Heterogeneous data generation tools for online education scenarios
Received date: 2024-07-03
Online published: 2024-09-23
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
周伟 , 王可 , 胡卉芪 . 面向在线教育场景的异构数据生成工具[J]. 华东师范大学学报(自然科学版), 2024 , 2024(5) : 114 -127 . DOI: 10.3969/j.issn.1000-5641.2024.05.011
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
Key words: online education; heterogeneous data; query loads
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