Data Analysis for Continuous School Improvement: For Continuous School Improvement

by Victoria L. Bernhardt

Data Analysis for Continuous School Improvement provides a new definition of school improvement, away from a singular focus on compliance, toward a true commitment to excellence. This book is a call to action. It is about inspiring schools and school districts to commit to continuous school improvement by providing a framework that will result in improving teaching for every teacher and learning for every student through the comprehensive use of data. A culmination of over 30 years of doing the hard work in schools and districts both nationally and internationally, Data Analysis for Continuous School Improvement shares new, evidence-based learnings about how to analyze, report, communicate, and use multiple measures of data. The updated edition provides a wealth of tools, protocols, timelines, examples, and strategies that will help schools and districts become genuine learning organizations.

Genres: Education, Leadership, Nonfiction, Professional Development

426 pages, Paperback

First published December 1, 2003

Reviews

[Jenna · Rating 3 out of 5]

Not a book I would recommend as pleasurable reading (ha!), however it was informative and appropriate to read as a school leader working with data. Very easy to digest, clear and straightforward method. Definitely a book to read if you need to understand how to compile, read, and report on data for school improvement.

[Bailey · Rating 4 out of 5]

I really liked the structure of this book and that it goes in a definitive timeline. I have read a lot of college books where you feel like it jumps all around, but this one was well structured.

[Rachel Hardy · Rating 5 out of 5]

Read for my master's work - it was insightful and helpful. Would recommend.

[Derek Dupuis · Rating 3 out of 5]

This was passable as textbooks go. Somewhat interesting.

[Brandon · Rating 3 out of 5]

Helpful handbook for school leaders hoping to move their schools toward a continuous improvement model.

[W Charles · Rating 5 out of 5]

The author presents a compelling case for developing data sets beyond test scores. When analyzing data, she argues that student data goes well beyond test scores and includes personal data on the students, data on the community, and data on the school as a whole. Once that is collected, then, and only then, can serious analysis begin and ways to improve the school developed. Solid book.