March 20, 2010
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Data-Driven Decision Making


Increasingly, school board members from around the country are using data to help make good decisions about improving public education for all children. Data-driven decision making can be used to better inform board decisions as school districts grapple with how to think systemically and strategically about reaching their student achievement goals.

Resources

  • NSBA Receives Grant to Help School Boards Use Data in Decision Making link type content icon
    The National School Boards Foundation has received a grant from the Bill & Melinda Gates Foundation to promote the effective use of data in school board decision-making. Over a 15-month period, NSBA will work with partner state school boards associations to develop training modules, online resources, and data tools.
  • Good Measures for Good Schools link type content icon
    How good are our schools? The Center for Public Education's Good Measures for Good Schools guide will help you answer this question.
  • Book: Improving School Board Decision-Making: The Data Connection pdf type content icon [PDF 962,475kb]
    A data guidebook for school board members from the National School Boards Foundation.
  • Testing and Assessment 101 pdf type content icon [PDF 436,591kb]
    From the American School Board Journal, January 2008, an article on testing and assessment terms and tools every board member needs to know to understand complex data.
  • ASBJ article: Crunching the Numbers pdf type content icon [PDF 572,483kb]
    With so much emphasis on accountability in education these days, school districts are gathering more data than ever before. However, capturing data is only the first step.
  • ASBJ Article: Making Data Count pdf type content icon [PDF 1,173,476kb]
    November 2001 article from American School Board Journal of transforming schooling through data-driven decision making.
  • ASBJ Article: Breaking Down the Data pdf type content icon [PDF 254,493kb]
    This February 2004 article from The American School Board Journal describes ways to improve instruction and student learning through data-driven decision making.
  • Every School Day Counts: The Forum Guide to Collecting and Using Attendance Data link type content icon
    This publication offers a comprehensive and easy-to-use approach to collecting and classifying attendance data. It is part of a series from the National Forum on Education Statistics, which assists districts in producing and maintaining comparable, uniform information and data that will assist policymaking.
  • Common Core of Data link type content icon
    A comprehensive, annual, national statistical database of information concerning all public elementary and secondary schools from the U.S. Department of Education's National Center for Education Statistics.
  • Educational Needs Index Project link type content icon
    The Educational Needs Index is a study of educational, economic, and population pressures that influence educational policy and planning at local, state and regional levels. This website provides education leaders, researchers, and public officials with data and analysis tools to better understand educational needs in their areas.
  • The "Data Wise" Improvement Process link type content icon
    Eight steps for using test data to improve teaching and learning.
  • Data-Driven Decisionmaking pdf type content icon [PDF 398,967kb]
    This Education Commission of the States' No Child Left Behind issue brief discusses how districts can support schools' use of data.
  • SchoolMatters: Clearinghouse link type content icon
    School Matters is an easily searchable database of data on student performance, demographics, and finances in schools across the nation.
  • Kids Count Data Book Online link type content icon
    This database gives policymakers access to more than 100 statistical indicators of health status, educational achievement, poverty and socio-economic status, family, and community demographics reflecting overall child well-being and risk factors that threaten well-being. Local, state, and national comparative data profiles can be easily generated.
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