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Kennesaw State University Kennesaw State University
DigitalCommons@Kennesaw State University DigitalCommons@Kennesaw State University
Doctor of Education in Educational Leadership for Learning Dissertations Educational Leadership
Winter 12-1-2020
The Influence of Student Discipline on Teacher Job Satisfaction The Influence of Student Discipline on Teacher Job Satisfaction
when Controlling for Workplace Characteristics, Personal when Controlling for Workplace Characteristics, Personal
Attributes, Human Capital Elements, and Principal Leadership Attributes, Human Capital Elements, and Principal Leadership
Joshua Pittman [email protected]
Follow this and additional works at: https://digitalcommons.kennesaw.edu/educleaddoc_etd
Part of the Educational Leadership Commons
Recommended Citation Recommended Citation Pittman, Joshua, "The Influence of Student Discipline on Teacher Job Satisfaction when Controlling for Workplace Characteristics, Personal Attributes, Human Capital Elements, and Principal Leadership" (2020). Doctor of Education in Educational Leadership for Learning Dissertations. 25. https://digitalcommons.kennesaw.edu/educleaddoc_etd/25
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The Influence of Student Discipline on Teacher Job Satisfaction when Controlling for
Workplace Characteristics, Personal Attributes, Human Capital Elements, and Principal
Leadership
Research Dissertation submitted
By
Joshua Thomas Pittman
Kennesaw State University
_____________________________________________________
Dissertation Committee:
Dr. David G. Buckman, Chair
Dr. Sheryl Croft, Committee Member
Dr. Sanjuana Carrillo-Rodriguez, Committee Member
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Dedication
This dissertation is dedicated to my wife, Shoni Pittman. You allowed me spend countless
minutes, hours, mornings, nights, days, weekends, and months to achieve this goal. Your
support, motivation, and encouragement to accomplish such a goal are greatly appreciated. The
obstacles you have encountered personally in the past few years are large mountains. Yet, be
encouraged as we have the power to cast mountains into the sea. Thank you!
I would also like to thank my children, Ethan and Makayla Pittman. The reason I get up
every morning is to ensure that you can go to sleep safe and sound every night. Your nightly
prayers for “Daddy” to finish his Doctorate have not gone in vain. As the word says in James
5:16, “The prayers of the righteous availeth much”! Continue to succeed in all of your endeavors
and learn valuable lessons from your experiences.
To my mother Earnestine Pittman, thank you! You installed in me a conviction or belief that
I could accomplish and/or become anything I planned to be, despite what anyone else said or
thought. Well, I believed you, and have I lived a life built on the principle of work ethic!
Lastly, I appreciate family members, friends, and colleagues who have supported me during
this process with encouraging words or prayers.
Thank you God for allowing this goal to be accomplished, as I say, “To God Be All the
Glory”!
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Acknowledgement
Foremost, I would like to thank Dr. Buckman for your leadership, support, guidance,
encouragement, and time as my dissertation chair during this process. Your willingness to
embrace this study and my ideas was very inspiring. The limitless hours you spent on Google
Meet calls answering my questions despite the day of the week was priceless! I appreciate the
expertise you have given me surrounding quantitative research. Thank you for allowing me an
opportunity to fulfill this significant component of my degree requirements!
To Dr. Croft, your motherly advice, divine wisdom, and thought-provoking comments as a
committee member, advisor, and professor are much appreciated! You care about each and every
student in the Educational Leadership program as a person and a leader. I have truly become a
better writer and educational leader because of you. Thank you!
Much gratitude and love goes to Dr. Carrillo-Rodriguez! You have been a supportive figure
in my educational career and I appreciate you serving on my committee. I am delighted that you
encouraged me to apply to Kennesaw State University. The feedback and encouragement you
have provided during this journey are valued!
May God continue to bless each one of you professionally and personally!
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Abstract
The purpose of this study was to contribute to the empirical literature related to the
influence of student discipline on teacher job satisfaction. Further, this research aimed to explore
the correlation between student discipline and teacher job satisfaction while controlling for the
contributing factors of job satisfaction (i.e., workplace characteristics, personal attributes, human
capital elements, and principal leadership). In addition, the results of this research study were
interpreted through the lens of the Affective Events Theory indicating a person’s emotions and
behaviors for the workplace may influence their job satisfaction. Descriptive and inferential
statistics were applied to see whether there is a significant relationship between student
discipline and teacher job satisfaction when teacher job satisfaction covariates have been
controlled.
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Table of Contents
The Influence of Student Discipline on Teacher Job Satisfaction when Controlling for ................ i
Dedication ................................................................................................................................... ii
Acknowledgement ......................................................................................................................... iii
Abstract .......................................................................................................................................... iv
Table of Contents ............................................................................................................................ v
Chapter One .................................................................................................................................... 1
Research Question ....................................................................................................................... 8
Null Hypothesis ........................................................................................................................... 9
Definition of Terms ..................................................................................................................... 9
Chapter Two.................................................................................................................................. 12
Historical Review of Job Satisfaction Theories ............................................................................ 12
Situational Theories................................................................................................................... 12
Dispositional Theories............................................................................................................... 18
Interactive Theories ................................................................................................................... 22
Motivational Theories ............................................................................................................... 26
Summary of Job Satisfaction Theories...................................................................................... 34
Facets of Job Satisfaction .......................................................................................................... 35
Work Related Factors that may influence Job Satisfaction .......................................................... 38
Class Size .................................................................................................................................. 38
Workload ................................................................................................................................... 40
Gender ....................................................................................................................................... 41
Age ............................................................................................................................................ 42
Race ........................................................................................................................................... 43
Experience ................................................................................................................................. 44
Education Level......................................................................................................................... 47
Pay ............................................................................................................................................. 48
Principal Leadership in General ................................................................................................ 50
Understanding the Job Dissatisfaction .......................................................................................... 54
Understanding the connection between Job Dissatisfaction and Job Satisfaction ........................ 55
Review of Student Discipline ....................................................................................................... 56
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History of Student Discipline Practices in Public Education .................................................... 56
Understanding Student Behavior .............................................................................................. 59
Student Behavior Leads to Student Suspension ........................................................................ 62
The Disproportionality of Discipline toward Minority Students .............................................. 63
Impact of Student Suspension on Students ............................................................................... 64
Classroom Management, Teacher Preparation, Teacher Anxiety, and Culture ........................ 65
The importance of Classroom Management ................................................................................. 66
Classroom Management and Teacher Preparation Programs ................................................... 67
Teacher Preparation Programs, Teacher Experience, and Teacher Anxiety ............................. 68
Culturally Responsive Teaching ............................................................................................... 69
School Administration’s Role in Managing Student Behavior ................................................. 70
The Impact of Student Discipline on School Climate and Teachers ............................................ 70
Understanding School Climate ..................................................................................................... 71
Impact of Student Behavior on School Climate ........................................................................ 71
Influence of Negative Student Behavior on Instruction ............................................................ 72
Impact of Student Behavior on Job Stress, Teacher Retention and Job Satisfaction ................... 74
Impact of Student Behavior on Teacher Retention or Burnout ................................................. 77
Theoretical Framework ................................................................................................................. 79
Chapter Three................................................................................................................................ 83
Methodology ................................................................................................................................. 83
Population.................................................................................................................................. 83
Representation ........................................................................................................................... 85
Data Gathering Methods ........................................................................................................... 86
Job Descriptive Index ............................................................................................................ 86
Data Collection Procedures ....................................................................................................... 88
Variables.................................................................................................................................... 89
Age......................................................................................................................................... 91
Race ....................................................................................................................................... 91
Tenure .................................................................................................................................... 92
Salary ..................................................................................................................................... 93
Principal Leadership in General ............................................................................................ 93
Independent variable .............................................................................................................. 94
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Dependent variable ................................................................................................................ 94
Psychometric Properties of the JDI/JIG .................................................................................... 95
Research Question ..................................................................................................................... 96
Data Analysis ............................................................................................................................ 96
Null Hypothesis ......................................................................................................................... 97
Statistical Method ...................................................................................................................... 98
Chapter Four ............................................................................................................................... 100
Descriptive Statistics ............................................................................................................... 100
Assumption Testing for Multiple Regression ......................................................................... 112
Inferential Statistics ................................................................................................................. 115
Chapter Five ................................................................................................................................ 120
Discussion ............................................................................................................................... 120
Implications ............................................................................................................................. 123
Limitations .............................................................................................................................. 124
Conclusion ............................................................................................................................... 125
References ................................................................................................................................... 127
Appendix A: ................................................................................................................................ 205
Appendix B: ................................................................................................................................ 206
Appendix C: ................................................................................................................................ 207
Appendix D: ................................................................................................................................ 208
Appendix E: ................................................................................................................................ 209
Appendix F: ................................................................................................................................ 212
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Chapter One
Introduction
Currently, job satisfaction is one of the most widely studied constructs within the field of
industrial psychology (Judge, Parker, Colbert, Heller, & Ilies, 2001; Hora, Ribas, & de Souza,
2018; Sahito, & Väisänen, 2020). Yet, job satisfaction is one of the most challenging constructs
to define as diverse authors have suggested a variety of approaches. Many of their theories are
discussed in this study (Adams, 1965; Chiu & Kosinski, 1999; Deci, 1971; Hackman & Oldham,
1975; Herzberg, 1967; Hoppock, 1935; Hulin, 1991; Locke, 1976; Locke & Latham, 1990;
McClleland, 1961; McGregor, 1957; Packer, 1985; Pardee, 1990; Vroom, 1964; Weiss &
Cropanzano, 1996).
Employee job satisfaction represents a combination of positive or negative emotions that
employees have towards their work (Davis & Nestrom, 1985). The term job satisfaction refers to
the behaviors and emotional states people have about their jobs. Optimistic and favorable
behaviors toward work are indicators of job satisfaction (Armstrong, 2006). Aimed as the focus
for this study, Spector’s (1997) research was used as the base for defining job satisfaction.
Spector’s (1997) work defines job satisfaction as how people feel about their employment and
the amount they like or dislike their jobs.
A person’s job satisfaction can be influenced by a variety of factors such as coworkers,
pay, working conditions, supervisors, promotion, and others (Ostroff, 1992). These concepts can
universally relate to an employee of any organization. For example, Buckman, Tran, and Young
(2016) demonstrated in a study of 244 elementary teachers (P-5) from Ohio and South Carolina,
how pay satisfaction is a dominant construct and can be used in studies as an exclusive
dependent variable.
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Judge et al. (2001) postulate when defining job satisfaction, the facets mentioned can be
divided into intrinsic and extrinsic motivators effecting a person’s level of job satisfaction or
dissatisfaction based on the situations, environments, and triggers (i.e., supervisors and
coworkers). Job dissatisfaction is defined as an unpleasant emotion where most people are
conditioned to respond by finding a solution that will minimize the level of dissatisfaction
(Afshar & Doosti, 2016; Okeke & Dlamini, 2013). Job dissatisfaction is most habitually related
to job stress as stated in Leung and Lee (2006), and their research suggested that support from
supervisors or colleagues predict the likelihood of someone quitting. An employee’s job
satisfaction is a necessity for a business to sustain a strong and productive work environment
(Chalofsky & Krisha, 2009; Likert, 1961; Truxillo, Bauer, & Erdogan, 2016). Because job
satisfaction is beneficial to any workplace, the importance of job satisfaction is evident in the
school setting for teachers.
In accordance with Ostroff’s (1992) research, teachers who are satisfied with their work
environment make a significant impact on the educational achievement of the school. For
instance, teachers who are pleased with the work environment reportedly have a substantial
influence on the morale of other teachers and students. Ma and MacMillian (1999) specified that
teachers who were satisfied with the classroom indicated they felt positive about their content
knowledge capacity and ability to apply learning through instructional strategies. In contrast,
dissatisfied workers, including teachers, are said to have detrimental attitudes and approaches
that can be unfavorable to an organization (Ostroff, 1992).
A stability problem in Georgia, literature from Owens and the Georgia Department of
Education (GADOE) (2015) reported that 47% of Georgia teachers leave the profession within
the first five years of teaching. The survey of 53,000 educators in Georgia also noted student
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discipline as 18.6% of the problem for why teachers are leaving the profession, along with 17.6%
reporting issues with a lack of administrative support (Owens & the GADOE, 2015). Ingersoll
and Perda (2009) describe teacher turnover by the movement of teachers from one school or
district to another or the abandonment of contract. During the 2000-2001 school year, the
National Commission on Teaching and America’s Future reported a 22% teacher turnover rate in
economically disadvantaged urban areas, a 16.4% rate for teachers in penuriously rural areas,
and a 12.8% rate for all other highly impoverished areas (Spradlin & Prendergast, 2006).
Ingersoll further expressed in an article by Walker (2015) that 48% of teachers leave the
profession due to dissatisfaction. In addition, approximately 30% to 50% of teachers leave the
profession within their first five years, and 30% of those educators cite negative student behavior
as a contributor to them leaving (Smart & Igo, 2010). Negative student behavior could possibly
generate negative emotions in teachers causing them to quit the profession. The purpose of this
study is to assess whether there is a relationship between student discipline and teacher job
satisfaction. By studying student discipline and teacher job satisfaction, this research will help
school district leaders identify areas that need to be addressed in support of minimizing negative
student behavior in the work environment for teachers.
Discipline teaches students social and moral lessons about responsiveness, relationships,
fairness, authority, and control, and essentially how the world operates through the lens of the
school administration and or classroom teacher (Marcucci & Elmesky, 2020). Using this
framework, teachers may perceive student behavior as negative based on normed expectations of
the school or classroom, likely leading to students getting in trouble for inappropriate actions.
Teachers working in challenging instructional environments probably experience stress from
disruptive student behaviors (Vassallo, 2014).
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Teachers generally identify student behavior as a significant problem to the work
environment (Public Agenda, 2004). When negative student behavior is perceived as a frequent
action, educators may struggle with concerns of low student scores on high stakes test (Skiba &
Rausch, 2004) and challenges could arise with the ability to maintain high quality learning
experiences during instructional time (Noguera, 2003). Students who exhibit disregard or
disrespect for school authority are identified as having poor student discipline, leading to them
being suspended or expelled from school.
To make matters worse, the discipline disproportionality between Blacks being overly
suspended from school in comparison to their White counterparts has almost doubled over the
past 20 years (Steinberg & Lacoe, 2017).These patterns of disproportionality are referred to as
the discipline gap between Blacks and Whites throughout school districts in the United States.
The cultural backgrounds of low income minority students are different from the institutionalized
norms developed by Whites for public schools (Ferguson 2000; Obidah & Teel, 2001).
Therefore, Blacks typically have been overly suspended from school than their White peers for
negative student behavior (Gastic, 2017; Gopalan & Nelson, 2019; Shores, Kim, & Still; 2020;
Skiba & Williams, 2014). Overall, Black males make up the largest population of students who
have been excluded from school (Girvan, Gion, McIntosh, & Smolkowski, 2016).
Due to the lack of cultural awareness, misunderstandings between teachers and students
may result in conflict, distrust, and even school failure for Black students (Irvine, 1990). Cultural
aversion may contribute to Black students being disciplined at higher rates than their White peers
due to teachers and administrators taking a color blind method to discussing race and cultural
tradition because of fear of causing racial dissonance (Irvine, 1990). The lack of synchronization
often leads to opposition between teachers and students, and could result in more confrontations
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between Black students and White teachers while in the work environment (Irvine, 1990). The
influence of teacher behavior on student discipline must receive notable consideration for why
Blacks are suspended from school three times more than White students (U.S. Department of
Education Office of Civil Rights, 2012, 2014).
As a result of poor student-teacher relationships and low cultural recognition (Verdugo,
2002), Black students are more probable to experience a sense of distrust and lack of connection
with teachers (Okonofua, Walton, & Eberhardt, 2016). Punitive and disproportionate discipline
for Black children actually begins in preschool (Skiba, & Williams, 2014) as Black preschool
students are 3.6 times more likely to receive suspension in comparison to White preschool
students (Gilliam, 2016). Discipline disparities are further concerning because they may
contribute to problematic results for Black students as they get older, such as school withdrawal,
academic failure, and imprisonment (Elias, 2013; Milner, 2012). Consequently, Blacks are five
times more likely to experience incarceration than Whites (Malik, 2017).
Gastic’s (2017) research further examined the disproportionality in student suspension by
reviewing the discipline statistics of 298,033 high school students of various races who lived in
Massachusetts. Blacks in the study were 2.52 times more likely to be suspended for fighting than
their White peers, and Latinos were 2.14 times more likely to be suspended for fighting than
their White peers (Gastic, 2017). Exploring the reasons behind such disparities, Skiba, Michael,
Nardo, and Peterson (2002) found that Whites generally were suspended for more objective
reasons (smoking, destruction of property, leaving campus without permission, vulgarity), while
Black students were more likely to be suspended for subjective behaviors (wandering, lack of
respect, intimidation, classroom disruption). Gregory, Skiba, and Noguera (2010) discussed how
a lack of research exist suggesting that the racial discipline gap could be explained through
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different exhibitions of negative student behavior from Black, Latino, and American Indian
students in comparison to White students.
Staats, Capatosto, Wright, and Contractor (2015) believe educators’ implicit biases might
contribute to such discipline disparities because these types of biases occur outside of the
conscious mind and might result in incorrect, excessive, or unfair consequences for minority
students. Reasons for the disproportionality of minority students involving student discipline
may include cultural difference, implicit bias, or negative outlooks by teachers (Gregory et al.,
2010). Educators should be reflective of their individual practices and beliefs that may influence
student outcomes, especially for minorities who experience a disproportionate amount of
exclusionary punishment.
Likewise, Pedro Noguera discussed how children of color are disproportionately
suspended from school more than their White peers (AccuTrain Corporation, 2020, 00:07).
Noguera expressed how some students of color do experience explicit racial biases (AccuTrain
Corporation, 2020, 00:42); however, Noguera doesn’t believe that explicit biases are the norm
throughout the United States (AccuTrain Corporation, 2020, 00:45). Noguera proposed that some
students may get into trouble for their own challenges, such as low reading skills,
inattentiveness, or household barriers (AccuTrain Corporation, 2020, 01:00). To further his
assertion, Noguera expressed for schools to focus on the underlying causes for why the negative
student behavior is being exhibited, and use systems to support the problem behavior (AccuTrain
Corporation, 2020, 01:15).
Despite this evident racial disparity, school administrators have used out-of-school
suspension as a technique for reducing student misconduct since the mid-twentieth century, and
have continued to use this technique to redirect negative student behavior since its evolution
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(Adams, 2000). Students may typically get in trouble for teacher perceived behaviors such as
disrespect, disregard of directions, inappropriate language, and, verbal or physical aggression
(Landers, Alter, & Servilio, 2008). These challenging experiences or misunderstood students are
usually addressed with office discipline referrals (ODRs). When ODRs are generally addressed,
students are given school consequences such as, verbal warnings, corporal punishment, teacher
or administrative detention, in-school suspension, and out-of-school suspension (Skiba &
Peterson, 2000; Townsend, 2000). A lack of teacher preparedness for working with diverse
students plausibly contributes to negative classroom disruptions that create a problematic
environment for teachers to work in.
Unfortunately, limited cultural diversity training in teacher collegiate programs has
contributed to preventing teachers from truly understanding a variety of student perspectives and
issues surrounding student discipline (Weinstein, Tomlinson-Clarke, & Curran, 2004). While
every incident of negative student behavior exhibited in a classroom is not connected to cultural
misunderstandings, an assessment of the lack of cultural synchronization between teachers and
students may reveal that many disciplinary actions are derived from teacher misunderstandings
of student behavior (Monroe, 2006). Because the culture of Black students are often
marginalized, misconstrued, or overlooked in many White dominated school settings, teachers
may misunderstand, criticize, or dismiss Black students’ voice, non-verbal prompts, bodily
movements, learning methods, or worldviews (Irvine, 1990).
Nonetheless, a preceding analysis of middle and high school teachers explained how 76%
of educators indicated they would be better able to teach students if negative student behavior
was not so prevalent, and over a third of teachers documented they would consider quitting the
educational profession because of extensive student behavioral challenges (Public Agenda,
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2004). Haynes (2014) indicated how America spends between 1 billion dollars to 2.2 billion
dollars each year on teacher replacements, and replacing such a major number of potentially
unsatisfied teachers is a massive task for school districts. Even more precisely, Martinez, Frick,
Kim, and Fried (2010) emphasized the high teacher attrition rate in Black populated schools and
the demands of the profession since 50% of teachers quit the profession within the first five years
(Balfanz & Legters, 2004). While in a disruptive environment, negative student behavior could
have a physical or emotional effect on a teacher’s job satisfaction.
School and district leadership personnel should be mindful of the elements that influence
teacher job dissatisfaction because they could give way to student behavioral issues. In turn,
teacher job dissatisfaction can result in worker strikes, absenteeism, and insubordinate teacher
behaviors (Ostroff, 1992). Skaalvik and Skaalvik (2017) described that the largest forecasters of
teacher motivation to quit the career was due to burnout (b = .54) and job satisfaction (b = -.35).
With teachers continuing to leave the profession as discussed in this introduction, more research
is needed to better support school and district leaders on topics related to teacher retention, such
as teacher job satisfaction. Currently, minimal studies exist exploring the relationship between
student discipline and job satisfaction, as these constructs should be examined more.
Research Question
Based on the information above, this study analyzed the relationship between student
discipline (independent variable) and teacher job satisfaction (dependent variable). Using only
secondary level teacher participants in one Georgia school district that serves 77.7%
economically disadvantaged students, this study assessed if the number of office discipline
referrals submitted during a given time period influences teacher job satisfaction. The following
research question guided this study:
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1. Is there a significant correlation between student discipline and the job satisfaction levels
of middle and high school teachers of as measured by the combined Job Descriptive
Index (JDI) and Job in General (JIG) when teacher job satisfaction covariates have been
controlled?
Null Hypothesis
H0: There is no significant correlation between student discipline and the job satisfaction
of middle and high school teachers at as measured by their JDI/JIG combined score when
teacher job satisfaction covariates have been controlled.
Definition of Terms
1. Burnout – a condition of psychological enervation, depersonalization, and reduced
individual achievement (Maslach, Schaufeli, & Leiter, 1996).
2. Classroom Management – having the ability to improve student behavioral skills through
the development of adequate classroom organization, instructional lesson planning, and
positive teacher-student relationships (Bailey & Jacob, 2014).
3. Cultural Aversion- the reluctance of teachers or administrators to discuss race and race
related issues like ethnicity, culture, prejudice, equality and social justice (Irvine, 1990).
4. Cultural Inversion- is related to black students’ perceptions that certain behaviors are
characteristics of White Americans and hence inappropriate for blacks (Irvine, 1990).
5. Cultural Synchronization- based on anthropological and historical research advancing the
belief that black Americans have a distinct culture founded on acknowledged norms,
language, behaviors, and attitudes from Africa (Irvine, 1990).
6. Dispositional Approaches – theories considering one’s personality and character traits
(Weiss & Adler, 1984).
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7. Hygienes- extrinsic elements promoting dissatisfaction through working conditions,
salary, and supervision (Herzberg, 1967; Sarveswara-Rao, 1972).
8. Industrial Psychology – is the science and study of behaviors and attitudes in the
workplace (Truxillo, Bauer, & Erdogan, 2016).
9. Interactive Theories – theories that consider both personal traits (Dispositional &
Situational) and the work to explain one’s satisfaction with work (Judge et al., 2001).
10. Job Facets – any feature of an occupation or its characteristic that could impact overall
job satisfaction (i.e., recognition/feedback, pay, working conditions, and supervision)
(Locke, 1976).
11. Job Satisfaction – how people feel about their employment and the amount they like or
dislike their jobs (Spector, 1997).
12. Motivators – The five essential or intrinsic needs of a person that must be obtained in
fixed order (i.e, 1) physiological needs; 2) safety and security needs; 3) social and
belongingness needs; 4) self-esteem needs; and 5) self-actualization (Berl, Williamson, &
Powell, 1984; Haggerty, 1999; Herzberg, 1967).
13. No Child Left Behind – a reauthorization of The Elementary and Secondary Education
Act of 1965 signed by President George W. Bush. This bill continued standardized based
reform in education with additional accountability requirements for teachers and school
districts (No Child Left Behind Act of 2001, 2002).
14. School Climate - the importance of the relationships among people at school, the learning
environment established for students, and alliance amongst administrators, teachers, and
other school personnel concerning student achievement (Cohen, McCabe, Michelli, &
Pickeral, 2009).
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15. Self-Efficacy – the belief that one has to achieve a goal (Bandura, 1982).
16. Situational Theories – theories based on one’s work environment, social situations, and
the work itself (Judge et al., 2001).
17. Student Behavior - a vast component of a classroom environment that can negatively
impact teaching and learning through inappropriate student actions (Ylimaki, Jacobson,
& Drysdale, 2007).
18. Student Discipline – the prime means for how signs of control and supremacy are
preserved (Noguera, 2009), and this governing concept teaches students social and moral
lessons about compassion, relationships, justice, authority, and control, and essentially
how the world functions (Marcucci & Elmesky, 2020).
19. Teacher Turnover- the movement of teachers from one school or district to another, or
abandonment of contract (Ingersoll & Perda, 2009).
