Child Development, July/August 2007, Volume 78, Number 4, Pages 1186 – 1203

Effects of Naturally Existing Peer Groups on Changes in

Academic Engagement in a Cohort of Sixth Graders

Thomas A. KindermannPortland State University

This study examined the effects of peer groups on changes in academic engagement in 11- to 13-year-old children.From the entire cohort of 366 sixth graders in a town, 87% participated at the beginning and end of the school year.Peer groups were assessed using socio-cognitive mapping; as an indicator of motivation, teachers reported onstudents’ classroom engagement. Peer groups were homogeneous in terms of engagement, and despiteconsiderable member turnover across time, their motivational composition remained fairly intact. Peer groupengagement levels in the fall predicted changes in children’s motivation across time. Although the magnitude ofeffects was relatively small, evidence for group influences persisted when controlling for peer selection and theinfluence of teacher and parent involvement.

Recent reviews of the concept of school engagementhave revealed its potential as a target in research andinterventions aimed at improving children’s academicachievement and resilience and preventing schooldrop-out and delinquency (Fredricks, Blumenfeld,& Paris, 2004; Jimerson, Campos, & Greif, 2003).A core feature of many models are the behavioralmanifestations of engagement, sometimes called par-ticipation or academic involvement, that refer tostudent’s energized, enthusiastic, emotionally posi-tive, cognitively focused interactions with academicactivities. Such involvement is the wellspring of high-quality learning and, over time, is hypothesized tolead to the kind of commitment to academic goals andidentification with school (Finn, 1989) that allowschildren to maintain participation in the face ofdifficulties and setbacks, and eventually to takeresponsibility for their own learning.

Most researchers agree that supportive relation-ships with adults and peers are critical to children’sengagement in school. However, although decades of

research have shown that warm and supportiverelationships with parents and teachers benefit stu-dents’ academic motivation, their self-perceptions, en-gagement, and performance (e.g., Englund, Luckner,Whaley,&Egeland, 2004;Grolnick&Slowiaczek, 1994;Noack, 2004; Ratelle, Guay, Larose, & Sen _ecal, 2004;Skinner, Zimmer-Gembeck, & Connell, 1998; for re-views, see Fredricks et al., 2004; Wigfield, Eccles,Schiefele, Roeser, & Davis-Kean, 2006), only recentlyhas the role of peer affiliations in students’ engage-ment been examined empirically.

Studies frommultiple traditions show that variouskinds of peer affiliations are associated with chil-dren’s motivation, their behavior in school, and theireventual academic success. For example, friendshipshave been shown to be positively related to academicmotivation and performance (e.g., Altermatt &Pomerantz, 2003; Berndt, Hawkins, & Jiao, 1999;Wentzel, McNamara-Barry, & Caldwell, 2004) andnegatively related to behavior problems in school(Ennett & Bauman, 1994; Poulin, Dishion, & Haas,1999). Sociometric categories and acceptance scoresare also correlated with school motivation and perfor-mance (e.g., Bukowski & Cillessen, 1998; Chen, Chang,& He, 2003; Guay, Boivin, & Hodges, 1999), as arefriendship groups, social crowds, and groups of childrenwho ‘‘hang out’’ together (e.g., Brown, 1999; Farmer& Rodkin, 1996; Kiesner, Poulin, & Nicotra, 2003;Kurdek & Sinclair, 2000; Wentzel & Caldwell, 1997; fora review, see Rubin, Bukowski, & Parker, 2006).

However, serious questions remain about how cor-relations between children’s academic performance

I am indebted to the late Robert B. Cairns for introducing me tosocio-cognitive mapping (SCM) and to Ellen A. Skinner for herinsightful critiques ofmy papers. I want to thank JaanValsiner, JeanLouis Gariepy, and James P. Connell for conceptual discussions; theschool officials, parents, and students of the Brockport, New Yorkschool district for their support; Peter Usinger and Marcus Danielsfor programming; Michael Belmont for organizing data collections;Tanya McCollam-Fantaski for her work on the SCM map; and 30undergraduate and graduate students for data collections andformatting. The projects were supported by Faculty DevelopmentGrants from Portland State University and by Academic ResearchEnhancement Awards from the National Institute of Child Healthand Human Development (1R15HD31687-01; 1R15 HD37848-01).

Correspondence concerning this article should be addressed toThomas Kindermann, Department of Psychology, P.O. Box 751,Portland State University, Portland, OR 97207-0751. Electronic mailmay be sent to kindermannt@pdx.edu.

# 2007 by the Society for Research in Child Development, Inc.All rights reserved. 0009-3920/2007/7804-0010

and their relationships with peers should be inter-preted. Although studies consistently show that children with high-quality peer relationships tend to dobetter in school, is this because peers support chil-dren’s school performance, or is it because childrenwho do better at school tend to affiliate with higherfunctioning peers? Or, are quality of peer relationsand school performance not causally related at all,because both are caused by a third variable, such ashigh-quality parenting or teaching? The key issue ishow to design studies so that processes of peerinfluence can be weighed against peer selection andthe role of external factors, thus minimizing thepotential that alternative explanations are responsiblefor findings that seem to suggest peer influences.

Goals of the Study

The goal of the current study was to examine howresearch on naturally existing peer groups can add tothe larger literature on peer influences on children’sacademic development. Although a child’s world ofpeers is complex, including friendships of variouslevels of closeness as well as sociometric status,popularity, and peer rejection, this study focused onnatural groups. These are the peers with whomindividual children interact most frequently andspend the most time at school. Along with closenessof relationships, frequency of interaction is likely todistinguish the peers who will contribute mostheavily to a given child’s development. The methodused to identify peer groups, socio-cognitive map-ping (SCM; Cairns, Perrin, & Cairns, 1985), has theadvantage that it allows for objective identification ofthe members of a child’s group and for assessment oftheir characteristics independently from the informa-tion provided by the individual.

The study examined whether the engagement ofa child’s peer groupmembers at the start of the schoolyear could predict the development of that child’sown engagement versusdisaffection across the schoolyear. Two previous small-scale studies (Kindermann,1993; Kindermann, McCollam, & Gibson, 1996) haveshown that children who are initially ‘‘rich’’ in termsof their own and their peer groups’ motivationalcharacteristics tend to become ‘‘richer’’ over time,whereas children who are initially ‘‘poor’’ showdeclines. Guided by an interactional perspective(Baltes, 1996; Bronfenbrenner & Morris, 1998), thestudieswere based on the assumption that peers exerttheir influence in social interactions. One likelymech-anism of influence, which has been documented inin vivo observations in the classroom, is peer rein-forcement. Changes in children’s own engagement

across time can be predicted from the levels ofcontingent support for on-task classroom behaviorprovided by their peer group members (Sage &Kindermann, 1999).

