Collaborative Research: Science Modeling through Physical Computing: Contextualized Computational and Scientific Learning in the Grade 5-6 Classroom

协作研究：通过物理计算进行科学建模：5-6 年级课堂中的情境化计算和科学学习

• 批准号: 1934173
• 负责人: Francis Quek
• 金额: $ 179.98万
• 依托单位: Texas A&M University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1934173&HistoricalAwards=false
• 关键词: Collaborative; Research; Science; Modeling; through

As computing has become integral to the practice of science, technology, engineering and mathematics (STEM), the STEM+Computing program seeks to address emerging challenges in computational STEM areas through the applied integration of computational thinking and computing activities within STEM teaching and learning in early childhood education through high school (preK-12). In this STEM+C project students will build science models to learn both science and computing in grades 5 and 6. Students will engage with computation to imbue physical models with functionality that represent various state, static, dynamic, and semantic scientific phenomena. A double-scaffolding strategy will be employed to simultaneously support scientific and computing learning in formal classrooms. First, learning will be scaffolded through students' construction of computational physical models (CMPs) to support understanding of formal science topics and develop model-based thinking. Second, the program will support a learning progression in computing to build the CMPs that is practice-oriented, with new concepts added to complete each set of successive models. The representational nature of science models will make abstract concepts concrete, and the use of multiple models for each concept will give students greater flexibility in understanding the concept in different representations. The project will be carried out longitudinally over two years in two public intermediate schools that serve predominantly underrepresented populations. Teachers will receive professional development using multiple science models and language and pedagogy that highlight the representational power of models. To support teaching computational content, the project will develop a Mentor Corps of college STEM students to work in collaboration with teachers in the classroom. Computational modeling activities will be integrated into the regular science classes, matching the models that the students build with the existing curriculum. The project research will examine the impact of the program on 1) learning science concepts through modeling, 2) learning computational constructs and developing computation as a habit of mind, and 3) the development of both science and computation identities. An array of data sources will be gathered from both treatment and control classrooms in each school, including knowledge assessments and surveys, semi-structured interviews, and video-taped observations of students' model construction. Both qualitative and quantitative analyses will be conducted to address the research questions and identify differences between groups. Findings will be broadly disseminated to research and practitioner audiences, and instructional materials and resources will be freely accessible.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

随着计算已成为科学、技术、工程和数学 (STEM) 实践中不可或缺的一部分，STEM+计算计划旨在通过在 STEM 教学和学习中应用计算思维和计算活动来解决计算 STEM 领域中出现的挑战。幼儿教育直至高中（preK-12）。在这个 STEM+C 项目中，5 年级和 6 年级的学生将构建科学模型来学习科学和计算。学生将参与计算，为物理模型注入代表各种状态、静态、动态和语义科学现象的功能。 将采用双支架策略来同时支持正式课堂中的科学和计算学习。 首先，学习将通过学生构建计算物理模型（CMP）来支撑，以支持对正式科学主题的理解并发展基于模型的思维。 其次，该计划将支持计算方面的学习进程，以构建面向实践的 CMP，并添加新概念来完成每组连续模型。 科学模型的表征性质将使抽象概念具体化，每个概念使用多个模型将使学生在理解不同表征中的概念时具有更大的灵活性。该项目将在两所公立中学纵向实施，历时两年，主要服务于代表性不足的人群。教师将使用多种科学模型以及突出模型代表性力量的语言和教学法获得专业发展。为了支持计算内容的教学，该项目将培养一个由 STEM 大学学生组成的导师团，与教师在课堂上合作。 计算建模活动将被整合到常规科学课程中，使学生构建的模型与现有课程相匹配。该项目研究将考察该计划对以下方面的影响：1）通过建模学习科学概念，2）学习计算结构并将计算发展为一种思维习惯，3）科学和计算身份的发展。将从每所学校的治疗和对照教室收集一系列数据源，包括知识评估和调查、半结构化访谈以及对学生模型构建的录像观察。 将进行定性和定量分析，以解决研究问题并确定群体之间的差异。 研究结果将广泛传播给研究和从业人员，教学材料和资源将免费提供。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。