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Chapter Two
Historical Review of Job Satisfaction Theories
To better understand the probable connection between student discipline and job
satisfaction, one must first understand job satisfaction and its many constructs and theories. Job
satisfaction has been defined as a worldwide construct, a universal emotion over a job (Brayfield
& Rothe, 1951), and is described as possibly the most widely researched topic in organizational
psychology (Judge et al., 2001). Judge et al. (2001) determined job satisfaction theories associate
with one of three categorical concepts (i.e., Situational, Dispositional, and Interactive theories).
The loosely suggested theoretical categories are important because they are representative of the
antecedent factors giving rise to a person’s overall job satisfaction (Judge et al., 2001).
Situational Theories
Situational theories assume job satisfaction is an outcome resulting from the nature of a
person’s job or other features of the work environment (Judge et al., 2001). A work environment
is defined as the location, social aspects and physical conditions that impact a person’s job and
influence his/her wellbeing, effectiveness, business relationships, and health (“5 Types of Work
Environments,” 2019). The major situational theories discussed in this review are Herzberg’s
Motivation-Hygiene Theory (two factory theory), the Job Characteristic Model, and the
Affective Events Theory.
Herzberg’s motivation-hygiene theory. Frederick Herzberg’s motivation-hygiene
theory is one of the most debatable theories in the history of organizational research (Sachau,
2007). The two-factor theory was posited by Herzberg in a study of 200 engineers and
accountants where subjects were asked to think of a time when they felt extremely happy or
unhappy, and identify what made them feel as such. Distinctions between the two kinds of
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factors were coined as motivators and hygienes, whereby motivators were intrinsic aspects
encompassing satisfaction, recognition, and advancement (Sarveswara-Rao, 1972). Hygienes
were extrinsic elements promoting dissatisfaction through working conditions, salary, and
supervision (Sarveswara-Rao, 1972).
Herzberg hypothesized that the motivators and hygiene factors relating to job satisfaction
and dissatisfaction respectively, both operate in two separate continuums (Wang, 1994).
Herzberg challenged the assumptions of what motivated employees by having the following
beliefs: (a) pay contributes minimally to job satisfaction, (b) all employees must grow mentally,
and (c) interpersonal skills presumably lead to dissatisfaction over satisfaction (Sachau, 2007).
Herzberg (1967) believed the factors which move toward satisfaction are often unlike those that
lead to dissatisfaction.
Further, hygiene factors could influence external elements such as supervision, salary,
company policies or procedures, and working conditions. Oladotun and Öztüren (2013) revealed
that motivational influences of Cyprus hospital employees conveyed that good working
environments lead to positive mindsets, pioneering employee contributions, and a greater
keenness to work (Alafi, Al-Qeed, & Alkayed, 2013). A similar study on the teacher job
satisfaction of Vietnamese secondary educators specified that teachers tended to be satisfied with
school guidelines, administration, work settings, and professional training, but were displeased
with characteristics of human relations, salary, extrinsic rewards, and personal safety while at
work (Wang and Tran, 2015).
Hulin and Smith (1967), Carroll (1973), and Wernimont (1996) voiced concern with the
Herzberg Motivation-Hygiene Theory. The main problem with Herzberg’s Motivation-Hygiene
Theory is that Hulin and Smith (1967), Carroll (1973), and Wernimont (1986) have replicated
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studies using similar methodologies as Herzberg’s test but found little success. In contrast,
research has revealed that intrinsic and extrinsic elements lead to satisfaction and dissatisfaction
(Carroll, 1973; Wernimont, 1966). Kahn (1961), Brayfield (1960), and Vroom and Maier (1961)
criticized how the two-factor theory assumes a satisfied person attributes the root of their
feelings to themselves, and a dissatisfied person attributes their failures to sources outside of
themselves (Sarveswara-Rao, 1972).
A recent study was conducted to assess the effectiveness of the Herzberg Two Factory
theory when determining which variables related to hygiene and motivator factors of 5,000 to
15,000 excellent teachers (Amzat, Don, Fauzee, Hussin & Raman, 2017). The study revealed
that the interpersonal relationship between working condition and supervision yielded the highest
value of .696, and the lowest interpersonal value was between responsibility and salary (.168
value) (Amzat, et al., 2017). An assumption can be made after reviewing Amzat et al. (2017) that
teachers value the working condition and expect supervision to increase based on the needs of
the environment.
In addition, Amzat et al.’s (2017) findings explained how motivating extrinsic factors like
salary may not be comparable to the large amount of responsibilities or intrinsic factors placed
on employees possibly contributing to a decrease in their satisfaction. Hypothetically, unlike
Herzberg’s two factory theory that is linked to internal and external factors determining
satisfaction, Hackman and Oldham (1975) believe the Job Characteristics Model (JCM) will
assess an employee on multiple criteria attributing to their satisfaction, either positively or
negatively.
Job characteristics model. Hackman and Oldham (1975) suggested five central job
design characteristics which are personal and work-related outcomes, and a regulated individual
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difference construct. The five central job characteristics proposed are the following: (a) Task
Identity (i.e., the totality of the work), (b) Task Significance (i.e., the importance of the work),
(c) Skill Variety (i.e., the variability of talents used), (d) Autonomy (i.e., employee control and
decision making), and (e) Feedback (i.e., evaluation of employee performance). As
aforementioned in Hackman and Oldham (1975), JCM theorizes that a positively contributing
relationship exists between job design and the three dire mental states are
1. experienced relevance of work,
2. experienced obligation for work results, and
3. knowledge of outcomes.
Quantitative studies testing the relationship between an employee’s job characteristics
and overall job satisfaction have frequently exhibited positive findings (Fried & Ferris, 1987;
Loher, Noe, Moeller, & Fitzgerald, 1985). Research claims a strong correlation between job
characteristics and job satisfaction (r = .50) (Frye, 1996). The connection between intrinsic job
characteristics and job satisfaction is contingent on employees’ Growth Need Strength (GNS),
which is an employees’ want for individual and work development (Hackman & Oldham, 1975).
Hackman and Oldham (1975) proposed the importance of individuals needing to be
prepared with a set of skills to complete a specific task and JCM described how particular jobs
will have a higher level of significance than others because of the meaningfulness related to the
work (i.e. Dentists over Cashiers) (Daniels, LeBlanc, & Davis, 2014). JCM also demonstrates
how specific jobs give individuals more autonomy to make important decisions and retain
ownership over assigned tasks (Hackman & Oldham, 1975). Hackman and Oldham (1975) also
expressed that this psychological state contributes to more satisfied employees because of the
intrinsic motivation attributed to the work. A recent study of 143 teachers in the city of Punjab
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used the JCM to find a significant correlation between the motivating potential of a teacher and
their age (Nagrath, 2019). This correlation results in teachers looking for variation within their
job to accomplish the five central characteristics proposed by Hackman and Oldham (Nagrath,
2019).
One limitation of the JCM is that most of its’ studies have reaped skepticism due to the
use of self-reports of job satisfaction (Robert & Glick, 1981) as opposed to more formal
assessments. Secondly, it is difficult to assume job satisfaction and the perceptions of job
characteristics have a direct impact on an individual’s characteristics toward their level of
satisfaction (James & Jones, 1980; James & Tetrick, 1986). Minimal evidence has been
referenced on how the psychological state of a person impacts the affiliation between job
characteristics and projected results (Judge et al., 2011).
Therefore, in evaluation of the JCM, clarity is needed to determine whether the key
characteristics of job satisfaction and intrinsic motivation will translate into desired results
(Parker & Ohly, 2008). Even so, JCM suggests that employers who embody the five
characteristics will have greater motivating potential and give employees greater chance of
satisfaction due to less absenteeism, and potentially higher job satisfaction (Daniels et al., 2014).
In disagreement with this assumption, Morgeson and Humphrey (2008) suggest the JCM is
narrow in scope and not reflective of the positive attributes of work. Contrarily, the Affective
Events Theory is a construct reflective of the positive and negative aspects of a person’s work
environment.
Affective events theory. Weiss and Cropanzano (1996) planned a framework to describe
the body, reasons, and consequences of affective experiences while at work, and these
experiences lead to consequences that are behavioral and attitudinal. Emotional experiences
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influence employees’ attitudes at work, and in effect, impacts the behaviors (i.e., judgment and
affect driven) exhibited in the workplace (Kwun & Saavedra, 2000). Affective Events Theory
(AET) has argued for an employee’s negative and positive emotions to be included when
determining job satisfaction (Carlson, Kacmar, Zivnuska, Ferguson, & Whitten, 2011),
especially when describing how work events can impact attitudes toward work and yield a
cognitive reaction based on a person’s determination of what has occurred.
AET has four main components suggesting (a) the nature, reason, and consequences of
emotion derive from the job environment; (b) events cause emotive responses in the job
environment; (c) feelings are predictable and vacillate over time; and (d) emotional experiences
evolve in a multidimensional environment (Weiss & Cropanzano, 1996). An empirical
investigation of 121 employees aging from 17 to 65 years old, Fisher (2000) described how a
significant link persist between employee attitude or mood, and job satisfaction. In a more
related study Wegge, Van Dick, Fisher, West, and Dawson (2006) surveyed 2,091 call center
workers in the United Kingdom to assess their moods, emotions, and job satisfaction. Although
limited by a lack of longitudinal data and control of employee pre-dispositions, their research
presented how environmental factors within the organization influences affective experiences,
and thus, impacts job satisfaction levels (Mitchell, 2011).
AET proposes that emotional states mediate relationships between perceptions and
evaluations of the workplace (i.e., job attitudes), and that affective traits moderate relationships
between perceived work events and sensitive reactions to them (Weiss & Cropanzano, 1996). In
a past assessment, positive affectivity rendered a moderately positive relationship with
satisfaction toward the work itself (r =.31), and modestly related to satisfaction with supervision
(r=.10), co-workers (r=.14), pay (r=.14), and promotion (r=.21). Negative affectivity was related
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to the work itself (r= -.28), supervision (r= -.19), and co-workers (r= -.22); while, pay had a
correlation coefficient of -.14 and promotion -.13 (Bowling, Hendricks, & Wagner, 2008).
Positive or negative affectivity both have moderate to low relationships with job satisfaction
indicating affective disposition has some influence on the way people perceive the work they do
in their work environment (Staw, Bell, & Clausen, 1986).
Watson, Clark, and Tellegen (1988) defined positive affectivity as high energy, interest,
and enjoyable engagement, whereas negative affectivity is described as being arduous, anxiety
driven, and unfulfilled engagement (Watson, Clark, & Tellegen, 1988). Thoresen and Judge
(1997) reviewed 29 studies of positive affectivity and 41 studies of negative affectivity.
Moreover, they discovered accurate score correlations of .52 and -.40, for positive and negative
affectivity, respectively. AET is a cognitive appraisal that suggests events occur in the workplace
are evaluated for their relevance toward the person (Frijda, 1996), and the relevance of the event
will assist in determining whether the event is beneficial or harmful to the individual’s goals
(Weiss & Cropanzano, 1996). Situational approaches such as AET indicate how experiences in
the work setting can influence a person’s thoughts, feelings, and behaviors whereas dispositional
approaches place more emphasis on the personality of the employee.
Dispositional Theories
Dispositional theories hypothesize that job satisfaction is grounded in the personality
traits of the human being (Judge et al., 2001). Dispositional theories are the most recently
developed theories out of the theories discussed, and possibly, the most poorly developed.
However, dispositional theories have significance as they may be ingrained in an individual’s
characteristic traits (Judge et al., 2001). Hoppock’s theory, individualism and collectivism, and
core self-evaluation construct will be reviewed in the upcoming section.
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Hoppock’s theory. Hoppock (1935) determined employees who are satisfied with their
jobs will have more emotional stability than those who are dissatisfied with their work; and in
this regard, Hoppock created the Job Satisfaction Blank survey (JSB) for measuring the
consistency of four questions on a 7-point Likert scale. The purpose of the JSB survey is for
discovering more information about a person’s satisfaction with their job. In 1932, Hoppock
surveyed 40 employed adults and 40 unemployed adults to see what they liked and disliked
about their jobs. Hoppock’s findings from the study identified multiple influences to job
satisfaction, including social status determined by a person’s career, control over one’s job, and
relationships with coworkers and supervisors (Bowling & Cucina, 2015).
When Hoppock’s instrument was tested for validity and reliability by McNichols, Stahl,
and Manley (1978), their one-tailed correlational test discovered that there is a strong correlation
between job satisfaction and satisfaction with work (r = .73). During their reliability test,
Chronbach’s alpha values ranged from .758 to .890, presenting more evidence of the usefulness
of Hoppock’s survey. After Staw et al. (1986) summarized Hoppock’s extensive study on job
satisfaction, they learned how dispositional and statistical elements may be significant when
determining how to define job satisfaction and assess the emotional disposition of a person’s
attitude toward work. Hoppock began the process of systematically studying job satisfaction and
identifying a range of elements contributing to job satisfaction that are still considered today (i.e.
work fatigue and job conditions) (Rose, 2003).
Individualism and collectivism. Individualism and collectivism is a one-dimensional
construct, as the individualistic side represents people who like to work in isolation, and the
collectivistic side represents people who place extraordinary importance on camaraderie (Judge
et al., 2001). Employees who have a collectivistic approach love to work in solidarity with others
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to complete tasks, while employees with an individualistic approach prefer to accomplish tasks
with minimal assistance from coworkers (Anderson, Ones, Sinangil, & Viswesvaran, 2001). To
better explain individualism and collectivism, Markus and Kitayama (1991) used cultural
differences to describe their definition of self through vertical and horizontal orientations. The
vertical “self” embraces inequality as the horizontal “self” believes that people should be on
similar levels of social status (Triandis, 1995).
Within the nature of the interaction an employee has with the employer will reside their
own perception of “self”, and this interaction will affect how he or she perceives themselves as a
part of the whole business (Triandis, 1995). In addition, the construct of vertical collectivism and
horizontal individualism are dominant constructs as vertical collectivists see themselves as a part
of an in-group but with different social statuses; however, horizontal individualists are people
who see themselves equal with their co-workers (Thomas & Au, 2002). Overall, studies by Chiu
and Kosinski (1999), and Hui, Yee, and Eastman (1995) have provided inconsistent outcomes
when evaluating individualism and collectivism in terms of job satisfaction.
For example, Chiu and Kosinski (1999) completed a research study of 626 nurses from
two individualistic countries (the United States and Australia) and two collectivistic countries
(Singapore and Hong Kong), and their research revealed how individualistic employees had
higher levels of job satisfaction than collectivistic employees. With different findings, another
study by Hui, Yee, and Eastman (1995) evaluated the relationship between collectivism and job
satisfaction of two samples of Hong Kong departmental employees, and their analysis examined
how collectivism was related to higher levels of job satisfaction (r = .25 and r = .18). The
findings of Hui, Yee, and Eastman are different from those of Chiu and Kosinski because, Hui,
Yee, and Eastman studied collectivism within one country as opposed to multiple countries, and
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the population of their study likely contributed to a positive relationship between collectivism
and job satisfaction. In summary, the cultural dynamics and values of a society play a role in a
person’s view of their place in the work environment, and more research should be conducted to
assess the various findings over individualism and collectivism in relation to job satisfaction.
Core self-evaluation construct. Core self-evaluation theory originated from Edith
Packer (Judge, Locke, & Durham, 1997), who is an Objectivist philosopher who believes people
intuitively make abstract evaluations of themselves affecting their assessments of other people
and events (Packer, 1985). Core self-evaluation theories demonstrate significant relationships
between job-connected outcomes and core self-evaluation constructs (Judge et al., 1997). Self-
evaluation is a personality construct consisting of the four following specific qualities: (a) Self-
esteem- appraisal of their self-worth, (b) Generalized self-efficacy- ability to perform and cope
with multiple situations, (c) Emotional stability- tendency to feel calm and secure, and show
fewer reactions, and (d) Locus of control- belief in one’s capacity to impact the environment and
create desired outcomes (Johnson, Rosen, & Levy, 2008). Judge and Bono (2001) completed a
meta-analysis of 169 independent correlations of the four specific qualities and job satisfaction,
and in summary, collectively joined to form an overall core quality coefficient of .37. The
literature from Judge and Bono demonstrates how a generally positive relationship exist between
how people view themselves as part of the world using the four specific qualities of core self-
evaluation in connection to job satisfaction.
Two self-evaluation constructs are self-efficacy and self-esteem, and they have been
observed as exact task conditions and general traits (Eden, 1988; Pierce, Gardner, Cummings, &
Dunham, 1989). Even though self-efficacy and self-esteem are similar constructs, they are not
the same construct. They are not the same because self-efficacy is more of a motivational
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construct (ability to act upon your belief) and self-esteem lends itself more to an affective
construct as it aligns with feelings, emotions, and overall confidence (Brockner, 1988; Eden,
1988, Gardner & Pierce, 1998). Contrary to Judge and Bono’s (2001) self-evaluation construct,
Chen, Gully and Eden (2001) explained that content and factorial validation processes for
measuring general self-efficacy stood out sharply in comparison to self-esteem. Betz and Klein
(1996) learned that general self-efficacy has a higher association to task-specific self-efficacy
beliefs rather than self-esteem. Self-evaluation theory is a motivational characteristic because
self-evaluation theory entails the ability to succeed in various conditions (Chen, Gully, & Eden,
2004).
In summary, the construct of core self-evaluation theory is defined as the fundamental
idea where individuals cognitively think about themselves and how they maneuver in the world
(Judge et al., 1997). Data was analyzed across three samples and Judge, Locke, Durham, and
Kluger (1998) presented empirical evidence to express that self-evaluations had an accurate total
effect score of .48 on job satisfaction when constructs were self-reported and .37 on job
satisfaction when assessed individually. In terms of the self-evaluation theory, minimal empirical
evidence on this theory makes it difficult to ascertain the influences that attitudes and behaviors
have on work-related outcomes. However, interactive theories embrace the attitudes and
behaviors of the employee, while also assessing the situation presented in the work environment.
Interactive Theories
Interactive theories are those involving the nature of the person and the situational
experiences (Judge et al., 2001). The interactive theories for review in the upcoming section are
the Cornell model, Value percept theory, and Vroom’s theory. Multiple variables are taken into
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consideration when analyzing interactive theories, such as intrinsic and extrinsic factors (Hulin,
1991)
Cornell model. Hulin (1991) recommended a model of job satisfaction where job
satisfaction is defined as a function of the stability among (a) role inputs, (b) what the person
puts into the work role (i.e., preparation, capability and time), (c) role effects, and (d) what is
given (i.e., salary, working environment, and intrinsic factors). While the model appears reliable
on surface, a lack of research has been presented to support the ideas of Hulin as reported in
Judge’s (1990) study. During periods of high unemployment, individuals will devalue the efforts
they are putting in as they may not translate into positive work environments or higher paying
wages due to the laborers being more prevalent than the actual supply (Judge et al., 2001).
Value-percept theory. Locke (1976) claimed that a person’s values would govern what
satisfied them with an employer and the only dissatisfied values are those that are unfulfilled
based off the individual. The Value Percept Theory is modeled below
𝑆𝑎𝑡𝑖𝑠𝑓𝑎𝑐𝑡𝑖𝑜𝑛 = (𝑊𝑎𝑛𝑡 – 𝐻𝑎𝑣𝑒) x 𝐼𝑚𝑝𝑜𝑟𝑡𝑎𝑛𝑐𝑒 (Locke, 1976).
Colquitt, Conlon, Wesson, Porter, and Ng (2001) expressed that want reflects how much value
the employee desires, while have determines how much value the job supplies, and importance
reflects on the necessity of employee value. As reported by Judge et al. (2001), one possible
issue with the value-percept theory is that what one wants and what one needs of worth are likely
to be strongly connected; albeit, the concepts are hard to distinguish from each other despite
being separate concepts.
A job facet, according to Locke (1976), is any feature of an occupation or its
characteristic that could impact overall job satisfaction. Locke (1976) hypothesized that the
have-want discrepancy is the perceived gap in the amount of a job facet that an employee wants
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to experience in comparison to the amount an employee realistically experiences (McFarlin,
Coster, Rice, & Cooper, 1995). Locke’s (1976) theory is also known as the range of affect
hypothesis where facet importance is the central element in deciding the level of satisfaction
linked with any specific job facet.
One criticism of the Value-Percept theory is that theories found in the United States are
not consistently generalizable to workers in other countries and this is evident by workers of
different countries having deviated beliefs toward the value of experiences in their work
environment. For instance, South African workers in a sample study perceived the have-want
discrepancy yielded indisputable support for Locke (Adler, 1991). Additionally, in 11 or 12 job
facets, the perceived discrepancy and facet importance was significant with a rate of 92%
(McFarlin et al., 1995). Facet importance monitors the relationship between facet amount and
facet satisfaction, and job satisfaction consistently argues that overall facet satisfaction is
predicted by the significance (high or low) of each facet satisfaction total (Rice, Gentile, &
McFarlin, 1991).
Vroom’s expectancy theory. Substantial preparations of expectancy theory (Campbell,
Dunnette, Lawler, & Weick, 1970; Graen, 1969; Lawler, 1970; Porter & Lawler, 1968; Vroom,
1964) hypothesize that a person's inspiration to work increases the relationship among effort, and
work-related prizes as the connection is often separated into effort-performance, performance-
reward, and worthwhile employee rewards. Lawler (1968), Sheridan, Slocum, and Richards
(1974), and Van Maanen (1972) assessed statistics over time and found varied results as
historical relationships of factors were substantially stronger than more fixed associations;
however, another study (Lawler & Suttle, 1973) found minimal evidence on the benefits
historical relationships among effort, performance, and reward.
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Kopelman and Thompson (1976) conducted a study consisting of 399 design and
development engineers from three large technology corporations who were assessing a 180
question survey over expectancy value. While examining incrementally growing correlations,
Kopelman and Thompson (1976) discovered the expectancy theory reports to be positively
related to supervisory performance rankings, motivational self-reports, and overall performance.
For example, two concurrent predictions of supervisory rated performance (r= .24; r = .33) are
within the range of coefficients found in prior research (r = -0.7 to r = .39) based on a 16
question survey (Kopelman, 1974).
Expectancy theory provides a theoretical basis for constructing a conceptual model of
motivation (Vroom, 1964). Likewise, expectancy theory of motivation suggests the expenditure
of a person’s effort will determine the expected outcomes and values that people place on their
minds (Isaac, Zerbe, & Pitt, 2001). Vroom (1964) examined expectancy theory predictions of
work motivation and job performance taking the following five conditions into account: (a) time,
(b) the initial level of criterion, (c) level of reward, (d) task-specific ability, and (e)
organizational control system responsiveness. Kopelman and Thompson (1976) found that a one-
year time lag increased the correlation of static prediction on supervisory rated performance (r
=.24). Nonetheless, the validity of the expectancy theory depends on the empirical test given as
conventional approaches to assessing the boundary conditions of this theory have varied (House,
Shapiro, & Wahba, 1974; Kopelman & Thompson, 1976; Reinharth & Wahba, 1974). Similarly
situational, dispositional, interactive and motivational theories are included in this study because
of the extensive research on job satisfaction (Deconinck, James, and Bachmann, 2009; Gurbuz,
Sahin, & Koksal, 2014; O’Reilly, Chatman, & Caldwell, 1991; Ramlall, 2004; Rasskazova,
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Ivanova, & Sheldon, 2016; Roberts, Kevin, and Lawrence, 1999; Rybnicek, Bergner, &
Gutschelhofer, 2019; Shoaib & Kohli, 2017; Taormina & Geo, 2013; Tietjen & Myers, 1998).
Motivational Theories
Motivational theories on employee commitment and job satisfaction as explained by
Robbins and Judge (2008), define motivation as the desire to wield higher altitudes of effort, by
way of effort’s ability to gratify an individual need. Motivational theories are incorporated within
this historical review of job satisfaction theories because motivation is a vital element in
improving work efficiency, and every educational school principal needs to have a concrete
understanding of how motivation correlates with job satisfaction and reward methods (Pardee,
1990). The theories discussed in the upcoming section are Maslow’s hierarchy of needs,
McGregor’s x y theory, McClelland’s need for achievement theory, and the Equity theory.
Maslow’s hierarchy of needs theory. Abraham Maslow hypothesized that people have
five categorizations of needs performing as motivators, such as
1. physiological needs,
2. safety and security needs
3. social and belongingness needs
4. self-esteem needs,
5. and self-actualization (Berl, Williamson, & Powell, 1984).
Maslow placed the five essential needs in a hierarchy (Haggerty, 1999). The physiological level
of hierarchy needs serve as the base for the preceding levels and generally the higher the need,
the less probable the need will be achieved (Peters, 1997). Thus, if a person doesn’t have a
consistent supply of food and water then they may not to not have a significant concern for
housing or love, until their physiological needs are met first.
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More recently, 386 working adults were examined using Maslow’s Hierarchy of Needs
Theory to see if there was a significant association between the level of hierarchal satisfaction
that doctors and lawyers have for their jobs in comparison to low-income immigrant workers
(Taormina & Geo, 2013). Taormina and Geo (2013) exhibited significantly positive
correlations among scales as each hierarchal need varied significantly (p < .001) in the
anticipated direction, with underemployed immigrants as (M = 2.55, SD = 0.49) lesser than
business professionals (M = 4.19, SD = 0.63) on the satisfaction of physiological needs (t(60) =
11.41). This information illustrates that the more people are satisfied with their basic needs then
the more expected they are to achieve a higher level need. Maslow’s Hierarchy of Needs Theory
is grounded on the “healthy man” idea from Peters (1997), where an individual is motivated by a
personal need to develop and reach his or her fullest potential.
