Collaborative Research: EvalFest (Evaluation Use, Value and Learning through Festivals of Science and Technology)

EvalFest（通过科学技术节评价使用、价值、学习）将在全国各地举行的科学技术节中测试创新评价方法，并评估其使用方式和效果。莫尔黑德天文馆和科学中心（北卡罗来纳大学教堂山分校）和加州大学旧金山分校与20多个科学节合作，将(1)调查多站点评估方法是否是为非正式STEM教育创建共同指标的有效模式，(2)开发衡量节日效果的共同方法，(3)创建一个包含50,000名节日参与者的可查询数据库，与非正式STEM学习领域共享；(4)记录这些努力是否也产生了与非正式STEM教育相关的新知识。该项目将为节日社区开发企业反馈管理（EFM）系统和可查询数据库。efm是一种系统，包括流程和软件，使团体（如节日网络）能够收集、组织、分析和共享数据。EFM系统将被设计成跨站点整合数据，并允许用户提取感兴趣的数据。该项目将改进目前在科学节联盟中使用的评估工具，评估自我报告的节日学习，以及参加节日的影响，动机和未来的科学参与。它将收集经济影响数据和纵向节日参加者数据。该项目还将开发一些新的评估工具，如秘密购物者观察协议。来自音乐节参与者的数据将在参加音乐节的现场收集。

EvalFest (Evaluation Use, Value, and Learning through Festivals of Science and Technology) will test innovative evaluation methods in science festivals that are being held across the country and assess in what ways and how effectively they are used. Morehead Planetarium and Science Center (at the University of North Carolina-Chapel Hill) and the University of California, San Francisco, in collaboration with over twenty science festivals, will (1) investigate whether a multisite evaluation approach is an effective model for creating common metrics for informal STEM education, (2) develop common methods to measure the effects of Festivals, (3) create a query-able database of 50,000 Festival attendees to share with the informal STEM learning field, and (4) document whether these efforts also result in new knowledge related to informal STEM education. The project will develop the Enterprise Feedback Management (EFM) system and query-able database for the festival community. EFMs are systems, including processes and software, that enable groups (such as the festival network) to collect, organize, analyze and share data. The EFM system will be designed to integrate data across sites and to allow users to extract data of interest. The project will refine evaluation tools currently used within the Science Festival Alliance that assess self-reported festival learning, and the effects of festival attendance, motivation, and future science participation. It will collect economic impact data and longitudinal festival attendee data. The project will also develop some new evaluation tools such as secret shopper observational protocols. Data from festival attendees will be collected onsite at participating festivals.