Integrating Interactive Metaverse Environments and Generative Artificial Intelligence to Promote the Green Digital Economy and e-Entrepreneurship in Higher Education

Abstract

The rapid evolution of the Fourth Industrial Revolution has significantly transformed educational practices, necessitating the integration of advanced technologies into higher education to address contemporary sustainability challenges. This study explores the integration of interactive metaverse environments and generative artificial intelligence (GAI) in promoting the green digital economy and developing e-entrepreneurship skills among graduate students. Grounded in a quasi-experimental design, the research was conducted with a sample of 25 postgraduate students enrolled in the “Computers in Education” course at King Khalid University. A 3D immersive learning environment (FrameVR) was combined with GAI platforms (ChatGPT version 4.0, Elai.io version 2.5, Tome version 1.3) to create an innovative educational experience. Data were collected using validated instruments, including the Green Digital Economy Scale, the e-Entrepreneurship Scale, and a digital product evaluation rubric. The findings revealed statistically significant improvements in students’ awareness of green digital concepts, entrepreneurial competencies, and their ability to produce sustainable digital products. The study highlights the potential of immersive virtual learning environments and AI-driven content creation tools in enhancing digital literacy and sustainability-oriented innovation. It also underscores the urgent need to update educational strategies and curricula to prepare future professionals capable of navigating and shaping green digital economies. This research provides a practical and replicable model for universities seeking to embed sustainability through emerging technologies, supporting broader goals such as SDG 4 (Quality Education) and SDG 9 (Industry, Innovation, and Infrastructure).

1. Introduction

The Fourth Industrial Revolution has contributed to significant developments in various areas of life, especially with regard to integrating the real world with the virtual world, through innovative artificial intelligence (AI) technologies such as virtual reality, augmented reality, the metaverse, virtual currencies, the Internet of Things, blockchain, smart robots, big data analysis technologies, and other Fourth Industrial Revolution technologies that have contributed significantly to environmental, economic, social, educational development, and other fields.

The metaverse is defined as a shared virtual space or collective virtual presence built through the convergence of virtual reality (VR) technologies and their integration with augmented reality (AR) [1]. It is also defined as a shared virtual space, through which computer-generated environments and physical reality are combined, providing a rich and immersive experience that can be navigated with great ease [2]. The metaverse environment has the potential to revolutionize the way we learn and work, as highlighted in [3]. It enables students to attend virtual classes and interact with their classmates and teachers in more engaging and interactive ways. Additionally, it offers access to a wide range of educational resources and experiences that are often unavailable in the physical world. Similarly, employees can work remotely and collaborate with colleagues around the globe more effectively. In this context, the metaverse serves as a dynamic platform for social interaction, creativity, and innovation.

There is a close relationship between AI and metaverse environments, as both benefit from each other. AI is one of the pillars upon which the metaverse will be built, both now and in the future. This begins with processing user-generated data and continues with the use of generative models that create realistic virtual environments. It also recognizes body movements and makes the metaverse experience more natural and realistic. AI will also enable the creation of digital characters that resemble users and allow users to understand each other in their own language through simultaneous speech translation. AI also helps develop metaverse applications, such as improving interaction and collaboration between learners and the virtual world, i.e., providing intelligent virtual characters capable of interaction [4].

Generative AI (GAI) can create new content such as text, graphics, video, website design, image generation, and programming code, among other things. Generative AI has great potential for innovation. It is a subset of machine learning that focuses on creating algorithms that generate new data based on patterns in existing data, which can be applied in education, design, and robotics. Therefore, organizations and individuals are increasingly interested in generative AI tools to design new content, video, graphics, code, and other electronic services [5]. One of the most important AI initiatives is UNESCO, which has developed its own deep learning library and made it open source to process the data it collects on customer views. This library serves as a recommendation engine; Amazon uses it to provide recommendations, and Facebook uses it through its People You May Know feature [6]. Generative AI platforms will improve the work environment and safety, while simultaneously increasing productivity and boosting the economy. A McKinsey report indicated that AI has the potential to increase (1.2%) the global GDP annually, and AI is expected to contribute approximately 13 trillion dollars to the global economy over the next decade [7]. Generative AI can significantly increase labor productivity across all areas of the economy, as confirmed in [8] This may contribute to annual productivity growth ranging from 0.1% to 0.6% until 2040, depending on technological advancement and the reallocation of workers’ time to other activities.

Modern economic growth is linked to the digital economy by directly linking GDP growth to technology, not only through labor and capital, but also through investment in physical capital (production technologies), human capital (technical expertise), and social capital (the knowledge system). Therefore, the digital economy is the primary driver of economic growth, due to its profound impact on businesses, jobs, and individuals [9]. The digital economy is considered a branch of the knowledge economy that emerged alongside the internet, making information and communications technology essential for its development and continuity, as noted in [10]. It is also referred to as the borderless economy, the internet economy, or the new economy.

It is a knowledge economy that relies on the application of human knowledge to every product as well as its production model. Thus, knowledge becomes a fourth element of production alongside the three traditional elements: capital, labor, and natural resources.

Another type of economy has emerged linked to the digital economy: the green economy, which links the economy to the environment, including resources such as water, oil, and forests. This helps shift the concept of economic development from simply increasing the exploitation of economic resources to achieving sustainable or continuous development. The green digital economy is one of the mechanisms for achieving sustainable development by encouraging creativity, innovation, and digital leadership, opening new markets, providing job opportunities, and applying technological innovations to achieve food security and ensure rural areas have access to energy, education, clean water, and various facilities [11]. The importance of the green digital economy lies in its role in preserving ecosystems that have been severely degraded since the Industrial Revolution, and in narrowing the gap between the rich and the poor—particularly regarding access to a safe, clean quality of life and improved well-being, as discussed in [12]. It also provides new job opportunities and new types of jobs related to green digital activities. Consequently, many institutions and countries have sought to move towards a green economy, either partially or entirely.

In this regard, and to strengthen the UAE’s role as a major global center for the green economy, Dubai hosted the eighth edition of the World Green Economy Summit in September 2022, with the participation of all sectors of the green economy and sustainable development from around the world. The summit concluded with the importance of comprehensive partnerships and the need to mobilize resources to support low-emission development initiatives, improve quality of life, and encourage the transition to a green economy, in addition to empowering youth to effect positive and effective change [13].

The ChatGPT chatbot is a pre-trained generative artificial intelligence application designed for artificial chat, which could play a significant role in the green digital economy. It is used to generate texts that resemble natural human language and relies on a deep learning algorithm, which enables it to learn from the massive data it is trained on or accesses [14]. In this regard, a study by [15] concluded that the ChatGPT platform can be used to assess learning credibility and develop critical and creative thinking skills. This is achieved by having teachers create content for a specific topic, and then having students evaluate and verify the information contained therein. It can also be used to improve student writing and generate new ideas and information.

With the advancement of the internet and artificial intelligence platforms in recent years, a new category in the field of entrepreneurship, known as digital entrepreneurship, has emerged. It is a social, economic, and technological phenomenon based on the digitization of operations and a focus on leveraging new digital technologies in smart ways, such as artificial intelligence platforms, smartphone applications, cloud computing, and others. The goal is to change the traditional method followed by most institutions to establish and conduct businesses in the digital age [15]. The skills that distinguish an e-entrepreneur from others can be categorized into five key dimensions: proactive behavior, a preference for innovation, self-efficacy, achievement motivation, and non-conformity, as identified in [16]. These skills raise an individual’s entrepreneurial motivation, enabling them to proactively seek opportunities and respond to challenges, obstacles, and tasks in an innovative manner. Therefore, many countries have adopted entrepreneurship education in their educational systems in order to educate their generations on entrepreneurship as the primary driver of economic development. In the United States of America, a week has been designated each year for individuals to practice entrepreneurship, and in Japan, universities have been given independence in entrepreneurship and reducing the gap between educational outcomes and the needs of the labor market [17]. A study in [18] indicated that the limited development of students’ entrepreneurial ideas and their involvement in digital entrepreneurial projects aimed at solving present and future challenges is primarily due to educational institutions’ insufficient emphasis on practical learning and real-world problem-solving, in contrast to their stronger focus on academic achievement. Similarly, the study in [19] concluded that universities show limited interest in fostering a culture of e-entrepreneurship among students. It also noted the absence of strategies to encourage creative entrepreneurial initiatives, with institutional visions and missions lacking support for e-entrepreneurship.

