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The impact of the mindful method Youth Empowerment Seminar (YES!) on students' self-efficacy, self-regulation, and academic performance for becoming college- and career-ready

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The impact of the mindful method Youth Empowerment Seminar (YES!) on students' self-efficacy, self-regulation, and academic performance for becoming college- and career-ready

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Content Running head: IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING 1

THE IMPACT OF THE MINDFUL METHOD YOUTH EMPOWERMENT SEMINAR (YES!)
ON STUDENTS’ SELF-EFFICACY, SELF-REGULATION, AND ACADEMIC
PERFORMANCE FOR BECOMING COLLEGE-AND CAREER-READY

by

Jeffrey Mark Knepper

A Dissertation Presented to the
FACULTY OF THE USC ROSSIER SCHOOL OF EDUCATION
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF EDUCATION

August 2015

Copyright 2015 Jeffrey Mark Knepper

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
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Acknowledgements

This study would not have been conceived or executed without the care, knowledge and
selfless offerings of many individuals. First I would like to acknowledge my family whose
inspiration and supportive love allowed this opportunity to manifest and come to fruition.
Secondly I want to acknowledge with deep gratitude His Holiness Sri Sri Ravi Shankar, whose
teachings and undying commitment to offer every individual the opportunity for a stress-free and
violence-free life, inspired and guided this study. Next my dissertation chair, Dr. Patricia Tobey,
whose masterful guidance and selfless sense of service to others, skillfully imparted her
knowledge and wisdom that inspired and nurtured me through this process which at times
seemed unfathomable. To my dissertation co-chair, Dr. Patrick Crispen, for his knowledge and
always welcomed sense of humor that helped lighten the load towards my study and Education
Doctoral success. I especially want to acknowledge and thank, Dr. James Gaskin, for voluntarily
providing the most practical tools on how to conduct a Structural Equation Model analysis.
Lastly I want to acknowledge the USC Rossier Staff and Faculty, specifically Dr. Hortensia
Amaro and Dr. David Black for offering their expertise in the field of mindfulness, as well as
fellow Educational Doctoral students of USC all for their continued support and encouragement
along this educational adventure for being an agent of change in the field of education.

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
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Table of Contents
Acknowledgements 2

List of Tables 5

List of Figures 6

Abstract 8

Chapter One: Overview of the Study 9

Background of the Problem 10

Statement of the Problem 14

Purpose of the Study 19

Significance of the Study 24

Limitations and Delimitations 24

Definition of Terms 27

Organization of the Study 32

Chapter Two: Literature Review 34

Mindfulness 39

Origin of Mindfulness 39

Application of Mindfulness in the West 41

Conceptualizing Mindfulness 43

Neuroscience Research on Mindfulness 45

Mindfulness Applied to Education 48

Mindfulness and Self-Regulation for Learning 50

Future Mindfulness Research Needed 55

Conceptualizing Self-Regulation 55

Social Cognitive Theory of Self-Regulation 56

Effects of Poor Management in Self-Regulation 66

Summary and Conclusion 68

Chapter Three: Methodology 71

Sample and Population 76

Instrumentation 79

Existing Data 79

Performance Data 79

Pre- and Post-Surveys 80

Data Collection 85

Collection of Pre-existing Data 86

Collection of Student Performance Data 86

Collecting the Pre-, Post-, and Follow-up Survey Data 86

Data Analysis 87

Chapter Four: Results 90

Descriptive Statistics & Demographic Variables 91

Analysis of Statistical Consistency 93

Mindfulness Reliability 93

Short Self-Regulation Questionnaire Reliability 94

Self-Efficacy Reliability 95

Analysis of Research Questions 96

Research Question 1 96

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
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Research Question 1a 101

Research Question 1b 104

Research Question 2 107

Research Question 2a 112

Research Question 2b 116

Research Question 3 121

Structural Equation Modeling 121

Preliminary Model 125

Exploratory Factor Analysis 129

EFA Model Revision 132

Confirmatory Factor Analysis 134

Structural Equation Model 138

Qualitative Results 141

Analysis of Open-Ended Questions 146

Self-Reported Focus in the Classroom 146

Self-Reported Goals Setting in the Classroom 148

Self-Reported Confidence in the Classroom 150

Self-Reported Learning in the Classroom 151

Summary 154

Chapter Five: Discussion 155

Summary of Findings 160

Research Question 1 161

Research Question 1a 162

Research Question 1b 164

Research Question 2 165

Research Question 2a 166

Research Question 2b 167

Research Question 3 168

Limitations 171

Implications for Practice 172

Recommendations for Research 174

Conclusions 177

References 180

Appendix A: Mindful Attention and Awareness Scale (MAAS) 202

Appendix B: Short Self-Regulation Questionnaire (SSRQ) 203

Appendix C: Self Efficacy Questionnaire (SE) 204

Appendix D: Pre, Post, and Follow-up Survey 206

Appendix E: Survey’s Open-Ended Questions. 212

Appendix F: Pearson’s Product Moment Correlation 213

Appendix G: USC IRB Approval Notice for Expedited Review 214

Appendix H: USC IRB Youth Assent-Parental-Permission Consent Form (English) 216

Appendix I: USC IRB Youth Assent-Parental-Permission Consent Form (Spanish) 219

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
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List of Tables
Table 1: Grouping Descriptive by Grade 91

Table 2: Mindfulness Pairwise Comparisons for Treatment group with
Bonferonni Adjustment 99

Table 3: Self-Regulation Pairwise Comparisons for Treatment group with
Bonferonni Adjustment 102

Table 4: Self-Efficacy Pairwise Comparisons for Treatment group with
Bonferonni Adjustment 105

Table 5: Mindfulness & Self-Regulation Pairwise Comparisons with
Bonferonni Adjustment 110

Table 6: Descriptive Statistics for Research Question 2 110

Table 7: Mindfulness & Self-Efficacy Pairwise Comparisons with
Bonferonni Adjustment 114

Table 8: Descriptive Statistics for Research Question 2a 115

Table 9: Mindfulness & GPA Pairwise Comparisons with Bonferonni Adjustment 119

Table 10: Descriptive Statistics for Research Question 2b 119

Table 11: Model Fit Metrics for CFA 135

Table 12: Convergent and Discriminant Validity 136

Table 13: Mediation Values for Structural Equation Model (SEM) 140

Table 14: Model Fit Metrics for Structural Equation Model 141

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
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List of Figures
Figure 1: Foundational Structural Equation Model Hypothesis 88

Figure 2: ANOVA Analysis Control Group Profile plot for MAAS Estimated Marginal Means
Over Three Different Time Periods (Pre, Post, Follow-Up) 100

Figure 3: ANOVA Analysis Treatment Group Profile Plot for MAAS Estimated Marginal
Means Over Three Different Time Periods (Pre, Post, Follow-Up) 100

Figure 4: ANOVA Analysis Control Group Profile Plot for SSRQ Estimated Marginal
Means Over Three Different Time Periods (Pre, Post, Follow-Up) 103

Figure 5: ANOVA Analysis Treatment Group Profile Plot for SSRQ Estimated Marginal
Means Over Three Different Time Periods (Pre, Post, Follow-Up) 103

Figure 6: ANOVA Analysis Control Group Profile plot for SE Estimated Marginal
Means Over Three Different Time Periods (Pre, Post, Follow-Up) 106

Figure 7: ANOVA Analysis Treatment Group Profile Plot for SE Estimated Marginal
Means Over Three Different Time Periods (Pre, Post, Follow-Up) 106

Figure 8: MANCOVA Analysis Profile Plot for MAAS Estimated Marginal Means
Over Two Different Time Periods (Post, Follow-Up) 111

Figure 9: MANCOVA Analysis Profile plot for SSRQ Estimated Marginal Means
Over Two Different Time Periods (Post, Follow-Up) 111

Figure 10: MANCOVA Analysis Profile Plot for MAAS Estimated Marginal Means
Over Two Different Time Periods (Post, Follow-Up) 115

Figure 11: MANCOVA Analysis Profile Plot For SE Estimated Marginal Means
Over Two Different Time Periods (Post, Follow-Up) 116

Figure 12: MANCOVA Analysis Profile Plot For MAAS Estimated Marginal Means
Over Two Different Time Periods (Post, Follow-Up) 120

Figure 13: MANCOVA Analysis Profile Plot For GPA Estimated Marginal Means
Over Two Different Time Periods (Post, Follow-Up) 120

Figure 14: The Mindfulness Conceptual Relationship in its Most Basic Form 126

Figure 15: The Mindfulness Conceptual Relationship with Disturbance and Error Added 127

Figure 16: Preliminary Hypothesized model used for Exploratory Factor Analysis 129

Figure 17: Revised Hypothesized Model Used for Exploratory Factor Analysis 132

Figure 18: Revised Confirmatory Factor Analysis 137

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
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Figure 19: Structural Equation Model 138

Figure 20: Control and Treatment group bar chart for Question 56 143

Figure 21: Control and Treatment Group Bar Chart for Question 57 144

Figure 22: Control and Treatment Group Bar Chart for Question 58 144

Figure 23: Control and Treatment Group Bar Chart For Question 59 145

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
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Abstract
Because self-regulation has been documented as the main cause of K-12 students’ lack of college
and career readiness, mindfulness interventions that augment self-regulation, self-efficacy and
academic performance may offer support. This study evaluated the effects of the Youth
Empowerment Seminar (YES!), a biophysical workshop for adolescents that teaches breathing
practices, meditation and other mindful practices to regulate stress, emotions, and attentional
focus on self-regulation, self-efficacy and academic performance. Approximately 339 Middle
school students (11-14 years of age) in the United States participated in YES! during their
physical education classes and continued weekly follow-ups over a two month period. Students
in a control group attended their usual curriculum and were tested in parallel. ANOVA and
MANCOVA analysis was used to determine significant growth in the variables. The causal role
of YES! on students’ self-efficacy, self-regulation, and academic performance was studied using
path analysis procedures. Additionally four open-ended questions were used to gather rich data
for explaining the phenomena. ANOVA analysis determined that the YES! program had a
significant impact on mindfulness and self-regulation from post to 1-month follow-up after
appropriate cultivation of mindfulness. A SEM causal path best-fit analysis found a direct effect
of mindfulness on academic performance was significant only when the mediators, self-
regulation and self-efficacy, are absent but when the mediators are present the direct effect
becomes insignificant and the indirect effect from mindfulness through the mediators to
academic performance becomes significant. The results suggest that YES! can promote
mindfulness, self-regulation, self-efficacy, and academic performance that increased directly
with longevity of practices and subsequent increased cultivation of mindfulness.

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
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CHAPTER ONE: OVERVIEW OF THE STUDY
The United States has adopted a national goal of being college- and career-ready by
2020 with the hopes of regaining its status as the world leader in college completion rate. The
United States led the world in college completion rate 50 years ago. Many research based
hypotheses have been generated to offer solutions for equipping our high school graduates to be
college- and career-ready with the abilities to apply key thinking and academic skills to a highly
evolved pupil-teacher relationship that highlights engagement, independent work, motivation,
and intellectual development (Conley, 2007; NRC, 2002; Roderick, Nagaoka, & Coca, 2009).
Conley (2007, 2008) has effectively managed to comprehensively capture the essence of college
readiness by distilling down the differing hypothesis into four facets: key cognitive strategies,
academic knowledge and skills, academic behaviors, and contextual skills and awareness.
Poor self-regulation has been documented as the main cause of K-12 students’ lack of
school readiness (Blair & Diamond, 2008). Consequently, the key facet that weaves throughout
the other three and hence holds foundational college readiness importance was academic
behavior. Conley (2008) posited “academic behaviors reflect a range of behaviors that reflect
greater student self-awareness, self-monitoring, and self-control of series of processes and
behaviors necessary for academic success.” (p. 16). Conley (2007) and Ritchhart (2002) stated
to acquire these skilled academic behaviors reside in the ability of an individual’s intellectual
character to self-regulate their own learning. Moreover self-regulatory factors have been found
to contribute independently to students’ academic attainment (Bandura et al., 1992).
Hence the key to obtaining our country’s college- and career-ready educational goal by
2020 lays in our students’ ability to self-regulate their own learning. However, one of the most
perplexing problems in education was how to effectively teach self-regulation skills and most
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
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importantly how to foster self-efficacy within the student to pursue self-regulation. This study
proposes that the answer to this paradox lie with the ancient practices for developing
mindfulness. Once mindfulness in a student has been cultivated, established and preserved, then
self-efficacy and the sub functions of self-regulation are activated, engaged, and maintained
within the student, which can be facilitated and developed further by the educator. The student’s
newfound ability to self-regulate their own learning due to cultivated mindfulness may provide
the essential foundation for achieving college- and career-readiness. This study explored the
impact of mindfulness on students’ self-efficacy and subsequent ability to self-regulate, and
academic performance to become college- and career-ready.
Background of the Problem
Led by President Barack Obama, the United States has adopted a national goal of being
college- and career-ready by 2020 with the hopes of the United States regaining its status as first
in the world for college completion (Foley et al., 2013). The Department of Education has
spearheaded this goal by granting 34 states and the District of Columbia waivers from the federal
education program, No Child Left Behind (NCLB), in exchange for adopting the college- and
career-ready standards, Common Core (U.S. Department of Education, 2013). Additionally,
forty-six states will vie for Department of Education funding through a program called ‘Race to
the Top’ that requires adoption of the Common Core State Standards in 2014-15, which are
designed for preparing college- and career-ready students (Foley et al., 2013). Subsequently,
congress has supported this national goal by passing the College Access Challenge Grant
Program with the intent to increase the number of low-income students who are ready for
college.
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
11

Nonetheless the current reality of our country producing college- and career-ready youth
is grave. In 2006 the Gates Foundation commissioned a report conducted by Civic Enterprises
and Hart Research Associated entitled, ‘The Silent Epidemic; Perspectives of High School
Dropouts’ (Bridgeland, Dilulio, & Morison, 2006). In this report 69% of the 470 dropouts from
around the country stated that schools did not motivate them to work hard because classes were
boring and not relevant to their lives or career aspirations. As a result one of the leading causes
for students’ dropping out was feeling unmotivated and disengaged from high school, even
though 70% of the dropouts were confident they could have graduated if they had tried. Another
research study conducted by the National Research Council (2004) confirmed a similar weakness
in student motivation when upwards to 40% of high school students were disengaged from
learning, were inattentive, exerted little effort on schoolwork, and reported being bored in
school.
The lack of college-readiness was demonstrated by 41% of college students enrolled from
2005-2011 not finishing and obtaining a bachelor’s degree (National Center for Education
Statistics [NCES], 2013). In October 2012, 41.4% of the nation’s 16- to 24- year-olds were not
enrolled in high school or college. These alarming statistic point not only to ill prepared college-
ready youth, but also reflect the lack of career-readiness among high school dropouts. This lack
of career-readiness has been reflected with an unemployment rate of 30.1% for 16- to 19- year-
olds not enrolled in school (U.S Department of Labor, 2013).
These poor educational performance statistics places the United States 19
th
out of the 23
countries in the Organisation for Economic Co-operation and Development (OECD) in regards
to tertiary completion rates (Organisation for Economic Co-operation and Development
[OECD], 2013). This completion rate gap is one of the most vexing problems in education
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
12

today, considering the United States led the world in tertiary completion rates just 40 years ago
(Roderick et al., 2009).
Consequently, the United States Department of Education -- since taking on this major
six-year goal -- has defined the crux of the completion rate gap problem to lie with high school
students not being college- and career-ready. The U.S. Department of Education (2013) defines
college- and career-ready graduation requirements as “minimum high school graduation
expectations (e.g., completion of a minimum course of study, content mastery, proficiency on
college- and career-ready assessments, etc.) that include rigorous, robust, and well-rounded
curriculum aligned with college- and career-ready that cover a wide range of academic and
technical knowledge and skills to ensure that students leave high school ready for college and
careers.” (p. 1)
Many research based hypotheses have been generated to offer solutions for equipping our
high school graduates to be college- and career-ready with the abilities to apply key thinking and
academic skills to a highly evolved pupil-teacher relationship that highlights engagement,
independent work, motivation, and intellectual development (Conley, 2007; NRC, 2002;
Roderick et al., 2009). Conley (2007, 2008) has effectively managed to comprehensively
capture the essence of college-readiness by distilling down the differing hypothesis into four
facets: key cognitive strategies, academic knowledge and skills, academic behaviors, and
contextual skills and awareness.
Poor self-regulation has been documented as the main cause of K-12 students’ lack of
school readiness (Blair & Diamond, 2008). Moreover the need for self-regulation is paramount,
as self-regulation has been found to independently effect academic attainment (Bandura et al.,
1992). Consequently, the key facets that weave throughout the other three and hence hold
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
13

foundational college-readiness importance are academic behaviors which self-regulation is part
of. Academic behaviors are necessary for academic success and reflect greater student self-
awareness, self-monitoring, and self-control Conley (2008). Therefore, these skilled behaviors
reside in the ability of an individual’s intellectual character to self-regulate their own learning
(Conley, 2007; Ritchhart, 2002).
American educational leaders since the founding of our country have stressed the
importance of self-regulation as an individual’s ability to assume personal responsibility and
control of their own acquisition of knowledge and skill, considering one of education’s major
functions was the development of life-long learning skills (Zimmerman, 1990, 2002). Benjamin
Franklin applied self-regulation of learning when he taught himself to write by setting learning
goals and modeling, claiming the process improved his arrangement of thoughts. Contemporary
national leaders have reaffirmed the importance of personal initiative, an aspect of self-
regulation, such as Gardner (1963), former Secretary of Health, Education, and Welfare, who
suggested that “the ultimate goal of the education system is shift to the individual the burden of
pursuing his own education” (Zimmerman, 1990, p21). And former U.S. Secretary of Education
from 1981 to 1985, Terrel H. Bell (2014), stated “there are three things to emphasize in teaching:
The first is motivation, the second is motivation, and the third is (you guessed it) motivation."
(para. 1).
Today in education the significance of effective self-regulation for producing academic
success is emphasized as a foundational core element. For example, Lounsbury, Fisher, Levy,
and Welsh (2009) found that self-regulation was among the character strengths most associated
with academic achievement in college students. According to Lassiter (2011), one of the most
powerful habits of a college-ready and self-regulating student is the metacognitive ability to
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
14

effectively analyze what he or she has to do and to do it automatically. Conversely, poor self-
regulation has been documented as the main cause for K-12 students’ lack of school readiness
(Blair & Diamond, 2008). Lastly Bandura et al. (1992) found that self-regulatory factors
independently affect academic attainment.
Hence the key to obtaining our country’s college- and career-ready educational goal by
2020 lays in our students’ ability to self-regulate their own learning. However, one of the oldest
and most perplexing problems in education is how to teach independent self-regulation within
the student. The key teachings that inspire a student to self-regulate are truly a mystery. This
study hoped to show how developing the ancient art of mindfulness enhanced self-efficacy and
self-regulation. And once mindfulness in a student has been established and maintained, then sub
functions of self-regulation are sparked within the student that can be facilitated and developed
by the educator. The student’s newfound ability to self-regulate their own learning due to
developed mindfulness may provide the essential foundation for achieving college- and career-
readiness. This study explored the benefits of mindfulness on students’ self-efficacy and
subsequent ability to self-regulate learning and achieves college- and career-readiness.
Statement of the Problem
The United States has established a goal to move from 18th to 1st in the world for college
completion rates by 2020 (Foley et al., 2013). This goal requires immense changes in education,
not only with the system but also teachers and most importantly our students. But, can our
students accomplish this? Do they have the self-efficacy or belief in themselves and the ability
to self-regulate and think about how they learn, considering self-regulatory factors are essential
to obtain academic achievement (Bandura et al., 1992). Moreover poor self-regulation has been
documented as the main cause of K-12 students’ lack of school readiness (Blair & Diamond,
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
15

2008). Therefore the challenge becomes how do schools activate and engage self-efficacy and
self-regulation for learning in our students? This study posited a solution for rekindling self-
regulation, self-efficacy, and subsequently academic performance that is as old as humankind
itself? A solution that has proven to ignite the natural ability to observe one’s own mind and
emotions without reacting impulsively but with greater capacity to see relationships between
thoughts, feelings, and actions. This solution can enable one to dispassionately discern the
meaning and causes of experience and behavior through self-regulation of attention,
metacognition, and self-efficacy (Bhatia, Kumar, Kumar, Pandey, & Kochupillai, 2003; Bishop
et al., 2004; Flavell, 1979; Caldwell et al., 2010; Sutherland; 2014). The solution proposed by
this study is the implementation of mindfulness practices.
Mankind has practiced mindfulness for thousands of years and the essence of
mindfulness has been a core element of many eastern philosophies’ such as Buddhism, Taoism,
and Hinduism. It’s true origin is still a mystery; however, many humanitarian leaders claim its
presence has always been with us. Consider His Holiness Ravi Shankar, international
humanitarian and founder of the International Association for Human Values (IAHV, 2015)
whose programs have touched over 370 million people in 152 countries around the world to
reduce stress and develop leaders so that human values can flourish, and creator of this study’s
intervention—Youth Empowerment Seminar (YES!) and Sudarshan Kriya (SKY Breath) declared
mindfulness is when you are waiting for something to happen, instead of catching to the
happening, you put your attention into the waiting (Shankar, 2010).
Today, mindfulness is a broad concept with varying definitions. For the purpose of this
paper, Bishop and western mindfulness experts (2004) collaborated and determined an
operational definition of mindfulness, which is a nonelaborative, non-judgmental, present-
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
16

centered awareness in which each thought, feeling, or sensation that arises in the attentional field
is acknowledged and accepted as it is. Bishop et al. (2004) further posited the attentional field,
which involves sustained attention, attention switching, and the inhibition of elaborative
processing, or worry-free consciousness, is the self-regulation of attention. In other words,
mindfulness brings the cognizant skill about one’s cognition and thus a metacognitive skill
(Flavell, 1979). Simply put, mindfulness is the ability of an individual to maintain a non-
judgmental, clearful awareness of one’s own thoughts, feelings, and emotions through self-
regulation of attention and metacognition. Moreover, Williams and Kabat-Zinn (2011) posit that
mindfulness practice can resolve the problematic challenge of self-regulation and self-efficacy
by un-clouding the already awakened and inherently wise mind filled with self-regulation
potential. The prevalent common theme defined for mindfulness is its similarity to a skill that
can be cultivated with practice (Bishop et al., 2004; Hinterberger, Kohls, Kamei, Feilding, &
Walach, 2011; Shapiro, Oman, Thoresen, Plante, & Flinders, 2008; Siegel, 2007).
A Vietnamese monk named, Thich Nhat Hanh, introduced mindfulness to the western
hemisphere first to Martin Luther King Jr. and later John Kabat-Zinn, who successfully applied
mindfulness to promote psychological health and well-being on a wide-scale through the medical
field as an effective therapeutically practice to promote psychological health and well-being
(Burke, 2009). The practices were found to decrease stress, anxiety, and depression (Shapiro et
al., 2008). Furthermore, the ability to regulate emotional reactions and cultivate a positive
psychological state was of particular interest (Shapiro et al.).
Intrigued by the phenomena of mindfulness practices, researchers began to analyze
mindfulness’s inner-workings. They uncovered a cognitive function enabled through
mindfulness that allowed a comprehension to be made of various objects. This cognitive ability
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
17

became known as a central aspect of mindfulness as stated by Dreyfus (2011). Hence,
mindfulness became defined as the ability to modulate one’s attention, correcting the mind when
it wanders and bringing it back to the object. Therefore, a foundational structural pattern of self-
regulation was identified in clear comprehension and nonjudgmental ability within a framework
of a cognitive dimension (Bishop et al., 2004). This opened the door into the relationship
between cognition and mindfulness and subsequently begged for a more analytical observation
of the association and potential effect on self-regulation.
Hence, research turned towards neuroscience, which had begun to unlock the significant
neurological effects of mindfulness on learning and self-regulation. First, mindfulness
strengthened one’s ability to learn by establishing the rest-principle, which enhanced the strength
of synaptic connection which in-turn progressed and strengthened learning. Secondly,
mindfulness practice increase growth in the areas of the brain that direct attention, conduct
concept of self, and regulate stress. Lastly, neuroscience has detected the ability of mindfulness
to directly affect two of the three core elements of self-regulation as defined by Bandura (1991)--
judgment and reactivity. Subsequently this cultivates the non-reactivity through non-judgmental
brain functioning and creates a formative field for affective self-regulation to transpire.
The application of mindfulness to the education field has generated significant positive
evidence towards the general educational benefits of mindfulness for growth, development, and
positive functioning of learners (Howell & Buro, 2011; Hyland, 2009; Langer, 2009; Wisner,
Jones, & Gwin, 2010). These positive educational results on the implementation of mindfulness
in the classroom suggested the logical conclusion for incorporating mindfulness in all education
levels (Hyland, 2009). Moreover, the intent of this study was to expand the mindfulness
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
18

envelope further into its effects on the mystery of self-regulation and its internal factor, self-
efficacy in the realm of educational learning.
The relationship between mindfulness and students’ self-regulation for learning has been
a relatively unexplored phenomena to date. In this review only four articles were found from a
multitude of mindfulness articles reviewed that address this relationship. Each study
implemented different mindfulness practices but all of them found a positive correlation between
mindfulness practices and increased self-regulation (Caldwell, Harrison, Adams, Quin, &
Greeson, 2010; Howell & Buro, 2011; Sibinga, Perry-Parrish, Chung, Johnson, Smith, & Ellen,
2012; Wisner et al., 2010). As a result of the limited promising findings and in hope to address
the nation’s educational challenge of poor self-regulation, this study analyzed the effects of
mindfulness on self-regulation and its internal factor of self-efficacy in student’s learning.
There are many varying definitions of self-regulation; however, Albert Bandura (1991)
posited what many consider today to be the cornerstone theory of self-regulation, entitled social
cognitive theory of self-regulation, (SCTSR) which Bandura et al. (1992) found contributed
independently to students’ academic attainment. For the purpose of this paper, SCTSR was the
theoretical concept driving the study’s analysis. SCTSR operates through three principal sub
functions: self-monitoring; judgmental; and self-reactive which are developed for self-directed
change (Bandura, 1986). The central concept driving the utilization of these three sub-functions
are self-efficacy. Each subcomponent of SCTSR can be positively associated to aspects of
mindfulness. These intrinsic relationships were explored through the existing literature available
on mindfulness and SCTSR.
Considering research on mindfulness practices and self-regulation effects are extremely
limited with only four studies to date, a gap in research was detected. Subsequently this gap in
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
19

research was the grounds for this study. This paper proposed that providing the intrinsic links
between mindfulness, self-regulation, and self-efficacy through existing literature identified the
potential of developing mindfulness for more effective learning through abating and managing
the negative tendencies towards education that reside in many of our youth today. Additionally,
a positive correlation of mindfulness, self-regulation, and self-efficacy in education can forge a
new path for educational success in preparing college- and career-ready students by 2020.
Purpose of the Study
There have been substantial studies of the application of mindfulness in education with
respect to emotional self-regulation, building stress resilience, and building adaptive
interpersonal capabilities (Davidson & Kabat-Zinn, 2004; Dreyfus, 2011; Howell & Buro, 2011;
Hyland, 2009; Langer, 2009; Siegel, 2007; Wisner et al., 2010). However, there has been little
research -- if any -- with respect to the phenomenon of mindfulness’ influence on self-regulation
and it’ use in learning for academic achievement both inside and outside of the classroom.
Sibinga et al. (2012) stated that there is a need for additional research to explore the impact of
mindfulness on self-regulation, the duration of the effect, and related social, psychological, and
behavioral outcomes.
As a result, this study attempted to divulge the benefits of mindfulness towards self-
regulation and its internal factor, self-efficacy, towards academic attainment in high school
students. Bandura et al., (1992) stated self-regulatory factors contributed independently to
students’ academic attainment, which stress the importance of self-regulation. Bandura (1991)
further emphasizes the importance of self-regulatory systems as the core of causal processes,
determining the effects of external influences on an individual and providing the foundation for
purposeful action or forethought. Moreover Bandura et al. identified the self-regulation structure
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
20

was operated through a set of three psychological sub functions: self-monitoring; judgmental;
and self-reactive which are developed for self-directed change (Bandura, 1986). The functioning
of this self-regulatory structure or system was centrally dependent on the self-efficacy
mechanism (Bandura, 1991). Self-efficacy is the belief an individual has about their capability
of appropriate self-functioning within internal and external situations (Bandura, 1991) -- simply
put, its one’s beliefs about their ability to do the task (Linnenbrink & Pintrich, 2003).
Additionally as stated by Bandura (1997) a learner’s motivation is essential for self-regulation
success. Motivation can be demonstrated through commitment to goals, self-expectant
outcomes, self-efficacy beliefs, and two subcomponents of self-regulation; self-monitoring, and
self-reactive states. Thus, utilizing the lens of social-cognitive theory of self-regulation helped
explain the phenomena of increased self-regulation usage in learning when a developed
mindfulness state is present and maintained.
The mindfulness influences on self-regulation as a phenomenon can be mutually
understood and experienced. Consequently, a concurrent mixed methods research design using
quantitative and qualitative approaches was used to depict the essential or invariant structure of
the mindful self-regulatory, self-efficacious and academic performance experience (Merriam,
2009; Creswell, 2013). Data was collected to inductively build towards the phenomenon and
understand how the phenomenon functions can be replicated in the future (Merriam, 2009). The
methods used are student self-reporting on-line surveys, progress report card grades,
demographic information (quantitative) and self-reporting on open-ended questions (qualitative)
to better understand the research questions. The research utilized quantitative methods along
with structural equation modeling (SEM) and qualitative methods to enhance the interpretation
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
21

of results and provide a triangulated, multiple-perspective review of latent or un-measurable
variables.
The quantitative design allowed for comparisons to be made between several variables
such as independent, dependent, mediating, moderating, or control variables (Creswell, 2013).
The independent variable was the mindful intervention YES! to be discussed later in this study.
The dependent variables that depend on the independent variable are self-efficacy, self-
regulation, and academic performance via grade point average (GPA). The intervening and
moderating variables were determined as the intervention and surveys were applied and the
structural equation model implemented. The quantitative data analyzed was from pre-existing
student data, current student performance data, and a third set of data gathered from pre and post
mindfulness training surveys using a Likert scale based on mindfulness, self-regulation, and self-
efficacy measures.
Student self-reporting pre- and post-surveys were used to describe, explain, and compare
their knowledge, feelings, values, and behaviors through self-administered questionnaires to help
understand the effectiveness of mindfulness on self-regulation and self-efficacy in learning
(Fink, 2009). Students’ self-regulation was assessed through a pre- and post-mindfulness
training survey using the Short Self-Regulation Questionnaire developed by Brown, Miller, &
Lawendowski (1999) and approved by the National Institute of Health. To measure self-
efficacy, the Motivated Strategies for Learning Questionnaire, (MSLQ) self-efficacy scale was
used. The self-efficacy scale is a self-appraisal of one’s ability to master a task. Self-efficacy
includes judgments about one’s ability to accomplish a task as well as one’s confidence in one’s
skills to perform that task. The self-efficacy scale designed by Pintrich and DeGroot (1990)
demonstrated an internal consistency of Alpha .89 and consisted of nine items regarding
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
22

perceived competence and confidence in performance of class work. The multivariate test for
self-efficacy was significant.
The final instrument used in the surveys to measure mindfulness was the Mindful
Attention Awareness Scale (MAAS), which assessed individual differences in the frequency of
mindful states over time (Brown and Ryan, 2003). The psychometric validity of MAAS was
verified by numerous studies (Black, Sussman, Johnson, & Milam, 2013; Johnson, Wiebe, &
Morera, 2013; Ledesma, Garcia, & Poo, 2014; MacKillop & Anderson, 2007; Mantzios, Wilson,
& Kyriaki, 2013; Morgan, Masuda, & Anderson, 2013).
The essential research questions formulated were based on the statement of the problem
and previously identified knowledge gaps in current research. The answers to the research
questions were collected from pre-existing data, performance data, and on-line survey
administered to all participating students. The research questions were as follows:
1. Was there a significant difference in students’ maturation levels of mindfulness
between the treatment and control groups over the duration of the study?
1a. Was there a significant difference in students’ maturation levels of self-
regulation between the treatment and control groups over the duration of the
study?
1b. Was there a significant difference in students’ maturation levels of self-
efficacy between the treatment and control groups over the duration of the study?
2. Was there a difference in the effect of mindfulness on self-regulation between
treatment and control groups while controlling for entry levels of self-regulation and
mindfulness?
2a. Was there a difference in the effect of mindfulness on self-efficacy between
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
23

treatment and control groups while controlling for entry levels of self-efficacy and
mindfulness?
2b. Was there a difference in the effect of mindfulness on academic performance,
GPA, between treatment and control groups while controlling for entry levels of
academic performance, GPA, and mindfulness?
3. Were student’s level of mindfulness relative to the degree of impact on self-
regulation, self-efficacy and do those variables significantly impact student academic
performance?
The hypothesis was generated from these research questions and based on findings from
previously conducted research on the topic. Consequently, the hypothesis stated the application
of the mindfulness development program, YES!, will have a significant positive impact on
students’ self-regulation that is centrally dependent on self-efficacy, which in-turn will
significantly increase academic performance or GPA. The theoretical lens used to analyze the
hypothesis and research questions is the self-cognitive theory of self-regulation.
Social-cognitive theory of self-regulation offers insights into the phenomena not
previously considered. For instance why learners apply modeled behaviors or skills for learning
can be determined by perceived self-efficacy and self-regulation (Bandura, 2001). Social
cognitive theory gives sideline attention to these factors; however, today these concepts are
prominent and influential in social cognitive theory and in understanding learning. Since the
aspect of self-regulation in educational learning was this study’s central context, social cognitive
theory of self-regulation was used for a more in depth and holistic understanding of self-
regulation and how mindfulness may have affected it.

