In-depth understanding of collective MPI communication is a major challenge for both beginners and experienced developers. It is challenging to grasp the operations of collective algorithms, as many performance analysis tools cannot break down collective operations into their underlying point-to-point communication. However, collective communication is a key factor in optimizing the performance of parallel programs. EduMPI is a novel tool for parallel programming education, providing near-real-time visualization of collective MPI algorithms. It displays per-process data exchange and highlights performance issues like Late Sender and Late Receiver. This paper introduces the visualization of collective communication in EduMPI, demonstrates how this representation aids in understanding the concept of collective communication and its relevance for performance optimization, and evaluates its effectiveness in an educational context. EduMPI bridges the gap in understanding complex collective MPI operations by providing a transparent view of the underlying processes, enabling students to visualize and better understand the communication flow.