Use Drives Quality: Considering Data Quality Issues in California’s Pursuit of a Cradle-to-Career Data System

by | Jan 2020

January 2020

An addendum to the series:
California Education Policy, Student Data, and the Quest to Improve Student Progress
By Colleen Moore

California is moving forward toward building a “cradle-to-career” data system, and faces a number of critical decisions about the purpose it will serve, and about its structure and function. Data quality—the accuracy and completeness of the data that will feed into the new data system—is one important issue to be considered. Most of California’s existing K-20 and Workforce data are of good quality, with problems no greater than would be expected in any large administrative data set, although data on early learning, adult education, and workforce training would need to improve in order to be included. While the perception of data quality problems is often larger than the reality, the issues that do exist can often be mitigated through good data management and research practices, as demonstrated in some of the important research that has already been done using California’s education and workforce data. Creating and using a longitudinal data system could even help improve data quality, both by revealing problems that aren’t currently recognized and by increasing the priority placed on collecting good quality information as the data are put into use to improve educational policy and practice, and to provide critical information for students and families.

These observations are drawn from conversations with 14 researchers and other experts who have significant experience using California’s existing education and workforce data systems to conduct research, to develop data tools for educators and the public, and for operational purposes. The brief is an addendum to EdInsights’ four-part series examining California’s approach to student-level data, aimed at supporting the state’s Cradle-to-Career Data Workgroup and other stakeholders as they make critical decisions about the structure and function of a statewide data system.

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