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Middle school students' perceptions of academic abilities as a result of an attribution retraining curriculum

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Middle school students' perceptions of academic abilities as a result of an attribution retraining curriculum

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Content Running head: ATTRIBUTION RETRAINING CURRICULUM 1

MIDDLE SCHOOL STUDENTS’ PERCEPTIONS OF ACADEMIC ABILITIES AS A
RESULT OF AN ATTRIBUTION RETRAINING CURRICULUM

by

Marini H. Smith

______________________________________________________________________________

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

May 2013

Copyright 2013 Marini H. Smith
ATTRIBUTION RETRAINING CURRICULUM 2
Dedication

For my husband and son, Tarik and Noah Smith;
my mother, Margaret Hamilton;
and in loving memory of my grandmother, Lois Craver.

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Acknowledgements
The writing of this dissertation has been one of the most arduous, yet fulfilling
accomplishments of my academic career. First and foremost, I extend my most heartfelt gratitude
to the faculty, administration, and students of Hudson Middle School for participating in my
study. In doing so, they helped me to reach one of my goals and bring to light some important
values and perspectives. My sincere hope is that the insights and realizations made by the
students will continue to help motivate them through their academic journey.
I would like to thank my chairperson, Dr. Kimberly Hirabayashi for her support and
helpful guidance. Her patience and advice helped to make this long road worthwhile. To my
dissertation committee members Dr. Helena Seli and Brandon Martinez, I would like to express
my appreciation for their unwavering enthusiasm and assistance. Collaboration with my
committee members has proven to be an invaluable experience. I would also like to thank my
writing advisor, Dr. Katie Moulton, as well as Dr. Ilda Jimenez y West, who both provided me
with much needed direction and feedback during the writing process. I thank them for all of the
time put in to help make this dissertation the best that it could be. In addition, I am sincerely
grateful to my classmate and friend, Keao Tano. His steadfast encouragement, writing advice,
and genuine support were significant motivators when I needed them most.
Finally, I would like to thank my family for their unwavering support and confidence in
my journey. My husband, Tarik Smith, who gave me pep talks and was always willing to care for
our son when I needed the time to write, was instrumental in my success. I would also like to
thank my mother for her continued support and encouragement, and my sister, Dori Hamilton,
for her selfless and nurturing child care provisions throughout this process. Lastly, I would like
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to acknowledge the many friends whose enthusiasm, interest, and support helped give me the
tenacity to realize this achievement.
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Table of Contents

Dedication ................................................................................................................. 2

Acknowledgements ................................................................................................... 3

Abstract ..................................................................................................................... 7

Chapter One: Introduction ........................................................................................ 8
Background of the Problem .......................................................................... 8
Statement of the Problem .............................................................................. 12
Purpose of the Study ..................................................................................... 13
Research Questions ....................................................................................... 14
Significance of the Study .............................................................................. 14
Methodology ................................................................................................. 15
Assumptions .................................................................................................. 16
Definition of Terms ....................................................................................... 16
Organization of the Study ............................................................................. 17

Chapter Two: Review of the Literature .................................................................... 18
Factors that Influence Motivation ................................................................. 18
Attribution Retraining ................................................................................... 36
An Attribution Retraining Curriculum in LAUSD ....................................... 48
Conclusion .................................................................................................... 58

Chapter Three: Research Methodology .................................................................... 61
Introduction ................................................................................................... 61
Research Questions ....................................................................................... 61
Research Design ............................................................................................ 62
Participants .................................................................................................... 63
Data Collection ............................................................................................. 64
Interview Protocol ......................................................................................... 65
Data Analysis ................................................................................................ 66

Chapter Four: Results ............................................................................................... 70
Introduction ................................................................................................... 70
Quantitative Results ...................................................................................... 71
Qualitative Results ........................................................................................ 74
Conclusion .................................................................................................... 82

Chapter Five: Discussion .......................................................................................... 83
Findings ......................................................................................................... 83
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Limitations and Delimitations ....................................................................... 84
Implications and Recommendations for Practice ......................................... 86
Recommendations for Future Research ........................................................ 93
Conclusion .................................................................................................... 96

References ................................................................................................................. 98

Appendix A ............................................................................................................... 103

Appendix B .............................................................................................................. 104

Appendix C .............................................................................................................. 111

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Abstract
Qualitative and quantitative measures were used with 105 middle-school English
students in an effort to better inform educators on ways to increase academic motivation at a time
when motivation tends to wane. The inquiry sought to determine if the students’ perceptions
about their intelligence would be positively influenced by an attribution retraining curriculum
administered over the course of 18 days. Analyses of student journal responses, survey
responses, and randomly administered interviews are discussed as they relate to the motivational
dimensions of attributions: locus dimension, stability dimension, and causality dimension.
Quantitative results support previous findings regarding the benefits of attribution retraining
programs on student motivation. Qualitative data revealed that students’ beliefs about the
malleability of intelligence were increased after students engaged in the attribution retraining
curriculum. Following a deductive analysis, patterns that emerged from journal responses and
randomly administered interviews showed that those students who indicated the most positive
change from the curriculum also showed the most adaptive characteristics on the attribution
dimension: internal, unstable, and controllable. Implications of the study include establishing
more adaptive practices in secondary school structures regarding class-size and evaluation,
attribution retraining professional development, and compulsory motivation research and
application in teacher education programs.
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Chapter One: Introduction

