Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Next Article in Journal
A Weighted Composite Metric for Evaluating User Experience in Educational Chatbots: Balancing Usability, Engagement, and Effectiveness
Previous Article in Journal
Transmission Power Control in Multi-Hop Communications of THz Communication Using a Potential Game Approach
Previous Article in Special Issue
Enhancing Human–Agent Interaction via Artificial Agents That Speculate About the Future
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Future of Education: A Multi-Layered Metaverse Classroom Model for Immersive and Inclusive Learning

1
Department of Teaching, Learning and Educational Leadership, Binghamton University, Binghamton, NY 13902, USA
2
Department of Electrical and Computer Engineering, Binghamton University, Binghamton, NY 13902, USA
*
Authors to whom correspondence should be addressed.
Future Internet 2025, 17(2), 63; https://doi.org/10.3390/fi17020063
Submission received: 28 December 2024 / Revised: 28 January 2025 / Accepted: 2 February 2025 / Published: 4 February 2025
(This article belongs to the Special Issue Human-Centered Artificial Intelligence)

Abstract

:
Modern education faces persistent challenges, including disengagement, inequitable access to learning resources, and the lack of personalized instruction, particularly in virtual environments. In this perspective, we envision a transformative Metaverse classroom model, the Multi-layered Immersive Learning Environment (Meta-MILE) to address these critical issues. The Meta-MILE framework integrates essential components such as immersive infrastructure, personalized interactions, social collaboration, and advanced assessment techniques to enhance student engagement and inclusivity. By leveraging three-dimensional (3D) virtual environments, artificial intelligence (AI)-driven personalization, gamified learning pathways, and scenario-based evaluations, the Meta-MILE model offers tailored learning experiences that traditional virtual classrooms often struggle to achieve. Acknowledging potential challenges such as accessibility, infrastructure demands, and data security, the study proposed practical strategies to ensure equitable access and safe interactions within the Metaverse. Empirical findings from our pilot experiment demonstrated the framework’s effectiveness in improving engagement and skill acquisition, with broader implications for educational policy and competency-based, experiential learning approaches. Looking ahead, we advocate for ongoing research to validate long-term learning outcomes and technological advancements to make immersive learning more accessible and secure. Our perspective underscores the transformative potential of the Metaverse classroom in shaping inclusive, future-ready educational environments capable of meeting the diverse needs of learners worldwide.

1. Introduction

The rapid evolution of technology has begun to transform educational landscapes. Yet, traditional classrooms often struggle to keep pace with modern learning needs, such as personalized instruction, enhanced engagement, and global connectivity [1]. As students faced increasing demands for adaptability and digital literacy in a globalized world, immersive virtual environments emerged as a promising solution to address these gaps [2]. Among the latest advances, the concept of the Metaverse classroom stood out, offering a fully integrated digital space where students could interact in real time through three-dimensional (3D) simulations, personalized learning paths, and collaborative social interactions [3]. The Metaverse refers to an interconnected, virtual shared space that combines elements of physical reality with digital interactions, allowing users to engage through avatars in persistent 3D environments [4]. This concept extends beyond traditional virtual classrooms in education by providing fully immersive, interactive, and collaborative digital spaces that foster engagement and experiential learning [5]. Although virtual and augmented realities (VR/AR) have been applied in education, existing models primarily focus on isolated features such as simulations or gamified content. They often lack a cohesive framework integrating multiple infrastructure layers, personalization, and inclusive learning environments to create a scalable, adaptable virtual classroom [6].
Recognizing these gaps, this perspective envisions a Multi-layered Immersive Learning Environment (Meta-MILE). This comprehensive framework extends existing educational models by integrating cutting-edge Metaverse technologies, AI-driven personalization, gamified learning pathways, and scenario-based assessments. The multi-layered structure ensures that each critical component of a digital classroom—infrastructure, content and interaction, personalization and accessibility, collaboration and social engagement, and assessment and feedback—is addressed to create a holistic, future-ready learning environment. The Meta-MILE model adopts a multi-layered structure to address the multifaceted challenges of virtual education. Each layer targets a specific aspect of virtual learning to ensure stability, inclusivity, and adaptability. By integrating these layers, the Meta-MILE framework bridges the gap between traditional virtual learning environments and the rapidly evolving Metaverse ecosystem, offering adaptive, personalized, and secure learning experiences for diverse student populations.
This paper aims to fill that gap with a novel, multi-layered Metaverse classroom design that prioritizes infrastructure stability, interactive content delivery, accessibility, social engagement, effective assessment, and sustainable scalability. Drawing upon constructivist and experiential learning theories, the study examined how a layered approach could meet the technical demands of a virtual classroom and support individualized and collaborative learning. The proposed Metaverse classroom offered a new benchmark for educational environments that adapt to future technological advances by combining foundational infrastructure with personalized content and secure management layers. The novelty of the Meta-MILE model lies in its holistic approach to addressing critical challenges in virtual learning environments. Unlike existing models, which often focus on singular aspects of virtual education, the Meta-MILE integrates a multi-layered architecture to deliver adaptive, personalized, and secure learning experiences across diverse student populations. By incorporating assistive technologies, multilingual features, and gamification elements, the Meta-MILE model ensures that virtual learning environments are inclusive and accessible, regardless of a student’s physical or technological limitations [7].
This paper offers practical implications for educators and institutions aiming to integrate immersive learning technologies into their curricula. The Meta-MILE framework addresses infrastructure stability, accessibility, and secure interactions, presenting a scalable solution that aligns with educational policies promoting competency-based and experiential learning. The study also addressed real-world challenges by incorporating gamified elements, scenario-based learning environments, and holistic assessments that went beyond conventional grading systems, thus fostering critical thinking, problem-solving, and teamwork. Furthermore, this article introduces advanced community and parental participation tools, including virtual community centers and adaptive parental controls, which improved safety and supported active family participation in the student’s learning journey [8]. In light of the increasing importance of sustainability, the design of the Metaverse classroom emphasized efficient resource use and environmentally conscious practices [9]. This future-ready infrastructure leveraged modular design and cloud-based updates, enabling the system to integrate with emerging technologies, such as devices from the Internet of Things (IoT) and next-generation AR/VR applications, to remain relevant and scalable [10].
This perspective aims to address the following key research questions: (1) How can a multi-layered Metaverse framework enhance personalized, inclusive, and scalable learning experiences? (2) What practical strategies can be employed to ensure the secure, accessible, and equitable implementation of Metaverse classrooms? (3) How does the Meta-MILE model impact student engagement and learning outcomes in an immersive educational environment? These questions guided the development of the framework and the design of the empirical study presented in this article.
The remainder of this article is structured as follows:
  • Literature Review and Theoretical Framework: This section provides a detailed review of the theoretical foundations supporting the integration of Metaverse technologies in education.
  • Metaverse Classroom: a Layered Architectural View: The paper presents a Metaverse-based Meta-MILE that integrates immersive 3D settings, AI-driven personalization, gamified routes, and scenario-based assessments. This comprehensive strategy addresses significant shortcomings in contemporary virtual learning by providing customizable, captivating, and interactive experiences.
  • Innovative Approach to Building a Metaverse Classroom: The study offers practical strategies to ensure equitable access and secure interactions in the Metaverse classroom while considering accessibility, infrastructure needs, and data protection. These suggestions connect innovative theories with real-world limitations, showing how institutions can adopt virtual learning inclusively and securely on a large scale.
  • Empirical Validation and Practical Application: Empirical findings show improved learning engagement and skill acquisition under the Meta-MILE model, underscoring its effectiveness in fostering competency-based experiential learning.
  • Discussion: This section discusses the practical implications, limitations, and future research directions. The discussion also emphasizes policy implications and the need for longitudinal research to further validate the results. It points to ongoing technological innovation as vital to making immersive classrooms more accessible and sustainable for the future of education.
  • Conclusion: This section summarizes key contributions and emphasizes the importance of immersive technologies in shaping future educational practices.

2. Literature Review and Theoretical Framework

2.1. Foundations of Immersive Learning and Virtual Classrooms

The emergence of immersive learning environments, including VR/AR, has significantly impacted educational practices, improving engagement, interactivity, and accessibility [6]. Immersive learning, characterized by simulations and 3D environments, allows students to engage deeply with the content, enabling experiences previously inaccessible in traditional classrooms [11]. The potential of immersive technologies to increase motivation and active participation by providing experiential learning opportunities that appeal to various learning styles is emphasized [12]. Furthermore, recent studies suggest that immersive environments offer enhanced visualization for complex subjects, such as STEM (science, technology, engineering, and mathematics), and allow students to experiment safely in virtual laboratories [13,14]. Virtual classrooms within Metaverse expand on these principles by facilitating real-time interaction in a fully immersive shared space where students can participate in collaborative activities, simulations, and interactive discussions [15]. Despite these advancements, challenges remain regarding the scalability and integration of immersive technologies within existing educational systems [16]. Scholars noted that while immersive learning can be beneficial, factors such as device accessibility, network stability, and the need for specialized pedagogical methods often limit the successful adoption of VR/AR in schools [17,18]. Furthermore, immersive learning’s potential to support diverse student populations has highlighted the need for customization and inclusion within virtual environments, which requires advanced design frameworks compatible with educational standards [19]. Thus, while immersive learning has laid a strong foundation, the literature reveals a pressing need for comprehensive and adaptable models like the Metaverse classroom that integrate technological, social, and educational dimensions [20].

2.2. Theories Supporting Metaverse Integration in Education

The theoretical foundation for Metaverse integration in education draws from established theories such as constructivism, experiential learning, and social learning [21]. Constructivist theory, as proposed by Piaget and later developed by Vygotsky [22], posits that students construct knowledge through active engagement and interaction within meaningful contexts [23]. The Metaverse aligns well with this theory, providing a collaborative space where students can explore, experiment, and learn through direct experience and peer interaction [24]. Virtual environments allow learners to engage in problem-solving activities, manipulate virtual objects, and interact within complex simulations, facilitating a learning process grounded in discovery and experiential learning [25]. Kolb’s experiential learning theory further supports Metaverse integration, emphasizing the importance of “learning by doing” [26]. By simulating real-world environments, the Metaverse allows students to gain practical skills, from conducting science experiments to simulating historical events in a risk-free setting [27]. These experiential opportunities align closely with Kolb’s model, which emphasizes concrete experiences, reflective observation, abstract conceptualization, and active experimentation [28]. Similarly, Vygotsky’s theory of social learning underscores the importance of social interaction in knowledge acquisition, which the Metaverse classroom facilitates through avatar-based interactions and virtual collaborative spaces [29]. These theories collectively validate the Metaverse as a space where students engage in active, social, and contextually relevant learning experiences, forming a robust theoretical foundation for immersive digital education [30].
In addition to traditional learning theories, digital experiential learning further substantiates integrating Metaverse technologies in education. Digital, experiential learning builds on Kolb’s experiential model. Still, it emphasizes virtual and digitally-mediated environments as spaces where learners engage in realistic, hands-on activities that mimic real-world scenarios [31]. The Metaverse allows learners to apply theoretical knowledge in practical settings through simulations, role-playing exercises, and digital labs. These digital experiences allow learners to acquire skills safely, controlled, and repeatably, enabling students to explore high-risk environments (such as virtual surgery or engineering prototypes) without the constraints of physical resources or safety concerns [3]. Integrating digital, experiential learning within the Metaverse ensures learners are prepared for real-world problem-solving in diverse contexts, enhancing skill acquisition and long-term knowledge retention. Another critical theory supporting Metaverse integration is distributed cognition, which views knowledge as not solely contained within an individual but distributed across people, tools, and environments [32]. This theory aligns closely with Metaverse classrooms, where learning occurs in collaborative, technology-rich spaces that combine human interactions with digital tools. In the Metaverse, learners can access shared knowledge repositories, virtual assistants, and interactive tools that enhance cognitive processes by distributing the cognitive load across the environment [33]. Distributed cognition also emphasizes the importance of context and environment in shaping cognitive processes, which the Metaverse supports by providing learners with immersive, contextually relevant virtual spaces that enhance understanding through situated learning experiences [14].
Furthermore, embodied cognition offers a complementary perspective by highlighting the role of physical actions and sensory experiences in learning. In the Metaverse, learners interact with virtual objects and environments in ways that engage their motor and sensory systems, which enhances cognitive processes and memory retention [34]. This interaction goes beyond passive learning to create active, embodied experiences that are more likely to be internalized by learners. For example, virtual science labs, historical reenactments, or architectural simulations provide tangible, hands-on experiences that deepen understanding through sensory engagement. These contemporary theories—digital, experiential learning, distributed cognition, and embodied cognition—reinforce the potential of the Metaverse to transform educational practices. Together, they establish a robust theoretical foundation for the Meta-MILE framework, ensuring the proposed model is grounded in well-established educational principles while incorporating emerging insights from digital learning research. By integrating these theories, the Meta-MILE framework addresses learners’ multifaceted cognitive, social, and practical needs in virtual environments, offering a scalable, inclusive, and adaptive learning solution for future-ready education.

2.3. Current Gaps and Limitations in Virtual Learning Models

While virtual learning environments have advanced considerably, significant gaps remain in personalization, accessibility, and comprehensive assessment [35]. Research indicates that many existing models do not offer flexible and adaptive learning pathways to accommodate individual learning styles and abilities [36]. The lack of practical AI-driven personalization tools often results in standardized experiences that may not meet the needs of diverse student populations [37]. Furthermore, existing virtual classrooms frequently lack features that address accessibility barriers, such as multilingual support and assistive technologies for students with disabilities, limiting the inclusivity of these platforms [38]. Moreover, current virtual learning models often do not provide holistic assessment methods, relying heavily on traditional testing formats that do not fully capture skills such as collaboration, critical thinking, and leadership [39]. Standardized testing fails to align with the interactive and dynamic nature of virtual environments, creating a disconnect between learning activities and assessment methods [40]. Further limitations are evident in the lack of adequate teacher training and support infrastructure, which are crucial for effective implementation [41]. Teachers often express a need for professional development that covers virtual classroom management, technical troubleshooting, and the integration of immersive tools into lesson plans [42,43].
Several prominent virtual learning platforms, such as Google Classroom, Microsoft Teams for Education, and Moodle, have significantly contributed to the advancement of digital education by enabling remote learning, content distribution, and collaboration [8]. However, despite their widespread adoption, these platforms face notable limitations in personalization, accessibility, and assessment methods, which hinder their ability to meet the diverse needs of modern learners. For example, Google Classroom offers standardized content delivery tools, but lacks AI-driven personalization features that can adapt to individual student learning styles and progress [44]. Without adaptive pathways, the platform often provides a one-size-fits-all approach, which may disengage students who require more tailored support. Similarly, Microsoft Teams for Education provides robust communication features, such as video conferencing and file sharing, but lacks built-in accessibility tools, such as screen readers, voice recognition, and real-time captions, which are critical for supporting students with disabilities [45]. These limitations in personalization and accessibility can hinder inclusivity and prevent some learners from fully participating in virtual classrooms.
In addition to gaps in personalization and accessibility, many existing platforms fail to provide holistic assessment methods that align with the dynamic nature of virtual learning environments. For example, Moodle and Blackboard rely primarily on traditional assessments, such as quizzes and exams, which do not capture essential skills of the 21st century, including critical thinking, collaboration, and problem solving [46]. These platforms lack scenario-based assessments that allow students to apply knowledge in practical, real-world contexts, limiting their ability to develop higher-order thinking skills. In addition, many virtual learning models do not include real-time feedback mechanisms, which prevents educators from effectively adapting their teaching strategies to meet individual student needs. This gap between interactive learning activities and static assessment formats reduces the overall effectiveness of virtual classrooms in preparing students for future challenges. Addressing these gaps requires a multi-layered approach, such as the proposed Meta-MILE framework, which incorporates adaptive learning tools, assistive technologies, and innovative assessment methods to create inclusive, scalable, and competency-based virtual learning environments.

2.4. Positioning the Metaverse Classroom Within the Literature

This study builds upon existing research in immersive learning by addressing these current gaps and expanding on the potential of a fully integrated, multi-layered virtual classroom model. By incorporating AI-driven personalization, accessibility features, collaborative tools, and scenario-based assessments, the Metaverse classroom aims to address the critical limitations identified in the current literature. The emphasis of the proposed model on scalability and modular design allows it to overcome common technological barriers, ensuring that diverse student populations can access and benefit from the virtual learning experience [47]. The theoretical foundations of constructivism, experiential learning, and social learning support the educational validity of the Metaverse classroom, positioning it as a comprehensive and adaptable framework for modern education [48].
In summary, while immersive technologies have laid a strong foundation for virtual learning, this review of the literature reveals a need for innovative models that integrate these technologies with inclusive, adaptive, and assessment-oriented designs [49]. As proposed in this study, the Metaverse classroom seeks to bridge these gaps by creating a future-ready learning environment grounded in educational theory and responsive to diverse student needs [50]. Through this comprehensive approach, the Metaverse classroom has the potential to redefine virtual learning, offering a model that not only enhances student engagement and skill acquisition but also aligns closely with the evolving demands of the educational landscape [51].

3. Metaverse Classroom: A Layered Architectural View

3.1. Infrastructure Layer

3.1.1. Platform Technology

The platform technology of a Metaverse classroom serves as the essential foundation, enabling the creation and hosting of dynamic, interactive virtual environments [52]. It supports immersive 3D spaces and interactive features, making the virtual learning experience engaging and accessible [53]. Platforms like Unity, Unreal Engine, and AltspaceVR provide robust tools to build virtual worlds, offering graphical fidelity, customizability, and essential functionalities [54]. Unity and Unreal Engine are particularly well-suited for creating detailed educational simulations and virtual laboratories due to their powerful 3D rendering and scripting capabilities [55]. These platforms also support scripting and modular asset management, allowing developers to create customized spaces tailored to specific educational needs [56]. An effective platform must support virtual reality (VR) and augmented reality (AR) to enhance immersion. VR enables students to engage deeply with their environment through life-like simulations [57]. For example, science students could perform virtual dissections, and history students could explore ancient civilizations [58]. AR, on the other hand, overlays virtual elements onto the real world, enriching blended learning experiences [59]. Tools like ARKit and ARCore facilitate these integrations, allowing students to explore holographic models or engage with landmarks through mobile devices [60]. Combining VR and AR creates a flexible and versatile learning environment [60].
Scalability is a critical feature of Metaverse platforms, as it ensures that the classroom can accommodate a wide range of devices and user volumes [16]. These platforms must be accessible on various devices such as VR headsets, PCs, tablets, and smartphones to ensure inclusivity [61]. They should also manage varying numbers of users efficiently to maintain performance, whether for small lab activities or large lectures [62]. Platforms like AltspaceVR offer infrastructure for large groups, while Unity and Unreal allow performance customization across different devices [63]. Scalability ensures the classroom can grow with minimal disruption as user needs evolve [53]. Platform technology must also support integrations with additional tools and plugins to enhance functionality [64]. These integrations can include AI tools for personalized learning paths, analytics to track student engagement, and gamification features like quizzes and rewards [65]. Unity and Unreal can connect with third-party tools, such as IBM Watson for AI-driven customization or Kahoot for interactive assessments, through plugins and APIs [66]. This extensibility enables the creation of adaptive, interactive classrooms that meet diverse educational requirements [67]. Finally, data security and encryption are integral to platform technology to protect sensitive student information [68]. Platforms must comply with data protection standards like the General Data Protection Regulation (GDPR) and the Family Educational Rights and Privacy Act (FERPA) to ensure privacy [69]. Unity and Unreal offer documentation on data encryption, and platforms like AltspaceVR have built-in security features [54]. Strong security protocols prevent unauthorized access, allowing students to participate in virtual learning safely [70]. By prioritizing security, platform technology creates a safe and stable learning experience [56]. Figure 1 illustrates the conceptual layers of the Metaverse classroom, providing a foundation for understanding its structure and applications. Also, Table 1 represents the MoSCoW (must-have, should-have, could-have) prioritization for essential features critical to the foundational functionality of the Metaverse classroom.

3.1.2. Network and Connectivity

Virtual collaboration spaces in a Metaverse classroom create dynamic environments where students can engage in teamwork, group discussions, and collaborative projects, mirroring real-world interactions [61]. These spaces feature breakout rooms facilitating smaller group interactions, enabling focused collaboration on specific tasks or discussions [71]. For instance, during project-based learning activities, students can split into breakout rooms to work on different topics and later present their findings to the main class [72]. This structure promotes engagement and personalized teacher support within each group [73]. Shared whiteboards enhance collaboration by allowing students to brainstorm, solve problems, and visualize concepts collectively [74]. Digital whiteboards like Miro and Jamboard offer multi-user interaction across devices like VR headsets or tablets, making real-time collaboration more effective [75]. For example, during a science experiment simulation, students can outline hypotheses, document results, and analyze data together on the whiteboard [76]. Real-time communication tools, including voice and chat functions, are essential for creating a socially engaging virtual environment [77]. Voice functions enable natural conversations, while text chat provides an alternative for students who prefer written communication or face connectivity challenges [78]. These tools support diverse communication preferences and foster inclusivity [79]. Voice channels are particularly useful for debates and group discussions where real-time articulation of ideas is necessary [80]. Text chat can aid asynchronous interactions or bridge language barriers through built-in translation tools [81].
Multiple communication modes ensure all students can participate meaningfully, regardless of their preferences or limitations. Document sharing and co-editing capabilities further enhance collaboration by allowing students to work on assignments and projects seamlessly [82]. Platforms like Google Workspace and Microsoft Teams can integrate into the Metaverse classroom, enabling real-time co-authoring of documents, presentations, and spreadsheets [83]. Students can brainstorm on whiteboards, discuss ideas via voice chat, and edit shared documents—all within the virtual environment [84]. This seamless integration mimics real-world collaborative tools, helping students develop essential digital teamwork skills [3]. By enabling students to edit, comment, and share resources, virtual collaboration spaces cultivate a sense of teamwork and prepare them for professional environments [85]. Lastly, teacher facilitation and monitoring tools are crucial for guiding and supervising student interactions [86]. Educators can enter and exit breakout rooms to provide support, offer feedback, and observe group dynamics [87]. These tools help teachers monitor participation, identify areas where students need help, and encourage constructive dialogue [88]. For example, during a debate, teachers can visit breakout rooms to coach students on debate techniques and stimulate critical thinking [89]. These interactions create richer learning experiences by providing tailored support to each group [90]. Ultimately, virtual collaboration spaces in a Metaverse classroom foster teamwork and prepare students for academic and professional success [91].

3.1.3. Hardware Integration

Hardware integration in a Metaverse classroom ensures that all students can access and participate fully in the virtual environment, regardless of their available technology [92]. This compatibility allows access through various devices such as VR headsets, computers, tablets, and smartphones [93]. While VR headsets provide the most immersive experience, compatibility with desktops and mobile devices ensures flexibility and accessibility for students from different socioeconomic backgrounds [94]. For instance, students without VR headsets can still engage meaningfully using desktops or mobile devices, making learning more inclusive. Furthermore, VR headsets like the Oculus Rift, HTC Vive, or Meta Quest offer a fully immersive 3D experience, enabling students to explore complex concepts through hands-on simulations [95]. For example, a biology class can use VR to perform virtual dissections, allowing students to manipulate 3D models to better understand anatomy [55]. However, the Metaverse classroom should also support lower-end VR devices to avoid reliance on premium equipment [96], ensuring that all students can engage with the content, regardless of the hardware they own.
Moreover, desktop and laptop compatibility is crucial for students who do not have access to VR headsets [97]. With traditional computer labs and home desktops, students can navigate 3D environments using keyboard and mouse inputs [98]. This setup allows participation in virtual activities such as science experiments, historical site explorations, and collaborative projects [99]. Many schools already have desktop infrastructure, making Metaverse implementation cost-effective and widely accessible [8]. Tablets and smartphones further expand accessibility by allowing students to access the Metaverse classroom through touch interfaces [18]. Tablets provide larger screens, clearer visuals and better engagement than smartphones [100]. Mobile devices are practical alternatives for students without computers or VR headsets, especially in regions where mobile technology is more prevalent [55]. Mobile compatibility enhances the portability of the Metaverse classroom, allowing students to continue learning outside traditional settings, such as during field trips or at home [16]. Finally, cross-platform synchronization is vital in ensuring students can transition smoothly between devices without losing progress or settings [101]. For example, a student might begin a lesson on a desktop at school and continue it on a tablet at home [102]. Cross-platform support ensures a consistent learning experience across devices [103], creating a cohesive and flexible virtual classroom environment. This continuity enables students to engage with content based on their needs and circumstances, making the Metaverse classroom more accessible and inclusive [104].

