不平衡的进步:美国学区学术表现的最新趋势

IF 3.5 1区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH
Kaylee T. Matheny, M. Thompson, Carrie Townley-Flores, Sean F. Reardon
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引用次数: 3

摘要

我们使用斯坦福教育数据档案的数据来描述2009年至2019年间学区平均学业成绩的趋势。虽然平均而言,各学区的考试成绩提高幅度不大(每年约0.001标准差),但各学区之间的差异很大。此外,我们发现非贫困学生和贫困学生以及白人和黑人学生之间的平均考试成绩差距正在扩大;白人和西班牙裔学生之间的差距正在缩小。我们没有发现成就-公平协同效应或权衡的证据:总体成就的提高与成就差距的趋势无关。最后,我们发现成绩差距趋势的最强预测因子是地区内种族和社会经济隔离的水平和趋势,以及获得认证教师的差异变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Uneven Progress: Recent Trends in Academic Performance Among U.S. School Districts
We use data from the Stanford Education Data Archive to describe district-level trends in average academic achievement between 2009 and 2019. Although on average school districts’ test scores improved very modestly (by about 0.001 standard deviations per year), there is significant variation among districts. Moreover, we find that average test score disparities between nonpoor and poor students and between White and Black students are growing; those between White and Hispanic students are shrinking. We find no evidence of achievement-equity synergies or trade-offs: Improvements in overall achievement are uncorrelated with trends in achievement disparities. Finally, we find that the strongest predictors of achievement disparity trends are the levels and trends in within-district racial and socioeconomic segregation and changes in differential access to certified teachers.
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来源期刊
American Educational Research Journal
American Educational Research Journal EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
8.70
自引率
0.00%
发文量
19
期刊介绍: The American Educational Research Journal (AERJ) is the flagship journal of the American Educational Research Association, featuring articles that advance the empirical, theoretical, and methodological understanding of education and learning. It publishes original peer-reviewed analyses that span the field of education research across all subfields and disciplines and all levels of analysis. It also encourages submissions across all levels of education throughout the life span and all forms of learning. AERJ welcomes submissions of the highest quality, reflecting a wide range of perspectives, topics, contexts, and methods, including interdisciplinary and multidisciplinary work.
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