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Titlebook: Emerging Technologies for Education; Third International Tianyong Hao,Wei Chen,Rynson Lau Conference proceedings 2018 Springer Nature Swit

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發(fā)表于 2025-3-21 19:17:59 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Emerging Technologies for Education
副標題Third International
編輯Tianyong Hao,Wei Chen,Rynson Lau
視頻videohttp://file.papertrans.cn/309/308417/308417.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Emerging Technologies for Education; Third International  Tianyong Hao,Wei Chen,Rynson Lau Conference proceedings 2018 Springer Nature Swit
描述.This book constitutes the thoroughly refereed post-workshop proceedings of the Third International Symposium, SETE 2018, held in conjunction with ICWL 2018, Chiang Mai, Thailand, in August 2018..The 23 full and 3 short papers were carefully reviewed and selected from 51 submissions.? The papers have been organized in the following topical sections: Emerging Technologies of Design, Model and Framework of Learning Systems; Emerging Technologies Support for Intelligent Tutoring; Emerging Technologies Support for Game-Based and Joyful Learning; Emerging Technologies of Pedagogical Issues; UMLL (International Symposium on User Modeling and Language Learning); ETLTL (International Workshop on Educational Technology for Language and Translation Learning). . .
出版日期Conference proceedings 2018
關鍵詞Adaptive learning; Artificial intelligence; Computer supported collaborative learning (CSCL); Curriculu
版次1
doihttps://doi.org/10.1007/978-3-030-03580-8
isbn_softcover978-3-030-03579-2
isbn_ebook978-3-030-03580-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2018
The information of publication is updating

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https://doi.org/10.1007/978-3-030-03580-8Adaptive learning; Artificial intelligence; Computer supported collaborative learning (CSCL); Curriculu
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The Clash of Language: Bakhtin and , on the data flow. It is rather hard make accurate analysis possible in the past. The Quantified Self Learning Algorithm (QSLA) will be the key to analyze education big data and realize adaptive learning. The learning process of foreign language writing is a complex system. It is influenced by many
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https://doi.org/10.1057/9780333977439utomated or semi-automated grading, for the management of student modeling, and for providing the teacher with feedback about the learners. Various models for the representation of peer assessment data have been proposed in the literature. In this paper we build on the availability of such a model b
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