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Titlebook: Artificial Intelligence in Education; 18th International C Elisabeth André,Ryan Baker,Benedict du Boulay Conference proceedings 2017 Spring

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發(fā)表于 2025-3-21 18:04:22 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Artificial Intelligence in Education
期刊簡稱18th International C
影響因子2023Elisabeth André,Ryan Baker,Benedict du Boulay
視頻videohttp://file.papertrans.cn/163/162442/162442.mp4
發(fā)行地址Includes supplementary material:
學(xué)科分類Lecture Notes in Computer Science
圖書封面Titlebook: Artificial Intelligence in Education; 18th International C Elisabeth André,Ryan Baker,Benedict du Boulay Conference proceedings 2017 Spring
影響因子.This book constitutes the refereed proceedings of the 18th International Conference on Artificial Intelligence in Education, AIED 2017, held in Wuhan,China, in June/July 2017. The 36 revised full papers presented together with 4 keynotes, 37 poster, presentations, 4 doctoral consortium papers, 5 industry papers, 4 workshop abstracts, and 2 tutorial abstracts were carefully reviewed and selected from 159 submissions. The conference provides opportunitiesfor the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology,linguistics as well as many domain-specific areas..
Pindex Conference proceedings 2017
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978-3-319-61424-3Springer International Publishing AG 2017
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/162442.jpg
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Delinquency Prevention and Labelingt have been demonstrated. Our work focuses on Invention activities, inquiry activities in which students generate representations that explain data presented as contrasting cases. To help teachers implement these activities in their classrooms, we have created and pilot-tested a dedicated adaptive c
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https://doi.org/10.1007/978-1-4615-7029-5he group. In this paper we combine data-mining and visualization tools to support teachers’ understanding of learners’ activities in an inquiry based learning environment. We use supervised learning to recognize salient states of activity in the group’s work, such as reaching a solution to a problem
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