The current study builds on previous research inthree ways. First, the study included an entire gradecohort of children in a small town. A limitation ofprevious studies has been a focus on selected class-rooms,whichplaces artificial boundaries on the rangeof members of students’ peer groups. By preadoles-cence and adolescence, peer groups are typically notconfined to specific classrooms. Hence, by includingall the students in sixth grade in a school system, thestudy incorporates a more ecologically valid andappropriate definition of the natural boundaries ofstudents’ peer groups. Second, the study directlyaddressed design problems that are created for social-ization researchers by the fact that children select themembers of their groups. Self-selection of groupmembers leads to problems not found in studies ofcontexts that are assigned to children (i.e., childrencannot select parents or teachers). Self-selectionmeansthat children can belong to more than one group, canleave their group, and, most important, they can selecttheir groups in a way that creates initial similaritiesamong group members, an issue referred to as ‘‘assor-tativeness’’ (Kindermann, 2003). Third, peer influenceswere examined in relation to competing influencesfrom teachers and parents. The study used a longitu-dinal design anda series of controls that allowanalysesto separate processes of peer influences fromprocessesof peer selection as well as from simultaneous pro-cesses of influence from parents and teachers.

Peer Relations and Classroom Engagement

The focus of the current study was whetherchanges in children’s own engagement across timecould be predicted from the characteristics of theirearlier peer group affiliates. The target outcome wasengagement versus disaffection in the classroom(Connell, 1990; Wellborn, 1991). At the core of thisconstruct are markers of engaged behaviors, includ-ing effort exertion, trying hard, and persistence, aswell as indicators of mental effort, such as attentionand concentration. This aspect of engagement hasalso been referred to as academic behavior, on-taskbehavior, or class participation (Fredricks et al., 2004).The conceptualization also includes engaged emo-tions, such as enthusiasm, interest, and enjoyment.The opposite of engagement is disaffection, which in-cludes the core behaviors of disengagement, namely,passivity, lack of initiation, lack of effort, and givingup. In addition, it includes mental withdrawal and

Peer Group Influence in School 1187

ritualistic participation, such as lack of attention,pretending to pay attention, and going through themotions. Disaffected emotions include those thatreflect enervated, alienated, or pressured participa-tion (e.g., sadness, boredom, anger, anxiety).

Engagement was the key construct in this studybecause it is a central construct in most currenttheories ofmotivation (Skinner, Kindermann, Connell,& Wellborn, 2007) and because, as an observablemanifestation of motivation, it is highly salient toteachers and peers (Skinner & Belmont, 1993).Research has shown that children’s active, enthusias-tic, and effortful engagement in learning activitiespredicts their achievement in and completion ofschool (e.g., Connell, Halpern-Felsher, Clifford,Crichlow, & Usinger, 1995; Connell, Spencer, & Aber,1994; Skinner, Wellborn, & Connell, 1990; Skinneret al., 1998; for a review, see Fredricks et al., 2004).

Challenges in the Study of Naturally OccurringPeer Group Influences

The study of children’s peer groups presents thornymethodological problems, chief among them, howmembers should be identified. Networks consist ofchildrenwho tend to hang out together and share timeand activities on a regular basis (Cairns et al., 1985).Such groups are typically self-organized, highly fluid,and formed for a variety of reasons. They are oftenpoorly defined, and obtaining accurate information isdifficult. In particular, doubts have been raised aboutthe accuracy of children’s self-reports of affiliationsbecause they tend to exaggerate their associationswithpopular peers (Cairns & Cairns, 1994; Leung, 1996).

SCM employs children as expert observers of socialinteractions because they have access to everydayexchanges in a way that cannot easily be matched byother observers. Multiple children in a classroom areasked to report about classmates whom they know tohang around frequently with one another, and com-posite maps are formed of the groups on whichreporters agree. Similar toMoreno’s (1934) sociograms,these maps depict the connections of children whoshare affiliations with one another (see Figure 1 for anexample). One strength of the approach is that theidentification of groups is based onmultiple observerswhose level of agreement can be determined; consen-sus maps have been shown to be consistent withindependent observations (Gest, Farmer, Cairns, &Xie, 2003). A second advantage is that more of a child’saffiliates are included than when dyadic friendshipsare considered. A third advantage is that, comparedwith most assessments of peer relationships, the accu-racy of SCM is not as dependent on participation rates.

Thus, when assessing reciprocal friends, each childwho does not participate will also be missing asa (potential) friend of the remaining children. ForSCM, not every student in a classroom needs toparticipate. If consensus is high and the sample ofreporters is fairly representative for a setting, reportsfrom slightly more than half of its members aresufficient toyield reliablemaps (Cairns&Cairns, 1994).

Individuals and their groups. Because natural groupsare (largely) self-selected, a child can be a member ofmany subgroups at the same time. In Figure 1, studentKER (lower right) has 8 members in her peer network,and COD has 14; manymembers are shared but manyothers are not. It becomes difficult to define groupsobjectively in a way that children are assigned to onlyone group. An alternative is to define a group withrespect to individuals, so that socialization processesare assumed to take place reciprocally between eachindividual and all of the others who are his or heraffiliates. This has one specific advantage: Instead ofassuming that socialization contexts are the same foreach member of a group, each member is seen ashaving his or her own unique network (all childrenwith whom he or she is affiliated). Thus, if a girl is ina groupwith two boys, she interactswith people of theopposite sex,whereas each boyhas amixed-sex group.This strategy makes it possible to examine interindi-vidual differences in socialization contexts, evenamong members of the same group.

Assessing group characteristics. A second challengeto the study of peer group influences is capturinga group’s influential features. Children’s self-reportsabout their peers tend to be closely matched to theirreports about their own characteristics, but using suchcorrelations to infer peer influence is ‘‘unsatisfactory’’(Jaccard, Blanton, & Dodge, 2005, p. 136) becausea child’s own characteristics likely shape his or herperception of affiliates. If instead groups are definedindependently, their psychological characteristics canbe assessed independently as well. Peer character-istics can be described by the peers themselves or byother reporters (such as teachers), and these can beaggregated to form a group profile. To form compos-ites, researchers have used scores averaged across themembers of a child’s group (Kindermann, 1996;Kurdek & Sinclair, 2000; Ryan, 2001). When groupsare fairly homogeneous, it is reasonable to assumethat the average across a child’s affiliates captures thecentral properties of his or her group.

Capturing peer influences. A third challenge ishow peer influences should be conceptualized andempirically evaluated. Such influences are usuallyconceived of as socialization processes, and correla-tions between a child and his or her peer group

1188 Kindermann

members are sometimes considered evidence of theirpresence. Traditionally, peer selection is seen asa threat to the validity of peer socialization studies(e.g., Kandel, 1978). Peer groups are characterized byassortativeness (Kindermann, 2003); they are notformed at random and children tend to be similar tothe peers with whom they chose to affiliate. Hence,correlations are as likely to reflect processes of selec-tion as they are to reflect processes of socialization.

Controls for selection. Because predictions are cor-relational, alternative explanations need to be elimi-nated; it is possible that processes other than peerinfluences could produce patterns of change in chil-dren that mimic those of socialization influences.There are several possible alternative explanations.First, in groups in which members are similar to oneanother, the members may follow similar develop-mental pathways because of their similarity. Oneempirical solution to this problem is to test forsocialization effects by examining whether the char-acteristics of a target child’s peer group at one point in

time predict changes in that child’s characteristicsacross time over and above his or her initial similaritywith the group.

Second, although longitudinal designs yield im-provements over concurrent correlations, results canstill be affected by peer selection; selection preferen-ces can exist for a variety of other characteristics thatare associated with differential developmentalchange (e.g., achievement, IQ, gender; Hamm, 2000).For example, girls tend to formgroupswith other girlsduring much of their school years and to be moremotivated and to achieve higher grades (e.g., Eccles,Wigfield, & Schiefele, 1998). Over time, correlationpatterns that look like positive influences from high-functioning groups may partly be explained by thefact that their affiliates were also girls. Similarly,children may have preferences for specific kinds ofgroups (e.g., in termsof size, homogeneity, or stability).Whenever positive changes in children are related tothe high functioning of their peer groups, this may bean outcome of interactions and group influence, but it

Figure 1. Subset of the composite socio-cognitive map of sixth graders’ social networks in a small town (the entire map can be viewed atwww.psy.pdx.edu/;thomas/Research). Circles denote girls and squares denote boys; letters inside the shapes represent individuals’names. The terms in quotation marks denote the names that students gave to the groups.

Peer Group Influence in School 1189

can also be an outcome of processes by which well-adjusted students become members of larger, morehomogeneous, or more stable groups that consist ofsimilarly well-adjusted members.

Third, assortativeness can also lead children to joina group whose members are similar with regard toinfluences they experience from outside of theirgroup. Teacher influences are likely the most power-ful determinants of children’s classroom behavior,and they seem to work in a way that students who dowell at one point in time tend to improve (or remainstable) across time (Skinner & Belmont, 1993). Whenteachers are effective in promoting ‘‘good’’ students’development, and such students form groups withsimilar other students, their own change over timecan be an outcome of teachers’ involvement over andabove group influences. The same can be true withregard to parent influences. Parental support andinvolvement have also been implicated as a factor indetermining children’s motivation and success inschool, and members of a peer group can experiencesimilar levels of stimulation and parent involvementat home (e.g., Fletcher, Darling, Steinberg, & Dorn-busch, 1995). Thus, children’s home environmentsmay be responsible for their change across time, andpeer influencesmaynot addmuch to this explanation.When group influences are examined, it is importantto make sure that predictions of children’s changeremain robust when potential alternative influencesfrom other social partners are controlled.

In sum, the current study, examining an entirecohort of students in a small town, focused onwhether the engagement profile of a child’s peergroup, assessed independently and reliably at thebeginning of the school year, would make a uniquecontribution to changes in that child’s engagementacross the school year over and above the effects ofselection preferences and the effects of involvementfrom parents and teachers. The general expectationwas that childrenwhoweremotivationally rich at thebeginning of the school year would selectively asso-ciate with peers who were also relatively high inmotivation (and that their parents and teacherswouldalso bemore supportive), whereas childrenwhoweremotivationally poor in the fall of sixth grade wouldassociatewith peerswhowere less engaged (andhaveparents and teachers who were less involved in thechildren’s school work). At the same time, whencontrolling for the effects of parents and teachers,peer selection, and children’s level of academic func-tioning, it was expected that the engagement profilesof children’s peer groups would predict changes inchildren’s own engagement and disaffection over the1st year of middle school, such that initially rich

children, through their association with engagedpeers, would become even richer, whereas motiva-tionally poor children would become even moredisaffected. By including controls for selection pref-erences and for simultaneous influences from othersocial partners, the study used a design that showspromise for capturing the complexity of peer groupswhile overcoming some of the problems that areassociated with the study of their influences.

Method

As part of a larger longitudinal project (Skinner et al.,1998), the study focused on an entire cohort of sixthgraders in a rural/suburban town in a northeasternstate, during the 1st year when children started inmiddle school. The town had about 15,000 inhab-itants; 90% were of European American descent, and87% of the adults had a high school or higher degree.The school was the only public school in town for thisage group; the distance to the next town was about16 miles. A small number of students who attendedprivate school or commuted to school outside of townwere not included in the study.

Setting and Sample

Out of the total of 366 sixth graders in the town(48% girls), 340 participated (93%) who consentedand had parental permission to participate. Informa-tion on ethnic backgroundwas not obtained. Studentswere grouped into homeroom classrooms; theschool’s intent was to have one teacher assigned toeach class who was primarily responsible for thestudents and saw them every day. All 13 teachersparticipated and all stated that they were very famil-iar with their students.

Design and Measures

Student questionnaires were administered at twotime points during regular classroom hours. The firstmeasurement point was within the first 3 monthsof the school year; the second was within 3 monthsof its end. Teachers completed questionnaires onstudents’ school engagement within a 1-month win-dow around both assessments.

Engagement versus disaffection. Academic engage-ment was assessed using a 14-item scale that tappedteachers’ perceptions of each student (Wellborn,1991). The measure consists of two components:behavioral and emotional engagement (e.g., ‘‘Thisstudent works as hard as he/she can’’; ‘‘In my class,this student appears happy’’). Previous studies have

1190 Kindermann

shown that the components are moderately intercor-related (r 5 .31, n 5 144) and that they form aninternally consistent indicator of engagement (a5 .95,n 5 185; Wellborn, 1991). Over an 8-month period,engagement ratings were highly stable (r 5 .73,p , .001, n 5 144) and moderately correlated withgrades and achievement scores (ranging from .40 inmathematics achievement to .58 in reading; Skinner&Belmont, 1993; Skinner et al., 1990).

At the beginning of sixth grade, teachers providedinformation on 318 students (93% of students whohad permission to participate; 87% of the population).Seven of the 340 participants were missed becausethey changedhomerooms, 8 had just recently enrolledand teachers did not know them well, and 7 had notyet arrived at school. At the end of the school year,reports on 322 students were obtained; 18 of the fallparticipants had left, but the 22 students who hadbeen missed in the fall were included. Three hundredstudents had teacher-reports at both time points.

Academic achievement. Students’mathematics gradeswere obtained at the end of fifth grade and at the end ofsixth grade. Letter grades were converted to numbersand both grades were averaged. Mathematics gradeswere chosen as indicators of achievement because theywere assumed to be close approximations of measuresof ability and, comparedwith other grades, less directlyaffected by students’ levels of engagement in theclassroom.

Teacher involvement. At the beginning of the schoolyear, students also reported on the extent to whichthey experienced differential levels of teacherinvolvement. The measure developed by Skinnerand Belmont (1993), consists of eight items tappingperceptions of the teacher availability, caring,warmth, and affection (e.g., ‘‘My teacher knows mewell’’; ‘‘My teacher doesn’t seem to enjoy having mein class’’), and has sufficient measurement character-istics (internal consistencies were between .79 and .85in Grades 3 through 7; stability was .55 over a schoolyear). In a previous study, the ratings were moder-ately correlated with teacher ratings of students’engagement (correlations were between .24 and .33in Grades 3 through 7) as well as achievement scores(correlations between .21 to .33, all ps , .01, n 5 401;Skinner et al., 1998).

Parent involvement. At the beginning of sixthgrade, students also reported on their perceptions oftheir parents’ involvement. The measure consists of16 items (an 8-item subscale of warmth, e.g., ‘‘Myparents understand me very well’’; and an 8-itemsubscale of rejection, e.g., ‘‘Sometimes I wonderwhether my parents like me’’). In a previous study,the subscales were shown to have high internal

consistencies (a 5 .88 and .83) and to be highlynegatively intercorrelated (r 5 .67, p , .001,n 5 1,247), and parent involvement was moderatelycorrelated with students’ self-reports of theiracademic competence (warmth: r 5 .28; rejection:r5 – .30, all ps, .01; Skinner, Johnson,&Snyder, 2005).

Peer groups. Students’ networks were assessed viaSCM (Cairns et al., 1985). In questionnaires, childrenwere asked to list groups of students in their gradewhom they knew to frequently ‘‘hang out’’ with eachother. Students were asked to list as many groups andmembers as they knew (in school and outside), toinclude dyads, to not forget to include themselves,and to include the same children as members ofdifferent groups if appropriate. The forms providedspaces for up to 20 groups and 20 members (nostudent exhausted the space). A typical report would,for example, denote Children A, B, and C to form onegroup, and D and E to form another. For purelydescriptive purposes, children were asked to giveeach group a name that characterized ‘‘what the groupwas about.’’ Discussions of the method are availableelsewhere (cf. Cairns, Gariepy, & Kindermann, 1990;Kindermann, 1996). The method relies on free recalland focuses on public knowledge of affiliations. Net-works are assumed to exist among students on whomobservers agree they are frequently affiliating.

At the beginning of sixth grade, 280 students (76%of the population; 56% were girls) provided informa-tion about peer networks in their grade; 60 children(18% of participants; almost evenly distributed acrosshomerooms and gender) did not provide such infor-mation (5 children had only illegible entries, 15indicated they did not know anything about groups,and 33 left this part of the questionnaire unanswered;7 had not yet arrived for the fall term). At the end ofsixth grade, network information was assessed toexamine stability; 219 students (60% of the cohort)provided peer group information.

Network identification. At the beginning of the year,the 280 informants issued 3,047 group member nom-inations for a total of 694 groups, each with between 2and 15 members. On average, a child nominated 2.7groups with about 5 members. At the end of theschool year, the 219 informants issued 3,590 nomina-tions for 664 groups (averaging 3 groups with 5.4members).

To identify group affiliations, the nominationswere arranged in a co-occurrence matrix denotingthe frequencies withwhich each child was nominatedto belong to the same group as any other child, acrossthe entire grade. A portion of the matrix is presentedin Table 1. Binomial z tests examined whether chil-dren were more likely to be nominated as being in

Peer Group Influence in School 1191

a group with any other candidate than could beexpected by chance. For example, in Table 1, acrossall 36 reports in which student KERwas nominated tohave a group, student RYB was noted 28 times asa member of the same group (78%). Overall, RYB wasnominated to be amember of 32 of the 694 groups thatwere generated (5%). Thus, the conditional probabil-ity of finding student RYB as a member of KER’snetwork, given that KER had a group (28/36 5 .78),was compared with the unconditional probabilitywith which RYB was found in any group (32/694 5 .05). The significant z score of 21.47 indicatesthat RYB was a member of KER’s group. Because ofthe many cases with low expected cell frequencies,Fisher’s exact test was used in addition (Sterling’sapproximation; von Eye, 1990), and only connectionsthat were significant (p , .01) using both strategieswere accepted. Significant connections that werebased on single conominations were not accepted; inalmost all cases, thesewere children’s self-nominations.

The resulting composite social map consisted of allsignificant network connections. A subset of the mapis presented as Figure 1 (individual placements arearbitrary). As a criterion for accurateness, kappaindices (Gest et al., 2003) indicated that individuals’reports were highly consistent with the compositemap (average kappa was .88). Only errors of commis-sion were considered; errors of omission wereexcluded because it is unrealistic to expect that allinformants would know the same amount about all

networks (e.g., girls may know less about boys’groups). It should be noted that the approach isindividual oriented: The method identifies children’sconnections with one another, not distinct groups.This has two advantages: First, multiple group mem-berships are retained so that a child can have con-nections that are not shared with the other membersof his or her group. Second, a child’s group context iscaptured as specific for that child so that interindivid-ual differences in context influences can be examined.

Network characteristics. The number of members ineach student’s group was used to indicate networksize. The number of students whom a student kept asgroupmembers across time was taken as an indicatorof network stability. Across each child’s group mem-bers, the percentage of students was computed whowere students of the same gender. As markers of theengagement characteristics of children’s groups, com-posite group profiles were formed; scores were cal-culated by averaging the teacher-rated engagementscores across the members of each child’s group. Forexample, the average engagement score of studentsRYB, DAL, COD, SUO, PAG, ROW, JEN, and JHO inFigure 1was taken as indicating the engagement levelof KER’s peer network. Finally, as a measure ofperson-to-group similarity, the (absolute) differencewas taken between each individual child and thecomposite score of his or her group. Group nameswere not analyzed systematically, but name charac-teristics on which there was high consensus were

Table 1

Co-Occurrence Matrix Among (Selected) Girls in a Cohort of Sixth Graders

KER RYB DAL COD SUO ROM STQ CHR KAA KAW ELT JEP LIP

Total

nominations

KER — 28 23 12 10 3 3 0 0 0 0 0 0 36

RYB 28 — 20 11 12 3 4 0 0 0 0 0 0 32

DAL 23 20 — 10 9 4 2 0 0 0 0 0 0 28

COD 12 11 10 — 19 8 13 0 0 0 0 0 0 29

SUO 10 12 9 19 — 9 10 0 0 0 0 0 0 29

ROM 3 3 4 8 9 — 4 0 0 0 0 0 0 11

STQ 3 4 2 13 10 4 — 0 0 0 0 0 0 17

CHR 0 0 0 0 0 0 0 — 10 10 9 10 0 14

KAA 0 0 0 0 0 0 0 10 — 13 13 12 0 16

KAW 0 0 0 0 0 0 0 10 13 — 13 10 0 17

ELT 0 0 0 0 0 0 0 9 13 13 — 10 0 18

JEP 0 0 0 0 0 0 0 10 12 10 10 — 0 13

LIP 0 0 0 0 0 0 0 0 0 0 0 0 — 24

No. of informants 260

Total nominations 3,047

No. of groups generated 694

Note. Total nominations are necessarily smaller than the sums of conominations; boldfaced cells denote significant conominations (p, .01).The abbreviations in the column and row headings denote names students gave to sixth-grade girls’ groups.

1192 Kindermann

examined for the extent to which these referred tolarger crowds.

Friendships. At the beginning of sixth grade, chil-dren also nominated their three best friends in class,in school, and outside of school. The goal was tocapture peer relationships of students whowould notbe members of peer networks, either because theywould not be known well enough in the grade orbecause they onlywould have relationships that werenot publicly known. Reciprocal friendships wereidentified using school and class rosters of studentsin the town; 294 students listed at least one friend(94% of participants).

Results

Afirst set of analyses gives descriptive information onindividuals and their change. A second set examinesthe characteristics of social networks. A third setfocuses on selection processes as well as on potentialsimultaneous influences from outside children’s peergroups. Controls are included for individual andnetwork characteristics that indicate children’s pref-erences for specific kinds of peer partners (sex,academic competence), for specific kinds of groups(gender composition, size, homogeneity, stability),and for the levels of their teachers’ and parents’involvement. The final set of analyses examineswhether children’s change in engagement can bepredicted from the characteristics of their peer groupsover and above the contributions of the selectioncontrols, as well as when potential competing influ-ences from teachers and parents are controlled.

Individual Engagement, and Teacher andParent Involvement

On average, students were highly engaged (Ms 53.09 to 3.25 on the 4-point scale) and remained highlystable (r 5 .75, p , .001, n 5 300). Students alsoperceived teachers and parents to be fairly involved(Ms 5 2.83 and 3.21 on the 4-point scale). There wereno differences between the students who participatedin the study and studentswho did not, but an analysisof variance confirmed that girls were more engagedthan boys (3.20 vs. 3.01), F(1, 298) 5 12.32, p , .01. Inthe following analyses, missing values were esti-mated using a full information maximum likelihoodprocedure (FIML; Amos 5; Arbuckle, 2003). As Table 2shows, student engagement was moderately corre-lated with student reports of teachers’ and parents’involvement, and involvement from adultswas highlyintercorrelated.

Social Networks

At the beginning of the school year, 293 students(80% of the cohort) were members of social networks.A typical student had 4.9 other children in his or hergroup (ranging from 0 to 17 members; 73% had net-works larger than dyads). Students with large net-works were typically simultaneous members ofseveral crowds. Figure 1 gives an illustration usingthe names students gave to girls’ groups (with nom-ination frequencies larger than 2; the entiremap can beviewed at www.psy.pdx.edu/;thomas/Research).Students RYB, KER, and COD were members ofa ‘‘cool’’ crowd. The male student RYB was also

Table 2

Correlations Between Individual Variables in Fall and Spring of Sixth Grade

1 2 3 4 5

Fall,

Teacher-Reported

Student Engagement

Spring,

Teacher-Reported

Student Engagement

Student

Mathematics

Achievement

Fall,

Student-Reported

Teacher Involvement

Fall,

Student-Reported

Parent Involvement

1 Fall, Teacher-reported

Student Engagement

.76*** .62*** .32*** .28***

2 Spring, Teacher-reported

Student Engagement

.48*** .36*** .31***

3 Student Mathematics

Achievement

.05 .22**

4 Fall, Student-reported

Teacher Involvement

.53***

5 Fall, Student-reported

Parent Involvement

Notes. N 5 366.** p , .01, *** p , .01.

Peer Group Influence in School 1193

a member of COD’s mostly female group of ‘‘jocks,’’andCODwas also amember of groups of ‘‘nerds’’ and‘‘in-betweeners.’’ Large crowds of cool students ornerds bridged between otherwise separate groups.For example, among the six crowds of nerds or‘‘geeks’’ in the cohort, two provided the connectionbetween the otherwise segregated male and femalecrowds of ‘‘popular’’ students. Note that group namesare depicted solely for descriptive purposes; in thefollowing analyses, groups were subjectively defined,so that RYB’s peer group was the set of all childrenwith whom he shared a connection.

Social inclusion. A total of 56 boys and 17 girls (20%of the cohort) had no network at the beginning of sixthgrade (about half of those remainedwithout a networkover time). Among those were the 18 students withoutpermission to participate. The 55 students withouta network who had teacher reports were less engagedthan the 263 who had networks and teacher scores,F(1, 316) 5 9.4, p , .01. However, they were notnecessarily isolated. They had about 1.3 reciprocalfriends (range5 0 – 6), nominated4.3 friends (countingparticipants only; range5 0 –11), and received 3.1 nom-inations (range5 0–10). Apparently, these friendshipswere not publicly known; 10% were cross-genderfriendships, 20% were denoted as friendships outsideof class, and 15% were friendships outside of school,even though the friends also attended the school.

The converse also held true: Children withoutfriends were not necessarily without networks.Twenty participating children had not listed a friend,but these had an average of 2.1 network members(range 5 0 – 8) and received 2.7 friendship nomina-tions (range 5 0 – 7). Similarly, the 14 children whoreceived no friendship nomination had an average of2.9 group members (range 5 0 – 13) and nominatedabout 3.5 friends (range5 0 – 9). In the cohort, only 27children (7%) did not have a reciprocal friendship orsocial network, and only 5 boys and 1 girl withouta network (2%) did not nominate a single friend orreceived one nomination (5 of these left the study).Thus, only 2% to 7% can be considered to be isolatedfrom the social fabric at school.

Network composition. A set of broad descriptorswas used to describe the extent to which childrenhad specific preferences for group members. Onaverage, 98% of a child’s group members were alsosixth graders (others were from between first andseventh grades). In addition, 94% of a child’s groupmembers were of the same gender as that child; 80%of networks were gender homogenous and 2% con-tained exclusively members of a different gender.Only about 60% of a child’s group members werestudents who were assigned to the same homeroom.

Membership stability. Stability of networkswas fair;most students changed networks extensively. Onaverage, a child maintained ties with 3 (61%) mem-bers (range 5 0 – 11). About 25% of the children lostnetwork connections to all of their earlier affiliates(conversely, 50% of the students with no network inthe fall formed new affiliations in the spring). About50% of the students lost connections to at least half oftheir members. Nevertheless, 19% remained withentirely stable networks.

Engagement and Network Composition

Several properties of children’s peer groups wererelated to students’ own engagement. Network sizeand stability were related to engagement, indicatingthat highly engaged children had selected largernetworks (r5 .22, p, .01) and groups that containeda higher number of stable members (r 5 .18, p , .01).Because girls belonged to higher engaged groups,F(1, 261)5 9.53, p,.01 (using pairwise deletion ofmis-sing data), analyses verified that these relations re-mained significant when children’s sex was controlled.

Similarity in engagement was considered to bea key selection criterion.However, itwas not expectedthat children would necessarily seek out candidatesaccording to classroom engagement; rather, it wasexpected the selection processes would target simi-larities in a wider range of characteristics, only someof which would be compatible with a focus on aca-demic work. Thus, homogeneity within networks wasexpected as a by-product of selection processes thatfollowed various interindividually different criteria.At the beginning of the school year, students werefound to be similar to their group members. Engagedstudents were members of groups that were similarlyengaged (r5 .49, p, .001) andnotmuchdifferent fromthe students themselves (using absolute person-to-group differences; r 5 – .20, p , .01). Most children(70%) had engagement scores that differed less than 1SD (.59) from the profile score of their network. Largergroups were as homogeneous as small groups.

Group homogeneity persisted over time. Althoughchildren exchanged about 40% of their initial groupmembers, children who were highly engaged in thefall remained to be with highly engaged groups in thespring (r 5 .40, p , .001), and there was moderatestability in the groups’ engagement profiles (r 5 .42,p , .001). Consistent with earlier studies on selectedclassrooms (Kindermann, 1993; Kindermann et al.,1996), member turnover occurred in a way that pre-served the groups’ engagement composition. Thus,one can expect that influences from peer groups on

1194 Kindermann

children’s own engagement would also remain fairlyconsistent across time.

