Open AccessData-driven decision making in early education: Evidence From North Carolina’s Pre-K program
Author(s) -
Michael Little,
Lora CohenVogel,
James Sadler,
Becca Merrill
Publication year - 2019
Publication title -
education policy analysis archives
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.727
H-Index - 46
ISSN - 1068-2341
DOI - 10.14507/epaa.27.4198
Subject(s) - formative assessment , context (archaeology) , survey data collection , data sharing , data collection , psychology , medical education , mathematics education , computer science , data science , sociology , medicine , geography , social science , statistics , mathematics , alternative medicine , archaeology , pathology
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.