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TEACHING SELF-EFFICACY OF GENERAL AND SPECIAL
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TEACHING SELF-EFFICACY OF GENERAL AND SPECIAL EDUCATION
PRESERVICE TEACHERS
By

Carrie Anna Courtad

A DISSERATION

Submitted to
Michigan State University
in partial fulﬁllment of the requirement
for the degree of

DOCTOR OF PHILOSOPHY
Special Education

2009

ABSTRACT

TEACHING SELF-BF F ICACY OF GENERAL AND SPECIAL EDUCATION
PRESERVICE TEACHERS

By
Carrie Anna Courtad

The beneﬁts of higher teaching self-efﬁcacy have been documented in a variety of
studies (Armor et al., 1976; Gibson & Dembo, 1984; Henson, 2001; Hoy & Woolfolk,
1990; Simmons et al., 1998; Tschannen-Moran et al., 1998, 2001). Ross (1994) found
robust correlations between teacher self-efﬁcacy and use of effective teaching practices
which, in turn, are beneﬁcial for students with disabilities (Chester & Beaudin, 1996;
Bender & Ukeje, 1989; Gibson & Dembo, 1984; Soodak & Podell, 1993). Studies
(Bender & Ukase, 1989) have found a positive correlation between teacher use of
effective instructional practices and high teaching efﬁcacy. Teachers with high teaching
self-efﬁcacy are particularly effective with students who may not do well in general
education classrooms, such as low-achieving students and students with disabilities.
Teachers with high efﬁcacy persist at the task of teaching, even when they encounter
obstacles and are less likely to refer students to special education programs, and are more
likely to accept responsibility for student learning (Soodak & Podell, 1994).

However the literature base is limited in the comparative studies between general
education student teachers and special education student teachers (Pugach, 2005)
especially in the area of teaching self-efﬁcacy (Brownell & Pajares, 1999). Tschannen-
Moran and Woolfolk Hoy (1998) proposed what they termed an “integrated model of

teacher efﬁcacy” (p. 227) that unites three theoretical frameworks with new conceptual

dimensions in the context and consideration of teacher tasks deﬁning teaching efﬁcacy as
“the teacher’s belief in his or her capability to organize and execute course of action
required to successfully accomplish a speciﬁc teaching task in a particular context” (p.
233). This study used Tschannen-Moran & Woolfolk Hoy’s conceptual model and
compared the teaching self-efficacy of two different groups of preservice teachers (n=73)
as they completed 16 weeks of student teaching. A survey was administered 3 times
through the semester and included the measurement of teaching self-efﬁcacy by the
Teaching Self-Efﬁcacy Scale (Tschannen-Moran & Woolfolk Hoy, 2001) and open
ended questions at each survey wave.

Over the course of a semester, there was no statistically signiﬁcant difference in
the TSES sum scores between the interns preparing to be general educators and those
preparing to be special educators on any of the three measurement waves. The means of
teaching self-eﬂicacy scores, as measured by the TSES, increased over the semester.
Information ﬁ'om the open ended survey questions revealed that ﬁeld instructors’
feedback plays a critical for the student teachers self-efﬁcacy judgments until the mid-
semester when the feedback tends to come from student performance. Proﬁles of interns
with the top and lowest teaching self—efﬁcacy scores indicated that those student teachers
in the lower group had a tendency to stay in the lower group for the whole semester, had

higher GPAs, reported less teaching time and were enrolled in the general education

preparation programs.

Copyright by
CARRIE ANNA COURTAD
2009

This is dedicated to my family:
My husband, Jim, this work could never have been completed without your inspiration
support and encouragement, I am truly blessed to have you by my side, I love you.
To my amazing sons, LC. and Jack, who have patiently waited while mommy worked
and never doubted that this was what I was meant to do.
I hope I will inspire you as you have me, I love you.
My parents, Faith and John Wooden, who always taught me I could do whatever I put my
mind to and always reminded me that just because my friends jump off a cliff doesn’t

mean I have to do the same.

ACKNOWLDGEMENTS

I would like to thank my advisor and chair Dr. Cynthia M. Okolo. Dr. Okolo provided me

with guidance and assistance through my whole doctoral career. I was not always an easy

student but due to her dedication, commitment, and extensive feedback multiple times, I

produced this body of work. I thank her for her assistance. Additionally I would like to

acknowledge:

My committee members: Drs. Emily C. Bouck, Troy V. Mariage, Cheryl L.
Rosaen, and Gary A. Troia for their support, suggestions and overall assistance
during the dissertation process.

The other professors with whom I have had the opportunity to learn and work and
who have shaped me during my doctoral career especially Drs. Carol Sue Englert,
Matthew K. Burns, Puyna Mishra, Michael Pressley, Susan Peters, Rand J. Spiro,
Janine L. Certo, and Steve Weiland.

The interns, instructors, ﬁeld instructors and cooperating teachers for their
participation and access especially, Edna F elmlee, Cindy Covell, Gina Garner,
Rebecca Norman and Shannon Sweeny.

My colleagues, who have pushed me to grow, supported me through program
milestones and have encouraged me through your friendship. I look forward to
collaborating with you in future projects.

My ﬁ'iends and family who supported me with their continued ﬁiendship,

understanding and aiding in life’s practical situations.

vi

TABLE OF CONTENTS

LIST OF TABLES ............................................................................................................. ix
LIST OF FIGURES ............................................................................................................ x
CHAPTER ONE INTRODUCTION .................................................................................. 1
Statement of Purpose ....................................................................................................... 5
Research Questions ......................................................................................................... 5
CHAPTER TWO REVIEW OF THE LITERATURE ....................................................... 7
Social Learning Theory ................................................................................................... 8
Attribution Theory ......................................................................................................... 10
Social Cognitive Theory ................................................................................................ 11
Integrated Framework for Teacher Self-Efﬁcacy ......................................................... 17
Frameworks for Previous Teacher Self-Efficacy Research .......................................... 19
Studies Using Locus of Control ................................................................................. 20
Combined Frameworks of Attribution and LRC ............................................... 22
Self-Efficacy Studies ................................................................................................. 23
Beneﬁts of High Teacher Self-Efficacy ........................................................................ 26
Malleability of Preservice Teacher Self-Efﬁcacy ......................................................... 32
Comparison Studies ....................................................................................................... 34
CHAPTER THREE METHOD ........................................................................................ 39
Participants .................................................................................................................... 39
Procedures ..................................................................................................................... 41
Instrumentation .............................................................................................................. 42
Data Analysis ................................................................................................................ 50
Teachers’ Self-Efficacy Scale .................................................................................... 50
Wave analysis ............................................................................................................ 54
Groups of High TSES Scores and Low TSES Scores ............................................... 54
Information Interns Used for Judgments ................................................................... 54
CHAPTER FOUR RESULTS .......................................................................................... 62
Differences between Special Education and General Education ............................... 62
Changes of Teaching Self-Efficacy ........................................................................... 64
Factors Inﬂuencing Teaching Self-Efficacy .............................................................. 64
Bias of Non-responders ............................................................................................. 65
Groups of High TSES Scores and Low TSES Scores ................................................... 67
Averages and Placement within High and Low groups ............................................. 67
Grade Point and Credit Hours .................................................................................... 70
Difﬁculties and effort in lesson presentation and planning ....................................... 75
Agreement .................................................................................................................. 77
CHAPTER FIVE DISCUSSION ...................................................................................... 78
Differences in Preparation Groups ............................................................................ 79

vii

Changes in Teaching Self-Efﬁcacy ........................................................................... 80

Factors Inﬂuencing Teaching Self-efﬁcacy ............................................................... 82
Proﬁles of those with High and Low Teaching Efﬁcacy .............................................. 83
Information Interns Considered for Perceptions of Success ......................................... 89

Agreement with Supervising Personnel ..................................................................... 93

Effort and Difﬁculty in Lesson Planning ................................................................... 94

Appendix A ..................................................................................................................... 100
Appendix B ..................................................................................................................... 105
Appendix C ..................................................................................................................... 11 1
References ....................................................................................................................... 113

viii

LIST OF TABLES

Table 3.1. Participant Response Rates ............................................................ 47
Table 3.2. Interns’ GPA and Class Composition ................................................ 49
Table 3.3. School Classiﬁcation of Placement .................................................. 49
Table 3.4. TSES scores of SPED Interns by Placement ........................................ 51
Table 3.5. ANOVA for SPED Interns ............................................................ 52
Table 4.1. Sum Means and Standard Deviations of All Interns ............................... 63
Table 4.2. Pairwise Comparisons Means of Sum Scores ....................................... 64
Table 4.3. Multiple Regression Chart ............................................................ 65
Table 4.4. Comparative Means of Low and High Groups ..................................... 68

ix

LIST OF FIGURES

Figure 2.1.Bandura’s conception reciprocal determinism .................................... 12
Figure 2.2. Tshcannen-Moran et al.’s model of the cyclical nature of teaching
self-efﬁcacy ......................................................................................... 18
Figure 4.1 . Percentage of interns (rounded) in low and high group at each wave ........ 69
Figure 4.2. GPA by high and low groups at each wave .................................................. 70
Figure 4.3. Credit hours by high and low groups at each wave ...................................... 71
Figure 4.4. Reported teaching time at each wave of high and low groups ................ 72
Figure 4.5. Perceived success of observation .................................................. 73
Figure 4.6. Information Interns’ used to make judgments about the performance ........ 74
Table 4.7. Interns’ perception of difficulty in lesson presentation .......................... 76
Figure 4.8. Perception of effort in preparing lesson ........................................... 76

CHAPTER ONE
INTRODUCTION
“Teaching was the hardest work I had ever done, and it remains the hardest work I have
done to date.” Ann Richards, 1992

Ann Richards was the Governor of Texas—a difficult job indeed—when she
made this statement. Governor Richards was a teacher for only a year in 1956, when
classrooms were much less diverse then they are now (Lewis, 2000). When preservice
teachers graduate today, they will encounter even more situations that increase the
complexity of teaching, including the wide diversity of learners in their class. As they
work to achieve professional certiﬁcation, they will ﬁnd that the number of children with
disabilities in general education classrooms has increased from previous years (U .S.
Department of Education, 2004). On average, students with disabilities currently receive
their education in the general education classroom approximately 80% of the time that
they are in school (U .S. Department of Education).

While attempting to fulﬁll the needs of diverse learners, new teachers will also
face the stringent accountability policies requiring their students to attain minimum test
scores, which sometimes serve as teachers’ only form of performance feedback. As they
struggle to serve their students, they will face the “conﬂict between the reality of their
role as teachers and the expectation that others place upon them in that role” (Brown &
Nagel, 2004, p. 36). Current laws such as the No Child Left Behind Act (NCLB; 2002)
and the Individuals with Disabilities Education Improvement Act (IDEA; 2004) add to
this challenge by imposing requirements that affect not only special educators and but

also general educators and all students.

As they work within the complexities of teaching, those who feel capable of
performing the tasks of teaching usually maintain more effective teaching behaviors.
General education teachers who perceive that their preparation program was strong and
consider themselves prepared feel better equipped to work with students with special
needs (Brownell & Pajares, 1999), are more amenable to including students with
disabilities in their classrooms, and have higher teaching self-eﬁ‘icacy (Chester &
Beaudin,l 996). Teaching self—efﬁcacy is the belief that one has the prerequisites to have
an effect on student outcomes (Bandura, 1977; Brownell & Pajares, 1999; Buell, 1999;
Dembo & Gibson, 1985; Leyser, 2002). While there are many relational studies
indicating high self-efﬁcacious teachers usually employ positive teaching behaviors,
teaching self-efficacy is not without it is critics. Over the years there has been debate
regarding the construct of self-efficacy, such as, how to measure teaching self-efficacy,
and which factors are encompassed in the concept of teaching self-efficacy (T Shannen-
Moran, Woolfolk, & Hoy, 1998). Chapter 2 provides an in-depth discussion of these
issues.

Gibson and Dembo (1984) found that teachers who have high teaching self-
efﬁcacy engage in instructional practices beneﬁcial to students such as giving support
and feedback to students and using ﬂexible grouping (Baker, Gersten, Haager, & Dingle,
2005; Stanovich & Jordan, 1998). Teachers with high self-efﬁcacy tend to persist in
aiding learners who struggle to keep pace with the general class whereas teachers with
low self-efficacy tend to give up on these students (Bender & Ukeje, 1989; Gibson &

Dembo). Pajares (1996) noted that teachers who have low self-efﬁcacy are more prone to

depression, have a narrow perspective on problem solving, and believe that their situation
is more challenging than do teachers with higher self-efficacy all of which foster stress.

High teaching self-efﬁcacy is not only positively related to good instructional
behaviors by teachers but also higher student achievement (Ashton & Webb, 1986).
Students taught by teachers with high teaching self-efﬁcacy tend to perform better in
academic subjects including math (Ashton & Webb) and reading (Armour et al., 1976).
Student taught by teachers with high teaching self-efﬁcacy tend to have a stronger belief
in their success (Midgley, F eldlaufer, & Ecclesl989), increased motivation (Ashton &
Webb, 1986), and increased self-direction (Rose & Medway, 1981).

Teachers with high teaching self-efﬁcacy are particularly effective with students
who may not do well in general education classrooms, such as low-achieving students
and students with disabilities. Teachers with high efﬁcacy persist at the task of teaching,
even when they encounter obstacles. Low-achieving students are more likely to believe in
their own abilities when taught by a teacher with high teaching self-efﬁcacy (Midgley et
a1, 1989). Teachers with high teaching self-efﬁcacy appear to provide more individual
instruction for students who are unable to learn at the pace of the entire class (Gibson &
Dembo, 1984), are less likely to refer students to special education programs, and are
more likely to accept responsibility for student learning (Soodak & Podell, 1994).

Teaching Self-Efﬁcacy of Preservice Teachers

The aforementioned studies explored the teaching self-efﬁcacy of practicing
teachers, or those that have more than three years experience in the classroom, often
referred to as in-service teachers. When one considers the teaching efﬁcacy of preservice

teachers, those who have not yet had classroom experience, it appears that the teaching

self-efﬁcacy does not remain constant. The self-efﬁcacy of preservice and novice
teachers (less than three years) has been found more malleable than that of in-service
teachers and experienced teachers (Henson, 2001; Tschannen-Moran, Woolfolk-Hey, &
Hoy, 1998; Woolfolk & Hoy, 1990). In one study, Hoy and Woolfolk (1990) found that
preservice teachers began their student teaching semester with a high and “unrealistic”
sense of self-efﬁcacy. In their study, Chester and Beaudin (1996) found that new teachers
who felt a high degree of congeniality within the school culture and personal inﬂuence on
the school environment experienced increases in self—efﬁcacy from the fall to spring
semester.
Teaching Self-Eﬂicacy of Special Educators

Research on the self-eﬂicacy of preservice special educators has included studies
of teaching self-efficacy when working with a speciﬁc type of student, such as limited
English proﬁciency (LEP) students (Paneque & Barbetta, 2006) or special education
students in rural schools (Brown, 2003). Few studies have compared the self-eﬁicacy of
preservice general educators to preservice special educators (Pugach, 2007). The results
of existing studies are difﬁcult to generalize to a larger population of preservice special
educators because of their small sample sizes. For example, Portrnan and Pontius (2000)
conducted research on only a small sample of special education preservice teachers (n =
6) but on a large sample of general education preservice teachers (n = 56). Other studies
are difﬁcult to generalize to the American educational system because they had been
conducted outside of the United States (Lyser, 2002).

Pugach (2005) discussed the dilemmas created by a lack of research on the

preparation of general educators working with students with disabilities and a shortage of

studies comparing preservice general educators to preservice special educators. This
investigation will attempt to ﬁll the gaps in the research identiﬁed Brownell and Pajares
(1999), who suggested that there is a great need to identify differences in special
education preservice preparation and general education preservice preparation and the

’9

“relationship of various program elements to general education teachers’ efﬁcacy beliefs
(p. 7).
Statement of Purpose

This study compared the teaching self-efﬁcacy of two different groups of
preservice teachers (hereafter referred to as interns) as they completed 16 weeks of
student teaching. Interns from two different programs, the general education and special
education, were the target population. This study examined the teaching self-efﬁcacy of
the interns, differences in teaching self-efﬁcacy between the two groups of interns, and
changes in the teaching self-efﬁcacy of the interns during a 16-week period. It also
examined other factors that inﬂuence teaching self-efﬁcacy, such as feedback received
ﬁom supervision personnel, the demographics of the classroom, the school population,
and the intern.

Research Questions
The following research questions guided the study:
1. What is the teaching self-efficacy of the elementary interns in general education and
special education?
a. In what way does the teaching self-efﬁcacy differ between general education
interns and special education interns?

2. How does the teaching self-efﬁcacy of interns change over a semester?

a. How does the teaching self—efﬁcacy change between general education interns?

b. How does the teaching self-efﬁcacy change among special education interns?

c. Is there a difference in the change across teaching self-efﬁcacy of these two

groups?

3. How do certain situational factors inﬂuence the judgment of the interns’ self efﬁcacy?

Consideration of these factors included; interns grade point average, class size in

the intem’s placement classroom, the number of students with disabilities in a

class, the time of administration of the measurement scale in the semester, they

classiﬁcation of the school, and the amount of reported teaching time by the
intern.

Four additional chapters follow this document. Chapter 2, which provides a
review of the literature that helped guide the development of the study, describes the
theoretical ﬁ'amework of self—efﬁcacy, teaching self-efficacy, and preservice teacher self-
efﬁcacy. Chapter 3 describes the research design of the study, including the participants,
data sources, and analytical methods for examining the data. Chapter 4 includes the

results of the study and Chapter 5 contains the discussion and implications of the study.

CHAPTER TWO
REVIEW OF THE LITERATURE

Bandura (1997) deﬁned self-eﬂicacy as “people's beliefs about their capabilities to
produce designated levels of performance that exercise inﬂuence over events that affect
their lives” (p. 3). Teaching self-efﬁcacy refers to the extent to which teachers believe
their actions will have a positive effect on student outcomes. As a construct, self-efficacy,
which has its roots in social learning, social cognitive theories and attribution theory, has
been studied for approximately 3 decades. Self-efﬁcacy scholars generally use one of
three conceptual frameworks when situating self-efﬁcacy (Knoblauch, & Hoy, 2008;
Woolfolk & Hoy, 1990). This chapter discusses the history of social learning and social
cognitive theories as they relate to self-efﬁcacy and the importance of examining the
impact of teacher self-efﬁcacy on teaching before proposing a study that will further
investigate teaching self-efﬁcacy.
Conceptually Situaling Self-eﬂicacy

Self-efﬁcacy is often difﬁcult to separate from other belief constructs, such as
motivation, attribution of success and failure, expectancy value, and goal setting (Pajares,
1996; Tschannen-Moran, Hoy, & Hoy, 1998). Because of this difﬁculty, there is an
overlap between self-efﬁcacy and other theories of human attainment and motivation.
However, this should not imply that self-efﬁcacy should be neglected as an area of study
because “self-efﬁcacy beliefs are strong determinants and predictors of the level of
accomplishment that individuals ﬁnally attain” (Pajares, p. 545). Pajares explained that
although individual self-perception of competence, motivation, and behavior are core

components of various expectancy theories, self-efﬁcacy is different from other

conceptual ﬁameworks because it is more precisely deﬁned and related to task situations,
and therefore more speciﬁc than generic self-perception and motivation.

