Educators in disciplines across the Sciences use MATLAB. Their main objective is to teach scientific concepts while instilling quantitative thinking in their students. To achieve that goal, educators must teach (and students must learn) computational skills and how to use them to express, analyze, and model scientific phenomena.
From code examples and how-to videos, to teaching activities, to assessment and auto-grading tools, there are multiple resources and tools to support learning in and out of the classroom. These resources lessen the educators’ workloads.
Whether you’re an individual educator, a member of a department-wide team, or a curriculum developer, these teaching resources can help you effectively teach the triad of science, analytical thinking, and computational skills.
Teach and Learn MATLAB
Teaching Physics with MATLAB
Teaching Geoscience with MATLAB
Teaching Biology with MATLAB
Teaching Calculus with MATLAB
Teaching Chemistry with MATLAB
Teaching Psychology and Neuroscience
Autograde MATLAB code
Get students up-to-speed via MATLAB Onramp, a free, interactive on-line tutorial.
SERC/MATHWORKS TEACHING COMPUTATION WORKSHOPS FOR FACULTY
Faculty and MATLAB experts came together at multiple annual workshops to share and create best practices for teaching science with MATLAB. View the aggregated learnings:
View resources and outcomes from the workshops, hosted by SERC, focused on Teaching Computation in the Sciences
View resources and outcomes from the Teaching Geoscience with MATLAB workshop hosted by SERC
Case Studies: Teaching with MATLAB
- Vanderbilt: Teaching Computer Programming to Students Everywhere
- Virginia Tech: Teaching Instrumentation of Biological Systems
- Technische Universiteit Eindhoven: Automatic Grading of MATLAB Assignments
MATLAB in the Sciences and Downloadable MATLAB code
- LIGO: Confirming the First-Ever Detection of Gravitational Waves
- Digitseis: Analyzing Decades-Old Seismograms at Harvard University
- GMT Support: MATLAB API for GMT (Generic Mapping Tools)
- ForWarn: NASA develops web-based forest early warning system