Translating sophisticated data analytic strategies regarding school attendance and absenteeism into targeted educational policy

IF 1.1 Q3 EDUCATION & EDUCATIONAL RESEARCH
C. Kearney, J. Childs
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引用次数: 1

Abstract

School attendance and absenteeism are critical targets of educational policies and practices that often depend heavily on aggregated attendance/absenteeism data. School attendance/absenteeism data in aggregated form, in addition to having suspect quality and utility, minimizes individual student variation, distorts detailed and multilevel modeling, and obscures underlying causes and disparities of absenteeism. Recent advances in data analytics/mining and modeling may assist researchers and other stakeholders by evaluating large-scale data sets in more targeted ways to identify key root causes and patterns of school absenteeism in a particular community, school, or group of students. This would allow for more accurate educational policies tailored to unique local conditions and student/family circumstances. This article provides a summary of recent algorithm- and model-based efforts in this regard. Algorithm-based efforts include classification and regression tree analysis, ensemble analysis, support vector machines, receiver operating characteristic analysis, and random forests. Model-based efforts include multilevel modeling, structural equation modeling, latent class analysis, and meta-analytic modeling. We then illustrate how these efforts can enhance a full and nuanced understanding of the root, interconnected causes of absenteeism, improve early warning systems, and assist multi-tiered systems of support interventions for absenteeism.
将关于出勤率和缺勤率的复杂数据分析策略转化为有针对性的教育政策
出勤率和缺勤率是教育政策和做法的关键目标,而这些政策和做法往往严重依赖于综合出勤/缺勤数据。综合形式的学校出勤/缺勤数据,除了质量和效用可疑之外,还最大限度地减少了学生的个体差异,扭曲了详细和多层次的模型,并模糊了缺勤的潜在原因和差异。数据分析/挖掘和建模方面的最新进展可以帮助研究人员和其他利益相关者以更有针对性的方式评估大规模数据集,以确定特定社区、学校或学生群体中学校缺勤的关键根本原因和模式。这将有助于制定更准确的教育政策,以适应独特的地方条件和学生/家庭情况。本文总结了最近在这方面基于算法和模型的努力。基于算法的工作包括分类和回归树分析、集成分析、支持向量机、接收器操作特征分析和随机森林。基于模型的工作包括多层建模、结构方程建模、潜在类分析和元分析建模。然后,我们说明了这些努力如何能够增强对缺勤根源的全面和细致的理解,改善早期预警系统,并协助支持缺勤干预的多层系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Improving Schools
Improving Schools EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
5.50
自引率
0.00%
发文量
4
期刊介绍: Improving Schools is for all those engaged in school development, whether improving schools in difficulty or making successful schools even better. The journal includes contributions from across the world with an increasingly international readership including teachers, heads, academics, education authority staff, inspectors and consultants. Improving Schools has created a forum for the exchange of ideas and experiences. Major national policies and initiatives have been evaluated, to share good practice and to highlight problems. The journal also reports on visits to successful schools in diverse contexts, and includes book reviews on a wide range of developmental issues.
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