Metaverse is a virtual world platform that enables users to create and explore 3D environments. Recently, this technology has gained traction due to its potential to revolutionize the way people interact and share information. This paper provides an overview of the current state of Metaverse technologies. It begins by introducing their core components and surveys recent research and development activities in the area. Next, the paper examines the potential applications of Metaverse technology in different domains, such as gaming, social networking, training, education, healthcare, and marketing. It then outlines the challenges and opportunities associated with the development and deployment of Metaverse technologies, including scalability, privacy, and security issues. Finally, the paper concludes with a discussion of the implications of Metaverse technologies for the future of digital communication and information sharing.

This paper aims to look at teachers, government officials, and students for Literacy & Numeracy Drive (LND), a smartphone app for students in Punjab province, Pakistan, to teach languages and math. Furthermore, to recognize LND usability and design problems while its use for grade three in schools. As the usability and design issues of LND were not discussed since the launch of this application. The methodology for this study is the questionnaire for teachers and semi-structured interviews for government officials of District Sheikhupura and students. The result shows that LND has various usability and design problems in its current form, i.e., buttons, icons, color schemes, sluggish performance, and fonts. Besides, teachers, government officials, and students suggested that game-based learning consists of an interactive interface, phonics, key animations to be created and adopted. Highly engaging and appealing delivery of the curriculum and improvements in the appraisal will improve the participation of students and deliver better outcomes.

Gamification has emerged as a transformative e-business strategy, introducing innovative methods to engage customers and drive sales. This article explores the integration of game design principles into business contexts, termed “gamification,” a subject of increasing interest among both scholars and industry professionals. The discussion systematically addresses key themes, like the role of gamification in marketing strategies, enhancing website functionality, and its application within the financial sector, including e-banking, drawing insights from academic and industry perspectives. By conducting a systematic literature review of 48 academic articles published between 2015 and 2024, this study examines the use of personalized, gamification-based strategies to mitigate cyber threats in the financial domain. The review highlights the growing digitization of financial services and the corresponding rise in sophisticated cyber threats, including traditional attacks and advanced persistent threats (APTs). This article critically assesses the evolving landscape of cyber threats specific to the financial industry, identifying trends, challenges, and innovative solutions to strengthen cybersecurity practices. Of particular interest is the application of AI-enhanced gamification strategies to reinforce cybersecurity protocols, particularly in the face of novel threats in gaming platforms. Furthermore, the review evaluates techniques grounded in user behavior, motivation, and readiness to enhance cybersecurity. The article also offers a comprehensive taxonomy of financial services, categorizing cyber threats into game-based (e.g., phishing, malware, APTs) and non-game-based (e.g., social engineering, compliance issues) threats. AI-driven measures for prevention and detection emphasize regular security assessments, user training, and system monitoring with incident response plans. This research provides valuable insights into the intersection of gamification and cybersecurity, offering a forward-looking perspective for both academic researchers and industry professionals.

Diabetic retinopathy, often resulting from conditions like diabetes and hypertension, is a leading cause of blindness globally. With diabetes affecting millions worldwide and anticipated to rise significantly, early detection becomes paramount. The survey scrutinizes existing literature, revealing a noticeable absence of consideration for computational complexity aspects in deep learning models. Notably, most researchers concentrate on employing deep learning models, and there is a lack of comprehensive surveys on the role of vision transformers in enhancing the efficiency of these models for DR detection. This study stands out by presenting a systematic review, exclusively considering 84 papers published in reputable academic journals to ensure a focus on mature research. The distinctive feature of this Systematic Literature Review (SLR) lies in its thorough investigation of computationally efficient approaches and models for DR detection. It sheds light on the incorporation of vision transformers into deep learning models, highlighting their significant contribution to improving accuracy. Moreover, the research outlines clear objectives related to the identified problem, giving rise to specific research questions. Following an assessment of relevant literature, data is extracted from digital archives. Additionally, in light of the results obtained from this SLR, a taxonomy for the detection of diabetic retinopathy has been presented. The study also highlights key research challenges and proposes potential avenues for further investigation in the field of detecting diabetic retinopathy.

Recent advancements in computer science have led to the automation of many business processes. However, this increased automation has also escalated cyber threats and attacks alarmingly, as most data breaches are attributed to human errors, which are critical in these incidents. The primary cause is a lack of cybersecurity awareness and insufficient hands‐on experience in real‐world scenarios. Serious game frameworks offer a promising solution by surpassing traditional learning methods and addressing cybersecurity education’s complex and evolving nature. This research employs the Preferred Reporting Items for Systematic reviews and Meta‐Analyses (PRISMA) technique to systematically analyze various studies, using a snowballing method to select relevant resources. The study conducted a systematic literature review of 68 selected studies within the domains of serious games and cybersecurity training, aiming at evaluating the contributions of other researchers. The review examined different frameworks, tools, technologies, methodologies, and serious games developed for cybersecurity training over the past 5 years. The key findings demonstrate that serious games can effectively engage learners, facilitating knowledge sharing within realistic cybersecurity environments. Additionally, the review assessed the methodologies used to evaluate these serious games across different educational settings. Finally, the study underscores the need for a structured classification of research in the cybersecurity domain, leveraging serious game frameworks along with its taxonomy. This classification would provide a clear direction for future research, building on the evaluation of techniques from previous studies.