Standards-based AI innovation transforms the learning ecosystem, offering new opportunities to enhance educational quality, accessibility, and personalization. By developing and applying frameworks and ethical guidelines, institutions ensure AI technologies in education are transparent, equitable, and aligned with learning goals. These standards build trust among educators, students, and policymakers, while supporting diverse learning environments. As AI becomes more integrated into teaching, assessment, and administration, a standards-driven approach guides responsible innovation and increases the positive impact on global learners. Standards-Based AI Innovation for the Learning Ecosystem explores the transformative potential of educational policy and standards in shaping the future of AI-driven education and training. It examines how adherence to standards enhances trust, accountability, and effectiveness in AI-powered educational tools. This book covers topics such as data science, ethics and law, and inclusive education, and is a useful resource for educators, policymakers, engineers, academicians, researchers, and scientists.
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Frederic Andres received his Ph.D. in Information Systems from the University of Paris VI "Pierre et Marie Curie" in 1993 and his Dr. Habilitation in Informatics from the University of Nantes in 2000. Dr. Frederic Andres has been associate professor in the Digital Content and Media Sciences Research Division of the National Institute of Informatics (NII) in Tokyo, Japan since 2000. He is author of more than 150 papers on international journals, books and conferences. His main research areas of interest include several topics such as collective intelligence-based knowledge, AI ethics, data science, supply chain and pedagogy and didactical web-based science education for all. He has been co-organising the International DECOR workshop since 2018 in conjunction with IEEE ICDE. His team won the 1st prize in IEEE Brain Data Bank Challenges and Competitions at COMPSAC 2018, July 2018. Dr. Frederic Andres received the IEEE CertifAIEd Authorized Lead Assessor recognition from IEEE SA on September 15, 2023. In addition, he was named "R10 Ethics Champion" by IEEE Region 10 on 22 Oct 2023.
Andreas Pester graduated in mathematics from Odessa State University in 1976, he got his PhD from Kiev State University in 1979 and he habilitated at the University of Technology Dresden in 1984. 2020 he retired from the University of Applied Sciences in Carinthia in Austria. Currently he is a professor for machine and deep learning at the British University in Egypt in Sherouk. He is the author and co-author of more than 75 publications. He was a guest professor at the UPC Barcelona, Technical University Porto, Technical Universities of Kharkov, Technical University Kiev, Polytechnic University St. Petersburg, State University of Petrozavodsk, BTH Karlskrona, University Maribor, UNESP Bauru (Brazil), AUA Erivan and others. Was and is involved in more than 20 EU- and national projects (as project leader or as collaborator), including Erasmus +, TEMPUS, MINERVA etc. His research interests are in deep learning, especially GNN architectures and Large Language Models. He was a chair of the IEEE Global Engineering Education Conference (EDUCON'21), Interactive Collaborative and Blended Learning (ICBL) conferences from 2008 - 2019, and is member of the PC of several other conferences etc. He holds the IEEE Education Society Distinguished Chapter Leader Award 2023. He also holds the EDUCON Meritorious Service Award or outstanding contributions to the administrative and management efforts for the IEEE EDUCON conference.
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Hardcover. Etat : new. Hardcover. Standards-based AI innovation transforms the learning ecosystem, offering new opportunities to enhance educational quality, accessibility, and personalization. By developing and applying frameworks and ethical guidelines, institutions ensure AI technologies in education are transparent, equitable, and aligned with learning goals. These standards build trust among educators, students, and policymakers, while supporting diverse learning environments. As AI becomes more integrated into teaching, assessment, and administration, a standards-driven approach guides responsible innovation and increases the positive impact on global learners. Standards-Based AI Innovation for the Learning Ecosystem explores the transformative potential of educational policy and standards in shaping the future of AI-driven education and training. It examines how adherence to standards enhances trust, accountability, and effectiveness in AI-powered educational tools. This book covers topics such as data science, ethics and law, and inclusive education, and is a useful resource for educators, policymakers, engineers, academicians, researchers, and scientists. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798337322353
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Hardcover. Etat : new. Hardcover. Standards-based AI innovation transforms the learning ecosystem, offering new opportunities to enhance educational quality, accessibility, and personalization. By developing and applying frameworks and ethical guidelines, institutions ensure AI technologies in education are transparent, equitable, and aligned with learning goals. These standards build trust among educators, students, and policymakers, while supporting diverse learning environments. As AI becomes more integrated into teaching, assessment, and administration, a standards-driven approach guides responsible innovation and increases the positive impact on global learners. Standards-Based AI Innovation for the Learning Ecosystem explores the transformative potential of educational policy and standards in shaping the future of AI-driven education and training. It examines how adherence to standards enhances trust, accountability, and effectiveness in AI-powered educational tools. This book covers topics such as data science, ethics and law, and inclusive education, and is a useful resource for educators, policymakers, engineers, academicians, researchers, and scientists. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9798337322353
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