Gaps in Computational Training in Undergraduate Biology Programs: Misalignment with Workforce Expectations in the Biosciences
To prepare students for emerging research technologies and careers in the life sciences, computational thinking and skills are increasingly essential in undergraduate biology programs. However, curricular change has not kept pace with the evolving demands of the biosciences workforce. At an independent, nonprofit research institute operating at the intersection of genetics and genomics and spanning academic research and biotechnology sectors, we observe a growing need for trainees and early-career scientists with both biological and computational expertise. To examine the alignment between workforce expectations and undergraduate preparation, we analyzed job descriptions at our institute over time and interviewed and surveyed faculty across the country to collect perspectives on undergraduate biology curricula. Our findings indicate that computational skills are increasingly emphasized in entry-level life science positions, while undergraduate biology curricula do not consistently reflect these expectations. Faculty reported persistent gaps in bioinformatics, computational biology, and data science, as well as barriers that constrain curricular updates. By comparing workforce expectations with faculty-reported challenges, this study provides insight into feasible pathways for integrating computational thinking and skills within existing curricular structures to better prepare students for careers in the biosciences.
Authors
- Therese Ingram Nissen
- Erica L. Gerace (ORCID: https://orcid.org/0009-0002-4148-0058)
- Sarah Wojiski
- William K. Barter (ORCID: https://orcid.org/0009-0000-8903-9523)
Institutions
- Yale University (US)
- Jackson Laboratory (US)
- Center for Genomic Science (IT)
Publication Details
- Journal
- The journal of college science teaching
- Published
- 2026-08-28
- DOI
- https://doi.org/10.1080/0047231x.2026.2722111
- Primary Topic
- Genetics, Bioinformatics, and Biomedical Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00