User Surveys: Following the virtual exploration, participants completed a detailed post-experience survey, which assessed their perceptions of the virtual environment in terms of authenticity, usability, and emotional engagement. The survey included Likert scale items to measure user satisfaction with various aspects of the Vecos platform, such as the ease of navigation, the quality of social interactions, and the educational value of the exhibits. Open-ended questions allowed participants to provide qualitative feedback, offering deeper insights into how the virtual environment compared to traditional, in-person museum experiences.
• Focus Groups: A series of focus groups was conducted with each of the virtual groups after their exploration of the museum. These focus groups provided a platform for more in-depth discussions about the participants’ experiences. The conversations were transcribed and subjected to a thematic analysis, which identified recurring themes related to user engagement, the perceived authenticity of the virtual environment, and the effectiveness of social interactions within the metaverse.

2.4.3. Analysis

Data analysis followed a mixed-methods approach, combining statistical and qualitative techniques to derive comprehensive insights from the collected data.

• Quantitative Analysis: The embedded analytics data were processed to identify patterns in users’ behaviors, such as the time spent on various exhibits, interaction frequencies, and navigation paths. Statistical methods, including regression analysis and ANOVA, were applied to determine the relationships between user engagement metrics and factors such as the group size and prior experience with virtual environments. Additionally, heatmaps were generated to visualize areas of high user interaction, providing a spatial representation of participant engagement within the virtual museum.
• Qualitative Analysis: The open-ended survey responses and focus group transcripts were analyzed using thematic coding, focusing on key themes such as authenticity, social interaction, and usability. The qualitative data were triangulated with the quantitative findings to provide a more nuanced understanding of how participants experienced the virtual environment. This convergent analytical approach allowed for a comprehensive evaluation of the research questions, ensuring that both behavioral patterns and subjective experiences were adequately captured.

The study adhered to institutional review board (IRB)-approved ethical standards: all participants gave informed consent, could withdraw at any time, and their data were anonymized. Employing a mixed quantitative–qualitative methodology, we recruited a diverse sample from the EUNICE European University Network to examine engagement, authenticity perceptions, and social interaction within the virtual Museum of L’Avesnois. Using Vecos’ interactive tools, AI avatars, and group-based exploration, we simulated individual and collaborative encounters with historical content. The design combined real-time embedded analytics with post-experience surveys and focus groups, enabling a robust triangulation of behavioral metrics and users’ perceptions. This comprehensive approach captures both objective and subjective dimensions of immersion and learning. In the Section 3, we will present the empirical findings on behavioral patterns, engagement levels, and social dynamics, offering insights into the reconstruction’s effectiveness and the potential of metaverse technologies for cultural heritage dissemination.

3. Results

This section presents the empirical findings from the mixed-methods analysis of user experiences in the virtual replica of the Museum of L’Avesnois. Reflecting the study’s focal points, the results are organized into three primary dimensions: user engagement, perceived authenticity, and social interaction. Each is accompanied by qualitative insights and supporting statistical outcomes. Where applicable, descriptive and inferential statistics are linked directly to the thematic discussions, ensuring that readers can readily see how numeric evidence underpins qualitative interpretations. From the total sample (N = 75), we collected both survey responses (quantitative) and in-depth interviews or focus group transcripts (qualitative). Table 1 (in Section 2.4.1) summarizes participants’ demographics, device usage, and participation modality. For the quantitative component, we computed descriptive measures (e.g., means, medians, and standard deviations), as well as reliability indices (Cronbach’s α) for the multi-item scales. We then performed a series of inferential tests (e.g., t-tests, ANOVAs, and regression analyses) to examine the relationships among user profile characteristics (e.g., age group, and VR experience) and key outcomes (e.g., engagement scale, authenticity ratings, and social satisfaction). All statistical analyses were conducted at a significance level of p < 0.05.