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24

Significance of the Study
The significance of this study hoped to reveal the positive correlation between a mindful
method practice YES! on students’ self-efficacy and self-regulated learning to increase academic
performance in preparing to be college- and career-ready students. More specifically this study
determined what sub functions of self-regulated learning are most positively affected by
mindfulness practices and their subsequent increase in academic performance. It was hoped that
a story emerged of students who developed a higher level of sustained mindfulness subsequently
increased their academic performance or GPA by increasing their self-efficacy and self-
regulation in the academic classroom. Additionally it was hoped this study supported Shapiro,
Brown, and Astin, (2011) findings that mindful education awareness can build stress resilience
and adaptive interpersonal capabilities for more effective learning through self-regulation.
The goal of this study was to find a strong positive correlation between a mindful method
practice that increased self-efficacy and self-regulated learning that in turn increased academic
performance, GPA, with an overall effect of creating better-prepared college- and career-ready
students. This positive relationship identified with the implementation of mindfulness in the
education setting hopefully implores educators, administrators, and policy-makers to embrace
and implement the mindfulness educational approach for systemically improving students’ self-
regulation to achieve our national educational goal to lead the world in college completion rates
by 2020.
Limitations and Delimitations
The study possessed limitation and delimitations that may affect or restrict the method
and analysis of research data. The limitations pointed to potential weaknesses that were unable
to be controlled or minimized in the study that may have threatened internal validity. There were
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
25

three scopes of limitations. The first scope of limitations involved the direct relationships of the
variables. Ruling out competing conceptualizations of inter-relationships between mindfulness
and self-regulation as well as self-efficacy was the first. Additional research is needed to rule
potential competing conceptualizations. The second limitation identified the longitudinal effect
of a mindful state on self-regulation, self-efficacy, and academic performance. Additionally
future research should be structured with greater cross-fertilization of research between
achievement related self-efficacy and self-regulation to positive psychology.
The second scope of limitations surrounded the methodological procedures for data
collection and the selection of sample population. First, the use of self-report surveys was based
from measuring mediators and moderators, which limited accuracy due to self-reporting.
Moreover, the use of non - self-reporting measures to verify validity of this self-reporting study
may have introduced a bias due to self-reporting and socially desirable answers that may have
inflated the associations between mindfulness and self-regulation as well as self-efficacy.
Secondly, a more diverse population would have been preferable to determine generalizations
among cultural groups; however, the study cannot be generalized for all middle school students
as the study was bounded due to a limited sample size of students from one school. Third, a
quasi-experimental design limited the study as not all subjects were randomly designed. Lastly,
a longitudinal academic performance corresponding to the development of mindfulness on self-
regulation and self-efficacy may provide more insight to self-efficacy and self-regulation’s
benefits.
The third scope of limitations involves the Structural Equation Model SEM). A path
confirmatory factor model of a path diagram was used to measure relationships between
observed values and latent values and determine best goodness of fit. The limitations with SEM
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
26

are; the problem of omitted variables, the importance of lower-order model components, and
potential limitations of models judged to be well fitting (Tomarken & Waller, 2005).
The delimitations of the study were the characteristics that limit the scope and define the
boundaries. Studying the benefits of self-efficacy and self-regulation due to mindfulness was
chosen over studying only intrinsic motivational effects because self-regulation encompasses the
latter in addition to identifying other necessary self-regulatory skills. Moreover, self-regulation
was a key foundational element in the four pillars of college and career readiness (Conley, 2007
& 2008). Additionally, self-regulation was chosen due to the early success of identifying a
positive correlation between mindfulness and positive emotional regulation. This positive
emotional regulation plays an instrumental role in self-regulation and points to potential gain in
the latter.
Social cognitive theory of self-regulation, SCTSR was chosen to analyze the structure
and mechanisms of self-regulation including self-efficacy through reciprocal interactions of
internal factors, behaviors, and environmental conditions which continuously change. Thus,
SCTSR had the potential to identify shifts in self-regulation as states of environmental influences
affecting mindfulness, while other theories of self-regulation are limited to internal factors only.
Consequently, SCTSR provided the best theoretical framework to develop the research questions
and analyze the data through a lens of dynamic internal and external factors and their subsequent
effects.
In terms of sample population chosen, the middle school students were chosen over
primary students because their level of maturity was more suited for capturing a higher validity
of data responses. The analysis of data used triangulation, which can establish broad numeric
trends from quantitative research and identify the detail of qualitative research (Creswell, 2013).
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
27

The delimitations of the methodological procedures helped to narrow the scope and identify the
effects of the study more precisely.
Lastly the SEM’s delimitations allowed for latent variables growth to be modeled through
multi-level SEM path models. Additionally SEM offered the approaches for dealing with
missing data with violations of normality assumptions (Tomarken & Waller, 2005).
Definition of Terms
Academic Knowledge and Skills
Academic knowledge and skills consist of big ideas, key concepts and vocabulary that
create the structure of the various disciplines and subjects (Conley, 2008)
Attentional field
The attentional field is the ability of the mind to remain focused and unified on its object
(Dreyfus, 2011)
AVID
AVID, Advancement Via Individual Determination, is a global nonprofit organization
dedicated to closing the achievement gap by preparing all students for college and other
postsecondary opportunities. Established more than 30 years ago with one teacher in one
classroom, AVID today impacts more than 800,000 students in 44 states and 16 other
countries/territories. AVID trains educators to use proven practices in order to prepare students
for success in high school, college, and a career, especially students traditionally
underrepresented in higher education (AVID, 2015)
Clear Comprehension
A form of discrimination (prajna, panna) closely connected to mindfulness that enables
the mind to observe, comprehend and evaluate what needs to be evaluated. It is seen as the
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28

central element of the practice of mindfulness for it provides the comprehension deriving from
paying close attention to experience. (Dreyfus, 2011)
College- and Career-Ready
College- and career-readiness is the minimum high school graduation expectations (e.g.,
completion of a minimum course of study, content mastery, proficiency on college- and career-
ready assessments, etc.) that include rigorous, robust, and well-rounded curriculum aligned with
college- and career-ready that cover a wide range of academic and technical knowledge and
skills to ensure that students leave high school ready for college and careers. (USDOE, 2013)
College Ready
College-readiness can be defined as the level of preparation a student needs in order to
enroll and succeed-without remediation-in a credit-bearing general education course at a post-
secondary institution that offers a baccalaureate program. (Conley, 2007)
Dispassion
A component of mindfulness where one observes thoughts and feelings as events in the
mind, without over-identifying with them and reacting to them in an automatic, habitual pattern
of reactivity (Bishop et al., 2004).
Discriminating Wisdom
Discriminating wisdom is the ability to discriminate skillful actions from unskillful
actions (Salzberg & Goldstein, 2001).
Emotional Regulation
Emotion regulation refers to the process by which individuals influence which emotions
they have, when they have them, and how they experience these emotions. (Gross, 1998)

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Metacognition
Metacognition construct entails an individual's ability to manage and monitor the input,
storage, search and retrieval of the contents of his own memory. It is further explained as any
kind of cognitive transaction with your environment, where a variety of information processing
activities may go on. It is the active monitoring, regulation and, orchestration of these processes
in relation to the cognitive objects or data referenced with respect to some concrete goal or
objective attainment (Flavell, 1971, 1976).
Mindfulness
A non-elaborative, non-judgmental, present-centered awareness in which each thought,
feeling, or sensation that arises in the attentional field is acknowledged and accepted as it is.
Bishop and colleagues (2004) further posit the attentional field, which involves sustained
attention, attention switching, and the inhibition of elaborative processing, or worry-free
consciousness, is the self-regulation of attention. In other words, mindfulness brings the skill of
cognition about one’s cognition and in this context can be considered a metacognitive skill
(Flavell, 1979). Simply put, mindfulness is the ability of an individual to maintain a non-
judgmental, clearful awareness of one’s own thoughts, feelings, and emotions through self-
regulation of attention and metacognition (Bishop et al., 2004). The prevalent common theme
defined in mindfulness is its similarity to a skill that can be cultivated with practice (Bishop et
al., 2004; Shapiro et al., 2008; Hinterberger et al., 2011; Siegel, 2007)
Mindfulness Meditation
Mindfulness meditation is the meditative act of cultivating awareness, acceptance, non-
judgment, and attention to the present moment (Hinterberger et al., 2011).

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Mindfulness Practice
Any practice that develops a mindfulness state or consciousness that can be seen to
consist of the important dimensions of self-regulation of attention and certain orientation to
experience (Siegel, 2007). Furthermore, mindfulness practices are programs of training for
reducing cognitive vulnerability to reactive modes of mind that may otherwise heighten stress
(Bishop et al., 2004)
Meditation
Meditation is a precise technique for resting the mind and attaining a state of
consciousness that is totally different from the normal waking state. Meditation is uplifting the
energy and mind and spreading it outward (Rama, 2013; Shankar, 2014)
In the educational field, the practice of meditation opens up the claustrophobic world of our
conditioning, revealing an array of options and allowing an individual to see clearly what’s going
on in their own mind and activating discriminating wisdom (Salzberg & Goldstein, 2001).
Non-Elaborative awareness
A mindfulness component that involves the ability to de-link from elaborative thought
streams about one’s experience and its origins, implications, and associations as they arise.
(Bishop et al., 2004)
Present-Centered Awareness
A mindfulness component that involves adopting a particular orientation toward one’s
experiences in the present moment. This orientation towards the present moment is
characterized by curiosity, openness, and acceptance (Bishop et al., 2004).

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Self-Regulation of Attention
A foundational component of mindfulness, where one brings awareness to a current
experience through observing and attending to the changing field of thoughts, feelings, and
sensations from moment to moment by regulating the focus of attention. This state leads to a
feeling of being very alert to what is occurring in the here-and-now (Bishop et al., 2004).
SKY Breath (Sudarshan Kriya)
Sudarshan Kriya® is a powerful yet simple rhythmic breathing technique that
incorporates specific natural rhythms of the breath, harmonizing the body, mind and emotions.
The technique eliminates stress, fatigue and negative emotions such as anger, frustration and
depression, leaving the mind calm, focused and the body energized, completely relaxed. Breath
is the main source of prana – the vital life-force energy. Prana is the very basis of health and
well-being for both, the body and mind. When the prana is high, one feels healthy, alert and
energetic. Sudarshan Kriya elevates the prana by flushing out more than 90% toxins and
accumulated stress, every day. Sudarshan Kriya harmonizes the rhythms of the body, mind and
emotions with those of Nature. Being in sync, we experience better health and joy, which in turn
brings harmony in our activities and relationships. Sudarshan Kriya facilitates physical, mental,
emotional and social well-being and is an integral part of the IAHV and YES! programs.
Sudarshan Kriya practitioners have reported better immunity, increased stamina and sustained
high-energy levels (Shankar, 2015)
Youth Empowerment Seminar (YES!)
The International Association for Human Values (IAHV) offers numerous programs to
millions of people from over 150 countries around the world for reducing stress and developing
leaders so that human values can flourish. The IAHV programs touch people in corporations,
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
32

veterans, disaster and trauma relief, women’s empowerment, prisoners, and schools (IAHV,
2015). Their program YES! for Schools is dedicated to providing youth with a healthy body, a
healthy mind and a healthy lifestyle by offering youth practical tools and life skills to manage
stress and emotions through meditation, breathing techniques, and yoga through the YES!
program. Two particular mindful techniques, SKY breath and focus meditation, have had
significant neurological results and will be discussed later. The experiential curriculum includes
stretching and exercise, targeted breathing techniques, life skills in conflict resolution, and life
lessons on human values such as responsibility, respect, friendliness, kindness and cooperation.
As students learn how to manage their stress in a healthy way, they exhibit greater confidence
and motivation to succeed in school and make healthy choices when faced with life’s challenges
(YES! for Schools, 2014).
Well-being
The indirect association between mindfulness and achievement-related self-regulation,
which facilitates self-regulation of behavior and thereby promotes well-being. (Howell & Buro,
2011).
Organization of the Study
Chapter 1 of the study has presented an introduction, the background of the problem, the
statement of the problem, the purpose of the study, the research questions answered, the
hypotheses, the significance of the study, a brief description of the methodology, the
assumptions, limitations, delimitations, and the definitions of terms.
Chapter 2 was a review of relevant literature that provides the intrinsic links between
mindfulness and self-regulation as well as self-efficacy and identifies the potential of developing
mindfulness for more effective self-regulated learning to become college- and career-ready high
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
33

school graduates. The chapter addresses the following topics: origin of mindfulness; application
of mindfulness in the west; conceptualizing mindfulness; neuroscience research on mindfulness;
mindfulness applied to education; mindfulness and self-regulation for learning; and future
mindfulness research needed. The self-cognitive theory of self-regulation, SCTSR, was the
theoretical lens applied to the study to study the benefits of mindfulness through its sub
functions.
Chapter 3 presented the methodology used in this study and explains how the initial
gathering of the quantitative data helped shape the qualitative interview questions making the
study more significant. The chapter also explained population and sampling procedure, the
instruments and their selection or development, as well as, information on validity and reliability.
Each of these sections concludes with a rationale, including strengths and limitations of the
design elements. The chapter goes on to describe the procedures for the mixed methods data
collection and the plan for data analysis.
Chapter 4 presented the results of the study. Chapter 5 discussed and analyzed the results,
culminating in conclusions and recommendations.

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CHAPTER TWO: LITERATURE REVIEW

Today the main cause for students’ lack of school readiness is poor self-regulation in the
classroom (Blair & Diamond, 2008). Given that emotional regulation is a necessary element in
the process of self-regulation as stated by Howell and Buro (2011), and the significant
emergence of mindfulness and its emotional regulation benefits have been significantly
documented; moreover, it is especially important to consider the effects of mindfulness on
students’ ability to self-regulate their own learning (Broderick and Metz, 2009; Khalsa, Hickey-
Schultz, Cohen, Steiner, & Cope, 2012; Mendelson, 2010; Metz, Frank, Reibel, Cantrell,
Sanders, & Broderick, 2013; Schonert-Reichl & Lawlor 2010; Wisner, 2013; Wisner et al., 2010)
To that end, this chapter explores the comprehensive preexisting literature related to the canon of
research on both mindfulness, self-regulation, and self-efficacy while highlighting self-regulation
and self-efficacy’s intrinsic relation to and influence of mindfulness.
The United States has established a goal to move from 18th to 1st in the world for college
completion rates by 2020 (Foley et al., 2013). This goal requires immense changes in education,
not only with the system but also teachers and most importantly our students. But, can our
students accomplish this? Do they have the self-efficacy or belief in themselves and the ability
to self-regulate and think about how they learn, considering poor self-regulation has been
documented as the main cause of K-12 students’ lack of school readiness (Blair & Diamond,
2008)? Therefore the challenge becomes how do schools activate, foster, and engage self-
regulation and self-efficacy for learning in our students? This study posited a solution for
rekindling self-efficacy and self-regulation that is as old as humankind itself? A solution that has
proven to ignite the natural ability to observe one’s own mind and emotions without reacting
impulsively but with greater capacity to see relationships between thoughts, feelings, and actions
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
35

and to dispassionately discern the meaning and causes of experience and behavior through self-
regulation of attention and metacognition (Bishop, et al., 2004; Flavell, 1979). This study
proposed mindfulness as that solution.
Mankind has practiced mindfulness for thousands of years and has been a core element of
many eastern philosophies’ such as Buddhism, Taoism, and Hinduism. Its true origin was still a
mystery; however, many humanitarian leaders have claimed its presence has always been with
us. Consider His Holiness Sri Sri Ravi Shankar (2010), international humanitarian and spiritual
leader, stated mindfulness is when you are waiting for something to happen, instead of catching
to the happening, you put your attention into the waiting.
Today, mindfulness is a broad concept with varying definitions. For the purpose of this
paper, Bishop and western mindfulness experts (2004) collaborated and determined an
operational definition of mindfulness, which was a nonelaborative, non-judgmental, present-
centered awareness in which each thought, feeling, or sensation that arises in the attentional field
was acknowledged and accepted as it was. Bishop and colleagues (2004) further posited the
attentional field, which involves sustained attention, attention switching, and the inhibition of
elaborative processing, or worry-free consciousness, was the self-regulation of attention. In
other words, mindfulness brings the skill of cognition about one’s cognition and in this context
can be considered a metacognitive skill (Flavell, 1979). Simply put, mindfulness is the ability of
an individual to maintain a non-judgmental, clearful awareness of one’s own thoughts, feelings,
and emotions through self-regulation of attention and metacognition.
A Vietnamese monk named, Thich Nhat Hanh, introduced mindfulness to the western
hemisphere first to Martin Luther King Jr. and later John Kabat-Zinn, who successfully applied
mindfulness to promote psychological health and well-being on a wide-scale through the medical
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
36

field as an effective therapeutically practice to promote psychological health and well-being
(Burke, 2009). The practices were found to decrease stress, anxiety, and depression (Shapiro et
al., 2008). Furthermore, the ability to regulate emotional reactions and cultivate a positive
psychological state was of particular interest (Shapiro et al., 2008). The benefits of the practice
resulted in further explorative research, which gave birth to mindful based stress reduction
(MBSR) and later mindful based cognitive therapy (MBCT). Today these therapies are widely
used to reduce psychological morbidity associated with chronic illness and to treat emotional and
behavioral disorders (1998).
Intrigued by the phenomenal success of mindfulness practices, researchers began to
analyze its inner-workings. They uncovered a cognitive function enabled through mindfulness
that allowed a comprehension to be made of various objects. This cognitive ability became
known as a central aspect of mindfulness as stated by Dreyfus (2011). Hence, mindfulness
became defined as the ability to modulate one’s attention, correcting the mind when it wanders
and bringing it back to the object. Moreover, a foundational structural pattern of self-regulation
was identified in clear comprehension and nonjudgmental ability within a framework of a
cognitive dimension (Bishop et al., 2004; Bandura, 1991). This opened the door into the
relationship between cognition and mindfulness and subsequently begged for a more analytical
observation of the association and potential effect on self-regulation and its internal factor, self-
efficacy.
Neuroscience has begun to unlock the significant neurological effects of mindfulness on
learning and self-regulation. First, the development of mindfulness laid a neurological positive
foundation by providing the rest principle (Hinterberger et.al, 2011, Taylor et.al, 2013).
According to Sinclair (2014), during the rest principle the synaptic connections get stronger
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
37

when they are rested right after use. Using the synapse over and over again without rest can
cause extinction, amnesia or reverse learning. By producing a restful state with mindfulness
practices and provided the synaptic connection was not overused, the synapse can reach a new
level of strength, higher than before. Consequently, learning can become stronger and progress,
rather than digress, which was the case when neurological connections are weakened, taxed or
unrested (Sinclair, 2014). Hence, the rest principle associated with mindfulness has set the stage
for a strong neurological foundation for self-regulation to operate in. Moreover, neuroscience has
detected the ability of mindfulness to directly affect two of the three core elements of self-
regulation as defined by Bandura (1991) -- judgment and reactivity. Siegel (2007) found that
mindful development may directly influence non-reactivity by altering the connections between
prefrontal cortex and limbic zones. Thus, non-reactivity was cultivated through non-judgmental
brain functioning and creates a formative field for affective self-regulation to transpire. Recently
Sutherland (2014) reported the National Center for Complimentary and Alternative Medicine
discovered mindfulness practitioners had more gray matter (brain cells) in the following areas:
superior partial cortex, involved in directing attention; the hippocampus, a region critical to
dampening stress; the precuneus and posterior cingulate cortex which are areas key to our
concept of self. The ability to direct attention and formulate a viable concept of self are both key
components of self-regulation and self-efficacy.
The application of mindfulness to the education field has generated significant positive
evidence towards the general educational benefits of mindfulness for growth, development, and
positive functioning of learners (Howell & Buro, 2011; Hyland, 2009; Langer, 2009; Wisner et
al., 2010). These positive educational results on the implementation of mindfulness in the
classroom suggest the logical conclusion for incorporating mindfulness in all education levels
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
38

(Hyland, 2009). Consequently, the mindfulness envelope can be pushed further into discovering
the potential beneficial of self-regulation.
The relationship between mindfulness and a students’ self-regulation for learning was a
relatively unexplored phenomena to date. In this review only four articles were found from a
multitude of mindfulness articles reviewed that address this relationship. Each study
implemented different mindfulness practices however all of them found a positive correlation
between mindfulness practices and increased self-regulation (Caldwell et al., 2010; Howell &
Buro, 2011; Sibinga et al., 2012; Wisner et al., 2010). As a result of the limited but few
promising findings and in hope to address the national’s educational challenge of poor self-
regulation, this study analyzed the effects of mindfulness on self-regulation and self-efficacy and
the subsequent impact of learning for students.
There are many varying definitions of self-regulation; however, Albert Bandura (1991)
posits what many consider to be the cornerstone theory of self-regulation, entitled social
cognitive theory of self-regulation, (SCTSR). Moreover SCTSR factors have been found to
contribute independently to students’ academic attainment, which supported this study’s
hypothesis (Bandura et al., 1992). For the purpose of this paper, social cognitive theory of self-
regulation was the theoretical concept driving the study’s analysis. Social cognitive theory of
self-regulation operates through three principal sub functions: self-monitoring, judgmental, and
self-reactive which are developed for self-directed change (Bandura, 1986). The central concept
driving the utilization of these three was self-efficacy. Each subcomponent of SCTSR can be
positively associated to aspects of mindfulness. These intrinsic relationships are explored
through the existing literature available on mindfulness and social cognitive theory of self-
regulation.
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39

Considering research on mindfulness practices and self-regulation effects are extremely
limited, since only four studies have been conducted to date, a gap in research was discovered.
Subsequently this gap in research was the grounds for this study. This paper proposed that
establishing the intrinsic links between mindfulness and self-regulation through existing
literature, identified the potential of developing mindfulness and as a result self-, self-efficacy for
learning by abating and managing the current lack of self-regulation residing in our youth and
their education today. Additionally, a positive correlation of mindfulness and self-regulation in
education can forge a new path for educational success in developing college- and career-ready
students by 2020.
Mindfulness
Origin of Mindfulness
Mindfulness was born from the art of meditation and the breath that has been practiced
for thousands of years. The mindfulness concept has been a core element of many eastern
philosophies’ such as Buddhism, Taoism, and Hinduism. Its true origin is still a mystery;
however, many humanitarian leaders have claimed its presence has always been with us.
International humanitarian and founder of the International Association for Human
Values, His Holiness Sri Sri Ravi Shankar, who has developed programs and initiatives
including YES!, has touched the lives of over 370 million people in 152 countries in only three
decades. Sri Sri has rekindled the traditions of yoga and meditation and has offered them in a
form that works in the 21st century. By reviving ancient wisdom, he has created new techniques
for personal and social transformation. These include a powerful technique called Sudarshan
Kriya® which has helped millions of people to find relief from stress and discover inner
reservoirs of energy and peace in daily life. Sri Sri has defined mindfulness quite simply,
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
40

What is happening right now? (laughter) Sense of mindfulness, yes? I am not saying
anything and you are waiting to catch something. Are you aware of this? Instead of
catching something, put your attention into the waiting. This is mindfulness. It is
meditative awareness. Are you getting what I am saying? What happens when you are
mindful? Suddenly a shift starts happening within you. From the scenery, you are going
towards the seer. Now you are the seer and the scenery (Shankar, 2010, para. 2).
This state of mind Sri Sri described above has been referred to as Samadhi, the meditative
mindful state of mind. Patanjali (1963) stated that yoga means concentration or Samadhi and it
is possible in whatever the state the mind may be. He defined five states of the mind: restless;
stupefied or infatuated; distracted; one-pointed; and arrested. In the restless state of mind lies the
heart of the challenge and subsequent solution for self-regulation. The ancient sage Patanjali
stated “in a restless state of mind one does not have the patience or intelligence necessary for
contemplation of a super-sensuous subject and consequently cannot think or comprehend any
subtle principle.” (p.3).
The Dalai Lama depicted mindfulness as the state of mind when one becomes aware of a
background noise that was always there, or an inner force that awakens you moments before the
alarm clock does (Dalai Lama, 2009). Mindfulness has been recognized as the chief factor in the
practice of satipatthana, the most well-known system of Buddhist meditation (Bodhi, 2011). Sati
and sampajanna are the most frequent terms used to describe satipatthana. Sati means
mindfulness and sampajanna means clear comprehension, which serve as the bridge between the
observational function of mindfulness and development of insight that lead to self-regulation.
Consequently a mindfulness practice can quell a restless state of mind and resolve the
problematic challenge of self-regulation by un clouding the already awakened and inherently
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
41

wise mind filled with self-regulation potential and subsequently applied to the academic
environment (Williams & Kabat-Zinn, 2011).
Application of Mindfulness in the West
The western culture awoke to the mindfulness phenomena and its benefits in the 1970s
(Meiklejohn et al., 2012). A Vietnamese monk, Thich Nhat Hanh, introduced the concept of
mindfulness to Martin Luther King Jr. and later John Kabat-Zinn, who successfully applied
mindfulness to promote psychological health and well-being on a wide-scale. The initial
documented discoveries that emerged in the medical field were found as effective approaches to
promote psychological health and well-being (Burke, 2009). The practices were found to
decrease stress, anxiety, and depression (Shapiro et al., 2008). Furthermore, the ability to
regulate emotional reactions and cultivate a positive psychological state was of particular interest
(Shapiro et al., 2008).
The benefits of the practice resulted in further explorative research, which gave birth to
and mindful based stress reduction (MBSR) and later mindful based cognitive therapy (MBCT)
as stated by Burke (2009) and Black, Milam, and Sussman (2009). MBSR came into being in
1979 at the Stress Reduction Clinic at the University of Massachusetts (Williams & Kabat-Zinn,
2011). It was created by Jon Kabat-Zinn to help people cope with stress - psychological, and
chronic illness - physical, (Black, 2009; Hyland, 2011). The success of MBSR broadened into
other contexts and settings including work with chronic pain sufferers, cancer patients and those
with personality disorders and expanded into prisons, inner-city communities, medical education
and corporate training (Kabat-Zinn, 2006).
MBCT was the offspring of MBSR and designed to aid the prevention, intervention and
maintenance strategies of depression relapse, specifically in major depressive disorder (Baer &
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42

Krietemeyer, 2006). The main emphasis of MBCT was for the patient to perceive the
challenging thoughts and emotions, as passing events of the mind and that do not reflect reality
nor reflect their true self (Crane, 2013). However, this disorder has been challenging for
depressed individuals as a negative perpetuating cycle has been established that brings feelings
of low self-esteem and self-blame, which can be triggered by one element (Williams, 2007).
MBCT has attempted to break this vicious self-destructive loop of thought and action by
introducing the healing power of non-judgmental awareness to these habitual and obsessive
patterns (Hyland, 2011). Fortunately MBCT and MBSR have proven effective to relieve the
suffering of the affected individuals with decades of evidence (Kabat-Zinn, 1990). In the past
decade, clinical trials using MBCT and MBSR have supported the anecdotal evidence. The two
therapies are now widely used to treat emotional and behavioral disorders and have proven to
mitigate stress and enhance emotional well-being (Astin, 1997; Kabat-Zinn, 1998; Shapiro,
Schwartz & Bonner, 1998; Williams, Kolar, Reger, & Pearson, 2001).
The growth of mindfulness in western society has been nothing short of astonishing.
From the early 1980’s until the late 1990’s, mindfulness based applications went along at a very
modest level under the guidance auspices of behavioral medicine. In the late 1990’s mindfulness
grew exponentially and continues today, evolving from behavioral or mind/body medicine to
clinical and health psychology, cognitive therapy, and neuroscience. In 2010, the National
Institute of Health funded over 150 research projects in mindfulness over the past five years.
This rate of growth was nothing short of astonishing and signals a phenomena convergence of
two different epistemologies and cultures, western empirical science and eastern contemplative
disciplines or meditation. There was an increasingly growing interest to explore the benefits of
mindfulness in primary and secondary education, higher education, the law, business, and
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43

leadership (Williams & Kabat-Zinn, 2011). The application of mindfulness in education was a
promising new frontier that offers potential benefits to increase students’ learning through self-
regulation and the purpose of this paper.
Conceptualizing Mindfulness
Mindfulness was a broad concept with meanings that vary according to author and has
functioned in the west without an operational definition. Recently leading experts in the field of
mindfulness met to conjointly create an operational definition of mindfulness. The agreed upon
operational definition of mindfulness offered by Bishop et al. (2004) and used for the purpose of
this study was “broadly conceptualized, mindfulness has been described as a kind of non-
elaborative, non-judgmental, present-centered awareness in which each thought, feeling, or
sensation that arises in the attentional field is acknowledged and accepted as it.” (p.232).
To elaborate further, when one was in a state of mindfulness, thoughts and feelings are
observed as passing events in the mind that disengages the automatic, habitual reactive state.
This state of self-observation or dispassion was believed to enable one to respond to situations
with a reflective approach rather than an automatic reactionary response (Bishop, et al., 2004).
This dispassionate state or attentional field was composed of awareness endowed with various
aspects of mental factors of which some pertain to the affective domain and others are conative
or cognitive in nature (Dreyfus, 2011). The key aspect of attentiveness was mindful ability to
pay close attention and not ‘wobble’ away from an object, or the ability of the mind to remain
focused and unified on its object, which allows a cognitive function to be enabled allowing
various aspects of the objects encountered so to make sense of them. This cognitive ability plays
a central aspect of mindfulness as stated by Dreyfus (2011). Moreover, Bishop and colleagues
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44

posit monitoring the stream of consciousness over time would likely lead to increased cognitive
complexity.
Nonetheless, mindfulness goes beyond attentiveness and retentive focus to the
development of clear comprehension or samprajnana. This was a form of mindful discrimination
that enables the mind to observe, comprehend and evaluate what needs to be evaluated. Simply
put, mindfulness was the knowing of what happens in one’s mind, body, breath and outside
objects. Therefore, as mindfulness was developed, the evolving proficiency of clear
comprehension was developed, which allows immediate detection of distractions and other
obstacles in the mind. Hence clear comprehension was the meta-attentive skill to monitor one’s
own mental states (Dreyfus, 2011). Simply put it was the ability to modulate one’s attention,
correcting the mind when it wanders and bringing it back to the object.
In this study one research question analyzed was if a specific mindfulness practice
benefits self-regulation. For that purpose, the main theoretical premise behind mindfulness as
stated above can be associated with the social cognitive theory of self-regulation. As stated by
Albert Bandura (1986), the three core sub functions of social cognitive theory of self-regulation
are: self-monitoring, judgmental, and self-reactive. The ability to maintain attention on a unified
field and engage cognition relies on one’s ability to self-monitor the attentional field and remains
present with a specific event or concept. When focused on an event in the attentional field,
mindfulness allows for a non-judgmental orientation towards thoughts and emotions that are
engaged from the experience. Lastly, mindfulness provided mindful discrimination, which
enabled the mind to observe, comprehend and evaluate what needs to be evaluated and provide
clear comprehension to produce a self-reactive state that promoted self-directive change as
opposed to reactionary change. The functioning of the social cognitive theory of self-regulation
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45

system was determined to be centrally dependent on the self-efficacy mechanism (Bandura,
1991). These connective elements offered bridges between mindfulness and self-regulation,
which this study has explored further as stated by the research questions.
To further understand the passive inner process of mindfulness, Kabat-Zinn (1990)
offered seven key characteristics. The first was simply being with thoughts absent of judgment
or reactive. Second, patience with mindfulness works by not striving to worry too much about
external ends or goals so that our present perception was clear and available. Next was to
cultivate a beginner’s mind by not letting our past experience get in the way of our present
thoughts and perceptions. Fourth was the development of a basic trust in the importance and
value of our own thoughts, feelings, and experiences. Fifth, non-striving, which highlighted the
meditative practice of mindfulness’s goal to have no goal beyond itself, leaving itself free of
constant criticism and revision. Simply, one pays attention to activity or non-activity that the
mind was employed in at any given moment. The sixth characteristic was acceptance of the full
reality of the present, which allows for change and development. Lastly, to let go of any strong
or reoccurring thoughts whether they are good or bad. The mind’s tendency was towards
aversion of bad thoughts and desire for good thoughts. Hence in mindfulness the gymnastics of
the mind was abandoned or better put, let go of. Additionally Siegel (2007) correlated these
characteristics with strengths of character, and Jarden et al. (2012) discovered the increased
amount of time spent using these strengths of character had been found to correlate significantly
with mindfulness.
Neuroscience Research on Mindfulness
Neuroscience has begun to unlock the significant effects of mindfulness. First, the
development of mindfulness lays a neurological positive foundation by providing the rest
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46