Despite the growing academic interest in metaverse technologies and generative artificial intelligence in education, the majority of studies remain theoretical and do not provide well-studied practical applications. According to a recent systematic review, a clear gap was identified related to the scarcity of research that employs these technologies in realistic educational environments to measure their actual impact on student learning, especially in fields such as the digital economy or higher education [20].

Despite the rapid growth in the use of generative AI tools in entrepreneurship, research still lacks clear theoretical and regulatory frameworks that govern this use to ensure innovation and sustainability. A recent review indicated that e-entrepreneurship research often focuses on technical capabilities without examining the regulatory or ethical aspects related to the responsible use of these tools [21]. The integration of generative AI into achieving the Sustainable Development Goals, particularly the Quality Education Goal (SDG 4), remains underutilized in current research. A recent study indicated that this type of intelligence can support personalized learning and bridge educational gaps, but it requires careful pedagogical planning and clear integration strategies within educational curricula [22].

To address the growing need for sustainability-oriented digital innovation in higher education, this research proposes an integrated model that combines interactive metaverse environments and generative artificial intelligence (GAI) tools to foster green digital entrepreneurship. By leveraging immersive virtual learning spaces and AI-based content generation platforms, the model aims to enhance students’ innovation capacity, entrepreneurial thinking, and alignment with green economy principles. The conceptual framework presented in Figure 1 summarizes the relationships among the research core variables and serves as the theoretical foundation for the research design and implementation.

2. Research Problem

With the increase in the number of students in universities and colleges, the consumption of physical and human energy has significantly grown. This expansion has been accompanied by rising levels of electronic waste, excessive use of printed materials, and increased dependence on energy-intensive technologies in lectures and administrative processes. These factors have contributed to heightened environmental pressure, including elevated levels of carbon dioxide emissions and a broader ecological footprint. In light of these challenges, it becomes essential to explore alternative, technology-enabled educational and administrative models that support institutional goals while minimizing environmental harm and advancing sustainability objectives [23].

Despite the rapid progress in the use of generative artificial intelligence in entrepreneurship, current research lacks clear regulatory frameworks that guide the use of these technologies to ensure innovation and sustainability. A recent systematic review indicates an urgent need to develop policies and regulations that ensure the ethical and effective use of generative artificial intelligence in entrepreneurship, with a focus on promoting innovation and sustainability [21].

Despite the significant potential of generative AI to enhance the quality of education and achieve the Sustainable Development Goals, there is a lack of research exploring how to effectively integrate these technologies into educational curricula. A recent study highlights the need to develop educational strategies that integrate generative AI to enhance personalized learning and achieve educational equity [22]. It has been observed in [24] that most students are primarily interested in the social connections they form through web-based digital platforms. Despite the frequent use of these tools by students, educational institutions have been slow to adopt them in ways that could foster engagement and entrepreneurial development. Additionally, [25] highlights the prevailing perception that universities tend to teach innovation rather than actively practice it. As a result, most learners remain confined within the "learning as usual" framework, relying on traditional definitions, knowledge, and information, with limited interest in generating innovative ideas.

The Arab Digital Economy Index 2020 emphasizes the need to transition to a green digital economy to address development challenges. This requires the Arab region to build new and innovative capabilities to address developmental and economic challenges, especially during crises [26]. In this regard, a study by [27] examined the difficulties faced by Arab university graduates when integrating into the labor market. The study concluded that the current labor market and its future prospects do not accommodate the outputs of higher education institutions. This is due to the unsuitability of these institutions’ outputs, in terms of quantity and quality, for the labor market. Universities focus on filling minds with dense knowledge and information, neglecting the skills that aim to foster innovation and entrepreneurship.

In this context, [28] highlights that Arab universities show limited interest in the field of digital entrepreneurship, often focusing on exam-oriented knowledge or passive learning approaches rather than fostering creativity and innovation. Similarly, the study in [29] identified several barriers to innovation and digital entrepreneurship, most notably the lack of institutional interest in emerging and dynamic technologies such as artificial intelligence, robotics, big data analytics, and the Internet of Things—tools that offer vast opportunities for technological advancement. Moreover, [30] argues that most technological tools are merely used to digitize traditional content, leading learners to believe they are engaging in innovation, when in reality, their understanding and creative capabilities remain limited. According to [31], many traditional technologies are outdated and fail to support the efficient delivery of information. Although curricula have evolved, there remains a pressing need to adopt modern technologies that enhance productivity for both educators and learners. Engaging students in hands-on, practical experiences is far more effective than relying solely on traditional instructional methods.

It has been noted in [32] that the modern world and labor market no longer prioritize graduates with high academic grades alone, but rather seek learners equipped with entrepreneurial skills capable of identifying and solving real-world educational, economic, and industrial challenges. In line with this, [33] emphasizes that traditional teaching methods have become less effective in the face of rapid technological advancement, necessitating a shift in instructional approaches. The metaverse is seen as a promising tool for advancing sustainable education; however, its successful integration into higher education remains hindered by several challenges, including the absence of clear educational policies, insufficient teacher training, and the need for curriculum reform. A recent study suggests that achieving social sustainability through the metaverse requires complementary policies focused on education, digital literacy, and social psychology to address issues such as social isolation, digital dependency, and inequality of access [34].

To confirm the current research problem and investigate the weaknesses in integrating metaverse technologies and generative AI in promoting the green digital economy and green e-entrepreneurship, the researchers conducted an exploratory study on a sample of 29 male and female graduate students at the College of Education at King Khalid University. The results of the study showed that 83.3% of the sample had never used any metaverse-based platform in their educational courses, and 78.5% of them indicated that they lacked sufficient knowledge of generative AI tools such as ChatGPT version 4.0, Elai.io version 2.5, or Tome version 1.3. Furthermore, 85.7% of participants indicated that current curricula do not provide opportunities to design digital entrepreneurial projects with a sustainable environmental dimension, reflecting a weakness in the development of green digital entrepreneurship. These findings support the urgent need to develop interactive learning environments based on generative AI and metaverse technologies to meet the requirements of the modern digital economy and achieve sustainable development goals.

The researchers conducted a series of semi-structured personal interviews with a sample of 12 male and female graduate students at the College of Education at King Khalid University. These interviews aimed to examine the reality of employing metaverse technologies and generative artificial intelligence in educational curricula and their impact on promoting concepts of the green digital economy and developing green digital entrepreneurship. Student testimonies revealed a clear gap between what they learned theoretically and what they were required to apply practically using these technologies. Most participants indicated that they had never experienced educational experiences based on the metaverse and expressed a lack of practical knowledge of using generative artificial intelligence tools to design digital content or sustainable entrepreneurial projects. These field observations supported the results of the exploratory study and contributed to shaping the scientific basis for the research problem. They also emphasized the need to design a modern, interactive educational environment in which these technologies are systematically integrated to enhance students’ digital competence and sustainable innovation.

From the above, the current research problem was identified as the lack of interest in promoting the green digital economy and green digital entrepreneurship skills among university students in the Computer Science in Education course. Therefore, the current research seeks to address this weakness by integrating the metaverse environment and generative artificial intelligence, which may contribute to enhancing the green digital economy, digital entrepreneurship skills, and the production of green digital entrepreneurial businesses.

3. Research Questions

Given the growing need to integrate sustainability into higher education through innovative digital tools, it is imperative to explore how immersive technologies and AI-powered platforms can support this transformation. Therefore, this research seeks to examine the impact of integrating interactive metaverse environments and generative AI tools on developing green digital entrepreneurship skills among graduate students. The current research seeks to answer the following questions:

• What is the impact of the integration of the interactive metaverse environment and generative artificial intelligence on promoting the green digital economy in the “Computers in Education” course for graduate students?
• What is the impact of the integration of the interactive metaverse environment and generative artificial intelligence on green e-entrepreneurship in the “Computers in Education” course for graduate students?
• What is the impact of the integration of the interactive metaverse environment and generative artificial intelligence on the production of a green digital entrepreneurial product in the “Computers in Education” course for graduate students?

4. Research Hypotheses

The current study attempted to verify the following hypotheses:

Hypothesis 1.

There is a statistically significant difference at the 0.05 level between the average scores of the pre- and post-tests on the Green Digital Economy Scale in the “Computer in Education” course for graduate students, in favor of the post-test.

Hypothesis 2.

There is a statistically significant difference at the 0.05 level between the average scores of the pre- and post-tests on the Green e-Entrepreneurship Scale in the “Computer in Education” course for graduate students, in favor of the post-test.

Hypothesis 3.

