Studying community development: a network analytical approach

TL;DR

This study employs social network analysis of classroom video data to examine how student interactions and conversation topics evolve during a summer STEM program, revealing shifts toward more on-task communication indicative of community development.

Contribution

It introduces a novel network analysis method based on coded classroom video to track community development through conversation topicality in a STEM learning environment.

Findings

Conversations become more on-task over time.

Shift in conversation topicality indicates community formation.

Network analysis reveals changes in student interaction patterns.

Abstract

Research shows that community plays a central role in learning, and strong community engages students and aids in student persistence. Thus, understanding the function and structure of communities in learning environments is essential to education. We use social network analysis to explore the community dynamics of students in a pre-matriculation, two-week summer program. Unlike previous network analysis studies in PER, we build our networks from classroom video that has been coded for student interactions using labeled, directed ties. We define 3 types of interaction: on task interactions (regarding the assigned task), on topic interactions (having to do with science, technology, engineering, and mathematics (STEM)), and off topic interactions (unrelated to the assignment or STEM). To study the development of community in this program, we analyze the shift in conversation topicality over the course of the program. Conversations are more on-task toward the end of the program and we propose that this conversational shift represents a change in student membership within their forming community.