When the No Child Left Behind Act of 2001 was signed into law, schools throughout the
nation were given the charge to employ methods of standards-based instruction. In addition,
these schools have been held accountable to produce subsequent data that will indicate student
academic progress at proficient or above. Consequently, many school districts throughout the
United States have implemented academic programs and support systems in an attempt to
improve student academic outcomes. However, many schools are struggling to meet standards of
student academic proficiency set by No Child Left Behind. In many cases, personal and
environmental factors can adversely affect student achievement. For example, students’ prior
beliefs about a task and their ability to perform that task can result in unsuccessful academic
achievement. Furthermore, student achievement may be influenced by environmental factors
such as teacher feedback and social norms (Schunk, Pintrich, & Meece, 2008). In many cases,
decreased student achievement is accompanied by diminished motivation, so it is important to
examine relevant research to better ascertain the underlying factors that may impact student
motivation, and ultimately, achievement.
Background of the Problem
The goal of most academic institutions is to produce students who master content
standards and demonstrate that mastery by achieving at high levels on standardized tests.
However, statistics from the California Department of Education indicate a decline in
standardized test scores as students enter middle school. Research contributes the decline in
academic achievement, in part, to the effort and ability conceptualizations held by adolescents,
which can adversely affect motivation. (Folmer, Cole, Sigal, Benbow, Satterwhite, Swygert, &
Ciesla, 2008). As indicated by Schunk, Pintrich, and Meece (2008), individuals are driven by a
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need to understand and master their environment, as well as themselves. As part of this search
for mastery, individuals seek to understand why things happen and why people exhibit certain
behaviors. Attribution theory describes this concept and helps to further understand the ways in
which individuals explain the causes for outcomes, both in everyday life and more complex
situations (Schunk, Pintrich, & Meece, 2008).
Attributions are defined as explanations about why particular behaviors occurred, and
explanations enhance an individual’s ability to predict and control similar events in the future.
Much of the foundation of attribution theory is based on the research of Weiner (1985). Although
Weiner’s research focused primarily on attributions as they related to sports, many of the
concepts apply to academics, as well. The three principal attribution dimensions are: locus of
causality, stability, and controllability. Locus of causality refers to whether cause of a particular
outcome is internal or external (inside or outside of the individual). Stability delineates whether a
cause will (stable) or will not (unstable) change over time. The degree to which a cause is
controllable or uncontrollable is determined by controllability. According to Schunk, Pintrich,
and Meece (2008), it is these causal dimensions that have the potential to greatly impact an
individual’s expectancies for success, self-efficacy beliefs, emotional disposition, and ultimately,
behavior. Understanding the principal attribution dimensions are a primary step toward an
individual having adaptive attributions that will lead to positive perceptions about intelligence,
increased motivation, and improved academic achievement.
When attributions are maladaptive, achievement motivation can be negatively affected. It
is important for both educators and learners to understand the relationship between attributions,
motivation, and achievement in order to implement methods to improve academic achievement.
Attribution retraining programs have been implemented with the goal of altering maladaptive
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attributions in order to increase student achievement by changing their beliefs about ability and
achievement.
According to Schunk, Pintrich, and Meece (2008), attribution-altering programs can
increase motivation and behavior by modifying students’ attributes for successes and failures.
Students who believe they lack the aptitude to successfully complete an academic task may put
forth minimal effort when attempting the task. When individuals are learning new content or a
new skill, it is likely the student will encounter difficulty. If the difficulty is attributed to low
ability, students will tend not to exert additional effort. This lack of motivation may ultimately
stifle skill development; consequently, these students would be ideal candidates for attribution
retraining (Schunk, 1992; Schunk, Pintrich, & Meece, 2008; Struthers & Perry, 1996).
Attribution retraining programs are designed to teach individuals to attribute academic failure to
controllable factors such as low effort or faulty strategy use, instead of low ability (Schunk,
Pintrich, & Meece, 2008).
Research to determine whether altering attributions for failure would assist children
exhibiting learned helplessness to cope better with failure was conducted by Dweck in 1975. One
of the first studies of its kind, Dweck found that students in the Attribution Retraining Treatment
demonstrated increased academic performance, especially when previous failures were attributed
to effort. This finding indicated that motivation could be positively influenced when participants
made a correlation between increased effort and improved academic performance (Dweck,
1975). This relationship between motivation, effort, and academic performance is an important
one to consider when assessing an attribution retraining program.
Forsterling (1985) and Robertson (2000) each conducted a meta-analysis of attribution
retraining programs to examine their design, implementation, and effectiveness. In his
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examination of the retraining programs, Forsterling first set out to identify desirable and
undesirable attributions and determined that a majority of attribution retraining programs deems
effort to be a key attribution for academic success. After reviewing the methodologies,
implementation and limitations of the fifteen programs reviewed, Forsterling (1985) concluded
that attribution retraining programs are successful in increasing both persistence and
performance. By indicating to program participants that academic failures are due to a lack of
effort, which is a controllable attribute, the attribution retraining programs could work to
increase effort output and, consequently, increase achievement. Robertson (2000) also set out to
determine the effectiveness of twenty attribution retraining programs, specifically, as an
intervention for students with learning disabilities. In this meta-analysis, Robertson noted that
while attribution retraining programs are beneficial, overall, mixed results of the studies make it
difficult to determine the best form of attribution retraining (Robertson, 2000). More
importantly, two of the major challenges highlighted by Robertson were the transferring of
attribution retraining from laboratory to classroom settings, and the practicality of
implementation in classroom settings. It is essential to examine these limitations in order to yield
optimum outcomes for future classroom-based attribution retraining programs.
Currently, there are gaps in attribution training research with regards to age group and
type of study. Robertson (2000) notes that low motivation is greatly problematic in secondary
schools, though none of the studies in his meta-analysis focused on this age group. Therefore, it
would be essential to conduct studies geared toward this demographic to begin to close the gap in
research. Furthermore, while there are quantitative studies done to evaluate the outcomes of
attribution retraining programs, there are far fewer which are qualitative in nature. In addition,
student perceptions of academic ability prior to and subsequent to participating in attribution
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retraining programs have had little documentation. This study sought to address this issue by
using qualitative methods to examine student perceptions about intelligence and effort and their
impact on achievement.
Statement of the Problem
Despite attempts made by the No Child Left Behind Act (NCLB) to improve academic
achievement in elementary and secondary schools across the nation, standardized test scores
indicate that achievement has not made the anticipated improvements, and in fact, tend to
decrease as students enter secondary school (Eccles, et al., 1993; Perry & Penner, 1990). Failure
of schools to demonstrate adequate progress on standardized assessments can result in corrective
measure in the form of supplemental educational resources, and, in the case of continued failure,
government intervention and reconstruction of schools. Attribution retraining programs, which
are designed to modify maladaptive attributions, can be introduced in schools as a mediating tool
to enhance academic achievement. To date, however, attribution retraining programs have not
been widely implemented in urban, public schools. Furthermore, while the benefits of attribution
retraining programs have been established in past studies, their influence on student perceptions
about achievement have yet to be adequately addressed.
As students mature and enter middle and high school, developmental factors may
influence their beliefs about intelligence and consequently impact motivation and academic
