







































Education, Society and Human Studies 
ISSN 2690-3679 (Print) ISSN 2690-3687 (Online) 

Vol. 3, No. 1, 2022 
www.scholink.org/ojs/index.php/eshs 

52 

Original Paper 

RULER: A Social Emotional Learning Program’s Impact on 

School Climate 
Caroline L. South1* & Nancy DeJarnette1 

1 University of Bridgeport, Bridgeport, Connecticut, USA 
* Caroline L. South, University of Bridgeport, Bridgeport, Connecticut, USA 

 

Received: January 3, 2021      Accepted: January 14, 2021      Online Published: January 22, 2022 

doi:10.22158/eshs.v3n1p52                       URL: http://dx.doi.org/10.22158/eshs.v3n1p52 

 

Abstract 

An urban public school system in the northeastern United States implemented the RULER Program, an 

evidence-based social emotional learning program, into schools in 2014. This case study investigates 

the impact of the RULER Program on school climate at one pre-K-8 school within that larger urban 

system. The study sought to determine if there are statistically significant changes in student 

suspensions, attendance, and academic achievement at that school since the initial implementation of 

the RULER Program by performing 2-proportion z tests. This study also sought to determine faculty 

and staff perceptions of school climate at the subject school by performing a descriptive analysis of 

survey data and coding interview and observation data for themes. The quantitative and qualitative 

data merge to provide a comprehensive explanation of the impact of a school wide social emotional 

learning program on school climate. 

Keywords 

social emotional learning, RULER program, emotional intelligence, emotional literacy, school climate 

 
1. Introduction 

Schools have a responsibility to address student behavioral, social, and emotional needs in order to 

better serve all students. This study provides information to school administrators regarding how a 

school wide Social Emotional Learning (SEL) program impacts teacher perceptions of school climate 

and student outcomes in one K-8 urban high-needs school. 

Decades of research on emotional intelligence has put a spotlight on SEL, which refers to the process 

of integrating thinking, feeling, and behaving in order to become aware of self and others, make 

responsible decisions, and manage one’s own behaviors and those of others (Brackett & Rivers, 2014). 

The RULER Program is based on the theory that individuals’ emotions impact life outcomes (Provini, 



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2014). Past studies from authors, Klem and Connell (2004) and Howes and Smith (1995), demonstrated 

that students in emotionally supportive classrooms reported being more engaged, chose more complex 

cognitive activities, performed better academically, and scored higher on standardized tests (Reyes, 

Brackett, Rivers, White, & Salovey, 2012). 

The program that this study explores is the RULER Approach to Social and Emotional Learning 

(RULER) (Brackett & Rivers, 2014). RULER is an acronym that represents five interrelated emotional 

literacy skills: Recognizing emotion, Understanding emotion, Labeling emotion, Expressing emotion, 

and Regulating emotion (Brackett & Rivers, 2014). RULER is an evidence-based SEL program that 

uses professional development and the incorporation of emotional literacy instruction into the 

classroom curricula to improve classroom interactions (Hagelskamp, Brackett, Rivers, & Salovey, 

2013). The program was developed by the Yale Center for Emotional Intelligence and is designed to be 

integrated into everyday teaching and learning activities (Meyer & Strambler, 2016). 

Teaching and learning in schools have strong social, emotional, and academic components (Zins, 

Weissberg, Wang, & Walberg, 2004). Typically, learning is not an independent activity undertaken by 

one person. Students learn through collaboration with teachers, peers, and families (Durlak, Weissberg, 

Dymnicki, Taylor, & Schellinger, 2011). As an integral part of how people learn, emotional processes 

must be taken into account when schools plan learning experiences for students. The diversity within 

21st-century schools makes addressing the emotional needs of students more challenging. Many 

students lack social-emotional competencies and a cycle of disengagement develops as they progress 

through elementary, middle, and high schools (Durlak et al., 2011).  

The purpose of this case study was to determine how a school wide SEL program impacted school 

climate at a high-needs urban public school by measuring faculty and staff perceptions of school 

climate as well as changes in student suspension data, attendance data, and standardized test scores at 

the PK-8 school since implementation of the RULER Program. The school, located in a large urban 

school district, implemented the RULER Program, an evidence-based social emotional learning 

program, in the 2014-2015 school year, as part of a district wide initiative. A positive school climate, a 

decrease in disruptive student behaviors, and improved academic achievement are desired outcomes of 

the RULER program. In this study, faculty and staff perceptions of a positive school climate, a decrease 

in disruptive behaviors as measured by student suspensions, a decrease in student chronic absenteeism, 

and a decrease in students scoring at the lowest level on the Smarter Balanced math assessment would 

be indications that RULER had positively impacted school climate and student outcomes. The results 

of this study inform school leaders and educators of the impact a school wide SEL program can have on 

school climate and student outcomes.  