There is a statistically significant difference at the 0.05 level between the average scores of the pre- and post-tests on the Green Digital Entrepreneurship Product Evaluation Card in the “Computers in Education” course for graduate students, in favor of the post-test.

5. Research Objectives

The current research aims to promote the green digital economy and develop green e-entrepreneurship skills in the “Computers in Education” course among graduate students through the integration of an interactive metaverse environment and generative artificial intelligence technology.

5.1. Significance of the Research

• Directing university education officials to pay attention to the need to employ three-dimensional virtual learning environments (the metaverse) in university education.
• Directing university education officials to pay attention to the need to employ modern generative artificial intelligence applications in university education.
• Providing a smart training environment based on the integration of the metaverse learning environment and modern artificial intelligence platforms, which can benefit those interested in sustainable development in promoting the green digital economy, as well as producing green digital entrepreneurial businesses that can benefit society and achieve environmental sustainability.
• Developing society and achieving sustainable development by encouraging students to design and produce green entrepreneurial projects and ideas.

5.2. Research Limitations

The current research was limited to the following limitations:

• The following artificial intelligence platforms: To ensure the provision of an integrated digital educational experience that supports innovation and sustainability, a group of modern digital platforms was employed, combining metaverse and generative artificial intelligence technologies. The FrameVR platform was used to provide a 3D virtual reality learning environment that allows students to interact in an immersive way. Poe was also employed to power the ChatGPT model to support students in content generation and provide immediate assistance. In educational media production, Elai.io was used to create professional educational videos, and Tome.app was used to design engaging presentations. Whimsical was used to design electronic mind maps to help organize ideas, while D-ID was used to convert still images into realistic audio-supported videos. Durable was used to create professional educational websites for students’ digital projects. Finally, Tutor AI was employed to design and create interactive educational lessons that enhance learner independence and contribute to the development of advanced digital skills.
• “Computer in Education—474 Approach-2” course.
• Green Digital Economy Skills: digital technology, digital transformation, continuous digital learning, digital sustainability.
• Green E-Entrepreneurship Skills: proactive action, innovation preference, self-efficacy, achievement motivation, non-conformity, and digital dynamics.

6. Research Literature

6.1. Metaverse and Green Digital Economy

The term “metaverse” consists of two parts: “meta,” meaning “beyond,” and “verse,” which is an abbreviation for “universe,” meaning the world or universe. The word “metaverse”, then, means “what lies beyond the physical world.” The metaverse can be defined as a third world and a fully immersive online environment that extends between the virtual world and the real world. It is based on virtual reality, and learners interact with each other using avatars [35].

The metaverse is a third world, extending between the virtual world and the real world. It is the third dimension of the internet. It is the next revolution in the development of the internet, based on Web 3.0, or the Semantic Web. Virtual reality will be one of its most prominent manifestations, which will significantly change our perception of the meaning and true nature of reality. The metaverse will be a sensory, graphic space, unlike the internet, which requires a login. Rather, life in it will be based on appropriate technology, which will be entirely dependent on virtual reality technologies. It will significantly change the concepts of human communication, transforming from real life to virtual reality [35].

The metaverse is a large ecosystem encompassing all fields, such as education, economics, aviation, health, and job creation. Individuals can purchase digital products such as clothing, shoes, books, games, and more. Companies will be present in the metaverse, and individuals will purchase digital items just as they do in the current physical environment. One of the positive benefits of the metaverse in education is its ability to stimulate learning and keep learners in a positive and happy mood. The virtual world can create a learning environment focused on collaboration and task completion. It can even make the educational institution resemble a video game, but it also contains numerous courses and educational lessons with tasks and activities that motivate learners to complete their tasks through gamification [36].

According to [37], the metaverse offers several advantages in the field of education. It can serve as a virtual classroom where students interact with peers and instructors while accessing various educational materials, including videos, documents, activities, and assessments. The metaverse also supports the creation of immersive learning experiences, allowing students to explore complex subjects—such as physics or history—within interactive, three-dimensional environments. Additionally, it facilitates skills training, including language acquisition and digital competencies, through gamified or simulation-based methods. Moreover, the metaverse provides a platform for international collaboration, enabling learners from different parts of the world to work together on projects, exchange ideas, and learn from one another.

On the other hand, a study by [38] concluded that the new economy is based on the recognition that knowledge, skills, and scientific competencies, combined with innovative and creative information technologies, play a significant role in the economic development of societies. Therefore, the use of modern technologies such as virtual reality, augmented reality, the metaverse, and other modern technologies resulting from the application and economic exploitation of knowledge in various fields has led to the emergence of the term “digital economy.” Metaverse technology helps raise the level of education; it can connect people from all over the world, allowing students to see the entire world in a way that was not possible before. It also enables individuals living in distant places to learn and exchange knowledge. It is also recognized that it contributes significantly to expanding the scope of knowledge and electronic participation in various areas of life [39].

Generative Artificial Intelligence (GAI) is one of the most powerful technological innovations available to humanity today, and the biggest mistake any organization can make is to ignore it. Leaders of countries and institutions alike see the magnitude of the opportunities AI brings and the dangers of falling behind in this field. In the United States, the White House issued a document affirming the strategic importance of AI, which will open new horizons for individuals and institutions in fields such as science, medicine, communications, information, and others. Therefore, the US administration emphasizes the importance of accelerating AI research in order to lead in this vital field. China has also developed an ambitious plan to leverage AI with the goal of becoming a global leader in this field by 2030 [6].

Generative AI online platforms are based on helping learners quickly access, generate, or produce scientific content. This content can be built, modified, or adapted by the teacher or the learner. To support participation, discussion, and integration across smart platforms [40]. The importance of the green digital economy in the education sector lies in its ability to leverage the comprehensive digital transformation implemented in higher education institutions, diversifying the sector’s sources of income, and addressing the various challenges and crises facing the sector. For example, the significant role digital transformation has played in enabling the digital economy during the COVID-19 crisis. It also works to reduce reliance on budgets that support education in various societies [26].

The above demonstrates that the use of metaverse technology and generative AI can play a significant and important role in the green digital economy and, consequently, sustainable development. Students interact with this technology to obtain rapid, diverse, and in-depth information in a way that enhances their learning and engagement with others. It also allows them to access texts, graphics, images, videos, or web pages anywhere and at any time. Furthermore, the continuous feedback mechanism available on electronic brainstorming sites makes them a powerful and unique educational tool.

6.2. Generative Artificial Intelligence and Education

Artificial intelligence and its various applications will change the rules and foundations of the field of education. Education and artificial intelligence can be considered two sides of the same coin. Education helps students learn and expand society’s accumulated knowledge, while artificial intelligence provides technologies and applications to understand the mechanisms behind intelligent thought and behavior [41].

By using ChatGPT, students can organize their thoughts and generate new, creative ideas and plans to enhance and develop their innovation and entrepreneurship skills. Students can also collaborate with their teachers to discuss and analyze ideas and information obtained from generative artificial intelligence platforms, thus generating insightful and useful insights and information that can significantly contribute to producing entrepreneurial ideas that serve society. Learners can also use ChatGPT to create an article on a specific topic, design a presentation, followed by an audio recording and editing, generate illustrative images and design avatars on a specific topic, design integrated online lessons, and many other uses of modern AI platforms. Therefore, it can be said that ChatGPT is a platform for preparing individuals for future careers.

As noted in [42], ChatGPT differs from traditional search engines like Google in that it is designed to generate personalized, conversational responses tailored to user input. While search engines typically provide a list of relevant web pages based on keywords, ChatGPT focuses on understanding user intent and producing context-specific answers. In contrast to search engines, which primarily retrieve and display existing content, ChatGPT presents information in a more direct and interactive manner, enhancing accessibility and user engagement.

Generative AI is a type of AI technology that uses algorithms to design content such as text, images, videos, music, programming codes for websites and electronic applications, data processing, etc. Generative AI is associated with terms such as machine learning, deep learning, artificial intelligence, and supervised learning, as illustrated in Figure 2 [43].

Figure 2 illustrates the hierarchical relationship among core fields in artificial intelligence that underpin the current educational model. At the broadest level, Artificial Intelligence (AI) encompasses all techniques that enable machines to simulate human intelligence. Machine Learning (ML), a subset of AI, allows systems to learn from data and improve over time without explicit programming. Within ML, Deep Learning (DL) refers to models using multi-layered neural networks for more complex pattern recognition, while Generative Artificial Intelligence (GAI)—such as transformer-based models and Generative Adversarial Networks (GANs)—represents a focused domain within deep learning that enables content creation. This layered structure helps clarify how specific algorithms used in GAI (e.g., GPT architectures for text generation, or diffusion models for image synthesis) are grounded in broader AI principles. Integrating these technologies into educational contexts supports advanced capabilities such as adaptive learning, automated content development, and intelligent feedback.

