THE RELATIONSHIP BETWEEN EMOTIONAL-SOCIAL INTELLIGENCE AND LEADERSHIP PRACTICES AMONG COLLEGE STUDENT LEADERS
Bryan Jeremy Cavins
A Dissertation
Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of
DOCTOR OF EDUCATION
December 2005
Committee:
Patrick D. Pauken, Advisor
Louis I. Katzner Graduate Faculty Representative
Sara A. Best
Julie R. Lengfelder
Craig A. Mertler
© 2005
Bryan Jeremy Cavins
All Rights Reserved iii
ABSTRACT
Patrick Pauken, Advisor
This dissertation explored the relationship between Emotional-Social Intelligence (ESI) and student leadership practices among college student leaders. Additionally, analyses were conducted to determine if these constructs related to student performance within a university- sponsored, cocurricular, four-year leadership development program (Program). The study of
Emotional Intelligences and its relationship to effective leadership is evident in the literature; however, little if any research has applied this concept to student leadership practices and more specifically, student performance within a leadership development program. Eighty-Three students enrolled in the Program completed the Emotional Quotient Inventory, EQ-i (Bar-On,
1997) and the Student Leadership Practices Inventory, S-LPI (Kouzes & Posner, 2005).
Additionally, the Program director completed a modified 360-degree assessment to help measure the extent that participants’ self-reported scores (EQ-i and S-LPI) were supported by their performance within the Program.
Pearson r correlations found that many S-LPI subscales positively correlated, either moderately or strongly, with the following EQ-i variables: overall ESI, the Intrapersonal subscale, Self-Actualization, the Interpersonal subscale, Social Responsibility, Empathy, Stress
Tolerance, the Adaptability subscale, Problem Solving, the General Mood subscale and
Optimism. Among leadership practices, Modeling the Way, Enabling Others to Act, and Inspiring a Shared Vision correlated most frequently with the ESI construct.
Top Performers in the Program scored significantly higher than did other performance groups (Middle and Bottom Performers) in 11 out of the 21 ESI variables. Additionally, Top and iv
Middle Performers scored significantly higher than did Bottom Performers in the following S-
LPI subscales: Modeling the Way, Inspiring a Shared Vision, and Challenging the Process.
In terms of demographic differences and ESI, significant differences were identified with gender, age, GPA, race, year in the Program (cohorts), and mother’s education level. And within student leadership practices, significant differences were only identified with GPA, race, and father’s education level. Within four of the five S-LPI subscales, participants with fathers who had 2- and 4-year degrees scored significantly higher than participants with fathers who did not have a college degree. Implications for practitioners of student leadership development programs are outlined, particularly the provision of student leadership development opportunities.
Recommendations for future research are discussed. v
This dissertation is dedicated to my mother, Judith Ann Cavins, whose memory reminds me to
love humanity, embrace each day as if it were my last, and love my family first.
Her unwavering maternal love, steadfast compassion for all people,
and humble nature are the fabric of my life.
vi
ACKNOWLEDGMENTS
My father once told me that life is like a series of forests and within each forest there are challenges, celebrations, and life lessons. The doctoral process is a forest that is virtually
impassable without supportive, encouraging, and committed advisors, committee members,
family members, and friends. So it is with humility and grateful appreciation that I acknowledge
the many individuals who have helped me throughout this journey.
Advisor and Dissertation Committee
Dr. Patrick D. Pauken, I have never met a professional more giving and dedicated than you are. My personal journey is only one of many examples in which you have sacrificed your own personal time and energy to help others succeed. I strive to one day have your uncompromising drive and commitment, thank you. Dr. Louis I. Katzner, thank you for your acute eye for detail and knowledgeable suggestions for improving and fully developing my dissertation. Dr. Craig A. Mertler, thank you for guiding me through the methodology process and being there when statistical challenges emerged. Dr. Julie R. Lengfelder (Julie), thank you for your friendship and strong commitment to my success. Your guidance, positive attitude, and encouragement are the foundation of my achievements. Sara A. Best, you are a kindred spirit in the field of Emotional Intelligence and I am very appreciative of your encouragement, suggestions, and feedback.
Family and Friends
I am certain that at the beginning of this journey and two years into our marriage, my wife, Tricia Sue Cavins, did not fully understand the sacrifices, time commitments, and struggles that encapsulated the doctoral process. Tricia, thank you for your unwavering support, encouragement, and respectful understanding. You are an amazing and loving mother, wife, and vii
life partner. You graciously reminded me that success in life is most dependent on family commitment and the love of our children, thank you. To my four beautiful, intelligent, and fun- loving children, Emma, Brigid, Chloe, and Sean, thank you. Through your unconditional love and joyful spirit, I obtained the energy, passion, and drive to finish what I had started. I love you
all. To my father, Bryan V. Cavins, who was always there to encourage me and lend support
when I needed it most, thank you. Your entrepreneurial spirit and never-give-up attitude have
pushed me farther than you will ever know. I love you.
Dr. David L. Groves, you are an unsung hero in my success. You provided me with consistent support throughout this process. When I took a few years off because of family and
work matters, you encouraged me to focus on dissertation topics. Additionally, you willingly
shared with me the process of writing and submitting articles. I cannot thank you enough for
your mentoring, encouragement and understanding.
To so many other family members and friends, thank you for all of your help, support,
and commitment at various points during the completion of my dissertation. To the Myers
family, thank you for your love, support, and inclusion into the family. Lieutenant Sean David
Young, you are my best friend; thank you for your unyielding encouragement, dedication, and
steadfast friendship. To past and present Outdoor Program student staff members, thank you for
your “high speed” commitment to the success of the program. I would not have made it without
your support. To each of the Leadership Studies cohorts that I shared intellectual discussions
with, thank you for making Tuesday nights memorable! And finally, to all of my BGSU
colleagues and Recreational Sports comrades, thank you for your heartfelt and genuine
encouragement throughout this process. BGSU has become my home and you all are part of my
family. viii
TABLE OF CONTENTS
Page
CHAPTER I. INTRODUCTION...... 1
Background of the Study ...... 2
Social Change and Emotional Intelligence...... 2
Emotional Intelligence and Leadership Effectiveness...... 3
Student Leadership Development and Emotional Intelligence...... 5
Statement of the Problem...... 6
Purpose of the Study ...... 8
Research Questions...... 8
Significance of the Study...... 9
Overview of the Methodology...... 11
Student Leadership Development Program Description...... 11
Data Collection Instrument...... 12
Definition of Variables ...... 14
Delimitations of the Study ...... 18
CHAPTER II. REVIEW OF THE LITERATURE...... 19
Leadership Theory...... 20
Leadership and Change...... 22
Relational Leadership ...... 24
Five Practices of Exemplary Leaders ...... 26
Emotional Intelligence...... 29
Definitions and Measures of Emotional Intelligence...... 31 ix
Trait Measures Research...... 34
Leadership and Emotional Intelligence ...... 35
Emotional Intelligence and Leadership Challenges...... 37
Emotional Intelligence and Leadership Research...... 40
Student Leadership Development...... 43
Leadership and Society...... 44
Higher Education and Emotional Intelligence...... 45
Higher Education and Student Leadership Development...... 46
Relational Leadership and Student Leadership Development...... 47
Student Leadership Practices Inventory Research...... 49
Summary ...... 51
CHAPTER III. METHODOLOGY ...... 52
Purpose of the Study ...... 52
Participants ...... 54
The Leadership Development Program ...... 55
Instrumentation ...... 57
The Bar-On Emotional Quotient Inventory (EQ-i)...... 58
The Kouzes & Posner Student Leadership Practices Inventory (S-LPI) ...... 61
Data Collection Process and Procedures...... 63
Data Analysis ...... 64
CHAPTER IV. RESULTS...... 66
Description of the Participants...... 67
Instrument Internal Reliability (Cronbach’s alpha) ...... 71 x
Results of Research Question One (EQ-i means for the Sample) ...... 73
Results of Research Question Two (S-LPI means for the Sample)...... 76
Results of Research Question Three (S-LPI and EQ-i Correlations) ...... 77
Results of Research Question Four (Program Performance, EQ-i and S-LPI)...... 82
Results of Research Question Five (Demographic Variables, EQ-i and S-LPI) ...... 94
CHAPTER V. DISCUSSION AND CONCLUSION ...... 115
Summary of the Results...... 116
Discussion of the Results...... 122
Student Leaders Profile and Bar-On’s (ESI) ...... 122
Student Leaders and Kouzes and Posner’s Student Leadership Practices..... 125
Gender Differences - ESI and Student Leadership Practices...... 126
GPA - ESI and Student Leadership Practices...... 128
Program Cohort and Age - ESI and Student Leadership Practices...... 129
Race - Emotional-Social Intelligence and Student Leadership Practices ...... 131
Parent’s Education Level - ESI and Student Leadership Practices - ...... 133
Relationships between ESI and Student Leadership Practices ...... 135
Performance - ESI and Student Leadership Practices...... 141
Recommendations for Practitioners...... 145
Limitations of the Study...... 149
Recommendations for Future Research...... 150
Conclusions ...... 152
REFERENCES ...... 155
APPENDIX A. CONSENT LETTER (STUDENTS) ...... 166 xi
APPENDIX B. CONSENT LETTER (DIRECTOR)...... 169
APPENDIX C. DEMOGRAPHIC INFORMATION SURVEY ...... 171
APPENDIX D. STUDENT LEADER PERFORMANCE WORKSHEET ...... 172
APPENDIX E. STUDENT LEADERSHIP PRACTICES INVENTORY - SELF ...... 173
APPENDIX F. PERFORMANCE POST HOC TESTS...... 176
APPENDIX G. INDEPENDENT T-TEST: GENDER, EQ-I AND S-LPI...... 177
APPENDIX H. ANOVA TABLE AGE, EQ-I, AND S-LPI...... 179
APPENDIX I. AGE, EQ-I AND S-LPI POST HOC TESTS ...... 181
APPENDIX J. ANOVA TABLE GPA, EQ-I, AND S-LPI...... 182
APPENDIX K. GPA, EQ-I, AND S-LPI POST HOC TESTS ...... 184
APPENDIX L. ANOVA TABLE ACADEMIC COLLEGES, EQ-I, AND S-LPI ...... 185
APPENDIX M. ANOVA TABLE COHORT, EQ-I, AND S-LPI...... 187
APPENDIX N. COHORT, EQ-I, AND S-LPI POST HOC TESTS...... 189
APPENDIX O. INDEPENDENT T-TESTS: RACE, EQ-I, AND S-LPI ...... 190
APPENDIX P. ANOVA TABLE MOTHER’S EDUCATION, EQ-I, AND S-LPI ...... 192
APPENDIX Q. MOTHER’S EDUCATION, EQ-I, AND S-LPI POST HOC TESTS..... 194
APPENDIX R. ANOVA TABLE FATHER’S EDUCATION, EQ-I, AND S-LPI...... 195
APPENDIX S. FATHER’S EDUCATION, EQ-I, AND S-LPI POST HOC TESTS...... 197
APPENDIX T. ARTICLE: NICHOLS, D. P. (1998). MY TESTS DON’T AGREE ...... 198 xii
LIST OF TABLES
Table Page
1 Bar-On Emotional Quotient Inventory Components and Subscales...... 13
2 Internal Reliability Coefficient and Student Leadership Practices Inventory ...... 62
3 Summary of Sample by Demographic Variables...... 69
4 Internal Reliability Coefficient (Cronbach’s alpha) for the EQ-i and S-LPI...... 72
5 Group Report Standard Score Interpretation Guidelines...... 74
6 Summary of Sample Emotional Quotient Inventory Mean Scores...... 75
7 Summary of Sample Student Leadership Practices Subscale Mean Scores ...... 76
8 Pearson r Correlation Matrix between EQ-I variables and S-LPI variables...... 81
9 Mean Emotional Quotient Inventory Variables by Program Performance...... 83
10 Total EQ-i Scores and Program Performance ANOVAs...... 84
11 Intrapersonal Subscale and Program Performance ANOVAs ...... 85
12 Interpersonal Subscale and Program Performance ANOVAs ...... 86
13 Stress Management Subscale and Program Performance ANOVAs...... 87
14 Adaptability Subscale and Program Performance ANOVAs ...... 88
15 General Mood Subscale and Program Performance ANOVAs ...... 90
16 Mean Student Leadership Practices Scores by Performance Groups ...... 91
17 Student Leadership Practices Inventory and Group Performance ANOVAs ...... 93
18 Mean Emotional Quotient Inventory Scores by Gender...... 95
19 Mean Student Leadership Practices Scores by Gender...... 96
20 Mean Emotional Quotient Inventory Scores by Age...... 98
21 Mean Student Leadership Practices Scores by Age...... 99 xiii
22 Mean GPA Cluster Scores for the Emotional Quotient Inventory ...... 101
23 Mean GPA Cluster Scores for the Student Leadership Practices Inventory...... 102
24 Mean Year in Program Cohort Scores for the Emotional Quotient Inventory ...... 105
25 Mean Years in Program Cohort Scores for the S-LPI ...... 106
26 Mean Emotional Quotient Inventory Scores by Racial Groups...... 108
27 Mean Student Leadership Practices Inventory Scores by Racial Group ...... 109
28 Mean Emotional Quotient Inventory Scores by Mother’s Education Level...... 111
29 Mean S-LPI Scores by Mother’s Education Level ...... 112
30 Mean S-LPI Scores by Father’s Education Level...... 113
31 Mean Emotional Quotient Inventory Scores by Father’s Education Level ...... 114
1
CHAPTER I. INTRODUCTION
The quest for effective leadership development programs that prepare college students
for the challenges of post-education careers and personal lives continues to intrigue educators,
researchers, and practitioners. Likewise, contemporary organizations are faced with demands and
pressures of ever expanding magnitude. As a result, Goleman, Boyatzis, and McKee (2002)
explained that, “leaders everywhere confront a set of irrevocable imperatives, changing realities
driven by profound social, political, economic, and technological changes. Our world … is in the
midst of transformational change, calling for new leadership” (p. 246). During this chaotic
period, it is most important for organizational leaders to stay attuned to their own emotional
reactions to pressures, as well as how those environmental pressures affect their constituents.
Therefore, current research has focused on the importance of emotional intelligence (EI) in
relation to leadership effectiveness (Goleman et al., 2002; Stein & Book, 2000; Higgs, 2002).
The concepts and theoretical frameworks associated with EI have gained popularity and support,
as well as academic inquiry in the United States and around the world. Researchers generally
agree that EI addresses one’s ability to identify, interpret, and control his or her own emotions, as
well as stay in tune with, understand, and relate to the emotions of groups and individuals
(Goleman et al., 2002; Bar-On, 2002; Mayer & Salovey, 1993). Additionally, EI stems from
one’s ability to utilize emotional information to appropriately solve problems and make
environmentally savvy decisions. The present study explored the relationships between emotional intelligence, or Emotional-Social Intelligence (ESI) as interpreted by Bar-On (2005), college student leadership practices, leadership program performance, and various demographic variables.
2
Background of the Study
This first chapter presents the background of the study, the specific problems focused on during the study, a description of the study’s significance, definition of variables, delimitations, and an overview of the methodology. In this section, it is important to provide a theoretical
framework for the study. First, this study explored the social implications of EI and leadership in
our rapidly changing and complex world. Second, the current perspectives of EI and leadership were reviewed. And finally, student leadership development theory and performance at colleges and universities was investigated through the lens of the proposed connection between EI and student leadership practices.
Societal Change and Emotional Intelligence
Modern society is confronted with complexities and changes previously unseen in human history (Mumford, Zaccaro, Harding, Jacobs, & Fleishman, 2000). Regarding the rapidity of change, Massey (2002) described the important connection between two primary functions of the human brain, emotional and rational thought. He explained that our emotional and rational thought processes are parallel operations, so that “it is inevitable that all judgments, perceptions, and decisions will have both emotional and rational components” (p. 25). However, historically researchers, educators, and academic scholars have focused more attention on rational thought in education, while placing minimal importance on understanding emotional thought (Tucker,
Sojka, Barone, & McCarthy, 2000). Ultimately, Massey concluded that with the continual evolution and turbulent change in society, educators and researchers should put increased emphasis on emotional thought, as well as the impacts emotions have on human development, social interactions, perception-building, and social benefits.
3
Emotional Intelligence and Leadership Effectiveness
In the last two decades of the 20th century and more recently in the 21st century, a
significant amount of research and attention has been given to identifying relationships between
emotional and social intelligence regarding, life satisfaction (Palmer, Donaldson, & Stough,
2002), personality (Higgs & Rowland, 2001; Schulte, Ree, & Carretta, 2004), social relationships
(Lopes, Salovey, & Straus, 2003; Massey, 2002), team performance (Rapisarda, 2002), education
(Jaeger, 2003; Zeidner, Roberts, & Matthews, 2002), outdoor leadership training (Thompson,
2004) and most significant to this study, leadership (Goleman, 1998, 2001; Dulewicz & Higgs,
2003; Cherniss & Goleman, 2001).
Massey (2002) further discussed the importance of emotional thought as related to
modern daily environments, events, and behaviors, such as the creation of societal norms and
values, the impacts of consumer marketing, the influence of political behaviors, the
establishment of social fears, prejudices, and stereotypes, and the effects of increasing
urbanization (pp. 21-24). He explained that it is emotions, and particularly our emotional
memory, that often function at a subconscious level. For example, when we observe media
outlets and other daily events, e.g., crime and violence, news broadcasts, and various advertising
mediums, these images fix readily into our emotional and strongly subconscious memory. These
memories, Massey explained, impact our perceptions of the world and how we interact socially
within our increasingly urban communities. It is clear then that emotional understanding is
significantly valuable to both individual and societal relationships (Schutte et al., 2004).
Historically, social changes have been charted, coordinated, and led by a few leaders who had the ability to energize and motivate constituents or community members to stand tall, shed fears, and push forward the need for change. With this in mind, and the increased popularity of 4
EI, researchers began to study the connection between EI and leadership effectiveness (Goleman,
1998; Goleman, Boyatzis, & McKee, 2002; and Caruso & Salovey, 2004). Dulewicz and Higgs
(2003), for example, identified common EI elements that have been linked to effective leadership
characteristics: (a) self-awareness, (b) emotional resilience, (c) motivation, (d) interpersonal
sensitivity, (e) influence, (f) intuitiveness, and (g) conscientiousness and integrity (p. 207). In
light of the increasingly complex and changing world, researchers have highlighted leadership
change competencies as paramount to modern leadership effectiveness (Higgs & Rowland, 2001;
Mumford, et al., 2000; Yukl & Lepsinger, 2004). Goleman, et al. (2002), when talking about
building a culture of change in an organization, assert the following:
Emotionally intelligent leaders know how to manage their disruptive emotions so
that they can keep their focus, thinking clearly under pressure. They do not wait
for crisis to catalyze a need for change; they stay flexible, adapting to new
realities ahead of the pack rather than just reacting to the crisis of the day. Even in
the midst of vast change, they can see their way to a brighter future, communicate
a vision with resonance, and lead the way. (p. 247)
Organizational change is often considered a transformational process and has been linked to individual attitude, personality, and emotional intelligence (Vakola, Tsaousis, & Nikolaou,
2004). Therefore, transformational leadership theory is one of several theories that focus on the importance of creating a positive and reciprocal relationship between leaders and constituents for organizational success. Yukl (1999) described a transformational leadership connection in which,
“followers feel trust, admiration, loyalty, and respect toward the leader, and they are motivated to
do more than they originally expected to do” (p. 286). Sosik and Megerian (1999) identified four
characteristics which overlap with EI and transformational leadership: (a) well-developed social 5
and emotional skills, (b) an increased level of self-motivation, (c) an ability to stimulate team member development and performance, and (d) a leader’s ability to provide personal attention to
each team member. Ultimately, leadership is a social and emotional process, and effective
leaders are able to harness those social and emotional ties to successfully pilot organizations
through chaos and rapid change.
Student Leadership Development and Emotional Intelligence
Even as EI theory and related constructs have gained popularity, student leadership
development practitioners and scholars at colleges and universities have not fully embraced and
incorporated these new ideas. As mentioned earlier in this section, the modern world is rapidly
evolving and has been described as challenging, conflict-ridden, changing, surprising, and one
that necessitates a new leadership approach (Yukl & Lepsinger, 2004; Kouzes & Posner, 2002;
Goleman, Boyatzis, & McKee, 2002). Astin and Astin (2000) called for a leader who can be
adaptive and promote creative solutions to modern societal problems. They further explained
that:
To cope effectively and creatively with these emerging national and world trends, future
leaders will not only need to possess new knowledge and skills, but will also be called
upon to display a high level of emotional and spiritual wisdom and maturity. (p. 1)
Hence, there is little doubt that our turbulent world requires a new perspective on leadership
(Komives, Lucas, & McMahon, 1998). There is no greater producer of corporate and civic
leaders than higher education.
With the increased need for effective leadership in society, leadership development
programs at colleges and universities continue to gain popularity. In 1998, the Center for
Creative Leadership estimated that over 700 colleges and universities across the United States 6 had leadership development programs (Schwartz, Axtman, & Freeman, 1998). However, quantity does not assure quality. Connaughton, Lawrence, and Ruben (2003) argued that many of these leadership development programs are inadequate because they rely on short-term, isolated approaches to developing leaders. They explained, when discussing popular leadership workshops, that “it is unrealistic to expect that enhanced leadership capabilities can be developed in a two-hour or even a week-long leadership workshop” (p. 46). Rather, Connaughton, et al. purported that leadership development programs should be systematic and multidisciplinary with the aim to develop leadership competencies over time through initiatives that incorporate personalized interpretations of leadership theory with practical experiences that promote leadership planning and reflection. Additionally, along with creating a systematic approach to collegiate leadership development, leadership programs have utilized measures and leadership inventories to chart and assist the leadership development process (Posner, 2004). No real mention of emotional intelligence and college student leadership development has been addressed in the research, which identifies a need for research.
Statement of the Problem
Many leadership development programs at colleges and universities are founded on leadership studies and training models that were developed for management and leadership in private and public-sector organizations (Posner & Brodsky, 1992; Kouzes & Posner, 1998;
Posner, 2004). Posner and Brodsky (1992) recognized that collegiate leadership models focus on post-graduation leadership settings, and they questioned whether these corporate-based models and associated measurements were applicable to college student leadership development (p. 5).
To that end, Kouzes and Posner created a measure designed assess the leadership practices of college student leaders. The use of this instrument is common among leadership development 7 programs. The S-LPI is a tool to assist leadership development opportunities among college student leaders (Posner & Brodsky, 1993; Kouzes & Posner, 1998). To determine leadership strengths and improvement opportunities, the S-LPI allows students to interpret their scores compared with a normative sample of other college student leaders. Through research in the area of “personal-best” experiences, Kouzes and Posner’s five identified leadership practices, which were identified through studies associated with the stories of leaders who were able to “get
“extraordinary things done in their organizations” (Kouzes & Posner, 2002, p. 13). These leadership practices include Modeling the Way, Inspiring a Shared Vision, Challenging the
Process, Enabling Others to Act, and Encouraging the Heart. These five practices are reviewed in detail in Chapter Two. Refer to Appendix E for a copy of the S-LPI. Taking into consideration the identified importance of Emotional Intelligence as it relates to leadership effectiveness, and the application of Kouzes and Posner’s model in college student leadership development programs, the current study explored the relationship between Kouzes and Posner’s Student
Leadership Practices model and Bar-On’s Emotional-Social Intelligence model.
A growing number of collegiate student leadership development programs utilize leadership inventories and assessments to provide a basis for leadership development and improvement (Kouzes & Posner, 1998; Berg, 2003). With the application of leadership assessments tools in collegiate leadership programs and the emergence of research connecting EI with leadership effectiveness, it was important to explore the connections and divisions between an existing student leadership development construct and an emotional intelligence construct.
Identifying the relationships between student leadership practices and ESI was a worthy purpose for this research study. However, other variables further enhanced the exploration of this study. 8
To assist practitioners in the field of student leadership development, this study explored
the relationship between emotional-social intelligence and leadership practices, and differences between student performance groups and other demographic variables. With regards to demographic variables, the present study explored the following variables: (a) gender, (b) race,
(c) GPA, (d) academic college, (e) the numbers of years students have participated in the four- year leadership development program, and (f) parents’ education level.
Purpose of the Study
The purpose of this research study was to explore the relationship between emotional- social intelligence (using Bar-On’s Emotional Quotient Inventory, EQ-i) and student leadership practices (as identified by Kouzes and Posner’s Student Leadership Practices Inventory, S-LPI) among college students enrolled in a four-year leadership program at a Midwestern University.
Additionally, a modified 360-degree method was used to determine if the self-report instrument scores of the students (EQ-i and S-LPI) were supported by an external assessment of the students’ performance within the four-year leadership development program.
Research Questions
1. Among identified student leaders, what is the level of emotional-social intelligence, as
measured by the five composite scales and the fifteen sub-scales of Bar-On’s Emotional
Quotient Inventory (EQ-i)?
2. Among student leaders, what are their leadership practices, as measured by Kouzes and
Posner’s Student Leadership Practices Inventory?
3. Among identified student leaders, what are the relationships between Bar-On’s
Emotional Quotient Inventory (EQ-i) subscales and components and Kouzes and
Posner’s Student Leadership Practices Inventory subscales (S-LPI)? 9
4. Among identified student leaders, to what extent are the students’ Emotional Quotient
Inventory and Student Leadership Practices Inventory scores supported by an external
assessment of their performance in a four-year leadership development program?
5. What differences exist between emotional-social intelligence and leadership practices
among each of the following population categories: (a) gender, (b) age, (c) GPA, (d)
academic college, (e) the number of years student leaders have in the four-year program
(first, second, third, or fourth), (f) race, (g) mother’s education level, and (h) father’s
education level?
Significance of the Study
The significance of this study rests in its contribution to literature of the following areas: general leadership theory, leadership development, emotional intelligence (EI), and the study of higher education. Several research studies have evaluated the relationships between EI and leadership effectiveness in business and corporate settings (Sosik & Megerian, 1999; Prati,
Douglas, Ferris, Ammeter, and Buckley, 2003; Dulewicz & Higgs, 2003). However, until this study an insufficient amount of research had been conducted exploring the relationship between
EI and leadership among college student leaders (Low, Lomax, Jackson, & Nelson, 2003). The results of this study identified gaps and connections between student leadership practices and
ESI, and provided practitioners with needed support for adding EI training to student leadership development programs at colleges and universities. Equipped with this new information, student leadership program developers can offer training and development opportunities for students without overlapping curriculum that is already included in the Kouzes and Posner model.
Connaughton, Lawrence, and Ruben (2003) argued “that colleges and universities have a fundamental responsibility to guide the development of the next generation of capable and 10 ethical leaders and that these institutions must do so through a highly focused, multidisciplinary approach” (p. 46). This research study explored EI characteristics that have been purported to enhance leadership effectiveness in a chaotic and turbulent world (Goleman, Boyatzis, &
McKee, 2002; Sosik & Megerian, 1999; Dulewicz & Higgs, 2003). The results of this study provides representation for the connection between emotional-social intelligence and leadership practice, and sets the groundwork or impetus for developing assessments in the area of student leadership and emotional-social intelligence.
This study provided results that encourage student leadership program developers and instructors associated with both curricular and co-curricular programs in either student affairs or academic affairs to include Emotional-Social Intelligence training and development opportunities to enhance leadership development in higher education. The important role of higher education in the development of societal leaders cannot be understated. Astin and Astin
(2000) explained:
Higher education plays a major part in shaping the quality of leadership in modern
American society. Our colleges and universities not only educate each new generation of
leaders in government, business, science, law, medicine, the clergy, and other advanced
professions, but are also responsible for setting the curriculum standards and training the
personnel who will educate the entire citizenry at the precollegiate level. (p. 1)
Realizing the significant connection between higher education and the future success of society, this research assists and encourages the advancement and proliferation of Emotional-Social
Intelligence education throughout institutions of higher education. 11
Overview of Methodology
The primary research structure followed a correlational methodology that systematically
collected, tabulated, and analyzed information gained through the administration of two primary
survey instruments: one designed to measure student leadership practices (Kouzes & Posner –
Student Leadership Practices Inventory) and the other designed to measure Emotional-Social
Intelligence (Bar-On – Emotional Quotient Inventory). College students enrolled in a university
sponsored, four-year, leadership development program at a Midwestern state university were
asked to complete the aforementioned surveys as accurately and honestly as possible.
Additionally, the director of the four-year student leadership development program completed a
“Student Leadership Performance Placement” worksheet (Appendix D), or modified 360-degree
assessment worksheet in which the director to place members the program into performance
groups: (a) top 25%, (b) bottom 25%, and (c) middle 50%, which were created by default.
Student Leadership Development Program Description
The university-sponsored leadership development program is designed for students who
seek to develop their leadership skills and are determined to assume practical leadership
positions on campus. To be selected into the program from high school, seniors progress
thorough an application and interview process that is highly selective. Each year over one
hundred and fifty high school seniors apply for the program and only 25 to 30 students are accepted. Part of the applicants’ acceptance into the program is based on their level of demonstrated leadership experiences at the high school level. The leadership development program follows a servant leadership curriculum, which focuses on the development of leadership competencies and high academic success. The first year focuses on self-exploration and followership as it relates to group dynamics. The second year focuses on career and 12 leadership skill development. The third year continues to expand career development and advance leadership training, and students begin to share their leadership knowledge and skills with first and second year members. Finally, fourth and fifth year students assume a higher level of responsibility for their own development and learning while planning for post-college experience. This population of student leaders had a proven track record for leadership experiences in high school and demonstrated a continual record of leadership development at college.
Data Collection Instruments
Bar-On Emotional Quotient Inventory (EQ-i)
The Bar-On Emotional Quotient Inventory (EQ-i) consists of 133-items on a 5-point
Likert-type scale that measures emotional and social intelligence traits for ages 16 and over. Bar-
On (2002) defined EI as “an array of personal, emotional, and social competencies and skills that influence one’s ability to succeed in coping with environmental demands and pressures” (p. 14).
The EQ-i measures five general subscales associated with EI that consist of 15 components as shown in Table 1.
13
Table 1.
Bar-On Emotional Quotient Inventory Components and Subscales
Subscales Components Intrapersonal 1. Emotional Self-Awareness 2. Assertiveness 3. Self-Regard 4. Self-Actualization 5. Independence Interpersonal 6. Empathy 7. Interpersonal Relationship 8. Social Responsibility Adaptability 9. Problem Solving 10. Reality Testing 11. Flexibility Stress Management 12. Stress Tolerance 13. Impulse Control General Mood 14. Happiness 15. Optimism
Kouzes & Posner Student Leadership Practices Inventory (S-LPI)
The Student Leadership Practices Inventory, designed for college students and young adults, is a self-reported instrument consisting of 30 statements that are assessed by participants on a five-point, Likert-type scale that measures student leadership strengths. Five key leadership behavior areas are measured by the S-LPI: challenging the process, inspiring a shared vision, enabling others to act, modeling the way, and encouraging the heart. 14
Definitions of Variables
Emotional-Social Intelligence- ESI is a “cross-section of interrelated emotional and social
competencies, skills and facilitators that determine how effectively we understand and express
ourselves, understand others and relate with them, and cope with daily demands” (Bar-On, 2005,
p. 3).
Bar-On’s (EQ-i): The Intrapersonal Subscale
Self-Regard (SR) - “Ability to respect and accept oneself as basically good.” Relates to a
person’s ability to feel fulfilled and satisfied with oneself regardless of perceived strengths and
weaknesses. SR relates greatly to a person’s levels of self-assuredness, self-esteem, and self- respect (Bar-On, 2002, p. 15).
Emotional Self-Awareness (ES) - “Ability to recognize one’s feelings.” ES is a person’s ability to (a) be aware of his or her feelings and emotions, (b) differentiate between them, (c) identify what one feels and why, and (d) to be aware of what caused the feelings or emotions
(Bar-On, 2002, p. 15).
Assertiveness (AS) - “Ability to express feelings, beliefs, and thoughts and defend one’s rights in a nondestructive manner.” There are three main components of AS: (a) the ability to express feelings, (b) the ability to openly express thoughts and beliefs, and (c) the ability to support and stand up for personal rights. Assertiveness is the balance between shyness and overbearing, or the ability to express beliefs without being aggressive or insulting (Bar-On, 2002, p. 15).
Independence (IN) - “Ability to be self-directed and self-controlled in one’s thinking actions and to be free of emotional dependency.” Independent people are self-reliant planners 15 and decision makers who are able to work autonomously without overly relying on the opinion, protection and support of others (Bar-On, 2002, p. 16).
Self-Actualization (SA) - “Ability to realize one’s potential capabilities.” Involving one in pursuits that lead to a rich, meaningful, and full life. SA is one’s ability to strive toward continual improvement of one’s abilities, capabilities, and talents (Bar-On, 2002, p. 16).
Bar-On’s (EQ-i): The Interpersonal Subscale
Empathy (EM) - “Ability to be aware of, to understand, and to appreciate the feelings of others.” EM is a person’s ability to be on the same wavelength with people and to diagnose, and truly understand how and why they feel the way they do (Bar-On, 2002, p. 16).
Social Responsibility (RE) - “Ability to demonstrate oneself as a cooperative, contributing, and constructive member of one’s social group.” RE relates to taking responsibility for doing good things for and with people. Ability to accept people in one’s group and “use their talents for the good of the collective” (Bar-On, 2002, p. 16).
Interpersonal Relationships (IR) - “Ability to establish and maintain mutually satisfying relationships that are characterized by intimacy and by giving and receiving affection.” One’s ability to establish and maintain positive and satisfying relationships with others (Bar-On, 2002, p. 16).
Bar-On’s (EQ-i): The Adaptability Subscale
Reality Testing (RT) - “Ability to assess the correspondence between what is experienced and what objectively exists.” RT is one’s ability to gather objective evidence about a current situation, accurately assess the evidence and determine ways to cope with the situation (Bar-On,
2002, p. 17). 16
Flexibility (FL) - “Ability to adjust one’s emotions, thoughts, and behaviors to changing situations and conditions.” FL refers to one’s “overall ability to adapt to unfamiliar, unpredictable, and dynamic circumstances” (Bar-On, 2002, p. 17).
Problem Solving (PS) - “Ability to identify and define problems as well as to generate and implement potentially effective solutions.” PS relates to one’s ability to confront problems rather than avoid them (Bar-On, 2002, p. 17).
Bar-On’s (EQ-i): The Stress Management Subscale
Stress Tolerance (ST) - “Ability to withstand adverse events and stressful situations without ‘falling apart’ by actively and positively coping with stress.” ST is having the capacity to choose how you react to stress, maintain a level of optimism that stress won’t last, and to feel that one can control or influence the stressful situation (Bar-On, 2002, p. 17).
Impulse Control (IC) - “Ability to resist or delay an impulse, drive, or temptation to act.”
IC is the capacity to accept one’s aggressive impulses, maintain composure, and control aggressive and irresponsible behaviors (Bar-On, 2002, p. 18).
Bar-On’s (EQ-i): The General Mood Subscale
Optimism (OP) - “Ability to look at the brighter side of life and to maintain a positive attitude, even in the face of adversity.” OP is one’s ability to approach life in a hopeful and positive manner (Bar-On, 2002, p. 18).
Happiness (HA) - “Ability to feel satisfied with one’s life, to enjoy oneself and others, and to have fun.” HA relates to one’s ability to feel generally cheerful and enthusiastic about life
(Bar-On, 2002, p. 18).
17
Kouzes and Posner’s (S-LPI) Student Leadership Practices
Challenging the process - A leader’s ability to search and identify opportunities for change and to experiment and take risks to bring about change. Leaders also create environments that both generate and support innovation within themselves and their organization (Kouzes &
Posner, 1998, pp. 11-12).
Inspiring a shared vision- A leader’s ability to envision an uplifting and better future for him/herself and his/her organization. Additionally, a leader’s capacity to encourages, motivate, and generate excitement in others about a unite goal or future (Kouzes & Posner, 1998, p. 12).
Enabling others to act- A leader’s ability to generate an atmosphere of mutual trust and respect within the organization. It is also a leader’s capability to create a team environment that feels like a collaborative family where members feel like they own a part of the organization
(Kouzes & Posner, 1998, p. 13).
Modeling the way- A leader’s ability to role model a set of principles and values, as well as encourage individuals within the organization to accept those principles and values as their own. Additionally, this subscale relates to a leader’s ability to plan incremental accomplishments that set the stage for future success and goal attainment (Kouzes & Posner, 1998, pp. 13-14).
Encouraging the heart- A leader’s ability to recognize individual contributions and demonstrate pride in team accomplishments. This is characterized by concise directions, considerable encouragement, personalized attention, and constructive feedback (Kouzes &
Posner, 1998, p. 14). 18
Delimitations of the Study
The delimitations for this study are found in three primary areas: (a) specific characteristics of the population and location, (b) instrument limitations, and (c) potential
response biases. The findings of this study demonstrated relationships that exist among one
population of student leaders enrolled in a four-year student leadership development program at
a Midwestern university. The data were collected at a particular moment in time and cannot be
generalized or transferable to all populations and settings. Furthermore, the problems identified
with internal reliability could have related to participant attitudes and perceptions during data
collection, i.e., at the end of the spring semester.
In terms of response biases, both instruments used in data collection, (S-LPI and EQ-i),
were self-report measures that asked questions about the frequency of personal behaviors
associated with either emotional-social intelligence or student leadership practices. Thus the
results depended greatly on the accuracy, truthfulness, and perception of the respondents.
Furthermore, the EQ-i requires thirty to forty minutes to complete which may have affected
responses. Additionally, because this study was coordinated through the director of the program,
participants may have experienced a level of social pressure to participate, which again may have
influenced their responses. 19
CHAPTER II. REVIEW OF THE LITERATURE
Introduction
There is little question that humanity today is experiencing a rate of change unlike any other in our history (Massey, 2002). The rapidity of changes has had both positive and negative impacts on the social and economic fabric of our society. Massey (2002) explained that humans survived “roughly 300,000 generations as hunter-gathers, 500 generations as agrarians, nine generations in the industrial era and one generation so far in the emerging post-industrial era” (p.
15). During these transitions of human social development and survival, Massey explained that during the hunter-gather and agrarian eras human brain functioning applied more emotional than rational thought; a fight or flight mentality. Progressively, as societies moved from agrarian to industrial, and now into the post-industrial era, rational thought has accelerated and is now prominent in society. He further explained that with the acceleration of change since 1900, and particularly with the advent of computers in the 1980s, every facet of social and economic life
(e.g., family structure, manufacturing, and labor) has been transformed from an industrial-base wealth structure to a wealth structure that is driven by the control and manipulation of information (p. 15). As a result, Massey argued that as organisms, the human race “cannot possibly have adapted to the environment to which we now find ourselves” (p. 15). Finally,
Massey proposed that the future success of the human race, hinges heavily on “how we think and how we function socially” (p. 15). In light of Massey’s thoughts, social and emotional intelligence are important constructs in the future of human existence.
