Vasileios Paliktzoglou – författare

This proceedings volume discusses the transformative impact of AI, digital transformation, and data science across education, literature, linguistics, and interdisciplinary sciences. It delves into how AI-driven personalized learning, immersive virtual and augmented reality, and adaptive systems are reshaping education by fostering inclusivity, creativity, and innovative teaching methods. In literature and linguistics, the book highlights AI-assisted literary analysis, machine translation, and digital preservation, offering new perspectives on language patterns and storytelling. It also examines how AI is enhancing interdisciplinary research, promoting cross-disciplinary collaboration, and enabling data-driven insights in social sciences and the digital humanities. With a focus on ethical considerations and the integration of technology into diverse fields, this insightful collection is ideal for academics, professionals, and policymakers, bridging AI-driven innovation and practice to offer a holistic view of how technology is reshaping society across multiple domains.

This proceedings volume discusses the transformative impact of AI, digital transformation, and data science across education, literature, linguistics, and interdisciplinary sciences. It delves into how AI-driven personalized learning, immersive virtual and augmented reality, and adaptive systems are reshaping education by fostering inclusivity, creativity, and innovative teaching methods. In literature and linguistics, the book highlights AI-assisted literary analysis, machine translation, and digital preservation, offering new perspectives on language patterns and storytelling. It also examines how AI is enhancing interdisciplinary research, promoting cross-disciplinary collaboration, and enabling data-driven insights in social sciences and the digital humanities. With a focus on ethical considerations and the integration of technology into diverse fields, this insightful collection is ideal for academics, professionals, and policymakers, bridging AI-driven innovation and practice to offer a holistic view of how technology is reshaping society across multiple domains.

This book presents a multidisciplinary exploration of sustainable development, integrating themes such as environmental management, social sciences, and AI-driven technology. It covers innovative approaches to sustainability in agriculture, biodiversity, energy, and urban planning, while addressing social equity, human rights, and the role of education. The book also highlights the impact of AI and technology on public health, resource management, and smart cities, alongside discussions on governance, policy, and ethical dimensions of sustainability. With contributions on economic growth, public health, and environmental justice, it serves as a comprehensive guide for advancing global sustainability initiatives.

This book presents a multidisciplinary exploration of sustainable development, integrating themes such as environmental management, social sciences, and AI-driven technology. It covers innovative approaches to sustainability in agriculture, biodiversity, energy, and urban planning, while addressing social equity, human rights, and the role of education. The book also highlights the impact of AI and technology on public health, resource management, and smart cities, alongside discussions on governance, policy, and ethical dimensions of sustainability. With contributions on economic growth, public health, and environmental justice, it serves as a comprehensive guide for advancing global sustainability initiatives.

This book presents recent research on generative artificial intelligence (GenAI) and its transformative role in education. It constitutes the proceedings of the Second International Symposium on Generative AI and Education (ISGAIE’2025). The book explores recent advancements in GenAI technologies and their emerging impact on teaching and learning practices across educational contexts. Beyond practical applications and various use cases, the book addresses emerging challenges and opportunities, offering critical reflections on the ethical, pedagogical, and institutional implications of GenAI adoption in education. This book serves as a comprehensive reference for researchers, teachers, education designers, technology developers, and decision-makers who are working to rethink education using generative AI.

This book presents recent research on generative artificial intelligence (GenAI) and its transformative role in education. It constitutes the proceedings of the Second International Symposium on Generative AI and Education (ISGAIE’2025). The book explores recent advancements in GenAI technologies and their emerging impact on teaching and learning practices across educational contexts. Beyond practical applications and various use cases, the book addresses emerging challenges and opportunities, offering critical reflections on the ethical, pedagogical, and institutional implications of GenAI adoption in education. This book serves as a comprehensive reference for researchers, teachers, education designers, technology developers, and decision-makers who are working to rethink education using generative AI.