achievement. Adolescents tend to perceive effort and ability to be reciprocally related constructs,
leading to the belief that intelligent students do not need to exert much effort on academic tasks
(Folmer, et al., 2008; Juvonen, 2000). This perception tends to hinder motivation, as students
may fail to persist in the face of academic setbacks. Furthermore, middle schools are structured
in a way that emphasizes social comparisons and performance-oriented goals, and, compared to
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elementary schools offer less opportunity for student control and autonomy (Eccles, et al., 1993;
Schunk, Pintrich, & Meece, 2008). In addition, grades in secondary schools place a strong
emphasis on achievement, which may consequently reinforce social comparisons and
performance goals. Based on these developmental factors and inherent school structure in
secondary education, it is essential that educators understand how emphasizing effort attributions
over ability attributions can bolster academic motivation. There is a lack of understanding about
attribution retraining programs in classroom settings, and an area that requires further research is
how these attribution retraining programs may impact the perceptions of ability and effort in
adolescents (Graham, 1991; McAuley, et al., 1992). A qualitative analysis of an attribution
retraining curriculum may provide further insight as to its influence on motivation and student
achievement.
Purpose of the Study
As the nationwide accountability for school performance increases, and the academic
achievement of students tends to decrease as they enter secondary school, it is imperative to
further investigate the factors that may adversely impact the academic progress of this
demographic. The purpose of this study was to gain a better understanding of the perceptions
middle school students have about their academic abilities. The ways in which an eighth grade
language arts attribution retraining curriculum influences these perceptions was also a focus of
this study. The goal of the research was to be able to present qualitative data derived from middle
school students and the curriculum that can further contribute to the understanding of student
beliefs, how these students are motivated, and how these students best learn. Consequently, these
findings could be applied to other classroom settings and contribute to an increase in academic
achievement of other students.
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Research Questions
The following research questions guided this study:
1. Is there a difference between students’ beliefs about their intelligence before and after
an attribution retraining curriculum in English language arts?
2. How have middle school students’ perceptions of their academic abilities changed as
the result of an attribution retraining curriculum in English language arts?
Significance of the Study
Forsterling (1985), Robertson (2000), and Schunk, Pintrich, and Meece (2008) conducted
comprehensive reviews of attribution retraining programs and found that these programs can be
largely instrumental in bolstering motivation and ultimately increasing student academic
achievement. These retraining programs examined the relationships between expectancies,
persistence, self-efficacy and performance and how these constructs impact student motivation.
While the methods of the attribution retraining programs had some variation, the prevalence of
their benefits help to garner a better understanding of student achievement motivation.
Providing middle school teachers and students with explicit knowledge and increased
understanding about the constructs related to motivation, and examining how a specific
attribution retraining program may influence these constructs, may provide other students,
educators, and academic institutions with valuable information to guide future curricula.
Following the study, data on student perceptions surrounding academic ability can inform school
faculty and help to mitigate the gap in academic achievement that tends to occur in secondary
schools. In addition, students can gain a deeper understanding about the factors that drive their
academic motivation, as well how these beliefs about effort and ability can be retrained for
optimal academic performance.
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Methodology
A vast majority of studies on attribution retraining have been quantitative in nature and
have not assessed affective change or perceptions (Forsterling, 1985). Therefore, the design used
to investigate this research problem will be one that is qualitative and addresses student
perceptions in order to gain deeper insight into the ways students’ attributions are exhibited and
how they can be modified. The methodology will begin with the selection of a public school,
where an eighth grade English teacher will be trained to administer a curriculum. The attribution
retraining curriculum used in this study was designed, in part, by Carol Dweck, and was
originally piloted in Los Angeles Unified School District (LAUSD).
The participating teacher taught the Unit One (Narrative) curriculum to five out of six of
her classes over a period of approximately three weeks, and the researcher conducted formal
observations of the implementation of these lessons. Student perceptions about their academic
ability were pre-assessed by having students compose written reflections in a journal as well as
completing a survey with six Likert- scale questions. Following the implementation of the
curriculum, students were assessed using written journal reflections and the same six Likert scale
questions on a survey. The use of the journal was essential to gain unbiased feedback from the
students about their perceptions, as well as a way to provide the study with subjective,
comprehensive and nuanced responses. The Likert-scale survey was beneficial in providing
consistent, benchmark data to be compared pre- and post-curriculum implementation. The survey
also provided a more streamlined account of the data. Finally, a random sampling of 20 students
was selected to participate in one-on-one interviews with the researcher to candidly discuss their
experience with the curriculum, without the potential threat of being influenced by the responses
of their peers in a group setting.
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Assumptions
For the purpose of this study, it was assumed that the participating teacher would
implement the attribution retraining curriculum with fidelity and in the manner in which it was
designed. While implementation was observed regularly, there were portions of the lessons
taught without the researcher being present. In addition, it was assumed that the student
participants would respond honestly in the survey, journal reflection, and respond openly and
honestly in the individual interviews.
Definition of Terms
Attributions- the specific causes people use to explain an outcome or a behavior, which shape the
development of individuals’ expectancy beliefs and their affective reactions to different
experiences (LeFoll, Rascle, & Higgins, 2008; Schunk, Pintrich, & Meece, 2008). Furthermore,
explanations for causes of events enhance people’s abilities to predict and control events in the
future (Coffee and Rees, 2007).
Attribution Retraining- A motivational intervention through which maladaptive attributions is
replaced with more adaptive attributions with the goal of changing them into healthier ones,
which consequently improve future persistence and performance. Attribution retraining programs
attempt to enhance motivation and behavior by modifying students’ attributions for successes
and failures (Jackson, Hall, Rowe, & Daniels, 2009; Horner & Gaither, 2004; Schunk, Pintrich,
& Meece, 2008).
Learned helplessness- Refers to the learning or perception of independence between one’s
behavior and the presence of and/or withdrawal from unpleasant events. These patterns of
learned perceptions lead an individual to see no likelihood between the behavior and the
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outcomes leading to hopelessness, depression, and passivity (Dweck, 1975; Schunk, Pintrich, &
Meece, 2008).
Self-efficacy- An individual’s perceived beliefs about their potential for learning and performing
at specific levels. Students’ self-efficacy for learning can include general abilities, task-specific
skills, interests, personality traits. Variations in student self-efficacy can be due to factors such as
prior academic experiences and support for learning (Schunk, Pintrich, & Meece, 2008). These
variations can be useful in informing the data received from student responses in this study.
Organization of the Study
Chapter 1 provided a foundation for understanding the issues leading to the problem
addressed, the research question, and the structure of the study, which illuminated an area of
student perceptions, which have not been adequately reviewed in research. Chapter 2 provides a
comprehensive review of recent research that is relevant to the current study, and looks closely at
factors that influence motivation such as theories of intelligence, feedback, and developmental
factors.
Emerging from the foundation provided by the information in Chapter 1 and Chapter 2, is
the research methodology discussed in Chapter 3. This chapter highlights the research design,
selection of participants, and methods for data collection. Chapter 4 presents the data of the study
and the results of the data, and Chapter 5 reviews and discusses the findings, suggests
applications of the findings, and provides recommendation for future research.

