| 来源类型 | Publication |
| 来源ID | Master Data Collection Protocol |
| Race to the Top-Early Learning Challenge (RTT-ELC): Descriptive Study of Tiered Quality Rating and Improvement Systems (TQRIS) | |
| Gretchen Kirby; Pia Caronongan; Andrea Mraz Esposito; Lauren Murphy; Megan Shoji; Patricia Del Grosso; Wamaitha Kiambuthi; and Melissa Clark | |
| 发表日期 | 2015-01-30 |
| 出版者 | Princeton, NJ: Mathematica Policy Research |
| 出版年 | 2015 |
| 语种 | 英语 |
| 概述 | This master data collection protocol describes the data that Mathematica collected for the Race to the Top-Early Learning Challenge Study of Tiered Quality Rating and Improvement Systems. This study was conducted for the Department of Education’s Institute of Education Sciences.", |
| 摘要 | This master data collection protocol describes the data that Mathematica collected for the Race to the Top-Early Learning Challenge Study of Tiered Quality Rating and Improvement Systems. This study was conducted for the Department of Education’s Institute of Education Sciences. The data were collected from reviews of applications, documents, and interviews with state administrators. |
| URL | https://www.mathematica.org/our-publications-and-findings/publications/race-to-the-top-early-learning-challenge-rtt-elc-descriptive-study-of-tiered-quality-rating |
| 来源智库 | Mathematica Policy Research (United States) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/487955 |
| 推荐引用方式 GB/T 7714 | Gretchen Kirby,Pia Caronongan,Andrea Mraz Esposito,et al. Race to the Top-Early Learning Challenge (RTT-ELC): Descriptive Study of Tiered Quality Rating and Improvement Systems (TQRIS). 2015. |
| 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 | ||
| RTT ELC Master Data （641KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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