Preprints
Filtering by Subject: Scholarship of Teaching and Learning
Is Biology Necessary to Advance Biology?
Published: 2026-07-14
Subjects: Biochemistry, Biophysics, and Structural Biology, Biodiversity, Bioinformatics, Biology, Cell and Developmental Biology, Computational Biology, Philosophy, Scholarship of Teaching and Learning, Systems Biology
AI is transforming the workflow of biological science. But what role remains for human cognition when the priority is deep theory? We propose a division of labor based on a “coverage asymmetry” between artificial and biological agents. AI excels at extending the encounterable: scaling known mechanisms and exploring complex parameter regimes. However, AI cannot (yet) perform kind formation – the [...]
Navigating the science policy interface: A co-created mind-map for early career researchers
Published: 2023-04-24
Subjects: Biodiversity, Environmental Education, Environmental Policy, Environmental Studies, Other Public Affairs, Public Policy and Public Administration, Scholarship of Teaching and Learning, Sustainability
The science-policy interface (SPI) is a complex space, in theory and practice, that sees the interaction of various actors and perspectives coming together to enable scientific knowledge to support decision-making. Early Career Researchers (ECRs) are increasingly interested in engaging with SPI, with the number of opportunities to do so increasing at national and international levels. However, [...]
Mixed-method analysis of college student perceptions towards R suggest lecture and self-paced tutorial introductions produce similar outcomes
Published: 2021-02-18
Subjects: Education, Higher Education, Scholarship of Teaching and Learning
Quantitative literacy is necessary to keep pace with the exponentially increasing magnitude of biological data and the complexity of statistical tools. However, statistical programming can cause anxiety in new learners and educators alike. In order to produce graduates that are well-prepared for quantitative research, overcoming the initial hurdles associated with statistical programming is a [...]