Project-Based Teaching: A Case Study of Learning Systems Theory and Signal Processing by a Dynamic Measurements Project

Research shows that, in learning science and engineering, guided project work leads to deeper understanding of theoretical concepts (as well as acquisition of hands-on skills) than the classical approach of textbook reading and attending lectures. In an approach to education based on project work, the role of the teacher is to create a stimulating learning environment and to supervise the students in accomplishing their objectives. The main challenge is to come up with projects that are engaging, diverse, and feasible in view of limited time and resources. In this paper, we describe such a signal processing project. The task is to improve the speed and accuracy characteristics of a sensor by real-time signal processing. It turns out that this is an application of Kalman filtering however the students need to identify a model of the sensor and implement the Kalman filter on a digital signal processor. The project consists of three main tasks: 1) mathematical formalization of the problem, 2) development of solution methods, and 3) implementation and testing of the methods. The testing is done on an inexpensive laboratory setup, using the Lego Mindstorms educational kit in combination with a temperature sensor. The learning outcomes are understanding of model representations, system identification, and state estimation as well as implementation in Matlab and C of real-time signal processing algorithms. Possible extensions are adaptive signal processing, multiple sensors data fusion, and nonconstant measured value estimation.