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

作为NSF推进非正式STEM学习计划的一部分，科学学习(SL)是美国和英国基金会之间的合作伙伴关系。SL颁发赠款奖励，采取变革性的步骤，告知、改进和推进非正式STEM学习经验和环境的知识库、实践和设计。SL的长期目标是扩大对STEM的参与，并更好地了解、加强和协调STEM的参与和终身学习。这是一个科学学习规划项目，将制定一项计划，说明如何利用现有的数据来源进行一项纵向研究，以便将参与校外环境中以科学为重点的方案拟订工作与长期成果联系起来。该项目的数据最终将来自“挖掘”美国和英国校外项目常规收集的现有数据集。4H是最初参与该项目的校外提供商，但理想情况下，该项目将扩大到包括其他以青年为基础的项目，如Girls Inc.和YMCA。在规划赠款期间，该项目将制定一项纵向研究计划，审查与非正式科学有关的因素和结果，包括：(A)教育成果的范围，(B)学习活动的多样性和结构，(C)与正规教育经验和成就措施的联系，以及(D)现有非正式科学计划数据收集基础设施的结构。规划期将不涉及对现有数据集的实际挖掘，但将探索关于不同非正式科学计划的数据收集的后勤问题，包括潜在的元数据集和工具，这些将：(A)确定和审查数据收集挑战，(B)探索共同数据管理系统的实施，(C)确定可能成为本研究候选对象的非正式科学计划，(D)比较和对比不同计划和小组提供的数据，以及(E)优化数据库管理。

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.