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. Author manuscript; available in PMC: 2019 Nov 1.
Published in final edited form as: J Educ Psychol. 2018 Mar 1;110(8):1192–1201. doi: 10.1037/edu0000265

Cooperative Learning in Middle School: A Means to Improve Peer Relations and Reduce Victimization, Bullying, and Related Outcomes

Mark J Van Ryzin 1,✉, Cary J Roseth 2
PMCID: PMC6430212  NIHMSID: NIHMS928848  PMID: 30911200

Abstract

Peer victimization is a highly stressful experience that impacts up to a third of all adolescents and can contribute to a variety of negative outcomes, including elevated anxiety, depression, drug use, and delinquency, as well as reduced self-esteem, school attendance, and academic achievement. Current prevention approaches (e.g., the Olweus program) have a mixed record in American schools. We propose a new approach to prevention that leverages theory and research surrounding the social aspects of bullying and victimization, particularly peer relations. Our approach attempts to (1) break down the process of homophily among bullies, and (2) provide a mechanism by which socially isolated students can develop new friendships. Our approach asks teachers to increase opportunities for positive peer interaction through carefully structured, group-based learning activities in school (i.e., cooperative learning). We hypothesized that these positive peer interactions would result in reductions in bullying, victimization, perceived stress, and emotional problems, as well as increases in peer relatedness, among more marginalized students. Using a cluster randomized trial with 15 rural middle schools in the Pacific Northwest (N = 1,460 7th grade students), we found that cooperative learning significantly reduced bullying, victimization, and perceived stress for marginalized students (i.e., moderated effects), and reduced emotional problems and enhanced relatedness for all students (i.e., main effects). Given that cooperative learning has already been shown to enhance student engagement and achievement in prior research, our results demonstrate that cooperative learning can be a permanent, sustainable component of teacher training and school culture.

Keywords: cooperative learning, bullying, victimization, peer relations, middle school

Introduction

Peer victimization, defined as the experience of harassment and aggression by peers, including teasing, threatening, and hitting, is one of the most stressful experiences that an adolescent can encounter (Sebastian, Viding, Williams, & Blakemore, 2010). Unfortunately, it is also quite common; research indicates that anywhere from a quarter to a third of all students are victimized by peers (Craig et al., 2009; World Health Organization, 2012). Biological and social changes during the teenage years render adolescents particularly vulnerable to the effects of peer victimization. From a biological perspective, adolescents become increasingly sensitive to social reward (Fareri, Martin, & Delgado, 2008; Sebastian et al., 2010), while they also begin to exhibit a significant physiological stress response (Stroud et al., 2009) and, concomitantly, a lag in self-regulatory capability (Prencipe et al., 2011). At the same time, peers become increasingly important as a source of social support and affiliation during this developmental period (Steinberg & Morris, 2001), and the transition to middle school is often accompanied by a surge in aggressive and exclusionary behavior (Cook et al., 2010; Robers, Kemp, & Truman, 2013).

As a result of these developmental changes, peer victimization can be highly impactful for adolescents. Research on a variety of different populations (e.g., U.S. vs. international, straight vs. LGBT) finds that victimization predicts a wide variety of negative outcomes in middle schoolers, including elevated levels of anxiety, depression, drug use, and delinquency, and lower levels of self-esteem, school attendance, and academic achievement (Arseneault, Bowes, & Shakoor, 2010; Barchia & Bussey, 2010; Cheng et al., 2010; Juvonen, Wang, & Espinoza, 2011; Martinelli et al., 2011; Rueger, Malecki, & Demaray, 2011; Russell, Ryan, Toomey, Diaz, & Sanchez, 2011; Sullivan, Farrell, & Kliewer, 2006; Thijs & Verkuyten, 2008). Research also finds that chronic stress in adolescence may have long-term negative effects in areas such as brain functioning (e.g., reduced hippocampal volume, impaired functioning of the serotonergic and dopaminergic systems; Brown & Spencer, 2013; Buwalda, Geerdink, Vidal, & Koolhaas, 2011) and physical health (e.g., cardiovascular disease, obesity, metabolic syndrome; Miller, Chen, & Parker, 2011; Pervanidou & Chrousos, 2012). All of this has led the World Health Organization (2012) to classify peer victimization as a significant public health problem, and researchers have emphasized middle school as a critical time to intervene in order to prevent negative long-term consequences (Rueger et al., 2011).

