Macrosystems Biology in R with NEON

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. It is designed for 3rd and 4th year traditional  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 (Introduction to Computing in R with NEON), and collaborative research feedback sessions as students develop their own research projects. The course culminates in a research presentation (poster or slide-based talk). Learning Outcomes 1. Conduct self-directed independent inquiry by using existing data sources to explore a biological question at a continental scale.  2. Apply introductory computing skills used in data science and bioinformatics to biological data sets. Specifically,  Demonstrate familiarity with metadata and reproducible workflows. Organize tabular data into computer readable formats following best practices in data science.  Use a programming language to download, manipulate, summarize and visualize data. Contents 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.  Future Development Future versions will integrate AI as a coding and research partner and update the course textbook. The course is currently taught at Saint Mary's College of California- instructors interested in developing and teaching a collaborative multi-institutional version of this course should contact the author.