Evolution of Simulation Technologies: AI-Enhanced Education

This article examines the historical development of simulation technologies and the transformation in artificial intelligence-enhanced education applications. At the outset of the historical process of simulation use, analog-based systems were primarily employed, typically finding application in fields such as military and engineering. Subsequently, with the advancement of digital technologies, simulations began to be used as an effective teaching tool in education. Currently, new generation technologies such as augmented reality (AR), virtual reality (VR), mixed reality (MR), gamification, and digital twins have been integrated into simulations. This has made learners' learning processes more interactive, personalizable, and secure. The integration of AI into these systems has created structures that offer learners individual feedback, track their performance, and adapt their learning experiences to their needs. These technologies are widely and actively used, especially in high-risk or application-based fields such as medicine, engineering, aviation, psychology, and military education. A review of the literature reveals that the contributions made in terms of effectiveness and efficiency are quite significant. However, there are various challenges in terms of access to and dissemination of these systems. In particular, infrastructure deficiencies, teachers' technological proficiency levels, ethical and legal responsibilities, data security, and access inequalities necessitate careful management of this process. AI enhanced simulations have great potential in terms of improving the quality of education and offering personalized learning experiences, clearly demonstrating that overcoming these challenges will have significant implications. In this context, this article, which examines the relevant challenges from a broad perspective, offers multidimensional recommendations for education policymakers, practitioners, software developers, and researchers; it emphasizes the need for future research to focus on different learning styles, long-term learning outcomes, and social inequalities.