Current School-based Approaches to Prevention

The most widespread approach to preventing victimization and related problems is the Olweus program (Olweus, 1993), which typically involves direct instruction in topics related to bullying (i.e., harassment or aggressive behavior directed at another in the context of a power imbalance) and victimization, including awareness, empathy, attitudes, and peer norms. To date, research has failed to establish a strong empirical justification for the Olweus approach. Specifically, the results of a meta-analysis of whole-school anti-bullying programs found significant effects, but effect sizes were small to negligible, and the authors concluded that the programs did not achieve practical significance (Ferguson, Miguel, Kilburn, & Sanchez, 2007). Another meta-analysis (Merrell, Gueldner, Ross, & Isava, 2008) included approximately 15,386 K-12 students in Europe and the US, and positive effect sizes were found for only about one-third of the study variables, which tended to be positive changes in knowledge, attitudes, and perceptions of bullying and victimization rather than actual behavior. A third meta-analysis by Ttofi, Farrington, and Baldry (2008) evaluated 44 bullying intervention studies, most of which were based on the Olweus program. Results indicated that bullying and victimization were reduced by 17–23% in experimental schools compared to control schools, although Ttofi and colleagues noted that anti-bullying programs were more efficacious in smaller-scale European studies and less effective in the United States, a conclusion that has been echoed in more recent reviews and meta-analyses (Evans, Fraser, & Cotter, 2014; Olweus & Limber, 2010). Finally, a recent large-scale trial of a middle school anti-bullying program in the U.S. that was based upon the Olweus approach reported significant effects on only two of seven outcomes, and only in one of the two states participating in the trial (Espelage, Low, Polanin, & Brown, 2015). Taken together, this research suggests that existing anti-bullying programs have not been universally effective in reducing bullying, victimization, and related outcomes in American schools.

A New Approach to Prevention

In this study, we take a different approach to prevention that leverages theory and research on the social aspects of bullying and victimization, particularly peer relations, which play a vital role in this behavior. For example, bullies tend to aggregate in a phenomenon known as homophily, in which individuals select friends based upon similarities in behavior and/or attitudes (Brechwald & Prinstein, 2011; Dishion et al., 1991). Within groups of bullies, social norms are established that view bullying positively, and these norms elicit and reinforce bullying behavior among group members (Hong & Espelage, 2012).

In addition, socially isolated students may be vulnerable to victimization due to their lack of friends. Research finds that students with more social connections are less likely to be victimized (Hodges, Malone, & Perry, 1997; Kendrick, Jutengren, & Stattin, 2012) and that those who are socially rejected by peers are more likely to be victimized (Hodges & Perry, 1999; Veenstra et al., 2007). Research also finds that victimized children are less likely to form new friendships (Ellis & Zarbatany, 2007), making it particularly difficult for victimized children to escape their social isolation and avoid future victimization.

Our prevention approach, which focuses solely on peer relations and peer networks, attempts to (1) break down the process of homophily among bullies, and (2) provide a mechanism by which isolated students can develop new friendships. To achieve both of these ends, our approach asks teachers to increase opportunities for positive peer interaction through carefully structured group-based learning activities in school. Theoretically, by giving students the opportunity to work with a range of peers, these group-based learning activities should lead to both reductions in homophily (as youth who may be prone to bullying are exposed to a greater cross-section of the social network, including peers less supportive of bullying) and reductions in social isolation (as marginalized youth are given the opportunity to develop new friendships).

