Differential Prediction for Disadvantaged Students and Schools: The Role of High School Characteristics

IF 3.5 3区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Aera Open Pub Date : 2024-04-29 DOI:10.1177/23328584241245088
Preeya P. Mbekeani, Daniel Koretz
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Abstract

Validity studies of college admissions tests have found that, on average, students who are Black or Hispanic earn lower freshman grade-point averages (FGPAs) than predicted by these test scores. This differential prediction is used as a measure of bias. These studies, however, conflate student and school characteristics. The differential prediction affecting minoritized groups may arise in part because they attended high schools in which college enrollees, regardless of race, perform worse than predicted. Using data on students who graduated from New York City public high schools in 2011 and enrolled in the City University of New York, we examined this using college admissions and high school test scores. There was no differential prediction based on race/ethnicity among students within high schools when school characteristics were accounted for. Instead, overprediction of FGPA was associated with the school proportion of enrolled Black and Hispanic students. Overprediction was larger in models with high school test scores.
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弱势学生和学校的差异预测:高中特征的作用
对大学入学考试的有效性研究发现,平均而言,黑人或西班牙裔学生的新生平均学分绩点(FGPA)低于这些考试成绩的预测值。这种预测差异被用来衡量偏差。然而,这些研究混淆了学生和学校的特征。影响少数群体的预测差异可能部分是由于他们就读的高中,不论种族,大学入学成绩都比预测的要差。我们利用 2011 年从纽约市公立高中毕业并进入纽约市立大学学习的学生数据,通过大学录取和高中考试成绩对这一问题进行了研究。在考虑学校特征的情况下,高中学生之间并不存在基于种族/族裔的预测差异。相反,对 FGPA 的预测过高与学校黑人和西班牙裔学生的入学比例有关。在包含高中考试成绩的模型中,预测过高的程度更大。
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来源期刊
Aera Open
Aera Open EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
5.00
自引率
7.10%
发文量
60
审稿时长
15 weeks
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