Despite the success of Maslow’s Hierarchy of Needs Theory, one major issue is the
prearranged worth placed on an individual’s needs. Locke (1976) admits although a person’s
needs may be comparable, his or her values may be different. Moreover, Tietjen and Myers
(1998) believe values have the most influence on the emotional response to one’s job. Maslow
used a hierarchy of needs to determine a person’s thoughts or actions as Locke used a person’s
values to identify his or her thoughts or actions.
Regardless of the varying opinions, Maslow’s Hierarchy of Needs Theory demonstrates
the significance of obtaining low-level needs as people may not desire to reach self-actualization
until their primary needs are met first. A research study of 10,827 Russian workers of a heating
and air company compared the effects of low and high-level need satisfaction (Rasskazova et al.,
2016). The effects size was .54 for the correlation between well-being and security in
comparison to the effect size of .32 for well-being and intrinsic motivation (Rasskazova et al.,
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2016). This study suggested with empirical evidence that Maslow’s theory is still relevant
because meeting one’s lower-level needs will help a person to obtain higher level needs, leading
to more positive results (Rasskazova et al., 2016).
McGregor’s x y theories. Douglas McGregor’s ideas were first detailed in his article
entitled, The Human Side of Enterprise (McGregor, 1957), and later described in his book in
1960 with the same title. Both sources questioned the fundamental assumptions about human
behaviors while in organizational environments (Kopelman, Prottas, & Davis, 2008).
McGregor’s Theory Y assumes that employees are not innately indolent, and are capable of self-
regulation and self-governance, and are more than capable of giving ideas to help produce
organizational effectiveness. In contrast, McGregor’s Theory X (1985) theorized that employees
are indolent, irresponsible, incapable of self-regulation and self-governance, and will offer
minimal efficiency to the organization.
McGregor’s X Y Theories are not empirically supported with on job performance as
findings has shown positive and negative correlations between Theory X Y attitudes and Theory
X Y behaviors of managers (Kopelman et al., 2008). In spite of inconsistent findings in support
of McGregor’s theories, Goldman (1983) believes some school administrators use these types of
approaches. By using Theory X, these leaders may feel they need to take more of a domineering
role to get employees to perform and may naturally develop a negative workplace that could
lower an employee’s job satisfaction. Accordingly, employees in a Theory X environment or
management structure tend to be motivated by a fear of failure, and typically feel overwhelmed,
less supported and undervalued (Friesen, 2015). In contrast, managers whose actions align more
with Theory Y will utilize a more positive view toward independence, entrustment, praise and
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responsibility (Lawter, Kopelman, & Prottas, 2015), and Theory Y could lend itself to a more
positive work environment that could produce higher employee job satisfaction.
A recent test was conducted to investigate the assertion of McGregor’s X Y Theory on
the impact of human behavior on employee satisfaction (Gurbuz et al., 2014). The results of
research by Gurbuz et al. (2014) detailed how the Theory Y managerial style is positive and
significantly connected with subordinates’ satisfaction level with the military leader, affective
obligation, and organizational allegiance. On the other hand, Theory X managerial style is
negative and significantly influences subordinates’ satisfaction with the military leader, even
though no significant influence occurs with affective obligation and organizational allegiance
(Gurbuz et al., 2014). While the articles discussed have explored McGregor’s X Y Theory from a
business perspective, future researchers should assess the impact school leaders would have on
employee job satisfaction that used a Theory X attitude/behavior (pessimistic leader view) versus
a Theory Y attitude/behavior (optimistic leader view).
McClelland’s need for achievement theory. The McClelland (1961) theory focused on
three areas: (a) achievement, (b) power, and (c) affiliation (Ramlall, 2004). In addition,
McClelland’s research supported the idea of the economic development level of a country being
related to its overall achievement and motivation (McClelland, 1961). McClelland developed the
following factors that reflect a high need for achievement:
1. Achievers like to be solution oriented.
2. Achievers set adequate goals and are willing to take risks.
3. Achievers appreciate receiving timely and useful feedback (McClelland &
Johnson, 1984).
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McClelland proposed that people with a need for achievement are believed more to become high
achievers and successful entrepreneurs. In contrast, those who need affiliation may tend to have a
hard time making decisions due to their disdain for being disliked (Kreiter & Kinicki, 1998;
Ramlall, 2004).
This theory asserts that workers differed in their need to achieve a task, and as a result
experienced greater work motivation when the reward met a personalized need of the worker
(McClelland, 1985). Recent empirical research made this more evident to today’s times when
Rybnicek et al. (2019) assessed the motivational influencers of 44 Master’s in Business
Administration (MBA) female students from Austria who had an average age of 25 and standard
deviation of 2.26. They determined whether opportunities for an individualized reward of a
company car, respected leadership, or high income influenced their motivation toward work.
Rybnicek et al. (2019) discovered a close match between the type of reward and the individual
need of the employee increasing the neurological activations in the brain. This finding further
supports the assumption of McClelland’s need theory for taking a personality approach toward
work rewards as the key to increasing work motivation and job satisfaction (Rybnicek et al.,
2019).
The theory of learned needs is not only a motivational tool for people, but Winter (1992)
contends that learned needs address most of the significant human concerns. People’s
achievement needs are fulfilled when they can realize their own goals in relation to or regardless
of the assistance of others (Yamaguchi, 2003). High achievers are more satisfied with
employment opportunities that include extraordinary skill capability and difficult expectations
(Eisenberger, Jones, Stinglhamber, Shanock, & Randall, 2005). Like high achieving workers,
high achieving organizations may value satisfaction from informal accountability, and this
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concept is where any person in the organization is willing to be held responsible for the attitudes
or behaviors of others within the organization, regardless of their position or rank with the
organization (Royle & Fox, 2011). Additionally, high achievers in the workplace seek felt
accountability, defined as the intrinsic value or importance a person feels they have toward the
success of a company that impacts their behavior at work (Royce & Hall, 2012). People who
desire high affiliation needs seek felt accountability (Royle & Hall, 2012), because felt
accountability makes people feel a sense of responsibility to the needs of power, achievement,
and affiliation as felt accountability intertwines with their goals personally and professionally.
Baron and Kenny’s (1986) three-step procedure was used by Royle and Hall (2012) on testing
independent, dependent, and mediator variability of felt accountability and informal
accountability, deriving from McClelland’s Need for Achievement Theory. Findings from Royle
and Hall’s (2012) research showed that felt accountability, was negatively related to needs for
power (b = -.21, p < .01).
In addition, employee needs for affiliation was significantly positive, related to the
dependent variable (b = .37, p < .001) (Royle & Hall, 2012). The need for achievement proved to
be a significant predictor (b = .27, p < .01) of informal accountability and felt accountability
(needs for power, achievement, and affiliation) was also a strong predictor (b = .33, p < .001) of
informal accountability. This research suggests testing the personality of employees could reduce
the risks of costs related to employee stress, reduce levels of job dissatisfaction, and turnover
(O’Reilly et al., 1991). However, the Equity Theory differs from McClleland’s Theory because
Equity theory doesn’t just look into the intrinsic or extrinsic motivation people have to complete
a task, but equity theory addresses how people compare the reward they receive to their
coworkers.
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Equity theory. Equity Theory recognizes people are not only concerned about the
amount of recognition or reward they receive from their employers but also care about the
rewards in comparison to their peers' efforts (Ramlall, 2004). This concept was first generated by
Adams (1965), as he explained the two individuals involved in this theory being the “person”
and the “other.” Adams continues in his research to describe the “person” as anyone who may
experience some inequity during his or her work, and the “other” represents any one or any
group that the “person” is using as a comparison.
With regard to a person’s inputs, Ramlall (2004) argued that effort, experience,
education, and competence can be compared to workplace outcomes, such as salary promotions,
fringe benefits, position promotions, and public recognition. He recognized that pay is the most
critical outcome in reference to a person’s willingness to remain or leave an employer. To
describe the causes of real and perceived inequity, Pinder (1984) expressed how feelings of
unfair treatment generally occur when people perceive they aren’t receiving equitable returns in
comparison to what they give to the company. Champagne and McAfee (1989) acknowledges
that employees may experience consequences when employees have a perceived inequitable
balance between their efforts and compensation. Some of these consequences include (a) a
decrease in input performance relative to the output, (b) an attempt to increase output by seeking
a more satisfying environment within the company that involves a salary increase, and (c)
withdrawing altogether and seeking new employment (Champagne & McAfee, 1989).
The relationship between the perception of equity and job satisfaction is very substantial
(Lambert, Hogan, & Griffin, 2007). Roberts et al. (1999) argues that equity can be observed in
pay level fairness, job security, promotional equity, and evaluative equity. Deconinck et al.
(2009) assessed the relationship between perceptional pay equity, job satisfaction, employee
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commitment, and potential turnover, and their research supported the assumption that pay equity
has a positive relationship with job satisfaction. Berkowitz, Fraser, Treasurer, and Cochran
(1987) studied the perceptional equity of 248 full time employed men and they discovered that
pay satisfaction and current perceptional inequity were negatively related, and future
perceptional equity and pay satisfaction were positively related. Livingston, Roberts, and
Chonko (1995) believe investigating the facets of equity can help supervisors concentrate their
actions on specific elements that may improve job satisfaction outcomes.
Adams (1961) and Mowday (1991) examined the perception of inequity on productivity
to assess whether people who believe they are underpaid for their work will reduce their level of
production Their inquiries strongly supported the idea that work underpayment decreased the
quantity or quality of production overtime. Conversely, Adams (1961) and Mowday (1991)
discovered that equity could be restored with a payment plan between the worker and the
employer. Also, work overpayment was inconsistent with showing a correlation between wages
and quality or quantity of production.
Unpredictability is the most apparent limitation of equity theory because determining
how a person will behave when attempting to regain trust with the organization after feeling their
hard work has not being rewarded is an extremely challenging task (Anderson et al., 2001). The
limitation of unpredictability severely limits the usability of equity theory and diminishes the
validity and reliability of the equity test overall. One of the most ambiguous parts of equity
theory is how the individual chooses the “referent other”, the person who they will be comparing
the perception of equity with in the workplace. Regardless of the assumption that people
generally choose one referent other when comparing their equity levels, Goodman (1974) and
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Summer and DeNisi (1990) demonstrated that multiple referents are used for equity theory
comparisons because one referent is not realistic for definitive testing.
Summary of Job Satisfaction Theories
In summary of all the job satisfaction theories and approaches, Judge et al. (2001)
believes that Locke’s value-percept theory, the job characteristics model and the dispositional
approach are the most supported theories from research. Judge et al. (1997) proposed that
intrinsic job characteristics support the association between the dispositional approach of self-
evaluation and job satisfaction. Job satisfaction is described as an optimistic, emotional state
(Locke, 1976), where a person’s assessment of their job experiences will have an impact on their
desired and actual job performance, and the amount to where the person’s values are not aligned
to the person’s performance.
When defining job satisfaction as a worldwide construct, scholars such as Smith,
Kendall, and Hulin (1969), recognize the typical facets or categories are promotion, salary,
administrative supervision, co-workers, and the work itself. Job satisfaction may be defined by
the cultural dynamics of an environment as Judge et al. (2001) explained in their research
regarding how countries found the disposition of individualism to have a positive association
with job satisfaction. However, Hue et al. (1995) conducted research in a country with a different
cultural background and found collectivism to have a positive association with job satisfaction.
Research indicates that job satisfaction is comprised of a combination of components that
Ferratt (1981) and Smith et al. (1969) describe as going beyond a constant level of satisfaction
into measuring the increase of overall job satisfaction with the satisfaction of each individual
facet (Conway, Williams, & Green, 1987). Many scholars have identified the relationships
between turnover, absenteeism, and job satisfaction to show that a person’s attitude toward a job
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may influence his or her behavior (Arnold & Feldman, 1982; Cheloha & Farr, 1980; Katz, 1978;
Locke, 1976; Michaels & Spector, 1982; Newman, 1976). In contrast, Conway et al. (1987)
explained that employee attitude surveys resemble behaviors of the organization and if facets are
identified in the survey to contribute to job satisfaction, then an assumption can be made that a
person can increase someone’s overall level of job satisfaction by altering one or more of those
facets.
Facets of Job Satisfaction
Job satisfaction is described by Spector (1997) as how people feel about their
employment and to the extent they like or dislike their jobs. Teacher job satisfaction can be
impacted by a variety of aspects such as principals, salary, working conditions, professional self-
growth, recognition for work done, the work itself, and other workers (Ostroff, 1992). Data
describes how employees who feel underrated and unrewarded may decide to leave their jobs for
something different (Calitz, Roux, & Strydom, 2014).
Salary. Salary or pay is the facet satisfying a person’s financial needs and influencing a
person’s outlook and behavior (Singh & Loncar, 2010). Research provided by Williams,
McDaniel, and Ford (2007) established that pay satisfaction is a multifaceted construct. Pay
factor is the respective income a person receives for the work completed, while pay management
is the structure of compensation that addresses working conditions (Ozpehlivan & Acar, 2016).
When studying job satisfaction, Berkowitz et al. (1987) detailed that a person’s level of pay
determines how satisfied they will be with their employment.
Pay satisfaction is defined by the various mechanisms of pay, such as pay level, pay
raises, benefit pay, and pay structure (Heneman & Schwab, 1985). In addition, Judge (1993)
researched how the mechanisms of pay were all interrelated toward the satisfaction people
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receive from a perceived satisfactory base pay or a pay raise. A meta-analysis of 213 examples
and 182 studies conducted by Williams et al. (2007) found a .79 and .81 correlation between pay
raise, pay level, and pay structure satisfaction, respectively, as these relationships should inspire
other experimental studies. Employee perception of the significance of individual performance
toward the possibility of obtaining a pay raise may gain more satisfaction with their pay raise
than people who do not value the correlation between performance and pay outcomes (Heneman,
Greenberger & Strasser, 1988).
Promotion. Luthans (1973) identified promotion as a component of a person’s job
satisfaction and a key element in the growth of job satisfaction. Kosteas (2007) argued that
promotion increases job satisfaction because workers who think positively about the idea of
receiving a promotion typically have higher levels of satisfaction. In contrast, Anfara, Andrews,
Hough, Mertens, Mizelle, and White (2003) argued that negativity is evident when employees
feel they have a minimal chance of promotion.
Shields and Ward’s (2001) review of satisfaction suggested job dissatisfaction may have
a higher influence on a person’s intentions to resign rather than the dissatisfaction a person may
have with the work itself or pay, because of promotions and professional growth opportunities.
Idson (1990) and Scherer (1976) both described in their employment survey research a negative
association between organization size and job satisfaction. They indicated that the relationships
between promotion rates and job satisfaction positively increased as an organization’s size
decreased. Promotional opportunities are suggested by Kosteas (2007) to enhance a person’s
satisfaction level because this factor is anticipated to bring about higher positions relative to a
person’s co-workers and higher potential for increased wages.
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Administrative supervision. Administrative supervision influences the satisfaction level
of teachers as explained by Boyd, Grossman, Ing, Lankford, Loeb, and Wyckoff (2011) because
district leaders, principals, and assistant principals play a significant role in the daily operations
and growth of every teacher. Administrative leadership plays a crucial role in empowering and
motivating teachers through self-determination (Bass, 1990; Bennis & Nannus, 1985). Educators
are highly satisfied according to Hulpia, Devos, and Rosseel (2009) and Tillman and Tillman
(2008) when they receive support and assistance from their building principals.
Co-workers. Professional learning communities with colleagues are essential to the
development of a trusting relationship amongst educators (McNeil, 2016). George and Jones
(2005) believe that co-workers have an influence on job satisfaction. Employees who support
each other are considered positive role models who improve job satisfaction for each person
(Churchill, Ford & Walker, 1974; Erdoğan, 1996; Hackman & Oldham, 1974; Mullins, 1996;
Wright & Kim, 2004).
The work place satisfaction. Work place conditions are reported a have a significant
influence on a person’s intentions to resign rather than the dissatisfaction a person may have with
the work itself (Bokemeier & Lacy, 1987). Price and Mueller (1986) believe people who spend
most of their time in the work environment, generally care about the type of satisfaction received
from the workplace. How much an employee likes or dislikes the culture of the workplace
around them will determine their thoughts and feelings. Taylor and Tashakkori (1995)
communicated that teachers use descriptive factors for employee satisfaction centered on how
they feel about work, such as student support, affiliation, professional interest, innovation,
resource adequacy, and principal leadership. However, when teachers are dissatisfied with the
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facets of job satisfaction that influence their individual situations, then dissatisfaction may arise
(Farrell, 2000).
Work Related Factors that may influence Job Satisfaction
The purpose of this section is to provide more guidance over identified factors that
influence job satisfaction. Research describes potential causes of low teacher satisfaction and
poor retention rates as the overwhelming increase of demand on teacher workload (Dinham &
Scott, 2000), increasing governmental controls and negative student discipline (Moriarty,
Edmonds, Blatchford, & Martin, 2001; Personnel Today, 2003; Sillitoe, 2003), principal
leadership or management style (Schultz & Teddlie, 1999), job associated stress (Evans, 1998),
minimal importance placed on teaching as a profession (Evans, 1997; Halpin, 2001; van der
Doef & Maes, 2002), oversized student classes (Maclean, 1992), challenges of working with
colleagues (van der Doef & Maes, 2002), negative associations of the social media’s impact of
working in a ‘failing’ school (National Union of Teachers, 2001; Scott & Dinham, 2003), and
pay (Chung, Dolton, & Tremayne, 2004). Class size, workload, gender, age, race, experience,
tenure, education level, salary, and principal leadership in general will all be discussed in this
section as work related factors influencing job satisfaction.
Class Size
Class size is defined as the number of students in a specific course or classroom,
precisely either (a) the exact number of students receiving instruction by individual teachers in a
course or classroom, or (b) the average number of students receiving instruction by teachers in a
school, county, or education system (The Glossary of Education Reform, 2015). Greenhouse,
Moyer, and Rhodes-Offutt (1992) performed a study to examine the correlation of educators,
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class size, and job satisfaction. Their findings reported the five areas that lowered job satisfaction
as miscellaneous work, low wage, angry parents, class sizes, and shortened instructional time.
Class size is an element that influences job satisfaction. Research from Alt, Kwon, and
Henke (1999) indicated that teacher job satisfaction decreases as the number of students in a
class increases. More specifically, they identified that 80% of educators who had classes of 15
or fewer students were satisfied with this size, while less than 40% of educators in classrooms of
more than 26 students were pleased with their roster sizes (Alt, Kwon & Henke, 1999).
Another study was designed to search how classroom size affects a teacher’s feelings
over job satisfaction and self-ability (Schwichtenberg, 2012). Cross-examined and surveyed
teachers from her research indicated that student achievement was the central provider of
emotions toward job satisfaction, and bigger class sizes reduced student achievement, thereafter
decreasing educator job satisfaction. The development also inspected ideal class sizes for regular
level courses for high school students and outcomes specify the optimum class size for high
school courses have a variance of 22-25 students per class (Schwichtenberg, 2012). More current
research suggested that class sizes of students between the range of 15 and 18 are recommended
overall to help in aiding a positive learning environment (Mathis, 2017).
In addition, some studies have expressed a linking between larger class rosters and
negative student behavior and smaller class rosters and positive student behavior (Achilles,
Kiser-Kling, Aust, & Owen, 1995; Bourke, 1986; Molnar, Smith, & Zahorik, 1999). Though,
Finn, Pannozzo, and Achilles (2003) found no significant difference between small and big
classes, and the number of unsuitable interactions between students and teachers. So, more
current research is needed to assess if class size does consistently influence job satisfaction,
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especially in schools with diverse populations. Nonetheless, empirical research shows there is a
relationship between class size and job satisfaction.
Workload
The tasks placed on workers define a person’s workload and can be categorized into
qualitative or quantitative work. Horn, Taris, Schaufeli, and Schreurs (2004), McNeil (2000),
Murnan and Papay (2010), and Spector (1997) define qualitative work as the energy or effort that
is put into the job behavior using one’s physical or responsive capacity to complete a task (e.g.,
effort given to content planning with a team of teachers). Alternatively, quantitative work is the
total amount of work or time needed to finish a duty (e.g., contractual workdays or total hours
required at work) (Podgursky, 2003; Spector, 1997). Both types of work could potentially have a
positive or negative influence on job satisfaction.
Workload (i.e., hours worked or effort given at the workplace) also relates to one’s belief
toward satisfaction with their job (Çogaltay, & Karadag, 2016). Teachers may serve multiple
roles or duties before school, during school, after school, or on the weekend beyond their
expected duty hours; such as, school leadership team member, focus group or committee team
member, department chair, coach, content lead teacher, tutoring, and more. These workloads
may consist of school duties performed outside the classroom, where educators will work over
40 hours per week on average, on the weekend, and may even work during their summer
vacation time (Cogaltay, & Karadag, 2016).
Educators encounter social interactions that happen on a regular basis with students,
supervisors, colleagues and parents. A teacher’s psychological, emotive, and or physical state
may be swayed by one or more of these relationships when having a substantial workload with
multiple interactions (Burke, Borucki, & Hurley, 1992). Hussain and Saif (2019) assessed the
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correlation between employee workload and job satisfaction by studying the results of
quantitative findings on 266 Pakistan teachers. As a result, their outcomes determined that a
major affiliation between workload and job satisfaction exist (t=2.55, p<0.05) because the t-
statistic is greater than 1.96, and this statistic reveals that workload has an influence on teacher
job satisfaction.
Gender
Research has shown that teacher gender does have a correlation with job satisfaction
possibly due to the stress generated from one’s job. Female teachers scored higher than male
teachers in dealing with stress; even so, male teachers scored higher than female teachers on
school environment factors, teacher efficacy, and job satisfaction (Tran, 2015). Female teachers
typically have more educational commitment toward their job than male teachers in the opinion
of Kamari and Jafri (2011), as they assessed male and female educators from Aligarh Muslim
University.
Other studies found that female teachers exhibit higher levels of job satisfaction than
male teachers (Chaplain, 1995; Klecker & Loadman, 1999; Poppleton & Riseborough, 1991).
Suki and Suki (2011) found no significant correlation between gender and job satisfaction,
because males and females were examined to have similar levels of job satisfaction. However,
Zilli and Zahoor (2012) discovered that female teachers have a higher level of organizational
commitment and job satisfaction than male teachers.
In spite of findings presented by Zilli and Zahoor (2012), Liu and Ramsey (2008)
recognized how females have lower job satisfaction than males, especially due to working
conditions and high stress levels as opposed to their male counterparts’ experience. Another
study by Kumari and Ibrahimi (2015) didn’t find a significant difference between male and
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female teachers because their results reported men have a mean of 24.2 and standard deviation of
1.20, while women educators received a mean of 24.6 and standard deviation of 1.90. But, a
study from a sample of 1,641 Chinese men and 1,375 Chinese women examined the correlation
between job satisfaction and gender by the use of a Chinese General Social Survey that described
women as being less satisfied with their jobs than men (Luo, 2016).
In contrast, Carrillo-García, Solano-Ruíz, Martínez-Roche, and Gómez-García (2013),
Sloane and Williams (2000), and Zou (2015) have conveyed how females show more job
satisfaction than their male colleagues. These analyses propose that besides the systematic
dissimilarities in working characteristics experienced by females and males, diverse job
expectations and values in job prizes cause the variances in job satisfaction between the two
groups. Throughout the review of related literature, evidence exist that teacher gender is
warranted as a factor contributing to job satisfaction in some capacity.
Age
Age is described as a factor influencing job satisfaction. Explanations are varied with
some (Herzberg et al., 1957) accrediting this to new personnel being eager and relishing the
challenge of labor while older personnel have accepted their place in the business and foresee
narrow career opportunities. Clark et al. (1996) claimed that employees’ expectations change
with age, but Oshagbemi (1999) argued that older employees are more capable or have
developed approaches to handle work-associated matters. Conversely, a negative linear
relationship exists among age and job satisfaction (Hickson & Oshagbemi, 1999). Justifications
for this negative relationship include older employees’ incapacity to adjust to new working
environments (Hickson & Oshagbemi, 1999) or older employees’ principles and desires are more
demanding than those of newer coworkers (Luthans & Thomas, 1989).
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More recently, the social-emotional selectivity proposed by Ng and Feldman (2010)
expressed that as people get older, the probability of experiencing positive sentiments rise and
negative sentiments decline as a product of fluctuating discernments toward how long they will
live. The research studies shared in reference to age show that wavering positions exist in
relation of age and job satisfaction overtime. Current research should be explored to gauge the
type of influence (positive or negative) between a teacher’s age and teacher job satisfaction.
Hence, age should be recognized as a factor that contributes to job satisfaction or dissatisfaction.
Race
Based on the research from Duncan (1977), multiple factors influence the relationship
between job satisfaction and race, such as marginal benefits, workplace settings, and
employment constancy. In order to consider the relationship between job satisfaction and race,
Bartel’s (1981) analysis indicates one must consider both the effect of race on wages and the
direct effect of race on measured job satisfaction. His research denotes how discrimination may
reduce Blacks from accessing the same job opportunities as their White counterparts, and
employers may desire to discriminate against minorities in nonwage aspects that may not be
apparent to recognize. Hence, the historical study discovered that Blacks may have lower job
satisfaction levels from Whites even if their wages are the same (Bartel, 1981).
