Peer Networks and Professional Identity in Data Science Classrooms

How does social capital generated between class-peers impact student's identity as data scientists? Does the type of instruction given in the classroom impact this relationship? We propose studying the peer networks generated in data science classrooms and exploring the influence of one's connection to peer-students on their identity as data scientists. Specifically, we propose exploring social capital in terms of network centrality, connectedness, support and reciprocity. We propose operationalising data science identity in terms of one's feeling of belonging and comfort in data science and the relevance of data science to their career. Finally, we explore whether student centredness vs. instructor centredness impacts the nature of this relationship. Or whether group activities and project-based learning can facilitate the types of peer interactions that generate social capital and help data science students develop professional identities. To collect data, we are surveying students throughout the semester. We will also code the syllabus of the course in which they are enrolled in terms of the pedagogical structure of the course.

Networks

Professional Identity

Data Science Education 

Education

Symposium on Data Science and Statistics (SDSS) 2025