A plethora of studies has investigated self-efﬁcacy in teaching (Armor et al.,
1976; Gibson & Dembo, 1984; Henson, 2001; Hoy & Woolfolk, 1990; Simmons et al.,
1998; Tschannen-Moran et al., 1998, 2001). Much of the criticism surrounding the
construct of self-efficacy has arisen from researchers neglecting to situate self-efﬁcacy
generally or teacher self-efﬁcacy speciﬁcally within a proper theoretical framework (1on
& Woolfolk; Pajares, 1996; Tschannen-Moran et al., 1998). For this reason, the following
section discusses three of the most common theoretical ﬁ'ameworks, social learning
theory, attribution theory and social cognitive theory and the conceptual framework that
will serve as the foundation for this investigation.

Social Learning Theory

Social learning theory emerged “out of the behaviorist tradition ﬁ'om which it
borrows a central premise, the principle that human action is a response to environmental
stimuli” (Howell, 2005, p. 162). Social learning theory attempts to maintain the scientiﬁc
rigor from which behaviorism beneﬁted as it examines the human behaviors that
behaviorism has traditionally ignored, such as individual internal thought (Paj ares &
Schunk, 2002). In his seminal Social Learning and Clinical Psychology, Rotter (1954)
explained that social learning theory assumes that the study of personality must focus
upon the study of the environment and behavior. Rotter’s assumption was backed by
Heider (195 8) in his equally inﬂuential The Psychology of Interpersonal Relations. These
social learning theorists asserted that the study of individual internal thought was

essential to the understanding of motivation and its relationship to success and failure.

Their continued research into the conceptual framework of social learning theory led
them to develop the locus of control theory and attribution theory.

Locus of Control

Ross (1992) traced the concept of teacher self-efﬁcacy back to Rotter’s (1954)
locus of control theory, from which it developed. Rotter (1990) explained that according
to locus of control theory, sometimes referred to as locus of control of reinforcement
(LCR) theory,

the reinforcement or outcome of behavior is contingent on [a person’s]

own behavior or personal characteristics versus the degree to which a

person expects that the reinforcement or outcome is a function of chance,

luck, or fate or under the control of others or is unpredictable. (p. 489)

The foundation of LCR theory is that behavior is reinforced through contingencies that
lead individuals to maintain beliefs about what causes the reinforcement of behavior. In
turn, these contingencies develop individual belief and shape the attitude that the
individual chooses to adopt.

Rotter incorporated aspects of expectancy-value theory, and argued that the
strength of motivation is determined by the value of the reinforcement one receives and
the expectancy of achieving a certain goal, into the framework of LCR theory (W einer,
1990). Rotter proposed that there is a general expectancy of control of reinforcement
based upon how individuals attribute their success or failure. These attributions could be
termed internal, as are attributions to individual effort or ability, or external, such as are

attributions to environmental factors (Ross, 1994). As regards teachers, LCR theory

explains how teachers attribute the success and failme of their performance and that of
their student’s performance.
Attribution Theory

Attribution theory’s roots are social psychology and attempts to explain social
perception, phenomenal causality, and stresses the interaction of perceptual and cognitive
processes in attribution (Weary, Stanley, & Harvey, 1989). An attribution is an inference
about why an event occurred or about a person’s disposition or other psychological states
(Weary et al., 1989, p. 3). However, there is no monolithic philosophy or body of work in
attribution theory that ties the work together (Weary et al., 1989) and therefore makes it
diﬂicult to situate the theory neatly into a larger framework of social learning theory or
social cognitive theory but still has a visible part in self—efﬁcacy studies.

Inﬂuenced by Rotter and Heider, Weiner’s View of (1985, 1990) attribution
theory, particularly his notion that individuals emphasize other properties of causality in
addition to locus when explaining failure or success. Weiner expanded Rotter’s work to
identify three dimensions of attribution theory: locus of causality, stability, and
controllability. Locus of causality is similar to LCR in that it identiﬁes whether success
or failure is attributed to factors internal or external to the self (W einer, 1990). Stability
describes how internal and external causal factors, such as mood and fatigue, can change
from moment to moment. Controllability describes how attributions are impacted by the
perception that outcomes are within individual control, such as the effort put forth to
accomplish a task, or not within individual control, such as aptitude.

I Weiner’s early work in attribution theory (1985, 1990) posited that four factors

inﬂuence motivation: the ability of the learner, the difﬁculty of the task, the effort the

10

learner is willing to invest in the task, and luck. Each of these factors is viewed in
conjunction with the three dimensions of attribution of success or failure. Ability is
considered an internal, stable factor over which the learner does not always have control.
Task difﬁculty is considered an external and stable factor beyond the control of the
learner whereas effort, an internal factor, and luck, an external factor, are both unstable.
Attribution theory asserts that individuals have great control over effort but very little
control over luck and that individuals are highly likely to make attributions in such a way
that allows them to maintain a positive self-image.

Students who are perceived as having expended effort are rewarded more by
teachers when they succeed and punished less when they fail than are students perceived
as having expended little effort (Weiner, 1992). Individual perceptions and attributions of
success and/or failure determine the amount of effort the individual applies in the future.
Weiner (1990) speculated that a motivation sequence is activated after an individual
interprets an outcome as a success or failure whereby the individual begins a causal
search to determine why it had occurred. Various conditions and antecedents aid the
individual in interpreting the causal attributions.

Social Cognitive Theory

The third conceptual framework in which to situate self-efﬁcacy is social
cognitive theory. In studies of self-efﬁcacy, this conceptual framework is most commonly
used. Bandura (1989) developed social cognitive theory to further address and explain
human thought and motivation. Bandura was not satisﬁed with social learning theory
because it regarded human behavior as guided by one-sided determinism, implying

human cognition did not affect behavior. Bandura (1997) explained that agency, a trait

11

that only humans possess, induces individuals to make decisions based upon their beliefs
about their abilities and examine the outcomes of their efforts to determine what they will
attend to or what course of action they will pursue. His ﬁ'amework consists of a triadic
model of reciprocal determinism that Pajares (1996) described as consisting of “(a)
personal factors in the form of cognition, affect, and biological events; (b) behavior; and
(c) environmental inﬂuences create interactions that result in a triadic reciprocally” (p.
544).

Figure 2.1. Bandura's conception of reciprocal determinism

Model of
Re<=llﬂ1§¢=§I Motivating
Determmrsm beliefs,
perceptions,
values, 1
' emotions, "
meanings

 

.9, V
Environmental factors Behavior

(reinforcers, punishers) ‘

3‘5.

I'I
.-

From Longman ’s Visuals for Learning.
Bandura (1997) explained that reciprocal determinism does not imply that all factors or
points are of equal strength but rather that their inﬂuence varies based upon the

circumstances. As a means of explaining the complexity of and motivations behind

12

human behavior, reciprocal determinism was the basis for Bandura’s development of the
concept of self-efﬁcacy.

Self-efﬁcacy beliefs determine how individuals feel, think, motivate themselves,
and behave (Pajares, 1997). Bandura’s (1997) conception of teaching self-eﬂicacy, which
he deﬁned as the judgment of one’s ability to complete future actions necessary to the
task of teaching, is based upon his general conception of self-efficacy. Speciﬁcally, he
described teaching self-efﬁcacy as a teacher’s belief that he or she has the capacity to
organize and execute the course of action required to produce student learning.

Sources of Self-Efﬁcacy

Bandura (1986) proposed that self-efﬁcacy is informed through four sources:
mastery experiences, vicarious experiences and modeling, physiological and emotional
arousal, and social persuasion. Mastery experiences, which result from successfully
performing tasks similar to the task in question, are indicators of the capacity to complete
the task. The perception that similar performances or experiences had been successful in
the past increases efﬁcacy beliefs, and is therefore the most powerful source informing
self-efﬁcacy (Bandura, 1997). However, not all mastery experiences encourage self-
efﬁcacy, especially if the individual perceives the performance as a failure, only achieves
success late in the experience or with much external assistance, or perceives the task as
unimportant (T schannen—Moran et al., 1998). For teachers, acts of teaching serve as
mastery experiences. As teachers gain experience, they develop beliefs about their ability
to organize and complete teaching tasks so that their students can learn.

Vicarious experiences are the experiences gained by watching another person who

would be modeling the behavior. Vicarious experience informs self-efﬁcacy by

13

communicating capability through viewing others or comparing others to oneself
(Bandura, 1986). Vicarious experiences include such events as watching other teachers
teach, either as a student in the classroom, or viewing teachers in college coursework, or
as comparing oneself to other teachers (Tshannen-Moran et al., 1998). Vicarious
experiences increase self-efﬁcacy as a person views someone successful at given task and
then compares himself or herself to that person. Vicarious experiences have a more
powerful impact when individuals observe others who are similar to them modeling an
action or behavior (Bandura, 1997 ).

Physiological and emotional arousal result in physical symptoms that inform self-
efﬁcacy. Speciﬁcally, the manner in which individuals interpret the physical signs of
stress such as sweaty palms or nausea is related to self-efﬁcacy; those who feel that these
physical signs are not associated with ability possess high self-efﬁcacy (Bandura, 1986).
When these sources are positively experienced in conjunction with a mastery experience,
they strengthen the impact of the experience. The feeling of “butterﬂies” in the stomach
can be either positive or negative, depending upon the circumstances and the individual’s
history and overall arousal (Bandura, 1997).

Social persuasion is a source of self-efﬁcacy in that others may be able to
convince an individual that he or she is competent to complete a task. Although possibly
powerful, it is not a consistent means of increasing self-efﬁcacy, especially if the
feedback provided is not realistic (Bandura, 1986). If the feedback in this source is
negative or unrealistic, it will decrease self-efﬁcacy. It is easier to decrease self-efﬁcacy

using this source than use it to achieve lasting increases in self-efﬁcacy. For a new

14

teacher, social persuasion often takes the form of supervisors or professors conveying
their judgment of the new teacher’s ability.

Interpretation of the Sources through Processes

The above sources of self-efﬁcacy are not directly transformed into judgments of
competence. Individuals interpret the results of events, and these interpretations provide
the information on which judgments are based. The types of information people attend to
and use to make efficacy judgments, and the rules they employ for weighting and
integrating them, form the basis for such interpretations (Bandura, 1994). The four types
of processes for the interpretations that govern Bandura’s (1994) self-efficacy theory are:
cognitive, motivational, aﬁrective, and selective processes. Cognitive processes, deﬁned
as thoughts that can enhance or undermine self-efﬁcacy, are usually embodied in actions
such as goal setting or conceptions such as anticipatory performance. Speciﬁcally,
cognitive processes are those internal actions by which individuals gain and organize the
use of information. In the context of teaching, Tsharrnen-Moran et a1. (1998) explained,
“Cognitive processing determines how the sources of information will be weighed and
how they will inﬂuence the analysis of teaching task and personal teaching competence”
(p. 230). Individuals’ beliefs in their capabilities inﬂuences their goal setting; the stronger
their perceived self-efﬁcacy, the higher the goals they set for themselves and the ﬁrmer
their commitment to their goals (Bandura, 1994). This relationship suggests that teachers
with higher self-efficacy set higher goals for themselves and their students and persist at
these goals, even when conﬁonted with adversity or initial failure.

Motivational processes address self-motivation and the regulators of behavior.

Motivation, which is the result of forces that activate and direct behavior, is reﬂected in

15

the choice of course of action and the intensity and persistence of effort (Bandura, 1997).
Motivation links self-efﬁcacy theory to three other cognitive theories: attribution theory,
expectancy value theory, and goal theory (Bandura, 1994). Motivation is linked to
attribution theory because both describe how individuals assign failure or success through
such factors as effort or ability (Ross, 1994). Individuals with higher self-efﬁcacy will
attribute their successes to insufﬁcient effort as opposed to low ability. Expectancy value
is linked to motivation because both describe how individual beliefs inﬂuence a desired
outcome. Goal theory is linked to motivation because it asserts that motivation is related
to the outcome of present as opposed to future goals. Therefore, individuals adjust the
goal according to their performance.

Under Bandura’s motivation process, attribution theory provides information that
inﬂuences the goals that individuals set, the amount of effort they dedicate to those goals,
and how long they persist in achieving those goals in the face of difﬁculties (Bandura,
1994). Individuals with lower self-efﬁcacy either readjust or give up their goal when they
encormter failure. The motivational process suggests that teachers with high self-efﬁcacy
are more willing to take responsibility for student achievement; they believe that speciﬁc
teaching strategies will produce the desired outcome and work to achieve small,
attainable goals (Ross, 1994).

Affective processes regulate emotional states and produce emotional reactions. As
they relate to efﬁcacy, they are, along with the aforementioned motivation process, an
individual’s belief of how well he or she can cope with stress and depression arising from

difﬁcult situations (Bandura, 1994). These processes, which relate to stress and the ability

l6

to cope with that stress, are based upon the assumption that the higher a teacher’s self-
efﬁcacy, the stronger his or her belief that he or she can cope with stress.

Selective processes is the theory that one makes selections in which they feel they
have the capability to achieve. The conception of selective processes is based upon the
assumption that those who have high self-efﬁcacy in a particular area are more likely to
seek challenges or experiences in that area than in areas in which they do not have high
self-efﬁcacy. Just as perceptions of self-efﬁcacy result in selective processes that shape
the course of one’s life by inﬂuencing the activities and environments one chooses,
perceptions of self-efﬁcacy result in selective processes that determine the subject or
grade that teachers choose to teach (Bandura, 1994, Tschannen-Moran et al., 1998).

Integrated Framework for Teacher Self-Efﬁcacy

Tschannen—Moran et al. (1998) proposed what they termed an “integrated model
of teacher eﬂicacy” (p. 227) that unites the theoretical frameworks previously discussed
with new conceptual dimensions in the context and consideration of teacher tasks. Their
work led them to further deﬁne teaching efﬁcacy as “the teacher’s belief in his or her
capability to organize and execute course of action required to successfully accomplish a
speciﬁc teaching task in a particular context” (p. 233). The integrated model posits that
cognitive processes strongly inﬂuence how teachers attend to the information they
receive through the four sources of self-efﬁcacy and that how they view sources of
efﬁcacy depends upon the types of attributions they make about their performance. In
addition, when judging their personal competence of ability, they regard how it relates to

a particular task.

17

Tschannen—Moran et al. (1998) described teaching efficacy as cyclical in nature
and likely to heavily inﬂuence teachers’ perceptions of their ability to achieve future
outcomes. Teachers’ perception of their performance creates a new mastery experience
that provides new information that contributes to their analysis of the teaching task and
their self-perception of teaching competence, inﬂuencing how they attribute and attend to
the mastery experience (see Figure 2.2).

Figure 2.2. Tschannen—Moran et al.’s model of the cyclical nature of teaching self-

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

efﬁcacy.
Source of Efﬁcacy .
Information Auk/S's 0‘
Teaching Task
Verbal Persuasion
Vicarious Experience Teacher
3 Efﬁcacy
Physiological Arousal I ssmen t
Mastery Experience of Personal
Teaching
Competence
New Sources of
Efﬁcacy Information
V
Consequences of
Teacher Efficacy
Performance ( JOﬂlS, effort, persistence,
etc.

 

 

 

 

 

 

From Teacher Efﬁcacy: Its Meaning and Measure by Tschannen-Moran et al., 1998, p.
228.

The four sources of efficacy and the manner in which teachers interprets the
performances all complete a picture of teachers’ self-efficacy. Over time, perceptions of

competency stabilize into a set of past and future efﬁcacy beliefs. For the purpose of this

18

study, teacher self-efﬁcacy will be situated within the framework of the integrated model
of teacher self-efﬁcacy developed by Tschannen-Moran et al.

This model brings together the aforementioned theories into one conceptual
ﬁ‘amework for viewing teachers’ self—efﬁcacy. This model includes the major inﬂuences
of the sources of self-efﬁcacy posed by Bandura (1986, 1997). This model addresses the
speciﬁcity of teaching context and tasks unlike previous models and addresses the idea
that one must assess their strengths and weakness as related to the task. The
interpretations of the sources of self-efﬁcacy are also addressed in this model through
cognitive processes. Cognitive processes are a regulatory process in which “individuals
attend to factors that might have been overlooked or to weight the importance of factors
differently” (T schannen-Moran et al., 1998, p. 231). This model allows teachers to
reﬂect on their teaching experience and make attributions to their success or failure
through the self-perception of teaching competence “while the judgment concerning the
resources and constraints in a particular teaching context is the analysis of the teaching
task” (Tschannen-Moran et al., 1998, p. 231).

Frameworks for Previous Teacher Self-Efﬁcacy Research

Of the aforementioned theoretical ﬁameworks of teacher self-efficacy, the
majority of researchers (Bender & Ukeje, 1989; Brownell, & Pajares, 1999; Gibson &
Dembo, 1984; Hoy & Woolfolk, 1990) use Bandura’s (1977) construct of self-efﬁcacy as
the foundation of their research (Ross, 1994). However, several prominent researchers
work within an attribution or locus of control framework for understanding teacher self-
efﬁcacy. Guskey (1981; Guskey & Passaro, 1994) equated teacher self-efﬁcacy with a

willingness to take responsibility for student success and failure. Other researchers have

19

attempted to incorporate the two theoretical frameworks in their research on teacher self-
efficacy. The majority of teacher self-efficacy studies are measures with a self-
administered questionnaire and are mostly correlational thus proving to be difﬁcult in
assuring the direction of inﬂuence of teacher self—efficacy (Ross, 1994).

Studies Using Locus of Control

In 1976, the RAND Corporation commissioned a study of a reading program for
minority elementary schools (n=20) in Los Angeles (Armor et al., 1976). This study,
which asked teachers (n=83) two questions regarding their perceptions of the inﬂuence
that they had on student motivation and learning, was the ﬁrst attempt to measure
teaching efﬁcacy and evaluate teacher perceptions of internal or external inﬂuences on
students (Ross, 1994; Tschannen-Moran et al., 2001). Assuming that student motivation
and achievement are signiﬁcant reinforcements for teacher behavior, the researchers of
the RAND study attempted to determine whether teachers’ control of reinforcement lay
within themselves or the environment (T schannen-Moran et al., 1998). By summing the
scores of the two questions, the researchers obtained a participant teaching efficacy score
that they found to be a signiﬁcant positive predictor of reading achievement for minority
students (a = .81 t = 2.54 p. = .05) and a strong predictor of the continuation of
instructional programs after formal funding had been depleted (Ashton, Olejnik, Crocker,
& McAuliffe, 1982).

The ﬁrst question in the RAND study, which assessed external factors in
motivation, asked the teachers whether they agreed or disagreed with the statement,
“When it comes right down to it, a teacher really can’t do much because most of a

student’s motivation and performance depends on his or her home environment ” The

20

second question, which measured the teachers’ belief in their ability to overcome
situations that make it difﬁcult for students to learn (i.e., their internal motivation), asked
teachers to agree or disagree with the statement, “If I try really hard I can get through to
even the most difficult or unmotivated students.” These items were based on Rotter’s
locus of control theory (Ashton et al., 1982; Tshcannen-Moran et al., 2001 ).
Studies Situated in Attribution Theory

In the early 19805, several researchers (Guskey 1982, 1988; Rose & Medway,
1981) used attribution as a ﬁamework to conceptualize teacher efﬁcacy as teachers’
belief that they have the capacity to affect student performance (Guskey, 1987). Guskey
(1981) developed the responsibility for student achievement (RSA) scale based on the
four attributions for success or failure in Weiner’s (1979) attribution theory: ability,
eﬂort, task, and luck. The RSA was administered to 215 elementary and secondary school
teachers. Two common factorial model accounts for 60.9% of the variance in the RSA
item responses. Guskey concluded that the RSA was assessing two different factors and
closely related to distinction between responsibility for student success (R+) and
responsibility for student failure (R-) (1981). The RSA score indicated a strong positive
correlation (an r between .72 and .81) between overall responsibility and positive
responsibility but a much weaker positive correlation (r = .20) between student failure
and efﬁcacy. These results suggest that positive student performance has a stronger
impact on a teachers’ efficacy than negative student performance, especially at the group
level as opposed to a single student. Teachers were also more conﬁdent in their ability to

achieve positive outcomes then prevent negatives outcomes.