principle (Hinterberger et.al, 2011, Taylor et.al, 2013). According to Sinclair (2014) the synaptic
connections get stronger when they are rested right after use. Using the synapse over and over
again only weakens it. Hinterberger and colleagues found that the mindful practice of meditation
simulated the resting state when measured with electroencephalogram (EEG). This resting state
delivered by mindfulness practices implies that neurological synaptic connections become
stronger when allowed to rest briefly due to mindfulness practice. Consequently learning
became stronger and progressed, rather than digressed, which was the case when neurological
connections are weakened, taxed or unrested (Sinclair, 2014). More recently Sutherland (2014)
stated the National Center for Complimentary and Alternative Medicine discovered mindfulness
practitioners had larger gray matter (brain cells) in the following areas: superior partial cortex,
involved in directing attention; the hippocampus, a region critical to dampening stress; the
precuneus and posterior cingulate cortex which are areas key to our concept of self. Hence, the
rest principal and larger brain volume associated with mindfulness sets the stage for a strong
neurological foundation for self-regulation and self-efficacy to operate in.
Furthermore research on the YES! SKY breath has found intriguing neurological
findings. First a significant decrease in the stress hormone, cortisol, suggests regular practice of
SKY breath produces greater levels of relaxation and more importantly resiliency to stress
(Sharma et al., 2008). Secondly a significant increase in beta frequency range of SKY breath
practitioners was a typical brain state of attentive information processing (Bhatia et al., 2003). A
third benefit found of the YES! program was a significantly decrease of impulsive behavior in
low-income high school students (Ghahremani et al., 2013). Finally Agrawal and Mizuhara-
Cheng (2010) self-published a case study on the YES program’s focus meditation alleviated
abnormality of a student’s ADHD as assessed by the test of variance attention, TOVA, within
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47

two weeks of administering the intervention and normality was retained throughout the entire 6-
month study while regularly continuing the focus meditation practice. These results suggested
SKY breath daily practitioners experienced decreased stress, increased stress resilience,
decreased impulsive behavior, and increased attentive information processing, which may be
linked to strengthening self-regulation, self-efficacy and academic performance.
Even though neuroscience has only begun to explore the phenomena of mindfulness, the
associative links to self-regulation have begun to surface. Davidson, Kabat-Zinn, Schumacher,
Rosenkranz, Muller, Santorelli, and Sheridan (2003) investigated the impact of mindfulness on
emotional regulation and found the practices changed neural functioning to help us be more
open, non-judgmental and non-reactive in responding to events and situations, which trigger
emotions. The positive effectiveness of mindful-based strategies on emotional based learning
was legitimized and reinforced by neuroscience research and data (Hyland, 2011). MRI and
EEG brain scanning have demonstrated that mindfulness meditation demonstrates a clear and
direct connection between meditation brain states and different types of emotions (Goleman,
2003).
As a result, to cultivate the non-reactivity through non-judgmental brain functioning
Siegel (2007) found the circuits in the brain that enable lower affect-generating circuits to be
regulated by the higher modulating ones; therefore, “mindful awareness may directly influence
non-reactivity by altering the connections between prefrontal cortex and limbic zones.” (p. 211).
Furthermore, Davidson (2000) and Siegel found that mindfulness produces long-term resilience
of emotional states as determined by establishing a calm and stable mind through integrating left
and right hemispheres of the brain. Brain scans of meditators supported this finding by
demonstrating movement towards the left prefrontal lobe, which denoted positive affective states
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48

and away from the right prefrontal lobe, which was believed to mediate distress and
uncomfortable emotions (Siegel). These neurological finding supported the benefits of
mindfulness and established the operational facilities the two sub-functions of self-regulation,
judgmental and self-reactive through its neurological ability to establish non-judgmental and
non-reactive brain traits.
Mindfulness Applied to Education
The mindful phenomena sparked the interest for potential application into other fields
such as education (Duerr, 2004; Meiklejohn et al., 2012). There has been a wealth of evidence
about the general educational benefits of mindfulness for growth, development, and positive
functioning of learners presented (Howell & Buro, 2011; Hyland, 2009; Langer, 2009; Wisner et
al., 2010). Hyland stated that mindfulness could assist in fostering self-esteem, confidence or
emotional intelligence, engagement, and motivation. Recently studies in school settings have
reported that physiological coherence, which was a result of mindful practice, improved
cognitive performance (Hart, 2004). Moreover, Black and Fernando (2013); Napoli, Krech, and
Holley (2005); Schonert-Reichl and Lawlor (2010); and Wisner (2013) found that students were
able to focus and pay attention to their academic lessons more easily. Wisner (2013) reported
perceived student benefit of enhanced student engagement. In fact, Jha, Stanley, Kiyonaga,
Wong, and Gelfand (2010) found that implementing mindfulness could facilitate working
memory capacity. Moreover, mindfulness practices posted a modest positive effect on key social
and emotional learning skills (Metz et al., 2013; Schonert-Reichl & Lawlor), and mindfulness
practices have enhanced academic performance as documented by Barangan et al. (2007),
Beaucheim et al. (2008), (Burnett) 2009, Chang and Hierbert (1989), Crane (2009), Cranson et
al. (1991), Hanson (2009), Leon (2009), Siegel (2007). Finally, ten minutes of mindful
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49

meditation practiced once a day or several times a week produced more successful students and a
calmer learning environment. These positive educational results on the implementation of
mindfulness in the classroom suggested the logical conclusion for incorporating mindfulness in
all education levels (Hyland, 2009).
Highlighting the crucial importance and immense potential of mindfulness integration in
education, Siegel (2007) posited ‘reflective thinking’ in the development of emotional wisdom
should be a fundamental part of basic education in so much as to call it the 4
th
R of education.
The first three R’s of education; reading, writing, and ‘rithmetic (sic) were once considered
luxuries for a selective few. Siegel further posited the fourth R, reflective thinking, can be
implemented through a mindsight curricula theme. Mindsight was generated from the unifying
goal for all mindfulness practices in contemplative, psychotherapeutic, and educational contexts
to develop the ability to ‘name and tame’ the emotions experienced rather then being
overwhelmed by them. Its important to note here, Hyland (2011) stated a perceived hazard of
mindfulness was apathy, unhappiness and destructive emotions such as anger, self-loathing,
aggression, and depression as described by Goleman (2003). Conversely, Siegel posited that
mindsight developed the capacity to sense the mind in ourselves and in others, otherwise our
mental states may remain confused and inchoate, and the minds of others may be understated or
missing from our perspectives on the world. Furthermore, Howell and Buro (2011) revealed a
direct association between mindfulness and well-being. In other words considering the current
state of student apathy towards education as stated by Bridgeland et al. (2006), mindfulness
offers a clear path to reigniting student engagement in education and overall well-being.
Bush (2006) and Duerr, Zajonc, and Dana (2003) reported there was a growing interest
for integrating meditation into education. Students who have received mindful awareness
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50

education have demonstrated a broad band of cognitive, social and psychological benefits that
have materialized in academic skills, executive functioning, and emotional self-regulation (Baer,
2003; Davidson et al., 2003; Grossman, Niemann, Schmidt, & Walach, 2004; Meiklejohn et al.,
2012; Tang, Lu, Geng, Stein, Yang, & Posner, 2010; Zylowska, Ackerman, Yang, Futrell,
Horton, Hale, & Smalley, 2008). Moreover Bhatia et al. (2003) reported an increase in beta
activity of the left temporo-centro-pareital region with practitioners of the SKY breath that
matches the increased information flow in the same region during mental arithmetic, which
points towards a potential link between increased mindfulness and increased mental math
performance.
Mindfulness and Self-Regulation for Learning
The relationship between mindfulness and a students’ self-regulation for learning was a
relatively unexplored phenomena to date. However, the emotional regulation benefits of
mindfulness have been the most researched aspect of the mindfulness application to education.
A multitude of studies have overwhelmingly supported the effect of mindfulness practices on
improved emotional regulation.
Mendelson (2010) evaluated a yoga-based intervention program for underserved urban
population of 4
th
and 5
th
graders. Students reported decreases in involuntary stress responses,
including emotional arousal. Khalsa et al. (2012) found that a semester of yoga with rural high
school students increased their ability to control anger. Broderick and Metz (2009) implemented
the MBSR model with high school senior females and found significant decreases in negative
affect and increase in self-reported calm, relaxation, and self-acceptance, which directly affected
emotional regulation. A non-randomized control trial mindfulness program for 4
th
through 7
th

conducted by Schonert-Reichl and Lawlor (2010) showed improvements in self-reported
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51

optimism, positive affect, externalizing behavior, and social-emotional competence. Metz et al.
(2013) implemented mindfulness practices on public high school students who demonstrated
large gains in emotional regulation skills including emotional awareness, access to regulation
strategies, and emotional clarity. Wisner (2013) study examined the perceived benefits of
mindfulness meditation for alternative high school students who reported enhanced emotional
coping. Similarly, Black and Fernando (2013) found an increase in self-control and improved
classroom behavior for elementary school children after mindful based intervention. Finally,
Wisner et al. (2010) found the intervention of mindfulness meditation interventions in school
settings led to improved emotional and behavioral self-regulation.
In conclusion, these studies overwhelmingly supported the effect of mindfulness
practices on improved emotional regulation. Considering, emotional regulation can only have a
causal effect on behavior regulation, which was a necessary element in the process of self-
regulation as stated by Howell and Buro (2011), these significant positive findings resulted in
emotional regulation points towards the next area to study, the effects of mindfulness on self-
regulation.
In this review only four articles were found from over one hundred reviewed that address
this relationship. Each study implemented different mindfulness practices but all of them found
a positive correlation between mindfulness practices and increased self-regulation (Caldwell et
al., 2010; Howell & Buro, 2011; Sibinga et al., 2012; Wisner et al., 2010).
Caldwell et al. (2010) studied the effects of mindfulness through movement-based
courses in college students on self-regulatory, self-efficacy, or the ability to motivate oneself to
keep trying difficult tasks. The research team found that mindfulness boosted self-regulatory
self-efficacy and increased self-regulatory capacity. The limitations of the study were twofold.
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52

The first was attributed to better sleep increasing mindfulness and the resulting effects. The
second considered that mindfulness might be a normal developmental process in college
students. However, the overall positive correlation pointed to an increased ability to motivate
oneself to keep trying difficult tasks when mindfulness was practiced.
The second study conducted by Sibinga et al. (2012) researched the effects on stress and
coping abilities of middle school male youth engaged in MBSR mindfulness practice. The
control group study found that MBSR boys: had significantly less anxiety; less negative coping;
and their cortisol or stress hormone levels remained constant compared to the control group
whose cortisol levels increased. The results suggested that MBSR practiced for urban middle-
school male youth specifically enhanced self-regulatory practices, including improved coping
and emotional regulation. The result indicators demonstrated a calmer state of the mind, which
was more conducive for self-regulation.
The third study looked at three different meditation practices with adolescents in schools
and its effect on self-regulation, emotional coping, and self-esteem. Wisner et al. (2010) found
that meditation practices in the school setting helped to improve self-regulation capacities and
coping abilities. The qualitative data indicated that students found mindful meditation helped to
increase: self-regulation; to calm themselves; relieve stress; increased relaxation; and improved
emotional coping. Moreover, the study correlated increased self-regulation with improved
school climate, which enabled all students to have a better environmental opportunity to acquire
the skills to become college- and career-ready. According to the local control accountability
plan for California, school climate was one of the eight areas to be measured in determining
successful implementation of the Common Core State Standards for enabling students to be
college- and career-ready (Muhammad & Hollie, 2012). The limitation of the study rests on the
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53

fact that a limited number of studies with small number of participants have focused on a few
meditation practices. As a result, a more cohesive model of meditation for youth was needed and
more extensive and empirical research on adolescents was encouraged to explore the depth of
this phenomena.
The final and most introspective of the four studies looked at the effect of mindfulness on
Canadian undergraduate college students self-reported through surveys in regards to achievement
related self-regulated functioning, and achievement emotions. Howell and Buro (2011) found
that two factors were significantly inter-correlated. The aspects of self-regulation measured were
goal achievement, delay of gratification, help seeking, cognitive and meta-cognitive learning
strategies, and self-control. Additionally Howell and Buro stated that no other study to date has
systematically examined individual differences in mindfulness with relation to a broad range of
achievement-related self-regulatory capacities and achievement-related emotions. Accordingly,
they tested four hypotheses. The first posited greater mindfulness was associated with
achievement related self-regulation indices such as; enhanced endorsement of implicit theories
for goal mastery; inspired greater willingness to seek help, delayed gratification, used learning
strategies; increased self-control; and lowered procrastination. The second hypothesized that
mindfulness was associated with a positive achievement-related emotional experience. The third
hypotheses posited that achievement-related self-regulation was associated with positive
achievement related emotional experience. Finally, achievement-related self-regulation could
mediate the relationship between mindfulness and achievement emotions.
Howell and Buro (2011) found their first three hypotheses supported by the data;
however, the fourth hypotheses showed an acceptable but poor fit which may be due to high
sensitivity due to a large sample size. The highest significant correlated causal path was found
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
54

from mindfulness to achievement-related self-regulation and from achievement-related self-
regulation to achievement emotions. The mechanism by which mindfulness was associated with
achievement-related self-regulation was identified by evidence boosting memory capacity, self-
control, attentional control, and possible involvement of executive processes. These executive
processes included enhanced attentional control, greater sustained attention, and greater freedom
from distraction.
The limitations of the cross study precluded drawing cause-effect inferences concerning
associations between mindfulness, achievement-related self-regulation, and achievement
emotions. Additional research is needed to rule out competing conceptualizations of inter-
relationships between mindfulness and self-regulation. A more diverse population was
preferable to determine generalizations among cultural groups. Actual academic performance
corresponding to self-regulation may provide more insight to self-regulation’s benefits. Use of
non self-reporting measures to verify validity of this self-reporting study, which may be biased
due to self-reporting and socially desirable answers, may inflate the associations between
mindfulness and self-regulation. Additional experimental research is needed on induction of
mindful states and their impact on self-regulation, while future research should be structured
with greater cross-fertilization of research between achievement related self-regulation and
positive psychology.
Current research on mindfulness practices and self-regulation are extremely limited
considering the four aforementioned studies are the only research to date conducted on this topic.
Admittedly Howell and Buro’s (2011) research demonstrated that self-regulation in the academic
domain was systematically associated with mindfulness and with an emotional balance, favoring
the positive. Additionally mindfulness has a causal effect on achievement related self-regulation.
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
55

Consequently, self-regulation was a highly adaptable attribute and mindfulness may be one
means by which self-regulation can be cultivated.
Future Mindfulness Research Needed
Considering the infancy of research on mindfulness and its educational effects, there is a
natural need for more research to be conducted. Mindfulness research in the context of academia
has received limited attention despite hyperbolic increases since 2007 (Howell & Buro, 2011).
Nevertheless, all the cited articles on mindfulness conclude that future research is needed, as
early results are positive and promising. Future research implications can be drawn from the
many articles cited on mindfulness in the education setting. These future research implications
are: further advanced empirical research (Meiklejohn et al., 2012; Williams & Kabat-Zinn,
2011); identify specific, appropriate and effective mindfulness practices (Greenberg & Harris,
2012); to understand the mechanisms that underlie the effects of these mindfulness approaches
(Frank, Jennings, & Greenberg, 2013); to determine benefits and long-term effects of
mindfulness practices (Wisner, 2013; Zelazo & Lyons, 2011); and larger samples and well-
designed trials (Black & Fernando, 2013; Greenberg & Harris, 2012). In respect to this study the
most important implications for additional research were to explore the impact of mindfulness on
self-regulation, the duration of the effect, and related social, psychological, and behavioral
outcomes (Sibinga et al., 2012).
Self-Regulation
Conceptualizing Self-Regulation
To explore self-regulation’s intrinsic relation to and influence of mindfulness, an
understanding of self-regulation was warranted first. Hence, in this section the discussion points
to the foundational elements of self-regulation. Self-regulation was a broad term with meanings
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56

that vary considerably from author to author. Zimmerman (2001) stated that self-regulation
refers to learning that results from students’ self-generated thoughts and behaviors that are
oriented systematically toward the attainment of an individual’s goals. While Vygotsky’s (2012)
theory of development provided the social constructivist foundation for self-regulation, which
stated that people learn through interacting with their social system. Hence, one definition was
derived from internal factors while the latter was derived from external factors. Bandura (1997)
stated that many self-regulation theories like Vygotsky’s assume a negative motivating force that
drives self-regulation; however, Bandura posited self-regulation was an internally driven
phenomenon motivated and regulated by self-influence (Bandura, 1991). This phenomenon was
similar to the development of mindfulness, which was also internally driven as stated by Kabat-
Zinn (1990). Hence, for the purpose of this paper self-regulation was referred to as influence
over one's own motivation, thought processes, emotional states and patterns of behavior
(Bandura, 1997; p.1). Additionally Bandura stated (1997) self-efficacy was essential for self-
regulation success through thought, affect, motivation, and action.
Social Cognitive Theory of Self-Regulation
Albert Bandura (1991) posited human behavior was comprehensibly motivated and
regulated by the cyclical process of self-influence. A person’s intention or desire alone does not
have much effect if that person was not capable of exerting influence over his or her own
motivation and behavior (Bandura & Simon, 1977). Hence, Bandura (1991) furthered the self-
regulation concept to the social cognitive theory of self-regulation (SCTSR). Bandura (1991)
stated that, “the major self-regulative mechanism operates through three principal subfunctions.
3 (p.248). These psychological subfunctions must be developed and mobilized for self-directed
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57

change. He further posited that self-regulation also encompasses the self-efficacy mechanism,
which plays a central role due to its strong impact on thought, affect, motivation, and action.
Self-Monitoring. The first, self-monitoring, enables motivation when one pays attention
to their own performance, the environmental factors involved and the immediate and distal
effects produced. This process was not simply auditing one’s behavior, but consists of pre-
existing cognitive structures and self-beliefs that wield influence over behavior. Additionally,
mood states can effect how behavior was self-monitored. The consistency, reliability and
timeliness of self-monitoring are crucial factors in determining the success of self-regulation.
Through consistency one can establish important self-diagnostic information by observing
thought patterns, emotional reactions and systematic behaviors to determine patterns.
Mindfulness practices may help regulate these states of varying adaptive and maladaptive
thoughts and feelings with greater attentional awareness, and more timely to strengthen self-
monitoring frequency and effectiveness as stated by Bishop and colleagues (2004) that was
enhanced by the superior parietal cortex increased ability to direct attention as reported by
Sutherland (2014) and Bhatia et al. (2003) and strengthened synapse connections due to
simulating the deferral mode network (Sinclair, 2014) . This self-diagnosis of reoccurring
patterns can help one determine self-corrective changes necessary for obtaining a more positive
sense of self and providing attentional direction for self-regulatory control.
As one applies this mindful self-monitoring they are naturally inclined to self-establish
progressive goals for improvement without being prompted by an outside influence. Yet the
effects of self-monitoring can increase, decrease, or have no effect on the behaviors necessary for
goal attainment. Furthermore, self-directedness comes into play by activating self-reactive
influences for necessary corrective choice and goal attainment. Bandura (1991) underlined the
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significance of establishing progressive goals by comparing varying degrees of personal goal
setting. Those who set no goals for themselves achieve no change in effort, while those who
seek to maintain a goal surpass the prior, and those who desire to go beyond the established goal
surpass all the others.
One self-reactive influence was temporal proximity, which allows self-directed change
on immediate and present behavior rather than it’s distal effects. This aspect appears to
determine the quality and effectiveness of self-directed change. A second self-reactive influence
was informativeness of performance feedback (Bandura, 1991). One must be aware of how one
was doing to perpetuate an increase in performance. A third self-reactive influence was
motivational level (Bandura). If one was motivated to self-monitor for goal attainment, then
self-evaluative reactions to behavior and progress enabled goal attainment. Lastly the valence of
behavior affected the strength of self-reactive influences. If one was self-satisfied with
performance in a valued domain, then aspirations are raised that can augment behaviors. On the
contrary, self-displeasure devalued behaviors and a neutral satisfaction had no significant effect
on behaviors. Focusing on success or failures can have polarizing affects. Whereas, only
focusing on failures may have positive effects by directing attention to possible causes for
failure, which suggests corrective actions. Behaviors can also be influenced by its amenability to
voluntary control; i.e. behaviors that are amenable to change remain changed, but behaviors that
are resistant to change have only transient influence from self-monitoring application and
reappeared as temporal distance increases (Bandura). Bishop and colleagues (2004) proposed
that mindfulness increases the ability to reduce the negative self-regulatory influences of these
self-reactive states, which may propel self-regulation positively.
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Judgmental. The second sub functional structure of self-regulation was the judgmental
sub function (Bandura, 1991). Any action gave rise to self-reactions through a judgmental
function that was composed of several subsidiary processes. The first was development of
personal standards, which guide self-direction for judging and guiding one’s actions (Bandura).
An individual’s evaluation based on personal standards determined if a specific performance was
considered favorable or unfavorable. Personal standards are developed from information offered
by three modes of influence; social modeling, evaluative reactions of others, and self-
construction (Bandura, 1986). Social modeling was extremely powerful in transmitting
standards when based on shared values and mutual support (Bandura). Additionally, the
evaluative support of an influential person prescribed standards in one’s social environment
helps influence personal standards. Finally, one may construct their own standards through
reflective processing of compound sources of direct and vicarious influences. A byproduct of
mindfulness was temporal perception rather then inherent of oneself, which may allow for a
more realistic processing of events and subsequent establishment of personal standards (Bishop
et al., 2004).
Often times, there was no absolute value to measure one’s performance; consequently
one must evaluate their performance based on other’s attainment. The second subsidiary process
of the judgmental component was called social referential comparisons and requires three
sources: social, self, and collective (Bandura, 1991). A key link of mindfulness and social
cognitive theory of self-regulation was social comparison, specifically; a student may compare
themself to a similarly performing student within their classroom to determine relative standing.
With self-comparison one continuously uses previous behavior as a reference for judging their
behavior. In collective comparison, one judges themselves against a group or culture’s collective
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principles. Bishop et al. (2004) propose that mindfulness allows negative judgmental thoughts to
be less influential on the observer’s perception, and their subsequent heightened awareness and
attentiveness effects produced strengthens social referential comparisons positively.
A third pertinent judgmental component of self-regulation was valuation of activities
(Bandura, 1991). If a person holds no value for an activity then self-reactions are not triggered.
Conversely, if the activity affects one’s welfare and self-esteem, then their performance
judgment activates self-reactions, which triggers self-regulation. The last judgmental
component was perceived performance determinants (Bandura). One can hold themselves
accountable for successes or failures derived from their own abilities or lack there of. Also, one
can hold external conditions for being at fault due to unusual circumstances, insufficient
capabilities, or unrealistic demands. Considering mindfulness increases a sense of well-being as
proposed by Bishop et al. (2004) and Kabat-Zinn (1990), self-esteem can increase and strengthen
valuation of activities, which hypothetically should enhance self-regulation skills.
Self-Reactive. This judgmental influence sets the stage for the third influence, self-
reactive (Bandura, 1991). Self-reactive was the process by which personal standards regulate a
course of actions. Consequently self-regulatory control was obtained by constructing incentives
for individual actions and anticipated reactions to behaviors as measured against internal
standards. This causes one to behave in a manner that produced positive self-reactions and desist
from behaviors that create self-reprimand. Consequently this process produces self-motivation
incentives that drive one towards goals by implementing the proper behaviors. These self-
motivating incentives may be either real outcomes or self-evaluative reactions. Specifically, one
can use incentives for a higher academic grade by completing homework and doing well on
quizzes. The completion of homework and resulting positive quiz grades are the real outcomes,
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while a poor performance on homework provided a self-reaction to study hard for a quiz and
obtain the real outcome of an ‘A’. In addition, one can use tangible motivators to reward them to
promote timely accomplishment as opposed to procrastination of attainment (Bandura, 1986).
As an illustration, one may reward them with a movie for accomplishing a 90% or better on a
unit quiz. This rewarding process allows one to accomplish more than those who monitor their
own behavior and set goals for themselves without a rewards system in place. This strategy also
works with externally prescribed activities. However it was important to keep in mind that most
people value their self-respect and satisfaction more highly then material rewards (Bandura,
1991).
Mindfulness may offer assistance in maintaining a healthy self-reactive ability when
negative challenges are met in obtaining goals. Bishop and colleagues (2004) propose
rumination plays a central role in exacerbating negative effects of self-efficacy when a goal was
not being fulfilled. Thus, mindfulness can disengage one from ruminative thinking and thereby
reduce cognitive vulnerability towards a negative perspective of self and self-efficacy.
Self-Efficacy. The functioning of the social cognitive theory of self-regulation system
was centrally dependent on the self-efficacy mechanism (Bandura, 1991). Self-efficacy was the
belief an individual has about their capability of appropriate self-functioning within internal and
external situations (Bandura). Simply put self-efficacy was one’s beliefs about their ability to do
the task (Linnenbrink & Pintrich, 2003). One’ s belief in their own efficacy influences the
choices they make, the goals they set, the effort put forth, the ability to persevere when
challenged, ability to discriminate between self-obstructing or self-supporting thought patterns,
possibility of depression, and the amount of stress experienced. Consequently self-beliefs of
efficacy play a central role in how the self-regulatory sub functional system operates (Bandura).
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They affect self-monitoring and cognitive processing of one’s performance and resulting
outcomes. Accordingly, people who consider themselves as efficacious attribute their failure to
insufficient effort, whereas people who consider themselves as inefficacious attribute their
failure to low ability. If one changes their self-efficacy beliefs then motivation and attainment
can also change. The more self-efficacious a person considers themselves to be, the higher the
goals they set. Motivation can be demonstrated through commitment to goals, self-expectant
outcomes, and self-efficacy beliefs. The setbacks that arise along the way can be motivating or
discouraging, depending on the degree of self-efficacy. A weak self-efficacy allowed one to be
easily dissuaded by obstacles or failures. A strong self-efficacy gave renewed commitment when
faced with failure that results in achievement. Furthermore, healthy self-efficacy contributes to
enduring interest in activities. In fact, self-efficacy determines interest rather than ability. The
more refined an individual self-efficacy conceptual interest was directly related to actual
engagement and learning (Linnenbrink & Pirntrich, 2003). Consequently the inherent power of
self-efficacy gives rise to achievement more so then one’s ability (Bandura).
Self-efficacy was key in promoting students’ engagement, learning, and better
achievement as posited by Linnenbrink and Pintirch (2003). They use a framework of three
constructs to discuss this issue. They are behavioral engagement, cognitive engagement, and
motivational engagement which self-efficacy plays a pivotal role in all. The first construct,
behavioral engagement, was an observed behavior by the teacher and can be defined by when a
student seeks help from teachers or peers in order to learn and understand the material
(Linnenbrink & Pintrich, 2003). Students with strong efficacy beliefs are more likely to exert
effort in the face of complexity and persist at a task when they possess the necessary skills.
Students with weaker efficacy perception are likely afflicted with self-doubts and give up easily
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when confronted with complexity even if they have the skills and knowledge to perform the task.
This positive association was based on studies in academics and other settings (Bandura, 1997;
Pintrich & Schunk, 1996). Subsequently, the role self-efficacy plays was directly related to the
quantity of effort and the willingness to persist at tasks (Bandura). This willingness to persist at
a task can manifest in help-seeking aspect. A positive correlation has been determined between
self-efficacy and help-seeking (Pintrich & Schunk, 1996). When a student possessed strong self-
efficacy they did not feel inhibited to ask for help; however, a student with low self-efficacy
refrained from asking feeling they were judged as unable or dumb (Linnenbrink & Pintrich,
2003). Hence, self-efficacy was positively related to students’ behavioral engagement, learning,
and better achievement.
The second construct of self-efficacy was cognitive engagement and more subtle then
behavioral engagement. For instance, a student may be focused on the teacher’s direct
instruction but thinking about something else. Cognitive engagement was when a student thinks
deeply about content to be learned, to think about what they know and do not know, to use
different strategies for learning that increase understanding, and think critically and creatively
about the material (Linnenbrink & Pintrich, 2003). Research shows that students use strategies
for learning that are linked to self-efficacy and achievement (Pintrich & Schrauben, 1992).
Students with high self-efficacy are more likely to be cognitively engaged then those who have
lower self-efficacy beliefs (Linnenbrink & Pintrich, 2003). Elaboration and organizational
cognitive strategies reflect an active learner who tries to do something cognitively with the
content then mere memorization. Hence, the quality of cognitive engagement reflects the quality
of student’s effort in the task, while simple quantity of effort, i.e. rehearsal, reflects behavioral
engagement. In addition, researchers have shown that students who are cognitively engaged are
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metacognitive in their learning (Weinstein & Mayer, 1986). A metacognitive student was one
who reflects on their own thinking, actions, and behavior to monitor and regulate their own
learning (Linnenbrink & Pintrich, 2003). Finally, higher levels of cognitive engagement are
associated with better learning and higher levels of achievement (Pintrich & Schrauben, 1992;
Weinstein & Mayer).
The third and final construct of self-efficacy was motivational engagement. Motivational
engagement was increased interest to learn, value of learned concept, and positive affective
experience while one was learning. Motivation research has shown that students as young as
first grade can distinguish their self-efficacy of a task from their liking or how useful the task
was. All of these aspects of motivational engagement can be related to actual learning and
achievement (Linnenbrink & Pintrich, 2003). Personal interest in a task results in higher
learning and comprehension (Eccles et al., 1998; Pintrich & Schunk, 1996). Value beliefs
operate by increasing the level of cognitive engagement and use of various cognitive and
metacognitive strategies ((Pintrich & Schrauben, 1992). Lastly, positive and negative affect can
be directly linked when research shows that high levels of anxiety, particularly test anxiety in the
classroom, are negatively related to learning and performance (Zeidner, 1998). Hence, research
suggests that self-efficacy was positively related to adaptive motivational beliefs and negatively
related to negative emotions. Therefore, self-efficacy was a motivational construct that was
evidently related to other motivational constructs, including personal interest and values such as
utility and importance beliefs (Pintrich & Schunk). Moreover future research should be focused
on how self-efficacy and these other motivational construct work together to influence students’
engagement in schoolwork. In summary, it was likely that all three components of engagement
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are correlated. However as to what component can exist with or without another needs to be
researched more.
Considering the nature of this study and its analysis of self-efficacy as an integral
dependent variable affected by mindfulness, the nature of self-efficacy and its maturation over
time needs to be defined. Zimmerman (2000) offers a rare description of the self-efficacy
maturation phenomena. He stated that self-efficacy does not carry trait like stability across time
and setting like self-beliefs. Consequently it can be assumed to be responsive to changes in
personal context and outcomes, whether they are experienced directly, vicariously, verbally, or
physiologically. As a result of this sensitivity, self-efficacy beliefs are studied as indicators of
initial individual differences and more importantly studied as indicators of change during times
of interventions.
Mindfulness can offer a principal role in maintaining self-efficacy through
disengagement of self-degrading thoughts that may arise when obstacles or failures are met
(Bishop et al., 2004). These self-degrading thoughts are recognized simply as thoughts and
subsequently students did not engage in former negative patterns that may result in low self-
efficacy and poor academic performance. Moreover, mindfulness practices provide
opportunities to gain insight into the nature of thoughts and feelings as passing events in the
mind rather than as inherent aspects of self (Teasdale et al., 1995). It can force one to step out of
the war with their thoughts and feelings about self and give up ineffective experiential avoidance
strategies (Bishop, et al.). Consequently, enabling self-efficacy to remain in tact and hence grow
from further positive interactions and use. Lastly current research from the National Center for
Complementary and Alternative medicine has found through brain mapping the precuneus and
the posterior cingulate had more gray matter or brain cells that suggests an increase in areas key
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to our concept of self (Sutherland, 2014). Consequently suggesting a positive link to the
simultaneously potential growth of self-efficacy.
Effects of Poor Management in Self-Regulation
This self-regulation process through personal standards, conditional self-evaluation, and
motivational effort provides a continual source of personal satisfaction, interest and self-esteem
(Bandura, 1986). Nonetheless, poor management of the self-regulation process can create
dysfunctions, which may cause lack of motivation, boredom, poor self-efficacy, and reliance on
momentary external stimulation for personal satisfaction. A continual internalization of
dysfunctional self-evaluation standards can produce emotional effects that undermine
performance motivation and psychological well-being. Moreover, these individuals can
experience vast amounts of self-inflicted stress, despondency, self-devaluation, and depression
(Bandura, 1991; Kanfer & Hagerman, 1981; Rehm, 1982). When a student was disengaged and
apathetic in a classroom there was a positive association between self-efficacy beliefs and
fortitude of effort (Bandura, 1997; Schunk, 1989). A student with low self-efficacy was faced
with difficulty they become plagued with self-doubts and give up even thought they may possess
the required knowledge or skills (Bandura, 1997; Pintrich & Schunk, 1996).
In self-regulation the individuals prone to depression misperceive their performance and
negatively distort their behaviors (Bandura, 1991). Conversely, healthy self-regulating
individuals remember successes and recall fewer failures. The depressed self-regulator’s
minimization of successes and emphasis on failures can give to despondency. In a desperate
attempt to dig oneself out of this hole, an individual sets higher unrealistic goals, which
perpetuate the despondency and depression. Therefore, the depressed individual was quick to
blame him or herself for failing. Additionally the individual compares themself to others with
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greater self-depreciating means and less value then those non-depressed individuals. This
polarizing effect spills over to self-reaction as well. The depressed individual reacts with less
self-rewards then non-depressed individuals and more self-critical for similar failures. As a
result, this despondency and self-devaluation feed on each other, which can create an apathetic
emotional state (Bandura).
Moreover, a weak self-efficacy can produce the side effect of learned helplessness
(Pintrich & Schunk, 1996). In learned helplessness, a student possesses low outcome
expectation no matter what exertion was placed into studying or effort into comprehending.
Hence, they believe they cannot control their own behavior and that there was no relationship
between behavior and outcome. In this situation research has consistently demonstrated that
students with learned helplessness are less likely to persist at tasks and consequently drop in
performance (Pintrich & Schunk, 1996).
Another contributor to apathy surfaces when students performing low in academic
performance and self-efficacy are less likely to seek help in the classroom (Karabenick & Knapp,
1991; Newmann, 1990; Ryan & Printrich, 1997). The research suggested that low self-efficacy
and low achieving students feel that by asking for help their teachers and peers thought they were
incapable or dumb, which hindered them in asking for help. Variations of this unwillingness to
ask for help can be influenced by personal goal orientations or classroom goal structure.
Finally, low motivation can be a detrimental element causing apathy within a student.
There are opposing theories as to the causal relationship of motivation and self-efficacy. The
first theory stated student’s motivation or liking of a task or topic area engages them into the
activity and self-efficacy develops (Renninger, Hidi, & Krapp, 1992). Consequently a student
showing apathy in a class may be bombarded with interest-first strategies as constituted by our
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cultural foundational belief in development of motivation and self-efficacy. The opposing theory
as stated by Bandura (1997) was that students’ motivation and value for an activity might have
developed from judgments of competency or efficacy for an activity. Moreover, there was
empirical evidence that emotions and efficacy have a reciprocal relationship, where one can
affect the other (Wright & Mischel, 1982).
Naturally, students with lower levels of self-efficacy usually experience negative
emotions such as anxiety or depression (Bandura, Barbaranelli, Caprara & Pastorelli, 1996;
Harter, 1992; Meece, Wigfield, & Eccles, 1990; Pintrich & De Groot, 1990; Pintrich, Roeser, &
De Groot, 1994). This increase in negative emotions most likely occurs because students with
low self-efficacy feel they cannot attain stated goals and become depressed at the hopelessness of
the situation. The increase in anxiety may result from the same type of student who values
performing well but feel they do not possess the skills to do so and consequently anxiety was
produced.
Mindfulness plays a crucial role in re-establishing an optimal equilibrium for positive
self-regulation. Bishop and colleagues (2004) posited that mindfulness encourages individuals to
surrender to the war of self-deprecating thoughts and feelings, thus altering these negative
responses. Additionally, Miller, Fletcher and Kabat-Zinn (1995) proved the effectiveness of
altering negative responses by observing a decrease in panic attacks and avoidance events when
mindfulness was applied. Thus, developed mindfulness can maintain healthy self-regulation
through remediation of negative responses.
Summary and Conclusion
Poor student self-regulation has been documented as the main cause of K-12 students’
lack of school readiness (Blair & Diamond, 2008). Moreover, research into individual
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differences in academic performance has signified that an important aspect of positive
educational performance was the extent to which students engage in self-regulatory activities
(McCann & Garcia, 1999). Furthermore Bandura et al. (1992) stated the importance of self-
regulatory factors for academic attainment. Considering our nation’s goal for students to be
college- and career-ready by 2020 and with the hopes of regaining our status as the world leader
in college completion rate, the improvement of students’ self-regulation for learning was the first
essential step to attain this goal.
The ability to enhance self-regulation strategies has been discussed in numerous studies;
however, what extent students’ engage in and maintain self-regulation for learning was the
quintessential question. As stated by Zimmerman (1989), self-regulated learning was “ the
degree that they are metacognitively, motivationally, and behaviorally active participants in their
own learning process” (p. 329). Consequently, it was necessary to address these core self-
regulative elements so that students can be active participants in their own learning.
The ancient art of mindfulness has been attributed to a wealth of beneficial qualities that
increase and maintain one’s own well-being. The literature explores the ability of mindfulness to
address the core self-regulative elements as stated by Zimmerman and Bandura (1991),
suggesting an intrinsic and significant positive link between mindfulness, self-efficacy and self-
regulation. Mindfulness has been found to positively impact the ability to motivate, increase
metacognition or self-monitor, and regulate behaviors through a healthy self-reactive and
judgmental perspective (Bishop et al., 2004; Black and Fernando, 2013; Broderick and Metz,
2009; Carmody & Velting, 2004; Flavell, 1979; Hyland (2009); Khalsa et al., 2012; Mendelson,
2010; Metz et al., 2013; Schonert-Reichl & Lawlor, 2010; Wisner et al., 2010; Wisner, 2013).
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This intrinsic relationship between mindfulness and self-regulation has begun to be
unveiled and explained by neuroscience. Researchers have found that mindfulness develops a
neurological positive foundation by providing the rest principle, which as stated by Sinclair
(2014) strengthens synaptic connection and increases learning. Researchers have begun to look
deeper into this phenomenon and found that mindful development may directly influence non-
reactivity by altering the connections between prefrontal cortex and limbic zones. Thus,
cultivating the non-reactivity through non-judgmental brain functioning and creating a formative
field for affective self-regulation to transpire as posited by Siegel (2007). Tying it all together,
neuroscience was detecting the ability of mindfulness to directly affect two of the three core
elements of self-regulation positively as defined by Bandura (1991)-- judgment and reactivity.
Future research will hopefully unlock further neurological insights into this intrinsic relationship
between mindfulness and self-regulation.
In sum, mindfulness attributes are innate in Bandura’s (1991) social cognitive theory of
self-regulation and the literature suggests the positive influence of mindfulness on each
individual sub component of self-regulation and self-efficacy. Consequently, the synergistic
effect of mindfulness on self-regulation has only begun to be explored. To date, only four
studies have been published that address the mindfulness-self-regulation relationship. Each
study implemented different mindfulness practices but all of them found a positive correlation
between mindfulness practices and increased self-regulation (Caldwell et al., 2010; Howell &
Buro, 2011; Sibinga et al., 2012; Wisner et al., 2010). As a result of these limited promising
findings and in hope of increasing self-regulative learning in students for addressing the
national’s educational challenge of poor self-regulation, this study analyzed the effects of
mindfulness on self-efficacy and self-regulation in learning for academic performance.
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CHAPTER THREE: METHODOLOGY
The United States has established a goal to move from 18th to 1st in the world for college
completion rates by 2020 (Foley et al., 2013). This goal requires immense changes in education,
not only with the system but also teachers and most importantly our students. But, can our
students accomplish this? Do they have the belief in themselves, the motivation to learn, and the
willingness to focus and think about how they learn? Especially since poor self-regulation has
been documented as the main cause of K-12 students’ lack of school readiness (Blair &
Diamond, 2008). Do they have the self-efficacy or belief in themselves and the ability to self-
regulate and think about how they learn? Therefore the challenge becomes how do schools
foster self-efficacy, to activate and engage self-regulation for learning in our students? This
study posited a solution for rekindling self-efficacy and self-regulation that is as old as
humankind itself? A solution that has proven to ignite the natural ability to observe one’s own
mind and emotions without reacting impulsively but with greater capacity to see relationships
between thoughts, feelings, and actions. A solution enables one to dispassionately discern the
meaning and causes of experience and behavior through self-regulation of directional attention,
metacognition, and self-efficacy (Bhatia et al., 2003; Bishop, et al., 2004; Flavell, 1979;
Sutherland, 2014). This study proposed a solution in mindfulness.
There have been substantial studies of the application of mindfulness in education with
respect to enhanced emotional self-regulation that build stress resilience and adaptive
interpersonal capabilities (Bhatia et al., 2003; Davidson & Kabat-Zinn, 2004; Dreyfus, 2011;
Howell & Buro, 2011; Hyland, 2009; Langer, 2009; Siegel, 2007; Wisner et al., 2010). However
there has been little research if any with respect to the impact of mindfulness on self-efficacy and
self-regulation, and subsequent impact on academic achievement. Sibinga et al. (2012) stated the
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need for additional research to explore the impact of mindfulness on self-regulation, the duration
of the effect, and related social, psychological, and behavioral outcomes. Consequently this
study uncovered the benefits of mindfulness towards self-efficacy, self-regulation and academic
performance in middle school students’ in their pursuit to become college- and career-ready.
The purpose of this chapter was to describe and justify the design of the study as a
meaningful approach to developing greater understanding of the research questions. The
essential research questions formulated was based on the statement of the problem and
previously identified knowledge gap in current research. The research questions are as follows:
1. Was there a significant difference in students’ maturation levels of mindfulness
between the treatment and control groups over the duration of the study?
1a. Was there a significant difference in students’ maturation levels of self-
regulation between the treatment and control groups over the duration of the
study?
1b. Was there a significant difference in students’ maturation levels of
self-efficacy between the treatment and control groups over the duration of the
study?
2. Was there a difference in the effect of mindfulness on self-regulation between
treatment and control groups while controlling for entry levels of self-regulation and
mindfulness?
2a. Was there a difference in the effect of mindfulness on self-efficacy between
treatment and control groups while controlling for entry levels of self-efficacy and
mindfulness?
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2b. Was there a difference in the effect of mindfulness on academic performance,
GPA, between treatment and control groups while controlling for entry levels of
academic performance, GPA, and mindfulness?
3. Were students’ level of mindfulness relative to the degree of impact on self-
regulation, self-efficacy and do those variables significantly impact student academic
performance?
The hypothesis was generated from these research questions and based on findings from
previously conducted research on the topic. Consequently, the hypothesis stated the application
of the mindful method program, YES!, has a significant positive impact on students’ self-
efficacy and self-regulation sub functions; self-monitoring, judgmental, and self-reactive, which
in-turn positively impact students’ academic performance, GPA. The lens used to analyze the
hypothesis and research questions was the self-cognitive theory of self-regulation.
In order to determine the causal effect of a mindful method intervention on self-efficacy
and self-regulation, a concurrent transformative mixed methods research design used quantitative
and qualitative approaches was used to depict the essential or invariant structure of the
mindfulness experience on self-regulation, self-efficacy and academic performance experience as
stated by Creswell (2013) and Merriam (2009). The first field of quantitative data collected at
three different time periods from both treatment and control groups was a self-report longitudinal
survey design implemented to provide a quantitative or numeric description of attitudes and
opinions of middle school students in regards to mindfulness, self-regulation, and self-efficacy
administered before the mindful method intervention, immediately after the intervention, and one
month after the mindful method follow-up program. The measurement tools used were the
Mindful Attention Awareness Scale (MAAS), the Short Self-Regulation Questionnaire (SSRQ),
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and the self-efficacy subscale (SE) of the Motivated Strategies for Learning (MSLQ). This pre-
and post-survey research design method involved multiple variables and treatments collected
through data to support or refute the research questions as stated by Creswell (2013). The
second field of data collected was existing data from the school records on individual students’
of both treatment and control groups in regards to: standardized testing scores; free and reduced
meals status; English Language learner level; and discipline referrals and suspensions. The third
field of data collected from both treatment and control group students was self-reported student
opinions on four open-ended questions at the end of the on-line survey addressed focus, goals,
confidence, and learning in the classroom. These three fields of quantitative data collected
helped to determine the causal effect of the mindful method intervention on self-efficacy, self-
regulation, and academic performance.
The quantitative design allowed for comparisons to be made between several variables
such as independent, dependent, mediating, moderating, or control variables (Creswell, 2013).
The independent or latent variable was the mindful method intervention used to develop
mindfulness, YES!. The dependent or observable variables that depend on the independent
variable are self-efficacy, self-regulation, and academic performance. The intervening and
moderating variables were determined as the intervention and surveys are applied and the
structural equation model implemented. Moreover this structural equation model was applied to
determine causal path and identify the collective strengths of multiple variables (Creswell). The
quantitative data analyzed was from existing student data, student performance data, and a third
set of data gathered from pre and post mindful method intervention surveys used a Likert scale
based on mindfulness, self-regulation, and self-efficacy.
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The mindful intervention method utilized to develop and optimize mindfulness was
called YES!. YES! is committed to providing youth with the tools for a healthy body, a healthy
mind, and a healthy lifestyle (YES! for Schools, 2014). This twenty hour experiential
curriculum provides youth with the tools and life skills to manage stress and emotions. YES! for
Schools declared once students learn how to manage their stress in a healthy way then students
demonstrate greater confidence and motivation to succeed in school and make healthy choices
when faced with life’s challenges (YES! for Schools). The healthy body module encourages
healthy food choices and physical fitness, which includes yoga. The healthy mind module
includes stress management and relaxation techniques that encourage a positive mental attitude
through targeted breathing techniques that reduce stress, anger, anxiety and depression; improve
focus and concentration; and enhance learning ability. The programs’ foundational technique is
called SKY breath, which to date has a number of research studies that identified the
neurological and behavioral benefits of its practice as previously cited. Additionally meditative
techniques are taught that help cultivate a calm state of mind, such as focus meditation, which
some of the students refer to later in the study as focus technique. The healthy lifestyle module
includes social emotional learning and life skills in conflict resolution through interactive
processes, teamwork exercises, games, and practical knowledge to make healthy choices in
school and life.
The Institutional Review Board (IRB) of the University of Southern California approved
the study, and all necessary clearances were obtained from: the school principal; the classroom
teacher; the sample population and parents, and the instruments of measure governing bodies.

