Simülasyon Teknolojilerinin Evrimi: Yapay Zeka ile Güçlendirilmiş Eğitim

Abstract

Bu makalede simülasyon teknolojilerinin tarihsel gelişim süreçleri ile birlikte yapay zeka (YZ) destekli eğitim uygulamalarındaki dönüşüm ele alınmıştır. Simülasyonların kullanımına yönelik tarihsel sürecin başlangıcında öncelikle analog temelli sistemler kullanılmış olup, genellikle askeri ve mühendislik gibi alanlarda uygulama yeri bulmuştur. Ardından dijital teknolojilerin gelişmesiyle birlikte eğitim alanında da etkili bir öğretim aracı olarak kullanımına başlanılmıştır. Mevcutta ise simülasyonlara artırılmış gerçeklik (AR), sanal gerçeklik (VR), karma gerçeklik (MR), oyunlaştırma ve dijital ikiz gibi yeni nesil teknolojiler entegre edilmiştir. Böylelikle öğrenenlerin öğrenme süreçleri daha etkileşimli, kişiselleştirilebilir ve güvenli hale gelmiştir. YZ'nın bu sistemlere entegrasyonu, öğrenenlere bireysel geribildirim imkanı sunan, performanslarını takip eden ve öğrenme deneyimlerini ihtiyaçlarına göre uyarlayabilen yapılar oluşturmuştur. Bu teknolojiler özellikle tıp, mühendislik, havacılık, psikoloji ve askeri eğitim gibi yüksek riskli ya da uygulama temelli alanlarda yaygın ve aktif olarak kullanılmaktadır. Alanyazın incelendiğinde etkililik ve verimlilik bağlamında sağlanan katkıların oldukça önemli olduğu görülmektedir. Ancak ne var ki, bu sistemlere erişim ve yaygınlaştırma bağlamında çeşitli zorluklar mevcuttur. Özellikle altyapı eksiklikleri, öğretmenlerin teknolojik yeterlilik düzeyleri, etik ve yasal sorumluluklar, veri güvenliği ve erişim eşitsizlikleri göz önünde bulundurularak bu sürecin dikkatle yönetilmesini zorunlu kılmaktadır. YZ destekli simülasyonlar, eğitimin kalitesini artırma ve kişiselleştirilmiş öğrenme deneyimleri sunma açısından büyük bir potansiyele sahip olması, bu zorlukların aşılması halinde sağlanacak olan katkısının önemli yansımalarının olacağı öngörüsünü net biçimde ortaya koymaktadır. Bu kapsamda ilgili zorlukların üstesinden gelinebilmesi için geniş bir perspektifle inceleme yapılan bu makalede eğitim politikaları, uygulayıcılar, yazılım geliştiricileri ve araştırmacılar için çok boyutlu öneriler sunulmuş olup; gelecekteki araştırmalar için farklı öğrenme biçimleri, uzun vadeli öğrenme çıktıları ve toplumsal eşitsizliklere odaklanılması gerekliliği vurgulanmıştır.

Keywords

• YZ destekli eğitim
• Simülasyon teknolojileiri
• Dijital dönüşüm

Evolution of Simulation Technologies: AI-Enhanced Education

Abstract

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.

Keywords

• AI enhanced education
• Simulation technologies
• Digital transformation

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