Secondary Student Mentorship and Research in Complex Networks: Process and Effects

Abstract

There is increasing interest in rethinking approaches to K-12 education that better prepare students to face an adult world and work life of data-driven and interdisciplinary science, technology, engineering, and mathematics (STEM). The science of complex networks, also known as network science, is the application of advanced graph theory to characterize, visualize, and analyze complex connected social, biological, technological, and physical systems. It is an important approach to study many problems in data-driven STEM and provides an intuitive pathway for students of any age to understand complex systems. This paper describes the development of a successful mentorship model that combines deep engagement with team research, enabling high school students and teachers to perform successful research projects in the science of complex networks.