Association for Public Policy Analysis & Management

Expanding early childhood programming holds myriad potential benefits (American Psychological Association, 2012; Barnett, 1998, Karoly, 2016, MacGillvary & Lucia, 2011). The proliferation of early childhood programs also, however, presents challenges to states. As they expand early childhood offerings, states must assemble early childhood data systems and utilize them to enact data-driven policies. Jordan and King (2015) have analyzed the challenges involved in the process of building early childhood data systems. Less attention has focused on how states can build capacity to utilize these data systems to drive policymaking. Utilizing data entails substantial organizational change.

This study leverages learning organization theory to assess state early childhood agencies’ capacities to utilize early childhood data systems to inform policymaking. Learning organizations encourage workers at all levels to inform decision-making by fostering transparency, trust, reflection, systems thinking, and, of course, learning. In a setting wherein a learning-organizational culture has been sufficiently espoused, the organization itself “remembers and learns” (Cors, 2003).

This study is designed to assess state early childhood agencies’ learning organization functionality and develop a framework for moving state early childhood agencies toward a learning organizational culture, taking into account the specific challenges of the early childhood space.

Design

This study follows a mixed-methods expansion design. The first phase of the study is based on a survey of items from the Dimensions of a Learning Organization Questionnaire (DLOQ, Marsick, 2003) and additional questions designed to provide guidance for state early childhood agencies to grow as learning organizations. We will conduct a descriptive quantitative analysis of the survey results to determine state early childhood agencies’ levels of learning organization functionality. We have administered the survey and have received some responses, are awaiting more before conducting this analysis.

We expect the survey analysis to generate new research questions, which we will use to inform the expansion phase of the study (to be conducted this summer). The new research questions stemming from the survey results will be driven by the variation in responses. Between-agency variation in terms of overall survey results will lead us to examine the elements and factors that allow an early childhood agency as a whole to function as a learning organization. We will use case studies to form profiles of states at these different functionality levels, and then use these profiles to construct a framework aimed at helping state early childhood agencies build capacity as learning organizations. If we see within-agency variation, we will focus on particular dimensions of learning organization theory that agencies perform well or poorly.

Sample

The sample for this study consists of officials at state early childhood agencies that have or are developing early childhood data systems. The sample will be generated using a sequential mixed methods approach (Teddlie & Yu, 2007). A survey has administered to all state early childhood agencies. From the results of the survey, we will use purposive sampling to select a subsample of agencies for further analysis.