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Chapter Two: Literature Review

Factors that Influence Motivation
While there are many factors that influence motivation in academic settings, student
attributions are particularly influential on student achievement. For the purpose of this literature
review, I will focus on attributions as one of the main influences of motivation in an academic
setting, and highlight three factors that greatly impact attributions: theories of intelligence,
feedback, and developmental factors. As the academic success of individual students, academic
institutions, school districts, and states are based on achievement data, it is crucial to examine the
key factors that influence academic success.
Student achievement is one of the most important areas of focus in academia, with
emphasis on the achievement of adolescent students in urban settings (Hareli & Weiner, 2002;
Long, et al., 2007). As students enter middle school, statistics indicate a decline in standardized
test scores. This decline in academic achievement is, in part, due to the effort and ability
conceptualizations held by adolescents, which can adversely affect motivation. (Folmer et al.,
2008). Concepts surrounding effort and ability are called attributions (Dweck & Goetz, 1978;
Horner & Gaither, 2004; Weiner, 1979). Student attributions are influenced, in part, by the
beliefs held by the student regarding their intelligence. Students who believe their intelligence is
fixed are less likely to exert cognitive effort when academic content is challenging. Conversely,
students who believe their intelligence is malleable believe that cognitive ability can grow with
effort, which can result in positive results in achievement. In order to better understand effort and
ability conceptualizations and their impact on student achievement it is necessary to examine
attributions more closely (Eccles & Wigfield, 2002; Karasawa, 1995; Zaccaro & Lowe, 1985).

