Extended reality (XR) is an umbrella term that includes all the immersive technologies, either the ones already existing - augmented reality (AR), virtual reality (VR), and mixed reality (MR) - or those that will be developed in the forthcoming years. Immersive technologies extend the experienced reality by either blending the virtual and real worlds or by creating a fully immersive experience. XR has been applied in training and educational settings to transform teaching/learning experiences through immersive environments. The incorporation of extended reality into classrooms and training sessions can provide students and trainees with more meaningful learning and training experiences by increasing their motivation. We are experiencing a rapid spread of the usage of extended reality applications in several domains. The book describes the current research status of extended reality usage and discusses the foreseen advancements in the design and development of various types of immersive learning environments, as well as the emerging pedagogical innovations in the field. The book is ideal for teachers, instructional designers, curriculum developers, program developers, administrators, educational software developers, policymakers, researchers, education professionals, training professionals, privacy practitioners, government officials, consultants, IT researchers, academicians, and students.

How can a group be empowered to improve their ability to make decisions while also reinforcing the group's intended values, beliefs, and behaviors? Like positive reinforcement, which introduces a desirable or pleasant stimulus after a behavior has been completed and has been found to be effective for reinforcing such behavior, serious games introduce the behavior as a pleasant experience through engagement and entertainment. Where positive reinforcement relies heavily on the willpower of the subject to complete the behavior on their own, serious games introduce a motivational factor from the beginning of the behavior. Serious games are designed for purposes other than entertainment, such as training, learning, creating awareness, or behavior transformation through the introduction of content, topics, narratives, rules, and goals. They are immersive, engaging, and enjoyable, which enhances motivation and learning. The development of serious games is grounded in theoretical backgrounds, such as motivation, constructivism, flow experience, problem-based learning, and learning by doing. This method has been used in a variety of industries, including education, healthcare, military, policy analysis, and business functions such as marketing or financial purposes. They facilitate problem solving through challenges and rewards and use entertainment and engagement components. Serious games can address specific skills for many domains, foster collaboration, provide risk-free environments, and be used as analytical tools for educational research. They reinforce intended values, beliefs, and behaviors of players while conveying knowledge, skills, and attitudes, providing an integrated and effective approach to the transformation of an individual, group, or organization. Decision-Making Capabilities Improvement With Serious Games: Research and Practice discusses the use of advanced technologies including extended and immersive reality, digital twins, augmented reality (AR), virtual reality (VR), mixed reality (MR), and IoT sensors to improve decision-making skills and learning through serious games. This book discusses user engagement, game adaptation, content adaptation, and sensor technology. It showcases how to increase decision-making skills in individuals and organizations and incorporates the latest developments in artificial intelligence and machine learning. Led by experts with over 20 years of experience and covering topics such as serious game design, intelligent content adaptation, and machine learning algorithms. This book is designed for professionals in education, instructional designers, curriculum developers, program developers, administrators, educational software developers, policymakers, researchers, training professionals, privacy practitioners, government officials, consultants, IT researchers, academicians, and students.

The growth of innovative cyber threats, many based on metamorphosing techniques, has led to security breaches and the exposure of critical information in sites that were thought to be impenetrable. The consequences of these hacking actions were, inevitably, privacy violation, data corruption, or information leaking. Machine learning and data mining techniques have significant applications in the domains of privacy protection and cybersecurity, including intrusion detection, authentication, and website defacement detection, that can help to combat these breaches. Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity provides machine and deep learning methods for analysis and characterization of events regarding privacy and anomaly detection as well as for establishing predictive models for cyber attacks or privacy violations. It provides case studies of the use of these techniques and discusses the expected future developments on privacy and cybersecurity applications. Covering topics such as behavior-based authentication, machine learning attacks, and privacy preservation, this book is a crucial resource for IT specialists, computer engineers, industry professionals, privacy specialists, security professionals, consultants, researchers, academicians, and students and educators of higher education.

The growth of innovative cyber threats, many based on metamorphosing techniques, has led to security breaches and the exposure of critical information in sites that were thought to be impenetrable. The consequences of these hacking actions were, inevitably, privacy violation, data corruption, or information leaking. Machine learning and data mining techniques have significant applications in the domains of privacy protection and cybersecurity, including intrusion detection, authentication, and website defacement detection, that can help to combat these breaches. Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity provides machine and deep learning methods for analysis and characterization of events regarding privacy and anomaly detection as well as for establishing predictive models for cyber attacks or privacy violations. It provides case studies of the use of these techniques and discusses the expected future developments on privacy and cybersecurity applications. Covering topics such as behavior-based authentication, machine learning attacks, and privacy preservation, this book is a crucial resource for IT specialists, computer engineers, industry professionals, privacy specialists, security professionals, consultants, researchers, academicians, and students and educators of higher education.

Extended reality has been applied in training and educational settings to transform teaching and learning experiences through immersive environments. The incorporation of extended reality into classrooms and training sessions can provide students and trainees with more meaningful learning and training experiences by increasing their motivation. Besides being able to be used in the classroom to illustrate complex concepts, simulations, and scenarios, extended reality has numerous applications in professional training to discover solutions to problems to learn how to respond to dangerous circumstances without putting their own life or the lives of others at risk. Methodologies and Use Cases on Extended Reality for Training and Education presents the forefront of research regarding the integration of extended reality in training and educational programs and establishes the foundations for course design, program development, and institutions' training and education policy planning. It provides an overall approach to extended reality in education without failing to mention applications of using extended reality in institutions of different levels of education. Covering topics such as 3D visualization, student perceptions, and laboratory virtualization, this premier reference source is a dynamic resource for instructional designers, curriculum developers, program developers, faculty and administers of both K-12 and higher education, educational software developers, educators, pre-service teachers, teacher educators, government officials, researchers, and academicians.