Artificial Intelligence in Education (AIED), exploring intelligent and adaptive educational applications that support learning and teaching. Machine Learning in Education, focusing on predictive and adaptive models for learning support, personalization, and educational decision-making. Deep Learning Pedagogy in Education, examining deep learning methods and their pedagogical integration in educational contexts. Educational Data Mining & Learning Analytics, investigating data-driven analysis of learner behaviors, prediction of learning outcomes, and optimization of instructional strategies. Intelligent Tutoring & Intelligent Learning Systems, designing adaptive systems that personalize instruction based on learner characteristics and performance. Immersive Technologies in Education, including augmented reality (AR), virtual reality (VR), and other immersive learning experiences to support engagement and skill development. IoT and Smart Classrooms, leveraging Internet of Things (IoT) technologies for connected learning environments and smart educational infrastructure. Gamification and Game-Based Learning with AI, integrating intelligent mechanisms into games and gamified systems for motivation, feedback, and learning outcomes. Digital Citizenship, Literacy & AI Ethics in Education, addressing responsible technology use, digital literacy, fairness, transparency, accountability, and ethical governance in educational settings.