21

Combined Frameworks of Attribution and LRC

Rose and Medway (1981) situated their study of the manner by which teachers’
casual perceptions inﬂuence the achievement of their students in both Rotter’s LCR
theory and attribution theory. To measure teacher locus of control (TLC), the authors
developed the TLC scale, which used forced choice items to assess teachers’ perception
of control in the classroom. The TLC contained 14 items that described negative or
failure situations and 14 items that described positive or success situations. The TLC
generated separate scores for internal responsibility for student success (1+) and failure
(I-).

Rose and Medway (1981) found that teachers’ use of discipline, accountability in
holding students responsible for performance, and engagement in instructional activity
was correlated with TLC. They administered the TLC and Rotter’s I-E scale, which
measures the individual differences in causal perceptions, to 89 female fourth grade
teachers from a 50,000-student school district. Based on the TLC scale, they found that
highly internal teachers for student success gave fewer disciplinary commands as
observed by independent raters during four separation occasions during a math class (r =
—.68, p < .02), had a lower rate of inappropriate student behavior (r = —.49, p < .09), and
maintained classrooms with a higher rate of student self-direction (r = .49, p < .01). Their
ﬁndings led the authors to conclude that teachers who scored high in internal
responsibility for student success used better educational practices than did teachers
scoring high in external responsibility for student success.

In a similar study, Greenwood, Olejnik, and Parkay (1990) surveyed 321 teachers

in 18 schools to examine the relationship between self-efficacy and locus of control. In

22

addition to administering the TLC scale, the two teaching-efﬁcacy items on the RAND
study were also administered. The authors categorized teacher self-efficacy beliefs into
one of four patterns: I can motivate students and other teachers can motivate students, I
cannot motivate students and other teachers cannot motivate students, other teachers can
motivate students but I cannot motivate students, or I can motivate students but other
teachers cannot motivate students. Their results indicated that teachers who believed that
they could motivate students and other teachers can motivate students scored higher in
TLC than teachers who believed that they could not motivate nor could other teacher
motivate (D 2= .518, F = 9.314,p < .0002). The authors concluded that teachers with high
teaching efﬁcacy tended to score higher in internal locus of control, indicating that
teachers who felt a high sense of efﬁcacy also felt a strong sense of internal locus of
control toward the act of teaching.
Self-Eﬁ‘icacy Studies

Researchers who have based the conceptual underpinning of their studies upon
Bandura’s theory have identiﬁed two types of teaching self-efﬁcacy (Ross, 1994).
Although research has consistently identiﬁed these two factors in the construct of
teaching self-efﬁcacy, researchers have disagreed over their meaning (Tschannen-Moran
et al., 1998). The majority of teacher efficacy studies conducted over the past 3 decades
have used Gibson and Dembo’s (1984) teacher eﬂicacy scale (TES), which is based on
Bandura’s construct of self-efﬁcacy (Henson, Krogan & Vacha-Haas, 2001; Ross, 1994;
Woolfolk & Hoy, 1990). The TES has 2 subscales, personal teaching efficacy (PTE) and
general teaching eﬁicacy (GTE). Although widely accepted as a research tool, there has

been some criticism of this scale.

23

Personal teaching eﬂicacy (PTE) is a teacher’s belief in his or her personal ability
to overcome factors that make student learning difficult. On the other hand, general
teaching eﬁ‘icacy (GTE) is a teacher’s overall belief in the power of teaching in general;
in other words, his or her belief that teachers in general have an impact on student
achievement in spite of external inﬂuences such as motivation and home environment
(Dembo & Gibson, 1985; Henson et al., 2001; Tschannen-Moran et al., 1998, 2001;
Woolfolk & Hoy, 1990).

Researchers agree that PTE is closely related to Bandura’s theory of self-efﬁcacy
because it addresses the manner by which an individual’s feeling of competence as a
teacher is conveyed in his or her belief that he or she will be able to perform actions that
lead to student learning (Tschannen-Moran et al., 2001). However, researchers disagree
over the conceptual underpinnings of GTE. Whereas Emmer and Hickman (1990)
speculated that GTE is actually a construct addressing external factors, others (Ashton &
Webb, 1986; Gibson & Dembo, 1984; Riggs & Enochs, 1990; Soodak & Podell, 1996)
categorized GTE as an outcome expectancy, a belief that an action will lead to learning.
In personal communication with Bandura, Woolfolk and Hoy (1990) disagreed with the
translation of the GTE as outcome expectancy construct (1990). Bandura argued that
“outcome expectation is a judgment of the likely consequence of an action, whereas
efficacy expectation is the judgment about ability to perform an action” (as cited in
Woolfolk & Hoy, 1990, p. 82).

Bandura (1977) suggested that because outcome expectation and eﬂicacy
expectation are both inﬂuenced by motivation, the two expectations are interrelated but

not the same. Bandura’s theory of self-efﬁcacy posits that efficacy expectation concerns

24

the ability to organize the actions necessary to accomplish a speciﬁc task at a desired
level whereas outcome expectation concerns the consequences of accomplishing a given
task at the desired level (Tschannen—Moran et al., 1998). Gibson and Dembo (1984)
agreed that outcome and efficacy are different; although individuals may believe that
certain behaviors will produce certain outcomes in general, they may not initiate those
behaviors or persevere if they initiate those behaviors if they do not believe that they can
produce those behaviors.

Gibson and Dembo (1984) conducted a three-phase study in which they measured
teacher self-efﬁcacy using a self-created scale; compared their measurements to other
measurements of self-efficacy; and conducted classroom observations to review the
behaviors of teachers in terms of academic focus, feedback, and persistence in failure
situations. After surveying 208 teachers using their scale, the authors identiﬁed 2 factors
that they labeled personal teaching eﬂicacy (PTE) and general teaching eﬁ‘icacy (GTE).
They found an alpha coefficient of .78 for PTE, an alpha coefficient of .75 for GTE, and
a total coefﬁcient of .79 for all 16 items. In their discussion of the study, they asserted
that the two factors are applicable to Bandura’s constructs of self-efﬁcacy.

During the second phase of their study, Gibson and Dembo (1984) administered
an open-ended and close-ended assessment of teacher self-efficacy to 55 teachers. Then
the authors picked a subset of teacher and measured their verbal ability and ﬂexibility
through the Teacher Aptitude battery of the Beginning Teacher Evaluation Study, Phase2
(Ekstrom, 1975 as cited in Gibson & Dembo). They found a positive correlation (r = .42,
p < .001) between efficacy and combined scores of verbal ability and ﬂexibility. For the

last phase of their study, a follow-up study of a limited sample of teachers (n = 8), they

25

further studied 4 teachers who had scored high on the efﬁcacy scale and 4 teachers who
had scored low during the ﬁrst phase of the study. In classroom observations, they
deﬁned persistence by the ratio of feedback interaction in which a teacher repeated the
question, provided a clue, or asked a new question following an incorrect student
response. They found that teachers with high teaching self-efficacy tend to persist in
providing necessary support for learners who are not keeping pace with the other students
whereas teachers with low teaching self-efficacy tend to give up on these students.
Gibson and Dembo also found that teachers who had low teaching self-efficacy were
more likely to provide feedback in the form of criticism to students who answered
incorrectly [t (6) = 5.1 7, p < .01].
Beneﬁts of High Teacher Self-Efﬁcacy

Over the past 30 years, researchers have conducted many studies in their efforts to
understand the inﬂuence of self-efﬁcacy. Their studies have investigated efficacy in such
academic subjects as math (Chen & Zimmerman, 2007), science (Dalgety, & C011, 2006),
and literacy (Massengill-Shaw, Dvorak, & Bates, 2007), as well as in the teaching of
science (Smolleck, Zembal-Saul, & Yoder, 2006) and the self-efﬁcacy of students with
disabilities (Klassen, & Lynch, 2007). Regardless of the conceptual underpinning of their
research, they have found a high correlation between teacher self—efﬁcacy and student
outcomes. Teachers with high self-efficacy tend to work longer with students to assist
them in learning material (Ashton & Webb, 1986), engage in positive and effective
instructional practices (Bender & Ukej e, 1989), and enhance student motivation (Rose &

Medway, 1981), all of which tend to lead to greater student achievement.

26

In their multiphase study of teacher self-efﬁcacy, Ashton and Webb (1986)
administered six different process product measures to 48 basic skills teachers at the high
school level and observed each participant in the classroom at least twice within a period
of 2 months. They found a signiﬁcant relationship between math teacher self-efficacy and
student math achievement (r = .78, p < .003) and a signiﬁcant relationship between
communication teacher self-efficacy and student language skills scores (r = .83, p < .02).
They also found that teachers with a stronger belief in teaching self-efﬁcacy were more
likely to hold students responsible for performance. Also, teachers who had higher GTE
were more likely to maintain a warmer classroom environment whereas teachers who had
lower GTE had a tendency to use harsher methods of control in the classroom (Ashton &
Webb, 1986).

Sinrilar studies have also found a positive correlation between teacher use of
effective instructional practices and high personal teaching efficacy as measured by the
TSE scale. Bender and Ukeje (1989) srn'veyed 50 teachers using the TSE scale and the
Bender Classroom Structure Questionnaire (BCSQ), a “Likert-type scale listing research-
proven instructional strategies” (p. 25). They found that general educators who had
higher PTE were more likely to engage in successﬁrl instructional strategies (r = .59)
when working with students with disabilities than were their counterparts with lower PTE
(r = —.28). This ﬁnding indicates that general education teachers with higher personal
teaching self-efﬁcacy tend to use research-based instructional strategies that are difﬁcult
but effective and to produce positive outcomes for all students (Starrovich & Jordan,

1998).

27

Several studies have indicated that teachers with higher teacher self-efﬁcacy tend
to accept responsibility for students with disabilities. In one study, Soodak and Podell
(1994) instructed 110 elementary teachers to read a case study about a male student 2
years below grade level and living in a single—parent household answer. They then asked
the teachers open-ended questions about how to teach this student before administering
the TES to measure their efficacy. They found that teachers who had higher PTE were
more likely to suggest using effective classroom-based effective strategies, indicating that
they felt a responsibility to help the student. They also found that teachers with lower
PTE had a tendency of not considering the general education classroom as an appropriate
placement for underperforrning students from a lower social economic status.

Many studies have found robust correlations between teacher self-efficacy and
use of effective teaching practices (Ross, 1994), which in turn is very beneﬁcial to
student with disabilities. Landrum and Kaufman (1992) found that colleagues of general
education teachers with high self-efﬁcacy judged them as more competent when working
with students with disabilities. Past studies have shown that teachers with high self-
efﬁcacy appear to sustain instruction longer with students who are unable to move at the
pace of the entire class (Gibson & Dembo, 1984; Massengill-Shaw, Dvorak, & Bates,
2007)

In 1996, Minke, Bear, Deemer, and Griffin compared the PTE of general
educators participating in coteaching classrooms, special educators participating in
coteaching classrooms, and general educators not participating in coteaching classrooms.
They found that general educators participating in coteaching classrooms had higher PTE

than did general educators not participating in coteaching classrooms and PTE similar to

28

. that of special educators. The general educators not participating in the coteaching
classrooms rated the general educators participating in the coteaching classrooms as more
effective in working with students with disabilities. In addition, the general educators not
participating in the coteaching classrooms scored lower in their belief in the feasibility of
offering modiﬁcation to students with disabilities and reported using fewer adaptations.
Although this study, as with most of the correlation studies, was unable to determine the
causal direction of these scores, it is assumed that access to information and collaboration
with a special education teacher could lead a general education teacher to higher PTE. It
is also possible that teachers who tend to exhibit high self-efﬁcacy traits also possess
traits seen as beneﬁcial to students with disabilities, and are therefore more likely to be
assigned to work in coteaching classrooms.

A teacher’s teaching self-efﬁcacy appears to have an impact on his or her
students’ self-efficacy. In 1989, Midgely, Feldlaufer, and Eccles measured the self-
efficacy of over 1,300 students and their teachers teaching self-efficacy as the students
transitioned ﬁom sixth to seventh grade. The researchers found that students who had a
6m-grade teacher with a higher teaching efficacy score had higher expectations of how
well they would do in seventh grade whereas students who had 6th-grade teachers with a
lower teaching self-efﬁcacy score had lower expectations of how well they would do in
seventh grade. These ﬁndings, which were more robust for low-achieving students,
indicate that teacher self-efficacy can affect students’ beliefs regarding their achievement,
especially students who have a history of low achievement and students with disabilities.

A large-scale effort to review the preparation of special educators included a

measure of a special educators teaching self-efficacy. Researchers, based on responses to

29

national surveys found that special education teachers tend to report higher teaching self-
efﬁcacy for certain teaching tasks. The Study of Personnel Needs in Special Education
(SPeNSE), was conducted to provide nationally representative data on teachers who work
with students with disabilities (n=8,061). Carlson, Brauen, Klein, Schroll, and Willig—
Westat (2002) found that special educators reported higher self-efﬁcacy, especially in the
area of planning effective lessons and monitoring students and less teaching self-efﬁcacy
in accommodating culturally and linguistically diverse students’ learning needs, using
professional literature to address problems, and using technology in instruction. Another
interesting ﬁnding is that a larger percentage of urban special educators strongly agreed
with the statement “your students are not capable of learning the material you are
supposed to teach them” compared with suburban or rural educators. This indicates that
urban special educators had less belief in the general teaching efﬁcacy domain that the
suburban or rural special educators.

Smylie (1988) found there was a correlation between the number of low-
performing students in a teacher’s classroom and the teacher’s PTE (r = -.2684). This
ﬁnding leads to the consideration of whether responsibility for teaching students with
disabilities results in decreased PTE after a certain amount of teachers experience and
interaction with these students. Smylie (1988) also found that PTE was a signiﬁcant
indicator of change (path coefficient of .2996) in classroom practices; the higher a
teacher’s PTE score, the greater the likelihood that the teacher would initiate an
innovative change in an instructional program. Bandura’s social cognitive theory (1974)
described the cyclical nature of self—efﬁcacy, as self-efficacy is impacted by both past

successes and failures. The ﬁnding that a teachers self-efﬁcacy scores tend to decrease

30

when they regularly work with students who have difficulty learning has implications for
general education classroom teachers who will encounter more children with disabilities
in the general education classroom.

Preservice Teachers and Teacher Self-Efﬁcacy

Preservice teachers who have higher self-efficacy have similar instructional
behaviors to those of in-service teachers who have more experience. Teacher level of
satisfaction with support and preparation during the intemship year of teaching is an
indicator of higher teaching self-efﬁcacy (1on & Spero, 2005). General education
student teachers who believe that they have the knowledge, skills, and ability to perform
the tasks required to teach students tend to have high teaching efﬁcacy; indeed, “efﬁcacy
beliefs of novice [ﬁrst-year] teachers are related . . . to satisfaction of support and
preparation” (Tschannen-Moran et al., 1998, p. 236).

Knoblauch et al. (2008) measured the teaching self-efficacy of 102 preservice
student teachers within rural, suburban, and urban settings to determine whether the
school setting inﬂuenced teacher self-efficacy. The authors found that the teaching self-
efficacy scores of all the preservice teachers increased signiﬁcantly, after they had
engaged in student teaching, leading them to conclude that setting was not a signiﬁcant
factor in preservice teaching self-efficacy. The authors also assessed the self-efﬁcacy of
the cooperating teachers as perceived by the student teachers, i.e. the student teachers
completed the survey about their cooperating teachers’ self-efﬁcacy. They found a
moderately strong correlation (r = .52, p < .001) between student teaching self-efﬁcacy
and the perceived teaching self-efﬁcacy of the cooperating teacher. The authors

suggested that perception and vicarious experiences play an important role in preservice

31

teachers’ views of efﬁcacy; if student teachers perceive their cooperating teachers as
having high teaching self-efﬁcacy, they are more likely to have high teaching self-
efﬁcacy themselves.
Malleability of Preservice Teacher Self-Efficacy

Preservice teacher teaching self-efficacy appears to change during the course of
student teaching, which Tschannen-Moran et al. (1998) hypothesized is related to the
acquisition of mastery experiences. More speciﬁcally, preservice teachers acquire ﬁrst-
time mastery experiences that contribute to their expectancy of future performance
(Bandura, 1997). However, this does not imply that teaching efficacy cannot change for
in-service teachers; however, it does imply that changes in efficacy are usually due to the
context of the task or situation rather than personal development (Tschannen-Moran et
al., 1998).

In their study of 191 undergraduate students, Hoy and Woolfolk (1990) compared
three groups of students: students participating in their student teaching semester (n = 59)
in a university preparation program, students enrolled in a methods course for the
completion of certiﬁcation requirements (n = 66), and students taking a developmental
psychology course who were not enrolled in the teacher education program (n = 66). The
researchers found that students participating in student teaching began the semester with
higher GTE; at the end of the student teaching semester, their GTE had decreased [t(5 8) =
1.74, p < .05] but their PTE had increased signiﬁcantly [t(57)= 5.74, p < . 01]. In contrast,
the GTE of the students in the education methods course showed no signiﬁcant change.

Although the study results were disappointing in that the student teachers’ decrease in

32

GTE indicated a decrease in their belief that education can overcome external
environments, their increase in PTE indicated an increase in their belief in their abilities.

Chester and Beaudin (1996) studied 173 newly hired teachers in the nine largest
school districts in Connecticut to test their hypothesis that changes in self-efﬁcacy are
related to resources, school practices, and teacher characteristics. Newly hired teachers
were those who had not been employed by the district in the previous year. This resulted
in two groups of teachers, novice teachers who were newly hired in the district, or
experienced teachers but newly hired in the district. Their results indicated that new
teachers in urban schools who were novice teachers experienced a small decrease in
general teaching self-efﬁcacy over their ﬁrst year of teaching whereas teachers who were
experienced teachers but new to the district reported a signiﬁcant increase in general
teaching self-efficacy. Thus, the increase in teaching self-efﬁcacy appeared to be
mediated by the experience of teaching. Common school practices, such as more than
ﬁve visits from a supervisor, positively inﬂuenced the teaching self-efﬁcacy of new
teachers. The authors concluded that increasing and improving teacher instructional
feedback contributes to an increase in teacher efﬁcacy.

Masengill-Shaw, Dvorak, and Bates (2007) administered the Theoretical
Orientation to Reading Proﬁle (TORP) and Teachers’ Sense of Efﬁcacy for Literacy
Instruction Scale (TSELS) and a researcher created knowledge test to 52 preservice
teachers during their senior year of study. The participants took all measurement scales
prior to completing the required ﬁeldwork and again after completing the ﬁeldwork. The
presurvey mean score was 6.45, indicating that they possessed some degree to quite a bit

of teaching self-efﬁcacy as it related to literacy instruction. Their postsurvey mean score

33

was 7.48, indicating that they possessed quite a bit to very much, which represented a
statistically signiﬁcant increase (t [51] = 6.21 , p < .00). The preservice teachers increased
their knowledge and increased their efficacy according to the TSELS. The authors
concluded that acquiring formal knowledge through the teacher preparation class had
positively affected the teachers’ beliefs in their teaching self-efficacy. In effect, they
found that preservice teachers came to their literacy methods class with high teaching
efﬁcacy and left with even higher teaching efficacy after engaging in practicum
experiences.

Comparison Studies

A plethora of studies of teaching self-efﬁcacy indicate that teachers who have
higher teaching self-efﬁcacy sustain instruction for a longer period with students unable
to maintain the pace of the rest of the class (Gibson & Dembo, 1984) and are more
conﬁdent in their ability to inﬂuence student performance (Tschannen-Moran et al.,
1998). In general, teachers who have higher teaching self-efficacy are more likely to
engage in successful instructional strategies than are those who have lower teaching self-
efficacy (Bender & Ukeje, 1989; Gibson & Dembo, 1984). Teachers who have higher
teaching self-efficacy take responsibility for student successes and are more willing to
implement innovations and stay in the ﬁeld (Guskey, 1982).

Studies of student teachers and interns have consistently found that personal
teaching efficacy increases during student teaching (Hoy & Woolfolk, 1990). Student
teaching is inﬂuential in the development of teaching self-efﬁcacy, partly due to its
provision of the factors identiﬁed by Bandura (1986), such the acquisition of mastery

experiences. According to Tshcannen—Moran et al. (1998), student teachers must analyze

34

the teaching task before they judge their ability to perform it and consider other factors,
including student motivation, student characteristics, and resources available to the new
teacher. Teaching self-efﬁcacy is a cyclical process; after teachers accomplish teaching
tasks, they View the sources through the cognitive processes.

Unfortunately, only a handful of researchers have investigated changes in the
teaching self-efﬁcacy of special education student teachers or compared the teaching self-
efficacy of student teachers from different programs. The studies that do exist compared
the teaching efﬁcacy of a small sample of preservice general educators to preservice
special educators; it is difficult to generalize their ﬁndings to a larger population.
Portrnan and Pontius (2000) compared the PTE and GTE of four groups of preservice
teachers: elementary school teachers (n = 56), middle school teachers (n = 9), secondary
school teachers (n = 33), and special education teachers (n = 6). They found that the PTE
of elementary and secondary school student teachers increased signiﬁcantly (p = .05)
after they had engaged in student teaching, with elementary having higher PTE overall.
Although all groups experienced an increase in PTE, three of the groups did have a
decrease in GTE however, it was not statistically signiﬁcant.

Freytag (2001) studied general education and special education in-service
teachers in his study. Based on the TES (Gibson & Dembo 1984), F reytag found
statistically signiﬁcant differences between the PTE and GTE scores (F = 4.291, p = .046,
112 = .115) ofthe two groups of teachers, 36 general educators and 12 special educators.
Speciﬁcally, they found that the special education teachers had both higher PTE and GTE

means.

35

Another study that examined the teaching self-efficacy of both general educators
and special educators was completed by Jordan, Stanovich, and Roach (1997). They
found that both general education and special education teachers teaching outside a large
city in Canada who had higher teaching self-efficacy (F= 22.60, B = .57, p =.001) had
more quality instructional interactions. These interactions were deﬁned by the authors as
an engaged individual conversation about concepts and content with students who had
been labeled with a disability. While the results did indicate that those teachers with
higher self-efficacy did engage in a higher level of the ﬁve levels deﬁned by the
researchers, there was not a direct comparison of teachers in different teaching ﬁelds.
Jordan et a1, investigated the presences of a special educator in the classroom predicted
higher levels of instructional interactions.

In his study directly comparing the teaching self-efficacy of in-service general
educators to in—service special educators in Israel (n = 699), Leyser (2002) found that the
mean PTE of the special educators (n = 139) was signiﬁcantly higher than that of the
general educators (n = 560; t =2.046, p = .041). Although this study directly compared
the teaching self-efﬁcacy of a large sample of teachers in different ﬁelds, it was
conducted outside of the United States, making it difficult to generalize its results to the
American school system.

According to Pugach (2005), the research base on general educators’ preparation
for working with students in special education in the general education classroom is very
small. Brownell and Paj ares (1999) recommended research to “identify differences in
special education preservice preparation for general educators and the relationship of

various program elements to general education teachers’ efﬁcacy beliefs” (p. 7). Because

36

research indicates that a high teaching self-efficacy is a strong predictor of various
positive outcomes listed above therefore beneﬁting all students investigating the
differences of teaching self-efﬁcacy in novice teachers in different preparation strands
can lead to a better understanding of the changes that occur between groups through the
student teaching experience.

Current Study

As previously discussed, few studies have compared the self-efﬁcacy of
American general education teachers and special education teachers. This study adds to
the literature by measuring and comparing the teaching self-efﬁcacy of both preservice
teacher populations, which has limited studies and identiﬁed the differences among
programs as possible variables in teaching self-efﬁcacy. This study used repeated
measures at three time points throughout the semester, unlike many other studies. The
majority of the teaching self-efﬁcacy studies discussed above employed a pre/post survey
design. This study also included a third measurement time to aiding to the understanding
the malleability of student interns teaching self-efﬁcacy.

Using the Tschannen-Moran et al., (1998) model of teacher self-efﬁcacy for this
study provided a deﬁned theoretical ﬁamework for the teaching self-efficacy as opposed
to previous studies. As indicated earlier the majority of the studies use Bandura’s (1997)
fiamework for self-efficacy studies however, there is some debate in the research
community about the one dimension of the teacher self-efficacy, speciﬁcally general
teaching efﬁcacy. However using Tschannen—Moran et al.’s (1998) model gives credence
to the construct of teaching self-efficacy because it speciﬁc enough for teachers yet not so

speciﬁc that it renders its power as a predictive measure. The model includes the notion

37

that a teachers’ self-efﬁcacy considers assessment of personal competence and the
analysis of the teaching task.

In addition, this study provided insight to other potential factors that inﬂuence the
change of teaching self-efﬁcacy. Other than preparation program, this study viewed the
impact other factors have on the teaching self-efficacy of student interns, including, the
amount of time a student teacher engages in teaching type behavior, the number of
students in a class and the number of students with disabilities in a general education
class and previous achievement of the student intern.

Study Procedure

This study measured the teaching efficacy of preservice general educators and
preservice special educators during the fall semester of their student teacher internship
year. Preservice teachers completed a survey three times during the semester to identify
changes in teaching efﬁcacy and to compare the teaching efﬁcacy of general education
student teachers and special education student teachers. It also investigated the
relationship of the student teacher and the impact of the classroom demographics, and

school population on the student teacher’s teaching efﬁcacy.

38

CHAPTER THREE
METHOD
Participants

Preservice student teachers were recruited from a large Midwestern university
serving over 35,000 students. The teacher preparation program at this university requires
5 years of education to gain teaching certiﬁcation. After students complete 4 years of
required classes, they earn a bachelor’s degree but are not yet certiﬁed. After successfully
completing 32 weeks (a ﬁfth full year, or 12 credits) of a student teaching internship,
general education preservice teachers receive certiﬁcation in general education. Special
education preservice teachers have two placement positions in the 32-week internship,
one in general education (16 weeks) and the other in special education (16 weeks).
Special education preservice teachers receive both general and special education
certiﬁcation. Depending on the level of certiﬁcation, special education interns pursue
certiﬁcation that will allow them to teach in either an elementary or secondary general
education classroom. They also receive a special education endorsement in either
learning disabilities or hearing impairment which allows them to teach in an elementary
or secondary special education classroom.

The population for this study was general education interns and special education
interns completing an internship in learning disability (hereafter referred to as either GEN
interns and SPED interns). The internship requires the students to enroll in 12 student
teaching credits in the 5th year. Along with 12 student teaching credits, interns are also

enrolled in 4 graduate level classes for 12 more credits for the year. These classes

39

traditionally meet on Fridays on the university campus during the school year, with some
meetings taking place at the interns’ placement school.

To aid in the recruitment of participants, incentives were used. The participants
who had successfully completed the study, deﬁned as those who had taken the survey
three times and turned in a report of cumulative GPA and total credit hours completed at
graduation, were eligible for the incentives. At the on campus classroom meetings at the
start of the school year, the researcher explained to the interns that their complete
participation in this study was considered part of a larger program of professional
development that could be described on their resumes. Certiﬁcates stating the
professional development were also given to the participants. The researcher offered free
consultation during the second semester of the internship year, whether by telephone, e-
mail, or a personal meeting, to provide advice on students with disabilities in the
classroom. The third incentive was enrolhnent in a rafﬂe. Four students were randomly
picked to receive a $50 gift certiﬁcate from a large superstore.

During fall 2008 there were ﬁve sections of the required general education intern
seminar classes grouped together by geographical location. The total enrollment of these
ﬁve sections consisted of 128 potential participants. Approximately 90% of these
potential participants were females. The researcher entered all ﬁve seminar classes to
recruit participants. A short presentation was given about the nature of the study along
with an explanation of the incentives for participation. Consents were passed to all the
interns in those classes. The researcher asked them to either sign or not and collected both
the blank and completed consents in order to protect participants privacy. The consent

forms asked for the student’s name and email address.

40

Through this procedure, 90 consents were collected out of 128 potential
participants; 84 females and 6 males with 1% listing their ethnicity as Hispanic, 1%
Asian, 1% Native American and 97% as white. The same procedure occurred for the
special education interns. The researcher visited the special education intern seminar
class of those students who were completing the LD certiﬁcation. There were 58 potential
special education participants, 47 special education interns consented to participate; 44
females and 3 males. Students described their ethnicity as follows: 6% African American,
2% Asian, 6% did not answer the question, and 85% white.

Procedures

Interns were asked to complete a survey three times during the fall semester of
2008. The ﬁrst survey, wave one, was administered the week of September 7, 2008. The
public schools in the state where this study occurred had a common start date of
September 2, 2008. Interns reported for their internship when each district required
teachers to report, typically 4 days prior to the start of the school year. Therefore, the
participants took the ﬁrst survey shortly after they had met their new students and became
familiar with typical classroom and building procedures.

The second survey, wave two, was administered the week of October 27, 2008,
chosen to coincide with the target dates in which an intern was expected to complete a
lead-teaching experience in their internship classroom. A lead teaching experience is
when the intern collaborates with the cooperating teacher to plan and implement lesson
plans. This week preceded parent-teacher conferences for most districts and followed the

administration of state achievement tests to students. The third survey, wave three, was

41

administered the week of December 8, 2008, which was close to the last full instructional
week for the majority of school districts prior to winter break.
Instrumentation

The survey contained 20 questions and took approximately 25 minutes to
complete via on online commercial survey software. The survey was administered in
three waves and was the same survey at each wave. The ﬁrst four question of the survey
asked for emails and identifying information. The next 8 questions asked about the
interns’ preparation, placement, grade level, number of students in their classes and how
many hours the engage in teacher type behavior. They are listed below:

I After receiving your certification, which of the following best describes what type of
employment you will seek: A general education teacher, a special education teacher,
school personnel other than a teacher, none of the above?

I Please list the school where you are completing your internship.

I How would you best describe the school of your placement: Inner city, suburban,
rural, I don 't know?

I In the fall semester, list the grade below in which you are completing your internship:

I List how many students are in the classroom where you are completing your
internship

I List how many students are in your general education classroom internship (fall
2008) that have an IEP or are receiving some type of special education services

I Including yourself and your cooperating teacher, please list how many adults are in

the classroom helping during the school day

42

I Approximately how many hours during a typical school day do you engage in
teacher-like behaviors (e. g., tutoring students, grading, presenting a lesson, writing
lesson plans, following up with parents or other school professionals, or conferencing
with students)?0ne, less than 1 hour, 1—2 hours, 2—3 hours, 3—4 hours, 4—5 hours, 5—
6 hours, 6—7 hours, more than 7 hours

The above part of the survey was followed by the Teachers’ Sense of Efﬁcacy Scale

(TSES) (Tschannen-Moran et a1, 1998), which is described in the following section.

Teachers ’ Sense of Eﬂicacy Scale (T SES)

Pajares (1996) warned, “There is a lot of mismeasurement in the area of self-
efﬁcacy” (p. 547). As discussed in chapter two, because judgments of self-efficacy are
task and domain speciﬁc, “global or inappropriately deﬁned self-efﬁcacy assessments
weaken effects” (p. 547). Therefore, it is important that measurements be task and
situation speciﬁc when investigating self-efﬁcacy. To address these concerns, this study
used the Teachers’ Sense of Efficacy Scale (TSES) created by Tschannen-Moran,
Woolfolk- Hoy (2001) (see Appendix A). This scale is based on the Teachers’ Efﬁcacy
Scale (TES) developed by Hoy and Woolfolk (1990) and the Teacher Efﬁcacy Scale
developed by Gibson and Dembo (1984). As discussed previously, the TSES is domain
and task speciﬁc and based on the integrated model of teaching self-efﬁcacy. Tschannen-
Moran et al. (2001) described the advantages of the TSES as follows:

It is superior to previous measures of teacher efﬁcacy in that it has a uniﬁed and

a stable factor structure and assesses a broad range of capabilities that teachers

consider important to good teaching, without being so speciﬁc as to render it

43

useless for comparisons of teachers across context levels and subjects. (pp. 801—

802)

The TSES consists of 24 items on a 9-point Likert scale ranging from not at all
certain to a great deal of certainty. Tschannen—Moran identiﬁed three moderately
correlated factors TSES for in-service teachers: self-efﬁcacy for classroom management,
self-efﬁcacy for instructional strategies, and self-efﬁcacy for student engagement. For all
three dimensions of efficacy, the higher the score of the participant, the greater the
teaching self-efficacy of the participant. Sample items from each subscale are:

Efﬁcacy for Classroom Management:

I How certain do feel that you can control disruptive behavior in the

classroom?

I How certain do feel that you can make your expectations clear about student

behavior?

Efﬁcacy for Instructional Strategies

I How certain do feel that you can provide an alternative explanation or

example when students are confused?

I How certain do feel that you can craﬁ good questions for your students?

Efﬁcacy for Student Engagement

I How certain do feel that you can motivate students who show low interest in

school work?

I How certain do feel that you can get through to the most diﬂicult students?

44

Researchers have argued that the three factor solution is not appropriate for
preservice teachers (Fives & Buehl, 2008). Several authors (Fives & Buehl, 2008; Flood,
2007; Henson, 2002; Tsigilis, Grammatikopoulos, & Koustelios, 2007) and the creators
of the TSES (Tschannen-Moran & Woolfolk-Hoy, 2001) noted that the factor structure is
less distinct for preservice teachers than in-service teachers and recommend using a one
factor solution when using the instrument with preservice teachers.

The TSES has been widely used and reported to be technically adequate based on
quality indicators of research (Gersten, Fuchs, Compton, Coyne, Greenwood, &
Innocenti, 2005; Odom, Brantlinger, Gersten, Homer, Thompson, & Harris, 2005). The
construct validity was examined by Tshcarmen—Moran and Woolfolk-Hoy (2001) who
concluded that the TSES was, “positively related to the Rand items (r=.l8 and 0.53,
p<.001) as well as to both the personal teaching efficacy (PTE) factor of the Gibson and
Dembo measure (F— 0.64, p. <0.01) and general teacher efficacy (GTE) factor (r=.16,
p<0.01)” (p.801). The strongest correlation occurred with the measures that assessed
PTE. Although it was found to be less strongly correlated with GTE, this may be due to
previous studies failing to correctly identifying GTE (Paj ares, 1996; Tschannen-Moran et
al., 1998, 2001).

Information Interns Considered

There were seven open—ended question included at the end of the survey. These
questions attempted to gather information interns used to make their judgments of their
teaching self-efficacy. The questions asked interns to identify if they felt successful
during their teaching, what information they used in that judgment and if supervising

personnel had an effect on that judgment. Also questions asked about the perceived

45

difﬁculties and effort interns experienced during teaching observations. They read as
follows:

Think back to your most recent visit ﬁ'om your university ﬁeld instructor—that is,
the instructor from MS U who visited you and provided feedback about your ﬁeld
experience. Please answer the following questions with the most recent visit in
mind.

1. You may have some impressions (good and bad) on how well you
completed your goals (for example: teaching students a learning objective,
tutoring a student, managing the classroom or other teacher type tasks) during
that observation. Please explain what your most significant impression was of
that observation (successﬁtl or unsuccessful) and why.

2. How diﬂicult was this lesson or activity for you to teach and why?

3. How much eﬁ'ort did you put into planning this lesson or activity? Please
explain.

4. Please describe the specific ﬁzedback you received ﬁom your university
field instructor.

5. Did you agree or disagree with the feedback, why and why not?

Think back to the most recent ﬁzedback you received from your
cooperating/collaborating teacher, either through formal or informal
observations, or through casual conversations.

7. Please describe speciﬁc feedback you most recently have received ﬁ'om your
cooperating teacher.

8. Did you agree or disagree with the feedback, why or why not?

46

Data Collection

The participants were sent an e-mail containing a link to the survey and asked to
complete it within two weeks for each wave of the survey. The researcher sent an e-mail
reminder to the interns who had not responded several days following the initial request
for each wave of the survey.

Out of 186 students enrolled in both the general education and special education
seminars, 137 consents were received and three email addresses were not valid addresses
(see table 3.1). During the ﬁrst wave 134 invitations were sent and 121 responses were
returned resulting in a 90% return rate for the ﬁrst wave. In the second wave 114 invites
were sent out, due to some participants opting out between wave one and wave two. Of
those 114 invites, 89 were returned for wave two resulting in 77% return rate. For the

third wave 89 potential participants were emailed, and 83 participants returned a survey

 

 

for a rate of 93%.
Table 3.1
Participant Response Rates
Total Informed Complete Complete Complete Final
potential consent surveys surveys surveys completed
participants Wave 1 Wave 2 Wave 3 surveys
Total Invites 134 l 14 89 83
Opted out 16 11 0
General Ed 128 90 78 58 54 48
Special Ed 58 47 43 31 27 25
Total 186 137 121 89 83 73

47

Table 3.1 Continued

Total potential Informed Comple Comple Complete Final Total

 

participants consent te te surveys complet potential
surveys surveys Wave 3 ed participants
Wave 1 Wave 2 surveys
Wave Return 90% 77% 93%
Rate from Initial 90% 66% 62% 54%

Participant data was included in the study if all three surveys had been completed.
Occasionally participants would sign onto the survey and not complete the survey
rendering their participation null. This resulted in a ﬁnal sample of 73 participants: 25
special education interns and 48 general education interns. There were only four male
participants; all were in the general education program. The self-reported grade point
averages and credit hours at the time of graduation with the Bachelor’s were similar
among the two groups. All participants had an average GPA of 3.47 with special
education interns having an average of 3.43 and general education interns having an
average GPA of 3.49. Credit hours and the number of students in the intern placement
class were very similar with a group average of 130 credit hours and 25 students in
classes. Special education interns reported more students with an IEP in'the classroom
then the whole group. The average GPA, credit hours taken, the number of students in the
placement class and the number of IEPs in classroom along with standard deviations can

be found on table 3.2.

48

Table 3.2

Interns’ GPA and Class Composition

 

GPA Credit Students Students with

Hours in Class IEPs

 

 

SPED Mean 3.43 129.52 25.72 6.32
SD .280 14.31 7.70 3.21

GEN Mean 3.49 131.41 25.55 4.06
SD .311 18.269 11.80 2.29

TOTAL Mean 3.47 130.78 25.61 4.84
SD .300 16.968 10.504 2.833

The majority of the placements (56%) for interns were in suburban schools. Twenty-nine
percent were placed in an urban setting and only 15% were placed in a rural setting for
their fall semester (see table 3.3).

Table 3.3

School Classiﬁcation of Placement

 

 

Sped Intern Gen Intern

Placement Placement
Total %
Urban 7 14 21 29
Suburban 11 30 41 56
Rural 7 4 1 1 1 5

49

Data Analysis

Teachers ’ Self-Efﬁcacy Scale

Before examining the relationship between the reported teaching self-efﬁcacy of
general and special education interns, the researcher examined the factor structure of the
Teaching Self-Efficacy Scale (TSES, Tschannen-Moran, Woolfolk-Roy, 2001). When
reviewing the pattern matrix of the factor analysis, a best ﬁt solution recommendation of
four factors appeared. Further examination of the pattern matrix of a three-factor loading
showed that the three factors did not load consistently on the matrix. To test the
appropriateness of using the ﬁrll TSES, a principal components analysis was completed
and all three factors loaded onto a single factor structure and accounted for 51% of the
variance. For the purpose of this data analysis, the dependent variable is the summed
score at each wave point of the 24 items on the TSES with the minimum score of 24 and
the maximum score of 216.

The researcher compared two different teacher programs and two different types
of internships. Because special education interns become dually certiﬁed, they participate
in both a general education internship for 16 weeks and a special education internship for
16 weeks On the other hand, general education interns participate in one general
education internship for 32 weeks. While both interns are completing their internship
they are also enrolled in classes.

Prior to the internship general educator interns complete classes in the Teacher
Education department. These classes are taken by both special educators and general
educators. The Teacher Education department follows an infused model, where special

education content is immersed within the curriculum. Students preparing to be special

50

educators also enroll for classes in the Special Education department where they take
classes related to special content only.

Because SPED interns have two different classroom placements throughout the
year, a preliminary analysis was conducted to compare the means on the TSES of special
education student interns who could be in one of two types of placement in the fall 2008.
The special education interns from the ﬁnal full data set were separated into two sub
groups, participants who were interning in a special education placement in the fall 2008
(SPEDinSPED) (n=9) and special education interns in a general education placement in
fall of 2008 (SPEDinGenplace) (n=16). The means for the SPED interns are reported in
table 3.4. There was no signiﬁcance difference between the placement types of special
education interns as indicated by table 3.5.

Table 3.4

TSES scores of SPED Interns by Placement

 

 

 

Std.
Placement Mean Deviation N
Wave One SPEDplace 147.89 29.67 9
Sum GENplace 151.25 27.88 16
Total 150.04 27.97 25
Wave Two SPEDplace 158.11 30.78 9
Sum GENplace 156.75 17.62 16
Total 157.24 22.58 25

51

Table 3.4.

 

 

 

 

 

 

 

Continued
Std.
Placement Mean Deviation N
Wave Three SPEDplace 166.56 22.90 9
Sum
GENplace 169.31 21.69 16
Total 168.32 21.70 25
Table 3.5
ANOVA for SPED Interns
Sum of '
Squares df Mean Square F Sig.
TMlSUM Between Groups 65.07 1 65.07 .080 .780
Within Groups 18705.89 23 813.30
Total 1 8770.96 24
TMZSUM Between Groups 10.67 1 10.67 .020 .889
Within Groups 12233.89 23 531.91
Total 12244.56 24
TM3SUM Between Groups 43.78 1 43.78 .089 .768
Within Groups 11253.66 23 489.29
Total 1 1297.44 24

 

52

(n=25) was used in further analyses. Data were examined to ensure assumptions of
normality, homogeneity of variances, sphericity, and linearity were met, and when
assumptions were not met, non-parametric equivalents were used to evaluate the data.

To discover of the differences between the reported teaching self-efﬁcacy of
general education interns and special education interns, as reported on the TSES, repeated
measure ANOVA was used to compare the means of the preparation groups at three
wave points in the fall semester. This analysis allowed the researcher to identify main
effects of preparation program and the interaction of group x time. When signiﬁcance
was detected for time but not for program type, a pairwise t- test was employed to
discover how the teaching self-efﬁcacy of interns change over a semester therefore
addressing the second research question how does the teaching self-efﬁcacy change over
the course of a semester.

A forward stepwise multiple regression analysis was used to answer the
question—Over the course of a semester, which factors inﬂuence interns’ teaching self-
efficacy? The dependent variable was the Stun of the TSES score at the third wave
(TM3 SUM), the independent variables were entered as follows: sum score on TSES at
wave one (TMl Sum), sum score on the TSES at wave two (TMZSUM), school type of
either urban, suburban, rural (schooltype), number of hours an intern reported in
engaging in teacher like behaviors at time 3 (hours3), number of students with IEPs in
intern placement (IEP), interns’ grade point average (GPA), number of credit hours the
intern obtained for bachelor degree (credit), type of program in which the intern is

enrolled(prep).

53

Wave analysis

To investigate a potential bias that non-responders present, a wave analysis was
completed, as recommended by Kano, F ranke, Aﬁﬁ, and Bourque (2008). Information
used in the analysis included the preparation program, and sum scores between wave one
and wave two and again between wave two and wave three. These means and range of
the scores were compared to the participants to see if those interns dropping out of the
study appeared share a unique characteristic that might indicate why they dropped such
as low teaching self-efficacy.

Groups of High TSES Scores and Low TSES Scores

In order to investigate if there were differences in the characteristics of interns
who had the lowest teaching self-efficacy and those who had highest teaching self-
efﬁcacy two groups were formed. At each wave of administration 20% of the total
participants or 10% of the top and 10% of the bottom (the top eight and bottom eight
participants determined by the sum score on the TSES), were separated ﬁ'om the larger
data set for separate analysis. The two groups were labeled high TSES and low TSES.
The two groups at each wave were compared to determine the stability of the groups at
each wave. The GPA and credit hours reported at the time of graduation, the reported
teaching time, composition of the interns’ classroom and school were also examined for
individuals in the low and high groups by reviewing and comparing descriptive statistics.

Information Interns Used for Judgments

In order to identify the information interns use to make their judgments of their
teaching self-efficacy, the survey included eight open-ended questions at the end. Only

seven of the eight questions were included in the analysis as the last question was

54

optional and did not include information directly related to the study. The questions were
completed at each wave point and were the same at each administration. The overarching
research question was “What information do interns identify in helping make their
judgment about their teaching self-efﬁcacy?”

Using a modiﬁed version of the Grounded Theory (Glaser & Strauss, 1967) all
answers were read at each wave point and coded in a broad format looking for emergent
themes (Dick, 2005). Each open-ended question was reviewed and coded (n=73) at each
wave of the survey. As the codebook was revised, responses to the seven questions fell
into three topic areas and some of the topic areas had subcategories. The three major
topics area were; “success or failure and why”, “difficulty and effort”, and “agreement
with supervisors”. The ﬁrst question of the survey contributed to the ﬁrst topic area
“success or failure and why” and was further broken down into two subcategories. The
survey question asked for the interns’ perception of their performance in the classroom
(e. g. were you successful) and the information they used to make the judgment (e.g.,
why, whose comments, actions, or outcomes provided information about their
performance). Survey questions two and three contributed to the “difficulty and effort”
topic area and were broken down into two subcategories, difficulty of lesson presentation
and effort in planning for the lesson. Questions four through seven contributed to the
topic area of “agreement with supervisors” and had two subcategories of agreement with
ﬁeld supervisor and agreement with cooperating teacher.

The codebook was completed for each of the three areas. A graduate student was
employed and trained to conduct inter rater reliability checks by reviewing seven open

ended survey questions of the three topic areas. For training purposes only ﬁve samples

55

for each topic area were scored with a chance for the graduate student and the researcher
to discuss any discrepancies. After the training, 25% of randomly chosen intern responses
were scored by both the researcher and graduate student. The researcher and the graduate
student achieved an overall 94 % agreement for all three topic areas combine and for
each topic area the reliability was 93% for “success or failure and why”, 92% agreement
for “difﬁculty and effort”, and 100% for “agreement with supervisor”. The rate was
calculated by adding the total number of agreements and disagreement and dividing by
the agreements. Responses were counted for each category and are discussed in Chapter
Four.

Success or failure and why. The ﬁrst topic area for the study resulted in two
subcategories success or not and why. In the ﬁrst subcategory interns identiﬁed their
performance as successful, unsuccessful, somewhat successful, or no response. Interns’
answers that included a positive perception of their observation, or their report indicated
that they felt successful were scored as indicating they felt successful. An example of this
included: “It was successful because I completed my lesson feeling conﬁdent that the
students learned about the /k/ sound.” Those interns who felt less successful, had a
negative perception of an observation, or declared they were unsuccessful, were scored as
interns feeling like they were unsuccessful during observation. These included such
reactions as, “I felt that I was very unsuccessful with my goals and objectives because I
was not able to keep the lesson ﬂow up because I was having major difﬁculties with my
materials and different things,” “I felt (it)[sic] went poorly,” “ It felt like 1 was creating
more confusion than clariﬁcation.” Those responses that were scored as somewhat

successful indicated the interns were not clear regarding their observations. They

56

included comments that fell into both the positive and negative feedback categories.
Examples included: “So, all in all, I felt okay about my lesson; one student continually
acted out and disrupted the class, so that made me feel as if the lesson was less
successful.” The responses that scored no response indicated the interns did not
understand the question or had not been formally observed. Examples included: “I have

’9 66

not yet been observed, my ﬁeld instructor really hasn't seen me actually teach in the
classroom yet,” “The only time that she has come in has been when my CT has been
teaching and I have been interacting around the classroom,” “At this point, I can't
thoroughly answer this question.” The last category was unscorable, suggesting the intern
gave no indication about how the observation went or answered the question out of the
context of what was asked. An example of this category is, “I agreed with everything she
said, both the good and the bad.”

The subcategory of the topic area “success or failure and why” was viewed as the
information the interns reported about why they deemed their performance successful or
unsuccessful. Six types of information emerged from the interns’ responses and were
labeled as, ﬁeld instructor (F I), cooperating teacher (CT), student feedback,
management, instructional, and engagement. Responses could be coded in more than one
type of answer if the response mentioned more than one aforementioned area.

When interns directly related the judgment of their performance to feedback from
the university ﬁeld supervisor, it was counted as ﬁeld instructor (F I). An example was:
“My ﬁeld instructor told me that I looked like I was enjoying myself, and that I showed

great conﬁdence. This made the most impression on me because I have been questioning

my teaching lately.” When an intern indicated the classroom cooperating teacher

57

contributed to the intern’s decision about their success or failure in their performance the
response was categorized as cooperating teacher (CT). An example of this category:
“My CT observed me and thought it went well.” Sometimes interns would mention
feedback from both the cooperating teacher and the ﬁeld instructor. In those cases, that
answer would be classiﬁed in both categories.

Student performance was another category in which the interns considered when
making judgments’ about their success. Answers coded in the student performance
category included: “During the past couple weeks I have been teaching the children
various writing techniques. During this time I have been able to observe the students’
progress increase dramatically in comparison to the beginning of the year. This was
signiﬁcant because I felt like I had accomplished my learning goals and impacted the
students in a positive way.” The instructional category included items where the intern
discussed speciﬁc instructional strategies or teaching a speciﬁc objective as information
in determining the success of the observation: “I have reached my goal of explainin [sic]
borrowing and carrying during addition and subtraction of two digit numbers,” “I thought
it went well because a variety of (instructional) methods were used.” Interns included
judgments of their students’ engagement during their observation and these were
categorized under the category of engagement. The following is an example of the
engagement category: “I think that the observation went well because students were
engaged,” “Teaching a lesson on moon phases went very well, the 5th graders were
attentive and engaged.” Management involved interns’ comments that they felt
successful or unsuccessful because of classroom management issues and included

answers such as: “So far, I have not done a very good job with my classroom

58

management,” “Successful because the lesson went well and I managed the students
well,” “Unsuccessful at managing the class.” The question was read and coded from the
revised codebook and counted for total responses.

Diﬁiculty and effort. The second and third question of the survey resulted in a
second topic area of “difficulty and effort” and encompassed the interns’ perception
regarding the difficulty of the lesson and the amount of effort exerted in the planning
process for a recent lesson. Responses for the difﬁculty subcategory were coded as easy,
somewhat, hard, or no response. Responses scored as easy indicated the intern felt the
lesson was easy to present. Examples of the easy category were as follows: “The lesson

,9 ‘6

was fairly easy to teac , . . .it was not difﬁcult because the lesson was about acrostic
poems and the students had an idea on how to write one.” A response of somewhat
indicated the intem’s response fell somewhere along the continuum. Examples were: “It
was slightly difficult,” “It was somewhat difficult ” The drﬂicult category was coded
when the answer indicated that the lesson was difﬁcult to teach. Examples included:
“Something that was abstract was difficult to teach,” “The lesson was extremely
difficult.” The category no response indicated that either the intern did not answer the
question or that the intern had not had a formal observation and felt that this question did
not pertain to that survey time point.

Effort asked about the intem’s perception of effort they put forth for the lesson in
which they were observed. Answer categories included little ,moderate, substantial, no
perception stated (NP) and no response. Little was the category coded when the interns

indicated they did not exert much effort on the lesson planning and included answers

such as: “Little effort was needed,” “I did not have to put much effort into the lesson.”

59

The moderate category was for interns who wrote that it was that indicated a nriddle
effort occurred in the planning of the lesson. Examples of answers in this category were:
“A mixture,” “1 put in some,” “it took some effort to think about how I was going to
model.” Similarly, if interns indicated they had exerted a large amount of effort, it was
categorized as substantial. Examples are: “I put a lot of effort into planning; A lot; I took
time to plan out what exactly we are doing and what the goals are.” If interns wrote
about how many hours they spent on their planning, but did not include a perception of
how much effort this was for them, the answer was coded no perception stated (N.P.).
Interns did not always reveal their judgment about the amount of effort exerted toward
the planning of the lesson but wrote about what they did to plan for the lesson. Examples
of answers in this category include: “One of the lessons I taught (math) that was
successful with classroom management took me about 40 minutes to plan and create a
Smartboard presentation,” “I spent about two hours planning this lesson.” Both
responses describe the amount of time the intern planned for the lesson but do not
indicate if the intern felt this was an extraordinary amount of time or if it was rather a
little amount of time. Therefore these answers were coded as N.P. indicating that they
answered the question but gave no judgment of the effort exerted. The category no
response indicated that either the interns did not answer the question or that they had not
had a formal observation and felt that this question did not pertain to that survey time
point.

Agreement with supervisors. The third and ﬁnal topic area was, “agreement with
supervisors,” and asked interns about their agreement or disagreement with feedback

from their supervising personnel (i.e., university ﬁeld supervisor and cooperating

60

teacher). The survey had four questions and asked if the intern agreed or disagreed with
the feedback given to the intern by ﬁeld instructor and cooperating teacher. There was
four answers for both sections of this area, agreement, disagreement, somewhat
agree/disagree and unscorable. Agreement indicated that the intern agreed with
supervisor, (i.e. “I agree”), the disagreement indicated that the intern disagreed with the
supervisors feedback (i.e. “I disagree” or “No I don’t”), somewhat indicated that intern
agreed with parts but also disagreed too. An examples of this category is: “Yes and No”
or “sort of”. Unscorable meant that the intern either left the questions blank, or did not

directly answer the question.

61

CHAPTER FOUR
RESULTS
This chapter discusses the results of the analysis completed on the data at three
wave points and is divided into three major sections. The ﬁrst section reviews the results
of statistic methods on the sum scores of the TSES by two different groups at each wave
point. The second section reviews the participants who scored in the highest 10% and the
lowest 10% of the TSES sum scores at each wave. The ﬁnal section looks at the
responses interns wrote about in the open-ended questions.

Diﬂerences between Special Education and General Education

The ﬁrst research question investigated if there were signiﬁcant differences
between the reported teaching self-efﬁcacy of general education interns (GEN) and
special education interns (SPED) over the semester. The sum of each of the participants’
(n=73) mean scores from the TSES scale were compared at wave one (TMl), wave two
(TM2), or wave three (TM3). A two group (SPED or GEN) by three (time of survey
administration: TMl, TM2, TM3) repeated measures ANOVA was used to investigate
differences between the reported teaching self-efficacy of general education interns and
special education interns. Mauchly’s Test of Sphericity proved to be signiﬁcant p=.005
indicating that that Sphericity assumption was not met. To minimize the potential for
Type II errors, a Huynh-Feldt correction was used (Field, 2009).

The means (with standard deviation in parentheses) for special education interns
(n=25) at each time point measuring teaching self-efficacy were as follows: 150.04 (SD

27.97), 157.24 (St) 22.59), and 168.32 (51) 21.70). Means (with standard deviations in

62

parentheses) for general education interns (n=48) were as follows: 147.25(SD 24.07),

150.40 (SD 23.71), and 159.13 (SD 23.50) (see table 4.1).

Table 4.1

Sum Means and Standard Deviations of All Interns

 

 

 

 

N Mean SD

Wave one SPED 25.00 150.04 27 .97
GEN 48.00 147.25 24.07

Total 73.00 148.21 25.31

Wave two SPED 25.00 157.24 22.59
GEN 48.00 150.40 23.71

Total 73.00 152.74 23.40

Wave three SPED 25.00 168.32 21.70
GEN 48.00 159.13 23.50

Total 73.00 162.27 23.17

 

The repeated measures AN OVA indicated that the main effect for wave was
signiﬁcant, F=19.448, p. =.000, with a Huynh-Feldt correction and an observed power of
1.00. However, time x group interaction was not signiﬁcant with the Huynh—Feldt
correction, F =.870, p. =.413 and an observed power of .19. This analysis showed that
there was a signiﬁcant change of reported teaching self-efﬁcacy over the semester with
no statistically signiﬁcant differences between intern groups. Due to a lack of a

statistically signiﬁcant difference between the special education and general education

63

interns the analysis for the following research questions were conducted as one group
(n=73).
Changes of Teaching Self-Eﬁ‘icacy

To investigate how the TSES varied from wave 1 to wave 2, from wave 1 to
wave 3, and from wave 2 to wave 3, a one-sample t-test was implemented. The means (u)
for the participants (n=73) were as follows: u=l48.21 wave one (SD 25.31); u= 152.74
(SD 23.40) wave two; and u=162.27 (SD 23.16) wave three. The results showed that
there was a signiﬁcant difference between wave one and wave three (TMl Sum,
TM3 Sum) and between wave two and wave three (TMZSum and TM3Sum) with a = .05.
However the difference between wave one and wave two (TMl Sum and TM2Sum) with
(1 =05 was not signiﬁcant (see table 4.2). The means increased at each wave point
indicating a rise in teaching self-efﬁcacy scores.
Table 4.2

Pairwise Comparisons Means of Sum Scores

 

 

Mean SD Std. Error t df Sig.
Mean (2-
tailed)
TMlSUM - TM2SUM -4.53 20.39 2.39 1.90 72 .061
TMlSUM - TM38UM -14.07 22.72 2.66 5.29 72 .000
TM2$UM - TM3SUM -9.53 16.02 1.88 5.09 72 .000

 

Factors Inﬂuencing Teaching Self-Eﬂicacy

A stepwise multiple regression analysis was employed to answer the research

question-“Over the course of a semester, which factors inﬂuence interns’ teaching self-

64

efficacy at the ﬁnal wave of collection?”— a stepwise multiple regression analysis was
employed. The sum score at the second measurement of the TSES (TM2SUM) and the
number of hours that students reported engaging in teacher-like behaviors (Hours3) at the
third measurement were the two variables that signiﬁcantly contributed to the variance of
sum score of the TSES at the third wave (see table 4.3).The sum of the second wave
(TM2SUM) variable explained 57% of the variance on the dependent variable and hours
engaging in teacher-like behaviors at the third measurement only accounted for an

additional 3% of the variance (12 of . 601) of the sum of the TSES at the third collection.

 

 

 

Table 4.3
Multiple Regression Chart
Unstandardized Standardized
Model Coefﬁcients Coefficients
B Std. Error Beta t Sig.
1 (Constant) 46.980 12.1 18 3 .877 .000
TM2SUM .753 .078 .762 9.619 .000
2 (Constant) 29.325 13.906 2.109 .039
TM2SUM .752 .076 .761 9.935 .000
Hours Teaching TM3 2.487 1.054 .181 2.361 .021

 

Bias of Non-responders

There is a possibility that interns who choose not to participate had a very low or

high score. The implications of those who dropped out were investigated in order to

65

investigate this potential bias. A wave analysis was completed with the information
available at each wave point. The analysis reviewed information of the interns who left
the study from wave one to wave two and from wave two to wave three.

In the ﬁrst to second wave, 33 intems dropped from study. The mean sum score
on the TSES of this group was 145.58 (SD 21.43) very close to the mean sum score of the
total participants at wave one 148.21 (SD 25.31). To limit a concern that those with lower
teaching self-efficacies would drop out of the study, the individual wave one averages of
the sum of the TSES were calculated. Next, all respondents at that wave were divided
into the top half and bottom half of the TSES sum scores. This revealed that of those who
dropped from the study, 17 of the 33 interns were in the bottom half and 16 were in the
top half. Again, these numbers indicate that interns who had higher and lower scores
dropped out from the study almost equally. Twelve of the participants or 36% who did
not complete the study were special education interns and 21 or 64% were general
education participants. Those participants who dropped out had an average of 24.5
children in class and 5.1 of those students had IEPs. When compared to analysis of the
participants who remained in the survey, the analysis of those who dropped out is very
similar.

Between the second wave and the third wave, only nine interns dropped out.
According to the sum scores at wave two, they averaged 153.6, (SD 30.64) just slightly
higher than the mean for the total survey participants of 152.7(SD 23. 40). The nine who
dropped had an 82-point range from, 115 to 197. The interns who dropped out had an
average of 23.4 students in their class and 5.8 of those students had IEPs. Again, at both

wave one and wave two, the participants were who dropped where similar to those who

66

remained in the study. The ﬁndings revealed that those who dropped out of the study had
sum scores that were equally distributed indicating that those who dropped out did not
cluster at either the top or bottom scores. There did not appear to be any systematic bias
between those who dropped and those who remained in the study. This alleviated some of
the concern that a bias might be present in the sample.

Groups of High TSES Scores and Low TSES Scores

Averages and Placement within High and Low groups

In order to examine different characteristics of interns who scored lower or higher
on the TSES, 20% of the participants were parsed from both the lowest (10%) sum scores
and the highest (10%) sum scores. This was completed for each wave of survey
administration with the complete dataset (n=73) and resulted in choosing the top eight
and bottom eight as determined by the score on the TSES. The group named High TSES
consisted of the top eight scores on the TSES at each wave.

The High TSES group at wave one had an average TSES sum score 188.75 and
this group scored between 208-177 producing a range of 31 points on the TSES scale.
Wave two high participants had an average TSES sum score of 191.5 and scored between
201 -1 84, producing a range of 17 points on the scale. Wave three for the high group had
an average of 198.25 TSES sum score, a range of 214-1 86 producing a range of 28
points. The sum TSES scores of the 9th participant (the cutoff point) at each wave point
were 176, 183, and 186. The standard deviations for the high group appear to stay
consistent through all three waves.

The Low TSES group consisted of the eight lowest scores at each wave point. The

Low TSES at wave one had an average of 105.13 and scored between 97-110 with a

67

range of 13 points, wave two had an average of 109.1 and scored between 88-123 with a
range of 35 points, wave three scores had an average of 117.63 and scored between 60-
138 with a range of 78 points. The large range in the third wave of the low TSES group
was due to the difference between the lowest two scores of 60 and 113 (55 points). The
sum scores of the 9th participant in the Low TSES group (the cutoff point) at each wave
were 111,126, and 143. The standard deviations for the this group also increase at each
wave with the third wave with more than twice of the high group (see table 4.4).

Table 4.4

Comparative Means of Low and High Groups

 

Wave 1 Wave 2 Wave 3

 

Mean SD Range Mean SD Range Mean SD Range

 

 

 

Low 105.13 4.97 97- 109.13 11.66 88- 1 17.625 24.64 60-
TSES ,
Group 1 10 123 138

 

High 188.75 10.02 177- 191.5 6.41 184- 198.25 10.99 186-
TSES
Group 208 201 214

 

When examining each of the interns who occupied a position in the low or the
high group, the interns in the high group did not have tend to stay in the high rank for all
three waves whereas those in the low group had a higher tendency to stay in low group
for all three waves. In the low TSES group there were four interns (out of 8 possible
positions) who were ranked in the bottom score at all three waves, whereas in the high
TSES group there only two interns (out of 8 possible positions) ranked in the high group

for all three waves. More interns shared the top 10% then those in the lower group, while

68

interns who scored in the lowest 10% had a tendency to stay in the lowest group (see

ﬁgure 4.1).

General Ed (n=48) I Special Ed (n=25)

20% 20%

    

 

 

 

High Low High Low
Figure 4.1. Percentage of interns (rounded) in low and high group at each wave.

More general education interns were in the low TSES group than the higher TSES
group. This could also be a function of those who were in the lower group tending to
stay in the lower group for all three waves. Figure 4.1 shows the percentage of general
education and special education interns that were in each group. At the ﬁrst and third
time points, three (6.3%) of general education interns (n=43) and ﬁve (20%) of special
education interns (n=25) were in the high group whereas, in the low group there were six
(12.5%) general education interns (n=43) and two (8%) special education interns (n=25)
out of eight possible positions. During the second time period, the composition of the low
group did not change; however the high group did change, having ﬁve (10.4%) general
educators and three (12%) special educators in the high group. These differences

however, were not tested for statistical differences.

69

Grade Point and Credit Hours

The next two ﬁgures compare the grade point average (GPA) and credit hours
reported by interns in the low and high scoring groups. At the start of the study, interns
reported their GPA and credit hours they had attained with their bachelor degree
immediately prior to starting their internship. At each wave point the lower group
reported a higher GPA however they also attempted less credit hours. The difference
between high and low groups at each wave point was wave one .29, wave two .09, and
wave three .28. The comparison of the interns GPA by high and low group is represented
in ﬁgure 4.2. The differences in credit hours between the high and low group for wave
one was 7.36 credit hours, wave two 9.18 credit hours, and wave three 5.29 credit hours.
The majority of classes in the teacher education program are 3 credit hours. Figure 4.3
compares the high TSES to the low TSES reported credit hours at the time of graduation

from the university.

I High TSES GPA CILOW TSES GPA

 

 

 

 

 

 

 

 

 

wave one wave two wave three

Figure 4.2. GPA by high and low groups at each wave.

70

I High TSES DLow TSES

143.18
141.50

138.57

134.14 1 34,00

 

 

133.28

 

     

 

 

 

 

 

 

 

 

 

wave one wave two wave three

Figure 4.3. Credit hours by high and low groups at each wave.

Interns at each survey administration were asked approximately how many hours
a day they engaged in teacher-like behaviors, which included tutoring students, grading,
presenting a lesson, writing lesson plans, following up with parents or other school
professional, conferencing with students. These hours were reported in ranges and
assigned a score according to the reported time by the intern. These scores were then
averaged to estimate the reported teaching hours range for the low and high groups.
The range of time was given to the intern to pick and followed by the score assigned by
the researcher were as follows, (a) none =1, (b) under one hour=2, (c) one to two
hours=3, ((1) two to three hours=4, (e) three to four hours=5, (f) four to ﬁve hours=6, (g)
ﬁve to six hours=7, (h) six to seven hours=8, and (i) more than seven= 9.

At all wave points, the interns in the high TSES reported more teaching time. At
the ﬁrst time point, the higher group scored an average of 6.75 which is the range of 4 to

6 hours of teaching time each day, with an estimation of 5.5 hours a day. In contrast, the

71

lower group scored an average of 4.38, indicating a range of 2 to 4 hours, an estimation
being closer to 3 hours of teaching time. At the second point, the high and low groups
appeared to be closer in averages score of teaching time, being only .50 apart; but the
higher goup reported more teaching time. At the third point, however, there appears to
be a large difference in reported teaching time, with the higher group scoring an average
of 8.13 which is estimated a range of 6 to 7 hours of teaching time whereas the lower
group scored an average of 6 which translates to the range of 4 to 5 hours of engagement

in teaching behavior (see ﬁgure 4.4).

I High TSES :1 Low TSES

8.13

     

 

wave one wave two wave three

Figure 4.4. Reported teaching time at each wave of high and low groups.

Information lntems Considered in Their J udgrnents about Observations
The coding and inter rater reliability were completed on the open ended questions and

then answers were tallied for the three topic areas. The ﬁrst area discussed addresses the

72

interns’ perception of success or failure of their observation and why, the second area
will discuss the perception of difﬁculties and effort in preparing the lesson and the third
area will discuss the agreement of feedback from supervising personnel.
Success or failure and why

The majority of the interns’ reported feeling successful at waves two and three,
with more than half the responses indicating success. In wave one the highest response
was no response, because a number of the interns reported not having an observation at
the time they took the ﬁrst survey and therefore responded with such. The highest
“unsuccessful” occurred in the second wave with 10 responses indicating they felt

unsuccessful (see ﬁgure 4.5).

E Successful Unsuccessful Somewhat 17 No Response l Uncodable

 

 

 

 

 

 

 

 

 

46
I: 44
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E l 1‘ H 10 10 —~
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C J I.“ -—--<
E 1 i T’ 2 f '“ 2 1
——L , l.-- : I1 : _

Wave One Wave Two Wave Three
Figure 4.5. Perceived success of observation.

73

The second part of the question asked interns why they judged their performance
as successful or unsuccessful. When an intern answered the “why” question, the response
it fell into one of the six categories described in Chapter Three. Responses could be
scored for more than one category. In the ﬁrst wave there were only 29 responses, in the

second wave there were 79 responses and in the ﬁnal wave there were 93 responses.

I Fl CI CI IIII Student Feedback I Management 9 Instructional a Engagment

   

 

 

 

 

20
16
FIFI'
11
4 4
3
2 2
I I] [inlE E 1:1
Wave one Wave two Wave three

Figure 4.6. Information Intems’ used to make judgments about the performance.

As the semester progressed interns were more detailed about the information they
used to make judgments about their teaching performance and often mentioned more than
category of information. In the ﬁrst wave the highest feedback category mentioned for
making judgments about the interns performance was management with 11 responses, in

the second wave, interns indicated feedback from the ﬁeld instructor was most often used

74

to make judgments of their performance, with 20 responses scoring in that category. In
the third wave the category most often mentioned as to where interns gathered
information to make a judgments of their performance was in the instructional category
with 26 responses scoring in that category. The second highest category for both wave
two and wave three was management (see ﬁgure 4.6).

Diﬂiculties and eﬂort in lesson presentation and planning

The second topic area of the open ended questions asked interns to reﬂect on the
perceptions of the difﬁculties in presenting the lessons and the effort the interns
perceived they put forth in the preparing for their lessons. In wave one the highest count
(33) was no response, with the second highest count at 17 responses indicating the interns
felt the lesson was easy to present. In wave two and three, easy was the highest category
each wave with 32 and 29 indications that the lesson was easy to present, with the second
highest category for wave two and three being “difﬁcult” indicating that there 20 and 21
4 responses felt it was difﬁcult to present the lesson (see table 4.7).

The next open-ended question for the second topic area asked for the interns’
perception of effort expended in preparing the lesson. For wave one of administration the
highest response was no response because a large number had not been formally
observed and therefore left the question blank. However in wave two and wave three 26
and 31 of the interns’ responses indicated that they had put forth a substantial amount of
effort and the second highest for both of those wave were “no perception” with 23 and 28
of the responses tallied for that category. This indicates that the most of the interns felt
they had put a substantial effort or a judgment of the effort was not clearly indicated in

the response (see ﬁgure 4.8).

75

"I Easy DSomewhat I Difﬁcult ENo Response El Uncodable

33

32

 

20

13 E
8
H ' 4
.2 2
a : all

Wave One Wave TWO

 

 

 

29

Elaﬂ

Wave Three

 

 

 

Table 4.7. Interns’ perception of difﬁculty in lesson presentation.

El Little/None 3 Moderate I Substantial GNP. II No Response

 

 

 

 

 

 

35
1 mp
26
23
1 9
1 l
9
H 4
Wave One Wave Two

Figure 4.8. Perception of effort in preparing lesson

76

3]

llllllll“
N
_

F

 

:1...

Wave Three

Agreement

The “agreement” question grouping examined the degree to which interns agreed
with feedback given by supervising personnel. The overwhelming majority of the interns
in all three waves agreed with the feedback given to them by either the university ﬁeld
instructor or the cooperating teacher. None of the 69 respondents in the ﬁrst wave
disagreed with their supervisors. In the second wave of survey collection, there were
three responses (4%) indicating that they somewhat agreed/disagreed and one response (<
1%) disagreed with the field instructor out of 72 responses. In the third wave, there were
three responses (4%) indicating that they somewhat agreed/disagreed with the feedback
out of 71 statements, and no responses indicated that they disagreed with the ﬁeld
instructor.

Seldom did interns write about disagreements with their cooperating teacher. In
the ﬁrst wave, 1% of the interns’ statements somewhat agreed/disagreed and 4%
disagreed out of 68 statements. Wave two had 7% of the statements indicating that the
interns somewhat agreed/disagreed and 3% disagreed out of 76 statements. In wave three,
of 71 statements, 4% of the statements only somewhat agreed/disagreed with the

feedback given by the cooperating teacher.

77

CHAPTER FIVE
DISCUSSION

The beneﬁts of higher teaching self-efﬁcacy have been documented in a variety of
studies (Armor et al., 1976; Gibson & Dembo, 1984; Henson, 2001; Hoy & Woolfolk,
1990; Simmons et al., 1998; Tschannen-Moran et al., 1998, 2001). Ross (1994) found
robust correlations between teacher self-efﬁcacy and use of effective teaching practices
which, in turn, are beneﬁcial for students with disabilities (Chester & Beaudin, 1996;
Bender & Ukeje, 1989; Gibson & Dembo, 1984; Soodak & Podell, 1993). Studies
(Bender & Ukase, 1989) have found a positive correlation between teacher use of
effective instructional practices and high teaching efﬁcacy. For example, teachers with
higher teaching self-efﬁcacy are less critical of mistakes (Gibson & Dembo), they persist
in the task of teaching even when faced with failure (Gibson & Dembo), are less likely to
refer to students to special education (Soodak & Podell), and positively affect students’
self-efﬁcacy (Midgely, Feldlaufer, & Eccles, 1989).

Preservice teachers who have higher self-efﬁcacy have similar instructional
behaviors to those of in-service teachers who have more experience. Teacher level of
satisfaction with support and preparation during the internship year of teaching is an
indicator of higher teaching self-efficacy (Hoy & Spero, 2005). General education
student teachers who believe that they have the knowledge, skills, and ability to perform
the tasks required to teach students tend to have high teaching efficacy;” (Tschannen-
Moran et al., 1998). Research also shows that preservice teachers’ teaching self- efﬁcacy
is more malleable during times of inexperience (Chester & Beaudin, 1996) and formal

knowledge can have an effect on preservice teachers’ efﬁcacy (Masengill-Shaw, Dvorak,

78

& Bates, 2007). It also appears that preservice teachers’ teaching self-efﬁcacy can be
inﬂuenced by contextual factors or sources of self-efficacy than in-service teachers
(Tschannen-Moran & Woolfolk Hoy, 2007).

The purpose of this study was to compare the teaching self-efficacy of two groups
of interns at three points in time over the semester using an integrated model of teaching
efficacy as a conceptual framework. The goal of this research was to understand more
about the teaching self-efficacy of interns and to provide more information regarding the
changes in and comparison of teaching self-efﬁcacy proﬁles of interns in two different
preparation programs, general and special education It was also an endeavor to answer a
call by Pugach (2001) and Brownell & Pajares (1999) to broaden the literature base of
comparative studies between preservice special educators and general educators.

Dijfkrences in Preparation Groups

The ﬁrst question asked if there was a difference in teaching self-efﬁcacy between
general and special education preservice teachers. Over the course of a semester, there
were no statistically signiﬁcant differences in the TSES sum scores between the interns
preparing to be general educators and those preparing to be special educators on any of
the three measurement waves. This indicates that general education and special education
interns teaching self—efficacy changed in similar ways. In addition, it did not matter
whether the special education interns were in their special education or general education
placement. The scores of special education interns in the two different placements were
not statistically signiﬁcantly different nor were they statistically signiﬁcantly different

from the general education interns.

79

It appears that no matter which preparation program or placement option (special
education interns had two different placements); the two groups of interns did not have
statistically signiﬁcant differences in their teaching self-efﬁcacy. Interns in both
preparation programs at this university will have another semester of internship and,
therefore, differences may appear later in the internship. However, differences did not
appear in the ﬁrst semester. These results suggest that, at least within this sample, that
placement and preparation program are not signiﬁcant factors in the development of
teaching self-efﬁcacy. The placement did not affect the developing TSES scores as
general and special education placements developed over the semester in the same
manner. The placement in type of school (urban, suburban and rural) was also not a
determining factor of the development of TSES along with the type of preparation
program.

Changes in Teaching Self-Efficacy

How teaching self-efﬁcacy changes over the course of one semester of student
teaching was the second question investigated. Tschannen-Moran et al. (1998) found that
preservice teachers teaching self-efﬁcacy increases during the course of student teaching.
The increase in teaching self-efﬁcacy through the semester, as Tschannen-Moran et al.
(1998) hypothesized, might be related to the acquisition of mastery experiences along
with vicarious experiences and verbal persuasion that informs preservice teachers’
judgments about their teaching self-efﬁcacy.

The means of teaching self-efficacy scores, as measured by the TSES,
increased from an average of 149 to 162. A pairwise comparison indicated there was a

signiﬁcant difference in the means from wave one to wave three and from wave two to

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wave three. This shows that changes in teaching self-efﬁcacy occurred primarily after the
second wave of administration. The change of teaching self-efficacy was typical of other
studies (Knoblauch & Woolfolk Hoy, 2008) in which researchers also found an increase
from pre to post survey. However, it appears that for this sample the changes occur about
half way into the ﬁrst semester of the internship. Hoy and Woolfolk (1999) found that
preservice teachers entered the student teaching experience with a higher sense of
General Teaching Efficacy (GTE) than when they ﬁnished the experience. Conversely
preservice teachers Personal Teaching Eﬁicacy (PTE) increased ﬁom before student
teaching to post student teaching. Interns, in this study, steadily increased what over the
semester, mirroring the results of PTE construct in the Hoy and Woolfolk study.

One major factor explaining the differences between the Hoy and Woolfolk study
and this study is Hoy and Woolfolk measured teaching self-efﬁcacy using the Gibson and
Dembo (1984) instrument. This instrument situated the concept of self-efficacy with two
constructs, GTE and PTE, and within those constructs GTE was the less deﬁned of the
two and many disagrees over the conceptual underpinnings of GTE. Emmer and
Hickman (1990) speculated that GTE is actually a construct addressing external factors,
others (Ashton & Webb, 1986; Gibson & Dembo, 1984; Riggs & Enochs, 1990; Soodak
& Podell, 1996) categorized GTE as an outcome expectancy, a belief that an action will
lead to learning. In personal communication with Bandura, Woolfolk and Hoy (1990)
disagreed with the translation of the GTE as outcome expectancy construct (1990).
Bandura argued that “outcome expectation is a judgment of the likely consequence of an
action, whereas efficacy expectation is the judgment about ability to perform an action”

(as cited in Woolfolk & Hoy, 1990, p. 82). The TSES appears to represent the PTE

81

construct as in both studies the teaching self-efﬁcacy increased over the course of a
semester.

Factors Inﬂuencing Teaching Self-eﬂicacy

The third research question asked about factors inﬂuencing teaching self-efﬁcacy.
A multiple regression model was used in an attempt to isolate factors that contributed to
self-efﬁcacy scores in the third wave. The sum of the second wave was the highest
predictor of the sum of the third wave. The only other variable that was signiﬁcant in the
multiple regression analysis was the reported amount of teaching time measured at the
third wave and it only accounted for 3% of the variance. Unfortunately, this type analysis
cannot determine whether or not hours of teaching during the internship are causally
related to self-efﬁcacy. Nor does the analysis suggest which came ﬁrst, whether an intern
has a higher teaching self-efﬁcacy therefore engages in more teacher-like behaviors, or if
the experience of engaging in teacher-like behaviors increases teaching self-efficacy.

None of the other variables, such as grade point average, credit hours or students
in the class, predicted the sum score in the third wave. Nor did school type (urban,
suburban, or rural) have an inﬂuence on preservice teaching self-efﬁcacy. This is similar
to Knoblauch et al. (2008) ﬁnding that individual teaching self-efﬁcacy scores of
preservice teachers increased signiﬁcantly after they engage in student teaching,
regardless of the type of placement of the school. This result led the authors to conclude
that setting was not a signiﬁcant factor in preservice teaching self-efﬁcacy, which seems

to be the case in this study

82

Proﬁles of those with High and Low Teaching Efficacy
To learn more about the proﬁles of the interns who scored either the lowest scores
or the highest scores according to the TSES, 20% of the participants from the total data
set (10% from the high group and 10% from the low group) were examined to determine
if distinctive or universal qualities for these group. There were three low groups and three
high groups to represent each wave of the survey. There were some notable differences
and similarities between the high and low groups.

Differences

The ﬁrst difference between the groups was that those in the lower group had a
tendency to stay in the lower group at all three waves, whereas those in the higher group
moved out of the top eight positions more often. In the low group there were four interns
(50%) who stayed in the low position for all three waves, whereas in the high group there
were only two interns (25%) who stayed in the high position for all three waves. This
appears to conﬁrm that those who score themselves lower on teaching efﬁcacy may be
more at risk than others for eventually developing into classroom teachers who have a
lower teaching self-efﬁcacy. The lower group appears to be less malleable than the higher
group in terms of teaching self-efﬁcacy. The standard deviation for the lower group
consistently increases and in the third wave appears to be twice as large as the high
group, possibly indicating those who scored in the higher group had scores that tended to
cluster together than the lower group.

More special education interns were in the high group than were general
education interns at each wave point. At the ﬁrst and third time points, three of general

education interns (n=43) and ﬁve special education interns (n=25) were in the high group

83

(8 possible positions) whereas, in the low group there were six general education interns
(n=43) and two special education interns (n=25) out of eight possible positions. During
the second time period, the composition of the low group did not change; however the
high group did change, having ﬁve general educators and three special educators in the
high group. As a group, special educators more often were among the top 10% of the
high teaching self-efﬁcacy groups, meaning that rated themselves higher more often than
the general education counterparts. There were fewer special education intern participants
than general education interns yet they occupied more of the spots in the higher group.
This could also indicate that more of the special education interns were near the higher
10%.

However, the lack of progress from the low group could be a function of the
interns with lower scores tending not to increase their teaching self-efficacy therefore
staying in the low group as opposed to those individuals in the higher group. Those with
lower teaching self-efficacy may have more difﬁculty increasing their teaching self-
efﬁcacy due to the cyclical nature of self—efficacy and if they have negative experiences
due to lack of self-efﬁcacy those experiences feed in to future expectations of teaching
performance and continue to create a lower self—efﬁcacy.

Pajares (1996) discussed characteristics of people with higher self-efﬁcacy,
stating they have a tendency to persist in a task and have more resilience whereas people
with lower self-efﬁcacy have a tendency to perceive situations as more difﬁcult than
those who have a higher self-efficacy (1996). This study suggests that there appears to be
some relation of the characteristics of people who have a general higher self-efﬁcacy and

those who have higher teaching self-efﬁcacy. Bandura (1977) suggests that teacher’s

84

self-efficacy beliefs are related to the goals they set, the time they invest in teaching, and
their ability to persevere in the face of setbacks (Tschannen-Moran et al., 1998). It is also
suggested that “teachers who do not expect to be successful with certain students are
likely to put forth less effort in preparation and deliver of instruction and give up easily at
ﬁrst sign of difficulty” (Tscannen-Moran & Hoy, 2007, p.945).

The interns who scored in the high TSES group consistently reported more
teaching hours in the placement class. The high group could have more teaching hours
due to their high self-efﬁcacy and, therefore, choosing to invest more time into teaching
or willing to risk more (i.e. not make a mistake) and, therefore, teach more. Or, perhaps
the reverse is true, i.e., they had higher self-efﬁcacy because the coopering teacher (CT)
or ﬁeld instructor (FI) allowed the intern more opportunities to engage in teacher-like
behavior, which, in turn, fed an intem’s teaching efficacy and increased it. It is
impossible from this study to determine if a preservice teacher teaches more in the CTs’
classes because they have higher self-efficacy, or if the time allotted by the CT for the
student intern to teach has informed the intem’s self-efficacy by giving them more
mastery experiences.

High TSES group of interns also reported taking more credit hours for their
degree, and having lower GPAs then those in the low TSES group. Perhaps higher self-
efﬁcacy ratings translated to preservice teachers via the lower GPA but have the
resiliency and risk to take more credit hours. This could partially explain why those with
higher teaching self-efﬁcacy also engaged in more credit hours, i.e., they were willing to

risk their GPA to take more credit hours. Future considerations for studying teaching

85

self-efﬁcacy should be the impact grades have at the undergraduate years and how grades
inform ones teaching self-efﬁcacy.
Similarities

The demographics of the interns’ placement classrooms were very similar in both
the high and low groups. These classes were comparable in both class size and the
number of students with individual education plans (IEP). Neither the number of students
nor the number of students with IEPs had a remarkable inﬂuence on the outcome of the
interns TSES score in terms of the highest group and lowest group. This could indicate
that class size or diversity of the class does not negatively or positively affect the
teaching self-efﬁcacy of interns according to the TSES.

High and Low TSES Groups and Judgments of Performance

Because those with lower self-efﬁcacy have a tendency to view their situation as
tougher than those with higher self—efﬁcacy, and possess a narrow vision of how to
problem-solve (Pajares 1996) the researcher expected that this would be reﬂected in the
eight open-ended survey questions from the low TSES group. The responses from the
group of interns in the high and low TSES groups in term of “success or failure and
why,” “difficulty and effort,” and “agreement with supervisors” were all similar.

One question at the end of the survey that was not analyzed for the whole group
because it was not a mandatory question and asked if participants had anything else they
wanted to share. It was in this response to this last question that the answers appeared to
show a difference in demeanor of the interns in the high and low groups as the comments
were likely to be more positive from those in the higher group. The high group and low

group both responded to the question (it was optional) at the same rate however, the high

86

group had a tendency to express excitement for the process of student teaching. The
following comments are two examples out of the four responses received in the ﬁrst
wave:

“I'm so enlightened to be learning so much about being a teaching [sic]. I'm looking
forward to a successful year student teaching.”

“I am loving my internship and am so glad that we will be well prepared after a whole
year of teaching. I also recommend urban schools because you get to see everything that
may present problems in your future teaching career and can learn about them before you
have to deal with them on your own!”

The low group in the ﬁnal question had two interns who voiced concern about
entering the work force as a teacher: Both of these comments were from interns who
were in the low group at wave one and only ﬁve of the eight interns answered the
question. Both of these interns did not remain in the low group and their sum scores did
increase as the semester increased.

“I feel frustrated because so much of the work so far has been labor intensive, but with
nothing really showing for the work. I think it will get better, but right now it is really
hard to view myself as a teacher who is actually effective and engaging.”
“So far it is going pretty well, but exhausting. Going into this internship I wasn't fully
sure of my decision to go into teaching, but I am starting to see myself in this role a bit
more. I'm not sure if it will be my lifelong career, but I am enjoying it.”

The initial wave of responses to the open ended optional question appears to be
conﬁrming previous studies about self-efficacy (Pajares, 1996) that those with lower self-

efﬁcacy appear to be more negative in general. However those in the low group, who

87

wrote about the concerns of entering the work force as teacher, were interns who did not
stay in the low group. Bandura (1994) indicates that those with lower self-efﬁcacy are
less likely to persist in the task and either readjust or give up their goal. Perhaps, those
interns readjusted their goal and moved out of the lower group.

The high and low group, at the second and third wave, respond to the optional
question with noticeable differences. Those in the higher group answered the question
more frequently (5 out of 8) and wrote longer responses (average word length 128 vs. 79)
and less likely to include a negative statement with a positive statements. Two comments
from the high TSES group are below.

“I am truly happy to be in a classroom where I have been allowed to teach the ELA
curriculum since the second week of school. My CT has conﬁdence in my abilities and
skills and he relinquishes the reins completely when I'm teaching LA or science,
observing and then giving me constructive criticism and feedback every few weeks. He
wants me to be the best professional that I can and I take his feedback very seriously. He
points out little things (like me re-voicing students' statements and questions) and asks
me questions about howl think I'm being perceived and judged by others. I have heard
from other interns that their CTs don't let them teach and/or do not communicate well
with them. I know that my CT trusts my abilities and experience with children and he
wants me to be the best that I can be.”

“I am loving this experience, I have really enjoyed being able to sit in on parent teacher
conferences with my CT because I have learned so much about my students from meeting
and talking to their parents. I hope I am able to absorb this experience completely

because sometimes everything is happening so fast that I feel I am just an observer.

88

Students have really started to open up, and they all noticed when I was present on a
Thursday and not at my University classes. They are genuinely interested in learning and
I just hope they are getting as much ﬁ'om me as I am getting from them.”
Only three interns in the low TSES group at the second wave point, and four interns at
the third wave point answered the optional question. The responses they wrote were
shorter and expressed more doubt and concerned:
“I feel that it is difficult not to doubt yourself, because you have so many pe0ple
observing and watching you.”
“I think that things are going great. I am getting much more responsibilities now. I am
still having problems with one student in particular with behavior issues. My CT, the
principle [sic] of my school, and his previous teachers have no idea of how to handle
him.”
The two aforementioned comments from the interns in the high group at the second wave
were not in the high group for all three waves, yet those aforementioned comments from
the interns at the low group at the second wave were in the low group at all three waves.
Perhaps at this point in the semester those with lower teaching efﬁcacy are more likely to
remain in the low group, unlike in the ﬁrst wave, it appears that those who took the time
to reﬂect did not increase their teaching self-efﬁcacy.
Information lntems Considered for Perceptions of Success

In order to identify the information interns use to make judgments of their
teaching self-efﬁcacy, eight open-ended questions were included at the end of the survey
while only seven were analyzed as mentioned earlier. Survey question one asked if an

intern felt successful in their teaching and why they felt that way made up the ﬁrst topic

89

 

area. During the ﬁrst wave of questions, many interns did not classify their observations
as successful because many had not had an observation at that point in time. In the
second wave of administration, more responses 63% indicated more interns felt they had
done well or had rated themselves as “successful” in their most recent observation and in
the third wave 60% of the interns felt successful. Whereas, 13% of the responses felt they
were unsuccessful in the second wave and 3% in the third wave. There appears to be a
relation between feeling successful and the current observation schedule. The growth in
the sum TSES score appeared after the second wave, which was scheduled in attempt to
capture interns teaching self—efficacy after a formal observation occurred (wave two).
Earlier statistics (t-tests) indicated that the differences between the sum scores appear
from wave one and wave three and wave two and wave three. A change occurred from
wave two and wave three with higher TSES score and more interns indicating that they
felt successful. Chester and Beaudin (1996) studied newly-hired teachers and found that
common school practices, such as more than ﬁve visits from a supervisor, positively
inﬂuenced the teaching self-efﬁcacy of new teachers. This ﬁnding may suggest that visits
from a ﬁeld instructor positively inﬂuence the sense of teaching self-efﬁcacy of interns
and, thereby, highlights the importance of those visits.

Other changes from wave two to wave three also included the information that
interns used to make judgments about their performance. Interns considered their success
based on feedback received from the ﬁeld instructor, the cooperating teacher, and/or
student performance. The interns wrote more in quantity and details about the
information that informed their teaching self-efﬁcacy judgments as the semester

progressed. There were 73 participants but only 25 offered a response (responses leﬁ

90

blank or that did not answer the “why” question were not scored) in the ﬁrst wave.
However, this number jumped to 79 in the second wave of administration and 93 in the
ﬁnal wave). In the third wave, the responses had the most depth; often indicating more
than one type of feedback was used in the judgment of the interns’ success. Over the
course of the semester, the interns’ identiﬁcation of the feedback grew in length with
more details, as indicated by scoring in more than one category at the second and third
wave. In the ﬁrst wave, there was not much indication of why an intern felt successful.

Along with detailed and longer responses, the individual to whom the intern
looked to for the feedback changed over the semester. The ﬁeld instructor category was
the largest in the second wave, with 25% of the responses indicating that information for
judgment of the interns’ teaching self- efﬁcacy came from the ﬁeld instructor. Only 3%
of the responses indicated feedback from the cooperating teacher was used to make
judgments about the interns’ performance. This could be due to the survey question
placement, as the question was asked immediately following a question that asked the
intern about the most recent observation conducted by the ﬁeld instructor. Other
possibilities could be, because observations were a part of the university requirement, the
cooperating teacher did not oﬁer feedback to the intern on that occasion and, therefore,
the intern did not consider it in his/her response or that the cooperating teacher did not
provide formal feedback to the intern. Borko and Mayﬁeld (1995) found that cooperating
teachers believed the major source of feedback about an intem’s teaching should not
come from them but, rather, the experience of actually being in front of the classroom
and engaging in teacher behaviors. Another consideration regarding the lack of

cooperating teacher feedback to the intern is that the coopering teachers may not want to

91

potentially provide conﬂicting feedback and, therefore, do not offer much (Borko &
Mayﬁeld).

Earlier in the semester, interns relied more on their ﬁeld instructors to tell them
they had been successful. As the semester progressed, interns considered their students’
feedback (both direct and indirect) in making judgments about their own teaching self-
efﬁcacy. lntems in the third wave were less likely to indicate they felt successful based
on the direct inﬂuence of the ﬁeld instructor (12% down from 25%), e.g., “I was
successful because my Fl said I did well.” It is as if the interns begin to conceptually
understand that teaching is less about a performance but more about students’ learning.
Tshannen-Moran et al. (1998) explained, “Cognitive processing determines how the
sources of information will be weighed and how they will inﬂuence the analysis of
teaching task and personal teaching competence” (p. 230). lntems in the third wave were
more likely to respond the source of student feedback in terms of performance of the
student to make their judgments of teaching self-efﬁcacy. Under Bandura’s (1994)
construct of self-efﬁcacy motivational process suggests that teachers with high self-
efficacy are more willing to take responsibility for student achievement; they believe that
speciﬁc teaching strategies will produce the desired outcome and work to achieve small,
attainable goals (Bandura, 1994; Ross, 1994). Interns pointed to indicators such as
student assessment results or other ways in which students demonstrated knowledge of
what the interns were trying to teach.

This increase in responses about the student feedback as the semester progresses
could potentially be a sign that a change is occurring within the interns regarding their

conﬁdence, belief, and attention to the act of teaching. In the second wave the student

92

feedback often listed was in the management category, 32%. lntems would indicate the
observation went well with the exception of something they felt was a class- management
issue. In the third wave, interns still wrote about management however instructional
strategies had an increase (ﬁ'om 21% to 33%) in feedback. By the second wave of
administration, more interns identiﬁed student feedback (both direct and indirect) as
reasons for feeling successful or not. This was true for the third wave of administration as
well. The number of responses and the shift in focus of the feedback was less on the
responsibility of the ﬁeld instructor and more on the students. This shift was seen in the
interns’ consideration of the information utilized to make their judgments about their
teaching self-efﬁcacy.

Agreement with Supervising Personnel

At all three waves, the majority of the interns agreed with the feedback given by
either the ﬁeld instructor or the cooperating teacher. If the interns did disagree with
supervisors’ feedback, which was rare to begin with, it was more often that the intern
disagreed with the coopering teacher (CT) rather than the ﬁeld instructor The
disagreements that occurred happened in the second wave and out of 73 responses only
out three disagreed and two out of three were disagreements with the cooperating
teaching. A possible explanation for this ﬁnding is that student teaching is generally
meant to encourage interns; therefore, there is a “high priority on being positive in the
[supervisors] interaction with student teachers to build their conﬁdence” (Borko &
Mayﬁeld, 1995, p. 516). Interns wrote that often feedback ﬁ'om their ﬁeld instructors was
more about their disposition and less about how they taught. (i.e. “The last lesson my

ﬁeld instructor observed, the most signiﬁcant impression she left with me was that my

93

having a generally calm personality translated to the children and how they worked in
calm matter.”) This response was typical of the feedback from the ﬁeld instructor that the
interns wrote about, suggesting that the signiﬁcant impressions from their observation
were usually positive in nature and therefore more difﬁcult to disagree with the feedback.

Eﬂort and Dzﬂiculty in Lesson Planning

Perceptions of effort and lesson difﬁculty remained somewhat constant through
each of the three waves of the survey. The responses indicated the majority of the interns
felt presenting their lesson was easy, with the exception of the ﬁrst wave, where interns
indicated it was not an applicable question because they had yet to have an observation.
When viewing perception of effort more of the interns indicated that their perception of
teaching the lesson was easy (44%) in wave two and (40%) in wave three. However,
perception of the effort extended for the lesson observed was reported as substantial
(3 6%) and (42%) for waves two and three respectively. It could be the case that the
lesson was considered easy to teach because of the large amount of effort expended in
preparation. For example, one intern reported that, “The lesson was easy because I was
prepared.” However, occasionally they would say it was easy because it was routine (a
classroom procedure) and not a “real” lesson.

While coding for perceptions of effort there were responses ﬁ'om interns that did
not address effort exerted in planning therefore making it difﬁcult for the researcher to
quantify the perception of the effort extended. The category was titled “N. P.” for “no
perception” and, as discussed in the previous chapter, meant the intern never indicated if
the effort extended was a substantial amount or a small amount. Interns would write

about the amount of time they took to prepare the lesson, whether it was hours of

94

 

research, meeting with their cooperating teacher, or preparing the materials; however,
sometimes they failed to indicate if they considered this to be a little effort or a large
amount of effort. This made it impossible to judge the intem’s perception of effort
extended. It was unfortunate that the intern did not provide a “judgment” of the effort
because this “N .P.” category became the second largest response in the second (n=23)
and third (n=28) waves.
Limitations

There are several limitations of this study. First, as is true of other research about
self-efﬁcacy, all data collected in this study were self-report data. Responses might be
inﬂuenced by a social desirability bias, that is, participants tend to report what they
believe a researcher wants to hear and in a manner that reﬂects positively on their
abilities (Cook & Campbell, 1979). Another potential limitation, inherent in survey
research, is selection bias. Perhaps those interns who have a higher teaching self—efﬁcacy
are also the ones who respond to a request for a survey whereas those who do not respond
might have a lower teaching self-efﬁcacy. This would skew the results in favor of those
who have higher teaching self-efﬁcacies. If this is the case, this study presents a very
limited view, especially when comparing the high teaching self-efﬁcacy group versus the
low teaching self-efﬁcacy group because there would be less of an opportunity to study
those who might have had lower teaching self-efﬁcacy than the participants. However,
the analysis of interns who left who left the study from wave one to wave two and from
wave two to wave three, as discussed earlier, suggests that this was not the case. Those
participants who dropped out of the study had a wide range of sum scores and did not

cluster around the lower end of the scores.

95

 

The ability to generalize to a larger population due to other factors is also a
limitation. The sample was drawn from one university whose student teaching internship
requires one year of participation, rather than 16 weeks, as do most traditional
preparation programs. The participants were mostly white rniddle-class females, as are
most students enrolled in the program, limits the ability to compare to a more diverse
group of interns. Also the nature of the ﬁeld placements, the nature of the cooperating
teacher, and the number of observations are all very speciﬁc to the study and this limits
ability to generalize.

Implications and Future Directions

Student interns at this institution have similar teaching self-efficacy, no matter
which program they complete. During the fall semester of their internship there is an
increase in their sense of teaching self-efficacy between the beginning and the end of the
ﬁrst semester. The information interns use to make judgments of successful teaching
experiences change from ﬁeld-instructor feedback to more student-centered information.
This study appears to have captured a glimpse of a transformative passage for interns as
they progress through the internship. When they start the internship, these preservice
teachers have a lower self-efﬁcacy and seldom report information used to make
judgments about the success of their observations. From wave one to wave two there was
not a statistically signiﬁcant increase in the TSES scores, nor were there many responses
from the interns indicating the information they used for judgments of success. However,
from wave two to wave three there is a signiﬁcant increase in scores along with more
responses from the interns indicting that information from the ﬁeld instructor helped

shaped their judgments about a successful observation. The ﬁeld instructor is a person

96

 

who helps shape the judgments the interns make about themselves. It wasn’t until after a
formal observation (wave two) that the interns’ self-efﬁcacy increased indicating that the
act of being formally observed may play a very important part of the intern experience.

These results demonstrate that the preservice teachers at this institution developed
a higher teaching self-efﬁcacy as the semester progressed, without any regression over
the course of the semester. Thus, it may be the case that teaching self-efﬁcacy will
continue to increase as the internship progresses in the spring semester. If this is the case,
it might be possible to speculate that programs such as this one, are preparing a new work
force that have a high teaching self-efﬁcacy and, perhaps, the effective teaching
behaviors associated with high teaching self-efﬁcacy. Self-efﬁcacy researchers would
beneﬁt ﬁ'om more long term studies to see how preservice teachers’ self-efﬁcacy
translates into their classroom when they enter the workforce.

Other teaching self-efﬁcacy studies indicate that teachers with a higher teaching
self-efﬁcacy possess a higher level of satisfaction with their support and preparation
during the internship year (W oolfolk Hoy, & Burke Spero, 2005). If interns in the ﬁrst
semester of student teaching develop a higher teaching self-efﬁcacy as the semester
progresses there is possibility that they will carry that into ﬁrst year of teaching and feel
well prepared by the institution. The preparation institution will beneﬁt because the new
teacher will act as an ambassador of sorts and promote the good will and preparation of
having been prepared at their institutions through the ﬁrst year of teaching.

For teacher educators, a lower teaching selﬁefﬁcacy score may be of concern as
interns enter the classroom. In this sample, the lower 10% scores appear relatively

constant. If lower scores are harder to increase then interns might enter into the

97

workforce with lower teaching self-efﬁcacy. Teachers in their ﬁrst year of teaching with
low self-efficacy may not use instructional practice that are as effective (Bender & Ukeje,
1989), and may be less likely to improve his/her self-efﬁcacy. Pajares (1996) noted that
teachers who have low self-efﬁcacy are more prone to depression, have a narrow
perspective on problem-solving, and believe their situation is more challenging than it
truly is, all of which foster stress and in turn increases teacher burnout (Pajares, 1996).
Ways to improve low self-efﬁcacy for the preservice teachers is an area that needs to be
examined in future research.

While this study began to look at the feedback an intern used to make judgments
about their performance during their student teaching experience more research needs to
be conducted to tease out the effect of different sources that inform teaching self-efﬁcacy.
Empirical evidence is nonexistent when examining how sources contribute to teaching
self-efficacy (Henson, 2001). This study touched on the importance and transformative
journey that occurs for interns however, it is difﬁcult to sort out what has the most impact
to the interns’ teaching self-efﬁcacy. Understanding more about the effects of sources on
teaching self-efficacy would allow educators to emphasize sources that produce the
biggest impact. Since teaching self-efﬁcacy is related to many positive attributes in the
classroom information about how to affect the change and nurture the development of

teaching self-efﬁcacy should begin the next generation of investigations.

98

Appendices

99

Appendix A

Survey Instrument

Please answer the following questions.

1. After your receive your certiﬁcation will you seek employment as:
General Education Teacher
Special Education Teacher
school employee other than a teacher
None of the above

2. How would you best describe the school of your placement?
Inner City
Suburban
Rural

3. List the grade where you will be completing your fall 2008 internship.

4. List the number of students in your class (Fall 2008) where you are completing
your internship?

6. How many students do you have in your general education classroom internship
(fall 2008) that have an IEP or are receiving some type of special education
services?

7. Has your placement changed since you last took the survey?
8. If the answer is yes above, please list the name of the new school and address.

9. Including yourself and your cooperating teacher how many adults are in the
general education classroom helping during the day. If you are in a special
education internship please write: SPED

10. Approximately, how many hours of typical school day do you engage in teacher
like behaviors (e.g. tutoring students, grading, presenting a lesson, writing lesson
plans, following up with parents or other school professional, conferencing with
students)

none

under one hour

one to two hours

two to three hours

three to four hours

four to ﬁve hours

ﬁve to six hours

six to seven hours

100

 

more than seven hours

11. Directions: This questionnaire is designed to help us gain a better understanding
of the kinds of things that create difﬁculties for teacher interns. Please indicate your

opinion about each of the statements below keeping in mind the students in your

classroom where the majority of your internship takes place.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

N A So Mo Ver
ot Litt me stly y
at le wh Cer Cer
A Cer at tain tain
ll tain Cer
tain
a) How certain do you feel that l 2 3 5 7 9
you can get through to the most
difﬁcult students?
b) How certain do you feel that l 2 3 5 7 9
you can help your students think
critically?
c) How certain do you feel that 1 2 3 5 7 9
you can control disruptive
behavior in the classroom?
(1) How certain do you feel that 1 2 3 5 7 9
you can motivate students who
show low interest in school work?
c) How certain do you feel that 1 2 3 5 7 9
you can make your expectations
clear about student behavior?
f) How certain do you feel that you 1 2 3 5 7 9
can get students to believe they can
do well in school work?
h) How certain do you feel that 1 2 3 5 7 9
you can respond to difﬁcult
questions ﬁom your students?
12. Please continue to rate the statements below.
Not A So Mo Ver
at Litt me stly y
All le wh Cer Cer
Cer at tain tain
tain Cer
tain
a) How certain do you feel that 1 2 3 5 7 9

 

 

 

 

 

 

 

 

 

 

 

101

 

 

 

you can establish routines to keep
activities running smoothly?
b) How certain do you feel that l 2 3 4 5 6 7 8 9
you can help your students’ value
learning?
c) How certain do you feel that l 2 3 4 5 6 7 8 9
you can gage student
comprehension of what you have
tagght?
d)How certain do you feel that you 1 2 3 4 5 6 7 8 9
can craft good questions for your
students?
c) How certain do you feel that l 2 3 4 5 6 7 8 9
cu can foster student creativity?
f) How certain do you feel that you 1 2 3 4 S 6 7 8 9
can get children to follow
classroom rules?
g) How certain do you feel that 1 2 3 4 5 6 7 8 9
you can improve the understanding
of a student who is failing?
h) How certain do you feel that l 2 3 4 5 6 7 8 9
you can calm a student who is
disruptive or noigy?
i) How certain do you feel that you 1 2 3 4 5 6 7 8 9
can establish a classroom
management system with each
group of students?

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

13. Please continue to rate the statements below.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Not at A So M Ve
All Lit me ost ry
tle wh ly Ce
Ce at Ce rta
rta Ce rta in
in rta in
in
a)How certain do you feel that 1 2 3 4 5 6 7 8 9
you can adjust your lessons to the
proper level for individual
students?
b)How certain do you feel that 1 2 3 4 5 6 7 8 9
you can use a variety of
assessment strateges?

 

102

 

c) How certain do you feel that 1 2 3 4 5 6 7 8 9
you can keep a few problem
students form ruining an entire
lesson?

 

d) How certain do you feel that 1 2 3 4 5 6 7 8 9
you can provide an alternative
explanation or example when

 

 

students are confused?

e) How certain do you feel that l 2 3 4 5 6 7 8 9
you can respond to deﬁant

students?

DHowcenaindoyoufeelthat 1 2 3 4 5 6 7 8 9

you can assist families in helping
their children do well in school?

 

g)Howcertaindoyoufeelthat l 2 3 4 5 6 7 8 9
you can implement alternative
strategies in your classroom?

 

h) How certain do you feel that 1 2 3 4 5 6 7 8 9
you can provide appropriate
challenges for very capable
students?

 

 

 

 

 

 

 

 

 

 

 

 

Think back to your most recent visit from your university ﬁeld instructor—that is, the
instructor from MSU who visited you and provided feedback about your ﬁeld experience.
Please answer the following questions with the most recent visit in mind.

14. You may have some impressions (good and bad) on how well you completed
your goals (for example: teaching students a learning objective, tutoring a student,
managing the classroom or other teacher type tasks) during that observation.
Please explain what your most signiﬁcant impression was of that observation
(successful or unsuccessful) and why?

15. How difﬁcult was this lesson or activity for you to teach and why?

16. How much effort did you put into planning this lesson or activity? Please
explain.

17. Please describe the speciﬁc feedback you received from your university ﬁeld
instructor.

18. Did you agree or disagree with the feedback, why and why not?

Think back to the most recent feedback you received ﬁom your cooperating/collaborating
teacher, either through formal or informal observations, or through casual conversations.

103

 

19. Please describe speciﬁc feedback you most recently have received from your
cooperating/collaborating teacher.

20. Did you agree or disagree with the feedback, why and why not?

21. Is there anything else you care to share about your internship?

Thank you for your time and effort. If you have any questions or additional comments
please email Carrie Anna Courtad at courtadc@msu.edu

104

 

Appendix B

 

Codebook Question Success/Why

 

Categories

Quotes -Not corrected

 

NA=Means they didn’t answer the questions
because they haven’t had an observation yet

My ﬁeld instructor really hasn't seen
me actually teach in the classroom yet.
The only time that she has come in has
been when my CT has been teaching
and I have been interacting around the
classroom At this point, I can 't
thoroughly answer this question

I have not yet taught a lesson on my
own.

 

 

Successﬁrl
They say that their perception is positive ,
they felt successful .

 

have reached my goal of explainin
borrowing and carrying during
addition and subtraction of two digit
numbers. I was successful after two
days of instruction because the
students had began ton understand
that borrowing from the tens place to
get more ones was necessary.

I think that the observation went well
because students were engaged

I have only read a story to the students
so far and I feel that they enjoyed it
and were able to answer correctly
when asked questions about the plot.

It was successful because I completed
my lesson feeling conﬁdent that the
students learned about the /k/ sounnd

was very good at managing the class
during a math group assignment. I
kept circulating the room and helping
student when needed! I also kept the
noise level down to a tolerable level!

I think I did well, I was able to engage

 

105

 

 

 

all students (to my surprise) and they
really got into the lesson. I think it
helped using computers with the
graphics to not only make it more
interesting but also to help students
understand more clearly.

read to the students and my CT
observed my and I thought it went
well. I thought I read too fast and
wasn't always sure how to respond to
students when they answered
questions, but overall it went well and
I think I stopped at good times to
check for understanding and predict.

 

Not Successful
They didn’t feel successful
Felt horrible

The other day I gave a ﬁnal spelling
test, but not all the students had to
take it if they had gotten a 100% on
the pretest. It was very diﬁ‘icult
keeping those students quiet and
engaged in other work while the other
students took the spelling test.

My ﬁeld instructor observed me
working with a group of students
during Guided Reading. I was slightly
upset because some of the students
were not following the classroom
behaviors that they know are expected
of them. A ﬁer

I feel like the lesson was unsuccessful.

Unsuccessﬁd at managing the class

 

 

Somewhat

They were not as clear as to how their
observation when. They included both
positive and negative feedback

 

Overall my teaching of a basic
spelling lesson went well. However the
students did not listen as well as I wish
they had They deﬁnitely listen to my
CT better than me. So far, I have not
done a very good job with my
classroom management. I have had a
hard time getting students to stop
talking and to listen to what I have to
say, which in turn means they are not

 

106

 

 

learning everything they are supposed
to. However, it has only been a week,
and we are reviewing my lesson
tomorrow, as well as getting stricter
and enforcing our routines more in the
classroom, which should help me with
the management and I 'II know more
about whether or not I have been able
to complete my lesson objective from
the review.

feel I am learning a lot of different
strategies ﬁom my CT and my F1 is
seeing me implement some of these
strategies...l am not sure if I feel that
meeting with my F] can be labeled
successﬁll or unsuccessﬁtl, but rather
ﬁtlfilling a requirement instead

 

BLANK/Unscorable

No indication about how it went/out of
context?

I was told that I didn't meet all of my
goals which was ﬁustrating.

I agreed with everything she said both
the good and the bad

 

 

Feedback by F I
The intern directly attributes the success to
something the FI has done or said

 

my most signiﬁcant impression was
that I looked like I beling up in ﬁ'ont of
the students. Mt ﬁeld instructor told be
that I looked like I was enjoying
rnyselﬁ and that I showed great
conﬁdence. This made the most
impression on me because I have been
questioning my teaching lately.

My F I could tell I was unprepared

I was really unsure of how my lesson
would go or how my FI would feel
about it, but she was actually really
positive about what I did She
mentioned that my relationship with
the student was obviously very
positive, which made me feel good
about my ability to gain trust with my
students.

 

107

 

 

 

Feedback by CI-The intern directly attribute

the success or failure to something the CT has

done or not done.

 

read to the students and my CT
observed my and I thought it went
well. I thought I read too fast and
wasn't always sure how to respond to
students when they answered
questions, but overall it went well and
I think I stopped at good times to
check for understanding and predict.

feel I am learning a lot of different
strategies from my CT and my F1 is
seeing me implement some of these
strategies...I am not sure if I feel that
meeting with my Fl can be labeled
successﬁd or unsuccessful, but rather
fulﬁlling a requirement instead

 

 

Feedback by Student performance

The observation was successful in
large part due to the lesson being
recieved well by the students. They
responded well, which provided the
discussive environment that I had as a
goal.

 

 

Management

 

Overall my teaching of a basic
spelling lesson went well. However the
students did not listen as well as I wish
they had They deﬁnitely listen to my
CT better than me.

So far, I have not done a very good job
with my classroom management. I
have had a hard time getting students
to stop talking and to listen to what I
have to say, which in turn means they
are not learning everything they are
supposed to. However, it has only been
a week, and we are reviewing my
lesson tomorrow, as well as getting
stricter and enforcing our routines
more in the classroom, which should
help me with the management and I 'll
brow more about whether or not I
have been able to complete my lesson
objective ﬁom the review.

 

108

 

 

 

11432 ﬁeld instructor observed me
working with a group of students
during Guided Reading. I was slightly
upset because some of the students
were not following the classroom
behaviors that they brow are expected
of them A ﬁer

Successful because the lesson went
well and I managed the students well.

Unsuccessful at managing the class

was very good at managing the class
during a math group assignment. I
kept circulating the room and helping
student when needed! I also kept the
noise level down to a tolerable level!

 

 

Engagement

 

I think that the observation went well
because students were engaged

Teaching a lesson on moon phases
went very well, the 5th graders were
attentive and engaged I think they
were particularly excited because they
didn't get much hands on learning.

The other day I gave a ﬁnal spelling
test, but not all the students had to
take it if they had gotten a 100% on
the pretest. It was very diﬂicult
keeping those students quiet and
engaged in other work while the other
students took the spelling test.

was impressed with the students’
engagement and the questions they
were able to generate during
discussion.

There was an idea (or reasoning) that
I was trying to get the students to come

 

109

 

 

to, but they just didn 't get there. I
wasn't sure how else to present it or
push them and was not really able to
get them to make the connections I
wanted them to, partially because, in
my opinion, the math ws above their
heads. (This is these students ' ﬁrst
year with EDM.)

 

 

Instructional

 

have reached my goal of explainin
borrowing and carrying during
addition and subtraction of two digit
numbers. I was successful after two
days of instruction because the
students had began ton understand
that borrowing from the tens place to
get more ones was necessary.

It was successﬁil because I completed
my lesson feeling conﬁdent that the
students learned about the /k/ sounnd
During the past couple weeks 1 have
been teaching the children various
writing techniques. During this time I
have been able to observe the students
progress increase dramatically in
comparison to the beginning of the
year. This was significant because I
felt like I had accomplished my
learning goals and impacted the
students in a positive way.

 

110

 

 

Appendix C

 

Codebook for Difﬁculties

 

How difficult was this lesson or activity
for you to teach and why?

Quotes-Direct (uncorrected)

 

Difﬁcult

It was a bit dzﬁ‘icult because i had to probe
students to get them thinking and
describing in words and to put those words
on paper, without giving them spelling or
imputting my ideas onto them. these
students do not have a writing background
which is difficult

This lesson was extremely diﬂicult for me
to teach because it was a mathematics
lesson and I have a grave ﬁzar when it
comes to approaching mathematics

 

Easy-Not difﬁcult-Simple

I taught a small math group and did an
activity working with base 10 blocks for
subtracting 2-digit numbers with
regrouping. The lesson was fairly easy to
teach

 

 

Somewhat

 

It was slightly difﬁcult because I have
trouble with time management and gauging
how long a lesson will take.

 

lll

 

References

112

 

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