教育中的大数据:用数据挖掘技术检测与学校有效性相关的ICT因素

F. Martínez-Abad, Adriana Gamazo, M. Rodríguez-Conde
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引用次数: 16

摘要

寻找与学校有效性相关的非情境过程因素已经成为一种传播非常广泛的研究,主要来自于无处不在的研究,其中包括对大规模评估的次要数据的分析。为了从2015年PISA评估的西班牙样本中发现与学校有效性相关的ICT因素,这项工作应用了数据挖掘的统计技术,特别是决策树,以优化这一过程。结果表明,尽管在教育环境和家庭中,信息通信技术的可用性和过度使用都是与低有效性相关的因素,但学生的其他更个性化的特征,如他们对信息通信技术管理的自我效能感的感知,或他们对技术使用的兴趣,可以被视为保护学校有效性的因素。最后,我们通过对以往研究的分析来讨论学校效能与学习成绩之间的关系,重点关注在这两个视角中发现的共同因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big Data in Education: Detection of ICT Factors Associated with School Effectiveness with Data Mining Techniques
The search for non-contextual process factors associated with school effectiveness has become a line of research with very broad dissemination, primarily from the ubiquity of research that includes analysis of secondary data from large-scale evaluations. With the aim of detecting ICT factors related to school effectiveness from the Spanish sample of the PISA 2015 evaluation, this work applies statistical techniques of data mining, specifically decision trees, for the optimization of the process. The results demonstrate that, while the availability and excessive use of ICTs, both in the educational environment and in the home, are factors associated with low effectiveness, other more personal characteristics of the pupils, such as their perception of self-efficacy in the management of ICT, or their own interest in the use of technologies, can be considered as factors in the protection of school effectiveness. We conclude by discussing the relationship between school effectiveness and academic performance through the analysis of previous studies, focusing on the common elements detected within both perspectives.
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