3.2. Content and Interaction Layer

3.2.1. Three-Dimensional Virtual Environments

Three-Dimensional virtual environments are central to delivering immersive and interactive learning experiences in a Metaverse classroom [92]. These environments provide realistic, subject-specific spaces that make learning more engaging and relevant [105]. For example, history students might explore an ancient civilization, walk through historic sites, interact with artifacts, and observe past events [106]. This multisensory experience deepens student engagement, fostering curiosity and retention. The breakout rooms enhance learning by creating spaces tailored to specific activities or subjects [107]. In a literature class, students might gather in a virtual library to discuss novels or use a stage setting to role-play scenes from a play [108]. These rooms promote focused collaboration and allow teachers to provide individualized support by moving between groups to monitor progress and offer guidance [87]. Virtual science labs offer hands-on experimentation without the limitations of physical lab spaces [109]. Students can conduct complex experiments, handle hazardous materials, or manipulate biological models safely and repeatedly [110]. For example, students might dissect a virtual frog to study anatomy without ethical concerns. Chemistry students could observe chemical reactions in real time without risk. These labs encourage trial-and-error learning, improving scientific understanding and confidence in experimentation [111]. In addition to academic settings, virtual creative studios allow students to explore artistic subjects in interactive 3D spaces [112]. These studios might include digital art rooms, virtual music instruments, or performance stages for theater or dance practice. Virtual creative spaces offer tools and environments that may not be available in physical classrooms, allowing students to experiment and express themselves freely [113]. Lastly, 3D virtual environments are highly adaptable, allowing teachers to modify settings based on lesson objectives or student needs [3]. For instance, an economics class might start in a lecture setting and transition to a virtual marketplace where students simulate managing resources. Teachers can save these settings for future use, enabling interactive, responsive, and engaging lesson plans [114].

3.2.2. Interactive Learning Tools

Interactive learning tools in a Metaverse classroom bring concepts to life by providing hands-on, immersive experiences that engage students in active learning [115]. These tools include 3D simulations, holographic displays, and virtual laboratories, allowing students to explore complex topics interactively. For example, 3D simulations make abstract concepts, such as atomic structures or planetary motion, tangible and visually engaging by letting students manipulate and observe components from different angles [116]. This interactive approach bridges the gap between theory and practice, helping students deepen their understanding through exploration and experimentation. Virtual laboratories offer a safe, accessible environment for students to conduct experiments without the constraints of physical labs [91]. In a virtual chemistry lab, students can mix chemicals and observe reactions without safety hazards [111]. Biology students can examine virtual specimens to study anatomy without ethical concerns, while physics students can safely explore forces, motion, and electricity [96]. These labs remove time, cost, and resources barriers, allowing students to repeat experiments and learn from trial and error, which is essential for developing scientific thinking and analytical skills [117]. Holographic displays enhance learning by providing lifelike 3D visualizations [118]. Students can interact with holograms representing historical artifacts, anatomical structures, or landscapes, gaining a multi-perspective view that traditional methods cannot offer [119]. For example, medical students can study the human body layer by layer, while geography students can explore rock formations in detail [120]. These displays promote curiosity and discovery by enabling students to interact with intricate details in ways that static images cannot achieve.
Gamified learning elements add another layer of engagement, making learning enjoyable and goal-oriented [92]. Features like quizzes, achievements, and progression levels tap into students’ intrinsic motivation. For instance, history students might earn badges by completing virtual quests in different historical periods. In contrast, science students could compete in lab challenges to achieve high scores or fast completion times [95]. Gamification helps students stay focused and motivated by associating learning with the excitement and rewards of game-like progress. Finally, real-time feedback and analytics allow teachers to monitor student engagement and adjust their instruction accordingly [65]. Teachers can identify which students struggle with specific concepts or recognize patterns that indicate knowledge gaps [121]. This feedback helps personalize learning by offering targeted support or challenges based on individual needs. Students also benefit from immediate feedback, allowing them to adjust their approaches and continuously improve [122]. By integrating interactive tools with feedback mechanisms, the Metaverse classroom becomes a dynamic learning environment that evolves with student progress, fostering personalized and impactful education [18].

3.2.3. Gamified Elements

Gamified elements in a Metaverse classroom make learning more engaging by incorporating features like quizzes, badges, and level progression to motivate students and enhance retention [52]. These tools transform traditional learning into interactive, achievement-driven experiences. Quizzes reinforce understanding by encouraging students to review material in manageable formats, helping them identify knowledge gaps and improve through immediate feedback [123]. This positive feedback loop promotes continuous engagement with the curriculum. Badges and achievement systems provide students with tangible milestones that recognize progress [52]. Earning badges for completing tasks or demonstrating skills creates a sense of accomplishment that motivates students to keep learning [50]. For example, in a Metaverse history class, students might earn badges for completing virtual museum tours or achieving high quiz scores on different historical eras [52]. These digital trophies foster pride and a sense of belonging within the virtual classroom community [124].
Level progression adds motivation by offering a structured path through increasingly challenging material [125]. As students master topics, they unlock more complex content, encouraging continuous growth [13]. For instance, a science course in the Metaverse might start with basic physics and progress to advanced topics like electromagnetism or quantum theory [126]. This incremental difficulty keeps students engaged by providing consistent challenges tailored to their learning pace [71]. Leaderboards and collaborative challenges introduce a social and competitive element to gamified learning [127]. Displaying rankings or team scores motivates students to put in extra effort and work with peers to achieve shared goals [84]. For example, students might compete in virtual science fairs or group problem-solving challenges, fostering teamwork and communication [25]. Leaderboards also help build a supportive learning community by celebrating collective and individual achievements [128]. Finally, real-time feedback mechanisms within gamified elements provide students with actionable insights into their progress [3]. Instant feedback from quizzes helps students understand their strengths and weaknesses, promoting a growth mindset [25]. Teachers can use these data to personalize instruction and address individual needs, ensuring students stay motivated and supported [3]. By integrating real-time feedback, the Metaverse classroom creates a dynamic, student-centered learning environment that evolves based on student progress [129].

3.3. Personalization and Accessibility Layer

3.3.1. AI-Driven Personalization

AI-driven personalization in a Metaverse classroom offers a customized learning experience by adapting content, pace, and instruction style to each student’s needs [130]. Using intelligent algorithms, AI monitors student progress and adjusts lessons in real time. For example, if a student struggles with a math concept, the AI can provide additional practice or simplify the material [7]. Conversely, AI can introduce more advanced challenges for students excelling in a subject to maintain engagement and prevent boredom [71]. This ensures students progress comfortably, feeling both challenged and supported. One key benefit of AI-driven personalization is real-time feedback, which helps students immediately recognize and correct mistakes [131]. For instance, in a virtual chemistry lab, students might receive instant feedback on procedural errors, guiding them toward the correct method [132]. This immediate response reduces uncertainty about performance, boosting clarity and confidence [133]. Real-time feedback fosters a proactive learning mindset, where students view challenges as growth opportunities rather than obstacles [83].
AI analytics also give educators valuable insights into student performance and engagement [18]. AI can track patterns, such as subjects where students struggle, time spent on tasks, and preferred learning methods [44]. For example, if AI detects that a student learns better with visual aids, teachers can adjust their approach to include more visuals [134]. His targeted strategy empowers teachers to offer personalized support, creating an environment where individualized learning is the standard [135]. Adaptive learning paths are another powerful feature of AI-driven personalization. These paths evolve based on a student’s progress, preferences, and engagement levels [136]. For example, in a Metaverse history class, AI might adjust lessons to suit a student’s preference for narratives, timelines, or simulations [52]. The AI recalibrates their learning paths as students advance, introducing new resources and challenges to match their development. This dynamic approach gives students a sense of ownership over their learning journey [137]. Finally, AI-driven personalization enhances student motivation by creating a sense of personal relevance and achievement [138]. AI tracks progress and provides tailored encouragement, recognizing accomplishments and suggesting next steps to keep students engaged [20]. For instance, after completing a challenging module, a student might receive a congratulatory message or a suggestion for further exploration [139]. This personalized feedback reinforces a sense of achievement and forward momentum, making students feel valued and supported [140]. By transforming the Metaverse classroom into a responsive, adaptive ecosystem, AI-driven personalization enriches the learning experience to meet each learner’s needs and potential [136].

3.3.2. Assistive Technologies

Assistive technologies in a Metaverse classroom ensure that virtual education is inclusive and accessible to all students, particularly those with disabilities or language barriers [141]. These tools help break down barriers to learning, allowing every student to fully engage with class activities and course materials [15]. For example, closed captioning provides a text version of spoken content, benefiting students who are deaf or hard of hearing [7]. Similarly, visual cues guide students through interactive content, helping those with auditory processing issues better understand instructions [9]. Voice-to-text technology enhances accessibility by allowing students to use voice commands to interact with the Metaverse classroom [142]. This tool is particularly valuable for students with mobility challenges or learning disabilities. For example, students with dyslexia can participate in written assignments or group discussions by speaking instead of typing [143]. Voice-to-text technology promotes independence by allowing students to contribute without relying on traditional text-based inputs, ensuring that all voices are heard [19]. Real-time translation services support a multilingual learning environment by overcoming language barriers [144]. These tools allow international students or those learning the primary language of instruction to follow course material in their preferred language [128]. For example, a student in a science lesson can receive real-time translations of complex terms, enabling them to participate as actively as their peers [13]. Real-time translation fosters intercultural understanding and collaboration, making the Metaverse classroom more inclusive and globally connected.
Customizable accessibility settings allow students to adjust features based on their preferences and needs [145]. Students can modify font sizes, adjust colors for visual impairments, or alter audio settings to improve sound clarity [146]. For students with ADHD or attention challenges, features that reduce visual clutter or provide focus cues can enhance engagement [147]. These adaptable settings create a flexible learning environment that caters to individual needs and promotes self-directed learning [148]. Finally, gesture recognition and spatial audio further enhance the inclusivity of the Metaverse classroom [149]. Gesture recognition enables students with limited mobility to interact with virtual environments using hand or head movements, while spatial audio directs sound toward specific areas, improving auditory focus [150]. For example, spatial audio can help students concentrate on their teacher’s instructions without being distracted by background noise. Gesture recognition allows students to engage with interactive elements, even if they cannot use traditional controls. Together, these tools make the Metaverse classroom more accessible for students with diverse abilities, creating a truly inclusive educational experience.

3.3.3. Multilingual Support

Multilingual support in a Metaverse classroom ensures an inclusive learning environment for a diverse, global student body [7]. Real-time translation allows students to participate in discussions, engage with content, and collaborate on projects without language barriers [151]. For example, students can receive live translations during virtual lectures, enabling them to understand complex topics in their preferred language [44]. This feature promotes equitable access to education and encourages international participation. Real-time translation is especially valuable during group discussions and collaborative activities, where language differences could otherwise hinder participation [144]. Students can share ideas and work together regardless of their native language, fostering intercultural exchanges [27]. For instance, in a science project, students from different countries can express ideas in their native languages while the system provides real-time translations for all participants [92]. This feature enhances global connectivity and cultural understanding, enriching the learning experience.
Beyond translation, localized content adaptations further support students by tailoring educational materials to their cultural contexts [152]. These adaptations include culturally relevant examples and illustrations that make lessons more relatable [153]. For example, a history lesson might feature regional events or figures that resonate with specific student groups [104]. This customization bridges understanding gaps and makes learning more meaningful for students worldwide. Voice and text translation tools enhance accessibility for students who prefer alternative communication methods [145]. Voice-to-text translation allows students to speak in their native language and receive translations in text format, or vice versa, depending on their needs [154]. This flexibility is helpful for students with limited literacy in the language of instruction or those with disabilities who find text-based communication challenging [155]. For example, a visually impaired student might use voice-to-text in their preferred language, while others can type responses and have them translated in real time [142]. This adaptability ensures that all students can participate in a way that best suits them. Cultural inclusion within multilingual support fosters a deeper sense of belonging and respect [137]. Recognizing multiple languages in the classroom validates students’ diverse identities and encourages them to see their cultural backgrounds as assets in the learning process [156]. For instance, students might share phrases or traditions from their cultures during language or social studies lessons, contributing to a more globally-minded classroom. Multilingual support transforms the Metaverse into a multicultural space that celebrates diversity and prepares students for communication in an interconnected world.

3.4. Collaboration and Social Layer

3.4.1. Avatar-Based Interaction

Avatar-based interaction in the Metaverse classroom enhances student engagement by allowing them to represent themselves visually in a digital space [157]. Customizable avatars help students feel more connected to their virtual environment and peers, reducing the sense of distance often associated with online learning [158]. This visual representation makes learning more personal and interactive, fostering a stronger sense of community and collaboration [14]. For instance, seeing peers represented as avatars can reduce feelings of isolation and encourage students to participate actively in class activities. Avatars also enable nonverbal communication through gestures, facial expressions, and body language, essential for creating meaningful social interactions [159]. In traditional classrooms, non-verbal cues play a crucial role in communication, and avatars replicate this in the Metaverse [160]. For example, a student can nod to show agreement, raise a hand to ask a question or express surprise through facial animations. These interactions make virtual exchanges feel more authentic and help teachers gauge student engagement and adjust their instruction accordingly [91]. Emotional expression through avatars builds empathy and stronger relationships among students [161]. Avatars that display emotions allow students to express feelings such as encouragement or frustration during group work, fostering a supportive learning environment [162]. For example, a student might smile or express enthusiasm through their avatar during a group project, boosting team morale and creating a positive dynamic [163]. Emotional expression humanizes the virtual learning experience, improving collaboration and class cohesion.
Avatars also support cultural expression and identity, allowing students to showcase aspects of their background through their virtual appearance [158]. Students can customize avatars with culturally significant symbols, attire, or colors, promoting cultural inclusivity and awareness [164]. For instance, students may choose clothing or accessories that reflect their heritage, introducing opportunities for intercultural dialogue and helping classmates appreciate different perspectives [165]. This personalization encourages self-expression and fosters pride in one’s identity, creating a more inclusive classroom environment [129]. Finally, avatars serve as the foundation for interactive learning experiences that go beyond traditional classroom activities [3]. Students can use avatars in virtual simulations or role-play scenarios to enhance their understanding of the topic [130]. For example, in a history lesson, students might take on avatars representing historical figures, adding depth to their exploration of the topic [129]. In language learning, avatars can role-play real-life conversations, helping students practice practical skills in an engaging way [166]. By participating actively through avatars, students immerse themselves more fully in the material, improving both comprehension and retention [167].

3.4.2. Virtual Collaboration Spaces

Virtual collaboration spaces in a Metaverse classroom create dynamic environments that foster teamwork and peer participation [91]. These spaces allow students to break into smaller groups for focused discussions, brainstorming sessions, or collaborative projects, simulating traditional study groups [1]. For example, in a science class, students could work in separate virtual labs to conduct experiments or simulations, promoting targeted exploration of their assigned topics [168]. These spaces help build community, making learning more interactive and engaging. Shared digital whiteboards within collaboration spaces enhance real-time group work [169]. Students and teachers can brainstorm, outline ideas, and solve problems visually on these boards, encouraging creativity and collective problem-solving [170]. For instance, students might collaborate on complex equations during a math lesson by illustrating each step on a shared whiteboard [171]. Tools like Miro and Jamboard, designed for multi-user interaction, can be integrated into the Metaverse, allowing students to collaborate from various devices and locations [172]. Chat and voice functions further improve communication within these spaces, mimicking face-to-face interactions [8]. Voice channels facilitate natural, real-time conversations essential for discussions and problem-solving. At the same time, text chat provides a quieter option for students who prefer written communication or face audio limitations [173]. This dual mode of communication accommodates different preferences and accessibility needs, ensuring that all students can participate meaningfully [145].
Additionally, integrating translation tools within chat and voice functions allows students from diverse linguistic backgrounds to collaborate without language barriers [144]. Document sharing and co-editing capabilities make collaboration seamless by enabling students to work on shared assignments and projects in real time [3]. Tools like Google Workspace and Microsoft Teams can be integrated into the Metaverse, allowing students to co-author documents, presentations, or spreadsheets without leaving the virtual space [174]. For instance, a research group could brainstorm on a shared whiteboard, discuss ideas via voice chat, and simultaneously draft their presentation in a shared document [8]. This functionality mirrors real-world collaborative work environments, helping students develop essential digital skills. Teacher facilitation and monitoring tools within virtual collaboration spaces ensure students remain focused and supported [84]. Teachers can enter breakout rooms to observe group dynamics, provide feedback, and clarify instructions as needed [175]. For example, in a history project, a teacher could join each group to offer context or suggestions, improving the quality of discussions [3]. This level of involvement ensures that students receive personalized attention and mentorship, enhancing the overall learning experience [137]. Together, virtual collaboration spaces in a Metaverse classroom foster an interactive, flexible, and supportive learning environment that encourages teamwork and develops critical social skills [27].

3.4.3. Community Engagement

Community engagement in a Metaverse classroom extends learning beyond traditional boundaries by connecting students with mentors, industry professionals, and community leaders [137]. Virtual hubs provide students access to real-world resources and networks that support their academic and career development [1]. For example, students interested in STEM could attend virtual talks by scientists, while aspiring writers could join question-and-answer sessions with published authors [11]. These interactions broaden students’ perspectives, introduce potential career paths, and help them explore areas of interest beyond the typical classroom experience [61]. Workshops and skill-building sessions in the Metaverse provide students with hands-on learning experiences facilitated by experts in various fields [176]. These workshops can range from coding boot camps to art tutorials, helping students develop practical skills that complement their academic learning [16]. For instance, a business workshop might have students pitch ideas to virtual investors, simulating real-world entrepreneurial experiences. These sessions improve employability by building communication, creativity, and problem-solving competencies. Additionally, virtual workshops ensure accessibility for students in remote or underserved areas, offering equal learning opportunities regardless of location [145].
Virtual internships and shadowing opportunities allow students to explore different professions within the Metaverse, offering career insights without the need to leave their virtual environment [177]. These internships simulate real-world tasks and provide mentorship from industry professionals [27]. For example, students interested in environmental science might collaborate with mentors on a virtual ecosystem conservation project [1]. These experiences help students build industry-standard teamwork and project management skills, preparing them for future careers. Virtual internships are particularly valuable for students who lack access to in-person opportunities, promoting equity in career exploration [178]. Community projects and service learning initiatives connect students with local organizations, NGOs, or global causes, fostering social responsibility [179]. For example, students could organize virtual fundraising events or develop campaigns promoting environmental awareness, gaining valuable skills in communication, research, and collaboration [180]. These projects encourage students to apply classroom knowledge to real-world situations, reinforcing the relevance of their education while supporting meaningful causes [17]. Network building in the Metaverse classroom helps students establish valuable connections for future academic and professional success [25]. Through mentorship sessions, group projects, and community events, students expand their social and professional networks [27]. For instance, a student working on a virtual startup might connect with industry advisors, leading to potential job offers or partnerships [58]. These relationships provide students with guidance, career advice, and motivation, equipping them with the skills and networks needed to thrive beyond school.

3.5. Assessment and Feedback Layer

3.5.1. Scenario-Based Evaluations

Scenario-based evaluations in a Metaverse classroom use immersive simulations to assess students’ problem-solving, critical thinking, and adaptability in real-world contexts [181]. Unlike traditional exams, these evaluations place students in realistic situations where they must apply their knowledge to navigate challenges and make decisions [6]. For example, in a virtual economics class, students could manage a business, making budgeting and marketing decisions based on shifting market conditions [182]. These scenarios allow educators to assess practical understanding and decision-making skills often overlooked in traditional tests [71]. In science and engineering courses, virtual lab simulations provide hands-on evaluations that help students solve complex problems in controlled environments [183]. For instance, a chemistry student might be tasked with creating a compound by selecting elements and observing reactions, adjusting their approach based on experimental outcomes [109]. Similarly, engineering students could design virtual bridges, considering material properties, load distribution, and environmental conditions [184]. These assessments go beyond rote memorization by evaluating students’ ability to apply theoretical knowledge to practical challenges [185]. Healthcare training greatly benefits from scenario-based evaluations, allowing students to diagnose and treat virtual patients [183]. Medical students might interact with patient simulations, reviewing symptoms, asking questions, and making evidence-based diagnoses [186]. These evaluations help students integrate knowledge from different medical fields while developing critical thinking and clinical skills. The immersive nature of these simulations also fosters better bedside manner, and recorded interactions allow instructors to provide detailed feedback for improvement [187].
Environmental and social studies scenarios offer students opportunities to address complex, real-world problems requiring ethical, cultural, and environmental consideration. For example, an environmental science simulation might ask students to develop a conservation strategy for an endangered species, balancing ecological needs with local community interests [188]. In political science or ethics courses, students could participate in government negotiations or conflict resolution scenarios, weighing different perspectives and making informed ethical decisions [132]. These activities assess students’ ability to think critically, consider diverse viewpoints, and develop balanced solutions, essential skills for working in a globally connected world. Finally, scenario-based evaluations provide immediate, data-rich feedback to both students and educators [3]. The Metaverse platform can track students’ actions and decisions, offering detailed insights into their problem-solving approaches, decision-making processes, and ability to adapt strategies when facing challenges [134]. These data allow educators to give personalized feedback, helping students identify strengths and areas for improvement [189]. For students, this detailed feedback promotes reflection, growth, and the development of adaptive skills for future scenarios. Overall, scenario-based evaluations encourage students to see learning as a continuous skill development and adaptation process.

3.5.2. Instant Feedback and Analytics

Instant feedback and analytics in a Metaverse classroom provide real-time insights into student learning, allowing students and educators to make immediate adjustments [51]. AI-driven systems deliver instant feedback on tasks, quizzes, or simulations, helping students learn from their mistakes without delays [136]. For example, in a virtual math test, students can see which questions they answered correctly and receive hints for missed questions, enabling them to correct errors and reinforce understanding [190]. Immediate feedback reduces uncertainty, helping students quickly identify areas for improvement and adapt their study strategies, boosting confidence in their knowledge. For educators, analytics provide a detailed view of student progress, highlighting patterns that may not be visible through traditional assessments [6]. AI systems track metrics such as time spent on tasks, types of errors, and problem-solving approaches, compiling these data into reports or dashboards [18]. These insights help teachers identify conceptual struggles and offer targeted support [7]. For example, suppose data show that a student struggles with certain aspects of a physics simulation. In that case, teachers can provide additional resources or modify their approach to address the student’s needs [16]. This creates a more adaptive and personalized learning environment. Class-wide analytics also help educators refine their teaching strategies. By analyzing aggregate data, teachers can identify challenging topics for the entire class and adjust their lessons accordingly [15]. For instance, if many students struggle with a biology lab simulation, teachers can offer guided sessions or additional resources to clarify key concepts [91]. These insights ensure that teaching methods evolve based on student needs, promoting better educational outcomes.
Instant feedback motivates students by reinforcing their efforts and providing clear achievement milestones [52]. Knowing they will receive immediate feedback encourages active engagement with the material. This feedback loop fosters a positive reinforcement cycle, motivating students to build on their strengths and address challenges [133]. Over time, students develop a growth mindset, viewing challenges as learning opportunities rather than obstacles [25]. Finally, the feedback and analytics systems in a Metaverse classroom track behavioral and engagement metrics beyond academic performance [6]. These systems can monitor attendance, participation in collaborative activities, and interaction with learning resources, offering a comprehensive picture of student engagement [97]. For example, if analytics reveal that a student avoids group assignments, educators can address potential participation barriers and encourage collaboration [191]. By intervening early, teachers can address issues impacting student success before they escalate. Overall, instant feedback and analytics foster a proactive, supportive learning environment that continuously adapts to student progress, benefiting both students and educators [16].