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Attributions. Attribution theory describes the ways in which individuals explain the
causes for outcomes, and when these attributions are maladaptive, achievement motivation can
be adversely impacted as a result. Furthermore, attributions have been found to shape the
expectancy beliefs of individuals, as well as their affective outcomes to different experiences
(Schunk, Pintrich, & Meece, 2008). Fosterling (1985) adds to this definition by asserting that
attribution theory is based on the premise that individuals seek to establish a reliable causal
understanding of their surroundings, as well as their actions. This understanding will enable them
to predict and control the events in their lives.
Much of the foundation of attribution theory is based on the research by Weiner.
Although Weiner’s research focused primarily on attributions as they related to sports, many of
the concepts apply to academics, as well. According to Schunk, Pintrich, and Meece (2008), in
attribution theory, the motivational drive of attributions stems from their classification along the
attribution dimensions. The three principal attribution dimensions are: locus of causality,
stability, and controllability. Locus of causality refers to whether the cause of a particular
outcome is internal or external (inside or outside of the individual). Stability delineates whether a
cause will (stable) or will not (unstable) change over time. The degree to which a cause is
controllable or uncontrollable by the individual making the attribution is categorized by
controllability.
Some researchers have found that while Weiner’s (1985) dimensions of attribution (locus
of control, stability, and controllability) are valuable and distinct, they are also highly related and
may seem contradictory. Therefore, combinations of attributions such as “external-controllable”
and “stable-controllable” are less likely to occur. Consequently, there have emerged alternative
ways to examine the causal attribution mechanism (Homsma, et al., 2007). Research has
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demonstrated that internal unstable attributions after failure (e.g. effort) tend to generate more
functional behavior than other attributions (Homsma, et al., 2007). In addition, Weiner (1980)
posited that unstable causal ascriptions after a failure tend to precede more constructive behavior
because the expectancy to perform those tasks in the future remains unaffected. For example,
optimal explanations for failure would be low effort (internal) or bad luck (external), because
those factors should lead to positive attributions and validate the belief that the individual had
control over future outcomes. In situations where attributions are deemed uncontrollable, an
individual may experience learned helplessness and have difficulty persisting in the face of
setbacks (Crase, 1988; Fowler & Peterson, 1981).
Attributions are described as the specific causes individuals use to explain a particular
behavior or outcome (Foll, Rascle, & Higgins, 2008). For example, a student may attribute
their grade on a test to study habits, the teacher’s like or dislike of the student, or physical
health. Because attributions are explanations about why a particular behavior occurs, these
explanations may enhance an individual’s ability to predict and control similar events in the
future.
The attributions held by an individual can greatly influence motivation in academic
settings. Weiner’s (1985) paradigm of achievement motivation indicates that there is a distinct
relationship between learning, emotion, and motivation. Weiner (1985) further posits that the
attributions made for academic failures and successes are vital to mediating the variables.
According to attribution theory, students can become unmotivated because of their beliefs
about why they fail or succeed at academic tasks (Robertson, 2000; Rudisill, 1989). For
example, if a student attributes the failure of a task due to low ability, it is unlikely that the
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student would be motivated to work harder on academic tasks in the future. This maladaptive
attribution is often related to the belief that failure is a result of internal, stable causes such as
low ability, and that success results from external, unstable causes such as luck (Robertson,
2000). Furthermore, this maladaptive attribution style is based on a belief that efforts are
unrelated to outcomes, and therefore, futile. Conversely, if a student attributes success of a
task to high effort, it is probable that the student would be motivated to exert effort in the
future to achieve similar results (Linnenbrick & Peterson, 2002).
Moely, Obach, Cassell, and Tonglet (1995) examined, through a cross-sectional and
longitudinal study, how motivational beliefs change over time for students in grades five
through eight grade students. One of the objectives of the study was to determine if the
motivational beliefs of the students changed in accordance with changes in their school
experiences. The evaluation method of the school changed from an individualized, mastery-
oriented method through grade four, to a more normative, comparative model from grades
five through eight. When students were in fifth grade, for example, they did not receive
traditional letter grades, but normative feedback, instead. Students in the study responded to
questionnaires which assessed beliefs regarding goal orientations, the value of school,
attributions applied toward academic success and failure, and feeling of perceived academic
competence (Moely et al., 1995).
The results of the study showed that as evaluation methods of the school changed over
time, students’ perceived value of the school declined, interest in the mastery of academic
mastery decreased and work-avoidant behaviors increased. Moely et al. (1995) found that
motivational beliefs of students who attended schools that used the traditional evaluative
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training method of giving conventional letter grades on tests, quizzes, and papers, did not
decrease over time. As a result, Moely et al. (1999) concluded that the concepts of the
students of the study changed in response to their school experience. When academic
achievement of students is compared to that of other students (normative model), students
were less likely to attribute academic achievement to effort. It was not specified in the study
to what the students attributed their success; however, it might be inferred that students
attributed academic success to ability instead of effort. Moely et al. (1995) also asserted that
schools which use the normative evaluation model may be discouraging motivational beliefs
that would foster student exploration and creativity.
Dweck (1975) conducted a study to examine the effects that attributional feedback
would have on perceived self-efficacy and achievement. Dweck (1975) posited that
attributing past failures to low effort had motivational effects and hypothesized that when
students believe that increased effort will result in success, students will be more motivated to
persist longer at a task to increase performance. Dweck (1975) also noted that effort, unlike
ability, luck, or task difficulty is controllable and subject to change. Students are more likely
to be motivated if they are aware of their ability to change an outcome based on the effort that
is exerted.
