Understanding interaction network formation across instructional contexts in remote physics courses

Abstract

Engaging in interactions with peers is important for student learning. Many studies have quantified patterns of student interactions in in-person physics courses using social network analysis, finding different network structures between instructional contexts (lecture and lab) and styles (active and traditional). Such studies also find inconsistent results as to whether and how student-level variables (e.g., grades and demographics) relate to the formation of interaction networks. In this cross-sectional research study, we investigate these relationships further by examining lecture and lab interaction networks in four different remote physics courses spanning various instructional styles and student populations. We apply statistical methods from social network analysis -- exponential random graph models -- to measure the relationship between network formation and multiple variables: students' discussion and lab section enrollment, final course grades, gender, and race/ethnicity. Similar to previous studies of in-person courses, we find that remote lecture interaction networks contain large clusters connecting many students, while remote lab interaction networks contain smaller clusters of a few students. Our statistical analysis suggests that these distinct network structures arise from a combination of both instruction-level and student-level variables, including the learning goals of each instructional context, whether assignments are completed in groups or individually, and the distribution of gender and major of students enrolled in a course. We further discuss how these and other variables help to understand the formation of interaction networks in both remote and in-person physics courses.

arXiv commentTo be published in Physical Review Physics Education Research

References in corpus (14)

• Teaching Critical Thinking
• A Model for Social Networks
• Studying physics during the COVID-19 pandemic: Student assessments of learning achievement, perceived effectiveness of online recitations, and online laboratories
• Value added or misattributed? A multi-institution study on the educational benefit of labs for reinforcing physics content
• Students' network integration as a predictor of persistence in introductory physics courses
• Investigating Student Communities with Network Analysis of Interactions in a Physics Learning Center
• Linking engagement and performance: The social network analysis perspective
• Beyond performance metrics: Examining a decrease in students' physics self-efficacy through a social network lens
• Exponential Random Graph models for Little Networks
• Educational commitment and social networking: The power of informal networks
• Network positions in active learning environments in physics
• Talking by the numbers: Networks identify productive forum discussions
• Practitioner's guide to social network analysis: Examining physics anxiety in an active-learning setting
• "Everyone is new to this": Student reflections on different aspects of online learning

Cited by in corpus (6)

• Gender Equity in Physics Labs: A Review
• Who and what gets recognized in peer recognition
• Person-centered and qualitative approaches to network analysis in physics education research
• Bias in physics peer recognition does not explain gaps in perceived recognition
• What topics of peer interactions correlate with student performance in physics courses?
• Investigating peer recognition across an introductory physics sequence: Do first impressions last?