As previously stated in Chapter one, there is little doubt that the popularity of EI has encouraged amplified discussion and consideration among practitioners (Goleman, 1995;
Salovey & Sluyter, 1997; Bar-On & Parker, 2000). Additionally, the benefits of emotional 20
intelligence, in terms of leadership effectiveness, have also been a focus of research and practice
(Goleman, 1998; Goleman, Boyatzis, & McKee, 2002; Caruso & Salovey, 2004). Perhaps most important to this study was the increased understanding that leadership development at
institutions of higher education play a major role in the quality of leadership produced in modern
society. Astin and Astin (2000) explained that:
Colleges and universities not only educate each new generation of leaders in government,
business, science, law, medicine, the clergy, and other advanced professions, but are also
responsible for setting the curriculum standards and training the personnel who will
educate the entire citizenry at the precollegiate level. (p. 1)
This chapter presents a review of related literature, which provides an underlying
framework for understanding four concepts that were central to this study: (a) leadership theory,
(b) emotional intelligence theory, (c) emotional intelligence and leadership theories, and (d) student leadership development theories in higher education.
Leadership Theory
Contrasting the comparatively recent emergence of emotional intelligence, researchers have been studying leadership and leadership development since the days of Aristotle and Plato
(Leonard, 2003). Yet, even with numerous years of research and countless books on leadership, a clearly defined and universally accepted definition of leadership and leadership theory continues to elude researchers and practitioners (Komives, Lucas, & McMahon, 1998; Rost, 1991; Burns,
1978; Bass, 1990; Gardner, 1990). Those loyal to the advancement of leadership studies have explained that there are as many definitions of leadership as there are theorists (Gardner, 1990;
Rost, 1991; Chemers, 1993; Hersey, Blanchard, & Johnson, 1996). Furthermore, Zaccaro and
Horn (2003) explained that part of the lack of a centralized thought in leadership theory comes 21
from the common disconnect between researchers and practitioners. To narrow the gap between theory and practice, Zaccaro and Horn called for “an on-going dialogue between researchers and practitioners that respects the values, perspectives, and agendas of each constituency” (p. 799).
In other words, this proposed dialogue would set egos, perceptions, and ideas of one group aside long enough to listen, reflect, and potentially integrate the egos, perceptions and ideas of the other. The outcome Zaccaro and Horn predicted would identify “more [leadership] problems that are informed by concepts, and more [leadership] theories that are molded by contextual realities”
(p. 799). The possibility of uniting researchers and practitioners toward a common vision for leadership studies in the future is a fascinating and worthwhile endeavor, and is one that requires considerable design and action steps to accomplish. Perhaps equally as challenging is the call for integration of leadership theories.
As mentioned earlier, the study of leadership has been plagued with an overabundance of theories with little common direction (Chemers, 1993; Northhouse, 1997; Day, 2001). Chemers
(1993) called for integration among leadership theories and approaches to provide a unified and
clear direction for leadership research. However, this integration of leadership studies has managed to elude researchers. Chemers (2000) conducted a historical overview and analysis of
leadership theories and concluded that common findings in leadership studies have led to the
following three tasks that leaders must achieve to be effective: (a) establish the legitimacy of
their authority, (b) coach, guide, and support their constituents in ways that allow for both group
and individual goal attainment, and (c) identify and employ the strengths and abilities found in
themselves, as well as their constituents, to accomplish the organizational mission (p. 40). There
is little doubt that researchers in the area of leadership studies would question Chemers’
conclusions and state that they are missing other important aspects of leadership effectiveness; 22
however, his findings are a step in the right direction. In summary, leadership and effective
leadership are still obscure, ambiguous, and controversial constructs in the literature. Many
researchers have focused on a leader’s ability to effectively navigate and successfully lead in the
chaotic and turbulent world of modern society (Goleman, Boyatzis, & McKee, 2002; Mumford,
Zaccaro, Harding, Jacobs, & Fleishman, 2000; Massey, 2002).
Leadership and Change
A central theme discussed over and over in this present research study is “change” and its impact on society and organizational and leadership success, as well as a number of other social constructs. Change leadership is a research area that developed out of the necessity for determining leadership competencies that manage and promote change throughout an
organization (Kotter, 1995; Higgs, 2002). To stay current with environmental conditions,
researchers have focused on leaders’ abilities to stay flexible and adaptable in ways that meet
both the personal and professional needs of their constituents, as well as help them balance their
lives on and off the job (Komives, Lucas, & McMahon, 1998; Kouzes & Posner, 2003; Goleman,
Boyatzis, & McKee, 2002). Komives, Lucas, and McMahon (1998) explained that the rapid,
confusing and unpredictable nature of change in our world requires a leadership paradigm shift
from a more egocentric style to an inclusive style. They describe this as a relational leadership
style that nurtures a Problem solving atmosphere within the organization and a willingness to
adapt and evolve with changing social and organizational situations. Additionally, they added
that the rapidly changing world has evolved from an industrial perspective of leadership to a
post-industrial perspective of leadership. The industrial perspective of the leadership
environment was characterized as more controlled, stable, balanced, and permanent. In contrast,
the post-industrial perspective was characterized as chaotic, with increased change and risk, a 23 higher level of disequilibrium or confusion, and temporary (p. 48). Cherniss (2000) explained,
“as the pace of change increases and the world of work makes ever greater demands on a person’s cognitive, emotional, and physical resources, this particular set of abilities will become increasingly important” (p. 10). In Kouzes and Posner’s third edition of The Leadership
Challenge (2002), they assert that in light of rapid change, the “leadership content” has not changed, but the “leadership context” has changed dramatically in recent years. They further explain that post-September 11, 2001, leaders have been called upon to lead in chaotic and uncertain times, which increases the need to develop leaders who:
1. are exemplary coaches and team players that are more collaborative and value people
first over profit (p. XIX)
2. can harness the value of a connected planet while appreciating the importance of face-to-
face interaction
3. can generate and encourage a human network or “social capital – the collective value of
people who know each other and what they’ll do for each other” (p. XX)
4. have a global understanding and show respect for people from many different cultural
backgrounds
5. can balance our “hurry up culture” with slowing down long enough to cultivate and
build-in “quality time” for indispensable human relationships (p. XXI)
6. are willing to create commitment by delivering “on the promise of offering exciting and
meaningful work and treating even the most temporary of workers with dignity and
respect” (p. XXII) and 24
7. can create an environment that “provides a climate for people to bring their souls to work,
not just their heads and hands,” and one that offers more hope in an increasingly cynical
world (XXIII).
In review of Kouzes and Posner’s description of what it takes to be a leader in society today, it is
easy to see that the modern definition of leadership is more than influencing others toward accomplishing organizational goals; it is about actively participating and developing healthy
relationships that create a balance between personal and organizational success. These
established relationships will help the organization, the leader, and the constituents make it
through even the most challenging and chaotic of times. Leaders who are most successful at
building relationships are referred to as “Relational Leaders and the next few paragraphs will
illustrate the relational leadership construct and fully describe a prominent relational leadership
model created by Kouzes and Posner (1998).
Relational Leadership
Effective leadership is about creating reciprocal relationships between the leader and
followers, subordinates, or constituents that in turn creates the foundation for organizational and
group success (Bass, 1985; Chemers, 1993; Komives, Lucas, & McMahon, 1998; Kouzes &
Posner, 2003; Potter, Rosenbach & Pittman, 2001). Yukl (1998) described a relationship between
leaders and constituents that promoted a shared view of leadership and empowered members
within a team or organization, regardless of hierarchical status, to demonstrate leadership
behaviors when pragmatic situations dictate the need (p. 3). Komives, Lucas, and McMahon
(1998) encouraged college students to define leadership as a holistic and socially beneficial
construct that they defined as “a relational process of people together attempting to accomplish
change or make a difference to benefit the common good” (p. 21). The Kouzes and Posner’s Five 25
Practices of Exemplary Leadership Model has been noted for its contributions to the Relational
Leadership paradigm (Komives, Lucas, & McMahon, 1998; Endress, 2000; Berg, 2003).
Sashkin and Rosenbach (2001) explained that there has been a paradigm shift in leadership theory and practice in recent decades. They purported that many of the contemporary models of leadership, including Kouzes and Posner’s, are rooted in Burns’ (1978) comparison between transformational and transactional views of leadership. The concept of transformational leadership was founded on the increased importance placed on followers within the leadership paradigm. Burns (1978) explained that leaders employ both traditional “transactional” practices such as, creating goals, delegating tasks, and managing goal attainment, as well as
“transformational” practices that empower, educate, encourage, and eventually transform constituents (p. 39). Burns’ view of transactional and transformational leadership placed the two concepts on a continuum, whereby a leader’s style fit some point along the continuum between transactional and transformational. Bass (1985) later identified the two leadership approaches as two separate leadership dimensions and he created the Multi-factor Leadership Questionnaire
(MLQ) The MLQ measured both transactional leadership, as well as transformational leadership.
The transactional aspect of the MLQ measured three subcategories: laissez-faire, contingent reward and management by exception. The transformational leadership aspects measured by the
MLQ included charisma, inspiration, individualized consideration, and intellectual stimulation.
Sashkin and Rosenbach (2001) explained that even though Bass’s theory of transformational leadership helped to expand Burns’ works, it lacked both the study of “personal” leadership characteristics and the impact of culture within an organization. Kouzes and Posner (1987) followed the works of Burns (1978) and Bass (1985) and created a model of transformational 26 leadership that considered personal leadership behaviors used during times of leadership effectiveness and organizational success.
Five Practices of Exemplary Leaders
Kouzes and Posner (1987) expanded Bass’s theory by conducting research in the area of
“personal best” leadership experiences. They developed a “Personal-Best Leadership
Experience” questionnaire, asked thousands of managers to complete the questionnaire, and conducted many follow-up interviews to gather additional information. The personal-best questionnaire asked managers to pick a project, program, or event that they characterized as their
“personal-best” leadership experience. After analyzing the data collected from questionnaires and interviews, Kouzes and Posner found that despite the variety in situations and types of leadership experiences, similar patterns were identified related to actions taken by the leaders during the experience. Through the analysis process they identified “Five Practices of Exemplary
Leadership” that contributed to “getting extraordinary things done in organizations”: (a)
Modeling the Way, (b) Inspiring a Shared Vision, (c) Challenging the Process, (d) Enabling
Others to Act, and (e) Encouraging the Heart (Kouzes & Posner, 2002, p. 13). In their third edition of The Leadership Challenge (2002) Kouzes and Posner outlined two “commitments” of leadership for each of the five leadership practices.
The first practice is “Modeling the Way,” in which leaders role model the behaviors they want the see in their constituents. Through action and involvement, leaders earn the right to lead and the respect of their followers. Kouzes and Posner (2002) explained that there are two courses of action, or commitments, that a leader needs to consider when improving the practice of
Modeling the Way. First, leaders need to reflect on and clarify personal values, which will in turn build confidence in and guide personal decisions and thoughts. The second commitment is 27 setting the example, and it involves generating shared values within the organization and basing organization decisions and practices around those established values. In many ways, Modeling the Way is about fostering common practices within the organization and then encouraging, motivating, and role-modeling those practices throughout the organization (pp. 43-105).
The second leadership practice is “Inspiring a Shared Vision.” This is when the leader imagines what the organization could be and then creates a vision that is attainable and attractive.
The leader connects this new vision to the hopes and dreams of his or her constituents to generate passion and enthusiasm for realizing the vision. To do this, a leader must first commit to the charge of exploring exciting and courageous new opportunities assertively. Second, the leader must be committed to breathing life into the vision by encouraging shared aspiration. This commitment is accomplished by relationship building, and it is about aligning a shared vision that promotes both organizational and constituent success (pp. 109-170).
The third leadership practice is “Challenging the Process.” Exemplary leaders are pioneers who know that innovation and change involves “experimentation, risk, and failure” (p.
17). A leader understands that change can feel uncomfortable and then builds constituent confidence by pursuing change incrementally and by accomplishing small victories. In this practice, leaders are proactive, not reactive, and they are committed to seeking out innovation that will change and help the organization grow and improve. The second commitment in this area has to do with the leader’s ability to take calculated risks and to experiment with ideas and organizational practices to improve and grow (pp. 173-237).
The fourth leadership practice involves “Enabling Others to Act.” Successful leaders understand that leadership is a team effort and are not afraid to share the leadership process.
Leaders foster collaboration and build trust by supporting and encouraging their constituents to 28
do good work. Leader’s who are able to build trusting and collaborative relationships find that
their constituents are higher performers and even exceed their own personal expectations (p. 19).
The first commitment in this category is a leader’s commitment to creating and encouraging
cooperative goals and building trust within the organization. A leader can accomplish this by
generating positive and healthy relationships in the work environment. The second commitment
is relative to the leader’s willingness to empower and support opportunities for constituents to
share leadership and make discretionary decisions. In Enabling Others to Act, leaders
demonstrate their trust and commitment to the growth and development of their constituents (pp.
241-311).
Finally, exemplary leaders “Encourage the Hearts” of their constituents to help them
carry on in the face of challenge, frustration, and discouragement. Leaders know that
“celebrations and rituals, when done with authenticity and from the heart, build a strong sense of collective identity and community spirit that can carry a group through extraordinarily tough
times” (p. 21). Encouraging leaders have high expectations of themselves, as well as their
constituents and they are committed to rewarding and providing the support to help constituents
meet expectation. Leaders provide clear direction, encouragement, and feedback and stay
actively aware of the motivational climate within the organization. Additionally, encouraging
leaders create a spirit of community by scheduling and planning opportunities for celebrating
organizational values and accomplishments. These leaders generate communal relationships by
staying positive, being compassionate and caring, and generating an atmosphere of fun and
excitement about the future direction of the organization (pp. 315-380). Research studies and
findings associated with Kouzes and Posner’s model of transformational leadership will be
reviewed in the Student Leadership Development section. 29
Underlying Kouzes and Posner’s Model of Exemplary Leadership Practices is the
leader’s ability to generate, encourage, and promote healthy, reciprocal, and collaborative
relationships. This interpersonal or relational aspect of leadership has recently been connected to
the emotional intelligence constructs that have gained popularity in recent decades (Mayer &
Salovey, 1997; Bar-On, 2002; Goleman, 1995). Higgs (2002) explained that leadership has
evolved from a personality or trait based leadership paradigm, through a behavioral and
contextual (or situational) period and more recently the transformational/transactional models.
He also purported that “the transformational model [of leadership] has come close to identifying the boundaries of leadership thinking in today’s organizations” (p. 203). Dulewicz and Higgs
(2003) also demonstrated that Kouzes and Posner’s model, which typifies
transformational/transactional models, focuses more thinking on the emotional aspects of
leadership. Additionally, Dulewicz and Higgs explained that a leader’s ability to establish and
maintain interpersonal relationships that embrace and enhance the personal feelings and well
being of constituents requires emotional intelligence. Before reviewing literature that has studied
and compared the connection between relational leadership models and emotional intelligence, it
is important to review general aspects of emotional intelligence.
Emotional Intelligence
Concepts of emotional intelligence have gained popularity in recent decades; however,
the characteristics and concepts associated with EI are rooted in research conducted throughout
the twentieth century. Earlier works identified competencies, other than general intelligence, that
contributed to life success. Thorndike (1937) reported the concept of “social intelligence.”
Wechsler (1940) fought for the addition of “non-intellective aspects” as a measure of general
intelligence. Likewise, Leeper (1948) purported that “emotional thought” should be considered 30
when reviewing the concept of “logical thought.” However, it was not until the 1980s that the
current concepts related to emotional intelligence started to emerge.
Gardner (1983) shared a theory of multiple intelligences that encouraged researchers to
step outside the notion that human beings are confined to a singular or plural view of
intelligence. Gardner also explained that there were other areas of human intelligence that were
traditionally ignored or overlooked by academic institutions, as well as society. Gardner (1983)
explained that there are two types of intelligence that have held the focus and emphasis of
traditional academic thought in institutions of higher education: language intelligence and
logical-mathematical intelligence. Nevertheless, Gardner purported that there were five more
intelligences that were equally important to collective human intelligence: musical intelligence, spatial intelligence, bodily-kinesthetic intelligence, interpersonal intelligence, and intrapersonal intelligence (p. 8). Within these multiple levels of human development or intelligences, a movement evolved that expanded two particular areas of Gardner’s approach (i.e., interpersonal and intrapersonal intelligences). According to Bar-On (2002), several researchers expanded
Gardner’s interpersonal and intrapersonal intelligences into six primary components of emotional intelligence: emotional self-awareness, assertiveness, empathy, interpersonal relationship, stress tolerance, and impulse control (p. 2). Several definitions of EI emerged through the advanced study of these six components. Recently, Bar-On (2005) explained that the multiplicity of definitions that came out of Gardner’s approach has plagued this line of research with confusion, controversy, and angst surrounding the best approach, definition, and measure of emotional and social intelligence. Since that point of advancement and divergence, from Gardner’s view of the construct, some researchers, (Goleman, 1998; Mayer & Salovey, 1997), for example named this construct "Emotional Intelligence" while Bar-On, 1997 chose to name it Emotional and Social 31
Intelligence, and recently Bar-On (2005) abbreviated the concept to Emotional-Social
Intelligence (ESI). Likewise for the purpose of this study and for the sake of the simplification,
the researcher encourages the reader to interpret, emotional intelligence, emotional and social
intelligence, and emotional-social intelligence as the same concept. The reader should also note
that the purpose of this study was not to dispute or support one definition or theory over another.
Definitions and Measures of Emotional Intelligence
Given the expansion and multiple perspectives of EI, researchers have attempted to
develop measures to assess the new constructs (Bar-On, 2002; Mayer, Salovey & Caruso, 1999;
Boyatzis, Goleman, & Rhee, 2000). The following few sections review three competing models and measures of emotional intelligences that are often cited in the literature (Mayer & Salovey,
1997; Bar-On, 2002; Goleman, 1995). Each construct of EI can be “distinguished according to the way they define emotional intelligence and the measurement approach they employ” (Mayer,
Caruso, & Salovey, 2000a, p. 338). Mayer, et al. explained that “there are two general models of emotional intelligence: a mental ability model and a mixed model that includes various personality dispositions” (p. 416). Two of the three models of emotional intelligence described in this section (Bar-On, 2002; Goleman 1995), are categorized by Mayer, Salovey, and Caruso
(2000b) as mixed models or trait models, while the other (Mayer & Salovey, 1997) is considered
a mental ability model. The next few paragraphs will further describe each model and a general
review of their associated measures.
In the 1990s, Mayer and Salovey developed a four-branch ability model of emotional
intelligence that divided EI abilities into four areas: (a) the capacity to accurately perceive
emotions, (b) the capacity to use emotions to facilitate thinking, (c) the capacity to understand
emotional meanings and (d) the capacity to manage emotions (Mayer & Salovey, 1997). Mayer, 32 et al. (2000a) explained that from these four branches of emotional intelligence, the Mayer,
Salovey, and Caruso Emotional Intelligence Test (MSCEIT) ability measure of EI was developed. The MSCEIT “yields an overall emotional intelligence score, as well as subscale scores for perception, facilitation, understanding, and management” of emotions (p. 329). In this ability model of emotional intelligence, the test is designed to assess respondents’ capacity (a) to identify emotion “in faces, in landscapes, and in abstract;” (b) to use emotions to facilitate thought; (c) to comprehend emotional meanings and vocabulary; and (d) to demonstrate a capacity to regulate emotions in oneself and others (Sagan, 2002, pp. 181-182). Mayer, et al.
(2000b) explained that “mental ability measures of emotional intelligence can be described as a standard intelligence and empirically meets the criteria for a standard intelligence” (p. 416).
The next two measures of “emotional intelligence” are two examples of somewhat controversial “trait approaches” to measuring emotional competencies. Mayer, Salovey, and
Caruso (2000) explained that trait-based measures of EI should not be used to describe measures of intelligence. Rather they are measures of personality traits or competencies that are related to emotional intelligence. Additionally, Matthews, Roberts, and Zeidner (2002) explained that self- report measures of EI generally sample a diversity of constructs and therefore assume a mixed model of EI that combine of both ability and personality traits. Nevertheless, researchers applying trait-based measures of emotional intelligence are numerous and have yielded some interesting results (Bar-On, 2002; Goleman, 1998; Schutte, Malouff, Simunek, McKenley, &
Hollander, 2002).
Dr. Reuven Bar-On followed the works of Thorndike (1920) in the area of “social intelligence,” Wechsler’s (1958) concept of “general intelligence,” and Gardner’s (1983)
“multiple intelligences” and he defined EI as “an array of noncognitive capabilities, 33
competencies, and skills that influence one’s ability to succeed in coping with environmental
demands and pressures” (Bar-On, 2002, p. 14). Bar-On (1997) described his theory of emotional
intelligence as “Emotional and Social Intelligence” and more recently (2005) abbreviated the
name of the construct to Emotional-Social Intelligence (ESI). In the 1980s, Bar-On originally
developed an instrument designed to measure major components of emotional and social performance that led to psychological health, and he eventually published the Emotional
Quotient Inventory (EQ-i) in 1997 (Bar-On, 2000, p. 364). The EQ-i renders a total emotional quotient (EQ) score, and the following five composite subscale scores and fifteen component scores:
(1) Intrapersonal EQ (Self-Regard, Emotional Self-Awareness, Assertiveness,
Independence, and Self-Actualization), (2) Interpersonal EQ (Empathy, Social
Responsibility, and Interpersonal Relationship), (3) Stress Management EQ (Stress
Tolerance and Impulse Control), (4) Adaptability EQ (Reality Testing, Flexibility, and
Problem Solving), and (5) General Mood EQ (Optimism and Happiness).
Mayer, Salovey, and Caruso (2000b) call Bar-On’s model a mixed model, and other researchers describe the model as “trait emotional intelligence.”
Goleman (1998) defined emotional competence as a “learned capability based on emotional intelligence that result in outstanding performance at work” (p. 24). Through research and analysis, Goleman developed a model of EI that included twenty-five competencies that were divided into five clusters: (1) the self-awareness cluster that included emotional awareness, accurate self-assessment, and self-confidence; (2) the self-regulation cluster that included self- control, trustworthiness, conscientiousness, adaptability, and innovation; (3) that motivation cluster that included achievement drive, commitment, initiative, and optimism; (4) the social 34
competence cluster that included understanding others, developing others, service orientation,
leveraging diversity, and political awareness; and (5) the social skills cluster that included influence, communication, conflict management, leadership, change catalyst, building bonds, collaboration and cooperation, and team capabilities (Goleman, 1998, pp. 26-27). Using
Goleman’s definition and framework as a guide, Boyatzis, Goleman, and Rhee (2000) developed the Emotional Competence Inventory (ECI) to measure the corresponding skills mentioned above. The ECI was designed to collect data from both the target individual, through a self- assessment, and from people in that target individual’s social or work environment (Salovey,
Mayer, Caruso, & Lopes, 2003). This method is referred to as 360-degree assessment in which comparisons are made between the individual assessment and the assessment of others (Boyatzis
& Goleman, 2001).
The assessment of emotional intelligence is continuing to expand in both definition and research. Currently, there are more self-assessment, trait emotional intelligence instruments than there are ability measures of EI and there exists considerable controversy regarding which measure is most reliable and valid (Antonakis, 2003; Judge, Colbert, & Ilies, 2004; and Salovey,
Mayer, Caruso, & Lopes, 2003). Regardless of some researchers’ views of trait-based emotional intelligence, several studies have yielded interesting results through the application of the more personality-based emotional competency models.
Trait Measures Research
Schutte, Malouff, Simunek, McKenley, and Hollander (2002) investigated the relationship between emotional intelligence and emotional well-being using a trait-based self- assessment scale. This particular study defined EI as the ability to understand and regulate emotions and emotional well-being as maintaining a positive mood and high self-esteem. Results 35
indicated that emotional intelligences were associated with a characteristically positive mood and higher self-esteem. Additionally, they found that individuals with higher EI were better able to
“maintain positive mood and self-esteem when faced with a negative state induction and maximize the positive mood impact of a positive state inductions” (p. 780).
Schutte, Malouff, Bobik, Coston, Greeson, Jedlicka, Rhodes, and Wendorf (2001) conducted a study that explored the association between self-reported trait emotional intelligence and various interpersonal relations. The results indicated that higher EI scores correlated with higher scores in (a) self-monitoring, (b) social skills, (c) cooperative behavior, (d) closer relationships, and (e) marital satisfaction. Additionally, they found that “participants anticipated greater satisfaction in relationships with partners high in emotional intelligence” (p. 535).
Schutte, et al. explained that these findings suggest that EI is perceived as a desirable quality and may lead to interpersonal attraction.
The next section of this literature review focuses on the connection between emotional intelligence and leadership practices. Much research has been completed in recent years highlighting the connection between the two constructs.
Leadership and Emotional Intelligence
This portion of the literature review examines the idea that effective leadership is paramount in meeting the challenges and changes facing modern times. To embrace the rapid change that exists in society today, studies in the area of leadership effectiveness demonstrate the importance of collaborative, caring, empathetic, people-centered, and motivational leadership skills (Higgs, 2002; Goleman, Boyatzis, & McKee, 2001). Transformational leadership models, i.e., relational leadership, are considered effective models for change environments, primarily because of the leader’s ability to create and manage strong relationships that hold the 36
organization together in times of uncertainty (Komives, Lucas, & McMahon, 1998; Yukl, 1999;
Higgs, 2002; Dionne, Yammarino, Atwater, & Spangler, 2004). When discussing change and the benefits of transformational leadership, Goleman (1998) explained that transformational
leadership “goes beyond management as usual; such leaders are able to rouse people through
sheer power of their own enthusiasm” (p. 196). Goleman went on to explain that effective
leaders do not bark out orders or direct their constituents; they inspire. Similarly, emotional
intelligence has been widely defined as one’s ability to identify and manage one’s own emotions,
as well as to understand and empathize with the emotions of others (Cherniss, 2000; Bar-On,
2002; Caruso & Salovey, 2004).
Researchers agree that there is considerable overlap between relational leadership and EI
competencies in both content analysis and empirical evidence (Higgs, 2002; Dulewicz & Higgs,
2003). Goleman (1998) made connections between emotional intelligence and leadership
practices in which he boldly claimed that highly emotionally intelligent leaders and work teams
contribute significantly to the overall success and “bottom line” of the organization (p. 315).
Goleman, Boyatzis, and McKee (2002) explained that great leaders inspire their constituents best
through emotions, and that regardless of task, goal, or assignment, it is the leader’s primal duty
to drive the emotional climate of the team or organization in a positive and productive direction.
Likewise, Goleman, et al. purported that if a leader fails to create a positive emotional climate
within their organization, “nothing they do will work as well as it could or should” (p. 3).
Positive emotional leadership is a necessity in times of chaos and change because constituents
closely examine and then emulate or “mirror” their leaders’ behaviors and actions (Goleman,
Boyatzis, & McKee, 2002). In other words, constituents, either consciously or unconsciously,
react to a leader’s verbal and non-verbal responses to a specific crisis or challenge (Caruso & 37
Salovey, 2004). Likewise, when a leader effectively manages his or her own reactions and maintains a positive emotional state, organizational members are more likely to follow the leader’s emotional response (Goleman, Boyatzis, & McKee). Researchers have drawn parallels between EI and leadership and have identified specific challenges wherein emotional understanding and control can provide assistance and guidance.
Emotional Intelligence and Leadership Challenges
Emotional intelligence skills provide developing leaders with an increased understanding of the impacts of emotions within a team or organization. Caruso and Salovey (2004) demonstrated the advantages EI has with respect to six common challenges in leadership: (a) building effective teams, (b) planning and deciding effectively, (c) motivating people, (d) communicating a vision, (e) promoting change, and (f) creating effective interpersonal relationships (p. 196). Throughout Caruso and Salovey’s descriptions of the six challenges, they cited a connection with Kouzes and Posner’s Effective Leadership Practices Model.
The first challenge was building an effective team. Caruso and Salovey discussed the need for clarifying personal values before attempting to formulate team values. Like Kouzes and
Posner’s model, Caruso and Salovey explained that leaders must identify their own values before clarifying team values. A significant level of trust is important for leading teams, and a leader must generate positive opportunities for meaningful team communication and interaction.
Additionally, a leader must have significant self-confidence to give team members credit for accomplishments and not blame them when shortfalls occur (p. 197).
Caruso and Salovey went on to explain that even though planning and decision-making can seem cognitive and practical, emotions contribute significantly to these activities.
Emotionally intelligent leaders possess the ability to remain flexible and open to other 38
alternatives. Additionally, EI leaders take into account how their team members may react to a
decision, and then attempt to make decisions that will fit in with the shared values of the team. In
the end, this type of flexible decision-making will contribute to the successful implementation of
the decision (p. 201).
Every leader at one point or another is faced with the question of how to motivate a team.
Caruso and Salovey cited Kouzes and Posner’s (2002) “encouraging the heart” model as a significant contribution to motivating a team. When a leader expresses appreciation for the accomplishments of team members, they are in many ways providing that added incentive for future successes. Caruso and Salovey also explained that it is important for a leader to celebrate team member successes without promoting or encouraging envy throughout the team (p. 202).
Furthermore, communication is among the most difficult challenges to leadership. EI leaders base their communication efforts “on delivering a message [they] want to deliver and delivering it in such a way that is heard and understood by others” (p. 205). Communication also entails a leader’s vision for the future. Caruso and Salovey emphasized that because an EI leader has the ability to understand and empathize with group feelings, he or she will be successful in encouraging team members to buy into their vision of the future.
In light of rapid worldly changes, a leader’s ability to facilitate and encourage change has been a hot topic recently (e.g., Kotter, 1995; Higgs & Rowland, 2001). Caruso and Salovey
(2004) explained that EI leaders challenge the status quo through innovation, experimentation, and risk-taking. They further explained that most people are resistant to change; however, EI leaders identify, empathize with, and acknowledge resistance and then communicate the need for change and clarify a road map toward successful implementation (p. 208). 39
Building effective interpersonal relationships is the foundation of the emotionally intelligent leader. Caruso and Salovey (2004) explained that effective interpersonal relationships include both “positive feedback and sincere criticism” (p. 209). EI leaders are able to generate relationships that are healthy and mature enough for members to express honest and tactful reactions with other members. Caruso and Salovey explained that “emotions contain data and
[those] data are primarily communicating information about people and relationships. Being accurately aware of emotions and their meaning provides the emotional intelligent manager with a solid base of understanding of themselves and of others” (p. 210). Along with understanding and interpreting emotions, it is equally important for leaders to understand the impact of emotions on individual and organizational performance.
Goleman, Boyatzis, and McKee (2002) shared two leadership styles that relate both positively and negatively to emotional intelligence and contribute significantly to productivity and work satisfaction: dissonance and resonance. Goleman, et al. explained that a dissonant leadership style demonstrated characteristics that are not emotionally effective or supportive within an organization. A dissonant leader is one who offends constituents and creates an unhealthy and unproductive emotional environment within the organization. They described dissonant leaders as leaders who are so out of touch with the feelings of their constituents that they create a negative environment, which in turn moves the organization’s attitude toward that leader on a “downward spiral from frustration to resentment, rancor to rage” (p. 19) Dissonant leaders were also described as authoritarian, untrustworthy, uncooperative with constituents, unharmonious with the group, abusive, and humiliating.
Resonant leaders, on the other hand, project an emotional atmosphere that is comfortable, cooperative, supportive, and enthusiastic. They inspire shared values and “rally people around a 40
worthy goal” (p. 25). Goleman, et al. described four leadership styles that build resonance within the organization: (a) visionary – “moves people towards a shared dream,” (b) coaching – connects personal desires with organizational goals, (c) affiliative – “creates harmony by connecting people to each other,” and (d) democratic – values input and builds commitment through participation (p. 55).
As mentioned earlier within the area of modeling, the concept of mirroring in
relationship to resonance and dissonance within the organization is very important when a leader
reacts to both positive and negative situations. When a leader reacts to a negative situation in a
concerned but positive fashion, his or her behavior becomes a model which the rest of the
organization can follow. Goleman, et al. explained that leaders within organizations are observed
for acceptance or rejection to thoughts, projects, or ideas. If a leader shows any nonverbal or
verbal gestures, constituents quickly notice and react to those gestures. Emotionally intelligent
leaders realize and understand how their emotional reaction can guide and steer the emotions of
the entire organization. This concept of resonant and dissonant leadership styles is one example
of the power of the emotional climate within an organization. Emotional intelligence has been
linked to a number of additional factors associated with effective leadership (Goleman, 1998;
Kouzes & Posner, 2002; Dulewicz & Higgs, 2003).
Emotional Intelligence and Leadership Research
Goleman (1998) conducted a study that assessed emotional intelligence levels of leaders
throughout the organization, and he found that “emotional intelligence played an increasingly
important role at the highest levels of the company, where technical skills are of negligible
importance” (p. 94). In other words, the highest ranking leaders within an organization often had
higher levels of emotional intelligence. More importantly, the research found that successful 41
organizations had CEOs and organizational leaders that possessed strong emotional intelligence.
Dulewicz and Higgs (2003) conducted a similar study that observed leadership rank within the
organization and found support for Goleman’s (1998) assertion that the higher one’s leadership
rank, the higher the emotional intelligence scores. In addition to EI and leadership rank,
researchers identified that self-awareness is the building block for both emotional intelligence
and leadership development (Goleman, 1998; Kouzes & Posner, 2002; Caruso & Salovey, 2004).
Sosik and Megerian (1999) found that increased levels of self-awareness determined the
predictability of leadership behavior and emotional intelligence. Leaders who were categorized
by their subordinates as self-aware demonstrated transformational and emotional quotient
behaviors that related positively with the following scales: (a) purpose-in-life (PIL) scores, (b)
personal efficacy, (c) interpersonal control, and (d) social self-confidence (p. 384). Additionally,
their findings contribute to the understanding that self-awareness is the foundation upon which
both transformational leadership and EI are developed.
Other researchers have explored the relationships between organizational change, emotional intelligence, and effective leadership (Kotter, 1995, Mumford, et al., 2000; Dulewicz
& Higgs, 2003; Higgs & Rowland, 2001; Higgs, 2002). Furthermore, Higgs (2002) found that the EI factors of interpersonal sensitivity and self-awareness were significantly related to five change leadership competencies: (a) creating the case, (b) structuring change, (c) engagement,
(d) implementation, and (e) facilitation. Vakola, Tsaouss, and Nikolaou (2003) found that attitude for organizational change could be predicted by an employee’s use of emotions for
Problem Solving. Respondents who were strong in the Problem Solving dimension were described as “optimistic, energetic, hopeful people who trust their abilities and prepare well- organized plans using and assessing their own emotions appropriately” (p. 104). 42
Ruderman, et al. (2001) conducted a study that measured the emotional intelligence (Bar-
On EQ-i) and leadership skills (Benchmark 360) of 302 managers who participated in a
Leadership Development Program sponsored by the Center for Creative Leadership. They found that higher levels of EI were associated with increased performance in each area of the
Benchmarks 360 leadership feedback instrument: (a) participative management, (b) putting people at ease, (c) self-awareness, (d) balance, (e) straightforwardness and composure, (f) building and mending relationships, (g) doing whatever it takes, and (h) resourcefulness.
Additionally, four themes stood out from their study. First, a participative management style was central to the connection between EI and leadership in that managers who have high levels of EI found it easier to demonstrate cooperation, interpersonal sensitivity, and awareness and control of personal emotions (p. 11). The second theme identified in the study had to do with self- awareness and the ability to balance one’s personal and professional life. Additionally, with this theme, a leader’s ability to demonstrate stress management, tolerance, and impulse control was equally apparent. The third theme highlighted the importance of assertiveness and meeting on- the-job challenges. In this area, independence, self-directedness, self-reliance, and perseverance were key factors. Finally, the fourth theme of this study observed how the lack of EI can influence the work environment and explained that the lack of EI involves problems with the interpersonal relationships. Ruderman, et al. explained that “organizations today are putting more value on interpersonal relationships” (p. 12).
With the identified benefits of emotional intelligence related to creating and developing positive relationships, combined with the understanding that positive relationships are the core of effective leadership, the idea of emotional intelligence and effective leadership is one that has been well established in the literature. Researchers have started to develop and assess 43
developmental programs for emotional intelligence that coincide with leadership development
programs and initiatives (Cherniss & Adler, 2000; Cherniss & Goleman, 2001). The question most pertinent to this study involved research and practice in the area of student leadership development and the process by which students currently learn about emotions and the power of emotion on leadership success.
Student Leadership Development
The common thread connecting each section of this literature review has been the idea that the leadership situation of modern society is in a state of continuous adaptation and change and requires a cooperative, supportive, empathetic, transformational relationship between leaders and followers (Kouzes & Posner, 2002; Goleman, Boyatzis, & McKee). As Komives, Lucas, and
McMahon (1998) explained, new maps for leadership are needed, maps “describing the leadership that is needed in era of rapid change” (p. 48). Furthermore, they explained that scholars in the field of leadership studies need to apply a contemporary analysis of current leadership paradigms and theories to identify new approaches to lead in our “quantum” or rapidly changing world.
The connection between emotional intelligence and relational leadership has been identified as a necessary combination for the future of organizational success (Higgs, 2002;
Hagenow, 2001; Caruso & Salovey, 2004). Likewise, prospective employers of college graduates have indicated that EI competencies are among the most sought after qualities in a new employee (Jaeger, 2003). In light of much support for the benefits of emotional intelligence, why is it that academic communities have been hesitant to embrace and put EI into practice
(Dulewicz & Higgs, 2003)? Higher education produces thousands and thousands of leaders every year in the United States, yet the W. K. Kellogg Foundation identified a societal need for more 44
and better leadership. The foundation established a grant program to inspire interest in innovative
student leadership development at colleges and universities and funded 31 institutions from
1990-1998 (Astin & Astin, 2000).
Leadership and Society
Astin and Astin (2000) acknowledged the aforementioned complexities that exist in
modern society and viewed leadership as an essential mechanism for positive social changes to cope with the continually evolving world (p. 1). To that end, they explained that there is
mounting evidence that leadership effectiveness in the United States has eroded in recent years.
