{"title":"整体大于部分的总和:人工智能与教育和培训之间的交集的可能性和潜力","authors":"J. Cohn, E. Vorm, Erin Baker","doi":"10.1177/15485129221078519","DOIUrl":null,"url":null,"abstract":"The fields of Artificial Intelligence (AI) and Education & Training (E&T) are experiencing an unprecedented resur-gence. This is due in no small part to recent advances in the science and technology that drive discovery and inno-vation in these fields. The development of ever more pow-erful and efficient processing systems, a renaissance in allied fields like neuroscience, data analytics and visualiza-tion, cognitive science, cognitive computing, and advances in materials science have collectively enabled the solution of challenges to these fields which, only a decade ago, appeared insurmountable. Consequently, it is timely to explore the possibilities and potential benefits to be accrued when these two fields intersect. The goals of this special issue are threefold: (1) to promote understanding of AI for education and training applications, (2) to gain awareness of research and development activities in AI that are appli-cable to education and training applications, and (3) to characterize the reciprocal benefits that advances in education and training have on the further advancement of AI. The issue begins with two ‘‘perspective pieces’’ that set the stage for understanding different approaches viewing the between AI a in a that unique of to frame the discussion of aligning AI with E&T to learning","PeriodicalId":44661,"journal":{"name":"Journal of Defense Modeling and Simulation-Applications Methodology Technology-JDMS","volume":"48 1","pages":"125 - 126"},"PeriodicalIF":1.0000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The whole is greater than the sum of its parts: possibility and potential at the intersection between artificial intelligence and education & training\",\"authors\":\"J. Cohn, E. Vorm, Erin Baker\",\"doi\":\"10.1177/15485129221078519\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The fields of Artificial Intelligence (AI) and Education & Training (E&T) are experiencing an unprecedented resur-gence. This is due in no small part to recent advances in the science and technology that drive discovery and inno-vation in these fields. The development of ever more pow-erful and efficient processing systems, a renaissance in allied fields like neuroscience, data analytics and visualiza-tion, cognitive science, cognitive computing, and advances in materials science have collectively enabled the solution of challenges to these fields which, only a decade ago, appeared insurmountable. Consequently, it is timely to explore the possibilities and potential benefits to be accrued when these two fields intersect. The goals of this special issue are threefold: (1) to promote understanding of AI for education and training applications, (2) to gain awareness of research and development activities in AI that are appli-cable to education and training applications, and (3) to characterize the reciprocal benefits that advances in education and training have on the further advancement of AI. The issue begins with two ‘‘perspective pieces’’ that set the stage for understanding different approaches viewing the between AI a in a that unique of to frame the discussion of aligning AI with E&T to learning\",\"PeriodicalId\":44661,\"journal\":{\"name\":\"Journal of Defense Modeling and Simulation-Applications Methodology Technology-JDMS\",\"volume\":\"48 1\",\"pages\":\"125 - 126\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2022-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Defense Modeling and Simulation-Applications Methodology Technology-JDMS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/15485129221078519\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Defense Modeling and Simulation-Applications Methodology Technology-JDMS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/15485129221078519","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
The whole is greater than the sum of its parts: possibility and potential at the intersection between artificial intelligence and education & training
The fields of Artificial Intelligence (AI) and Education & Training (E&T) are experiencing an unprecedented resur-gence. This is due in no small part to recent advances in the science and technology that drive discovery and inno-vation in these fields. The development of ever more pow-erful and efficient processing systems, a renaissance in allied fields like neuroscience, data analytics and visualiza-tion, cognitive science, cognitive computing, and advances in materials science have collectively enabled the solution of challenges to these fields which, only a decade ago, appeared insurmountable. Consequently, it is timely to explore the possibilities and potential benefits to be accrued when these two fields intersect. The goals of this special issue are threefold: (1) to promote understanding of AI for education and training applications, (2) to gain awareness of research and development activities in AI that are appli-cable to education and training applications, and (3) to characterize the reciprocal benefits that advances in education and training have on the further advancement of AI. The issue begins with two ‘‘perspective pieces’’ that set the stage for understanding different approaches viewing the between AI a in a that unique of to frame the discussion of aligning AI with E&T to learning