Simply putting students in groups, however, does not guarantee that positive social interactions will occur. In fact, social psychological research on stereotyping, prejudice, and discrimination demonstrates that imposing contact among students who belong to different social cliques can actually exacerbate perceived differences by reinforcing and strengthening the latent competitive dynamic underlying in- and out-group perceptions (Dovidio, Gaertner, & Saguy, 2009; Pettigrew & Tropp, 2000). In order for peer interaction to promote true social integration, the social context must promote the breakdown of biases and prejudices among students who belong to different social groups (Pettigrew, 1998; Pettigrew & Tropp, 2008).

Theory and research (e.g., Allport, 1954; Johnson, Johnson, & Maruyama, 1983) suggest that the key ingredient for creating such a social context is positive interdependence, i.e., when goals are structured such that individuals can attain their goals if (and only if) others in their group also reach their goals. Under conditions of positive interdependence, patterns of peer interaction change; instead of competing with or ignoring one another, peers are more likely to promote the success of one another through mutual assistance, emotional support, and sharing of resources (Deutsch, 1949, 1962). In turn, these positive social interactions increase interpersonal attraction and acceptance, reduce social isolation, and support the development of new friendships (Johnson, Johnson, Roseth, & Shin, 2014; Mikami et al., 2005). Indeed, research on peer interactions reviewed by Bierman (2004) suggests that gains in social skills and knowledge alone are insufficient to reduce social isolation; rather, only positive interdependence (and the subsequent positive social interactions that arise from these experiences) can motivate youth to re-evaluate previous conclusions regarding the social desirability of others.

Cooperative learning is one of the few empirically supported instructional approaches that ensures the establishment of positive interdependence in group-based learning activities. Cooperative learning is an umbrella term that includes reciprocal teaching, peer tutoring, jigsaw, and other group-based activities in which peers work together to maximize one another’s learning (Johnson, Johnson & Holubec, 2013). Cooperative learning has robust empirical evidence documenting its positive effects on interpersonal attraction, social acceptance, and academic achievement (Ginsburg-Block et al., 2006; Johnson & Johnson, 1989, 2005). In a meta-analysis of 148 studies representing over 17,000 early adolescents, Roseth et al. (2008) showed that cooperative goal structures (i.e., cooperative learning) were associated with greater achievement (effect sizes .46 to .65) and more positive peer relationships (effect sizes .42 to .56) compared to competitive and individualistic goal structures. In addition, the relative effects of cooperative goal structures on achievement and peer relationships were positively correlated, with positive changes in peer relationships accounting for 33 to 40% of the variance in achievement. These findings suggest that cooperative learning is an effective way to promote academic achievement while simultaneously addressing some of the social processes that encourage bullying and victimization.

To be clear, the use of cooperative learning as a means of building more positive peer relationships and reducing bullying and victimization has been advocated previously as one aspect of a broader prevention framework (e.g., Espelage & Swearer, 2004; Olweus, 1993). Our approach proposes that an intervention focused solely on increasing cooperative activities in the classroom can reduce bullying, victimization, and related problems. In other words, rather than introducing a school-wide prevention program that has the potential to divert time and resources from classroom instruction, the hypothesis tested here is that simply implementing cooperative learning in the classroom will change peer relations in a way that reduces bullying and victimization without the need for a structured anti-bullying curriculum.

Current Study

This paper reports on a small-scale cluster randomized trial of the Johnsons’ approach to cooperative learning (Johnson et al., 2013) as an intervention to prevent bullying and victimization in middle school. We hypothesized that cooperative learning would result in reductions in both bullying and victimization, as well as reductions in important side-effects of victimization, including perceived stress and emotional problems (i.e., anxiety, fearfulness). However, given that victimization is experienced by between a quarter and a third of all adolescents (Craig et al., 2009; World Health Organization, 2012), we did not necessarily expect to see effects across the entire sample. Rather, we hypothesized that effects would be found among those youth who were socially marginalized or disengaged. Thus, we evaluated whether the effects of cooperative learning on victimization, perceived stress, and emotional problems would be moderated by baseline levels of marginalization, which we defined as those students who were the least engaged in school at baseline.