Peer Networks and Children’s Engagement Across Time

Similarity between individuals and the membersof their group can be an outcome of three processes:peer selection (e.g., according to similarity), socialinfluence from members of a group, and similarity ofinfluences from people outside the peer context.Structural equation modeling (SEM; Amos 5;Arbuckle, 2003) was used to examine the extent towhich children’s subsequent (spring) engagementcould be predicted from the previous (fall) engage-ment levels of their peer groups when indicators ofassortativeness were controlled. It was expected thatthe indicatorsof assortativeness (i.e., peer selectionandinfluences from teachers and parents) would explaina substantial portion of the variance (e.g., Epstein,1983; Kandel, 1978) but that group profileswould alsopredict children’s resulting engagement.

Figure 2 shows the results. The first set of controlsaddressed structural aspects of groups that can resultfrom selection processes. Controls were included forstudents’ sex (because of gender differences inengagement and because member selection was gen-der specific), the size of their peer groups (largergroups consisted of more motivated members), net-work stability (to balance differential amount ofexposure because stable networks were typicallymore engaged), and children’s academic achievement(mathematics grades because students with higheracademic ability had more engaged networks). Onlyachievement and sex were unique predictors.

A second set of controls addressed similaritiesbetween children and their group members. Homo-geneity in the groups’ gender composition wasincluded because of children’s preferences for same-sex affiliates. Similarity in engagement between children and their groups (absolute difference) was ofinterest because children who were more similar totheir group tended to be more engaged. Neithervariable contributed significantly.

A third set of controls addressed the extent towhich subsequent engagement scores can be out-comes of the influences of involvement from teachersand parents. Separate regressions showed thatteacher and parent involvement were both predictorsof children’s engagement in the spring (b 5 .37,t 5 5.95, p , .001, n 5 222; and b 5 .30, t 5 4.66,p , .001, n 5 230; using pairwise deletion of missingvalues). When both teacher and parent involvementwere used together, teacher involvement continued tobe a significant predictor (b 5 .30, t 5 3.99, p , .001,

n 5 212) but at the expense of parent involvement.Thus, both involvement scores were summed as anindicator of adult involvement, which made a strongcontribution to the spring engagement.

The resulting model (see Figure 2) showed a goodfit with the data (v25 19.005, p5 .214; 15 df, minimumdiscrepancy/DF [CMIN/DF] 5 CMIN/DF 5 1.267,comparative fit index [CFI] 5 .996, root mean squareerror of approximation [RMSEA] 5 .027; 90% confi-dence interval [CI] 5 .000 to .059). Children’s groupprofiles remained significant predictors of their en-gagement over and above the effects of the controls.The entire set of variables explained 47% of thevariance in engagement. Nested comparisons showedthat all network variables explained 24% of thevariance and that the assortativeness controls ac-counted for half of this percentage. On the one hand,this is consistent with traditional assertions that atleast half of the similarity between children and theirgroups would be the outcome of member selectionprocesses (e.g., Hamm, 2000; Kandel, 1978). On theother hand, the simple time-lagged analysis focusedon engagement at the end of the year, not on individ-ual change. It shows that children’s previous networkprofiles were related to their own engagement at theend of the school year over and above the contribu-tions of the assortativeness variables. Some of thissimilarity likely denotes socialization influences, butsome also reflect continuity of children’s prior engage-ment. If groups are hypothesized to exert influences,analyses need to examine whether group profilespredict how children change.

Peer Group Influences on Engagement

Hypotheses about peer group socialization effectsfocused on intraindividual change as an outcome ofthe influences that group members exert on a child.Analyses examined whether children’s peer groupaffiliations at the beginning of sixth grade predictedtheir engagement at the end of the school year overand above their own initial engagement. A firstanalysis used a simultaneous regression to show thatchanges in children’s engagement could be predictedby the engagement composition of their initial peergroups, when only children were included whohad nonmissing peer group profiles. The effect wassignificant (b 5 .10, t 5 2.33, p , .05, n 5 263) andconfirmed Kindermann’s (1993) findings. However,the partial correlation was small and matched bysmall average change. Members of networks thatshowed higher than average engagement at thebeginning of the year (who tended to be moreengaged themselves) remained stable across time

Peer Group Influence in School 1195

(3.30 vs. 3.29), whereas children who were with lessengaged groups decreased (by 1.5% on the 4-pointscale, from 2.96 to 2.90). Even children with peergroups in the lowest quartile of all groups in the gradedid not showmore than a 2% decrease. Nevertheless,there were subsets of children for whom peer influ-ences appeared to be more powerful: Peer groupsexplained 3% of the variance in changes in engage-ment when only students below the median wereconsidered, and 13% when only the 41 students whochanged more than 1 SD on the engagement scalewere considered.

The study’s main analysis included attention togroup-member-selection processes as well as to alter-native influences. When children select their ownpeer group members, it is possible that the kinds ofcriteria they use to select their peers are betterindicators of their own developmental pathways thanthe actual engagement characteristics of their groupmembers. The selection controls that are included(sex, gender homogeneity, achievement levels, net-work size, and person-to-group similarity) mayappear limited in terms of the extent to which theycover the entire range of possible criteria (i.e., the

Figure 2. Structural equation model predicting students’ engagement at the end of sixth grade.*p , .05. **p , .01. ***p , .001.

1196 Kindermann

group names in Figure 1 suggest a multitude ofcriteria). However, in a longitudinal design, childrenserve as their own controls and it can be assumed thatthe controls for person-to-group similarity in engage-ment (in relative as well as absolute terms) reflectcontrols for the extent to which various selectionpreferences have produced similarities in levels ofengagement. Finally, because it is also possible thatinfluences from parents and teachers are better pre-dictors of children’s change than influences frompeergroup members, levels of adult involvement wereincluded as additional controls. SEM (Amos 5;Arbuckle, 2003) was used to determine whetherchildren’s peer network characteristics were able topredict their own changes in engagement over andabove the control variables and the alternative influ-ences. Missing values were estimated using FIML.

Figure 3 shows the results. The data fit the modelwell (v2 5 22.660, p 5 .481; 23 df, CMIN/DF 5 .985,CFI5 1.00, RMSEA5 .000, 90%CI5 .000 to .042). Peergroup engagement profiles remained predictors ofchildren’s change across time over and above thecontributions of the controls (b 5 .128, p , .05). Themodel showed that children’s sexwas also a significantpredictor of engagement change (b 5 .094, p , .05;denoting that girls showedmore positive changewhentheir groups’ engagement levels were held constant).Network size was a negative predictor when thegroups’ engagement level was controlled (b 5 – .141,p , .01), although group size had been positivelyrelated to engagement at each time point; if a child’sgroup was larger at the average level of engagement,this was associatedwith negative change. Finally, adultinvolvement was also a significant predictor over andabove group profiles (b 5 .090, p , .05). Academicachievement and the other control variables werecorrelated with individual and group engagement butwere not related to change in engagement over time.

In sum, although peer group influences were small,they existed over and above the contributions of theselection variables and the (similarly small) influencesfrom adults. Three features of the model should benoted. First, SEM methods allow researchers to takecorrelations between measurement errors into consid-eration. In themodel, individuals’measurement errorswere assumed to be correlated across time, and peergroup influences were examined over and above thecorrelated errors. One may argue that this is unrealis-tic. High stability of children’s engagement in terms ofteacher perceptions may be due to ‘‘real’’ stability, butit also may be due to stability of measurement errors;both are part of the real world. However, the controldid not lower stability to an unrealistic level. Whenpeer group influences on engagement are concerned, it

seems preferable to focus on how peers can affectunique teacher ratings independently of effects onmeasurement errors.

