Signal analysis is a central component in engineering education. While the theoretical foundation is taught in detail in many courses like e.g. signal theory, the curricula often offer only few application-based learning opportunities. The reason for this is that physical implementation of signal processing requires expensive experimental equipment. Alternatively, students can experiment with digital signal processing, but this requires specific programming skills. Another problem is that typically, despite several signal analysis methods are taught, problem solving strategies are not. This becomes evident when students are confronted with real-world problems. They often possess the necessary knowledge and they can explain specific methods, but they do not know what to apply to a given problem.
In order to provide students with experimental learning opportunities with a focus on problem solving at the undergraduate level, an easy-to-use signal processing software, the 'Multi Channel Analyser' (MCA), is in development at our group. The MCA, which is an open source project, enables virtual signal processing by connecting processing blocks graphically, thus requiring no programming skills. It can be used in courses such as about measurement, instrumentation, and signal analysis, or in laboratory courses. For example, the function of circuits to be designed in a laboratory course can be examined virtually on a block-level to aid in choosing a fitting circuit implementation. The MCA is written in Python and also provides an easy-to-use, well-documented API to implement new signal processing blocks.
In this workshop, the attendees will first be shown how an application-oriented task can be designed using the MCA. Attendees are asked to bring their own laptop to be able to test the MCA in their preferred operating system. After the introduction, the attendees will take the role of a student and try to solve an exemplary task themselves. Based on the experiences in this practical part, the following questions will be discussed:
- Do the attendees use any similar software/methods in their daily teaching?
- How was the user experience in solving the given task and were there problems in using the MCA?
- Could the attendees imagine to use our software and are there suggestions for improvement?
If feasible, we will implement the discussed improvements in our software and publish them for everyone to use.
We will also elaborate on our first experiences in teaching with the MCA. However, as the software development is still ongoing, broad usage in our lectures still has to be established and the influence on the learning outcome has to be examined. In the future, it should also be investigated to what extent an automated evaluation of the user interaction with the MCA is possible.