The central research question guiding this study was, “How does the presence of a school wide SEL 

program impact school climate?” More specific research questions included: 

Quantitative 



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1) Has there been a statistically significant change in disruptive student behavior, as measured by 

percentage of suspensions, at the subject school since implementation of the RULER Program? 

2) Has there been a statistically significant change in student attendance, as measured by the 

percentage of chronically absent students, at the subject school since implementation of the RULER 

Program? 

3) Has there been a statistically significant change in percentage of students scoring at Level 1 on 

the Smarter Balanced math assessment at the subject school since implementation of the RULER 

Program? 

4) Do faculty and staff perceive a positive school climate at the subject school three years after the 

implementation of the RULER Program, as measured by the “Panorama Staff Survey”? 

Qualitative 

1) What are teacher perceptions of school climate as measured by the semi-structured interview data 

and observation data? 

The subject school’s school system partnered with Yale University in 2014 to launch the RULER 

Program district-wide to “support the social and emotional well-being of students and district staff” 

(Meyer & Strambler, 2016, p. 2). A 2016 Yale University report to the community stated that students 

in this school system reported more self-control, had higher grades, fewer absences, were less likely to 

be suspended or expelled. Those who reported more student-teacher trust also had higher grades and 

were less likely to be suspended or expelled (Meyer & Strambler, 2016). 

The theoretical framework that guides this study relies on three theories: Positive youth development 

theory, ecological systems theory, and self-determination theory. Environment is a critical factor in 

education. Positive youth development theory maintains that the needs of youth will be met by creating 

environments that promote outcomes like student achievement and positive relationships (Brackett & 

Rivers, 2014). SEL programs emphasize positive learning environments, school climates, and 

relationship-building. SEL is grounded in positive youth development theory and accepts the notion 

that youth will essentially adapt to the environment around them. For this same reason, RULER is a 

program that focuses on the development of supportive and safe environments.  

In addition to positive youth development theory, RULER draws upon Urie Broffenbrenner’s 

ecological systems theory, which states that the setting in which youth exist shapes their development, 

and self-determination theory, which states that “youth are more likely to flourish when in settings that 

address their social and emotional needs” (Brackett & Rivers, 2014, p. 6). According to ecological 

systems theory, human development and behavior should be studied through a multi contextual 

approach, which recognizes that individuals participate in multiple social contexts at the same time as 

well as enter and exit different contexts throughout their lives (Kirk, 2009, p. 482). Broffenbrenner 

(1986) stated that in order to understand a child, the child’s environment must be investigated (Burns, 

Warmbold-Brann, & Zaslofsky, 2015). The social-emotional climate of a classroom refers to the 



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relationships between and among students and teachers as “demonstrated by supportive and caring 

interactions, positive feelings, a shared sense of cohesion and respect, and teachers’ sensitivity to 

student needs” (Hagelskamp, Brackett, Rivers, & Salovey, 2013, p. 2). The “success of any attempt to 

educate the whole child is dependent upon the extent to which learning occurs in caring, supportive, 

safe, and empowering settings” (Brackett & Rivers, 2014, p. 6).  

 

2. Method 

2.1 Participants 

An urban public school system in the northeastern United States implemented the RULER Program, an 

evidence-based social emotional learning program, into schools in 2014. This convergent parallel 

mixed methods case study investigates the impact of the RULER SEL Program on school climate at 

one PK-8 school within a large urban district. 

The participants included in the suspension data and student attendance data are from the collective 

student body at the subject school, kindergarten through grade 8. The 2014-2015 school year was 

representative of all of the years before the RULER program was implemented and the 2017-2018 

school year was representative of all of the years after the program was implemented. The total student 

population in 2014-2015 was 562 (N=562) and the total student population in 2017-2018 was 549 

(N=549). The participants included in the standardized test score data included only students in grades 

3, 5, 6, and 7. Fourteen (N=14) school staff and faculty participated in the “Panorama Staff Survey” 

(Panorama Education, 2018). All of these participants were certified faculty members, such as teachers, 

although the opportunity was presented to all staff and faculty, including non-certified staff such as 

paraprofessionals, office staff, and security. Six (N=6) classroom teachers participated in the classroom 

observations and 5 (N=5) of those classroom teachers participated in interviews. 

2.2 Quantitative Data Collection and Analysis 

The quantitative strand of this study includes four data sources: Suspension data, student attendance 

data, Smarter Balanced math assessment scores, and survey data. The year 2014-2015 represents the 

pre-implementation population that had no school wide SEL program, and the year 2017-2018 

represents the post-implementation population that did have a school wide SEL program. The third year 

of implementation, as opposed to the first year of implementation, was selected because the RULER 

Program is meant to be embedded in the school curricula and there may be an adjustment period for 

staff and students, thus the data better illustrates the long-term effects of the RULER Program.  

The student suspension data was analyzed using a 2 proportion z test to demonstrate if the two 

populations differ significantly on a single characteristic (suspensions). Since the 2014-2015 group and 

the 2017-2018 group are similar in composition and size, this test is appropriate. Statistical significance 

was set at .01. 

 



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Discipline data has been used as a measure of the effects of reform efforts in schools to combat 

negative student behaviors and has been determined to be a valid and reliable measurement of student 

behavior (Sugai, Sprague, Horner, & Walker, 2000; Anderson, 2009; Barkley, 2013). Further, student 

behaviors are an indicator of school climate: Negative student behaviors reflect poor school climates 

and positive student behaviors reflect positive school climates (Story, 2010). Thus, student suspension 

data is an appropriate measure. 

The second dataset used in the quantitative phase of this study is student attendance data. The data was 

organized into a table showing the proportion of students who were chronically absent in the 

2014-2015 and 2017-2018 school years. The student attendance data was analyzed using a 2 proportion 

z test to demonstrate if the two populations differ significantly on a single characteristic (chronic 

absenteeism). Statistical significance was set at .01.  

The third dataset used in the quantitative phase of this study is the Smarter Balanced Assessment. Math 

scores were analyzed by grade level in the 2014-2015 and the 2017-2018 school years. The only grade 

levels that were analyzed were grades 3, 5, 6 and 7. Only scores from the math portion of the Smarter 

Balanced Assessment were used. All grades had a 100% participation rate in the 2014-2015 and 

2017-2018 school years. The data was organized into a table showing the number of students in grades 

3, 5, 6, and 7 who scored Level 1 (Not Met) on the standardized test.  

A 2 proportion z test was used to determine if the 2014-2015 data and the 2017-2018 data differ 

significantly on the number of students scoring Level 1 (Not Met) on the math portion of the Smarter 

Balanced Assessment. The researcher measured students scoring Level 1 (Not Met) instead of those 

scoring Level 2 (Approaching), Level 3 (Met), or Level 4 (Exceeded) because the data required to 

perform a statistical analysis on these other levels is not available due to the suppression of data for 

student confidentiality. Statistical significance was set at .01.  

The fourth form of quantitative data was the results of the “Panorama Staff Survey” (Panorama 

Education, 2018). A link to an electronic version of the survey was made available to all school staff 

and faculty. The surveys provide ordinal data which was converted to numerical data that was 

organized into a frequency table. Descriptive analysis was conducted to determine the mean, median, 

mode, and standard deviation. These procedures have been used and been found effective in analyzing 

survey data (Barkley, 2013). The measures of central tendency are important to give an overview of the 

survey results. The mean score for each item identifies specific items that have scored very high or very 

low. This indicates that as a group, the teachers feel school climate is strong or poor.  

Determining the Standard Deviation (SD) of each item indicates how much teachers agreed on each 

item. A SD of .50 or lower implies that most teachers agreed on an item; a higher SD suggests that 

teachers varied in their responses to a particular item and that the item could be an area in which 

teachers have conflicting views (Gruenert & Whitaker, 2015). The results are presented. 

 



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Considering the small number of participants in this survey, a descriptive analysis of data to determine 

the mean, median, mode, and standard deviation of each survey item number is provided as opposed to 

inferential analysis. To begin analysis, the survey’s ordinal scale was converted to its numerical 

equivalent. The more positive responses are reflected in higher, positive numbers; the more negative 

responses are reflected in lower or negative numbers.  

The measures of central tendency are important to give an overview of the survey results. The mean 

score for each item identifies specific items that have scored very high or very low. This indicates 

which survey items teachers feel strongly about. Statistical significance was set at .05. A standard 

deviation of .50 or lower indicates that most teachers agreed about an item; a higher standard deviation 

would suggest that teachers varied in their responses to a particular item and that the item could be an 

area in which teachers have conflicting views (Gruenert & Whitaker, 2015). 

2.3 Qualitative Data Collection and Analysis 

The qualitative strand of this study includes two data sources: Classroom observations and 

semi-structured interviews. The purpose of classroom observations was to collect data about teacher 

implementation of RULER in the classroom. To analyze both the classroom observation data and the 

semi-structured interview data, the researcher followed Creswell’s (2012) steps in the process of 

analyzing and interpreting qualitative data. This process included conducting a preliminary analysis of 

the data by reading through it to obtain a general sense of the data, playing back the recorded 

interviews, transcribing the interviews, and reviewing all field notes and memos. 