As with Bartel (1981), Hersch and Xiao (2015) reviewed the 2010 National Survey of
College Students and determined a correlation between race and job satisfaction among Asians,
Blacks, Hispanics/Latinos, and Whites. Their study found that Blacks and Asians of the same sex
have distinctly low levels of satisfaction than their White Counterparts. Yet, the limitation of the
study was the inability to distinguish if the lower level satisfaction was due to discrimination or
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from individual differences in job expectations. As a result, research explains that race can
influence job satisfaction and future studies will help in assessing their relationship.
Experience
Minimal studies have discussed the correlation between teacher experience and job
satisfaction. Although, Oshagbemi’s (1997) research suggests that teacher experience has a
positive effect on job satisfaction. Other results by Oshagbemi (2000) indicate greater levels of
satisfaction among employees with 10 years of experience and experience increases with each
additional decade of experience. In contrast, evidence proposes that teachers with five or less
years of experience are the most satisfied and teachers with 15 to 20 years are usually the least
satisfied (Poppleton & Risborough, 1991). Less experienced teachers can be described by the
positive energy they have being in alignment with Herzberg et al.’s (1957) thesis, or by the
varying expectations of seasoned veterans (Luthans & Thomas, 1989).
Research developed from work of Huberman’s foundation (1989) discovered that
teachers generally experience increases in organizational commitment motivation, and
satisfaction as they work with a company. However, when teachers work more than 24 years
they typically experience a decline in motivation or satisfaction (Day & Gu, 2007). In fact,
recent statistics show that most American teachers have an average of about 14 years of
experience, and 60% of teachers have 10 or more years of experience (Klassen & Chiu, 2010;
U.S. Department of Education, 2009). A reasonable assumption is that job motivation will
associate with job satisfaction because teacher demographics, school characteristics, and human
resources have been mutual variables used to regulate levels of job satisfaction (i.e., gender,
ethnicity, age, years of experience, education, region, and student enrollment) (Crossman &
Harris, 2006; Perie & Baker, 1997).
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Consequently, since the 1987-1988 school year, the National Center for Education
Statistics (NCES) has occasionally tracked teacher turnover with a survey known as the Schools
and Staffing Survey (SASS). Among the teachers tracked, attrition rates have ranged from 13.1%
to a high of 16.7%, and reportedly less than 15% of teachers leave the profession for retirement
(Kelly & Northrop, 2015). On the other hand, majority of educators leave the profession during
the first five years of employment due to dissatisfaction with the job (Kelly, 2004). Despite
mixed findings from studies, evidence shows a relationship between teacher experience and
teacher job satisfaction is present.
Tenure. Organizational tenure is defined as the length of employment in an organization
(McEnrue, 1988; Shirom & Mazeh, 1988), and it has been considered as a quantitative indicator
of work experience because by remaining with a firm for additional years, employees can
develop a wider set of work skills and become more familiar about the company as a whole
(Bird, 1996). Tenure cannot be achieved without accruing experience within an organization. In
the State of Georgia, Education Law Code Section 20-2-940 reports that tenure in Georgia is
granted when teachers receive their fourth consecutive contract from the same location board of
education as this provides the educator with more legal rights to a hearing if the local school
principal recommends dismissing their employment to local board of education (“Find Law”,
2020). Section 20-2-940 explains that a teacher is considered to have accepted a fourth
consecutive school year contract if, while the teacher is serving under the third consecutive
school year contract, the local board does not serve notice to the teacher by May 15th that they
do not intend to renew the teacher's contract for the ensuing school year, and the teacher does not
serve notice in writing to the local board of education by June 1st of the third consecutive school
year that he or she does not accept the fourth consecutive school year contract.
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Bedeian, Ferris, and Kacmar (1992), Ng and Feldman (2010), Hochwarter, Ferris,
Perrewe, Witt, and Kiewitz (2001) have dedicated more effort to focusing on age rather than
tenure as a time metric. Bird (1996) and Ng and Feldman (2010) claimed that 92% of studies
involving organization tenure measured tenure as a continuous variable (i.e., years of
employment) where the average tenure was 8.1 years (SD = 4.5 years). Studies have generated
contradictory empirical evidence about the affiliation between tenure and job satisfaction,
including adverse (Bedeian et al., 1992), positive (Ng & Feldman, 2010), and no correlation
(Clark, Oswald, & Warr, 1996; Hochwarter et al., 2001; Kalleberg & Loscocco, 1983).
Intellectuals advocating for a positive association between tenure and job satisfaction claim that
unsatisfied staff members leave their employer, while satisfied staff members continue with the
organization (Sarker, Crossman, & Chinmeteepituck, 2003). Furthermore, employees with longer
tenure may experience grander opportunities related to job satisfaction, such as advancement,
rank, and control (Kalleberg & Matstekaasa, 2001).
Moreover, as tenure rises, staffers may engage in reflective reasoning to justify the status
of their present employment situation (London, 1983), resulting in greater job satisfaction. Or
staffers may find ways to cope with their current environment through the areas of their job that
are less desirable. In conflict, Clark et al. (1996) argue that a negative relationship exists between
job satisfaction and tenure because increased tenure can result in monotony and minor job
satisfaction. More current research (Riza, Ganzach, & Liu, 2018) corroborated Clark et al.’s
(1996) theory and shows a need for further research because their study of 21,670 participants
from 40 years of statistical data demonstrated that age and tenure have contrasting relationships
with job satisfaction, such that job satisfaction increased as people matured but decreased as
tenure progressed, only to receive an increase when people transitioned to a new employer.
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Education Level
Education is another factor that influences either positive or negative employee job
satisfaction (Ganzach, 2003). The level of education may have a positive unintended effect on
job satisfaction because highly educated people are able to obtain more gratifying jobs and
experience better job satisfaction. Education level could have a negative impact job satisfaction,
because the demands of attempting to achieve advanced degrees may negatively contribute to an
employee’s job satisfaction (Arvey, Carter, & Buerkley, 1991; Bowles & Gintis, 1976).
Ganzach (1998) argued that an increase in educational level can only lead to enhanced
job satisfaction, because of its positive influence on work related characteristics, and shouldn’t
lead to a reduction in job satisfaction. More specifically, a correlation exists between teacher
education level and job satisfaction as salary may be influenced by the type of degree a person
holds. Usually, a teacher’s salary will rise when a higher level degree is achieved (e.g., Master’s
Degree, Educational Specialist Degree, Doctoral Degree) (GADOE, 2019).
Overall, educational advancement is generally an investment of human capital (Trusty &
Niles, 2004). Trusty and Niles (2004) recommend that advanced degrees may reinforce the
relationship between organizational tenure, job performance, and job satisfaction. Formal
education can possibly provide complex skills and self-actualized opportunities to enhance job
performance or satisfaction even more. Experience and advanced degrees are beneficial to
developing human capital and acquiring knowledge needed to sharpen work related skills
through authentic experiences (Schmidt, Hunter, & Outerbridge, 1986). Furthermore, education
level helps to determine the kinds of jobs that individuals are able to obtain and thus, strongly
affects whether employees will land in professional or high-skilled jobs that may influence their
level of job satisfaction.
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Pay
Pay is important to the company and the worker, contributing monetary satisfaction to
both parties (Singh & Loncar, 2010). Tactically, pay is used to inspire employees for productive
workplace behaviors and to minimize teacher turnover (Milkovich & Newman, 2008). Singh and
Loncar (2010) performed a study of 200 nurses from a unionized hospital to advance their
understanding of the connection between job satisfaction, pay satisfaction, and employee
turnover.
Their findings discovered that each element of pay: pay level (r = -.32, p <.01), pay
structure (r = -.33, p < .01), pay raise (r = -.30, p < .01), and benefits (r = -.17, p<.01) were all
significantly interconnected with a teacher’s intent to quit (Singh & Loncar, 2010). Furthermore,
job satisfaction (r = -.42, p < .05) was negatively associated with teacher’s intentions to quit
(Singh & Loncar, 2010). More specifically, the outcomes revealed that when job satisfaction was
included, only two out of four pay dimensions were perceived as significant, pay level and pay
raise. Salary is one form is pay used in many companies today. This research demonstrates how
pay can play a major role in someone’s intent to stay or leave a company, and pay has been
recognized as a determinant of job satisfaction.
Salary. Salary is a method of intervallic compensation from a company to its employee,
and the amount of earnings is outlined in an employment contract (Chaudhry, Sabir, Rafi, &
Kaylar, 2011). A person’s salary is balanced with sectional remunerations, where each job, job
period, or other segment is compensated markedly, rather than on a sporadic base. Salary is
presumed to be a noteworthy return to employees for the purpose of motivating their behavior to
continue to pursue the goals of the employer (Oshagbemi, 2000).
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Another study in Bethesda, Maryland using National Cancer Institute alumni (n=114) and
the Kirschstein National Research Service Award respondents (n=140) assessed the correlation
between job satisfaction and salary competitiveness, and job satisfaction and race (Faupel-
Badger, Nelson, & Izmirlian, 2017). Their research discovered that overall 61% of participants
reported having higher levels of job satisfaction in relation to their company salary. Moreover,
higher salary and job satisfaction exhibited an odds ratio of 2.86 at a 95% confidence interval
between 1.07 and 7.69; however, races other than White and job satisfaction revealed an odds
ratio of .40 at a 95% confidence interval between .20 and .82. This empirical evidence shows that
higher salaries might produce higher levels of job satisfaction, and minority races may
experience less job satisfaction than their White counterparts albeit in the same profession
(Faupel-Badger et al., 2017).
300 garment factory workers in Dhaka City, Bangladesh were utilized to assess the
correlation between job satisfaction and salary (Muhammad & Akhter, 2010). Their research
identified the correlation co-efficient between the scores of salary and job satisfaction was 0.829
and the significance level was at 0.001. Muhammad and Akhter (2010) contend that employee
salary is positively associated with job satisfaction. Similarly, in the 2015-2016 school year,
online surveys of P-12 teachers found that 55% of teachers were not satisfied with their salaries
and 45% of teachers were satisfied with their salaries (Spiegelman, 2018), although, no actual
salary demographics were provided in their findings. Nevertheless, experiential research does
exist in the field of education to assess the level of influence of actual teacher salary on job
satisfaction.
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Principal Leadership in General
A number of investigators have explored the relationship between principals’ leadership
style and teacher job satisfaction and performance (Kirby, Paradise, & King, 1992; Koh, Steers,
& Terborg, 1995; Silins, 1992). The principal leadership styles of transformational and
transactional have stood out through research to reasonably influence teacher job satisfaction. An
investigation by Bogler (2001) discovered that principals’ transformational leadership affects
teachers’ satisfaction positively (β=.31, p<.0001). This information identifies that teacher job
satisfaction increases as they acknowledge their principals’ leadership style to be more
transformational and less transactional.
Nazim and Mahmood (2018) define leadership style by the common way a leader acts
toward his or her employees for accomplishing objectives. Burns (2003) described effective
leadership through the ability to create social change and the leadership style of transformational
links to the definition of a person who supports his followers, and activates their services to meet
the needs of the organization. Transformational leadership comprises of four mechanisms
including, ideal influence, rousing motivation, scholarly stimulation, and individualized
deliberation (Northouse, 2007).
Transformational leaders can create a positive operational climate, reach objectives more
easily, and grow the altitudes of job satisfaction and organizational assurance of stakeholders as
a product of motivating people and executing responsiveness (Rowold & Scholtz, 2009).
Nonetheless, a transactional leader sets the marks and makes a clear the relationship between
performance and prizes for employee work habits (Aydin, Sarier, & Sengul, 2013). Thus,
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transactional leaders ensure employees know what is expected in order to receive
acknowledgement for reaching or surpassing organizational goals.
Transactional leaders recognize responsibilities of the employees, establish the
organizational plan, and emphasize the plan and work schedule (Aydin et al., 2013). A
component of transactional leadership is contingent reward and this component demands that the
prime focus of transactional leader is to achieve organizational objectives (Bass & Riggio, 2006).
Bogler (2001) also discovered in his research that a principals’ transactional leadership affects
teachers’ job satisfaction negatively (β=.-13, p<.001), and this correlation demonstrates the
influence transactional leadership could have on teacher satisfaction. Transactional leaders may
be active or passive in the role of administration
If the administration is active, leaders will correct the errors of subordinates by
monitoring their performance; and if the administration is passive, leaders will allow
subordinates to make errors so they are severely apparent (Aydin et al., 2013). The findings from
a recent study indicate there is a significant association between leadership styles
(transformational and transactional) and job satisfaction (Nazim & Mahmood, 2018). As a result,
transactional and transformational leadership styles support the idea that many teachers are
expected to enjoy being recognized in various ways while reaching their self-actualization. More
specifically, the results of a recent study of 2,150 teachers in Punjab (State in Northern India)
revealed that transformational leadership has a positively directed connection with job
satisfaction rather than transactional; so, Nazim and Mahmood (2018) suggest for
transformational leadership to be considered as the preferred leadership style of principals.
Teachers seem to be more fulfilled when they have greater control over classrooms and
when they obtain support and leadership from the principal (Tillman & Tillman, 2008; Hulpia et
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al., 2009). In the end, school administration has reasonable to great effects on school climate, and
school administration has effects on student achievement when a using transformational
leadership style (Bruggencate, Luyten, Scheerens, & Sleegers, 2012; Thoonen, Sleegers, Oort,
Peetsma, & Geijsel, 2011) and instructional leadership style (Hallinger, Bickman, & Davis,
1996). Principal leadership is postulated as a multi-dimensional concept that is affixed by two
leadership traits, specifically, transformational and instructional (Dutta & Sahney, 2016).
An instructional leadership inventory and transformational leadership inventory was used
as assess the level of effectiveness of principals using a 12-item Likert scale survey for each
assessment, respectively. Regardless of the need of principals focusing on improving teaching
and learning, outcomes show that instructional leadership has poor indirect (0.083) and direct
effects (0.068, p<0.01) on teacher job satisfaction (Dutta & Sahney, 2016). Transformational
leadership shows low indirect effects (0.027, p<0.01) on job satisfaction and this association
explains how the effects of principal leadership styles on student achievement are facilitated by
educator job satisfaction (Dutta & Sahney, 2016). With its hierarchal order on school
improvement and academic knowledge, instructional leadership has been the major pattern
attributed to principal behavior since the 1980s (Dutta & Sahney, 2016).
Instructional principals are projected as facilitators who oversee all academic areas, and
orchestrate others to achieve prearranged academic goals. The transformational style originated
in lessons of business and political leadership that became present following the American
school reorganization of the 1990s (Hallinger, 2003). Opposite of the instructional leadership
behavior, a transformational leader is visualized as a change representative with a focus on
subordinate to administrative participation.
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In the face of this abstract contradiction, instructional and transformational behaviors
share many common features, namely, academic mission, vision development, goal making, and
promoting consistent professional learning for staff. These two behaviors have mutual
correlations as purposeful school leaders may occupy both instructional and transformational
practices (Valentine & Prater, 2011). Principals might use all of the mentioned leadership styles
in different capacities when leading their schools and leadership styles may be assumed to
influence the job satisfaction of their staff members in different ways.
Alternatively, research has been used to determine the correlation between servant
leadership and job satisfaction as well. Effective schools are characterized by the servant
leadership characteristics of their principals because these actions result in greater heights of
teachers’ job satisfaction (Cerit, 2009; Zigarelli, 1996), and so, Herbst (2003) contends, have a
positive impact on student success. Greenleaf (2002) explains that a “servant leader” is focused
on serving first rather than leading first, therefore, meeting the needs of their followers is more
important than self-actualization. His research explains that school administrators with servant
leadership tactics achieve their objectives from the inside out, by creating a shared visualization
and enabling their groups to accomplish the vision by using their talent and budding potential.
Barbuto and Wheeler (2006) used employee job satisfaction as a variable to indicate the
possible legitimacy of each of the five sub-components of servant leadership. Their results
indicated that the self-reported servant leadership components associated positively with job
satisfaction of employees. A study of 356 Oman (Arab county in South Eastern Arabian
Peninsula) teacher perceptions toward servant leadership and job satisfaction denoted from a
servant leadership scale that the dimensions ranged from 2.78 to 4.20 on a 5-point scale, and the
standard deviation showed a moderate correlation from 0.75 to 1.07 between the two constructs
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(Al-Mahdy, Al-Harthi, & Salah El-Din, 2016). As an outcome, teachers appeared to be
moderately satisfied with the type of leadership style they encountered from their principals.
Further experimental evidence was provided in the marine industry exploring the
effectiveness of a captain’s servant leadership in an effort to build employee job satisfaction and
trust. The results of 239 employee questionnaires indicated that 52% of the respondents believed
servant leadership influenced their level of job satisfaction and trust with their organization (Kim
& Kim, 2017). To add, servant leadership within the hotel industry has a connection with job
satisfaction showing the importance of servant leadership toward improving employee
commitment (Park & Lee, 2014).
As lower levels of job satisfaction may lead to teacher attrition, Boyd et al. (2011) found
in a study of 4,360 New York teachers that a teacher’s perception of the principal had an
influence on his or her chances of returning to the school, transferring within system, and/or
leaving the profession altogether. An increase in a teacher’s perception of the principal decreases
his or her chances of transferring by nearly 44% in comparison to returning to the same school
and decreases his or her chances of leaving teaching by almost 28% in comparison to returning
to the same school (Boyd et al., 2011). With the mentioned information provided in this section,
principal leadership should not be ignored in future research studies as a factor that influences
teacher job satisfaction.
Understanding the Job Dissatisfaction
Job dissatisfaction is defined as an unpleasant emotion where most people are
conditioned to respond by finding a solution to minimize the level of dissatisfaction (Afshar &
Doosti, 2016; Okeke & Dlamini, 2013). Consistent with teacher turnover research from Farrell
(2000), dissatisfied teachers may first quit the displeasing job altogether; secondly, they may
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implement strategies to attempt to make the frustrating situation better; and thirdly, the
dissatisfied teacher may take a passive approach by accepting the unhappy environment and not
offering any possible solutions. Whether an employee leaves a position intentionally or
unintentionally, Mahmoud and Reisel (2015), and Saeed, Waseem, Sikander, and Rizwan (2014)
believe employers should keep employees emotionally attached because those who feel
disconnected have a propensity to leave (Mahmoud & Reisel, 2015; Saeed, Waseem, Sikander,
& Rizwan, 2014).
Job Dissatisfaction surrounding teacher emotions over student behavior may influence
their capacity to teach when disrupted (Allensworth, Ponisciak, & Mazzeo, 2009; Ladd, 2011;
Marinell & Coca, 2013). A study revealed that approximately 30% to 50% of teachers leave the
profession within their first five years, and 30% of those educators allude to disruptive student
behavior as a contributor to them leaving (Smart & Igo, 2010). Smart and Igo (2010) suggest that
astronomical percentages of teacher turnover for new educators mixed with job dissatisfaction
will create difficulty with obtaining excellent teacher retention. For the aforementioned reasons,
turnover has been researched as an outcome of job dissatisfaction; but, the reasons or intentions
that lead the employee to turnover should be studied (Paulsen, 2014).
Understanding the connection between Job Dissatisfaction and Job Satisfaction
Job dissatisfaction and job satisfaction may be determined by various elements as cited in
Herzberg, Mausner, and Snyderman (1959). Still, while satisfaction elements may generally stay
the same, an increase in dissatisfaction could enhance the chance of a teacher resigning (Dinham,
1995). Job Dissatisfaction is most frequently related to job stress as stated in Leung and Lee
(2006), and their research suggested that minimal support from supervisors or colleagues predict
the likelihood of someone quitting. More research is encouraged to be tested with various models
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of job satisfaction and job dissatisfaction as Dinham and Scott (1998), Herzbeg et al. (1959), and
Sergiovanni (1967) have argued how the facets of satisfaction may not be at opposite ends of the
same spectrum.
Review of Student Discipline
The upcoming section provides an historical review of student discipline practices in
public education. A clear understanding of student behavior will be defined and the direct
influence it has on student suspension. Disproportionality plays a significant role in who is being
suspended and implications for why the disparity exists are discussed. Lastly, student suspension
has a detrimental influence on the outcomes of students and this will be discussed.
History of Student Discipline Practices in Public Education
Unbecoming student behavior in schools is not a new phenomenon in public education
because educators have recounted student behavioral problems in schools since the initial years
of the public-school system (Morris & Howard, 2003). School administrators addressed these
problematic student issues with consequences such as, verbal warnings, corporal punishment,
teacher or administrative detention, in-school suspension, and out-of-school suspension (Skiba &
Peterson, 2000; Townsend, 2000). For example, in the 1960s, school administrators began to use
out-of-school suspension as a technique for reducing student misconduct and have continued to
use this technique to redirect inappropriate behavior since its evolution (Adams, 2000).
Research began to show suspending students from school actually stimulated more
adverse behavior and did not redirect negative student behavior (Hochman & Worner, 1987;
Sauter, 2001). Despite research revealing that suspension didn’t change negative behavior,
educational leaders continue to utilize this tactic and as a result, removing students from the
learning. In fact, out of school suspension creates an environment where suspended students are
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destined to be removed from school again due to unwanted behavior being exhibited multiple
times (Costenbader & Markson, 1998).
Even when short and long-term suspension procedures are followed, Elias (1998), and
Morrison and Skiba (2001) acknowledge that suspension does not address the causes of
misbehavior, and they believe suspension is a reactionary method for addressing negative student
behavior. School districts must distinguish severe versus non-severe infractions to uphold the
safety and security of every child and staff member (Stone & Stone, 2011). Numerous student
behaviors that teachers find challenging are at the minor level as reported by Sullivan et al.
(2014), and finding research-based strategies for addressing minor and major behaviors are
critical toward the success of classroom management. In the 21st century, the No Child Left
Behind Act developed under President George W. Bush’s administration, and school districts
were empowered to develop zero tolerance policies to remove consistently disruptive students
from classrooms (National Association of School Psychologists, 2007).
In the 2011–2012 school year, 3.5 million U.S. students were given the consequence of
ISS and 3.45 million were give the consequence of OSS (U.S. Department of Education Office of
Civil Rights, 2014). Yet, previous research purported that zero-tolerance policies are not
effective in lowering severe student behavior and, instead, can increase the chance of further
suspensions resulting in students dropping out of high school (Verdugo, 2002). Regardless of the
purpose for zero-tolerance policies to keep schools safe, the number of disciplinary infractions
reported by schools for physical violence, non-compliance, disorderly conduct and weapon
possession have not changed to a substantial degree since its inception (National Center for
Educational Statistics, 2009).
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Another major issue with suspending students from school is that out of school
suspension leads to low academic achievement for most behaviorally challenged students
(Allman & State, 2011). After returning to school students attempt to get caught up; however,
catching up can become an insurmountable task for students who may already have difficulties
with learning. Failure to catch up on coursework may mount frustration and might lead to more
undesired behaviors in the classroom. Frustration from school behavioral issues and low
academic success could potentially cause for students to get discouraged with school, and
ultimately, dropout in their teenage years (Connecticut State Board of Education, 2007).
ISS began in the late 1960s and early 1970s when many school systems began to use in-
school suspension (ISS) to give students a consequence without removing them from the entire
school atmosphere (Amuso, 2007; Morris & Howard, 2003). The dynamics of ISS typically
consist of isolation from the traditional classroom setting, leading to minimal or no time with
academic teachers (Amuso, 2007; Morris & Howard, 2003), placement in a classroom with a
paraprofessional or certified teacher, isolated lunch time, and individual work provided by
worksheets or computer-based assignments (Allman & Slate, 2011). Currently, ISS remains the
most often used form of discipline in majority of public schools.
For major ODRs, OSS is regularly used to remove students from schools for extended
periods. Major ODRs are characterized by zero-tolerance policies including drug activity,
fighting, gang association, and possession of weaponry (Allman & Slate, 2011). Subsequently,
school districts began to use zero-tolerance policies across the United States for less violent
behaviors, such as tobacco use/possession, school disturbance, and other less severe violations of
the student code of conduct (Skiba & Peterson, 1999).
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Continued ODRs from teachers to school administration for major infractions could lead
to a student being sent to a disciplinary hearing, and eventually, an alternative school setting.
Discipline alternative education programs are still used for common disciplinary protocols in
schools (Texas Education Agency, 2009). Though, alternative education programs generally
offer different services than the opportunities students might receive in a traditional setting.
These may include: mandatory counseling, social work involvement, and unique schedules that
could benefit students who display behavioral problems in the regular school environment
(Kemerer & Walsh, 2000). Also, advantages and disadvantages exist in the use of various
student discipline practices, and because there are no conclusive findings on their impact,
schools continue to use many of the practices mentioned in this summary today.
Understanding Student Behavior
Although, no universal definition for student behavior exist, student behavior is
conceptualized as a vast component of a classroom environment that can negatively impact the
teaching and learning process or orderly operation of the classroom through inappropriate
student actions (Finn, Fish, & Scott; Thompson, 2009; Ylimaki, Jacobson, & Drysdale, 2007).
Negative student behavior influences student achievement, school climate, school safety, school
suspension, school dropout rates and ultimately, the classroom teacher. ODRs are standardized
records of problem behaviors occurring in schools as an indicator of negative student behavior
(McIntosh, Frank, & Spaulding, 2010). Blank and Shavit (2016) have identified factors
connecting negative student behavior and student achievement, such as student background,
student gender, and peer distractions.