They cited a long list of societal problems that are related to ineffective leadership: unstable race
relations, growing economic inconsistencies and inequalities, a weakening public school system,
irresponsible mass media, declining civic commitment, and the increasing ineptitude of
government (p. 2). Additionally, they viewed these social problems from the standpoint of a lack
of socially effective leadership rooted in higher education’s current inability to “empower
students, by helping them develop those special talents and attitudes that will enable them to
become effective social change agents” (p. 2). Astin and Astin further explained that most
institutions of higher education place little attention on the educational goals of leadership
development and the majority of faculty members continue to focus on the acquisition of
knowledge in traditional disciplines. As a solution for the poor quality of leadership that
characterizes much of American society, they argued that educational goals should place more
emphasis on those “personal qualities that are most likely to be crucial to effective leadership:
self-understanding, listening skills, empathy, honesty, integrity, and the ability to work
collaboratively” (p. 3). Pertinent to the present study, Astin and Astin asserted that many of these
effective leadership qualities exemplify aspects of emotional intelligence (p. 3). The current 45 understanding of leadership has evolved into an increasingly collaborative and transformational process that involves an identification of a shared vision and commitment between leaders and constituents (Bass, 1985; Komives, Lucas, & McMahon, 1998; Yukl, 1999; Kouzes & Posner,
2003).
Higher Education and Emotional Intelligence
Higher education continues to evolve with the changing needs of society and humanity.
According to Chickering and Stamm (2002), the purpose of higher education is to “prepare students for responsible and satisfying lives in a pluralistic society” (p. 31). One could argue that once a student departs the hallowed halls of academia, it is hard to quantify whether or not they are indeed living responsible and satisfying lives. Furthermore, the assessment structures of most institutions of higher education focus primarily on the more tangible cognitive domain of learning rather than the less tangible affective or emotional domain (Tucker, Sojka, Barone, &
McCarthy, 2000). There is growing research however, that connects the affective or emotional development to increased life satisfaction, performance and productivity, leadership, career success, and health (Goleman et al., 2002; Stein & Book, 2000; Ciarrochi, Forgas, & Mayer,
2001; Caruso & Salovey, 2004). Consequently, when reflecting on the role of higher education in society, one must look at the big picture. It is short sighted to envision higher education solely in terms of knowledge acquisition and cognitive development. As Low, Lomax, Jackson, and
Nelson (2003) explained, much focus is put on cognitive development in education primarily because of the litany of standardized tests that are required, e.g., SAT, ACT, GRE, etc. In fact, emotional development is often mystified, misunderstood, or relegated to other learning environments, such as family, religion, or counseling (p. 3). Low, et al. asserted that it is time for academia to fully embrace the emotional development of our students. They further explained 46
that a “research-based model of emotional intelligence that is easily understood, practical, and
organized around specific skills and competencies may provide a new structure for student
development” (p. 3). Nelson and Low (2003) wrote a book, entitled Emotional Intelligence:
Achieving Academic and Career Excellence, designed to assist students in the exploration and
development of their own emotional intelligence. Nelson and Low explained that higher
education has two primary curricula, a cognitive curriculum and an emotional curriculum. The
cognitive curriculum is based on “academic content areas, grade point averages, semester hours,
and academic honor societies” and is described as structural, rational, and organized (p. 8). On
the other hand, the emotional or covert curriculum is centered on relationship development,
social activities, and recreational and leisure activities. Nelson and Low purported that the
emotional curriculum develops attitudes and behaviors that lead to life-long emotionally
intelligent decision-making and relational behaviors. (p. 8). Nelson and Low organized their
book around the development of four emotional intelligence competencies: (a) interpersonal
skills, (b) leadership skills, (c) self-management skills, and (d) intrapersonal skills. The EI skills
associated with leadership skills include social awareness, empathy, decision-making, and
positive influence.
Higher Education and Student Leadership Development
Leadership development begins early in life, and perhaps it relates to sibling and family
structure, informal leadership experiences with friends, and/or more formal experiences such as
Boy Scouts, Girl Scouts, or high school leadership opportunities. Furthermore, after high school,
collegiate experiences contribute greatly to leadership development and the refinement of
leadership practices (Kouzes & Posner, 2002; Zimmerman-Oster & Burkhart, 2001). College
students have endless opportunities to enhance and explore their leadership abilities (Astin & 47
Astin, 2000). Some of the more popular leadership opportunities include student organizations,
Greek-affiliated fraternities and sororities, campus activities, student employment, resident advisor positions, undergraduate student government, honor societies, professional associations
and many other organizations on campus that encourage and offer students leadership
opportunities (Berg, 2003). These leadership opportunities offer a structured process for student
development and leadership advancement (Posner, 2004).
With the world growing increasingly complex, the need for effective leadership in the
workplace as well as in the community has increased significantly (Astin & Astin, 2000).
Demonstrated societal need for effective leadership has increased the interest and growth of
leadership development programs at the collegiate level across the United States (Posner, 2004).
Zimmerman-Oster and Burkhart (1999) estimated that there were 800 leadership programs
serving students across the country (p. 64). The size, scope, and type of leadership programs are
as varied as the definitions and approaches to leadership generally (Zimmerman-Oster &
Burkhardt, 2001). Part of the reason for the variance can be explained by the many definitions of
leadership that exist in the research and the lack of a unified and agreed-upon definition among
researchers and practitioners (Komives, Lucas, & McMahon, 1998; Rost, 1991; Bass, 1990;
Gardner, 1990). Bell (1994) found that up to 65 % of collegiate leadership programs operate without clearly defining what they mean by “leadership.” Contemporary views of student leadership development programs are quite varied and somewhat ambiguous (Berg, 2003;
Posner, 2004).
Relational Leadership and Student Leadership Development
Leadership research in the 1990s focused considerable attention on transformational and
relational leadership (Higgs, 2002; Rosenbach & Sashkin, 2001; & Komives, Lucas, McMahon, 48
1998). The unpredictability of economic times, changing business environments, and rapid increases in technology stimulated leaders and researchers to question how leaders promote and motivate change within their organizations (Hagenow, 2001; Higgs & Rowland, 2001).
Transformational leadership focused on the leaders’ ability to establish collaborative relationships with their followers that would motivate followers to transcend personal interests and focus more on the interests of the group (Bass, 1990). In earlier works, Bass (1985) proposed that transformational leadership would be more effective during times of turbulence and change.
Several years into the new millennium, change continues to be one of the most challenging aspects of leadership (Higgs, 2002; Hagenow, 2001). Both private and public organizational leaders are feeling pressure to promote innovation, interpret future trends, and promote change to meet environmental demands (Goleman et al., 2002). To motivate followers in these turbulent times, Yukl and Lepsinger (2004) explained that leaders must encourage institutions not to look at change as a catastrophe but to look at change as a “continuous process of adjustments that involve a combination of many, frequent incremental improvements and occasional major challenges” (p. 96). Kouzes and Posner’s Five Practices of Exemplary Leadership model is a prominent example of a leadership development approach that came out of Bass’s (1985) theory of transformational leadership.
Kouzes and Posner are two researchers who have contributed significantly to the growing body of research in leadership studies. Their line of research focused on the “personal-best leadership experiences” of thousands of leaders. By analyzing personal best leadership experiences, they discovered five effective leadership trait categories (Kouzes & Posner, 2002).
The first effective leader category is “modeling the way.” In this category, effective leaders model the behaviors that they want to see in their followers. Second, effective leaders “inspire a 49 shared vision” by “imagining an exciting, highly attractive future for their organization.” Third,
Kouzes and Posner’s research demonstrated that effective leaders “challenge the process…; they search for opportunities to innovate, grow, and improve.” Fourth, leaders “enable others to act” by instilling trust and building collaboration and fostering a sense of real ownership and shared leadership. Finally, effective leaders “encourage the heart;” they reach into the souls of their constituents and encourage them to carry on and draw people toward common goals (Kouzes &
Posner, 2002, pp. 13-19).
From these five effective leadership trait categories, Kouzes and Posner created the
Leadership Practices Inventory (LPI) and later (Posner & Brodsky, 1992) modified the LPI to appropriately study college students and created the Student Leadership Practices Inventory (S-
LPI), found in Appendix E. The S-LPI measures strengths and weakness in each of the five leadership categories. In terms of leadership development, the S-LPI is designed to assist developing student leaders explore their perceived leadership strengths and weaknesses (Kouzes
& Posner, 1998). Upon completion of the inventory, students are able to visually identify, among the five effective leadership trait categories, areas for improvement and refinement. Currently, the S-LPI is one of only two measure that assess college student leadership practices; consequently the S-LPI has gained popularity among college and university leadership programs as a tool for identifying and improving leadership skills (Posner, 2004).
Student Leadership Practices Inventory Research
In 1992, Posner and Brodsky utilized the S-LPI to assess fraternity chapter presidents and found a correlation between chapter presidents and each of the five leadership behaviors. They found “statistically significant (p<.001) correlations between all five student leadership practices and both internal and external effectiveness” (p. 235). 50
In 1993, Posner and Brodsky investigated the relationship between resident advisor and
effectiveness assessment and leadership practices. RA effectiveness was measured by nine
questions associated with RA job performance and social abilities of their assigned residents.
RAs completed the Student LPI-Self form and their Hall Director/Supervisor completed the
Student LPI-Observer form and comparisons were made between the two forms. Posner and
Brodsky found that those RAs who engaged in the five leadership practices most frequently, as compared to those who engaged in the five practices less often, were viewed as more effective by both themselves and their supervisors (p. 302). In 2004, Posner modified the S-LPI and a description of the new version, administered in the present study, is presented in Chapter I.
Student Leadership Development Program Description
Berg (2003) completed a study of leadership development programs in the United States, with the aim of identifying a leadership development framework that could be implemented and emulated at Canadian universities and colleges. He consulted leaders, educators, and students
and asked them to describe their perceptions of ideal leadership and ideal leadership
development. In terms of structure, Berg explained that leadership development programs at
colleges and universities break up into two primary initiatives: co-curricular leadership
programs, and undergraduate leadership programs. Co-curricular programs are described as
“leadership initiatives sought to reach across campuses to provide opportunities for interested
students to develop leadership thinking and ability” (Berg, 2003, p. 71). Overall, co-curricular
initiatives focus on developing student leadership through “seminars, conferences, certification
programs, service learning projects, mentoring, student leadership involvement, and fostering
leadership development among high school students” (p. 75). Undergraduate programs, in
contrast, are offered in academic undergraduate majors and minors in leadership and vary greatly 51 in programmatic design. Some programs offer combined academic and co-curricular designs that offer four-year leadership development program much like the student leadership program participants who took part in this research. The variety in definitions, formats, and length of leadership development programs and initiatives demonstrates both a lack of uniformity in the field and significant diversity between the missions of institutions of higher education.
Ultimately, Berg’s research called for leadership development programs that are holistic and multidisciplinary in their approaches.
Summary
This literature review started with an analysis of current leadership constructs that relate most readily with both the changing realities of modern society and the objectives of this study.
Transformational leadership has been included in the idea of relational leadership. The literature demonstrated that successful leadership in times of organizational uncertainty and radical change requires a leader who is able to successfully build solid relationships within the organization.
The next section reviewed the evolving construct of EI to demonstrate the development and variability between related models and measures of ability-based and trait-based structures. The third section of this literature review demonstrated the relationship between EI and leadership effectiveness. The most significant relationship between EI and leadership effectiveness was the established ability for leaders with highly developed EI to create and enhance positive relationships that promote both organizational and individual success. Lastly, this review assessed the current nature of student leadership development programs at colleges and universities in United States, and demonstrated a societal need for effective leaders and higher education’s role in their development. 52
CHAPTER III. METHODOLOGY
Purpose of the Study
The purpose of this study was to explore the relationship between emotional-social
intelligence and student leadership practices among an identified population of college student
leaders enrolled in a university sponsored, co-curricular four-year leadership development
program at a Midwestern state university. To examine this relationship, student leaders enrolled
in the leadership development program completed two self-report data collection instruments.
The first instrument was Bar-On’s Emotional Quotient Inventory (EQ-i) (2002), which assessed
total emotional quotient score, five subscale scores, and 15 component scores within Bar-On’s
construct of Emotional-Social Intelligence. The second instrument participants completed was
Kouzes and Posner’s (2004) Student Leadership Practice Inventory (S-LPI), which assessed five leadership practices: Challenging the Process, Inspiring a Shared Vision, Enabling Others to
Act, Modeling the Way, and Encouraging the Heart. See Appendix E. Both instruments measured the participants’ perceived frequency of behaviors associated with either Emotional-
Social Intelligence (EQ-i) or student leadership practices (S-LPI) respectively.
Additionally, the director of the four-year leadership development program participated in a modified 360-degree evaluation of the participants’ performance within the leadership development program. The director completed a “Student Leadership Performance Placement” worksheet (Appendix D) which placed approximately 25% of the participants into a Top
Performers category, approximately 25% of the participants into a Bottom Performers category, and the remaining participants were clustered into the Middle Performers category (50%). The researcher describes this methodology as a “modified” 360-degree assessment for two reasons:
(1) the researcher did not systematically collect assessment from peers or the director specifically 53 about the participants’ ESI or leadership practices, and (2) the participants did not complete a self-assessment of their own performance within the program with which to compare to the director’s placement (Chappelow, 1998, p. 31). The goal of this design was to determine if EQ-i and S-LPI scores were corroborated or supported by the director’s placement of participants into performance groups.
Finally, participants in this study were asked to complete a demographic survey
(Appendix C), sharing information about their (a) gender, (b) age, (c) GPA, (d) academic college, (e) number of years in the four-year leadership development program, (f) race, (g) mother’s education level, and (h) father’s education level.
This study was based on a correlational research design that expected to “seek out traits, abilities, or conditions that covary, or correlate” between the EQ-i scores and the S-LPI score of a population of college student leaders (Mertler & Charles, 2005, p. 298). After data collection, four types of data analyses were conducted. First, descriptive statistics were observed and frequencies were calculated to further describe participant demographics. Second, participants in the study completed two instruments and the instrument data sets were correlated using the
Pearson product-moment correlation. And finally, to explore the degrees of relationships between test instrument data variables, performance placement groups, and demographic variables, Analyses of Variance (ANOVAs) and t-tests were conducted. These procedures were used to address the following research questions:
1. Among identified student leaders, what is the level of emotional-social intelligence, as
measured by the five composite scales and the fifteen sub-scales of Bar-On’s Emotional
Quotient Inventory (EQ-i)? 54
2. Among student leaders, what are their leadership practices, as measured by Kouzes and
Posner’s Student Leadership Practices Inventory?
3. Among identified student leaders, what are the relationships between Bar-On’s
Emotional Quotient Inventory (EQ-i) subscales and components and Kouzes and
Posner’s Student Leadership Practices Inventory subscales (S-LPI)?
4. Among identified student leaders, to what extent are the student’ Emotional Quotient
Inventory and Student Leadership Practices Inventory scores supported by an external
assessment of the student’s performance in a four-year leadership development program?
5. What differences exist between emotional-social intelligence and leadership practices
among each of the following population categories: (a) gender, (b) age, (c) GPA, (d)
academic college, (e) the number of years student leaders have in the four-year program
(first, second, third, or fourth), (f) race, (g) mother’s education level, and (h) father’s
education level?
This chapter describes the research methods used for this study, and is divided into four sections: (a) participants, (b) instrumentation, (c) data collection, and (d) data analysis.
Participants
This study involved the participation of student leaders enrolled in a university sponsored, four-year student leadership development program at a Midwestern state university.
The intention of this study was to recruit all student leaders enrolled in the program during the
2004-2005 school year. Data were collected from each of the 83 students that were enrolled in the program at the point of data collection. Four cohorts divided the population into 28 first-year students, 17 second-year students, 25 third-year students, and 13 fourth and fifth year students.
However, after analysis of EQ-i scores, 10 participants were eliminated from the study based on 55
“Negative Impression Scores” that exceeded two standard deviations from average or M > 130.
Bar-On (2002) explained that if a respondent’s “Negative Impression Scale” score is over 130,
their inventory should be considered invalid (pp. 41-42). Then after reducing the population to (n
= 73), the four cohorts clustered into 20 First-Year students, 16 Second-Year students, 25 Third-
Year students, and 12 fourth and fifth year students.
The Leadership Development Program Description
The leadership development program was established in 1997 and was designed for
students who want to develop their leadership skills and are committed to assuming leadership positions on campus and in the surrounding community. The program follows a servant leadership curriculum designed to promote both leadership competencies and academic success.
Each year of the program contains systematic initiatives to progressively enhance student
leadership and academic success. The first year of the program focuses on self-exploration and
followership as it relates to group dynamics. The second year focuses on career and leadership
skills development. The third year continues to expand career development and offers advanced
leadership training opportunities. Additionally, in the third year students begin to share their
leadership knowledge and skills with emerging members. And finally, during the fourth and fifth
years, students assume a heightened level of responsibility for which they self-lead their own
leadership development through practical leadership experiences and planning for post-college
life.
Selection Process for Enrollment into the Student Leadership Program
One of the most important elements of this research design is the program’s identification
and recruitment of well developed and experienced student leaders. To establish a level of
credibility for assessing this particular population, the next few paragraphs describe the selection 56
and evaluation process for acceptance into this co-curricular four-year student leadership
development program, and demonstrate the rationale and motivation for using the population in
this study. The primary reasons for recruiting students from this leadership development program
are the strenuous and detailed criteria for acceptance into the program.
Each year approximately 150 high school students apply for this program. Among other
demographic information, applicants are required to include the following information:
1. Cumulative high school GPA
2. Combined ACT or SAT scores
3. High school activities and leadership experiences
4. High school employment and community activities and leadership experiences
5. High school community engagement activities
6. Honors and awards
Additionally, applicants are required to write a 300-600 word essay that answers various
questions about leadership in modern society. Submitted applications are examined by an
application review committee, consisting of a mixture of approximately 10 students, faculty, and administrators. Committee members are asked to assess each applicant’s materials utilizing the following set of criteria and ranking each criterion on a five-point scale ranging from (1) poor to
(5) excellent, with (0) none listed as a final option. The first criterion is leadership-based and evaluates the quality and quantity of sustained leadership commitments in high school. The second criterion is service-based and assesses the quality and quantity of community service experiences in high school. The third criterion is award-based and calculates that amount of recognition an applicant receives in high school regarding either sustained leadership commitments or dedication to community service. Finally, the fourth criterion in the application 57
review process assesses the applicant’s essay. The essay is evaluated for both grammar and
content and is awarded up to a maximum of 25 points. Roughly one-half of the applicants are offered an interview opportunity.
During the interview process, applicant answers to interview questions are assessed by applying a rubric that quantifies both the content and organization of their responses, as well as the applicant’s non-verbal presentation style during their responses. The types of questions asked in the interview include (a) the applicant’s general knowledge about the four-year leadership program, (b) general information about themselves (family, hobbies, interests, etc.), (c) their most memorable leadership experience in high school, (d) their most memorable community service experience in high school, (e) what they hope to gain from the college experience, and (f) thoughts that occurred while they wrote the essay. Each applicant is evaluated using a four-point scale for the content and organization of their responses and their presentation style. After the interview process, thirty applicants with the highest combined scores between the application critique and the interview evaluation are accepted into the program.
Instrumentation
The two primary instruments used to collect data in this study were Bar-On’s (1997)
Emotional Quotient Inventory (EQ-i) and Kouzes and Posner’s (2004) Student Leadership
Practices Inventory (S-LPI). View the S-LPI in Appendix E. One reason for selecting these two instruments was the similarity between methodological approaches. Both instruments are self- report measures that assess the participant’s perceptions of their own abilities within each construct. Additionally, both measurements utilize Likert-type scales to rate the level of frequency of behaviors associated with emotional competencies as interpreted by the EQ-i, and student leadership practices as interpreted by the S-LPI. Additionally, both instruments have 58
been employed in studies of college students and various leadership settings. Moreover, each
instrument measures competencies that are associated with the interpersonal aspects of
leadership. As demonstrated in the next few paragraphs, each instrument has undergone extensive validation and reliability studies.
The Bar-On Emotional Quotient Inventory (EQ-i)
The Bar-On Emotional Quotient Inventory (EQ-i) is a multidimensional test instrument that consists of 133-items on a 5-point Likert scale ranging from “very seldom or not true of me” to “very often true of me or true of me.” The EQ-i is a self-report measure that “provides an estimate of one’s emotional and social intelligence” for ages 16 and over (Bar-On, 2000, p. 364).
Readability for the EQ-i is rated at the American sixth grade level (Bar-On, 2000). Bar-On
(2002) defines emotional intelligence as “an array of personal, emotional, and social competencies and skills that influence one’s ability to succeed in coping with environmental demands and pressures” (p. 14). The EQ-i assesses a total emotional quotient score, five composite scores, and 15 subscale scores within Bar-On’s construct of Emotional-Social
Intelligence. The five composite factors and 15 subscales measured by the EQ-i include
Intrapersonal components (1. Emotional Self-Awareness, 2. Assertiveness, 3. Self-Regard, 4.
Self-Actualization, 5. Independence); Interpersonal components (6. Empathy, 7. Interpersonal
Relationship, 8. Social Responsibility); Adaptability components (9. Problem Solving, 10.
Reality Testing, 11. Flexibility); Stress Management components (12. Stress Tolerance, 13.
Impulse Control); and General Mood components (14. Happiness, 15. Optimism) (Bar-On,
2002). Also refer to Table 1 in Chapter 1.
Bar-On (2002) explained that the EQ-i has nearly 20 years of supported research. It was originally developed as an experimental instrument in 1980 and, then after three experimental 59 phases, was published in 1997. Reviews of the EQ-i were conducted by the Buros Institute for
Mental Measurements in 1999 and both the 13th and 14th Supplement to the Mental Measurement
Yearbooks (Plake & Impara, 1999, 2001). The adult version of the EQ-i was normed using a sample population of over 4,000 North American adults. The North American sample is very diverse in terms of ethnicity, age, socioeconomics, education, occupation, and is geographically representative (Bar-On, 2000, p. 366). Analyses of variance were completed to examine the effects of gender, age, and ethnicity on EQ-i scores. Findings revealed significant differences between EQ-i scores and age and demonstrated that social and emotional intelligence increases until the fifth decade of life where scores dip slightly (Goleman, 1998). In terms of gender, general scores revealed no significant differences between men and women; however, a few factorial components of the construct demonstrated relatively small differences. Based on the normative sample, Bar-On (2000) explained that:
Females appear to have stronger interpersonal skills than males, but the latter have a
higher intrapersonal capacity, are better at stress management, and are more adaptable.
More specifically, women are more aware of emotions, demonstrate more empathy, relate
better interpersonally, and act more socially responsible than men; on the other hand,
men appear to have better self-regard, are more independent, cope better with stress, are
more flexible, solve problems better and are more optimistic than women. (p. 367)
Finally, Bar-On (2002) explained that the North American normative sample did not identify significant differences among ethnic groups.
EQ-i Validity
Bar-On (2002) found that the EQ-i had more than adequate validity and was examined using nine types of studies: “content, face, factor, construct, convergent, divergent, criterion- 60
group, discriminant, and predictive validity” (p. 89). Dawda and Hart (2000) demonstrated
“similar patterns of validity results for men and women” which provided evidence of no gender
bias for the EQ-i (p. 809).
To improve the instrument’s validity four validity indicators are assessed in the EQ-i.
These include omission rate, inconsistency index, positive impression, and negative impression.
The omission rate evaluates the number of omitted responses and invalidates instruments that are
missing a set number of responses. Inconsistency measures consistency between similar types of
items. The positive impression scale measures the tendency to exaggerate positive responses.
Likewise, the negative impression scale measures the opposite, the tendency to exaggerate negative responses. To adjust for negative or positive impression scores the EQ-i has a built-in correction feature that automatically adjusts the scale score based on the two impression scores.
This built-in feature helps to minimize the “distorting effects of social response bias” (Bar-On,
2000, p. 365).
EQ-i Reliability
Reliability, internal consistency and retest reliability studies have been conducted on the
Bar-On EQ-i to verify its reliability. In “examining the results of the internal consistency and retest reliability studies, it can be concluded that the EQ-i has demonstrated more than adequate reliability” (Bar-On, 2002, p. 88). These studies have found the average Cronbach alpha coeffiencents are high for all subscales, ranging from a .69 (Social Responsibility) to a .86 (Self-
Regard), with an overall average internal consistency of .76 (Bar-On, 2002, p. 87). Additionally,
Van der Zee and Wabeke (2004) in a study of EI and Big Five personality traits found
Cronbach’s alphas for the EQ-i ranging from a .61 (Social responsibility) to .82 (Emotional self- 61
awareness). The moderate to high alpha scores demonstrated that the Bar-On EQ-i is a reliable
instrument.
Kouzes and Posner Student Leadership Practices Inventory (S-LPI)
The Student Leadership Practices Inventory (S-LPI) is based on the Leadership Practices
Inventory and was re-designed for college students and young adults. See Appendix E to view a copy of the S-LPI. It is a self-reported instrument consisting of 30 statements that are rated on a
five-point, Likert-type scale ranging from “rarely” to “very frequently.” The statements “focus
on leadership behaviors and on the frequency with which the person engages in those particular
behaviors” (Kouzes & Posner, 1998, p. 7). See Appendix E. The S-LPI measures five key
composite leadership practices and within each area Kouzes and Posner list two leadership
commitments that further define the construct. The first composite leadership practice is
“challenging the process” and involves the leader’s ability to search for opportunities,
experiment and take risks. The second composite is “inspiring a shared vision” and involves the
leader’s commitment to envisioning an uplifting future and enlisting others in a common vision.
The third composite is “enabling others to act” and involves fostering collaboration and
strengthening or empowering others. The fourth composite is “modeling the way” and involves a
leader’s commitment to setting the example and achieving small wins to move the organization
forward. Finally, the fifth composite leadership practice is “encouraging the heart.” In this area,
leaders focus on recognizing individual contributions and celebrating team accomplishments.
(Kouzes & Posner, 1998, pp. 11-14).
Kouzes and Posner developed the original Leadership Practices Inventory (LPI) in 1987
using case studies to generate a set of behaviors that people identified using during effective
leadership experiences. A content analysis was then conducted on the leadership behaviors and 62
patterns were observed and leadership practices were clustered into the aforementioned five
categories. Posner and Brodsky (1992) adapted the original version to reflect questions and terminology that was appropriate to college student and student leadership development. The S-
LPI has been administered with a variety of student leader populations: (a) male fraternity presidents, (b) female sorority presidents, (c) fraternity officers, (d) sorority officers, (e) resident advisors, (f) orientation advisors, (g) dietetics students, and (h) hospitality students (Posner,
2004). However, Posner found that the internal reliability coefficients for the S-LPI self-report measures tended to be low. Table 2 indicates the range of internal reliability coefficients found when applying the S-LPI self-report inventory.
Table 2.
Internal Reliability Coefficient for the Student Leadership Practices Inventor
S-LPI Factors Low Range High Range
Challenging the process .55 .74
Inspiring a shared vision .61 .81
Enabling others to act .61 .70
Modeling the way .61 .69
Encouraging the heart .66 .83
After identifying a pattern of low reliability coefficients, Posner conducted a study that
explored the content and face validity of the S-LPI and found that some of the instrument’s items
need to be modified to increase understanding and validity. Recently, Posner (2004) completed
the first study that utilized the revised S-LPI and found that the internal reliability coefficient
scores were “compatible with those found in previous studies involving the original Student LPI” 63
(p. 453). However, additional studies are needed to generate a clearer picture of the internal reliability coefficient for the newly revised instrument. With that in mind, the researcher’s decision to utilize the new version of the S-LPI was to further assess it validity and reliability.
Data Collection Process and Procedures
As with any data collection process, a series of requests and approvals were conducted for this study. First, the researcher discussed this research idea with the director of the four-year, co-curricular, leadership development program. Then upon gaining the program director’s permission, the researcher followed the guidelines and procedures utilized by the Human
Subject’s Review Board at the host institution. In terms of approval to use the data collection instruments, a written request and application process was completed for both the EQ-i publisher
(Multi-Health Systems Inc.) and the S-LPI (Kouzes and Posner).
After gaining approval from the director of the leadership program, the researcher visited four regularly scheduled program meetings and recruited students to participate in the study.
After a brief explanation of the study, the researcher distributed an informed consent document
(Appendix A) to all participants and allowed them time to read through it. Then the rearcher read the informed consent sheet out loud to the participants. This was to ensure that all of the participants thoroughly understood the necessary information regarding their participation in the study. The researcher then asked the potential participants if they have any questions regarding the study or their rights as participants. The researcher answered any questions to the satisfaction of the participants. At that time, the researcher explained again that their completion and submission of the data collection instruments indicated their consent to participate.
After participants agreed to participate, and to improve participant confidentiality, each participant received a code number that corresponded with numbers on the test instruments and 64
folder. The test instrument folders included: (a) one copy of the Cavins’ Dissertation
Demographic Survey (Appendix C), (b) one copy of the S-LPI test booklet with corresponding
data collection sheet, and (d) one copy of the EQ-i test booklet with corresponding data
collection sheet. The researcher then distributed instruments and answer sheets with corresponding code numbers. After the students completed the instruments, each test instrument was collected and stored in a secure location to insure confidentiality.
In terms of the Director’s Student Leader Performance Placement Worksheet, the director received the worksheet and then completed it on his own and returned the completed form back to the researcher. To ensure confidentiality, this document was locked in a secured location as well. In addition, the director of the program did not have access to participant code numbers, and as a result, he does not know who participated in the study nor does he know how any of the participant score on the test instruments. All findings were reported in group mean format.
Data Analysis
The data encoding process for the four instruments utilized in this study consisted of different procedures. First, for the EQ-i, the researcher transferred scores from the hand-written
EQ-i test sheets to an on-line EQ-i test application on the Multi-Health Services (MHS) website.
Upon encoding all of the test instrument data into the on-line service, Multi-Health Services then sent the researcher, via email, a Microsoft Excel document with a raw score data set. This data set was then transferred to SPSS 12.0 for windows for data analysis. With the S-LPI (Appendix
E), Demographic survey (Appendix C), and the director’s “Student Leadership Performance
Placement Worksheet” (Appendix D) the researcher transferred scores and data from the survey instruments to a Microsoft Excel document and then transferred the data into the same SPSS 12.0 document that contained the EQ-i data. After the transfers were completed, all data for the study 65
were included in one SPSS document. As mentioned earlier in this chapter, ten participants were
eliminated from this study because of high “Negative Impression Scale” scores on the EQ-i, which invalidated their instruments. Consequently, the data of 73 participants were explored and assess to identify the results of this study.
The Pearson correlation coefficients, r, were used to test the degree of relationship between emotional intelligence scores and leadership practices scores among college student
leaders enrolled in the program. The Pearson’s r correlations were used to “explore the
relationship between variables expressed in continuous interval data, such as numerical test
scores” (Mertler & Charles, 2005, p. 301). The results of the Pearson’s r indicated the degree of
association shared by the various subscale variables collected through the S-LPI and the EQ-i.
This study also used Analyses of Variance (ANOVAs) and t-tests to identify differences between
demographic clusters and performance groups related to emotional-social intelligence scores and student leadership practices scores. 66
CHAPTER IV. RESULTS
This chapter presents the results of statistical analyses of the data in this study, beginning
with a description of the participant demographics and a brief explanation of the analyses applied
to assess each research question. The first set of data describes the participants’ scores within the
area of Emotional-Social Intelligence as measured by the five subscales and 15 components of
Bar-On’s Emotional Quotient Inventory (EQ-i). The second section describes the participants’
leadership practices as measured by Kouzes and Posner’s Student Leadership Practices Inventory
(S-LPI), see Appendix E. The third section presents identifies relationships between the
Emotional Quotient Inventory variables and the Student Leadership Practices Inventory
variables. The fourth section analyzes the mean differences between performance groups as
indicated by Emotional Quotient Inventory scores and Student Leadership Practices Inventory
scores. Finally, the fifth section addresses mean differences between participant demographic
variables and both the EQ-i scores and the S-LPI scores.
The primary purpose of this research study was to explore the relationship between
Emotional-Social Intelligence (using Bar-On’s Emotional Quotient Inventory, EQ-i) and student
leadership practices (as identified by Kouzes and Posner’s Student Leadership Practices
instrument, S-LPI) among college students enrolled in a four-year leadership program at a
Midwestern University. Additionally, a performance placement worksheet (Appendix D) was
used to determine if the students’ self-evaluative instrument scores of the students (EQ-i and S-
LPI) were supported by an external assessment of the students’ performance within the four-year
leadership development program.
. 67
Description of the Participants
The targeted population for this study consisted of student leaders enrolled in a university
sponsored, four-year leadership development program at a Midwestern state university. The
accessible population included 83 students enrolled in the program and 100% participation was achieved in this study. However, after processing participant data on the Emotional Quotient
Inventory (EQ-i), ten participants failed the “Negative Impression Scale (NIS),” meaning their
NIS scores “exceed[ed] two standard deviations from the mean (30 points), and [their] results are
considered invalid” by the standards of this test instrument (Bar-On, 2002, pp. 41-42). As a
result, this study analyzed data collected from the remaining 73 participants.
Along with the completion of test instruments, participants were asked to provide
demographic information, which included gender, age, current GPA, academic college, current
year enrolled in the leadership development program, race, mother’s education level, and father’s
education level. Table 3 provides detailed descriptions of the demographic compositions of the
complete sample. Over 60% of the sample were women, and the mean age for the sample was 20
years old. The mean GPA was 3.13; and participants, in order of frequency, were enrolled in the
College of Arts and Sciences (n = 25, 34.2%), Education and Human Development (n = 21,
28.8%), Business Administration (n = 12, 16.4%), Health and Human Services (n = 7, 9.6%),
Technology (n = 6, 8.2%), Musical Arts (n = 1, 1.4%) and undecided students (n = 1, 1.4%). In
terms of longevity with the leadership development program, the first-year cohort constituted
27.4 % of the sample (n = 20); the second-year cohort was 21.9% (n = 16); the third-year cohort
equaled 34.2% (n = 25); and the fourth and fifth-year cohorts combined to a total of 16.4% (n =
12). Taking into account racial diversity, 45.2% were African American (n = 33), 42.5% of the
participants were white (n = 31), 5.5% were Hispanic/Latino (n = 4), 4.1% described themselves 68 as “other” (n = 3), one participant listed Asian-Pacific Islander, and one participant listed multiracial. Within the category of Mother’s Education Level, 49.3 % indicated that their mothers did not achieve a college degree (n = 36), 30.1% explained that their mother achieved either an associate or bachelor’s degree (n = 23), while 19.2% listed that their mother had achieved a postgraduate degree (n = 14). Within the category of Father’s Education Level, 46.6% indicated that their fathers did not achieve a college degree (n = 34), 31.5% explained that their fathers achieved either an associate or bachelor’s degree (n = 23), while 19.2% listed that their father had achieved a postgraduate degree (n = 14). Note that two participants did not respond to this question about Father’s Education Level. Finally, an external assessment of participant performance within the four-year leadership development program was collected from the program director using a “Student Leader Performance Placement Worksheet” (Appendix D).
The director was asked to place 22 or 26.5% of program members into a “Top Performers
Group,” and 22 or 26.5% into a “Bottom Performers Group.” The remaining 39 or 47% of the participants not placed in either top or bottom performance group were clustered into the
“Middle Performers Group.” However, because 10 participants were eliminated from the study due to the “Negative Impression Scale” on the EQ-i, the final break down of participant program performance groups were as follows: Top Performers (n = 20, 27.4%), Middle Performers (n =
35, 47.9%), and Bottom Performers (n = 18, 24.7%). The director placed participants into performance groups based on three primary criteria: (a) the student’s overall GPA, (b) the student’s progression through the program (i.e., specific first, second, third, and fourth-year learning and performance objectives), and (c) the student’s involvement with leadership positions on campus. 69
Table 3.
Summary of Sample by Demographic Variables
Demographic Variable n %
Population 83 Adjusted Sample Size 73
Gender Male 28 38.4 Female 45 61.6
Age 18 10 13.7 19 13 17.8 20 24 32.9 21 20 27.4 22 5 6.8 23 1 1.4
GPA Cluster 1.00 - 1.99 1 1.4 2.00 - 2.49 10 13.7 2.50 – 2.99 15 20.5 3.00 – 3.49 21 28.8 3.50 – 4.00 23 31.5 Missing Variables 3 4.1
Academic College Arts and Sciences 25 34.2 Business Administration 12 16.4 Education and Human Development 21 28.8 Health and Human Services 7 9.6 Musical Arts 1 1.4 Technology 6 8.2 Undecided 1 1.4
70
Demographic Variable n %
Year Currently Enrolled in Program First 20 27.4 Second 16 21.9 Third 25 34.2 Fourth/Fifth 12 16.4
Race White 31 42.5 African-American 33 45.2 Hispanic/Latino 4 5.5 Asian-Pacific Islander 1 1.4 Multi-Racial 1 1.4 Other 3 4.1
Mother’s Education Level Less than High School 0 0 High School/GED 22 30.1 Some College 14 19.2 2-year college degree (associate) 13 17.8 4-year college degree (BA, BS) 10 13.7 Master’s Degree 14 19.2 Doctoral Degree 0 0 Professional Degree (MD, JD) 0 0
Father’s Education Level Less than High School 2 2.7 High School/GED 21 28.8 Some College 11 15.1 2-year college degree (associate) 11 15.1 4-year college degree (BA, BS) 12 16.4 Master’s Degree 13 17.8 Doctoral Degree 1 1.4 Professional Degree (MD, JD) 0 0 Missing Score 2 2.7
Program Performance Groups Top Performers 20 27.4 Middle Performers 35 47.9 Bottom Performers 18 24.7 71
Instrument Internal Reliability (Cronbach’s alpha)
Cronbach’s alpha coefficients of internal consistency were used to assess the internal
reliability of the EQ-i and the S-LPI. Table 4 presents the internal consistency coefficients for the
15 components of the EQ-i and the five S-LPI subscales. The Cronbach alpha coefficients are
high for all components of the EQ-i except Independence and Flexibility. These findings are
inconsistent with the coefficient scores of prior research where alpha scores for Independence
ranged from .69 to .77 and Flexibility ranged from .71 to .75 (Bar-On, 1997; Petrides &
Furnham, 2001).
There has been little published research using the 2005 version of the S-LPI. However,
Posner (2004) found that the updated S-LPI produced the following alpha coefficients for a sample of Fraternity presidents and a sample of other officers that ranged from: Modeling the
Way, 0.55 - 0.59; Inspiring a Shared Vision, 0.67 - 0.75; Challenging the Process, 0.61 - 0.64;
Enabling Others to Act, 0.61 - 0.63; and Encouraging the Heart, equal alphas at 0.77. The alpha
scores for the present study found similarities with Inspiring a Shared Vision (α = 0.74),
Challenging the Process (α = 0.69), and Encouraging the Heart (α = 0.77); however, differences were identified between this study’s lower scores in Enabling Others to Act (α = 0.51) and higher scores in within the Modeling the Way (α = 0.68) subscale. The fluctuation and identification of low scores indicates that additional research is needed to further test the internal reliability of the 2005 S-LPI. 72
Table 4.
