Developing Students’ Systems Thinking and Data Analytics Skills in Civil and Environmental Engineering

该项目旨在通过创造积极的学习体验，帮助学生发展土木工程和环境工程方面的系统思维和数据分析技能，从而服务于国家利益。学生将学习如何分析土木工程系统以支持数据驱动的决策。这些技能将使学生能够设计、建造、操作、监控和维护大型复杂的民用基础设施系统。基于项目的学习方法可以通过将课堂上教授的工程方法应用于现实世界的问题来帮助学生学习系统设计和分析技能。该项目将开发七个教育模块，其中包括一个微型项目、一个土木工程系统的数据集、评估问题和解决实例问题的多媒体内容。这些单元在改善学生系统思维和数据分析技能方面的有效性将在现有多门土木工程课程的背景下进行评估。结果将用于为模块的开发和实施提供信息。将为土木工程学院提供互动讲习班，以传播项目成果，培训教师使用模块，并获得有助于指导模块开发和使用的反馈。对采用这些模块感兴趣的教职员工可以从在线资源库下载。这个项目将帮助学生为他们在工程工作中遇到的复杂系统问题做好准备。这个项目的目标是通过在现有课程中引入系统思维和数据分析的交叉主题来改善学生在土木工程方面的学习。该项目将为交叉主题开发七个教育模块：(1)系统思维；(2)建模；(3)成本、经济和长期规划；(4)优化和决策；(5)机器学习；(6)网络分析；(7)数据收集。每个模块将包括描述如何使模块适应课程的教学材料、帮助教师教授模块中使用的技术的演示文稿、如何解决相关问题的示例、用于评估学生学习结果的问题、数据集和一个迷你项目，以便学生能够应用所学的技术。本项目将通过回答一组研究问题来评估对学生的影响，这些问题包括：(1)在使用模块后，学生对系统/分析的学习增加了多大程度？(2)学生可以在多大程度上在不同的民用基础设施规划、运营和管理环境中应用分析技术？(3)学生对系统思考和分析的重要性的心态/态度是否因模块的影响而改变？这项研究将收集不使用模块的对照组和使用模块的治疗组的评估数据，以确定模块的差异。为了传播成果并从包括工业界和工程教育界在内的多个利益攸关方那里获得反馈，将举办两次讲习班。讲习班将作为一种互动形式的参与者参与，征求反馈意见和思考，以共同创造知识。NSF IUSE：EHR计划支持研究和开发项目，以提高所有学生的STEM教育的有效性。通过机构和社区转型轨道，该计划支持高等教育机构和学科社区转变和改进STEM教育的努力。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to serve the national interest by creating active learning experiences that will help students develop systems thinking and data analytics skills in civil and environmental engineering. Students will learn how to analyze civil engineering systems to support data-driven decision making. These skills will enable students to design, build, operate, monitor, and maintain large complex civil infrastructure systems. A project-based learning approach can help students learn system design and analysis skills by applying engineering methods taught in class to real world problems. This project will develop seven educational modules that include a mini project, a dataset for a civil engineering system, assessment questions, and multimedia content in which example problems are solved. The effectiveness of the modules in improving students’ systems thinking and data analytics skills will be assessed in the context of multiple existing civil engineering courses. The results will be used to inform the development and implementation of the modules. Interactive workshops will be offered for civil engineering faculty to disseminate project results, train faculty in the use of the modules, and obtain feedback that will help guide the development and usage of the modules. Faculty who are interested in adopting the modules will be able to download them from online repositories. This project will help prepare students for the complex systems problems that they will encounter in the engineering workforce.The goal of this project is to improve student learning in civil engineering by introducing cross-cutting themes of systems thinking and data analytics in existing courses. This project will develop seven educational modules for the cross-cutting themes: (1) systems thinking; (2) modeling; (3) cost, economics, and long-range planning; (4) optimization and decision making; (5) machine learning; (6) network analysis; and (7) data collection. Each module will include instructional materials describing how to adapt the module to courses, a presentation to help instructors teach the techniques used in the module, examples showing how to solve related problems, questions for assessing student learning outcomes, a dataset, and a mini project so that students can apply the techniques they have learned. This project will assess the impact on students by addressing a set of research questions including: (1) To what extent does student learning of systems/analytics increase after use of the modules? (2) To what extent can students apply analytics techniques in different civil infrastructure planning, operations, and management contexts? (3) Have students’ mindset/attitude about the importance of systems thinking and analytics changed as a result of the modules? This study will collect assessment data for a control group that does not use the modules and a treatment group that uses the modules to determine differences due to the modules. To disseminate the results and obtain feedback from multiple stakeholders, including industry and the engineering education community, two workshops will be convened. The workshops will be run as charrettes, an interactive form of participant engagement that solicits feedback and reflection for the co-creation of knowledge. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Institutional and Community Transformation track, the program supports efforts to transform and improve STEM education across institutions of higher education and disciplinary communities.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.