Macrosystems Biology in R with NEON
<p>This resource describes a stand-alone computational lab course called Macrosystems Biology that takes students through the process of conducting continental-scale research in environmental biology using existing data from the National Ecological Observatory Network (NEON). In the process it teaches elementary coding in R.&nbsp;It is designed for 3rd and 4th year traditional &nbsp;undergraduates in Biology or Environmental Science who have never used a programming language. The course is taught as a lab that includes live-coding demonstrations, self-paced individual work through an online textbook (<a href="https://qubeshub.org/publications/6059/about">Introduction to Computing in R with NEON</a>), and collaborative research feedback sessions as students develop their own research projects. The course culminates in a research presentation (poster or slide-based talk).</p> <p><strong>Learning Outcomes</strong></p> <p>1.&nbsp;Conduct self-directed independent inquiry by using existing data sources to explore a biological question at a continental scale.&nbsp;</p> <p>2.&nbsp;Apply introductory computing skills used in data science and bioinformatics to biological data sets. Specifically,&nbsp;</p> <ul> <li>Demonstrate familiarity with metadata and reproducible workflows.</li> <li>Organize tabular data into computer readable formats following best practices in data science.&nbsp;</li> <li>Use a programming language to download, manipulate, summarize and visualize data.</li> </ul> <p><strong>Contents</strong></p> <p>This resource includes an example syllabus that follows a standards-based grading framework, along with an example of a grading table used to assess learning outcomes. It also includes a description of three research feedback sessions used to guide students through the research process and assess LO2.&nbsp;</p> <p><strong>Future Development</strong></p> <p>Future versions will integrate AI as a coding and research partner and update the course textbook.</p> <p>The course is currently taught at Saint Mary&#39;s College of California- instructors interested in developing and teaching a collaborative multi-institutional version of this course should contact the author.</p>
Authors
- Jessica Coyle (ORCID: https://orcid.org/0000-0001-5428-8669)
Institutions
- Saint Mary's College of California (US)
Publication Details
- Journal
- QUBES
- Published
- 2026-07-23
- DOI
- https://doi.org/10.25334/b215-he26
- Primary Topic
- Genetics, Bioinformatics, and Biomedical Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00