Serious games offer an innovative blend of entertainment and learning in medical education. This chapter examines the technological underpinnings, challenges, and potential future developments in this domain. Drawing from publications between 2018 and 2023, this systematic review highlights the role of technologies such as web and mobile applications, game engines, augmented reality, virtual reality, mixed reality, and artificial intelligence in personalizing and enhancing the learning experience. However, the use of serious games in medical education also faces several challenges, including the need for adequate technological infrastructure, complex effectiveness assessments, and integration into existing curricula. Moreover, this chapter outlines projections for further research. The authors reveal how serious games have the potential to transform medical education to be more engaging, interactive, and effective, and inspire future research in the development of innovative technologies and learning methods.

The integration of cutting-edge technologies into health literacy and medical practice presents unprecedented opportunities and ethical challenges. This chapter delves into the technoethical considerations crucial for navigating this new landscape, guided by a posthumanist framework. Embracing this framework encourages us to reevaluate traditional boundaries, inviting a more inclusive understanding of humanity's relationship with technology. The chapter also explores the intricate relationship between technology and ethics, advocating for a technoethical framework that ensures technological advancements in healthcare are employed ethically, responsibly, and with a deep understanding of their societal impact. By doing so, this chapter serves as a guiding beacon for healthcare professionals, technologists, ethicists, and policymakers, urging a future where technology and human values coalesce to foster a healthcare ecosystem that is not only advanced but also compassionate, equitable, and ethically grounded.

With the increasing popularity of artificial intelligence (AI) applications in medical practices, the integration of AI technologies into medical education has garnered significant attention. However, there exists a noticeable research gap when it comes to providing comprehensive guidelines and recommendations for its successful integration into this domain. Addressing this research gap is crucial as the responsible and effective incorporation of AI in medical education not only ensures that current and future healthcare professionals are well-prepared for the demands of modern medicine but also upholds ethical standards, maximizes the potential benefits of AI, and minimizes potential risks. The objective of this chapter is to fill this gap by offering practical tips and actionable insights for incorporating AI into medical education, encompassing practical, ethical, pedagogical, and professional implications. Consequently, it equips medical educators and learners alike with the knowledge and tools necessary to navigate the evolving landscape of medical education in the age of AI.

In the field of tourism, serious games are a pedagogical media application that helps players develop travel knowledge and expertise based on game content. A tourism serious game requires a scenario control system to visualize an attractive travel scenario. This paper proposes an Automatic Scenario Control in the serious game to visualize travel recommendation scenarios choice according to the player’s expectations of potential tourism destinations criteria. There are two stages in system development, namely scenario design and scenario selection. In the scenario design stage, we use the Hierarchical Finite State Machine to translate challenge-based stories according to the type of attraction. While at the scenario selection stage, Dynamic Weight Topsis is a method for selecting one of the player’s recommended scenarios. This study uses tourism destinations recommendations as to alternative variables, characteristics of tourism destinations as criteria, and players’ expectations of tourism destinations’ characteristics as weight criteria. In the implementation phase, the tourism serious game uses the content of tourism destinations in Mojokerto Indonesia. The test results show that Automatic Scenario Control generates a preference value for each alternative as a reference for choosing tourism destination scenarios for the player. Three things affect the scenario choice results, including the choice of month of tourist visits, player expectations of tourist destinations, and alternative input from the recommender system.

Tourism destinations serious game (TDSG) requires the ability to respond to players through recommendations for selecting appropriate tourist destinations for them as potential tourists. This research utilizes ambient intelligence technology to regulate the response visualized through a choice of serious game scenarios. This research uses the Multi-Criteria Recommender System (MCRS) to produce recommendations for selecting tourist destinations as a reference for selecting scenario visualizations. Recommender systems require a decentralized, distributed, and secure data-sharing concept to distribute data and assignments between nodes. We propose using the Ethereum blockchain platform to handle data circulation between parts of the system and implement decentralized technology. We also use the known and unknown rating (KUR) approach to improve the system's ability to generate recommendations for players who can provide rating values or those who cannot. This study uses the tourism theme of Batu City, Indonesia, so we use personal characteristics (PC) and rating of destinations attribute (RDA) data for tourists in that city. The test results show that the blockchain can handle decentralized data-sharing well to ensure PC and RDA data circulation between nodes. MCRS has produced recommendations for players based on the KUR approach, indicating that the known rating has better accuracy than the unknown rating. Furthermore, the player can choose and run the tour visualization through game scenarios that appear based on the recommendation ranking results.

This chapter examines the potential of serious games in physical education, focusing on technology integration, implementation, and evaluation. It explores how serious games enhance learning outcomes, curriculum integration, and user engagement by merging AI technologies with learning theories. Aimed at educators, researchers, and developers, the chapter uses a systematic literature review and case studies to illustrate practical applications. It highlights various technologies like exergaming, game-based learning models, and computer-aided tools, showing their impact on student motivation and engagement. Despite challenges like cost and training needs, the chapter underscores the promise of AR, VR, MR, and immersive tools in revolutionizing physical education. Through adaptive programs, culturally responsive pedagogies, and diverse evaluation methods, the chapter demonstrates the effectiveness of serious games in creating inclusive and engaging physical education programs while addressing the need for cost-effective solutions and comprehensive training for educators.