Blank and Shavit (2016) argue that a student’s home environment influences their
behavior and achievement. Typically, children from more affluent backgrounds or households
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behave better and experience high achievement levels, as opposed to students from
underprivileged families or communities who tend to rebel against school authority and have
lower-ranking achievement (Gregory et al., 2010; Hattie, 2009; Organization for Economic Co-
operation & Development, 2010). School districts with greater percentages of black students
generally are located in communities with higher poverty indexes and subsequently receive less
funding per pupil than most districts with fewer minority youth (Kozol, 2005).
Further, empirical research studied how the association between behavioral disruptions
and student achievement relates to the negative student behavior of peers. Student behavior
identified as disruptive or rebellious within a classroom can influence negative behavioral
patterns that obstruct learning from multiple peers (Osher, Bear, Sprague, & Doyle, 2010;
Thomas, Bierman, & the Conduct Problems Prevention Research Group, 2006). Additionally,
Neidell and Waldfogel (2010) claimed only a few unruly students can impact the learning of an
entire classroom.
When domestic violence is a contributor to a youth male’s home environment, Carrell
and Hoekstra (2010) presented evidence on how one male student can cause for student behavior
in a classroom to negatively influence student test scores of an entire classroom by two points.
More research is needed to assess the impact of student behavior on the daily grades of students.
Student gender also connects with student behavior. Gender helps to explain the
connection between student disciplinary climate and academic achievement (Buchmann,
DiPrete, & McDaniel, 2008; DiPrete & Buchmann, 2013; Frenzel, Pekrun, & Goetz, 2007).
Morris (2008) and DiPrete and Buchmann (2013) proposed that females are prone to comply
with authority unlike their male counterparts who typically exhibit behaviors that lead to
discipline infractions and less student success. Lavy and Schlosser (2011) indicated from
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research that when the proportion of girls in classroom increases to 10%, then test scores will
increase by 4% to 5% because of less male distractions within the learning environment. These
distracting behaviors can truly influence a teacher’s ability to effectively and comfortably
provide instruction in their work environment.
Even though violent or negative behaviors toward teachers have not been studied
extensively, they have become regular incidents in schools (Espelage, Anderman, Brown, Lane,
& McMahon, 2013). Teachers all over the world have been subject to verbal and physical
harassment, bullying, terrorizations, and attacks from students while in the workplace (Chen &
Astor, 2008; Dzuka & Dalbert, 2007; Espelage et al., 2013; Khoury-Kassabri, Astor, &
Benbenishty, 2009; Mcmahon, Martinez, Espelage, Rose, Reddy, Lane, & Brown, 2014; Robers,
Zhang, Morgan, & Musu-Gillette, 2015; Wilson, Douglas, & Lyon, 2011). A task force
assembled to investigate the violent actions that have been directed toward teachers, and the
investigation expressed the importance of protecting teachers from negative attacks impacting
their mental and physical health (Espelage et al., 2013). When teachers observe violent or
negative student behaviors in schools that are not addressed by administration satisfactorily,
whether directed toward them or not, teacher stress levels may increase, and the satisfaction for
their jobs could possibly decline (Fox & Stallworth, 2010).
One study reflected that out of 731 teachers, 144 were victims of physical aggression
without a weapon being used, while 15 were actually attacked with a weapon (Wilson et al.,
2011). Another study of violence toward U.S. educators also recognized threats (49%) as a more
protuberant concern than physical attacks (25%) (McMahon et al., 2014). With so many verbal
attacks from students, these types of external experiences may have a tendency to affect the
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satisfaction, or dissatisfaction a teacher has due to the stressful interactions or episodes that take
place in the work environment.
Teacher unfair treatment may have unwanted effects on teacher retention, teacher
optimism, satisfaction, and commitment (Allensworth, Ponisciak, & Mazzeo, 2009; Dzuka &
Dalbert, 2007; Evans, 2001; Galand, Lecocq, & Philippot, 2007; Ingersoll, 2001; Marinell &
Coca, 2013). Smith and Smith (2006) found that educators employed in inner city or
metropolitan locations remembered specific incidents of violence, especially those involving
them, when asked to reflect on their time as a teacher and why they chose to leave the profession.
Violence focused toward teachers has been identified as a problem in the United States
(Gerberich, Nachreiner, Ryan, Church, McGovern, Geisser, & Pinder, 2014; Kondrasuk, Greene,
Waggoner, Edwards, & Nayak-Rhodes, 2005; Robers et al., 2015), so severe that the American
Psychological Association dedicated resources to figure out how to avert verbal/physical
aggression or attacks on U.S. teachers (Espelage et al., 2013; Mcmahon et al., 2014).
Student Behavior Leads to Student Suspension
Despite the findings mentioned, multiple student behaviors that teachers find challenging
are at the minor level and discovering research-based strategies for addressing minor or major
behaviors are critical toward the success of classroom management (Sullivan, Johnson, Owens,
& Conway, 2014). Examples of minor negative behaviors are disrespect, excessive talking, not
sitting down, offending others, and verbal aggression (Reinke, Herman, & Stormont, 2013;
Sullivan et al., 2014; Xenos, 2012). Despite the needed alternative strategies for minor or major
student behavioral infractions, research by Adams (1992), Elias (1998), Morris and Howard
(2003), and Morrison and Skiba (2001) concluded that suspension is used habitually, nationally
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and internationally to remove disruptive students from the classroom or the entire school
building.
The Disproportionality of Discipline toward Minority Students
Black male students are suspended for negative behavior more than their White
counterparts. Skiba et al. (2011) specify that Black youths in the United States are 3.78 times
more probable than White students to be sent to the principal and receive a severe consequence.
Related literature indicated that out of school suspension is negatively correlated with academic
results for students, and this correlation increases the likelihood of students dropping out of high
school (Brooks, Schiraldi, & Ziedenberg, 2000; Civil Rights Project, 2000; Skiba, Peterson &
Williams, 1997; Suh, Suh, & Houston, 2007). The discipline disparity between Black and White
students has increased and even doubled over the past almost twenty years (Steinberg & Lacoe,
2017). Excessive school suspension also increases the odds of minority students entering the
juvenile justice system as described by Nicholson-Crotty, Birchmeier, and Valentine (2009).
Christle, Jolivette, and Nelson (2007) conducted a study on 161 middle schools and
found that educational institutions with a higher population of students living with low
socioeconomic demographics and schools with more substantial amounts of minority students
are connected to greater proportions of suspension. From a school funding perspective, Balfanz
and Legters (2004), Kozol (2005), and Orfield, Losen, Wald, and Swanson (2004) described how
schools with a high minority populations will generally have less monetary resources as opposed
to their White counterparts. In summary, Rabrenovic and Levin (2003) provide a statistic in
representation of the relationship between race and school suspensions highlighting where
Hispanic and Black students make up less than 20% percent of the U.S. public school population,
but makeup 56.7% of school suspensions.
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Unfortunately, stereotyping occurs in schools when Black students are perceived to be
classroom disruptors based on their race, gender, or social classification. Violent, offensive and
gang-oriented stereotypes of Blacks are considerably perpetuated by biased social media
portrayals (Irvine, 1990). Wooldridge and Richman (1985) discovered that 216 southern teachers
were less inclined to write discipline referrals on Black male students because of the belief that
they only stole and fought anyway so writing a discipline referral would not matter. Eyler, Cook,
and Ward (1982) claimed that Blacks are suspended more for subjective reasons, such as
disobedience, dress code, and disrespectful behavior; unlike White students who were suspended
more for drug related offenses, possession of alcohol, and truancy.
Irvine’s (1990) research is not to suggest that all White teachers are ineffective with
Black students, or that all Black teachers are always effective with Black students. However,
Irvine (1990) does suggest that a group of White teachers are more likely than Black teachers to
hold a negative perception or set of expectations for a Black student. Irvine (1990) also contends
that White teachers are more likely to have a lack of synchronization with understanding Black
students rather than a group of Black teachers. Negative perceptions or expectations of Black
students are still contributing to the disproportionality of Black student suspension in today’s
times and must not be ignored.
Impact of Student Suspension on Students
Consistent school suspension is a contributing factor toward the school dropout rate (Suh
& Suh, 2007). Their research received data from high schools across the United States with the
National Longitudinal Survey of Youths which is a database provided by the U.S. Department of
Labor. Suh and Suh (2007) analyzed the contributing factors to school dropout, and their
research discovered that 6,192 students (12 -16 years old) with a previous history of suspension
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yielded 78% of those students actually dropped out. Christle et al. (2007) studied high school
students in Kentucky and determined that schools with high dropout percentages had high
discipline referral numbers, substantial proportions of high school students from economically
disadvantaged areas, and greater percentages of students who experienced grade retention. In
spite of the high usage of suspension as a discipline practice in schools today, temporary removal
from school does not prevent disruptive behaviors from continuing (Lauer & QualQuest, 2014).
Student discipline consequences leading to suspension can negatively impact students
overall and affect student achievement (U.S. Department of Education, 2014). An investigation
performed by Atkins, McKay, Frazier, Jakobsons, Arvantis, and Cunningham (2002) revealed
how students who are suspended more frequently generally experience lesser academic
achievement as compared to students with fewer suspensions. Granted, the relationship between
student suspensions and academic achievement may not be completely transparent, several
studies have provided results to demonstrate that students suspended more from school perform
worse on high-end stakes assessments, have poorer grade point averages, and have a higher
potential to quit school rather than students with fewer suspensions (Skiba, 2002; Noguera, 2003;
Townsend, 2000). American Academy of Pediatrics (2013) indicated when students continue to
be suspended by schools, they often continue to misbehave, and each consecutive suspension
contributes to a higher chance of becoming a school drop-out or juvenile delinquent. Due to
violent acts at school, the safety of classrooms and school buildings as a whole has been an
important topic in America.
Classroom Management, Teacher Preparation, Teacher Anxiety, and Culture
The following section will discuss how classroom management, teacher preparations
programs, teacher experience, and teacher anxiety are significant components that influence
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student discipline. Further, cultural responsiveness is imperative to the growth of any educator
and should not be overlooked as a vital tool for building positive relationships with students that
minimize classroom conflicts. With school culture in mind, administrators and teachers play an
essential role in developing how a school or classroom will address student behavior.
Additionally, factors contributing to support teachers when preparing for classroom management
are proactive management strategies (Vincent, Sprague, Pavel, Tobin, & Gau, 2015), effective
disciplinary practices (Hoffman, 2014), professional development (McIntosh, Girvan, Horner, &
Smolkowski, 2014), positive behavior reinforcement (Gregory & Weinstein, 2008), helpful
student-teacher relationships (Gregory, Clawson, Davis, & Gerewitz, 2016), and multicultural
competency (Monroe, 2005).
The importance of Classroom Management
With regards to the challenges teachers face when implementing effective disciplinary
practices, Rosenberg and Jackman (2003) described how teachers write ODRs after becoming
frustrated from losing control of the classroom environment due to negative student behavior.
Teachers on a regular basis face negative student behaviors such as apathy, bullying, theft,
avoidance, verbal or physical hostility, and substance exploitation (Walker, Homer, Sugai, Bulis,
Sprague, & Bricker, 1996) that impact classroom instruction. To sustain a beneficial teaching
and learning environment, Johnson (2006) believes that teachers must give attention to
developing positive relationships with their students, communicating effectively with parents,
and be willing to develop connected relationships with colleagues, principals, and other district
leaders.
Wiseman and Hunt (2008) argue that effective teachers are reflective in their practices
and can develop methods to address negative behaviors and motivate students who act
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inappropriately in the classroom setting. Therefore, Pas, Cash, O’Brennan, Debnam, and
Bradshaw (2015) found that when teachers practice less reactive tactics to behavior management,
less condemnation, and more opportunities for students to participate, then students met the
behavioral guidelines regularly. In contrast, classrooms where teachers displayed significant
amounts of disapproval and reactive conduct, students were found uncooperative (Pas et al.,
2015).
According to Wiseman and Hunt (2008), teachers choose to manage their instructional
areas using the following behavioral strategies: 1) normative - managing a classroom through a
traditional set of norms and expectations where each person knows their role; 2) remunerative -
using the power of rewards to get someone to behave in a particular manner; or 3) coercive -
using the power of punishment if someone doesn’t behave in an appropriate manner. On the
other hand, other research indicates how many teachers have not obtained effective training on
behavior management strategies (Eisenman, Edwards, & Cushman, 2015; Hammerness, 2011)
and this lack of knowledge has led to unsuccessful classroom management practices. Jones,
Bailey, and Jacob (2014) suggests for educators to improve behavioral management they must
develop adequate classroom organization, instructional lesson planning, and positive teacher-
student relationships.
Classroom Management and Teacher Preparation Programs
Classroom behavioral management skills must be learned. One reason inadequate
classroom management still exists is that teacher preparatory programs force beginning teachers
to learn on the job under a sink or swim philosophy without providing an adequate classroom
management course that is relevant in support of teacher practices (Kwok, 2016). Hammerness
(2011) examined syllabi for 31 new teachers in New York from 26 collegiate certification
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programs and five alternate route certification programs. Her research found that merely 11 of
the 26 collegiate certification programs and only three out of five alternate route certification
programs actually require a classroom management course for completion of the program. The
lack of course results in many educators entering into new teaching positions with no research-
based knowledge of effective classroom management practices (Hammerness, 2011).
Reupert and Woodcock (2010) surveyed 336 novice teachers to investigate the type of
approaches they used to manage classrooms and how frequently their strategies were employed.
Their findings concluded that new teachers mostly depended on reactive approaches to address
behavior (i.e. close proximity) because they felt more confident employing those methods than
preventative strategies, even though teachers reported preventative strategies were more
effective. Additionally, research shows the connection between teacher experience, classroom
management and teacher anxiety (Önder & Önder-Öz, 2018).
Teacher Preparation Programs, Teacher Experience, and Teacher Anxiety
Önder and Önder-Öz (2018) performed a study over 468 collegiate students (pre-service
teachers) in various collegiate certification programs in Turkey to determine the level of
classroom management anxiety according to teacher experience when compared to professional
competence, motivation, and managing problematic groups of students. Classroom management
anxiety in accordance with teaching experience differs considerably in elements such as
professional competence t(466) = -2.14; p<.05), motivation t(466)=-4.29; p<.01), and
management of problematic groups t(466) = 2.10; p<.05) (Önder & Önder-Öz, 2018). Their
conclusions advise that teachers in certification programs with some form of teaching experience
from any setting typically have lower levels of anxiety and higher levels of professional
competence; although, pre-service teachers with no experience are anticipated to experience
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classroom management challenges. Ultimately, to better prepare teachers with classroom
management strategies before employment, all teacher preparation programs should offer
teachers support with learning what proactive skills will address negative student behavior.
Culturally Responsive Teaching
Research demonstrates that general classroom management strategies are useful, but does
not effectively meet the behavioral needs of each student (Siwatu & Starker, 2010), or close the
discipline gap for Black students in comparison to their White counterparts (Vincent, Swain-
Bradway, Tobin, & May, 2011). Thus, culture plays an important role toward what should be
identified as a negative student behavior versus what is considered to be part of a person’s ethnic
characteristics (Irvine, 1990). Culture has been described as the consistent display of human
behavioral norms encompassing the racial, traditional, spiritual, or social make up of a group
(Day-Vines, Wood, Grothaus, Craigen, Holman, Dotson-Blake, & Douglass, 2007). The
understanding, appreciation, and inclusion of a student’s culture into the classroom environment
are known as culturally responsive teaching (Larson, Pas, Bradshaw, Rosenberg, & Day-Vines,
2018).
Culturally responsive classroom management requires teachers to reflect on the ways that
educational systems preserve discriminatory practices against minority students (Weinstein,
Curran, Tomlinson-Clarke, 2003). Teachers who engage in culturally responsive training
sessions will contribute positively toward their understanding and preparedness for teaching
diverse groups of students. Additionally, the teachers’ use of culturally responsive teaching
practices (e.g., teaching authentic lessons, using positive humor, implementing question and
answer) was also related to positive assessments of observed student behavior (Larson et al.,
2018). While minimal research exists on the impact of cultural responsive teaching and student
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behavior, Larson et al. (2018) and Weinstein et al. (2003) have described a positive association
between the constructs.
School Administration’s Role in Managing Student Behavior
Unfortunately, school administrators usually respond to negative student behavior by
giving harsh consequences for student discipline that minimize the instructional opportunities
available for learning (Osher, Bear, Sprague, & Doyle, 2010). Apart from this approach, De
Nobile, Mariam, and London (2015) claimed when schools extend superior efforts to implement
school wide behavior management systems, participants perceive the amount of negative student
behaviors as reduced. De Nobile, Mariam, and London (2015) identified a significant association
between comprehensive school approaches to classroom management, educator job satisfaction,
and educator stress.
Conversely, a failure of school leadership to effectively implement school wide behavior
management systems to address the negative student behaviors may impart overall to
unsatisfactory student, school, and societal outcomes (Coloney & Goldstein, 2004). To this
point, teacher efficacy and shared decision making centered on a culture that encourages teacher
flexibility and diminishes teacher attrition are important for educational leaders to develop
positive school climates (Jiang, 2005). Rosenburg and Jackman (2003) discussed how the role of
an educational leader is to be a solution starter who generates conversations with teachers,
parents, and other related personnel to design a comprehensive plan for addressing the negative
behaviors of students in a preventive manner.
The Impact of Student Discipline on School Climate and Teachers
School climate plays a significant part in how people feel based on the established expectations
that have been set within a school. This section will define school climate and explore the
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significance of having a positive school climate. Student behavior impacts school climate and
ultimately, student behavior influences how teachers feel.
Understanding School Climate
Habitually negative student behavior has a negative influence on teacher morale that
consequently influences school climate (Phillips, 2018). School climate is determined by the
importance of the relationships among people at school, the learning environment established for
students, and alliance amongst administrators, teachers, and other school personnel concerning
student achievement (Cohen, McCabe, Michelli, & Pickeral, 2009). A positive school climate
encourages a favorable learning atmosphere and is connected to student success (Zullig, Hubner,
& Patton, 2011).
Thapa, Cohen, Guffey, and Higgins-D’Alessandro (2013) proposed that positive school
climate can promote a safe and supportive school environment. So, school climate is associated
with a healthy learning atmosphere promoting high expectations for all students (Collie, Shapka,
& Perry, 2012). Principals are encouraged to enhance a teacher’s understanding of school
climate by empowering teachers to be role players in the decision-making process and by
ultimately, removing any obstacles impacting the teaching and learning process (Way, Reddy, &
Rhodes, 2007). A positive school environment feasibly results in an increase in teacher job
satisfaction (Taylor & Tashakkori, 2010), and will usually contribute to a decrease in student
behavior and workload stress (Collie et al., 2012).
Impact of Student Behavior on School Climate
Colombi and Osher (2015) argued that exclusionary practices actually hurts school
climate because they do not address the inappropriate behaviors of student and nor do they help
to cause healthy relationships between teachers and students. A study of 6,900 educators claimed
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that teachers working in schools with high discipline referrals have unpleasant school climates
attributing to low teacher retention, insufficient teacher morale, and negative teacher perceptions
of safety (Aloe, Amo, & Shanahan, 2014; Kipps-Vaughn, 2013). In contrast, schools with
positive climates are believed to exhibit a decline in discipline issues, violent behaviors, and
suspensions (Cohen & Geier, 2010; Gregory, Cornell, Fan, Sheras, Shih, & Huang, 2010; Lee,
Cornell, Gregory, & Fan, 2011). The summarized literature on school climate explains how
school climate is a function of student behavior (Aloe et al., 2014; Colombi & Osher, 2015; Lee
et al., 2011).
Influence of Negative Student Behavior on Instruction
Stringent teacher evaluations systems, decreased enrollment in teacher preparation
programs (Sutcher, Darling-Hammond, & Carver-Thomas, 2016), and increased educator
attrition rates are considered as detrimental outcomes of an era of accountability (Ingersoll,
Merrill, & Stuckey, 2014). Subsequently, the effect of high-stakes assessments and the
consequence of revised leadership goals may modify teachers daily working conditions and
impact their feelings regarding the profession (Johnstone, Dikkers, & Luedeke, 2009; Marks &
Nance, 2007; Quinn & Ethridge, 2006).
Deleterious classroom conduct restricts instruction and causes teachers to miss important
time due to classroom management issues (Feurborn & Chinn, 2012). When students are
insubordinate, teachers have to delay instructional activities to address classroom management
issues instead of focusing on student learning (Sida-Nicholls, 2012). Studies confirm how the
most general forms of unruly behavior are disorderly conduct, noncompliance, and deliberate
defiance (Bryan, Day-Vines, Griffin, & Moore-Thomas 2012; Mitchell & Bradshaw, 2013).
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Students who exhibit disruptive behavioral actions in the presence of their peers tend to make an
educator’s job of teaching difficult.
Teachers working in challenging instructional environments are likely to experience
stress from negative student behaviors (Black, 2010; Klassen & Anderson, 2009; Spilt, Koomen,
& Thijis, 2011; Vassallo, 2014). Disruptive behavior and disorderly conduct interfere with a
teachers’ ability to instruct students effectively and are viewed as malfunctions of classroom
management (Canter, Paige, Roth, Romero, & Carroll, 2004; Granström, 2006). Also, in a study
of 8th
grade students by Blank and Shavit (2016) assessed that a typical group of students in a
reasonably positive classroom environment would achieve a test score 77.7 in a Hebrew
language class; however, when placed in a disruptive and ill managed classroom, the same group
of students received a lower test grade score of 73.6. Negative student behavior not controlled or
addressed by the teacher truly can influence the instructional setting for students and the work
environment for teachers.
Managing challenging behaviors continues to be a struggle for many teachers leading to a
loss of instructional time and greater heights of frustration (Robers, Kemp, Truman, & Snyder,
2013). Micek (2013) and Sullivan, Johnson, Owens, and Conway (2014) have described how
student discipline has been a significant topic within the past decade. To advance their assertion,
Han and Akiba (2011) stated that student discipline is becoming problematic and strategies are
needed to improve behavior across the country because of the impact student discipline has on
classroom management.
In a survey of 10,000 teachers, Bill and Melinda Gates and Scholastic (2012) reported
that 62% of teachers (working at one school for at least 5 years) agreed on student behavioral
issues having particularly worsened. The report asserted that over half of the teachers (68%
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elementary teachers, 64% middle school teachers, and 53% high school teachers) expressed an
abundant amount frustration when managing negative student behaviors (Gates & Scholastic,
2012). Chang (2013) suggests that student misbehavior causes emotional instability for teachers
often relating to inadequate classroom management. Negative student behavior and ineffective
classroom management may influence teacher burnout over time (Tsouloupas, Carson, Mathews,
Grawatch, & Barber, 2010).
Reglin, Akpo-Sanni, and Losike-Sedimo (2012) suggested that many teachers believe
continuous misconduct and disruption from students can impede instructional time. To add, the
inconsistency of managing challenging student behaviors can have repercussions for the entire
learning environment since negative student behavior may receive reinforcement from peers for
engaging in similar troublesome actions (Powers & Bierman, 2013). Based on Powers and
Bierman (2013), negative student behavior could have a physical and emotional impact on
teachers potentially bringing about stress.
Impact of Student Behavior on Job Stress, Teacher Retention and Job Satisfaction
The following section will define stress and explain the different types of stress. Student
behavior is a construct that might influence teacher burnout and teacher retention due to the
various types stress placed on teachers. Job satisfaction may perhaps be influenced by the
emotional stress teachers experience from the altered work environment because of negative
student behavior.
Impact of Student Behavior on Job Stress
Stress is defined as either a physical stress-work overload, lack of rest or dieting, mental
stress-physiological state of mind, and/or situational stress determined by our interaction with the
world (Bannerjee & Mehta, 2016). Theoretically, Collie et al. (2012), Kyriacou (2001), Liu and
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Onwuegbuzie (2012) define teacher stress as an unfortunate emotional experience that results
from any specific feature of a teacher’s labor. Teachers around the world have a multitude of
reasons for why they could become stressed with the profession, and they describe stressors as
outlined curriculum standards, end of the course assessments, low funding or resources,
unwelcoming school climate, meager mentoring programs, and negative student behavior
(Chakraborty & Ferguson, 2010). Data analysis of 2,569 Norwegian teachers from Skaalvik and
Skaalvik (2011) revealed that teacher perception of time anxiety and student behavioral issues
projected emotional fatigue (b = .48 and .21, correspondingly).
Two different types of stress heavily cited in the literature are stress related to workload
stress and stress related to negative student behavior (Borg & Riding, 1991; Boyle, Borg, Falzon
& Baglioni, 1995; Chaplain, 2008). The American Federation of Teachers (2015) completed a
questionnaire of over 30,000 teachers, and results revealed that 73% of the responders expressed
they were stressed with their job. Betoret (2006) and Jepson & Forrest (2006) identified feelings
of stress for undesired performance as low attendance, abandonment, resignation, exhaustion,
misery, and negative job satisfaction. Common stressors for teachers include the following: lack
of proper training, administrative support, minimal instructional resources, insufficient work-life
balance, and an undesirable work environment (Sickmund, 2010).
In summary, studies suggest that greater student academic achievement is encouraged
when teachers believe they have stronger teaching efficacy, better job satisfaction, and lesser
stress (Caprara, Barbaranelli, Steca, & Malone, 2006). In a study of 540 randomly chosen
teachers in the Albanian School System to assess the correlation between teacher stress level and
disruptive student behavior, and administrative relationships and co-worker relationships, Karaj
and Rapti (2013) concluded that the correlation between teacher stress level and disruptive
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student behavior exhibited a significant association. Furthermore, literature from Klassen and
Chiu (2010) has shown how work stress leads to job fatigue or burnout. Teachers may be apt to
become fatigued from addressing disruptive student behavior.