We also wished to explore whether cooperative learning reduced bullying among marginalized youth, which could potentially be considered “reactive aggression”, i.e., bullying perpetrated by victimized youth as a reaction against their victimized status. In contrast, “proactive aggression” is more carefully planned and is generally exhibited by more socially dominant youth (Hubbard, McAuliffe, Morrow, & Romano, 2010).

Finally, we wished to establish that cooperative learning was not just reducing negative behavior but also promoting more positive outcomes, such as positive relationships among students. Thus, we evaluated intervention effects on students’ sense of relatedness (i.e., peer acceptance), again focusing on the more marginalized students.

Method

All aspects of this study were approved by the Institutional Review Board (IRB) at the Oregon Research Institute. This study was registered as trial NCT03119415 in ClinicalTrials.gov under Section 801 of the Food and Drug Administration Amendments Act.

Sample

The sample was derived from a small-scale randomized trial of cooperative learning in 15 rural middle schools in the Pacific Northwest. Schools were matched based upon size and demographics (e.g., free/reduced lunch percentage) and randomized to condition (i.e., intervention vs. waitlist control). We were concerned about the likelihood of losing schools assigned as controls, so we randomized an extra school to this condition (i.e., 8 waitlist-control vs. 7 intervention schools).

Our analytic sample included N = 1,460 7th grade students who enrolled in the project in the fall of 2016 (see Figure 1). We achieved greater than 80% student participation at each school by using a passive consent procedure and providing research staff to oversee the data collection. We also offered compensation to the schools for participating in the project, and enrolled participating students in a prize raffle. Student demographics by school are reported in Table 1. Overall, the sample was 48.2% female (N = 703) and 76.4% White (N = 1,116). Other racial/ethnic groups included Hispanic/Latino (14.3%, N = 209), multi-racial (4.2%, N = 61), and American Indian/Alaska Native (3.5%, N = 51); our sample included less than 1% Asian, African-American, and Native Hawaiian/Pacific Islander. Overall, 13.9% (N = 203) were reported as having Special Ed status, 79.6% (N = 1162) did not have Special Ed status, and 6.5% (N = 95) were missing this designation. Free and reduced price lunch (FRPL) status was not made available by the schools, although school-level FRPL figures (obtained from state records) are reported in Table 1.

Figure 1.

Figure 1

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CONSORT diagram.

Table 1.

Descriptive data by school

School Intervention N % female % White % Special Ed % FRPLa
1 Yes 211 48.8 74.4 13.3 53
2 Yes 47 55.3 78.7 12.8 66
3 Yes 94 39.4 62.8 n/a 62
4 No 80 50.0 92.5 26.3 65
5 Yes 89 47.2 85.4 18.0 72
6 Yes 93 46.2 90.3 18.3 71
7 No 44 45.5 93.2 18.2 33
8 Yes 70 51.4 80.0 12.9 57
9 No 63 42.6 84.1 19.0 45
10 Yes 64 31.3 71.9 4.7 95
11 No 144 47.2 66.7 16.7 61
12 No 170 54.1 48.8 11.8 84
13 No 158 50.6 89.9 11.4 66
14 No 43 48.8 88.4 16.3 39
15 No 90 53.3 82.2 15.6 46
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a

State records.

Note. One school did not provide Special Ed status.

Procedure

Training for intervention school staff began in the fall of 2016 and continued throughout the 2016–2017 school year, consisting of 3 half-day in-person sessions, periodic check-ins via videoconference, and access to resources (e.g., newsletters). Training sessions were conducted by D. W. and R. T. Johnson, supported by the authors, and utilized Cooperation in the Classroom, 9th Edition by Johnson, Johnson, and Holubec (2013); each staff member was given a copy of the book. The three in-person training sessions per school were conducted in (1) late September and early October, (2) late October through early December, and (3) late January through late March. Due to the geographic dispersal of the schools, each school received training individually according to their own schedule for professional development.

Under the Johnson’s approach, cooperative learning can include reciprocal teaching, peer tutoring, collaborative reading, and other methods in which peers help each other learn in small groups under conditions of positive interdependence. The Johnsons’ approach also emphasizes individual accountability, explicit coaching in collaborative skills, a high degree of face-to-face interaction, and guided processing of group performance. Cooperative learning is viewed as a conceptual framework within which teachers can apply the principal of positive interdependence to design their own group-based activities using existing curricula.

Measures

Student data collection was conducted in September/October 2016 (baseline) and March 2017 (follow-up) using on-line surveys (i.e., Qualtrics; https://www.qualtrics.com/). The time between data collection points varied across schools but averaged five and a half months. To assess fidelity of implementation, we also conducted teacher observations. A Certificate of Confidentiality was obtained for these data from NIAAA (#CC-AA-17-011). To shrink the overall number of items and reduce participant burden, existing data from other studies were used to select the highest-loading items from each scale below (additional information available from the first author).

Bullying and victimization

We used subscales from the University of Illinois Bully Scale, a measure that has been an integral part of other studies of bullying and victimization (Espelage & Holt, 2001). Bullying was assessed using 5 items, including “I teased other students while we were in a group” and “I spread rumors about other students”. Alpha reliability was .74 and .77 at baseline and follow-up, respectively. Victimization was assessed using 3 items, including “Other students picked on me” and “Other students made fun of me”. Alpha reliability was .93 and .94 at baseline and follow-up, respectively. For both subscales, students responded on a 5-point scale from 0 (Never) to 4 (7 or more times) and items were averaged to arrive at the subscale scores.

Perceived stress

We used 4 items from the Perceived Stress Scale (Cohen, Kamarck, & Mermelstein, 1983), a widely used measure that has been applied in previous studies of bullying and victimization (e.g., Estévez, Murgui, & Musitu, 2009; Martinelli et al., 2011; Tynes, Giang, Williams, & Thompson, 2008). Items includes “In the last month, how often have you been upset because of something that happened unexpectedly?” and “In the last month, how often have you felt that things were going your way?” (reverse scored). Students responded on a 5-point scale from 0 (Never) to 4 (very often). Alpha reliability was .59 at baseline and .63 at follow-up. Items were averaged to arrive at the scale score.

Emotional problems

We used three items from the Emotional Problems subscale of the Strengths and Difficulties Questionnaire (Goodman, Meltzer, & Bailey, 1998), which has been used extensively in studies of adolescents (Muris, Meesters, & van den Berg, 2003; Van Roy, Veenstra, & Clench-Aas, 2008). Items included “I worry a lot” and “I am often unhappy, depressed or tearful”. Students responded on a 3-point scale from 1 (Not true) to 3 (Certainly true). Alpha reliability was .71 at baseline and .75 at follow-up. Items were averaged to arrive at the scale score.

Relatedness

We used 4 items from the Relatedness Scale, which has been used in previous research as a predictor of positive school adjustment in adolescents (Furrer & Skinner, 2003). Items included “When I’m with my classmates, I feel accepted” and “When I’m with my classmates, I feel unimportant” (reverse scored). Students responded on a 4-point scale from 1 (Not at all true) to 4 (Very true). Alpha reliability was .71 at baseline and .79 at follow-up. Items were averaged to arrive at the scale score.

Engagement

We used 4 items from the Behavioral Engagement subscale of the Engagement vs. Disaffection with Learning Scale (Skinner & Belmont, 1993), which has been linked to the quality of peer relations in previous research (Furrer & Skinner, 2003; Tucker et al., 2002). Items included “I try hard to focus in class” and “In class, I do just enough to get by” (reverse scored). Students responded on a 4-point scale from 1 (Not at all true) to 4 (Very true). Alpha reliability was .75 at baseline. Items were averaged to arrive at the scale score.

