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Race to the Top-Early Learning Challenge (RTT-ELC): Descriptive Study of Tiered Quality Rating and Improvement Systems (TQRIS)

Author

Listed:
  • Gretchen Kirby
  • Pia Caronongan
  • Andrea Mraz Esposito
  • Lauren Murphy
  • Megan Shoji
  • Patricia Del Grosso
  • Wamaitha Kiambuthi
  • Melissa Clark

Abstract

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.

Suggested Citation

  • Gretchen Kirby & Pia Caronongan & Andrea Mraz Esposito & Lauren Murphy & Megan Shoji & Patricia Del Grosso & Wamaitha Kiambuthi & Melissa Clark, "undated". "Race to the Top-Early Learning Challenge (RTT-ELC): Descriptive Study of Tiered Quality Rating and Improvement Systems (TQRIS)," Mathematica Policy Research Reports f7eb0ac082d143359d14baecd, Mathematica Policy Research.
    • Handle: RePEc:mpr:mprres:f7eb0ac082d143359d14baecd4d347bc
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    File URL: https://www.mathematica.org/-/media/publications/pdfs/rtt-elc-master-data-collection-protocol.pdf
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    More about this item

    Keywords

    Race to the Top; Early Learning Challenge; Quality Rating and Improvement Systems; QRIS;
    All these keywords.

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