ConceptScape: Collaborative Concept Mapping for Video Learning
ConceptScape: Collaborative Concept Mapping for Video Learning
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DOI：
10.1145/3173574.3173961
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发表时间：
2018-04
期刊：
影响因子：
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通讯作者：
Ching Liu;Juho Kim;Hao-Chuan Wang
中科院分区：
文献类型：
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作者：
Ching Liu;Juho Kim;Hao-Chuan Wang
虽然视频已成为广泛采用的在线学习媒体，但现有的视频播放器对导航和学习的支持有限。很难找到视频中与特定概念相关的部分。此外，大多数视频播放器提供被动观看，从而使元认知技能有限的学习者难以深入参与内容并反思他们的理解。为了支持概念驱动的导航和理解的讲座视频，我们提出了ConceptScape，一个系统，生成并呈现一个概念图的讲座视频。ConceptScape通过促使人群工作者在视频上具体化思考来协同生成概念图。我们提出了两项研究表明，（1）交互式概念图可以是基于概念的视频导航和理解的有用工具，（2）与ConceptScape，新手人群工作者可以协同生成复杂的概念图，匹配的质量专家。
While video has become a widely adopted medium for online learning, existing video players provide limited support for navigation and learning. It is difficult to locate parts of the video that are linked to specific concepts. Also, most video players afford passive watching, thus making it difficult for learners with limited metacognitive skills to deeply engage with the content and reflect on their understanding. To support concept-driven navigation and comprehension of lecture videos, we present ConceptScape, a system that generates and presents a concept map for lecture videos. ConceptScape engages crowd workers to collaboratively generate a concept map by prompting them to externalize reflections on the video. We present two studies to show that (1) interactive concept maps can be useful tools for concept-based video navigation and comprehension, and (2) with ConceptScape, novice crowd workers can collaboratively generate complex concept maps that match the quality of those by experts.