There are many platforms that rely on generative AI systems and are used in the field of education, including tracking educational data to track student behavior, as well as providing support for students at risk of dropping out of school. When analyzing a learner’s interaction with multiple-choice questions in mathematics, teachers look at the learner’s result and the grades they obtained, while AI platforms can delve deeper to learn more about the real difficulty facing the learner. AI platforms can determine whether the student is struggling with the general concept or whether there is ambiguity in the question that is causing confusion for the student. In other words, AI applications can identify the essential step that the student missed; This helps them learn the correct method. Among the most important applications of artificial intelligence in education are the following [41]:

• Smart Content:

The majority of e-learning platforms focus on designing smart content by transforming textbooks into smart books closely related to educational goals. An example of this is the Next Learning application, which integrates smart content with practice exercises and assessment. This allows teachers to design digital curricula and integrate them with audio and video media, with the possibility of self-assessment. Next also provides an educational cloud platform for modern workplaces, where employers can design customizable learning systems with applications, simulations, virtual courses, self-assessments, video conferencing, and other tools [44].

2.

Smart Learning:

Given the importance of smart learning, programmers have made great efforts to innovate numerous models and fields, including adaptive learning, intelligent agents, expert systems, automatic learning, and other smart learning systems that possess significant capabilities and potential to serve the field of education. In this regard, a study by [45] concluded that an artificial intelligence-based teaching system was effective in developing a deep understanding of nuclear reactions and the ability to self-learn among secondary school students.

3.

Chat GPT:

Chat GPT is an artificial intelligence-powered chatbot created by OpenAI, a non-profit company. It was released on 30 November 2022. Less than a week after its launch, OpenAI founder Sam Altman announced that the number of users had surpassed one million. What distinguishes Chat GPT is its ability to mimic humans through conversation and rapid conversational responses via a free and easy-to-use web interface. Therefore, Chat GPT will become a part of our daily lives.

The study in [46] explored the impact of artificial intelligence applications—specifically chatbots—on language teaching and learning. Students engaged in a series of activities, including converting text to audio, and later provided feedback. The findings indicated that chatbots are effective tools in supporting language acquisition. The same study also presented a comprehensive analysis of the user experience with ChatGPT and its implications for education. It emphasized that learning tasks and activities should be designed to incorporate AI in ways that foster critical and creative thinking, as well as problem-solving skills relevant to real-world contexts.

Similarly, [47] found that ChatGPT can serve as a valuable support tool for both teachers and students, particularly within flipped classroom environments. Students are encouraged to use ChatGPT to prepare for lessons, thereby saving time and effort for both parties. The study also highlighted ChatGPT’s potential as a virtual teacher—capable of answering questions, summarizing information, facilitating collaboration and content creation, and offering immediate feedback. As a result, the study recommended training both educators and learners in the effective use of ChatGPT and stressed the importance of verifying information obtained through online interactions to uphold academic integrity.

The global adoption of generative AI platforms in education could lead to significant changes in the teaching and learning processes. Generative AI and its various applications represent one of the methods that can help determine what learners can and cannot do. Generative AI platforms can also design adaptive online content and intelligently deliver it to learners according to their abilities and needs. Generative AI platforms then help identify each learner’s capabilities and provide assistance and clarification for any areas they do not understand. As a result, AI platforms can help develop learners’ various capabilities with high efficiency.

6.3. Green Digital Entrepreneurship

Since the launch of the technology revolution in the contemporary world, life has witnessed significant and astonishing changes across all areas of life. The field of education has garnered the lion’s share of these positive changes. It has adopted new approaches that have overcome traditional methods based on rote learning and indoctrination, which are now far removed from the developments of the digital and technological world and the applications of artificial intelligence. These have produced applications and devices that support new horizons, embracing the concept of self-learning and supporting learning based on creativity, innovation, and entrepreneurship. This has enriched students’ educational journey toward a digital future where there is no place for the traditional learner and the teacher who instructs [48].

As emphasized in [49], there is an urgent need to foster entrepreneurial skills among students enrolled in courses delivered through smart electronic platforms. To achieve this, such courses must be designed with a strong emphasis on interaction to promote effective student participation, engagement, and leadership. Digital engagement and leadership are considered key strategies for mitigating student burnout, which tends to be 10–20% higher in distance learning environments compared to traditional classrooms. Therefore, educators and instructional designers using smart platforms should carefully select content and structure activities in ways that empower students to take active leadership roles in their learning.

The Fourth Industrial Revolution, artificial intelligence, and its various applications will have a clear impact on the future job market. Some jobs will disappear, while others will emerge. This requires anticipating the future and preparing for it through knowledge, experience, and ongoing discussions. The wording of academic degree advertisements will soon change. Instead of specifications stating, “holding a certain degree with a certain grade and a certain number of years of experience,” the specifications will become a list of skills that will be tested. If they possess these skills, they will be accepted for the job, regardless of the degree they hold. Therefore, universities will face further challenges in developing the educational process so that university degrees have real value. Therefore, academic institutions must focus on updating educational content to align with artificial intelligence applications and labor market requirements [50].

The digital skills required by the labor market today are advanced digital skills, such as computer programming, artificial intelligence, big data, encryption, cybersecurity, the Internet of Things, mobile application development, and advanced design software. The labor market is likely to receive more graduates with such advanced digital skills in the coming years [51].

Study [52] highlighted several technical activities linked to technological innovation, with artificial intelligence and expert systems being among the most significant. The advancement of AI technologies, particularly those rooted in computer science, and their integration into education, plays a vital and effective role in enhancing the quality and efficiency of the educational process. Artificial intelligence applications can produce educational and training programs capable of interacting and engaging with the learner and their environment, as well as electronic platforms and innovation. Innovation is one of the most important functions of electronic platforms. The shift from the production undertaken by the research team to a broader horizon is achieved by opening up resources, utilizing them efficiently, and being open to innovation. Platforms are a system that can be adapted to needs and outlets that the original designers do not have to consider. Therefore, platforms advance towards creativity and innovation [53].

Given the importance of digital leadership in the current era, study [54] concluded that digital leadership plays a key role in achieving institutional excellence and in enhancing the production of pioneering digital solutions that meet labor market needs. In a related context, [55] explained that the philosophy of green e-entrepreneurship centers on identifying and seizing available opportunities, transforming them into ventures that offer value—whether material, cultural, or social—through creativity, innovation, and calculated risk-taking. This philosophy is closely tied to technological progress, particularly the rise of artificial intelligence platforms and the growing shift of educational institutions toward smart digital transformation.

6.4. This Research Is Distinguished

What distinguishes the present research is its pioneering approach in empirically combining both interactive metaverse environments and generative artificial intelligence (GAI) tools within a unified instructional design aimed at fostering green digital entrepreneurship among postgraduate students. Unlike previous studies that tend to explore each technology in isolation—often focusing either on immersive environments or on AI-powered tools—this research offers a comprehensive educational experience by integrating both dimensions into a single, structured intervention. This dual approach allowed for the creation of a dynamic and student-centered learning environment that enhances creativity, innovation, and sustainability awareness.

Moreover, to the best of our knowledge, this is one of the first research efforts in the context of higher education to utilize specific platforms such as FrameVR for metaverse interaction, alongside ChatGPT, Elai.io, and Tome.app as generative AI tools, all applied in a pedagogical model targeting the development of green digital economy skills. This innovative combination not only fills a clear gap in the existing literature but also aligns with current global priorities calling for the integration of advanced technologies to achieve educational sustainability and entrepreneurial empowerment. Thus, the research contributes both theoretically and practically to digital and green education.

7. Methods and Procedures

7.1. Research Methodology

The current research used a quasi-experimental approach based on a single-group design with pre- and post-test performance measures.

7.2. Research Procedures

To identify the impact of the interactive metaverse environment and generative artificial intelligence on promoting the green digital economy and green e-entrepreneurship among King Khalid University students, Figure 3 shows the steps of the search procedure.

7.2.1. Selecting the Research Sample

The research sample was intentionally selected from graduate students at the College of Education, King Khalid University. The sample consisted of 25 students who were taught the “Computers in Education” course using the integration of the interactive 3D metaverse environment (https://framevr.io) and generative artificial intelligence (https://poe.com/).

