Course Improvement of An Introduction to Programming Course in ECE: Customizing Learning Paths for Parallel Computing Topics

As data sets grow larger and computational problems become more complex, parallel computing is increasingly recognized as a key solution for unlocking the potential of computer resources and achieving more efficient task resolution. Parallel computing offers many advantages, such as faster computations, significant cost savings, reduced energy consumption, and the ability to create dynamic models. Despite its widespread use in today's world, introductory Electrical and Computer Engineering (ECE) courses often do not cover this essential topic and its associated skills. To address this issue, a team at University of Illinois Urbana-Champaign has designed custom learning paths to introduce parallel computing at an earlier stage through additional learning modules, aiming to enable students to extend their knowledge while preparing them for advanced computing courses in the future. This paper focuses on the design, improvement, and assessment of the course, investigating the implementation and outcomes of optional learning opportunities created in a 200-level introduction to programming course. The paper presents the details of each extended learning opportunity and analyzes the differences in student performance on a related extra credit quiz in correlation with their course grade, the difficulty level of parallel computing topics introduced, and the lessons learned by students and instructors that can be applied to future programs.