This book examines the rapidly evolving role of generative artificial intelligence (GenAI) in higher education assessment, with particular emphasis on its theoretical foundations, practical implementations, and ethical implications. It includes case studies on AI-supported assessment practices from a range of international contexts. The volume is structured into three parts: an overview of GenAI in educational assessment, its application across diverse educational settings, and a collection of case studies and practical implementations in higher education.The first part of the book provides an overview of how generative AI is transforming educational assessment, particularly in shaping the perceptions and practices of early-career teachers. The second part centers on personalization, showcasing AI-driven frameworks that utilize digital twins in immersive environments, GenAI-created math assessments, and novel tools for formative self-assessment. The final part of the book presents international case studies that bring GenAI’s influence into real-world educational contexts—from ESL instruction and STEM curriculum design to privacy concerns and regulatory frameworks.By addressing both the transformative opportunities and the practical challenges posed by generative AI (GenAI) in educational assessment, this book offers a timely and essential resource for educators, researchers, and policymakers. It aims to deepen understanding of how AI can be responsibly harnessed to innovate and improve academic assessment practices.

This book examines the rapidly evolving role of generative artificial intelligence (GenAI) in higher education assessment, with particular emphasis on its theoretical foundations, practical implementations, and ethical implications. It includes case studies on AI-supported assessment practices from a range of international contexts. The volume is structured into three parts: an overview of GenAI in educational assessment, its application across diverse educational settings, and a collection of case studies and practical implementations in higher education.The first part of the book provides an overview of how generative AI is transforming educational assessment, particularly in shaping the perceptions and practices of early-career teachers. The second part centers on personalization, showcasing AI-driven frameworks that utilize digital twins in immersive environments, GenAI-created math assessments, and novel tools for formative self-assessment. The final part of the book presents international case studies that bring GenAI’s influence into real-world educational contexts—from ESL instruction and STEM curriculum design to privacy concerns and regulatory frameworks.By addressing both the transformative opportunities and the practical challenges posed by generative AI (GenAI) in educational assessment, this book offers a timely and essential resource for educators, researchers, and policymakers. It aims to deepen understanding of how AI can be responsibly harnessed to innovate and improve academic assessment practices.

This book shows what happens when classrooms meet climate action and AI meets equality. Bringing together educators, technologists, and policy thinkers, this volume maps how AI, ICT, data, and IoT can advance the UN SDGs—especially SDG 4 (Quality Education), SDG 8 (Decent Work), SDG 10 (Reduced Inequalities), SDG 11 (Sustainable Cities), and SDG 13 (Climate Action). With Generation Beta growing up in hyper-digital environments, the book asks a timely question: how do we design learning that is tech-empowered, human-centered, and planet-positive? Readers will find pragmatic guidance on AI-supported teaching and assessment with clear privacy and ethics guardrails; low-bandwidth, multilingual, offline-first models that narrow divides; studio projects using IoT and digital twins for real urban and climate challenges; routes from micro-credentials to green jobs; and faculty development that scales. We also examine rankings, gender gaps, and research incentives—where they drive excellence and where they distort it. Acknowledging debate around AI in assessment, personalization versus agency, and ed-tech’s carbon footprint, the book offers metrics that matter and a practical roadmap for teachers, leaders, policymakers, funders, and researchers committed to equitable, sustainable learning.

This book explores AI ethics in digital pedagogy, offering a structured framework for responsible AI integration in education. The integration of Artificial Intelligence (AI) in education is transforming digital pedagogy by enhancing personalization, automating administrative processes, and improving accessibility. However, these advancements bring ethical concerns, including data privacy, bias, transparency, and equitable access. It covers ethical guidelines, data protection, AI-driven assessments, professional development, and strategies for inclusivity. By providing theoretical foundations, case studies, and policy recommendations, this book equips educators, policymakers, and researchers with the knowledge to foster AI-driven learning environments that are ethical, transparent, and inclusive.