Running head: PEER INFLUENCES IN READING Peer Influence on Children’s Reading Skills: A Social Network Analysis of Elementary School Classrooms North Cooc The University of Texas at Austin College of Education

Research has found that peers influence the academic achievement of children. However, the mechanisms through which peers matter remain underexplored. The present study examined the relationship between peers’ reading skills and children’s own reading skills among 4,215 total secondand third-graders in 294 classrooms across 41 schools. One innovation of the study was the use of social network analysis to directly assess who children reported talking to or seeking help from and whether children who identified peers with stronger reading skills experienced higher reading skills. The results indicated that children on average identified peers with stronger reading skills and the positive association between peer reading skills and children’s own reading achievement was strongest for children with lower initial levels of reading skills. The study has implications for how teachers can leverage the advantages of peers via in-class activities. Keywords: peer effects, social networks, reading skills Submission date: October 25, 2016 PEER INFLUENCE IN READING 2 Educational Impact and Implications Statement This study shows that early elementary school children report identifying and interacting with peers with stronger reading skills within the same classroom. Children with low initial reading skills are more likely to identify such peers than high achieving children and those who do so experience higher reading outcomes later on. The study suggests that peer effects may occur through the peer-seeking patterns of children and the direct expertise of their peers. PEER INFLUENCE IN READING 3 Peer Influence on Children’s Reading Skills: A Social Network Analysis of Elementary School Classrooms The influence of peers on student learning and achievement has long been an interest of educators, parents, and researchers. Classroom decisions about student grouping, whether through formal tracking or informal reading activities, are often guided by beliefs about how students interact and learn from each other (e.g., Hong, Corter, Hong, & Pelletier, 2012). Parents may also make decisions about schools in part due to beliefs about the advantages of learning from high-achieving peers, the benefits of adopting the norms established in these environments, or the value of a diverse population (Kimelberg & Billingham, 2012; Roda & Wells, 2013). These beliefs about student learning are supported in extensive empirical research showing that peer interactions and relationships are associated with a range of adolescent behaviors and longterm academic outcomes (Fujimoto, Unger, & Valente, 2012; Justice, Petscher, Schatschneider, & Mashburn, 2011; Mashburn, Justice, Downer, & Pianta, 2009; Sacerdote, 2001; Zimmer, 2003). The extent to which peers matter relative to other family and school inputs is important for educators in addressing disparities in academic achievement and designing appropriate instructional practices. Consequently, numerous studies across disciplines have focused on identifying how peer effects are distributed across schools and whether they matter more for some students than others (e.g., Hanushek, Kain, Markman, & Rivkin, 2003; Justice et al., 2011). Although evidence suggests that peers matter in many educational contexts, few studies examine how peers influence one another (see review in Harris, 2010). Part of the challenge is linking theories of peer influence to empirical evidence. Different theories may yield similar or ambiguous predictions of student outcomes, making it difficult to test the mechanisms of peer influence. For instance, peers may have a direct influence through student-to-student interaction PEER INFLUENCE IN READING 4 in learning groups, while an indirect influence may occur via specific norms within a classroom of similar peers. Studies that define peer influence broadly are less able to distinguish the two, which has implications for how to tailor classroom practice. A related challenge is how studies operationalize the concept of peer influence with empirical data. Different measures of peer effect may lead to different findings across studies that can affect policy decisions. Both challenges—theory and measurement—are important to address in order for educators to develop more informed interventions that leverage the benefits of peers (Mashburn et al., 2009). In this study, we address the theoretical and measurement challenges in the peer influence literature by using a social network analysis approach that more directly identifies who children report talking to and seeking help from in classrooms and assesses whether the average achievement of these peer groups predicts individual achievement. We also replicate and extend previous studies in several ways. Whereas many other studies have used smaller classroom samples to examine peer influence (e.g., Delay, Hanish, Martin, & Fabes, 