Effective communication is a critical component of successful collaboration in group projects and team settings. However, tracking and analyzing these communications can be challenging, especially in ..
Effective communication is a critical component of successful collaboration in group projects and team settings. However, tracking and analyzing these communications can be challenging, especially in complex, multi-member teams. This paper explores an information-theoretic approach that leverages encoding techniques and graph theory to model and monitor communication networks within a university group project. By applying encoding methods, such as Huffman Coding, we will provide efficient data transmission and minimize misunderstandings through the results. Additionally, graph theory will be used to represent communication structures, identifying key nodes, information bottlenecks, and interaction patterns. MATLAB algorithms will help determine influential members and detect potential gaps in communication. This research will demonstrate that the methods proposed can provide insights into team dynamics, enhance collaboration efficiency, and support adaptive strategies for improving information flow in academic team settings. This research will contribute to the broader understanding of structured communication tracking and improved teamwork in educational and professional environments.