7.2.2. Preparing Research Materials

Designing a Learning Environment Based on the Integration of Metaverse Technology and Generative Artificial Intelligence:

To design a learning environment based on an interactive metaverse environment and generative artificial intelligence, previous studies were reviewed, such as the [56] study and the [32] study. The general ADDIE design model was followed as below:

Phase 1: Analysis: In this phase, the following procedures were carried out:

• Defining the general objectives of the training environment based on the integration of an interactive metaverse environment and generative artificial intelligence platforms. The overall objective of this environment is to promote the green digital economy and green e-entrepreneurship.
• Defining Learner Characteristics: Graduate students at the College of Education, King Khalid University, are studying the “Computers in Education—474 Approaches-2” course in the first semester of the academic year (2023). They come from a similar environment with similar conditions, and their skills in using computers and the internet are almost identical. The research group comprised 25 students.
• Educational environment capabilities: the metaverse platform (https://framevr.io) and the generative artificial intelligence platform (https://poe.com) were used.
• Educational material: The educational content was defined as five educational topics in the “Computers in Education” subject.

Phase 2: Design Phase:

The design phase included defining the operational objectives for the learning environment based on the integration of the interactive metaverse environment and generative artificial intelligence platforms, and developing a comprehensive vision for the content, learning strategy, various appropriate activities, and assessment methods, as follows:

A. Operational objectives for the learning environment based on the integration of the metaverse and generative artificial intelligence:

• The first topic, “Computer Software,” covers the basics of understanding software and its types. It aims to enable students, upon completion, to discuss the nature of software and differentiate between its various types, with a focus on application software. Students are also expected to be able to compare these software programs in terms of function and use, and to acquire the skill of designing a professional presentation using modern digital tools that creatively reflect their understanding of the theoretical content.
• The second topic, “Computer Uses,” focuses on exploring the roles of computers in the educational process. It aims to enable students to clarify the various uses of computers in education and discuss the patterns of their employment in the classroom and virtual environments. The student is also expected to acquire the ability to use available electronic content authoring tools and employ them to design interactive electronic content that supports active learning and enhances the student’s digital experience.
• The third topic, “Electronic Mind Maps,” addresses the concept of mind maps in their digital form. It aims to enable the student to discuss the nature of these maps and explain their importance in organizing ideas and enhancing the visual understanding of content. The student is also expected to develop their technical skills by designing an electronic mind map using specialized tools and to be able to publish and share it in electronic learning environments that support collaboration and interactive learning.
• The fourth topic, “The Internet and Education,” addresses the basics of internet technology and its relationship to digital education. Upon completion of this topic, the student is expected to be able to accurately define the internet and differentiate between the concepts of the internet, the intranet, and the web in terms of structure and uses. They are also expected to discuss the most important services the internet provides to support education, such as e-learning, synchronous and asynchronous learning, and access to knowledge resources. On the practical side, students must acquire the ability to design an interactive educational website that utilizes their learning to support the educational process in a creative and comprehensive manner.
• The fifth topic, “e-Learning,” focuses on understanding the theoretical and practical foundations of this type of education. It aims to enable students to discuss the nature of e-learning as a modern method of education based on digital technology. Students are also expected to be able to differentiate between its various types, such as synchronous and asynchronous learning, self-paced learning, and blended learning. They are also expected to clarify the importance of e-learning in expanding access to education and achieving flexibility in learning. On the practical level, students are required to design a professional interactive video employing appropriate digital tools that reflect their understanding of the content and contribute to enhancing the e-learning experience.

B. Learning Environment Content:

The learning environment content, based on the integration of metaverse technology and generative artificial intelligence, included the following topics:

• Topic 1: Computer Software
• Topic 2: Computer Uses
• Topic 3: Electronic Mind Maps
• Topic 4: The Internet and Education
• Topic 5: e-Learning

C. Learning strategy and activities followed in the metaverse environment and generative artificial intelligence:

In light of the procedural objectives and content of the learning environment, the learning strategy using metaverse technology and generative artificial intelligence proceeded according to the flowchart shown in Figure 4.

D. Assessment Methods:

Assessment methods varied, including pre-assessment at the beginning of each subject to assess prior learning, formative assessment throughout each course to guide student learning and provide feedback, and summative assessment, which is conducted after completing the entire educational content designed using metaverse technology and generative artificial intelligence. This assessment aims to enhance the green digital economy and develop the green e-entrepreneurship skills of the research sample.

Phase 3: Development:

In this phase, researchers used a range of artificial intelligence platforms and modern technologies to support the digital learning environment and provide integrated and interactive educational content. The FrameVR.io platform was used to create a 3D virtual metaverse environment that simulates classrooms and allows students to interact live within an immersive digital learning space, as shown in Figure 5. The ChatGPT model was also deployed via Poe.com to support intelligent communication and generate instant text content. On the media side, Elai.io was used to produce professional educational videos, and Tome.app was used to design high-quality presentations. In the field of visual thinking, the Whimsical.com platform was used to design electronic mind maps that help organize educational concepts. Images were also converted into interactive videos using D-ID, professional educational websites were designed via Durable.co, and integrated educational lessons were created using Tutor AI. This technological integration helped promote sustainable education practices and green e-entrepreneurship.

Phase 4: Implementation Phase:

In this phase, the electronic content of the “Computers in Education” course was implemented using the metaverse environment and generative artificial intelligence for 25 users. The learning environment and the tasks required were explained.

Phase 5: Evaluation Phase:

In this phase, the training content was presented to a group of specialists in the field of educational technology and information technology. Measurement tools were also applied, including the Green Digital Economy Scale, the e-Entrepreneurship Scale, and the Entrepreneurial Digital Product Evaluation Card, after studying all the educational content of the research group’s students.

7.3. Preparing Research Tools

Green Digital Economy Scale:

The Green Digital Economy Scale was prepared according to the following steps:

A.

Defining the Scale’s Objective:

The scale aimed to measure the green digital economy skills of graduate students at the College of Education, King Khalid University. After reviewing a number of studies, such as the study by [57] and the study by [9], the dimensions of this scale were determined, consisting of four dimensions: digital technology, digital transformation, continuous digital learning, and digital sustainability.

B.

Scale Items:

The scale consisted of four dimensions: the digital technology dimension, with nine statements; the digital transformation dimension, with nine statements; the continuous digital learning dimension, with eight statements; and the digital sustainability dimension, with eight statements. Thus, the total number of statements in the scale reached 34 statements.

C.

Refining the scale by:

Presenting the initial version of the scale to a group of judges: After the formulation of the scale’s vocabulary was completed, it was presented to a group of specialists in the fields of technology, business administration, and psychology. Their opinions clarified the scale’s suitability for the purpose for which it was developed, with the deletion of some phrases in the fifth dimension and the linguistic rewording of some phrases.

• Exploratory application of the scale: The scale was applied to a pilot sample of 16 graduate students at the College of Education, King Khalid University, to determine the linguistic and scientific suitability of the statements. Their responses demonstrated the linguistic and scientific suitability of the scale statements.
• Internal consistency of the scale:

A Pearson correlation coefficient matrix was created between the scale dimensions and the total score according to

Table 1. Pearson’s correlation coefficient matrix between the scale dimensions and the total score.

Dimension	Digital Technology	Digital Transformation	Continuous Digital Learning	Digital Sustainability
Digital technology	1
Digital transformation	0.41	1
Continuous digital learning	0.38	0.70 **	1
Digital sustainability	0.52 *	0.66 *	0.75 **	1
The scale as a whole	0.69 *	0.88 **	0.76 **	0.78 **

* significant at the 0.05 level and ** significant at the 0.01 level.

.

It is clear from the above that the correlation coefficient of the first dimension with the scale as a whole is 0.69, the correlation coefficient of the second dimension with the scale as a whole is 0.88, the correlation coefficient of the third dimension with the scale as a whole is 0.76, and the correlation coefficient of the fourth dimension with the scale as a whole is 0.78. All of these values are statistically significant and acceptable. This indicates that the scale dimensions measure the same thing as the scale as a whole, demonstrating the validity of the scale and its dimensions.

Calculating the Average Scale Time: The scale time was calculated by finding the average of all students’ times, each according to their speed, and it was approximately 40 minutes.

Calculating the Reliability of the Scale Scores: The reliability of the scale scores was calculated using Cronbach’s alpha equation and was found to be approximately 0.79, which is an appropriate reliability coefficient.

