Improving systematic use of student data to inform the work of teachers, schools, and districts has become a hot topic in education reform. Learning Forward's Standards for Professional Learning stress better use of data, and particularly student performance data, within an integrated approach to improving practice. While better use of data by…

Limiting data collection to a sample group is one way to increase effectiveness in dealing with data. The paper describes how to draw a sample group (random sampling, stratified random sampling, purposeful sampling, and convenient or opportunity sampling) and discusses how to determine the size of the sample group. (SM)

Getting answers to questions about schools and student learning requires that educators know how to collect, analyze, and interpret data. Six critical steps in this process include: posing questions, establishing judgment criteria, making a plan, gathering data, analyzing data, and interpreting results. These steps can serve as a beginning guide…

Presents a model to help schools pose and answer data-based questions about teaching and learning, describing different types of data that educators can use to piece together pictures of their schools (e.g., student learning statistics, demographic data, and school process data) and discussing how educators can cross data from different categories…

Extensive practice and research in program evaluation have led to this eight-step process that a professional developer can use to determine a program's effectiveness and strengthen the program as it evolves. An unbiased, systematic process of evaluation can help justify putting resources into professional learning and make it easier to determine…

A carefully developed, comprehensive professional development plan takes time, energy, and coordination of resources, but when it's done well, it can seem as effortless as a perfectly pitched curve ball. Seven steps, each with a set of guiding questions, can help planners meet the goal and create a program that produces results. [Appended to this…

Several Colorado schools hired data analysts to help with school improvement efforts. The analysts are teachers who participate on school leadership teams and who support school action research teams. They collect and organize baseline data, help teams measure results of proposed changes, and evaluate results after implementation. Because they are…

This year's winners of the U.S. Department of Education's Model Professional Development Awards exemplify schools and districts where everyone's job is to learn. In these models, time and resources are spent on teacher-run institutes, data analysis and collection, peer coaching, curriculum writing, collaborative lesson planning, examining student…

Educators who thoroughly investigate data, raise questions, examine student learning, test their hypotheses, and then share their findings are mirroring effective math and science instruction. Using collaborative inquiry, data teams can help improve teacher knowledge and help teachers change their practice in ways that will enhance student…

Provides examples of schools and districts nationwide that use data-based decision making effectively to enhance beginning teacher induction, multi-age reading classes, literacy education, tracking of student achievement, ongoing staff development, and school discipline efforts. The programs share a commitment to putting data at the center of…