Data-Enabled Engineering Projects for Undergraduate Data Science and Engineering Education

Auburn University, Auburn AL

Investigators

Abstract

With support from the NSF Improving Undergraduate STEM Education Program: Education and Human Resources (IUSE: EHR), this project aims to serve the national interest by equipping undergraduate engineering students with the data science skills needed by current and future job markets. It intends to accomplish this goal by developing data-enabled engineering research modules that can be used as standalone enhancements to courses or assembled into complete course-based undergraduate research experiences (CUREs). The modular structure will make the modules and CUREs easy to integrate into existing courses. These research experiences will provide students with hands-on experience using large datasets from sensors embedded in industrial systems that use Internet-of-Things technologies. This approach is expected to increase student motivation, since the source of the data (e.g., Wi-Fi-enabled wheat moisture detection systems) is relevant to and easily understood by students. The research experiences will emphasize computational aspects of data science including machine learning, classification, regression, and clustering, thus helping to prepare data-capable engineers. It is expected that the modules and CUREs will also contribute fundamental knowledge to industrial Internet-of-Things data science research. The project will study the impact of the data-enabled research modules and CURES on student motivation, engagement, and achievement. Results of this research could inform the broader STEM education community about successful approaches for integrating data science education into STEM disciplines beyond engineering. In addition to investigating the impact of the data-enabled research modules and CUREs on student motivation, engagement, and achievement, the project will also test the hypothesis that data-enabled engineering research experiences will enhance students' reflection and metacognition. All of these student characteristics will be measured via standard instruments. For example, the Metacognition Awareness Inventory will be used to quantify changes in students' metacognition awareness between the beginning and end of a set of courses. Evaluation of the project will be conducted by the Auburn Center for Evaluation and the evaluation and project research findings will be disseminated through an Auburn University-hosted website, conference presentations, and publications. The project goals align well with NSF's goal of equipping undergraduate students with data science and engineering skills that are in high demand in the current and future job markets. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. This is an Engaged Student Learning Project, an IUSE: EHR track that supports the creation, exploration, and implementation of promising practices and tools. 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.