D.

Final Form of the Scale: After formulating the scale and statistically adjusting it, the scale became valid for final application.

Green e-Entrepreneurship Scale:

The Green e-Entrepreneurship Scale was developed according to the following steps:

A.

Defining the Scale’s Objective:

The scale aimed to measure the green e-entrepreneurship skills of graduate students at the College of Education, King Khalid University. After reviewing a number of studies, such as the study by [19] and the study by [18], the dimensions of this scale were determined, consisting of five dimensions: proactive behavior, preference for innovation, self-efficacy, achievement motivation, and non-conformity.

B.

Scale Items:

The scale consisted of five dimensions: the proactive behavior dimension, which comprises seven statements; the preference for innovation dimension, which comprises seven statements; the self-efficacy dimension, which comprises six statements; the achievement motivation dimension, which comprises six statements; the non-conformity dimension, which comprises six statements; and the digital vitality dimension, which comprises eight statements. Thus, the total number of statements in the scale was 40.

C.

Scale adjustment through:

Presenting the initial version of the scale to a group of arbitrators. After completing the formulation of the scale’s vocabulary, it was presented to a group of specialists in the fields of educational technology, business administration, and psychology. Their opinions clarified the scale’s suitability for the purpose for which it was developed, with the deletion of some phrases in the third dimension and the linguistic rewording of some phrases.

Exploratory application of the scale: The scale was applied to a pilot sample of 16 graduate students at the College of Education, King Khalid University, to determine the linguistic and scientific suitability of the phrases. Their responses clarified the linguistic and scientific suitability of the scale’s phrases.

D.

Internal consistency of the scale:

A Pearson correlation coefficient matrix was created between the scale’s dimensions and the total score according to

Table 2. Pearson’s correlation coefficient matrix between the scale dimensions and the total score.

Dimension	Proactive Action	Preferring Innovation	Self-Efficacy	Achievement Motivation	Non-Conformity	Digital Vitality
Proactive action	1
Preferring innovation	0.38	1
Self-efficacy	0.26	0.74 **	1
Achievement motivation	0.31	0.61 *	0.46	1
Non-conformity	0.44	0.47	0.39	0.43	1
Digital Vitality	0.34	0.52 *	0.62	0.47	0.42	1
The scale as a whole	0.65	0.88 **	0.79 **	0.77 **	0.69 **	0.82 **

* significant at the 0.05 level and ** significant at the 0.01 level.

.

It is clear from the above that the correlation coefficient of the first dimension with the scale as a whole is 0.65, the correlation coefficient of the second dimension with the scale as a whole is 0.88, the correlation coefficient of the third dimension with the scale as a whole is 0.79, the correlation coefficient of the fourth dimension with the scale as a whole is 0.77, the correlation coefficient of the fifth dimension with the scale as a whole is 0.69, and the correlation coefficient of the sixth dimension with the scale as a whole is 0.82. All of these are statistically significant and acceptable values. This indicates that the scale dimensions measure the same thing as the scale as a whole, demonstrating the validity of the scale and its dimensions.

Calculating the average time for the scale: The time for the scale was calculated by finding the average time of all students, each according to their speed, and it came out to be approximately 40 min.

Calculating the reliability of the scale scores: The reliability of the scale scores was calculated using Cronbach’s alpha equation, and it was found to be approximately 0.86, which is an appropriate reliability coefficient.

E.

Final Form of the Scale: After formulating the scale and statistically adjusting it, the scale became valid for final application.

Preparing a Product Evaluation Card:

This card was prepared according to the following steps:

A.

Objective of the Card:

The card aimed to evaluate the pioneering green digital product designed by graduate students at the College of Education, King Khalid University, in the “Computers in Education—474 Approach-2” course.

B.

Card Paragraphs:

After reviewing research and studies focused on the field of e-entrepreneurship, the card’s main paragraphs, totaling 15 were identified. These paragraphs varied between the general appearance of the product, its connection to solving a societal problem, the scarcity of this product in society, its compatibility with all mobile devices and all internet browsers, and its ease of use by the user.

C.

Presenting the initial version of the card to a group of judges:

After completing the card’s preparation, it was presented to a group of specialists in the fields of information technology, educational technology, and psychology. Their opinions clarified the card’s suitability for the research sample, with some paragraphs being reworded and the ninth paragraph being deleted.

D.

Exploratory Application of the Card:

After obtaining the opinions of the arbitrators, the card was applied to a pilot sample of 16 graduate students at the College of Education, King Khalid University, to determine the validity of the card’s linguistic formulation and its suitability for the students, as well as to calculate its reliability.

E.

Calculating the Card’s Scores:

After presenting the card to a group of expert judges in this field from King Saud University and King Khalid University and testing it on 16 male and female graduate students at the College of Education at King Khalid University, the card’s stability was calculated using Cooper’s equation, and it was found to be close to 0.94, which is an appropriate percentage for the card’s stability.

F.

Final Form of the Card:

After drafting the card, presenting it to a group of arbitrators, and statistically adjusting it, the card was ready for final application.

Pre-application of Measurement Tools:

The measurement tools, represented by the observation card, the knowledge economy skills scale, and the digital confidence building scale, were applied to the study group.

Implementing the Research Experiment:

After clarifying the purpose of the experiment, the researcher implemented the research experiment during the first semester of 2024 at the College of Education over a period of approximately 7 weeks. The research group consisted of 25 students who were taught the “Computers in Education” course using an integrated 3D Metaverse environment (https://framevr.io) and generative artificial intelligence (https://poe.com/).

Post-application of measurement tools:

After completing the research experiment, the measurement tools, namely: the Green Digital Economy Scale, the green e-Entrepreneurship Scale, and the Green Digital Product Evaluation Card, were applied pre- and post-tested to the two research groups, corrected, and monitored.

8. Research Results and Discussion

After monitoring students’ scores in the pre- and post-tests on the Green Digital Economy Scale, the green e-Entrepreneurship Scale, and the Green Digital Entrepreneurship Product Scorecard in the “Computers in Education” course, the research questions were answered as follows:

The first question stated: What is the impact of integrating the interactive metaverse environment and generative artificial intelligence on promoting the green digital economy in the “Computers in Education” course for graduate students?

To answer this question, the following hypothesis was formulated: There is a statistically significant difference at the 0.05 level between the average scores of the pre-test and post-test on the Green Digital Economy Scale in the “Computers in Education” course for graduate students, in favor of the post-test.

To test the validity of this hypothesis, statistical analysis was performed using the Wilcoxon test for two related samples to compare the scores of the Green Digital Economy Scale in the pre- and post-tests.

Table 3. Wilcoxon test results on the Green Digital Economy scale in the pre- and post-tests.

The Tool	Application	N	Average Rank	Total Ranks	Z-Value	Significance Level	Significance
Green Digital Economy Barometer	Pre	23	0.00	0.00	−4.581 **	0.001	Significance
	Post	23	12.00	23.00

** significant at the 0.01 level.

shows the results of the Z-test for the significance of the difference between the pre- and post-test scores on the Green Digital Economy scale in the “Computers in Education” course.

Table 3 shows that the calculated z-value (−4.581) on the Green Digital Economy Scale is significant at the 0.05 level, indicating a statistically significant difference between the pre- and post-tests of the Green Digital Economy Scale, in favor of the higher average scores, i.e., the pre-test. Thus, the Hypothesis 1 of the research was accepted, which stated that there is a statistically significant difference at the 0.05 level between the average scores of the pre-tests and post-tests on the Green Digital Economy Scale among graduate students, in favor of the post-tests. The researchers believe that the previous result can be attributed to the following:

The FrameVR interactive 3D platform (https://framevr.io) facilitated student learning by providing an immersive virtual learning environment that helped them overcome difficult and incomprehensible parts of the “Computers in Education” course content. This environment provided a visual and experiential approach that enabled students to interact with educational concepts directly and personally. This platform created a personalized learning environment for each student, allowing them to explore content based on their individual needs, enhancing their understanding and comprehension. Thanks to its user-friendly nature, students were able to navigate the educational environment without technical difficulties, contributing to enhanced engagement and motivation toward self-learning.

In parallel, generative AI platforms, most notably Poe, the platform for running ChatGPT (https://poe.com), helped students pose their inquiries and receive immediate AI-powered responses, helping consolidate and apply knowledge. This integration between the metaverse and generative AI has been reflected in promoting the concepts of a green digital economy by developing students’ technical skills and encouraging them to design sustainable digital learning solutions.