3.1. User Engagement

3.1.1. Quantitative Outcomes

Participants reported high levels of engagement overall, with 85% rating the digital environment as “immersive and engaging.” The mean engagement scale score was 4.3 out of 5 (SD = 0.6), and the internal consistency of this scale was acceptable (Cronbach’s α = 0.82). As depicted in Figure 10, novice users (N = 43) had a statistically lower mean engagement (M = 3.8, SD = 0.5) than experienced users (n = 32) (M = 4.6, SD = 0.4), t(73) = 3.23, p < 0.01, Cohen’s d = 0.78. This suggests a large practical effect: individuals familiar with immersive platforms navigated the environment more readily and derived more enjoyment from the 3D interactions.

Regarding specific features, 70% of participants stated that “manipulating 3D artifacts” heightened their sense of involvement, though 35% also reported frustration with controls or interface complexity. In line with this, we found a moderate positive correlation (r = 0.42, p < 0.01) between participants’ perceived ease of navigation and their overall satisfaction levels, indicating that usability strongly influences perceived engagement.

3.1.2. Qualitative Insights

Interviewees frequently described the virtual environment as “visually rich” and “surprisingly lifelike”. One participant stated, “It felt like I was truly walking through the museum”, pointing to the significance of spatial realism in fueling immersion. Conversely, novices sometimes felt overwhelmed: “There’s so much going on visually that I sometimes found it hard to focus on a single exhibit”, one user commented, aligning with the frustration data captured in the surveys. Moreover, multiple participants noted that they appreciated exploring artifacts “that aren’t normally accessible in the physical museum”, underscoring how digital reconstruction can deepen their curiosity. However, the perceived learning curve, especially regarding movement controls or menu systems, occasionally dampened novices’ enthusiasm. Together, these comments reinforce the quantitative finding that the user experience level is a strong determinant of engagement outcomes.

3.1.3. Interpretation and Link to Study Variables on UE

The results align with prior research suggesting that interactive 3D elements can boost user engagement, provided that the interface remains approachable. Statistical analyses clearly show how the experience level moderates engagement, highlighting a design tension: advanced features may attract experienced VR users but risk alienating novices. Future interface refinements could offer adaptive “onboarding” pathways, one for first-time users seeking guided tutorials and another for experienced explorers desiring open-ended interaction. This tension underscores the importance of user-centered design in virtual museum environments. Developers must balance interactivity with accessibility to ensure that all users, regardless of their digital literacy, can fully engage with the content. These variabilities contribute to the broader literature on digital engagement, supporting the argument that virtual environments can surpass physical spaces in terms of accessibility and exploration, but only if designed with the user’s cognitive load in mind.

3.2. Perceived Authenticity

3.2.1. Quantitative Outcomes

Users’ ratings of authenticity were more varied: 62% agreed that digitized artifacts felt “credible and realistic”, whereas 38% expressed difficulties reconciling the virtual environment with their expectations of authenticity (Figure 11). The mean authenticity rating was 3.9 (SD = 0.8), indicating moderate agreement on real-to-virtual fidelity. An age-based one-way ANOVA revealed a significant main effect of authenticity across three groups (18–24 vs. 25–29 vs. 30+), F(2,72) = 4.58, p = 0.013, partial η² = 0.11. Post hoc comparisons indicated that older participants (30+) rated authenticity significantly lower (M = 3.1, SD = 0.9) than younger cohorts (M = 4.0, SD = 0.5), suggesting generational variance in comfort with digital surrogates.

Notably, participants who leveraged the integrated “storytelling tours” (n = 49) scored authenticity about 15% higher than those who navigated purely visually. This difference was statistically significant at p < 0.01, underlining the importance of narrative context in bolstering perceived realism.

3.2.2. Qualitative Insights

Focus group transcripts offered nuanced perspectives on what “feels authentic”. Many participants noted that “interactive storytelling” enhanced emotional resonance: “When the virtual guide explained the backstory, it felt more real.” Others lamented the absence of physical tangibility. One older respondent stated, “I miss the smells, textures, and a sense of history that physical walls provide”, evoking the tension between high visual fidelity and the intangible aura of genuine artifacts.

An emergent theme was the concept of layered context, combining images, documentary footage, or personal testimonies with the interactive model. Some participants praised the “digital diaries” and “oral histories” in the schoolhouse or marketplace stalls, perceiving them as bridging the experiential gap: “Hearing actual testimonies from that era made it more real to me than just 3D objects would”.

