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+提供赠款奖励，采取转型步骤，以告知，改进和推进非正式STEM学习体验和环境的知识基础，实践和设计。 SL+的长期目标是扩大对STEM的参与，更好地理解、加强和协调STEM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，说明如何使用现有数据源进行纵向研究，这些数据源可以将校外环境中以科学为重点的规划参与与长期成果联系起来。 该项目的数据最终将来自“挖掘”现有的数据集，这些数据集是由美国和英国的校外项目定期收集的。 4H是最初的校外提供者，将参与该项目，但该项目将理想地扩大到包括其他以青年为基础的方案，如女孩公司。YMCA的在规划补助金期间，该项目将通过审查与非正式科学有关的因素和成果，制定一项纵向研究计划，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衡量标准的联系，以及（d）现有非正式科学计划数据收集基础设施的结构。规划期间将不涉及现有数据集的实际挖掘，但将探索不同非正式科学计划中数据收集的后勤工作，包括潜在的元数据集和工具，这些数据集和工具将：（a）确定和审查数据收集方面的挑战，（B）探索实施通用数据管理系统，（c）确定可作为本研究候选项目的非正式科学项目，（d）比较和对比不同方案和团体提供的数据，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.