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Titlebook: Learning Technologies for Transforming Large-Scale Teaching, Learning, and Assessment; Demetrios Sampson,J. Michael Spector,Stylianos Ser

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書(shū)目名稱(chēng)Learning Technologies for Transforming Large-Scale Teaching, Learning, and Assessment
編輯Demetrios Sampson,J. Michael Spector,Stylianos Ser
視頻videohttp://file.papertrans.cn/583/582806/582806.mp4
概述Represents the very latest work in the area where Internet, information and communications technology, learning psychology and instructional design intersect.Emphasizes implications for teacher educat
圖書(shū)封面Titlebook: Learning Technologies for Transforming Large-Scale Teaching, Learning, and Assessment; Demetrios Sampson,J. Michael Spector,Stylianos Ser
描述.This volume provides a contemporary glance at the drastically expanding field of delivering large-scale education to unprecedented numbers of learners. It compiles papers presented at the CELDA (Cognition and Exploratory Learning in the Digital Age) conference, which has a goal of continuing to address these challenges and promote the effective use of new tools and technologies to support teaching, learning and assessment. Given the emerging global trend to exploit the potential of existing digital technologies to improve the teaching, learning and assessment experiences for all learners in real-life contexts, this topic is a unifying theme for this volume..The book showcases how emerging educational technologies and innovative practices have been used to address core global educational challenges. It provides state-of-the-art insights and case studies of exploiting innovative learning technologies, including Massive Open Online Courses and educational data analytics, to address key global challenges spanning from online Teacher Education to large-scale coding competence development. This volume will be of interest to academics and professional practitioners working in the area of
出版日期Book 2019
關(guān)鍵詞Large-Scale Teaching and Learning; Online Learning; Blended Learning; Educational Technology; Educationa
版次1
doihttps://doi.org/10.1007/978-3-030-15130-0
isbn_softcover978-3-030-15132-4
isbn_ebook978-3-030-15130-0
copyrightSpringer Nature Switzerland AG 2019
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978-3-030-15132-4Springer Nature Switzerland AG 2019
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Releasing Personal Information Within Learning Analytics Systemsning analytics systems and various constructs closely related to individual characteristics of students, it is concluded that students need to be equally involved when implementing learning analytics systems at higher education institutions.
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Online Learners’ Navigational Patterns Based on Data Mining in Terms of Learning Achievementhomepage, content, discussion, messaging, profile, assessment, feedback, and ask the instructor. Data transformed into sequential patterns by the researchers were organized in navigational pattern graphics by taking frequency and ratio into consideration. The . test was used to test the significance
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Performance Analysis of a Serial Natural Language Processing Pipeline for Scaling Analytics of Acadesitions in higher education, a subset of the British Academic Written English (BAWE) corpus. It elaborates on computational requirements of analytics elements involving Natural Language Processing (NLP) and offers recommendations for building scalable big data NLP pipelines adapted to the analysis o
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