Dweck’s study of attributional feedback involved primary-aged students who had
below average subtraction skills. Some students received subtraction training with effort
attributional feedback concerning past achievement. Another group of students received
feedback concerning future achievement, and a third group received no feedback. The results
indicated that students who received attributional feedback for past achievement showed more
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skill improvement in subtraction, as well as increased self-efficacy. Dweck (1975) explained
that past performance provides a reliable basis for judging personal capabilities, so students in
the group that received attributional feedback for past achievements responded to the
evidence that past effort and achievement was a predictor of future academic achievement. As
a result, students who attributed academic success or improvement to effort that was
demonstrated through past performance would be more motivated to attempt difficult tasks
than the students in the two other feedback groups.
In summary, the review of the literature above demonstrates that attributions are key
components to understanding academic performance and play an important role in motivation.
When academic success or failure is attributed to something within the control of the student,
such as effort, the student is likely to be motivated to persist when cognitive tasks are
challenging. In many cases, decreased student achievement is accompanied by diminished
motivation, so it is important to examine relevant research to better ascertain the underlying
factors that may impact student motivation, and ultimately, achievement. Increasing
understanding about attributions in academic settings may bring educators and students
several steps closer to improving student achievement.
Factors that Impact Attributions
Attributions can be influenced by theories of intelligence, as well as feedback and
developmental factors. With the advent of No Child Left Behind, many school districts
throughout the nation have adopted a variety of programs with the hopes of improving student
achievement. In many cases, personal and environmental factors may serve as obstacles to
these improvements, and these obstacles may hamper student performance in academic
settings. For example, students may base unsuccessful academic achievement on prior beliefs
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about the task and their ability, or they may consider environmental factors such as teacher
feedback and social norms (Schunk, 1983).
Theories of Intelligence. Much of the foundation of attribution theory stems from an
individual’s belief about his or her intelligence. Understanding these beliefs about intelligence
is important, as these beliefs can have a significant impact on student performance. Many
theories of intelligence stem from beliefs about the nature of intelligence and the perceptions of
the stability of that intelligence. Beliefs about ability are not correlated to an individual’s
intelligence quotient; however, the beliefs can have a notable impact on thoughts and behaviors
in academic settings (Thompson & Musket, 2005).
The research of Dweck (2005) indicates that individuals’ ideas about their intelligence
fall under two types of mindsets: fixed and growth. Individuals with a fixed mindset (also
referred to as entity intelligence) believe that people are born with a certain amount of
intelligence, and as a result, those with fixed mindsets give up easily, avoid challenges, find little
to no utility in effort, ignore useful negative feedback, and feel threatened by the success of
others. On the other hand, those demonstrating growth mindset (also referred to as incremental
intelligence) traits believe that intelligence is malleable and can grow with increased effort. As a
result, these individuals embrace challenges, persist in the face of setbacks, view criticism as an
opportunity to learn, and are inspired by the success of others. Dweck (2005) also asserts that
newer research indicates that the brain is a muscle that changes and grows the more that it is
used. When students understand the concepts presented in this brain research, they may be more
inclined to exert cognitive effort on difficult task. This concept promotes a belief in incremental
intelligence, where students will likely perceive that they can influence their own learning based
on effort.
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On the other hand, an entity view of intelligence can be detrimental to a student’s
academic progress. Evidence shows that an entity view of ability is linked with social
comparison goals and poor performance (Struthers & Perry, 1996). Individuals who possess an
entity view of ability believe that their ability is fixed and cannot change. Individuals who are
driven by social comparison goals will tend to avoid challenges and learning opportunities when
they perceive that failure is likely. An individual who perceives their intelligence and abilities to
be “fixed” will tend to focus on impressing peers and gaining acceptance from others, while also
avoiding negative judgments. When individuals are concerned with impressing others, the
individuals may not attempt a task they perceive they will not be good at (Thompson & Musket,
2005).
Conversely, an incremental view of ability, which describes the belief that ability is
malleable and can be improved upon, is linked with a mastery goal orientation and positive
achievement outcomes (Schunk, 1992) An individual who has a growth mindset about their
intelligence and abilities will most likely work towards increasing their competence, which
results in adaptive learning patterns and positive achievement outcomes. If an individual has a
fixed view of intelligence, then failure on a task might be attributed to a lack of ability or overall
lack of intelligence. Conversely, an individual who has an incremental view of intelligence will
likely attribute low performance to factors that are within an internal locus of control, such as
not studying hard enough and not exerting sufficient effort.
Perceptions about intelligence also influence a student’s motivation for participating in
an academic task. Goal-orientation theory describes the purposes or reasons for engaging in
achievement behaviors, and many of these reasons stem from an individual’s mindset about
their intelligence (Pintrich, 2003). In general, two models emerge from goal-orientation
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constructs: mastery goal orientation and performance-goal orientation (Schunk, Pintrich, and
Meece, 2008). Mastery-goal orientation is defined as a focus on learning and mastering tasks,
setting goals for oneself for improvement, acquiring new skills, and attempting to accomplish
more challenging tasks and gain further understanding.
Beliefs about intelligence can also differ by gender. Byer (1997) investigated gender
differences in causal attributions and emotions to success and failure. Some research suggests
that women attribute successful outcomes more externally, or more to effort than ability then
men (Byer, 1997). With regard to failures, males deem internal causes such as a lack of ability as
less important than females do. Males’ causal attributions are similar to those of individuals with
high self-esteem (Byer, 1997). On the other hand, Byer (1997) notes that causal attributions of
females more closely resemble those with low self-esteem. Other research has shown that