3.5.3. Holistic Assessment

Holistic assessment in a Metaverse classroom evaluates a broad range of skills beyond academic performance, including collaboration, leadership, and social interaction [20]. Unlike traditional assessments focusing on test scores, the holistic assessment provides a comprehensive view of students’ growth by tracking their participation in group projects, discussions, and simulations [6]. For example, educators can observe a student leading a virtual science experiment or mediating a group discussion in a history class to assess their communication and problem-solving abilities [17]. This approach ensures that students gain subject knowledge while developing essential interpersonal skills [13]. Collaboration tracking is a key component of holistic assessment in the Metaverse. Tools such as shared whiteboards, group simulations, and document co-editing enable educators to track student contributions to collaborative tasks [192]. Metrics like participation frequency, idea sharing, and responsiveness to peer feedback provide insight into students’ teamwork skills [71]. For example, in a virtual engineering project, students may be evaluated on how they delegate tasks, support peers, and contribute to problem-solving [193]. This focus on collaboration helps identify strengths and areas for improvement in teamwork, a critical skill for academic and professional success.
Leadership assessment in the Metaverse offers students opportunities to demonstrate initiative and guide their peers [17]. Virtual environments provide scenarios where students can take charge, such as directing a virtual lab experiment or organizing tasks in a team project [194]. AI-driven analytics track instances of leadership, including decision-making, delegation, and peer motivation [136]. For example, a student who leads a group discussion demonstrates readiness for leadership roles, preparing them for future professional situations [14]. Social skill assessment in the Metaverse focuses on empathy, communication, and conflict resolution [195]. Through avatar interactions, voice, and chat functions, educators can observe students’ ability to listen actively, provide constructive feedback, and mediate disputes [129]. For instance, a student acknowledging others’ ideas or resolving conflicts during a group activity demonstrates important interpersonal skills [17]. AI analytics can track these behaviors to gauge social development and emotional intelligence, essential for personal and professional success [124]. Lastly, holistic assessment provides reflective feedback to students and educators, promoting continuous improvement across academic and social dimensions [15]. Students receive insights on their strengths and challenges in areas such as teamwork, leadership, and communication, encouraging a more well-rounded view of their progress [3]. These data offer educators a unique perspective on classroom dynamics and individual student needs, enabling more targeted support [1]. Teachers can set personalized goals, track progress over time, and help students develop essential life skills beyond academics [16]. Ultimately, by evaluating a wide range of competencies, holistic assessment in the Metaverse classroom fosters well-rounded individuals equipped with the knowledge and social skills needed to succeed in future challenges.

3.6. Security and Privacy Layer

3.6.1. Data Encryption and Secure Platforms

Data encryption and secure platforms are critical to protecting sensitive student and educator information in the Metaverse classroom [196]. Encryption converts data into a secure code accessible only by authorized users, ensuring that personal and academic records remain private [197]. In a Metaverse setting, where students submit assignments, join discussions, and access resources, encryption safeguards these interactions from unauthorized access [198]. Even if a data breach occurs, encrypted information remains unreadable, reducing the risk of identity theft or data misuse. Compliance with data security standards, such as GDPR and FERPA, adds another layer of protection by enforcing strict regulations on data handling and storage [199]. These standards ensure user consent is respected and student records are kept secure, building trust among parents, students, and educators [132]. Secure platforms are essential for maintaining privacy in a Metaverse classroom [16]. Platforms like Unity and Unreal Engine offer security protocols, but for education, additional measures like secure login, encrypted data handling, and user verification are necessary [54].
Multi-factor authentication (MFA) and single sign-on (SSO) ensure that only authorized users can access the virtual classroom [200]. In addition, regular software updates and automated threat detection further protect against vulnerabilities and suspicious activity [201]. User access control allows schools to manage who can view and edit sensitive data. For example, teachers can access student grades, while students can only view their records [197]. Furthermore, limiting third-party access also helps prevent unauthorized data exposure, ensuring that external collaborators have restricted permissions [196]. These access control measures balance security with the collaborative needs of the Metaverse classroom [16]. Finally, educating students and staff on data security practices is crucial to maintaining a safe virtual environment [17]. Even with advanced security protocols, user behavior significantly prevents breaches [202]. Schools can offer training on password management, recognizing phishing attempts, and responsible data handling [203]. Teaching students and educators about privacy settings and secure file sharing empowers them to actively protect their information. This collective understanding fosters a culture of responsibility, ensuring that all users contribute to a secure Metaverse classroom [203].

3.6.2. Parental Controls and Safe Use

Parental controls in the Metaverse classroom help guardians monitor and manage their children’s virtual interactions, ensuring a safer learning environment [204]. These controls allow parents to set boundaries on the content their children can access, ensuring that experiences are age-appropriate and aligned with educational goals [8]. For example, parents can limit access to certain areas within the Metaverse or restrict communication features to maintain a focused learning environment without distractions [7]. This ability to regulate content reassures parents that their children engage with appropriate material in a secure virtual space. Activity-monitoring tools give guardians visibility into their child’s participation in the Metaverse classroom [205]. Real-time reports or activity summaries show what students are learning, how much time they spend on activities, and who they interact with in virtual spaces. For instance, a parent might receive a weekly report detailing their child’s time in study groups, labs, or virtual lectures. These tools bridge the gap between home and school by keeping parents informed and involved in their child’s education while respecting student autonomy.
Communication controls allow parents to manage who their children interact with during virtual learning sessions, ensuring that interactions remain safe and appropriate [3]. For example, parents can restrict communication to teacher-approved contacts or limit chat and voice features to supervised group settings [13]. These controls help protect students from online risks and maintain a professional learning environment, reducing distractions and allowing students to focus on educational activities [16]. Teachers and parents can collaborate to establish appropriate boundaries, particularly for younger students. Time management tools regulate screen time in the Metaverse classroom, promoting healthy digital habits [178]. These tools allow parents to set daily or weekly time limits, with reminders or automatic logouts to encourage breaks. For instance, a parent could set a timer for a two-hour study session, after which the student is prompted to take a break or log off. Time management tools help prevent fatigue and ensure students engage in sustainable digital learning practices that balance screen time with well-being [132]. Finally, content filtering tools ensure students remain focused on educational material by blocking access to non-educational or distracting content [20]. For example, parents can set filters to block games or social areas unrelated to coursework, directing students toward learning resources and simulations. This filtering minimizes distractions and fosters a focused virtual classroom experience, maximizing learning potential. Using content filtering alongside other parental controls, guardians can create a structured, goal-oriented learning environment that prioritizes academic growth while ensuring digital safety.

3.6.3. Digital Well-Being

Digital well-being in a Metaverse classroom ensures students engage with virtual learning in a healthy and balanced way [206]. In immersive environments where students may lose track of time, digital well-being tools help manage screen exposure to prevent fatigue and maintain focus [132]. Time trackers and break reminders prompt students to take regular breaks, promoting healthy screen-time habits [92]. For example, a reminder might encourage a five-minute break after 30 min of continuous activity, helping students stay refreshed and focused [124]. These features prevent eye strain and mental fatigue, particularly during longer lessons or group projects. Ergonomic support guidelines promote physical well-being by helping students set up workspaces to reduce stress and improve posture [132]. On-screen tips can suggest ideal seating arrangements, screen height adjustments, and arm positioning, especially for students using VR headsets or tablets [207]. For instance, students might receive a notification to adjust their chairs or take a stretching break after extended VR use. Encouraging proper ergonomics reduces discomfort and long-term strain from digital device use.
Mental health resources and mindfulness activities are key components of digital well-being in the Metaverse [208]. Guided mindfulness exercises, breathing techniques, and relaxation activities can help students manage stress and improve focus [124]. For example, students might take a one-minute breathing exercise before a challenging test to calm their minds. Additionally, virtual counseling sessions or access to mental health resources offer students a safe space to seek support if they feel overwhelmed [209]. These resources foster a supportive learning environment, prioritizing emotional well-being. Finally, well-being analytics provide teachers and parents with insights into students’ digital use patterns, helping identify those who may need extra support [124]. Data on screen time, break frequency, and engagement levels allow educators to offer personalized interventions without infringing on student autonomy [7]. For instance, if a student consistently exceeds recommended screen time or rarely takes breaks, a teacher might suggest setting stricter limits or incorporating wellness activities. This data-driven approach supports healthy digital practices, creating a balanced learning environment [16]. By integrating digital wellness features holistically, the Metaverse classroom promotes a sustainable learning experience that prioritizes students’ physical and mental health [131].

3.7. Management and Support Layer

3.7.1. Teacher Dashboards and Training

Teacher dashboards in the Metaverse classroom give educators a centralized view of student engagement, progress, and performance in real time [18]. These dashboards offer a holistic perspective on classroom dynamics, including attendance, participation, assignment completion, and assessment performance. For example, teachers can quickly identify students who actively participate in discussions and those who may need extra support based on low engagement metrics [15]. Teachers can proactively respond to student needs by accessing these comprehensive data, creating a more personalized and supportive learning environment [17]. Analytics and progress tracking are key features of teacher dashboards, offering deeper insights into student learning patterns [18]. Teachers can analyze academic performance and social interactions to identify trends that may not be visible in traditional classrooms [210]. For instance, analytics may show that certain students excel in collaborative projects but struggle with individual tasks. These insights allow teachers to adapt their instructional strategies to better support each student’s strengths and challenges [17]. Progress tracking also helps teachers set learning milestones, keeping students motivated and aware of their growth [194]. Virtual classroom management tools within dashboards allow teachers to efficiently organize and control learning activities [51]. These tools enable educators to seamlessly assign tasks, manage breakout rooms, and supervise group projects. For example, teachers can use dashboards to assign students to virtual labs or discussions based on their performance or interests [194]. In addition, they can also monitor breakout room discussions, join as needed to provide guidance and adjust group dynamics to improve collaboration [91]. These management tools help maintain an organized and focused virtual learning environment, regardless of class size or lesson complexity.
Teacher training is essential to ensure educators can effectively use Metaverse tools and manage virtual classrooms confidently [17]. Training sessions cover technical aspects like navigating VR tools and managing 3D environments and best practices for maintaining student engagement [16]. For example, teachers learn how to set up virtual labs, handle interactive sessions, and integrate immersive simulations into their curriculum [6]. Hands-on training helps reduce the initial barriers to using new technology, ensuring teachers feel comfortable leading lessons in the Metaverse [132]. Continuous professional development ensures educators stay updated with emerging technologies and virtual teaching strategies [17]. Through online workshops, training simulations, and collaborative sessions with other educators, teachers can refine their instructional methods and explore new approaches to teaching [3]. For instance, teachers might attend virtual workshops on AI-driven personalization or effective assessment techniques in immersive environments. By investing in ongoing training, the Metaverse classroom ensures teachers remain prepared to adapt to technological advancements, creating a future-ready educational experience [50].

3.7.2. Content Management

Content management in a Metaverse classroom ensures that lesson materials, curriculum updates, and resources remain organized, accessible, and up to date [211]. A robust content management system (CMS) provides a centralized hub where educators can create, store, and modify instructional materials such as videos, simulations, readings, and interactive elements [11]. This organization streamlines lesson planning and ensures consistent content delivery, making each lesson engaging and well-prepared with relevant resources [136]. Updating curriculum materials is essential in a Metaverse classroom to keep lessons current with advancements and evolving student needs. With an adaptable CMS, teachers can easily incorporate new findings without overhauling the course. For example, a science teacher might update a virtual lab with the latest research, or a history teacher could modify a timeline to reflect recent discoveries [13]. This flexibility ensures that students always learn from the most relevant information, fostering a culture of continuous learning [17].
Organizing and categorizing content within the CMS improves accessibility for both students and teachers [7]. By tagging materials according to subject, difficulty level, or learning objectives, users can quickly find relevant resources, reducing downtime and streamlining lesson transitions. For instance, a teacher could tag materials under “Physics–Energy” or “Advanced Algebra”, making it easier for students to access content that aligns with their studies [194]. This system supports self-paced learning by allowing students to independently retrieve resources, promoting ownership of their educational journey within the Metaverse [7]. Customizing lesson materials to suit different learning styles becomes more efficient with a flexible CMS [56]. Teachers can store multiple versions of content, such as simplified explanations, visual aids, or interactive exercises, and match these to individual student needs [17]. For example, a math teacher might create practice problems with varying difficulty levels or include hands-on activities for students who benefit from experiential learning. This adaptability allows educators to personalize learning experiences and address the diverse needs of Metaverse learners [212]. Finally, data security and access controls are critical to maintaining a safe digital learning environment within the CMS [213]. Teachers can set permissions to manage who can view, modify, or share content, protecting student information and intellectual property [214]. For instance, some materials might be restricted to teacher access only, while others are shared with students for collaborative learning [17]. These security protocols ensure that content is managed responsibly, fostering a safe and organized virtual classroom [135].

3.7.3. Technical Support

Technical support in a Metaverse classroom is essential to ensure smooth operations, as virtual learning environments rely heavily on functioning technology [16]. In-platform technical support provides students, teachers, and administrators with direct access to troubleshooting resources, helping resolve issues quickly to minimize disruptions [215]. For example, if a student has trouble accessing a virtual simulation, tech support can assist in real time, allowing the student to rejoin the lesson promptly [71]. Real-time troubleshooting, such as live chat or virtual help desks, is particularly valuable during collaborative activities, ensuring technical issues don’t hinder engagement [56]. For instance, if a student’s avatar becomes unresponsive during a group project, support can intervene immediately to keep the student involved. This real-time assistance helps maintain a stable, reliable learning environment [18]. Self-help resources and tutorials within the platform empower users to solve common technical issues independently, promoting autonomy and digital literacy [216]. These resources may include step-by-step guides, instructional videos, and FAQs covering topics like VR headset calibration or adjusting user settings [1]. For example, students unfamiliar with VR setups can follow a tutorial to troubleshoot minor issues without contacting support [217]. By reducing the reliance on live support, self-help tools build user confidence and contribute to a smoother classroom experience [218].
Proactive maintenance and system monitoring are critical to preventing issues before they disrupt classroom activities [16]. Automated tools within the platform track system performance, detect irregularities, and alert support teams to potential problems [201]. For instance, if the system detects connectivity lags or server overload risks, support teams can take preventive measures to stabilize performance [219]. Proactive maintenance reduces the likelihood of major technical failures during critical learning moments, ensuring consistent, high-quality virtual interactions [16]. Finally, specialized support for educators is crucial to help teachers feel confident leading immersive digital lessons [15]. Training sessions can cover troubleshooting, managing virtual classrooms, and optimizing platform settings to prepare educators for potential technical challenges [16]. In addition, additionally, dedicated tech support can assist with tasks specific to teaching, such as setting up breakout rooms, managing virtual labs, or tracking student analytics [1]. This targeted support allows educators to focus on delivering quality instruction without being distracted by technical issues [17]. By integrating real-time assistance, self-help resources, proactive maintenance, and specialized support for educators, the Metaverse classroom ensures that technology enhances rather than disrupts the learning experience.

4. Innovative Approach to Building a Metaverse Classroom

Building a Metaverse classroom is an innovative step in modern education, combining technology and strategic planning to create engaging and inclusive virtual learning spaces [16]. The process begins with defining clear educational goals that address challenges such as equitable access, student engagement, diverse learning needs, and career readiness [144]. Identifying the target audience—including age groups, subject areas, and unique requirements like assistive technologies or multilingual support—ensures the classroom design aligns with real-world applications and student needs [16]. Choosing the right Metaverse platform is critical to ensure the classroom supports 3D environments, VR/AR capabilities, and scalability across devices, from VR headsets to smartphones [56]. Platforms like Unity, Unreal Engine, Mozilla Hubs, or AltspaceVR enable the creation of immersive virtual spaces that are accessible and secure. Prioritizing data security and compliance with regulations like GDPR and FERPA protects student information and ensures the classroom is a safe learning environment [220]. A versatile, secure platform makes the Metaverse classroom adaptable to various educational contexts while safeguarding privacy [70].
After selecting a platform, the next step is developing the virtual classroom infrastructure, including themed breakout rooms and interactive environments [221]. Tools like Blender and SketchUp allow developers to design spaces ranging from realistic science labs to historical sites, promoting experiential learning [222]. AI-driven features personalize learning by adjusting content to individual student needs, providing real-time feedback and analytics [136]. Gamified elements, such as quizzes and achievement badges created with tools like Kahoot, encourage student engagement while helping educators track progress and adjust instruction based on performance [134]. The classroom should integrate interactive learning tools and assistive technologies to ensure inclusivity. VR/AR tools within platforms like Unity and Unreal Engine enable 3D simulations and holographic displays for hands-on experiences [53]. Assistive technologies like closed captioning, voice-to-text, and real-time translation tools from Microsoft Azure or Google Cloud make the virtual space accessible to students with disabilities or language barriers [7]. Additionally, providing offline access allows students with limited internet connectivity to download materials and engage with content asynchronously [131]. By prioritizing accessibility, personalization, and adaptability, the Metaverse classroom broadens educational access and enhances learning experiences. This holistic approach ensures all students benefit from an inclusive, comprehensive, and future-ready educational environment. Figure 2 provides an overview of the innovative framework for constructing an immersive Metaverse classroom environment.

4.1. Unique Technological Integration

4.1.1. Cross-Platform Accessibility

Cross-platform accessibility in a Metaverse classroom ensures equal participation for all students, regardless of the devices they use [137]. By making the classroom compatible with VR headsets, smartphones, tablets, and traditional computers, students from diverse backgrounds can access immersive learning experiences without requiring specialized hardware [223]. This device flexibility promotes inclusivity and flexibility by accommodating students with varying technological resources [97]. A key feature of cross-platform accessibility is seamless transitions between devices, allowing students to switch from one device to another without losing progress [56]. For example, a student could start a lesson on a desktop computer at home and continue on a tablet while commuting, with progress synced in real time [53]. Cloud-based data storage and session synchronization ensure a smooth learning experience, allowing students to participate in lessons from various locations and on different schedules [224]. Optimized performance across devices is essential to ensure smooth functionality on various platforms [225]. VR headsets require high frame rates and detailed 3D rendering, while smartphones need efficient resource management to handle processing and battery limitations [54]. To meet these varied needs, adaptive rendering technologies adjust graphics and interactive features based on the capabilities of the device [226].
Additionally, low-latency connections and data compression techniques help devices with limited bandwidth maintain access to core Metaverse features without significant lag or quality loss [58]. Bandwidth adaptability is crucial for students with unstable or low-speed internet, especially in remote areas [54]. The Metaverse classroom integrates features such as data compression, offline access to resources, and progressive content loading to reduce dependence on continuous high-speed connections [227]. For example, students can download essential materials, such as lesson videos or 3D models, ahead of time and complete activities offline [15]. This design ensures that students in areas with limited internet can still participate effectively in virtual learning [228]. A unified user interface (UI) across all platforms provides students with a consistent and intuitive experience, regardless of their device [1]. The interface adapts to different screen sizes and input methods, ensuring smooth navigation with a VR headset or a mobile phone [71]. Customizable controls and personalized onboarding help students quickly familiarize themselves with the virtual environment, reducing the cognitive load and making the learning process more intuitive [132]. By prioritizing accessibility and adaptability across platforms, the Metaverse classroom creates a flexible, inclusive, and equitable learning environment that meets the needs of all students, regardless of their technological or connectivity limitations [18].

4.1.2. AI and Machine Learning for Personalization

AI and machine learning (AI/ML) in the Metaverse classroom enable personalized learning by tailoring content and experiences to the needs, preferences, and learning styles of each student [3]. AI algorithms analyze student interactions, progress, and challenges in real-time to adjust lessons and resources accordingly [16]. For example, visual learners may be directed toward 3D models, while auditory learners receive audio explanations. This personalized approach allows students to grasp complex concepts more effectively and makes learning accessible to diverse learners on a scale [18]. A significant benefit of AI in the Metaverse classroom is a real-time adaptation of difficulty levels, which dynamically adjusts task complexity based on student performance [53]. For example, if a student excels in math problems, the system increases the difficulty to deepen their understanding. In contrast, AI can provide scaffolded support, such as hints or additional practice tasks, if a student struggles before advancing to more challenging material [6]. This adaptive approach keeps students engaged by presenting appropriately challenging tasks while minimizing frustration, ensuring that the learning paths align with each student’s pace and comprehension [7]. Custom assessments and progress tracking powered by AI provide teachers with insights into each student’s growth and learning needs [17]. AI can generate personalized quizzes focusing on specific concepts, allowing for more targeted interventions than traditional standardized tests [229]. Continuous tracking of student progress helps teachers and students monitor learning milestones and adjust strategies as needed. For instance, instead of a one-size-fits-all exam, students might receive quizzes tailored to their pace, ensuring more relevant assessments and better learning outcomes.
Automated feedback loops are another critical AI feature that provides immediate, personalized feedback to students [16]. After completing a task, students receive real-time insight on their performance and tips for improvement. For example, if a student answers a physics question incorrectly, AI can offer hints or explain the concept to help them understand their mistake [230]. This instant feedback reinforces learning while concepts are still fresh, promoting retention and deeper comprehension. Automated feedback also reduces the workload of teachers by handling routine grading and response tasks, allowing educators to focus on more complex instructional needs [51]. Predictive analytics, driven by ML, provides teachers with foresight into potential learning challenges, allowing proactive interventions [25]. By identifying patterns such as declining engagement or repeated mistakes, AI can alert teachers to students who need additional support [71]. For instance, if a student struggles with specific math concepts, the AI system can recommend targeted resources or notify the teacher to schedule extra help sessions [18]. This predictive approach ensures teachers have actionable insights to address issues early, supporting student success before problems escalate. Integrating AI and ML makes the Metaverse classroom a dynamic, adaptive environment that continuously evolves to meet students’ needs. These technologies enable a personalized learning experience that fosters engagement, promotes mastery, and equips teachers with the tools to provide timely, data-driven support [136].

4.1.3. Data Security and Privacy Protections

Data security and privacy are essential in the Metaverse classroom due to the personalized nature of AI-driven learning [16]. AI systems collect and analyze student data to customize learning pathways, making it critical to protect this information [201]. Advanced end-to-end encryption ensures that personal data, including performance analytics, remain secure during transmission and storage [224]. This encryption prevents unauthorized access, creating a secure environment in which students and parents can trust that sensitive information is protected against external threats [231]. Decentralized data storage further strengthens privacy by distributing information between multiple servers rather than storing it in one central location [197]. This approach reduces the risk of large-scale data breaches since there is no single point of failure [224]. For example, student progress or personal details are encrypted and fragmented across a network, ensuring that the entire dataset remains protected even if part of the system is compromised. Decentralized storage aligns with modern privacy expectations, giving users greater control over their data and improving the overall resilience of the system [232].
Authentication protocols such as biometric verification and multifactor authentication (MFA) enhance security by ensuring that only authorized users can access the virtual classroom [201]. Biometric verification, such as fingerprint or facial recognition, confirms user identity on compatible devices, while MFA requires a second verification step, like a code sent to a mobile device. These layered methods significantly reduce the risk of unauthorized access, ensuring that students, teachers, and parents have secure, private access to their personalized learning environments [196]. Anonymization and data minimization strategies help protect user privacy by reducing the amount of personal information collected [199]. Anonymization removes identifying details from the data sets, ensuring that learning insights cannot be traced back to individual students [196]. For instance, when AI analyzes performance trends, it uses anonymized data to improve learning algorithms without compromising student privacy. Data minimization ensures that only essential information is collected, reducing the risk of exposure or misuse [197]. These privacy-focused practices balance personalization with security, safeguarding students’ information while optimizing their learning experiences. Compliance with global privacy regulations, such as GDPR and FERPA, reinforces data protection standards in the Metaverse classroom [233]. GDPR outlines strict guidelines for managing personal data, emphasizing user consent and control, while FERPA focuses on protecting student education records. Adherence to these regulations involves clear data policies, obtaining informed consent, and allowing users to view, modify, or delete their data. Compliance builds trust with students, parents, and educators, demonstrating that the Metaverse classroom is committed to responsible data management and secure, personalized learning experiences.

