Result: Active learning of parallel programming in engineering through recurring problems

The teaching of parallel programming in undergraduate engineering programs poses challenges related to high cognitive load and limited student engagement. This study presents a pedagogical strategy aimed at facilitating meaningful learning through a reduction in problem domain complexity and active learning techniques. The proposed approach was implemented in a core course on multiprocessor programming in an undergraduate Computer Engineering degree. Three well‐known problem patterns were selected to guide students through different parallel implementations (OpenMP, PThreads, and MPI). This problem reduction strategy enabled scaffolded learning experiences while minimizing the cognitive barriers typically associated with high‐performance computing education. The approach was designed to promote student motivation and autonomy through guided discovery, hands‐on sessions, and peer interaction. Results from student feedback and course outcomes suggest that this methodology improved comprehension, confidence, and engagement. The article discusses the implications of using reduced problem domains and active learning for teaching parallelism in engineering education, and proposes a replicable framework for similar contexts.