华东师范大学学报(自然科学版) ›› 2024, Vol. 2024 ›› Issue (5): 114-127.doi: 10.3969/j.issn.1000-5641.2024.05.011

• 教育数据管理 • 上一篇    下一篇

面向在线教育场景的异构数据生成工具

周伟, 王可, 胡卉芪*()   

  1. 华东师范大学 数据科学与工程学院, 上海 200062
  • 收稿日期:2024-07-03 出版日期:2024-09-25 发布日期:2024-09-23
  • 通讯作者: 胡卉芪 E-mail:hqhu@dase.ecnu.edu.cn
  • 基金资助:
    国家重点研发计划项目(2023YFC3341202)

Heterogeneous data generation tools for online education scenarios

Wei ZHOU, Ke WANG, Huiqi HU*()   

  1. School of Data Science and Engineering, East China Normal University, Shanghai 200062, China
  • Received:2024-07-03 Online:2024-09-25 Published:2024-09-23
  • Contact: Huiqi HU E-mail:hqhu@dase.ecnu.edu.cn

摘要:

在数字化教育应用领域, 在线课堂等平台的开发人员在追求数据驱动的优化过程中, 面临着隐私问题和现有数据集规模不足的挑战. 针对此, 构建了一种适应教育特性的异构数据模型, 并实现了相应的数据生成工具 (E-Tools), 用于模拟复杂教育场景下的数据交互. 实验表明, 该工具在多种数据规模下, 都能保持高效的数据生成速度 (64 ~ 74 $ {\rm{MB}}\cdot{\rm{s}}^{-1} $), 展现了良好的线性扩展能力, 验证了所提模型的有效性及工具生成较大数据量的能力. 同时, 设计了反映学生学习行为的异构数据查询负载, 为教育平台的性能评估与优化提供了强有力的支持.

关键词: 在线教育, 异构数据, 查询负载

Abstract:

In the digital education application domain, developers of platforms such as online classrooms face the challenges of privacy issues and existing datasets’ insufficient size in their pursuit of data-driven optimization. To address this, a set of heterogeneous data models adapted to the characteristics of education were constructed, and corresponding data generation tools (E-Tools) that can be used to simulate data interactions in complex educational scenarios were implemented. Experimental results have shown that the tool can maintain an efficient data generation speed (64–74 $ {\rm{MB}}\cdot {{\rm{s}}^{-1}} $) under a variety of data sizes, demonstrating good linear scaling ability, which validates the model’s effectiveness and the tool’s ability to generate larger data volumes. A heterogeneous data query load reflecting students’ learning behaviors was also designed to provide strong support for performance evaluation and the education platform’s optimization.

Key words: online education, heterogeneous data, query loads

中图分类号: