1. printed by www.postersession.com PURPOSE & GOALS OF STUDY METHODS DISCUSSION INTRODUCTION School Context and Peer Networks in Diverse Rural Communities Bryan C. Hutchins, Matthew J. Irvin, Thomas W. Farmer, and Judith L. Meece National Research Center on Rural Education Support, University of North Carolina at Chapel Hill The purpose of this study was to report on structural characteristics of naturally occurring peer networks across 31 rural high schools who took part in a recent national survey. Specifically, this investigation explored relations between characteristics of the schools (enrollment and locale) and structural characteristics of the peer group (size, cohesion, grade level homophily, individual centrality, and group salience hierarchy), in a series of regression analyses controlling for school socioeconomic differences. On average, rural students affiliated with 6.93 (SD = 3.53) peers. In general, students in large rural schools (> 200) were members of larger peer groups. Group cohesion was highest in rural schools that were closer to urban areas (r =.77) compared to small rural remote (r =.75) and large rural remote schools (r =.71). Students in large schools were less likely to affiliate with peers across grade level than students in small schools regardless of locale. Small rural remote schools had the highest proportion of students with high status (20.7%) compared to all other schools. Large rural remote schools had the lowest proportion of students with high status (8.8%). Finally, a greater proportion of students in large rural remote schools (70.8%) were members of groups with high salience hierarchy (group members were of different prominence levels) compared to all other schools. Peers play a central role in the lives of adolescents. The quality and characteristics of adolescents’ peer relations have been linked to a number of social, behavioral, and academic outcomes. For most adolescents, school is an important context for peer relations (Hamm & Zhang, 2010). Schools provide an opportunity for students to form peer groups based on a number of processes including familiarity, similarity, and propinquity (Gifford-Smith & Brownell, 2003). The role of schooling experiences is reflected in the fact that most studies of peer relations take place in schools where students are typically asked to restrict their nominations to peers at school. Although a number of studies have examined structural characteristics of peer groups within schools (e.g., Urberg, Degirmencioglu, Tolson, & Halliday-Scher, 1995) few studies acknowledge the fact that peer relations may be influenced by characteristics of the schools in which these investigations take place (Hamm & Zhang, 2010). Relations between school characteristics and peer groups may be particularly salient for rural youth. For example, due to limited resources, many rural school districts have turned to large consolidated schools. Rural youth must often travel greater distances to attend school and may have limited opportunities to meet peers outside of school. In larger consolidated rural schools, students come into contact with a large number of new and unfamiliar peers from different communities whereas students in smaller community schools come into contact with fewer and possibly more familiar peers. Such unique schooling experiences may impact peer relational processes in rural schools. ABSTRACT Results of this study suggest that structural characteristics of peer groups were related to school characteristics. Because this current analysis was preliminary, only broad school indicators were considered (i.e., enrollment and locale). However, there were a number of interesting findings related to the size of the school and distance from a metropolitan area. One of the more interesting set of findings in this analysis were on the differences between large and small rural remote schools. For example, groups in large rural remote schools tended to be less cohesive than groups in small rural remote schools. Also, twice as many students in small rural remote schools had high status compared to students in large rural remote schools. Finally, students in small rural remote schools tended to be members of groups with less salience hierarchy than students in large rural remote schools. These findings have clear implications for future peer relational and rural education investigations. However, these findings should be interpreted in light of three important limitations. First, although the regression models were statistically significant school characteristics accounted for only a small portion of the variance in peer group characteristics. Second, only school socioeconomic differences were controlled in this analysis. More sophisticated analyses should be undertaken to control for additional school differences and to explore other possible school level influences on peer relations. Third, results of preliminary HLM analysis revealed potential nesting effects associated with this study. HLM may be the more appropriate analytic approach for future analyses. This study is part of a broader national investigation to examine adolescents’ preparation for the transition to adulthood in rural high schools across the United States. Data were collected during the 2007-08 academic year. Youth in grades 9 – 12 