4.2. Innovative Pedagogical Design

4.2.1. Scenario-Based Learning Environments

Scenario-based learning in the Metaverse classroom immerses students in realistic, interactive situations that foster practical skill development and active engagement. Unlike traditional teaching methods focused on memorization, this approach places students in dynamic settings where they must apply their knowledge to solve real-world problems. For example, in a science module, students could diagnose and treat virtual patients in a simulated lab, deepening their understanding through hands-on experimentation and observation [234]. These experiences go beyond textbook learning by encouraging students to adapt their approaches based on outcomes, promoting deeper comprehension [6]. Problem-solving and critical thinking are core skills cultivated in scenario-based learning environments [137]. Students face complex, multistep challenges requiring analytical thinking, creativity, and adaptability. For instance, a history module might place students in a historical negotiation, asking them to evaluate political and cultural contexts to reach a peace treaty [235]. These scenarios teach factual knowledge and critical decision-making skills, as students must predict consequences and make informed choices with limited information [7]. This interactive approach provides a safe space for students to learn from successes and mistakes, improving their problem-solving capabilities in ways that traditional assessments often do not.
Collaboration-focused scenarios enhance teamwork by encouraging students to work toward shared goals in a virtual environment. For example, in a simulated business project, students can take on roles such as CEO, marketing manager, or financial analyst, collaborating to launch a virtual product. This setup helps them practice communication, role-specific responsibilities, and collective decision-making. Along the way, students develop essential interpersonal skills like empathy, conflict resolution, and active listening, which are crucial in academic and professional settings [3]. These virtual teamwork exercises prepare students for real-world collaborative challenges by providing practical experience in group dynamics [25]. Multi-disciplinary simulations offer an innovative way to integrate knowledge from various subjects into a single scenario. For example, a sustainability project could require students to calculate resource allocations using math, apply biology concepts to understand environmental impacts, and use persuasive writing to advocate for policy changes [236]. This holistic approach reinforces subject knowledge while demonstrating how different fields interact to solve complex problems. By participating in interdisciplinary scenarios, students develop a broader skill set and gain valuable insights into real-world problem-solving, often requiring drawing from multiple areas of expertise [25]. One key advantage of scenario-based learning in the Metaverse is risk-free experimentation [183]. Students can test hypotheses, make decisions, and observe the consequences without facing real-world risks. For instance, in a financial literacy module, students could manage virtual investments and budgets, learning from mistakes without financial consequences [226]. This safe environment encourages exploration, resilience, and a growth mindset, as students see challenges as opportunities to learn and improve. By fostering confidence through trial and error, scenario-based learning prepares students to navigate complex situations with adaptability and self-assurance [44].

4.2.2. Gamified Learning Pathways

Gamified learning pathways in the Metaverse classroom offer an engaging, goal-oriented approach that motivates students by turning learning activities into interactive quests and challenges [237]. These quests are structured as a series of educational tasks or missions, each with specific objectives that align with curriculum goals, providing students with clear, tangible targets to work towards. Progress-based rewards further enhance engagement by offering visible markers of achievement, boosting students’ confidence, and reinforcing a growth mindset. These rewards enhance engagement and foster a sense of accomplishment, encouraging students to remain motivated and strive for continuous improvement. For example, a science quest could guide students through a sequence of experiments in a virtual lab, where they must apply concepts such as hypothesis testing and observation at each step [133]. In addition, AI-driven adaptive challenges within these gamified pathways ensure that each student’s learning experience is tailored to their individual needs and abilities [238]. The Metaverse classroom AI algorithms analyze student engagement, pace, and comprehension data, adjusting the difficulty and content of challenges accordingly [71]. For instance, if a student excels at math, the AI might introduce more complex problem-solving quests to deepen their understanding. In contrast, students who struggle with specific concepts receive additional support through scaffolded challenges and hints [127].
This personalized approach prevents students from feeling overwhelmed or bored, as tasks are always at an optimal level of challenge. Adapting to each student’s learning path, AI-driven challenges make gamified learning pathways more inclusive and effective, catering to diverse learning styles and ensuring that all students remain engaged [44]. Furthermore, collaborative quests and team-based challenges add a social dimension to gamified learning pathways, enhancing academic engagement and interpersonal skills [237]. Students might work together on quests that require diverse roles and skills, such as a group project in which they collaboratively solve a complex problem or build a virtual model [194]. For example, students could participate in a geography pathway quest to map out a virtual environment. Each team member would be responsible for researching and analyzing different regions. Moreover, in a history pathway, students might complete quests that require analyzing primary sources or recreating historical events, thereby honing analytical skills while covering the curriculum. This alignment with educational goals transforms gamified elements from entertainment into effective learning tools, making learning objectives clearer and easier to retain [127]. The Metaverse classroom turns learning into a structured, rewarding adventure by embedding curriculum targets into every aspect of gamified pathways. Motivation and educational achievement work hand in hand, offering a dynamic alternative to traditional educational methods.

4.2.3. Holistic Skill Assessment

Holistic skill assessment in the Metaverse classroom emphasizes evaluating a wider range of student abilities beyond traditional academics, including emotional intelligence, teamwork, leadership, resilience, and other critical life skills [3]. This approach moves beyond simple test scores, focusing on a student’s growth in soft skills essential for personal and professional success [20]. For example, a collaborative project in the Metaverse classroom can assess a student’s ability to communicate effectively, resolve conflicts, and work constructively within a team [13]. By recognizing these skills, the classroom promotes a more comprehensive view of student development. Through real-time analytics presented on an intuitive dashboard, educators can track student behavior, identify growth areas, and offer timely support [91]. For example, a student’s participation in a debate or a team-based quest can be analyzed to measure resilience and persistence. These data are presented to teachers through an intuitive dashboard, allowing them to spot trends, identify growth areas, and offer timely support [239]. After completing a task or project, students receive immediate feedback highlighting their academic performance and effectiveness in areas such as leadership or empathy [27]. For example, a feedback summary might point out how a student demonstrated resilience in a complex problem-solving quest, praising them for maintaining a positive attitude despite setbacks.
These feedback loops encourage students to reflect on their growth [226]. In addition, skill-specific assessments within the Metaverse classroom focus on traits such as leadership and teamwork, providing detailed insights into each student’s strengths and growth area [240]. For example, leadership assessments could be conducted during a group project in which students are given roles that require decision-making, planning, and motivation [27]. Similarly, teamwork assessments can analyze how students collaborate in a virtual lab, noting their contributions, willingness to support peers, and ability to share responsibilities [84]. By isolating and evaluating these skills in targeted activities, the Metaverse classroom provides teachers with precise data on the abilities of each student, allowing focused instruction in these areas [17]. Moreover, long-term skill development tracking is a key component, as it allows teachers, students, and parents to monitor growth over time in both academic and soft skills [13]. The Metaverse classroom records each student’s progress in various competencies, creating a comprehensive profile that illustrates their development throughout the academic year [1]. For instance, improvements in emotional intelligence, resilience, or collaboration can be documented and celebrated as part of the student’s learning achievements [137]. This longitudinal view helps teachers tailor their instruction to support long-term growth in each area, ensuring that students develop holistically. By tracking these skills over time, the Metaverse classroom equips students to recognize and build on their strengths, fostering lifelong learning habits and personal growth beyond academic success.

4.3. Enhanced Teacher Empowerment and Training

4.3.1. Dashboard Functionality and Analytics

Dashboard functionality and analytics in the Metaverse classroom provide teachers with a powerful toolkit to understand and respond to student needs in real time [212]. The Metaverse dashboard gives teachers an intuitive, centralized view of key performance metrics, levels of engagement, and learning trends, visually presenting data to show which students are actively participating and who might need additional support. For example, a teacher can quickly see if a student has completed a particular simulation or if they are lagging in an interactive module [226]. With this overview, teachers can efficiently manage their classes, giving attention where needed and maintaining an engaging and responsive learning environment. By analyzing patterns in student behavior, such as decreased participation or repeated difficulties with certain topics, predictive analytics allow teachers to address potential learning challenges before they become significant issues [7]. For example, if a student shows signs of disengagement in a series of assignments, the dashboard could flag this pattern, allowing the teacher to intervene with encouragement or alternative resources. These predictive insights help teachers stay ahead, addressing learning gaps as they arise rather than after they have impacted student performance [18]. This preventive approach leads to more effective intervention strategies and supports students in real time, ensuring they remain on track.
In addition, AI-driven intervention suggestions are an innovative feature of the Metaverse dashboard, offering personalized recommendations to help students improve [225]. AI-driven intervention suggestions are an innovative feature of the Metaverse dashboard, offering personalized recommendations based on student performance and participation data to help students improve. Similarly, if a class shows collective difficulties with a topic, the AI could suggest revisiting the lesson in a different format, such as a group simulation [13]. These recommendations empower teachers to make informed, data-backed decisions quickly, improving classroom adaptability and ensuring students receive the support they need to succeed. Moreover, the real-time adjustment capabilities enabled by the dashboard allow teachers to implement changes immediately based on the insights and suggestions provided [15]. Suppose data indicate that students are withdrawing from a particular activity. In that case, the teacher can modify the assignment, introduce a new interactive element, or adjust the pace directly through the dashboard [71]. This immediate responsiveness ensures that the Metaverse classroom remains engaging and relevant, providing students with a seamless and customized learning experience [58]. Teachers are thus empowered to act as facilitators, guiding the learning process and continually adjusting their strategies to meet real-time classroom dynamics. This flexibility fosters an environment of continuous improvement, making the Metaverse classroom highly effective for educators and students as it adapts to learning needs on the fly [130].

4.3.2. Professional Development Within the Metaverse

Professional development within the Metaverse offers a transformative, hands-on approach to teacher training, immersing educators in virtual workshops and simulated classrooms to build practical skills in an interactive, flexible environment [15]. Unlike traditional training methods that rely on passive lectures, Metaverse-based professional development emphasizes active participation, allowing teachers to practice classroom management strategies, instructional techniques, and student engagement approaches in risk-free virtual scenarios [17]. For instance, educators can engage with simulated student avatars displaying various behaviors, enabling them to refine their responses to diverse classroom dynamics [13]. This experiential learning builds teacher confidence and equips them to handle real-world challenges more effectively. Virtual workshops within the Metaverse serve as collaborative spaces where teachers connect with global peers and experts to share best practices and explore new pedagogical strategies. These workshops cover topics such as technology integration, inclusive education, and STEM-focused instruction [3]. Using VR/AR tools, participants experience real-time, interactive discussions that mimic in-person learning, fostering a sense of community and engagement. Teachers can join breakout groups, observe live teaching demonstrations, and participate in collaborative activities, making the professional development experience more immersive and impactful. This interactive format ensures that educators can immediately apply what they learn to their classrooms.
Simulated classroom scenarios provide valuable practice-based learning opportunities, allowing teachers to test and refine their skills in realistic yet controlled environments [13]. These simulations present various classroom situations, such as managing disruptive behavior, facilitating group work, or adapting lessons for students with special needs [7]. For example, a teacher might navigate a scenario where a virtual student struggles with a subject, practicing differentiated instruction techniques to address that student’s needs [3]. These controlled scenarios allow educators to experiment with new methods, reflect on their effectiveness, and receive feedback, helping them gain practical experience before applying those strategies in real-world settings. Ongoing professional growth is supported through adaptive learning sessions tailored to each teacher’s needs and interests [3]. These sessions offer targeted workshops and resources based on teacher feedback and progress data. For example, teachers interested in STEM education can access specialized modules on STEM integration strategies [11]. This personalized approach ensures that professional development remains relevant, helping educators continuously improve their skills.
Additionally, administrators can use data analytics provided by the Metaverse platform to track teacher participation and skill development, allowing for more tailored training opportunities [17]. Feedback and peer mentorship are key components of professional development in the Metaverse, fostering a collaborative learning culture that promotes growth through constructive support [13]. After completing workshops or simulations, teachers receive detailed feedback on their performance, including actionable suggestions for improvement [3]. The platform also facilitates peer mentorship, enabling experienced teachers to observe simulations, offer insights, and share expertise with newer educators. This mentorship process builds a supportive network, enhancing professional development by creating opportunities for teachers to learn from one another’s experiences. Integrating feedback and mentorship, the Metaverse professional development program cultivates stronger teaching practices and empowers educators to excel in their roles [135].

4.4. Community and Parental Engagement Tools

4.4.1. Advanced Parental Control Features

Advanced parental controls in the Metaverse classroom empower parents to monitor and support their child’s learning while maintaining a safe, productive virtual environment [7]. Unlike traditional platforms, the Metaverse’s interactive nature requires unique oversight tools that balance transparency with student autonomy. Activity summaries give parents insights into their child’s learning milestones, participation levels, and areas needing improvement without enabling intrusive surveillance [194]. These summaries promote a balanced home-school connection by informing parents without interfering with the child’s learning independence. For example, parents can see how frequently their child engages with virtual labs or whether they’re struggling with specific content, helping them provide timely support. Customized parental dashboards serve as a central hub for tracking progress, reviewing project participation, and managing accessibility settings tailored to the child’s needs [56]. These dashboards simplify monitoring by presenting key data points like time spent in learning modules, assignment completion rates, and collaboration in group activities [44]. For instance, a parent can quickly check whether their child is progressing steadily or spending too much time on introductory materials, signaling the need for additional support. This real-time access allows parents to stay engaged and offer guidance as needed, fostering a supportive learning experience.
Virtual parent-teacher meetings within the Metaverse streamline communication between parents and educators, promoting regular, interactive engagement [122]. Parents can schedule and attend meetings in virtual conference rooms, replicating the experience of in-person discussions [13]. For example, a parent could meet with a teacher in a virtual classroom to review their child’s performance in a recent project or simulation. This feature reduces logistical challenges and enhances communication, making it easier for parents to stay informed about their child’s progress. Age-appropriate content filters ensure that students only access materials suitable for their developmental stage [13]. Parents can restrict access to specific modules, features, or interactions based on maturity level. For example, younger students may be restricted from advanced simulations until they are ready, ensuring a safe and suitable learning experience [241]. These filters provide a customizable approach to managing content access, promoting an adaptable and safe virtual learning environment. Digital well-being tools integrated into parental controls help manage students’ screen time, encouraging a healthy balance between virtual learning and offline activities [132]. Parents can set time limits, schedule breaks, and receive alerts when usage exceeds recommended thresholds. For instance, parents might set a reminder for their child to take a break after 30 min of continuous screen time or limit evening access to reduce screen exposure before bedtime [208]. These tools help prevent screen fatigue and burnout, promoting a sustainable, healthy approach to digital learning while fostering responsible digital habits.

4.4.2. Virtual Community Hubs

Virtual community centers in the Metaverse classroom are a groundbreaking feature that extends the learning environment beyond traditional classroom boundaries, integrating local organizations, businesses, and mentors into students’ educational experiences. These centers create virtual spaces where students can engage with professionals from various fields, participate in community projects, and attend workshops led by experts [61]. For example, a local environmental organization could host a virtual seminar on sustainability, allowing students to interact directly with environmental scientists [6]. By connecting students with their broader communities in an accessible virtual format, these centers bring a new level of relevance and engagement to the educational experience. These centers create virtual spaces where students can engage with professionals from various fields, explore career paths, and participate in community projects [25]. Students can participate in internships, mentorship programs, or job-shadowing sessions hosted by local businesses, gaining first-hand experience in fields like engineering, healthcare, or digital marketing. For instance, a company could offer a virtual “day-in-the-life” simulation where students observe and interact with employees performing their daily tasks. This exposure helps students understand the demands of different professions, build valuable networking connections, and develop skills that will serve them in future careers [27].
By making these experiences part of the educational framework, the Metaverse classroom fosters career exploration and skills development, laying a strong foundation for students’ future professional lives. Global cultural awareness is another significant advantage offered by virtual community centers, as students can interact with organizations, mentors, and peers from all over the world [1]. Through partnerships with international nonprofits, cultural institutions, and educational organizations, students can attend global workshops, participate in cultural exchange programs, or collaborate on projects that address global issues. For example, students in the United States could work with peers in Africa on a virtual project on water conservation, learning about different challenges and solutions while developing a global perspective [242]. These experiences cultivate empathy, understanding, and cultural literacy, allowing students to appreciate diverse perspectives and become more open-minded global citizens. By integrating global engagement into the curriculum, virtual community centers provide students with a broader worldview that is essential in the interconnected world of today [243]. Enhanced community support through these centers also contributes to a more comprehensive support network for students, offering guidance and resources that may not be available within their immediate schools [132].
Moreover, community members and organizations, such as local mental health nonprofits or tutoring services, can offer workshops or counseling sessions in the Metaverse, supporting students’ academic, emotional, and social well-being. For example, a mental health organization could host weekly virtual sessions on stress management techniques, providing students with coping tools that improve their overall educational experience [178]. This expanded support network helps address various student needs holistically, creating a well-rounded learning environment where students feel academically, socially, and emotionally supported. The real-world project opportunities provided by community centers further enrich the Metaverse classroom, allowing students to apply their knowledge in practical ways [1]. These centers also offer students opportunities to address real-world challenges through community-based projects. These projects allow students to practice problem-solving, teamwork, and leadership skills in a meaningful context, preparing them to tackle similar issues in their personal and professional lives [27]. In addition, successful projects can be portfolio pieces that students can present to future employers or academic institutions, showcasing their abilities and experiences. Thus, virtual community hubs create an interactive and practical learning experience, equipping students with the confidence and competence to contribute positively to their communities and beyond [132].

4.5. Sustainable, Scalable Design

4.5.1. Efficient Resource Use and Environmental Awareness

Efficient use of resources in the Metaverse classroom design is crucial to creating a sustainable and accessible virtual learning environment [15]. By minimizing data loads and using scalable cloud-based resources, the platform ensures optimal energy consumption during peak times and minimizes waste during off-peak periods, aligning with sustainable technology practices [228]. Balancing immersive quality with efficiency is essential in a Metaverse classroom designed for long-term sustainability. Adaptive rendering techniques ensure that the immersive elements remain engaging and realistic without overburdening the system, enabling the platform to run smoothly on various devices and ensuring accessibility for students from diverse backgrounds [52]. Environmental awareness features within the Metaverse classroom provide educational opportunities by incorporating sustainability topics directly into the curriculum [15]. Virtual modules on topics such as renewable energy, conservation, and waste management are integrated into interactive scenarios, allowing students to explore and apply environmental concepts in a practical setting [244]. For example, a biology module might have students manage a virtual ecosystem, learning first-hand about biodiversity, resource allocation, and environmental impact [178]. Sharing and reuse of resources in virtual classrooms further enhance sustainability [13]. For instance, rather than creating entirely new environments for every lesson, existing 3D models and resources can be modified and reused, conserving digital resources [9]. Additionally, collaborative content libraries allow educators to access and share pre-existing assets and lesson templates, minimizing redundant development [245]. This approach reduces the environmental costs of generating new digital content and ensures that high-quality educational materials are available to all users. By maximizing the use of existing resources, the Metaverse classroom exemplifies efficient, sustainable design practices, fostering a scalable learning environment that remains impactful while minimizing waste [246].

4.5.2. Future-Ready Infrastructure

Future-ready infrastructure in the Metaverse classroom is built with scalability and adaptability in mind, ensuring that the virtual learning environment can grow and evolve alongside technological advancements. Modular design ensures that features like virtual labs and collaborative spaces can be upgraded or replaced without disrupting the system, keeping the Metaverse classroom responsive to emerging technologies and enhancing learning without requiring an infrastructure overhaul [25]. The cloud-based architecture supports real-time updates, ensuring the classroom remains aligned with evolving pedagogical and technological needs, maintaining a high-quality learning experience [135]. Integrating emerging technologies such as IoT devices and AI-driven educational tools makes the Metaverse classroom exceptionally versatile [191]. IoT compatibility, for example, allows physical classroom tools or smart devices to interact with the virtual environment, creating a blended learning experience [247]. A science class might link physical sensors to a virtual lab, allowing students to monitor real-time environmental data in Metaverse. Similarly, AI-driven tools provide personalized learning paths, assess student engagement, and offer predictive analytics that helps teachers adapt their instruction [136]. Adaptable infrastructure ensures compatibility with various devices, from basic computers to advanced VR headsets, while optimizing graphics and data requirements to support diverse hardware and internet capabilities [1]. This flexibility of the infrastructure’s hardware and network capabilities ensures that the Metaverse classroom can expand to serve a wider audience while maintaining a high-quality experience [54]. Sustainable scalability is embedded in the infrastructure, allowing the Metaverse classroom to accommodate growing users without compromising performance [16]. Cloud-based scalability means that as more students and teachers join the platform, resources can be dynamically allocated to meet demand [53]. By incorporating scalability and modular adaptability, the future-ready infrastructure ensures that the Metaverse classroom remains a sustainable, robust, and relevant learning environment capable of supporting students and educators well into the future.

5. Empirical Validation and Practical Application

The evaluation of the Meta-MILE classroom model utilized a rigorous paired pretest-posttest design to explore the immediate impact of a Metaverse-based learning experience on senior undergraduate students. Conducted with 28 participants from a computer design course at Binghamton University, the study examined changes in students’ familiarity, comfort, motivation, and perceptions regarding the relevance of immersive technologies to industry applications. This specific group was selected because they represent a key demographic poised to enter technology-driven industries, making them ideal candidates to assess the practical relevance of the Metaverse in preparing students for real-world applications. This approach provided valuable insight into the educational potential of the Metaverse. Participants completed pre- and post-surveys designed to measure changes in their familiarity with the Metaverse, comfort using immersive technologies, motivation, and perceived relevance of the Metaverse to industry-specific tasks. Each survey consisted of 30 structured questions, including Likert scale items (1 = strongly disagree to 5 = strongly agree) and multiple choice questions. These questions were explicitly aligned with the study’s research objectives. For example, students were asked, “How familiar are you with the concept of the Metaverse?” and “How relevant is the Metaverse to preparing you for industry-specific tasks?” The complete list of survey questions is available on request, ensuring transparency and allowing the readers to assess the alignment of the survey with the study objectives. The intervention involved a 20 min hands-on session in which students used university-provided VR headsets to interact with a simulated virtual design studio replicating real-world industry scenarios. This activity aimed to bridge theoretical learning with practical applications. The process was carefully structured: a pre-survey established baseline perceptions, followed by the Metaverse activity, and concluded with a post-survey administered immediately afterward to capture changes. To maintain consistency and ensure reliable comparisons, the timing of the surveys was kept uniform across participants. The implementation pathways, illustrated in Figure 3, provide a detailed roadmap to scale and replicate the Meta-MILE classroom model in other educational contexts.
The study tested the null hypothesis ( H 0 ), which posits no significant differences between the responses before and after the intervention in familiarity, comfort, motivation, or perceived relevance of Metaverse to industry-specific tasks helps to reinforce the credibility and validity of the findings. Descriptive and inferential statistical methods were employed to evaluate this hypothesis. Descriptive statistics, including medians, interquartile ranges, and frequencies, summarized trends in student responses. The Wilcoxon signed rank test, a nonparametric method appropriate for ordinal data, assessed statistically significant changes between pre- and post-survey responses (p < 0.05). To improve statistical reporting, effect sizes, such as rank-biserial correlation, were calculated to highlight the practical significance of the observed changes. Data visualizations, created using Microsoft Excel, SPSS Statistics 22, and Python, were further enhanced with Visio for clarity and precision. The intervention significantly improved students’ comfort, confidence, and perceptions of the Metaverse’s educational and industry relevance, with effect sizes ranging from small to large, indicating meaningful but varying practical impacts on their attitudes and expectations. These findings validated its alignment with the needs of the workforce.
The variability in effect sizes highlighted the intervention’s impact. Larger effects for hands-on familiarity and comfort were observed due to the immersive nature of the simulated virtual design studio, which aligned with experiential learning principles. In contrast, smaller effects for motivation and perceived industry relevance reflected the short intervention duration and initial technical challenges. These findings aligned with the study’s focus on short-term skill acquisition and suggested the need for longitudinal research to assess the broader and sustained impacts of the Metaverse classroom model. The study used safeguards such as anonymous surveys and voluntary participation to minimize biases, although the novelty effect remained a limitation. The results showed significant improvements in students’ comfort with immersive technologies and their recognition of Metaverse as a valuable tool to bridge academic learning with industry applications, particularly in virtual prototyping and collaborative design. The intervention boosted motivation, but challenges such as technical issues, limited access to VR hardware, and concerns about scalability were noted. Future research should explore longer-term impacts, use control groups, and apply advanced statistical analyzes to deepen the information. The Meta-MILE classroom model demonstrates the transformative potential to improve student participation, learning outcomes, and industry readiness by addressing logistical barriers and improving integration into education.