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76

Sample and Population
The goal of this study was to make a significant positive correlation effect of the mindful
intervention, YES!, increase in self-efficacy and self-regulation, which in-turn would increase
academic performance, GPA, to create better-prepared college- and career-ready students. It is
hoped by identifying the direct causal connection between mindfulness and self-efficacy, self-
regulation, and academic performance will implore more educators, administrators and policy
makers to embrace and implement the mindful method YES! approach to education. Thus
embarking on a more realistic and sincere attempt to achieve our national educational goal to
lead the world in college completion rates by 2020. With only six years to realize this goal and
to showcase the capability of mindful method practices increasing self-efficacy and self-
regulation for attaining this goal, the study focused on 6
th
, 7
th
, and 8
th
grade students from one
middle school, which were both ethnically and economically diverse. The diversity of students’
economic status allows for measurement of varied economic backgrounds, including 48% of the
student body qualifying as socioeconomically disadvantaged, which is the target focus area for
Congress’s, College Access Challenge Grant Program as reported on the school accountability
report card (SARC) (SARC, 2014; USDOE, 2014). Additionally the school’s district was a Title
1 funded district in its 4
th
year of program improvement (SARC).
This uniquely diverse California middle school houses 1000 students and 44 highly
qualified teachers. The collective student body did not reach the overall average yearly progress
(AYP) goal, nor did they meet the English Language Arts and Mathematics AYP percent
proficient goals (SARC, 2014). Moreover, the school’s diversity was reflected in the varied
advanced and proficient standardized testing performance according to ethnicity subgroups:
Hispanic 54%, Black of African American 51%, and White 84% (SARC). However, the overall
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
77

percentage of students that achieved proficient or advanced levels in standardized testing was
above the California state average in all four-core subject areas. The demographics of the student
body are 51% Latino, 31% White, 11% African American, 5% Asian and 1% students of 2 or
more ethnicities. English language learners make up 22% of the student body. The school
qualifies as a federally funded Title 1 school since appropriate annual yearly progress was not
made which identifies the school for this program improvement. The student and expulsion rate
of the school was 5%, which is one percent below the state average (SARC, 2014, CDE, 2014).
The Hispanic and Asian students are mostly first generation Americans, which meant
their parents were born in other countries and immigrated to Los Angeles. In regards to the
Hispanic population, many of the parents do not have a high school diploma from their home
country but instead obtained a 5
th
or 6
th
grade education. These students’ parents are dual
income earners with a majority of parents holding two or more jobs. In some cases this leaves
the middle school student taking parental responsibilities for younger siblings until the parent
returns home from work in the evening, which may often leave little time for homework.
Moreover, in some cases the parents are unable to help the student with homework due to lack of
educational knowledge.
An introspective analysis on the impact of developing mindfulness on self-efficacy and
self-regulation was used to steer the sampling. Consequently the first criterion was that they are
middle school students representing the 6
th
, 7
th
, and 8
th
grades. The second criterion was to
designate a treatment and control group of students. Students who participate in the mindful
method program, YES!, on a regular and full-participatory basis represented the treatment group.
The control group did not receive any mindful method training. All three fields of data were
collected from both groups. The treatment and control groups were determined by randomly
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
78

selecting one 6
th
grade, one 7
th
grade, and one 8
th
grade physical education class to participate in
each group. Each physical education class was approximately 30-45 students.
The middle school represents ethnically typical academic performance standards that do
not demonstrate any atypical, extreme, deviant, or intensely unusual as stated by Patton (1990).
The reasoning for selecting a sample of middle school students as opposed to younger age
students was twofold. First the level of emotional and intellectual maturity was appropriate for
this study’s self-report study as opposed to elementary school children. Secondly, students’ self-
efficacy and self-regulation abilities are a key capacity for achieving college and career readiness
success in the core content areas.
The sample design was single stage as the study had access to the students and sample
populations can be chosen (Creswell, 2013). The sample populations were randomly selected
according to convenience sampling protocol as stated by Creswell, because classes of students
were chosen based on class availability and convenience within a specific time period consisting
of the Fall 2014 semester schedule. The YES! Intervention occurred in 15 physical education
classes, which are pre-determined by the school’s master schedule and consequently identified as
an element of the bounded system as stated by Merriam (2009). A treatment group of
approximately 325 students were assigned to receive the mindful method training, while a
second group of approximately 375 students were not assigned to the mindful method training
and thus serve as the control group. Thus a minimum sampling size of approximately 700
students was needed to assure that a reasonable analysis of this causal effect through a structural
equation model could be implemented. A natural attrition was expected of three students per
classroom is expected, which totals to 45 students for the study. However to properly protect the
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
79

study’s students the IRB warranted a signed Youth Assent Parental Permission Form, which 339
were returned and thus a sample population of 169 treatment group and 170 control group.
Instrumentation
Three different fields of data collection instrumentation were used in this mixed methods
study. The three different fields of data collected are; pre-and post- surveys, open-ended
question responses, existing student data and student performance data. The three different time
periods of data collection were before the YES! intervention, immediately after the intervention,
1 month, and four weeks later, 2 months, during the follow-up phase of the YES! intervention.
Existing Data
The first field of data instrumentation collected was students’ existing data. The
students’ existing data was found through the middle school’s internal data information system.
This data on students ranged from current grade, ethnicity, gender, and AVID college
preparatory intervention class. This data was collected for the treatment and control groups at
three specific points of time; immediately before the mindful method intervention training,
immediately after the mindful method intervention training, an one month into the mindful
method YES! intervention follow-up program.
Performance Data
The second field of data instrumentation collected was students’ classroom performance
indicators or progress report card grades at three specific points of time; immediately before the
mindful method intervention training, immediately after the mindful method intervention
training, an one month into the mindful method YES! follow-up program. The data was
obtained from the students’ 7-week progress report cards and teachers’ performance data
obtained from students’ core classes that quantitatively reflect their overall performance in a
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
80

single letter grade. An analysis of the pre and two post-performance data collections provided
rich data to further explain the self-regulation phenomena as a result of mindful method training.
Pre- and Post-Surveys
The third field of data instrumentation collected was pre- and two post on-line surveys
administered to both the treatment and control groups at the same three different points of time
during the semester as mentioned above. Student survey data was used to describe, explain, and
compare their knowledge, feelings, values, and behaviors through self-administered
questionnaires to help understand the benefits of the mindful method YES! on self-efficacy self-
regulation, and learning (Fink, 2009). Students’ mindfulness, self-efficacy, and self-regulation
was assessed at the same three specific points of time stated above and used the Mindful
Attention Awareness Scaled, the Short Self-Regulation Questionnaire, the self-efficacy scale of
the Motivated Strategies for Learning Questionnaire, and 4 qualitative short open-ended
questions.
To measure mindfulness, the Mindful Attention Awareness Scale (MAAS), which
assesses individual differences in the frequency of mindful stated over time, was used. The
MAAS was focused on the presence or absence of attention to, and awareness of, what has
occurred in the present rather than on attributes such as acceptance, trust, empathy gratitude, or
the various others that been associated with mindfulness (Shapiro & Schwartz, 1999). MAAS
measures dispositional mindfulness or a present-centered attention-awareness, which was
considered the foundation of mindfulness (Brown & Ryan, 2003).
Brown and Ryan (2003) drafted the original 184-item survey to reflect mindfulness and
mindlessness in general terms as well as specific day to day circumstances, which included
variations in awareness of and attention to actions, interpersonal communication, thoughts,
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
81

emotions, and physical states. After item reduction by the authors, the 55-items remained were
distributed across cognitive, emotional, physical, interpersonal, and other domains. Further
exploratory factor analysis showed a strong single-factor solution and almost identical factor
loadings. Consequently Brown and Ryan retained 15 items that loaded on the first factor. The
one-factor structure was confirmed by a confirmatory factor analysis on data from a sample of
college students. The internal consistency measured by Cronbach’s alpha was .82, and 4-week
test-retest reliability was indicated by Pearson r of .81 (Brown & Ryan, 2003).
The MAAS survey consists of 15 questions that use a 1-6 Likert scale from 1, almost
always, to 6 almost never, (Brown & Ryan, 2003) (see Appendix B). MAAS has shown to be
sensitive to individual differences in mindfulness (Brown & Ryan). Varying studies provided
evidence for the psychometric adequacy and concurrent validity of MAAS (Brown & Ryan,
2003; Johnson, Wiebe & Morera, 2013; Ledesma, Garcia & Poo, 2014; Mantzios, Wilson &
Giannou, 2013; Montes, Ledesma, Garcia & Poo, 2014; Morgan, Masuda & Anderson, 2013).
The MAAS was constructed to be free from attitudinal, motivational, and other psychological
phenomena. MAAS has shown to discriminate between groups expected to differ in degree of
mindfulness. Consequently the uses of MAAS as an instrument enabled this study to measure
the degree of mindfulness present within a student and compare this to the degree of self-
regulated learning demonstrated and hence determine significant correlations.
The Self- Regulation Questionnaire developed by Brown, Miller, and Lawendowski
(1999) and approved by the National Institute of Health. This questionnaire was developed to
assess seven self-regulatory processes through self-report. The seven dimensions or subscales
designed by Miller and Brown (1991) are; informational input, self-evaluation, instigation to
change triggered by perceptions of discrepancy, search for ways to reduce discrepancy, planning
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
82

for change, implementation of behavior change, and evaluation of progress towards a goal.
These seven processes were determined from a three-step theory of self-regulation formulated in
1970 by Kanfer (1970). Kanfer’s three-step theory on self-regulation was self-monitoring, self-
evaluation, and self-reinforcement. Brown (1998) posits that deficits in any of these self-
regulatory processes can contribute to disorders of behavioral self-regulation.
The Self-Regulation Questionnaire (SRQ) was a 63-item instrument designed to measure
the generalized ability to regulate behavior so as to achieve desired future outcomes (Carey, Neal
& Collins, 2004). The original SRQ assesses seven dimensions of self-regulation as posited by
Miller and Brown (1991). Each scale was rationally derived and contains 9 items. Brown
(1998) defined the Self-Regulation Questionnaire as, “the capacity to plan, guide, and monitor
one’s behavior flexibly in the face of changing circumstances” (p. 162). Miller and Brown
recommended using the total sum score as a measure of self-regulatory skills. The SRQ was
internally consistent, alpha=.91, and temporally stable over two days, r(83)=.94. An initial
psychometric analysis of the SRQ found one principal dimension rather than specific dimensions
corresponded to the rational subscale. Consequently Carey, Neal, and Collins (2004) found a
single dimension structure, which 31 items loaded significantly. They called this 31-item
instrument assessment the Short Self-Regulation Questionnaire (SSRQ) (see Appendix A for
original survey). However a follow up psychometric analysis conducted by Neal and Carey
(2005) of the SSRQ found that a one-dimension solution was not fully supported; however, a
two-dimension solution with statistically significant correlated factors was demonstrated. The
two dimensions identified were impulse control and goal setting behavior (Neal & Carey, 2005).
The 31-item SSRQ correlated highly with the original 63-item SRQ. The SSRQ was internally
consistent (alpha = .92) and temporally stable over two days, r=.96. Consequently the 31-item
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
83

SSRQ survey was administered to determine students’ ability to self-regulate through the two-
factor lens of impulse control and goal setting.
To measure self-efficacy, the Motivated Strategies for Learning Questionnaire, (MSLQ)
self-efficacy scale was used. A team of researchers from the National Center for Research to
Improve Postsecondary Teaching and Learning (NCRIPTAL) and the school of education at the
University of Michigan developed the MSLQ measurement (Pintrich, 1991). The MSLQ was a
self-report instrument designed to assess college students’ motivational orientations and their use
of different learning strategies for a college course. The MSLQ was based on a general cognitive
view of motivation and learning strategies (Pintrich). There are essentially two sections to the
MSLQ, a motivation section, and a learning strategies section. There are 15 different scales on
the MSLQ that can be used together or singly (Pintrich). All scales were constructed by taking
the mean of the items that make up the scale, such as the self-efficacy scale.
For the purpose of this study, the self-efficacy scale, which represents students’
judgments of their capability to do the course work, was used (Pintrich, 2004). The self-efficacy
scale was a self-appraisal of one’s ability to master a task. Self-efficacy includes judgments
about one’s ability to accomplish a task as well as one’s confidence in one’s skills to perform
that task (Pintrich, 1991).
The MSLQ’s confirmatory analysis of the motivational analysis revealed five constructs
the self-efficacy sub-scale questions helped address. These five constructs were: intrinsic goal
orientation, extrinsic goal orientation, task value, control beliefs about learning, and self-efficacy
for learning and performance (Pintrich, Smith, Garcia & McKeachie, 1993). The MSLQ’s self-
efficacy subscale suggested the following constructs were valid measures of the motivational and
cognitive constructs: intrinsic goal orientation, extrinsic goal orientation, task value, control
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
84

beliefs about learning, and self-efficacy for learning. The following positive motivational belief
constructs of the self-efficacy subscale were positively associated with the use of cognitive,
metacognitive, and resource management strategies: intrinsic goal orientation, task value, self-
efficacy for learning, and control beliefs about learning.
Pintrich et al. (1990) adapted the MSLQ for administering the measurement tool to 173
seventh graders from a predominantly White, middle-class, small city school district in
southeastern Michigan. There were 100 girls and 73 boys with a mean age of 12 years and 6
months. Additionally the sample of students included a range of student achievement levels.
The students’ rated themselves on a seven point Likert scale from “not at all true of me” to “very
true of me” in terms of their behavior in a specific science or math class. The self-efficacy scale
designed by Pintrich and DeGroot (1990) demonstrated an internal consistency of Alpha .89 and
consisted of nine items regarding perceived competence and confidence in performance of class
work (see Appendix C for SE Questionnaire). The multivariate test for self-efficacy was
significant. Pintrich and DeGroot research found that students with higher self-efficacy were
more likely to report use of cognitive strategies and self-regulatory strategies, thus demonstrated
the significant impact of self-efficacy towards self-regulation.
Consequently the pre- and posts on-line survey consisted of three measurements to
collect and analyze data for identifying the validity of this study’s research questions (see
Appendix D for entire student survey). The first was a quantitative measurement tool, MAAS, to
determine the degree of mindfulness obtained by a student. The second measurement, SSRQ,
determines the degree of self-regulation acquired at the time of the survey. The third
measurement instrument was the self-efficacy questions from the Motivation Strategies for
Learning Questionnaire. Additionally, four open-ended questions appeared at the end of the
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
85

survey to address mindfulness, self-regulation, and self-efficacy to better understand the
phenomena (see Appendix E for survey’s open ended questions). Concurrent and convergent
validity (Campbell & Fiske, 1959) of these measures was established through factor analysis,
and was found to at an adequate level. The reliability of these existing instruments; SSRQ,
MAAS, and MSLQ were determined by their high internal consistency and stability reported by
Cronbach alpha; thus, one can draw meaningful and useful inferences from the scores on these
instruments (Creswell, 2013).
Data Collection
The convenience sample groups selected are from the middle school’s classes. Random
selection was used to determine which classes would receive the mindful method treatment and
which classes would not receive the mindfulness treatment. Hence a treatment group and a
control group were determined.
In order for trends to be captured in data analysis, the data was directly identifiable so
existing data, performance data, and survey data can be linked through a coding system. An
essential step in the quantitative design study and IRB protocol was to gain proper consent from
the participants when identifiable data was used. The importance of this step allowed the data to
be collected and analyzed by cross-referencing data according to an individual student for
establishing inter-item correlations and trends. To gain consent for this pilot study two steps
were taken, the first step was to gain permission from the principal to gather data then administer
the surveys to the students. The second step was to give the students an assent form and the
parents a consent form. These assent and consent forms identified the purpose of the study,
invite students to participate in the study, inform students of their participation involvement,
ensure confidentiality of data obtained; and state investigator and IRB contact information.
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
86

Collection of Pre-existing Data
Pre existing student data was obtained on every participant prior to the online survey
collection from the following categories; ethnicity, gender, grade, report card grades, and
identifying participation in the AVID college preparatory program. This data helped to identify
specific characteristics of the sample population.
Collection of Student Performance Data
Student performance data was collected from three progress reports distributed over the
semester. The progress report cards state the current grade for a student in every enrolled class.
The reported grades can range from A+ to F. The first progress report card grades were posted
immediately before the YES! intervention began. The second progress report card grade was
posted immediately following the YES! intervention. The third and final semester report card
grades were posted one month after the YES! intervention was administered.
Collecting the Pre-, Post-, and Follow-up Survey Data
The participants in both convenience sample groups completed pre and post on-line
comprehensive surveys, which included the MAAS, SSRQ, MSLQ-SE (self-efficacy scale only),
and 4 open-ended questions (see Appendix C for the entire student survey) without having a
previous knowledge on the nature of this study. The pre and post-surveys were conducted at
three different time periods. The first was immediately before the mindful method intervention.
The second was immediately after the mindful method intervention. And the third was 1-month
after the mindful method intervention. The survey was delivered on-line with every student
having their own computer for keying in their answers to identical questionnaires. All
participants had up to ninety minutes to compete the on-line survey. The principal investigator
administered the on-line surveys, only answering technical questions for proper technical
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
87

completion of the survey. The mindful method intervention, YES!, was administered to the
treatment group over a four-week period in their physical education class. The control group did
not receive the YES! training and thus continued on with their normal physical education class
curriculum.
Data Analysis
The inferential statistics tests to be used to examine the research questions relationships
among variables in this study are regression analysis tests, considering the categorical
information collected from the control and treatment groups based on the independent variable,
mindfulness, and the continuous information on the dependent variables, self-efficacy, self-
regulation, and academic performance (Creswell, 2013). Consequently three different bi- and
multivariate inferential statistical analyses were run as stated by the Institute for Digitial
Research and Education (IDRE, 2014)
The first statistical analysis was a one-way co-variant analysis (ANOVA) to look at
difference between the control and treatment groups with respect to the variable of mindfulness.
The ANOVA analysis was run before the mindfulness intervention and after to ensure internal
consistency and stability. Once a significant positive difference has been determined in the level
of mindfulness for the treatment group as compared to the control group, then a second statistical
analysis was run to determine if mindfulness affects self-efficacy, self-regulation, and student
performance as determined by GPA. The multivariate analysis of covariates (MANCOVA) was
used to control for mindfulness and study the correlation between the dependent variables of
self-efficacy, self-regulation, and student performance.
The final statistical analysis was to create a customized structural equation model (SEM).
The SEM models represent relationships among observed variables to provide a quantitative test
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
88

of the proposed hypothesis or research questions (Lomax, Schumacker, & Randall, 2012). The
foundation for the structural equation model was based from the proposed hypothesis that when
mindfulness increases so would self-efficacy and self-regulation in learning and to what degree
as measured by student performance GPA (Figure 1).

Figure 1. Foundational Structural Equation Model Hypothesis
Data analysis through the structural equation model passed through many modifications
based on best practice guidelines and after acceptable reliability levels were met then the
measure be included in the model. Both an exploratory factor analysis and confirmatory factor
analysis was used to measure relationships between observed values and latent values. The path
model was a logical extension of multiple regression models to show more meaningful
theoretical relationships as stated by Lomax and colleagues (2012). The path model would be
used to analyze the relationship between the observed variables or measurable constructs. The
instrument to measure mindfulness was MAAS, to measure self-regulation was SSRQ, and to
measure self-efficacy was the MSLQ-SE sub-scale.
Student

Mindfulness
Prac1ces

Impacts
Self-‐Efficacy
Impacts
Self-‐Regula1on

Synergiis1cally
impacts

student
academic

perfromance
for
College-‐
&

Career-‐Readiness

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
89

The SEM path model purpose was to confirm the proposed relationship between self-
efficacy, self-regulation and student performance as a result of increased mindfulness from the
sample population. However, the limitation to this model was the inability to adjust for
measurement error, which was possible with MAAS and SSRQ instruments (Lomax and
Schumacker, 2012). Conversely the SEM confirmatory factor model allows for measurement
error because the latent or un-measurable variables are analyzed, allowing more flexibility to test
the hypothesis. In this case, the latent variables are the constructs of mindfulness and self-
regulation. The subsequent latent factors or subscales for mindfulness are: non-judgmental
ability; non-elaborative tendency; emotional regulation; goal setting and attainment. The latent
factors for self-regulation follow the subfunctions of Bandura’s (1991) self-regulation theory:
self-monitoring, judgmental, and self-reactive, and self-efficacy. These general subscales are
used to guide the structural models to run with the entire dataset and evaluate for overall fit.

