This study investigates the Metaverse-based class-room, an innovative educational approach combining virtual reality (VR) technologies with traditional learning methods. It focuses on developing and evaluating a prototype in a controlled setting involving students and teachers. The Metaverse concept in education is grounded in constructive learning theory, em-phasizing active engagement and experience, and the theory of social presence in online learning, enhancing the sense of being in a shared space. The prototype, showcased at the Dubai G ITEX event in 2023, integrates features from existing online platforms like Zoom and Microsoft Teams, such as resource and screen sharing, with the immersive experience of VR, where users interact via avatars. This design aims to utilize VR's benefits to boost engagement and interactivity in learning. The prototype's effectiveness was further assessed in a real classroom environment, involving typical activities like lectures and discussions. Feedback from the GITEX event and classroom evaluations, including observations, user feedback, and interviews, were analyzed using grounded theory and thematic analysis. Findings indicate a positive reception of the Metaverse-based classroom, particularly its immersive and interactive aspects, which enhance engagement and offer a novel learning experience. However, chal-lenges were identified, including hardware discomfort, software glitches, and concerns about the Metaverse's applicability in diverse educational settings. These insights highlight the need for improved hardware ergonomics, software usability, and inclusive design, pointing to future research directions for optimizing Metaverse- based learning environments.

Education is essential for achieving many Sustainable Development Goals (SDGs). Therefore, the education system focuses on empowering more educated people and improving the quality of the education system. One of the latest technologies to enhance the quality of education is Artificial Intelligence (AI)-based Machine Learning (ML). As a result, ML has a significant influence on the education system. ML is currently widely applied in the education system for various tasks, such as creating models by monitoring student performance and activities that accurately predict student outcomes, their engagement in learning activities, decision-making, problem-solving capabilities, etc. In this research, we provide a survey of machine learning frameworks for both distributed (clusters of schools and universities) and centralized (university or school) educational institutions to predict the quality of students' learning outcomes and find solutions to improve the quality of their education system. Additionally, this work explores the application of ML in teaching and learning for further improvements in the learning environment for centralized and distributed education systems.

Instagram, as many social media platforms, has been increasingly used by users to shop for goods and products from business or other individuals. Recently, studies have shed lights on acceptance and usage of Insta shopping from users’ perspectives by following popular technology models, such as technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT). However, more rich and in-depth insights about using Instagram for commercial purposes within a certain context are yet to be discovered. Therefore, this study aims at discovering experiences and interactions with Insta shopping, the factors and the drivers that impact users’ acceptance of Insta shopping, the weight of each factor (degree of consensus among participants), and their direction (positive, negative, or both). The study followed a qualitative approach, by creating four homogeneous focus groups (six participants each) of IT students in United Arab Emirates (UAE) universities. The data analysis approach considered is an axial coding technique as part of the grounded theory, which includes open coding, axial coding, and selective coding stages. The results revealed that the time factor, trust in Insta shops (and its drivers such as reviews, word of mouth, trading license, and others), distrust (and its drivers such as fake comments and reviews, extremely low prices, and others), and the associated risks (financial for losing money, security because of online payments, and some privacy issues) can impact users’ behaviors toward Insta shopping. Also, the study classified participants’ viewpoints and experiences’ themes into advantages, disadvantages, and issues that are associated with Insta shopping. The study indicated theoretical and practical implications and suggests future research directions.

In this growing technology epoch, one of the main concerns is about the cyber threats. To tackle this issue, highly skilled and motivated cybersecurity professionals are needed, who can prevent, detect, respond, or even mitigate the effect of such threats. However, the world faces workforce shortage of qualified cybersecurity professionals and practitioners. To solve this dilemma several cybersecurity educational programs have arisen. Before it was just a couple of courses in a computer science graduate program. Now a day’s different cybersecurity courses are introduced at the high school level, undergraduate computer science and information systems programs, even in the government level. Due to some peculiar nature of cybersecurity, educational institutions face many issues when designing a cybersecurity curriculum or cybersecurity activities.