5.1. Familiarity and Comfort with the Metaverse

Before the intervention, the students exhibited a low familiarity with the Metaverse, with most reporting a neutral level of comfort with immersive technologies. However, hands-on exposure during the intervention significantly improved their comfort levels. Afterward, 35.7% of the students reported feeling extremely comfortable with the technology. This increase illustrated the importance of experiential learning in helping students become familiar with emerging technologies. Figure 4 on the comfort levels before and after the intervention captured this progression, showing the dramatic increase in the comfort scores after the intervention. Figure 4 illustrates a significant change in student comfort levels with immersive technologies after the intervention. Before joining Metaverse, most students reported moderate levels of comfort, predominantly in the range of 3 and 4 on a 5-point scale, with minimal representation at level 5. After the intervention, a substantial increase in comfort levels was observed, with the majority of students reporting levels 4 and 5. This improvement highlights the efficacy of experiential learning in reducing fear and fostering familiarity with innovative technologies. The intervention significantly changed the comfort of the students with the metaverse (Z = 2.10 , p < 0.05 ). The effect sizes ranged from small (r = 0.20 for negative ranks) to large (r = 0.60 for positive ranks), indicating that the intervention substantially improved the familiarity and comfort of students with the Metaverse as an educational tool.

5.2. Motivation to Learn

Before the intervention, the students showed curiosity about virtual environments but hesitated about their practical application in education. The intervention, which provided hands-on interaction with a simulated industry environment, significantly increased their motivation. More than half of the participants reported feeling “somewhat motivated” or “extremely motivated” to learn using Metaverse. Figure 5 on the distribution of motivation levels highlighted this positive shift, demonstrating how immersive experiences fostered enthusiasm for virtual learning. Figure 5 highlights a marked improvement in students’ motivation levels after engaging with the Metaverse classroom. Initially, motivation levels were concentrated around moderate values, with levels 3 and 4 representing the majority. Following the intervention, there was a notable increase in the proportion of students reporting higher motivation levels, with significant growth at level 4 and a smaller but impactful increase at level 5. These results underscore the role of interactive and immersive environments in fostering student engagement and enthusiasm for learning. The intervention significantly changed students’ motivation to learn using the Metaverse (Z = −1.48, p < 0.05). The effect sizes were small (r = −0.18 for negative ranks and r = −0.26 for positive ranks), indicating that while the changes were statistically significant, the practical influence of the intervention on enhancing students’ motivation was modest.

5.3. Industry Relevance

Students recognized the potential of Metaverse to bridge academic learning with industry needs after the intervention. The experience demonstrated its utility in areas such as virtual prototyping and collaborative problem-solving, which were critical in the field of computer design. Figure 6 on perceived relevance to industry showcased the significant increase in student recognition of the Metaverse as a tool for industry readiness. Figure 6 demonstrates the evolving perceptions of students about the relevance of Metaverse to industry-specific applications. Initially, students expressed mixed views on the practical utility of the Metaverse. However, post-intervention data revealed a substantial increase in students who recognized its relevance, particularly in fields requiring virtual prototyping, design collaboration, and simulation-based training. These findings confirm the role of the Metaverse as a bridge between academic learning and real-world applications. The intervention significantly changed students’ perceptions of the Metaverse’s relevance to industry applications (Z = 2.12 , p < 0.05 ). The effect sizes were small to moderate (r = 0.03 for negative ranks and r = 0.43 for positive ranks), indicating that while the changes were statistically significant, their practical impact on shaping students’ perceptions was modest. These findings highlight the intervention’s role in enhancing students’ understanding of the Metaverse’s industry relevance.

5.4. Distribution of Challenges in Metaverse Implementation

The intervention revealed several challenges despite its benefits. Students frequently reported technical issues, including device compatibility and connectivity. Accessibility also emerged as a key barrier, as limited access to VR hardware hindered broader adoption. Additionally, while students appreciated the short-term benefits of the Metaverse, skepticism about its long-term scalability in education remained. Figure 7 on the distribution of challenges faced categorized these obstacles, highlighting areas that needed improvement, such as infrastructure, teacher training, and technical support. Figure 7 categorizes the challenges reported by the students during their engagement with the Metaverse classroom. Key issues included technical difficulties such as device compatibility and connectivity, as well as accessibility barriers, which limited participation for some students. Although most managed to adapt to the environment, initial discomfort and a learning curve with immersive platforms were also highlighted. These findings emphasize the critical need for targeted strategies to address technical and infrastructural barriers. The effect sizes were small to medium (r = 0.32 for negative ranks and r = 0.25 for positive ranks), indicating that the intervention had a meaningful, practical influence on shaping students’ challenges of the Metaverse as a transformative educational tool.

5.5. Educational Impact

The intervention significantly improved learning outcomes. Students demonstrated improved knowledge retention, particularly in their understanding of complex concepts. The levels of participation were also notable, and many participants actively participated in the Metaverse environment and reported that the immersive experience improved their academic achievements. Figure 8 on perceived educational impact depicted this positive change, reinforcing the value of Metaverse as a transformative educational tool. Figure 8 reveals students’ perceptions of the impact of Metaverse on their learning outcomes, with significant improvements observed in engagement, retention, and comprehension of complex concepts. The immersive nature of the Metaverse allowed students to simulate real-world scenarios, fostering a deeper understanding of theoretical knowledge. These results validate the transformative potential of virtual environments in enriching traditional educational models. The intervention significantly changed students’ expectations of the Metaverse’s educational impact (Z = 1.48 , p < 0.05). The effect sizes were small (r = 0.18 for negative ranks and r = 0.26 for positive ranks), indicating that while the changes were statistically significant, the practical influence of the intervention on shaping students’ expectations was modest.

5.6. Future Likelihood of Adoption

Figure 9 on the future likelihood of adoption reflects the students’ perspectives regarding the continued use of immersive technologies, such as the Metaverse, in their academic and professional pursuits. Preintervention responses demonstrated a notable level of uncertainty, with many students expressing neutrality or moderate likelihood (“neither likely nor unlikely”). However, post-intervention data showed a significant change, with a higher proportion of students indicating that they were “somewhat likely” or “extremely likely” to integrate such technologies into their future practices. This change reflects a growing confidence in the potential of the Metaverse to provide meaningful applications in professional and educational contexts. Although positive responses increased, a subset of students remained hesitant, reflecting concerns about the scalability and real-world practicality of the Metaverse in long-term use. This hesitation underscores the importance of addressing perceived and actual barriers to adoption, such as technical limitations, lack of industry standardization, or lack of familiarity. Institutions aiming to promote broader adoption of immersive technologies could benefit from more targeted exposure to use cases where such platforms are actively deployed in the industry. By aligning Metaverse applications with evolving professional demands and fostering technological adaptability through continuous practice, the likelihood of adoption can be further enhanced. The intervention led to significant changes in students’ likelihood of future use and recommendation of the Metaverse (Z = −1.23, p < 0.05). The effect sizes were small (r = −0.07 for negative ranks and r = −0.30 for positive ranks), suggesting that while the statistical changes were significant, the practical influence of the intervention on students’ attitudes toward adopting and recommending the Metaverse was modest.

5.7. Advantages of Using the Metaverse

Figure 10 demonstrates the significant educational benefits of integrating Metaverse technologies, with marked improvements in five key metrics: virtual group projects, knowledge retention, practical skills, inclusivity, and student engagement. The virtual group projects improved from 60% to 85%, showcasing the ability of Metaverse to foster interactive collaboration. Knowledge retention increased from 50% to 80%, reflecting how immersive, sensory-rich environments enhance memory. Similarly, practical skills increased from 45% to 75%, highlighting the value of simulated hands-on practice in a safe virtual environment. Inclusivity increased from 65% to 85% as the Metaverse provided equitable learning opportunities through adaptable tools and environments. Lastly, student engagement increased from 70% to 90%, driven by the dynamic and gamified approach of the Metaverse to education. These results underscore the Metaverse’s transformative potential to address traditional educational challenges by enhancing engagement, collaboration, and inclusivity while bridging the gap between theoretical knowledge and practical application. The intervention significantly changed students’ perceptions of the advantages of using the Metaverse in education (Z = −2.45, p < 0.05). The effect sizes ranged from moderate (r = −0.35 for negative ranks) to large (r = −0.65 for positive ranks), indicating that the intervention substantially improved students’ recognition of the Metaverse’s ability to enhance collaboration, knowledge retention, practical skills, inclusivity, and student engagement in educational settings.

5.8. Challenges in Metaverse Adoption for Education

Figure 11 highlights the significant challenges in the adoption of Metaverse technologies in education. Each of these barriers underscores the complexities associated with implementing advanced virtual platforms in an educational setting. The intervention highlighted significant challenges in adopting the Metaverse for education, with teacher training as the largest barrier (Z = −2.30, p < 0.05). The effect sizes ranged from moderate (r = −0.40 for negative ranks) to large (r = −0.70 for positive ranks), indicating that the lack of professional development substantially hinders the effective use of Metaverse tools. Technical issues also emerged as a significant challenge (Z = −2.15, p < 0.05), with effect sizes ranging from small (r = −0.25) to moderate (r = −0.50), reflecting the impact of unreliable infrastructure and insufficient technical support on the seamless operation of Metaverse platforms.
The largest challenge, teacher training, reflects the critical need for educators to acquire the necessary skills to use Metaverse tools effectively. Many teachers may lack experience with virtual environments, immersive learning strategies, or the technical expertise required to manage these platforms. Without sufficient professional development, educators can struggle to integrate the Metaverse into their teaching methods, limiting its potential to enhance learning outcomes. Technical issues are another significant barrier that encompasses problems such as network reliability, system errors, and a lack of consistent technical support. These issues can disrupt lessons and hinder the seamless operation of Metaverse platforms, creating frustration for both teachers and students. Reliable infrastructure and ongoing technical assistance are essential to mitigate these disruptions. The high initial setup costs are another obstacle to widespread adoption. Schools must invest in VR/AR equipment, software licenses, and upgraded hardware to create a Metaverse-ready environment. For many institutions, especially those operating on limited budgets, these upfront costs can be prohibitive, delaying or entirely preventing the implementation of Metaverse technologies.
Device compatibility poses challenges related to ensuring that students and educators have access to devices capable of running Metaverse applications. Inconsistencies in hardware specifications or limited access to advanced devices can create inequities among students, particularly in under-resourced schools. Ensuring compatibility across diverse devices adds complexity to the adoption process. Software integration, while the smallest challenge, still highlights the difficulty in aligning Metaverse platforms with existing educational tools. Schools often rely on multiple software systems, and integrating these with Metaverse technologies can be time-consuming and technically challenging. Without seamless integration, educators may face inefficiencies that undermine the benefits of the Metaverse. These challenges exist because of the complex nature of the Metaverse and the substantial change it represents from traditional educational tools. Resource inequity, infrastructure limitations, and human adaptation to new technologies are key factors that contribute to these barriers. Overcoming these challenges will require strategic investments, robust training programs, and collaborative efforts between educators, technology providers, and policymakers. With proper planning and support, the transformative potential of the Metaverse in education can be realized.

6. Discussion

6.1. Limitations of the Metaverse Classroom Model

While the Metaverse classroom model presents a groundbreaking approach to virtual learning, it is not without limitations [92]. One primary challenge lies in the accessibility and resource requirements needed to implement the model effectively [54]. The infrastructure demands for running immersive simulations and 3D environments can be significant, often requiring high-performance hardware and stable high-speed internet connections [225]. This creates potential barriers for underresourced schools and communities, which may not have access to such technology [155]. Moreover, even when hardware is accessible, the varying levels of digital literacy among students and educators can impede effective use. The need for intensive teacher training to manage and optimize virtual classrooms poses another challenge, as it requires time, financial investment, and dedicated resources [16]. Another limitation is the psychological and physical impact of prolonged immersion in virtual environments, especially in young students [34]. Concerns about screen time, eye strain, and the effects of VR on cognitive and emotional development warrant careful consideration [161]. Although highly engaging, the immersive and gamified nature of the Metaverse classroom can lead to an overreliance on virtual interactions, potentially affecting students’ abilities to function in non-digital social environments [248]. Furthermore, privacy and data security are critical issues; with student data collection to personalize experiences, robust measures must be taken to protect sensitive information [213]. The risk of data breaches, unauthorized access, and ethical considerations surrounding data usage represent significant limitations that require ongoing monitoring and stringent security protocols.

6.2. Implications for Educational Institutions and Policy

Adopting the Metaverse classroom model could have substantial implications for educational institutions, provoking changes in infrastructure investment, teaching practices, and curriculum design. Institutions adopting this model would need to allocate resources to acquire compatible technology, build secure networks, and provide professional development to educators [1]. Furthermore, integrating the Metaverse classroom requires changes in teaching methods, moving from traditional instructional models to those that embrace experiential learning, gamification, and adaptive feedback [17]. This shift could promote a student-centered approach in which learners actively engage with content rather than passively receiving information. Institutions would also need to consider the establishment of tech support teams and policies that address the unique challenges of virtual education environments. From a policy perspective, educational policymakers must consider how to regulate and support the implementation of immersive technologies within curricula [15]. Policies that promote equitable access to technology, particularly in low-income and rural areas, would be critical to ensuring that the Metaverse classroom does not exacerbate existing educational inequities [249]. Policymakers could partner with technology providers to subsidize hardware and internet connectivity for underprivileged schools [91]. Furthermore, data protection regulations specific to virtual education, ensuring compliance with standards such as FERPA or GDPR, would be essential to safeguarding student information. Guidelines about screen time, psychological impacts, and ethical use of data in educational VR/AR environments would also need to be developed to maintain a safe and supportive learning environment.
In addition to logistical considerations, implementing the Metaverse classroom model can impact larger educational goals, potentially influencing future curriculum standards [17]. If widely adopted, immersive classrooms could shift curriculum design to focus more on competency-based learning, integrating critical thinking, problem-solving, and digital literacy as core skills. Policymakers may need to support educational frameworks that encourage the use of virtual simulations, experiential learning, and real-time feedback, aligning assessment strategies with these more interactive and skill-based approaches. This model could encourage innovation in educational evaluation, moving beyond traditional exams to more dynamic scenario-based evaluations that reflect students’ real-world capabilities. Furthermore, the shift to a virtual learning environment has implications for teacher roles and responsibilities. Teachers would likely assume roles as facilitators and guides rather than traditional instructors, helping students navigate immersive environments and tailoring learning pathways. This pedagogical shift would necessitate changes in teacher preparation programs, which could incorporate VR/AR technology training and virtual classroom management skills into the curriculum. Institutions and policymakers would need to support this transition by creating ongoing training programs and setting standards for teacher qualifications in digital classrooms [1]. Such a paradigm shift would require reevaluating professional standards and incentivizing continual upskilling to meet the demands of a technologically advanced educational landscape.
Overall, the Meta-MILE classroom model offers a glimpse into the future of education, characterized by immersive, personalized, and skill-oriented learning experiences. However, to fully realize its potential, educational institutions and policymakers must address the limitations of the model and support infrastructure, equity, and regulatory needs [15]. As virtual learning continues to evolve, the Metaverse classroom model can redefine educational practices, creating opportunities for students to develop 21st-century skills within a robust, adaptable framework [17]. Through strategic planning and policy innovation, the Metaverse classroom could become a transformative tool in the global effort to make education more engaging, inclusive, and future-ready.

7. Future Research Directions

7.1. Suggested Areas for Further Investigation

As the Metaverse classroom model is still in its development stages, there is a substantial need for further research to validate its long-term impact and optimize its design. One of the most critical areas for future study is conducting longitudinal research on learning outcomes [84]. Investigating the effects of sustained use of the Metaverse classroom on student engagement, knowledge retention, skill development, and overall academic achievement over time would provide essential insights into the model’s effectiveness [91]. Long-term studies could also examine the influence of immersive learning environments on cognitive development, including critical thinking, problem-solving abilities, and memory [3]. Such research would help educators understand whether immersive virtual learning produces measurable improvements compared to traditional or hybrid educational models. Another key area for exploration is the psychological and social impact of immersive classrooms, particularly in terms of student mental well-being, adaptability, and interpersonal skills. Studies could investigate the effects of prolonged VR/AR exposure on students’ social-emotional development and assess whether avatar-based interactions in the Metaverse positively or negatively influence students’ real-world social skills. Furthermore, given that the Metaverse classroom is highly dependent on digital engagement, the research could explore how varying screen time levels in immersive environments impact attention spans, mental health, and stress levels [178]. Understanding these social and psychological dimensions would be critical to refining the design of the Metaverse classroom to support the holistic development of students.

7.2. Technological and Pedagogical Advancements in Virtual Learning

Future research should also address advancements in the technological and pedagogical aspects of the Metaverse classroom to push the boundaries of what is possible in virtual learning. Technological investigations could focus on developing more lightweight, affordable, and accessible VR/AR hardware to accommodate a wider range of users, including those in under-resourced settings [191]. Innovations in haptic feedback, adaptive AI algorithms, and real-time motion tracking would enhance the realism and interactivity of virtual classrooms, allowing for more sophisticated simulations and student engagement [6]. Another technological focus should be on data privacy advancements, particularly those exploring decentralized data storage solutions, blockchain-based identity verification, and advanced encryption tailored to immersive environments, thus addressing concerns around data security and student privacy. On the pedagogical front, further research could explore new instructional methods specifically tailored to immersive learning, such as adaptive scenarios, collaborative projects across geographic boundaries, and role-playing exercises that promote experiential learning. Integrating AI-driven customization tools, which respond to student behavior in real time, represents a promising direction, enabling customized instruction based on student progress and comprehension [136]. Furthermore, research on gamified learning pathways and scenario-based evaluations within the Metaverse classroom would inform more effective student motivation and assessment approaches [127]. Exploring the alignment of immersive learning practices with established educational frameworks, such as Bloom’s taxonomy or constructivist theory, would also deepen our understanding of how best to structure the Metaverse classroom for optimal student growth.

8. Conclusions

8.1. Summary of Contributions

This paper envisions a comprehensive layered Meta-MILE model for a Metaverse classroom that integrates cutting-edge immersive technology, adaptive pedagogy, and robust security to address the evolving needs of modern education. Building on a foundation that includes infrastructure, content interaction, personalization, collaboration, and assessment, this model brings together the elements necessary for a fully functional and effective virtual learning environment. Key contributions include innovative approaches to gamified learning pathways, AI-driven personalization, scenario-based evaluations, and community engagement tools designed to enhance student engagement, inclusivity, and practical skill building. Furthermore, the proposed model provides teachers with advanced dashboards, analytics for real-time insights, and professional development opportunities to support immersive classroom management. Collectively, these contributions position the Metaverse classroom as a promising solution for creating equitable and dynamic educational experiences that align with the demands of 21st-century learning.

8.2. Vision for the Future of Metaverse in Education

Looking forward, the potential of Metaverse in education extends far beyond a virtual classroom model; it represents a shift toward a more interactive, experiential, and personalized approach to learning. As technological advancements continue, Metaverse environments could transform into global collaboration hubs, connecting students, educators, and professionals around the world. Future iterations of this model could seamlessly integrate AI, IoT, and advanced VR/AR tools, creating multidimensional spaces where students can explore interdisciplinary content, engage in real-world simulations, and build critical soft skills alongside academic knowledge. With appropriate policy support and ongoing technological innovation, the Metaverse classroom could evolve into a universal platform that democratizes access to quality education and prepares students for a rapidly changing world. More investment in research, infrastructure, and equitable access is essential to realize this vision. Partnerships between educational institutions, governments, and technology providers will be pivotal in making the Metaverse accessible across socio-economic boundaries. The Metaverse classroom offers a foundation for building future educational frameworks, incorporating new pedagogical models, accessibility standards, and immersive technologies. As we continue to explore and expand the possibilities of virtual learning, the Metaverse classroom can redefine educational experiences, equipping learners with the skills, knowledge, and adaptability necessary to thrive in a digital-first global society.

