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来源类型 | Research Report |
规范类型 | 报告 |
Identifying High-Performing Schools for Historically Underserved Students | |
其他题名 | Exploring a Multistate Model |
Theresa Anderson; Erica Blom; Constance A. Lindsay; Semhar Gebrekristos; Macy Rainer; Carolyn Vilter | |
发表日期 | 2020-01-30 |
出版年 | 2020 |
语种 | 英语 |
概述 | This report describes the results of the model refining phase of the Robust and Equitable Measures to Inspire Quality Schools (REMIQS) project. The project seeks to inspire high schools to generate positive long-term outcomes for historically underserved students. In this phase, we develop a multistate model to identify the best-performing schools in Kentucky, Massachusetts, and Virginia. We find that a |
摘要 | This report describes the results of the model refining phase of the Robust and Equitable Measures to Inspire Quality Schools (REMIQS) project. The project seeks to inspire high schools to generate positive long-term outcomes for historically underserved students. In this phase, we develop a multistate model to identify the best-performing schools in Kentucky, Massachusetts, and Virginia. We find that a multistate model is possible but is limited by the comparability of data and by fundamental differences in state contexts; schools that “add value” based on traditional test score measures are not necessarily equally good at enrolling students in college; and, generally, high schools that excel along one success metric may not excel along all or even several metrics. A separate technical appendix provides details about the model described in this report. |
主题 | Education and Training |
URL | https://www.urban.org/research/publication/identifying-high-performing-schools-historically-underserved-students |
来源智库 | Urban Institute (United States) |
资源类型 | 智库出版物 |
条目标识符 | http://119.78.100.153/handle/2XGU8XDN/480886 |
推荐引用方式 GB/T 7714 | Theresa Anderson,Erica Blom,Constance A. Lindsay,et al. Identifying High-Performing Schools for Historically Underserved Students. 2020. |
条目包含的文件 | ||||||
文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
identifying_high-per(2206KB) | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 |
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