Teaching Project-Based Learning with Model-Based Design to Engineering Students at King’s College
“We want to formalize how students approach complex problems by introducing them to requirements-based testing, model-driven development, and evidence collection from operating a physical prototype. The model-based approach provides a robust foundation upon which to impart systems thinking and develop integration skills. It is important to appreciate the value of systems engineering from early on, and hopefully it lasts a lifetime.”
Key Outcomes
- Students were exposed to Model-Based Design early on, learning to apply it to real-world projects
- Improved student engagement by cultivating a sense of accountability and ownership over a physical product
- Students learned teamwork, role-based design, and systems thinking, gaining valuable employability skills
A Simulink 3D visualization of a student-built sample ship (above), along with a high-level view of the ship’s Simulink model (below).
King’s College London (KCL) is one of the oldest and most renowned universities in the United Kingdom. In 2019, KCL relaunched its General Engineering (GE) program with project-based learning modules making up 25% of student work time.
Currently, 220 KCL students are enrolled in the GE program, in which they learn systems thinking while gaining experience in role-based teams that reflect professional working environments. In the first-year module, Design: Making a Connection, student teams build a remote-controlled vessel with Model-Based Design to collect floating debris out of a water tank. The ship and its control strategy are developed and tested in Simulink®, after which a physical prototype is built and refined in the makerspace. Designs finally compete in a water tank to demonstrate their capabilities.
The combination of Simulink, Simscape™, and Arduino® Hardware support packages allow students to experience an end-to-end workflow for industrial design. By implementing a digital twin of the platform, learners can validate their modeling and control system design by comparing results between the simulation and the physical prototype.