were recruited from 73 randomly selected rural and small town schools. Trained research personnel traveled to schools to group administer a student survey to all consented participants. A subsection of this survey asked students to provide information about school social networks. To be included in the study, 50% of students participating within a school had to complete this portion of the survey. Of the 68 rural schools participating in the larger study, 31 schools (46%) met the participation criteria and were included in analysis. Characteristics of these participating schools are presented in Table 1. Participants This study included 3,391 students (52.4% girls, 47.6% boys). The largest self-identified ethnic and racial groups included Whites (73.4%), Hispanics or Latinos (8.3%), African Americans (4.6%), and Native Americans (2.8%). In addition, 2.6% reported other and 8.3% of students self-identified as multi-racial. Measures Social Cognitive Map (SCM) Procedure. Participants were asked to nominate (from free recall) groups of students who “hang around together a lot.” Students could nominate any peer who attended the same school. This information was used to create a composite social “map” by aggregating individual perceptions of the social network (Cairns, Gariepy, Kindermann & Leung, 1996). This procedure was used to generate information about the structural characteristics of students’ peer groups (see Xie & Shi, 2009 for details). Dependent Variables Size. Group size was measured by the total number of peers within a student’s peer group. Cohesion. Group cohesion was defined as the level of overall similarity among members of a student’s peer group in their relationship profiles. A correlation matrix produced by the SCM procedure provided the degree of similarity between any two individuals’ profiles of co-occurrence in the same groups. For each group the median correlation between any two members was used as an indicator of group cohesion. Grade Level Homophily. Grade level homophily was assessed by calculating a variance score based on grade level of peers within a student’s peer group. Individual Centrality. Centrality scores were calculated at the student and group level based on number of peer nominations. Students were high on centrality if they were a prominent member of a prominent group, medium if they were a secondary member in a prominent group or a prominent member in secondary group, and low if they were a peripheral member of any group, or a member of a peripheral group. Salience Hierarchy. The SCM procedure assigned each member of a group with one of three levels of prominence within group based on number of nominations: peripheral, secondary, and nuclear. Groups with all members of the same prominence level were classified as low on salience hierarchy. Medium groups were comprised of those with two levels of prominence and high groups were comprised of members with all three levels of prominence. Each student received a salience score based on his or her group. The purpose of this current study is to provide preliminary results from analyses examining relations between school characteristics and peer group structural characteristics across 31 rural high schools. The rural high schools in this investigation differ in a number of ways (see Table 1). However, because of the preliminary nature of this study only two aspects of rural schools were considered: school enrollment and geographic locale. Building on prior research of peer networks (e.g., Urberg et al., 1995), the specific questions addressed in this study included the following: 1. What are the general characteristics of peer networks in a national sample of rural high schools? 2. What are the relations between school enrollment and geographic locale (controlling for school socioeconomic differences) on the following structural aspects of peer networks: group size, cohesion, grade level homophily, individual group member centrality, and salience hierarchy of the group? This poster is based on research conducted by the National Research Center on Rural Education Support (NRCRES) at the University of North Carolina. This work was supported by grant #R305A04056 from the Institute of Education Sciences. The authors are responsible for the contents of this poster. No statement in this poster should be construed as an official position of the granting agency. Descriptives. On average, students affiliated with 6.93 peers (SD = 3.53). Average group cohesion was r =.76 (SD =.13). Overall, 45.8% of students were in groups that were grade level homogenous. The majority of students (51.3%) had average status within the school, 33.9% had low status and 14.8% had high status. Most students (59.0%) were members of peer groups that had high salience hierarchy, 35.0% had medium salience hierarchy, and 6.0% were in groups with low salience hierarchy. Group Size. Students in large rural remote and large rural fringe/distant schools were more likely to be members of larger groups (7.26 and 7.53, respectively) than students in small rural remote and small rural fringe/distant schools (6.73 and 5.99, respectively). Additionally, the difference between small rural remote and small rural fringe/distant schools was statistically significant, suggesting that students in small rural remote schools tended to