课题基金 / 基金详情

Research on Effects of Integrating Computational Science and Model Building in Water Systems Teaching and Learning

Research on Effects of Integrating Computational Science and Model Building in Water Systems Teaching and Learning
计算科学与模型构建相结合在水系统教学中的效果研究
批准号:
1543228
负责人:
John Moore
金额:
$220.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-09-15 至 2022-05-31

项目摘要

项目成果

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中文摘要
翻译
随着计算能力日益变革,并成为科学、技术、工程和数学(STEM)学科实践中不可或缺的一部分,STEM计算(STEM C)伙伴关系计划寻求在K-12 STEM教与学中整合计算方法的使用。COMP水电项目将解决STEM C计划的目标,以及社会面临的一个紧迫问题:提供清洁水作为支持人类使用和生态完整性的生态系统服务。Comp Hydro的愿景是在高中生构建和使用物理、数学和概念模型时,通过整合真实的、基于地点和基于数据的学习来培养水和计算科学素养。COMP HELDRO的方法和资源将在各种各样的环境中制定--学校和学校系统的类型、学生和教师人口、教学环境以及区域对水质量和可获得性的挑战和限制。全国四个地点的团队将使以地表水和地下水为主题的计算机模块适应当地环境和学校的情况,将在高中地球和环境科学课堂上进行试点测试,并将合作开展关于学生和教师STEM学习的教育研究。大约2400名学生将参与该项目并从中受益。参与学区的多样性将通过确保所开发的调查结果和工具反映不同人群和地区的需求,在STEM中吸引人口统计上的不同学生群体,并帮助该项目实现重大的更广泛的影响。通过课程资源的创建和教师的专业发展,Comp Hydro将帮助建设每个学区整合计算和环境科学的能力。以学习进度为基础的教学材料将支持学生培养知情公民决策所需的水科学素养。COMP HELDRO项目将解决培养学生科学素养方面最艰巨的挑战之一:以真实、创新和有效的方式将以地点为基础的环境科学的关键思想和实践与计算和定量科学的教与学结合起来。该项目的基本前提是,要在环境科学中实现基于模型的推理,学生需要同时开发更复杂的计算推理。将开发四个课程/专业发展模块,以整合地球系统和计算思维的内容。他们将侧重于这些计算概念和实践:访问和操纵来自多个来源的数据的能力;使用计算工具开发模型、分析数据、生成数据可视化和确定关键趋势的能力;应用计算推理和基于模型的理解来构建关于水文系统的定量、科学的解释和预测。该项目将:1)开发和完善地表水和地下水教学单元,每个单元包括两个为期一周的单元;2)聘请教师作为合作伙伴和传播媒介;3)研究教师和学生的学习;4)探索对教学的支持和制约;5)建立一个项目研究、开发和传播的平台。该项目将雇用四个团队,每组6名教师,他们将在两个学年内与四个不同地点(亚利桑那州、科罗拉多州、马里兰州和蒙大拿州)的教育工作者和科学家一起工作。Comp Hydro将利用基于设计的研究方法,以学习进展为基础,作为其研究和教学材料的理论和方法框架。该项目将把计算和数据理解的实践和理解纳入水系统学习进程。它将产生一个学习轨迹和相关的评估工具,描述学生如何在综合科学实践方面变得更加复杂,包括分析、解释和表示数据;开发和使用模型;使用计算思维;以及构建关于水文系统的科学解释和预测。该项目还将开发一套设计原则和一个相关的计算机平台,以供更广泛的传播和支持教师将大数据和小数据集的使用整合到与高中生有意义的环境科学学习体验中。
英文摘要
As computational capabilities increasingly revolutionize and become integral to the practice of science, technology, engineering, and math (STEM) disciplines, the STEM+Computing (STEM+C) Partnerships program seeks to integrate the use of computational approaches in K-12 STEM teaching and learning. The Comp Hydro project will address the goals of the STEM+C program, as well as an urgent issue facing society: the availability of clean water as an ecosystem service supporting human uses and ecological integrity. The vision of Comp Hydro is to foster water and computational science literacy by integrating authentic, place- and data-based learning as high school students build and use physical, mathematical and conceptual models. The approaches and resources of Comp Hydro will be developed in a broad diversity of settings - types of schools and school systems, student and teacher populations, instructional contexts, and regional challenges and constraints on water quality and availability. Teams in four locations around the country will adapt surface water- and groundwater-themed computer modules to local environmental and school contexts, will pilot test them in high school Earth and environmental science classes, and will partner in education research on student and teacher STEM learning. Approximately 2,400 students will be involved with and benefit from the project. The diverse nature of the participating school districts will both engage a demographically diverse student population in STEM and help the project achieve significant broader impacts, by assuring that the findings and tools developed reflect the needs of a broad diversity of people and places. Through curricular resource creation and professional development for teachers, Comp Hydro will help to build the capacity of each school district to integrate computational and environmental science. Instructional materials based on learning progressions will support students in developing water science literacy required for informed citizen decision-making. The Comp Hydro project will address one of the most daunting challenges to developing scientific literacy in students: integrating teaching and learning of key ideas and practices of place-based environmental science with computational and quantitative science in authentic, innovative and effective ways. The basic premise of the project is that to achieve model-based reasoning in environmental science, a student needs to concurrently develop more sophisticated computational reasoning. Four curriculum/professional development modules will be developed to integrate Earth system and computational thinking content. They will focus on these computational concepts and practices: ability to access and manipulate data from multiple sources; ability to use computational tools to develop models, analyze data, produce data visualizations, and identify key trends; application of computational reasoning and model-based understanding to construct quantitative, scientific explanations and predictions regarding hydrologic systems. The project will: 1) develop and refine instructional units for surface and groundwater, each comprising two 1-week modules, 2) engage teachers as partners and agents of dissemination, 3) study teacher and student learning, 4) explore supports and constraints on teaching, and 5) build a platform for project research and development and dissemination. The project will engage four teams of 6 teachers, who will work over two school years with educators and scientists at four diverse sites (Arizona, Colorado, Maryland, and Montana). Comp Hydro will utilize a design-based research approach, grounded in learning progressions as a theoretical and methodological frame, for both its research and instructional materials. The project will integrate computational and data sense making practices and understandings into the Water Systems Learning Progression. It will produce a trajectory of learning and associated assessment instruments that can describe how students become more sophisticated with respect to integrated scientific practices, including analyzing, interpreting and representing data; developing and using models; using computational thinking; and constructing scientific explanations and predictions about hydrologic systems. The project also will develop a set of design principles, and an associated computer platform for broader dissemination and for supporting teachers in integrating the use of big and small data sets into meaningful environmental science learning experiences with high school students.
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