Exploring Longitudinal Research on Out-of-school Time Experiences in STEM

University Of Virginia Main Campus, Charlottesville VA

Investigators

Abstract

As part of NSF's Advancing Informal STEM Learning program, Science Learning+ (SL+) is a partnership among US and UK foundations. SL+ makes grant awards that take transformational steps to inform, improve, and advance the knowledge bases, practices, and design of informal STEM learning experiences and environments. The long-term SL+ goals are to broaden participation in STEM and to better understand, strengthen and coordinate STEM engagement and lifelong learning. This is a Science Learning+ planning project that will develop a plan for how to conduct a longitudinal study using existing data sources that can link participation in science-focused programming in out-of-school settings with long-range outcomes. The data for this project will ultimately come from "mining" existing data sets routinely collected by out-of-school programs in both the US and UK. 4H is the initial out-of-school provider that will participate in the project, but the project will ideally expand to include other youth-based programs, such as Girls Inc. and YMCA. During the planning grant period, the project will develop a plan for a longitudinal research study by examining informal science-related factors and outcomes including: (a) range of educational outcomes, (b) diversity and structure of learning activities, (c) links to formal education experiences and achievement measures, and (d) structure of existing informal science program data collection infrastructure. The planning period will not involve actual mining of existing data sets, but will explore the logistics regarding data collection across different informal science program, including potential metadata sets and instruments that will: (a) identify and examine data collection challenges, (b) explore the implementation of a common data management system, (c) identify informal science programs that are potential candidates for this study, (d) compare and contrast data available from the different programs and groups, and (e) optimize database management.