How to Become Data Literate

The Basics for Educators

By (author) Susan Rovezzi Carroll, David J. Carroll

Hardback - £63.00

Publication date:

16 March 2015

Length of book:

132 pages

Publisher

Rowman & Littlefield Publishers

ISBN-13: 9781475813319

In this follow up to Statistics Made Simple for School Leaders Carroll and Carroll have provided an updated, easy to comprehend, manual for practitioners. Now more than ever, educators are being held accountable by taxpayers, students, parents, government officials and the business community for supportable documentation of educational results. Data management has become everyone’s job and everyone’s concern. But the regression of data has exposed a raw nerve. The lack of comfort that many educators have in working with data poses a great challenge as school districts make the transition from a data rich to an information rich environment. How to Become Data Literate is the solution. Educators need the ability to formulate and answer questions using data as part of evidence-based thinking, selecting and using appropriate data tools, interpreting information from data, evaluating evidence-based differences, using data to solve real problems and communicating solutions. This book is intended to be a user-friendly, educator’s primer. It will leave the reader with the confident attitude that “I can do this." In the long run, it is intended to underscore the magnificence of data. Decisions based on excellent data produce meaningful action strategies that benefit students, parents, staff, and the community at large.

In How to Become Data Literate, Susan Rovezzi Carroll and David J. Carroll, affiliated with Words & Numbers Research, provide succinct yet comprehensive support for administrators wading through applied basic quantitative statistics as a tool for data analysis. In fewer than 150 pages, the authors offer instruction for managing, manipulating, visualizing and interpreting the findings of data analysis projects. . . .[T]he book provides support for administrators seeking to understand and use common statistical techniques. I plan to apply this text in the education courses I teach and will strongly recommend it to my doctoral students. But the text also should be considered by educational leaders looking for an introduction to or a refresher of quantitative statistics. If your work responsibilities include making sense of data and analyzing results from a practical, programmatic perspective, or if you need support for quantitative statistics courses that you might be taking, I suggest you consider this work.