Motivated by a National Academy of Sciences report on Data Science for Undergraduates, this is the first time interdisciplinary faculty from Virginia Tech (VT), North Carolina Agricultural and Technical University (NC A&T, an HBCU), and Vanderbilt University (VU) have proposed a large-scale collaborative effort to promote innovation and change in undergraduate STEM+C curricula. This unique effort s informed by investigators’ prior successful NSF grants and will generate new knowledge about data science-integrated STEM learning. Two unique, high-frequency data monitoring systems – one at VT and another at VU – are the key data sources that will facilitate the proposed teaching, learning, and research activities. This project impacts at least 8 interdisciplinary courses in computer science, engineering, biology, and environmental science, from sophomore to senior levels, reaching about 1300 students over the 3-year project period. The overall goal of this project is to develop and implement an interdisciplinary collaborative approach to support undergraduate students in developing Data Science expertise through various SEM+C disciplines including engineering, computer science, environmental science and biology. Specific objectives are to: (i) integrate real-world data from two high frequency monitoring systems (one on water monitoring at VT and another on traffic monitoring at VU) into 8 relevant SEM+C courses at VT, VU, and NC A&T; (ii) conduct research on student learning using data across various disciplines, institutions, gender, ethnicity, and develop and implement learning modules’ transferability plan to extend the breadth of the impact of this project beyond the partnering universities.