Internal Reliability Coefficient (Cronbach’s alpha) Scores for the EQ-i and S-LPI
Test Variables Alpha # of Items
Emotional Quotient Inventory Variables
Self-Regard 0.84 9
Emotional Self-Awareness 0.73 8
Assertiveness 0.78 7
Independence 0.48 7
Self-Actualization 0.79 9
Empathy 0.71 8
Social Responsibility 0.81 10
Interpersonal Relationships 0.69 11
Stress Tolerance 0.71 9
Impulse Control 0.80 9
Reality Testing 0.69 10
Flexibility 0.63 8
Problem Solving 0.77 8
Optimism 0.80 8
Happiness 0.71 9
Student Leadership Practice Inventory Variables
Modeling the Way 0.68 6
Inspiring a Shared Vision 0.74 6
Challenging the Process 0.69 6
Enabling Others to Act 0.51 6
Encouraging the Heart 0.77 6
73
Results of Research Questions
Research Question #1: Among identified student leaders, what is the level of emotional-social intelligence, as measured by the five composite scales and the fifteen sub-scales of Bar-On’s
Emotional Quotient Inventory (EQ-i)?
The first research question for this study examined levels of Emotional-Social
Intelligence, as measured by the five subscales and the fifteen components of Bar-On’s
Emotional Quotient Inventory (EQ-i) among students enrolled in the four-year leadership development program. Table 5 presents interpretation guidelines for standard scores for the EQ-i.
And Table 6 provides a list of the overall mean scores and standard deviations for each variable assessed. For the total EQ-i the mean score was 101.75 with a minimum score of 69 and a maximum score of 127. In terms of the five subscales of the EQ-i, Intrapersonal (M = 105.14,
SD = 12.638) and General Mood (M = 104.49, SD = 12.147) subscales produced the two highest mean scores of the five subscales. The scores decreased with the Stress Management (M =
100.32, SD = 12.971) and Adaptability (M = 99.56, SD = 12.463) subscales; and the
Interpersonal subscale represented the lowest mean subscale score (M = 98.85, SD = 12.012).
The 15 components of the EQ-i provided a more detailed indication of this sample’s level of
Emotional-Social Intelligence. From the highest to the lowest mean scores, the top five component scores were Self-Regard (M = 107), Self-Actualization (M = 106.53), Happiness (M =
105.15), Independence (M = 103.36), and Interpersonal Relationships (M = 103.30). The middle
five composite mean scores were Optimism (M = 102.73), Emotional Self-awareness (M =
102.14), Stress Tolerance (M = 101.89), Flexibility (M = 101.45), and Assertiveness (M =
101.15). The bottom five composite mean scores were Problem Solving (M = 99.88), Impulse
Control (M = 98.40), Reality Testing (M = 97.84), Empathy (M = 96.86) and Social 74
Responsibility (M = 95.60). As indicated in Table 5, this sample scored in the “Average: Typical, usually adaptive emotional capacity” category, as interpreted by Bar-On (2002). Only two component mean scores that fit into the “High Average: Well developed emotional capacity” category: Self-Regard and Self-Actualization.
Table 5.
Group Report Standard Score Interpretation Guidelines
Standard Score Guidelines 110 and Over High: Atypically well developed emotional capacity 105 to 110 High Average: Well developed emotional capacity 95 to 105 Average: Typical, usually adaptive emotional capacity 90 to 95 Low Average: Under-developed emotional skills Under 90 Low: Markedly under-developed emotional skills Bar-On (2002, p. 202) 75
Table 6.
Summary of Sample Emotional Quotient Inventory Means Scores
Emotional Quotient Inventory Variables MSD
Total EQ-i Score 101.75 11.745 Intrapersonal Subscale 105.14 12.638 Interpersonal Subscale 98.85 12.012 Stress Management Subscale 100.32 12.971 Adaptability Subscale 99.56 12.463 General Mood Subscale 104.49 12.147 EQ-i Component Scores Self-Regard 107.00 11.700 Emotional Self-Awareness 102.14 12.609 Assertiveness 101.15 15.862 Independence 103.36 10.679 Self-Actualization 106.53 13.236 Empathy 96.86 14.037 Social Responsibility 95.60 15.472 Interpersonal Relationships 103.30 11.890 Stress Tolerance 101.89 12.125 Impulse Control 98.40 15.004 Reality Testing 97.84 13.454 Flexibility 101.45 11.900 Problem Solving 99.88 13.592 Optimism 102.73 14.547 Happiness 105.15 12.883 Bolded information represents “High Average” scores 76
Research Question #2: Among student leaders, what are their leadership practices, as measured
by Kouzes and Posner’s Student Leadership Practices Inventory?
The second research question for this study examined student leadership practices, as
measured by Kouzes and Posner’s Student Leadership Practices Inventory (S-LPI), among
students enrolled in the four-year leadership development program. Table 7 provides mean
scores and standard deviations for each variable assessed by the S-LPI. In terms of the five S-LPI
subscales, from the highest to the lowest mean score on a 30-point scale, “Enabling Others to
Act” had the highest mean score (M = 24.44, SD = 2.533). Respectively, the mean for
“Encouraging the Heart” was (M = 23.95, SD = 3.681), “Inspiring a Shared Vision” was (M =
23.49, SD = 3.621) and “Modeling the Way” was (M = 22.32, SD = 3.240). The lowest subscale mean score for this sample was “Challenging the Process” with (M = 22.11, SD = 3.474). Each of the S-LPI mean scores of this sample scores fit within the “Moderately Strong” leadership qualities (Kouzes & Posner, 1998).
Table 7.
Summary of Sample Student Leadership Practice Subscale Mean Scores
S-LPI Variables MSD Modeling the Way 22.32 3.240
Inspiring a Shared Vision 23.49 3.621
Challenging the Process 22.11 3.474
Enabling Others to Act 24.44 2.533
Encouraging the Heart 23.95 3.681
77
Research Question # 3: Among identified student leaders, what are the relationships between
Bar-On’s Emotional Quotient Inventory (EQ-i) subscales and components and Kouzes and
Posner’s Student Leadership Practices Inventory subscales (S-LPI)?
The third research question for this study examined relationships between Bar-On’s
Emotional Quotient Inventory variables and Student Leadership Practices variables among
students enrolled in the four-year leadership development program. Pearson product-moment
correlations, or “Pearson r correlations,” were used to evaluate the relationships between test
score variables. More specifically, Pearson r correlations are used to “explore relationships
between variables expressed in continuous interval data” like the data collection instruments
used in this study (Mertler & Charles, 2005, p. 301). Table 8 presents the total list of Pearson r-
values. Colors within Table 8 can be interpreted as follows: (a) green – r-values > .500, p = 0.01;
(b) yellow – r-values > .300 but < .499, p = 0.01; and (c) red – r-values > .234 but < .299, p =
0.05.
The overall Emotional Quotient Inventory score correlated significantly with all five categories of the S-LPI. The two practices with the strongest correlations were Modeling the Way
(r = .542, p < .01, two-tailed) and Enabling Others to Act (r = .499, p < .01, two-tailed). The other three leadership practices had moderate correlations: Inspiring a Shared Vision (r = .433, p
< .01, two-tailed), Challenging the Process (r = .406, p < .01, two-tailed), and Encouraging the
Heart (r = .281, p < .05, two-tailed). These statistically significant relationships indicated that as
students’ emotional-social intelligence increases, each of the five student leadership practices
also increases. The next few paragraphs assess the relationships between each of the Kouzes and
Posner’s Student Leadership Practices and each of the EQ-i variables. 78
Modeling the Way
Of the 15 components of the EQ-i, three components yielded strong positive correlations with Modeling the Way: Optimism (r = .618, p < .01, two-tailed); Self-actualization (r = .572, p <
.01, two-tailed); and Problem Solving (r = .548, p<.01, two-tailed). Additionally, several components of the EQ-i produced significant moderate correlations (r > .300 and r < .499), at p
= .01: Social Responsibility, Stress Tolerance, Empathy, Happiness, Interpersonal Relationships, and Reality Testing. Likewise, small correlations (r > .100 and r < .299), were identified at p=
.05: Flexibility, Emotional Self-Awareness, and Self-Regard. Assertiveness, Independence, and
Impulse Control were not significant at the p = .01 or p = .05 level. In conclusion, 12 of the 15 components of the EQ-i correlated positively with Kouzes and Posner’s Modeling the Way practice.
Inspiring a Shared Vision
Like Modeling the Way, Inspiring a Shared Vision also generated a strong, positive correlation with Optimism (r = .545, p < .01, two-tailed). Likewise, six components were identified as having moderately significant relationships at the p < .01 level: Problem Solving,
Self-Actualization, Emotional Self-Awareness, Interpersonal Relationships, Stress Tolerance, and Assertiveness. Four components yielded small correlations significant at p < .05: Social
Responsibility, Flexibility, Empathy, and Self-Regard. While Happiness, Independence, Reality
Testing, and Impulse Control were not statistically significant at p = .01 or p = .05.
Challenging the Process
Comparable to Modeling the Way and Inspiring a Shared Vision, Challenging the
Process also generated a strong, positive correlation with Optimism (r = .550, p < .01, two-
tailed). Similarly, five components were identified as having significant moderate relationships 79
at the p = .01 level: Problem Solving, Self-actualization, Stress Tolerance, Self-Regard, and
Assertiveness. Two components produced small correlations significant at p < .05: Social
Responsibility and Happiness. And those components that did not correlate significantly with
Challenging the Process were Interpersonal Relationships, Flexibility, Emotional Self-
Awareness, Empathy, Independence, Reality Testing, and Impulse Control.
Enabling Others to Act
The two leadership practices assessed by Kouzes and Posner’s Student Leadership
Practices Inventory that correlated most significantly with the 15 components of Bar-On’s
Emotional Quotient Inventory were Modeling the Way and Enabling Others to Act. These two leadership practices correlated significantly with many of the same EQ-i components. For the
Enabling Others to Act practice, Empathy (r = .588, p < .01, two-tailed) and Social
Responsibility (r = .574, p < .01, two-tailed) possessed the strongest correlation. Additionally, five components of the EQ-i produced statistically significant moderate correlations, at p < .01:
Problem Solving, Flexibility, Reality Testing, Self-Actualization, and Optimism. Furthermore,
Stress Tolerance and Impulse Control weighed in with a small correlation at p < .05, while
Interpersonal Relationships, Emotional Self-Awareness, Self-Regard, Happiness, Assertiveness, and Independence were not significant at the p = .01 or p = .05 level. In summary, 9 of the 15 components of the EQ-i correlated positively with Kouzes and Posner’s Enabling Others to Act practice.
Encouraging the Heart
Of the five leadership practices in the S-LPI framework, Encouraging the Heart produced fewer and weaker correlations with emotional-social intelligence variables. Empathy
held the strongest correlation with Encouraging the Heart (r = .499, p < .01, two-tailed). The two 80
components of the EQ-i that yielded significant moderate correlations at p < .01 were Social
Responsibility and Problem Solving, while Interpersonal Relationships and Self-Actualization
generated small correlations at the p = .05 level. The components that were not statistically
significant at either the p = .01 or p = .05 level were Optimism, Flexibility, Impulse Control,
Stress Tolerance, Happiness, Emotional Self-Awareness, Self-Regard, Reality Testing,
Assertiveness, and Independence.
Summary
As demonstrated in Table 8, the Pearson Product-Moment Correlation Coefficient
generated significant moderate to strong correlations between the total Emotional Quotient
Inventory with all five of the Student Leadership Practices Inventory. Likewise, the EQ-i
subscales, with a few exceptions, produced small to large correlations with the S-LPI subscales
at the p = .01 or the p = .05 level. The Interpersonal and General Mood subscales displayed the strongest correlations followed by the Adaptability subscale and the Intrapersonal and Stress
Management subscales were the least correlated with the S-LPI subscales. Of the fifteen components of the EQ-i, Problem Solving, Self-Actualization, and Social Responsibility produced statistically significant correlations with all five of the student leadership practices.
Empathy, Stress Tolerance, and Optimism produced statistically significant findings in four out of the five S-LPI subscales. Additionally, the following components were moderately significant
(r > .300 and r < .499), in at least one of the five S-LPI subscales: Self-Regard, Emotional Self-
Awareness, Assertiveness, Interpersonal Relationships, Reality Testing, Flexibility, and
Happiness. Independence and Impulse Control demonstrated the lowest statistical relationships with student leadership practices.
. 81
Table 8. Pearson r Correlation Matrix between EQ-i variables and S-LPI variables (n = 73) Modeling the Inspiring a Challenging the Enabling Others Encouraging the Variables Way Shared Vision Process to Act Heart Total EQ-i Score .542** .433** .406** .499** .281* Intrapersonal Subscale .389** .386** .365** .234* .079 Self-Regard .263* .235* .346** .172 .050 Emotional Self-Awareness .276* .403** .192 .176 .054 Assertiveness .227 .301** .307** .030 -.015 Independence .117 .098 .152 .027 -.093 Self-Actualization .572** .417** .394** .411** .246* Interpersonal Subscale .481** .404** .298* .529** .459** Empathy .389** .287* .182 .588** .499** Social Responsibility .452** .297* .296* .574** .409** Interpersonal Relationships .329** .354** .207 .208 .256* Stress Management Subscale .325** .168 .224 .337** .227 Stress Tolerance .404** .311** .381** .290* .188 Impulse Control .159 -.010 .017 .286* .193 Adaptability Subscale .481** .351** .287* .575** .225 Reality Testing .315** .089 .052 .434** .030 Flexibility .293* .289* .201 .452** .212 Problem Solving .548** .497** .469** .488** .343** General Mood Subscale .580** .442** .478** .322** .202 Optimism .618** .545** .550** .392** .226 Happiness .334** .179 .237* .144 .099 **. Correlation is significant at the 0.01 level (2-tailed) *. Correlation is significant at the 0.05 level (2-tailed) 82
Research Question Four: Among identified student leaders, to what extent are the students’
Emotional Quotient Inventory and Student Leadership Practices Inventory scores supported by an external assessment of the student’s performance in a four-year leadership development program? A “modified 360-degree” or “Student Leader Performance Placement Worksheet” was designed to assess the extent to which EQ-i scores and S-LPI scores are supported by an external assessment of student performance in the four-year leadership development program (Appendix
D). The director of the leadership development program was asked to place 22 students / 26.5% into a Top Performance group and 22 students / 26.5% into Bottom Performance group. And the remaining 39 or 47% students were placed into the Middle Performance group. However, as discussed earlier, because 10 participants were eliminated from the study due to their overall
“Negative Impression Scale (NIS)” score on the EQ-i, the final categorization of program performance groups was: Top Performers (n = 20, 27.4%), Middle Performers (n = 35, 47.9%), and Bottom Performers (n = 18, 24.7%). As a review, the director placed participants into performance groups based on three primary criteria: (a) the student’s overall GPA, (b) the student’s progression through the program (i.e. specific first, second, third, and fourth-year learning and performance objectives), and (c) the student’s involvement with leadership positions on campus.
Emotional Quotient Inventory Scores and Program Performance
Table 9 presents the means for each performance group within each variable of the
Emotional Quotient Inventory (EQ-i). To explore the differences among performance groups,
Analyses of Variance (ANOVAs) were performed. 83
Table 9.
Mean Emotional Quotient Inventory Scores by Program Performance Placement
Dependent Variables Bottom Performer Middle Performer Top Performer ANOVA T - B T - M MSDMSDMSD p p p Total EQ-i Score 96.22 10.871 100.71 11.908 108.55 9.145 0.003 0.003 0.034 Intrapersonal Subscale 102.50 12.798 103.74 12.629 109.95 11.781 0.128 Self-Regard 105.11 11.432 105.31 12.667 111.65 9.126 0.113 Emotional Self-Awareness 98.44 12.229 100.77 12.582 107.85 11.604 0.046 Assertiveness 103.44 16.267 100.17 15.188 100.80 17.234 0.776 Independence 105.11 9.311 102.57 12.260 103.15 9.028 0.716 Self-Actualization 99.17 15.883 105.97 11.608 114.15 9.167 0.001 0.001 Interpersonal Subscale 92.94 12.100 99.00 12.000 103.90 9.910 0.017 0.012 Empathy 91.17 12.382 97.80 14.054 100.35 14.521 0.113 Social Responsibility 89.17 15.823 95.51 15.309 101.55 13.682 0.046 0.035 Interpersonal Relationships 99.83 13.365 103.03 12.191 106.90 9.210 0.186 Stress Management Subscale 95.94 13.331 99.09 14.172 106.40 7.701 0.032 0.033 Stress Tolerance 96.28 12.361 101.89 12.748 106.95 8.532 0.023 0.017 Impulse Control 96.61 15.871 96.14 15.915 103.95 11.385 0.151 Adaptability Subscale 94.39 9.648 98.20 13.094 106.60 10.845 0.006 0.006 0.034 Reality Testing 95.17 12.397 95.83 13.921 103.75 12.273 0.067 Flexibility 98.72 10.835 101.20 10.718 104.35 14.492 0.346 Problem Solving 92.33 9.081 98.83 14.269 108.50 11.302 0.001 0.001 0.019 General Mood Subscale 95.56 11.628 104.26 11.736 112.95 6.378 0.001 0.001 0.012 Optimism 95.28 14.847 101.17 13.791 112.15 10.669 0.001 0.001 0.012 Happiness 96.56 16.415 106.00 10.971 111.40 7.749 0.001 0.001 Bolded information indicates significant within-group and pairwise differences T – B: Post hoc test p-values for significant pairwise differences between Top Performers and Bottom Performers T – M: Post hoc test p-values for significant pairwise differences between Top Performers and Middle Performers *** There no statistically significant difference between Middle Performers and Bottom Performers 84
Table 10 shows there were significant differences between program performance groups
with respect to total EQ-i scores (p = .003). Tukey Post Hoc testing, displayed in Appendix F, identified that difference as occurring between top performers and bottom performers (p = .003), and between top performers and middle performers (p = .034). As displayed in Table 9, the mean score for top performers total EQ-i (M = 108.55) was significantly higher than that of both middle (M = 100.71) and bottom (M = 96.22) performers.
Table 10.
Total EQ-i score and Program Performance ANOVAs
Dependent Variable Source SS df MS F p
Total EQ-I Score Between Groups 1,512.358 2 756.179 6.287 0.003
Within Groups 8,419.20470 120.274
Total 9,931.56272
Within the Intrapersonal subscale, Emotional Self-Awareness (p = .046) and Self-
Actualization (p = .001) demonstrated significant differences at the p = .05 level between
performance groups on the F-test, see Table 11. However, the Tukey Post Hoc tests, found in
Appendix F, only demonstrated significant differences in the Self-Actualization component
between top and bottom performers (p = .001). Nichols (1998), SPSS representative, described
this inconsistency between ANOVAs and Post Hoc tests as follows: while the F-statistic
identified that the intersect between all group means is equal, at least of one of the group means
was unequal which produced a non-significant p-value on the t-Test for Emotional Self-
Awareness. Unfortunately, this inconsistency appeared more often than the researcher would 85 have preferred, so to assist the reader, the researcher included the article by Nichols, entitled
“My Tests Don’t Agree” in Appendix T.
Table 11.
Intrapersonal Subscale and Program Performance ANOVAs
Dependent Variables Source SS df MS F p
Intrapersonal Subscale Between Groups 656.494 2 328.247 2.119 0.128
Within Groups 10,844.13670 154.916
Total 11,500.63072
Self-Regard Between Groups 596.1292 298.065 2.2530.113
Within Groups 9,259.87170 132.284
Total 9,856.00072
Emotional Self-Awareness Between Groups 963.464 2 481.732 3.217 0.046
Within Groups 10,483.16670 149.760
Total 11,446.63072
Assertiveness Between Groups 130.7272 65.363 0.2540.776
Within Groups 17,984.61670 256.923
Total 18,115.34272
Independence Between Groups 77.8412 38.920 0.3350.716
Within Groups 8,132.89970 116.184
Total 8,210.74072
Self-Actualization Between Groups 2,148.143 2 1,074.071 7.184 0.001
Within Groups 10,466.02170 149.515
Total 12,614.16472 86
Within the area of the Interpersonal subscale, the overall subscale (p = .017) and the
Social Responsibility component (p = .046) demonstrated significant differences between performance groups while each of the other components of the subscale, Empathy and
Interpersonal Relationships, was not significant at the p = .05 level, see Table 12. Tukey Post
Hoc tests, as indicated in Appendix F, demonstrated that the differences for both the overall
Interpersonal subscale (p = .012), and Social Responsibility (p = .035) occurred between Top
and Bottom Performers. As indicated in Table 9, the mean scores for Top Performers and the
Interpersonal subscale (M = 103.90) and Social Responsibility (M = 101.55) were significantly
higher than that of the Bottom Performers at (M = 92.94) and (M = 89.17), respectively.
Table 12.
Interpersonal Subscale and Program Performance ANOVAs
Dependent Variables Source SS df MS F p
Interpersonal Subscale Between Groups 1,138.598 2 569.299 4.308 0.017 Within Groups 9,250.74470 132.153 Total 10,389.34272 Empathy Between Groups 857.9802 428.990 2.2530.113 Within Groups 13,328.65070 190.409 Total 14,186.63072 Social Responsibility Between Groups 1,453.287 2 726.643 3.223 0.046 Within Groups 15,782.19370 225.460 Total 17,235.47972 Interpersonal Relationships Between Groups 478.098 2 239.049 1.725 0.186 Within Groups 9,701.27170 138.590 Total 10,179.37072
87
Likewise, the Stress Management subscale demonstrated significant differences between the performance groups (Table 13) on the overall Stress Management subscale scores (p = .032) and Stress Tolerance (p = .023), while Impulse Control was not significant at the p = .05 level.
Tukey Post Hoc tests demonstrated that the differences in the overall Stress Management subscale (p = .033) and Stress Tolerance (p = .017) were significant between top and bottom performers. A review of Table 9 indicates that the mean scores for the Top Performers in both the Stress Management subscale (M = 106.40) and Stress Tolerance (M = 106.95) were significantly higher than those of Bottom Performers, (M = 95.94) and (M = 96.28), respectively.
Table 13.
Stress Management Subscale and Program Performance ANOVAs
Dependent Variables Source SS df MS F p
Stress Management Subscale Between Groups 1,137.266 2 568.633 3.626 0.032
Within Groups 10,976.48770 156.807
Total 12,113.75372
Stress Tolerance Between Groups 1,079.019 2 539.510 3.973 0.023
Within Groups 9,506.10470 135.801
Total 10,585.12372
Impulse Control Between Groups 851.966 2 425.983 1.942 0.151
Within Groups 15,357.51370 219.393
Total 16,209.47972
Within the Adaptability subscale significant differences were found between performance group mean scores. The overall Adaptability subscale (p = .006) and Problem Solving (p = .001) 88
were significant at the p = .05 level, while Reality Testing and Flexibility were not. See Table 14.
Tukey Post Hoc tests, as shown in Appendix F, demonstrated that the differences in the overall
Adaptability subscale scores were significant between Top and Bottom Performers (p = .006), and between Top and Middle Performers (p = .034). Problem Solving scores were also
significant between Top and Bottom Performers (p = .001), and between Top and Middle
Performers (p = .019). Again, a review of Table 9 indicates that the mean score for Top
performers and the Adaptability subscale (M = 106.60) was higher than that of both Middle (M =
98.20) and Bottom (M = 94.39) performers. Problem Solving scores for Top Performers (p =
108.50) were also significantly higher than both the Middle (p = 98.83) and Bottom (p = 92.33)
Performers.
Table 14.
Adaptability Subscale and Program Performance ANOVAs
Dependent Variables Source SS df MS F p
Adaptability Subscale Between Groups 1,537.295 2 768.647 5.578 0.006 Within Groups 9,646.67870 137.810 Total 11,183.97372 Reality Testing Between Groups 968.806 2 484.403 2.811 0.067 Within Groups 12,063.22170 172.332 Total 13,032.02772 Flexibility Between Groups 304.3212 152.161 1.0770.346 Within Groups 9,891.76170 141.311 Total 10,196.08272 Problem Solving Between Groups 2,549.919 2 1,274.959 8.301 0.001 Within Groups 10,751.97170 153.600 Total 13,301.89072 89
Within the General Mood subscale, significant differences were found between the
performance groups (Table 15) and all three of the General Mood subscale variables: overall
General Mood subscale scores (p = .001), Optimism (p = .001), and Happiness (p = .001). The
Levene’s Test for Homogeneity found that equal variance could be assumed for Optimism and a
Tukey Post Hoc test (Appendix F) was used to determine the location of significant mean differences. Significant differences were found between both the Top and Middle Performers (p
= .012) and between the Top and Bottom Performers (p = .001). Equal variance could not be assumed for the overall General Mood subscale and Happiness and Games-Howell Post Hoc tests were performed to assess these unequal variances. Findings indicate that the overall
General Mood subscale mean scores were significantly different between both Top and Middle
Performers (p = .002) and between the Top and Bottom Performers (p = .001). Additionally, a
Games-Howell Post Hoc test found significant difference in the Happiness component between only Top and Bottom Performers (p = .005) A review of Table 9 indicates that the mean score for Top Performers in the General Mood subscale (M = 112.95) was significantly higher than that of both the Middle (M = 104.25) and Bottom (M = 95.56) performers. Optimism scores also demonstrated that the Top Performers mean score (M = 112.15) was significantly higher than that of both Middle (M = 101.17) and Bottom (M = 95.28) performers. Lastly, Happiness scores for Top Performers (M = 111.40) were significantly higher than that of Bottom Performers (p =
96.56). 90
Table 15.
General Mood Subscale and Program Performance ANOVAs
Dependent Variables Source SS df MS Fp
General Mood Subscale Between Groups 2,870.166 2 1,435.083 12.955 0.000
Within Groups 7,754.080 70 110.773
Total 10,624.247 72
Optimism Between Groups 2,859.388 2 1,429.694 8.086 0.001
Within Groups 12,377.133 70 176.816
Total 15,236.521 72
Happiness Between Groups 2,136.098 2 1,068.049 7.619 0.001
Within Groups 9,813.24470 140.189
Total 11,949.34272
Student Leadership Practices Inventory Scores and Program Performance
Table 16 presents the means and standard deviation data for each performance group within each variable of the Student Leadership Practice Inventory. To explore the differences between performance groups, Analyses of Variance (ANOVAs) were performed. See Table 17. 91
Table 16.
Mean Student Leadership Practices Scores by Performance Groups
Student Leadership Practices Bottom Performers Middle Performers Top Performers M SD M SD M SD Modeling the Way 19.89a b 2.948 22.66a 2.807 23.90b 3.076
Inspiring a Shared Vision 20.67c d 3.199 24.06c 3.180 25.05d 3.426
Challenging the Process 20.06e f 2.754 22.40e 3.336 23.45f 3.605
Enabling Others to Act 23.39 2.453 24.69 2.471 24.95 2.564
Encouraging the Heart 22.39 3.987 24.31 3.279 24.70 3.840
The bolded information reports the p-values for each significant pairwise comparison: (a) p = .005, (b) p = .001, (c) p = .002, (d) p = .001, (e) p = .042, and (f) p = .006.
Within the Modeling the Way subscale, significant differences were found between performance groups (p = .001). Tukey Post Hoc tests (Appendix F) indicated that the differences in the Modeling the Way subscale scores were significant between Top and Bottom Performers
(p = .001), and between Middle and Bottom Performers (p = .005), while differences between
Top and Middle Performers were not significant. A review of Table 16 indicates that the mean scores for Top Performers (M = 23.90) and for the Middle Performers (M = 22.66) in Modeling the Way were significantly higher than that of the Bottom Performers (M = 19.55).
The ANOVA conducted for the Inspiring a Shared Vision subscale also found significant differences between the performance groups (p = .001). Tukey Post Hoc tests (Appendix F) indicated that the differences in the Inspiring a Shared Vision subscale scores were significant between Top and Bottom Performers (p = .001), and between Middle and Bottom Performers (p
= .002). The difference between Top and Middle Performers was not significant. A review of
Table 16 indicates that the mean scores for Inspiring a Shared Vision for the Top Performers (M 92
= 25.05) and the Middle performers (M = 24.06) were significantly higher than that for the
Bottom Performers (M = 20.67).
The Challenging the Process subscale also found significant differences between the performance groups (p = .007). Tukey Post Hoc tests (Appendix F) indicated that the differences in the Challenging the Process subscale scores were significant between Top and Bottom
Performers (p = .006), and between Middle and Bottom Performers (p = .042). Likewise, the difference between Top and Middle Performers was not significant. A review of Table 16 indicates that the mean scores for Challenging the Process for both the Top Performers (M =
23.45) and the Middle Performers (M = 22.40) were significantly higher than that for the Bottom
Performers (M = 20.06).
The mean score differences between performance groups and the Enabling Others to Act and Encouraging the Heart subscales were not significant. A review of Table 16 shows minimal variance in the scores between the Enabling Others to Act subscale and Top (M = 24.95), Middle
(M = 24.69) and Bottom (M = 23.39) Performers. Similarly, the mean scores for the Encouraging the Heart subscale demonstrated minimal differences between Top (M = 24.70), Middle (M =
24.31), and Bottom (M = 22.39) Performers. 93
Table 17.
Student Leadership Practices Inventory and Group Performance ANOVAs
Dependent Variables Source SS df MS Fp
Modeling the Way Between Groups 160.290 2 80.145 9.421 0.000
Within Groups 595.463 70 8.507
Total 755.753 72
Inspiring a Shared Vision Between Groups 203.411 2 101.705 9.610 0.000
Within Groups 740.836 70 10.583
Total 944.247 72
Challenging the Process Between Groups 114.829 2 57.414 5.328 0.007
Within Groups 754.29470 10.776
Total 869.12372
Enabling Others to Act Between Groups 27.202 2 13.601 2.190 0.120
Within Groups 434.77170 6.211
Total 461.97372
Encouraging the Heart Between Groups 59.760 2 29.880 2.283 0.109
Within Groups 916.02170 13.086
Total 975.78172
94
Research Question Five: What differences exist between emotional-social intelligence and
leadership practices among each of the following population categories: (a) gender, (b) age, (c)
GPA, (d) academic college, (e) the number of years student leaders have in the four-year program (first, second, third, or fourth), (f) race, (g) mother’s education level, and (h) father’s education level?
Participants in this study were asked to complete a demographic survey (Appendix C), sharing information about their (a) gender, (b) age, (c) GPA, (d) academic college, (e) number of years in the four-year leadership development program, (f) race, (g) mother’s education level, and (h) father’s education level. To identify differences between emotional intelligence and student leadership practices and the aforementioned demographic variables, descriptive statistics were calculated and then a series of t-tests or Analyses of Variance (ANOVAs) were conducted depending on the number of levels of the independent variable tested. The t-tests and ANOVAs first identified whether differences between groups were significant at the .05 level and then a
Levene’s Test of Homogeneity tested for equal variance between groups. Then based on the equality of variance, either a Tukey (Equal Variance Assumed) or a Games-Howell (Equal
Variance Not Assumed) Post Hoc test were conducted to determine specifically which groups differed significantly at p = .05 (Mertler & Vannatta, 2002).
Gender and Emotional Quotient Inventory Scores
Table 18 presents the means for both men and women participants within each variable of the Emotional Quotient Inventory (EQ-i). To explore the differences between men and women participants, t-tests were performed. Simple observation of the average means between males and females identifies that the mean scores for nearly all EQ-i variables were higher for women than men, except for Emotional Self-Awareness and Flexibility. However, after conducting the t-tests, only Self-Actualization (t = -2.423, df = 71, p = .018) was significantly higher for women than for men. Refer to Appendix G for full lists of t-test scores for EQ-i gender p-values. 95
Table 18.
Mean Emotional Quotient Inventory Scores by Gender
Emotional Quotient Inventory Male Female M SD M SD Total EQ-i Score 99.54 11.881 103.13 11.577 Intrapersonal Subscale 102.61 10.979 106.71 13.446 Self-Regard 103.82 8.990 108.98 12.805 Emotional Self-Awareness 103.57 11.074 101.24 13.520 Assertiveness 100.50 15.952 101.56 15.972 Independence 101.25 8.661 104.67 11.662 Self-Actualization * 101.93 14.353 109.40 11.764 Interpersonal Subscale 98.07 12.637 99.33 11.726 Empathy 96.82 13.875 96.89 14.293 Social Responsibility 94.71 16.325 96.16 15.079 Interpersonal Relationships 102.54 12.207 103.78 11.803 Stress Management Subscale 98.54 13.459 101.42 12.684 Stress Tolerance 99.39 12.170 103.44 11.969 Impulse Control 97.86 14.501 98.73 15.462 Adaptability Subscale 98.46 12.621 100.24 12.457 Reality Testing 96.43 12.671 98.71 13.986 Flexibility 101.50 11.157 101.42 12.464 Problem Solving 98.46 13.060 100.76 13.986 General Mood Subscale 101.46 13.245 106.38 11.150 Optimism 99.93 15.360 104.47 13.908 Happiness 101.93 13.955 107.16 11.890 * Bold - Significant at p<.05
96
Gender and Student Leadership Practices Scores
Table 19 presents the mean scores for both male and female participants within each of
the five subscales of the Student Leadership Practices Inventory (S-LPI). A t-test was conducted
to assess the differences between male and female mean scores and no statistically significant
differences were identified.
Table 19.
Mean Student Leadership Practices Scores by Gender
S-LPI Subscales Male Female M SD M SD Modeling the Way 21.96 4.041 22.53 2.651
Inspiring a Shared Vision 23.36 4.201 23.58 3.258
Challenging the Process 22.21 3.552 22.04 3.464
Enabling Others to Act 24.32 3.068 24.51 2.170
Encouraging the Heart 23.82 4.028 24.02 3.493
*** No significant differences were identified.
Age and Emotional Quotient Inventory Scores
In terms of age, participants were separated into five age groups: 18 (n = 10), 19 (n = 13),
20 (n = 24), 21 (n = 20), and 22 (n = 5). One participant was 23 and was dropped from the
analysis. Table 20 presents the mean scores of the Emotional Quotient Inventory for each of the
five age groups. Analyses of Variance (ANOVAs) identified statistically significant differences between age groups and the following EQ-i categories: total EQ-i Scores, F(4, 67) = 2.689, p =
.038; Interpersonal Subscale, F(4, 67) = 3.533, p = .011; Empathy, F(4, 67) = 4.233, p = .004;
Problem Solving, F(4, 67) = 2.629, p = .042: the General Mood subscale, F(4, 67) = 2.835, p =
.042 (Levene’s not assumed equal); Happiness, F(4, 67) = 3.387, p = .014. Complete ANOVA 97
table and Tukey Post Hoc tests are found in Appendixes H and I. Tukey Post Hoc tests were
conducted to determine the significant differences between age groups. Within the total EQ-i
scores, 21-year-old participants scored significantly higher than 18-year-old participants (p =
.049). With the Interpersonal subscale, 22-year-old participants scored significantly higher than
18-year-old participants (p = .003). Within the Empathy component, 22-year-old participants
scored significantly higher than each of the following groups: 18 (p = .001), 20 (p = .011), and
21 (p = .022). However, the Problem Solving component produced statistical significance (p =
.042) at the ANOVA stage, but rendered no individual differences between group means with the
Tukey HSD test. Similarly, with the General Mood subscale a Games-Howell Post Hoc showed no significant group differences at the p = .05 level. As discussed earlier, dichotomies between
F-values and t-values are not uncommon and can be explained as these two variables demonstrated significant difference between all age groups, but did not identify pairwise differences between individual groups. Finally, in the Happiness component both 20-year-olds (p
= .010) and 21-year-olds (p = .017) scored significantly higher than 18-year-olds. Overall, within the aforementioned emotional-social intelligence variables, scores increased with the age for this sample. 98
Table 20.
Mean Emotional Quotient Inventory Scores by Age
Emotional Quotient Inventory 18 19 20 21 22 MMMM M Total EQ-i Score 93.60a 98.85 102.50 105.80a 108.60 Intrapersonal Subscale 97.30 101.69 106.83 109.10 109.00 Self-Regard 103.70 103.62 108.42 108.40 112.00 Emotional Self-Awareness 95.80 98.08 102.25 108.25 104.40 Assertiveness 95.20 98.69 100.38 106.85 104.00 Independence 99.10 103.46 104.96 104.20 103.80 Self-Actualization 96.50 104.23 109.92 107.65 112.20 Interpersonal Subscale 91.30b 99.15 99.17 98.80 114.40b Empathy 88.20c 98.54 95.46d 96.80e 117.00c,d,e Social Responsibility 87.80 93.00 96.42 95.95 111.60 Interpersonal Relationships 97.90 104.46 103.88 102.90 114.60 Stress Management Subscale 96.30 99.31 99.92 104.00 100.20 Stress Tolerance 94.90 102.38 102.38 104.95 102.40 Impulse Control 97.80 96.00 97.54 101.80 97.20 Adaptability Subscale 95.10 95.92 98.00 105.30 103.80 Reality Testing 91.60 95.23 96.17 104.60 99.40 Flexibility 102.20 100.85 100.83 102.75 100.80 Problem Solving 94.50 94.38 98.54 105.30 109.80 General Mood Subscale 95.20 101.92 106.33 107.65 111.80 Optimism 98.00 98.62 102.67 106.05 111.60
Happiness 93.20f,g 104.15 108.38f 108.05g 109.00 The bolded information reports the p-values for each significant pairwise comparison: (a) p = .049, (b) p = .003, (c) p = .001, (d) p = .011, (e) p = .022, (f) p = .010, and (g) p = .017.
99
Age and Student Leadership Practices Inventory Scores
In terms of the Student Leadership Practice Inventory, no statistically significant
differences were identified through Analyses of Variance (ANOVAs) between age groups and S-
LPI scores. As indicated in Table 21, on average, the mean scores for the S-LPI increase with
age, however the increases were not significant at p = .05.
Table 21.