The qualitative research question focused on teacher perceptions of school climate at the subject school. 

Instrumentation to measure perceptions of school climate included semi-structured teacher interviews 

and classroom observations. Of the six classroom teachers who were observed, five participated in 

interviews.  

After initial coding of the interview data, twenty-five initial codes emerged. After reviewing these 

initial codes, the researcher was able to identify relationships among the codes and pare down to twenty 

axial codes, five of which are main concepts.  

Field notes collected from the classroom observations included descriptive and reflective notes 

focusing on the implementation of RULER and the overall climate of the observed classrooms. The 

researcher utilized a coding process to analyze the data and was able to identify relationships among 

the codes and pare down to fourteen axial codes, four of which were main analytical concepts. 

 

3. Result 

3.1 Quantitative Data Collection and Analysis 

The results of the 2 proportion z tests to determine if the 2014-2015 data and the 2017-2018 data differ 

significantly on student suspensions as seen in Table 1. A 2 proportion z test indicated that there was a 

statistically significant positive change in suspensions since the RULER Program was implemented. 



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Table 1. Students with at Least One Suspension in the Academic Year 

Academic Year At Least One Suspension No Suspension Total Student Enrollment 

2014-2015 122 440 562 

2017-2018 73 476 549 

 

A 2 proportion z test indicated that the proportion of students chronically absent from school differed 

significantly before and after implementation of the RULER program as seen in Table 2. The 

percentage of students who were chronically absent from school was higher before implementation of 

the RULER program. 

 

Table 2. Students Chronically Absent from School 

Academic Year Chronically Absent Not Chronically Absent Total Enrollment 

2014-2015 140.5 421.5 562 

2017-2018 88.94 460.06 549 

 

The results of the 2 proportion z tests on the Smarter Balanced math assessment data are displayed in 

Table 3. The z-score was for Grade 3 was 2.77 and the p-value was 0.003. This is significant at.01 so 

there is evidence that the percentage of students scoring at Level 1 was higher before the 

implementation of the program. The z-score was for Grade 5 was 0.053 and the p-value was 0.48. This 

is not significant at .01 so there is no evidence that percentage of students scoring at Level 1 was higher 

before the implementation of the program. The z-score was for Grade 6 was 2.11 and the p-value was 

0.017. This is significant at .01 so there is evidence that percentage of students scoring at Level 1 was 

higher before the implementation of the program. The z-score was for Grade 7 was 0.785 and the 

p-value was 0.22. This is not significant at .01 so there is no evidence that percentage of students 

scoring at Level 1 was higher before the implementation of the program. 

 

Table 3. Smarter Balanced Math Assessment 2 Proportion Z Test Results 

Grade Level Z Score P Value Significant 

3 2.77 0.003 Yes 

5 0.053 0.480 No 

6 2.11 0.017 Yes 

7 0.785 0.220 No 

p value = 0.01 

 

 

 



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Evidence that the percentage of students scoring at Level 1 was higher before implementation indicates 

that a statistically significant number of students were scoring lower on the Smarter Balanced math 

assessment prior to implementation of the RULER Program. Grades 3 and 6 do demonstrate that the 

percentage of students scoring at Level 1 was higher before the implementation of the program but 

grades 5 and 7 fail to provide evidence of the same. The results of these tests, therefore, do not 

consistently demonstrate that the percentage of students scoring at Level 1 was higher before the 

implementation across the grade levels presented.  

Based on the results of the “Panorama Staff Survey”, particularly the preponderance of high means 

indicating favorable responses, the researcher concludes that faculty and staff perceive a positive 

school climate at the subject school, three years after implementation of the RULER Program. Results 

of the survey are shown in Table 4. 

 

Table 4. Panorama Staff Survey Descriptive Statistics (N=14) 

Question Mean Median Mode Standard Deviation 

1. On most days, how enthusiastic are 

the students about being at school? 

3.93 4.00 4.00 1.00 

2. To what extent are staff trusted to 

work in the way they think is best? 

4.36 4.00 4.00 .50 

3. How positive are the attitudes of your 

colleagues? 

3.64 4.00 4.00 .74 

4. How supportive are students in their 

interactions with each other? 

3.57 4.00 4.00 .51 

5. How respectful are the relationships 

between staff and students? 

3.93 4.00 4.00 .62 

6. How optimistic are you that your 

school will improve in the future? 

