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Titlebook: Digital Knowledge Maps in Education; Technology-Enhanced Dirk Ifenthaler,Ria Hanewald Book 2014 Springer Science+Business Media New York 2

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发表于 2025-3-21 16:29:26 | 显示全部楼层 |阅读模式
书目名称Digital Knowledge Maps in Education
副标题Technology-Enhanced
编辑Dirk Ifenthaler,Ria Hanewald
视频videohttp://file.papertrans.cn/280/279476/279476.mp4
概述Provides the only cross-disciplinary model for creating digital knowledge maps in higher education.Includes concrete examples of technology enhanced curriculum design prototypes utilizing digital know
图书封面Titlebook: Digital Knowledge Maps in Education; Technology-Enhanced  Dirk Ifenthaler,Ria Hanewald Book 2014 Springer Science+Business Media New York 2
描述.Digital knowledge maps are ‘at a glance’ visual representations that enable enriching, imaginative and transformative ways for teaching and learning, with the potential to enhance positive educational outcomes. The use of such maps has generated much attention and interest among tertiary education practitioners and researchers over the last few years as higher education institutions around the world begin to invest heavily into new technologies designed to provide online spaces within which to build resources and conduct activities. The key elements of this edited volume will comprise original and innovative contributions to existing scholarship in this field, with examples of pedagogical possibilities as they are currently practiced across a range of contexts. It will contain chapters that address, theory, research and practical issues related to the use of digital knowledge maps in all aspects of tertiary education and draws predominantly on international perspectives with a diverse group of invited contributors. Reports on empirical studies as well as theoretical/conceptual chapters that engage deeply with pertinent questions and issues raised from a pedagogical, social, cultur
出版日期Book 2014
关键词Concept mapping in higher education; Concept maps in higher education; Digital knowledge maps in highe
版次1
doihttps://doi.org/10.1007/978-1-4614-3178-7
isbn_softcover978-1-4939-5293-9
isbn_ebook978-1-4614-3178-7
copyrightSpringer Science+Business Media New York 2014
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Making Sense of Knowledge Integration MapsUsing multiple quantitative and qualitative methods in combination allows triangulating of changes in students’ understanding. This chapter introduces a novel form of concept map, called knowledge integration map (KIM), and uses KIMs as examples for an overview of concept map analysis methods. KIMs
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Investigating Through Concept Mapping Pre-service Teachers’ Thinking Progression About “e-Learning” about the concept of “e-learning” before and after the completion of the course .. It sought to understand what the students selected as keywords that were associated with e-learning for their pre-course concept maps and how they shifted them in the post-course concept maps to demonstrate their unde
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Collaborative Work with Digital Knowledge Maps on Improving ESL Learners’ Reading Skillsve learning for English as Second Language (ESL) learners. First, when learners discuss one text without representing their ideas visually, it is difficult to communicate or share their ideas with each other. Second, when learners work collaboratively, it is hard to determine each learner’s existing
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Researching Individual and Collaborative Pair Learning in Primary School Students Using Digital Knowely or individually formed, but also requires investigating equally the learning process as well as the learning outcomes. The dynamic nature of knowledge maps, their potential as a life-long learning strategy, and their evaluation through a valid assessment protocol could serve those requirements.
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Developing Australian Undergraduate Students’ Science Communication Skills Through Collaboratively C metropolitan campus—with the view of increasing learning outcomes in future years. It explores the impact and extent of the students’ learning, especially their prior knowledge, their attitude about working collaboratively in small groups, their perspective on using technology rich learning in gene
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