Demographics

Youth sex, ethnicity, and Special Ed status were obtained from school records. Ethnicity was dichotomized to White (0) vs. non-White (1); the latter included Hispanic/Latino students. Sex was coded as Male (0) and Female (1), and Special Ed status was coded as No (0) and Yes (1).

Observed intervention fidelity

Research staff blind to intervention assignment observed teaching practices in intervention and control schools. We trained our observers to adequate reliability using simulated data before they were permitted to conduct observations in actual classrooms, and we used an established observation protocol for key aspects of cooperative learning (e.g., positive interdependence; Krol, Sleegers, Veenman, & Voeten, 2008; Veenman et al., 2002). Observations were conducted once in the late fall/early winter and again in the spring. Observers remained in a classroom for an entire class period. In smaller schools, observers were generally able to observe all 7th grade teachers within a single day; for large schools, observers randomly selected a subset of all 7th grade teachers.

Analysis Plan

The multilevel nature of our data (i.e., students within schools) required an analytical approach that addressed the statistical dependencies created by nesting. Thus, we evaluated our hypotheses with linear mixed models in R (the lme4 package; Bates et al., 2013), which allocate variance either “within” or “between” groups. In this model, student data (e.g., victimization, perceived stress) were at Level 1 (“within”) and school data (i.e., intervention condition) were at Level 2 (“between”). All predictors were uncentered. Our small sample did not permit the inclusion of random effects at the school level, so all individual-level effects were fixed. We used interaction terms to represent moderation of intervention effects by baseline levels of marginalization (i.e., low engagement); if the interaction effect was not significant, we removed it and reported main effects. We controlled for sex differences in these analyses, given existing research that has found such differences in bullying, perceived stress, and emotional problems (Archer, 2004; Hampel & Petermann, 2006; Piccinelli & Wilkinson, 2000).

Results

Descriptive data for all variables and correlations are presented in Table 2. ANOVA models indicated that students in intervention and control schools did not differ in terms of baseline levels of bullying [F(1,1451) = 1.99, ns], victimization [F(1,1450) = .05, ns], perceived stress [F(1,1447) = 1.52, ns], or relatedness [F(1,1445) = .04, ns]. The two groups were different, however, in terms of emotional problems [F(1,1454) = 6.34, p < .05], with intervention schools being slightly lower; this effect was small (R2 < .01). With regards to fidelity observations, ANOVA indicated significantly higher levels of observed positive interdependence in intervention schools as compared to control schools, F(1,98) = 10.79, p < .01, R2 = .10.

Table 2.

Correlations and descriptive data

1 2 3 4 5 6 7 8 9 10 11 12
1. Victimization (baseline) —
2. Victimization (follow-up) .60*** —
3. Perceived stress (baseline) .42*** .36*** —
4. Perceived stress (follow-up) .29*** .44*** .58*** —
5. Emotional problems (baseline) .36*** .28*** .58*** .45*** —
6. Emotional problems (follow-up) .24*** .35*** .48*** .63*** .59*** —
7. Bullying (baseline) .22*** .16*** .14*** .04 .06* .06* —
8. Bullying (follow-up) .14*** .26*** .11*** .16*** .03 .14*** .43*** —
9. Relatedness (baseline) −.43*** −.35*** −.51*** −.36*** −.39*** −.30*** −.17*** −.07* —
10. Relatedness (follow-up) −.35*** −.45*** −.42*** −.55*** −.35*** −.44*** −.07* −.16*** .50*** —
11. Engagement (baseline) −.12*** −.05 −.18*** −.11*** .01 .05 −.29*** −.23*** .24*** .14*** —
12. Sex −.01 .05 .22*** .22*** .29*** .33*** −.06** −.05 −.05* −.11*** .14*** —
N 1452 1323 1449 1323 1456 1325 1453 1324 1447 1309 1455 1460
M .99 1.04 1.97 2.03 1.79 1.78 .26 .30 3.07 2.99 3.38 .48
SD 1.23 1.27 .86 .88 .53 .56 .50 .53 .68 .74 .60 -
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*

p < .05.

