Collaborative Research: Group-Based Cloud Computing for STEM Education Project

合作研究：基于群体的 STEM 教育项目云计算

• 批准号: 1614745
• 负责人: Uri Wilensky
• 金额: $ 58.78万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1614745&HistoricalAwards=false
• 关键词: Collaborative; Research; Group; Based; Cloud

This project will advance efforts of the Innovative Technology Experiences for Students and Teachers (ITEST) program to better understand and promote practices that increase students' motivations and capacities to pursue careers in fields of science, technology, engineering, or mathematics (STEM) by designing, developing, implementing, and studying a socio-technological system for group-centered STEM teaching and learning consistent with a nationally recognized pre-service program. The project will use results from more than 30 years of research to demonstrate how network supported, group-based learning grounded in principles of Generative Design can improve learning for all learners, across racial/ethnic backgrounds. The project will also offer detailed analyses of activity designs and implementation strategies that will help pre-service teachers to develop more fully participatory and socially-supported approaches to classroom learning, using authentic STEM practices in group-centered learning environments. This work will be particularly important to advancing knowledge in the field for pre-service teacher preparation, since few pre-service programs use this approach in preparing teachers for today?s classrooms. Through a focus on the initial implementation of twelve model activities taught by pre-service teachers in K-12 classrooms nationwide, this study will also provide concrete and quantitative evidence that group-based learning is both appealing to early-career and induction-years teachers, and that it is feasible to implement in real classrooms.The project takes a design-based research approach to creating and studying technologies and materials that support generative teaching and learning in STEM. Sites associated with a nationally recognized and expanding approach to STEM teacher preparation and certification will serve as incubators and testbeds for the project?s innovation and development efforts. Computational thinking, including agent-based modeling, and simulation across STEM domains as well as geo-spatial reasoning about personally meaningful learner-collected data will provides an important scientific foundation for the project. This will be achieved by developing a highly-interactive and group-optimized, browser- and cloud-based, device-independent and open-source architecture and by integrating and extending leading computational tools including the NSF-funded NetLogo Web agent-based modeling language and environment. The project will also achieve this outcome by publishing its technology-mediated activities and materials in the public domain and by capturing extensive qualitative and quantitative data on the intensity and nature of use of these technologies and materials. Collectively, the project will foster the growth of educational infrastructures to enable the dissemination and effective adoption of generative teaching and learning in STEM.

该项目将推动学生和教师创新技术体验(ITEST)计划的努力，以更好地了解和促进实践，通过设计、开发、实施和研究与国家认可的职前计划一致的以小组为中心的STEM教与学的社会技术系统，提高学生在科学、技术、工程或数学(STEM)领域追求职业生涯的动机和能力。该项目将使用30多年的研究结果来展示基于生成性设计原则的网络支持的小组学习如何改善所有学习者的学习，不分种族/民族背景。该项目还将对活动设计和实施战略进行详细分析，以帮助职前教师在以小组为中心的学习环境中使用真实的STEM做法，制定更充分参与和得到社会支持的课堂学习方法。这项工作对于促进职前教师准备领域的知识尤其重要，因为很少有职前课程使用这种方法来为今天的S课堂准备教师。通过在全国范围内的K-12课堂上初步实施12项由职前教师教授的示范活动，本研究还将提供具体和定量的证据，证明基于小组的学习对职业生涯初期和入职教师都有吸引力，并且在实际课堂上实施是可行的。该项目采用基于设计的研究方法来创造和学习支持STEM生成性教学的技术和材料。与国家认可和扩展的STEM教师培养和认证方法相关的地点将作为项目-S创新与发展努力的孵化器和试验台。计算思维，包括基于代理的建模，跨STEM领域的模拟，以及对学习者收集的个人有意义的数据进行地理空间推理，将为该项目提供重要的科学基础。这将通过以下方式实现：开发高度互动和分组优化的、基于浏览器和云的、独立于设备和开放源码的架构，并集成和扩展领先的计算工具，包括NSF资助的NetLogo基于Web代理的建模语言和环境。该项目还将通过在公共领域公布其以技术为中介的活动和材料，并通过收集关于这些技术和材料的使用强度和性质的大量定性和定量数据来实现这一成果。总的来说，该项目将促进教育基础设施的发展，使STEM能够传播和有效地采用生成性教学和学习。