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

基本信息

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

项目摘要

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）的日常实践不可或缺的一部分。结果，STEM+计算合作伙伴关系（STEM+C）计划旨在将新的多学科方法推向STEM教学中计算的整合以及基于证据的理解，以及在旨在构建旨在构建计算的纪律特定努力中的集成K-12中计算机科学教学的证据基础，包括在不同人群中。该项目将在计算天气预测中开发，实施和研究一个创新的多周中学课程单元，以整合学生对气象，数学以及计算思维概念和实践的学习和使用。在康科德财团的调查人员的带领下，项目团队包括天气科学家，计算机科学家，教育开发人员以及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大学的科学家。该课程由教学材料和技术组成，这些材料和技术将教室转变为动态的天气模拟，然后将学生（a）从模拟天气事件中收集和分析数据时，将教室转变为脚手架的学生学习和使用科学，数学和计算思维；（b）从这些数据中开发和完善计算模型；（c）并使用计算模型来制作和评估天气预测。与气象学家的实时网络广播使学生能够从研究的相同数据集中了解他们如何做出预测。大约有430名学生将参与该项目并受益。参与学校的多样性将吸引人口统计学上多样化的学生人数，并通过确保发现的结果和课程发展反映了广泛的人和地方的需求，从而帮助该项目实现了更广泛的影响。该项目将针对学生发展STEM素养的挑战：将教学和学习科学和数学的关键思想和实践与真实，创新和有效的方式相结合。该项目将利用年轻人对天气的普遍兴趣以及现代气象学的计算密集型实践，以开发一种基于询问的课程，在该课程中，学生在探索，解释和预测天气现象时发挥了科学专家的作用，这些科学专家的作用运用了计算思维。该课程由a）四个与标准的教学序列组成； b）一组技术，软件系统和天气数据集； c）专业发展研讨会和材料，以支持教师的课程实施。该干预措施将针对中学生和教师的特定需求，以了解下一代科学标准，数学的共同核心州标准以及STEM中计算思维的最新共识框架。在三年的时间里，该项目将与八名教师及其430名学生联系，他们将与项目团队成员合作，在伊利诺伊州，马萨诸塞州和阿拉斯加的独特中学环境中测试课程。混合方法基于设计的研究将使用一系列学生测试，反思，叙述的计算机模型（称为屏幕截图）以及课堂活动期间学生的视频记录作为证据。该研究试图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计算思维实践的顺序和复杂性而演变。该研究进一步旨在了解课程的一组核心设计元素如何促进学生的计算思维和关于天气事件的推理。研究和外部评估将通过阐明发现和设计元素如何推广到独特的人群（例如阿拉斯加因纽特人学生）以及他们所学的环境来探索可复制性和规模。该项目将产生基于循证的学习轨迹，描述学生如何在天气科学的理解以及对天气事件的科学解释和预测中，以及他们使用关键的收集，解释和代表的关键计算实践，并预测天气事件的科学解释和预测。数据;通过计算模型评估和预测。该项目还将制定一套基于证据的设计原理，以进行更广泛的传播。研究结果将与Concord联盟的广泛网络共享25,000多名教师，研究人员和政策制定者，并通过更传统的方式，例如同行评审的期刊和会议演讲中的论文。该课程将通过开放源代码和开放内容许可获得许可，并通过Concord Consortium的网站自由分发给其他教师，课程设计师和研究人员。