The educational philosophy of FrameVR’s interactive platform (https://framevr.io) and generative AI platform is based on the principle of deep content learning. These platforms provide a digital environment powered by big data that allows students to access information from multiple sources and in a variety of ways that suit their individual needs. The function of these platforms is not limited to providing information only, but they also pose directed questions to enhance critical thinking and in-depth understanding of the content, motivating students to reformulate knowledge and apply it in new situations. This integration of virtual reality technologies and smart interaction has directly contributed to enhancing the concept of the green digital economy among graduate students, by developing their abilities to use technology to produce sustainable digital educational solutions within the context of the “Computers in Education” course. This is illustrated in Figure 6.

The second question stated: What is the impact of the integration of the interactive metaverse environment and generative artificial intelligence on green e-entrepreneurship in the “Computers in Education” course for graduate students?

To test the validity of this hypothesis, statistical processing was performed using the Wilcoxon test for two related samples to compare the scores on the green e-entrepreneurship scale in the pre- and post-tests.

Table 4. Wilcoxon test results on the e-Entrepreneurship Scale in the pre- and post-tests.

The Tool	Application	N	Average Rank	Total Ranks	Z-Value	Significance Level	Significance
Green e-Entrepreneurship Scale	Pre	23	0.00	0.00	−4.214 **	0.001	Significance
	Post	23	12.00	23.00

** significant at the 0.01 level.

shows the results of the Z-test to show the significance of the difference between the pre-test and post-test scores on the green e-entrepreneurship scale in the “Computers in Education” course.

Table 4 shows that the calculated Z-value (−4.214) on the green e-Entrepreneurship Scale is significant at the 0.05 level, indicating a statistically significant difference between the pre- and post-test of the green e-Entrepreneurship Scale, in favor of the higher average scores, i.e., the pre-test.

Thus, the Hypothesis 2 of the research was accepted, which stated that there is a statistically significant difference at the 0.05 level between the average scores of the pre-test and post-test on the green e-Entrepreneurship Scale among graduate students, in favor of the post-test. The researchers believe that the previous result can be attributed to the following:

The FrameVR interactive platform provides a set of digital tools that give students complete freedom to edit content, whether by adding or deleting, which enhances their sense of intellectual ownership of the educational content they produce. Students can also benefit from generative artificial intelligence platforms to verify the validity of new content and develop it creatively, reflecting their deep understanding of the educational material. The added value of this digital environment lies in the intellectual fluency it provides. Generative AI platforms provide a fertile environment for generating and sharing ideas, allowing students to learn from their peers’ experiences and ideas and adopt best practices. Through this ongoing cognitive interaction, graduate students have been able to develop their digital fluency and computational innovation skills, which have positively impacted their academic performance and their ability to employ technology in sustainable and creative educational contexts.

Generative AI platforms are fertile environments for generating and sharing entrepreneurial ideas. They are characterized by their ability to propose diverse and interconnected ideas on research topics, allowing students to expand their thinking horizons, pose new questions about these ideas, and discuss them within the platform itself or with colleagues. This intelligent cognitive interaction has helped generate a number of green digital initiatives and projects and has contributed significantly to the development of green digital entrepreneurship skills among the research sample students. In the same context, the FrameVR interactive platform provided students with a high level of freedom and flexibility to carry out educational tasks and activities within an easy-to-use 3D environment. This helped improve their engagement with content and enhance their ability to achieve and innovate within a modern and sustainable digital learning environment.

The ease of use of generative AI platforms contributed to increasing students’ motivation to learn, providing an encouraging interactive environment that enabled them to explore educational content in flexible and personalized ways. This contributed to fostering innovative and entrepreneurial tendencies within the “Computers in Education” course. These platforms were distinguished by their high ability to analyze and evaluate students’ responses in real-time, enabling the identification and remediation of individual weaknesses while enhancing each learner’s strengths. These platforms also provided diverse and rich sources of ideas and information, which helped develop students’ intellectual fluency and broaden their horizons toward creative solutions. This helped develop green digital entrepreneurial skills that keep pace with the requirements of a sustainable digital economy.

The third question stated: What is the impact of the integration of the interactive metaverse environment and generative artificial intelligence on the production of a green digital entrepreneurial product in the “Computers in Education” course for graduate students?

To answer this question, the following hypothesis was formulated: There is a statistically significant difference at the 0.05 level between the average pre- and post-application ranks on the green digital entrepreneurial product evaluation card in the “Computers in Education” course for graduate students, in favor of the post-application. To test the validity of this hypothesis, statistical processing was performed using the Wilcoxon test for two related samples to compare the scores of the green digital entrepreneurial product evaluation card application in the pre- and post-application.

Table 5. Wilcoxon test results on the green digital entrepreneurial product evaluation card in the pre- and post-application.

The Tool	Application	N	Average Rank	Total Ranks	Z-Value	Significance Level	Significance
Green Digital Entrepreneurship Product Scorecard	Pre	23	0.00	0.00	−4.002 **	0.001	Significance
	Post	23	12.00	276.00

** significant at the 0.01 level.

shows the results of the Z-test to indicate the significance of the difference between the pre- and post-application ranks of the observation card in the “Computers in Education” course.

Table 5 shows that the calculated Z-value (−4.002) on the Green Digital Entrepreneurship Product Evaluation Card is significant at the 0.05 level, indicating a statistically significant difference between the pre- and post-application of the Green Digital Entrepreneurship Product Evaluation Card, in favor of the higher average ranks, i.e., the pre-application. Thus, the Hypothesis 3 of the research was accepted, which stated that there is a statistically significant difference at the 0.05 level between the average ranks of the pre-application and post-application of the Green Digital Entrepreneurship Product Evaluation Card among graduate students, in favor of the post-application. The researchers believe that the previous result can be attributed to the following:

The FrameVR interactive platform (https://framevr.io) provided a set of advanced 3D tools that facilitated the process of sharing ideas among students within a dynamic virtual learning environment. This enabled learners to collaborate on complex educational problems and simplified any obstacles that might hinder their understanding of the content. This virtual environment also provided visual and experiential simulations that enhanced students’ ability to grasp abstract concepts. At the same time, generative AI platforms provided precise, easy-to-use, and intelligently designed tools that enabled students to produce creative digital content that reflects their understanding of the curriculum and contributes to the formation of pioneering, green, and sustainable digital products. This was clearly reflected in the learning outcomes of graduate students, by improving the quality of their digital production and developing their innovative capabilities in advanced technology-based educational environments.

Generative AI platforms provide a variety of tools designed to respond immediately to learners’ inquiries, enabling them to complete digital tasks with high accuracy and in record time. This helped accelerate the learning process and achieve effective results in producing quality digital content. In the same vein, the interactive metaverse environment, delivered through the FrameVR platform, provided a collaborative and interactive learning experience for all students, enabling them to work within collaborative teams without any pressure or restrictions, fostering a spirit of participation and facilitating the exchange of experiences. This positive interaction between students within the digital environment has honed their technical and creative skills, resulting in the production of pioneering, green digital computing businesses characterized by innovation and sustainability.

8.1. Practical Significance of the Research Results

Through Table 3, Table 4 and Table 5, it was possible to determine the practical or applied significance of the research results by finding the magnitude of the effect of the independent variable on the dependent variables.

Table 6. Scientific and applied significance of the research results.

Independent Variable	Dependent Variable	Z-Value	η2 Eta Square	Effect Size
Interactive Metaverse Environment and Generative AI Platforms	Green Digital Economy	−4.581	0.96	Big
	Green e-entrepreneurship	−4.214	0.87	Big
	Green digital products	−4.002	0.83	Big

illustrates the scientific and applied significance of the study’s findings by reporting both statistical significance (Z-values) and practical significance (Eta squared effect sizes). The Z-values confirm that the differences between pre- and post-test scores across all dependent variables are statistically significant at p < 0.05. However, beyond statistical confirmation, the effect sizes—represented by Eta squared (η²)—offer insight into the magnitude of the intervention’s impact, which is critical for understanding its real-world educational implications.

• Green Digital Economy (η² = 0.96):

The integration of the interactive metaverse environment and generative AI platforms had a very strong effect on promoting the green digital economy. An Eta squared value of 0.96 indicates that 96% of the variance in students’ improvement in green digital economy awareness and competencies can be attributed to the educational intervention. This is a remarkably high value, suggesting that the combination of immersive virtual experiences and AI-enhanced tools plays a transformative role in helping learners understand, internalize, and apply sustainability-oriented economic practices. The remaining 4% of variance could be explained by external factors such as prior technological proficiency, peer interaction, or learning motivation.

