Data Science For STEM

Project Summary

• Overview: 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) proposed a large-scale collaborative effort to promote innovation and change in undergraduate STEM+C curricula. This unique effort is informed by investigators’ prior successful NSF grants and will generate new knowledge about data science-integrated STEM learning.
• Project Goals: Develop and implement an interdisciplinary collaborative approach to support undergraduate students in developing Data Science expertise through various STEM+C disciplines including engineering, computer science, environmental science and biology. Specific objectives are to:
  • 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 STEM+C courses at VT, VU, and NC A&T
  • conduct research on student and instructor perspectives of data science learning using data across various disciplines, institutions, gender, and ethnicity
  • and extend the impact of this project beyond the partnering universities through the dissemination of learning materials created with key considerations for integrating data science into different STEM+C courses. 
• Data Sources: Two unique, high-frequency data monitoring systems – one at VT and another at VU – facilitated the proposed teaching, learning, and research activities.
• Project Impact: 8 interdisciplinary courses in computer science, engineering, biology, and environmental science, from sophomore to senior levels, reached about 1300 students over the 3-year project period