Date of Award
Doctor of Philosophy (PhD)
Education and Human Development
Dr. Russell Marion, Committee Chair
Dr. James Satterfield
Dr. Michelle Boettcher
Dr. Thomas Zagenczyk
As funding for institutions of higher education becomes tighter, state and federal entities have turned to student retention and graduation rates as measures of success to determine levels of financial support. A concept, supported by student development theories, used to increase retention and graduation rates is creating living learning communities (LLCs). Researchers previously concluded that student participation in an LLC positively affects student academic performance, engagement, and retention. The purpose of this study was to investigate how networks developed in a living learning community and what, if any, network variables contributed to academic performance. Specifically, dynamic network analysis using ORA software provided network statistics to determine how network density, component statistics, and cliques developed over the course of the semester. Additionally, ORA software determined social, advice, and study network Newman groupings to study how clusters of students developed during the semester. Finally, a regression analysis using JMP software and ORA derived network measures was accomplished to determine what network variables contributed to positive academic performance. Results found students who are well connected are likely to have better GPAs and consequently higher retention rates than students who are not well connected in the network. It was also interesting to note that residence hall living configurations restricted networking among LLC participants. Specifically, networking did not seem to take place between resident hall occupants who lived on different floors in the residence hall. Practitioners should schedule and promote and students should participate in activities that further network development.
De Julio, Edward B., "A Business School Living Learning Community: A Complexity Theory Study of Collaborative Engagement Using Network Analysis" (2017). All Dissertations. 2075.