**

p < .01.

***

p < .001.

Next, we evaluated the effects of the intervention using linear mixed models that included the interaction term (i.e., intervention condition by baseline engagement) predicting bullying, victimization, perceived stress, emotional problems, and relatedness at follow-up, controlling for baseline levels of each variable and student sex. Results are reported in Table 3; intervention effect sizes, which ranged from moderate to large, were calculated as the percentage of the variance explained at each level of the model.

Table 3.

Intervention effects at follow-up

Model #1: Bullying (follow-up)
Predictor B (SE) Sig Effect size
Level 1
 Bullying (baseline) .42 (.03) p < .001 .15
 Engagement (baseline) −.15 (.03) n/a -
 Sex −.01 (.03) ns -
Level 2
 Intervention condition −.37 (.16) n/a -
 Intervention*Engagement (baseline) .09 (.04) p < .05 .37
Model #2: Victimization (follow-up)
Predictor B (SE) Sig Effect size
Level 1
 Victimization (baseline) .63 (.02) p < .001 .36
 Engagement (baseline) −.10 (.07) n/a -
 Sex .12 (.06) p < .05 -
Level 2
 Intervention condition −.76 (.33) n/a -
 Intervention*Engagement (baseline) .21 (.09) p < .05 .69
Model #3: Perceived stress (follow-up)
Predictor B (SE) Sig Effect size
Level 1
 Perceived stress (baseline) .56 (.02) p < .001 .31
 Engagement (baseline) −.15 (.05) n/a -
 Sex .18 (.04) p < .001 .01
Level 2
 Intervention condition −.80 (.23) n/a -
 Intervention*Engagement (baseline) .21 (.07) p < .01 > .99
Model #4: Emotional problems (follow-up)
Predictor B (SE) Sig Effect size
Level 1
 Emotional Problems (baseline) .56 (.02) p < .001 .30
 Sex .20 (.03) p < .001 .04
Level 2
 Intervention condition −.05 (.03) p < .05 .55
Model #5: Relatedness (follow-up)
Predictor B (SE) Sig Effect size
Level 1
 Relatedness (baseline) .54 (.03) p < .001 .24
 Sex −.13 (.04) p < .001 .01
Level 2
 Intervention condition .10 (.04) p < .05 .43
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Results indicated that the interaction terms were significant for bullying, victimization, and perceived stress, but not for emotional problems (B = .05, SE = 04, ns) or relatedness (B = −.10, SE = 06, ns). Thus, we evaluated models for these two outcomes that did not contain the interaction effect, and found that the main effect of the intervention was significant in both cases, indicating that the intervention promoted lower levels of emotional problems and higher levels of relatedness at follow-up across the sample rather than being found mainly among the marginalized students. As per recommended practice (Jaccard & Turrisi, 2003), the main effects for engagement at baseline and the intervention condition were not interpreted when the interaction effect was significant. Mirroring previous research, we found that females reported significantly higher levels of perceived stress and emotional problems. Unexpectedly, we found no gender differences in bullying, and found that girls reported greater levels of victimization and lower levels of relatedness.

The interaction effects are displayed in Figure 2 for two groups: low engagement (1 SD below the mean) and high engagement (1 SD above the mean) at baseline. The left-hand side of Figure 2 shows that low-engagement students in the intervention schools reported lower levels of bullying, victimization, and perceived stress compared to similar students in the control schools, while the right-hand side of Figure 2 shows that there were no such differences among high-engagement students. Finally, in a post-hoc analysis (discussed in more detail below), we evaluated the main effect of the intervention on bullying; it was not significant (B = −.06, SE = 04, ns).

Figure 2.

Figure 2

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Interaction effects.