4.50 4.50 4.00 and 

5.00 

.52 

7. How often do you see students 

helping each other without being 

prompted? 

3.86 4.00 4.00 .53 

8. When new initiatives are presented at 

your school, how supportive are your 

colleagues? 

3.79 4.00 4.00 .43 

9. Overall, how positive is the working 

environment at your school? 

4.29 4.00 4.00 .47 

Note: Response anchors: 1-Not at all, 2-Slightly, 3-Somewhat, 4-Quite, 5-Extremely. 

 



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3.2 Qualitative Data Analysis and Results 

When the interview and observation data were analyzed together, the main analytical concepts of 

relationships, shared vision, belief in social emotional education, school leadership, and 

student-centered outcomes emerged, as seen in Table 5. 

 

Table 5. Combined Interview and Observation Thematic Table 

Main Analytical Concepts Interview Subcategories Observation Subcategories 

Relationships Environment 

Building Trust 

Safety 

Positive student-teacher interactions  

Promoting community 

Positive reinforcement 

Calming music 

On-task behaviors 

Clear routines and structured environment 

Shared Vision Fidelity of Implementation 

Putting Children First 

Ongoing Process 

Fidelity of Implementation: Elements of 

RULER present in classrooms 

Belief in Social Emotional 

Education 

Positive Behavior Interventions and 

Supports 

Faculty and Staff Buy-In 

Incorporation of Other SEL Programs 

PBIS used as positive reinforcement 

PBIS used as punitive threat 

School Leadership High Expectations of Administrators 

Support of Administrators 

Administrators’ Belief in Program 

 

Student-Centered Outcomes Student self-advocacy and 

self-awareness 

Improved student behaviors 

Student and faculty emotion 

management 

Productive student-student interactions 

 

The only main analytical concept that was not present in both datasets was that of school leadership. 

School leadership must be included as a main analytical concept because of its prominence in the 

interview data as a factor contributing to school climate. In all of the interviews, the topic of leadership 

emerged and the perception among all of the participants was that the strong leadership at the subject 



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school has had a profound and positive impact on school climate. The fact that school leadership did 

not emerge as a main analytical theme in the observation data makes sense because the researcher was 

observing everyday classroom routines and lessons where the administrator was not present. 

 

4. Discussion 

Marzano, Waters, and McNulty (2005) found that the overall climate of a school and the climate of 

individual classrooms can have a positive or negative influence on a school’s effectiveness and 

ultimately student performance. The results of this study demonstrate that the presence of a school wide 

Social Emotional Learning (SEL) program has impacted school climate positively as evidenced by a 

decrease in student suspensions, a decrease in chronic absenteeism among students, staff and faculty 

positive responses on the “Panorama Staff Survey”, and the emergence of the main analytical themes of 

relationships, shared vision, belief in social emotional education, school leadership, and 

student-centered outcomes from the qualitative data. 

Based on the results of the suspension data analysis, the chronic absenteeism data analysis, the survey 

data analysis, and the interview and observation data analyses, the researcher concluded that the 

presence of a school wide SEL program impacts school climate by decreasing disruptive student 

behaviors, decreasing chronic absenteeism, and improving faculty and staff perceptions of school 

climate. Overall, the presence of a school wide SEL program improved school climate at the subject 

school.  

The survey and interview data demonstrated that faculty and staff perceived implementation of the 

RULER program and strong school leadership to be two significant factors that have resulted in a 

positive school climate. The elements of this positive climate are strong and meaningful relationships 

among staff and students, a shared vision for the school, the belief that faculty and staff have in social 

emotional education, and the focus on student-centered outcomes. Outcomes of the climate are 

improved student behavior, improved student attendance, and positive faculty and staff perceptions of 

school climate. 

This study provides school leaders with evidence that SEL programs do impact student outcomes and 

school climate. It also provides evidence that the programming that school leaders select needs to be 

supported by strong building administrators and that purchasing a program is not enough. Faculty and 

staff need to be trained and supported in their daily implementation of the program and best practices in 

school leadership need to be continued (Hill, Palmer, Klein, Howell, & Pelletier, 2010).  

The results of this study support the use of the RULER Program because of its impact at the subject 

school. School leaders must select programming based on the needs of the individual school and select 

one which can be integrated into the day to day functions. Purchasing a SEL program is not sufficient. 

School leaders need to make the SEL program an ingrained part of the school in order to see results 

(Brackett & Rivers, 2014). 



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Schools need to be a place in which students feel safe, both physically and emotionally. Continued 

research on school climate and SEL programming will help us better understand how to create 

environments in which students feel safe and in which students can find the most success. 

 

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