LEADER 05006nam 22005775 450 001 9910887817703321 005 20240918130229.0 010 $a9783031727900 010 $a3031727908 024 7 $a10.1007/978-3-031-72790-0 035 $a(MiAaPQ)EBC31682230 035 $a(Au-PeEL)EBL31682230 035 $a(CKB)36043959400041 035 $a(DE-He213)978-3-031-72790-0 035 $a(EXLCZ)9936043959400041 100 $a20240918d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aInevitability of AI Technology in Education $eFuturism Perspectives for Education for the Next Two Decades /$fby Yoav Armony, Orit Hazzan 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (206 pages) 311 08$a9783031727894 311 08$a3031727894 327 $aChapter 1. The story of technology in our life The characteristics of technology and its affect on us Inevitable technology -- Chapter 2. What causes technology to become inevitable? Methods for future research When does technology become inevitable? -- Chapter 3: Why does technology implementation fail in the education system? -- Chapter 4. - AI, VR & AI-Companion -- Chapter 5. What is Omni-Assistant Omni-Assistant -- Chapter 6. Omni-Assistant - feasible scenario in the education system -- Chapter 7. Could Omni-Assistant become 'inevitable' in the education system? -- Chapter 8. Omni-Assistant - desired scenario in the education system. 330 $aThis book layouts historic and future perspectives at the introduction of technology into education systems: On the one hand, the book attempts to explain why despite numerous attempts, technology has struggled to integrate successfully into the education system for over a century; on the other hand, it explores whether this trend will persist in the foreseeable future, questioning if emerging technologies, like virtual reality or Gen-AI will ever be embraced by education systems worldwide, and introducing a hypothesis that these technologies will become inevitable so that education systems will have a little choice in adopting them. The underlying perspective is that education systems need to prepare for this new future and better start doing so now. The book encompasses three key areas: education, technology, and future studies, with a focus on how technology will shape the future of education. It begins by examining past failures of integrating technology into education, analyzing the reasons behind these setbacks. It progresses to assess the potential integration of future technologies (10-20 years from now), exploring a feasible scenario and the force implications on learning, teachers, and the system. Examining recent attempts to implement technology in education reveals numerous reasons for failure. A significant contributing factor appears to be inherent conflicts within the education system's fundamental structure. These conflicts, involving goals, curricula, organizational structure, pedagogy, and student management, prevent the system from embracing reforms or new technologies. Envisioning a future where technology will deeply 'know' the students, 'sense' their environment, 'understand' the context and the situation, 'explain' and 'advise' them on the best suitable behavior or activity, the book anticipates applications in education ranging from ensuring personal safety and health to enhancing knowledge acquisition and decision-making. As the book explores the potential inevitability of technology in education, it recognizes the transformative impact on teachers and students and outlines possible desire scenario to aid in preparation, such as, personalized education to better suit student's capabilities, needs, and desires; how to motivate students to learn in an environment where all tasks can be done by machines; ethical issues; the new role of the school, the educator, and the system, etc. This book is especially suitable for teachers, educators, public officials, and anyone interested in the future of education. 606 $aEducational sociology 606 $aEducational technology 606 $aTeaching 606 $aSociology of Education 606 $aDigital Education and Educational Technology 606 $aDidactics and Teaching Methodology 615 0$aEducational sociology. 615 0$aEducational technology. 615 0$aTeaching. 615 14$aSociology of Education. 615 24$aDigital Education and Educational Technology. 615 24$aDidactics and Teaching Methodology. 676 $a371.334 700 $aArmony$b Yoav$01794616 702 $aHazzan$b Orit 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910887817703321 996 $aInevitability of AI Technology in Education$94335420 997 $aUNINA LEADER 03784nam 22005655 450 001 9910483689303321 005 20251113181701.0 010 $a3-030-66007-9 024 7 $a10.1007/978-3-030-66007-9 035 $a(CKB)4100000011747022 035 $a(MiAaPQ)EBC6469877 035 $a(PPN)253859026 035 $a(DE-He213)978-3-030-66007-9 035 $a(EXLCZ)994100000011747022 100 $a20210204d2021 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aRecent Metaheuristic Computation Schemes in Engineering /$fby Erik Cuevas, Alma Rodríguez, Avelina Alejo-Reyes, Carolina Del-Valle-Soto 205 $a1st ed. 2021. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021. 215 $a1 online resource (xi, 277 pages) 225 1 $aStudies in Computational Intelligence,$x1860-9503 ;$v948 311 1 $a3-030-66006-0 327 $aIntroductory Concepts of Metaheuristic Computation -- A Metaheuristic Scheme Based on the Hunting Model of Yellow Saddle Goatfish -- Metaheuristic Algorithm Based on Hybridization of Invasive Weed Optimization and Estimation Distribution Methods -- Corner Detection Algorithm Based on Cellular Neural Networks (CNN) and Differential Evolution (DE) -- Blood Vessel Segmentation Using Differential Evolution Algorithm -- Clustering Model Based on the Human Visual System -- Metaheuristic Algorithms for Wireless Sensor Networks -- Metaheuristic Algorithms Applied to the Inventory Problem. 330 $aThis book includes two objectives. The first goal is to present advances and developments which have proved to be effective in their application to several complex problems. The second objective is to present the performance comparison of various metaheuristic techniques when they face complex optimization problems. The material has been compiled from a teaching perspective. Most of the problems in science, engineering, economics, and other areas can be translated as an optimization or a search problem. According to their characteristics, some problems can be simple that can be solved by traditional optimization methods based on mathematical analysis. However, most of the problems of practical importance in engineering represent complex scenarios so that they are very hard to be solved by using traditional approaches. Under such circumstances, metaheuristic has emerged as the best alternative to solve this kind of complex formulations. This book is primarily intended for undergraduate and postgraduate students. Engineers and application developers can also benefit from the book contents since it has been structured so that each chapter can be read independently from the others, and therefore, only potential interesting information can be quickly available for solving an industrial problem at hand. . 410 0$aStudies in Computational Intelligence,$x1860-9503 ;$v948 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aCooperating objects (Computer systems) 606 $aComputational Intelligence 606 $aArtificial Intelligence 606 $aCyber-Physical Systems 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aCooperating objects (Computer systems) 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aCyber-Physical Systems. 676 $a519.6 700 $aCuevas$b Erik$0761169 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483689303321 996 $aRecent metaheuristic computation schemes in engineering$92918867 997 $aUNINA