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This edited book is a collection of selected research papers presented at the 2022 3rd International Conference on Artificial Intelligence in Education Technology (AIET 2022), held in Wuhan, China, on July 1-3, 2022. AIET establishes a platform for AI in education researchers to present research, exchange innovative ideas, propose new models, as well as demonstrate advanced methodologies and novel systems.
The book is divided into five main sections - 1) AI in Education in the Post-COVID New Norm, 2) Emerging AI Technologies, Methods, Systems and Infrastructure, 3) Innovative Practices of
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Produktbeschreibung
This edited book is a collection of selected research papers presented at the 2022 3rd International Conference on Artificial Intelligence in Education Technology (AIET 2022), held in Wuhan, China, on July 1-3, 2022. AIET establishes a platform for AI in education researchers to present research, exchange innovative ideas, propose new models, as well as demonstrate advanced methodologies and novel systems.

The book is divided into five main sections - 1) AI in Education in the Post-COVID New Norm, 2) Emerging AI Technologies, Methods, Systems and Infrastructure, 3) Innovative Practices of Teaching and Assessment Driven by AI and Education Technologies, 4) Curriculum, Teacher Professional Development and Policy for AI in Education, and 5) Issues and Discussions on AI In Education and Future Development. Through these sections, the book provides a comprehensive picture of the current status, emerging trends, innovations, theory, applications, challenges and opportunitiesof current AI in education research.

This timely publication is well aligned with UNESCO's Beijing Consensus on Artificial Intelligence (AI) and Education. It is committed to exploring how AI may play a role in bringing more innovative practices, transforming education in the post-pandemic new norm and triggering an exponential leap toward the achievement of the Education 2030 Agenda. Providing broad coverage of recent technology-driven advances and addressing a number of learning-centric themes, the book is an informative and useful resource for researchers, practitioners, education leaders and policy-makers who are involved or interested in AI and education.
Autorenporträt
Dr. Eric Cheng is a specialist in knowledge management and Lesson Study. He is an Associate Dean of the Faculty of Education and Human Development of the Education University of Hong Kong. He earned his Doctor of Education in education management from the University of Leicester. His research focuses on exploring organizational and technological factors, and management strategies that enable school leaders and teachers to leverage pedagogical knowledge assets. Such leveraging aims at improving student learning and capitalizing on the knowledge assets as school intellectual capital for sustainable development. His publication covers the areas of knowledge management, AI in education school management, Lesson and Learning Study. He is the author and edited author of five academic books. Eric has successfully launched more than 20 research and teaching development projects with external and competitive funds in the capacity of Principal Investigator. Dr. Tianchong Alex Wang is currently a Lecturer, Secondary Teacher Education and Course Director, Secondary Education in the Department of Education at Swinburne University of Technology, Australia. Dr Wang obtained an Ed.D. degree from the Chinese University of Hong Kong, an M.Sc. degree from the University of Hong Kong and a B.A. Hons degree from Hong Kong Baptist University. He has a solid technical background in Information and Communication Technologies (ICTs); he holds several professional qualifications such as MCP, MCSA, MCSE, MCDBA, MCTS, MCITP, ACSP, ACTC and THXCP. He is also a member of IEEE. As an advocate of using digital technologies to enhance education quality and inclusion, Dr Wang's current research interests include AI in education, blended learning, mobile learning, and digital learning for development. He has been participating in research projects commissioned or supported by international organizations such as UNESCO, IDRC and the HEAD Foundation. He often serves as aresource person for development aid agencies, conducting teacher capacity-building activities in the Global South. Prof. Dr. Tim Schlippe is a professor of Artificial Intelligence at IU International University of Applied Sciences and CEO of the company Silicon Surfer. He studied computer science at Karlsruhe Institute of Technology and did his master's thesis at Carnegie Mellon University. After successfully completing his PhD at the Karlsruhe Institute of Technology, Prof. Dr. Schlippe worked at Across Systems GmbH as a consultant and project manager for several years before founding the company Silicon Surfer. At Silicon Surfer, he develops AI-powered products and services that have social value, e.g., the WaveFont technology which automatically and intuitively visualizes information and emotion from the voice in subtitles and captions. Prof. Dr. Schlippe has in-depth knowledge in the fields of artificial intelligence, machine learning, natural language processing, multilingual speech recognition/synthesis, machine translation, language modeling, computer-aided translation, and entrepreneurship, which can be seen in his numerous publications at international conferences in these areas. Prof. Dr. Schlippe's current research interests are primarily in the fields of AI in Education, Natural Language Processing, and Subtitling/Captioning. As IU International University of Applied Sciences grows rapidly, especially in distance learning, he investigates innovative methods such as automatic short answer grading, conversational AI, and gamification, which are then used in practice at IU to provide optimal support to both students and teaching staff. Dr. Grigorios Beligiannis was born in Athens, Greece, in 1974. He graduated from the Department of Computer Engineering and Informatics of the University of Patras in 1997. He finished his postgraduate studies in "Computer and Information Technology" in 2000 and his doctoral dissertation in 2002 at the same time department. In 2007, he was elected to the lecturer's degree with knowledge area "Management Information Systems." In 2011, he has evolved at the rank of an assistant professor; in 2016, at the rank of an associate professor; and in 2020, at the rank of a professor with subject "intelligent information systems." He has 42 published research papers in international scientific journals, 45 published papers in scientific conferences and 3 chapters in edited book series. He is an associate editor of International Journal of Artificial Intelligence and a member of the Editorial Board of Applied Soft Computing, Helyion, International Journal of Intelligent Information Systems and Artificial Intelligence Research. He has been a member of the technical committee at more than 77 international scientific conferences. His research interests focus on intelligent algorithms of decision theory, on intelligent algorithm applications to system identification, parameter estimation and operations research problems and on business intelligence systems.