As teacher frustration develops over time, it may have an impact on the level of employee
satisfaction (Landers et al., 2008). Friedman (2013) identified insolent student conduct toward
other students and/or teachers as a predictor of teacher exhaustion. A study of 554 teacher
emotional responses surrounding negative student behavior by Chang (2009) argues that teacher
perceptions of student behavior influences the overall unfavorable emotion that teachers
experience toward the classroom environment.
DeVoe, Kaufman, Miller, Noonan, and Snyder, (2004), McFadden, March, Price, and
Hwang, (1992), Morgan-D’Atrio, Northrup, LaFleur, and Spera, (1996) describe how teachers
across the United States experience several challenging student behaviors, such as, disrespect,
non-compliance, profanity, disorderly conduct, chronic tardiness, verbal aggression, and physical
altercations on a regular basis. In this regard, multiple authors proposed that teacher confidence
level for classroom management is adversely related to emotional fatigue, and positively related
to a sense of accomplishment (Betöret, 2009; Bümen, 2010; Chang, 2009; Durr, 2008).
Student behavioral problems have been identified as one of the major forecasters of
teacher stress (Lambert, McCarthy, Fitchett, Lineback, & Reiser, 2015) and student behavioral
problems also impede on teacher enthusiasm (Kunter, Frenzel, Nagy, Baumert, & Pekrun, 2011).
Frenzel, Goetz, Stephens, and Jacobs (2011) found a positive association between good
classroom discipline and teacher satisfaction, while research from Sutton (2007) revealed a
negative association between ineffective classroom discipline and teacher anger or anxiety. The
psychological and physiological pressure of being a teacher could result in low job satisfaction,
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high absenteeism, and employee turnover due to headaches, excessive stress, sleeping problems,
hypertension, alcoholism, and smoking (Friedman-Krauss, Raver, Morris, & Jones, 2014).
Findings from a study of 64 instructors at Western University indicated how student
discipline has a strong relationship with teacher satisfaction and the connection of negative
student behavior with teacher satisfaction was r = -.50, p < .05 (Ruggeri-Dilello, 2015). When
students do not comply with the general expectations of the classroom, negative student behavior
may show correlations with lessening teacher job satisfaction (Kohut, 2015). A teacher’s job
satisfaction may be affected by their confidence in their ability to competently deal with negative
student behavior (Cooper & Yan, 2014). Once teacher satisfaction is not being met due to
negative student behavior, research shows that workers who feel unrecognized and
misunderstood may consider departing their jobs for something different due to dissatisfaction
(Calitz, Roux, & Strydom, 2014).
Impact of Student Behavior on Teacher Retention or Burnout
Teacher burnout is believed to be a multifaceted concept encompassing individual-
demographic or personality variables, organizational-job characteristics, administrative support,
and transactional interactions between organizational, individual factors, and social factors
(Maslach, Schaufeli, & Leiter, 2001). Burnout is explained as a condition of psychological
enervation, depersonalization, and reduced individual achievement (Maslach, Schaufeli, &
Leiter, 1996). Pines and Aronson (1988) describe psychological enervation as having continuous
lassitude or minimal energy. One of the factors contributing to burnout is negative student
behavior in the classroom. A survey of middle and high school teachers described that 76% of
educators specified they would be better able to teach students if student behavior was not so
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disruptive, and over a third of teachers documented they are considering quitting the educational
profession because of persistent student behavioral challenges (Public Agenda, 2004).
Many teachers who have experienced the inability to change negative student behavior
may leave their current school for a different work environment. Ingersoll and Perda (2009)
define teacher turnover by the movement of teachers from one school or district to another, or
abandonment of contract. In addition, Ingersoll (2003) describes how teacher turnover is higher
in economically disadvantaged populations. Teacher burnout or turnover may result from
negative student behavior causing lessened levels of job satisfaction.
In line with Skaalvik and Skaalvik (2010), teacher burnout is also adversely related to
teacher motivation and overall job satisfaction. A study of 546 teachers from ten senior high
schools by Skaalvik and Skaalvik (2017) described that the largest forecasters of teacher
motivation to quit the career was due to burnout (b = .54) and job satisfaction (b = -.35). Studies
by Lasagna (2009) and Kokkinos (2007) articulated that primarily teachers’ burn out and leave
the profession because of the difficulty they experience managing classrooms. Tsouloupas,
Carson, Mathews, Grawatch, and Barber (2010) expressed that negative student behavior can
create a mental and psychological emotion of defeat on teachers because of the demand imposed
on teachers to perform the job.
Haynes (2014) indicated in his research that America spends from 1 billion dollars to 2.2
billion dollars annually on teacher replacements. Replacing such a significant number of
dissatisfied teachers is an enormous task for school districts. Martinez, Frick, Kim, and Fried
(2010) emphasized that teacher attrition in high Black populated schools is challenging because
50% of teachers leave the profession within the first five years before realizing their probable
impact on student achievement. Negative student behavior in schools with similar types of
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demographics is projected to influence teacher attrition due this behavior being more prevalent in
economically disadvantaged areas (Brunson & Miller, 2009).
Theoretical Framework
The independent variable for my study is student discipline and the dependent variable is
job satisfaction. As described during my literature review, Judge et al. (2001) have postulated
several theories over job satisfaction and the influence it has on employee behaviors. To further
this notion, Judge et al. (2001) identified dispositional, situational, and motivational theories as
determinants of job satisfaction.
The Affective Events Theory (AET), a situational theory, is a more appropriate theory for
framing this research than others because this theory is a mental evaluation based on the positive
or negative events that happen in the workplace that impacts a person’s perception toward the
attainment of individual goals optimistically or pessimistically (Frijda, 1996; Weiss &
Cropanzano, 1996). Weiss and Cropanzano (1996) explained that employee attitudes, sentiments,
and mental behaviors are the best forecasters of job satisfaction. When individuals experience
positive affectivity, they become more inspired to devote time and energy, and overcome hurdles
when chasing their career goals partly because they perceive to have more governance over
attaining their desired goals or objectives. As a consequence, teachers could affectively
experience more success in obtaining their goals if teachers believe they have more influence
over the teaching and learning that is taking place in their classrooms.
Based on Cohen’s research, positive affectivity has a significantly positive correlation
with retention and a mostly negative correlation with teacher attrition (Cohen, 1988). A
comparable study was led by Gloria, Faulk, and Steinhardt (2012) to evaluate the connection
between positive affectivity and a person’s ability to adapt to stress (resilience). The study of 267
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teachers discovered that positive affectivity was positively correlated with resilience (r = .65,
p<.001) and positive affectivity negatively correlated with teacher burnout (r =-.57, p<.001).
This empirical evidence exhibits how the environment teachers work in psychologically
influences their thinking, emotional state, and behaviors.
In contrast, long-term inner and outer affective responses are demonstrated by workers
through work performance, job satisfaction, and organizational efficacy when negative emotional
or psychological bearing events occur at the workplace (Sundstrom, De Meuse, & Futrell, 1990).
Stressful work environments force people to cope with the demands of the job and these various
encounters will influence the affective reactions of a person as a primary consequence (Seckin-
Celik, 2015). Zhang and Sapp (2008) believe teachers are extremely affected by the stressfulness
of their workplace. Longitudinal data indicates that roughly 95 % of all teachers experience
growing levels of apparent work stress over time (Chan, Chen, & Chong, 2010), and this stress
may be caused due to student discipline, workload, conflicts with colleagues, and/or curriculum
(Montgomery & Rupp 2005).
Since teachers encounter a multitude of various student behavioral problems on a regular
basis in the classroom environment (i.e. disrespect, verbal abuse, physical aggressive, profanity,
extreme tardiness, and disorderly conduct) (DeVoe et al., 2004), it is probable this behavior will
impede their ability to teach and will eventually affect their attitude or emotion toward the job.
Workplace conditions are generally identified as a significant feature of job satisfaction where
examining specific aspects of this construct may help to bring understanding to influences of
greater teacher dissatisfaction (Kapa & Gimbert, 2018). Student non-compliance and negative
student behavior are influential workplace conditions that generates job dissatisfaction for
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educators (Klassen & Anderson, 2009; Landers, Alter, & Servilio, 2008; Skaalvik & Skaalvik,
2011; Stauffer & Mason, 2013).
Klassen and Anderson (2009) researched sources of educator job dissatisfaction from
1962 to 2007 and claimed that student misconduct and negative attitudes have ascended almost
to the top of the list regarding the profession, after originally being near the bottom in 1962.
Unsurprisingly, teachers are not comfortable when expected to perform in working conditions
that simply feel unsafe (Kapa & Gimbert, 2018). For that reason, teachers may become frustrated
and upset within the work environment due to the influence of negative student behavior on their
mood or emotion. When the situational environment of a teacher is impacted by challenging
students, the environment may ultimately have an impact on their decision to stay or leave the
profession.
Hagenauer, Hascher, and Volet (2015) studied 86 female teachers and 45 male teachers
from the secondary level to assess the correlation between student discipline, teacher joy, and
teacher anger. In result, teacher anger was best predicted by a lack of appropriate student
behavior in the classroom environment. A lack of student behavior within the classroom emerged
to have a substantially negative correlation with teacher joy, and negative student behavior
resulted in a significantly positive prediction for teacher anxiety (Hagenauer et al., 2015).
Chang and Davis (2011) argued negative student behavior in a classroom environment
significantly correlates with detrimental emotions (e.g. stress, anxiety, anger) posing a risk to the
effectiveness of instructional time. Research by Liljestrom, Roulston, and Démarrais (2007) and
Sutton (2007) has demonstrated that teacher anger is dominantly impacted by student behavior
whether positively or negatively. Undesirable classroom environments may cause teachers to
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isolate themselves from students in a manner contributing to decreased teacher satisfaction,
worsened teacher-student relationships, and increased teacher burnout (Hagenauer et al., 2015).
Schwarzer and Hallum (2008) define teacher burnout as an emotional exhaustion or stress
component that occurs when teachers feel overworked or overly stressed from the physical
dynamics of teaching in a classroom. And so, it is rational to theorize through AET that the
physical classroom environment influenced by student behavior, positively or negatively, can
cause for teachers to experience an emotional reaction to the elements of the setting.
Subsequently, if negative student behavior within the classroom causes for teachers to feel
stressed or burnt out, then negative student behavior may correlate with teacher job satisfaction.
Henceforth, it is reasonable to assume the type of student discipline exhibited in a classroom
environment will impact the number of office discipline referrals that a teacher submits to the
administrative office, potentially influencing their job satisfaction, either positively or
negatively.
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Chapter Three
Methodology
The purpose of this chapter is to provide guidance of the population, representation, and
data gathering methods used in this research study. Variables and psychometric properties will
be shared in this chapter. Additionally, the research question, data analysis, null hypothesis and
statistical method will be discussed during this methodology.
Population
For an accurate assessment of teacher satisfaction, a population from two suburban
school districts in state of Georgia was used. Georgia is the representative focal state for this
study because, in terms of teacher attrition, 47% of teachers in Georgia leave the teaching
profession within their first five years of teaching (Owens & GADOE, 2015). A sample
population was gathered from these two suburban school districts in Georgia. More specifically,
middle and high school teachers who returned from the 2019-2020 school year in these school
districts were selected to participate in this study. The teaching population consists of 53%
White, 43% Black, 1.4% Hispanic, 1% Asian, and less than 1% Multiracial.
The sample population has 13 participating secondary schools from two different school
districts in Georgia. Although the researcher serves as a school administrator in Georgia, the
researcher’s school was not selected to be one of the participating schools for this study. The
student demographics from the two participating school districts consist of 58.05% Black, 24.5%
White, 5.5% Asian, 2.4% Multiracial, and 1.5% American Indian. Historically, marginalized
populations of these district’s student subgroups are composed of 74% economically
disadvantaged, 5.75% English Language Learners, and 12.3% of students have disabilities.
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Although the population of Black students served in the sample is 58.05%, Black
students account for 71.95% of students suspended with ODRs (Governor’s Office of Student
Achievement, 2019). Consistent with research provided in the literature review, a higher
percentage of Black student suspensions over other races in the sample support the selection of
these school systems for the purpose of this study (Governor’s Office of Student Achievement,
2019). In relation to job satisfaction, both of these school districts were selected for this study as
they have expressed interest in gathering research related to the job satisfaction of their teachers
and/or have made efforts to complete initiatives to gather data on the sentiments of certified
employees.
For the teaching body, 768 middle and high school teachers returned to the sample
population after the 2019-2020 school year and were used as participants for this study. Thus, the
total number of participants in the population of this study is 768 (n =768). Middle and high
school teachers who returned from the 2019-2020 school were used because these participants
can share the average number of discipline referrals submitted to the administrative office during
the 2019-2020 school year. Empirical data gathered from these districts assessed the relationship
between student discipline (independent variable) and teacher job satisfaction (dependent
variable).
In the design to control for principal leadership, schools within the districts were coded
“0 through 12”. The principal with the most survey responses was used as the reference group of
“0” for this covariate. Employees of these school districts were invited to participate in this study
because they have district leaders who have exhibited a concern for job satisfaction.
Additionally, these districts both serve majority economically disadvantaged students. Thus,
research explains how schools with greater rates of students from impoverished backgrounds and
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schools with larger percentages of minority students were connected with higher numbers of
student suspension (Christle, Nelson, & Jolivette, 2004).
Power Analysis. To determine the number of participants needed to reduce the
likelihood of type one and type two error, an a-priori power analysis was conducted. The
influence of student discipline toward job satisfaction was assessed for a medium effect size of
(f² = .15), a distinct level of significance set at ( = .05), and a power level (= .80). For this
specific study, the effect size of one independent variable (student discipline), one dependent
variable (job satisfaction), and 10 job satisfaction covariates were assessed. Cohen’s f² serves as
the effect size measure for variance and explained variance (Cohen, 1988). An Ordinary Least
Squares Model of Multiple Regression was used to analyze the relationship between student
discipline and teacher job satisfaction. Using the parameters suggested by Cohen (1988), the
recommended minimum number of participants is 97. From this figure, utilizing the full
population of middle school and high school teachers (n=768) will generate enough statistical
power to detect statistical significance of the regression variables.
Response Rates. Research indicated there were approximately 68 dissertations in the
education field that utilized online surveys as of 2010 (Trespalacious & Perkins, 2016).
However, this study used online surveys because the use of online or electronic based surveys
has increased to 140 since that time (Trespalacious & Perkins, 2016). Past research supports the
use of online surveys through email format when specific groups of people (educators) access the
internet at a high volume (Kaplowitz, Hadlock, & Levine, 2004).
Representation
Simple random sampling occurs when each participant has a likelihood of being included
in the survey and where all potential samples of a given size have the same likelihood of being
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selected (West, 2016). Teachers were sectioned into smaller segments determined from the
middle or high school they currently serve within these districts. More specifically, the total
number of surveys distributed was 768. Simple random sampling was used as the sampling
procedure to select participants and survey results.
All participants who volunteer from each school group were used as part of this research
because they are directly connected to the parent population. A group sampling of the empirical
study should be selected in such a manner where the data was statistically generalizable to the
population served (Onwuegbzie & Leech, 2007). Therefore, this research study was
generalizable to the entire population of the school districts served (i.e., all middle and high
schools in both districts) because all participants (n = 768) were given an opportunity to
voluntarily participate as part of the sample.
Data Gathering Methods
Job Descriptive Index. A quantitative method of gathering data was applied using the
Job Descriptive Index (JDI) Survey owned by Bowling Green State University. Data was
collected via Qualtrics Surveying Software and analyzed through Statistical Package for Social
Sciences (SPSS). All the participants took the 72-item questionnaire via online platform. Each
item requires teachers to respond with a “yes,” “no,” or “uncertain/?” response.
Five facets of job satisfaction (i.e., pay, promotion, supervision, people present on your
job (co-workers), and the work itself) have been identified by research for the survey (Kosteas,
2007; Ostroff, 1992; Ozpehlivan & Acar, 2016; Singh & Loncar, 2010; Taylor & Tashakkori,
1995; Williams et. al., 2007). For the JDI Survey, educators were able to give three responses,
“yes,” “no,” and “uncertain”. The value of “yes” was coded as 3, “no” was coded as 0, and
“uncertain/?” was coded as 1. Each phrase or adjective describes the job situation as either “yes”
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(meaning the phrase or adjective does describe the job situation), “no” (meaning the phrase or
adjective doesn’t describe the job situation, and “uncertain” (meaning the participant could not
decide).
Job in General. Balzer, Kihm, Smith, Irwin, Bachiochi, and Robie (1997) developed the
Job in General (JIG) to obtain a comprehensive score of job satisfaction encompassing elements
not measured in the JDI and recommend that the JDI and the JIG be given at the same time.
Hence, the JIG was administered in the same survey with the JDI and all participants answered
the additional 18 questions with a selection of “yes”, “no”, or “uncertain”, similar to the JDI
scale. This study supported the use of JDI and JIG by having a composite score to develop a
combined or overall score used to operationalize job satisfaction. SPSS data was utilized for the
purpose of coding and analyzing job satisfaction data.
Demographic Information Survey. As a separate portion of the JDI survey, a survey
was included to identify each participant’s teacher demographic information such as their name,
actual school name, average class size, workload, gender, age, race, teaching experience (years),
tenure status, educational level, current salary, and the number of discipline referrals submitted
to the administrative office during the 2019-2020 school year. Additionally, participants received
the following information via email:
1) An introductory email explaining the researcher’s background as well as the goals and
purpose for the study
2) Background information on the Job Descriptive Index Survey
3) Information explaining their voluntary participation in the study and agreement to
provide the most accurate information related to their job satisfaction and demographic
data
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4) Ethical and confidentiality practices that were taken during the research study
5) The Job Descriptive Index and Demographic Information Survey (link)
Data Collection Procedures
All current middle and high school teachers within the sample were invited to participate
in the online survey administration of the JDI Survey and Demographic Questionnaire. Teachers
were emailed one survey link to their school email account. The initial email provided
information to the prospective participant informing them of the research being conducted, the
goal of the study, and confidentiality measures (i.e., Kennesaw State University’s informed
consent protocol). Once a participant opened the survey link, they were provided an opportunity
to choose whether or not they wanted to participate. If the participant chose “yes”, they have
specified their consent to participate and were provided access to the survey. On the other hand,
if the participant chose “no”, the software automatically exited them from the survey.
Teachers had four weeks (i.e., 20 weekdays) to complete the survey. At any time during
the process, a teacher may have opted out of taking part in the study. Teachers who expressed a
desire not to participate in the study requested to exclude themselves from participation and any
information received was removed from the collection of data. Teachers who have not completed
the survey after the introductory email received a gentle reminder email on weekday 6 (2nd
email), weekday 11 (3rd
email), and weekday 16 (4th
email) of the 20-day data collection process.
The JDI/JIG survey consist of five sections related to the facets of Job Satisfaction (i.e.,
promotion, pay, work itself, co-workers, and supervision) and the additional section for the Job
in General portion of the survey. An Ordinary Least Squares Model of Multiple Linear
Regression was utilized to assess the influence of student discipline on teacher job satisfaction
covariates. The multiple linear regression tests served to identify the relationship between job
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satisfaction (dependent variable) and student discipline (independent variable) as well as any
relationships between job satisfaction and each of the ten covariates.
Variables
Covariates, alias for statistical controls, were included to account for elements that could
influence the dependent variable outside of the independent variable as well as reduce the
potential of type-I and type-II error (Becker et al., 2015; Huck, 2012). Furthermore, when
covariates are not applied there can be a misguiding representation of the actual connection
between the independent and dependent variable, thus leading to an inaccurate null hypothesis
not being denied or an accurate null hypothesis not being accepted (Huck, 2012).The research on
teacher job satisfaction highlights 10 covariates purported to influence teacher job satisfaction
(i.e., class size, workload, gender, age, race, experience, tenure, educational level, salary, and
principal leadership in general).
Research has determined that multiple factors influence job satisfaction and could hinder
the results of this study if they are not accounted for. To address the associated factors that
influence job satisfaction, personal attributes served as covariates because of the great amount of
research acknowledged in empirical literature supporting their relationship with job satisfaction
(Buckman, 2017; Crossman & Harris, 2006; Perie & Baker, 1997). Other factors such as
workplace characteristics (Colgaltay & Karadag, 2016; Schwichtenberg, 2012), human capital
elements (Faupel-Badger, Nelson, & Izmirlian, 2017; Ganzach, 2003; Ng & Feldman, 2010;
Oshagbemi, 2000), and principal leadership (Dutta & Sahney, 2016; Kim & Kim, 2017; Nazim
& Mahmood, 2018) have all been identified through literature to correlate with teacher job
satisfaction.
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Class size. Research has indicated a potential influence of class size on job satisfaction
(Alt, Kwon, & Henke, 1999; Greenhouse, Moyer, & Rhodes-Offutt, 1999). Schwichtenberg
(2012) surveyed educators to assess the comparison of class size and job satisfaction and found
that student achievement was an important trigger of emotions toward job satisfaction and
greater class sizes reduced student achievement, ultimately contributing to decreased teacher job
satisfaction. In agreement with Public School Review, the average teacher/student ratio in a
Georgia Public School is 16:1 (Georgia, 2018), but for the purpose of this research, participants
selected the average numerical value of students they teach per class. Because of the literature
supporting the impact of class size on teacher job satisfaction, this variable was included in the
analysis.
Workload. Based on previous research, workload is a substantial factor when assessing
job satisfaction (Spector, 1997). Lesson planning, grading papers, contacting parents, checking
emails, attending conferences, holding team meetings, and coaching student extracurricular
activities are all part of the workload that some teachers may not be compensated for in addition
to the traditional 40 contractual hours they work each week. In defining how workload was
operationalized for this study, participants calculated the average number of unpaid hours they
work per week including the additional school related activities they engaged in outside of their
contractual 40-hour work week. Since the relationship between workload and job satisfaction has
been found in other teacher job satisfaction studies (Burke, Borucki, & Hurley, 1992; Hussain &
Saif, 2019), workload was used as a covariate for this study.
Gender. After reviewing prior literature, research has found women to be more satisfied
than their male colleagues as ministers (McDuff, 2001), scientists (Dhawan, 2000), lawyers
(Hull, 1999), and clinicians (Bashaw, 1999), and these repeated findings have summarized
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females as generally content in most work professions overall. To add, results of an independent
sample t-test comparing the job satisfaction of a sample of 141 elementary female teachers and
92 elementary male teachers in Turkey, indicated a significant difference between the genders (t
= 4.429, p < .05), with male teacher mean job satisfaction ( X = 73.26) being lesser than their
females counterparts ( X = 76.06) (Sak, 2018). Because of the gender difference associated with
job satisfaction highlighted in the literature, gender was utilized as a control variable in this study
and provided demographic information as part of the survey.
Age. Personal attributes (i.e., age, gender, and race) served as covariates because of the
large amount of research documented in empirical literature supporting their relationships with
job satisfaction (Buckman, 2017; Crossman & Harris, 2006; Perie & Baker, 1997). Age was
recognized as a discrete variable for this study calculating their age based on their year of birth
given. Since research has discussed the relationship between age and job satisfaction, age was
included as a covariate for this study.
Race. Race has historically been identified as an element of influence toward job
satisfaction, and Bartel (1981), Duncan (1977), Hersch and Xiao (2015) have conducted various
studies to assess the relationships between these two concepts. Mukerjee (2014) discovered that
Blacks reported a considerably lower job satisfaction than their White counterparts, and that
controlling for potential discriminating elements could reduce the black-white disparity in job
satisfaction. Since literature indicates the association of race and job satisfaction, race was used
as a covariate for this study and participants selected their race as part of the demographic
information.
Experience. Experience based on the number of years serving as a teacher is a factor of
job satisfaction. Experience was recognized as a discrete variable for this study counting each
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year of experience earned per teacher. Perie and Baker (1997) insist that newer employed and
fewer experienced teachers in public schools are more likely to be satisfied with the teaching
profession when in comparison to teachers in the later phases of experienced careers. On the
contrary, Oshagbemi’s (1997) research suggest that teacher experience has a positive influence
on job satisfaction and additional results by Oshagbemi (2000) specify that employees with 10 or
more years of experience have greater levels of satisfaction. For these reasons, teacher
experience is justified as a covariate for this study because of the association it has with
decreasing teacher dissatisfaction.
Tenure. The concept of tenure was used as a covariate in this research study because
empirical evidence has correlated its influence on job satisfaction (Bedeian, Ferris, & Kacmar,
1992; Clark, Oswald, & Warr, 1996; Hochwarter, Ferris, Perrewe, Witt, & Kiewitz, 2001;
Kalleberg & Loscocco, 1983; Ng & Feldman, 2010). Additionally, Ng and Feldman (2010)
reported that 8% of studies measured organizational tenure as an ordinal variable (e.g., 1 = 0-5
years, 2 = 6-10 years, 3 = 11-15 years, . . . 7 = more than 30 years). As discussed in the literature,
for the purpose of this study, tenure was defined by any teacher who had received their fourth
consecutive contract by the same local school board of education. Using Georgia’s operational
definition of teacher tenure discussed in the literature review, tenure serves as a dichotomous
variable and individuals with three or more consecutive years of teaching experience were
characterized as tenured and those with less than three completed years of teaching experience
were characterized as untenured.