Mean Student Leadership Practices Scores by Age
Student Leadership Practices Inventory 18 19 20 21 22 MMM M M Modeling the Way 20.80 21.31 22.21 23.30 24.60
Inspiring a Shared Vision 23.00 22.31 23.63 23.90 25.60
Challenging the Process 21.50 20.15 22.63 22.40 24.40
Enabling Others to Act 22.90 24.15 24.63 24.75 26.00
Encouraging the Heart 22.60 23.92 24.38 22.90 27.60
*** No significant differences were identified.
GPA and Emotional Quotient Inventory Scores
In terms of GPA and Emotional Quotient Inventory scores, GPA scores were clustered
into four categories: 1.50 – 2.49 (n = 11), 2.50 – 2.99 (n = 15), 3.00 – 3.49 (n = 21), and 3.50 –
4.00 (n = 23). Three participants did not report their current GPA. Table 22 presents the mean scores for the Emotional Quotient Inventory and for each of the four GPA groups. Analyses of
Variance (ANOVAs) identified statistically significant differences between GPA groups and the following EQ-i categories: Total EQ-i scores, F(3, 66) = 2.746, p = .050; Self-Actualization, F(3,
66) = 4.219, p = .009; Problem Solving, F(3, 66) = 5.554, p = .002; the General Mood subscale,
F(3, 66) = 4.306, p = .008; Optimism, F(3, 66) = 5.058, p = .003; and Happiness, F(3, 66) = 100
3.315, p = .025. Complete ANOVA table and Post Hoc test for GPA groups and EQ-i are listed
in Appendix J. Tukey Post Hoc tests (equal variance assumed) and Games-Howell Post Hoc tests
(equal variance were not assumed) are listed in Appendix K. Post hoc tests found that students
with GPAs 3.50 and above had higher scores than the students with GPAs between 1.50 – 2.49 in
the total EQ-i (p = .050) and Self-Actualization (p = .005). Within the Problem Solving component students with GPAs 3.50 and above scored significantly higher than the following
GPA clusters: 1.50 – 2.49 (p =.002) and 3.00 – 3.49 (p = .038). Likewise, within the General
Mood subscale, students 3.50 and above scored significantly higher than both 1.50 – 2.49 (p
=.012) GPA cluster and the 2.50 – 2.99 (p = .044) GPA cluster. Similarly, within the Optimism component the 3.50 – 4.00 GPA cluster scored significantly higher than both 1.50 – 2.49 (p
=.004) GPA cluster and the 3.00 – 3.49 (p = .040) GPA cluster. The Happiness component failed the Levene’s Test of Homogeneity and a Games-Howell Post Hoc test found no significant differences between GPA cluster groups and Happiness. 101
Table 22.
Mean GPA Cluster Scores for Emotional Quotient Inventory
Dependent Variables 1.50 – 2.49 2.50 – 2.99 3.00 – 3.49 3.50 – 4.00 MMM M Total EQ-i Score 96.36a 100.47 100.86 107.22a
Intrapersonal Subscale 102.09 102.00 104.67 109.65
Self-Regard 102.55 107.87 104.95 111.17
Emotional Self-Awareness 102.82 96.53 100.52 107.39
Assertiveness 104.27 98.87 99.33 101.65
Independence 103.55 99.13 105.29 104.22
Self-Actualization 96.82b 105.00 108.00 112.39b
Interpersonal Subscale 94.55 100.00 97.71 102.09
Empathy 92.18 100.33 96.29 99.04
Social Responsibility 86.91 100.07 93.86 99.30
Interpersonal Relationships 103.55 102.53 101.86 105.61
Stress Management Subscale 95.36 99.87 99.29 105.00
Stress Tolerance 95.00 100.33 102.67 106.52
Impulse Control 96.55 98.80 96.24 101.96
Adaptability Subscale 94.91 100.07 97.19 105.43
Reality Testing 94.73 98.73 95.29 102.70
Flexibility 102.55 98.67 101.67 104.09
Problem Solving 89.91c 102.80 96.67d 107.04c,d
General Mood Subscale 97.73e 100.87f 104.52 111.04e,f
Optimism 93.09g 104.00 99.05h 110.61g,h
Happiness 102.00 98.00 108.33 109.43 The bolded information reports p-values for each pairwise comparison: (a) p = .050, (b) p = .005, (c) p = .002, (d) p = .038, (e) p = .012, (f) p = .044, (g) p = .004, and (h) p = .030. 102
GPA and Student Leadership Practices Inventory Scores
In terms of participant GPA and Student Leadership Practices scores, Table 23 presents the mean scores for the Student Leadership Practices Inventory and each of the four GPA groups.
Analyses of Variance (ANOVAs) identified statistically significant difference between GPA groups and only one of the S-LPI subscales: Inspiring a Shared Vision, F(3, 65) = 3.714, p =
.016. A complete ANOVA table for GPA groups and the S-LPI is listed in Appendix K. Tukey
Post Hoc tests were conducted to determine where mean differences were statistically significant between GPA clusters. For Inspiring a Shared Vision, students with GPAs above 3.50 score significantly higher than those students with in the 1.50 – 2.49 GPA cluster group (p = .018).
Table 23.
Mean GPA Cluster Scores for the Student Leadership Practices Inventory
Dependent Variables 1.50 – 2.49 2.50 – 2.99 3.00 – 3.49 3.50 – 4.00 MMM M Modeling the Way 20.73 22.33 22.14 23.43
Inspiring a Shared Vision 20.91* 23.53 23.48 24.83*
Challenging the Process 19.91 22.33 22.24 22.96
Enabling Others to Act 23.18 25.13 24.76 24.65
Encouraging the Heart 22.18 24.07 24.33 24.52
* Bold - Pairwise significance at p = .018.
Academic Colleges, Student Leadership Practices and the Emotional Quotient Inventory
With regards to the Academic College where participants were enrolled, Analyses of
Variance (ANOVAs) were conducted and identified no statistically significant differences between Academic Colleges. See Appendix L.
103
Number of Years in the Four-Year Leadership Development Program and EQ-i scores
In terms of the number of years the participant has been enrolled in the program,
participants were clustered into four cohort groups: First-Year (n = 20), Second-Year (n = 16),
Third-Year (n = 25), and Fourth and Fifth Year combined (n = 12). Table 24 presents the mean
scores for the Emotional Quotient Inventory and each of the four cohorts. Analyses of Variance tests (ANOVAs) identified statistically significant difference between cohorts on the following
EQ-i variables: total EQ-i score, F(3, 69) = 3.727, p = .015; Intrapersonal Subscale, F(3, 69) =
2.988, p = .037; Emotional Self-Awareness, F(3, 69) = 3.734, p = .015; the Adaptability subscale,
F(3, 69) = 3.766, p = .015; Reality Testing, F(3, 69) = 6.555, p = .001; Problem Solving F(3, 69)
= 3.419, p = .022; the General Mood subscale, F(3, 69) = 3.891, p = .013 (Equal variance not assumed); and Happiness, F(3, 69) = 3.101, p = .032 (Equal variance not assumed). Complete
ANOVA tables and Tukey Post Hoc tables for cohorts and EQ-i are listed in Appendixes M and
N. Tukey Post Hoc tests were conducted to determine where EQ-i variables’ mean differences were statistically significant between cohorts. For those variables that failed the Levene’s Test of
Homogeneity, Games-Howell Post Hoc tests were conducted. The Third-Year Cohort scored significantly higher than the First-Year Cohort in the following variables: total EQ-i scores (p =
.009), the Intrapersonal subscale (p = .025), Emotional Self-Awareness (p = .025), and the
Adaptability subscale (p = .022). Likewise, the Third-Year cohort scored significantly higher
than both the First-Year cohort (p = .012) and Second-Year cohort (p = .001) in Reality Testing
component. Within the Problem Solving component the Fourth and Fifth-Year cohort scored
significantly higher than the First-Year Cohort (p = .010). The Games-Howell Post Hoc test was
used to determine differences between the cohorts on variables with which equal variance could
not be assumed. Within the General Mood subscale, the Third-Year cohort scored significantly 104 higher than the First-Year cohorts (p = .014). After running the Games-Howell Post Hoc test, however, no significant differences were found between specific cohorts and the Happiness component. In summary, most pairwise differences identified that the Third-Year cohort scored significantly higher than the First-Year cohort. 105
Table 24.
Mean Year in Program Cohort Scores for the Emotional Quotient Inventory
Dependent Variables 1st Year 2nd Year 3rd Year 4th / 5th Year MMM M Total EQ-i Score 95.80a 100.25 106.68a 103.42
Intrapersonal Subscale 99.60b 103.31 110.20b 106.25
Self-Regard 103.10 107.50 110.12 106.33
Emotional Self-Awareness 97.25c 97.88 107.68c 104.42
Assertiveness 98.00 97.06 106.00 101.75
Independence 100.15 104.56 106.00 101.58
Self-Actualization 101.20 106.06 109.36 110.17
Interpersonal Subscale 95.45 98.94 99.72 102.58
Empathy 93.25 98.69 95.40 103.50
Social Responsibility 90.15 96.94 95.88 102.33
Interpersonal Relationships 101.30 102.38 105.36 103.58
Stress Management Subscale 96.75 99.94 104.08 98.92
Stress Tolerance 96.95 104.19 105.52 99.50
Impulse Control 96.90 95.19 101.72 98.25
Adaptability Subscale 94.70d 95.44 105.16d 101.50
Reality Testing 94.10e 89.63f 105.64e, f 98.75
Flexibility 100.75 98.75 104.68 99.50
Problem Solving 92.35g 101.50 101.96 105.92g
General Mood Subscale 97.35h 107.31 108.44h 104.42
Optimism 95.85 105.44 105.76 104.25
Happiness 98.65 108.00 109.24 103.67 The bolded information reports the p-values for each significant pairwise comparison: (a) p = .009, (b) p = .025, (c) p = .025, (d) p = .022, (e) p = .012, (f) p = .001, (g) p = .027, and (h) p = .010. 106
Number of Years in the Four-Year Leadership Development Program and S-LPI Scores
In terms of the number of years the participant has been enrolled in the program and
Student Leadership Practices, Table 25 presents the mean scores for each of the four cohort groups. ANOVAs identified no statistically significant differences between cohorts and S-LPI subscales.
Table 25.
Mean Year in Program Cohort Scores for the Student Leadership Practice Inventory
Dependent Variables 1st Year 2nd Year 3rd Year 4th / 5th Year MM M M Modeling the Way 21.10 22.00 22.68 24.00
Inspiring a Shared Vision 22.30 24.75 23.16 24.50
Challenging the Process 20.55 23.19 22.12 23.25
Enabling Others to Act 23.55 24.25 25.12 24.75
Encouraging the Heart 23.20 24.25 23.52 25.67
*** No significant differences were identified.
Race and EQ-i scores
With respect to racial differences and Emotional Quotient Inventory scores, participants were clustered into two groups: Students of Color (n = 42) and White Students (n = 31). It is noteworthy that the racial diversity in this particular sample is far more equivalent than that in the student population found at the participating students’ Midwestern state university, where the student body is predominantly White. Table 26 presents the mean scores for the Emotional
Quotient Inventory and the two race categories. Independent t-tests found significant differences between racial groups and the following EQ-i variables: Assertiveness, (t = -2.152, df = 71, p =
.035); Self-Actualization, (t = 2.156, df = 71, p = .035); the Stress Management subscale, (t = 107
2.017, df = 71, p = .047); and Impulse Control, (t = 2.118, df = 71, p = .038); the General Mood subscale, (t = 2.520, df = 71, p = .014); and Happiness, (t = 2.397, df = 71, p = .019). A complete t-Test table for racial groups and EQ-i is listed in Appendix O. Students of Color scored significantly higher than White students in the Assertiveness component, while White students scored significantly higher than Students of Color in Self-Actualization, the Stress Management subscale, Impulse Control, the General Mood subscale, and Happiness. 108
Table 26.
Mean Emotional Quotient Inventory Scores by Racial Group
EQ-i Variables White Students Students of Color MSDM SD Total EQ-i Score 103.87 10.664 100.19 12.375
Intrapersonal Subscale 105.03 11.203 105.21 13.735
Self-Regard 107.81 10.477 106.40 12.618
Emotional Self-Awareness 102.74 11.556 101.69 13.454
Assertiveness * 96.61 15.788 104.50 15.245
Independence 101.55 8.992 104.69 11.696
Self-Actualization * 110.16 10.511 103.86 14.475
Interpersonal Subscale 101.55 11.781 96.86 11.928
Empathy 99.35 14.018 95.02 13.931
Social Responsibility 99.26 14.360 92.90 15.873
Interpersonal Relationships 104.61 11.735 102.33 12.052
Stress Management Subscale * 103.81 10.410 97.74 14.147
Stress Tolerance 103.81 10.438 100.48 13.177
Impulse Control * 102.32 9.881 95.50 17.426
Adaptability Subscale 101.13 11.644 98.40 13.052
Reality Testing 98.32 12.191 97.48 14.450
Flexibility 102.39 13.032 100.76 11.102
Problem Solving 102.52 12.756 97.93 14.008
General Mood Subscale * 108.52 10.462 101.52 12.561
Optimism 105.94 11.843 100.36 15.983
Happiness * 109.23 10.911 102.14 13.510 * Bold - Significant at p<.05 109
Race and Student Leadership Practices Scores
Regarding racial differences and Student Leadership Practices Inventory, Table 27 presents the mean scores for the Student Leadership Practices Inventory subscales and the two
race categories. Independent t-tests found that White students scored significantly higher than
Students of Color in the following S-LPI categories: the Modeling the Way subscale (t = 2.517,
df = 71, p = .014); and the Challenging the Process subscale, (t = 2.362, df = 71, p = .021).
Table 27.
Mean Student Leadership Practices Inventory Scores by Racial Group
S-LPI Variables White Students Students of Color MSDM SD Modeling the Way * 23.39 3.148 21.52 3.110
Inspiring a Shared Vision 24.39 3.490 22.83 3.615
Challenging the Process * 23.19 3.420 21.31 3.331
Enabling Others to Act 24.65 2.665 24.29 2.452
Encouraging the Heart 24.87 3.324 23.26 3.819
* Bold - Significant at p<.05
Mother’s Education Level, EQ-i Scores, and S-LPI Scores
In terms of the evaluation of Mother’s Education Level, participants were clustered into three groups: (a) Without a College Degree (n = 36), (b) with a Two- or Four-Year Degree (n =
23), or (c) with a postgraduate degree (n = 14). Tables 28 and 29 present the mean EQ-i scores and S-LPI scores respectively for each of the three Mother’s Education groups. Analyses of
Variance (ANOVAs) found no statistically significant difference between Student Leadership
Practice Inventory scores and the Mother’s Education Levels. However, ANOVAs did identify significant differences between Mother’s Education Levels and the following EQ-i variables: the 110
Interpersonal subscale, F(2, 70) = 3.396, p = .039; Empathy, F(2, 70) = 4.396, p = .016; the
Stress Management subscale, F(2, 70) = 3.981, p = .023; and Impulse Control F(2, 70) = 4.138, p
= .020. Tukey HSD tests found significant differences between participants with mothers who did not have a college degree and those who had mothers with a postgraduate degree in the following three EQ-i variables the Interpersonal subscale (p = .031), Empathy (p = .019), and
Impulse Control (p = .026). Those students whose mothers have a post graduate degree scored significantly higher than those students whose mothers have no college degree. Notice that, due to a statistical anomaly, post hoc tests did not reveal any significant differences among groups on the Stress Management subscale (p = .053). See Appendixes P and Q for complete ANOVA tables and Post Hoc tests. 111
Table 28.
Mean Emotional Quotient Inventory Scores by Mother’s Education Level
Dependent Variables No College Two- or Four- Postgraduate Degree Year Degree Degree M SD M SD M SD Total EQ-i Score 99.06 11.737 103.87 10.657 105.21 12.644
Intrapersonal Subscale 104.31 12.946 106.26 12.498 105.43 12.841 Self-Regard 104.64 12.695 109.26 10.498 109.36 10.360 Emotional Self-Awareness 102.67 11.125 101.30 13.123 102.14 15.932 Assertiveness 101.31 17.697 101.22 16.059 100.64 10.653 Independence 103.31 12.042 103.43 10.413 103.36 7.592 Self-Actualization 106.14 14.102 108.35 10.701 104.57 15.190 Interpersonal Subscale 95.89a 12.855 99.52 10.879 105.36a 9.128 Empathy 92.47b 14.433 99.26 13.417 104.21b 10.199 Social Responsibility 91.69 17.360 98.87 13.240 100.29 11.532 Interpersonal Relationships 102.31 12.542 101.30 10.585 109.14 11.107 Stress Management Subscale 96.19 13.242 103.61 10.339 105.50 13.552 Stress Tolerance 99.61 12.470 104.83 11.292 102.93 12.206 Impulse Control 93.78c 15.623 101.09 12.649 105.86c 13.682 Adaptability Subscale 97.81 12.515 100.52 10.799 102.50 14.893
Reality Testing 96.75 14.223 97.43 12.558 101.29 13.211 Flexibility 101.19 10.381 100.78 12.771 103.21 14.624 Problem Solving 96.92 13.166 103.48 13.908 101.57 13.375 General Mood Subscale 102.64 12.753 107.22 10.379 104.79 13.204 Optimism 101.25 16.417 105.39 13.027 102.14 11.844 Happiness 102.94 13.567 107.87 9.716 106.36 15.355 The bolded information reports the p-values for each significant pairwise comparison: (a) p = .031, (b) p = .019, and (c) p = .026.
112
Table 29.
Mean Student Leadership Practices Inventory Scores by Mother Education Levels
Dependent Variables No College Two- or Four- Postgraduate Degree Year Degree Degree M SD M SD M SD Modeling the Way 22.28 3.575 22.74 2.615 21.71 3.384
Inspiring a Shared Vision 23.31 3.487 24.39 3.487 22.50 4.090
Challenging the Process 22.06 3.355 22.91 3.813 20.93 3.050
Enabling Others to Act 24.14 2.830 24.61 2.330 24.93 2.056
Encouraging the Heart 23.31 3.853 24.48 3.449 24.71 3.561
*** No significant differences were identified.
Father’s Education Level, EQ-i scores, and S-LPI scores
In terms of the evaluation of Father’s Education Level, Emotional Quotient Inventory scores, and Student Leadership Practices Inventory scores, participants were clustered into three groups depending on the their Father’s Education Level: (a) Without a College Degree (n = 34),
(b) with a Two- or Four-Year Degree (n = 23), or (c) with a Postgraduate Degree (n = 14). Two participants did not list a Father’s Education Level. Tables 30 and 31 present the mean EQ-i scores and S-LPI scores respectively for each of the three Father’s Education categories.
Analyses of Variance (ANOVAs) found no statistically significant difference between Emotional
Quotient Inventory scores and the three Father’s Education Levels. See Appendix R. However,
ANOVA testing did identify significant differences between Father’s Education Levels and the following S-LPI variables: Inspiring a Shared Vision, F(2, 68) = 3.157, p = .049; Challenging the Process, F(2, 68) = 3.755, p = .028; Enabling Others to Act, F(2, 68) = 3.630, p = .032; and
Encouraging the Heart, F(2, 68) = 3.780, p = .028. Tukey HSD tests found that participants with fathers who have a Two- or Four-Year Degree scored significantly higher than those participants 113 whose father did not have a college degree: Inspiring a Shared Vision (p = .047), Challenging the Process (p = .049), and Encouraging the Heart (p = .022). Additionally, a Tukey HSD test found that participants with fathers who have Postgraduate Degrees scored significantly higher than those participants whose father had a Two- or Four-year Degree in the Enabling Others to
Act subscale See Appendixes R and S for complete ANOVA tables and Post Hoc tests.
Table 30.
Mean Student Leadership Practice Inventory Scores by Father’s Education Level
No College Two or Four Year Post Graduate Dependent Variables Degree Degree Degree MSDMSD MSD Modeling the Way 22.09 3.232 23.35 3.113 20.93 3.245
Inspiring a Shared Vision 22.62a 3.508 24.91a 3.161 22.86 4.016
Challenging the Process 21.44b 3.164 23.61b 3.327 21.00 3.783
Enabling Others to Act 24.35 2.485 25.48c 2.484 23.29c 2.268
Encouraging the Heart 23.03d 4.041 25.65d 3.113 23.71 2.920
The bolded information reports the p-values for each significant pairwise comparison: (a) p = .047, (b) p = .049, (c) p = .027, and (d) p = .022. 114
Table 31.
Mean Emotional Quotient Inventory Scores by Father’s Education Level
No College Two or Four Year Post Graduate Dependent Variables Degree Degree Degree MSDMSD MSD Total EQ-i Score 99.88 10.843 104.30 12.794 101.43 12.817
Intrapersonal Subscale 104.74 12.783 106.09 13.584 103.14 11.615 Self-Regard 106.12 10.502 107.70 13.766 106.2911.458 Emotional Self-Awareness 101.21 12.718 102.91 12.365 101.71 13.059 Assertiveness 100.29 16.199 103.61 17.341 98.4313.899 Independence 104.82 11.582 101.48 8.538 103.2912.168 Self-Actualization 106.38 14.370 108.35 10.986 102.0013.548 Interpersonal Subscale 95.53 12.592 103.09 10.255 100.29 12.325 Empathy 94.41 13.667 102.43 12.135 96.7914.771 Social Responsibility 92.97 15.730 99.78 10.821 96.21 20.276 Interpersonal Relationships 100.21 13.084 105.87 9.767 105.21 11.423 Stress Management Subscale 97.88 10.333 101.48 15.762 104.21 14.305 Stress Tolerance 100.26 10.983 103.39 13.671 102.71 13.286 Impulse Control 95.94 13.269 98.96 17.915 104.00 14.229 Adaptability Subscale 98.09 11.753 102.00 13.847 99.00 12.800 Reality Testing 96.56 13.656 99.09 13.996 98.57 12.924 Flexibility 101.32 11.135 102.78 10.167 100.0016.966 Problem Solving 97.65 11.497 103.48 17.622 99.00 11.149 General Mood Subscale 103.29 9.741 107.70 12.088 99.71 15.429 Optimism 101.50 13.097 106.43 16.211 98.1414.909 Happiness 103.76 12.053 107.74 9.905 101.4317.069 *** No significant differences were identified. 115
CHAPTER V. DISCUSSION AND CONCLUSION
As an aid to the reader, this chapter will start with a review of the purpose, statement of
the problem, and the primary methodology used in this study, followed by a brief summary of the results for each of the five research questions. Afterward, this chapter presents a discussion and interpretation of the results, as well as how these results related to previous research.
Subsequently, training and curriculum development recommendations for leadership development educators and professionals will be provided. The chapter concludes with implications for future research.
As discussed in Chapter 1, many leadership development programs at colleges and universities are founded on leadership studies and training models that were developed for post- graduate management and leadership settings in private and public-sector organizations (Posner
& Brodsky, 1992; Kouzes & Posner, 1998; Posner, 2004). Kouzes and Posner’s (2005) Student
Leadership Practices Inventory (S-LPI) is a leadership assessment tool that was initially created for corporate leadership settings and then later modified to fit student leadership environments.
The S-LPI is a popular tool to assist the advancement of relational leadership skills among college student leaders (Posner & Brodsky, 1993; Kouzes & Posner, 1998). See Appendix E for a copy of the S-LPI. Likewise, emotional intelligence, as reviewed in Chapter 2, is a construct that has gained popularity among researchers in the area of leadership effectiveness (Higgs,
2002; Goleman, et al., 2002; Caruso & Salovey, 2004). Inspired by growing empirical evidence associating emotional intelligence with leadership effectiveness in postgraduate settings, and the common application of Kouzes and Posner’s model in college student leadership programs, the current study explored the relationships between leadership practices and Emotional-Social
Intelligence (ESI) among college students enrolled in a university-sponsored, cocurricular, four- 116
year leadership development program at a Midwestern University. Also, a modified 360-degree
method was used to determine if the students’ self-reported scores (EQ-i and S-LPI) were
supported by an external assessment of their performance within the leadership development
program. To gain more insight about both ESI and leadership practices, participants were asked
to complete a demographic survey that included items regarding gender, age, race, current GPA,
academic college, year in the four-year leadership program, mother’s education level, and father’s education level. In terms of data analyses, bivariate correlations were used to assess the relationships between EQ-i and S-LPI variables; and then Analyses of Variance (ANOVAs) and t-tests were employed to identify significant differences between demographic clusters and performance groups.
Summary of the Results
The following summary of results provides a synopsis of the present study’s findings.
Within the Emotional Quotient Inventory scores, the present study found that this sample demonstrated “average or usually adaptive emotional capacity” (scores between 95 and 105) on total EQ-i scores and all five of the emotional-social intelligence subscales. Scores identified that this sample had higher than average (M ≥ 100) scores in the Intrapersonal, General Mood and
Stress Management Subscales, while the Adaptability and Interpersonal subscales demonstrated
lower than average scores (M < 100). Concerning the 15 EQ-i components, this sample scored
the highest in Self-Regard, Self-Actualization, and Happiness (M ≥ 105) which represents a
“high average or well developed emotional capacity” in those components (Table 5), while the rest of the components scored in the “average or usually adaptive emotional capacity” category.
The lowest mean scores that were closest to the “low average or underdeveloped emotional
skills” (scores between 90 and 95) category, were found in the Empathy and Social 117
Responsibility components. Both of these components are part of the Interpersonal subscale. In brief, except for the aforementioned subscales and components, the participant mean scores for
Emotional-Social Intelligence were considered average as interpreted by the EQ-i interpretive guidelines found in Table 5 (Bar-On, 2002, p. 202). According to Kouzes and Posner’s guidelines, this sample of students enrolled in the four-year leadership development program scored well within the “Moderate” range for the Student Leadership Practices Inventory subscales.
Overall, the relationship between the total Emotional Quotient Inventory scores and
Student Leadership Practices Inventory scores produced moderate to strong positive correlations.
The S-LPI subscale, Encouraging the Heart produced the fewest correlations, and on average the
Intrapersonal and Stress Management subscales for the EQ-i produced the weakest Pearson r correlations with S-LPI construct. The Interpersonal, General Mood, and Adaptability subscales produced, on average, moderate correlations with the S-LPI construct. To further demonstrate the relationships between the two constructs, each of the five S-LPI subscales are presented in the next several paragraphs in relation to their identified r-scores with the 15 components of the
EQ-i.
The Modeling the Way subscale correlated significantly with every EQ-i variable except
Assertiveness, Independence, and Impulse Control. Strong correlations were found with
Optimism, total EQ-i scores, the General Mood subscale, Self-Actualization, and Problem
Solving at the p = 0.01 level. Overall, the Modeling the Way subscale correlated either strongly or moderately with each of the five EQ-i subscales.
Inspiring a Shared Vision correlated strongly with Optimism and Problem Solving and moderately with total EQ-i scores, the Intrapersonal subscale, Assertiveness, Emotional Self- 118
Awareness, Self-Actualization, the Interpersonal subscale, Interpersonal Relationships, Stress
Tolerance, the Adaptability subscale, and the General Mood subscale. Non-significant
correlations were identified with Independence, the Stress Management subscale, Impulse
Control, Reality Testing, and Happiness. Results of Pearson r correlations indicated that
moderate to strong relationships exist between the Emotional-Social Intelligence construct and
the Inspiring a Shared Vision subscale.
The Challenging the Process subscale correlated strongly with Optimism and moderately
with the total EQ-i score, the Intrapersonal subscale, Self-Regard, Assertiveness, Self-
Actualization, Stress Tolerance, Problem Solving, and General Mood subscale. The variables
that did not correlate significantly with Challenging the Process were Emotional Self-Awareness,
Independence, Empathy, Interpersonal Relationships, the Stress Management subscale, Impulse
Control, Reality Testing, and Flexibility.
The Enabling Others to Act subscale correlated strongly with the total EQ-i scores, the
Interpersonal subscale, Empathy, Social Responsibility, and the Adaptability subscale.
Additionally, moderate correlations were found with Self-Actualization, Reality Testing,
Flexibility, Problem Solving, the General Mood subscale, and Optimism. In contrast, non- significant relations were identified with Self-Regard, Emotional Self-Awareness, Assertiveness,
Independence, Interpersonal Relationships, and Happiness.
Finally, the Encouraging the Heart subscale correlated strongly with the Interpersonal
subscale, Empathy, Social Responsibility, and moderately with Problem Solving. Several EQ-i
variables produced non-significant relationships with Encouraging the Heart, but Assertiveness
and Independence produced non-significant, weak, negative relationships. Even though this
subscale correlated with fewer components, the identified strong relationships with the 119
Interpersonal Subscale established a significant relationship with the emotional-social
intelligence construct.
Student Leadership Performance: EQ-i and S-LPI Scores
Study results indicated that the student leaders’ scores on both the Emotional Quotient
Inventory and the Student Leadership Practices Inventory were supported by an external
assessment of their performance within the four-year student leadership development program.
The director of the Student Leadership program placed students enrolled in the program into Top
and Bottom Performance groups and the rest of the participants became the Middle Performance
group. Top Performers scored statistically higher than both the Middle and Bottom Performers in
the following emotional-social intelligence variables: the total EQ-i score, the Adaptability subscale, Problem Solving, the General Mood subscale, and Optimism. Additionally, Top
Performers scored statistically higher than only Bottom Performers within the following
variables: Self-Actualization, the Interpersonal subscale, Social Responsibility, the Stress
Management subscale, Stress Tolerance, and Happiness. It is also important to note that, while not statistically significant, the Independence and Assertiveness components were the only two components where Bottom Performer means scores were higher than the Top Performers. In review, Top Performers have higher emotional-social intelligence than other participants in Self-
Actualization, Social Responsibility, Stress Tolerance, Problem Solving, Optimism and
Happiness.
In terms of the Student Leadership Practices Inventory, both Top Performers and Middle
Performers scored significantly higher than Bottom Performers in Modeling the Way, Inspiring a
Shared Vision, and Challenging the Process. Conversely, the differences between Enabling 120
Others to Act and Encouraging the Heart scores were not significant among the three performance groups.
Demographic Differences and EQ-i and S-LPI scores
In terms of gender and EQ-i differences, the only difference found to be statistically significant between men and women was that women scored significantly higher in the Self-
Actualization component. And with the S-LPI, no statistically significant differences were identified between men and women. In reference to age, 21-year-old students scored significantly higher than 18-year-old student in overall EQ-i scores and the Interpersonal subscale. Additionally, 22-year-old students scored significantly higher in Empathy than the 21-,
20-, and 18-year-old students. Moreover, 20- and 21-year-old students scored significantly
higher than 18-year-old students within the Happiness component.
In terms of GPA, students with GPAs of 3.50 or higher scored significantly higher than
students with GPAs between 1.50-2.49 in Total EQ-i scores and Self-Actualization. Furthermore,
students who had a GPA of 3.50 and above scored significantly higher than both students in the
1.50-2.49 and the 3.00-3.49 GPA groups in the Problem Solving and Optimism components.
Additionally, students in the 3.50-4.00 GPA group scored significantly higher than both to 1.50-
2.49 and 2.50-2.99 GPA groups the General Mood subscale. Ultimately, students with GPAs above 3.50 scored significantly higher than other GPA groups in total EQ-i scores, Self-
Actualization, Problem Solving, the General Mood subscale, and Optimism. Concerning S-LPI scores, participants with GPAs of 3.50 and above scored significantly higher than participants in the 1.50-2.49 GPA in the Inspiring a Shared Vision subscale. This study also found that the
Academic College students were enrolled in produced no statistically significant differences with regards to either EQ-i scores or S-LPI scores. 121
Pertaining to the number of years that participants were enrolled in the leadership development program, the Third-Year cohort scored significantly higher than the First-Year cohort in the following variables: total EQ-i scores, the Interpersonal subscale, Emotional Self-
Awareness, the Adaptability subscale, and the General Mood subscales. Within the Reality
Testing component, the Third-Year cohort scored significantly higher than both First- and
Second-Year cohorts. And the Problem Solving component found that the Fourth/Fifth-Year cohort scored significantly higher than the First-Year cohort. No statistically significant differences were found between cohorts and the Student Leadership Practices subscales.
Considering race, Students of Color scored significantly higher than White students in the
Assertiveness component, while White students scored significantly higher than Students of
Color in the following EQ-i variables: Self-Actualization, the Stress Management subscale,
Impulse Control, the General Mood subscale, and Happiness. In terms of student leadership practices, White participants scored significantly higher in both Modeling the Way and
Challenging the Process. In terms of Mother’s Education Level participants who had mothers with a Postgraduate degree scored significantly higher than participants whose mother did not have a college degree in the following EQ-i variables: the Interpersonal subscale, Empathy, the
Stress Management subscale, and Impulse Control. In reference to S-LPI scores, no statistically significant differences were identified between Mother’s Education groups. Finally, with respect to Father’s Education Level, no significant differences between Father’s Education Level and
EQ-i scores were identified. However, in relation to the Student Leadership Practices subscales, student whose father possessed an associate or bachelor’s degree scored significantly higher than students whose father had no college degree in the following S-LPI subscales: Inspiring a Shared
Vision, Challenging the Process, and Encouraging the Heart. Likewise, in the Enabling Others 122 to Act subscale students with fathers who had a Postgraduate degree scored significantly higher than students with fathers who only had an associate or bachelor’s degree.
Discussion of the Results
Prior to discussing the results of this study, it is important to review the appropriateness of the population sample that participated. The participants were recruited and selected for this study based on their involvement in a highly selective collegiate leadership development program at a Midwestern state university. More specifically, the participants were members of a university-sponsored, four-year leadership development program that, upon application, required applicants to demonstrate leadership experience at the high school level. As a result, when the participants were selected for this leadership development program, they already possessed pre- college leadership experiences. Furthermore, the leadership development program’s curriculum demonstrated a core set of activities and requirements that focused on both leadership education and campus leadership involvement. With the aforementioned leadership education and experience, the participants of this study proved to be ideal for assessing student leadership practices and emotional-social intelligence.
Student Leaders Profile and Bar-On’s Emotional-Social Intelligence (ESI)
Bar-On (2005) defined Emotional-Social Intelligence (ESI) as “a cross-section of interrelated emotional and social competencies, skills, and facilitators that determine how effectively we understand and express ourselves, understand others and relate with them, and cope with daily demands” (p. 3). The sample mean score for the participants of this study was slightly above average for overall Emotional-Social Intelligence (where the average is 100). Bar-
On (2002) explained that average scores for group assessments range from 95 to 105 and typically indicate a “usually adaptive emotional capacity” (p. 202). The overall ESI scores for the 123
demographic and performance clusters fell within Bar-On’s average range (Table 5). However,
18-year-olds, the First-Year cohort, students with GPAs between 1.50 and 2.49, and Bottom
Performers scored in or within two points of the low average range (90 – 95), which Bar-On described as having “under-developed emotional skills.”
At the other end of the scale, the participants with overall ESI scores ranging from 105 to
110, indicating high average or “well developed emotional capacity,” were the following: (a) 21- and 22-year-old participants, (b) students with GPAs above 3.5, (c) members of the Third-Year cohort, and (d) Top Performers. This is virtually the reverse finding of those participant clusters with lower ESI scores. Based on inferences gleaned regarding the overall ESI scores, participants with lower ESI scores tended to be younger students with lower grade point averages who were fairly new to the leadership development program or were identified as poor performers in the program. Likewise, participants with higher ESI scores tended to be older students with high
grade point averages, who had more experience with the leadership program, or were identified
as higher performers. These inferences are not surprising, because other researchers have found that GPA (Parker, et al., 2004; Swart, 1996), age (Bar-On, 1997; Mayer, Salovey, & Caruso,
1997) and leadership performance (Ruder, et al., 2001) are positively related to emotional intelligence.
Additionally, higher scores within the Intrapersonal and General Mood subscales for this sample demonstrated that, on average, students involved with the four-year leadership development program are “individuals who are in touch with their feelings, feel good about themselves, and feel positive about what they are doing in their lives” (Bar-On, 2002, p. 44).
These results support the findings of Scheusner (2002), where student leaders of campus organizations scored significantly higher on the Intrapersonal subscale than the members of 124 these organizations did. Bar-On further expounded that higher scores in the General Mood subscale “generally indicate cheerful, positive, hopeful, and optimistic individuals who know how to enjoy life” (p. 44). As a result of the identified scores in the General Mood subscale among participants in the present study, it can be inferred that on average the participants within the four-year leadership development program are students who are generally happy and optimistic and a strong sense of self worth and confidence in their own futures. Within the Stress
Management subscale, this population of student leaders scored an average score (near 100), which indicated a “usually adaptive emotional capacity” to handle stressful situation without falling apart or losing control (p. 44). However, participants produced collectively weaker scores
(below 100) in the Adaptability and Interpersonal subscales. These results show that regarding
Adaptability, the participants have room improve their ability to identify and assess troubling situations and determine ways to dealing with and handle problematic situations. Likewise, in terms of the Interpersonal subscale, participants demonstrated an opportunity to improve their ability to interact and be empathetic towards others, which also involves demonstrating a commitment to social responsibility and one’s overall dependability (p. 44). It is important to note that the aforementioned conclusions are based on the mean scores of the entire population.
Interesting differences are identified when comparing the Interpersonal and Adaptability subscale mean scores for the sample with those of only Top Performers. For the Interpersonal subscale, Top Performers scored significantly higher than Bottom Performers, and within the
Adaptability subscale, Top Performers scored significantly higher than the rest of the sample. So that, while the population as a whole scored low on the Adaptability and Interpersonal subscales,
Top Performers in the program scored significantly higher. These comparisons further explain the importance of these two subscales in relation to performance within a leadership 125
development program and the necessity of these programs to provide opportunities for students to exercise adaptability and interpersonal intelligences.
Student Leaders and Kouzes and Posner’s Student Leadership Practices
Kouzes and Posner (1998) provided a chart for graphing S-LPI scores based on the
collection and distribution of scores collected from student leaders nationwide (n = 1,200),
explaining that most of the scores fall near the fiftieth percentile. They offered this chart to
compare scores with the normative sample (p. 31). When compared to Kouzes and Posner’s
sample from the 1998 version of the S-LPI, the participants’ means scores in this study were as
follows: Challenging the Process (M = 22.11, 55th percentile), Inspiring a Shared Vision (M =
23.49, 63rd percentile), Enabling Others to Act (M = 24.44, 44th percentile), Modeling the Way
(M = 22.32, 47th percentile), and Encouraging in the Heart (M = 23.95, 49th percentile).
Overall, all of the sample’s mean scores fall within the 30th and 70th percentiles and are considered “Moderate” (Kouzes & Posner, 1998). Again, individual demographic and performance group mean score fluctuated up or down depending on S-LPI subscales and individual groups.
Even though the percentile chart is based on an older version of the S-LPI and not the
2005 version used in this study, Posner (2005) explained that scores for the new version have been reporting similarly to the population categories assessed by the 1998 version. Specifically,
Posner compared scores collected from Greek chapter presidents (n = 113) and other officers (n
= 491) with the revised 2005 version of the S-LPI. He explained that the results of his study with
Greek Presidents and officers were compatible with previous studies involving the 1998 version and similar populations, i.e., chapter presidents and fraternities (p. 453). 126
Essentially, the participant mean scores for this study were “average” within the ESI
construct and “moderate” on the student leadership practices subscales. However, the overall
results of this study identify more significant differences between demographic variables and
program performance groups within the ESI construct than exist within the leadership practices construct. The following sections interpret the results of each demographic group; however, there may be some general reasons for the uneven differences between demographic clusters and performance groups. Primarily, regardless of leadership education and experience, ESI will increase with age and other life experiences associated with the college life (Bar-On, 1997;
Goleman, 1998), whereas leadership development requires additional leadership education and practical leadership experience. Moreover, the leadership development program curriculum pursued by the participants of this study is not based solely on Kouzes and Posner’s Student
Leadership Practices model. Program participants are exposed to a variety of leadership theories
and concepts throughout the four-year process, which may have precluded the specific use of the
leadership practices found in Kouzes and Posner’s framework. Similarly, the curriculum
requirements for the four-year leadership development program do not place as much emphasis
on practical leadership experiences until the second and third years in the program, which may
have impacted participant responses regarding the frequency of leadership practices.
