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）领域日常实践的一个组成部分。因此，STEM+Computing Partnerships（STEM+C）计划旨在推进新的多学科方法，以及对STEM教学和学习中计算整合的循证理解，以及旨在为K-12计算机科学教学建立证据库的计算学科特定努力，包括在不同人群中。该项目将开发，实施和研究一个创新的多周计算天气预报中学课程单元，整合学生的学习和使用气象学，数学和计算思维概念和实践。该项目由Concord Consortium的研究人员领导，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。该课程包括教学材料和技术，将教室转化为动态天气模拟，然后为学生学习和使用科学，数学和计算思维提供支架，因为他们（a）收集和分析来自模拟天气事件的数据;（B）从这些数据中开发和改进计算模型;（c）使用计算模型进行和评估天气预测。与气象学家的实时网络广播使学生能够了解他们如何从学生检查的相同数据集进行预测。大约430名学生将参与并受益于该项目。参与学校的多样性将使STEM中人口统计学上多样化的学生群体参与进来，并通过确保所开发的研究结果和课程反映广泛多样性的人和地方的需求，帮助该项目实现更广泛的影响。该项目将解决发展学生STEM素养的艰巨挑战：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的教学与计算思维相结合。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，开发一个基于探究的课程，学生在其中扮演科学专家的角色，在探索，解释和预测天气现象时应用计算思维。该课程包括a）四个标准一致的教学序列; B）一套技术、软件系统和天气数据集;以及c）专业发展讲习班和材料，以支持教师的课程实施。该干预措施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的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。在三年的时间里，该项目将聘请八名教师和他们的430名学生，他们将与项目小组成员合作，在伊利诺斯州、马萨诸塞州和阿拉斯加州的独特中学环境中测试课程。混合方法设计为基础的研究将使用一套丰富的学生测试，反思，叙述计算机模型（称为screencasts），以及学生在课堂活动中的视频记录作为证据来源。该研究旨在了解学生如何使用计算思维实践来生成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。研究进一步试图了解一套核心设计元素的课程如何促进学生的计算思维和推理的天气事件。研究和外部评估将通过阐明研究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。该项目将产生一个以证据为基础的学习轨迹，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，并结合他们使用收集，解释和表示数据的关键计算实践;评估和预测计算模型。该项目还将制定一套循证设计原则，供更广泛地传播。研究结果将与Concord Consortium的25，000多名教师，研究人员和政策制定者的广泛网络共享，并通过更传统的方式分享，例如同行评审期刊和会议演讲中的论文。该课程将通过开源和开放内容许可证获得许可，并通过Concord Consortium的网站免费分发给其他教师，课程设计师和研究人员。

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.