Data-driven decision making in early education: Evidence From North Carolina’s Pre-K program

• Published in: Education policy analysis archives Vol. 27; no. 18; pp. 18 - 44
• Main Authors: Little, Michael Harris, Cohen-Vogel, Lora, Sadler, James, Merrill, Becca
• Format: Journal Article
• Language: English
• Published: Colleges of Education at Arizona State University and the University of South Florida 04.03.2019; Arizona State University
• Subjects: Data Use; Decision Making; Early Childhood Education; education policy; Educational Policy; Evidence; Formative Evaluation; pre-k; Preschool Education; Rural Areas; Screening Tests; North Carolina
• DOI: 10.14507/epaa.27.4198
• ISSN: 1068-2341

The purpose of this study is to shed light on the use of data in early education settings—specifically, North Carolina’s Pre-K program. In this mixed-methods study, we draw upon in-depth interviews and survey data to examine (1) the types of data available to educators in Pre-K, (2) the ways in which data are intended to be used, (3) how data are reportedly used, and (4) the facilitators and inhibitors of effective data-driven decision making. Our findings reveal that Pre-K settings are data-rich environments, often with informal data collected through developmental screening tools and formative assessment systems. We find that engagement with and use of these data for instruction is variable. Finally, we find data sharing between grades is inconsistent, but an important factor predicting data sharing is co-location of Pre-K programs within elementary school buildings. We consider our findings in the context of existing academic literature and discuss the implications for policy and practice.