Education level. Education is an element that influences job satisfaction and it could
have both an impact either positively or negatively (Ganzach, 2003). In public education, a
teacher’s education level will affect their salary and this can influence their level of satisfaction
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with pay and unintentionally influence their overall employee satisfaction. Typically, a teacher’s
salary will increase when a higher level degree is earned (e.g., Master’s Degree, Educational
Specialist Degree, Doctoral Degree) (GADOE, 2019). Education level was used as a covariate
for this study.
Salary. In order to capture teacher pay, salary was used as a covariate for this study
because research purported that salary is a determinant of job satisfaction (Berkowitz, Fraser,
Treasurer, and Cochran, 1987; Faupel-Badger, Nelson, & Izmirlian, 2017; Muhammad &
Akhter, 2010). Public school districts provide a fixed based teacher salary schedule that includes
teacher step increases in pay determined by years of gained experience. Teachers are provided
incremental increases in pay each year until they reach the salary cap for their particular
education level status by reaching the total number of years of service allowed by the respective
school district (Buckman, 2017). Teacher salary was operationalized by identifying participants’
total salary which included their annual based salary defined by the district’s fixed rate salary
schedule as well as any supplemental pay provided by the district.
Principal Leadership in General. The relationship between principals’ leadership style
and teacher job satisfaction and performance has been explored substantially (Al-Mahdy et al.,
2016; Dutta & Sahney, 2016; Kirby, Paradise, & King, 1992; Koh, Steers, & Terborg, 1995;
Silins, 1992). There are many leadership styles that may be used in a business setting, however,
the principal leadership styles that frequently influence teacher job satisfaction are
transformational leadership (Nazim & Mahmood, 2018; Northouse, 2007; Rowold & Scholtz,
2009), transactional leadership (Ayden et al., 2013; Bogler, 2001), instructional leadership (Dutta
& Sahney, 2016), and servant leadership (Al-Mahdy et al., 2016; Barbuto & Wheeler, 2006; Kim
& Kim, 2017). To capture principal leadership for this study, the principal’s leadership in
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general was controlled for based on the school they serve at as principal in relation to the
dependent variable and independent variable. Principals at the pseudonyms Principal 0, Principal
1, Principal 2, Principal 3, Principal 4, Principal 5, Principal 6, Principal 7, Principal 8, Principal
9, Principal 10, Principal 11, and Principal 12 had their leadership in general controlled using the
results of its relationship with job satisfaction and student discipline, respectively.
Independent variable. A survey of 53,000 Georgia educators (Owens & GADOE, 2015)
unsurprisingly reported that student discipline (18.6%) is the top reason why teachers are the
leaving the profession. Based on the findings of Owens and GADOE (2015), this study used
student discipline as the independent variable to identify the relationship student discipline has
with teacher job satisfaction. The independent variable was measured by the number of ODRs
that a teacher has submitted to the office for processing within one academic school year.
A numerical value was entered to represent the estimated number of ODRs that have
been submitted for the academic school year up to the specific point when research was
collected. ODR numbers were self-reported to the researcher by each individual participant
based on the number of referrals submitted during the 2019-2020 school year. The student
discipline data from the teachers of 13 secondary level schools was used to assess whether there
is a significant relationship between student discipline (measured by office discipline referrals)
and teacher job satisfaction as measured by the JDI/JIG survey. ODRs were operationalized as
the measure to assess student discipline per each participant in the sample.
Dependent variable. Job satisfaction is the dependent variable for this study. The 2009
revised Job Descriptive Index survey composed of 5 facets (i.e., promotion, pay, work itself, co-
workers, and supervision) that were developed by Smith, Kendall, & Hulin (1969). On the
JDI/JIG survey, job satisfaction was analyzed as a composite score. Each facet of job satisfaction
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identifies a subscale, and each subscale contains 9 to 18 responses where teachers can express
their feelings toward various components that make up job satisfaction. Facets were measured
exclusively, in addition to being measured as a general score representative of overall job
satisfaction.
This research used the JDI/JIG survey because it is a popular leading mechanism for
determining job satisfaction (Buckley, Carraher, & Cote, 1992; Smith & Stanton, 1998) and the
JDI/JIG survey has exhibited reliable and valid results with various populations (Johnson, Smith
& Tucker, 1982). Because a paucity of current research exist that examines the correlation
between student behavior and job satisfaction (Klassen & Anderson, 2009; Landers, Alter, &
Servilio, 2008; Skaalvik & Skaalvik, 2011; Stauffer & Mason, 2013), it would be beneficial for
school or district leaders to explore this relationship. Validity and trustworthiness are imperative
to this study because of the importance toward receiving accurate results and the impact of the
results on future school district practices.
Psychometric Properties of the JDI/JIG
According to DeVellis (2003), a valid instrument measures what it is supposed to
regulate. Since its conception (Smith et al., 1969), the JDI Survey has become a very popular
study to assess job satisfaction. JDI has been widely employed in over 100 published studies
measuring job satisfaction in a variety of occupational environments.
Due to the abundance of studies employing the JDI, extensive normative data are
available for potential users of the scale. The extensive body of research using the scale provides
evidence of both the reliability and the validity of the instrument. The JDI/JIG survey was
selected as the basis for quantifying job satisfaction (i.e., composite score) in order to ensure
consistent reliability and validity when determining job satisfaction (Ironson, Smith, Brannick,
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Gibson, & Paul 1989). For assurance when evaluating the JDI and JIG for reliability, a
Cronbach’s coefficient alpha method was utilized (Brodke et al., 2009). A strong degree of
reliability is measured with an alpha of .80 or higher. JDI facets have been psychometrically
examined for internal stability at the following measures: pay .88, work .90, promotion .91, co-
workers .92, supervision .92, and JIG .92.
Pearson correlations helped to determine the validity with other scaled mechanisms (i.e.,
quitting intentions scale, stressful feelings scale, and the single item measure of job satisfaction).
Each job facet was correlated to a significance level of 0.01 (2-tailed). For example, when the
JIG was compared with the quitting intentions scale, stressful feelings scale, and the single item
measure of job satisfaction, the scores totaled -0.61, -0.30, and 0.79, respectively. In alignment
with the populace involved in this study, the JIG correlates with school demographic concepts
and offers the expected reliability and validity across diverse populations (Gillet & Schwab,
1975; Johnson, Smith, & Tucker, 1982; Kinicki et al., 2002). Both the JDI and JIG were used to
capture job satisfaction in this study through a composite score.
Research Question
This study assessed the following research question:
1. Is there a significant correlation between the job satisfaction levels of middle and high
school teachers as measured by the combined JDI and JIG when teacher job satisfaction
covariates have been controlled?
Data Analysis
Descriptive and inferential statistics were utilized in the explanation of the data received
for this study. Detailed or descriptive statistics (i.e., central tendency) were used to explain the
independent, dependent, and control variables (i.e. class size, workload, gender, years of
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experience, age, race, tenure, educational level, salary, and principal leadership in general).
Inferential statistics were used to assess if a correlation exists between the variables.
An Ordinary Least Squares (OLS) multiple regression analysis was conducted whereby
each variable was placed into the regression model using a concurrent entry order (Huck, 2012).
In support of the literature discussed during the review, covariates were needed in this study to
weaken the chances of having any potentially inaccurate or conflicted findings (Huck, 2012).To
avoid such occurrences; multiple regression analysis was selected for the statistical measure
instead of using a simple linear regression. OLS was used to ascertain the best-fit line for the
investigation.
The sole regression prototype to postulate the assumption included the dependent
variable (job satisfaction) and each of the covariates. An alpha level of .05 or less was used as
the criteria to classify significant variables in the multiple linear regression analysis. Each
covariate or control variable was entered identically (simultaneously in order of entry) to find
each variables viability (i.e., precision). Considering research has not provided a reason to enter
the variables in a tiered manner, this method of entry is expected (Huck, 2012). With a multiple
linear regression analysis, the examination provided the range of variance related with all
covariates on the dependent variable as well as the range of variance related with the
independent variable when all other components have been controlled.
Null Hypothesis
This study was designed to identify whether a significant correlation exists between
student discipline and the job satisfaction of middle and high school teachers when teacher job
satisfaction covariates have been controlled. An alpha value .05 (α = .05) was used to either
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accept or reject the null hypothesis. The null hypothesis examined in this research was the
following:
H0: There is no significant correlation between student discipline and the job satisfaction
of middle and high school teachers as measured by their JDI/JIG combined score when
teacher job satisfaction covariates have been controlled.
Statistical Method
In reference to the above-mentioned research question and hypothesis, the following
procedures were performed. A multiple linear regression procedure was utilized to ascertain the
relationship between the independent variable, dependent variable, and covariates. The data was
entered in the analysis with a concurrent order using an ordinary least squares method to
approximate the unspecified parameters in the linear model. An examination of the data was
conducted using the Statistics Package for Social Science (SPSS).
The multiple linear regression analysis was an analysis of all covariates and their
correlation with the dependent variable to define the amount of adjustment (i.e., variance) the
covariates account for in the model. Covariates for this study were categorized as: (a) workplace
characteristics (i.e., class size and workload), (b) personal attributes (i.e., age, race, and gender),
b) human capital elements (i.e., experience, tenure, education level, and salary) and (d) principal
leadership (i.e., principal leadership in general). These covariates aided in decreasing statistical
error by controlling for components that influence job satisfaction external of the independent
variable and helped in determining if there was a statistical relationship between a teacher’s
overall job satisfaction and each of the job satisfaction covariates. In sum, 10 factors served as
covariates: (a) class size, (b) workload, (c) gender, (d) age, (e) race, (f) experience, (g) tenure, (h)
educational level, (i) salary, and (j) principal leadership in general.
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Chapter Four
Results
This section provides the results from this study in regards to the relationship between
student discipline and teacher job satisfaction. Tables will be included in this section to give a
deeper analysis of the data used to describe the dependent variable, independent variable, and the
covariates. Within this section, descriptive statistics, assumption testing, and inferential statistics
will be discussed.
Descriptive Statistics
Participants within this study were selected from a population of middle and high school
teachers from two suburban school districts in the state of Georgia. This study was performed to
assess whether there is a statistically significant relationship between student discipline and
teacher job satisfaction. From a population of 768 middle and high school teachers who returned
to their schools in the 2020-2021 school year, a simple random sampling technique was used that
consisted of all 768 teachers (n=768) from two school districts in the state of Georgia where each
teacher was likely to be selected as a participant.
To find a suitable sample size for the study, Cohen’s (1988) power analysis was used.
Cohen’s power analysis includes the number of independent variables, covariates, effect size,
significance level, and power to make a decision on an appropriate sample size. Based on
Cohen’s power analysis, 97 participants were needed to achieve adequate power to detect
statistical significance between variables. The influence of student discipline toward job
satisfaction was assessed based on the following parameters: a medium effect size of (f² = .15), a
distinct level of significance set at ( = .05), and a power level (= .80).
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Qualtrics, an electronic survey delivery process, was implemented to communicate with
the sample. Electronic surveys were selected as the most appropriate method to reach school
teachers because they typically utilize email applications for communication on a daily basis
(Kaplowitz et. al., 2004). With the heightened use of computer devices through virtual learning
as a result of the Coronavirus pandemic, electronic delivery (i.e., email) may potentially elicit
more responses from the participants.
Seven hundred and sixty-eight middle and high school teachers from two suburban
school districts in Georgia were sent the job satisfaction survey along with demographic
questions. In sum, 256 surveys were opened and 216 participants started and/or submitted the
survey. All surveys received were reviewed for potential survey completion to assess if the
participant’s data could be used as part of the study. Ninety participants were removed from the
original 216 surveys that were started and/or submitted due to having incomplete data or missing
values. After removal, it was determined that 126 participants completed all components of the
job satisfaction survey and answered all of the demographic questions. As such, the 126
participants who completed the survey in full were chosen as the sample group for the study
rendering a final response rate of 16 percent.
The survey and questionnaire administered to participants addressed demographic
information (i.e., personal attributes, human capital elements, and workplace characteristics),
principal leadership, and job satisfaction. To examine the Job Descriptive Index (JDI) survey,
internal consistency via Cronbach’s Alpha’s rating was determined (Huck, 2012). The
recommended range of reliability using a Cronbach’s Alpha is .70 or greater. A Cronbach’ Alpha
rating of .947 was reported in terms of the JDI survey.
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Dummy coding is a technique of multiple regression used to categorize a variety of
nominal or ordinal independent variables (i.e., marital status) (Huck, 2012), and each dummy
code is compared to the reference group. Thus, all nominal and ordinal variables (i.e., gender,
race, tenure, principal, degree level) were dummy coded for analysis purposes. This coding
process was essential for the statistical software (i.e., SPSS) to evaluate the data and the
following tables provide an account of the descriptive statistics.
The average number of discipline referrals submitted from the sample group was 6.3 (see
table 4.1). Discipline referrals ranged from a minimum of 0 to a maximum of 50 referrals.
Descriptive statistics revealed that the average teacher’s age of the sample group was 45.38.
Teachers’ ages ranged from a minimum of 24 years to a maximum of 76 years. Additionally, the
average class size of the sample group ranged from 24.71 students to 41 students.
Participants in the sample population had a workload (non-paid hours worked outside of
contractual hours) average of 16.89 hours. Teacher workload showed a range from 0 unpaid
hours to 75 unpaid hours. Mean scores of experience ranged from 13.64 years’ experience with 1
as the lowest total of years in teaching to 35 as the highest total of years in teaching. Further, the
average salary of the sample group was $56,994.57. The sample salaries ranged from a minimum
of $33,000 to a maximum of $93,000.
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Table 4.1
Discipline, Age, Class Size, Workload, Experience, and Salary
Variable N Mean Range SD
Discipline 126 6.30 50 9.235
Age 126 45.38 52 10.156
Class Size a 126 24.71 41 7.308
Workload 126 16.89 75 13.106
Experience 126 13.64 34 8.40
Salary 126 56994.57 93000 10.68
Note. aAverage Class Size.
bWeekly Hours Worked Outside of Contractual Hours.
cU.S. Dollar
Teacher degree level was used as an ordinal variable and was determined based on the
highest category of the degree level obtained (i.e., Bachelor’s, Master’s, Specialist or credits
beyond Master’s, Doctorate). Descriptive statistics indicated 26.2% of participants received a
Bachelor’s Degree, 47.6% of participants earned a Master’s Degree, 19.0% earned a Specialist
degree or credits above a Master’s Degree, and 7.1% earned a Doctorate Degree (see Table 4.2).
Table 4.2
Frequency of Participants by Degree Level
Variable Frequency Percent Valid Percent Cumulative
Percent
Bachelors 33 26.2 26.2 26.2
Masters 60 47.6 47.6 73.8
Specialist 24 19.0 19.0 92.9
Doctorate 9 7.1 7.1 100.0
Total 126 100.0 100.0
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In addition to workplace characteristics and human capital elements, teachers were asked
questions about their personal attributes. Descriptive statistics indicated that females accounted
for 63.5% of the teachers within this study while males accounted for 36.5% (see Table 4.3).
This finding aligns with empirical literature indicating females account for the majority of
teacher workforce across the United States (Moore, 2012; Perie & Baker, 1997).
Table 4.3
Frequency of Participants by Gender
Variable Frequency Percent Valid Percent Cumulative
Percent
Female 80 63.5 63.5 63.5
Male 46 36.5 36.5 100
Total 126 100.0 100.0
Race was also used as a control variable in monitoring the percentage breakdown of the
sample group. Black teachers accounted for 47.6% of the sample group, while White teachers
accounted for 46.0% of the sample group (see Table 4.4). Only 6.3% of teachers were either
multiracial or their race resided in the other category. Due to the low percentage of teachers who
were non-Black or White, those participant races were accounted for in the Multiracial/Other
category.
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Table 4.4
Frequency of Participants by Race
Variable Frequency Percent Valid Percent Cumulative
Percent
Black 60 47.6 47.6 93.7
White 58 46.0 46.0 46.0
Multiracial/Other 8 6.3 6.3
Total 126 100.0 100.0
Another variable used in the research was the analysis of teacher tenure. This
dichotomous variable was operationalized by teachers who worked in their current district for at
least three school years or more (i.e., Tenured) versus those who have worked less than three
school years within the same school district (i.e., Untenured). The data indicated 76.2% of
teachers identified as tenured in their school district, while 23.8% of teachers identified as
untenured in their current school district (see Table 4.5).
Table 4.5
Frequency of Tenured Teachers in the Sample
Variable Frequency Percent Valid Percent Cumulative
Percent
Yes 96 76.2 76.2 76.2
No 30 23.8 23.8 100.0
Total 126 100.0 100.0
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Since principal leadership (i.e., transformational, transactional, instructional, and servant)
has been recognized as a variable that influences teacher job satisfaction (Ayden et al., 2013;
Dutta & Sahney, 2016; Kim & Kim, 2017; Nazim & Mahmood, 2018), each school was dummy
coded to capture the job satisfaction of teachers at each respective school participating in the
study. Table 4.6 (below) shows that the highest frequency of teacher surveys were for Principal 0
with 33 completed surveys, Principal 8 with 20 completed surveys, and Principal 6 with 16
completed surveys. The principals who had the highest frequency of teachers who participated in
the study also made up 26.2%, 15.9%, and 12.7% of the sample, respectively. The principal
leadership variable was coded as a nominal variable to track which school the participants
served.
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Table 4.6
Frequency of Participants by School/Principal
Variable Frequency Percent Valid Percent Cumulative
Percent
0 33 26.2 26.2 26.2
1 8 6.3 6.3 32.5
2 5 4.0 4.0
36.5
3
4
5
6
7
8
9
10
11
12
Total
2
10
4
16
3
20
5
9
9
2
126
1.6
7.9
3.2
12.7
2.4
15.9
4.0
7.1
7.1
1.6
100
1.6
7.9
3.2
12.7
2.4
15.9
4.0
7.1
7.1
1.6
100
38.1
46.0
49.2
61.9
64.3
80.2
84.1
91.3
98.4
100
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The focus of this study was on the relationship of the dependent variable (i.e., job
satisfaction) with the independent variable (i.e., student discipline) while controlling for
covariates (human capital elements, workplace characteristics, personal attributes, and principal
leadership in general). Table 4.6 is used to display the relationship of the variables using
Pearson’s correlations. Within the correlations matrix (Table 4.7), there are no independent
variables that have a significant relationship (i.e., p < 0.05) with the dependent variable. Only
marginal significance could be captured from the relationship between the dependent variable
(job satisfaction) and the independent variable (student discipline) because a negative correlation
exists (r = -.074).
Additionally, no control variables exhibited a significant relationship with the
independent variable (student discipline). The lack of statistically significant correlations
between the dependent and independent variables may have resulted from missing values and
from negatively skewed data where the distribution was distinctly pointed to the left of the bell
curve prior to transforming the data.
Some of the covariates used in this study were statistically significant with one another
after reviewing the correlations matrix (see Table 4.7). The descriptive statistics indicated gender
and race had a positive relationship with each other (r =.252, p < .01). This relationship shows
that males and Whites correlate significantly as covariates. With 63.5% of females accounting
for this sample group, the majority of the educators are identified as Black and White teachers.
Further, descriptive statistics showed a positive relationship between experience and age (r =
.578, p < .01).This correlation indicates an increase in experience will by default increase a
person’s age. However, this study doesn’t account for the educators who may be older in age due
to entering the teaching profession as a second career.
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Moreover, tenure and experience have a significantly negative correlation (r= -.363,
p<.05). Tenure was dummy coded as “0” for “yes”, meaning the reference group represents
teachers who have obtained tenure, and “1” was dummy coded for teachers who have not
obtained tenure in their current school district. The negative relationship between tenure and
experience indicates how teachers who have obtained tenure generally have more teaching
experience than those who have not obtained tenure in their school district. Another relationship
exists between degree level and tenure (r=.270, p<.05). This correlation suggests that as teachers
complete advanced degrees, they are more likely to obtain tenure at their place of employment.
Salary is another variable that exhibited correlations with other covariates. Salary
correlates positively with workload (r =.197, p<. 05). This result supports the notion that teachers
work more non-contractual hours when they are already benefiting from higher salaries.
Additionally, a correlation exists between salary and experience (r = .687, p< .01). The
relationship between salary and experience indicates statistical significance and shows how
salary is likely to increase as experience increases.
On the other hand, salary has a negative relationship with tenure (r = -.279, p< .01). The
negative relationship between salary and tenure indicates that as salary increases, tenure may be
less likely to be obtained as teachers may move around to other employers who offer higher
salary grades.
Lastly, principal leadership correlated positively with workload (r = .225, p< .05).
Principal leadership was a nominal variable and workload was utilized as a continuous scale
variable. This statistically significant relationship suggests that the school principal’s leadership
may influence a teacher’s workload outside of their contractual hours. The directionality of the
coefficient indicates that when comparing the leadership of principal 0 to the scores associated
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with workload, all other schools typically had principals who encountered teachers with larger
workloads (unpaid hours worked outside of their contractual hours) than principal 0. No
additional information is evident to assess why principals at schools that are dummy coded as
“1” through “12” typically work more unpaid hours than those of the reference group (principal
0).
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Table 4.7
Correlation of All Variables
1 2 3 4 5 6 7 8 9 10 11
Discipline 1
Age
-.028
1
Race
.140 .004 1
Gender
-.016 .30 .252** 1
Class Size
.066 -.115 .004 .151 1
Workload
.000 .117 -.141 -.117 .093 1
Experience
-.083 .578** -.017 .048 -.043 .154 1
Tenure
.136 -.167 -.065 -.114 .012 .028 -.363* 1
Degree
-.149 .153 .085 -.044 -.068 .129 .270** -.068 1
Salary
-.110 .415 -.010 .121 -.015 .197* .687** -.279** .590 1
Principal
.161 -.060 .109 -.126 -.199 .225* .001 -.007 .011 -.54 1
Job Satisfaction -.074 -.014 .035 .089 -.016 -.36 .005 .090 .004 .092 -.078
Correlation of All Variables
Note. **Correlation is significant at the 0.01 level (2-tailed).
*Correlation is significant at the 0.05 level (2-tailed).
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Assumption Testing for Multiple Regression
For the purpose of meeting statistical assumption necessary to avoid inaccurate findings,
Huck (2012) recommends that Shapiro-Wilk and Komolmogorov-Smirnov be used to test the
normality level of the dependent variable prior to completing multiple linear regression. More
specifically, the assumptions that should not be violated are normality, equal variance, and
multicollinearity. To obtain normality, the Shapiro-Wilk should be non-significant at a level of
.05 or higher (Shapiro-Wilk = .000, p >.05) and the Komolmogorov-Smirnov should be non-
significant at .05 or higher (Kolmogorov-Smirnov =.000, p >.05) (Huck, 2012). Analyzing the
original dependent variable (job satisfaction) didn’t meet the normality level as the Shapiro-Wilk
and Komolmogorov-Smirnov exhibited a non-normal distribution.
According to Huck (2012), to meet the assumptions for normality, data can be
transformed without compromising the results of the research. Data transformation can be
conducted by using a log reflection transformation (Hammouri, Sabo, Alsaadawi, & Kheirallah,
2020). In an effort to obtain normality, a logarithm and reflection were used to transform the data
for executing a multi linear regression test. After 90 participants were excluded from the dataset
due to incomplete data, the number of participants moved from 216 to 126 (n = 126).
Since the distribution of the original job satisfaction scores were negatively skewed, a
logarithm and reflection were implemented to produce a normality level of non-significance at
.09 for the Shapiro Wilk test (sw = .09, p > .05) and a normality level of non-significance at .061
for the Komologorov-Smirnov test (ks = .061, p > .05). No additional outliers appeared in the
findings to justify needing to exclude any more participants from the sample group. Therefore,
the transformation indicates the assumption for normality was met.
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Another assumption that should be met before testing the null hypothesis is the
assumption of equal variance (Huck, 2012). The assumption of equal variance is known as the
homogeneity of variance. In this study, the assumption for equal variance was analyzed using
Leven’s Test for Equality of Variances (Huck, 2012). When the data was analyzed, the
significance value was greater than .05 (i.e., Levene Statistic = .370, p > .05). Therefore, the
assumption of equal variance was met.
In test of the multicollinearity, none of the variables that correlate based on the
correlations matrix (Table 4.7) actually exhibit a value of greater than 0.7. To decrease high
correlations between the independent variable (student discipline) and control variables, each
variable was tested for multicollinearity. When testing for multicollinearity, an acceptable
Variance of Inflation Rate (VIF) is 3.0 or less. The only variable exhibiting VIF over 3.0 is
salary with a score of 3.083 (see Table 4.8). With multiple findings that support salary as a
determinant of job satisfaction, salary was kept as a control variable (Buckman, 2017; Faupel-
Badger, Nelson, & Izmirlian, 2017; Muhammad & Akhter, 2010). Additionally, the tolerance
level is expected to be less than 1.0 and this assumption test was met with the independent
variable and all 10 control variables (see Table 4.8).
Other assumptions that should be met for multiple regression are: 1) a linear correlation
with the dependent variable and independent variable, 2) standard residuals in a range between -
3 and 3, and 3) a Cook’s distance no greater than 1.00 (Huck, 2012). The dataset met the
assumption of a linear correlation between the dependent and independent variable because the
standard residual fell within a range of -3 to 3 as observed on a scatter plot. Furthermore, the
linear correlation is observed in compliance as all data points fell around the line on the
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probability-probability plot. Finally, the Cook’s distance should not have a value greater than
1.00 and in this study, the minimum Cook’s distance was .000 and the maximum was .083.