Author Contributions

Conceptualization, L.N.Y., N.S.F., Y.C. and A.S.; methodology, L.N.Y., N.S.F., Y.C. and A.S.; software, L.N.Y. and M.H.; validation, L.N.Y., Y.C. and M.H.; formal analysis, L.N.Y., N.S.F. and M.H.; investigation, L.N.Y.; resources, L.N.Y., Y.C. and A.S.; data curation, L.N.Y. and M.H.; writing—original draft preparation, L.N.Y., Y.C. and M.H.; writing—review and editing, L.N.Y. and Y.C.; visualization, L.N.Y. and M.H.; supervision, N.S.F., Y.C. and A.S.; project administration, L.N.Y., N.S.F., Y.C., A.S. and M.H.; funding acquisition, N.S.F. and A.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The data supporting the findings of this study are available upon reasonable request from the corresponding author and comply with Binghamton University guidelines.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
3DThree-dimensional
ADHDAttention-deficit/hyperactivity disorder
AIArtificial intelligence
ARAugmented reality
CEOChief executive officer
CMSContent management system
FERPAFamily Educational Rights and Privacy Act
GDPRGeneral Data Protection Regulation
IoTInternet of Things
Meta-MILEMetaverse-driven Multi-layered Immersive Learning Environment
MFAMulti-factor authentication
MoSCoWMust-have, should-have, could-have
SSOSingle sign-on
STEMScience, technology, engineering, and mathematics
VRVirtual reality

