Most schools focus their data-based decision making efforts on standardized test score and other outcome-based, quantitative data. Outcome data have the potential to produce a misleading picture of actual conditions in schools and districts, thereby creating a wallpaper effect. Outcome data, like wallpaper, can cover up cracks or other unwanted blemishes. However, there are numerous sources of "hidden" data that have been shown to improve student achievement but are rarely analyzed and monitored. Some of these sources are non-academic, such as teacher and student attendance, school calendars, referrals, suspensions, disciplinary policies, and more.



Data Strategies to Uncover and Eliminate Hidden Inequities shows educators what quantitative and qualitative data sources they should be looking at and provides activities to engage the reader. Johnson and Avelar-La Salle help educators identify the questions that get below the surface and demonstrate how powerful these data can be in answering important equity questions.





With examples of schools that exemplify these data models, this book provides a springboard for explaining how to pull different data sources together into a continuous improvement plan aimed at raising the achievement of all students.