Integrating Meteorology, Mathematics, and Computational Thinking: Research on Students' Learning and Use of Data, Modeling, and Prediction Practices for Weather Forecasting

整合气象学、数学和计算思维：学生学习和使用天气预报数据、建模和预测实践的研究

• 批准号: 1640088
• 负责人: Carolyn Staudt
• 金额: $ 249.37万
• 依托单位: Concord Consortium
• 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: 2016-09-15 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1640088&HistoricalAwards=false
• 关键词: Integrating; Meteorology; Mathematics; Computational; Thinking

Computing and computational thinking are an integral part of everyday practice within modern fields of science, technology, engineering, and math (STEM). As a result, the STEM+Computing Partnerships (STEM+C) program seeks to advance new multidisciplinary approaches to, and evidence-based understanding of, the integration of computing in STEM teaching and learning, and discipline-specific efforts in computing designed to build an evidence base for teaching and learning of computer science in K-12, including within diverse populations. This project will develop, implement, and study an innovative multi-week middle school curriculum unit in computational weather forecasting that integrates students' learning and use of meteorology, mathematics, and computational thinking concepts and practices. Led by investigators at Concord Consortium, the project team includes weather scientists, computer scientists, education developers, and learning scientists from Argonne National Laboratory, Millersville University, and the University of Illinois at Chicago. The curriculum consists of instructional materials and technologies that transform classrooms into dynamic weather simulations and then scaffold students' learning and use of science, mathematics, and computational thinking as they (a) collect and analyze data from the simulated weather events; (b) develop and refine computational models from these data; (c) and use computational models to make and evaluate weather predictions. Live webcasts with meteorologists enable students to learn about how they made predictions from same data sets students examined. Approximately 430 students will be involved with and benefit from the project. The diverse nature of the participating schools will both engage a demographically diverse student population in STEM and help the project achieve significant broader impacts, by assuring that the findings and curriculum developed reflect the needs of a broad diversity of people and places. This project will address a daunting challenge to developing STEM literacy in students: integrating teaching and learning of key ideas and practices of science and mathematics with computational thinking in authentic, innovative and effective ways. The project will exploit young people's universal interest in weather and the computationally intensive practice of modern meteorology to develop an inquiry-based curriculum in which students play the role of scientific experts that apply computational thinking as they explore, explain, and predict weather phenomena. The curriculum consists of a) four standards-aligned instructional sequences; b) a suite of technologies, software systems, and weather data sets; and c) professional development workshops and materials to support teachers' curriculum implementation. The intervention will address specific needs of middle school students and teachers with regard to relevant disciplinary content, practices, and computation as specified in Next Generation Science Standards, Common Core State Standards for mathematics, and recent consensus frameworks for computational thinking in STEM. Over three years the project will engage eight teachers and their 430 students who will work with the project team members to test the curriculum in distinctive middle school settings in Illinois, Massachusetts, and Alaska. The mixed methods design-based research will use a rich set of student tests, reflections, narrated computer models (called screencasts), and video recordings of students during classroom activities as sources of evidence. The research seeks to understand how students use computational thinking practices to generate explanations and predictions of weather events, and how these explanations and predictions evolve with the sequence and complexity of computational thinking practices. The research further seeks to understand how a set of core design elements of the curriculum facilitate students' computational thinking and reasoning about weather events. The research and external evaluation will explore replicability and scale by elucidating how findings and design elements generalize to unique populations, such as Alaskan Inuit students, and the contexts in which they learn. The project will produce an evidence-based trajectory of learning that describes how students become more sophisticated in their understanding of weather science and in their scientific explanations and predictions of weather events in conjunction with their use of key computational practices of collecting, interpreting, and representing data; evaluating and predicting with computational models. The project will also produce a set of evidence-based design principles for broader dissemination. The research findings will be shared with Concord Consortium's extensive network of more than 25,000 teachers, researchers, and policymakers, and by more traditional means, such as papers in peer-reviewed journals and conference presentations. The curriculum will be licensed via open source and open content licenses and freely distributed to other teachers, curriculum designers, and researchers through Concord Consortium's website.