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
90

CHAPTER FOUR: RESULTS
The analysis of the data followed a four-step mixed-methods process designed to
investigate the affects of mindfulness on academic performance from several frames of
reference, helping to develop the richest possible understanding of the treatment at work in the
study. The first step was to examine the basic demographics and descriptive statistics of the
sample. Then, the psychometric validity of the instruments was tested to confirm appropriate
performance with this particular sample.
Then, the results were analyzed using statistical strategies to understand the basic
relationship between variables as posed by the research questions. These analyses included
descriptives, Cronbach alpha, within subjects analysis of variance ANOVA with repeated-
measures, and MANCOVA with repeated-measures. The results of these tests were compared
against the research questions for the study.
A basic structural equation model was proposed and formulated from the hypothetical
theory and investigated using AMOS software. This initial model was subsequently modified to
improve goodness of fit, producing viable models that describe the behavior of the latent factors
and observed variables of interest.
Finally, qualitative data was gathered from pre-treatment, post 1-month, and follow up 2-
month surveys and then analyzed for common themes and insight into the behaviors observed in
the initial statistical analyses and structural equation modeling.
This chapter’s purpose is to review the results of these analyses in detail, beginning with
the descriptive statistics, continuing with Cronbach alpha, ANOVA with repeated-measures, and
MANCOVA with repeated-measures grouped by research question, following with the results of
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
91

structural equation modeling, and concluding with a brief look at qualitative data gathered in the
initial surveys.
Descriptive Statistics & Demographic Variables
The descriptive statistics from the SPSS Statistics output helps determine a general trend
for the data. This includes information on sample size, which levels of the within-subjects factor
had the higher/lower mean score and if there are any trends, and if the variation in each level was
similar (Pallant, 2007).
As discussed in Chapter 3, the sample consisted of middle school students from the 6
th
,
7
th
, and 8
th
grades. The middle school followed a traditional calendar and sample students
participated in the study during their required physical education class. Demographic
information was provided by 339 of the participants, and was summarized in Table 1.
Table 1
Grouping Descriptive by Grade
Groups Grade
% of Total
Sum N Sum
% of Total
N
1.0 Treatment 6.0 8.6% 62 9186 18.3%
7.0 6.1% 48 6505 14.2%
8.0 6.6% 59 7063 17.4%
Total 21.2% 169 22754 49.9%

2.0 Control 6.0 30.1% 67 32294 19.8%
7.0 10.7% 30 11423 8.8%
8.0 38.0% 73 40731 21.5%
Total 78.8% 170 84448 50.1%

Total 6.0 38.7% 129 41480 38.1%
7.0 16.7% 78 17928 23.0%
8.0 44.6% 132 47794 38.9%
Total 100.0% 339 107202 100.0%
N=number of participants.
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92

The full sample had 339 participants, all of whom were middle school students enrolled
in the 6
th
, 7
th
, or 8
th
grade. The 6
th
grade was comprised of 129 (38.1%) participants, 7
th
grade 78
(23%) participants, and 8
th
grade consisted of 132 (38.9%) participants. In the control group
were 170 (50.1%) participants and in the treatment group there were 169 (49.9%) participants.
In regards to gender of the total sample population, 163 (48.1%) were female and 176 (51.9%)
were male. The nearly exact number of participants in each experimental group allowed for a
more stable ANOVA analysis.
The overall ethnicity encompassed two major groups Hispanic and White. The white
group reported 102 (30.2%) participants overall, 50 (29.4%) participants in the control group,
and 52 (30.1%) participants in the treatment group, while the Hispanic group demonstrated a 180
(53.3%) participants overall, 50 (58.8%) participants in the control group, and 80 (47.6%)
participants in the treatment group. Hispanic students were much better represented in both the
control and treatment groups. There was 10 other minor ethnicity groups reported that comprised
16.5% of the total sample population.
In the treatment group 62 (36.7%) participants were 6
th
graders, 48 (28.4%) participants
were 7
th
graders, and 59 (34.9%) participants were 8
th
graders. The control group was composed
of 67 (39.4%) participants were 6
th
graders, 30 (17.6%) participants were 7
th
graders, and 73
(43.0%) participants were 8
th
graders. In regards to gender within groups, the treatment group
consisted of 52.7% males and 47.3% females. The control group contained 51.1% male and
48.9% female. The treatment group had nearly 10% more 7
th
graders and nearly 10% less 8
th

graders then the control group.
The middle school operates a college preparatory program called AVID for their students
who have the opportunity to be the first college-going generation of their family. The full
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
93

sample had 38 AVID participants, all of whom were middle school students enrolled in the 6
th
,
7
th
, or 8
th
grade. The 6
th
grade was comprised of 0 AVID participants, 7
th
grade 8 AVID
participants, and 8
th
grade consisted of 30 AVID participants. In the control group were 13
AVID participants and in the treatment group there were 25 AVID participants. In regards to
gender of the total AVID sample population, 6.8% were female and 4.4% were male. The 7
th

grade was composed of 5 female and 3 male, and the 8
th
grade included 18 female and 12 male
AVID participants. In the experimental design AVID groups, the control group contained 10
female and 3 male, while the treatment group consisted of 13 female and 12 male.
Analysis of Statistical Consistency
All variables were scored for both control and treatment groups at three different time
periods consisting of Pre, Post 1 month, and follow-up 2 months or Post Post, designated PRE, P,
and PP in the dataset. The items from the appropriate administrations of the combine instrument
were used.
Mindfulness Reliability
To examine the reliability and validity of the mindful attention awareness scale (MAAS)
as a whole, Cronbach’s alpha was calculated for both the control and treatment groups. The
Cronbach’s alpha coefficient is a measure of the degree to which the instrument’s items are
correlated, as a way of understanding the internal consistency and general construct validity of
the scale (DeVellis, 2012). DeVellis recommends the use of instruments with a
demonstrated Cronbach’s alpha coefficient of .70 or greater. Standardized Cronbach’s
Alpha was used, with the assumption of equal variances when all items are self-reported
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Likert scale items with the same size scale (Falk & Savalei, 2011). The instrument measuring
mindfulness was composed of the 15 items from the Mindful Attention Awareness Scale,
MAAS, each a 6-point Likert scale (Brown and Ryan, 2003).
The MAAS has good internal consistency, with a Cronbach alpha coefficient reported of
.86. The Cronbach Alpha values shown in the reliability statistics for the MAAS control and
treatment groups in this study were all greater then .8 suggesting very good internal consistency
(Pallant, 2013). In the current study, the MAAS Cronbach alpha was .883 for the control group
and .896 for the treatment group, indicating strong inter-item correlation and a strong internal
consistency. The inter-item correlation matrix and corrected-item total correlation tables values
were positive proving none of the items were reverse scored or incorrectly scored. The corrected
item-total correlations values shown in the item-total statistics were above .3 establishing the
item was measuring according to the scale as a whole. Additionally this table confirms no items
need to be removed as the overall Cronbach alpha was greater then .7 and the final alpha was
greater then the alpha if item was deleted (Pallant).
Short Self-Regulation Questionnaire Reliability
To examine the reliability and validity of the short self-regulation questionnaire (SSRQ)
as a whole, Cronbach’s alpha was calculated for both the control and treatment groups. The
instrument measuring mindfulness was composed of 39 items from the short self-regulation
survey, SSRQ, each a 5-point Likert scale of which 17 were reverse scored (Brown et al., 1999).
The SSRQ has good internal consistency, with a Cronbach alpha coefficient reported of
.85. The Cronbach Alpha values shown in the reliability statistics internal for the SSRQ were all
greater then .8 suggesting very good internal consistency (Pallant, 2013). In this study the
Cronbach alpha was .922 for the control group and .915 for the treatment group, indicating
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strong inter-item correlation and a strong internal consistency. The inter-item correlation matrix
and corrected-item total correlation tables values were positive; proving none of the items were
reverse scored or incorrectly scored. The corrected item-total correlations values shown in the
item-total statistics were above .3 establishing the item was measuring according to the scale as a
whole. Additionally this table confirms no items need to be removed as the overall Cronbach
alpha was greater then .7 and the final alpha was greater then the alpha if item was deleted
(Pallant).
Self-Efficacy Reliability
To examine the reliability and validity of the self-efficacy scale as a whole from the
MSLQ, Cronbach’s alpha was calculated for both the control and treatment groups. The
instrument measuring mindfulness was composed of 9 items from the self-efficacy scale of the
MSLQ, SE, each a 6-point Likert scale (Pintrich and DeGroot, 1990).
The SE has good internal consistency, with a Cronbach alpha coefficient reported of .78.
The Cronbach Alpha values shown in the reliability statistics internal for the SE were all greater
then .8 suggesting very good internal consistency (Pallant, 2013). In this study the Cronbach
alpha was .92 for the control group and .93 for the treatment group, indicating strong inter-item
correlation and a strong internal consistency. The inter-item correlation matrix and corrected-
item total correlation tables values were positive; proving none of the items were reverse scored
or incorrectly scored. The corrected item-total correlations values shown in the item-total
statistics were above .3 establishing the item was measuring according to the scale as a whole.
Additionally this table confirms no items need to be removed as the overall Cronbach alpha was
greater then .7 and the final alpha was greater then the alpha if item was deleted (Pallant).
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A Pearson's product-moment correlation was run to assess the relationship between all
variables: mindfulness, self-regulation, self-efficacy, and GPA for all grades and both treatment
and control groups. There was a mild to strong positive correlation between each set of variables.
Preliminary analyses showed the relationship to be linear with variables normally distributed, as
assessed by Shapiro-Wilk test (p > .05), and there were no outliers. There was a moderate
positive correlation between all variables (see Appendix F for Pearson’s Product Moment
Correlation).
Analysis of Research Questions
Research Question 1
The first research question asked, “Was there a significant difference in students’
maturation levels of mindfulness between the treatment and control groups over the duration of
the study?” To better understand this foundational research question for determining significant
changes in mindfulness within the treatment and control groups and between them over a period
of three different occasions; pre-treatment, post-treatment, and follow-up, an ANOVA with
repeated measures was conducted. The ANOVA with repeated measures was an extension of
the paired-samples t-test and was used to determine whether there are any statistically significant
differences between the population means of three or more levels, time, of a within-subjects
factor or dependent variable. The levels are related because they contain the same cases or
participants in each level. The participants are the same individuals tested on three or more
occasions on the same dependent variable, mindfulness.
The first step was to determine if the assumption of sphericity was violated or not. The
assumption of sphericity was the differences between the levels of the within-subjects factor,
mindfulness, have equal variances. When this assumption is violated, an adjustment needs to be
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made to the degrees of freedom so that the test still returns a valid result. However Mauchly's
test of sphericity is considered a poor method to detect violations of sphericity with it often
failing to detect departures from sphericity in small samples and over-detecting them in large
samples (Kesselman et al., 1980). Moreover, Maxwell and Delaney (2004) recommend that the
unadjusted test be never used, partly due to the extreme sensitivity of the one-way repeated
measures ANOVA to departures from sphericity. They suggest ignoring the result of Mauchly's
test of sphericity and simply interpreting the result of using a Greenhouse-Geisser correction
regardless. Assuming sphericity was biased and too easily returns a statistically significant
result, a correction can be made to correct for this bias by adjusting the degrees of freedom used
in calculating the p-value. This correction was called epsilon (ε) and the Greenhouse-Geisser test
was used to determine where adjustments according to Greenhouse and Geisser (1959) have
been made to the degrees of freedom for both the time and error effect.

Consequently this study
assumed that sphericity was most likely violated and interpreted the results of using a
Greenhouse-Geisser correction regardless.
For the mindfulness, MAAS measurement, control group Epsilon (ε) was 0.648, as
calculated according to Greenhouse and Geisser (1959), and was used to correct the one-way
repeated measures ANOVA. The mindfulness intervention elicited statistically significant
changes in MAAS concentration over the duration of the study, F(1.191, 266.752) = 7.956, p <
.0005, partial η
2
= .056, with MAAS concentration increasing from pre-intervention (M = 4.43,
SD = 0.878) to 1 month post-intervention (M = 4.64, SD = 0.888) to 2 months follow-up (M =
4.692, SD = 0.938). Post hoc analysis with a Bonferroni adjustment revealed that MAAS
concentration had a statistically significant increase from pre-intervention to 1 month post-
intervention (M = 0.211 ,95% CI [0.042, 0.38], p =.009), and from pre-intervention to 2 months
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follow-up (M = 0.264 , 95% CI [0.089, .438], p = .001), but no significant increased from 1
month post-intervention) to 2 months follow-up (M = 0.053, 95% CI [-0.112, .218], p = 1.000).
For the mindfulness, MAAS measurement, treatment group Epsilon (ε) was 0.648, as
calculated according to Greenhouse and Geisser (1959), and was used to correct the one-way
repeated measures ANOVA. The mindfulness intervention elicited statistically significant
changes in MAAS concentration over the duration of the study, F(1.872, 237.774) = 5.260, p
=.007, partial η
2
= .040, with MAAS concentration decreasing from pre-intervention (M = 4.37,
SD = 0.953) to 1 month post-intervention (M = 4.39, SD = 0.953) and increasing to 2 months
follow-up (M = 4.54, SD = 0.945). Post hoc analysis using the Bonferroni adjustment revealed
the mindfulness concentration was not statistically significantly decreased from pre-intervention
to 1 month post-intervention (M = -0.031, 95% CI [-0.192, 0.129], p =1.000), and no statistical
significant increase from pre-intervention to 2 months follow-up (M = 0.167 , 95% CI [-0.009,
.342], p = .069), but the increase from 1 month post-intervention to 2 months follow-up was
statistically significant (M = 0.198, 95% CI [0.059, .337], p =.002). The pairwise comparison
with Bonferroni adjustment can be found in Table 2 and the profile plot for the repeated
measures ANOVA analysis can be found in Figures 2 and 3.

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Table 2
Mindfulness Pairwise Comparisons for Treatment group with Bonferonni Adjustment
Pairwise Comparisons
Measure: MAAS
(I) Time (J) Time
Mean
Difference (I-J) Std. Error Sig.
b

95% Confidence Interval for
Difference
b

Lower Bound Upper Bound
1 2 .031 .066 1.000 -.129 .192
3 -.167 .072 .069 -.342 .009
2 1 -.031 .066 1.000 -.192 .129
3 -.198
*
.057 .002 -.337 -.059
3 1 .167 .072 .069 -.009 .342
2 .198
*
.057 .002 .059 .337
Based on estimated marginal means
*. The mean difference is significant at the
b. Adjustment for multiple comparisons: Bonferroni.

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Control
Group

Figure 2. ANOVA Analysis Control Group Profile plot for MAAS Estimated Marginal Means
Over Three Different Time Periods (Pre, Post, Follow-Up)

Treatment
Group

Figure 3. ANOVA Analysis Treatment Group Profile Plot for MAAS Estimated
Marginal Means Over Three Different Time Periods (Pre, Post, Follow-Up)

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Research Question 1a
Under Research Question 1, the first sub-question asked, “Was there a significant
difference in students’ maturation levels of self-regulation between the treatment and control
groups over the duration of the study?” To better understand this research question for
determining significant changes in self-regulation within the treatment and control groups and
between them over a period of three different occasions; pre-treatment, post-treatment, and
follow-up, an ANOVA with repeated measures was conducted. This study assumed that
sphericity was most likely violated and interpreted the results of using a Greenhouse-Geisser
correction regardless.
For self-regulation, SSRQ measurement, control group Epsilon (ε) was 0.648, as
calculated according to Greenhouse and Geisser (1959), and was used to correct the one-way
repeated measures ANOVA. The mindfulness intervention elicited statistically significant
changes in SSRQ concentration over time, F(1.785, 232.106) = 4.085, p =.022, partial η
2
= .030,
with SSRQ concentration increasing from pre-intervention (M = 3.57, SD = 0.506) to 1 month
post-intervention (M = 3.63, SD = 0.557) to 2 months follow-up (M = 3.66, SD = 0.664). Post
hoc analysis with a Bonferroni adjustment revealed that SSRQ concentration was not statistically
significant increased from pre-intervention to 1 month post-intervention (M = 0.067, 95% CI [-
0.07, 0.141], p =.089), and from pre-intervention to 2 months follow-up showed no statistical
significance (M = 0.090 95% CI [-0.002, .182], p = .057), and again no statistical significance
from 1 month post-intervention to 2 months follow-up (M = 0.023 95% CI [-0.047, .094], p =
1.000).
For self-regulation, SSRQ measurement, treatment group Epsilon (ε) was 0.648, as
calculated according to Greenhouse and Geisser (1959), and was used to correct the one-way
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repeated measures ANOVA. The mindfulness intervention elicited statistically significant
changes in SSRQ concentration over time, F(1.875, 219.409) = 4.085, p <.0005, partial η
2
=
.079, with SSRQ concentration increasing from pre-intervention (M = 3.62, SD = 0.472) to 1
month post-intervention (M = 3.63, SD = 0.501) to 2 months follow-up (M = 3.74, SD = 0.530).
Post hoc analysis with a Bonferroni adjustment revealed that SSRQ concentration was not
statistically significant increased from pre-intervention to 1 month post-intervention (M = 0.010 ,
95% CI [-0.059, 0.078], p =1.000), but the increase from pre-intervention to 2 months follow-up
was statistically significant (M = 0.118, 95% CI [0.039, .198], p = .001), and again statistically
significant from 1 month post-intervention to 2 months follow-up (M = 0.109 , 95% CI [0.044,
.174], p < .0005). The pairwise comparison with Bonferroni adjustment can be found in Table 3
and the profile plot for the repeated measures ANOVA analysis can be found in Figures 4 and 5.
Table 3
Self-Regulation Pairwise Comparisons for Treatment group with Bonferonni Adjustment
Pairwise Comparisons
Measure: SSRQ
(I) Time (J) Time
Mean
Difference (I-J) Std. Error Sig.
b

95% Confidence Interval for
Difference
b

Lower Bound Upper Bound
1 2 -.010 .028 1.000 -.078 .059
3 -.118
*
.033 .001 -.198 -.039
2 1 .010 .028 1.000 -.059 .078
3 -.109
*
.027 .000 -.174 -.044
3 1 .118
*
.033 .001 .039 .198
2 .109
*
.027 .000 .044 .174
Based on estimated marginal means
*. The mean difference is significant at the
b. Adjustment for multiple comparisons: Bonferroni.

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Control
Group

Figure 4. ANOVA Analysis Control Group Profile Plot for SSRQ Estimated Marginal
Means Over Three Different Time Periods (Pre, Post, Follow-Up)

Treatment
Group

Figure 5. ANOVA Analysis Treatment Group Profile Plot for SSRQ Estimated Marginal Means
Over Three Different Time Periods (Pre, Post, Follow-Up)

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Research Question 1b
Under Research Question 1, the second sub-question asked, “Was there a significant
difference in students’ maturation levels of self-efficacy between the treatment and control
groups over the duration of the study?” To better understand this research question for
determining significant changes in self-efficacy within the treatment and control groups and
between them over a period of three different occasions; pre-treatment, post-treatment, and
follow-up, an ANOVA with repeated measures was conducted. This study assumed that
sphericity was most likely violated and interpreted the results of using a Greenhouse-Geisser
correction regardless.
For self-efficacy, SE measurement, control group Epsilon (ε) was 0.648, as calculated
according to Greenhouse and Geisser (1959), and was used to correct the one-way repeated
measures ANOVA. The mindfulness intervention elicited non-statistically significant changes in
SE concentration over time, F(1.918, 262.738) = 1.245, p =.289, partial η
2
= .009, with SE
concentration decreasing from pre-intervention (M = 5.50, SD = 1.096) to 1 month post-
intervention (M = 5.48, SD = 1.112) and increasing to 2 months follow-up(M = 5.58, SD =
1.104). Post hoc analysis with a Bonferroni adjustment revealed that mindfulness concentration
was not statistically significantly decreased from pre-intervention to 1 month post-intervention
(M =-0.024, 95% CI [-0.171, 0.123], p =1.000), and from pre-intervention to 2 months follow-up
no statistical significance (M = 0.077, 95% CI [-0.099, .254], p = .870), and from 1 month post-
intervention to 2 months follow-up showed no statistical significance (M = 0.101, 95% CI [-
0.062, .265], p =.407).
For self-efficacy, SE measurement, treatment group Epsilon (ε) was 0.648, as calculated
according to Greenhouse and Geisser (1959), and was used to correct the one-way repeated
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measures ANOVA. The mindfulness intervention elicited non-statistically significant changes in
SE concentration over time, F(1.833, 241.933) = .198, p =.802, partial η
2
= .001, with SE
concentration increasing from pre-intervention (M = 5.71, SD = 1.037) to 1 month post-
intervention (M = 5.75, SD = 1.018) and increasing to 2 months follow-up (M = 5.72,
SD = 1.124). Post hoc analysis with a Bonferroni adjustment revealed that mindfulness
concentration was not statistically significant from pre-intervention to 1 month post-intervention
(M =.038, 95% CI [-0.107, 0.184], p =1.000), from pre-intervention to 2 months follow-up also
was not statistical significant (M = 0.006, 95% CI [-0.176, .188], p = 1.000), and from 1 month
post-intervention to 2 months follow-up showed no statistical significance (M = -0.033 , 95% CI
[-0.181, .116], p =1.000). The pairwise comparison with Bonferroni adjustment can be found in
Table 4 and the profile plot for the repeated measures ANOVA analysis can be found in Figures
6 and 7.
Table 4
Self-Efficacy Pairwise Comparisons for Treatment group with Bonferonni Adjustment
Pairwise Comparisons
Measure: SE
(I) Time (J) Time
Mean
Difference (I-J) Std. Error Sig.
a

95% Confidence Interval for
Difference
a

Lower Bound Upper Bound
1 2 -.038 .060 1.000 -.184 .107
3 -.006 .075 1.000 -.188 .176
2 1 .038 .060 1.000 -.107 .184
3 .033 .061 1.000 -.116 .181
3 1 .006 .075 1.000 -.176 .188
2 -.033 .061 1.000 -.181 .116
Based on estimated marginal means
a. Adjustment for multiple comparisons: Bonferroni.

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Control
Group

Figure 6. ANOVA Analysis Control Group Profile plot for SE Estimated Marginal Means
Over Three Different Time Periods (Pre, Post, Follow-Up)

Treatment
Group

Figure 7. ANOVA Analysis Treatment Group Profile Plot for SE Estimated Marginal Means
Over Three Different Time Periods (Pre, Post, Follow-Up)

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Research Question 2
The second research question asked, “Was there a difference in the effect of mindfulness
on self-regulation between treatment and control groups while controlling for entry levels of self-
regulation and mindfulness?” To more fully understand the relationship and potential effect of
mindfulness on self-regulation a repeated measures multivariate analysis of covariates
(MANCOVA) was utilized. To better understand why this analysis was used an initial
understanding of MANCOVA was essential. Basically a MANCOVA explores the effect of two
or more dependent variables simultaneously across one or more independent variable, controlling
for one or more covariates (Mayers, 2013). A covariate is a variable that is not part of the main
analysis but may have an impact on the outcome as error variance or interference depending on
its independence or dependence to the experimental effect. This study used covariates to control
for entry-level pre-conditions of the variables; mindfulness, self-regulation, self-efficacy, and
GPA to determine these variables true results without their entry-level measures confounding the
observed outcome.
The method used to calculate multivariate and covariate outcomes was cross product and
cross-product partitions represented by F ratios, from which statistical significance can be
established. For this repeated-measures MANCOVA, the independent variables of groups,
control or treatment are explored across the dependent variables of mindfulness and self-
regulation at 2 survey assessment time points, post-treatment 1 month and follow-up 2 months,
while controlling for pre-intervention measurement levels of the dependent variables, or
covariates.
There are assumptions and restrictions considered before running MANCOVA. The first
consideration was the Pearson correlation analysis to determine the presence of a multivariate
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effect between the dependent variables and between the covariates and the dependent variables.
The dependent variables had strong correlation between themselves from .30 and .90 and
demonstrated a multivariate effect (Mayers, 2013). The covariates and dependent variables also
had a strong correlation from .30 and .90. The covariates were further tested to determine if they
differed across independent variables. There was no significant difference in mindfulness scores
F(1, 309) = .027, p = .869, nor in self-regulation scores F(1, 310) = .061, p = .805. Mindfulness
scores were normally distributed for post 1-month control group but not for others, as assessed
by Kolmogorov-Smirnov test (p < .05). Self-regulation scores were normally distributed for
both control and treatment, as assessed by Kolmogorov-Smirnov test (p > .05). Levene’s test for
equality of variances indicated that the assumption for between-group homogeneity of variance
across groups was met for both dependent variables with significance greater than .05 except for
self-regulation at follow-up 1 month was .03. Box’s M test was run to ensure correlation
between the dependent variables was equal across independent variable groups, p=.012.
Homogeneity of regression slopes was determined by non-significant values found in the tests of
between-subjects effects for group*pre mindfulness in respect to post mindfulness and post self-
regulation scores, and homogeneity of regression for group*pre self-regulation in respect to post
mindfulness and post self-regulation scores was determined. Hence correlation between the
covariates and dependent variables across control and treatment groups do not differ. The
multivariate analysis Pillai’s trace was used because 2 groups were being measured, control and
treatment. Mauchly’s test of sphericity was dismissed as only 2 time measurements were being
used and sphericity was not established.
There was significant multivariate outcome, prior to covariate adjustment, in respect of
total mindfulness and self-regulation across treatment and control groups F(2, 259) = 3.028,
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p =.05, η
2
=.023. After the covariates were applied, a non-significant multivariate outcome in
respect of total mindfulness and self-regulation across treatment and control groups remained
F(2, 235) = 2.154, p =.118, η
2
=.018. The Bonferonni corrected post hoc test for estimated
marginal means pairwise comparisons between groups with respect to the dependent variables
found the treatment group compared to the control group had a statistically significant mean
difference in mindfulness of -.197, 95% CI [-0.36, -0.04], p < .05, and non significant mean
difference in self-regulation of -.004 , 95% CI [-0.09, 0.08], p =.918. The pairwise comparisons
with Bonferroni adjustment can be found in Table 5.
After the covariates, mindfulness and self-regulation, were controlled the descriptive
statistics showed no statistical significance between groups with respect to mindfulness F(1,260)
= 2.560, p = .111, partial η
2
= .010, and no statistical significance between groups with respect
to self-regulation F(1,260) = .150, p = .611, partial η
2
= .001. As demonstrated in the profile
plots for mindfulness, MAAS, and self-regulation, SSRQ, there was a direct relationship
increase from post-treatment 1-month to follow-up 2-months while controlling for entry levels
for both the treatment and control groups. The descriptive statistics table can be found in Table 6
and the profile plots of the repeated measures MANCOVA controlling for entry-levels of
mindfulness and self-regulation can be found in Figures 8 and 9.

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Table 5
Mindfulness & Self-Regulation Pairwise Comparisons with Bonferonni Adjustment
Pairwise Comparisons
Measure (I) Groups (J) Groups
Mean
Difference
(I-J) Std. Error Sig.
b

95% Confidence Interval
for Difference
b

Lower
Bound
Upper
Bound
MAAS 1.0 Treatment 2.0 Control -.197
*
.080 .015 -.355 -.039
2.0 Control 1.0 Treatment .197
*
.080 .015 .039 .355
SSRQ 1.0 Treatment 2.0 Control -.004 .042 .918 -.087 .078
2.0 Control 1.0 Treatment .004 .042 .918 -.078 .087
Based on estimated marginal means
*. The mean difference is significant at the
b. Adjustment for multiple comparisons: Bonferroni.

Table 6
Descriptive Statistics for Research Question 2

Groups Mean Std. Deviation N
Post MAAS ALL
Avg
1.0 Treatment
4.3240 .98324 114
2.0 Control 4.6411 .87892 128
Total 4.4917 .94104 242
Post1 MAAS
ALL Avg
1.0 Treatment
4.572 .9590 114
2.0 Control 4.676 .9452 128
Total 4.627 .9511 242
Post SSRQ ALL
Avg
1.0 Treatment
3.6418 .50314 114
2.0 Control 3.6482 .55495 128
Total 3.6452 .53009 242
Post1 SSRQ ALL
Avg
1.0 Treatment
3.7465 .53610 114
2.0 Control 3.6709 .66455 128
Total 3.7065 .60738 242
Note. MAAS = Mindfulness measure; SSRQ = Self-regulation measure;
Post = Post treatment 1 month; Post1 = Follow-up 2 months.

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Figure 8. MANCOVA Analysis Profile Plot for MAAS Estimated Marginal Means Over
Two Different Time Periods (Post, Follow-Up)

Figure 9. MANCOVA Analysis Profile plot for SSRQ Estimated Marginal Means Over Two
Different Time Periods (Post, Follow-Up)

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Research Question 2a
Under Research Question 2, the first sub-question asked, “Was there a difference in the
effect of mindfulness on self-efficacy between treatment and control groups while controlling for
entry levels of self-efficacy and mindfulness?” To more fully understand the relationship and
potential effect of mindfulness on self-efficacy a repeated measures multivariate analysis of
covariates (MANCOVA) was utilized. The method used to calculate multivariate and covariate
outcomes was cross product and cross-product partitions represented by F ratios, from which
statistical significance can be established. For this repeated-measures MANCOVA, the
independent variables of groups, control or treatment are explored across the dependent variables
of mindfulness and self-efficacy at 2 survey assessment time points, post-treatment 1 month and
follow-up 2 months, while controlling for pre-intervention measurement levels of the dependent
variables, or covariates.
There are assumptions and restrictions considered before running MANCOVA. The first
consideration was the Pearson correlation analysis to determine the presence of a multivariate
effect between the dependent variables and between the covariates and the dependent variables.
The dependent variables should have a strong correlation between themselves from .30 and .90
as suggested by Mayers (2013). The dependent variables demonstrated a less strongly correlated
multivariate effect. Additionally the covariates and dependent variables also demonstrated a less
strongly correlated multivariate effect. The covariates were further tested to determine if they
differed across independent variables. There was no significant difference in mindfulness scores
F(1, 309) = .027, p = .869, nor in GPA scores F(1, 317) = 2.166, p = .142. Mindfulness scores
were normally distributed for post 1-month control group but not for others, as assessed by
Kolmogorov-Smirnov test (p < .05). Self-efficacy scores were not normally distributed for both
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113

control and treatment, as assessed by Kolmogorov-Smirnov test (p > .05). Levene’s test for
equality of variances indicated that the assumption for between-group homogeneity of variance
across groups was met for both dependent variables with significance greater than .05. Box’s M
test was run to ensure correlation between the dependent variables was equal across independent
variable groups, p=.095. Homogeneity of regression slopes was determined by non-significant
values found in the tests of between-subjects effects for group*pre mindfulness in respect to post
mindfulness and post self-efficacy scores, and homogeneity of regression for group*pre self-
efficacy in respect to post mindfulness and post self-efficacy scores was determined. Hence
correlation between the covariates and dependent variables across control and treatment groups
do not differ. The multivariate analysis Pillai’s trace was used because 2 groups were being
measured, control and treatment. Mauchly’s test of sphericity was dismissed as only 2 time
measurements were being used and sphericity was not established.
There was significant multivariate outcome, prior to covariate adjustment, in respect of
total mindfulness and self-efficacy across treatment and control groups F(2, 278) = 5.688,
p =.004, η
2
=.039. After the covariates were applied, a weaker significant multivariate outcome
in respect of total mindfulness and self-efficacy across treatment and control groups remained
F(2, 254) = 2.470, p =.087, η
2
=.019. The Bonferonni corrected post hoc test for estimated
marginal means pairwise comparisons between groups with respect to the dependent variables
found the treatment group had a statistically significant mean difference in mindfulness of -.220,
95% CI [-0.37, -0.07], p < .05, and non significant mean difference in self-efficacy of .064 , 95%
CI [-0.09, 0.21], p =.408. The pairwise comparisons with Bonferroni adjustment can be found in
Table 7.
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The descriptive statistics showed that after the covariates, mindfulness and self-efficacy,
were controlled for there was no statistical significance between groups with respect to
mindfulness F(1,255) = 3.058, p = .082, partial η
2
= .012, and no statistical significance between
groups with respect to self-efficacy F(1,255) = .744, p = .389, partial η
2
= .003. As demonstrated
in the profile plot for mindfulness, MAAS, there was a mean direct relationship increase from
post-treatment 1-month to follow-up 2-months while controlling for entry levels for both the
treatment and the control groups. However the self-efficacy means between treatment and
control groups displayed an inverse relationship with the control group increasing and the
treatment group decreasing. The descriptive statistics table can be found in Table 8 and the
profile plots of the repeated measures MANCOVA controlling for entry-levels of mindfulness
and self-efficacy can be found in Figures 10 and 11.
Table 7
Mindfulness & Self-Efficacy Pairwise Comparisons with Bonferonni Adjustment
Pairwise Comparisons
Measure (I) Groups (J) Groups
Mean
Difference
(I-J) Std. Error Sig.
b

95% Confidence Interval
for Difference
b

Lower
Bound
Upper
Bound
MAAS 1.0 Treatment 2.0 Control -.220
*
.077 .004 -.371 -.069
2.0 Control 1.0 Treatment .220
*
.077 .004 .069 .371
SE 1.0 Treatment 2.0 Control .064 .077 .408 -.088 .215
2.0 Control 1.0 Treatment -.064 .077 .408 -.215 .088
Based on estimated marginal means
*. The mean difference is significant at the
b. Adjustment for multiple comparisons: Bonferroni.

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Table 8
Descriptive Statistics for Research Question 2a

Groups Mean
Std.
Deviation N
Post MAAS ALL
Avg
1.0 Treatment 4.3265 .95628 126
2.0 Control 4.6390 .88782 135
Total 4.4881 .93294 261
Post1 MAAS
ALL Avg
1.0 Treatment 4.546 .9441 126
2.0 Control 4.692 .9380 135
Total 4.621 .9420 261
Post SE ALL
Avg
1.0 Treatment 5.7981 .96777 126
2.0 Control 5.5185 1.08934 135
Total 5.6535 1.03993 261
Post1 SE ALL
Avg
1.0 Treatment 5.7425 1.10233 126
2.0 Control 5.6115 1.09574 135
Total 5.6748 1.09877 261
Note. MAAS = Mindfulness measure; SE = Self-efficacy measure;
Post = Post treatment 1 month; Post1 = Follow-up 2 months.

