Advances in AI-Augmented E-Learning for Smart Cities

Dear Colleagues,

The evolution of smart cities is significantly reshaping the landscape of e-learning and distance learning, offering innovative pathways for enhancing the accessibility, personalization, and quality of education. Smart cities, with their integrated IoT architecture and high-speed network connectivity, facilitate the growth of dynamic, adaptive and responsive e-learning environments.

This Special Issue aims to explore the latest advances in educational technology and examine the role of smart cities in the development of advanced e-learning solutions such as AI-augmented adaptive learning platforms. These platforms are powered by artificial intelligence tools and dynamically adjust content delivery based on the performance and preferences of learners. Furthermore, ubiquitous connectivity through 5G, edge computing and smart IoT devices ensures seamless access to both learning materials and real-time smart city data sources, and supports the creation of various formal, informal and lifelong learning scenarios. Smart city infrastructure is the foundation of immersive and interactive learning environments that utilize technologies such as augmented reality (AR), virtual reality (VR) and digital twins. AR and VR technology can be employed to build immersive virtual labs and smart classrooms within smart campuses. Digital twins are an advanced tool that can be used to create realistic, data-driven simulations of urban environments that allow learners to experiment, analyze, and optimize city systems in a safe, interactive, and adaptive learning space. Gamification in AI-augmented e-learning for smart cities can enhance learner engagement and motivation by integrating game-like elements such as challenges, rewards, and progress tracking into urban-focused educational experiences. This Special Issue will also examine the data analysis of adaptive e-learning systems integrated into smart city infrastructure using methods such as data mining, process mining and learning analytics. Moreover, this Special Issue will address the application of formal methods in the specification and verification of e-learning systems using model checking.

The scope of this Special Issue encompasses a wide range of topics, including but not limited to, the following:

• Adaptive e-learning technologies;
• Artificial intelligence in e-learning;
• Mobile learning and microlearning;
• Smart cities infrastructure for e-learning;
• Edge computing, IoT and 5G networks in e-learning;
• Usage of digital twins in e-learning;
• Immersive learning environments using augmented and virtual reality;
• Virtual labs and smart classrooms;
• Smart campuses;
• Lifelong learning for Climate change adoption
• Data analysis in e-learning – data mining, process mining and learning analytics;
• Formal methods in e-learning systems specification and verification.

We look forward to receiving your contributions.

Dr. Frano Škopljanac-Mačina
Dr. Ivona Zakarija
Dr. Mihaela Vranić
Prof. Dr. Damir Pintar
Dr. Ljiljana Seric
Guest Editors

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