have larger groups than students in small rural fringe/distant schools. Group Cohesion. Students in both large and small rural fringe/distant schools were more likely to be members of groups that were more cohesive (.77 and.77, respectively) than students in small and large rural remote schools (.75 and.71, respectively). Additionally, the difference between small rural remote and large rural remote schools was statistically significant, suggesting that students in large rural remote schools tended to have less group cohesion than students in small rural remote schools. Grade Level Homophily. Students in large rural remote and large rural fringe/distant schools were more likely to be members of groups with higher grade level homophily as indicated by lower variance scores (.28 and.30, respectively) than students in small rural remote and small rural fringe/distant schools (.46 and.43, respectively). Differences based on locale within large and small schools were not significant, suggesting that students in large schools were less likely to affiliate with peers across grade level than students in small schools regardless of locale. Individual Status. Small rural remote schools had the highest percentage of students with high status (20.7%), whereas large rural remote schools tended to have the lowest (8.8%). In addition, large and small rural fringe/distant schools both had slightly lower percentages of students with high status (15.5% and 16.5%, respectively) than students in rural remote schools. Salience Hierarchy. Students in large rural remote schools (70.8%) were more likely to be members of groups with high salience hierarchy compared to all other schools (small rural remote = 56.8%, large rural fringe/distant = 55.8%, and small rural fringe/distant = 50.0%). The difference between small rural remote and large rural fringe/distant schools was not statistically significant. Analytic Plan Schools were classified into groups based on school enrollment and school locale. School enrollment was dichotomized into large schools (enrollment > 200) and small schools (enrollment < 200). School locale was dichotomized into rural remote (NCES locale code 43) and rural fringe/distant schools (locale codes 41 and 42). There were three continuous dependent variables (group size, group cohesion, grade level homophily) and two categorical dependent variables (individual centrality, group salience hierarchy). Continuous dependent variables were analyzed using hierarchical linear (OLS) regression. Categorical variables were analyzed using hierarchical logistic regression. To control for school socioeconomic differences, percentage of students within school receiving free/reduced lunch was included in all models at step 1. Students in small rural remote schools served as the reference group for all regression models. RESULTS Table 1 School and Community Characteristics of Study Schools Rural RemoteRural Fringe/Distant Small (n = 16)Large (n = 3)Small (n = 6)Large (n = 6) School and Community CharacteristicMeanRangeMeanRangeMeanRangeMeanRange Enrollment 82(32 - 187)251(219 - 295)119(82 - 168)274(207 - 374) Free/Reduced Lunch (%) 49(21 - 85)42(11 - 65)57(22 - 81)50(34 - 74) Median income of school community 29,349(16,996 - 43,843)39,998(30,195 - 56,000)33,812(23,600 - 40,597)26,644(22,200 - 30,212) Poverty rate of school community (%) 15.1(9.7 - 26.9)13.2(10.0 - 18.3)15.7(8.8 - 20.7)18.0(11.7 - 30.2) Population of school community 785(269 - 2,275)1,103(1003 - 1153)1,946(394 - 5514)1,749(416 - 3556) Population density of school county (%) 12.4(0.7 - 37.6)23.7(9.5 - 39.8)44.4(13.9 - 95.0)29.1(20.6 - 42.3) Closest town with a population above 50,000 (miles) 109(36 - 232)81(42 - 109)42(16 - 78)47(17 - 88) Closest college/university (miles) 68(27 - 187)56(21 - 110)32(14 - 53)41(27 - 72) Colleges/universities within 100 miles (#) 3.4(0 - 8)4.7(0 - 9)6.2(3 - 11)5.3(2 - 8) Note. Small schools defined as having total enrollment of less than 200 students. Rural remote schools defined as NCES locale code 43. All other rural schools defined as locale codes 41 (Rural Fringe) and 42 (Rural Distant). Table 2 Hierarchical Linear Regression Analysis Predicting Group Size, Group Cohesion, and Grade Level Homophily From School Size and Rural Locale Group SizeGroup CohesionGrade Level Homophily School CharacteristicsBSE BβB βB β Step 1 School Poverty-.864*.389-.042 5.563**1.435.078.283**.064.095 Step 2 Small Remote ….(reference) Small Fringe/Distant-.710**.214-.071 1.843*.776.053-.060.036-.040 Large Remote.520*.203.055-3.734**.732-.113-.157**.032-.116 Large Fringe/Distant.805**.162.109 1.789**.622.065-.154**.027-.138 R2R2.023**.029**.027** Note. * p <.05 **p <.01 Table 3 Hierarchical Logistic Regression Predicting Individual Centrality and Group Salience Hierarchy From School Size and Rural Locale Individual CentralityGroup Salience Hierarchy Low/Medium vs High School CharacteristicsB (SE)Odds-RatioB (SE)Odds-Ratio Step 1 School Poverty.928** (.311)2.528 -.717** (.222)0.488 Step 2 Small Remote (Reference) Small Fringe/Distant-.346* (.161).707 -.243* (.123).784 Large Remote -.962** (.186).382.597** (.124)1.817 Large Fringe/Distant -.356** (.121).701-.041 (.093).960 Model Chi-square37.927** 46.309** -2logL246.134300.482 Pseudo R 2 0.023 Note. Low/Medium served as the reference group. * p <.05 **p <.01