Communities of color across the nation face increasing challenges with affordable access to safe drinking water. Using data science to explore why, where and how this is happening, and what is being done about it, provides a powerful vehicle for the engagement of students in science, technology, engineering, and mathematics (STEM), and to help develop a digital work force with appropriate representation from the affected communities.

Relatively little research exists on the use of experiences with physiological sensors to support STEM education. In this work, we draw on techniques from physiological computing and computer science education to explore novel ways to build students' computational thinking skills.

This project is a multiyear study of the impact of an enrichment program that the US National Science Foundation (NSF) managed in the 1990s. The Young Scholars Program (YSP) involved around 18,000 7th–12th grade students and 600 separate grants between 1989 and 1996. The purpose of YSP was to introduce high-achieving middle and secondary school students to science, technology, engineering, and mathematics (STEM) fields to encourage their entry into those fields and thus increase the size and quality of the nation’s STEM workforce.

We will develop a unique community-based ecosystem for teaching high school students about how the intersection between rapidly developing technologies such as data science and machine learning impact critical healthcare decisions. Students will learn and apply technological skills valued for high-paying jobs within our workforce and proving the importance of diversity.

This project aims to adapt the Geospatial Semester for Career and Technical Education in a large urban district through effective teacher professional development and lesson design.

Data Jam engages students in the process of exploring, analyzing, and summarizing long-term data about nearby ecosystems that are the subject of extensive long-term study by LTER.