Table 4.8
Multi-Collinearity Diagnostics Table
Model Tolerance VIF
Discipline .902 1.108
Agree .643 1.556
Race .849 1.177
Gender .840 1.190
Class Size .884 1.132
Workload .836 1.197
Experience .381 2.627
Tenure .828 1.208
Degree Level .567 1.764
Salary .324 3.083
Principal .823 1.215
Note. Variance Inflation Factor (VIF) of less than 3.0 utilized to avoid multi-collinearity.
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Inferential Statistics
For the purpose of this study, an Ordinary Least Squares (OLS) multiple regression was
used to evaluate the dependent variable, independent variable, and covariates. Job satisfaction
(i.e., dependent variable) was regressed on the independent variable (i.e., student discipline) and
each covariate. OLS was used to determine whether the following null hypothesis was accepted
or rejected.
H0: There is no significant correlation between student discipline and the job satisfaction
of middle and high school teachers as measured by their JDI/JIG combined score when
teacher job satisfaction covariates have been controlled.
An alpha level of .05 (𝛼= 0.05) was used as criteria to assess if the null hypothesis would be
accepted or rejected. The first step in the analysis was to determine how much variance was
accounted for in the model when the dependent variable was regressed with only the covariates.
All covariates were entered simultaneously in the multiple linear regression equation and
accounted for an approximate amount of 5% of the model 1 variance (see Table 4.9).
Table 4.9
Multiple Regression Model Summary
Model R square Adjusted
R square
Std. error
of
estimate
R square
change
F. change Sig F. Chance
1 .050 -.041 .20278 .050 555.1 .865
An analysis of the null hypothesis was used to determine whether the dependent variable
(job satisfaction) had a statistically significant relationship with the independent variable.
Further, the level of significance was determined by interpreting the regression coefficients table.
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Table 4.10 below indicates that job satisfaction doesn’t have a statistically significant
relationship with student discipline (b = -.077, p > .05). Additionally, no covariates exhibited
statistical significance with job satisfaction after reviewing the regression coefficients table.
Although salary and job satisfaction doesn’t exhibit a statistically significant relationship (b =
.232, p>.05), salary serves as the covariate that is closest to statistical significance out of all the
covariates in this study (p = .15). Thus, a marginally significant relationship with job
satisfaction and salary is consistent with research that supports a direct correlation between these
variables (Buckman, 2017; Ganzach, 2003; Nazim & Mahmood, 2018).
Tenure has the second strongest level of marginal significance within the analysis (p =
.217). The positive directionality of this variable (b = .125, p >.05) supports research that
teachers who have obtained tenure generally like their job (Kalleberg & Matstekaasa, 2001).
Despite the transformation of data to meet assumption testing expectations, neither the
independent variable nor the covariates produced a statistically significant correlation with job
satisfaction. Based on the findings of this study, the high probability value of the null hypothesis
below failed to be rejected, and thus, is accepted:
H0: There is no significant correlation between student discipline and the job satisfaction
of middle and high school teachers as measured by their JDI/JIG combined score when
teacher job satisfaction covariates have been controlled.
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Table 4.10
Multiple Regression Table of Student Discipline on Teacher Job Satisfaction
Variables Contribution to Overall Regression Equation
Note. a. Dependent Variable: Log10 Job Satisfaction
B Std.
Error
Beta T Sig. Tolerance VIF
Constant
2.014
.156
12.901
.000
Discipline -.002 .002 -.077 -.796 .428 .902 1.108
Age -.001 .002 -.062 -.541 .590 .643 1.556
Race -.005 .032 -.016 -.158 .875 .849 1.177
Gender .032 .041 .077 .778 .438 .840 1.190
Class Size -.001 .003 -.022 -.231 .818 .884 1.132
Workload -.001 .002 -.060 -.598 .551 .836 1.197
Experience -.002 .003 -.086 -.582 .561 .381 2.627
Tenure .058 .047 .125 1.242 .217 .828 1.208
Degree Level -.019 .028 -.083 -.683 .496 .567 1.764
Salary 3.683E-6 .000 .232 1.449 .150 .324 3.083
Principal -.001 .005 -.029 -.288 .774 .823 1.215
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Sub Analysis Using Entire Sample without Data Transformation
Prior to the use of a log transformation, a multiple linear regression analysis was
executed despite not meeting the assumption testing expectations for reaching a non-significant
level of normality. The results show that student discipline is not statistically significant with job
satisfaction, and none of the covariates are statistically significant with job satisfaction (see
Table 4.11). These results indicate that data transformation and the removal of outliers had no
significant effect on the findings of the study in terms of the relationship between the
independent variable (i.e., student discipline) and the dependent variable (i.e., teacher job
satisfaction).
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Table 4.11
Multiple Regression Table of Student Discipline on Teacher Job Satisfaction without Data
Transformation and Removal of Outliers
Variables Contribution to Overall Regression Equation
Note. a. Dependent Variable: Job Satisfaction
B Std.
Error
Beta T Sig. Tolerance VIF
Constant
146.980
33.0
09
4.453
.000
Discipline -.344 .437 -.076 -.787 .433 .902 1.108
Age -.195 .471 -.047 -.413 .680 .643 1.556
Race -1.763 6.84
9
-.025 -.257 .797 .849 1.177
Gender 6.686 8.65
7
.077 .772 .442 .840 1.190
Class Size -.229 .558 -.040 -.409 .683 .884 1.132
Workload -.133 .320 -.041 -.414 .680 .836 1.197
Experience -.302 .739 -.060 -.409 .683 .381 2.627
Tenure 13.740 9.85
8
.140 1.394 .166 .828 1.208
Degree Level -5.325 5.92
7
-.109 -.898 .371 .567 1.764
Salary .001 .001 .243 1.520 .131 .324 3.083
Principal -.41.8 1.07
0
-.039 -.391 .697 .823 1.215
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Chapter Five
Discussion, Implications, Limitations, and Conclusion
The purpose of this chapter is to provide overall guidance with interpreting the
discussion, sharing implications, and providing the study’s limitations. Job satisfaction is studied
widely because workers who are not satisfied with their job have been known to display negative
behaviors that affect their co-workers and performance (Ostroff, 1992). Considering how job
satisfaction can influence a teacher’s behavior in the educational workplace as well as the
adverse effects poor teacher job satisfaction can have on student outcomes, job satisfaction
remains a construct that warrants further exploration. Thus, this study provided educational
leaders a school centered analysis of variables that relate to job satisfaction based on previous
research.
Discussion
This study included 768 middle and high school teachers from two suburban school
districts who returned to their schools during the 2020-2021 school year. These teachers were all
included as participants to make up the study’s sample and they were sent an email that provided
information about the survey along with the actual survey link. The survey included questions
concerning job satisfaction, workplace characteristics, personal attributes, human capital
elements, and principal leadership. From the entire sample, 126 teachers completed all of the
survey questions correctly and rendered a response rate of 16%.
To ensure the data provided was not misleading, assumption tests were completed. While
testing the dependent variable (i.e., job satisfaction) for normality, the data returned negatively
skewed resulting in a failed normality assumption test. For the purpose of addressing negatively
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skewed data, a log transformation and reflection was performed to make the data interpretable
while not comprising the reliability of the results (Huck, 2012). Therefore, when the data of the
dependent variable was transformed using a log transformation and reflection, the variable was
able to meet the assumptions of normality (Kolmogorov-Smirnov = .061, p > .05; Shapiro-Wilk
= .09, p > .05). Additionally, the equal variance test (Levene Statistic = .370, p > .05) was
performed and results indicated a non-statically significant p value which identified the variances
among the groups as normally distributed.
Within this study, the null hypothesis states that there is no significant relationship
between student discipline and job satisfaction using the JDI/JIG combined survey when job
satisfaction covariates have been controlled. Ultimately, the findings indicated that the null
hypothesis was accepted because no statistical significance was evident between job satisfaction
and student discipline. However, the directionality of the slope for the regression coefficient
coded as discipline (b = -.077, p = .428, p > .05) does indicate a negative correlation exist
between job satisfaction and student discipline.
After executing the multi linear regression analysis, no covariates correlated with the
dependent variable (i.e., job satisfaction) and independent variable (student discipline). Only
marginal significance was observed between job satisfaction and salary (b = .232, p = .150, p >
.05). In further review of the multilinear regression analysis, the covariates that exhibit positive
directionality in relation to job satisfaction were gender (b = .077, p = .438, p > .05) and tenure
(b = .125, p = .217, p > .05). Despite not having statistical significance, the positive directionality
of gender and job satisfaction and tenure and job satisfaction are consistent with research
(Chaplain, 1995; Klecker & Loadman, 1999; Ng & Feldman, 2010; Poppleton & Riseborough,
1991).
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Minimal empirical literature exists that has studied the relationship between job
satisfaction and student discipline. However, Betöret (2009) Bümen (2010), Chang (2009) and
Durr (2008) all expressed how negative student behavior can lead to teacher fatigue and low
teacher satisfaction toward classroom instruction. This assumption was framed with the AET,
where the satisfaction of employees is influenced by the negative or positive experiences that
occur in the workplace (Weiss & Cropanzano, 1996). For the purpose of this study, AET was
used to postulate how the negative experiences of teachers within the classroom may be
heightened by negative student behavior, and in turn, job satisfaction may decrease as negative
student behavior persist.
Consistent with the findings of another study (Landers et. al., 2008), having a negative
correlation between job satisfaction and student discipline was expected. Landers et al. (2008)
indicated that the higher the grade level (i.e., middle school & high school), then the more
prevalent disrespect was toward teachers, and the more likely teacher job satisfaction would
decrease overall. Although their survey used a different job satisfaction survey, Landers et al.
(2008) believed disrespect was a consistent student behavioral concern that negatively influenced
teacher job satisfaction. The difference in their study of negative student behavior and job
satisfaction and this study is that Landers et al. (2008) looked at specific types of student
behaviors in instead of student discipline in general, and they used a 12-item Likert scale
instrument to operationalize job satisfaction instead of the JDI/JIG survey.
To assess the job satisfaction of employees, the JDI/JIG survey was used to determine the
job satisfaction of all middle and high school teachers who returned to their same school district
from two districts in the state of Georgia. Additionally, demographic questions were selected for
this study that would assist in capturing participant individualized data on the electronic survey.
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This study was designed to further empirical research surrounding job satisfaction and student
discipline by assessing these respective variables through a sample population.
Implications
Previously mentioned, in the state of Georgia, 47% of teachers leave the profession in the
first five years of teaching and 18.6% leave the profession due to student discipline problems
(Owens & GADOE, 2015). Research has expressed multiple practices that may be helpful in
support of negative student behavior that should be implemented by school district leaders for
improving student behavioral issues. These practices are cultural responsiveness (Larson et. al,
2008; Weinstein et. al, 2003), teacher preparation programs (Önder and Önder-Öz, 2018),
progressive discipline methods (Hoffman, 2014), positive behavior interventions (Gregory &
Weinstein, 2008), professional development (McIntosh et. al, 2014), and helpful student-teacher
relationships (Gregory et. al, 2016). Practices that benefit student learning and relationships may
help to improve the discipline issues teachers’ experience, and in result, support job satisfaction.
Considering the findings of this study, school district leaders should be mindful of the
core facets that determine job satisfaction, such as, co-workers, pay, promotion, supervision, and
the workplace (Boyd et. al, 2011; Kosteas, 2007; Ozpehlivan & Acar, 2016; Taylor and
Tashakkori, 1995; Wright & Kim, 2004). These core facets likely contributed to teacher job
satisfaction in this study as the JDI/JIG scores were generally high, and thus, caused the data to
be negatively skewed. Although student discipline didn’t exhibit a statistically significant
correlation with job satisfaction in this study, this generalization is not evident for all
populations. Therefore, researchers are encouraged to continue to explore the constructs of
student discipline and job satisfaction in future studies with larger sample sizes.
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Based on the findings of the sample size within this study, participant data supports how
negative student behavior did not contribute significantly to teacher job satisfaction. This may be
due to other demands on these teachers such as, increasing governmental controls (Moriartyet al.,
2001; Personnel Today, 2003; Sillitoe, 2003), job associated stress (Evans, 1998), minimal
support (Evans, 1997; Halpin, 2001; van der Doef & Maes, 2002), challenging work
environments (Van Der Doef & Maes, 2002), testing and/or low performing schools (National
Union of Teachers, 2001; Scott & Dinham, 2003), and pay (Buckman, 2017; Chung et. al,
2004;). Since the data was negatively skewed when job satisfaction was analyzed, this study
shows that most of the participants in this sample of school districts generally like their current
teaching positions.
Limitations
This study was performed in the state of Georgia with middle and high school teachers
from two school districts. Results are only generalizable to the population who served as
participants in this study. Additionally, the sample size was decreased from 216 participants to
126 participants after surveys with missing values were removed. Having a larger sample of
completed surveys would have helped this study become more generalizable.
Another limitation of this study was having negatively skewed results. A log
transformation and reflection had to be performed to meet the requirements of the assumption
test of normality. Not having a normally distributed bell curve significantly influenced the results
of this sample size. If more participants were included in the study, the likelihood of producing a
normally distributed bell curve may have increased.
Due to the Coronavirus pandemic, some schools and/or districts chose not to participate
in this study as they wanted to focus on other matters and were not interested in participating in
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this empirical research during school closure or virtual learning. In the midst of a pandemic,
some participants within the sample may have altered their view of student discipline or job
satisfaction because of influential life altering circumstances. More participants could have
included themselves in this study, yet they chose to not participate due to not having time. From
the 216 respondents, 5 respondents (2%) informed the researcher electronically that they didn’t
have time to complete the survey.
Conclusion
In summary, job satisfaction is a widely known phenomenon that influences employees
in any organization, positively or negatively (Judge et. al, 2001). Job satisfaction may not only
have the potential to determine if someone likes or dislikes their profession, it may also
determine if someone chooses to stay or leave a profession (Farrell (2000; Smart & Igo, 2010).
As it relates to education, teachers have multiple experiences that could create negative emotions
while in the workplace.
Student behavior is a component of a classroom environment that can negatively impact
the teaching and learning process or disrupt school operations (Finn, Fish, & Scott, 2008;
Thompson, 2009). A discipline disparity exists where Blacks have been suspended at higher
rates over time than their White counterparts (Steinberg & Lacoe, 2017). Many schools use
office discipline referrals to punish students for misbehavior in teacher classrooms across the
country (Adams, 1992; Elias, 1998; Morris & Howard, 2003; Morrison & Skiba, 2001). Teachers
working in difficult classrooms are likely to be stressed from negative student behaviors (Black,
2010; Klassen & Anderson, 2009; Spilt, Koomen, & Thijis, 2011; Vassallo, 2014). Yet, minimal
studies have been performed to assess the correlation between student discipline and teacher job
satisfaction.
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The present study is expected to add to the limited empirical research on determining
whether student discipline has an influence on job satisfaction while controlling for job
satisfaction covariates. This study provided an historical review of job satisfaction and student
discipline and theorized how AET contributes to the relationship between these two variables.
With descriptive and inferential statistics, this research determined that student discipline doesn’t
have a statically significant relationship with teacher job satisfaction. However, the regression
coefficient indicates that a negative correlation does exist between student discipline and job
satisfaction (b = -.077, p > .05). Overall, more research surrounding this topic should be explored
to determine whether a statically significant relationship exists between these two constructs in
other settings, environments, and circumstances.
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Appendix A:
Cover Letter for First E-mailing to Teachers
Dear [Teacher]:
Your role as a teacher in the state of Georgia and more specifically, in this school district is very
vital to teaching and learning. Hence, you are aware of the factors that impact job satisfaction as
an educator. Administrative support, pay, job environment, co-workers, and promotional
opportunities would likely impact job satisfaction in any place of employment. The challenges
brought upon teachers to sustain high levels of quality instruction, while managing other
professional duties such as student discipline are great.
Have you ever thought about the influence of student discipline on your individual job
satisfaction? Class size, workload, gender, years of experience, age, race, tenure, educational
level, salary, and principal leadership have all been identified by research as factors that
influence teacher job satisfaction. That’s why your experience as an educator makes your input
extremely valuable to this research study. Time is always of essence as an educator, however,
your participation in a roughly 10 minute survey is needed to advance the research in
understanding how school and district leaders can better support teachers by being mindful of the
potential impact student discipline may have on job satisfaction.
As you have been chosen to participate as a secondary level educator in this survey, inside this
email you will find a link to the actual survey. The survey will request responses pertaining to
job satisfaction and demographic information. Please complete the entire survey as honestly as
possible to the best of your knowledge.
Confidentiality of your voluntary participation will be treated with the highest ethical regard and
all information will remain anonymous when being reported in the findings. The results and
implications of this study will be provided to the school districts involved in this study.
I have been in education at the secondary level for the past 15 years and 7 of which have been in
school administration. Thank you for taking the time to contribute to this important topic. Your
time is greatly valued. Please feel free to contact me with any questions or concerns
([email protected] ).
Sincerely,
Joshua Pittman
Kennesaw State University
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Appendix B:
Cover Letter for Second E-mailing to Teachers
Dear [Teacher]:
A week ago you received a brief survey for a research project regarding the influence of student
discipline on the job satisfaction of secondary level teachers in various school districts. If you
responded to that e-mailing, I offer my genuine appreciation for your participation in the survey.
If you have not yet responded to that request, I ask you the favor of a few minutes of your
valuable time in completing the survey. This study represents an important exploration of the
limited research discovering the impact of student discipline on job satisfaction, and this study
will provide implications for how school district leaders can better support teachers when
making decisions that influence job satisfaction and student discipline.
Thank you for your time and consideration. Please rest assured that your participation in this
study will be treated with the highest level of confidentiality and your anonymity will be
completely respected in the findings. The results and implications of this study will be provided
to district personnel at their request. Thank you for your potential participation. Below you will
find a link to the survey.
Sincerely,
Joshua Pittman
Kennesaw State University
([email protected] )
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Appendix C:
Cover Letter for Third E-mailing to Teachers
Dear [Teacher]:
As an educator in Georgia, you are uniquely positioned to assist in ascertaining how discipline
referrals, class size, workload, gender, years of experience, age, race, tenure, educational level,
salary, and principal leadership influence job satisfaction. Because of your important role as a
teacher in this school district and your experience as a teacher in the 2019-2020 school year, you
have been selected to participate in a study focused on student discipline and job satisfaction.
Two weeks ago you received a survey asking information related to teacher job satisfaction and
student discipline. If you responded to my previous email then you may disregard this email, and
I offer my sincere appreciation. If you have not yet responded to that request, I ask you the favor
of a few minutes of your limited valuable time in completing the survey.
Thank you for your time and consideration with completing this survey. Confidentiality of your
voluntary participation will be treated with the highest ethical regard and all information will
remain anonymous when being reported in the findings. A link to the survey is provided below.
Please let me know if you have any questions or comments ([email protected] ).
Sincerely,
Joshua Pittman
Kennesaw State University
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Appendix D:
Cover Letter for Fourth E-mailing to Teachers
Dear [Teacher]:
I truly need your help! Your expertise and experience as a secondary level educator in this school
district is extremely valuable to my research study. You have been selected to participate in a
study focused on discovering the relationship between job satisfaction and student discipline.
Three weeks you I shared a survey requesting your input in topic areas of job satisfaction and
general demographic information. If you responded to my previous email then you may
disregard this email, and I offer my heartfelt gratitude. If you have not yet responded to that
request, I ask you the favor of a few minutes of your valuable time in completing the survey.
Thank you for your time and consideration with completing this survey. Confidentiality of your
voluntary participation will be treated with the highest ethical regard and all information will
remain anonymous when being reported in the findings. Please feel free to contact me if you
have any questions or concerns ([email protected] ). A link to the survey is
provided below:
Sincerely,
Joshua Pittman
Kennesaw State University
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Appendix E:
Demographic Information Survey
Please complete this portion of the survey by entering information that best describes your
demographic data, teaching setting and experience:
1. Write in the name of your current school:
___________________________
2. Teacher Gender
Select your gender below:
_____ Female
_____ Male
_____Transgender
_____ Do not identify as female, male, or transgender
3. What is your current age?
(e.g., 45):__________
4. Race
Select the race that you most identify with below:
_____ Asian/Pacific Islander
_____ Black/African American
_____Hispanic/Latino/Spanish
_____Multiracial
_____Native American
_____White
_____Other
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5. Teaching Experience
List the number of complete years you have in the teaching profession (e.g., 3.5 = 3 years):
__________.
6. Tenure
Have you worked 3 or consecutive more years in your current school district?
_____Yes
_____No
7. Educational Level
Select the highest degree you have earned to date:
_____Bachelor’s degree
_____Master’s degree
_____Educational Specialist or credits above Master’s degree
_____Doctorate degree
8. Salary
List your current base Gross Salary per year: $__________.
9. Class Size
List below the average number of students that you taught per class in the 2019-2020 school
year: __________.
10. Workload/Unpaid Work Hours
Teachers may serve multiple roles or duties before school, after school, or on the weekend
beyond their expected duty hours; such as, school leadership team member, focus group or
committee team member, department chair, coach, content lead teacher, tutoring, lesson planning
and more. To quantify workload, list the weekly average number of unpaid hours you work per
week in addition to the general 40 hour contractual work week: (e.g., 9):_______________.
11. Office Discipline Referrals
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List the numbers of office disciplinary referrals you submitted during the 2019-2020 school year:
__________.
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Appendix F:
The Job Descriptive Index Survey
People on Your Present Job: Think of the majority of people with who you work or meet in
connection with your work. How well does each of the following words or phrases describe these
people? In the blank beside each word or phrase below type Y for “Yes” if it describes the
people with whom you work, N for “No” if it does not describe them, and ? for “Uncertain” if
you cannot decide.
1) _____ Stimulating
2) _____ Boring
3) _____Slow
4) _____Helpful
5) _____ Stupid
6) _____Responsible
7) _____Likeable
8) _____Intelligent
9) _____ Easy to make enemies
10) _____ Rude
11) _____ Smart
12) _____ Lazy
13) _____ Unpleasant
14) _____Supportive
15) _____Active
16) _____Narrow Interests
17) _____ Frustrating
18) _____ Stubborn
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Work on Present Job: Think of the work you do at present. How well does each of the
following words or phrases describe your work? In the blank beside each word or phrase below,
type: Y for “Yes” If it describes your work, N for “No” if it does not describe it, and ? for
“Uncertain” if you cannot decide.
1) _____ Fascinating
2) _____ Routine
3) _____ Satisfying
4) _____ Boring
5) _____ Good
6) _____ Gives sense of accomplishment
7) _____ Respected
8) _____ Exciting
9) _____ Rewarding
10) _____ Useful
11) _____ Challenging
12) _____ Simple
13) _____ Repetitive
14) _____ Creative
15) _____ Dull
16) _____ Uninteresting
17) _____ Can see results
18) _____ Uses my abilities
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Pay: Think of the pay you get now. How well does each of the following words or phrases
describe your present pay? In the blank beside each word or phrase below, type: Y for “Yes” if it
describes your pay, N for “No” if it does not describe it, and ? for “Uncertain” if you cannot
decide.
1) _____ Income adequate for normal expenses
2) _____ Fair
3) _____ Barely live on income
4) _____ Bad
5) _____ Comfortable
6) _____ Less than I deserve
7) _____ Well Paid
8) _____ Enough to live on
9) _____ Underpaid
Opportunities for Promotion: Think of the opportunities for promotion that you have now.
How well does each of the following words or phrases describe these? In the blank beside each
word or phrase below, type: Y for “Yes” if it describes opportunities for promotion, N for “No”
if it does not describe them, and ? for “Uncertain” if you cannot decide.
1) _____ Good opportunities for promotion
2) _____ Opportunities somewhat limited
3) _____ Promotion on ability
4) _____ Dead-end job
5) _____ Good chance for promotion
6) _____ Very Limited
7) _____ Infrequent promotions
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8) _____ regular promotions
9) _____ Fairly good chance for promotion
Supervision: Think of the kind of supervision that you get on your job. How well does each of
the following words or phrases describe this? In the blank beside each word or phrase below,
type: Y for “Yes” if it describes the supervision you get on the job, N for “No” if it does not
describe it, and ? for “Uncertain” if you cannot decide.
1) _____ Supportive
2) _____ Hard to please
3) _____ Impolite
4) _____ Praises for work
5) _____ Tactful
6) _____ Influential
7) _____ Up- to-date
8) _____ Unkind
9) _____ Has favorites
10) _____ Tells me where I stand
11) _____ Annoying
12) _____ Stubborn
13) _____ Knows job well
14) _____ Bad
15) _____ Intelligent
16) _____ Poor planner
17) _____ Around when needed
18) _____ Lazy
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Job In General: Think of your job in general. All in all, what is it like most of the time? In the
blank beside each word or phrase below, type: Y for “Yes” if it describes your job, N for “No” if
it does not describe it, and ? for “Uncertain” if you cannot decide.
1) _____ Pleasant
2) _____ Bad
3) _____ Great
4) _____ Waste of time
5) _____ Good
6) _____ Undesirable
7) _____ Worthwhile
8) _____ Worse than most
9) _____ Acceptable
10) _____ Superior
11) _____ Better than most
12) _____ Disagreeable
13) _____ Makes me content
14) _____ Inadequate
15) _____ Excellent
16) _____ Rotten
17) _____ Enjoyable
18) _____ Poor