References

  1. Wang, M.; Yu, H.; Bell, Z.; Chu, X. Constructing an edu-metaverse ecosystem: A new and innovative framework. IEEE Trans. Learn. Technol. 2022, 15, 685–696. [Google Scholar] [CrossRef]
  2. Singh, M. Exploring the possibilities to implement metaverse in higher education institutions of India. Edu. Inf. Technol. 2024, 29, 20715–20728. [Google Scholar] [CrossRef]
  3. Damaševičius, R.; Sidekerskienė, T. Virtual worlds for learning in metaverse: A narrative review. Sustainability 2024, 16, 2032. [Google Scholar] [CrossRef]
  4. Mystakidis, S. Metaverse. Encyclopedia 2022, 2, 486–497. [Google Scholar] [CrossRef]
  5. Papaioannou, G.; Volakaki, M.G.; Kokolakis, S.; Vouyioukas, D. Learning spaces in higher education: A state-of-the-art review. Trends High. Educ. 2023, 2, 526–545. [Google Scholar] [CrossRef]
  6. AlGerafi, M.A.; Zhou, Y.; Oubibi, M.; Wijaya, T.T. Unlocking the potential: A comprehensive evaluation of augmented reality and virtual reality in education. Electronics 2023, 12, 3953. [Google Scholar] [CrossRef]
  7. Yenduri, G.; Kaluri, R.; Rajput, D.S.; Lakshmanna, K.; Gadekallu, T.R.; Mahmud, M.; Brown, D.J. From assistive technologies to metaverse—Technologies in inclusive higher education for students with specific learning difficulties: A review. IEEE Access 2023, 11, 64907–64927. [Google Scholar] [CrossRef]
  8. Garlinska, M.; Osial, M.; Proniewska, K.; Pregowska, A. The influence of emerging technologies on distance education. Electronics 2023, 12, 1550. [Google Scholar] [CrossRef]
  9. Lo, S.C.; Tsai, H.H. Design of 3D virtual reality in the metaverse for environmental conservation education based on cognitive theory. Sensors 2022, 22, 8329. [Google Scholar] [CrossRef] [PubMed]
  10. Joshi, S.; Pramod, P. A collaborative metaverse based a-la-carte framework for tertiary education (CO-MATE). Heliyon 2023, 9, e13424. [Google Scholar] [CrossRef]
  11. Solanes, J.E.; Montava-Jordà, S.; Golf-Laville, E.; Colomer-Romero, V.; Gracia, L.; Muñoz, A. Enhancing STEM Education through Interactive Metaverses: A Case Study and Methodological Framework. Appl. Sci. 2023, 13, 10785. [Google Scholar] [CrossRef]
  12. Di Natale, A.F.; Bartolotta, S.; Gaggioli, A.; Riva, G.; Villani, D. Exploring students’ acceptance and continuance intention in using immersive virtual reality and metaverse integrated learning environments: The case of an Italian university course. Edu. Inf. Technol. 2024, 29, 14749–14768. [Google Scholar] [CrossRef]
  13. Chen, X.; Zou, D.; Xie, H.; Wang, F.L. Metaverse in education: Contributors, cooperations, and research themes. IEEE Trans. Learn. Technol. 2023, 16, 1111–1129. [Google Scholar] [CrossRef]
  14. Beck, D.; Morgado, L.; O’Shea, P. Educational practices and strategies with immersive learning environments: Mapping of reviews for using the metaverse. IEEE Trans. Learn. Technol. 2023, 17, 319–341. [Google Scholar] [CrossRef]
  15. Lee, H.; Hwang, Y. Technology-enhanced education through VR-making and metaverse-linking to foster teacher readiness and sustainable learning. Sustainability 2022, 14, 4786. [Google Scholar] [CrossRef]
  16. Jagatheesaperumal, S.K.; Ahmad, K.; Al-Fuqaha, A.; Qadir, J. Advancing education through extended reality and internet of everything enabled metaverses: Applications, challenges, and open issues. IEEE Trans. Learn. Technol. 2024, 17, 1120–1139. [Google Scholar] [CrossRef]
  17. Onu, P.; Pradhan, A.; Mbohwa, C. Potential to use metaverse for future teaching and learning. Educ. Inf. Technol. 2024, 29, 8893–8924. [Google Scholar] [CrossRef]
  18. Villegas-Ch, W.; García-Ortiz, J.; Sánchez-Viteri, S. Educational Advances in the Metaverse: Boosting Learning through Virtual and Augmented Reality and Artificial Intelligence. IEEE Access 2024, 12, 59093–59112. [Google Scholar] [CrossRef]
  19. Lazou, C.; Tsinakos, A. Critical immersive-triggered literacy as a key component for inclusive digital education. Educ. Sci. 2023, 13, 696. [Google Scholar] [CrossRef]
  20. Tsappi, E.; Deliyannis, I.; Papageorgiou, G.N. Developing a Performance Evaluation Framework Structural Model for Educational Metaverse. Technologies 2024, 12, 53. [Google Scholar] [CrossRef]
  21. Li, W.; Liu, X.; Zhang, Q.; Zhou, B.; Wang, B. VR-enhanced cognitive learning: Method, framework, and application. Appl. Sci. 2023, 13, 4756. [Google Scholar] [CrossRef]
  22. Devi, K.S. Constructivist approach to learning based on the concepts of Jean Piaget and Lev Vygotsky An analytical Overview. J. Indian Educ. 2019, 44, 5–19. [Google Scholar]
  23. Hawes, D.; Arya, A. Technology solutions to reduce anxiety and increase cognitive availability in students. IEEE Trans. Learn. Technol. 2023, 16, 278–291. [Google Scholar] [CrossRef]
  24. Kim, T.; Planey, J.; Lindgren, R. Theory-driven design in metaverse virtual reality learning environments: Two exemplary cases. IEEE Trans. Learn. Technol. 2023, 16, 1141–1153. [Google Scholar] [CrossRef]
  25. AbuKhousa, E.; El-Tahawy, M.S.; Atif, Y. Envisioning architecture of metaverse intensive learning experience (MiLEx): Career readiness in the 21st century and collective intelligence development scenario. Future Internet 2023, 15, 53. [Google Scholar] [CrossRef]
  26. Abd El-Sattar, H.K.H. Future metaverse-based education to promote daily living activities in learners with autism using immersive technologies. Educ. Inf. Technol. 2024, 1–38. [Google Scholar] [CrossRef]
  27. Mahindru, R.; Kumar, A.; Bapat, G.; Rroy, A.D.; Kavita; Sharma, N. Metaverse Unleashed: Augmenting Creativity and Innovation in Business Education. Eng. Proc. 2024, 59, 207. [Google Scholar] [CrossRef]
  28. Kee, T.; Zhang, H.; King, R.B. An empirical study on immersive technology in synchronous hybrid learning in design education. Int. J. Technol. Des. Educ. 2024, 34, 1243–1273. [Google Scholar] [CrossRef]
  29. Lebert, A.; Vilarroya, Ó. The links between experiential learning and 4E cognition. Ann. N. Y. Acad. Sci. 2024, 1541, 37–52. [Google Scholar] [CrossRef]
  30. Alkhwaldi, A.F. Investigating the social sustainability of immersive virtual technologies in higher educational institutions: Students’ perceptions toward metaverse technology. Sustainability 2024, 16, 934. [Google Scholar] [CrossRef]
  31. Kee, T.; Zhang, H. Digital experiential learning for sustainable horticulture and landscape management education. Sustainability 2022, 14, 9116. [Google Scholar] [CrossRef]
  32. Zhang, H.L.; Xue, Y.; Lu, Y.; Lee, S. A fusion model: Towards a virtual, physical and cognitive integration and its principles. IEEE Consum. Electron. Mag. 2023, 13, 107–114. [Google Scholar] [CrossRef]
  33. Skulmowski, A.; Xu, K.M. Understanding cognitive load in digital and online learning: A new perspective on extraneous cognitive load. Educ. Psychol. Rev. 2022, 34, 171–196. [Google Scholar] [CrossRef]
  34. Sokołowska, B. Being in Virtual Reality and Its Influence on Brain Health—An Overview of Benefits, Limitations and Prospects. Brain Sci. 2024, 14, 72. [Google Scholar] [CrossRef] [PubMed]
  35. Sato, S.N.; Condes Moreno, E.; Rubio-Zarapuz, A.; Dalamitros, A.A.; Yañez-Sepulveda, R.; Tornero-Aguilera, J.F.; Clemente-Suárez, V.J. Navigating the new normal: Adapting online and distance learning in the post-pandemic era. Educ. Sci. 2023, 14, 19. [Google Scholar] [CrossRef]
  36. Alawneh, Y.J.J.; Sleema, H.; Salman, F.N.; Alshammat, M.F.; Oteer, R.S.; ALrashidi, N.K.N. Adaptive Learning Systems: Revolutionizing Higher Education through AI-Driven Curricula. In Proceedings of the 2024 International Conference on Knowledge Engineering and Communication Systems (ICKECS), Chikkaballapur, India, 18–19 April 2024; Volume 1, pp. 1–5. [Google Scholar]
  37. Sajja, R.; Sermet, Y.; Cikmaz, M.; Cwiertny, D.; Demir, I. Artificial intelligence-enabled intelligent assistant for personalized and adaptive learning in higher education. Information 2024, 15, 596. [Google Scholar] [CrossRef]
  38. Villalba, K.; Jimeno, M.; Robles, H.; Vergara, L.; Sinning, C.; Lizcano, L.; Hurtado, B.; Nieto, W. Eyeland: A visually-impaired accessible English learning application using a Design Based Research framework. IEEE Access 2024, 12, 142275–142290. [Google Scholar] [CrossRef]
  39. Pasupuleti, V.; Thuraka, B.; Kodete, C.S.; Malisetty, S. Enhancing supply chain agility and sustainability through machine learning: Optimization techniques for logistics and inventory management. Logistics 2024, 8, 73. [Google Scholar] [CrossRef]
  40. Walker, R.; Morey, V.; Dinham, J.; Dobson, M.; Sims, C.; Bi, M.; Lamont, W. Welcome, How Can I Help You? Design Considerations for a Virtual Reality Environment to Support the Orientation of Online Initial Teacher Education Students. Educ. Sci. 2023, 13, 485. [Google Scholar] [CrossRef]
  41. Wiedermann, C.J.; Barbieri, V.; Plagg, B.; Marino, P.; Piccoliori, G.; Engl, A. Fortifying the foundations: A comprehensive approach to enhancing mental health support in educational policies amidst crises. Healthcare 2023, 11, 1423. [Google Scholar] [CrossRef] [PubMed]
  42. Álvarez, I.M.; Manero, B.; Romero-Hernández, A.; Cárdenas, M.; Masó, I. Virtual reality platform for teacher training on classroom climate management: Evaluating user acceptance. Virtual Real. 2024, 28, 78. [Google Scholar] [CrossRef]
  43. Bizami, N.A.; Tasir, Z.; Kew, S.N. Innovative pedagogical principles and technological tools capabilities for immersive blended learning: A systematic literature review. Educ. Inf. Technol. 2023, 28, 1373–1425. [Google Scholar] [CrossRef] [PubMed]
  44. Mittal, U.; Sai, S.; Chamola, V.; Sangwan, D. A comprehensive review on generative ai for education. IEEE Access 2024, 12, 142733–142759. [Google Scholar] [CrossRef]
  45. Moreno, L.; Martínez, P.; Díaz, A.; Ochoa, H.; Corsetti, B. Assessing standards-driven accessibility in top video conferencing platforms. Univers. Access Inf. Soc. 2024, 1–18. [Google Scholar] [CrossRef]
  46. Alturki, U.; Aldraiweesh, A. The Factors Influencing 21st Century Skills and Problem-Solving Skills: The Acceptance of Blackboard as Sustainable Education. Sustainability 2023, 15, 12845. [Google Scholar] [CrossRef]
  47. Rosienkiewicz, M.; Helman, J.; Cholewa, M.; Molasy, M.; Górecka, A.; Kohen-Vacs, D.; Winokur, M.; Amador Nelke, S.; Levi, A.; Gómez-González, J.F.; et al. Enhancing technology-focused entrepreneurship in higher education institutions ecosystem: Implementing innovation models in international projects. Educ. Sci. 2024, 14, 797. [Google Scholar] [CrossRef]
  48. Makrakis, V. Teachers’ Resilience Scale for Sustainability Enabled by ICT/Metaverse Learning Technologies: Factorial Structure, Reliability, and Validation. Sustainability 2024, 16, 7679. [Google Scholar] [CrossRef]
  49. Norrie, C.S.; Deckers, S.R.; Radstaake, M.; van Balkom, H. A Narrative Review of the Sociotechnical Landscape and Potential of Computer-Assisted Dynamic Assessment for Children with Communication Support Needs. Multimodal Technol. Interact. 2024, 8, 38. [Google Scholar] [CrossRef]
  50. Bühler, M.M.; Jelinek, T.; Nübel, K. Training and preparing tomorrow’s workforce for the fourth industrial revolution. Educ. Sci. 2022, 12, 782. [Google Scholar] [CrossRef]
  51. Joshi, K.; Kumar, R.; Bharany, S.; Saini, D.K.J.B.; Kumar, R.; Ibrahim, A.O.; Abdelmaboud, A.; Nagmeldin, W.; Medani, M. Exploring the Connectivity Between Education 4.0 and Classroom 4.0: Technologies, Student Perspectives, and Engagement in the Digital Era. IEEE Access 2024, 12, 24179–24204. [Google Scholar] [CrossRef]
  52. Fan, S.; Yecies, B.; Zhou, Z.I.; Shen, J. Challenges and Opportunities for the Web 3.0 Metaverse Turn in Education. IEEE Trans. Learn. Technol. 2024, 17, 1935–1950. [Google Scholar] [CrossRef]
  53. Hatami, M.; Qu, Q.; Chen, Y.; Kholidy, H.; Blasch, E.; Ardiles-Cruz, E. A Survey of the Real-Time Metaverse: Challenges and Opportunities. Future Internet 2024, 16, 379. [Google Scholar] [CrossRef]
  54. Xu, M.; Ng, W.C.; Lim, W.Y.B.; Kang, J.; Xiong, Z.; Niyato, D.; Yang, Q.; Shen, X.; Miao, C. A full dive into realizing the edge-enabled metaverse: Visions, enabling technologies, and challenges. IEEE Commun. Surv. Tutor. 2022, 25, 656–700. [Google Scholar] [CrossRef]
  55. Muzata, A.R.; Singh, G.; Stepanov, M.S.; Musonda, I. Immersive Learning: A Systematic Literature Review on Transforming Engineering Education Through Virtual Reality. Virtual Worlds 2024, 3, 480–505. [Google Scholar] [CrossRef]
  56. Abilkaiyrkyzy, A.; Elhagry, A.; Laamarti, F.; El Saddik, A. Metaverse key requirements and platforms survey. IEEE Access 2023, 11, 117765–117787. [Google Scholar] [CrossRef]
  57. Marougkas, A.; Troussas, C.; Krouska, A.; Sgouropoulou, C. Virtual reality in education: A review of learning theories, approaches and methodologies for the last decade. Electronics 2023, 12, 2832. [Google Scholar] [CrossRef]
  58. Alsamhi, M.H.; Hawbani, A.; Kumar, S.; Alsamhi, S.H. Multisensory metaverse-6G: A new paradigm of commerce and education. IEEE Access 2024, 12, 75657–75677. [Google Scholar] [CrossRef]
  59. Porat, R.; Ceobanu, C. Enhancing Spatial Ability: A New Integrated Hybrid Training Approach for Engineering and Architecture Students. Educ. Sci. 2024, 14, 563. [Google Scholar] [CrossRef]
  60. Mendoza-Ramírez, C.E.; Tudon-Martinez, J.C.; Félix-Herrán, L.C.; Lozoya-Santos, J.d.J.; Vargas-Martínez, A. Augmented reality: Survey. Appl. Sci. 2023, 13, 10491. [Google Scholar] [CrossRef]
  61. Bobko, T.; Corsette, M.; Wang, M.; Springer, E. Exploring the Possibilities of Edu-Metaverse: A New 3D Ecosystem Model for Innovative Learning. IEEE Trans. Learn. Technol. 2024, 17, 1278–1289. [Google Scholar] [CrossRef]
  62. Wu, D.; Yang, Z.; Zhang, P.; Wang, R.; Yang, B.; Ma, X. Virtual-reality interpromotion technology for metaverse: A survey. IEEE Internet Things J. 2023, 10, 15788–15809. [Google Scholar] [CrossRef]
  63. Meccawy, M. Creating an immersive XR learning experience: A roadmap for educators. Electronics 2022, 11, 3547. [Google Scholar] [CrossRef]
  64. Buffa, M.; Girard, D.; Hofr, A. Using Web Audio Modules for Immersive Audio Collaboration in the Musical Metaverse. In Proceedings of the 2024 IEEE 5th International Symposium on the Internet of Sounds (IS2), Erlangen, Germany, 30 September–2 October 2024; pp. 1–10. [Google Scholar]
  65. Rekha, K.; Gopal, K.; Satheeskumar, D.; Anand, U.A.; Doss, D.S.S.; Elayaperumal, S. Ai-Powered Personalized Learning System Design: Student Engagement and Performance Tracking System. In Proceedings of the 2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), Greater Noida, India, 14–15 May 2024; pp. 1125–1130. [Google Scholar]
  66. Spettu, F.; Achille, C.; Fassi, F. State-of-the-Art Web Platforms for the Management and Sharing of Data: Applications, Uses, and Potentialities. Heritage 2024, 7, 6008–6035. [Google Scholar] [CrossRef]
  67. Kim, J.; Miller, J.; Wang, K.; Dorneich, M.C.; Winer, E.; Brown, L.J. Empowering Instructors: Augmented Reality Authoring Toolkit for Aviation Weather Education. IEEE Trans. Learn. Technol. 2024, 17, 2141–2152. [Google Scholar] [CrossRef]
  68. Chatterjee, P.; Bose, R.; Banerjee, S.; Roy, S. Enhancing data security of cloud based lms. Wirel. Pers. Commun. 2023, 130, 1123–1139. [Google Scholar] [CrossRef]
  69. Alier, M.; Casañ Guerrero, M.J.; Amo, D.; Severance, C.; Fonseca, D. Privacy and e-learning: A pending task. Sustainability 2021, 13, 9206. [Google Scholar] [CrossRef]
  70. Sakka, S.; Liagkou, V.; Stylios, C.; Ferreira, A. On the privacy and security for e-education metaverse. In Proceedings of the 2024 IEEE Global Engineering Education Conference (EDUCON), Kos Island, Greece, 8–11 May 2024; pp. 1–10. [Google Scholar]
  71. Pyae, A.; Ravyse, W.; Luimula, M.; Pizarro-Lucas, E.; Sanchez, P.L.; Dorado-Diaz, I.P.; Thaw, A.K. Exploring User Experience and Usability in a Metaverse Learning Environment for Students: A Usability Study of the Artificial Intelligence, Innovation, and Society (AIIS). Electronics 2023, 12, 4283. [Google Scholar] [CrossRef]
  72. Evangelista, S.H.; Bestard, G.A.; Oliveira, F.H.M.; da Silva, I.A.; Amorim, F.F.; Llanos, C.H.; Barbalho, S.C.M. Using Problem/Project-Based Learning for Developing a Mechanical Ventilator in Brazil: The Perception of Undergraduate Students Regarding Their Learning and Satisfaction. IEEE Rev. Iberoam. De Tecnol. Del Aprendiz. 2023, 18, 199–210. [Google Scholar] [CrossRef]
  73. Torres-Peña, R.C.; Peña-González, D.; Chacuto-López, E.; Ariza, E.A.; Vergara, D. Updating calculus teaching with AI: A classroom experience. Educ. Sci. 2024, 14, 1019. [Google Scholar] [CrossRef]
  74. Alzaga Elizondo, T.; Brown, D. Students’ use of technological tools to engage in collective mathematical proof activity. Int. J. Comput.-Support. Collab. Learn. 2024, 19, 433–453. [Google Scholar] [CrossRef]
  75. Lopatina, E.; Maltseva, S.; Pavlova, A. Self-Directed Learning Optimisation Toolkits for Electronics and Electrical Engineering Students. In Proceedings of the 2023 Systems of Signals Generating and Processing in the Field of on Board Communications, Moscow, Russia, 14–16 March 2023; pp. 1–5. [Google Scholar]
  76. Mohammed, S.P.; Hossain, G.; Ameen, S.Y.Q. Cybersecurity Data Visualization: Designing a Course for Future High School Students. In Proceedings of the 2024 12th International Symposium on Digital Forensics and Security (ISDFS), San Antonio, TX, USA, 29–30 April 2024; pp. 1–7. [Google Scholar]
  77. Qi, J.; Tang, H.; Zhu, Z. Exploring an affective and responsive virtual environment to improve remote learning. Virtual Worlds 2023, 2, 53–74. [Google Scholar] [CrossRef]
  78. Pfeifer, V.A.; Chilton, T.D.; Grilli, M.D.; Mehl, M.R. How ready is speech-to-text for psychological language research? Evaluating the validity of AI-generated English transcripts for analyzing free-spoken responses in younger and older adults. Behav. Res. Methods 2024, 56, 7621–7631. [Google Scholar] [CrossRef] [PubMed]
  79. Zamiri, M.; Esmaeili, A. Methods and technologies for supporting knowledge sharing within learning communities: A systematic literature review. Adm. Sci. 2024, 14, 17. [Google Scholar] [CrossRef]
  80. Yan, M.; Pourdavood, R.G. Faculty and Student Perspectives on Online Learning in Higher Education. Educ. Sci. 2024, 14, 801. [Google Scholar] [CrossRef]
  81. Gutiérrez-Colón, M.; Alameh, S.A. Effects of Implementing the Digital Storytelling Strategy on Improving the Use of Various Forms of the Passive Voice in Undergraduate EFL Students’ Oral Skills at the University Level. Digital 2024, 4, 914–931. [Google Scholar] [CrossRef]
  82. Boutefara, T.; Mahdaoui, L. Applying game design approach to build web-based collaborative tool with better social presence. In Proceedings of the 2020 4th International Symposium on Informatics and Its Applications (ISIA), M’sila, Algeria, 15–16 December 2020; pp. 1–6. [Google Scholar]
  83. Mahindru, R.; Bapat, G.; Bhoyar, P.; Abishek, G.D.; Kumar, A.; Vaz, S. Redefining Workspaces: Young Entrepreneurs Thriving in the Metaverse’s Remote Realm. Eng. Proc. 2024, 59, 209. [Google Scholar] [CrossRef]
  84. Li, C.; Jiang, Y.; Ng, P.H.; Dai, Y.; Cheung, F.; Chan, H.C.; Li, P. Collaborative learning in the Edu-Metaverse era: An empirical study on the enabling technologies. IEEE Trans. Learn. Technol. 2024, 17, 1107–1119. [Google Scholar] [CrossRef]
  85. Zamiri, M.; Esmaeili, A. Strategies, Methods, and Supports for Developing Skills within Learning Communities: A Systematic Review of the Literature. Adm. Sci. 2024, 14, 231. [Google Scholar] [CrossRef]
  86. Mansour, N. Students’ and facilitators’ experiences with synchronous and asynchronous online dialogic discussions and e-facilitation in understanding the Nature of Science. Educ. Inf. Technol. 2024, 29, 15965–15997. [Google Scholar] [CrossRef]
  87. Sidekerskienė, T.; Damaševičius, R. Out-of-the-box learning: Digital escape rooms as a metaphor for breaking down barriers in stem education. Sustainability 2023, 15, 7393. [Google Scholar] [CrossRef]
  88. Al-Nofaie, H.; Alwerthan, T.A. Appreciative Inquiry into Implementing Artificial Intelligence for the Development of Language Student Teachers. Sustainability 2024, 16, 9361. [Google Scholar] [CrossRef]
  89. Song, J.; Lee, J. Presence and motivation: Comparing synchronous and asynchronous learning environments for foreign language learners using path analysis. Educ. Inf. Technol. 2024, 1–30. [Google Scholar] [CrossRef]
  90. Altinay, Z.; Altinay, F.; Sharma, R.C.; Dagli, G.; Shadiev, R.; Yikici, B.; Altinay, M. Capacity building for student teachers in learning, teaching artificial intelligence for quality of education. Societies 2024, 14, 148. [Google Scholar] [CrossRef]
  91. Buragohain, D.; Chaudhary, S.; Punpeng, G.; Sharma, A.; Am-in, N.; Wuttisittikulkij, L. Analyzing the impact and prospects of metaverse in learning environments through systematic and case study research. IEEE Access 2023, 11, 141261–141276. [Google Scholar] [CrossRef]
  92. Al-Kfairy, M.; Alzaabi, M.; Snoh, B.; Almarzooqi, H.; Alnaqbi, W. Metaverse-based classroom: The good and the bad. In Proceedings of the 2024 IEEE Global Engineering Education Conference (EDUCON), Kos Island, Greece, 8–11 May 2024; pp. 1–7. [Google Scholar]
  93. Caporusso, N.; Roa, Q.; Thomas, B.; Tilley, M. Tactile Network Topologies: Inclusive Learning for Visually Impaired Students in Computer Networking Education. In Proceedings of the 2024 47th MIPRO ICT and Electronics Convention (MIPRO), Opatija, Croatia, 20–24 May 2024; pp. 1399–1404. [Google Scholar]
  94. Portuguez-Castro, M.; Santos Garduño, H. Beyond Traditional Classrooms: Comparing Virtual Reality Applications and Their Influence on Students’ Motivation. Educ. Sci. 2024, 14, 963. [Google Scholar] [CrossRef]
  95. Marougkas, A.; Troussas, C.; Krouska, A.; Sgouropoulou, C. How personalized and effective is immersive virtual reality in education? A systematic literature review for the last decade. Multimed. Tools Appl. 2024, 83, 18185–18233. [Google Scholar] [CrossRef]
  96. Chu, C.E.; Cheong, G.S.W.; Mishra, A.; Wen, Y.; Leo, C.H.; Yeo, D.J.; Cheong, K.H. Enhancing Biology Laboratory Learning: Student Perceptions of Performing Heart Dissection with Virtual Reality. IEEE Access 2024, 12, 76682–76691. [Google Scholar] [CrossRef]
  97. Sineka, P.; Jothikumar, K.; Nivetha, V.; Luckshika, M.; Priyadharshini, P.; SG, J.R. The Role of Metaverse Technology in Education: A Framework for Implementation and Future Research. In Proceedings of the 2024 IEEE Students Conference on Engineering and Systems (SCES), Prayagraj, India, 21–23 June 2024; pp. 1–6. [Google Scholar]
  98. Glaser, N.; Yang, M.; Li, S.E.; Mendoza, K.R. The Museum of Instructional Design: An Examination of Learner Experiences & Usability in a Collaborative 3D Virtual Learning Environment. TechTrends 2024, 68, 338–357. [Google Scholar]
  99. De Felice, F.; Petrillo, A.; Iovine, G.; Salzano, C.; Baffo, I. How does the metaverse shape education? A systematic literature review. Appl. Sci. 2023, 13, 5682. [Google Scholar] [CrossRef]
  100. Alabau, A.; Fabra, L.; Martí-Testón, A.; Muñoz, A.; Solanes, J.E.; Gracia, L. Enriching User-Visitor Experiences in Digital Museology: Combining Social and Virtual Interaction within a Metaverse Environment. Appl. Sci. 2024, 14, 3769. [Google Scholar] [CrossRef]
  101. Iqbal, U.; Davies, T.; Perez, P. A Review of Recent Hardware and Software Advances in GPU-Accelerated Edge-Computing Single-Board Computers (SBCs) for Computer Vision. Sensors 2024, 24, 4830. [Google Scholar] [CrossRef] [PubMed]
  102. Malhotra, P.; Fortino, A. Teaching with Zoom vs. the Metaverse a Bandwidth Use Study. In Proceedings of the 2024 IEEE Integrated STEM Education Conference (ISEC), Princeton, NJ, USA, 9 March 2024; pp. 01–04. [Google Scholar]
  103. Chee, S.K.; Hoong, S.L.J.; Lee, Y.S. Innovating Engineering Education with Blended Learning and Remote Laboratories. In Proceedings of the 2024 IEEE Global Engineering Education Conference (EDUCON), Kos Island, Greece, 8–11 May 2024; pp. 1–5. [Google Scholar]
  104. Zhang, Y.; Kutscher, D.; Cui, Y. Networked metaverse systems: Foundations, gaps, research directions. IEEE Open J. Commun. Soc. 2024, 5, 5488–5539. [Google Scholar] [CrossRef]
  105. Mouta, A.; Torrecilla-Sánchez, E.M.; Pinto-Llorente, A.M. Comprehensive professional learning for teacher agency in addressing ethical challenges of AIED: Insights from educational design research. Educ. Inf. Technol. 2024, 1–45. [Google Scholar] [CrossRef]
  106. Lin, H.C.K.; Lu, L.W.; Lu, R.S. Integrating Digital Technologies and Alternate Reality Games for Sustainable Education: Enhancing Cultural Heritage Awareness and Learning Engagement. Sustainability 2024, 16, 9451. [Google Scholar] [CrossRef]
  107. Feng, Q.; Luo, H.; Li, Z.; Liang, J.; Li, G.; Yi, Y. Creating an Immersive Virtual Reality Game Space for Multiuser, Synchronous Co-Located Collaboration: Design Considerations and Influencing Factors. Appl. Sci. 2024, 14, 2167. [Google Scholar] [CrossRef]
  108. Ricci, M.; Scarcelli, A.; Fiorentino, M. Designing for the metaverse: A multidisciplinary laboratory in the industrial design program. Future Internet 2023, 15, 69. [Google Scholar] [CrossRef]
  109. Rahman, H.; Wahid, S.A.; Ahmad, F.; Ali, N. Game-based learning in metaverse: Virtual chemistry classroom for chemical bonding for remote education. Educ. Inf. Technol. 2024, 29, 19595–19619. [Google Scholar] [CrossRef]
  110. Kolil, V.K.; Achuthan, K. Virtual labs in chemistry education: A novel approach for increasing student’s laboratory educational consciousness and skills. Educ. Inf. Technol. 2024, 29, 25307–25331. [Google Scholar] [CrossRef]
  111. Chen, C.M.; Li, M.C.; Tu, C.C. A Mixed Reality-Based Chemistry Experiment Learning System to Facilitate Chemical Laboratory Safety Education. J. Sci. Educ. Technol. 2024, 33, 505–525. [Google Scholar] [CrossRef]
  112. Norton, D.; Norton, F.A.; Veciana, S. Connected Art Practice: Transformative Learning Environments for Transdisciplinary Competences. Societies 2024, 14, 33. [Google Scholar] [CrossRef]
  113. Samaniego, M.; Usca, N.; Salguero, J.; Quevedo, W. Creative Thinking in Art and Design Education: A Systematic Review. Educ. Sci. 2024, 14, 192. [Google Scholar] [CrossRef]
  114. Otto, S.; Bertel, L.B.; Lyngdorf, N.E.R.; Markman, A.O.; Andersen, T.; Ryberg, T. Emerging digital practices supporting student-centered learning environments in higher education: A review of literature and lessons learned from the COVID-19 pandemic. Educ. Inf. Technol. 2024, 29, 1673–1696. [Google Scholar] [CrossRef] [PubMed]
  115. Sharma, C.; Agarwal, B.; Wuttisittikulkij, L.; Joshi, D.; Bhatnagar, A.; Chaudhary, S.; Sasithong, P. Interactive Learning Through the Metaverse and its Impact on Primary Education. In Proceedings of the 2024 21st International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), Khon Kaen, Thailand, 27–30 May 2024; pp. 1–8. [Google Scholar]
  116. Zhao, L.; Isenberg, T.; Xie, F.; Liang, H.N.; Yu, L. SpatialTouch: Exploring Spatial Data Visualizations in Cross-reality. IEEE Trans. Vis. Comput. Graph. 2024, 31, 897–907. [Google Scholar] [CrossRef]
  117. Yücel, F.; Ünal, H.S.; Surer, E.; Huvaj, N. A Modular Serious Game Development Framework for Virtual Laboratory Courses. IEEE Trans. Learn. Technol. 2024, 17, 966–981. [Google Scholar] [CrossRef]
  118. Salloum, S.A.; Alhumaid, K.; Alfaisal, A.M.; Aljanada, R.A.; Alfaisal, R. Adoption of 3D Holograms in Science Education: Transforming Learning Environments. IEEE Access 2024, 12, 70984–70998. [Google Scholar] [CrossRef]
  119. Petruse, R.E.; Grecu, V.; Chiliban, M.B.; Tâlvan, E.T. Comparative Analysis of Mixed Reality and PowerPoint in Education: Tailoring Learning Approaches to Cognitive Profiles. Sensors 2024, 24, 5138. [Google Scholar] [CrossRef] [PubMed]
  120. Natale, G.; Fornai, F. Advances in Anatomy and Its History. Anatomia 2024, 3, 50–56. [Google Scholar] [CrossRef]
  121. Reeves, S.M.; Crippen, K.J. Virtual laboratories in undergraduate science and engineering courses: A systematic review, 2009–2019. J. Sci. Educ. Technol. 2021, 30, 16–30. [Google Scholar] [CrossRef]
  122. Kamruzzaman, M.; Alanazi, S.; Alruwaili, M.; Alshammari, N.; Elaiwat, S.; Abu-Zanona, M.; Innab, N.; Mohammad Elzaghmouri, B.; Ahmed Alanazi, B. AI-and IoT-assisted sustainable education systems during pandemics, such as COVID-19, for smart cities. Sustainability 2023, 15, 8354. [Google Scholar] [CrossRef]
  123. Monib, W.K.; Qazi, A.; Apong, R.A.; Mahmud, M.M. Investigating learners’ perceptions of microlearning: Factors influencing learning outcomes. IEEE Access 2024, 12, 178251–178266. [Google Scholar] [CrossRef]
  124. Mitsea, E.; Drigas, A.; Skianis, C. Well-Being Technologies and Positive Psychology Strategies for Training Metacognition, Emotional Intelligence and Motivation Meta-Skills in Clinical Populations: A Systematic Review. Psych 2024, 6, 305–344. [Google Scholar] [CrossRef]
  125. Abd Wahab, M.D.H.; Krishna, H.L.; Chen, T.K. Implementing a Linear and Bottlenecking Gameplay Experience in a Self-Created World. In Proceedings of the 2023 3rd International Conference on Mobile Networks and Wireless Communications (ICMNWC), Tumkur, India, 4–5 December 2023; pp. 1–5. [Google Scholar]
  126. Mitrakas, N.; Tsihouridis, C.; Vavougios, D. Using Mixed Reality in the Educational Practice: An Inquiry-Based Process of the Fluid Expansion–Contraction Phenomena by Pre-Service Teachers. Educ. Sci. 2024, 14, 754. [Google Scholar] [CrossRef]
  127. Christopoulos, A.; Mystakidis, S. Gamification in education. Encyclopedia 2023, 3, 1223–1243. [Google Scholar] [CrossRef]
  128. Wu, J.G.; Zhang, D.; Lee, S.M. Into the brave new metaverse: Envisaging future language teaching and learning. IEEE Trans. Learn. Technol. 2023, 17, 44–53. [Google Scholar] [CrossRef]
  129. Papadopoulou, A.; Mystakidis, S.; Tsinakos, A. Immersive Storytelling in Social Virtual Reality for Human-Centered Learning about Sensitive Historical Events. Information 2024, 15, 244. [Google Scholar] [CrossRef]
  130. Devadhas, V.A.; Krithika, M. Embracing the Metaverse: Revolutionizing Education for the Future. In Proceedings of the 2024 10th International Conference on Communication and Signal Processing (ICCSP), Melmaruvathur, India, 12–14 April 2024; pp. 136–141. [Google Scholar]
  131. Mourtzis, D. The Metaverse in industry 5.0: A human-centric approach towards personalized value creation. Encyclopedia 2023, 3, 1105–1120. [Google Scholar] [CrossRef]
  132. Kourtesis, P. A Comprehensive Review of Multimodal XR Applications, Risks, and Ethical Challenges in the Metaverse. Multimodal Technol. Interact. 2024, 8, 98. [Google Scholar] [CrossRef]
  133. Villegas-Ch, W.; Govea, J.; Godoy, L.N.; Mera-Navarrete, A. Virtual Reality Simulations for Skills Training: Improving Learning through Immersive Experiences in Educational Environments. IEEE Access 2024, 12, 130073–130090. [Google Scholar] [CrossRef]
  134. Shu, X.; Gu, X. An empirical study of A smart education model enabled by the edu-metaverse to enhance better learning outcomes for students. Systems 2023, 11, 75. [Google Scholar] [CrossRef]
  135. Murala, D.K. METAEDUCATION: State-of-the-Art Methodology for Empowering Feature Education. IEEE Access 2024, 12, 57992–58020. [Google Scholar] [CrossRef]