Second, initial measurement errors of the peergroup engagement profiles were also assumed to becorrelated with initial measurement errors of individ-ual engagement. This is justified because peer groupprofiles were averaged across the individual scores ofthe members of a child’s peer group. The errorsshould be correlated; the analysis examined person-to-group similarity independently of similarity inmeasurement errors. Finally, for reasons of caution,one further peer context variable was included ina follow-up analysis: the engagement profiles ofchildren who were reciprocal friends of a child butnot members of his or her peer group network. Thegoal was to make sure that their inclusion would notalter the findings. These profiles did not contribute tochildren’s change in engagement, and their inclusionhad no effect on the fit of the model (v2 5 23.947,p 5 .579, 26 df, CMIN/DF 5 .921, CFI 5 1.0,RMSEA 5 .000; v2 difference 5 1.347, 1 df ).

Discussion

The main goal of this study was to examine the effectsof sixth graders’ naturally existing peer groups onchanges in their classroom engagement across the firstyear of middle school. Based on SCM, 80% of thestudents were identified as members of social net-works; 73%hadnetworks larger thandyads.Networkswere found to be homogeneous in their members’levels of engagement. Althoughmember turnoverwashigh across the school year (40%), members wereexchanged in such away that the groups’motivationalhomogeneity remained fairly intact. Most importantly,peer group profiles of engagement predicted changesin students’ ownengagement from the fall to the springof sixth grade. Students who initially shared networkswith highly engaged peers remained engaged or evenincreased, whereas students with less engaged groupsshowed declines. Across the school year, the magni-tude of peer influence amounted to about 2% on the4-point engagement scale.

Several design features supported the contentionthat these effects can be interpreted as socializationinfluences. The study included the entire population ofsixth-grade students in a small town,used independentreporters of peergroupmembership (consensusmaps),and classroom engagement (teacher report), relied onindicators of school engagement that are part of every-day social interactions in the classroom, examinedstudents’ intraindividual change as the target outcome,

Peer Group Influence in School 1197

disentangled peer group selection from peer groupinfluences, and controlled for simultaneous socializa-tion influences from teachers and parents. The currentfindings of peer group influences in a whole townmay appear to be less powerful than those found inprior studies that confined the range of students’network members to classmates (Kindermann, 1993;Kindermann et al., 1996), but they remained significantwhen considered over and above the simultaneous

contributions of peer selection processes and the sig-nificant contributions from teachers and parents.

Mechanisms of Influence

The design of this study allowed for clear identifi-cation of one source of peer influences. However, thenature of the processes that were responsible forchange in children’s engagement was not explicitlyexamined. The literature on socialization proposes

Figure 3. Structural equation model of peer group influences on students’ engagement during sixth grade.*p , .05. **p , .01. ***p , .001.

1198 Kindermann

several possible (general) processes, such as model-ing, reinforcement, and pressure to conform (e.g.,Altermatt & Pomerantz, 2003; Harris, 1995;Kindermann, 2003). Beyond these, a variety of othermechanisms have been proposed. Theories of motiva-tion focus on the engagement of peers as an energizingresource; their enthusiastic participation makesschoolworkmore fun and enjoyable. Studies in whichindividual relatedness to friends, peers, and class-mates has been found to predict changes in individualengagement over the school year (e.g., Furrer &Skinner, 2003) are consistent with such explanations.Engaged peers may also be sources of help, support,and instrumental aid in tracking and completingseatwork, class projects, and homework assignments.

By the same token, there are additional mecha-nisms through which peer group disaffection couldexert a downward pressure on children’s ownengagement in school. Disaffected peersmaydiscour-age children from becoming involved in current (ortrying out new) learning activities, leading children towithdraw their own effort or exertion. If peers valueand prioritize nonacademic activities, this may dis-tract children from active participation in school. Peergroupswho believe that enthusiasm about learning isnot ‘‘cool’’ may undercut children’s willingness todemonstrate their interest and commitment to class-roomactivities (e.g., Graham, Taylor, &Hudley, 1998).All of these are ‘‘amplifying’’ mechanisms in whichthe rich get richer and the poor get poorer, effects thatare consistent with the findings of the current study.

A key direction for future studies on peer influen-ces will be to observe how social influences work innatural environments. Such studies are rare and timeconsuming, but they have documented a variety ofinteractions (e.g., discussions, evaluative discourse,prosocial interchanges, and social learning contingen-cies) that can be mechanisms of influence (e.g.,Altermatt, Pomeranz, Ruble, Frey, & Greulich, 2002;Berndt, Laychak, & Park, 1990; Dishion, Andrews, &Crosby, 1995; Hawley, Little, & Pasupathi, 2002; Sage& Kindermann, 1999; Wentzel et al., 2004). The studyof peer influences would be strengthened by directexamination of such mechanisms.

Processes of Selection

Although the goal of the present study was todisentangle selection from socialization effects toobtain an estimate of the magnitude of peer influen-ces, findings also revealed strong effects of groupmember selection. Children sorted themselves intopeer groups that were relatively homogeneous inengagement, and although they reshuffled them-

selves across the school year, the resulting groupsagain showed similar profiles of engagement(a phenomenon described as assortativeness). If peergroups exert an impact on the trajectories of children’sown engagement, it is important to understand howchildren move into (and out of) peer groups.

It is possible, although not necessary, that childrenprefer to affiliate with others who show the samedegree of interest and enthusiasm for school, that is,the same level of engagement. However, selectionusing any criteria that are associated with engage-ment produces similar assortativeness effects. Thecontrol variables used in this study suggest multipleavenues of peer selection. Onewould be achievement:Childrenmay select their peers based on their level of‘‘smarts,’’ preferring to affiliate with children at aboutthe same level of academic performance. Anotherwould be gender: Consistent with most studies onschool motivation and peer groups (cf. Eccles et al.,1998), there were gender differences in engagement,corresponding peer group profiles, and changes inmotivation. Girls’ engagement remained relativelystable whereas boys’ decreased, and differences intrajectories coexisted with similarities in processes ofhow boys and girls selected groupmembers and howthey were influenced by their groups.

Many alternative pathways are possible. Childrenmay be excluded frompeer groups based on their lackof interest in school or their poor grades (as suggestedby the literature on peer rejection; e.g., Bierman, 2004;Buhs, Ladd, &Herald, 2006). Childrenmay also selectpeers based on their preferred activities (as suggestedby the literature on social crowds and friendshipgroups; e.g., Brown, 1999; Urberg, Degirmencioglu,& Pilgrim, 1997); childrenwho aremore into sports orsocial activities may not be as academically engagedas those focused on good grades. Looking beyond theimmediate group itself, children may also preferothers whose parents have similar values and expecta-tions because it allows them to feel more comfortableand to create peer groups whose priorities are consis-tent with those from home; parents may also try toinfluence peer associates directly. Finally, childrenmay prefer to spend time with peers who like theteacher as much (or as little) as they do. A key avenuefor future research is the study of the processes bywhich selection (and reselection) occur.