females are more likely to show maladaptive patterns of attributing success to external causes
such as luck and effort, and attribute failure to internal and stable causes such as lack of ability
(Dweck, & Leggett 1988).
Koch, Muller, and Sieverding (2008) conducted a study to determine the impact
stereotype threat might have on women’s attributions when a computer task was deemed
unsuccessful. The college-aged male and female participants were asked to engage in a
computer-based task. Prior to the task, participants were told that that either men usually perform
better than the women (negative threat condition), or women usually perform better than men
(positive threat condition). The control group of participants was not given any gender-specific
information about the task before beginning. The results of the study indicated that women’s
attributions of failure were related to a stereotype threat effect which is described by Steele
(1997) as a social and psychological threat that occurs when in individual is engaged in a task for
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which a negative stereotype about one’s group applies. The female participants in the negative
threat group attributed failures on the computer task to internal factors such as their own lack of
ability. On the other hand, the men in this same group associated their computer-task failures to
external factors such as faulty technical equipment.
Furthermore, Koestner, Zuckerman, and Koestner (1989) found that male and female
children may respond differently to praise and have varying interpretations about the meaning of
praise. Males tend to view praise as a reflection of their capabilities at a task, while female
children may perceive praise as a method of control, which diminishes feelings of self-
determination and consequently undermines their intrinsic motivation (Koestner, Zuckerman, &
Koestner, 1989). Further details regarding praise and their influence on attributions will be
discussed in the next section.
Clear conclusions about gender differences in attributions cannot be made, however,
because of the methodological differences in the research and varied reliability. (Henderlong &
Lepper, 2002). Studies which measure gender differences in attributions have been conducted in
both classrooms and laboratories, and measures of attributions have been recorded before and
after feedback. In addition, the aptitude levels of participants in these studies have varied, as
well. (Schunk, Pintrich, & Meece, 2008)
Feedback. As noted by Schunk, Pintrich, and Meece (2008), teacher feedback can
greatly influence students’ attributions and therefore has implications for students’ academic
performance. Schunk, Pintrich, and Meece (2008) explain that the perceived causes of events
are determined by both environmental factors and personal factors. Personal factors can include
the beliefs an individual has about himself or herself, and environmental factors can include
feedback. Research resulting from attribution retraining programs suggests that teachers
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provide accurate feedback to their students about their failure and strive to make valid and
precise attributions. For example, students could become frustrated if they are told to work
harder at a task by a teacher, if in fact, the student is working hard but does not have the
knowledge or skills to achieve the task. Instead, it would be more appropriate for the teacher to
explicitly inform the student that it is knowledge and skills the student lacks, indicate that these
can be learned, then teach the knowledge and skills. If this is done, the student would likely
attribute the difficulty level of the task to a deficit in knowledge and skills, which can be
acquired, rather than attributing the difficulty of the task to inherent lack of ability or aptitude,
which is often believed by children to be static. Therefore, the child could be encouraged to
apply increased effort toward obtaining and applying new skills. Teacher feedback given to a
student for increased effort would promote continued effort on new and challenging academic
tasks (Schunk, 1982).
In addition, effort feedback has been shown to have a positive impact on students with
learning disabilities, according to Schunk and Cox (1986). Children with learning disabilities
often exhibit the characteristics of learned helplessness. These children typically attribute
their failures to low ability, and their successes to the ease of the task (Cooley & Ayres, 1988,
Okolo, 1992). Children who received effort feedback during academic instruction exhibited
increases in skill, self-efficacy, and motivation, especially when the effort feedback was given
early in the instructional program. Children who received effort feedback in the beginning
stages of instruction may have been more likely to attribute future successes to effort, as well.
When students make attributions based on feedback, the credibility of the feedback is
very important as it can influence academic outcomes (Schunk, Pintrich, & Meece, 2008). In
order to offer credible feedback, teachers, for example must monitor student behavior so that
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attribution feedback will mesh with student perceptions (Schunk, Pintrich, & Meece, 2008).
For example, effort feedback should be given when students are exerting minimal effort, and
ability feedback for success should be offered when students are able to succeed easily and
with little effort (Heyman & Dweck, 1998; Schunk, Pintrich, & Meece, 2008). In order for
attribution feedback for academic areas to be successful, it should be intentional and strategic,
with special attention given to the time of the feedback, the context of the feedback, and the
age of the child receiving the feedback (Schunk, Pintrich, & Meece, 2008). Pearl (1985) also
notes the complexities illustrated by the inverse relationship between ability and effort. It is
important to note that attribution retraining programs, which emphasize effort, may lead low
achieving students to infer that because they must try harder than others, they have low
ability. These findings indicate the importance of understanding student capacity and
capabilities before offering blanket statements of effort feedback that can potentially be
detrimental.
Whether or not a student receives positive feedback for superior achievement or for
exerting sustained effort can positively or negatively affect attributions. Positive feedback,
also referred to as praise, can be described as positive evaluations made by a person of
another individual’s products, performances, or attributes. When the feedback is given, the
evaluator presumes the validity of the standards on which the evaluation is based (Meyer,
1992). Effects of praise can vary depending on the context of the praise as well as the context
in which it was delivered. Each individual may internalize the praise differently, based on
previously held attributions and self-efficacy. According to Henderlong and Lepper (2002),
praise can be shown to increase a child’s desire to engage in the praised task. For example,
fourth-graders who were praised for creating humorous endings for riddles were more likely
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to select more riddles to complete at the end of the study than they had during the initial
period. However, Henderlong and Lepper (2002) note that alternative explanations could not
