Teaching

About | Research | Teaching | Network Tutorials | CV | Visualising Grime

I love teaching! As a first-generation college student, I found the prospect of teaching at university daunting. However, over the last five years I have developed a passion for helping undergraduate and graduate students discover their interests and their talents. This passion is substantiated by the strongly positive feedback I have received from my students. Please see HERE for evidence of my teaching effectiveness.

I have taught courses across multiple disicplines and modalities. Those within sociology I have taught to undergraduate students while the methods and data science courses I have taught to undergraduate and graduate students. Here is a list of the courses that I have taught to-date.

Sociology

• SOC 202 Introduction to Sociology
• SOC 205 Jobs and Work

Methods/Data Science

• DSA 295 Introduciton to Network Analysis
• SOC 300 Social Research Methods (lab)
• Peer Scholars Program in-person - Social Network Analysis
• Peer Scholars Program -asynchronous - Social Network Analysis

Teaching Philosophy and Example Activity

As a teacher, I’m mindful of my role in either reinforcing or challenging the exclusion of diverse perspectives. Like in my research, I intentionally include multiple viewpoints in my teaching. For instance, in teaching sociological methods, I highlight foundational work by marginalized scholars like Du Bois, whose data visualizations remain influential. I also adapt my teaching to reflect local histories and diverse thought. After realizing I had overlooked local context in a course on the sociology of race while at NC State, I incorporated events like the Greensboro sit-ins, the Wilmington Massacre, and the Cherokee Nation’s removal. In doing so, students engaged more deeply with concepts like the Colour Line and the veil by connecting theory to local history.

Furthermore, I beleive in teaching using fun, accesible methods. In fact, part of my work at the Data Science and AI Academy has been to develop a student-centred model for teaching data science across disicplines (more on ADAPT here). Part of this is to find relatable, even fun ways to teach complex concepts. For example, when I teach methods, I find or construct fun datasets to work with. Below is an example.

Two Mode Networks

This is an activity I created using Harry Potter data to demonstrate how to measure the duality of individuals and groups using networks. Static versions of this content is available in my TRAILS publication. Here, I provide interactive networks. The Interactivity provides students with a physical experience while learning about networks.

First, students map Harry Potter characters’ relationships to groups in the serries (click to move and scroll in and out).

Second, students look at the symbolic connections between groups who share students. (Hover over the node to see the group names). An obvious “good” and “bad” divide here!

Students also examine the symbolic connections between characters based on mutual group affiliation. Through community detection they discuss the latent communities of individuals and groups that are symbolically connected through dual mutual affiliation or shared affiliates.

Further Open-source Teaching Material