individual

What campus are you from?

Daytona Beach

Authors' Class Standing

Christine Sessions, Graduate Student

Lead Presenter's Name

Christine Sessions

Faculty Mentor Name

Dr. Bryan Watson

Abstract

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. Through utilizing Shannon Entropy and applying Ecological Network Analysis techniques, this research aims to understand how an Embry-Riddle Aeronautical University student project team evolves over the first semester of the project. This research aims to answer the question “Does Project COMET’s team structure evolve the same way ecosystems do, and if so, how are they similar?” Graph theory will be used to represent communication structures, identify key nodes, information bottlenecks, and interaction patterns. The goal of this work is to determine influential members and detect potential communication gaps. This research will also demonstrate an approach to measuring team communication structures quantitatively. Lastly, the student-led research project’s graph theory metrics will be compared with and contrasted against a young ecosystem and a mature ecosystem. The methods proposed may help quantify and provide insights into key performance indicators like team dynamics, collaboration efficiency, and adaptive strategies for observing information flow in team structures. In the long term, this research aims to lay the foundation for the advancement of structured communication tracking and improved teamwork in educational and professional environments.

Did this research project receive funding support from the Office of Undergraduate Research.

No

Share

COinS
 

Leveraging Information Theory & Graph Theory to Monitor Communication Networks in Team Settings

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. Through utilizing Shannon Entropy and applying Ecological Network Analysis techniques, this research aims to understand how an Embry-Riddle Aeronautical University student project team evolves over the first semester of the project. This research aims to answer the question “Does Project COMET’s team structure evolve the same way ecosystems do, and if so, how are they similar?” Graph theory will be used to represent communication structures, identify key nodes, information bottlenecks, and interaction patterns. The goal of this work is to determine influential members and detect potential communication gaps. This research will also demonstrate an approach to measuring team communication structures quantitatively. Lastly, the student-led research project’s graph theory metrics will be compared with and contrasted against a young ecosystem and a mature ecosystem. The methods proposed may help quantify and provide insights into key performance indicators like team dynamics, collaboration efficiency, and adaptive strategies for observing information flow in team structures. In the long term, this research aims to lay the foundation for the advancement of structured communication tracking and improved teamwork in educational and professional environments.

 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.