3.2.3. Interpretation and Link to Study Variables on PA

These findings highlight how authenticity in a metaverse setting extends beyond graphical realism. Statistical data reinforce the notion that generational familiarity and the presence of narrative scaffolding substantially shape perceptions of authenticity. The disparity among age groups suggests that bridging “material gaps” may require innovative add-ons, such as integrated sensory or audio cues, or more robust storytelling arcs. From a design perspective, the synergy of narrative immersion and user-driven exploration emerges as a pivotal lever for enhancing authenticity judgments.

3.3. Social Interaction

3.3.1. Quantitative Outcomes

The survey analysis indicated that participants who engaged in social features (Figure 12) (live group tours or AI/avatar-led events) scored significantly higher in overall satisfaction (M = 4.5, SD = 0.6) than those exploring solo (M = 3.9, SD = 0.7), t(73) = 2.86, p = 0.006, Cohen’s d = 0.66. Approximately 40% of respondents reported minimal social interaction, citing an unawareness of chat features or a preference for solitary exploration.

Interestingly, the regression analysis revealed that “minutes spent in group discussions” predicted 21% of the variance in the emotional engagement subscale (R² = 0.21, p < 0.01), suggesting that group-driven dialogue fosters deeper engagement.

3.3.2. Qualitative Insights

Interviewees who participated in synchronous group tours often used terms like “shared experience” or “collective discovery”. One participant recounted how their group collaboratively solved a “historic puzzle” embedded in the marketplace area: “It felt like an escape room combined with a history lesson.” Another user described the AI avatar-facilitated group discussion as “effortless yet surprisingly communal”.

However, a subset of participants indicated confusion about using the chat function or connecting to voice channels, sometimes leading to isolated experiences. A few novices felt overwhelmed when coordinating with others and simultaneously learning controls, paralleling the earlier usability concerns.

3.3.3. Interpretation and Link to Study Variables on SI

Consistent with social presence theories, real-time communication significantly enhanced overall satisfaction, reaffirming that community-oriented designs may amplify the emotional resonance of digital heritage experiences (Figure 13).

The data spotlight a divide: those who actively tapped into group-based interactions benefited from a higher social presence and sense of immersion, whereas participants who faced technical or preference-related barriers missed out on potential gains in engagement (Figure 14).

This underscores the necessity of clear onboarding around social tools, interface consistency, and optional “solo vs. group” routes.

3.4. Summary of the Findings and Statistical Integration

By triangulating surveys, focus group discussions, and system logs, we discern the following key insights:

• User Engagement

  ∘

  High overall engagement was observed (M = 4.3), which was particularly pronounced among experienced VR users (p < 0.01).

  ∘

  Engagement correlates with feature mastery (r = 0.42), implying that well-designed tutorials or adaptive layouts could mitigate novice overload.

• Perceived Authenticity

  ∘

  Moderate authenticity ratings were observed (M = 3.9), with significant intergenerational gaps (p < 0.05).

  ∘

  Story-driven tours boost the authenticity perception by approximately 15%, suggesting that layered narratives and additional context effectively bridge the aura deficit.

• Social Interaction

  ∘

  Engaging in group-based or AI-led events substantially improves emotional engagement (p < 0.01).

  ∘

  Technical or cognitive hurdles hinder some users from enjoying communal features, presenting an opportunity for refined user flow and targeted support.

Collectively, these results align with established findings on immersive and user-centered design. More extensive correlations and inferential results can be found in the Supplementary Materials, including additional charts and regression tables delineating how the device type, demographic factors, and in-system behaviors intersect to shape user outcomes.

4. Conclusions

By combining quantitative and qualitative data, we were able to provide a multifaceted analysis of how users interact with cultural content in a virtual environment. This discussion interprets the findings within the broader context of existing research on virtual museums, immersive technologies, and digital heritage, while also considering the theoretical implications and practical applications of the results. Despite these contributions, this study is subject to several limitations, including a modest and relatively homogeneous sample, short-term exposure to the virtual environment, and the reliance on self-report measures that may introduce bias. Future research should address these issues by expanding the sample size, incorporating longitudinal methods, integrating neurotechnological assessments for real-time cognitive and emotional insights, and exploring adaptive interface designs across multiple virtual museum contexts. These avenues for future research will further enhance our understanding of immersive digital heritage experiences and inform the development of more effective and engaging virtual environments.

