Providing K-12 students with proper science, technology, engineering, and math (STEM) education is important to ensuring an innovative and prosperous economy. A highly skilled STEM workforce can lead to increased productivity and competitiveness, which can lead to a host of new ideas being researched and developed. STEM workers make added-value products, build bridges and roads, and conduct lifesaving medical research, among other important activities. The use of virtual reality (VR) technology for both education and workforce training has grown in recent years. VR technology can accelerate these processes at maximum efficacy and minimum costs and can have a significant impact on productivity gains, earnings, new jobs, innovation through research and development, and high-growth industries. This paper presents the development of a series of VR modules using the Unity game engine, the HTC VIVE Pro VR headset, and the Hi5 VR glove for the purposes of K-12 STEM education. Specifically, these developed modules have been designed to instruct K-12 students on topics related to motion and heat, with future goals to expand the modules to cover topics related to light, magnetism, electricity, radioactivity, sound, and waves. This paper will cover the methodology and design considerations that went into developing these modules, with a focus on how these modules relate to various learning strategies as well as with existing research on the use of VR in K-12 education.

Virtual reality (VR) has emerged as a powerful tool for cultural heritage preservation; however, most existing VR museum studies rely on descriptive statistics for evaluation, lacking the predictive depth that data-driven approaches can offer. This paper addresses this gap by integrating machine learning (ML) techniques into the evaluation of a VR museum dedicated to traditional Jordanian women's clothing, focusing on Bedouin garments from Wadi Rum, Ma'an, and Petra. Seven historically accurate 3D costumes were reconstructed using Blender based on ethnographic references and expert consultations, integrated into a navigable museum environment in Unity, and deployed on the Meta Quest 2 headset. A total of 150 university students participated in the evaluation, providing demographic data and Likert-scale ratings across four experience dimensions: engagement, cultural understanding, navigation intuitiveness, and visual realism. Six ML classifiers, K-Nearest Neighbors, Support Vector Machine, Decision Tree, Random Forest, Naive Bayes, and Logistic Regression, were trained using 5-fold stratified cross-validation to predict user satisfaction. Logistic Regression achieved the best performance (accuracy: 84.67%, F1-score: 0.7884), while Decision Tree performed the lowest (accuracy: 71.33%, F1-score: 0.5947). Random Forest feature importance analysis revealed that cultural understanding (0.189), visual realism (0.173), and navigation (0.168) were the strongest predictors, whereas demographic factors such as gender (0.023) and prior VR experience (0.034) had minimal influence. K-Means clustering identified three distinct user profiles: Passive Observers (27.3%), and two Selective Explorer groups (39.3% and 33.3%) with divergent interaction patterns. These results demonstrate that ML can effectively predict and profile user satisfaction in VR heritage environments, offering data-driven insights for designing adaptive and personalized virtual museums.

The future of the Internet lies in the utilization of contemporary virtual technology, the metaverse is a virtual ecosystem for communication and interaction. This study aims to determine how the metaverse can enhance customer awareness, interest, engagement and experience. The study population consists of customers of retail clothing stores. A questionnaire was developed to collect study data and distribute it electronically. The number of respondents reached (77) customers. Using path coefficients, the results indicate that metaverse can enhance customer awareness, interest, engagement and experience.

As a potential treatment intervention for youngsters with Social Anxiety Disorder (SAD) in UAE, this study aims to investigate the use of virtual reality socialization groups on the widely used social media platform Facebook. The purpose of this research is to examine how social anxiety, sadness, and anxiety symptoms change after receiving treatment. The quantitative approach used in the study yields very small impact sizes. No discernible differences emerged, however, between the test and control groups at the statistical level. It investigates how cultural factors, including the unique social norms and expectations in UAE, play a crucial role in determining the success of interventions. Specifically adapted virtual reality therapies for various cultural settings are emphasized. In addition, it highlights the importance of understanding the therapeutic implications of small effect sizes. Prospective research directions are explored in this article; special attention is paid to the development of ever-better technologically-driven treatments across a variety of cultural settings.

Industries all throughout the world are preparing to understand the ramifications of the emerging metaverse, which is a merger of the virtual and physical worlds. Notably, the banking industry stands on the cusp of a monumental shift, with the metaverse offering unprecedented operational enhancements. While the potential transformations brought about by the metaverse are discussed in various sectors, there is a discernible gap in understanding its specific applications in banking, especially with respect to advanced technologies such as NFTs, blockchain, and smart contracts. The study adopts a comprehensive approach to bridge this knowledge gap, employing convenience non-probability sampling to engage 48 subject matter experts specializing in Metaverse-Enabled Innovation in Banking. Data was collected using both mailed and electronic questionnaires. The empirical analysis offers strong evidence supporting the pivotal role of technologies like Digital Twins, Artificial Intelligence, and Blockchain-Based Assets in the metaverse's preliminary stages. We discover a plethora of business potential for banks within the metaverse, including client communication, cross-border transactions, mortgages, digital assets, green loans, and data security.‎‎

This paper sought to test the impact of mixed reality technologies on student engagement in Kuwait universities. Physical reality, augmented reality, augmented virtuality, and virtual reality have been relied upon as mixed reality technologies. Moreover, behavioural, cognitive, and emotional engagement were used as measures of students' engagement according to self-determination theory. The data used in the analysis were received from 812 students in various disciplines in Kuwaiti universities with a response rate of 86.19%. Structural equation modeling (SEM) was the statistical approach used in data analysis. The results indicated varying relative importance levels for mixed reality techniques, although the relative importance level for students' engagement was high. Besides, all mixed reality technologies had a positive impact on students' engagement, with the highest impact of augmented reality and the lowest impact of augmented virtuality. This paper provided contributions to the development of an empirical approach based on new technologies to improve student engagement in developing country universities. Accordingly, the paper emphasized the need for Kuwaiti universities to invest in augmented reality technologies, for example, interactive screens and 3D mobile applications to increase students' exploratory ability.

Virtual reality (VR) is a new technology that has applications in a variety of sectors, including medical, education, gaming, psychology, and sociology. The application of VR in education is intriguing and warrants further examination, but research on the subject is currently restricted. VR can benefit education by allowing students to participate in memorable and engaging experiences that they would not otherwise be able to have. Traditional approaches are still used to teach students, which is an essential element of the curriculum for those who want to conceive problem-solving. As a result, there is a scarcity of study on VR deployment. In this paper, we investigated the factors affecting the adoption of VR in higher educational institutes. To this end, we extended the technology Acceptance Model (TAM) with four additional factors and formulated a set of hypotheses. The hypotheses are then evaluated using a dataset collected from 503 Jordanian students. The result shows that the factors perceived facilitating condition, perceived effort expectancy, and perceived compatibility significantly affected the intention to use VR systems and tools for educational purposes. We believe that this study will help decision makers to build sustainable learning and educational systems in Jordan universities.