ExeVis: concept-based visualization of exercises in online learning

IF 1.7 4区计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Visualization Pub Date : 2024-03-14 DOI:10.1007/s12650-024-00956-4

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Abstract

In recent years, online learning has gained popularity and proven to be an effective way of education. Numerous studies have analyzed teaching materials and learning behaviors. However, most of the existing studies ignore the relationships between learning concepts and exercises, which can convey teaching performance and student behaviors. Presenting the relationships between concepts and exercises in online learning not only can help educators explore the distribution of exercises and concepts to consolidate knowledge but also can provide intuitive feedback on student behavior in online courses, which can enhance the teaching strategy. In this work, we extract learning concepts from exercises, establish logical relationships between concepts and exercises, and construct the hierarchical structures of concepts via both automatic models and semi-automatic models. To help users analyze and evaluate concepts and exercises effectively and intuitively, we design and implement a visual analysis prototype system, named ExeVis, integrating multiple interactive visualization graphs. ExeVis is equipped with multiple interactive and intuitive visualization charts including a control view to select and display basic information, an overview with hierarchical structures to present the distribution and mastery of concepts and exercises, a correlation view to reveal relationships between exercises, and a performance view to show individual capability. Case studies with real data and expert interviews demonstrate the usefulness and effectiveness of ExeVis in providing educators with valuable insights into the appropriateness of exercises and enabling them to adjust their teaching methods.

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ExeVis：基于概念的在线学习练习可视化

摘要近年来，在线学习越来越受欢迎，并被证明是一种有效的教育方式。许多研究对教材和学习行为进行了分析。然而，大多数现有研究都忽略了学习概念与练习之间的关系，而这种关系能够传递教学效果和学生行为。呈现在线学习中概念与习题之间的关系，不仅能帮助教育者探索习题和概念的分布，巩固知识，还能直观地反馈学生在在线课程中的行为，从而提升教学策略。在这项工作中，我们从练习中提取学习概念，建立概念与练习之间的逻辑关系，并通过自动模型和半自动模型构建概念的层次结构。为了帮助用户有效、直观地分析和评价概念与习题，我们设计并实现了一个集成多种交互式可视化图形的可视化分析原型系统，命名为 ExeVis。ExeVis 配备了多个交互式直观可视化图表，包括用于选择和显示基本信息的控制视图、用于呈现概念和练习分布及掌握程度的分层结构概览、用于揭示练习间关系的关联视图以及用于显示个人能力的绩效视图。利用真实数据和专家访谈进行的案例研究证明了 ExeVis 的实用性和有效性，它为教育工作者提供了有关练习是否合适的宝贵见解，使他们能够调整自己的教学方法。图表摘要

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来源期刊

Journal of Visualization COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY

CiteScore

3.40

自引率

5.90%

发文量

审稿时长

>12 weeks

期刊介绍： Visualization is an interdisciplinary imaging science devoted to making the invisible visible through the techniques of experimental visualization and computer-aided visualization. The scope of the Journal is to provide a place to exchange information on the latest visualization technology and its application by the presentation of latest papers of both researchers and technicians.