4.1. Enhancing User Engagement: Opportunities and Challenges

The study finds that the metaverse markedly boosts engagement through interactive, immersive features: most participants valued manipulating 3D models, zooming in on details, and exploring objects from multiple angles, echoing prior research on the role of interactivity in digital environments. VR/AR technologies deliver dynamic, hands-on experiences that foster a sense of agency absent in static displays. However, this interactivity can overwhelm novice users, as about 35% reported frustration with navigation and system complexity (Figure 15). Such cognitive overload aligns with studies on sensory saturation in highly interactive settings, where too many options or non-intuitive interfaces hinder focus. Hence, designers must balance rich interactive elements with clear, usable interfaces to prevent user overload.

The tension between interactivity and usability requires balancing rich, exploratory features for experienced users with guided, structured pathways for novices, an adaptive-design approach that tailors experiences to users’ skill levels. Qualitative feedback also underscores that digitizing and showcasing rare, physically inaccessible artifacts markedly enhances engagement, as virtual museums democratize access to space-limited collections and enable global audiences to explore items that are otherwise unavailable.

4.2. Authenticity in the Virtual Space: Perception vs. Reality

Users’ perceptions of authenticity in virtual environments were split: 62% found the digital artifacts authentic, while 38% did not, reflecting the known challenges of replicating authenticity online. Walter Benjamin’s concept of an artifact’s “aura” [4], its unique presence tied to time and place, is diminished by digital reproduction, which, despite visual fidelity, often lacks materiality and historical context, leading participants to describe artifacts as “detached” or “lacking substance” (Figure 16). This emotional detachment suggests that visual and intellectual engagement alone cannot forge a full museum experience. Interestingly, narrative elements, virtual guides, and storytelling boosted perceived authenticity, as users who accessed contextual histories reported stronger connections. Therefore, virtual museums must move beyond high-resolution 3D models to embed immersive storytelling and emotional engagement tools, embracing “experiential authenticity”, which prioritizes users’ cognitive and emotional bonds with the cultural content.

4.3. The Role of Social Interaction in the Metaverse

Participants who joined group tours or live discussions in the metaverse reported significantly higher satisfaction, aligning with research on social presence enhancing immersion. Real-time communication through avatars, chat, and virtual guides replicates traditional museum dynamics by supporting discussions, shared interpretations, and collaborative exploration. Yet, about 40% of users avoided social features, preferring personal AI avatars over group interactions. This shift reflects evolving expectations: AI-driven guides offer personalized, flexible, non-intrusive engagement by adapting to individuals’ preferences, delivering context-specific guidance, and allowing self-paced exploration without the coordination or anxiety of group settings. Users valued the novelty and sophistication of AI avatars, the immersive storytelling, real-time feedback, and lifelike interactions more than conventional social activities. Moreover, these AI interactions removed barriers to participation, creating a stress-free environment conducive to learning. Such findings underscore the need for virtual museum designers to provide dual pathways, robust social tools alongside adaptive AI features, to accommodate diverse user preferences and maximize meaningful, immersive engagement.

4.4. Implications for Cultural Heritage Institutions

This study shows that virtual museums can vastly improve accessibility and engagement by digitizing collections into interactive, social environments that reach global audiences and democratize heritage. Yet, perceived authenticity, especially among older visitors used to physical museums, remains a barrier, calling for holistic experiences that blend visual fidelity with narrative, emotional, and social elements. User-centered design is also vital: platforms must offer multiple pathways to suit both novices and experts. The overall success hinges on thoughtfully integrating interactivity, storytelling, and community tools to create meaningful, immersive experiences. Looking forward, our next phase will integrate neurotechnology (e.g., Emotiv and Emwave) to gather real-time metrics on emotional engagement, cognitive load, and stress, going beyond surveys and interviews. This approach will pinpoint which features enhance or detract from immersion, enabling the more precise, data-driven optimization of virtual cultural experiences.