• Green e-Entrepreneurship (η² = 0.87):

The effect size here also reflects a strong practical impact. An η² of 0.87 means that 87% of the development in green e-entrepreneurial skills—such as innovation, proactive problem solving, and sustainability-focused business ideation—can be directly linked to the instructional model. This finding underscores the effectiveness of combining generative AI platforms (such as ChatGPT and Elai.io) with immersive digital learning environments (like FrameVR) in fostering not just cognitive understanding but also entrepreneurial agency and innovation among students.

• Green Digital Products (η² = 0.83):

The intervention also showed a large effect on students’ ability to design and produce digital products with sustainable value. An Eta squared of 0.83 implies that 83% of the improvement in the quality and innovation of student-generated digital outputs can be attributed to the use of AI-enhanced design tools and virtual collaboration platforms. This suggests that the educational model not only supported theoretical knowledge but also translated into practical digital competencies that are directly applicable to real-world challenges in sustainability and entrepreneurship.

• Overall Interpretation:

All three effect sizes fall well within the range considered “large” by conventional standards (Cohen’s benchmark: η² > 0.14 for large effects), indicating that the research intervention had a substantial educational impact. These findings validate the pedagogical potential of combining interactive metaverse technologies with generative AI in advancing sustainable education goals—particularly in higher education contexts that aim to integrate digital transformation with environmental responsibility. This is evident in Figure 7.

8.2. Discussion of Research Results

The current research aimed to enhance the skills of the green digital economy and green e-entrepreneurship among university students in the “Computers in Education” course for graduate students at the College of Education, King Khalid University. This was achieved by designing a training environment based on the integration of an interactive metaverse environment and generative artificial intelligence. The research questions were as follows:

What is the impact of the integration of an interactive metaverse environment and generative artificial intelligence on promoting the green digital economy among graduate students? The results showed a statistically significant difference between the average scores of the pre- and post-applications on the green digital economy scale for graduate students, in favor of the post-application. This indicates that students have greatly benefited from the metaverse environment and its integration with generative artificial intelligence technology in promoting the green digital economy. This may be due to the interactive 3D metaverse environment (https://framevr.io) and generative AI technology. These include an easy-to-use and interactive 3D user interface, as well as responsive tools through which learners can quickly and accurately access information. They can also share this information with others for discussion and interaction, thus gaining valuable insights that have helped graduate students enhance their digital economy. This result is consistent with the findings of [56,57].

What is the impact of the integration of the interactive metaverse environment and generative AI on green e-entrepreneurship among graduate students? The results showed a statistically significant difference between the average scores of the pre- and post-applications on the green e-Entrepreneurship Scale for graduate students, in favor of the post-application. This indicates that graduate students have benefited significantly from the interactive metaverse environment and generative AI technology. This may be due to the interactive metaverse environment (https://framevr.io) and generative AI technology, which allow students freedom and flexibility, enabling them to freely generate and exchange creative ideas with others. Through this environment and its integration with big data AI technology, students were open to and benefited from others’ ideas, thus gaining access to new ideas and knowledge. This contributed to the development of green e-entrepreneurship skills among graduate students. This result is consistent with the findings of [16,18].

What is the impact of the integration of the interactive metaverse environment and generative AI on the production of a green digital entrepreneurial product among graduate students? The results showed a statistically significant difference between the average scores of the pre-application and post-application on the green digital entrepreneurial product assessment card for graduate students, in favor of the post-application. This means that graduate students have greatly benefited from the integration of the interactive metaverse environment and generative AI technology. This may be due to the fact that the interactive metaverse environment (https://framevr.io) and generative AI technology provide students with easy-to-use tools that offer a high degree of precision, design, and innovation. This has helped graduate students produce pioneering digital products, such as the https://designs.ai/ platform. This platform allows students to produce logos, videos, banners, and other content quickly and efficiently. This finding is consistent with the results of [39,51] studies.

In interpreting the results of this research, it is important to acknowledge that while the findings show statistically and practically significant improvements across the target dimensions, other contextual factors may have contributed to these outcomes. For example, students’ prior familiarity with digital platforms, their intrinsic motivation to engage with emerging technologies, or even peer interaction dynamics could have played a role in shaping the observed effects. While the integration of metaverse environments and generative AI tools appears to be effective, further research is needed to isolate their specific contributions in more controlled settings. Acknowledging these alternative interpretations provides a more nuanced and rigorous understanding of the findings and supports the development of more generalizable educational models.

The findings of this research offer valuable implications for higher education policy and strategic planning, particularly in light of global shifts toward sustainability and digital transformation. Institutions seeking to align with the Sustainable Development Goals (SDGs), particularly SDG 4 (Quality Education) and SDG 9 (Industry, Innovation, and Infrastructure), should consider adopting policy frameworks that effectively promote the integration of advanced technologies—such as the metaverse and generative AI—into academic programs. These tools not only enhance student engagement and innovation but also support the development of future-ready green competencies and entrepreneurial skills. Thus, university leaders and policymakers are encouraged to invest in digital infrastructure, faculty development, and interdisciplinary initiatives that embody sustainability, technology, and education.

From a curriculum and pedagogy perspective, the research emphasizes the importance of rethinking traditional course designs to include technology-enhanced experiential learning models. Integrating green digital entrepreneurship as a core learning outcome enables students to engage in finding solutions to real-world environmental challenges using immersive AI-powered platforms. This requires flexible curricula that blend theoretical foundations with applied digital tasks, encouraging students to transition from passive content consumption to active innovation. Educators should be supported in redesigning their teaching strategies to leverage virtual collaboration, AI-generated content creation, and sustainability-focused problem-solving, creating learning environments that are not only technologically advanced but also socially and environmentally responsible.

9. Conclusions

Amid the rapid digital transformations the world is witnessing, and in light of the environmental, educational, and economic challenges facing higher education institutions, the integration of interactive metaverse technologies and generative artificial intelligence (AI) is a pivotal step toward building more efficient and innovative learning environments. The results of this research demonstrate the importance of this integration in promoting the concepts of the green digital economy and developing sustainable e-entrepreneurship skills among graduate students. This innovative educational model provides students with the opportunity to interact within immersive 3D environments and utilize AI tools to produce digital content that reflects their creative abilities while simultaneously responding to the requirements of sustainable development. The study also revealed a clear gap in awareness and prior knowledge of these technologies among a large segment of students, calling for a revision of university curricula and the systematic and purposeful integration of these applications.

The future of university education cannot be separated from accelerating technological progress, and this research confirms that the integration of the metaverse and generative AI into education not only supports the achievement of educational objectives, but also contributes to green digital transformation and empowers students to actively participate in the knowledge economy. Therefore, the study recommends investing in training academic staff and students in the use of these technologies and developing educational policies that foster innovation and digital leadership. This approach will strengthen the future readiness of higher education institutions and position them at the forefront of efforts to achieve the Sustainable Development Goals—particularly Goal 4: Quality Education, which aims to ensure inclusive, equitable, and quality education for all and promote lifelong learning opportunities.

Goal 4: Quality Education.

Building on the findings of this research, several concrete directions are proposed for future work. First, it is recommended to replicate this study using larger and more diverse samples, including participants from different academic programs, institutions, and cultural contexts, to improve the generalizability and external validity of the results. Second, future research may explore the long-term effects of integrating interactive metaverse environments and generative AI tools on learners’ sustainability competencies, entrepreneurial attitudes, and digital behavior beyond the classroom. Third, researchers are encouraged to investigate the educational potential of emerging AI-powered and XR technologies, such as holographic simulations, adaptive learning algorithms, and multimodal intelligent agents, to further personalize the learning process and enhance the development of green digital entrepreneurship skills. These directions aim to extend the impact of this research and support the evolution of digitally empowered, sustainability-oriented educational models in higher education.

The conclusions drawn from this research are directly supported by the quantitative and qualitative data presented. The statistically significant improvements observed across all target variables demonstrate the potential of integrating interactive metaverse environments and generative AI platforms to support sustainability-driven entrepreneurial learning. However, these findings should be interpreted in light of certain contextual limitations, such as the restricted sample size and the specific institutional setting in which the research was conducted. Despite these constraints, the results have broader implications for curriculum design and higher education policy, particularly in promoting green digital competencies and advancing sustainable innovation through emerging technologies.