Gender Differences - Emotional-Social Intelligence and Student Leadership Practices
The study of gender differences and emotional-social intelligence identified only one area
of significance: Self-Actualization. Other studies have identified that women have higher scores
within Interpersonal competencies like “emotional awareness” (Petrides, Furnham, & Martin,
2004). Additionally, Mandell and Pherwani (2003), using the EQ-i, found that women scored
significantly higher than men did in overall emotional-social intelligence. Except for the 127 identification of Self-Actualization, the present study supports Bar-On’s (1997) findings that there is little statistical difference between men and women and emotional-social intelligence.
Although Bar-On (2002) identified small effect size differences between men and women, in that women “seem to have stronger interpersonal skills than men” and men have “higher intrapersonal capacity, are more adaptable, and are better at stress management” (p. 81), more studies are needed to further explore emotional-social intelligence and gender differences, particularly differences in Self-Actualization among men and women in college.
In terms of student leadership practices, no significant differences were identified between men and women, which is consistent with earlier S-LPI research (Posner & Brodsky,
1993, 1994; Pugh, 2000; Posner, 2004). These findings strengthen the conclusion that leadership ability and gender stereotypes may be overstated (Boatwright & Egidio, 2003; Eagly,
Johannensen-Schmidt, & Van Egen, 2003). However, the present study found that women did score higher on all five S-LPI subscales, but the mean differences were not statistically significant. In contrast to the present study, researchers have found that women leaders typically displayed leadership styles that are more transformational or relational in practice, while men display more transactional or task-oriented practices (Buttner, 2001; Eagly, et al., 2003). The contrast between Eagly, et al. (2003) and the findings of the present study may be due to the different settings in which the studies took place. The Eagly, et al. study was conducted in corporate or post-graduation leadership settings, and the present study was conducted in a collegiate setting. The differences between collegiate and corporate leadership settings may have contributed to the lack of significance between gender and the S-LPI. The differences between the two environments are immense, with heightened expectations regarding the acceptance and 128 execution of job responsibilities, demonstration of self-leadership skills, and more serious and immediate repercussions for poor performance and failure in the post-graduation corporate arena.
GPA - Emotional-Social Intelligence and Student Leadership Practices
The literature regarding GPA and emotional intelligence has identified conflicting findings. Swart (1996, as cited in Bar-On, 1997) found that academically successful students scored significantly higher than unsuccessful students in the total EQ-i, Self-Actualization,
Problem Solving, Reality Testing, Stress Tolerance, Happiness, and Optimism. Likewise,
O’Connor and Little (2003) found positive correlations between GPA and total EQ-i, the
Intrapersonal subscale, and the Stress Management subscale scores. Conversely, in an attempt to predict academic achievement, Newsome, Day, and Cantano (2000) found no statistical support that EI can predict academic achievement. The present study found support for the connection between ESI and academic achievement. Students with GPAs 3.50 or higher demonstrated significantly higher scores than students with GPAs between 1.50 and 2.49 in the following EQ-i components: (a) total EQ-i scores, (b) Self-Actualization, (c) Problem Solving, and (d) Optimism.
The reader should notice the similarities between Swart’s findings and the results of the present study. Ultimately, this study contributed significantly to the connection between academic achievement and emotional-social intelligence.
In general, previous studies using the older 1998 versions of the Student Leadership
Practices Inventory, did not find significant differences between academic achievement or GPA and student leadership practices (Posner, 2004; Pugh, 2000; and Edington, 1995). However, with this population of student leaders, students with a GPA above 3.50 had significantly higher scores within the Inspiring a Shared Vision subscale. This particular subscale of the S-LPI involves an individual’s ability to envision a successful future for an organization, encourage and 129
enlist constituent support, and set goals and milestones to move the organization towards that
vision (Kouzes & Posner, 2002). Bar-On (1997) explained that goal-setting, optimism, and
personal motivation contributed greatly towards academic performance; so, perhaps there exists
a relationship between the Inspiring a Shared Vision practice, goal-setting, and academic
performance.
Program Cohort and Age - ESI and Student Leadership Practices
The relative similarities between cohorts in the program and participant age necessitate a
combined discussion. For all intents and purposes, as age increases, so does the advancement
with year in the program, with the participants starting the program as freshmen at 18-years-old,
and finishing the program as seniors at 21- or 22-years-old. However, even with the logical
similarities in the two demographic variables (age and cohort), the results identified were not all
that similar. First of all, the ESI differences identified within the program cohorts variable
revealed that the Third-Year cohort scored significantly higher than the First-Year cohort on the
following measures: total EQ-i score, the Intrapersonal subscale, Emotional Self-Awareness, the
Adaptability subscale, Reality Testing, Problem Solving, and the General Mood subscales. For
the most part, ESI mean scores between cohorts increase with each year in the program;
however, the Fourth/Fifth-Year cohort means scores dropped from the Third-Year cohort, except
for the Interpersonal subscale and components. In terms of age, this study found that only total
EQ-i scores, Empathy and Happiness, increased significantly from 18-year-olds to 22-year-olds.
The findings of this study supported growing research that found that emotional
intelligence increases with age (Bar-On, 1997; Palmer, Manocha, Gignac, & Stough, 2003; Van
Rooy, Alonso, & Viswesvaran 2005). In terms of cohort differences, aside from age, additional
ESI components were found to increase from cohort to cohort. Prior research specific to 130
participation within a four-year leadership development program does not exist; however certain inferences can be made about cohort findings. As discussed in Chapter 1, the leadership development program curriculum focuses heavily on values clarification, interpersonal communications, community service, and critical thinking, which may increase overall
emotional-social intelligence and the abovementioned variables as a student progresses through
the program. Additionally, the natural process by which a student advances through college
encourages a level of social and emotional development to allow one to cope and manage daily
stressors and challenges (Chickering, 1969).
Perhaps most surprising was the identified lack of significance between cohorts and age
with the student leadership practices subscales. The mean scores for each of the five leadership
practices, four cohorts, and the age groups respectively, identified no discernable progression in
S-LPI scores from year to year. As discussed in the previous paragraph, the four-year leadership
development program focuses on progressive development of leadership education and practice,
yet for some reason, significant differences between cohort groups were not observed. More
specifically, the four-year leadership development program curriculum moves sequentially
through specific learning outcomes for each year. Some characteristics that guide the curriculum
are as follows: (a) beginning to advanced leadership theory, (b) leadership education to
leadership practice, and (c) from passive to active participation in the leadership within the
program. As mentioned earlier, the lack of significance here may be related to the fact that the
leadership development program curriculum does not align exclusively with Kouzes and
Posner’s Student Leadership Practices model, as other leadership constructs and theories take a
more prominent role. Results of a similar study to the present one may find that if the Student
Leadership Practices model were fully integrated into the program, significant difference 131
between age groups may produce more significant increases in leadership practice changes from
year to year.
Race - Emotional-Social Intelligence and Student Leadership Practices
This study provided a unique perspective on differences in emotional-social intelligence
between Students of Color and White Students. Historically, results from other studies in both
ESI and Student Leadership Practices have been limited by the inequality of sample sizes
between racial groups. For example, Bar-On (1997) conducted analyses of a North American
normative sample that consisted of primarily white participants (79%). In contrast, this study’s
sample consisted of 57.5% Students of Color. However, the level of racial diversity is limited to
two dominant groups: African American students (45.2%) and White students (42.5 %);
unfortunately, because of the limited number of students within other racial categories, only two
racial clusters were assessed: Students of Color and White students. Notably, the Midwestern
state university home to this study, and the participants, had a predominantly white student
population. Specifically, the University’s Institutional Research department reported that at the
time of the study the racial percentages for the main campus undergraduate students were as
follows: (a) White, 83.7 %, (b) Black, 7.6%, (c) Hispanic, 3.1%, and (d) Other Students of Color,
5.6%. It is noteworthy that Students of Color scored significantly higher in the Assertiveness
component than White students did. Bar-On (2002) describes individuals with high Assertiveness
scores as “individuals who are able to express feelings, thoughts, and beliefs and defend their rights in a nondestructive manner” (p. 15). The findings in the present study support Lineberger and Calhoun’s (1983) study of assertive behaviors among undergraduate students, in which they found that “overall assertiveness scores indicated significant differences in the assertive responses of black and white students: blacks were more assertive than whites on all inventories 132 that assessed level of overall assertion” (p. 146). The difference between the Students of Color and White students within the Assertiveness component here may be related to cultural responses to racial inequalities in the United States and on the university campus at large. Or perhaps in their experiences up to the point of this study, students of color have had to rely on and enhance their assertiveness skills to be successful. Additionally, there is also the possibility that Bar-On’s definitions of the EQ-i variables and the questions on the test instrument do not account for cultural and racial differences, an important question for future research.
Additionally, White students scored significantly higher than Students of Color did in the following EQ-i variables: Self-Actualization, the Stress Management subscale, Impulse Control, the General Mood subscale and Happiness. According to Bar-On (2002) higher scores in Self-
Actualization indicate that White students were more apt to identify self-improvement opportunities and realize their potential capabilities (p. 14). Additionally, within the Impulse
Control component White students had an increased “ability to resist or delay an impulse, drive, or temptation to act” which contributes to one’s ability to maintain composure and control aggressive behavior (p. 18). Finally, increased scores in the Happiness component demonstrated that White students have a heightened capacity to feel generally cheerful and enthusiastic about life (p. 18).
With the exception of a parallel with Lineberger and Calhoun (1983), this study’s findings do not support the limited and divergent results of prior research regarding racial differences and emotional intelligence. Van Rooy, Alonso, and Viswesvaran (2004) found that
Hispanic students scored significantly higher in emotional intelligence scores than White students. Additionally, they found the scores of Black students were higher than White students, but not significantly. On the contrary, Bar-On (1997) with a normative sample of 79% white 133
participants found that the “North American sample did not reveal significant differences on
emotional and social intelligence between various ethnic groups” (p.78). Due to the lack of
consistent results in the literature, additional research concerning emotional-social intelligence is
needed.
With regards to student leadership practices and race, previous research found that
differences in student leadership practices could not be explained by racial differences (Posner,
2004; Pugh, 2000; Edington, 1995). However, within this study, White students scored significantly higher than Students of Color in Modeling the Way and Challenging the Process.
These results suggest that White students have a clearer understanding of their own personal
values and beliefs and are willing to set a positive example within the leadership environment.
Additionally, White students have a higher capacity to “seek out new opportunities and [are]
willing to change the status quo” whereby demonstrating an aptitude for experimentation and
risk-taking (Kouzes & Posner, 1998, p. 3). The racial differences identified for this sample of students enrolled in the four-year student leadership development and emotional-social
intelligence and student leadership practices demonstrates a need for additional research and
discussion. Specifically, racial differences regarding the opportunities for, and quality and
quantity of, practical leadership experiences, and the frequency of student leadership practices,
might offer another perspective of the differences between Students of Color and White students.
Parent’s Education Level: Emotional-Social Intelligence and Student Leadership Practices
Within the area of mother’s education, it was interesting to find that Empathy scores
increased statistically as mothers’ education increased, so that participants with mothers who
have post graduate degrees scored significantly higher in Empathy. One could speculate that
mothers with higher education levels display a higher level of empathy, which in turn was taught 134
to their children. Additionally, Impulse Control increased statistically with a Mother’s Education
Level. This suggested that as mother’s education level increased, so did the mother’s ability to
role model appropriate emotional control and resist the impulse to overreact or lose control in
adverse situation. However, Father’s Education Level produced no significant differences within
the emotional-social intelligence construct. In terms of student leadership practices, Mother’s education level did not demonstrate significant differences between groups. On the other hand, significant differences were found between Father’s Education Levels and student leadership practices. Specifically, participants whose father had advanced levels of education scored significantly higher in the following: Inspiring a Shared Vision, Challenging the Process,
Enabling Others that Act, and Encouraging the Heart.
The results of this study may indicate a higher level of emotional and development involvement among parents with higher education. The research in the area of parenting indicates positive impacts of parental involvement and emotional stability as related to the success of their children. Gottman (1997) asserts that parental “Emotional Coaching” and guidance positively influences the emotional development of their children. Furthermore, studies of two-parent families have identified that emotionally and socially active parents, i.e., parents with an “authoritative” style, positively influence the likelihood that their children will (a) be
academically successful, (b) have control over their emotions, (c) have increased self-esteem and life satisfaction, and (d) effectively interact in social settings (Zimmerman, Salem, & Maton,
1995; and Marsiglio, Amato, Day, & Lamb, 2000). In terms of fathers’ involvement, Marsiglio, et al. (2000) concluded that the results of research findings in the 1990s, demonstrated that
“positive father involvement is generally beneficial to children” (p. 1183).
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Relationships between Emotional-Social Intelligence and Student Leadership Practices
Considering the definition of ESI, this study found significant relationships between ESI and leadership practice. Specifically, this study found strong correlations between the Kouzes and Posner’s Student Leadership Practices (a relational leadership model), and Bar-On’s
Emotional-Social Intelligence concept of Emotional Intelligence. These findings lend considerable support to those researchers who have identified similar findings (Goleman,
Boyatzis, & McKee, 2002; Higgs, 2002; Cherniss, 2000; and Caruso & Salovey, 2004).
On the basis of this study alone, it is difficult to be certain about the factors accounting
for relationships between emotional-social intelligence and college student leadership practices.
However, the results presented in Chapter Four offered promising connections between the two
constructs. Kouzes and Posner’s model is considered a relational leadership model and, as a
result, the identified connections between S-LPI and ESI, and particularly the strong positive
correlations between the Interpersonal and General Mood subscales are not particularly
surprising. Relational leadership is described as a leader’s ability to create and maintain positive
relationships with his or her constituents, which over time will hold the organization together
during periods of uncertainty and change (Komives, Lucas, & McMahon, 2002; Yukl, 1999;
Higgs, 2002; Dionne, Yammarino, Atwater, & Spangler, 2004). This description of relational
leadership certainly impresses the thought that one’s emotional and social abilities play a
significant role in successful leadership. Similarly, Bar-On (2005) described emotional-social
intelligence (ESI) as “a cross-section of interrelated emotional and social competencies, skills,
and facilitators that determine how effectively we understand and express ourselves, understand
others and relate with them, and cope with daily demands” (p. 3). As was discussed in Chapter 1,
the last part of Bar-On’s definition relates significantly to the rapid, complex and irrevocable 136
change occurring in modern society. These complex changes and societal stressors encourage the
need for linking emotional-social intelligence to relational leadership and vice versa. To that end,
the results of this study demonstrated through Pearson r Correlation Coefficients, that a leader’s
ability to model the way, inspire a shared vision, challenge the process, enable others to act, and
encourage the heart related significantly with a leader’s level of emotional-social intelligence.
The next few sections of this chapter discuss the extent to which the overall ESI, the five
subscales, and the 15 components of the EQ-i related with each of the five Student Leadership
Practices. The researcher decided to present the findings of the correlation coefficients from ESI
to S-LPI rather than S-LPI to ESI primarily to simplify the discussion. The decision to discuss
results in this manner is not meant to project relative importance of one construct over the other.
At this point, it should be assumed that the relationships between variables are mutually
influential where, based on respective r-values, as one variable increases so does the other and
vice versa.
Modeling the Way
Of the S-LPI subscales, Modeling the Way has the strongest correlation with overall
emotional-social intelligence. Self-Actualization correlated most strongly with Modeling the
Way; they both relate to one’s ability to identify personal values and strive towards continual
self-improvement of one’s abilities and talents. Additionally, the Modeling the Way subscale has
to do with a leader’s ability to plan projects through application of incremental successes. This
requires a significant amount of Reality Testing and Problem Solving ability, so the relationship there is not surprising. Furthermore, Kouzes and Posner (2002) explained that that the most mentioned leaders throughout history were those leaders who possessed “strong beliefs about matters of principle... unwavering commitment to a clear set of values... passion about their 137
cause” (p. 45). Routinely, leaders support causes that involve improving situations within an
organization or for society’s greater good (Astin & Astin, 2000). The Modeling the Way subscale
requires a foundation of collaborative, supportive, and healthy relationships, which substantiates
the moderate correlations with all of the Interpersonal subscale components. Additionally, this
leadership practice is about setting the example within an organization and displaying a level of
personal integrity and positive energy for others to follow. To that end, the strongest correlation
between the EQ-i and S-LPI test instruments was found between Modeling the Way and
Optimism. This finding strengthens Goleman, et al. (2002) assertion that “a leader who is optimistic can roll with punches, seeing opportunity rather than a threat in a set back” (p. 255).
Furthermore, the discovery of non-significant relationships between Modeling the Way and both
Assertiveness and Independence was somewhat surprising.
One would have speculated that Assertiveness would correlate significantly with
Modeling the Way, because Assertiveness is important when one needs to openly “express feelings, beliefs and thoughts” and stand-up for personal rights (Bar-On, 2002, p. 15).
Additionally, Independence should have related to Modeling the Way, because that is the point in the leadership process where a leader needs to be clear and persistent about his or her own values and beliefs. Independence can be described as one’s ability to be self-directed and self-controlled in terms of thinking and actions (p. 16). Even though one would have anticipated a significant correlation, the non-significant relationship may be due, in part, to the age and experience level of the participants. Researchers have found that overall work success in occupation settings correlated with Self-Actualization, Happiness, Optimism, Self-Regard, and Assertiveness (Stein
& Book, 2000).
138
Inspiring a Shared Vision
With Inspiring a Shared Vision, a leader must first imagine what the organization could
be and then create a vision that is attainable and attractive. Next the leader connects this new
vision to the hopes and dreams of his or her constituents to generate passion and enthusiasm for
realizing the vision (Kouzes & Posner, 2002). Based on this brief explanation the identified moderate correlation between emotional-social intelligence and Inspiring a Shared Vision is not surprising. Both the Interpersonal and Intrapersonal subscales of the EQ-i correlated significantly with Inspiring a Shared Vision. First, leaders must possess interpersonal abilities, i.e., personal confidence and assertiveness, to create a vision. After creating a vision, a leader must demonstrate the interpersonal skills to be able to enlist and motivate constituents to share that vision (Caruso & Salovey, 2004). Additionally, Inspiring a Shared Vision correlated moderately with Stress Tolerance and Problem Solving, which improve a leader’s ability to resiliently move the vision forward by managing day-to-day stressors and eliminating impeding barriers (Dulewicz & Higgs, 2003). Finally, the present study provides support for the relative importance of Optimism in leadership settings. Goleman, et al. (2002) discussed the concept of resonant leadership in which the leader is in tune with the feelings of his or her constituents and enthusiastically moves the emotional climate of the organization in a positive and uplifting direction (p. 20). An optimistic view of the future is essential to a leader’s ability to build positive relationships and gather support for a common purpose and vision (Cherniss &
Goleman, 2001).
Challenging the Process
Challenging the Process also produced moderate correlations with the emotional-social intelligence model. Both Inspiring a Shared Vision and Challenging the Process involve a 139
leader’s ability to identify opportunities for change and then, more importantly, act on those
opportunities. The results of the present study found that Assertiveness, Self-Regard, and Self-
Actualization moderately correlated with a leader’s ability for Challenging the Process.
Additionally, to see the change process through to completion, a leader must possess a
significant ability to tolerate stress and solve problems in order to adapt to and overcome
organizational setbacks (Higgs, 2002). Similarly, as was found in the Inspiring a Shared Vision
and Modeling the Way subscales, Optimism strongly correlated with Challenging the Process,
because a leader’s tendency towards an optimistic view of the future is the driving force behind
maintaining constituent support for and dedication towards successful change (Bader & Calarco,
2004). It was a bit surprising that the Interpersonal subscale components only produced small or
non-significant relationships with Challenging the Process. Change leadership talks about a
leader’s ability to rally and enlist constituent support for change and the Interpersonal
components contribute to a leader’s ability to motivate and encourage change (Kotter, 1995;
Higgs, 2002, Kouzes & Posner, 2002). As mentioned earlier, the identified small relationship
with the Interpersonal subscale components may be due in part to the age of the participants and
their developing experiences with leadership (Stein & Book, 2000).
Enabling Others to Act
Enabling Others to Act is a leader’s ability to generate an atmosphere of mutual trust and
respect within the organization. Additionally, this subscale relates to a leader’s capacity to create a team environment that feels like a collaborative family, where members feel like they own a part of the organization (Kouzes & Posner, 1998, p. 13). Given the social nature of this leadership practice, the strong relationship between Enabling Others to Act and the Interpersonal subscale, specifically Empathy and Social Responsibility, is not shocking. Basically, Enabling 140
Others to Act stems from a leader’s ability to create an organizational climate that promotes shared leadership and empowers members of the organization to assume a leadership role, as organizational dynamics require (Yukl, 1998). Of this leadership practice, the strong relationship with the Adaptability subscale indicate that a leader’s ability to actively and accurately assess the leadership setting and the feelings of constituents’ related significantly to his/her ability to
effectively problem solve and adapt to organizational struggles (Bar-On, 2002). Additionally, the
relationship between the Stress Management subscale and Enabling Others to Act demonstrates
in a need for leaders to be able to cope with and tolerate stressful situations without negative
emotional outbursts (Bar-On, 2002). Quite unexpectedly, however, the Intrapersonal subscale
did not correlate significantly with Enabling Others to Act. One might expect that for leaders to
encourage and promote the development and success of constituents, they would need to
demonstrate higher levels of Self-Regard and Self-Actualization in which they accept and respect
themselves, and are able to realize their own potential.
Encouraging the Heart
The Encouraging the Heart subscale correlated with the least amount of EQ-i variables.
However, the most significant correlations were found within the Interpersonal subscale and the
Problem Solving component. This is not surprising, because Encouraging the Heart has to do
with a leader’s capacity to recognize and celebrate the accomplishments of individuals, as well
as the organization (Kouzes & Posner, 2002). To do this effectively requires a leader to
appreciate the feelings of their constituents, demonstrate that they are part of the team, and
establish and maintain satisfying relationships with organization members (Bar-On, 2002). The
results show that a heightened level of Empathy contributed to a leader’s ability to be aware of,
appreciate and understand the feelings of constituents, as well as demonstrate concern for their 141
well being. Moreover, the connection between Encouraging the Heart and the Social
Responsibility and Interpersonal Relationships components demonstrates that leaders should
possess the ability to work side-by-side with constituents and truly be a part of the team. These
findings lend themselves to other researchers’ work purporting that relational leadership starts
with the leader’s ability to establish and maintain positive relationships with constituents (Bass,
1985; Chemers, 1993; Komives, Lucas, & McMahon, 1998; Kouzes & Posner, 2003; Potter,
Rosenbach & Pittman, 2001). Finally, the connection with the Problem Solving component is not
surprising because problem-solving skills allow leaders to accurately assess personal and social problems within an organization and identify accurate and appropriate solutions (Bar-On, 2002).
Nevertheless, it was a bit surprising that the components of the Stress Management subscale did
not correlate significantly with Encouraging the Heart. One might project that a leader’s ability
to manage their own emotional reaction to daily stressors or major events would contribute to
their ability to maintain and role model positive, uplifting, and appropriate organizational behaviors (Vakola, Tsaousis, & Nikolaou, 2004).
Performance: Emotional-Social Intelligence and Student Leadership Practices
Top Performers in the Student Leadership Development Program
Perhaps the most important finding of this study was the support for other research that found a connection between emotional intelligence and leadership performance (Brackett,
Mayer, and Warner, 2004; Pellitteri, 2002; Bar-On, Handley, & Fund, 2005). Findings showed that Top Performers scored statistically higher than other performance groups in 11 of the 21
EQ-i variables: total EQ-i scores, Self-Actualization, the Interpersonal subscale, Social
Responsibility, Stress Management subscale, Stress Tolerance, the Adaptability subscale,
Problem Solving, the General Mood subscale, Optimism and Happiness. Observations of the 142
mean scores between performance groups indicated that, on average, the means for all EQ-i
variables increased from bottom to middle to top performers consistently except for two
variables: Assertiveness and Independence, where no statistical differences were observed.
Top Performers scored high or within the “atypically well developed emotional capacity”
category in the Intrapersonal subscale with Self-Regard and Self-Actualization, and in the
General Mood subscale with Optimism and Happiness (Table 5, Bar-On’s “Group Report
Standard Score Interpretation Guidelines”). They scored high average or demonstrated a “well developed emotional capacity” in the Emotional Self-Awareness, Interpersonal Relationships,
Stress Tolerance, and Problem Solving components. Ultimately, these Top Performers can be described as possessing “High Average” emotional-social intelligence. Specifically, they are leaders who separated themselves from other performance groups by remaining extraordinarily optimistic and happy about life, and possessing high amounts of self-confidence and self-
satisfaction, and possessing heightened awareness of personal feelings. Similarly, they are
students who are able to generate and maintain positive relationships with others, while
displaying a high tolerance for stressful situations, and an ability to solve problems (Kouzes &
Posner, 2002; Bar-On, 2002).
In terms of the Student Leadership Practices scores, the mean scores for each of the five
practices increased progressively from bottom, to middle, to top performers. Moreover, both Top and Middle Performers scored significantly higher than Bottom Performers in Modeling the Way,
Inspiring a Shared Vision, and Challenging the Process. These findings support other research that found that successful student leaders engage more frequently in each of the five student leadership practices (Posner & Brodsky, 1993; Posner & Rosenberger, 1997; Pugh, 2000;
Posner, 2004). Moreover, the results demonstrated the importance of practical, hands-on 143
leadership opportunities within the leadership development process. Given that Top Performers
were selected, in part, because of their increased involvement with leadership positions on-
campus, they have apparently taken more opportunities to practice the leadership skills and
behaviors they have learned from theory.
Along with leadership experience, Top Performer mean scores demonstrated increased
frequency of leadership practice compared to Bottom Performers. Using Kouzes and Posner’s
(1998) “Chart for Graphing Your Scores,” Top Performers scored at the 70th percentile for
Challenging the Process (Bottom Performers (BP), P = 31st), 86th percentile in Inspiring a
Shared Vision (BP, P = 43rd), 47th percentile in Enabling Others to Act (BP, P = 30th), 65th
percentile in Modeling the Way (BP, P = 21st), and the 60th percentile for Encouraging the
Heart (BP, P = 33rd). These comparisons and ANOVA findings (Appendix F) indicate that Top
Performers clearly report using Kouzes and Posner’s leadership practices more frequently than
Bottom Performers. Similarly, the results clearly explained that the director’s modified 360, or placement of students into performance groups, supported the students’ self-reported perceptions of both their emotional-social intelligence and their student leadership practices.
Bottom Performers
As was expected, Bottom Performers scored statistically lower than Middle and Top
Performers on many of the Emotional-Social Intelligence variables and the Student Leadership
Practices subscales. Specifically, Bottom Performers scored in the “under-developed emotional skill” category (Table 5) for the Interpersonal and Adaptability subscales. Moreover, the Social
Responsibility component represented their lowest score (M = 89.17), which fell into the
“markedly under-developed emotional skill” category of the EQ-i. These findings indicated that not only Intrapersonal prowess increased program performance, but performance also required 144
increased interpersonal skills, which permits one to (a) get along better with people, (b)
understand and relate well with others in a variety of settings, (c) build trust in others and be part
of a team, and (d) maintain positive expectations regarding social exchanges (Stein & Book,
2000). In reality, Bottom Performers demonstrated their highest mean scores within the
Intrapersonal subscale in the Self-Regard, Assertiveness, and Independence components, and
demonstrated below average scores in all other EQ-i variables. Bottom Performers may have
been successful in high school based on their high levels of confidence and personal
assertiveness, but those qualities are not sufficient to make a student successful within a leadership development program at college.
In terms of the Student Leadership Practices scores, the mean scores for each of the five
practices decreased with Bottom Performers, and as discussed earlier, Bottom Performers scored
significantly lower in three of the five leadership practices: Modeling the Way, Inspiring a
Shared Vision, and Challenging the Process. These findings also support research that found that
unsuccessful student leaders engage less frequently in each of the five student leadership
practices (Posner & Brodsky, 1993; Posner & Rosenberger, 1997; Pugh, 2000; Posner, 2004).
Regarding the mean scores of the Student Leadership Practices Inventory, compared to the
percentile ranks of the 1998 version, Bottom Performers scored comparatively lower than Top
Performers on all five practices. It is clear that the director’s placement of students into
performance groups were supported by both the emotional-social intelligence scores and student
leadership practices scores of the Bottom Performers.
Ultimately, the present study supports the connection between emotional intelligence and
performance (Goleman, et al, 2002; Stein & Book, 2002; McColl-Kennedy & Anderson, 2002).
To that end, Top Performers, or those students who had proven success academically within the 145
leadership program curriculum and in practical leadership positions, scored significantly higher
in both ESI and S-LPI variable than Bottom Performers.
Recommendations for Practitioners
Given the strong relationship between Student Leadership Practices and Emotional-
Social Intelligence identified in this study, it is incumbent upon professionals within both
Student Affairs and Academic Affairs to develop innovative, meaningful and practical leadership
development opportunities that incorporate ESI concepts. The four-year leadership development
program that set the context for this study is a great model for leadership development. On its
surface, it is designed for success, because of the systematic, long-term, and comprehensive
leadership education and applied leadership process. However, like other leadership development programs across the country, this leadership program has not fully embraced or included emotional-social intelligence concepts into the leadership curriculum. It is now time to create systematic, well-organized, leadership development programs in higher education that include the identified connection between ESI and leadership effectiveness.
Higher education is in the business of producing educated, mature, ethical, and contributing citizens and leaders (Astin & Astin, 2000). Around the world, incredible changes are occurring exponentially, and in it is to that end that effective leaders have the greatest opportunity for helping constituents cope with change and make positive differences in society.
The research shows that the numbers of college and university leadership programs are increasing to meet the need for effective leadership in society (Berg, 2003; Posner, 2004).
However, researchers have also found that increased numbers of programs does not always indicate success leadership development programs (Connaughton, Lawrence, & Ruben, 2003).
Regularly, collegiate leadership initiatives focus on short-term results, are disorganized, and are 146
ill-defined. More often than not, these short-lived programs are destined for marginal success or
failure, because of the lack of long-term campus-wide investment for a comprehensive student leadership development plan (Schwartz, Axtman, & Freeman, 1998).
This study cannot say for certain that the leadership development program influenced the participants Emotional-Social Intelligence, or that the program necessarily impacted Student
Leadership Practices; however, it is clear that Top Performers scored significantly higher than other performance groups in both constructs. Therefore, the researcher’s recommendation to practitioners is that a comprehensive program, much like the one highlighted in this study, is a good model for developing and expanding student leadership success on campus. Administrators of higher education need to strongly consider creating leadership development programs that are systematic, progressive, developmentally appropriate (from education to practice), and supported throughout the institution. They also need to take a close look at top-performing students and the factors that contribute to their academic and leadership success. The next few paragraphs outline a general leadership development model based on study results and general knowledge gain through this study.
Past and present research indicates that self-awareness is the foundation for leadership development; i.e., knowing one’s leadership skills and abilities, as well as understanding one’s emotional needs and reactions to events (Yukl & Lepsinger, 2004; Komives, Lucas, &
McMahon, 1998; Goleman, et al., 2002). Bar-On’s Emotional-Social Intelligence model is designed to help individuals clarify and understand their own emotional reactions to the world, as well as enhance their ability to accurately interpret the emotions of others, while coping with and adapting to the environmental challenges of daily-living. So, from a practical standpoint, as was found in this study, it is only fitting that leaders with higher ESI demonstrate increased 147
success and performance. Similarly, because leadership development is about knowing oneself first and because emotional-social intelligence is a vehicle for self-exploration, a central component to leadership development is self-discovery through ESI and leadership education.
Once student leaders have a sound understanding and knowledge of their own personal leadership strengths and weaknesses, they can focus on continual professional improvement and development.
Furthermore, the criteria for Top Performers used in this study provide a foundation for effective student leadership development. The results of this study found that students with higher GPAs scored significantly higher in ESI than those students with lower GPAs. Moreover,
Top Performers in this study were those leaders who, in part, possessed high GPAs. Therefore, leadership development programs need to place significant importance on student academic achievement early and continually throughout the development process. Academically successful students have higher ESI and make better leaders, so leadership programs need to place just as much emphasis on academic performance as they do on leadership development.
Through the process of self-exploration and academic success, student leaders will be able to first identify their leadership strengths and weaknesses and then they will possess the academic skills to create a plan for improving their leadership. An important component in this process is a systematic, long-term, comprehensive, and reflective leadership curriculum. As identified in this study, part of the leadership curriculum must focus on the development of ESI.
And to that end, researchers have found that ESI can be developed and enhanced through training (Goleman et al., 2002; Stein & Book, 2000; Bar-On, 2002). Likewise, the results of this study demonstrated that students who successfully advance through the leadership theory and leadership education requirements have higher emotional-social intelligence and apply more of 148
Kouzes and Posner’s leadership practices. Hence, a fully defined leadership education curriculum that features ESI training is another key to the successful development of student leaders.
The next step in the leadership development process incorporates practical leadership experiences. Top Performing leaders in this study possessed a significant amount of hands-on and active leadership experiences. They were students who embraced their college experiences to observe other leaders, learn leadership theory and skills, and then practice those leadership skills within student organizations, student employment opportunities, and various other leadership positions. They were able to take risks, be assertive, and learn through trial and error.
To further advance the leadership development process, colleges and universities must provide and encourage practical leadership experiences both on an off campus.
The leadership development process should provide frequent opportunities for feedback and reflection about both ESI characteristics and leadership skills. Honest feedback and assessment can be rewarding when offered tactfully and received graciously. Unfortunately, it is human nature for both the evaluator and the evaluatee to feel anxiety and discomfort through the feedback and assessment process; however, the development of ESI can eliminate some of the angst. Moreover, the creation and development of positive relationships within the leadership development process opens the door for open and honest feedback. Along with feedback, the reflection process provides developing leaders with opportunities to reevaluate personal leadership behaviors and ESI to identify ways to improve their performance. The inclusion of both feedback and reflection should occur frequently and structurally throughout the leadership process. These two approaches are the tools that move leadership development from just another educational process to an amazing, impactful and life changing process. 149
Finally, near the end of the collegiate and ultimately the student leadership development
process, more emphasis must be placed on the students’ successful transition into their careers
and roles in society. Collaborative opportunities with university career services and co-op
programs can help guide students on the road to securing their first professional positions outside
of college. Additionally, leadership development programs can provide ESI information and
leadership tools to enhance student success after college in their first career position. Ultimately, the student’s acquisition of employment completes the student leadership development process and then starts their professional leadership development.
In the end, the researcher suggests first securing campus-wide support, both human and financial assistance, to develop the most comprehensive, systematic, and progressive leadership development program as resources allow. Once adequate support is gained, create a master plan that provides a road map or leadership curriculum for student progress through both academic and leadership development. Within the leadership curriculum, create feedback and reflection opportunities that focus on ESI and personal leadership exploration and improvement. In terms of application, leadership development programs must encourage the identification of opportunities for applying leadership skill in practical settings. Lastly, this process starts with the college and university mission, and it is ultimately up to university administrators to gain support and encouragement from faculty, staff, and students for the creation of a systematic, comprehensive, lasting leadership development process.
Limitations of the Study
The limitations for this study are found in four primary areas: the unique characteristics of the population and location, instrument characteristics and reliability, research design, and
response biases. The results of this study were limited to the elite status of the participants. As 150 members of a highly selective four-year, co-curricular, student leadership development program, the results of this study may not be generalized to other populations of student leaders. This study did not compare a population of student leaders with non-student leaders, which minimized the understanding of the true effects of ESI on leadership.
Low Cronbach’s Alpha scores on three of the test variables for this population adds question to the validity of findings. Additionally, an oversight in the research design inappropriately assessed participant GPA twice: once in the director’s criteria for program performance, and again with the demographic survey. A true 360-degree assessment of the student leaders, by the director of the program, may have presented a more accurate representation of their emotional-social performance and student leadership practices.
The research design did not include factorial analyses and precluded the testing of interaction between variables. In other words, because of limitations in the research design, the researcher could not further explain the effects of a combination of two independent variables
(race, age, parents education level, performance groups, gender, GPA, etc.) on emotional-social intelligence or student leadership practices.
In terms of response bias, there were three primary factors that could have impacted participant responses. First, participants may have felt social or programmatic pressures to participate. Second, the combined length of the test instruments may have contributed to respondent fatigue. Third, data collection took place near the end of the spring semester and collegiate pressures may have distracted respondents during survey completion.
Recommendations for Future Research
After completing this study, several recommendations for future research were established. For instance, a parallel study could be conducted comparing two different groups of 151 student leaders, i.e., leaders in a four-year leadership development program and student leaders who are not, or sorority and fraternity presidents, student organization presidents and dining services student managers, or perhaps a comparison of leaders and non-leaders to see if there really are differences between ESI and LPI, etc. The differences between samples would further identify the relationship between the two constructs and identify differences in leadership settings.
This study’s methodology could be applied comparing a sample of student leaders with a sample of post-graduate leaders in a corporate setting. Interesting gender comparisons might be identified between leaders in corporate settings and college settings. Similarly, this study identified the relationships between Emotional-Social Intelligence and Student Leadership
Practices, but did not establish causality between these variables. Future research could pursue the exploration of causality, between the five leadership practices and the variables of Bar-On’s
EQ-i. The identification of causality would assist practitioners in the development of programs and educational opportunities to improve either leadership practices or emotional-social intelligence. Factorial analyses of variance may also reveal interaction effects among independent variables, such as gender and race, race and parent’s education level, race and program performance, and age and program performance. This type of information would further identify the impacts or effects of one demographic variable on another. Researchers would be able to explore combinations of independent variables and determine which interactions have the most impact on ESI or student leadership practices.
Moreover, qualitative studies could be conducted which may enhance the interpretation of the quantitative findings of this study by adding other factors that may influence EQ-i and S-
LPI scores. Furthermore, with the identified racial differences in terms of both Emotional-Social 152
Intelligence and Student Leadership Practices, qualitative interviews could be conducted to
explore, for example, what Assertiveness means to students of color, etc. In that same vein,
additional study is needed to determine the significance of Father’s Educational Level and
increased use of Student Leadership Practices.
To track the progress and differences among program graduates, within the area of
leadership practices and emotional-social intelligence, longitudinal studies could be conducted to
trace changes over the years, pre- and post-graduation. Qualitative information could be gathered
to provide researchers with more details regarding to the four-year leadership program experience and the perspectives and thoughts of program graduates and their advancement of
ESI and leadership practices.
