PS 26-99 - From courses to curricula: Integrating data science skills into life science education

Abstract: The Biological and Environmental Data Education (BEDE) Network’s (NSF RCN-UBE) main objective is to support instructors as they integrate data science skills across undergraduate biology and environmental science curricula, through curricular maps, instructor training, and a network of supportive colleagues. BEDE Network will cultivate an inclusive community of educators that grows beyond training workshops. Continued engagement will prolong interactions and facilitate greater self-efficacy, potentially changing attitudes about teaching data science in biology and environmental sciences courses more broadly. In the first two years, BEDE Network has brought together scientists and educators at two annual meetings (over 50 people), three workshops (over 30 participants), and through the QUBESHub and Slack groups (108 and 62 members respectively). Modern ecology has increasingly recognized the need for data science skills to be part of the undergraduate curriculum, but instructor- and department- driven changes to academic coursework and mentoring face several challenges. The BEDE Network aims to address these challenges by building upon data-driven inquiry that identifies instructor needs and key barriers to data science instruction in undergraduate biology and environmental science classrooms. Our survey results indicate that data management, visualization, and analysis are taught by many instructors (40%, 70%, and 80% respectively), and viewed as important data science skills (65%, 85%, and 90% respectively). Coding, modeling, and reproducibility were less valued by the instructors, although this differed according to institution type and career stage (e.g. 42% of instructors at doctoral universities frequently use coding compared to 26% at baccalaureate colleges). The greatest barriers to instruction were instructor and student background, and space in the curriculum.



Here, we summarize the themes that emerged from conversations at our first two annual meetings (2022 and 2023) focused on inclusive teaching practices and on designing a curriculum map for data science in undergraduate coursework. We also provide initial results for an ongoing project that addresses the pedagogical and technical challenges of integrating data science into large and small classrooms and a more targeted survey approach that quantifies data science skills currently being taught across undergraduate life science curricula. We invite others to join the BEDE Network and to participate in our ongoing efforts to share open education resources, mentor other faculty, and contribute to workshop and curricular design tools that will improve integration of data science skills in undergraduate classrooms and instructor self-efficacy.