2016; Justice et al., 2011), we surveyed over 4,200 children about their peer relationships. This replication, which to our knowledge is the largest to examine peer influence on young children, improves on the generalizability and stability of prior findings. We expanded on the literature by using improved measures of who children report interacting with and the characteristics of those peers to explore the mechanisms through which peer effects may occur. This is important because knowing that children in classrooms with high achievers on average tend to perform better than in classroom with low achievers, as previous research indicate (e.g., Hanushek et al., 2003), is less useful to teachers on a day-to-day basis than understanding the relationships between peers and how students learn from each other. This study addressed whether children reported identifying peers who are strong readers within the classroom, which allowed us to analyze one potential PEER INFLUENCE IN READING 5 mechanism of peer influence. The results have implications for classroom instruction decisions related to structured peer activities and class time for students to work together. Lastly, to better support struggling readers, this study analyzed whether interacting with higher achieving peers is associated with larger benefits for students who have lower initial reading achievement. Finding differential effects for struggling readers provides another way to reduce achievement gaps. To be clear, throughout the paper and discussion of the methods and results, our use of the terms “peer influence” and “peer effects” refers to statistical associations between the achievement of children and their peers, controlling for confounding factors. We focus on describing these associations in peer relationships and acknowledge here and in the limitation section that the design of the study was not intended to allow for causal inferences about peers. Although we have made efforts to avoid the use of causal language, the terms “peer influence” and “peer effects” in this paper refer only to statistical associations in a non-experimental study. We have retained these terms to be consistent with the research literature on this topic. Theories of Peer Influence Social Contagion Studies exploring how peers influence academic outcomes or adolescent behaviors are generally grounded in an “epidemic” or “contagion” theory in which children emulate their peers (Christakis & Fowler, 2013; Jencks & Mayer, 1990). For instance, if peers are high achievers who engage in academically oriented habits like studying and homework completion, then students who interact with these peers may adopt those habits and perform better academically (Harris, 2010). The contagion model suggests that these habits maybe absorbed without explicit modeling from peers. This process also implies differential benefits whereby more disadvantaged students gain more from peers who are stronger academically (e.g., Justice, Logan, Lin, & PEER INFLUENCE IN READING 6 Kaderavek, 2014), while peers who struggle academically may lower a student’s own scores. A concern within preschool programs that enroll mostly low-income students is that children are less exposed to peers with school readiness skills who can indirectly provide academic stimulation (Schechter & Bye, 2007). Studies on children’s language growth have found that children with lower initial language skills saw more gains when in classrooms with peers who had higher levels of language development (Masburn et al., 2009; Justice et al., 2011). Related research indicates similar contagion processes occur when examining peer behaviors like smoking (Fujimoto et al., 2012). While these studies provide support of the contagion model, it is unclear how children interact with each other beyond attending the same classroom or school. Instrumental Model In contrast to the social contagion models, psychologists have emphasized the mediating and active role of peer collaboration to enhance the cognitive development of lower-ability children. These theories argue that peers can provide expertise or directly model behaviors and skills that are “instrumental” to academic achievement (Harris, 2010; Ryan & Shim, 2012). Expert guidance (Vygotsky, 1978; Wood, Bruner, & Ross, 1976) and observational learning (Bandura, 1977, 1986; Schunk, 1998) are potentially two mechanisms through which peer effects operate. For example, in an experimental study involving pre-school children, Azmitia (1988) found that peer collaboration promoted greater learning than independent work, particularly for novice learners. Peer effects were largely mediated through experts’ guidance in supporting the learning of novices and novices’ own initiative in observing, imitating, and learning from experts (Vygotsky, 1978; Ellis & Rogoff, 1986). Importantly, experimental research indicates that peer effects involve both experts’ direct assistance in supporting novices’ learning and novices’ helpseeking behaviors in learning from experts (Bandura, 1977; Wood, 1980). Observation of peer PEER