Additionally, studies could be conducted using a “true” 360-degree assessment where
both EQ-i and S-LPI data are systematically collected from peers, coworkers, or supervisors,
about the participants’ ESI or leadership practices. And then participants’ scores could be
compared to other raters to identify differences in perceptions and identify a more accurate
understanding of the participants ESI and student leadership practices (Chappelow, 1998, p. 31).
Conclusions
Emotional intelligence relates significantly with effective leadership performance
(Cherniss & Goleman, 2001; Goleman, Boyatzis, & McKee, 2002; Mayer & Salovey, 1993). The
results of this study found that Top Performing student leaders, within a student leadership
development program, have higher emotional-social intelligence than Bottom Performing student
leaders. Until this study, a direct connection between student leadership practices and emotional-
social intelligence had not been identified. This connection offers significant evidence and
motivation for including emotional and social enhancement opportunities in higher education 153
leadership development programs.
The next few paragraphs highlight important findings as they relate to the following:
institutions of higher education, practical leadership experiences, and the societal need for
leadership. It is clear that colleges and universities are responding to the societal need for
effective leadership, as seen by the increased popularity and development of student leadership
initiatives (Schwartz, Axtman, & Freeman, 1998). However, many of these university-sponsored
leadership activities are short-run and disconnected from a central campus-wide leadership
initiative (Connaughton, Lawrence, & Ruben, 2003). Such leadership initiatives have historically
overlooked or ignored the benefits of enhancing college student emotional-social intelligence
(Low, Lomax, Jackson, & Nelson, 2003). The findings of this study validate the connection between advanced leadership abilities and high emotional-social intelligence.
This study reinforces the importance of practical leadership experiences at the college
level. Top Performing leaders were placed in that category because of their successful
advancement through the program’s leadership curriculum, as well as their established participation and involvement in leadership positions on campus. The success of these Top
Performers involves two key components. First, student leaders must possess the assertiveness,
confidence, and drive to take advantage of and learn from these opportunities. Colleges and
universities must provide the educational and practical opportunities for leadership advancement.
Ultimately, colleges and universities possess the ability and resources to create these
opportunities.
This study also focused on the need for transformational or relational leadership practices
to allow leaders to effectively cope with, manage, and ultimately be successful despite of
turbulent change. Society is looking for leaders who possess the ability to adapt and encourage 154 change, motivate and empower constituents, and foster a human network of support and commitment within communities and organizations. It is a reality that leaders must possess the ability to lead even in the face of chaotic, frenzied, and sometimes distressful environments
(Komives, Lucas, & McMahon, 1998; Kouzes & Posner, 2003, Goleman, Boyatzis, and McKee,
2002). Each year institutions of higher education graduate the next generation of leaders, and it is to that end that these institutions should provide opportunities for student leaders to gain the foundational knowledge and experience to be successful in society (Astin & Astin, 2000). The identified connection between Bar-On’s Emotional-Social Intelligence and Kouzes and Posner’s
Leadership Practices model offers even more evidence that these two constructs can provide significant impacts on the development of adaptive, caring, and empowering leaders through the higher education process.
155
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166 APPENDIX A
Division of Educational Administration and Bowling Green State University Leadership Studies 510 Education Building School of Leadership and Policy Studies Bowling Green, Ohio 43403-0250 (419) 372-7377 FAX: (419) 372-8448 www.bgsu.edu/colleges/edhd/LPS
Informed Consent Letter: Student Leader
Principal Investigator: Bryan Cavins 419-352-6939 109 Perry Field House, BGSU [email protected] Bowling Green, OH 43403
Project Title: The Relationship between Emotional Intelligence and Leadership Practices among College Student Leaders
March 21, 2005
Dear Student Leader:
I am a doctoral student in the Leadership Studies program at Bowling Green State University conducting research for my dissertation. The topic of my dissertation is the Relationship between Emotional Intelligence and Leadership Practices among College Student Leaders. I am inviting you to voluntarily participate in my study, but you are in no way obligated.
The purpose of this study is to explore the relationship between emotional intelligence (using Bar-On’s Emotional Quotient Inventory, EQ-i) and student leadership practices (as identified by Kouzes and Posner’s Student Leadership Practices instrument, S-LPI) among university students enrolled in the President’s Leadership Academy (PLA) at Bowling Green State University. This study is NOT a program assessment; I am not trying to assess the effectiveness of the PLA. My interests are in the connections and differences between the two test instruments. This study intends to provide data that will encourage student leadership program developers and instructors, associated with both curricular and co-curricular programs in either student affairs or academic affairs, to include emotional intelligence training and development opportunities to enhance leadership development in higher education.
Your participation in this study involves your completion of two hand-written, self-report surveys and one demographic information sheet. The first survey is designed to measure student leadership practices (Kouzes & Posner – Student Leadership Practices Inventory, S-LPI) and the other survey measures social and emotional intelligence quotient (Bar-On – Emotional Quotient Inventory, EQ-i). In total, you will allocate approximately 45 minutes to one hour completing the two instruments and demographic survey sheet. The Bar-On Emotional Quotient Inventory takes approximately 30-40 minutes to complete and the Kouzes and Posner Student Leadership Practices requires approximately 15-20 minutes.
167 There are little or no risks associated with this study. As the facilitator of this study, I will attempt to make you as comfortable as possible at all times. There are no foreseeable risks greater than those encountered in your daily life.
All information you provide will remain confidential. I will keep the information in a locked drawer in my office. I will not audio or videotape you at anytime. You will be assigned a code number that will help me keep data collection instruments and answer sheets organized. I will be the only person who will have access to both the participant code list and the data collection sheets. Please DO NOT put your names on any of the data collection instruments. Additionally, I will only report data in summary form and will not report individual scores.
It is important that you have been informed that your completion and submission of the survey instruments indicates your consent to participate.
Your participation in this study is voluntary and you may withdraw from the study at anytime or refuse to take part in any activity in which you feel uncomfortable. It is my responsibility to answer all questions and concerns about the study and you have the right to request a summary or copy of the results of the study.
If you have further questions or concerns with regard to this project, please let me know now. If you decide later that you have questions or concerns, please contact me via telephone at 419-352-6939 or email at [email protected]. You may also contact my advisor, Dr. Patrick Pauken by telephone at 419-372-2550 or by email at [email protected]. Additionally, if you have any questions regarding the conduct of this project or your rights as a participant, please do not hesitate to contact the Chair of the Bowling Green State University Human Subjects Review Board (HSRB) via telephone at 419-372-7716 or fax 419-372-6916 or by email at [email protected].
Thank you very much for your time and participation.
Sincerely,
Bryan J. Cavins Dr. Patrick Pauken Doctoral Candidate Associate Professor Advisor to Bryan J. Cavins 168
Informed Consent Script
Good Evening PLA members,
My name is Bryan Cavins and I am a doctoral student in the Leadership Studies program at Bowling Green State University, and I am conducting a research study on Emotional Intelligence and Student Leadership Practices as partial fulfillment of the requirements for completion of a terminal degree in the Leadership Studies program here at the University.
Tonight, I am formally asking each of you to participate in my study. Your participation is not mandatory, and if you chose not to participate, there will be no hard feelings or repercussions of any sort. Additionally, your participation in this study will in no way affect your enrollment in the President’s Leadership Academy at this university.
This research is strictly for educational purposes and is not designed to evaluate the President’s Leadership Academy or your performance within the program. Primarily, I want to know the relationships between Emotional Intelligence and Student Leadership Practices.
At this time, I am going to give each of you an Informed Consent Document. Please follow along while I read it out loud. You will not need to sign or return this document to me. Please keep it for your records.
I will read the Informed Consent Document out loud
At this time I would like to ask if anyone has any questions or concerns regarding the study.
I will answer any and all questions to the satisfaction of the potential participants
Upon seeing no further questions, I will begin distributing the test instruments. However, before I do that, I would like to emphasize that your open and honest responses to the survey questions is vital to the validity of this study. Remember that your answers are completely confidential! Upon turning in your answers, there will be no way for me to determine who filled out each document.
After all test instruments are collected, I will thank them for their time.
169 APPENDIX B
Division of Educational Administration and Bowling Green State University Leadership Studies 510 Education Building School of Leadership and Policy Studies Bowling Green, Ohio 43403-0250 (419) 372-7377 FAX: (419) 372-8448 www.bgsu.edu/colleges/edhd/LPS
Informed Consent Letter: Director
Principal Investigator: Bryan Cavins 419-352-6939 109 Perry Field House, BGSU [email protected] Bowling Green, OH 43403
Project Title: The Relationship between Emotional Intelligence and Leadership Practices among College Student Leaders
March 21, 2005
Dear Leadership Program Director:
I am a doctoral student in the Leadership Studies program at Bowling Green State University conducting research for my dissertation. The topic of my dissertation is the Relationship between Emotional Intelligence and Leadership Practices among College Student Leaders. I am inviting you to voluntarily participate in my study, but you are in no way obligated.
The purpose of this study is to explore the relationship between emotional intelligence (using Bar-On’s Emotional Quotient Inventory, EQ-i) and student leadership practices (as identified by Kouzes and Posner’s Student Leadership Practices instrument, S-LPI) among university students enrolled in the President’s Leadership Academy (PLA) at Bowling Green State University. This study is NOT a program assessment; I am not trying to assess the effectiveness of the PLA. My interests are in the connections and differences between the two test instruments. This study intends to provide data that will encourage student leadership program developers and instructors, associated with both curricular and co-curricular programs in either student affairs or academic affairs, to include emotional intelligence training and development opportunities to enhance leadership development in higher education.
The student leaders will complete the aforementioned instruments; however, your participation in this study involves the completion of a “Student Leader Performance Placement Worksheet.” This worksheet asks that you review the program performance of the 87 student leaders currently enrolled in the President’s Leadership Academy at Bowling Green State University. After reviewing their performance within the program, you will be asked to pick 22 or approximately 25% of the students you feel represent “Top Performers” within the program and 22 or approximately 25% of the students you feel represent “Bottom Performers” within the program. In the tables provided in the worksheet, please write the first and last names of the students you feel fit into the top or bottom 22 or 25% of performers within the program. This activity should not take you longer than 30 minutes to complete.
170 All information you and the student leaders provide will remain confidential. I will keep the information in a locked drawer in my office. I will not audio or videotape you or the students at anytime. The data collection instruments will be completed confidentially, so that there will be no way to match your specific placement with individual student leaders. Additionally, I will only report data in summary form and will not report individual scores or placements. In summary, you will not have access to individual student leader scores on the instruments, and the student leaders will not have access to your list of performance placement.
It is important that you have been informed that your completion and submission of the placement worksheet indicate your consent to participate.
Your participation in this study is voluntary and you may withdraw from the study at anytime or refuse to take part in any activity in which you feel uncomfortable. It is my responsibility to answer all questions and concerns about the study. In addition, you have the right to request a summary or copy of the results of the study.
If you have further questions or concerns with regard to this project, please let me know now. If you decide later that you have questions or concerns, please contact me via telephone at 419-352-6939 or email at [email protected]. You may also contact my advisor, Dr. Patrick Pauken by telephone at 419-372-2550 or by email at [email protected]. Additionally, if you have any questions regarding the conduct of this project or your rights as a participant, please do not hesitate to contact the Chair of the Bowling Green State University Human Subjects Review Board (HSRB) via telephone at 419-372-7716 or fax 419-372-6916 or by email at [email protected].
Thank you very much for your time and participation.
Sincerely,
Bryan J. Cavins Dr. Patrick Pauken Doctoral Candidate Associate Professor Advisor to Bryan J. Cavins
171 APPENDIX C
Cavins’ Dissertation Research Demographic Information Survey
Directions: Please review the following demographic questions and provide a written response where indicated or blacken in the circle that represents your demographic information. Thank you.
1. What is your gender?
o Male o Female
2. What is your age?
3. What is your current GPA?
4. What academic college are you currently enrolled?
o College of Arts and Sciences o College of Health & Human Services o College of Business Administration o College of Musical Arts o College of Education & Human o College of Technology Development o Undecided o College - Firelands
5. In what year are you currently enrolled in the President’s Leadership Academy?
o First o Third o Second o Fourth/Fifth
6. What is your race?
o White o Native American o African-American o Multiracial o Hispanic/Latino o Other o Asian-Pacific Islander
7. What is the highest level of education your mother has completed?
o Less than High School o 4-year college degree (BA, BS) o High School/GED o Master’s Degree o Some college o Doctoral Degree o 2-year college degree (Associates) o Professional Degree (MD, JD)
8. What is the highest level of education your father has completed?
o Less than High School o 4-year college degree (BA, BS) o High School/GED o Master’s Degree o Some college o Doctoral Degree o 2-year college degree (Associates) o Professional Degree (MD, JD)
172
APPENDIX D
Cavins’ Dissertation Research Student Leader Performance Placement Worksheet
Directions: From your perspective, please choose approximately 25% of the students enrolled in the President’s Leadership Academy at Bowling Green State University that you feel represent “Top Performers” within the program. Likewise, choose approximately 25% of the students enrolled in the program that you feel represent “Bottom Performers” within the program. It is not necessary to rank the students within the groups. The order in which the names are listed with each table is not important.
In the tables provided, please write the first and last names of the students you feel fit into the top (left side) or bottom (right side) 25% of performers within the program. (Put one name per open cell, up to 25% in each table). The unused names will represent the middle 50% of performers within the program.
Top Performers in the PLA: Bottom Performers in the PLA:
173
APPENDIX E
STUDENT LEADERSHIP PRACTICES INVENTORY – SELF
Instructions
On the next two pages are 30 statements describing various leadership behaviors. Please read each statement carefully. Then rate yourself in terms of how frequently you engage in the behavior described. This is not a test (there are no right or wrong answers). The usefulness of the feedback from this inventory will depend on how honest you are with yourself and how frequently you actually engage in each of these behaviors.
Consider each statement in the context of a student organization with which you are now (or have been most) involved with. This organization could be a club, team, chapter, group, unit, hall, program, project, and the like. Maintain a consistent organizational perspective as you respond to each statement. The rating scale provides five choices:
(1) If you RARELY or SELDOM do what is described in the statement, circle the number “1” (2) If you do what is described ONCE IN A WHILE, circle the number two “2” (3) If you SOMETIMES do what is described, circle the number three “3” (4) If you OFTEN do what is described, circle the number four “4” (5) If you do what is described VERY FREQUENTLY or ALMOST ALWAYS, circle the number “5”
In selecting the response, be realistic about the extent to which you actually engage in the behavior. Do not answer in terms of how you would like to see yourself or in terms of what you should be doing. Answer in terms of how you typically behave.
For example, the first statement is “I set a personal example of what I expect from other people.” If you believe you do this once in a while, circle the number “2”. If you believe you set a personal example of what you expect from others fairly often, circle the number “4”. Select and circle only one option (response number) for each statement.
Please respond to every statement. If you can’t respond to a statement (or feel that it doesn’t apply), record a “1”. When you have responded to all 30 statements, please turn to the response sheet on the back page and transfer your responses as instructed.
Thank you.
© Copyright 2005. James M. Kouzes and Barry Z. Posner. All rights reserved. 174
STUDENT LEADERSHIP PRACTICES INVENTORY – SELF
How frequently do you typically engage in the following behaviors and actions? Circle the number to the right of each statement, using the scale below, that best applies.
1 2 3 4 5 RARELY or ONCE IN A SOMETIMES OFTEN VERY SELDOM WHILE FREQUENTLY
1. I set a personal example of what I expect from other 1 2 3 4 5 people.
2. I look ahead and communicate about what I believe 1 2 3 4 5 will affect us in the future.
3. I look around for ways to develop and challenge my 1 2 3 4 5 skills and abilities.
4. I foster cooperative rather than competitive 1 2 3 4 5 relationships among people I work with.
5. I praise people for a job well done. 1 2 3 4 5
6. I spend time and energy making sure that people in our organization adhere to the principles and 1 2 3 4 5 standards we have agreed upon.
7. I describe to others in our organization what we 1 2 3 4 5 should be capable of accomplishing.
8. I look for ways that others can try out new ideas and 1 2 3 4 5 methods.
9. I actively listen to diverse points of view. 1 2 3 4 5
10. I encourage others as they work on activities and 1 2 3 4 5 programs in our organization.
11. I follow through on the promises and commitments I 1 2 3 4 5 make in this organization.
12. I talk with others about sharing a vision of how much 1 2 3 4 5 better the organization could be in the future.
13. I keep current on events and activities that might 1 2 3 4 5 effect our organization.
14. I treat others with dignity and respect. 1 2 3 4 5
15. I give people in our organization support and express 1 2 3 4 5 appreciation for their contributions.
© 2005. James M. Kouzes and Barry Z. Posner. All rights reserved. 175
1 2 3 4 5 RARELY or ONCE IN A SOMETIMES OFTEN VERY SELDOM WHILE FREQUENTLY
16. I find ways to get feedback about how my actions 1 2 3 4 5 affect other people’s performance.
17. I talk with others about how their own interests can 1 2 3 4 5 be met by working toward a common goal.
18. When things do not go as we expected, I ask, “What 1 2 3 4 5 can we learn from this experience?”
19. I support the decisions that other people in our 1 2 3 4 5 organization make on their own.
20. I make it a point to publicly recognize people who 1 2 3 4 5 show commitment to our values.
21. I build consensus on an agreed-upon set of values 1 2 3 4 5 for our organization.
22. I am upbeat and positive when talking about what our 1 2 3 4 5 organization aspires to accomplish.
23. I make sure that we set goals and make specific plans 1 2 3 4 5 for the projects we undertake.
1 2 3 4 5 24. I give others a great deal of freedom and choice in deciding how to do their work.
25. I find ways for us to celebrate accomplishments. 1 2 3 4 5
26. I talk about the values and principles that guide my actions. 1 2 3 4 5
27. I speak with conviction about the higher purpose and meaning of what we are doing. 1 2 3 4 5
28. I take initiative in experimenting with the way we can do things in our organization. 1 2 3 4 5
29. I provide opportunities for others to take on leadership responsibilities. 1 2 3 4 5
30. I make sure that people in our organization are creatively recognized for their contributions. 1 2 3 4 5
© Copyright 2005. James M. Kouzes and Barry Z. Posner. All rights reserved. 176
APPENDIX F
Tukey HSD and Games-Howell: Student Leadership Performance and Emotional Quotient Inventory Dependent Variable (I) Peformance 3-1 (J) Peformance 3-1 M Dif. (I-J) SE Sig. Total EQ-i Score Middle 50% Performer Bottom 25% Performer 4.492 3.181 0.340 Top 25% Performer Bottom 25% Performer 12.328(*) 3.563 0.003 Top 25% Performer Middle 50% Performer 7.836(*) 3.074 0.034 Self-Actualization Middle 50% Performer Bottom 25% Performer 6.805 3.547 0.141 Top 25% Performer Bottom 25% Performer 14.983(*) 3.973 0.001 Top 25% Performer Middle 50% Performer 8.179 3.427 0.051 Interpersonal Subscale Middle 50% Performer Bottom 25% Performer 6.056 3.334 0.172 Top 25% Performer Bottom 25% Performer 10.956(*) 3.735 0.012 Top 25% Performer Middle 50% Performer 4.900 3.222 0.288 Social Responsibility Middle 50% Performer Bottom 25% Performer 6.348 4.355 0.318 Top 25% Performer Bottom 25% Performer 12.383(*) 4.878 0.035 Top 25% Performer Middle 50% Performer 6.036 4.209 0.329 Stress Management Middle 50% Performer Bottom 25% Performer 3.141 3.632 0.664 Subscale Top 25% Performer Bottom 25% Performer 10.456(*) 4.068 0.033 Top 25% Performer Middle 50% Performer 7.314 3.510 0.101 Stress Tolerance Middle 50% Performer Bottom 25% Performer 5.608 3.380 0.228 Top 25% Performer Bottom 25% Performer 10.672(*) 3.786 0.017 Top 25% Performer Middle 50% Performer 5.064 3.267 0.274 Adaptability Subscale Middle 50% Performer Bottom 25% Performer 3.811 3.405 0.505 Top 25% Performer Bottom 25% Performer 12.211(*) 3.814 0.006 Top 25% Performer Middle 50% Performer 8.400(*) 3.291 0.034 Problem Solving Middle 50% Performer Bottom 25% Performer 6.495 3.595 0.175 Top 25% Performer Bottom 25% Performer 16.167(*) 4.027 0.000 Top 25% Performer Middle 50% Performer 9.671(*) 3.474 0.019 General Mood Subscale Middle 50% Performer Bottom 25% Performer 8.702(*) 3.383 0.038 Top 25% Performer Bottom 25% Performer 17.394(*) 3.090 0.000 (Unequal Variance) Top 25% Performer Middle 50% Performer 8.693(*) 2.443 0.002 Optimism Middle 50% Performer Bottom 25% Performer 5.894 3.857 0.284 Top 25% Performer Bottom 25% Performer 16.872(*) 4.320 0.001 Top 25% Performer Middle 50% Performer 10.979(*) 3.727 0.012 Happiness Middle 50% Performer Bottom 25% Performer 9.444 4.290 0.090 Top 25% Performer Bottom 25% Performer 14.844(*) 4.239 0.005 (Unequal Variance) Top 25% Performer Middle 50% Performer 5.400 2.538 0.094 (*) Bold. The mean difference is significant at the .05 level. (Unequal Variance). Variable failed the Levene Test of Homogeneity of Variance, therefore necessitated a Games-Howell Post Hoc.
Tukey HSD: Student Leadership Program Performance and Student Leadership Practice Inventory Dependent Variable (I) Peformance 3-1 (J) Peformance 3-1 M Dif. (I-J) SE Sig. Modeling the Way Middle 50% Performer Bottom 25% Performer 2.768(*) 0.846 0.005 Top 25% Performer Bottom 25% Performer 4.011(*) 0.948 0.000 Top 25% Performer Middle 50% Performer 1.243 0.818 0.288 Inspiring a Shared Vision Middle 50% Performer Bottom 25% Performer 3.390(*) 0.944 0.002 Top 25% Performer Bottom 25% Performer 4.383(*) 1.057 0.000 Top 25% Performer Middle 50% Performer 0.993 0.912 0.524 Challenging the Process Middle 50% Performer Bottom 25% Performer 2.344(*) 0.952 0.042 Top 25% Performer Bottom 25% Performer 3.394(*) 1.067 0.006 Top 25% Performer Middle 50% Performer 1.050 0.920 0.492 (*) Bold. The mean difference is significant at the .05 level.
177
APPENDIX G
Independent Sample Test: Gender and Emotional Quotient Inventory
Levene's Test t-test for Equality of Means Sig. (2- Mean Std. Error F Sig. t df tailed) Difference Difference Total EQ-i Score Equal variances assumed 0.054 0.817 -1.278 71 0.205 -3.598 2.815 Equal variances not assumed -1.270 56.276 0.209 -3.598 2.832 Intrapersonal Equal variances Subscale assumed 0.545 0.463 -1.357 71 0.179 -4.104 3.024 Equal variances not assumed -1.423 65.764 0.160 -4.104 2.885 Self-Regard Equal variances assumed 3.543 0.064 -1.862 71 0.067 -5.156 2.769 Equal variances not assumed -2.018 69.871 0.047 -5.156 2.555 Emotional Self- Equal variances Awareness assumed 1.313 0.256 0.765 71 0.447 2.327 3.044 Equal variances not assumed 0.801 65.653 0.426 2.327 2.905 Assertiveness Equal variances assumed 0.118 0.732 -0.275 71 0.784 -1.056 3.843 Equal variances not assumed -0.275 57.468 0.784 -1.056 3.842 Independence Equal variances assumed 3.301 0.073 -1.336 71 0.186 -3.417 2.556 Equal variances not assumed -1.431 68.661 0.157 -3.417 2.388 Self-Actualization Equal variances assumed 1.780 0.186 -2.423 71 0.018 -7.471 3.083 Equal variances not assumed -2.313 49.032 0.025 -7.471 3.230 Interpersonal Equal variances Subscale assumed 0.338 0.563 -0.434 71 0.666 -1.262 2.908 Equal variances not assumed -0.426 54.143 0.672 -1.262 2.960 Empathy Equal variances assumed 0.110 0.742 -0.020 71 0.984 -0.067 3.402 Equal variances not assumed -0.020 58.716 0.984 -0.067 3.379 Social Equal variances Responsibility assumed 0.041 0.841 -0.385 71 0.702 -1.441 3.746 Equal variances not assumed -0.378 53.945 0.707 -1.441 3.817 Interpersonal Equal variances Relationships assumed 0.245 0.622 -0.432 71 0.667 -1.242 2.878 Equal variances not assumed -0.428 55.937 0.670 -1.242 2.901 Stress Management Equal variances Subscale assumed 0.512 0.477 -0.924 71 0.359 -2.887 3.125 Equal variances not assumed -0.911 54.815 0.366 -2.887 3.169 Stress Tolerance Equal variances assumed 0.017 0.896 -1.397 71 0.167 -4.052 2.899 Equal variances not assumed -1.392 56.682 0.169 -4.052 2.911 178
Levene's Test t-test for Equality of Means Sig. (2- Mean Std. Error F Sig. t df tailed) Difference Difference Impulse Control Equal variances assumed 0.152 0.698 -0.241 71 0.810 -0.876 3.635 Equal variances not assumed -0.245 60.219 0.808 -0.876 3.581 Adaptability Equal variances Subscale assumed 0.376 0.542 -0.591 71 0.557 -1.780 3.014 Equal variances not assumed -0.589 56.839 0.558 -1.780 3.023 Reality Testing Equal variances assumed 0.059 0.809 -0.702 71 0.485 -2.283 3.250 Equal variances not assumed -0.719 61.697 0.475 -2.283 3.175 Flexibility Equal variances assumed 0.000 0.998 0.027 71 0.979 0.078 2.884 Equal variances not assumed 0.028 62.197 0.978 0.078 2.810 Problem Solving Equal variances assumed 0.003 0.956 -0.698 71 0.488 -2.291 3.283 Equal variances not assumed -0.709 60.407 0.481 -2.291 3.231 General Mood Equal variances Subscale assumed 0.505 0.480 -1.702 71 0.093 -4.913 2.886 Equal variances not assumed -1.635 50.085 0.108 -4.913 3.005 Optimism Equal variances assumed 0.046 0.830 -1.302 71 0.197 -4.538 3.485 Equal variances not assumed -1.272 53.097 0.209 -4.538 3.567 Happiness Equal variances assumed 1.061 0.306 -1.708 71 0.092 -5.227 3.060 Equal variances not assumed -1.645 50.568 0.106 -5.227 3.177
Independent Sample Test: Gender and Student Leadership Practices
Levene's Test t-test for Equality of Means Sig. (2- Mean Std. Error F Sig. t df tailed) Difference Difference Modeling the Way Equal variances assumed 5.257 0.025 -0.727 71 0.469 -0.569 0.782 Equal variances not assumed -0.662 41.564 0.512 -0.569 0.860 Inspiring a Shared Equal variances Vision assumed 1.918 0.170 -0.251 71 0.802 -0.221 0.877 Equal variances not assumed -0.237 46.955 0.814 -0.221 0.931 Challenging the Equal variances Process assumed 0.154 0.696 0.202 71 0.841 0.170 0.842 Equal variances not assumed 0.201 56.304 0.842 0.170 0.847 Enabling Others to Equal variances Act assumed 6.067 0.016 -0.309 71 0.758 -0.190 0.614 Equal variances not assumed -0.286 43.826 0.776 -0.190 0.664 Encouraging the Equal variances Heart assumed 1.134 0.290 -0.225 71 0.823 -0.201 0.892 Equal variances not assumed -0.218 51.291 0.829 -0.201 0.922 Bold Italicized. Equal variance could not be assumed. 179
APPENDIX H
ANOVA: Age Groups and Emotional Quotient Inventory Dependent Variable SS df MS F Sig. Total EQ-i Score Between Groups 1,347.285 4 336.821 2.689 0.038 Within Groups 8,392.492 67 125.261 Total 9,739.778 71 Intrapersonal Subscale Between Groups 1,222.609 4 305.652 2.045 0.098 Within Groups 10,014.003 67 149.463 Total 11,236.611 71 Self-Regard Between Groups 468.801 4 117.200 0.846 0.501 Within Groups 9,285.810 67 138.594 Total 9,754.611 71 Emotional Self-Awareness Between Groups 1,383.527 4 345.882 2.401 0.058 Within Groups 9,651.973 67 144.059 Total 11,035.500 71 Assertiveness Between Groups 1,132.775 4 283.194 1.140 0.345 Within Groups 16,648.544 67 248.486 Total 17,781.319 71 Independence Between Groups 254.411 4 63.603 0.555 0.696 Within Groups 7,685.089 67 114.703 Total 7,939.500 71 Self-Actualization Between Groups 1,535.787 4 383.947 2.323 0.066 Within Groups 11,075.991 67 165.313 Total 12,611.778 71 Interpersonal Subscale Between Groups 1,780.419 4 445.105 3.533 0.011 Within Groups 8,441.526 67 125.993 Total 10,221.944 71 Empathy Between Groups 2,861.886 4 715.471 4.233 0.004 Within Groups 11,323.989 67 169.015 Total 14,185.875 71 Social Responsibility Between Groups 1,994.361 4 498.590 2.196 0.079 Within Groups 15,211.583 67 227.039 Total 17,205.944 71 Interpersonal Relationships Between Groups 951.119 4 237.780 1.836 0.132 Within Groups 8,677.756 67 129.519 Total 9,628.875 71 Stress Management Between Groups 448.372 4 112.093 0.650 0.629 Subscale Within Groups 11,557.503 67 172.500 Total 12,005.875 71 Stress Tolerance Between Groups 684.026 4 171.006 1.174 0.330 Within Groups 9,757.752 67 145.638 Total 10,441.778 71 Impulse Control Between Groups 334.317 4 83.579 0.353 0.841 Within Groups 15,855.558 67 236.650 Total 16,189.875 71 Adaptability Subscale Between Groups 1,177.496 4 294.374 1.980 0.108 Within Groups 9,962.823 67 148.699 Total 11,140.319 71 Reality Testing Between Groups 1,470.612 4 367.653 2.139 0.085 Within Groups 11,514.041 67 171.851 Total 12,984.653 71 Flexibility Between Groups 54.602 4 13.651 0.091 0.985 Within Groups 10,085.176 67 150.525 Total 10,139.778 71 Problem Solving Between Groups 1,804.576 4 451.144 2.629 0.042 Within Groups 11,496.535 67 171.590 Total 13,301.111 71 General Mood Subscale Between Groups 1,492.780 4 373.195 2.835 0.031 Within Groups 8,821.206 67 131.660 Total 10,313.986 71 180
Dependent Variable SS df MS F Sig. Optimism Between Groups 1,056.759 4 264.190 1.255 0.296 Within Groups 14,102.560 67 210.486 Total 15,159.319 71 Happiness Between Groups 1,926.008 4 481.502 3.387 0.014 Within Groups 9,525.867 67 142.177 Total 11,451.875 71 Bold. F is significant at the .05 level. Bold Italicized. Games-Howell (GH) Post Hoc Test was used because “Equal Variance” could not be assumed. GH did not find Significant differences between individual age groups (t-test was not significant at p = 0.05)
ANOVA: Age Groups and Student Leadership Practices Inventory Dependent Variable SS df MS F Sig. Modeling the Way Between Groups 81.925 4 20.481 2.037 0.099 Within Groups 673.728 67 10.056 Total 755.653 71 Inspiring a Shared Vision Between Groups 46.592 4 11.648 0.872 0.486 Within Groups 895.394 67 13.364 Total 941.986 71 Challenging the Process Between Groups 87.683 4 21.921 1.888 0.123 Within Groups 777.817 67 11.609 Total 865.500 71 Enabling Others to Act Between Groups 39.685 4 9.921 1.575 0.191 Within Groups 421.967 67 6.298 Total 461.653 71 Encouraging the Heart Between Groups 110.663 4 27.666 2.239 0.074 Within Groups 827.948 67 12.357 Total 938.611 71
181
APPENDIX I
Tukey HSD and Games-Howell: Age Groups and Emotional Quotient Inventory Dependent Variable (I) Age (J) Age M Difference (I-J) SE Sig. Total EQ-i Score 19 18 5.246 4.708 0.798 20 18 8.900 4.213 0.227 (Consistency between ANOVA & Tukey 20 19 3.654 3.854 0.877 HSD) 21 18 12.200(*) 4.335 0.049 21 19 6.954 3.987 0.415 21 20 3.300 3.389 0.866 22 18 15.000 6.130 0.116 22 19 9.754 5.890 0.468 22 20 6.100 5.502 0.801 22 21 2.800 5.596 0.987 Interpersonal Subscale 19 18 7.854 4.721 0.463 19 21 0.354 3.999 1.000 (Consistency between ANOVA & Tukey 20 18 7.867 4.225 0.348 HSD) 20 19 0.013 3.865 1.000 20 21 0.367 3.398 1.000 21 18 7.500 4.347 0.426 22 18 23.100(*) 6.148 0.003 22 19 15.246 5.907 0.085 22 20 15.233 5.518 0.056 22 21 15.600 5.612 0.053 Empathy 19 18 10.338 5.468 0.332 19 20 3.080 4.477 0.958 (Consistency between ANOVA & Tukey 19 21 1.738 4.632 0.996 HSD) 20 18 7.258 4.893 0.577 21 18 8.600 5.035 0.436 21 20 1.342 3.936 0.997 22 18 28.800(*) 7.121 0.001 22 19 18.462 6.841 0.065 22 20 21.542(*) 6.391 0.011 22 21 20.200(*) 6.500 0.022 Problem Solving 18 19 0.115 5.510 1.000 20 18 4.042 4.930 0.924 (ANOVA identified overall differenced 20 19 4.157 4.511 0.888 between age groups, but Tukey HSD did 21 18 10.800 5.073 0.220 not detect pairwise differences) 21 19 10.915 4.667 0.146 21 20 6.758 3.966 0.438 22 18 15.300 7.175 0.219 22 19 15.415 6.893 0.179 22 20 11.258 6.440 0.412 22 21 4.500 6.550 0.959 General Mood Subscale 19 18 6.723 6.026 0.797 20 18 11.133 4.663 0.190 (ANOVA identified overall differences 20 19 4.410 4.303 0.840 between age groups, but the Game- 21 18 12.450 5.024 0.151 Howell Post Hoc did not detect pairwise 21 19 5.727 4.691 0.740 differences) 21 20 1.317 2.727 0.988 22 18 16.600 9.193 0.442 22 19 9.877 9.016 0.804 22 20 5.467 8.168 0.954 22 21 4.150 8.379 0.984 Happiness 19 18 10.954 5.015 0.198 20 18 15.175(*) 4.488 0.010 (Consistency between ANOVA & Tukey 20 19 4.221 4.106 0.842 HSD) 20 21 0.325 3.610 1.000 21 18 14.850(*) 4.618 0.017 21 19 3.896 4.248 0.889 22 18 15.800 6.531 0.123 22 19 4.846 6.275 0.938 22 20 0.625 5.862 1.000 22 21 0.950 5.962 1.000 (*) Bold. The mean difference is significant at the .05 level.
182
APPENDIX J
ANOVA: GPA Clusters and Emotional Quotient Inventory Dependent Variables Groups SS df MS F Sig. Total EQ-i Score Between Groups 1,036.508 3 345.503 2.746 0.050 Within Groups 8,304.763 66 125.830 Total 9,341.271 69 Intrapersonal Subscale Between Groups 720.650 3 240.217 1.533 0.214 Within Groups 10,344.793 66 156.739 Total 11,065.443 69 Self-Regard Between Groups 714.154 3 238.051 1.795 0.157 Within Groups 8,752.717 66 132.617 Total 9,466.871 69 Emotional Self-Awareness Between Groups 1,164.200 3 388.067 2.501 0.067 Within Groups 10,240.086 66 155.153 Total 11,404.286 69 Assertiveness Between Groups 250.544 3 83.515 0.316 0.814 Within Groups 17,425.799 66 264.027 Total 17,676.343 69 Independence Between Groups 363.112 3 121.037 1.080 0.364 Within Groups 7,398.659 66 112.101 (Unequal Variance) Total 7,761.771 69 Self-Actualization Between Groups 1,889.757 3 629.919 4.219 0.009 Within Groups 9,855.115 66 149.320 Total 11,744.871 69 Interpersonal Subscale Between Groups 485.732 3 161.911 1.142 0.339 Within Groups 9,354.839 66 141.740 Total 9,840.571 69 Empathy Between Groups 516.774 3 172.258 0.874 0.459 Within Groups 13,006.212 66 197.064 Total 13,522.986 69 Social Responsibility Between Groups 1,503.802 3 501.267 2.235 0.092 Within Groups 14,801.283 66 224.262 Total 16,305.086 69 Interpersonal Relationships Between Groups 172.990 3 57.663 0.392 0.759 Within Groups 9,696.510 66 146.917 Total 9,869.500 69 Stress Management Between Groups 790.878 3 263.626 1.581 0.202 Subscale Within Groups 11,008.565 66 166.796 Total 11,799.443 69 Stress Tolerance Between Groups 1,056.604 3 352.201 2.581 0.061 Within Groups 9,007.739 66 136.481 Total 10,064.343 69 Impulse Control Between Groups 422.392 3 140.797 0.596 0.620 Within Groups 15,583.893 66 236.120 Total 16,006.286 69 Adaptability Subscale Between Groups 1,128.539 3 376.180 2.652 0.056 Within Groups 9,362.733 66 141.860 Total 10,491.271 69 Reality Testing Between Groups 778.072 3 259.357 1.506 0.221 Within Groups 11,364.270 66 172.186 Total 12,142.343 69 Flexibility Between Groups 272.318 3 90.773 0.632 0.597 Within Groups 9,480.553 66 143.645 Total 9,752.871 69 Problem Solving Between Groups 2,604.511 3 868.170 5.554 0.002 Within Groups 10,316.932 66 156.317 Total 12,921.443 69 General Mood Subscale Between Groups 1,680.476 3 560.159 4.306 0.008 Within Groups 8,586.110 66 130.093 Total 10,266.586 69 183
Dependent Variables Groups SS df MS F Sig. Optimism Between Groups 2,754.603 3 918.201 5.058 0.003 Within Groups 11,981.340 66 181.535 Total 14,735.943 69 Happiness Between Groups 1,503.167 3 501.056 3.315 0.025 Within Groups 9,974.319 66 151.126 (Unequal Variance) Total 11,477.486 69 Bold. F is significant at the .05 level. (Unequal Variance). Variable failed the Levene Test of Homogeneity of Variance, therefore necessitated a Games-Howell Post Hoc.