Discussion

Although cooperative learning possesses robust empirical evidence supporting its ability to encourage academic motivation and achievement (Johnson et al., 2014), as well as interpersonal attraction and social acceptance (Ginsburg-Block et al., 2006; Roseth et al., 2008), it has not yet been tested as a stand-alone prevention program aimed at bullying, victimization, and related affective consequences. In this study, we found that marginalized (i.e., less engaged) students in intervention schools reported significantly lower levels of bullying, victimization, and perceived stress as compared to control schools. Interestingly, we found no significant interaction effects for emotional problems and relatedness, but did find significant main effects, suggesting that the benefits of cooperative learning in reducing emotional problems and enhancing relatedness were not found exclusively among marginalized students.

In a post-hoc exploratory analyses, we did not find a significant main effect for bullying, suggesting that, at least for our sample, the effects of cooperative learning on bullying were found mainly among the marginalized students. In other words, cooperative learning appeared to have a significant effect on the behavior of bully-victims (i.e., reactive aggression), but not necessarily on the proactive aggression of bullies. We note that the findings for victimization among marginalized students suggest that bullying was reduced quite substantially within intervention schools, so our inability to detect a main effect for bullying may be related to limitations in statistical power arising from our small sample of middle schools. Future research with a larger sample of schools could explore whether cooperative learning is, in fact, able to interrupt the process of homophily among bullies and reduce the more proactive forms of aggression in middle school.

Overall, our results suggest that increased cooperative interactions during group-based learning activities were able to significantly improve marginalized students’ experiences in school. By encouraging the development of more positive social relations among students, cooperative learning provided an avenue for socially marginalized students to escape their victimized status and, in turn, reduced their perceived stress. These results are particularly noteworthy given the stability of victimization in middle school (i.e., year-to-year stability from .37 to .52; Juvonen et al., 2000; Salmivalli, Lappalainen, & Lagerspetz, 1998). Cooperative learning also had salutary effects on the broader student population in terms of increased peer relatedness and reduced emotional problems, suggesting that the school climate was seen as more friendly and welcoming.

This research is limited in three key ways. First, it is based upon a relatively homogeneous sample of rural students that was about three-quarters White, which limits the external validity (generalizability) of the results. Second, all measures were self-report, and in some cases had lower reliability, which limits internal validity. Future research should consider additional data sources, such as teachers and/or parents, and more diverse populations. Third, the small number of schools in our sample (i.e., 15) and the small number of time points (i.e., 2) limited the complexity of the models that we were able to fit to the data, so we were unable to explore mechanisms of effects (e.g., victimization may mediate the effects of cooperative learning on perceived stress, at least among marginalized students). Future research should examine these mechanisms in more detail.

Conclusion

The results of this randomized trial extend prior research on cooperative learning by demonstrating that it not only promotes academic achievement, but also reduces bullying, victimization, and stress among marginalized students and reduces emotional problems and promotes peer relatedness across the general student population. Furthermore, the positive peer interactions that arise out of cooperative learning have previously been found to reduce deviant peer clustering and escalations in alcohol use in middle school (Van Ryzin & Roseth, 2017), suggesting that schools implementing cooperative learning may realize widespread improvements in student behavior in addition to the anticipated gains in achievement.

In addition to its efficacy in promoting achievement and addressing a range of behavioral problems in middle school, cooperative learning presents many other advantages compared to existing curriculum-based prevention programs. For example, it does not require the sacrifice of instructional time, and can be used in any subject, ensuring students receive a high “dosage” across the school day. Importantly, cooperative learning techniques can be shared among staff members, modified to fit new academic curricula and learning objectives, and taught to new teachers by existing staff, ensuring that implementation can be sustained despite teacher turnover and providing opportunities for best practices to spread within and across schools and districts. Thus, our hope is that the results reported here contribute to renewed interest in cooperative learning as a core aspect of teacher training and school culture that can support positive academic, social, and behavioral outcomes simultaneously.

Acknowledgments

The National Institute on Alcohol Abuse and Alcoholism provided financial support this project (R34AA024275-0; PI: M. J. Van Ryzin). The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of NIAAA or the National Institutes of Health.

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