What topics of peer interactions correlate with student performance in physics courses?

Abstract

Research suggests that interacting with more peers about physics course material is correlated with higher student performance. Some studies, however, have demonstrated that different topics of peer interactions may correlate with their performance in different ways, or possibly not at all. In this study, we probe both the peers with whom students interact about their physics course and the particular aspects of the course material about which they interacted in six different introductory physics courses: four lecture courses and two lab courses. Drawing on methods in social network analysis, we replicate prior work demonstrating that, on average, students who interact with more peers in their physics courses have higher final course grades. Expanding on this result, we find that students discuss a wide range of aspects of course material with their peers: concepts, small-group work, assessments, lecture, and homework. We observe that in the lecture courses, interacting with peers about concepts is most strongly correlated with final course grade, with smaller correlations also arising for small-group work and homework. In the lab courses, on the other hand, small-group work is the only interaction topic that significantly correlates with final course grade. We use these findings to discuss how course structures (e.g., grading schemes and weekly course schedules) may shape student interactions and add nuance to prior work by identifying how specific types of student interactions are associated (or not) with performance.

arXiv commentSubmitted to European Journal of Physics

References in corpus (13)

• Teaching Critical Thinking
• A Model for Social Networks
• 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
• Modernizing use of regression models in physics education research: a review of hierarchical linear modeling
• 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
• 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
• Understanding interaction network formation across instructional contexts in remote physics courses
• Snowboot: Bootstrap Methods for Network Inference