ANOVA: GPA Clusters and Student Leadership Practices Inventory Dependent Variables Groups SS df MS F Sig. Modeling the Way Between Groups 56.847 3 18.949 1.834 0.149 Within Groups 681.739 66 10.329 Total 738.586 69 Inspiring a Shared Vision Between Groups 114.258 3 38.086 3.046 0.035 Within Groups 825.185 66 12.503 Total 939.443 69 Challenging the Process Between Groups 70.834 3 23.611 1.955 0.129 Within Groups 797.008 66 12.076 Total 867.843 69 Enabling Others to Act Between Groups 26.875 3 8.958 1.441 0.239 Within Groups 410.397 66 6.218 Total 437.271 69 Encouraging the Heart Between Groups 45.025 3 15.008 1.099 0.356 Within Groups 900.975 66 13.651 Total 946.000 69 Bold. F is significant at the .05 level.
184
APPENDIX K
Tukey HSD: GPA Clusters and Emotional Quotient Inventory Dependent Variables (I) GPA Clustered (J) GPA Clustered M Diff. (I-J) SE Sig. Total EQ-i Score 2.50 - 2.99 1.50 - 2.49 4.10 4.453 0.793 3.00 - 3.49 1.50 - 2.49 4.49 4.175 0.705 (Consistency between ANOVA & Tukey HSD) 3.00 - 3.49 2.50 - 2.99 0.39 3.792 1.000 3.50 - 4.00 1.50 - 2.49 10.85 4.112 0.050 3.50 - 4.00 2.50 - 2.99 6.75 3.723 0.276 3.50 - 4.00 3.00 - 3.49 6.36 3.386 0.247 Self-Actualization 2.50 - 2.99 1.50 - 2.49 8.18 4.851 0.339 3.00 - 3.49 1.50 - 2.49 11.18 4.548 0.076 (Consistency between ANOVA & Tukey HSD) 3.00 - 3.49 2.50 - 2.99 3.00 4.131 0.886 3.50 - 4.00 1.50 - 2.49 15.57 4.480 0.005 3.50 - 4.00 2.50 - 2.99 7.39 4.055 0.272 3.50 - 4.00 3.00 - 3.49 4.39 3.688 0.635 Problem Solving 2.50 - 2.99 1.50 - 2.49 12.89 4.963 0.055 2.50 - 2.99 3.00 - 3.49 6.13 4.227 0.473 (Consistency between ANOVA & Tukey HSD) 3.00 - 3.49 1.50 - 2.49 6.76 4.653 0.472 3.50 - 4.00 1.50 - 2.49 17.13 4.583 0.002 3.50 - 4.00 2.50 - 2.99 4.24 4.149 0.737 3.50 - 4.00 3.00 - 3.49 10.38 3.774 0.038 General Mood Subscale 2.50 - 2.99 1.50 - 2.49 3.14 4.528 0.899 3.00 - 3.49 1.50 - 2.49 6.80 4.245 0.385 (Consistency between ANOVA & Tukey HSD) 3.00 - 3.49 2.50 - 2.99 3.66 3.856 0.779 3.50 - 4.00 1.50 - 2.49 13.32 4.181 0.012 3.50 - 4.00 2.50 - 2.99 10.18 3.785 0.044 3.50 - 4.00 3.00 - 3.49 6.52 3.443 0.241 Optimism 2.50 - 2.99 1.50 - 2.49 10.91 5.348 0.184 2.50 - 2.99 3.00 - 3.49 4.95 4.555 0.698 (Consistency between ANOVA & Tukey HSD) 3.00 - 3.49 1.50 - 2.49 5.96 5.015 0.637 3.50 - 4.00 1.50 - 2.49 17.52 4.939 0.004 3.50 - 4.00 2.50 - 2.99 6.61 4.472 0.456 3.50 - 4.00 3.00 - 3.49 11.56 4.067 0.030 Happiness 1.50 - 2.49 2.50 - 2.99 4.00 6.129 0.914 3.00 - 3.49 1.50 - 2.49 6.33 4.522 0.517 (ANOVA identified overall differences between GPA clusters, but Games- 3.00 - 3.49 2.50 - 2.99 10.33 5.115 0.214 Howell did not detect pairwise 3.50 - 4.00 1.50 - 2.49 7.43 4.409 0.365 differences) 3.50 - 4.00 2.50 - 2.99 11.43 5.015 0.139 3.50 - 4.00 3.00 - 3.49 1.10 2.835 0.980 Bold. The mean difference is significant at the .05 level.
Tukey HSD: GPA Clusters and Student Leadership Practices Inventory Dependent Variables (I) GPA Clustered (J) GPA Clustered M Diff. (I-J) SE Sig. Inspiring a Shared Vision 2.50 - 2.99 1.50 - 2.49 2.62 1.404 0.251 2.50 - 2.99 3.00 - 3.49 0.06 1.195 1.000 (Consistency between ANOVA & Tukey HSD) 3.00 - 3.49 1.50 - 2.49 2.57 1.316 0.217 3.50 - 4.00 1.50 - 2.49 3.92 1.296 0.018 3.50 - 4.00 2.50 - 2.99 1.29 1.174 0.690 3.50 - 4.00 3.00 - 3.49 1.35 1.067 0.588 Bold. The mean difference is significant at the .05 level.
185
APPENDIX L
ANOVA: Academic Colleges and Emotional Quotient Inventory Dependent Variable Groups SS df MS F Sig. Total EQ-i Score Between Groups 902.828 6 150.471 1.100 0.372 Within Groups 9,028.734 66 136.799 Total 9,931.562 72 Intrapersonal Subscale Between Groups 572.657 6 95.443 0.576 0.748 Within Groups 10,927.973 66 165.575 Total 11,500.630 72 Self-Regard Between Groups 361.211 6 60.202 0.418 0.864 Within Groups 9,494.789 66 143.860 Total 9,856.000 72 Emotional Self-Awareness Between Groups 182.099 6 30.350 0.178 0.982 Within Groups 11,264.531 66 170.675 Total 11,446.630 72 Assertiveness Between Groups 1,552.436 6 258.739 1.031 0.413 Within Groups 16,562.907 66 250.953 Total 18,115.342 72 Independence Between Groups 624.918 6 104.153 0.906 0.496 Within Groups 7,585.822 66 114.937 Total 8,210.740 72 Self-Actualization Between Groups 539.176 6 89.863 0.491 0.813 Within Groups 12,074.988 66 182.954 Total 12,614.164 72 Interpersonal Subscale Between Groups 1,370.164 6 228.361 1.671 0.142 Within Groups 9,019.179 66 136.654 Total 10,389.342 72 Empathy Between Groups 945.809 6 157.635 0.786 0.584 Within Groups 13,240.821 66 200.619 Total 14,186.630 72 Social Responsibility Between Groups 1,780.638 6 296.773 1.267 0.284 Within Groups 15,454.841 66 234.164 Total 17,235.479 72 Interpersonal Relationships Between Groups 890.469 6 148.412 1.055 0.399 Within Groups 9,288.900 66 140.741 Total 10,179.370 72 Stress Management Between Groups 770.848 6 128.475 0.748 0.613 Subscale Within Groups 11,342.905 66 171.862 Total 12,113.753 72 Stress Tolerance Between Groups 881.755 6 146.959 1.000 0.433 Within Groups 9,703.369 66 147.021 Total 10,585.123 72 Impulse Control Between Groups 1,048.301 6 174.717 0.761 0.603 Within Groups 15,161.179 66 229.715 Total 16,209.479 72 Adaptability Subscale Between Groups 923.806 6 153.968 0.990 0.439 Within Groups 10,260.167 66 155.457 Total 11,183.973 72 Reality Testing Between Groups 924.875 6 154.146 0.840 0.543 Within Groups 12,107.153 66 183.442 Total 13,032.027 72 Flexibility Between Groups 995.273 6 165.879 1.190 0.323 Within Groups 9,200.809 66 139.406 Total 10,196.082 72 Problem Solving Between Groups 691.934 6 115.322 0.604 0.726 Within Groups 12,609.957 66 191.060 Total 13,301.890 72 186
Dependent Variable Groups SS df MS F Sig. General Mood Subscale Between Groups 1,574.621 6 262.437 1.914 0.091 Within Groups 9,049.626 66 137.116 Total 10,624.247 72 Optimism Between Groups 1,740.365 6 290.061 1.418 0.221 Within Groups 13,496.155 66 204.487 Total 15,236.521 72 Happiness Between Groups 1,275.294 6 212.549 1.314 0.263 Within Groups 10,674.048 66 161.728 Total 11,949.342 72
ANOVA: Academic Colleges and Student Leadership Practices Inventory Dependent Variables Groups SS df MS F Sig. Modeling the Way Between Groups 32.242 6 5.374 0.490 0.813 Within Groups 723.511 66 10.962 Total 755.753 72 Inspiring a Shared Vision Between Groups 52.222 6 8.704 0.644 0.695 Within Groups 892.024 66 13.516 Total 944.247 72 Challenging the Process Between Groups 45.859 6 7.643 0.613 0.719 Within Groups 823.264 66 12.474 Total 869.123 72 Enabling Others to Act Between Groups 46.246 6 7.708 1.224 0.306 Within Groups 415.727 66 6.299 Total 461.973 72 Encouraging the Heart Between Groups 31.733 6 5.289 0.370 0.896 Within Groups 944.048 66 14.304 Total 975.781 72
187
APPENDIX M
ANOVA: Program Cohorts and Emotional Quotient Inventory Dependent Variables Groups SS df MS F Sig. Total EQ-i Score Between Groups 1,385.005 3 461.668 3.727 0.015 Within Groups 8,546.557 69 123.863 Total 9,931.562 72 Intrapersonal Subscale Between Groups 1,322.143 3 440.714 2.988 0.037 Within Groups 10,178.488 69 147.514 Total 11,500.630 72 Self-Regard Between Groups 556.893 3 185.631 1.377 0.257 Within Groups 9,299.107 69 134.770 Total 9,856.000 72 Emotional Self- Between Groups 1,598.773 3 532.924 3.734 0.015 Awareness Within Groups 9,847.857 69 142.723 Total 11,446.630 72 Assertiveness Between Groups 1,058.155 3 352.718 1.427 0.242 Within Groups 17,057.188 69 247.206 Total 18,115.342 72 Independence Between Groups 441.336 3 147.112 1.306 0.279 Within Groups 7,769.404 69 112.600 Total 8,210.740 72 Self-Actualization Between Groups 930.600 3 310.200 1.832 0.149 Within Groups 11,683.564 69 169.327 Total 12,614.164 72 Interpersonal Subscale Between Groups 417.498 3 139.166 0.963 0.415 Within Groups 9,971.844 69 144.519 Total 10,389.342 72 Empathy Between Groups 896.443 3 298.814 1.551 0.209 Within Groups 13,290.188 69 192.611 Total 14,186.630 72 Social Responsibility Between Groups 1,168.685 3 389.562 1.673 0.181 Within Groups 16,066.794 69 232.852 Total 17,235.479 72 Interpersonal Between Groups 200.743 3 66.914 0.463 0.709 Relationships Within Groups 9,978.627 69 144.618 Total 10,179.370 72 Stress Management Between Groups 634.309 3 211.436 1.271 0.291 Subscale Within Groups 11,479.444 69 166.369 Total 12,113.753 72 Stress Tolerance Between Groups 970.496 3 323.499 2.322 0.083 Within Groups 9,614.628 69 139.342 Total 10,585.123 72 Impulse Control Between Groups 485.952 3 161.984 0.711 0.549 Within Groups 15,723.528 69 227.877 Total 16,209.479 72 Adaptability Subscale Between Groups 1,573.475 3 524.492 3.766 0.015 Within Groups 9,610.498 69 139.283 Total 11,183.973 72 Reality Testing Between Groups 2,890.467 3 963.489 6.555 0.001 Within Groups 10,141.560 69 146.979 188
Dependent Variables Groups SS df MS F Sig. Total 13,032.027 72 Flexibility Between Groups 432.892 3 144.297 1.020 0.389 Within Groups 9,763.190 69 141.496 Total 10,196.082 72 Problem Solving Between Groups 1,721.464 3 573.821 3.419 0.022 Within Groups 11,580.427 69 167.832 Total 13,301.890 72 General Mood Subscale Between Groups 1,537.182 3 512.394 3.891 0.013
Within Groups 9,087.064 69 131.697 (Unequal Variance) Total 10,624.247 72 Optimism Between Groups 1,321.223 3 440.408 2.184 0.098 Within Groups 13,915.298 69 201.671 Total 15,236.521 72 Happiness Between Groups 1,419.566 3 473.189 3.101 0.032
Within Groups 10,529.777 69 152.605 (Unequal Variance) Total 11,949.342 72 Bold. F is significant at the .05 level. (Unequal Variance). Variable failed the Levene Test of Homogeneity of Variance, therefore necessitated a Games-Howell Post Hoc.
ANOVA: Program Cohorts and Student Leadership Practices Inventory Modeling the Way Between Groups 68.513 3 22.838 2.293 0.086 Within Groups 687.240 69 9.960 Total 755.753 72 Inspiring a Shared Vision Between Groups 68.687 3 22.896 1.804 0.154 Within Groups 875.560 69 12.689 Total 944.247 72 Challenging the Process Between Groups 82.846 3 27.615 2.423 0.073 Within Groups 786.278 69 11.395 Total 869.123 72 Enabling Others to Act Between Groups 29.133 3 9.711 1.548 0.210 Within Groups 432.840 69 6.273 Total 461.973 72 Encouraging the Heart Between Groups 52.674 3 17.558 1.312 0.277 Within Groups 923.107 69 13.378 Total 975.781 72 Bold. F is significant at the .05 level. 189
APPENDIX N
Tukey HSD and Games-Howell: Program Cohorts Clusters and Emotional Quotient Inventory Dependent Vars. (I) Year in Program (J) Year in Program M Diff. (I-J) SE Sig. Total EQ-i Score Second Year Cohort First Year Cohort 4.450 3.733 0.634 Third Year Cohort First Year Cohort 10.880(*) 3.339 0.009 (Consistency between ANOVA & Tukey HSD) Third Year Cohort Second Year Cohort 6.430 3.563 0.280 Third Year Cohort Fourth and Fifth Year Cohort 3.263 3.909 0.838 Fourth and Fifth Year Cohort First Year Cohort 7.617 4.064 0.249 Fourth and Fifth Year Cohort Second Year Cohort 3.167 4.250 0.878 Intrapersonal Second Year Cohort First Year Cohort 3.713 4.074 0.799 Subscale Third Year Cohort First Year Cohort 10.600(*) 3.644 0.025 Third Year Cohort Second Year Cohort 6.888 3.888 0.296 (Consistency between ANOVA & Tukey HSD) Third Year Cohort Fourth and Fifth Year Cohort 3.950 4.265 0.791 Fourth and Fifth Year Cohort First Year Cohort 6.650 4.435 0.443 Fourth and Fifth Year Cohort Second Year Cohort 2.938 4.638 0.921 Emotional Self- Second Year Cohort First Year Cohort 0.625 4.007 0.999 Awareness Third Year Cohort First Year Cohort 10.430(*) 3.584 0.025 Third Year Cohort Second Year Cohort 9.805 3.825 0.059 (Consistency between ANOVA & Tukey HSD) Third Year Cohort Fourth and Fifth Year Cohort 3.263 4.196 0.864 Fourth and Fifth Year Cohort First Year Cohort 7.167 4.362 0.362 Fourth and Fifth Year Cohort Second Year Cohort 6.542 4.562 0.483 Adaptability Second Year Cohort First Year Cohort 0.737 3.958 0.998 Subscale Third Year Cohort First Year Cohort 10.460(*) 3.541 0.022 Third Year Cohort Second Year Cohort 9.723 3.778 0.058 (Consistency between ANOVA & Tukey HSD) Third Year Cohort Fourth and Fifth Year Cohort 3.660 4.145 0.814 Fourth and Fifth Year Cohort First Year Cohort 6.800 4.309 0.398 Fourth and Fifth Year Cohort Second Year Cohort 6.063 4.507 0.538 Reality Testing First Year Cohort Second Year Cohort 4.475 4.066 0.690 Third Year Cohort First Year Cohort 11.540(*) 3.637 0.012 (Consistency between ANOVA & Tukey HSD) Third Year Cohort Second Year Cohort 16.015(*) 3.881 0.001 Third Year Cohort Fourth and Fifth Year Cohort 6.890 4.258 0.375 Fourth and Fifth Year Cohort First Year Cohort 4.650 4.427 0.720 Fourth and Fifth Year Cohort Second Year Cohort 9.125 4.630 0.209 Problem Solving Second Year Cohort First Year Cohort 9.150 4.345 0.161 Third Year Cohort First Year Cohort 9.610 3.887 0.073 (Consistency between ANOVA & Tukey HSD) Third Year Cohort Second Year Cohort 0.460 4.148 1.000 Fourth and Fifth Year Cohort First Year Cohort 13.567(*) 4.731 0.027 Fourth and Fifth Year Cohort Second Year Cohort 4.417 4.947 0.809 Fourth and Fifth Year Cohort Third Year Cohort 3.957 4.550 0.820 General Mood Second Year Cohort First Year Cohort 9.963 3.889 0.068 Subscale Second Year Cohort Fourth and Fifth Year Cohort 2.896 5.155 0.942 Third Year Cohort First Year Cohort 11.090(*) 3.400 0.014 (Consistency between ANOVA & Games- Third Year Cohort Second Year Cohort 1.128 2.907 0.980 Howell) Third Year Cohort Fourth and Fifth Year Cohort 4.023 4.797 0.835 Fourth and Fifth Year Cohort First Year Cohort 7.067 4.190 0.339 Happiness Second Year Cohort First Year Cohort 9.350 4.417 0.170 Second Year Cohort Fourth and Fifth Year Cohort 4.333 4.702 0.794 (ANOVA identified overall differences between GPA Third Year Cohort First Year Cohort 10.590(*) 4.084 0.068 clusters, but Games- Third Year Cohort Second Year Cohort 1.240 2.953 0.975 Howell did not detect pairwise differences) Third Year Cohort Fourth and Fifth Year Cohort 5.573 4.391 0.595 Fourth and Fifth Year Cohort First Year Cohort 5.017 5.484 0.797 * Bold. The mean difference is significant at the .05 level.
190
APPENDIX O
Independent Sample Test: Race and Emotional Quotient Inventory Levene's Test t-test for Equality of Means Sig. (2- SE F Sig. t df tailed) MD Diff. Total EQ-i Score Equal variances assumed 0.361 0.550 1.331 71 0.188 3.680 2.766 Equal variances not assumed 1.361 69.230 0.178 3.680 2.704 Intrapersonal Subscale Equal variances assumed 1.011 0.318 -0.060 71 0.952 -0.182 3.014 Equal variances not assumed -0.062 70.237 0.951 -0.182 2.922 Self-Regard Equal variances assumed 1.076 0.303 0.503 71 0.616 1.402 2.785 Equal variances not assumed 0.518 69.954 0.606 1.402 2.708 Emotional Self- Equal variances assumed 0.628 0.431 0.350 71 0.727 1.051 3.004 Awareness Equal variances not assumed 0.358 69.301 0.721 1.051 2.935 Assertiveness Equal variances assumed 0.192 0.663 -2.152 71 0.035 -7.887 3.665 Equal variances not assumed -2.141 63.497 0.036 -7.887 3.684 Independence Equal variances assumed 1.555 0.217 -1.247 71 0.216 -3.142 2.519 Equal variances not assumed -1.297 70.858 0.199 -3.142 2.422 Self-Actualization Equal variances assumed 4.799 0.032 2.056 71 0.043 6.304 3.066 Equal variances not assumed 2.156 70.990 0.035 6.304 2.924 Interpersonal Subscale Equal variances assumed 0.281 0.598 1.670 71 0.099 4.691 2.810 Equal variances not assumed 1.673 65.242 0.099 4.691 2.804 Empathy Equal variances assumed 0.040 0.842 1.310 71 0.195 4.331 3.307 Equal variances not assumed 1.308 64.572 0.195 4.331 3.311 Social Responsibility Equal variances assumed 0.009 0.923 1.759 71 0.083 6.353 3.611 Equal variances not assumed 1.786 68.027 0.079 6.353 3.557 Interpersonal Equal variances assumed 0.005 0.945 0.808 71 0.422 2.280 2.822 Relationships Equal variances not assumed 0.811 65.739 0.420 2.280 2.811 Stress Management Equal variances assumed 1.303 0.257 2.017 71 0.047 6.068 3.008 Subscale Equal variances not assumed 2.111 71.000 0.038 6.068 2.874 Stress Tolerance Equal variances assumed 1.678 0.199 1.163 71 0.249 3.330 2.864 Equal variances not assumed 1.204 70.604 0.233 3.330 2.766 Impulse Control Equal variances assumed 6.578 0.012 1.958 71 0.054 6.823 3.485 Equal variances not assumed 2.118 67.098 0.038 6.823 3.222 Adaptability Subscale Equal variances assumed 0.126 0.724 0.922 71 0.360 2.724 2.954 Equal variances not assumed 0.938 68.399 0.351 2.724 2.903 Reality Testing Equal variances assumed 0.191 0.663 0.264 71 0.793 0.846 3.206 Equal variances not assumed 0.271 69.664 0.787 0.846 3.125 Flexibility Equal variances assumed 0.948 0.333 0.574 71 0.568 1.625 2.831 Equal variances not assumed 0.560 58.471 0.577 1.625 2.901 Problem Solving Equal variances assumed 0.188 0.666 1.436 71 0.155 4.588 3.195 Equal variances not assumed 1.456 67.842 0.150 4.588 3.150 General Mood Equal variances assumed 1.480 0.228 2.520 71 0.014 6.992 2.775 Subscale Equal variances not assumed 2.590 69.899 0.012 6.992 2.699 Optimism Equal variances assumed 2.452 0.122 1.638 71 0.106 5.578 3.405 Equal variances not assumed 1.713 70.995 0.091 5.578 3.257 Happiness Equal variances assumed 0.562 0.456 2.397 71 0.019 7.083 2.955 Equal variances not assumed 2.476 70.374 0.016 7.083 2.861 Bold. t-value is significant at the .05 level.
191
Independent Sample Test: Race and Student Leadership Practices Levene's Test t-test for Equality of Means Sig. (2- SE F Sig. t df tailed) MD Diff. Modeling the Way Equal variances assumed 0.129 0.720 2.517 71 0.014 1.863 0.740 Equal variances not assumed 2.513 64.347 0.015 1.863 0.742 Inspiring a Shared Equal variances assumed 0.347 0.558 1.842 71 0.070 1.554 0.844 Vision Equal variances not assumed 1.852 66.033 0.069 1.554 0.839 Challenging the Equal variances assumed 0.166 0.685 2.362 71 0.021 1.884 0.798 Process Equal variances not assumed 2.352 63.829 0.022 1.884 0.801 Enabling Others to Act Equal variances assumed 0.229 0.634 0.597 71 0.553 0.359 0.602 Equal variances not assumed 0.589 61.606 0.558 0.359 0.610 Encouraging the Heart Equal variances assumed 1.448 0.233 1.878 71 0.064 1.609 0.857 Equal variances not assumed 1.918 69.008 0.059 1.609 0.839 Bold. t-value is significant at the .05 level.
192
APPENDIX P
ANOVA: Mother’s Education Level and Emotional Quotient Inventory Dependent Variables Groups SS df MS F Sig. Total EQ-i Score Between Groups 532.707 2 266.353 1.984 0.145 Within Groups 9,398.855 70 134.269 Total 9,931.562 72 Intrapersonal Subscale Between Groups 55.128 2 27.564 0.169 0.845 Within Groups 11,445.502 70 163.507 Total 11,500.630 72 Self-Regard Between Groups 396.045 2 198.023 1.465 0.238 Within Groups 9,459.955 70 135.142 Total 9,856.000 72 Emotional Self-Awareness Between Groups 26.046 2 13.023 0.080 0.923 Within Groups 11,420.584 70 163.151 Total 11,446.630 72 Assertiveness Between Groups 4.576 2 2.288 0.009 0.991 Within Groups 18,110.766 70 258.725 Total 18,115.342 72 Independence Between Groups 0.234 2 0.117 0.001 0.999 Within Groups 8,210.505 70 117.293 Total 8,210.740 72 Self-Actualization Between Groups 135.213 2 67.606 0.379 0.686 Within Groups 12,478.952 70 178.271 Total 12,614.164 72 Interpersonal Subscale Between Groups 918.833 2 459.417 3.396 0.039 Within Groups 9,470.509 70 135.293 Total 10,389.342 72 Empathy Between Groups 1,582.866 2 791.433 4.396 0.016 Within Groups 12,603.764 70 180.054 Total 14,186.630 72 Social Responsibility Between Groups 1,102.375 2 551.187 2.392 0.099 Within Groups 16,133.105 70 230.473 Total 17,235.479 72 Interpersonal Relationships Between Groups 605.147 2 302.574 2.212 0.117 Within Groups 9,574.223 70 136.775 Total 10,179.370 72 Stress Management Subscale Between Groups 1,237.136 2 618.568 3.981 0.023 Within Groups 10,876.617 70 155.380 Total 12,113.753 72 Stress Tolerance Between Groups 400.335 2 200.167 1.376 0.259 Within Groups 10,184.788 70 145.497 Total 10,585.123 72 Impulse Control Between Groups 1,713.717 2 856.858 4.138 0.020 Within Groups 14,495.763 70 207.082 Total 16,209.479 72 Adaptability Subscale Between Groups 253.095 2 126.547 0.810 0.449 Within Groups 10,930.878 70 156.155 Total 11,183.973 72 Reality Testing Between Groups 212.768 2 106.384 0.581 0.562 Within Groups 12,819.259 70 183.132 Total 13,032.027 72 Flexibility Between Groups 56.173 2 28.087 0.194 0.824 Within Groups 10,139.909 70 144.856 Total 10,196.082 72 Problem Solving Between Groups 653.973 2 326.986 1.810 0.171 Within Groups 12,647.918 70 180.685 Total 13,301.890 72 General Mood Subscale Between Groups 295.671 2 147.835 1.002 0.372 Within Groups 10,328.576 70 147.551 Total 10,624.247 72 193
Optimism Between Groups 246.578 2 123.289 0.576 0.565 Within Groups 14,989.943 70 214.142 Total 15,236.521 72 Happiness Between Groups 365.631 2 182.815 1.105 0.337 Within Groups 11,583.712 70 165.482 Total 11,949.342 72 Bold. F-value is significant at the .05 level.
ANOVA: Mother’s Education Level and Student Leadership Practices Inventory Dependent Variables Groups SS df MS F Sig. Modeling the Way Between Groups 9.239 2 4.620 0.433 0.650 Within Groups 746.514 70 10.664 Total 755.753 72 Inspiring a Shared Vision Between Groups 33.629 2 16.815 1.293 0.281 Within Groups 910.617 70 13.009 Total 944.247 72 Challenging the Process Between Groups 34.480 2 17.240 1.446 0.242 Within Groups 834.644 70 11.923 Total 869.123 72 Enabling Others to Act Between Groups 7.260 2 3.630 0.559 0.574 Within Groups 454.712 70 6.496 Total 461.973 72 Encouraging the Heart Between Groups 29.546 2 14.773 1.093 0.341 Within Groups 946.235 70 13.518 Total 975.781 72 Bold. F-value is significant at the .05 level. 194
APPENDIX Q
Tukey HSD: Mother’s Education Level Groups and Emotional Quotient Inventory Dependent Variable (I) Mother's Ed. 3 Groups (J) Mother's Ed. 3 Groups M Diff. (I-J) SE Sig. Interpersonal Has a Two or Four Year Degree Without a College Degree 3.633 3.105 0.475 Subscale Has a Post Graduate Degree Without a College Degree 9.468(*) 3.664 0.031 Has a Post Graduate Degree Has a Two or Four Year Degree 5.835 3.943 0.307 Empathy Has a Two or Four Year Degree Without a College Degree 6.789 3.582 0.148 Has a Post Graduate Degree Without a College Degree 11.742(*) 4.226 0.019 Has a Post Graduate Degree Has a Two or Four Year Degree 4.953 4.549 0.524 Has a Post Graduate Degree Has a Two or Four Year Degree 7.839 3.964 0.125 Stress Has a Two or Four Year Degree Without a College Degree 7.414 3.327 0.073 Management Has a Post Graduate Degree Without a College Degree 9.306 3.926 0.053 Subscale Has a Post Graduate Degree Has a Two or Four Year Degree 1.891 4.225 0.896 Impulse Control Has a Two or Four Year Degree Without a College Degree 7.309 3.841 0.145 Has a Post Graduate Degree Without a College Degree 12.079(*) 4.533 0.026 Has a Post Graduate Degree Has a Two or Four Year Degree 4.770 4.878 0.593 * Bold. The mean difference is significant at the .05 level. * Bold Italicized. The ANOVA showed significance, but the pairwise assessment does not find mean difference significant at the .05 level.
195
APPENDIX R
ANOVA: Father’s Education Level and Emotional Quotient Inventory Dependent Variables Groups SS df SM F Sig. Total EQ-i Score Between Groups 268.905 2 134.452 0.951 0.392 Within Groups 9,615.828 68 141.409 Total 9,884.732 70 Intrapersonal Subscale Between Groups 76.434 2 38.217 0.232 0.794 Within Groups 11,206.158 68 164.796 Total 11,282.592 70 Self-Regard Between Groups 36.631 2 18.316 0.131 0.878 Within Groups 9,515.256 68 139.930 Total 9,551.887 70 Emotional Self-Awareness Between Groups 40.349 2 20.175 0.126 0.882 Within Groups 10,918.242 68 160.562 Total 10,958.592 70 Assertiveness Between Groups 266.034 2 133.017 0.509 0.604 Within Groups 17,785.966 68 261.558 Total 18,052.000 70 Independence Between Groups 153.927 2 76.964 0.658 0.521 Within Groups 7,955.537 68 116.993 Total 8,109.465 70 Self-Actualization Between Groups 354.049 2 177.024 1.015 0.368 Within Groups 11,855.247 68 174.342 Total 12,209.296 70 Interpersonal Subscale Between Groups 816.339 2 408.170 2.915 0.061 Within Groups 9,521.154 68 140.017 Total 10,337.493 70 Empathy Between Groups 891.474 2 445.737 2.476 0.092 Within Groups 12,240.245 68 180.004 Total 13,131.718 70 Social Responsibility Between Groups 639.379 2 319.689 1.351 0.266 Within Groups 16,085.241 68 236.548 (Unequal Variance) Total 16,724.620 70 Interpersonal Relationships Between Groups 523.419 2 261.709 1.884 0.160 Within Groups 9,444.525 68 138.890 Total 9,967.944 70 Stress Management Subscale Between Groups 445.163 2 222.582 1.299 0.279 Within Groups 11,649.626 68 171.318 Total 12,094.789 70 Stress Tolerance Between Groups 149.977 2 74.988 0.491 0.614 Within Groups 10,386.953 68 152.749 Total 10,536.930 70 Impulse Control Between Groups 650.908 2 325.454 1.428 0.247 Within Groups 15,502.839 68 227.983 Total 16,153.746 70 Adaptability Subscale Between Groups 214.927 2 107.463 0.670 0.515 Within Groups 10,906.735 68 160.393 Total 11,121.662 70 Reality Testing Between Groups 98.757 2 49.379 0.266 0.767 Within Groups 12,635.637 68 185.818 Total 12,734.394 70 Flexibility Between Groups 70.308 2 35.154 0.237 0.790 Within Groups 10,107.354 68 148.638 (Unequal Variance) Total 10,177.662 70 Problem Solving Between Groups 477.736 2 238.868 1.268 0.288 Within Groups 12,809.504 68 188.375 Total 13,287.239 70 General Mood Subscale Between Groups 588.200 2 294.100 2.118 0.128 Within Groups 9,440.786 68 138.835 Total 10,028.986 70 196
Dependent Variables Groups SS df SM F Sig. Optimism Between Groups 655.598 2 327.799 1.555 0.219 Within Groups 14,331.866 68 210.763 Total 14,987.465 70 Happiness Between Groups 391.174 2 195.587 1.238 0.296 Within Groups 10,739.981 68 157.941 Total 11,131.155 70 (Unequal Variance). Variable failed the Levene Test of Homogeneity of Variance, therefore necessitated a Games-Howell Post Hoc.
ANOVA: Father’s Education Level and Student Leadership Practices Inventory Dependent Variables Groups SS df SM F Sig. Modeling the Way Between Groups 53.034 2 26.517 2.595 0.082 Within Groups 694.881 68 10.219 Total 747.915 70 Inspiring a Shared Vision Between Groups 77.585 2 38.793 3.157 0.049 Within Groups 835.570 68 12.288 Total 913.155 70 Challenging the Process Between Groups 83.914 2 41.957 3.755 0.028 Within Groups 759.861 68 11.174 Total 843.775 70 Enabling Others to Act Between Groups 43.385 2 21.693 3.630 0.032 Within Groups 406.361 68 5.976 Total 449.746 70 Encouraging the Heart Between Groups 95.941 2 47.970 3.780 0.028 Within Groups 863.045 68 12.692 Total 958.986 70 Bold. F-Value is significant at p = 0.05.
197
APPENDIX S
Tukey HSD: Father’s Education Level Groups and Student Leadership Practices Inventory Dependent Variable (I) Father's Ed. 3 Groups (J) Father's Ed. 3 Groups M Diff. (I-J) SE Sig. Modeling the Way Without a College Degree Has a Post Graduate Degree 1.160 1.015 0.492 Has a Two or Four Year Degree Without a College Degree 1.260 0.863 0.317 Has a Two or Four Year Degree Has a Post Graduate Degree 2.419 1.084 0.073 Inspiring a Shared Has a Two or Four Year Degree Without a College Degree 2.295(*) 0.946 0.047 Vision Has a Two or Four Year Degree Has a Post Graduate Degree 2.056 1.188 0.201 Has a Post Graduate Degree Without a College Degree 0.239 1.113 0.975 Challenging the Without a College Degree Has a Post Graduate Degree 0.441 1.062 0.909 Process Has a Two or Four Year Degree Without a College Degree 2.168(*) 0.902 0.049 Has a Two or Four Year Degree Has a Post Graduate Degree 2.609 1.133 0.062 Enabling Others Without a College Degree Has a Post Graduate Degree 1.067 0.776 0.360 to Act Has a Two or Four Year Degree Without a College Degree 1.125 0.660 0.211 Has a Two or Four Year Degree Has a Post Graduate Degree 2.193(*) 0.829 0.027 Encouraging the Has a Two or Four Year Degree Without a College Degree 2.623(*) 0.962 0.022 Heart Has a Two or Four Year Degree Has a Post Graduate Degree 1.938 1.208 0.251 Has a Post Graduate Degree Without a College Degree 0.685 1.131 0.818 * Bold. The mean difference is significant at the .05 level.
198
APPENDIX T
MY TESTS DON'T AGREE!
David P. Nichols
From SPSS Keywords, Number 66, 1998
A common question asked of SPSS Statistical Support is how to interpret a set of tests that are testing the same or logically related null hypotheses, yet produce different conclusions. The prime example of this would be a situation where an omnibus F-test in an analysis of variance (ANOVA) produces a significance level (p-value) less than a critical alpha (such as .05), but follow up tests comparing levels of the factor do not produce any p-values less than alpha, or conversely, where the omnibus F-test is not significant at the given alpha level, while one or more pairwise comparisons are significant.
For an example, consider a one way ANOVA model of a very simple form: three groups, equal sample sizes, with standard independence, normality, and homogeneity of variance assumptions met. Further, assume that our numbers have been measured without error. The null hypothesis tested by the omnibus F-test is that all three population means are equal:
µ1 = µ2 = µ3.
The null hypothesis tested by a pairwise comparison of groups i and j is that these two population means are equal:
µi = µj.
The hypotheses tested by the omnibus test and pairwise comparisons are thus logically related: the omnibus null hypothesis is the intersection of all pairwise null hypotheses. That is, all population means can only be equal if any two chosen from the set are equal. However, as many readers may know, the results of significance tests using sample data frequently produce logical contradictions. How can this be?
The reason that such contradictory results can occur is that when we are making inferences about population parameters (such as population means) using sample data, our estimates are subject to sampling error. Were we dealing with the entireties of finite populations, we could simply compute the mean or other parameter(s) of interest in each population, and compare the results. There would be no sampling error, and hence no need for measures of precision of estimation, such as standard errors. Our decisions with regard to the above stated null hypotheses would then be logically consistent: the numbers would all be equal, or else some would differ from others.
Since we generally do not have the luxury of addressing problems where we can identify entire finite populations and measure all values, we are forced to work with samples and to make inferences about the unknown population values. The mean or other parameter values that we compute are estimates of the true unknown values, and these estimates are subject to sampling error. Thus, the means computed from several random samples from populations with the same mean will not generally be equal. We are not able to specify what the value of a sample mean will be even if we know the population value. What we can specify is the distribution of sample means and various related statistics under such circumstances.
Thus, the logic behind the standard F-test in an ANOVA is that if all of the assumptions are met, the distribution of F- values in repeated samples will follow the theoretical central F distribution with appropriate degrees of freedom if the null hypothesis is true. The logic behind the pairwise comparison tests is identical: if the model assumptions are met and the two population means of interest are equal, the t or F statistics produced by repeated sampling will follow the 199 appropriate theoretical central t or F distributions. The important point is that the methodology of statistical inference does not allow us to state what will happen in a particular case, only the distributions of results in repeated random samples. It thus does not preclude the possibility of logically contradictory results. This state of affairs, while disconcerting to many, is simply part of the price we pay when we seek to make inferences based on samples.
In the case of a significant omnibus F-statistic and nonsignificant pairwise comparisons, some people have proposed the explanation that while no two means are different, some more complicated contrast among the means is nonzero, leading to the significant omnibus F. Such an explanation mistakes the mechanics of the methodology of the F-statistic for the hypothesis being tested. That is, while the F-statistic can be constructed as a function of the maximal single degree of freedom contrast computable from the sample data, the hypothesis tested is still that the population means are all equal, and the contrast value can only be nonzero in the population if at least one population mean is different from the others.
To broaden the discussion a bit and reinforce the point, consider a simple two way crosstabulation or contingency table. The two most popular test statistics for testing the null hypothesis of no population association between rows and columns are the Pearson and the Likelihood Ratio (LR) chi-squared tests. These statistics are testing the same null hypothesis and follow the same theoretical distribution under that null hypothesis, but they will sometimes yield different conclusions for a set of sample data. Again, the reason is that sampling variability means that we can only know about the distributions of the test statistics, not what they will be in particular cases.
What can we do about this? We cannot generally avoid the problem, as we are not usually in a position to identify finite populations of interest and measure all members of these populations. The best we can do is to understand the true nature of the problem and accept its implications. One is that the problem will always be with us in standard situations. The other is that we can minimize it by using larger samples, which provide us with greater levels of precision, and reduce the probability of seeing such results. As sample sizes increase to infinity, sampling errors converge to 0. Though we cannot achieve infinite sample sizes, the larger our samples, all other things being equal, the firmer our results.
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