C-SoDA Spring Lecture Series

The Center for Social Data Analytics will be hosting Trevion Henderson, Assistant Professor of Mechanical Engineering at Tufts University, as our second guest speaker in our Spring 22 lecture series. His talk will be held on Friday, March 25 at 12:15 - 1:30 p.m. via Zoom.  His talk is titled: "Multilayer ERGM for Education Research: Opportunities and Limitations for Diversity Research".  Trevion's information is listed below.

Zoom: https://psu.zoom.us/j/94829018373?pwd=UEk0WmN6RmhBMUR1eVJKLzN2VlhZdz09 ​ passcode: 194972

Bio: Dr. Trevion Henderson is an Assistant Professor of Mechanical Engineering at Tufts University. He earned his Ph.D. in Higher Education from the University of Michigan, as well as his M.A. in Higher Education and Student Affairs and his B.S. in Computer Science and Engineering from The Ohio State University. Dr. Henderson holds secondary appointments in the STEM Education program in the Department of Education and the Institute for Research on Learning and Instruction (IRLI) at Tufts University. Dr. Henderson’s research is broadly concerned with how students’ in- and out-of-classroom experiences affect their learning, focusing particularly on the ways that the culture of engineering education produces and reifies systems of inequality. As a first-year professor at Tufts, Dr. Henderson teaches courses on engineering design education, computing in engineering, and education research methods.

Abstract: Education researchers are often concerned with the role of social relationships in facilitating critical academic and social outcomes. Understanding social relationships is particularly important when analyzing the nature and consequences of diversity, equity, and inclusion concerns in educational research. As a result, network methodologies, which focus our attention on the relationships between actors, are increasingly popular approaches to studying educational processes both in and outside of the classroom. However, existing research is limited in that we often analyze social relationships in isolation, neglecting the ways that some relationships inform, and are informed by, others. In this talk, I will discuss a method for examining multiple social relationships simultaneously—the multilayer exponential random graph model (ERGM). Drawing on findings from a study of student teamwork in engineering, I will point to both the power and limitations of this novel approach for studying educational processes. Additionally, I will discuss how other sources of data, particularly qualitative data, can enrich our understandings of diversity, equity, and inclusion issues in education research that draws on network methodologies.