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，帮助学生在土木和环境工程方面培养系统思维和数据分析技能，从而为国家利益服务。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，帮助学生学习系统设计和分析技能。该项目将开发7个教育模块，包括一个小型项目、土木工程系统的数据集、评估问题和解决示例问题的多媒体内容。这些模块在提高学生系统思维和数据分析技能方面的有效性将在多个现有土木工程课程的背景下进行评估。结果将用于通知模块的开发和实施。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。有兴趣采用这些模块的教师可以从在线存储库下载这些模块。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。该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。本项目将为跨领域主题开发七个教育模块：(1)系统思维；(2)建模;(3)成本、经济性和长期规划；(4)优化决策；(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，展示如何解决相关问题的示例，评估学生学习成果的问题，数据集和一个小项目，以便学生可以应用他们所学的技术。该项目将通过解决一系列研究问题来评估对学生的影响，这些问题包括：(1)在使用这些模块后，学生对系统/分析的学习在多大程度上增加了？(2)学生在多大程度上可以将分析技术应用于不同的民用基础设施规划、运营和管理环境？(3)这些模块是否改变了学生对系统思维和分析重要性的心态/态度？本研究将收集未使用模块的对照组和使用模块的治疗组的评估数据，以确定模块造成的差异。为向业界及工程教育界等不同持份者传播研究结果及征求意见，我们将举办两次研讨会。研讨会将以charrettes的形式进行，这是一种参与者参与的互动形式，征求反馈和反思，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的STEM教育转型和改善。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.