Building Equitable Education Datasets for Developing Nations: Equity-Minded Data Collection and Disaggregation to Improve Schools, Districts, and Communities

被引：1

作者：

Taylor, Z. W. ^{[1
]}

Kugiya, Jase ^{[2
]}

Charran, Chelseaia ^{[3
]}

Childs, Joshua ^{[2
]}

机构：

[1] Univ Southern Mississippi, Educ & Human Sci, Hattiesburg, MS 39406 USA

[2] Univ Texas Austin, Dept Educ Leadership & Policy, Austin, TX 78712 USA

[3] Univ Quebec Trois Rivieres, Dept Psychoeduc, Trois Rivieres, PQ G8Z 4M3, Canada

来源：

EDUCATION SCIENCES | 2023年 / 13卷 / 04期

关键词：

education; datasets; big data; decision-making; developing nations; equity; DECISION-MAKING; STUDENTS; ATTAINMENT;

D O I：

10.3390/educsci13040348

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

Many studies of education engage with large datasets to attempt to solve educational problems. However, no studies have provided a systematic overview of how large datasets could be compiled with an eye toward solving educational problems related to equity, especially as it relates to racial, gender, and socioeconomic equity. This study provides a synthesis of literature and recommendations for how developing nations can learn from peers and collect, disaggregate, and analyze data in ways that promote equity, thus improving schools, school districts, and communities.

引用

页数：13