Figure 10. MANCOVA Analysis Profile Plot for MAAS Estimated Marginal Means
Over Two Different Time Periods (Post, Follow-Up)

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Figure 11. MANCOVA Analysis Profile Plot For SE Estimated Marginal Means Over Two
Different Time Periods (Post, Follow-Up)

Research Question 2b
Under Research Question 2, the second sub-question asked, “Was there a difference in
the effect of mindfulness on grade point average (GPA) between treatment and control groups
while controlling for entry levels of GPA and mindfulness?” To more fully understand the
relationship and potential effect of mindfulness on GPA a repeated measures multivariate
analysis of covariates (MANCOVA) was utilized. The method used to calculate multivariate and
covariate outcomes was cross product and cross-product partitions represented by F ratios, from
which statistical significance can be established. For this repeated-measures MANCOVA, the
independent variables of groups, control or treatment are explored across the dependent variables
of mindfulness and GPA at 2 survey assessment time points, post-treatment 1 month and follow-
up 2 months, while controlling for pre-intervention measurement levels of the dependent
variables, or covariates.

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There are assumptions and restrictions considered before running MANCOVA. The first
consideration was the Pearson correlation analysis to determine the presence of a multivariate
effect between the dependent variables and between the covariates and the dependent variables.
The dependent variables should have a strong correlation between themselves from .30 and .90
as suggested by Mayers (2013). The dependent variables demonstrated a strong multivariate
effect except for mindfulness, which is less strongly correlated with GPA. Additionally the
covariates and dependent variables also had a strong correlation except for mindfulness, which is
less strongly correlated with GPA. The covariates were further tested to determine if they
differed across independent variables. There was no significant difference in mindfulness scores
F(1, 309) = .027, p = .869, nor in GPA scores F(1, 336) = 2.153, p = .143. Mindfulness scores
were normally distributed for post 1-month control group but not for others, as assessed by
Kolmogorov-Smirnov test (p < .05). GPA scores were not normally distributed for both control
and treatment, as assessed by Kolmogorov-Smirnov test (p > .05). Levene’s test for equality of
variances indicated that the assumption for between-group homogeneity of variance across
groups was met for the mindfulness dependent variable with significance greater than .05 but not
for the GPA dependent variable. Box’s M test was run to ensure correlation between the
dependent variables was equal across independent variable groups, p=.047. Homogeneity of
regression slopes was determined by non-significant values found in the tests of between-
subjects effects for group*pre mindfulness in respect to post mindfulness and post GPA scores,
and homogeneity of regression for group*pre GPA in respect to post mindfulness was
determined; however GPA did not exhibit homogeneity of regression slopes. Hence correlation
between the covariates and dependent variables across control and treatment groups do not differ
but for one exception. The multivariate analysis Pillai’s trace was used because 2 groups were
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being measured, control and treatment. Mauchly’s test of sphericity was dismissed as only 2
time measurements were being used and sphericity was not established.
There was a non-significant multivariate outcome, prior to covariate adjustment, in
respect of total mindfulness and GPA across treatment and control groups F(2, 282) = 1.854,
p =.159, η
2
=.013. After the covariates were applied, a stronger significant multivariate outcome
in respect of total mindfulness and self-efficacy across treatment and control groups remained
F(2, 255) = 18.959, p <.001, η
2
=.129. The Bonferonni corrected post hoc test for estimated
marginal means pairwise comparisons between groups with respect to the dependent variables
found the treatment group had a statistically significant mean decrease in mindfulness of -.192,
95% CI [-0.35, -0.36], p < .05, and non significant mean decrease in GPA of -.060,
95% CI [-0.19, -0.07], p =.369. The pairwise comparisons with Bonferroni adjustment can be
found in Table 9.
After the covariates, mindfulness and GPA, were controlled for there was no statistical
significance between groups with respect to mindfulness F(1,256) = .181, p = .671, partial η
2
=
.001, but there was statistical significance between groups with respect to GPA F(1,256) =
37.092, p < .001, partial η
2
= .127. As demonstrated in the profile plot for mindfulness, MAAS,
and GPA there was a mean direct relationship increase from post-treatment 1-month to follow-up
2-months for both treatment and the control groups. The descriptive statistics table can be found
in Table 10 and the profile plots of the repeated measures MANCOVA controlling for entry-
levels of mindfulness and GPA can be found in Figures 12 and 13.

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Table 9
Mindfulness & GPA Pairwise Comparisons with Bonferonni Adjustment
Pairwise Comparisons
Measure (I) Groups (J) Groups
Mean
Difference
(I-J) Std. Error Sig.
b

95% Confidence Interval
for Difference
b

Lower
Bound
Upper
Bound
MAAS 1.0 Treatment 2.0 Control -.192
*
.079 .016 -.348 -.036
2.0 Control 1.0 Treatment .192
*
.079 .016 .036 .348
GPA 1.0 Treatment 2.0 Control -.060 .066 .369 -.190 .071
2.0 Control 1.0 Treatment .060 .066 .369 -.071 .190
Based on estimated marginal means
*. The mean difference is significant at the
b. Adjustment for multiple comparisons: Bonferroni.

Table 10
Descriptive Statistics for Research Question 2b

Groups Mean
Std.
Deviation N
Post MAAS ALL
Avg
1.0 Treatment 4.3465 .95219 127
2.0 Control 4.6390 .88782 135
Total 4.4972 .92943 262
Post1 MAAS
ALL Avg
1.0 Treatment 4.544 .9445 127
2.0 Control 4.692 .9380 135
Total 4.620 .9423 262
GPA14GP2ALL 1.0 Treatment 3.15252 .710836 127
2.0 Control 3.19678 .632188 135
Total 3.17532 .670532 262
GPA14GP3ALL 1.0 Treatment 3.18455 .718278 127
2.0 Control 3.24690 .656402 135
Total 3.21668 .686477 262

Note. MAAS = Mindfulness measure; GPA14GP1,2,3 = Grade Point Average report card measure for
progress report card 1, 2, 3; Post = Post treatment 1 month; Post1 = Follow-up 2 months.

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Figure 12. MANCOVA Analysis Profile Plot For MAAS Estimated Marginal Means
Over Two Different Time Periods (Post, Follow-Up)

Figure 13. MANCOVA Analysis Profile Plot For GPA Estimated Marginal Means Over Two
Different Time Periods (Post, Follow-Up)

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Research Question 3
The third research question asked, “Were student’s level of mindfulness relative to the
degree of impact on self-regulation, self-efficacy and do those variables significantly impact
student academic performance?” This research question was founded on an inferential model
designed by this researcher due to previous hands on experience and empirical research on the
mindfulness theory. Consequently, to best answer this question a structural equation model was
used to determine a goodness of fit for the most appropriately evolved model reached through
confirmatory factor analysis.
Structural Equation Modeling
Structural Equation Modeling (SEM) is a statistical methodology that undertakes a
confirmatory approach to the analysis of a structural theory of various models to depict
relationships among observed variables hypothesized by the researcher through inference,
conjecture, and speculation in attempt to explain a phenomenon (Byrne, 2013; Lomax &
Schumacker, 2012). To put it succinctly numerous variables can be tested in SEM, hypothesizing
how sets of variables define constructs and how these constructs are related to each other or as
Bentler (1988) stated the theory normally represents causal processes that generate observations
on multiple variables. The term SEM was founded on two important aspects of the procedure:
“(a) that the causal processes under study are represented by a series of structural (i.e.,
regression) equations, and (b) that these structural relations can be modeled pictorially to enable
a clearer conceptualization of the theory under study” (Byrne, 2013, p. 3). The model can be
tested statistically in a simultaneous analysis of the entire system of variables and determine to
what extent it was consistent with the data. If a statistical 'goodness of fit' is determined then the
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hypothesized model argues for probability of the model or if an inadequate fit then the model
was rejected (Byrne).
Several aspects of SEM set it apart from older generations of multivariate procedures.
First SEM takes a confirmatory rather than exploratory traditional approach to data analysis,
allowing for a researcher's inferentially deduced models to be tested. Conversely, most other
multivariate procedures are essentially descriptive by nature, making hypothesis testing difficult,
if not impossible (Byrne, 2013). Secondly SEM provides exact estimate of error variance
parameters which traditional multivariate procedures are unable to assess or correct for
measurement error. Third, the traditional procedures are based only on observed measurements;
however, SEM can encompass both observed and unobserved variable called 'latent' variables.
Lastly, to date, there are no widely and easily applied multivariate models available other than
SEM. Furthermore SEM was used when methods for testing theories are not well established
and ethical feasibility was not apparent (Bentler, 1980).
The effect of mindfulness on self-regulation, self-efficacy and subsequently academic
performance was a theoretical construct that cannot be directly observed. Subsequently in SEM
this abstract phenomena are labeled latent variables or factors to give value and hence meaning
to the model. Hence it becomes the researcher's task to define the latent variable of interest in
terms of an observable behavior, which can be directly measured, and through association the
linked unobservable latent variable can be indirectly measured (Byrne, 2013). In this study the
measurement of mindfulness, MAAS, self-regulation (SSRQ), self-efficacy (SE), and academic
performance (GPA) were termed manifest variables in SEM and serve as indicators of the
underlying, unobserved constructs, which they are presumed to represent as stated by Byrne. As
a result careful selection of assessment measures are necessary for SEM to operate functionally.
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Latent variables within SEM can be of two types, exogenous and endogenous.
Exogenous latent variables are synonymous with independent variables that cause other latent
variables values to fluctuate in SEM. However any changes in the exogenous variable was not
explained by SEM but considered influenced by factors outside of SEM (Byrne, 2013).
Endogenous latent variables are synonymous with dependent variables and influenced directly or
indirectly by the exogenous variables in the model. The model explains their influences.
Factor analysis was the most reliable statistical procedure for analyzing relations between
observed and latent variables, where the co-variation among observed variables gives meaning to
the underlying latent construct, which are represented by factor loadings (Byrne, 2013). Hence,
there are two types of factor analyses, exploratory and confirmatory. Exploratory factor analysis
was used when links between observed and unobserved variables are uncertain. In contrast, the
confirmatory factor analyses was used when the researcher’s underlying knowledge of the latent
variable construct postulates relations between observed and latent variables, which are then
used to test hypothetical structures statistically as stated by Byrne. This confirmatory factor
analysis determines a goodness of fit between the hypothesized model and sample data through
regression analysis. Because a perfect fit was highly unlikely between the two, a differential
evolved and this differential was called residual. Subsequently the model fitting approach can be
defined as:
Data = Model + Residual
Furthermore the results of the confirmatory factor model determined if the researcher accepts or
rejects the model and no further modifications are made. If the model was rejected the
researcher may continue on with alternative competing models grounded in theory to determine
which model best fits the data (Byrne).
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SEM models use symbolic notation to represent path diagrams that provide the variables
causal relationships and subsequent underlying model construct. The path diagram was the
graphical equivalent of its mathematical representation and set of equations relating endogenous
variables to their exogenous variables (Byrne, 2013). SEMs consist of four geometric symbols;
circle, square, single-headed arrow, and double-headed arrow. Circles represent unobserved
latent variables. Squares represent observed variables. Single-headed arrows represent the
impact of one variable on another or structural regression coefficients, and double-headed
variables are covariances or between pairs of variables (Bynre). Additionally associated with
each observed variable was an error term, err1, and with the factor being predicted a residual
term, resid1. Error terms represent measurement errors with random measurement or error
uniqueness. Residual terms represent an error in the prediction of endogenous factors from
exogenous factors (Bynre). Every relationship in the model can be represented by a basic
structural equation (regression) of the form:
Variable = Factor(s) + Error
Lastly SEMs’ are composed of two sub-models, measurement and structural. The measurement
model defines relationships between observed and latent variables for a confirmatory factor
analyses. The structural model defines direct or indirect relationships among the latent variables
and subsequent changes in values. A combination of these two models was considered full or
complete, where one can hypothesize the impact of a latent variable on another in causal
direction through regression analysis, utilizing the structural equation model to confirm (Byrne).
When a full model identifies a one directional cause between latent variables, the model was
called recursive. If the model identifies two-way directional cause or feedback effects, the model
was called non-recursive.
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Given the large number of model configurations possible to specify in SEM, it was
important to consider on what level a model was identified. As stated by Bryne (2013)
identification is determined by whether the data is consistent with a unique set of parameters. If
the values of the structural parameters are unique and therefore testable then the model is
identified. In contrast, when the model has different parameter values that can define the same
model it is unidentifiable and cannot be evaluated empirically (Byrne). Justified models can
either be; just-identified, over identified, or under identified as stated by Byrne. A just-identified
model has a one-to-one correspondence between variances and co-variances, data, and structured
parameters and undesirable to researchers because it offers no degrees of freedom, making it
impossible to be scientifically rejected. An over-identified model has positive degrees of
freedom because there are more data points then estimable parameters and favorable for
research, allowing the model to be rejected. An under identified model has negative degrees of
freedom because there are less data points then estimable parameters and subsequent infinite
model combinations.
An advanced statistical methodology for the multivariate causal analysis of a theory, and
particularly useful in exploring variables, such as this study's mindfulness, self-regulation, self-
efficacy, and Grade Point Average variables, which cannot be directly observed.
Preliminary Model
In the current study, the AMOS software package, version 22.0.0 (Arbuckle,
2013), was used to create and analyze a hypothetical structural model for the relationship of
mindfulness on self-regulation, self-efficacy, and academic performance, GPA. An initial causal
path model was created from the theoretical literature reviewed earlier and tested for goodness of
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fit using the data collected in this study. Further models were strategically developed until the
optimal goodness of fit was discovered.
The initial model was formulated to most accurately depict this study's hypothesis
analyzing the impact of mindfulness on students’ self-efficacy, self-regulation, and academic
performance. To depict this model graphically in its basic form circles were used for the latent
variable mindfulness, self-efficacy and self-regulation, and a rectangle was used for the
observable variable, academic performance, GPA. The model was path recursive, analyzing the
effect of mindfulness on self-regulation, self-efficacy, and GPA through structural regression
coefficients and can be found in Figure 14.

Figure 14. The Mindfulness Conceptual Relationship in its Most Basic Form
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Because self-regulation and self-efficacy had a prior influence on academic performance
before a mindfulness treatment was introduced, the SEM must reflect this influence on the
variables with disturbance or error. Hence, the SEM evolved to justify this by representing the
disturbance on the latent variables with ‘d’ and error on the observed variable with ‘err’. The d1
circle depicts the disturbance influence on self-efficacy, d2 circle on self-regulation, and err1
circle represents the error on the observed variable of academic performance can be found in
Figure 15.

Figure 15. The Mindfulness Conceptual Relationship with Disturbance and Error Added
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Following from this most basic conceptual relationship, the sub-scales of each
endogenous latent variable instrument, SSRQ and SE, are added to the model to analyze their
influence respectively. Each instrument comprised multiple subscales, each of which was
designed to examine a particular latent concept that was itself a component of the two primary
latent factors, self-regulation and self-efficacy. Because of this, the most thorough model would
include a second level of latent variables, each influenced by their overall concept and
influencing the observed scores on each survey item associated with that concept. This would,
however, introduce enough statistical complexity to the model that a sample as small as the one
in the present study would be inadequate to accurately assess. In order to facilitate realistic
testing of the model, the summary score from each subscale was therefore accepted as an
observed variable in and of itself. In the interest of parsimony, the location variable was not
added to the model, since the preliminary analysis showed no significant influence on either self-
regulation or self-efficacy. Subsequently, the sub-scales are recognized as observed variables
and depicted with rectangles and identified with their respective subscale heading and error
adjustment. These steps resulted in the preliminary hypothesized model, shown in Figure 16.
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Figure 16. Preliminary Hypothesized model used for Exploratory Factor Analysis
Exploratory Factor Analysis
Exploratory factor analysis (EFA) was a method for identifying a structure, factors, or
dimensions that underlies the relations among a set of observed variables. Factor analysis was a
technique that transforms the correlations among a set of observed variables into smaller number
of underlying factors, which contain all the essential information about the linear
interrelationships among the original test scores. This statistical procedure involved the
relationship between observed variables, measurements, and the underlying latent factors
(Gaskin, 2012). Hence, factor analysis was considered a fundamental component of structural
equation modeling by determining how the variables relate and group based on inter-variable
correlations.
The EFA was a statistical approach for determining the correlation among the variables
in a dataset. This type of analysis provides a factor structure or a grouping of variables based on
strong correlations and was used for cleaner structural equation modeling. The EFA
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predetermined problematic variables and underlying factors before the confirmatory factor
analysis was run.
The case and variable data was first screened to for atypical data to ensure a valid
exploratory factor analysis (Lowry & Gaskin, 2014). The cases were screened for missing data,
unengaged responses, and outliers. Missing data was eliminated if a case had missing data on
5% or more of the variables (Gaskin, 2012). Cases that had missed data on less than 5% of the
variables remained in the data set. Unengaged responses existed when a student answered the
entire survey with the same Likert scale number. A standard deviation formula across variables
was used to determine if a student demonstrated variance among answers to help determine
relationships. If the standard deviation was zero the case was eliminated and if the standard
deviation was less than .5 then a visual inspection for atypical use was applied to determine
variance before elimination from data set. A total of 18 cases were eliminated from the data set
using the two previously mentioned techniques. The third technique, outliers, was suggested to
run for identifying atypical data. Considering that the latent variables, self-regulation and self-
efficacy, were latent variables measured with a closed Likert scale, an outlier did not exist in this
scenario. Additionally the sample population was middle school students either in 6
th
, 7
th
, or 8
th

grade and their gender or placement in AVID program was considered fixed. Consequently
there are no outliers in these scenarios.
The variables were screened for atypical data by identifying missing data and exploring
kurtosis due to Likert scale results. Missing variable data was replaced with mean average of the
variable since the each variable was a pre-determined calculation of several Likert scale
questions grouped together for determining observed latent variable tendencies. The result was
no missing data in 152 cases. Kurtosis was explored through SPSS and if found to be greater
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then the absolute value of 2 the variable was considered to exhibit kurtosis. Kurtosis was not
found in the data set as all variables kurtosis was less then the absolute value of two.
The preliminary model used for exploratory factor analysis model was recursive, and has
29 variables, which consisted of 13 observed and 16 unobserved variables. In the model, 15
elements are exogenous, functioning as independent factors, which includes mindfulness; 14 are
endogenous—functioning, at least in part, as dependent variables, which includes the latent
variables of self-regulation and self-efficacy. Additionally, 14 of the unobserved exogenous
variables are residual. There are 455 distinct sample moments with 145 distinct parameters that
were estimated. Consequently the model has 310 degrees of freedom (455-145=310), indicating
that the model was sufficiently over-identified.
The appropriateness or adequacy of data was determined next using the Kaiser-Meyer-
Olkin Measure of sampling adequacy (KMO). The KMO was .909, demonstrating high
credibility. Bartlett's test of sphericity demonstrated significance of .001and determined the
variables do relate to one another enough to run a meaningful EFA. In other words the matrix
was not an identity matrix. The communality or the extent to which an item correlates with all
other items and subsequently loads significantly demonstrated adequacy when determined
through maximum likelihood were < .3 (Gaskin, 2012). Total variance explained was sufficient
with 65.821% cumulative. The goodness-of-fit test was adequate and showed no significance
.099 based on chi-squared of 65.463. The pattern matrix was executed using maximum
likelihood extraction method and Promax with Kaiser normalization rotation method. The
results demonstrated all items loaded onto factors and none loaded negatively; however, a
potential problem was detected when 3 items cross-loaded, suggesting potential convergent and
discriminant invalidity (Gaskin, 2012). Consequently this model was rejected.
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EFA Model Revision
A process of trial and error was used for dropping observed self-regulation subscale items
that cross-loaded until an acceptable or clean pattern matrix was found and subsequent model run
for analysis. The optimal model was produced when the observed variable of self-regulation,
self-regulation implement, or the ability to implement self-regulation was deleted from the
model. The revised EFA model is shown in Figure 17.

Figure 17. Revised Hypothesized Model Used for Exploratory Factor Analysis. SRII= Self-
Regulation Information Input; SRP = self-regulation planning; SRS = self-regulation search;
SRPE = self-regulation plan evaluation; SRSEV = self-regulation self-evaluation; SRITC = self-
regulation instigation to change; SECBL = self-efficacy beliefs about learning; SEEGO = self-
efficacy extrinsic goal orientation; SETV = self=efficacy task value; SELP = self-efficacy for
learning performance; SEIGO = self-efficacy for intrinsic goal orientation.
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The resulting KMO was .910, demonstrating slightly higher credibility then the original
EFA model run. Bartlett's test of sphericity demonstrated significance of .001and determined the
variables do relate to one another enough to run a meaningful EFA. The communality or the
extent to which an item correlates with all other items and subsequently loads significantly
demonstrated adequacy when determined through maximum likelihood were < .3, except for 1
item which was .288 for instigation to change self-regulation (Gaskin, 2012). However, since it
was very close to .3 it was not problematic when the rest of the model was run. Total variance
explained was sufficient with 60.617% cumulative. The goodness-of-fit test significance = .001,
which was below the accepted level of >.05 based on chi-squared of 95.852. However
researchers such as Kenny and McCoach (2003) have expressed misgivings about the accuracy
of the figure with small sample size and low numbers of variables such as the current study.
Consequently a variety of other goodness of fit standards has been developed (Bentler, 1990;
Brown et al., 1993; Gaskin, 2012; Hu & Bentler, 1999; Kenny & McCoach; Wheaton et al.,
1977). These other goodness-of-fit tests results explained in conjunction with the model fit
metrics for the confirmatory factor analysis model presented later. The pattern matrix was
executed using maximum likelihood extraction method and Promax with Kaiser normalization
rotation method. The results demonstrated all items loaded, none loaded negatively, all were
above .5, and no cross loadings. The absence of cross loadings demonstrates convergent and
discriminant validity (Gaskin, 2012). Additionally the total average for each factor should be
>.7 so loadings are high enough to be convergent (Gaskin, 2012). The overall averages for
factor 1 was. 809 and factor 2 was .725. Subsequently loadings are demonstrating convergence.
An adequate pattern matrix allowed discriminant validity to be explored in the pattern
matrix and factor correlation mix. The first identifier of discriminant validity was no cross
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loadings were present in the pattern matrix. The second identifier lied in the factor correlation
matrix where no factors correlated above .7 and 50%. The results were .528 for factor 1, self-
efficacy subscales, and .528 for factor 2, all self-regulation subscales except implementation.
These results demonstrated a 28% variance was shared between factors. Reliability was
confirmed on each factor when Cronbach alpha was >.7. Factor 1’s, self-efficacy subscales,
Cronbach alpha was .918 and factor 2’s, all self-regulation subscales except implementation
Cronbach alpha was .871. Hence, the EFA model revision has reliability.
Confirmatory Factor Analysis
The confirmatory factor analysis (CFA) was the next step after EFA to determine the
factor structure of the dataset and confirm the factor structure extracted in the EFA. The first
essential step was determining model fit. Model fit refers to how sufficiently the proposed
model accounts for the major correlations between variables in the dataset. The metrics for this
study’s model fit are reported in Table 11.

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Table 11
Model Fit Metrics for CFA
Measure Study Results Threshold
Chi-square/df (cmin/df) 1.808 <3 good (fits within threshold)
p-value for the model .001 >.05 (poor fit – likely due to small sample
size and low number of variables (Kenny &
McCoach (2003)
CFI .944 >.90 traditional (fits within threshold)
GFI .850 >.85 permissible (fits within threshold)
AGFI .779 >.75 permissible (fits within threshold)
RMSEA .041 <.05 good (fits within threshold)
PCLOSE .997 >.05 (fits within threshold)
Note. CFA = Confirmatory Factor Analysis; CFI = comparative fit index; GFI = goodness-of-fit
index; AGFI = adjusted goodness-of-fit index; RMSEA = root mean square error of
approximation; PCLOSE = p of close fit.

The goodness of fit was met in all metrics presented in Table 2 except p-value. As
previously discussed, the p-value most likely was not being met due to the small sample size and
low number of variables as stated by Kenny and McCoach 2003).
Establishing convergent and discriminant validity, as well as reliability, was essential for
CFA in order to test a causal model or structural equation model. The model met convergent and
discriminant validity as stated by Hair (2010) and Gaskin (2012). The convergent and
discriminant variable can be found in Table 12.

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Table 12
Convergent and Discriminant Validity

CR AVE MSV ASV
Threshold CR>0.7 AVE>0.5 MSV<=AVE ASV<=AVE
Self-Regulation 0.88 0.56 0.17 0.17
Self-Efficacy 0.94 0.75 0.17 0.17
Note. CR = composite reliability; AVE = average variance extracted; MSV = maximum shared
variance; ASV = average shared variance.

The next step to confirm the analysis model was to establish if external factors other than
the measures’ questions influenced the responses given. An online survey used in this study may
introduce systemic response bias that can inflate or deflate responses (Podsakoff P., MacKenzie,
Lee, Podsakoff N., 2003). Consequently a common method bias (CMB) test was run using a
common latent factor (CLF). The CMB demonstrated some evidence of common method bias in
self-regulation and self-efficacy factors but not in any others. Hence, self-regulation and self-
efficacy were slightly affected by common method bias. By retaining CLF, the model has
common method bias adjusted variables or values and these subsequent imputed composite
variables were carried into the structural equation model later.
Before creating composite variables or groups for a path analysis, configurable and
metric invariance was tested to validate that the factor structure and loadings area sufficiently
equivalent across groups. Subsequently, an invariance test was run on the groups of grade level,
gender, and AVID program. The configurable and metric tests confirmed the model was
metrically invariant and measured the same underlying latent construct for all groups. The
correlation loadings between variables were favorable for best-of-fit with the exception between
self-regulation and GPA which would be noted for any potential challenges arising with
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goodness-of-fit metrics. In conclusion, the confirmatory factor analysis was acceptable and the
structural equation model was built next and tested. The revised CFA models with maximum
likelihood parameter estimates are shown in Figure 18.

Figure 18. Revised Confirmatory Factor Analysis. Completely standardized robust maximum
likelihood parameter estimates. The residual variance components (error variances) indicate the
amount of unexplained variance. SRII= self-regulation information input; SRP = self-regulation
planning; SRS = self-regulation search; SRPE = self-regulation plan evaluation; SRSEV = self-
regulation self-evaluation; SRITC = self-regulation instigation to change; SECBL = self-efficacy
beliefs about learning; SEEGO = self-efficacy extrinsic goal orientation; SETV = self=efficacy
task value; SELP = self-efficacy for learning performance; SEIGO = self-efficacy for intrinsic
goal orientation.

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Structural Equation Model
Structural equation modeling (SEM) was derived from and functions similarly to multiple
regression. However, SEM was more powerful because it takes into account the modeling of
interactions, correlated independents, measurement error, correlated error terms, multiple latent
independents with each measured by multiple indicators, and one or more latent dependents also
each with multiple indicators. SEM was an umbrella concept for analyses such as mediation,
moderation, and interactions while controlling for potentially confounding variables and was
applied to this study for answering the third research question.
To build the structural model accurately the confounding variables of gender, grade level,
and AVID program participation were controlled for so that their potential effect on the model’s
outcome or dependent variables are reduced greatly. The structural equation model in Figure 19
depicts the control variables role.

Figure 19. Structural Equation Model
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Figure 19. Structural Equation Model. The residual variance components (error variances)
indicate the amount of unexplained variance. Control variables = Grade, Gender, AVID; AVID
= Advancement via Individual Determination for college and career readiness

Since the CFA model had common method bias adjusted variables and values due to
CLF, the structural model no longer reflects the CFA subscale items of the self-regulation and
self-efficacy variable, but instead reflected the effects of CLF and created imputed composite
variables and values for self-regulation and self-efficacy. Linearity was tested to verify causal
paths from the exogenous variable, mindfulness, to the endogenous variables; self-regulation,
self-efficacy, and academic performance. A curve estimation was run on all relationships in the
model and determined that all the relationships were sufficiently linear and tested using
covariance based structural equation modeling algorithm, such as used in AMOS. Subsequently
the model had no multi-collinear issues, meaning the model captured enough of the affect
independent variables have on each of the dependent variable because they are the same linear
effect.
The next step was to use a meditational model to illustrate the mechanisms through which
the causal effect of mindfulness on academic performance was related by advancing a causal
relationship through the mediating variables, self-regulation and self-efficacy (Mathieu &
Taylor, 2006). Mediation models are used to describe chains of causation. Mediation was often
used to provide a more accurate explanation for the causal effect the antecedent variable has on
the dependent variable. The mediator was usually the variable that was the missing link in a
chain of causation.

The mediation test was run through AMOS and full mediation was found for
both self-regulation and self-efficacy paths according to Baron and Kenny moderator mediator
approach (1986). This means that the direct effect of mindfulness on GPA was significant only
when the mediators, SR and SE, are absent, but when a mediator, SR or SE, are present the direct
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effect becomes insignificant and the indirect effect from mindfulness to mediator, SR or SE, to
GPA becomes significant. However when bootstrapping was performed the indirect causal path
showed no significance. The mediation results are shown in Table 13.
Table 13
Mediation Values for Structural Equation Model (SEM)
Relationship Direct without
Mediator
Direct with Mediator Indirect
Mindfulness SR
GPA
.190 (.010) -.018(.819) NS no mediation

Mindfulness SE
GPA
.190 (.010) -.019(.780) NS no mediation
Note. SR=Self-regulation. SE=Self-efficacy. GPA=Grade point average. NS=not sufficient.
Additional results were discovered about the causal path of a single moderator when the
other moderator and its effects were taken out of the model. In regards to self-regulation the
regression and standardized regression analysis indicated that a significant (.001) regression
weight estimate (.559) from mindfulness treatment to self-regulation was reported. However,
from self-regulation to GPA a regression and standardized regression analysis indicated no
significance (.385) regression weight estimate (.061). The self-efficacy moderator regression
and standardized regression analysis indicated that no significance (.149) regression weight
estimate (.133) from mindfulness treatment to self-efficacy was reported. However, from self-
efficacy to GPA a regression and standardized regression analysis indicated significance (.001)
regression weight estimate (.436).
The multi-group and interaction moderation effects were not needed to answer the
hypothesis of this study and subsequent research questions. Hence they were not measured.
Finally the structural model goodness-of-fit needed to demonstrate sufficient exploration of
alternative models was thorough and accounted for all the major correlations inherent in the
dataset. The model fit metrics were run and sufficiently met all model fit thresholds as stated by
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Hu and Bentler (1999). Hence this SEM model was used at the best-fit model to most accurately
answer this study’s research question 3. The SEM model fit metrics are displayed in Table 14.
Table 14
Model Fit Metrics for Structural Equation Model
Measure Study Results Threshold
Chi-square/df (cmin/df) .360 <3 good (fits within threshold)
p-value for the model .838 >.05 (fits within threshold)
CFI 1.000 >.90 (fits within threshold)
GFI .997 >.95 (fits within threshold)
AGFI .981 >.80 (fits within threshold)
RMSEA .001 <.05 (fits within threshold)
PCLOSE .910 >.05 (fits within threshold)
Note. CFA = Confirmatory Factor Analysis; CFI = comparative fit index; GFI = goodness-of-fit
index; AGFI = adjusted goodness-of-fit index; RMSEA = root mean square error of
approximation; PCLOSE = p of close fit.

Qualitative Results
The qualitative section, the third leg of triangulation, was designed to advance the
mindfulness phenomena in respect to self-regulation, self-efficacy, and academic performance by
exploring relationships and comparisons among ideas that evolve. Combining the quantitative
methods, qualitative methods, and SEM analysis allows us to better understand the research
questions through triangulating broad numeric trends from quantitative research and the detail of
qualitative research (Creswell, 2013).
At the end of the on-line survey containing the quantitative measures for mindfulness,
self-regulation, and self-efficacy, there were four open-ended questions to help better understand
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the depth of in which mindfulness, self-regulation, and self-efficacy were integrated into the
sample population over the duration of the 3 month study. The qualitative analysis software
program used to analyze, categorize, and coded over 3600 responses to the open-ended questions
was Atlas.ti 7.0.
The four open-ended questions asked at the end of the on-line survey were:
1. Can you easily stay focused on a class lesson? Why or why not?
2. What kind of goals do you set for yourself in your classes and how do you make sure
you achieve these goals?
3. Are you confident that you will do well in your classes? Why or why not?
4. Have you noticed any difference recently in how you learn in the classroom? Please
explain.
The first analysis measured the percentage of positive change over the study in both
control and treatment groups for each individual question. Each question’s set of answers was
reviewed for a positive change towards the stated question’s objective over the three different
time periods the on-line survey was administered, pre-treatment, post-treatment, and follow up.
An overall net-percentage change from pre-treatment to follow-up regarding focus in the
classroom was calculated at -1% for the control group and 12% for the treatment group, class
goals were 9% control and 11% treatment group, class confidence was 0% control and 10%
treatment, and the only negative cumulative result was learning in the classroom for both control
and treatment groups, control (c=-7%) and treatment (t=-4%). The subsequent cumulative net
positive result for all four questions between groups was control (c=4%) and treatment (t=29%).
A significant 25% (29-4=25) difference in growth between the treatment versus the control
group. Additionally the treatment group reported positive growth across all four areas addressed
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from pre-treatment to post while the control group reported only one area of positive growth in
class goals. Moreover the treatment group reported positive growth across all areas except
learning in classroom, while the control group reported positive growth in one area, class goals.
For a bar chart analysis of overall results see Figures 20 through 23.

