Author(s):
Need:This project builds on the American Association for the Advancement of Science ’s 2011 Vision and Change call for increased engagement of undergraduate students in scientific research experiences, particularly ethnic racialized minorities at historically black college and universities (HBCUs) where there are shortages of research laboratories, low student achievement, and high attrition rates from STEM majors. Current efforts to improve undergraduate STEM education include the adoption of course based undergraduate research experiences (CUREs) that have been inserted into college curricula and designed to successfully engage large numbers of undergraduate students in scientific research. CUREs broaden access to the high impact practice of research and are a novel way to engage students using research as a teaching modality. To date, relatively few studies on the outcomes of CUREs have been conducted at minority-serving institutions; therefore, not much is known about the unique student outcomes and design challenges associated with implementation of CUREs in these environments. The Donald Danforth Plant Science Center (DDPSC), a non-academic, non-profit plant science research facility collaborated with faculty at Harris Stowe State University a HBCU, to design and implement a CURE that engages students in basic computer programming in Python to conduct digital image data processing and analysis using an open-source software program built on general image analysis tools. The data science CURE was implemented in STEM undergraduate classrooms over two Fall semesters, Fall 2022 and 2023.Guiding question: How does engagement in a plant image data science CURE impact student learning outcomes at a HBCU?Outcomes: Qualitative data on participant undergraduate students’ outcomes reveals gains in computer science skills, research skills and practices and data science skills including Python programming, image analysis, research methodologies, and data manipulation. Participant undergraduate students also demonstrated heightened engagement in data science learning and developed interests in data science careers.Broader Impacts: This project has a multifaceted impact. It has enabled the development of a novel course and curricula in data science based on plant image data, that integrates biology, mathematics and computer science disciplines facilitating collaboration, and faculty professional development across disciplines. It has also effectively engaged racially minoritized students, deepening their understanding of complex data science concepts and equipping them with valuable technical skills for future careers. This project has also exposed racially minoritized students to careers in data science and fostered the development of a pipeline connecting students from a HBCU to careers in plant science and data science at diverse organizations ultimately contributing to STEM diversification and broadening participation efforts.
Coauthors
Ruth J Kaggwa, Donald Danforth Plant Science Center; Precious Hardy, Donald Danforth Plant Science Center