计算和计算思维是现代科学、技术、工程和数学(STEM)领域日常实践中不可或缺的一部分。因此，STEM+计算伙伴关系(STEM+C)计划寻求推动新的多学科方法和对计算在STEM教与学中的整合的基于证据的理解，以及特定学科在计算方面的努力，旨在为K-12阶段的计算机科学教学和学习建立一个证据基础，包括在不同的人群中。该项目将开发、实施和研究一个创新的、为期数周的中学计算天气预报课程单元，该单元整合了学生对气象学、数学和计算思维概念和实践的学习和使用。由协和联盟的研究人员领导的项目团队包括来自阿贡国家实验室、米勒斯维尔大学和伊利诺伊大学芝加哥分校的气象科学家、计算机科学家、教育开发人员和学习科学家。课程包括教学材料和技术，将课堂转化为动态天气模拟，然后为学生学习和使用科学、数学和计算思维奠定基础，因为他们(A)收集和分析模拟天气事件的数据；(B)根据这些数据开发和改进计算模型；(C)使用计算模型进行天气预报和评估。气象学家的网络直播使学生能够了解他们如何根据学生检查的相同数据集进行预测。大约430名学生将参与该项目并从中受益。参与学校的多样性既将吸引人口统计上不同的STEM学生群体，也将通过确保制定的调查结果和课程反映广泛的人和地区的需求，帮助该项目实现重大的更广泛的影响。该项目将解决培养学生STEM素养的一项艰巨挑战：以真实、创新和有效的方式将科学和数学的关键思想和实践与计算思维的教与学结合起来。该项目将利用年轻人对天气的普遍兴趣和现代气象学的计算密集型实践来开发基于探究的课程，在课程中，学生扮演科学专家的角色，在他们探索、解释和预测天气现象时应用计算思维。课程包括a)四个符合标准的教学序列；b)一套技术、软件系统和天气数据集；以及c)支持教师课程实施的专业发展讲习班和材料。这项干预将解决中学生和教师在下一代科学标准、数学共同核心国家标准和最近STEM计算思维共识框架中规定的相关学科内容、实践和计算方面的具体需求。该项目将在三年内聘请8名教师和他们的430名学生，他们将与项目团队成员一起在伊利诺伊州、马萨诸塞州和阿拉斯加州的独特中学环境中测试课程。这项基于设计的混合方法研究将使用一套丰富的学生测试、反思、有叙述的计算机模型(称为截屏视频)和学生在课堂活动中的视频记录作为证据来源。这项研究旨在了解学生如何使用计算思维实践来产生对天气事件的解释和预测，以及这些解释和预测如何随着计算思维实践的顺序和复杂性而演变。这项研究进一步试图了解课程的一组核心设计元素如何促进学生对天气事件的计算思维和推理。研究和外部评估将通过阐明调查结果和设计元素如何推广到独特的人群，如阿拉斯加因纽特学生，以及他们学习的环境，来探索可复制性和规模。该项目将产生一个基于证据的学习轨迹，描述学生如何在他们对天气科学的理解以及他们对天气事件的科学解释和预测方面变得更加复杂，并结合他们使用关键的计算实践来收集、解释和表示数据；使用计算模型进行评估和预测。该项目还将制定一套以证据为基础的设计原则，以供更广泛的传播。研究结果将与协和联盟由25,000多名教师、研究人员和政策制定者组成的广泛网络共享，并通过更传统的方式共享，例如在同行评议期刊上发表论文和会议演示文稿。课程将通过开源和开放内容许可证获得许可，并通过协和联盟的网站免费分发给其他教师、课程设计者和研究人员。

项目成果

Weathering the virtual storm: Using computational thinking to make a forecast. Massicotte, J., Staudt, C., & McIntyre, C. (2021). Weathering the virtual storm: Using computational thinking to make a forecast. Science Scope. 44(5): 18–27.

抵御虚拟风暴：利用计算思维进行预测。

• 发表时间: 2021
• 期刊: DN science scope
• 作者: Massicotte, J.