Figure 20. Control and treatment group bar chart for Question 56
Figure 20. Reported positive growth bar chart in percentage. Q56 = Can you easily stay focused
on a class lesson? Why or why not? Cntrl = Control. Trmnt = treatment. Series 1 = percentage
respondents that answered question favorably.
0%

10%

20%

30%

40%

50%

60%

70%

Q56
Cntrl

Pre

Q56
Cntrl

Post

Q56
Cntrl

Follow
up

Q56

Trmnt
Pre

Q56

Trmnt

Post

Q56

Trmnt

Follow
up

Series1
55%
52%
54%
54%
57%
68%

%
Posi've
Response

Q56
Focus
-‐
Reported
Posi've
Growth
%

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Figure 21. Control and Treatment Group Bar Chart for Question 57
Figure 21. Reported Positive Growth Bar Chart in Percentage. Q57 = What kind of goals do you
set for yourself in your classes and how do you make sure you achieve these goals? Cntrl =
Control. Trmnt = treatment. Series 1 = percentage respondents that answered question
favorably.

Figure 22. Control and Treatment Group Bar Chart for Question 58
Figure 22. Reported Positive Growth Bar Chart in Percentage. Q58 Are you confident that you
will do well in your classes? Why or why not? Cntrl = Control. Trmnt = treatment. Series 1 =
percentage respondents that answered question favorably.

0%

10%

20%

30%

40%

50%

60%

Q57
Cntrl

Pre

Q57
Cntrl

Post

Q57
Cntrl

Follow
up

Q57

Trmnt
Pre

Q57

Trmnt

Post

Q57

Trmnt

Follow
up

Series1
41%
52%
50%
39%
43%
50%

%
Posi've
Response

Q57
GOALS
-‐
Reported
Posi've
Growth
%

66%

68%

70%

72%

74%

76%

78%

80%

82%

Q58
Cntrl

Pre

Q58
Cntrl

Post

Q58
Cntrl

Follow
up

Q58

Trmnt
Pre

Q58

Trmnt

Post

Q58

Trmnt

Follow
up

Series1
80%
80%
80%
72%
78%
82%

%
Posi've
Response

Q58
CONFIDENCE
-‐
Reported
Posi've
Growth
%

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Figure 23. Control and Treatment Group Bar Chart For Question 59
Figure 23. Reported positive growth bar chart in percentage. Q59 Have you noticed any
difference recently in how you learn in the classroom? Please explain. Cntrl = Control. Trmnt
= treatment. Series 1 = percentage respondents that answered question favorably.

Through the data analysis a story emerged of students’ who increased their use of self-
regulation and self-efficacy in the academic classroom through a combination of support
strategies stemming from a renewed ability to focus on content and its deliver, adopt or
reevaluate class goals, restore confidence in academic ability, and recognize personal
metacognitive learning that all in turn positively affect self-regulation and/or self-efficacy after
mindful practices are implemented. This qualitative study emergent story supports Williams and
Kabat-Zinn (2011) theory that mindfulness practice can resolve the problematic challenge of
self-regulation by un-clouding the already awakened and inherently wise mind filled with self-
regulation potential and reinforces Hyland’s (2009) findings that mindfulness can assist in
fostering self-esteem, confidence or emotional intelligence, engagement, and motivation. There
were treatment students who claimed no net positive change in their ability to focus, set goals,
0%

5%

10%

15%

20%

25%

30%

35%

40%

Q59
Cntrl

Pre

Q59
Cntrl

Post

Q59
Cntrl

Follow
up

Q59

Trmnt
Pre

Q59

Trmnt

Post

Q59

Trmnt

Follow
up

Series1
39%
32%
32%
33%
35%
28%

%
Posi've
Response

Q59
LEARNING
-‐
Reported
Posi've
Growth
%

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feel confidence, or shifts in learning which may be due to incorrect implementations of the
mindful breathing techniques, or lack of mindful practice longevity, which will be discussed
further in chapter 5.
Analysis of Open-Ended Questions
Self-Reported Focus in the Classroom
Mindfulness activates attentiveness, which as Dreyfus (2011) declares is the mindful
ability to pay close attention and not ‘wobble’ away from an object, or the ability of the mind to
remain focused and unified on its object. Students reported varying degrees of improved ability
to focus in the classroom, which supports Black and Fernando (2013); Napoli, Krech, and Holley
(2005); Schonert-Reichl and Lawlor (2010); and Wisner (2013) findings that students were able
to focus and pay attention to their academic lessons more easily. To take a case in point Student
C, a Caucasian 7
th
grade female, reported on the pre treatment survey, “I have a hard time
staying focused in class because I end up talking or doodling or just zoning out.” Immediately
following the mindfulness treatment student C noted, “I get off task/distracted pretty easily and I
feel like I am becoming more focused in class.” And finally one month after the mindful
treatment and continued mindful practice once a week student C stated, “Yeah because I have
become more focused.” Similarly student D, a Hispanic 8
th
grade male AVID participant,
reported before the mindfulness treatment, “I havent seen any difference in my class rooms
teaching style it seems everything is the same.” However immediately following the mindfulness
treatment student D wrote, “I noticed i am more attentive because i breath better to focus.”
Lastly student F, a Hispanic female, reported immediately following the mindfulness treatment,
“yes i have, in my math class i finish my work faster because i focus better but sometimes i get
distracted.” And one month later student F began to incorporate the mindfulness techniques into
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practice, “i have when I'm really bored in class i take deep breathes in and out i focus a lot
better.”
Other students experienced a shift in attentiveness and ability to focus but were unable to
ascertain the exact reason for the shift. For instance student A, a African-American 6
th
grade
male, reported before the mindfulness treatment, “.no because i talk a lot with my friend.”
Immediately following the mindfulness treatment student A conveyed, “yes because i know i can
do good.” And one month after the mindfulness treatment and weekly mindful practice sessions,
student A recounted, “Yes because I'm not moved next to my friends.” As the mindfulness
practices progressed student A most likely became more attentive in class, which renewed a self-
efficacious confidence in the student’s performance ability and in-turn engaged self-monitoring,
hence the student moved away from the friend so the student would not talk during class and
subsequently chose to engage in classroom learning. Both self-efficacy and self-regulation were
initiated by an increase in attentiveness or the ability to unify focus on the classroom learning
experience. Hence the student’s belief in their own efficacy allowed a new personal goal to
formulate as stated by Linnenbrink and Pintrich (2003). In conjunction with this positive shift in
self-efficacy, the ability to engage one of the self-regulation foundational pillars, self-monitoring,
was engendered, and subsequently as stated by Bandura (1997), the student was naturally
inclined to self-establish the progressive goal of moving her seat for improved classroom
performance without being prompted by an outside influence.
Finally a number of students reported an increase in focus ability due to the mindfulness
training and implementing mindful breathing practices during class and outside.

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Self-Reported Goals Setting in the Classroom
Howell and Buro (2011) first posited greater mindfulness was associated with related
self-regulation indices such as; enhanced endorsement of implicit theories for goal mastery.
Students reported varying degrees of goal specificity theories that ranged from goal
establishment to goal mastery. To take case in point, student H, an African-American 6
th
grade
male, accounted before the mindfulness practice treatment, “i don't have goals.” And then
during the 1 month follow-up survey he reported ,” One goal i set was to get good grades.”
Subsequently this student’s goal progress from no grades to good grades demonstrates an
implicit achievement related self-regulation goal mastery establishment.
Furthermore one of the three psychological sub-functions of self-regulation as stated by
Bandura (1997), self-reactive was enlivened through mindfulness. Consider student K, a
Hispanic 6
th
grade male, reported before mindfulness treatment, “Is set goals like not to be bad or
not talk when the teacher is talking and i don't do it.” He acknowledges his misalignment with
his intended goal; however, immediately following the mindfulness treatment he realigns himself
to the goal and established other goal attainment with success, “I expect myself to do my
homework, pay attention, follow the directions and etc. I do them by focusing.” By the one-
month follow-up student K reported mastering the original pre treatment goal, “I set goals not to
talk and to be a good person by doing it.” The student’s self-motivated growth path towards goal
mastery was a self-reactive psychological sub function as prescribed by Bandura (1991). The
student was motivated to self-monitor for his original goal attainment and his subsequent self-
evaluative reactions to behavior and progress enabled his goal attainment. Other students stated
similar outcomes of acquiring originally stated unobtainable goals by implementing implicit
goals as reported by student I during the one month follow-up survey, a Hispanic 8
th
grade
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female AVID participant, “to not get distracted and the way I do it is to pay attention to my
teacher.”
An additional benefit of mindfulness becomes prevalent when a student provided mindful
discrimination, which enabled the mind to observe, comprehend and evaluate what needs to be
evaluated and provide clear comprehension to produce a self-reactive state that promoted self-
directive change as opposed to reactionary change. This can be seen in student J, a African
American 8
th
grade female AVID participant, who during the pre-mindfulness treatment
expounded, “I want to be focused in class ad have a good behavior, because I tend to talk back a
lot. I also want to get good grades.” Her continued lack of effort immediately following the
mindfulness treatment becomes more self-evident, “the goals i TRY to set for myself is I want to
try and be more active in class, because some times im so focused on other people I dont focus
on my work.”. However after two months of mindfulness practices the student utilized the self-
directive aspect of self-regulation as stated by Bandura (1991) and began to achieve her goal, “i
try to be a better student by not talking to the people around me and not eating in class and doing
my actual work.”
Finally mindfulness practices can assist in lifting despondency when attempting to
achieve unrealistic goals and provide adjusted realistic goals to ensure healthy self-efficacy
beliefs. To take a case in point student L, a Caucasian 7
th
grade male, stated prior to mindfulness
treatment, “I like to have all A's however i have developed a habit of not doing the work so that i
fail. I need to work on this. A month later immediately following mindfulness treatment he
continued to struggle with his previously stated goal, “to get A's i work hard”. However, finally
after two months of mindful practices he pronounces a revised goal and retains commitment, “i
am certain that i will at least pass everything.” Hence he maintained his self-efficacy beliefs and
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motivation rather then failing and giving way to despondency which triggers a desire to dig out
of this hole by setting higher unrealistic goals that perpetuate the despondency and can result in
deeper depression and poor self-efficacy (Bandura, 1991). The mindfulness practices may help
regulate his state of maladaptive thoughts and feelings with greater awareness, and timelier to
strengthen self-monitoring frequency and effectiveness as stated by Bishop and colleagues
(2004). Moreover mindfulness practices can offer a principal role in maintaining self-efficacy
through disengaging self-degrading thoughts in the future that may arise when the student may
meet obstacles or failures.
Self-Reported Confidence in the Classroom
As stated by Pintrich and DeGroot (1990) self-efficacy includes judgments about one’s
ability to accomplish a task as well as one’s confidence in one’s skills to perform that task.
Hence this question on confidence in the classroom was formulated to uncover a student’s
predisposition towards self-efficacy and it’s subsequent growth or lack. Moreover Hyland
(2009) stated that mindfulness can assist in fostering self-esteem, confidence or emotional
intelligence, engagement, and motivation. Hence the students’ reports that follow intend to
highlight an enhancement of classroom confidence and subsequent self-efficacy. To take a case
in point, student N, a Hispanic 8
th
grade female, experienced a robust growth of self-efficacy in
the classroom. From her initial despondent pre-mindful treatment statement, “maybe because i
can't stay focused on my goals i just don't try any more.” to a resilient report two months after
mindfulness practices describing confidence in doing better in her classes, “yes sometimes
because sometimes i do not understand the subject.” The statement implies an absence of
despondency and increase in self-efficacy and willingness to put forth effort. Additionally the
student’s pronounced awareness to discern between areas of comprehension and lack of
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comprehension points towards a natural inclination to self-establish implied areas for
improvement and subsequent goal setting without being prompted by an outside influence
(Bandura, 1997).
Take another case in point, Student M, a Caucasian 8
th
grade male, stated a lack of any
confidence for performing well in his classes prior to the mindfulness training, “No, because i
cannot focus and it takes too much brain to do so.” Conversely immediately following the
mindfulness training he reported a noteworthy shift in academic confidence, “Yes because I
usually understand the course, when i don't i have tutors and such to aid me.” His statement
acknowledges a 180-degree turn from lack of any confidence to a resilient self-efficacious
confidence in his academic performance ability. Furthermore after the one-month follow-up
mindful practice sessions the student resounded with a fervent comment, “Yes, i can focus.” His
definitive declaration accentuates a monumental break through in comprehending educational
concepts and lessons offered. The student was now experiencing cognitive engagement by
proclaiming his ability to comprehend classroom lessons and materials without the aid of tutors
but instead by utilizing different strategies for learning and critical thinking independence
(Linnenbrink & Pintrich, 2003). Furthermore the student’s growth in self-efficacy gave rise to
achievement more so than intellectual ability as he initially implied (Bandura, 1991). His GPA
climbed from a pre-mindfulness score of 2.5 to 2.833 after only two months of mindfulness
practices.
Self-Reported Learning in the Classroom
Greater mindfulness has been associated with achievement related self-regulation indices
such as; enhanced endorsement of implicit theories for goal mastery; inspired greater willingness
to seek help, delayed gratification, used learning strategies; increased self-control; and lowered
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procrastination as posited by Howell and Buro (2011). The subsequent student reports highlight
the aforementioned effects of mindfulness on learning.
Students reported an increased sense of self-control, for instance, student V, a Hispanic
8
th
grade female AVID participant recognized, “yes i can stay calm when i get upset.”. She
further explained this feeling and of emotional self-regulation, “yes, i can stay a little bit more
focused and i do the breathing when i get angry at my teacher.” Student U, another Asian 8
th

grade male AVID participant explained a new personal learning strategy he had incorporated
immediately after receiving the mindfulness treatment, “Yes i started to take notes to help myself
learn a lesson.” Lastly, student O, a Hispanic 8
th
grade female, acknowledged another new
personal learning strategy that she used, “i have been listening then copying, i have been
studying more often and more determined to get pass a test.”.
Numerous students reported an increase in ability to learn but struggled to identify
combination of learning techniques or strategies utilized for achieving this increased ability to
learn. Frequently identified by students as the main attribute to their increased ability to learn
were the breathing techniques learned from the YES! program. Student Z, a Hispanic 6
th
grade
female, reported, “yes because the breathing helps with tests and projects.” Student AA, a
Hispanic 8
th
grade male AVID participant, revealed, “yes these breathing techniques help a lot.”
Student X, a Hispanic 8
th
grade female, stated, “yes. know that i have been doing all the thing
that the yes program has taught me then I've been doing much better.” Student Y, a Caucasian
6
th
grade male, declared, “Yes, because the Yes program made me focus more on the subject.”
Student BB, a Caucasian 6
th
grade male, asserted, “I have learned to breath better and to be calm
in class.” Student CC, a Hispanic 7
th
grade female, acknowledged, “i have when I'm really bored
in class i take deep breathes in and out i focus a lot better.” Student P, a Hispanic 8
th
grade male,
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reported, “Yes, I pay more attention and become more efficient than when I stop and breathe
than when I don't.” He also reported, “thanks to the yes program I have noticed a pleasant slight
change that helps me in tests and other subjects in classes.” Finally student W, an African
American 8
th
grade AVID participant recognized, “yes because i use the focus technique when i
get distracted to get back on track.”
Other students whose pre-mindfulness treatment comments stated nothing had changed in
their learning were simply amazed at their increased ability to learn. Some cases in point are:
student R, a Hispanic 8
th
grade male, asserted, “yes i have that I'm learning more and studying
more.”; student B, a Caucasian 6
th
grade female, declared, “yes, suddenly I stay more focused on
work and i actually understand it.”; student S, a Caucasian 6
th
grade male, stated, “I am more
focused in class and more relaxed and how I study is different.”.
Many theories are contributed to explaining these learning phenomena such as, Sinclair
(2014) posited the resting state delivered by mindfulness practices implies that neurological
synapse connections become stronger when allowed to rest briefly due to mindfulness practice
and subsequent learning becomes stronger and progresses. Moreover Sinclair reports that
mindfulness practitioners experience a neurological growth in areas of the brain that direct
attention, build concept for self, and reduce stress. In regards to students’ self-reported
phenomena of increased self-efficacy, Linnenbrink and Pirntrich (2003) posited self-efficacy was
key in promoting students’ engagement, learning, and better achievement. Additionally they
posited the more refined an individual self-efficacy conceptual interest was directly related to
actual engagement and learning. Self-regulation reported increase, simply stated, was a
phenomena and potentially be best explained by Williams and Kabat-Zinn (2011) theory that
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mindfulness practice can resolve the problematic challenge of self-regulation by un-clouding the
already awakened and inherently wise mind filled with self-regulation potential.
Summary
Overall this mixed methods study had several significant results and findings.
Mindfulness increased significantly from the YES! mindfulness treatment to 1 month later.
Moreover the treatment group had reported significant growth in self-regulation over the entire
study and between the mindfulness treatment to 1 month later. Additionally the interaction of
mindfulness with self-regulation for the treatment group had quadratic significant when analyzed
within-subjects contrast however the effect size was small at 1.9%.
Through structural equation modeling a clearer causal path of the phenomena’s effect of
mindfulness on self-regulation, self-efficacy and subsequently academic performance was
determined from a best-fit structural equation model that was derived from an exploratory factor
analysis, followed by a confirmatory factor analysis using observed and unobserved variables.
The structural equation model depicted modeling of interactions, correlated independents,
measurement error, correlated error terms, multiple latent independents with each measured by
multiple indicators, and one or more latent dependents also each with multiple indicators, which
helped define the constructs and how mindfulness, self-regulation, self-efficacy, and academic
performance are related to each other.
The qualitative portion of the mixed methods study showed strong relationships between
mindfulness and its positive effect on elements of self-regulation and self-efficacy in the
classroom such as the ability to focus, set goals, confidence and learning, suggesting further
exploration of these effects. A more robust discussion of these results and findings, their
implications, limitations, and suggestions for future research are presented in chapter five.
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CHAPTER FIVE: DISCUSSION
The United States has established a goal to move from 18th to 1st in the world for college
completion rates by 2020 (Foley et al., 2013). This goal requires immense changes in education,
not only with the system but also teachers and most importantly our students. But, can our
students accomplish this? Do they have the self-efficacy or belief in themselves and the ability
to self-regulate and think about how they learn, especially since poor self-regulation has been
documented as the main cause of K-12 students’ lack of school readiness (Blair & Diamond,
2008). Moreover the need for self-regulation is paramount, as self-regulatory factors have been
found to contribute independently to students’ academic attainment (Bandura et al.,1992).
Therefore the challenge becomes how do schools activate and engage self-efficacy and self-
regulation for learning in our students? This study posited a solution for rekindling self-
regulation, self-efficacy, and subsequently academic performance that is as old as humankind
itself? A solution that has proven to ignite the natural ability to observe one’s own mind and
emotions without reacting impulsively but with greater capacity to see relationships between
thoughts, feelings, and actions. This solution can enable one to dispassionately discern the
meaning and causes of experience and behavior through self-regulation of attention,
metacognition, and self-efficacy (Bhatia et al., 2003; Bishop, et al., 2004; Flavell, 1979;
Sutherland, 2014). The solution proposed by this study was the implementation of mindfulness
practices.
There have been substantial studies of the application of mindfulness in education with
respect to emotional self-regulation, building stress resilience, and building adaptive
interpersonal capabilities (Davidson & Kabat-Zinn, 2004; Dreyfus, 2011; Howell & Buro, 2011;
Hyland, 2009; Langer, 2009; Siegel, 2007; Wisner et al., 2010). However, there has been little
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research -- if any -- with respect to the phenomenon of mindfulness’ influence on self-regulation
and it’ use in learning for academic achievement both inside and outside of the classroom.
Sibinga et al. (2012) stated that there was a need for additional research to explore the impact of
mindfulness on self-regulation, the duration of the effect, and related social, psychological, and
behavioral outcomes.
As a result, this study attempted to divulge the benefits of mindfulness towards self-
regulation and it’s internal factor, self-efficacy, towards learning in high school students.
Bandura et al., (1992) stated self-regulatory factors contributed independently to students’
academic attainment, which stress the importance of self-regulation. Bandura (1991) further
emphasizes the importance of self-regulatory systems as the core of causal processes,
determining the effects of external influences on an individual and providing the foundation for
purposeful action or forethought. The self-regulation structure was operated through a set of
three psychological sub functions: self-monitoring; judgmental; and self-reactive which are
developed for self-directed change (Bandura, 1986). The functioning of this self-regulatory
structure or system was centrally dependent on the self-efficacy mechanism (Bandura, 1991).
Self-efficacy was the belief an individual has about their capability of appropriate self-
functioning within internal and external situations (Bandura, 1991) -- simply put, its one’s beliefs
about their ability to do the task (Linnenbrink & Pintrich, 2003). Additionally as stated by
Bandura (1997) a learner’s motivation was essential for self-regulation success. Motivation can
be demonstrated through commitment to goals, self-expectant outcomes, self-efficacy beliefs,
and two subcomponents of self-regulation; self-monitoring, and self-reactive states. Thus,
utilizing the lens of social-cognitive theory of self-regulation helped explain the phenomena of
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increased self-regulation usage in learning when a developed mindfulness state was present and
maintained.
The essential research questions formulated were based on the statement of the problem
and previously identified knowledge gaps in current research. The answers to the research
questions were collected from pre-existing data, performance data, and on-line survey
administered to all participating students. The research questions were as follows:
1. Was there a significant difference in students’ maturation levels of mindfulness between
the treatment and control groups over the duration of the study?
1a. Was there a significant difference in students’ maturation levels of self-
regulation between the treatment and control groups over the duration of the
study?
1b. Was there a significant difference in students’ maturation levels of
self-efficacy between the treatment and control groups over the duration of the
study?
2. Was there a difference in the effect of mindfulness on self-regulation between treatment
and control groups while controlling for entry levels of self-regulation and mindfulness?
2a. Was there a difference in the effect of mindfulness on self-efficacy between
treatment and control groups while controlling for entry levels of self-efficacy and
mindfulness?
2b. Was there a difference in the effect of mindfulness on academic performance,
GPA, between treatment and control groups while controlling for entry levels of
academic performance, GPA, and mindfulness?
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3. Were students’ level of mindfulness relative to the degree of impact on self-regulation,
self-efficacy and do those variables significantly impact student academic performance?
The hypothesis was generated from these research questions and based on findings from
previously conducted research on the topic. Consequently, the hypothesis stated the application
of the mindfulness development program would have an significant positive impact on students’
self-efficacy and self-regulation sub functions; self-monitoring, judgmental, and self-reactive,
which in-turn would positively impact students’ academic performance or GPA. The theoretical
lens used to analyze the hypothesis and research questions was the self-cognitive theory of self-
regulation.
In order to determine the causal effect of a mindfulness intervention on self-regulation
self-efficacy, and academic performance a concurrent mixed methods research design using
quantitative and qualitative approaches were used to depict the essential or invariant structure of
the mindful learning experience and provide the opportunity for triangulation of results and
findings (Merriam, 2009; Creswell, 2013). For the quantitative design, a post-positivist, quasi-
experimental quantitative survey design was applied. The self-report longitudinal survey design
provided a quantitative or numeric description on attitudes and opinions of high school students.
This pre- and post-survey research design method involved multiple variables and treatments
collected through data to support or refute the research questions (Creswell). Moreover, a
structural equation model was applied to confirm a causal path and identify the collective
strengths of multiple variables (Creswell). Finally, in consideration that the population of
students was selected by their pre-determined class assignments and not randomly assigned, this
portion of the research was quasi-experimental (Creswell).
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The quantitative design allowed for comparisons to be made between several variables
such as independent, dependent, mediating, moderating, or control variables (Creswell, 2013).
The independent variable used to develop mindfulness was the mindful intervention, YES!,
which will be discussed later in this study. The dependent variables that depend on the
independent variable are self-efficacy, self-regulation, and academic performance via GPA. The
intervening and moderating variables were determined as the intervention and surveys were
applied and the structural equation model implemented. The quantitative data analyzed was
from pre-existing student data, current student performance data, and a third set of data gathered
from pre and post mindfulness training surveys using a Likert scale based on mindfulness, self-
regulation, and self-efficacy measures.
Student self-reporting pre, post, and follow-up on-line surveys were used to describe,
explain, and compare their knowledge, feelings, values, and behaviors through self-administered
questionnaires to help understand the effectiveness of mindfulness on self-regulation and self-
efficacy in learning (Fink, 2009). The Mindful Attention Awareness Scale (MAAS), which
assessed individual differences in the frequency of mindful states over time, was used (Brown
and Ryan, 2003). Students’ self-regulation was assessed through a pre, post, and follow-up
mindfulness training survey using the Short Self-Regulation Questionnaire developed by Brown
et al. (1999) and approved by the National Institute of Health. The final instrument used in the
surveys to measure self-efficacy was, the Motivated Strategies for Learning Questionnaire,
(MSLQ) self-efficacy scale was used. Additionally, a special analysis procedure of structural
equation modeling (SEM) was used to enhance the interpretation of results and provide a
multiple-perspective review of latent or un-observable variable constructs.
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Qualitative data was collected during the on-line surveys to inductively build towards the
phenomenon and understand how the phenomenon functions can be replicated in the future
(Merriam, 2009). Four open-ended questions on some of the essential elements of self-
regulation, self-efficacy, and academic performance were used. The findings were tabulated
numerically and reported through student self-reporting descriptions.
Summary of Findings
Overall this mixed methods study had several significant results and findings. The YES!
program increased mindfulness significantly between post 1-month to follow up 2-months for the
treatment group. Moreover the treatment group had reported significant growth in self-
regulation over the entire study and between post 1-month and follow up 2-month assessment.
Additionally the interaction of mindfulness with self-regulation for the treatment group was
quadratically significant when analyzed within-subjects contrast however the effect size was
small at 1.9%. Finally when mindfulness and self-regulation were controlled for entry levels the
treatment group experienced seven times more growth in mindfulness then the control group, and
4.5 times more growth in self-regulation then the control group.
Through structural equation modeling a clearer conceptualization of the phenomena’s
effect of mindfulness on self-regulation, self-efficacy and subsequent academic performance was
determined from a best-fit structural equation model that was derived from an exploratory factor
analysis, followed by a confirmatory factor analysis using observed and unobserved variables.
The structural equation model depicted modeling of interactions, correlated independents,
measurement error, correlated error terms, multiple latent independents with each measured by
multiple indicators, and one or more latent dependents also each with multiple indicators, which
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helped define the constructs and how mindfulness, self-regulation, self-efficacy, and academic
performance are related to each other.
The qualitative portion of the mixed methods study showed strong relationships between
mindfulness and its positive effect on elements of self-regulation and self-efficacy in the
classroom such as the ability to focus, set goals, confidence and learning, suggesting further
exploration of these effects.
Seven quantitative research questions were designed to capture the mindfulness
phenomena effects and inter-correlations towards self-regulation, self-efficacy, and academic
performance. While the statistical analysis was reported in the previous chapter for each
research question, this section will briefly discuss the interpretations, meaningfulness and
connection to the literature for the findings of each research question.
Research Question 1
This question was designed to capture the essence of the hypothesis by first measuring
the effect of the YES! treatment on the independent variable, mindfulness, through a statistical
analysis exploration to determine if there was a significant difference in students’ maturation
levels of mindfulness between the treatment and control groups over the duration of the study?
Considering the on-line survey was administered on three separate occasions, a repeated
measures analysis of variance, ANOVA, was necessary to analyze significance. A repeated
measures ANOVA was an extension of the paired-samples t-test and was used to determine
whether there are any statistically significant differences between the population means of three
or more levels, time, of a within-subjects factor or dependent variable. Both treatment and
control groups demonstrated significant growth over the duration of the study; however, using
Bonferroni adjustment in post hoc analysis revealed that mindfulness concentration was
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statistically significantly increased only in the treatment group from post 1 to follow-up 2
months. The explanation for the dramatic increase in the later phase of the study rather than
immediately following the mindfulness treatment can be attributed to increased cultivation of
mindfulness over time, which was directly correlated to length and duration of mindfulness
practice. As stated by Bishop et al. (2004), Hinterberger et al. (2007), Jarden et al. (2011),
Shapiro et al. (2008), Siegel (2012) mindfulness was the act of cultivating awareness,
acceptance, non-judgment, and non-reactivity and is like a skill that can be developed with
mindfulness techniques and practice. Hence the longer mindfulness was practiced and cultivated
through breathing, meditative practices, and day-to-day behavior the more significant the
increase of mindfulness. Additionally as stated by Jarden et al. the increased amount of time
spent using the mindful qualifying strengths of character have been found to correlate
significantly with mindfulness development.
Research Question 1a
This question was designed to capture the essence of the hypothesis by measuring the
effect of the YES! treatment on the dependent variable, self-regulation, through a statistical
analysis exploration to determine if there was a significant difference in students’ maturation
levels of self-regulation between the treatment and control groups over the duration of the study?
Considering the on-line survey was administered on three separate occasions, a repeated
measures analysis of variance, ANOVA, was necessary to analyze significance. A repeated
measures ANOVA was an extension of the paired-samples t-test and was used to determine
whether there are any statistically significant differences between the population means of three
or more levels, time, of a within-subjects factor or dependent variable. The ANOVA analysis
determined both treatment and control groups displayed significant growth over the duration of
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the study, and the treatment group yielded the strongest effect size of 7.9%. The post hoc
analysis with Bonferroni adjustment revealed that only the treatment group showed significant
growth in self-regulation from post 1 month to follow-up 2 months and from pre-treatment to
follow-up 2 months.
The significant growth in the treatment group’s self-regulation may be contributed to
mindfulness practice’s cultivating ability to engage the three psychological sub-functions of self-
regulation as posited by Bandura (1986), which are developed for self-directed change. An
initial cultivation of mindfulness allows one to regulate states of varying adaptive and
maladaptive thoughts and feelings with greater awareness, and more timely to strengthen self-
monitoring frequency and effectiveness as stated by Bishop and colleagues (2004). A second
major contributing element to increased self-monitoring was the ability of mindfulness practices
to produce a restful state, default mode network, that allows the neurological connection,
synapse, to reach a new level of strength, higher than before and strengthen mindfulness’
inherent quality of self-monitoring. This increased ability to self-monitor was one of Bandura’s
three principal psychological sub-functions. He further stresses the importance of self-
monitoring and its ability to enable one to maintain attention on a unified field and engage
cognition, which in turn triggers the second sub-function, judgment. Judgment places value,
which in turn engages motivation for goal attainment. This goal attainment motivation engages
the third and final sub function of self-evaluative reactionary behavior. The self-evaluative
reactions to behavior and progress enabled goal attainment (Bandura, 1991). Hence mindfulness
induces the initial sub-function, self-monitoring, which in turn engage the other two sub-
functions for self-regulation and subsequent significant increase in the treatment group’s self-
regulation scores as self-reported by SSRQ.
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Research Question 1b
This question was designed to capture the essence of the hypothesis by measuring the
effect of the YES! treatment on the dependent variable, self-efficacy, through a statistical
analysis exploration to determine if there was a significant difference in students’ maturation
levels of self-efficacy between the treatment and control groups over the duration of the study?
Considering the on-line survey was administered on three separate occasions, a repeated
measures analysis of variance, ANOVA, was necessary to analyze significance. A repeated
measures ANOVA was an extension of the paired-samples t-test and was used to determine
whether there are any statistically significant differences between the population means of three
or more levels, time, of a within-subjects factor or dependent variable. The ANOVA analysis
determined both treatment and control groups displayed no significant growth in self-efficacy
over the duration of the study The post hoc analysis with Bonferroni adjustment again revealed
no significant growth in self-efficacy for either group.
Although there was no significant growth in self-efficacy, the data demonstrated an initial
growth for the treatment group in self-efficacy from pre-treatment to post 1 month and then a
drop in self-efficacy from post 1 month to follow-up 2 months. An explanation of this
inconsistent result was offered by Zimmerman (2000) who posits that self-efficacy does not
carry trait like stability across time and setting like self-beliefs, and its subsequent sensitivity
allows for it to be studied as an indicator of change during interventions such as the mindfulness
treatment. Consequently self-efficacy’s lack of stability did not only explain for the increase
directly after mindfulness intervention as explained above, but also account for the decrease in
self-efficacy 1 month after the intervention due to its instability. Additionally the lack of
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significant growth in self-efficacy can be contributed to factors that will be discussed later in the
limitations section.
Research Question 2
The purpose of this research question was to look deeper into the correlational effect of
the independent variable, mindfulness, on the dependent variable, self-regulation, through a
statistical analysis exploration to determine was there a difference in the effect of mindfulness on
self-regulation between treatment and control groups while controlling for entry levels of self-
regulation and mindfulness? A repeated measures multivariate analysis of covariates
(MANCOVA) was utilized to more fully understand the relationship and potential effect of
mindfulness on self-regulation. This study used covariates to control for entry-level pre-
conditions of self-regulation and mindfulness to determine these variables true results without
their entry-level measures confounding the observed outcome.
The pairwise comparisons with Bonferroni multiple adjustments for mindfulness
displayed a significant higher mean difference for control group then the treatment group can be
attributed to the control group’s higher post-treatment 1-month mean. The MANCOVA analysis
determined a mean direct relationship increase of self-regulation and mindfulness from post-
treatment 1-month to follow-up 2-months while controlling for their entry level was greater for
the treatment group then the control group in all cases. When mindfulness and self-regulation
were controlled for entry levels the treatment group experienced 7 times more growth in
mindfulness mean then the control group, and 4.5 times more growth in self-regulation mean
then the control group. The growth in self-regulation for the treatment group can be attributed to
the increased mindfulness inducing the initial self-regulation sub-function, self-monitoring,
which in turn engage the other two sub-functions for self-regulation and subsequent increase in
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the treatment group’s self-regulation scores as self-reported by SSRQ. Moreover the qualitative
results supported similar findings of the effects of mindfulness on self-regulation’s three
psychological sub-functions as well as self-efficacy, motivation, and confidence. The lack of
significant growth for self-regulation and mindfulness in the treatment group can be contributed
to factors that will be discussed later in the limitations section.
Research Question 2a
The purpose of this research question was to look deeper into the correlational effect of
the independent variable, mindfulness, on the dependent variable, self-efficacy, through a
statistical analysis exploration to determine was there a difference in the effect of mindfulness on
self-efficacy between treatment and control groups while controlling for entry levels of self-
efficacy and mindfulness? A repeated measures multivariate analysis of covariates (MANCOVA)
was utilized to more fully understand the relationship and potential effect of mindfulness on self-
regulation. This study used covariates to control for entry-level pre-conditions of self-efficacy
and mindfulness to determine these variables true results without their entry-level measures
confounding the observed outcome.
The pairwise comparisons with Bonferroni multiple adjustments for mindfulness
displayed a significant higher mean difference for control group then the treatment group can be
attributed to the control group’s higher post-treatment 1-month mean. The MANCOVA analysis
determined a mean direct relationship increase of mindfulness from post-treatment 1-month to
follow-up 2-months while controlling for entry level was greater for the treatment group then the
control group. However the self-efficacy means between treatment and control groups displayed
an inverse relationship with the control group increasing as the treatment group decreased.
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An explanation for this inverse relationship between the two dependent variables was
offered by Zimmerman (2000) who posits that self-efficacy does not carry trait like stability
across time and setting like self-beliefs, and its subsequent sensitivity allows for it to be studied
as an indicator of change during interventions such as the mindfulness treatment. Consequently
self-efficacy’s lack of stability did not only explain for the increase directly after mindfulness
intervention as explained above, but also account for the decrease in self-efficacy 1-month after
the intervention due to its instability. Additionally the lack of growth in self-efficacy can be
contributed to factors that will be discussed later in the limitations section.
Research Question 2b
The purpose of this research question was to look deeper into the correlational effect of
the independent variable, mindfulness, on the dependent variable, academic performance,
through a statistical analysis exploration to determine was there a difference in the effect of
mindfulness on academic performance between treatment and control groups while controlling
for entry levels of academic performance, GPA, and mindfulness? A repeated measures
multivariate analysis of covariates (MANCOVA) was utilized to more fully understand the
relationship and potential effect of mindfulness on self-regulation. This study used covariates to
control for entry-level pre-conditions of GPA and mindfulness to determine these variables true
results without their entry-level measures confounding the observed outcome.
The pairwise comparisons with Bonferroni multiple adjustments for mindfulness
displayed a significant higher mean difference for control group then the treatment group can be
attributed to the control group’s higher post-treatment 1-month mean. The MANCOVA analysis
determined a mean direct relationship increase of mindfulness from post-treatment 1-month to
follow-up 2-months while controlling for entry level was greater for the treatment group then the
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control group. The mean increase for GPA was also a direct relationship; however, the control
group had a minimally greater increase, 1.5, then the treatment group.
The positive academic performance results in the later phase of the study may be a pre-
cursor for continued future growth in academic performance due to an increased cultivation of
mindfulness as stated by Bishop et al. (2004), Hinterberger et al., (2011), Jarden et al., (2012),
Shapiro et al., (2008), and Siegel, (2007), which in-turn effects self-regulation, self-efficacy and
subsequently effects academic performance (Bandura et al., 1992, Caldwell et al., 2010; Howell
& Buro, 2011; Sibinga et al., 2012; Wisner et al., 2010). This causal path will be explored
further in the third research question to follow. The lack of significant growth in academic
performance could be contributed to factors that will be discussed later in the limitations section.
Research Question 3
The purpose of this research question was to explore the best-fit causal path structural
equation model that would determine a student’s level of mindfulness relative to the degree of
impact on self-regulation, self-efficacy and do these variables significantly impact student
academic performance? SEM was more powerful because it takes into account the modeling of
interactions, correlated independents, measurement error, correlated error terms, multiple latent
independents with each measured by multiple indicators, and one or more latent dependents also
each with multiple indicators. A direct causal path was confirmed and the structural equation
model goodness-of-fit metrics were run and sufficiently met all model fit thresholds as stated by
Hu and Bentler (1999).
The recursive model path demonstrated full mediation was found for both self-regulation
and self-efficacy paths according to Baron and Kenny moderator mediator approach (1986).
This means that the direct effect of mindfulness on GPA was significant only when the
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mediators, SR and SE, are absent, but when a mediator, SR or SE, are present the direct effect
becomes insignificant and the indirect effect from mindfulness to mediator, self-regulation or
self-efficacy, to GPA becomes significant. This direct effect without mediators was consistent
with the positive correlation found between mindfulness and academic performance as revealed
by Beaucheim et al. (2008), Barangan et al. (2007), Chang and Hierbert (1989), Cranson et al.
(1991), and Leon (2009). Additionally the qualitative results reported increased ability to focus
which enables a student pay attention to their academic lessons more easily and contribute to
increased academic performance (Black and Fernando, 2013; Napoli, Krech, and Holley, 2005;
Schonert-Reichl and Lawlor, 2010; and Wisner, 2013). Additionally, mindfulness practices
increase the gray matter, brain cells, in the superior parietal cortex of the brain, which helps to
regulate direction of attention that is a necessary element for focus (Sutherland, 2014). Similarly
Bhatia et al. (2003) discovered the increased beta activity and frequency range activated by SKY
breath practitioners was typical of brain state of attentive information processing. Moreover the
qualitative results supported similar reports of students experiencing increased learning results
attributed to the mindfulness treatment and its subsequent increase in ability to focus, generate
and maintain academic goals, increase and maintain confidence in academics, and discover new
methods for learning strategies and techniques. The lack of a significant direct effect on
academic performance when the mediators are present could be contributed to factors that will be
discussed later in the limitations section.
In regards to self-regulation the regression and standardized regression analysis indicated
that a significant (.001) regression weight estimate (.559) from mindfulness treatment to self-
regulation was reported and from self-regulation to GPA a regression and standardized
regression analysis indicated significance (.001) regression weight estimate (.436). Again this
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remains consistent with the ANOVA and MANCOVA analysis mindfulness’ significant effect
on self-regulation. The mindfulness enables the three psychological sub-functions for self-
regulation through a chain-reaction effect triggered by an increase in self-monitoring and
supported Bandura and Zimmerman’s (1992) finding that self regulatory factors influenced
students academic attainment. The initial cultivation of mindfulness allows one to regulate states
of varying adaptive and maladaptive thoughts and feelings with greater awareness, and more
timely to strengthen self-monitoring frequency and effectiveness as stated by Bishop and
colleagues (2004). A second major contributing element to increased self-monitoring was the
ability of mindfulness practices to produce a restful state, default mode network, that allows the
neurological connection, synapse, to reach a new level of strength, higher than before and
strengthen mindfulness’ inherent quality of self-monitoring. Bandura’s (1986) further stresses
the importance of self-monitoring and its ability to enable one to maintain attention on a unified
field and engage cognition, which in turn triggers the second sub-function, judgment. Judgment
places value, which in turn engages motivation for goal attainment. This goal attainment
motivation engages the third and final sub function of self-evaluative reactionary behavior. The
self-evaluative reactions to behavior and progress enabled goal attainment (Bandura, 1991).
Hence mindfulness induces the initial sub-function, self-monitoring, which in turn engage the
other two sub-functions for self-regulation and subsequent significant increase in the treatment
group’s self-regulation scores as confirmed by the structural equation model. The lack of
significant results for self-efficacy and academic performance can be contributed to several
factors that will be discussed later in the limitations section.

