教育大数据可视化研究综述

doi:10.3778/j.issn.1673-9418.2009014

摘要/Abstract

摘要：

教育大数据可视化分析对于复杂教育规律的理解与挖掘具有重要作用，已成为当前教育信息科学研究领域的重要课题。首先归纳了教育大数据的典型特征，从促进学生元认知发展、辅助教师监督学习过程及提升管理者科学决策水平三个角度介绍了教育大数据应用的最新研究成果，并简述了利用教育大数据实施可视化分析的基本流程。然后重点对文本数据可视化、多维数据可视化、网络数据可视化、时间序列数据可视化以及地理空间数据可视化等五种主流的教育大数据可视化呈现方法进行特征描述，并给出具体的应用场景。随后介绍了动态查询与过滤技术、可缩放/变形界面技术和多视图联动技术三个实施教育大数据可视化的关键交互技术方法。最后依据最新研究动态，从多模态教育数据融合、人机交互、人机协同范式以及教育数据可视化设计的标准规范和评价体系四方面对教育大数据可视化未来研究方向进行了展望。

关键词: 教育大数据;可视化分析, 大数据可视化；数据融合；人机交互

Abstract:

Visualization analysis of big data in education plays an important role in understanding and mining com-plex educational rules, which has become an important topic in the field of educational information science research. This paper first summarizes the typical characteristics of big data in education, introduces the latest research results in the application of big data in education from three aspects: promoting students?? metacognitive development, assis-ting teachers to supervise the learning process and improving managers?? scientific decision-making level, and describes the basic process of visual analysis using big data in education. Then, this paper focuses on five mainstream visua-lization presentation methods of big data in education, including text data visualization, multidimensional data vis-ualization, network data visualization, time series data visualization and geospatial data visualization, and gives specific application scenarios. Then it introduces the dynamic query and filter technology, scalable/deformable interface technology and multi-view linkage technology, three key interactive technology methods to implement the visuali-zation of big data in education. Finally, according to the latest research trends, the future research direction of big data visualization in education is prospected from four aspects: multi-mode education data fusion, man-machine interac-tion, man-machine collaboration paradigm, and the standard specification and evaluation system of visual design of education data.

Key words: big data in education, visualization analysis, big data visualization, data fusion, man-machine interaction

郑娅峰, 赵亚宁, 白雪, 傅骞. 教育大数据可视化研究综述[J]. 计算机科学与探索, 2021, 15(3): 403-422.

ZHENG Yafeng, ZHAO Yaning, BAI Xue, FU Qian. Survey of Big Data Visualization in Education[J]. Journal of Frontiers of Computer Science and Technology, 2021, 15(3): 403-422.

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