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Titlebook: Bridging Human Intelligence and Artificial Intelligence; Mark V. Albert,Lin Lin,Lemoyne S. Dunn Book 2022 Association for Educational Comm

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發(fā)表于 2025-3-21 18:19:15 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Bridging Human Intelligence and Artificial Intelligence
影響因子2023Mark V. Albert,Lin Lin,Lemoyne S. Dunn
視頻videohttp://file.papertrans.cn/191/190760/190760.mp4
發(fā)行地址Offers a forward-thinking, multi perspective for significant and sustained improvement in learning at all levels.Includes links to promising technologies available at no cost and accessible to all rea
學(xué)科分類(lèi)Educational Communications and Technology: Issues and Innovations
圖書(shū)封面Titlebook: Bridging Human Intelligence and Artificial Intelligence;  Mark V. Albert,Lin Lin,Lemoyne S. Dunn Book 2022 Association for Educational Comm
影響因子This edited volume is based on contributions from the TCET-AECT “Human-Technology Frontier: Understanding the Learning of Now to Prepare for the Work of the Future Symposium” held in Denton, Texas on May 16-18, sponsored by AECT. The authors embrace an integrative approach to designing and implementing advances technologies in learning and instruction, and focus on the emerging themes of artificial intelligence, human-computer interactions, and the resulting instructional design. The volume will be divided into four parts: (1) .Trends and future. in learning and learning technologies expected in the next 10 years; (2) .Technologies. likely to have a significant impact on learning in the next 10 years; (3) .Challenges. that will need to be addressed and resolved in order to achieve significant and sustained improvement in learning; and (4) .Reflections. and insights from the Symposium that should be pursued and that can form the basis for productive research collaborations. The primary audience for this volume is academics and researchers in disciplines such as artificial intelligence, cognitive science, computer science, educational psychology, instructional design, human-computer
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https://doi.org/10.1007/978-3-322-97794-6are presented followed by different pre-trained models in the fields of computer vision and natural language processing. We explored prominent models like VGG-16, Inception, ULMFiT, and BERT. After mentioning the successful models, applications and limitations of transfer learning have been discussed.
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Book 2022of the Future Symposium” held in Denton, Texas on May 16-18, sponsored by AECT. The authors embrace an integrative approach to designing and implementing advances technologies in learning and instruction, and focus on the emerging themes of artificial intelligence, human-computer interactions, and t
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,Bedingte Immunisierung von Entnahmepl?nen, subcortical nuclei that are responsible for a host of tasks including procedural learning, cognition, and emotion. Within this chapter, the parallels between the basal ganglia and current machine learning are clearly evaluated with thoughtful deliberation of their future relationship.
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