Data Science in Undergraduate Life Science Education: A Need for Instructor Skills Training. (27th October 2021)

• Record Type: Journal Article
• Authors: Emery, Nathan C; Crispo, Erika; Supp, Sarah R; Farrell, Kaitlin J; Kerkhoff, Andrew J; Bledsoe, Ellen K; O'Donnell, Kelly L; McCall, Andrew C; Aiello-Lammens, Matthew E
• Is Part Of: BioScience. Volume 71:Number 12(2021)
• Page Start: 1274
• Page End: 1287
• Publication Date: 2021-10-27
• Subjects: biology -- environmental science -- data science -- pedagogy -- higher education; Life sciences -- Periodicals; Life sciences -- Research -- Periodicals; Life sciences -- United States -- Periodicals; Life sciences -- Government policy -- United States -- Periodicals; Biology -- Periodicals; Biotechnology industries -- Periodicals; 570
• DOI: 10.1093/biosci/biab107
• Languages: English
• ISSNs: 0006-3568

Abstract

Abstract: There is a clear demand for quantitative literacy in the life sciences, necessitating competent instructors in higher education. However, not all instructors are versed in data science skills or research-based teaching practices. We surveyed biological and environmental science instructors (n = 106) about the teaching of data science in higher education, identifying instructor needs and illuminating barriers to instruction. Our results indicate that instructors use, teach, and view data management, analysis, and visualization as important data science skills. Coding, modeling, and reproducibility were less valued by the instructors, although this differed according to institution type and career stage. The greatest barriers were instructor and student background and space in the curriculum. The instructors were most interested in training on how to teach coding and data analysis. Our study provides an important window into how data science is taught in higher education biology programs and how we can best move forward to empower instructors across disciplines.