Network analysis can inform our understanding of student network formation in classrooms and the types of impacts these networks have on students. These relationships, and the larger networks they create, have significant effects on student behavior. While groups on campus exist to facilitate social interactions, the classroom is a principle domain wherein working relationships form between students. Social relationships are a major aspect of the undergraduate experience. Our aims are to convince readers that using SNA in classroom environments allows rich and informative analyses to take place and to provide some initial tools for doing so, in the process inspiring future educational studies incorporating relational data. We also cover practical issues, such as the unique aspects of human subjects review for network studies. We explore generative processes that create observed study networks between students and also test for an association between network position and success on exams. We conduct descriptive analyses of the structure of the network of costudying relationships. We introduce basic concepts in SNA, along with methods for data collection, data processing, and data analysis, using a previously collected example study on an undergraduate biology classroom as a tutorial. Social network analysis (SNA) provides the necessary tool kit for investigating questions involving relational data. Understanding how learning relationships form in undergraduate classrooms, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve educational reform. Social interactions between students are a major and underexplored part of undergraduate education.
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