连接阅读和绘图:在绘制概念图时,阅读注释在促进反馈中的作用

IF 3 2区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Information Systems Pub Date : 2024-09-06 DOI:10.1016/j.is.2024.102458
Oscar Díaz, Xabier Garmendia
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引用次数: 0

摘要

概念图是组织知识的可视化工具,常用于教育和设计领域。这一过程通常涉及阅读和开发概念模型,其中反馈至关重要。学习者(如学生、设计师)通常会参考阅读材料,并根据自己绘制的地图从指导者(如教师、利益相关者)那里获得反馈。然而,学习者所做的注释(如高亮部分)通常不为指导者所见,从而限制了有针对性的反馈。我们建议将注释做法纳入概念图。学习者可以突出显示文本,并将这些突出显示链接到概念图中现有的或新创建的概念。这样,教师就可以同时访问概念图和相关阅读内容,从而获得更好的反馈。Concept&Go 是 CmapCloud 编辑器的一个插件,它实现了这一愿景。该插件旨在实现概念图绘制过程中绘图、阅读和反馈之间的相互作用。通过焦点小组(5 人)和UTAUT 评估(12 人)证明了这种方法的有效性。Concept&Go已公开发布。
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Bridging reading and mapping: The role of reading annotations in facilitating feedback while concept mapping

Concept maps are visual tools for organizing knowledge, commonly used in education and design. The process often involves reading and developing conceptual models, where feedback is crucial. Learners (e.g., students, designers) often refer to reading materials, and receive feedback from instructors (e.g., teachers, stakeholders) based on the maps they create. However, annotations made by learners, like highlights, are usually not visible to instructors, limiting tailored feedback. We propose incorporating annotation practices into concept mapping. Learners could highlight text and link these highlights to existing or newly created concepts in their concept map. This way, instructors can access both the concept map and the relevant readings for better feedback. This vision is realized through Concept&Go, a plug-in for the editor CmapCloud. This extension aims at the interplay between mapping, reading, and feedback during concept mapping. The effectiveness of this approach is demonstrated through a focus group (n=5) and a UTAUT evaluation (n=12). Concept&Go is publicly available.

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来源期刊
Information Systems
Information Systems 工程技术-计算机:信息系统
CiteScore
9.40
自引率
2.70%
发文量
112
审稿时长
53 days
期刊介绍: Information systems are the software and hardware systems that support data-intensive applications. The journal Information Systems publishes articles concerning the design and implementation of languages, data models, process models, algorithms, software and hardware for information systems. Subject areas include data management issues as presented in the principal international database conferences (e.g., ACM SIGMOD/PODS, VLDB, ICDE and ICDT/EDBT) as well as data-related issues from the fields of data mining/machine learning, information retrieval coordinated with structured data, internet and cloud data management, business process management, web semantics, visual and audio information systems, scientific computing, and data science. Implementation papers having to do with massively parallel data management, fault tolerance in practice, and special purpose hardware for data-intensive systems are also welcome. Manuscripts from application domains, such as urban informatics, social and natural science, and Internet of Things, are also welcome. All papers should highlight innovative solutions to data management problems such as new data models, performance enhancements, and show how those innovations contribute to the goals of the application.
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