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Limitations
The study possessed limitations that may have affected or restricted the method and
analysis of research data. The limitations pointed to potential weaknesses that were unable to be
controlled or minimized in the study that may have threatened internal validity. There were three
scopes of limitations. The first scope of limitations involved the direct relationships of the
variables. Ruling out competing conceptualizations of inter-relationships between mindfulness
and self-regulation as well as self-efficacy was the first. This was attempted through the
ANOVA, MANCOVA, and SEM analysis but due to lack of significance for all dependent
variables it was unable to be managed with 100% confidence. The second limitation within this
scope was the lack of a longitudinal effect needed to cultivate mature mindfulness. As found by
Bishop et al. (2004) mindfulness develops over time with practice and a more robust cultivation
of mindfulness over time in-turn can have a more significant effect on self-regulation as posited
by Bhatia et al. (2003), Caldwell et al. (2010), Howell and Buro (2011), Sibinga et al. (2012),
Sutherland, (2014), and Wisner et al. (2010) self-efficacy as affirmed by Caldwell et al. (2010)
and Sutherland (2014), and enhance academic performance as documented by Barangan et al.
(2007), Beaucheim et al. (2008), (Burnett) 2009, Chang and Hierbert (1989), Crane (2009),
Cranson et al. (1991), Hanson (2009), Leon (2009), Siegel (2007).
The second scope of limitations surrounded the methodological procedures for data
collection and the selection of sample population. First, the use of self-report surveys was based
from measuring mediators and moderators, which limited accuracy due to self-reporting.
Moreover, the use of non - self-reporting measures to verify validity of this self-reporting study
may have introduced a bias due to self-reporting and socially desirable answers that may have
inflated the associations between mindfulness and self-regulation as well as self-efficacy.
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Additionally the measure used for mindfulness, MAAS, and self-regulation, SSRQ, did not
directly address the use of self-regulation for learning in the classroom. Moreover academic
performance may have been limited by only measuring GPA of 10-week triennial semester.
Secondly, the sample size of n =339 with a subsequent treatment group size of 169, with
only 128 students providing completed data for running the structural equation, proved
challenging in determining meaningful analysis as discussed earlier in the confirmatory factor
analysis section. A more diverse population would have been preferable to determine
generalizations among cultural groups; however, the study cannot be generalized for all middle
school students as the study was bounded due to a limited sample size of students from one
school. Third, a quasi-experimental design limited the study as not all subjects could be
randomly designed. Lastly, a longitudinal academic performance data collection of core class
grades only may have reflected a more accurate statistical description and insight on the
influence of mindfulness in academic performance.
The third scope of limitations involves the Structural Equation Model (SEM). A path
confirmatory factor model of a path diagram was used to measure relationships between
observed values and latent values and determine best goodness of fit. The limitations with SEM
are; the problem of omitted variables, the importance of lower-order model components, and
potential limitations of models judged to be best-of-fit (Tomarken & Waller, 2005).
Implications for Practice
This study had significantly emergent results that can inform educators on a new mindful
approach for students to direct their attention towards academic lessons more easily and
experience success in the classroom (Black and Fernando, 2013; Napoli, Krech, and Holley,
2005; Schonert-Reichl and Lawlor, 2010, and Wisner, 2013). Moreover a positive correlation
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between mindfulness practices and increased self-regulation and self-efficacy were found
(Caldwell et al., 2010; Howell & Buro, 2011; Sibinga et al., 2012; Sutherland, 2014; Wisner et
al., 2010). Additionally Caldwell et al. found that mindfulness boosted self-regulatory capacity

and as stated by Barangan et al. (2007), Beaucheim et al. (2008), (Burnett) 2009, Chang and
Hierbert (1989), Crane (2009), Cranson et al. (1991), Hanson (2009), Leon (2009), Siegel (2007)
enhanced academic performance.
The first implication for mindful practice was to choose the strongest mindfulness
program. This study chose the YES! program due to its combination of breath work and
meditation which appears to be the most direct path to cultivating mindfulness as suggested by
research depicting neurological benefits towards learning SKY breath. Recognizing the strong
performance of YES! program’s significant return on increased mindfulness in a very short
period of time, 2 months, as reported in research question 1 (RQ1) F(1.872, 237.774) = 5.260, p
=.007, partial η
2
= .040. Moreover the most significant increase in mindfulness was experience
between post 1 month to follow-up 2 months (M = 0.198, 95% CI [0.059, .337], p =.002), which
was most likely due to a richer cultivation and maturity of mindfulness over time through the
SKY breath and focus meditation. Consequently to further strengthen the cultivation of
mindfulness a number of mindful programs including YES! suggests a daily 20-minute mindful
practice be implemented to continue positive cultivation of mindfulness. Subsequently educators
should prepare their daily school schedule to incorporate mindfulness practices for at least 20
minutes a day after the initial mindful training to attain the most substantial and significant
results for increased self-regulation. Additionally it is recommended that faculty participate in
mindfulness training and daily practices for their own stress management and stronger sense of
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well-being to better facilitate students’ use of mindfulness tools in the classroom when needed
and deliver more effective lessons and teaching attentiveness.

The effect of mindfulness on self-regulation for learning over the duration of the study
was significant as determined by ANOVA, F(1.875, 219.409) = 4.085, p <.0005, partial η
2
=
.079. Moreover the most significant increase in self-regulation was experienced between post 1-
month to 2-month follow-up (M = 0.109, 95% CI [0.044, .174], p < .0005). Consequently the
late maturity of self-regulation appears to coincide with the late maturity of mindfulness, which
may also have a delayed effect on self-efficacy and academic performance over time when
mindfulness practice is continued in longevity. Subsequently educators should strategically plan
their self-regulation and self-efficacy scaffolding lessons around this delayed cultivation of
mindfulness. After students have experienced the initial mindfulness training and their ability to
focus, emotionally regulate, and self-monitor has begun to shift, educators may begin to
introduce self-regulation and self-efficacy lessons for optimal student comprehension and
retention.
Recommendations for Research
It is hoped that the results of this study inspire new directions for further investigation to
establish the significance of using mindfulness to enhance self-regulation, self-efficacy, and
academic performance. Additional research is needed to rule out potential competing
conceptualizations of inter-relationships between mindfulness and self-regulation, self-efficacy,
and GPA. Moreover future research should be structured with greater cross-fertilization of
research between achievement related self-efficacy and self-regulation for positive psychology to
isolate the independent effect of mindfulness. Additionally a larger sample size of 250 or more
for each treatment and control group would behoove a more robust SEM analysis.
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175

The measures for mindfulness and self-regulation were not designed to measure their
effectiveness for learning in the classroom setting. Consequently using measures that were
designed for the K-12 school setting may produce a more accurate picture of the latent variables
at work. For example a self-regulation measure such as Pintrich and DeGroot’s (1990) MSLQ
self-regulation subscale or Banduras’ et al., (1992) children’s multi dimensional self-efficacy
scales for measuring perceived self-regulatory efficacy for academic achievement may prove to
be a more accurate measure for the use of self-regulation in the classroom. Similarly a different
mindfulness measure designed for youth in the school setting could be used to more accurately
depict the latent variable’s effects, such as the Child and Adolescent Mindfulness Measure
(CAMM) as assessed by Greco, Baer, and Smith (2011). Furthermore a new mindfulness
measuring instrument designed specifically the school classroom setting could be formulated to
provide richer insight into the mindfulness phenomena.
Further research on longevity of mindfulness practices and their net effects on learning
variables such as self-regulation, self-efficacy, focus, goals, confidence, and learning are needed
for determining proper length and frequency of mindfulness practice. In this study mindfulness
training and practice was offered every other day, due to school scheduling issues, as opposed to
every day, which many mindful programs recommend. For example a public K-12 school in
India instituted the YES! for School daily SKY breath and meditation practice and experienced
strong significant results in academic performance among their first generation school going
students, who demonstrated a 100% passage rate for the end of year standards test. (IAHV,
2015).
Additional research is needed to determine if collection of longitudinal academic
performance data, GPA, in core classes only may have reflected a more accurate statistical
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
176

description and insight on the influence of mindfulness in academic performance, eliminating
electives and Physical Education which may create a disturbance when measuring academic
performance. Additionally alternative measures for academic performance should be considered
not only from core class grades but also include common core assessments, periodic
assessments, mid-terms, finals, and possible end of unit tests to determine a more accurate
picture of academic performance.
Exploring research further may offer insights on the neurological effects mindfulness
practices has on students’ learning and give a deeper understanding of this study’s mindfulness
and learning phenomena. For example, the YES! for school’s SKY breath has reported increased
beta activity of the left temporo-centro-pareital region with practitioners that matches the
increased information flow in the same region during mental arithmetic, which points towards a
potential link between increased mindfulness and increased mental math performance (Bhatia et
al., 2003). Current research suggests SKY breath daily practitioners experienced decreased
stress, increased stress resilience, decreased impulsive behavior, and increased attentive
information processing. Consequently future research is needed to identify specific aspects that
most strongly target strengthening self-regulation, self-efficacy and academic performance.
Furthermore Bhatia et al. found that SKY breath practitioners increased beta activity of the left
temporo-centro-pareital region matches the increased information flow in the same region during
mental arithmetic. In conclusion SKY breath daily practitioners experienced decreased stress,
increased stress resilience, decreased impulsive behavior, and increased attentive information
processing, which may be linked to strengthening self-regulation, self-efficacy and academic
performance, imploring further research is needed of the multifaceted benefits of SKY breath.
Moreover the YES! program’s SKY breath was found to significantly decrease impulsive
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
177

behavior in low-income high school students (Ghahremani et al., 2013). In addition the National
Institute for Complementary and Alternative Medicine’s recent discovery of more gray matter,
brain cells, in the areas of the brain that control directing attention and concept of self as reported
by Sutherland (2014), and Sinclair’s (2014) research that found synapse strength increased from
mindfulness practices which can strengthen learning. These revolutionary findings implore
education to demand further research into these neurological findings and their potential
connections to the learning mind. This pioneering research may discover more detailed
information on how the learning brain works and subsequently prescribe explicit mindful
practices to address specific individual challenges for self-regulation, self-efficacy, and other
specific learning challenges such as when focus meditation brought ADHD into normality
(Agrawal & Mizuhara-Cheng, 2010).
Conclusions
Considering the United States has established a goal to move from 18th to 1st in the
world for college completion rates by 2020 (Foley et al., 2013), immense changes in education,
not only with the system but also teachers and most importantly our students need to take place.
The main cause of K-12 students’ lack of school readiness has been identified as poor self-
regulation (Blair & Diamond, 2008). Moreover the need for self-regulation is paramount, as
self-regulatory factors, such as self-efficacy, have been found to contribute independently to
students’ academic attainment. With the new common core learning standards, it is necessary
for the success of our students to engage metacognitive and critical thinking skills in a much
deeper level then ever before. In order for this to happen successfully our students must be
equipped with the essential foundational building blocks of self-regulation and self-efficacy.
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
178

Many theorists consider the strength of these constructs to be determined ultimately by the
practitioner and their subsequent use.
Mindfulness has proven to ignite the natural ability of the practitioner to observe one’s
own mind and emotions without reacting impulsively but with greater capacity to see
relationships between thoughts, feelings, and actions. The mindfulness solution can enable one
to dispassionately discern the meaning and causes of academic experience and behavior through
increased self-regulation, self-efficacy, metacognition, and academic performance.
Consequently this study posited schools can activate and engage self-efficacy and self-regulation
for higher academic performance through implementing the effective mindfulness practice,
YES!. The program’s SKY breath has reported decrease of stress, increased stress resilience,
increased attentional focus, and increased beta activity that increases informational flow for
reasoning. Consequently additional research on the neurological benefits of SKY breath and
other mindfulness techniques are needed to uncover further hidden neurological benefits towards
students’ learning minds.
This new wave of research surrounding mindfulness and its many benefits are too
significant to ignore. Consequently it is of paramount importance that the education research
community increase its efforts on studying the benefits of mindfulness towards education
immediately. This undertaking is of paramount importance as our public education system is
flailing with mediocrity and repeated measures of insignificant academic gains. The educational
answers to renewed student motivation, academic responsibility self-regulation, self-efficacy,
critical thinking, and increased academic performance may very well be available to our student
community right now through mindfulness. Hence it is our personal and professional
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
179

responsibility to whole-heartedly engage in the implementation of mindfulness programs as soon
as possible. Our students’ success and well-being of our society may depend on it.

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
180

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Appendix A
Mindful Attention and Awareness Scale (MAAS)
1. I could be experiencing some emotion and not be conscious of it until sometime later.
2. I break or spill things because of carelessness, not paying attention, or thinking of something
else.

3. I find it difficult to stay focused on what’s happening in the present.
4. I tend to walk quickly to get where I’m going without paying attention to what I experience
along the way.

5. I tend not to notice feelings of physical tension or discomfort until they really grab my
attention.

6. I forget a person’s name almost as soon as I’ve been told it for the first time.
7. It seems I am “running on automatic” without much awareness of what I’m doing.
8. I rush through activities without being really attentive to them.
9. I get so focused on the goal I want to achieve that I lose touch with what I am doing right now
to get there.

10. I do jobs or tasks automatically, without being aware of what I’m doing.
11. I find myself listening to someone with one ear, doing something else at the same time.

12. I walk or ride to places on “automatic pilot” and then wonder why I went there.
13. I find myself preoccupied with the future or the past.
14. I find myself doing things without paying attention.
15. I snack without being aware that I’m eating.
Note . Items were introduced by the following: “Below is a collection of statements about your
everyday school experience. Using the 1–6 scale below, please indicate how frequently or
infrequently you currently have each experience. Please answer according to what really reflects
your experience rather than what you think your experience should be.” The accompanying 6‐
point scale is 1 = almost always, 2 = very frequently, 3 =somewhat frequently, 4 = somewhat
infrequently, 5 = very infrequently, and 6 = almost never.

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Appendix B
Short Self-Regulation Questionnaire (SSRQ)

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204

Appendix C
Self Efficacy Questionnaire (SE)
1. Compared with other students in my classes I expect to do well.
1 2 3 4 5 6 7
not at all very true
true of me of me

2. I’m certain I can understand the ideas taught in my classes.
1 2 3 4 5 6 7
not at all very true
true of me of me

3. I expect to do very well in my classes.
1 2 3 4 5 6 7
not at all very true
true of me of me

4. Compared with others in my classes, I think I’m a good student.
1 2 3 4 5 6 7
not at all very true
true of me of me

5. I am sure I can do an excellent job on the problems and tasks assigned for my classes.
1 2 3 4 5 6 7
not at all very true
true of me of me

6. I think I will receive good grades in my classes.
1 2 3 4 5 6 7
not at all very true
true of me of me

7. My study skills are excellent compared with others in my classes.
1 2 3 4 5 6 7
not at all very true
true of me of me

8. Compared with other students in my classes I think I know a great deal about the subjects.
1 2 3 4 5 6 7
not at all very true
true of me of me

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205

9. I know that I will be able to learn the material for my classes.
1 2 3 4 5 6 7
not at all very true
true of me of me

Note . Items were introduced by the following: “The following questions ask about your learning
strategies and study skills for this class. There are no right or wrong answers, just answer as
accurately as possible. Use the scale below to answer the questions. If you think the statement is
very true of you, circle 7; if a statement is not at all true of you, circle 1. If the statement is more
or less true of you, find the number between 1 and 7 that best describes you.”

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Appendix D
Pre, Post, and Follow-up Survey
PART 1
Below is a collection of statements about your everyday school experience.

Using the 1–6 scale below, please indicate how frequently or infrequently you currently have
each experience. Please answer according to what really reflects your experience rather than
what you think your experience should be.

The accompanying 6‐point scale is 1 = almost always, 2 = very frequently, 3 =somewhat
frequently, 4 = somewhat infrequently, 5 = very infrequently, and 6 = almost never.

I could be experiencing some emotion and not be conscious of it until sometime later.
Almost Always 1 2 3 4 5 6 Almost Never

I break or spill things because of carelessness, not paying attention, or thinking of something
else.
Almost Always 1 2 3 4 5 6 Almost Never

I find it difficult to stay focused on what’s happening in the present.
Almost Always 1 2 3 4 5 6 Almost Never

I tend to walk quickly to get where I’m going without paying attention to what I experience
along the way.
Almost Always 1 2 3 4 5 6 Almost Never

I tend not to notice feelings of physical tension or discomfort until they really grab my attention.
Almost Always 1 2 3 4 5 6 Almost Never

I forget a person’s name almost as soon as I’ve been told it for the first time.
Almost Always 1 2 3 4 5 6 Almost Never

It seems I am “running on automatic” without much awareness of what I’m doing.
Almost Always 1 2 3 4 5 6 Almost Never

I rush through activities without being really attentive to them.
Almost Always 1 2 3 4 5 6 Almost Never

I get so focused on the goal I want to achieve that I lose touch with what I am doing right now to
get there.
Almost Always 1 2 3 4 5 6 Almost Never

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
207

I do jobs or tasks automatically, without being aware of what I’m doing.
Almost Always 1 2 3 4 5 6 Almost Never

I find myself listening to someone with one ear, doing something else at the same time.
Almost Always 1 2 3 4 5 6 Almost Never

I walk or ride to places on “automatic pilot” and then wonder why I went there.
Almost Always 1 2 3 4 5 6 Almost Never

I find myself preoccupied with the future or the past.
Almost Always 1 2 3 4 5 6 Almost Never

I find myself doing things without paying attention.
Almost Always 1 2 3 4 5 6 Almost Never

I snack without being aware that I’m eating.
Almost Always 1 2 3 4 5 6 Almost Never

PART 2
Below is another collection of statements about your everyday school experience. Please respond
to the following questions by circling the response that best describes how you are.

Using the 1–5 scale below, please indicate how frequently or infrequently you currently have
each experience. Please answer according to what really reflects your experience rather than
what you think your experience should be.

The accompanying 5‐point scale is 1 = strongly disagree, 2 = disagree, 3 =uncertain or unsure, 4
= agree, and 5 = strongly agree.

I usually keep track of my progress toward my goals.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I have trouble making up my mind about things.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I get easily distracted from my plans.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I didn’t notice the effects of my actions until it’s too late.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I am able to accomplish goals I set for myself.
Strongly Disagree 1 2 3 4 5 Strongly Agree

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
208

I put off making decisions.
Strongly Disagree 1 2 3 4 5 Strongly Agree
It’s hard for me to notice when I’ve “had enough” (food, sweets)
Strongly Disagree 1 2 3 4 5 Strongly Agree

If I wanted to change, I am confident that I could do it.
Strongly Disagree 1 2 3 4 5 Strongly Agree

When it comes to deciding about a change, I feel overwhelmed by the choices.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I have trouble following through with things once I’ve made up my mind to do something.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I don’t seem to learn from my mistakes.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I can stick to a plan that’s working well.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I usually only have to make a mistake on time in order to learn from it.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I have personal standards, and try to live up to them.
Strongly Disagree 1 2 3 4 5 Strongly Agree

As soon as I see problem or challenge, I start looking for possible solutions.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I have a hard time setting goals for myself.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I have a lot of willpower.
Strongly Disagree 1 2 3 4 5 Strongly Agree

When I’m trying to change something, I pay a lot of attention to how I’m doing.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I have trouble making plans to help me reach my goals.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I am able to resist temptation.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I set goals for myself and keep track of my progress.
Strongly Disagree 1 2 3 4 5 Strongly Agree
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
209

Most of the time I don’t pay attention to what I’m doing.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I tend to keep doing the same thing, even when it doesn’t work.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I can usually find several different possibilities when I want to change something.
Strongly Disagree 1 2 3 4 5 Strongly Agree

Once I have a goal, I can usually plan how to reach it.
Strongly Disagree 1 2 3 4 5 Strongly Agree

If I make a decision to change something, I pay a lot of attention to how I’m doing.
Strongly Disagree 1 2 3 4 5 Strongly Agree

Often I don’t notice what I’m doing until someone calls it to my attention.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I usually think before I act.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I learn from my mistakes.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I know how I want to be.
Strongly Disagree 1 2 3 4 5 Strongly Agree

I give up quickly.
Strongly Disagree 1 2 3 4 5 Strongly Agree

Part 3
The following questions ask about your learning strategies and study skills for this class. There
are no right or wrong answers, just answer as accurately as possible. Use the scale below to
answer the questions. If you think the statement is very true of you, circle 7; if a statement is not
at all true of you, circle 1. If the statement is more or less true of you, find the number between 1
and 7 that best describes you.

Compared with other students in my classes I expect to do well.
1 2 3 4 5 6 7
not at all very true
true of me of me

I’m certain I can understand the ideas taught in my classes.
1 2 3 4 5 6 7
not at all very true
true of me of me
IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
210

I expect to do very well in my classes.
1 2 3 4 5 6 7
not at all very true
true of me of me

Compared with others in my classes, I think I’m a good student.
1 2 3 4 5 6 7
not at all very true
true of me of me

I am sure I can do an excellent job on the problems and tasks assigned for my classes.
1 2 3 4 5 6 7
not at all very true
true of me of me

I think I will receive good grades in my classes.
1 2 3 4 5 6 7
not at all very true
true of me of me

My study skills are excellent compared with others in my classes.
1 2 3 4 5 6 7
not at all very true
true of me of me

Compared with other students in my classes I think I know a great deal about the subjects.
1 2 3 4 5 6 7
not at all very true
true of me of me

I know that I will be able to learn the material for my classes.
1 2 3 4 5 6 7
not at all very true
true of me of me

Part 4

The following open-ended questions ask you about how you learn in your classes. There are no
right or wrong answers, just answer with as much detail as possible to help us understand how
you learn.

Can you easily stay focused on a class lesson? Why or why not?

What kind of goals do you set for yourself in your classes and how do you make sure you
achieve these goals?

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
211

Are you confident that you will do well in your classes? Why or why not?

Have you noticed any difference recently in how you learn in the classroom? Please explain.

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
212

Appendix E
Survey’s Open-Ended Questions.
Part 4

1. Can you easily stay focused on a class lesson? Why or why not?

2. What kind of goals do you set for yourself in your classes and how do you make sure you
achieve these goals?

3. Are you confident that you will do well in your classes? Why or why not?

4. Have you noticed any difference recently in how you learn in the classroom? Please explain.

Note . Items were introduced by the following: “The following open-ended questions ask you
about how you learn in your classes. There are no right or wrong answers, just answer with as
much detail as possible to help us understand how you learn. “

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
213

Appendix F
Pearson’s Product Moment Correlation

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
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Appendix G
USC IRB Approval Notice for Expedited Review

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
215

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
216

Appendix H
USC IRB Youth Assent-Parental-Permission Consent Form (English)

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
217

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
218

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
219

Appendix I
USC IRB Youth Assent-Parental-Permission Consent Form (Spanish)

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
220

IMPACT OF MINDFUL METHOD YES! ON STUDENT LEARNING
221

Abstract (if available)

Abstract Because self‐regulation has been documented as the main cause of K-12 students’ lack of college and career readiness, mindfulness interventions that augment self‐regulation, self‐efficacy and academic performance may offer support. This study evaluated the effects of the Youth Empowerment Seminar (YES!), a biophysical workshop for adolescents that teaches breathing practices, meditation and other mindful practices to regulate stress, emotions, and attentional focus on self‐regulation, self‐efficacy and academic performance. Approximately 339 Middle school students (11-14 years of age) in the United States participated in YES! during their physical education classes and continued weekly follow‐ups over a two month period. Students in a control group attended their usual curriculum and were tested in parallel. ANOVA and MANCOVA analysis was used to determine significant growth in the variables. The causal role of YES! on students’ self‐efficacy, self‐regulation, and academic performance was studied using path analysis procedures. Additionally four open‐ended questions were used to gather rich data for explaining the phenomena. ANOVA analysis determined that the YES! program had a significant impact on mindfulness and self‐regulation from post to 1‐month follow‐up after appropriate cultivation of mindfulness. A SEM causal path best‐fit analysis found a direct effect of mindfulness on academic performance was significant only when the mediators, self‐regulation and self‐efficacy, are absent but when the mediators are present the direct effect becomes insignificant and the indirect effect from mindfulness through the mediators to academic performance becomes significant. The results suggest that YES! can promote mindfulness, self‐regulation, self‐efficacy, and academic performance that increased directly with longevity of practices and subsequent increased cultivation of mindfulness.

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Asset Metadata

Creator Knepper, Jeffrey Mark (author)

Core Title The impact of the mindful method Youth Empowerment Seminar (YES!) on students' self-efficacy, self-regulation, and academic performance for becoming college- and career-ready

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 07/22/2015

Defense Date 05/13/2015

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag academic performance,breath,breathing techniques,college and career‐ready,focus meditation,Meditation,metacognition,mindful,mindfulness,mindfulness practice,OAI-PMH Harvest,self‐efficacy,self‐regulation,SKY Breath,Sudarshan Kriya,YES!,Yoga,Youth Empowerment Seminar

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Crispen, Patrick (committee chair), Tobey, Patricia Elaine (committee chair), Seli, Helena (committee member)

Creator Email jknepper108@gmail.com,jmkneppe@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-603706

Unique identifier UC11299800

Identifier etd-KnepperJef-3675.pdf (filename),usctheses-c3-603706 (legacy record id)

Legacy Identifier etd-KnepperJef-3675.pdf

Dmrecord 603706

Document Type Dissertation

Format application/pdf (imt)

Rights Knepper, Jeffrey Mark

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA