洪丹丹, 李飞, 姚磊, 徐墨, 锁志海. 在线学习行为分析数据可视化快速开发框架设计与实践[J]. 微电子学与计算机, 2018, 35(7): 6-12.
引用本文: 洪丹丹, 李飞, 姚磊, 徐墨, 锁志海. 在线学习行为分析数据可视化快速开发框架设计与实践[J]. 微电子学与计算机, 2018, 35(7): 6-12.
HONG Dan-dan, LI Fei, YAO Lei, XU Mo, SUO Zhi-hai. Design and Implementation of A Fast Data Visualization Framework For E-learning Behavior Analysis[J]. Microelectronics & Computer, 2018, 35(7): 6-12.
Citation: HONG Dan-dan, LI Fei, YAO Lei, XU Mo, SUO Zhi-hai. Design and Implementation of A Fast Data Visualization Framework For E-learning Behavior Analysis[J]. Microelectronics & Computer, 2018, 35(7): 6-12.

在线学习行为分析数据可视化快速开发框架设计与实践

Design and Implementation of A Fast Data Visualization Framework For E-learning Behavior Analysis

  • 摘要: 为了充分挖掘高校在线学习平台中的用户学习行为, 发挥各类用户行为数据的价值并增强各类在线统计数据的可读性, 以统计学理论为基础, 结合JFinal轻量级框架及ECharts前端数据可视化技术研究设计了一款可扩展、通用性强的轻量级数据分析可视化快速开发框架.并以典型的在线学习平台中用户最喜爱课程分析实例为背景, 对其部分数据库模型、算法指标模型、前端数据可视化及后端数据处理等关键技术进行了详细研究及实现.以框架在西安交通大学在线学习平台中的实践结果表明, 其可以满足数据分析快速可视化需求且支持数据关联分析和数据逐级下钻可视化.最后, 对未来大数据环境下的高校学习平台用户学习行为分析提出建设意见.

     

    Abstract: In order to analyze the userse-leaning behaviors in university campus, a fast and extensible development framework is designed and implemented that combined with JFinal lightweight framework and ECharts visualization technology. Based on the university e-leaning platform, a typical analysis theme was chosen as the development background, the key technologies such as algorithms model, front-end data visualization, database model and back-end data processing were studied and implemented in detail. The result of the implementation shows that the framework developed in this paper can support various visualization requirements of the data analysis in the e-learning platform. Meanwhile, the future constructions were put forward for the e-learning behavior analysis in big data environment.

     

/

返回文章
返回