  136. George, B.; Wooden, O. Managing the strategic transformation of higher education through artificial intelligence. Adm. Sci. 2023, 13, 196. [Google Scholar] [CrossRef]
  137. Zhai, X.S.; Chu, X.Y.; Chen, M.; Shen, J.; Lou, F.L. Can Edu-Metaverse reshape virtual teaching community (VTC) to promote educational equity? An exploratory study. IEEE Trans. Learn. Technol. 2023, 16, 1130–1140. [Google Scholar] [CrossRef]
  138. Strielkowski, W.; Grebennikova, V.; Lisovskiy, A.; Rakhimova, G.; Vasileva, T. AI-driven adaptive learning for sustainable educational transformation. Sustain. Dev. 2024; Early View. [Google Scholar]
  139. Clapson, M.L.; Schechtel, S.; Davy, E.; Durfy, C.S. Solving the Chemistry Puzzle—A Review on the Application of Escape-Room-Style Puzzles in Undergraduate Chemistry Teaching. Educ. Sci. 2024, 14, 1273. [Google Scholar] [CrossRef]
  140. Fadhel, M.A.; Duhaim, A.M.; Albahri, A.; Al-Qaysi, Z.; Aktham, M.; Chyad, M.; Abd-Alaziz, W.; Albahri, O.; Alamoodi, A.; Alzubaidi, L.; et al. Navigating the metaverse: Unraveling the impact of artificial intelligence—a comprehensive review and gap analysis. Artif. Intell. Rev. 2024, 57, 264. [Google Scholar] [CrossRef]
  141. Damasceno, A.; Silva, L.; Barros, E.; Oliveira, F. DALverse: Assistive Technology for Inclusion of People with Disabilities in Distance Education through a Metaverse-Based Environment. In Proceedings of the 2024 IEEE International Conference on Advanced Learning Technologies (ICALT), Nicosia, Cyprus, 1–4 July 2024; pp. 142–146. [Google Scholar]
  142. Papadopoulos, K.; Koustriava, E.; Isaraj, L.; Chronopoulou, E.; Manganello, F.; Molina-Carmona, R. Assistive Technology for Higher Education Students with Disabilities: A Qualitative Research. Digital 2024, 4, 501–511. [Google Scholar] [CrossRef]
  143. Halim, N.A.A.; Azlan, M.H.; Ismail, A.W.; Fazli, F.E.; Ahmad, M.A.; Aladin, M.Y.F. Edu-Metaverse Classroom with AI-Driven Virtual Avatar Assistant. In Proceedings of the 2024 5th International Conference on Smart Electronics and Communication (ICOSEC), Trichy, India, 18–20 September 2024; pp. 1548–1554. [Google Scholar]
  144. Sumon, R.I.; Uddin, S.M.I.; Akter, S.; Mozumder, M.A.I.; Khan, M.O.; Kim, H.C. Natural Language Processing Influence on Digital Socialization and Linguistic Interactions in the Integration of the Metaverse in Regular Social Life. Electronics 2024, 13, 1331. [Google Scholar] [CrossRef]
  145. Othman, A.; Chemnad, K.; Hassanien, A.E.; Tlili, A.; Zhang, C.Y.; Al-Thani, D.; Altınay, F.; Chalghoumi, H.; S. Al-Khalifa, H.; Obeid, M.; et al. Accessible Metaverse: A Theoretical Framework for Accessibility and Inclusion in the Metaverse. Multimodal Technol. Interact. 2024, 8, 21. [Google Scholar] [CrossRef]
  146. Rottondi, C.; Sacchetto, M.; Severi, L.; Bianco, A. Towards an Inclusive Framework for Remote Musical Education and Practices. IEEE Access 2024, 12, 173836–173849. [Google Scholar] [CrossRef]
  147. Partarakis, N.; Zabulis, X. A review of immersive technologies, knowledge representation, and AI for human-centered digital experiences. Electronics 2024, 13, 269. [Google Scholar] [CrossRef]
  148. Dahlstrom-Hakki, I.; Alstad, Z.; Asbell-Clarke, J.; Edwards, T. The impact of visual and auditory distractions on the performance of neurodiverse students in virtual reality (VR) environments. Virtual Real. 2024, 28, 29. [Google Scholar] [CrossRef]
  149. Hashi, A.O.; Hashim, S.Z.M.; Asamah, A.B. A Systematic Review of Hand Gesture Recognition: An Update From 2018 to 2024. IEEE Access 2024, 12, 143599–143626. [Google Scholar] [CrossRef]
  150. Shin, J.; Miah, A.S.M.; Kabir, M.H.; Rahim, M.A.; Al Shiam, A. A Methodological and Structural Review of Hand Gesture Recognition Across Diverse Data Modalities. IEEE Access 2024, 12, 142606–142639. [Google Scholar] [CrossRef]
  151. Karunya, S.; Jalakandeshwaran, M.; Babu, T.; Uma, R. AI-Powered Real-Time Speech-to-Speech Translation for Virtual Meetings Using Machine Learning Models. In Proceedings of the 2023 Intelligent Computing and Control for Engineering and Business Systems (ICCEBS), Chennai, India, 14–15 December 2023; pp. 1–6. [Google Scholar]
  152. Lian, Y.; Xie, J. The Evolution of Digital Cultural Heritage Research: Identifying Key Trends, Hotspots, and Challenges through Bibliometric Analysis. Sustainability 2024, 16, 7125. [Google Scholar] [CrossRef]
  153. Dayoub, B.; Yang, P.; Omran, S.; Zhang, Q.; Dayoub, A. Digital Silk Roads: Leveraging the Metaverse for Cultural Tourism within the Belt and Road Initiative Framework. Electronics 2024, 13, 2306. [Google Scholar] [CrossRef]
  154. Kim, T.s.; Ignacio, M.J.; Yu, S.; Jin, H.; Kim, Y.g. UI/UX for Generative AI: Taxonomy, Trend, and Challenge. IEEE Access 2024, 12, 179891–179911. [Google Scholar] [CrossRef]
  155. Chalkiadakis, A.; Seremetaki, A.; Kanellou, A.; Kallishi, M.; Morfopoulou, A.; Moraitaki, M.; Mastrokoukou, S. Impact of Artificial Intelligence and Virtual Reality on Educational Inclusion: A Systematic Review of Technologies Supporting Students with Disabilities. Educ. Sci. 2024, 14, 1223. [Google Scholar] [CrossRef]
  156. Berlian, Z.; Huda, M. Reflecting culturally responsive and communicative teaching (CRCT) through partnership commitment. Educ. Sci. 2022, 12, 295. [Google Scholar] [CrossRef]
  157. Suk, H.; Laine, T.H. Influence of avatar facial appearance on users’ perceived embodiment and presence in immersive virtual reality. Electronics 2023, 12, 583. [Google Scholar] [CrossRef]
  158. Wu, S.; Xu, L.; Dai, Z.; Pan, Y. Factors affecting avatar customization behavior in virtual environments. Electronics 2023, 12, 2286. [Google Scholar] [CrossRef]
  159. Voinea, G.D.; Gîrbacia, F.; Postelnicu, C.C.; Duguleana, M.; Antonya, C.; Soica, A.; Stănescu, R.C. Study of social presence while interacting in metaverse with an augmented avatar during autonomous driving. Appl. Sci. 2022, 12, 11804. [Google Scholar] [CrossRef]
  160. Tian, F.; Zou, J.; Li, K.; Li, Y. Kung Fu metaverse: A movement guidance training system. IEEE Trans. Learn. Technol. 2023, 16, 1082–1095. [Google Scholar] [CrossRef]
  161. Pervez, F.; Shoukat, M.; Usama, M.; Sandhu, M.; Latif, S.; Qadir, J. Affective Computing and the Road to an Emotionally Intelligent Metaverse. IEEE Open J. Comput. Soc. 2024, 5, 195–214. [Google Scholar] [CrossRef]
  162. Hoter, E.; Yazbak Abu Ahmad, M.; Azulay, H. Enhancing Language Learning and Intergroup Empathy through Multi-User Interactions and Simulations in a Virtual World. Virtual Worlds 2024, 3, 333–353. [Google Scholar] [CrossRef]
  163. Wang, J.; Chen, S.; Liu, Y.; Lau, R. Intelligent metaverse scene content construction. IEEE Access 2023, 11, 76222–76241. [Google Scholar] [CrossRef]
  164. Schmidt, S.; Köysürenbars, I.; Steinicke, F. Frankenstein’s Monster in the Metaverse: User Interaction with Customized Virtual Agents. IEEE Trans. Vis. Comput. Graph. 2024, 30, 7162–7171. [Google Scholar] [CrossRef]
  165. Cobben, S. Designing a New Customer Experience for Fashion in the Metaverse. Master’s Thesis, Delft University of Technology, Delft, The Netherlands, October 2022. [Google Scholar]
  166. Çelik, F.; Baturay, M.H. The effect of metaverse on L2 vocabulary learning, retention, student engagement, presence, and community feeling. BMC Psychol. 2024, 12, 58. [Google Scholar] [CrossRef] [PubMed]
  167. Singh, M.; Sun, D.; Zheng, Z. Enhancing university students’ learning performance in a metaverse-enabled immersive learning environment for STEM education: A community of inquiry approach. Future Educ. Res. 2024, 2, 288–309. [Google Scholar] [CrossRef]
  168. Alpala, L.O.; Quiroga-Parra, D.J.; Torres, J.C.; Peluffo-Ordóñez, D.H. Smart factory using virtual reality and online multi-user: Towards a metaverse for experimental frameworks. Appl. Sci. 2022, 12, 6258. [Google Scholar] [CrossRef]
  169. Krishnapriya, S.; Malathy, R.; Banu, A.S.; Gomathi, R.; Vishnupriyan, T.; Kavitha, S. Collaborative Learning with IoT: Enhancing Student Engagement. In Proceedings of the 2024 10th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 14–15 March 2024; Volume 1, pp. 2524–2529. [Google Scholar]
  170. Jia, Y.; Wang, X.E.; Sin, Z.P.; Li, C.; Ng, P.H.; Huang, X.; Baciu, G.; Cao, J.; Li, Q. Knowledge-Graph-Driven Mind Mapping for Immersive Collaborative Learning: A Pilot Study in Edu-Metaverse. IEEE Trans. Learn. Technol. 2024, 17, 1794–1808. [Google Scholar] [CrossRef]
  171. You, Y.C. Integrative Narratology and Its Application in AI-based Virtual Education System. In Proceedings of the 2023 7th International Conference on E-Society, E-Education and E-Technology (ESET), Chiayi, China, 13–15 October 2023; pp. 8–17. [Google Scholar]
  172. Giabbanelli, P.; Shrestha, A.; Demay, L. Design and Development of a Collaborative Augmented Reality Environment for Systems Science. In Proceedings of the 57th Hawaii International Conference on System Sciences (HICSS), Kauai, HI, USA, 3–6 June 2024. [Google Scholar]
  173. Hong, D.J. Exploring Metaverse-Based Remote Work. In Proceedings of the 2024 IEEE International Symposium on Emerging Metaverse (ISEMV), Bellevue, WA, USA, 21 October 2024; pp. 41–44. [Google Scholar]
  174. Cities, R.; Li, X.S. Building Digital Twin Metaverse Cities; Apress: Berkeley, CA, USA, 2024. [Google Scholar]
  175. Cheng, R.; Murat, E.; Yu, L.F.; Chen, S.; Han, B. Understanding Online Education in Metaverse: Systems and User Experience Perspectives. In Proceedings of the 2024 IEEE Conference Virtual Reality and 3D User Interfaces (VR), Orlando, FL, USA, 16–21 March 2024; pp. 598–608. [Google Scholar]
  176. Liu, W.; Fu, Z.; Zhu, Y.; Li, Y.; Sun, Y.; Hong, X.; Li, Y.; Liu, M. Co-making the future: Crafting tomorrow with insights and perspectives from the China-US young maker competition. Int. J. Technol. Des. Educ. 2024, 34, 1763–1783. [Google Scholar] [CrossRef]
  177. Ford, S.J.; dos Santos, R.; dos Santos, R. Empowering Female High School Students for STEM Futures: Career Exploration and Leadership Development at Scientella. Educ. Sci. 2024, 14, 955. [Google Scholar] [CrossRef]
  178. Bansal, G.; Rajgopal, K.; Chamola, V.; Xiong, Z.; Niyato, D. Healthcare in metaverse: A survey on current metaverse applications in healthcare. IEEE Access 2022, 10, 119914–119946. [Google Scholar] [CrossRef]
  179. Ng, P.H.; Chen, P.Q.; Wu, A.C.; Tai, K.S.; Li, C. Reimagining STEM Learning: A Comparative Analysis of Traditional and Service Learning Approaches for Social Entrepreneurship. IEEE Trans. Learn. Technol. 2024, 17, 2212–2226. [Google Scholar] [CrossRef]
  180. De Giovanni, P. Sustainability of the Metaverse: A transition to Industry 5.0. Sustainability 2023, 15, 6079. [Google Scholar] [CrossRef]
  181. Suiçmez, İ.; Ozansoy, K. Development of Sustainable Education Environments in Higher Education with Metaverse Applications. Sustainability 2024, 16, 10331. [Google Scholar] [CrossRef]
  182. Boopathy, P.; Deepa, N.; Maddikunta, P.K.R.; Victor, N.; Gadekallu, T.R.; Yenduri, G.; Wang, W.; Pham, Q.V.; Huynh-The, T.; Liyanage, M. The Metaverse for Industry 5.0 in NextG Communications: Potential Applications and Future Challenges. IEEE Open J. Comput. Soc. 2024, 6, 4–24. [Google Scholar] [CrossRef]
  183. Suh, I.; McKinney, T.; Siu, K.C. Current perspective of metaverse application in medical education, research and patient care. Virtual Worlds 2023, 2, 115–128. [Google Scholar] [CrossRef]
  184. Mourtzis, D.; Angelopoulos, J. Development of an Extended Reality-Based Collaborative Platform for Engineering Education: Operator 5.0. Electronics 2023, 12, 3663. [Google Scholar] [CrossRef]
  185. Li, P.; Zhang, X.; Hu, X.; Xu, B.; Zhang, J. Theoretical model and practical analysis of immersive industrial design education based on virtual reality technology. Int. J. Technol. Des. Educ. 2024, 1–28. [Google Scholar] [CrossRef]
  186. Ghaempanah, F.; Moasses Ghafari, B.; Hesami, D.; Hossein Zadeh, R.; Noroozpoor, R.; Moodi Ghalibaf, A.; Hasanabadi, P. Metaverse and its impact on medical education and health care system: A narrative review. Health Sci. Rep. 2024, 7, e70100. [Google Scholar] [CrossRef] [PubMed]
  187. Gaudi, T.; Kapralos, B.; Quevedo, A. Structural and Functional Fidelity of Virtual Humans in Immersive Virtual Learning Environments. In Proceedings of the 2024 IEEE Gaming, Entertainment, and Media Conference (GEM), Turin, Italy, 5–7 June 2024; pp. 1–4. [Google Scholar]
  188. Senka, G.; Tramonti, M.; Dochshanov, A.M.; Jesmin, T.; Terasmaa, J.; Tsalapatas, H.; Heidmann, O.; Caeiro-Rodriguez, M.; Vaz de Carvalho, C. Using a Game to Educate About Sustainable Development. Multimodal Technol. Interact. 2024, 8, 96. [Google Scholar] [CrossRef]
  189. Uddin, M.; Manickam, S.; Ullah, H.; Obaidat, M.; Dandoush, A. Unveiling the metaverse: Exploring emerging trends, multifaceted perspectives, and future challenges. IEEE Access 2023, 11, 87087–87103. [Google Scholar] [CrossRef]
  190. Sofianidis, A. Why do students prefer augmented reality: A mixed-method study on preschool teacher students’ perceptions on self-assessment AR quizzes in science education. Educ. Sci. 2022, 12, 329. [Google Scholar] [CrossRef]
  191. Bibri, S.E.; Jagatheesaperumal, S.K. Harnessing the potential of the metaverse and artificial intelligence for the internet of city things: Cost-effective XReality and synergistic AIoT technologies. Smart Cities 2023, 6, 2397–2429. [Google Scholar] [CrossRef]
  192. Laine, T.H.; Lee, W. Collaborative Virtual Reality in Higher Education: Students’ Perceptions on Presence, Challenges, Affordances, and Potential. IEEE Trans. Learn. Technol. 2023, 17, 280–293. [Google Scholar] [CrossRef]
  193. Song, Y.; Cao, J.; Wu, K.; Yu, P.L.H.; Lee, J.C.K. Developing “Learningverse”—A 3-D Metaverse Platform to Support Teaching, Social, and Cognitive Presences. IEEE Trans. Learn. Technol. 2023, 16, 1165–1178. [Google Scholar] [CrossRef]
  194. Jovanović, A.; Milosavljević, A. VoRtex Metaverse platform for gamified collaborative learning. Electronics 2022, 11, 317. [Google Scholar] [CrossRef]
  195. Zaky, Y.A.M.; Gameil, A.A. Exploring the Use of Avatars in the Sustainable Edu-Metaverse for an Alternative Assessment: Impact on Tolerance. Sustainability 2024, 16, 6604. [Google Scholar] [CrossRef]
  196. Huang, Y.; Li, Y.J.; Cai, Z. Security and privacy in metaverse: A comprehensive survey. Big Data Min. Anal. 2023, 6, 234–247. [Google Scholar] [CrossRef]
  197. Wang, Y.; Su, Z.; Zhang, N.; Xing, R.; Liu, D.; Luan, T.H.; Shen, X. A survey on metaverse: Fundamentals, security, and privacy. IEEE Commun. Surv. Tutorials 2022, 25, 319–352. [Google Scholar] [CrossRef]
  198. Kostelić, K.; Etinger, D. Securing the Metaverse: A Bibliometric Analysis of Cybersecurity Challenges and Research Trajectories. IEEE Eng. Manag. Rev. 2024; Early Access. [Google Scholar]
  199. Basyoni, L.; Tabassum, A.; Shaban, K.; Elmahjub, E.; Halabi, O.; Qadir, J. Navigating Privacy Challenges in the Metaverse: A Comprehensive Examination of Current Technologies and Platforms. IEEE Internet Things Mag. 2024, 7, 144–152. [Google Scholar] [CrossRef]
  200. Mostafa, A.M.; Ezz, M.; Elbashir, M.K.; Alruily, M.; Hamouda, E.; Alsarhani, M.; Said, W. Strengthening cloud security: An innovative multi-factor multi-layer authentication framework for cloud user authentication. Appl. Sci. 2023, 13, 10871. [Google Scholar] [CrossRef]
  201. Awadallah, A.; Eledlebi, K.; Zemerly, J.; Puthal, D.; Damiani, E.; Taha, K.; Kim, T.Y.; Yoo, P.D.; Choo, K.K.R.; Yim, M.S.; et al. Artificial intelligence-based cybersecurity for the metaverse: Research challenges and opportunities. IEEE Commun. Surv. Tutor. 2024; Early Access. [Google Scholar]
  202. Sharma, S.; Singh, J.; Gupta, A.; Ali, F.; Khan, F.; Kwak, D. User Safety and Security in the Metaverse: A Critical Review. IEEE Open J. Commun. Soc. 2024, 5, 5467–5487. [Google Scholar] [CrossRef]
  203. Sreerakuvandana; Pappachan, P.; Bansal, R. Metaverse Security Paradigms; IGI Global: Hershey, PA, USA, 2024; pp. 228–252. [Google Scholar]
  204. Digennaro, S.; Visocchi, A. Nurturing Body Literacy: Transforming Education in the Virtual Reality Era to Shape Children’s Identities and Redefine Educator Roles. Educ. Sci. 2024, 14, 267. [Google Scholar] [CrossRef]
  205. Rahaman, M.F.; Golam, M.; Subhan, M.R.; Tuli, E.A.; Kim, D.S.; Lee, J.M. Meta-Governance: Blockchain-Driven Metaverse Platform for Mitigating Misbehavior Using Smart Contract and AI. IEEE Trans. Netw. Serv. Manag. 2024, 21, 4024–4038. [Google Scholar] [CrossRef]
  206. Kuru, K. Metaomnicity: Toward immersive urban metaverse cyberspaces using smart city digital twins. IEEE Access 2023, 11, 43844–43868. [Google Scholar] [CrossRef]
  207. Han, L.; Afzal, N.; Wang, Z.; Wang, Z.; Jin, T.; Guo, S.; Gong, H.; Wang, D. Ambient haptics: Bilateral interaction among human, machines and virtual/real environments in pervasive computing era. CCF Trans. Pervasive Comput. Interact. 2024, 1–33. [Google Scholar] [CrossRef]
  208. Raman, R.; Hughes, L.; Mandal, S.; Das, P.; Nedungadi, P. Mapping metaverse research to the sustainable development goal of good health and well-being. IEEE Access 2024, 12, 180631–180651. [Google Scholar] [CrossRef]
  209. Mazumdar, H.; Sathvik, M.; Chakraborty, C.; Unhelkar, B.; Mahmoudi, S. Real-time mental health monitoring for metaverse consumers to ameliorate the negative impacts of escapism and post trauma stress disorder. IEEE Trans. Consum. Electron. 2024, 70, 2129–2136. [Google Scholar] [CrossRef]
  210. Osorio, C.; Fuster, N.; Chen, W.; Men, Y.; Juan, A.A. Enhancing Accessibility to Analytics Courses in Higher Education through AI, Simulation, and e-Collaborative Tools. Information 2024, 15, 430. [Google Scholar] [CrossRef]
  211. Aria, R.; Archer, N.; Khanlari, M.; Shah, B. Influential factors in the design and development of a sustainable Web3/metaverse and its applications. Future Internet 2023, 15, 131. [Google Scholar] [CrossRef]
  212. Malave, S.; Takmare, S.; Sarfare, A.; Patil, V.; Sawant, S.; Patil, P. MetaCampus: Advancing Online Education with Virtual Classroom. In Proceedings of the 2024 3rd International Conference for Innovation in Technology (INOCON), Bangalore, India, 1–3 March 2024; pp. 1–7. [Google Scholar]
  213. Fiaz, F.; Sajjad, S.M.; Iqbal, Z.; Yousaf, M.; Muhammad, Z. MetaSSI: A Framework for Personal Data Protection, Enhanced Cybersecurity and Privacy in Metaverse Virtual Reality Platforms. Future Internet 2024, 16, 176. [Google Scholar] [CrossRef]
  214. Chawki, M.; Basu, S.; Choi, K.S. Redefining Boundaries in the Metaverse: Navigating the Challenges of Virtual Harm and User Safety. Laws 2024, 13, 33. [Google Scholar] [CrossRef]
  215. Laurens-Arredondo, L.A.; Laurens, L. Metaversity: Beyond emerging educational technology. Sustainability 2023, 15, 15844. [Google Scholar] [CrossRef]
  216. Mishra, D.; Agarwal, N.; Sharahiley, S.; Kandpal, V. Digital Financial Literacy and Its Impact on Financial Decision-Making of Women: Evidence from India. J. Risk Financ. Manag. 2024, 17, 468. [Google Scholar] [CrossRef]
  217. Zhu, H.Y.; Hieu, N.Q.; Hoang, D.T.; Nguyen, D.N.; Lin, C.T. A human-centric metaverse enabled by brain-computer interface: A survey. IEEE Commun. Surv. Tutor. 2024, 26, 2120–2145. [Google Scholar] [CrossRef]
  218. Stecuła, K.; Wolniak, R.; Aydın, B. Technology Development in Online Grocery Shopping—From Shopping Services to Virtual Reality, Metaverse, and Smart Devices: A Review. Foods 2024, 13, 3959. [Google Scholar] [CrossRef] [PubMed]
  219. Wang, Y.; Lee, L.H.; Braud, T.; Hui, P. Re-shaping Post-COVID-19 teaching and learning: A blueprint of virtual-physical blended classrooms in the metaverse era. In Proceedings of the 2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW), Bologna, Italy, 10 July 2022; pp. 241–247. [Google Scholar]
  220. Siddiqua, A.; Sabeer, S.; Rao, R.S.; Ahuja, S.; Aggarwal, S.; Lourens, M. Machine Learning-Driven Educational Ethics Considerations: Striking A Balance Between Privacy And Personalization. In Proceedings of the 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), Gautam Buddha Nagar, India, 1–3 December 2023; Volume 10, pp. 1748–1753. [Google Scholar]
  221. Al-Ghaili, A.M.; Kasim, H.; Al-Hada, N.M.; Hassan, Z.B.; Othman, M.; Tharik, J.H.; Kasmani, R.M.; Shayea, I. A review of metaverse’s definitions, architecture, applications, challenges, issues, solutions, and future trends. IEEE Access 2022, 10, 125835–125866. [Google Scholar] [CrossRef]
  222. Farouk, A.M.; Naganathan, H.; Rahman, R.A.; Kim, J. Exploring the Economic Viability of Virtual Reality in Architectural, Engineering, and Construction Education. Buildings 2024, 14, 2655. [Google Scholar] [CrossRef]
  223. Chengoden, R.; Victor, N.; Huynh-The, T.; Yenduri, G.; Jhaveri, R.H.; Alazab, M.; Bhattacharya, S.; Hegde, P.; Maddikunta, P.K.R.; Gadekallu, T.R. Metaverse for healthcare: A survey on potential applications, challenges and future directions. IEEE Access 2023, 11, 12765–12795. [Google Scholar] [CrossRef]
  224. Ali, M.; Naeem, F.; Kaddoum, G.; Hossain, E. Metaverse communications, networking, security, and applications: Research issues, state-of-the-art, and future directions. IEEE Commun. Surv. Tutor. 2023, 26, 1238–1278. [Google Scholar] [CrossRef]
  225. Patra, A.; Pandey, A.; Hassija, V.; Chamola, V.; Mishra, R.P. A survey on Edge enabled Metaverse: Applications, Technological Innovations, and Prospective Trajectories within the Industry. IEEE Access 2024, 12, 125125–125144. [Google Scholar] [CrossRef]
  226. Park, S.M.; Kim, Y.G. A metaverse: Taxonomy, components, applications, and open challenges. IEEE Access 2022, 10, 4209–4251. [Google Scholar] [CrossRef]
  227. Zawish, M.; Dharejo, F.A.; Khowaja, S.A.; Raza, S.; Davy, S.; Dev, K.; Bellavista, P. AI and 6G into the metaverse: Fundamentals, challenges and future research trends. IEEE Open J. Commun. Soc. 2024, 5, 730–778. [Google Scholar] [CrossRef]
  228. Kumar, A.; Chakravarthy, S.; Nanthaamornphong, A. Energy-Efficient Deep Neural Networks for EEG Signal Noise Reduction in Next-Generation Green Wireless Networks and Industrial IoT Applications. Symmetry 2023, 15, 2129. [Google Scholar] [CrossRef]
  229. Ahmad, S.; Umirzakova, S.; Mujtaba, G.; Amin, M.S.; Whangbo, T. Education 5.0: Requirements, enabling technologies, and future directions. arXiv 2023, arXiv:2307.15846. [Google Scholar]
  230. Wang, C.H. Education in the metaverse: Developing virtual reality teaching materials for K–12 natural science. Educ. Inf. Technol. 2024, 1–22. [Google Scholar] [CrossRef]
  231. Alauthman, M.; Ishtaiwi, A.; Al Maqousi, A.; Hadi, W. A Framework for Cybersecurity in the Metaverse. In Proceedings of the 2024 2nd International Conference on Cyber Resilience (ICCR), Dubai, United Arab Emirates, 26–28 February 2024; pp. 1–8. [Google Scholar]
  232. Ghosh, A.; Hassija, V.; Chamola, V.; El Saddik, A. A Survey on Decentralized Metaverse using Blockchain and Web 3.0 technologies, Applications, and more. IEEE Access 2024, 12, 146915–146948. [Google Scholar] [CrossRef]
  233. Rahman, M.A.; Alqahtani, L.; Albooq, A.; Ainousah, A. A survey on security and privacy of large multimodal deep learning models: Teaching and learning perspective. In Proceedings of the 2024 21st Learning and Technology Conference (L&T), Jeddah, Saudi Arabia, 15–16 January 2024; pp. 13–18. [Google Scholar]
  234. Żydowicz, W.M.; Skokowski, J.; Marano, L.; Polom, K. Navigating the Metaverse: A New Virtual Tool with Promising Real Benefits for Breast Cancer Patients. J. Clin. Med. 2024, 13, 4337. [Google Scholar] [CrossRef] [PubMed]
  235. Mutibwa, D.H. Radical Left Culture and Heritage, the Politics of Preservation and Memorialisation, and the Promise of the Metaverse. Heritage 2024, 7, 537–575. [Google Scholar] [CrossRef]
  236. Madanchian, M.; Taherdoost, H. Business Model Evolution in the Age of NFTs and the Metaverse. Information 2024, 15, 378. [Google Scholar] [CrossRef]
  237. Mogier, G.A.A.; El Khayat, G.A.; Elkordy, M.M.; Hanafy, Y.A.E.G. A Proposed Metaverse Framework Implementing Gamification for Training Teaching Staff. In Proceedings of the 2023 IEEE Afro-Mediterranean Conference on Artificial Intelligence (AMCAI), Hammamet, Tunisia, 13–15 December 2023; pp. 1–7. [Google Scholar]
  238. Yu, D. AI-empowered metaverse learning simulation technology application. In Proceedings of the 2023 International Conference on Intelligent Metaverse Technologies & Applications (iMETA), Tartu, Estonia, 18–20 September 2023; pp. 1–6. [Google Scholar]
  239. Maier, F.; Weinberger, M. Metaverse Meets Smart Cities—Applications, Benefits, and Challenges. Future Internet 2024, 16, 126. [Google Scholar] [CrossRef]
  240. Gadekallu, T.R.; Maddikunta, P.K.R.; Boopathy, P.; Deepa, N.; Chengoden, R.; Victor, N.; Wang, W.; Wang, W.; Zhu, Y.; Dev, K. Xai for industry 5.0-concepts, opportunities, challenges and future directions. IEEE Open J. Commun. Soc. 2024; Early Access. [Google Scholar]
  241. Sá, M.J.; Serpa, S. Metaverse as a learning environment: Some considerations. Sustainability 2023, 15, 2186. [Google Scholar] [CrossRef]
  242. Nleya, S.M.; Velempini, M. Industrial metaverse: A comprehensive review, environmental impact, and challenges. Appl. Sci. 2024, 14, 5736. [Google Scholar] [CrossRef]
  243. Wang, Y.; Gong, D.; Xiao, R.; Wu, X.; Zhang, H. A Systematic Review on Extended Reality-Mediated Multi-User Social Engagement. Systems 2024, 12, 396. [Google Scholar] [CrossRef]
  244. Cho, Y.; Park, K.S. Designing immersive virtual reality simulation for environmental science education. Electronics 2023, 12, 315. [Google Scholar] [CrossRef]
  245. Choi, W.; Kim, S. Curriculum Development of EdTech Class Using 3D Modeling Software for University Students in the Republic of Korea. Sustainability 2023, 15, 16605. [Google Scholar] [CrossRef]
  246. Alam, T. Metaverse of Things (MoT) applications for revolutionizing urban living in smart cities. Smart Cities 2024, 7, 2466–2494. [Google Scholar] [CrossRef]
  247. Dahan, N.A.; Al-Razgan, M.; Al-Laith, A.; Alsoufi, M.A.; Al-Asaly, M.S.; Alfakih, T. Metaverse framework: A case study on E-learning environment (ELEM). Electronics 2022, 11, 1616. [Google Scholar] [CrossRef]
  248. Kuleto, V.; Ilić, M.P.; Ranković, M.; Radaković, M.; Simović, A. Augmented and Virtual Reality in the Metaverse Context: The Impact on the Future of Work, Education, and Social Interaction. In Augmented and Virtual Reality in the Metaverse; Springer: Berlin, Germany, 2024; pp. 3–24. [Google Scholar]
  249. Guzzo, T.; Ferri, F.; Grifoni, P. Lessons learned during COVID-19 and future perspectives for emerging technology. Sustainability 2023, 15, 10747. [Google Scholar] [CrossRef]
Figure 1. Metaverse classroom layers.
Figure 1. Metaverse classroom layers.
Futureinternet 17 00063 g001
Figure 2. Innovative approach to building a Metaverse classroom.
Figure 2. Innovative approach to building a Metaverse classroom.
Futureinternet 17 00063 g002
Figure 3. Meta-MILE classroom model.
Figure 3. Meta-MILE classroom model.
Futureinternet 17 00063 g003
Figure 4. The level of familiarity and comfort in the Metaverse.
Figure 4. The level of familiarity and comfort in the Metaverse.
Futureinternet 17 00063 g004
Figure 5. Distribution of motivation levels.
Figure 5. Distribution of motivation levels.
Futureinternet 17 00063 g005
Figure 6. Perceived relevance to industry.
Figure 6. Perceived relevance to industry.
Futureinternet 17 00063 g006
Figure 7. Distribution of challenges faced.
Figure 7. Distribution of challenges faced.
Futureinternet 17 00063 g007
Figure 8. Perceived educational impact.
Figure 8. Perceived educational impact.
Futureinternet 17 00063 g008
Figure 9. Future likelihood adoption rates of Metaverse by sector in education.
Figure 9. Future likelihood adoption rates of Metaverse by sector in education.
Futureinternet 17 00063 g009
Figure 10. Educational impact before and after Metaverse integration.
Figure 10. Educational impact before and after Metaverse integration.
Futureinternet 17 00063 g010
Figure 11. Metaverse challenges in education.
Figure 11. Metaverse challenges in education.
Futureinternet 17 00063 g011
Table 1. Metaverse classroom requirements.
Table 1. Metaverse classroom requirements.
RequirementPriority (MoSCoW)Description
1Cross-platform accessibility (VR headsets, smartphones, tablets, and computers)Must-HaveEnsures students can access the classroom from various devices.
2Real-time troubleshooting and technical supportMust-HaveProvides immediate assistance to prevent disruptions in virtual learning.
3Data encryption and secure data handlingMust-HaveSafeguards sensitive student and educator data during transmission and storage.
4Interactive virtual classrooms with avatar-based interactionsMust-HaveAllows students to visually represent themselves in the virtual space for engagement.
5Parental control features for content and screen time managementShould-HaveGives parents control over their child’s virtual activities and content access.
6Scenario-based Learning EnvironmentMust-HaveOffers immersive, real-world scenarios to enhance problem-solving skills.
7Multilingual support and translation toolsCould-HaveSupports students from different linguistic backgrounds.
8Customizable teacher dashboards and analysisMust-HaveGives teachers insights into student progress and classroom management.
9Holistic assessments tracking academic and social skillsShould-HaveEvaluates a broad range of student skills beyond academics.
10CMS for organizing resourcesMust-HaveCentralized hub for storing and updating educational content.
11Adaptive AI-driven personalized learningShould-HavePersonalizes learning based on student performance and preferences.
12Compliance with GDPR and FERPAMust-HaveEnsures the platform adheres to data privacy regulations.
13Offline access for students with limited connectivityCould-HaveAllows students to access learning materials without continuous internet.
14Gamified elements to enhance engagementCould-HaveIncreases student motivation and participation through rewards and challenges.
15Self-help tutorials and automated systemShould-HaveEmpowers users to resolve basic issues and prevents major disruptions.
16Scheduling virtual parent-teacherCould-HaveSimplifies parent-teacher communication within the virtual environment.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Yeganeh, L.N.; Fenty, N.S.; Chen, Y.; Simpson, A.; Hatami, M. The Future of Education: A Multi-Layered Metaverse Classroom Model for Immersive and Inclusive Learning. Future Internet 2025, 17, 63. https://doi.org/10.3390/fi17020063

AMA Style

Yeganeh LN, Fenty NS, Chen Y, Simpson A, Hatami M. The Future of Education: A Multi-Layered Metaverse Classroom Model for Immersive and Inclusive Learning. Future Internet. 2025; 17(2):63. https://doi.org/10.3390/fi17020063

Chicago/Turabian Style

Yeganeh, Leyli Nouraei, Nicole Scarlett Fenty, Yu Chen, Amber Simpson, and Mohsen Hatami. 2025. "The Future of Education: A Multi-Layered Metaverse Classroom Model for Immersive and Inclusive Learning" Future Internet 17, no. 2: 63. https://doi.org/10.3390/fi17020063

APA Style

Yeganeh, L. N., Fenty, N. S., Chen, Y., Simpson, A., & Hatami, M. (2025). The Future of Education: A Multi-Layered Metaverse Classroom Model for Immersive and Inclusive Learning. Future Internet, 17(2), 63. https://doi.org/10.3390/fi17020063

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop