With the enactment of "No Child Left Behind," every school and district in the country need to analyze their data to ensure adequate yearly progress. Sometimes, looking at another’s analyses makes it easier to see things you would not have seen while looking only at your own analyses. When it comes to analyzing student achievement data, the first two questions educators ask are "Now that we have the data, What analyses should we make? and What do the analyses tell us?" These questions are hard to answer on the spot, so I have taken up the challenge to develop a series of books with the purposes of showing what analyses can be made, describing what these analyses are telling us, and illustrating how to use these analyses in continuous improvement planning. This series of books includes: Using Data to Improve Student Learning in Elementary Schools, Using Data to Improve Student Learning in Middle Schools, Using Data to Improve Student Learning in High Schools, and Using Data to Improve Student Learning in School Districts. I believe that most of the time we must look at K-12 data (district level) to ensure a continuum of learning that makes sense for all students. I have purposefully separated building levels in these books so there would be ample space to do a fairly comprehensive job of data analysis at each organizational level and to make the point about needing to understand results beyond one school level. Each of these four publications uses real data (with some slight alterations to blur identities and to fill gaps where data are missing) and shows the actual descriptive analyses I would perform if I were the person analyzing the data at that particular level. You will see that no matter how much or how little data your school or district has, the data can tell the story. The study questions at the end of each chapter serve as guides for the reader. I have described what I saw in the analyses following the study questions for readers who want the feedback. For the purposes of this publication, I have not included facilities, food services, construction, and financial data. These data were not available. My goal with this book is for anyone to be able to set up these analyses, regardless of the statistical resources available. Therefore, in addition to showing the analyses in the text, the graphing templates, narratives, text templates, and supplementary tools appear on the accompanying CD. This book is intended for school and district teachers and administrators who want to use data to continuously improve what they do for children; and for college and university professors who teach school administrators, teachers, and support personnel how to analyze school data. It is my belief that all professional educators must learn how to use data in this time of high-stakes accountability. My hope is that you will find this book and the CD to be helpful as you think through the analyses of your data to improve learning for all students.

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