Jackie Matthes teaches courses across all levels of the biology curriculum at Wellesley College, where she works to integrate data science and quantitative methods into her courses. She has developed many open education resources for her courses, which are linked below.
BISC 111: Introduction to Organismal Biology, Spring 2017-19, 2021
This is an introductory course for the Biological Sciences major. For this course, Jackie has developed several open education resources for introducing simulation modeling and data analysis into introductory biology. The apps are hosted at QUBES a web platform and server where modules can be run interactively by hundreds of students at once. Modules developed for BISC 111 include:
- Modeling the Mechanisms of Evolution, example class exercise, Shiny app is hosted on QUBES
- Investigating Trade-offs among Mammal Traits, example class exercise, Shiny app is hosted on QUBES
- Outstanding Oaks: Quercus Phenology at NEON Sites, module materials and Shiny app are hosted on QUBES
BISC 201: Ecology with Laboratory, Fall 2018, 2020
This course is a comprehensive introduction to ecology, designed primarily for sophomore and junior Biological Sciences or Environmental Studies majors. Click here to see the most recent syllabus from Fall 2020, when this course was taught in a remote format in a compressed 7-week term.
BISC 204: Biological Modeling with Laboratory, Spring 2017-18
This course is an introduction to using math and computer science to simulating dynamical processes in biology. We develop skills representing biological models conceptually, mathematically, and with computer code. The lab exercises in the course all focus on the theme of disease, are written in R, and are available on GitHub. The most recent course syllabus is available here.
BISC/ES 307: Ecosystem Ecology with Laboratory, Fall 2016-18, 2020
This senior-level course serves as an introduction to both ecosystem ecology and data science with R. Lab exercises for this course involve data collection in the field, analysis of field data with R, and aggregation and analysis of long-term ecological datasets from the NSF LTER and NEON programs.