2023 ASEE Annual Conference & Exposition

Data science is an emerging field that encompasses several STEM domains and offers exciting career prospects in a wide range of engineering applications. Several studies have emphasized that the use of data science in the present civil engineering undergraduate curricula is mostly restricted to simple introductory subjects, usually with the use of Microsoft Excel. The curriculum does not encourage students to fully benefit from big data since data science is not extensively used. In Additionally, there is a lack of clear guidance on how to strengthen the synergy between common civil engineering courses and data science.

In this paper, the authors will report on a recently introduced course entitled “Data Science and Engineering Systems Analysis,” at XXX University, incorporating the integration of R programming into data analytics, and systems thinking for the analysis and design of civil engineering applications. The course aims at empowering students with the necessary tools to apply statistics in a civil engineering context, perform data transformation, data wrangling, visualization, and modeling using R for data science. In this course, students learn how to gather and analyze data as part of the engineering design process, apply systems thinking to an engineering or societal phenomenon, collaborate with peers to find solutions, and effectively present solutions to an audience.

This work will aim at reporting four main issues, namely (1) the unique components of the current integrated Data Science and Engineering Systems Analysis Course, (2) an account of selected civil engineering projects using R for data science, (3) a survey result collecting data on students’ attitude and belief towards data analysis and its impact on the civil engineering profession, and (4) strategy to enhance synergy between data science and other engineering courses within the curriculum. It is anticipated that a thorough examination of the course's features, students' perceptions, and course synergy-enhancing factors would help to develop a guideline for data science curriculum development, implementation, and evaluation in civil engineering.