It is important to note that even though severalcommon selection characteristics were related tochildren’s own engagement, indications of groupinfluence effects persisted evenwhen these character-istics were controlled. Consistent with earlier studies(e.g., Kindermann et al., 1996; Sage & Kindermann,1999), influence processes from peer groups are

Peer Group Influence in School 1199

present across children with a variety of differentselection preferences, and the influences appear todiffer only in terms of the levels of engagement atwhich they operate.

Interplay of Selection and Socialization

The most informative studies of peer influencesconsider how processes of selection and socializationwork together over time. A simple example canbe drawn from the current study: If children selectothers who are similar to themselves to begin with,peer interaction processes do not have as great anopportunity to socialize children toward further sim-ilarity (e.g., Altermatt & Pomerantz, 2003). However,it is also possible that if selection occurs primarily onthe basis of similarity, socialization effectsmay lead tomaintenance or even to increasing diversity overtime. For example, childrenmay select peers who likethem just theway they are andmay stay engagedwithpeers only as long as they remain supportive. Fromthis perspective, the role of peer groups might beprimarily to support or amplify pre-existing charac-teristics. Or peer groups may create diversity: Oncesimilar children join together, peers may socializechildren to different roleswithin the groupor childrenmaywork toward expressing their individuality. Suchprocesses would lead not to increasing homogeneitybut to patterns of change in which groups and theindividual children within themwould becomemoredifferent from each other over time.

The openness of natural groups, to which childrencan aspire and from which they can freely exit, mayalso shape socialization influences in complex ways.For example, mechanisms of influence that rely onnegative interactions, such as criticism or coercion,may not be found as frequently in peer groups. Ifaversive interactions are common, a child would belikely to leave or the group itself might break up.Moreover, such openness may paradoxically allowsocialization influences to come before selection oc-curs, as children try to take on characteristics andbehaviors that facilitate group entry. In designingstudies, it will be important to recognize that theinterplay between selection and socialization is anongoing process that iterates over time.

Limitations of the Study

The goal of the study was to examine influencesfrom reliably identified peer groups on school motiva-tion in an entire social system. Of course, the focus ona rural town invites new questions about sampling, forexample, whether the findings would generalize tolarger townsordifferent school systems.However, two

previous studieswith children in suburbanelementaryschools (Kindermann, 1993; Sage&Kindermann, 1999;average engagement levels were 3.0 and 3.2, respec-tively) and one studywith adolescents in an inner-cityschool (Kindermann et al., 1996; average engagementlevel was 2.60) have found comparable effects of peerselection and socialization processes. Thus, it seemslikely that the findings can be generalized.

A second limitation is that 20% of the children inthis study did not have a social network. However,researchersusingSCMshouldnotnecessarily concludethat all students without social networks are isolatedat school; many (76%) of these children had friends.SCM tends to overestimate social isolation for stu-dents whose ties are not publicly known or whosefriendships are private. Conversely, friendship as-sessments can underestimate the extent to whichchildren without friends are nevertheless embeddedin well-known peer groups of frequently interactingchildren.Most of the participants without a reciprocalfriend (57%) and most of the children who did notnominate a friend (66%) were identified as membersof social networks.

Finally, the magnitude of peer effects was modest,particularly when assortativeness was controlled. Sev-eral factors place constraints on the magnitude of peereffects, explaining why their influences should notnecessarily be larger. First, findings from earlier studies(Kindermann, 1993; Kindermann et al., 1996) suggestthat effects can be larger when only classrooms ofvolunteering teachers, and not an entire social system,are included. The current study included all classroomsina townaswell as cross-classroomnetworks, and theirinclusion should give a more appropriate estimate ofthemagnitude of peer effects. Second, childrenwith an‘‘average’’ level of motivation tend to select ‘‘average’’peers, and only children whose own levels of engage-mentdeviatemarkedly from thoseof their peers shouldbe influenced more. Third, although peer influencescontribute about 2% to the variance in changes inchildren’s engagement, teachers andparents contributeonly about 4%more. It may bewise not to overestimatethe extent towhich any single kind of context agent canaffect changes in children’s engagement. Unless sub-groups of students can be identified who are particu-larly susceptible to peer influences, the strongestpredictors of children’s engagement will always betheir past behavior, which includes the cumulativeeffects of a history of selection and socialization bypeers and adults. Finally, there seems to be a pattern ofcontinuous decline in children’s motivation across theyears they spend in school (see Fredricks et al., 2004).The current study traced the path of only one schoolyear, and it is possible that the peer influences that

1200 Kindermann

appear small in any given year can accumulate sub-stantially across a child’s entire school career.

Future Research on Social Influences onClassroom Engagement

The current study focused onpeer groups and theirinfluence on changes in children’s classroom engage-ment. This focus converges with almost all develop-mental theories in postulating that social partnerswho interact most frequently with a child should bemost influential, and it follows the perspective thatsocial interactions are the engine of development(Bronfenbrenner & Morris, 1998). To better under-stand how these proximal processes operate, futureresearch should focus on processes of selection andreselection, studying how children come to be mem-bers of multiple groups, as well as on mechanisms ofinfluence, investigating the pathways through whichthese peers can shape children’s development(Kindermann, 2003). The findings of the study alsosuggest that a child’s peer world is more complex thancan be captured by any single approach and that futurestudies will benefit from combining different methodsof assessing children’s peer contexts. Different rela-tionships may be differentially influential. As friend-ship researchers assert (e.g., Gest, Graham-Berman, &Hartup, 2001; Laursen, 2005), peer influences maydepend not only on frequency of interaction but alsoon levels of interpersonal closeness among affiliates.Closenessmay boost the influence of peer groups (e.g.,Ladd, Birch, & Buhs, 1999), and influences may bestrongest frompeerswho are close to childrenandwhointeract with them frequently. Moreover, researchersneed to be open to the possibility that closeness andfrequency of interaction are not the only features ofpeer relationships that matter. For example, victimiza-tion researchers (Hodges & Card, 2003; Juvonen,Nishina, & Graham, 2000; Snyder et al., 2003) havepointed out that peers whom a child is actively tryingto avoid cannevertheless haveaprofound influence onhis orherdevelopment in school.A child’s socialworldinvolves more than relationships with friends andfrequent interaction partners. If studies attempt toexamine overall patterns of peer influences, additionalpeer partners would need to be considered.

Finally, future studies may be less concerned withthe unique effects from peer groups and more con-cerned with questions about whether (and how)influences from peers work synergistically or antag-onistically with actual influences that emerge fromparents or teachers (e.g., Fletcher et al., 1995; Wentzel,1998). Recently, studies have begun to explore specificcombinations of effects from multiple partners (e.g.,

Chen, Chang,He, & Liu, 2005; Goldstein, Davis-Kean,& Eccles, 2005; Ladd et al., 1999; Mounts & Steinberg,1995; Pettit, Bates, Dodge, & Meece, 1999; Wentzel,1998). For future studies incorporating the effects ofchildren’s affiliations with peers on their develop-ment in school, both alone and in combination withother social partners, the current study supportsassumptions about the unique importance of peers.At the same time, it highlights strategies that showmuch promise for tackling the complex conceptualand empirical issues of how to detect peer groupinfluence effects in naturalistic studies.

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