be ruled out because there was no “no-praise” control group in the study.
Furthermore, researchers have looked at how praise can be detrimental if it addresses
the subject’s characteristics rather than their efforts. In certain contexts, praise can be
considered harmful or detrimental to a child’s beliefs about their abilities and can impact
future achievement (Henderlong & Lepper, 2002). Students praised for intelligence are found
to be more concerned with performance goals relative to learning goals than children who
were praised for effort (Mueller & Dweck, 1998). Attributions that are characterized by traits
related to ability show more detrimental effects in the face of setbacks than those attributions
characterized by traits related to effort. Following failure, those who were praised for
intelligence and consequently had entity views of intelligence demonstrated diminished task
persistence, less task enjoyment, more low-ability attributions and worse task performance
than those children praised for effort (Mueller & Dweck, 1998). Furthermore, when children
are praised for accomplishments that are easily achieved by others, they may perceive the
praise as an indication of their low ability. In addition, as Dweck (1999) notes, giving students
easy tasks and praising their success can be sending students the message that they are
perceived to be unintelligent and were simply being praised in order to feel good about their
limited ability.
Henderlong and Lepper (2002) suggest that it is crucial to not only focus on explicit
attributional messages embedded in praise, but also on implicit messages that can be inferred
from the context in which the praise is given. In addition, it is noted that in certain situations,
children may become uncomfortable with praise that is evaluative and will often resist praise
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of this nature. Furthermore, Wilder, Simon, and Myles (1996) note that some children will
misbehave to prove the basis for their received praise to be incorrect.
Although praising a child’s ability or self-worth, in general, has previously been found
to boost self-esteem, new research has revealed that this type of praise can also be detrimental
because it limits the child’s ability to cope with setbacks (Dweck, 1999; Wilder, et al., 1996).
The article, “Caution: Praise Can be Dangerous” (Dweck, 1999), posits that when a child’s
strategy, process, or effort is criticized they tend to be better equipped to cope with
challenges, possibly because strategy, process, and effort are conditional (and situational) and
therefore can be improved. Conversely, if a child’s traits are criticized, coping tends to me
more challenging because traits are perceived to be fixed and less malleable. As a result, these
children display characteristics of helplessness when faced with adverse situations. Those
children who are praised for effort typically respond to challenges with a mastery-oriented
pattern (Dweck, 1999).
Authors Kamins and Dweck (1999) attempted to examine how both praise and
criticism can affect a child differently when encountering difficult tasks or situations. Their
study describes two specific types of praise or criticism feedback children can receive person-
or trait-related feedback and process feedback. Whether the praise is directed at the child as a
whole or the child’s effort, determines how the child may cope with setbacks in the future.
Kamins and Dweck (1999) formulated one study involving 67 children who were five to
seven years of age, and 64 children with a mean age of five years and six months participated
in a second study. The hypothesis was that whole child praise would create a child who
demonstrated more helplessness when encountering obstacles. The results of the study
indicated that when a child received person criticism or praise, the child exhibited more
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helpless responses, as well as self-blame than when the child received criticism or praise
directed towards their process. Kamins and Dweck (1999) found when students’ abilities
were negatively evaluated, those students would tend to exhibit lower expectations for future
successes. These students would also be more likely to exhibit traits indicative of a helpless
response pattern, as the student perceives inherent abilities as stable and uncontrollable.
Conversely, students who are encouraged to focus on strategies or effort tend to perceive
future success as more probable. Strategy and effort are unstable, internal, and controllable
motivational dimensions, and as a result, students might not be discouraged by the feedback
because they could improve future academic outcomes. Consequently, Kamins and Dweck
asserted that person feedback, even when positive, can elicit feelings of vulnerability and
contingent self-worth. As a result, feedback yields more positive results when it is directed
towards a process behavior such as effort, rather than trait-related feedback. If a child is able
to separate their achievement potential from perceived intrinsic characteristics or traits, the
child is more likely to exert effort when academic content is challenging.
Additional research further supports the assertion that feedback can influence student
attributions and academic performance. In a series of six studies conducted by Dweck and
Mueller (1999), 400 fifth-grade students from various ethnic backgrounds and parts of the
country were used to determine the effects of praise for intelligence. The purpose of the study
was, in part, to determine how praise might affect the children’s attributions, and, in turn,
influence achievement. Each study consisted of several activities where students worked on
puzzle tasks that were challenging, but within the child’s zone of proximal development.
After the first set of tasks, a third of the children were praised for their intelligence (“You got
a good score. You must be really smart at this.”), a third were praised for their effort (“You
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must have worked really hard.”), and a third were simply given neutral praise for their
performance, with no additional comments about why they were successful. Results indicated
that after the first trial, subjects revealed similar responses in that they enjoyed the task
equally, anticipated working on the problems at home, and were confident about their future
performance. The effects of attribution on achievement were revealed when the subjects were
asked to choose a subsequent and potentially more challenging task. Most students, who
attributed their success on the puzzle task to intelligence, as they had received praise for their
intelligence, selected an easier task that allowed them to continue to look intelligent. This
performance-goal orientation is typically associated with a fixed view of intelligence and
ultimately, poor performance (Thompson & Musket, 2005).
Developmental Factors. According to developmental research, attribution theory may
vary according to age. Folmer et al. (2008) describes four levels of development regarding
children’s differentiation of ability and effort. At Level 1 (ages 5-6 years), children do not
make clear distinctions between effort and ability, so the implications are unclear. At Level 2
(ages 7-9 years), children attribute outcomes entirely to effort that is exerted. At Level 3 (ages
10-11 years), distinctions between ability and effort begin to emerge and children
inconsistently attribute outcomes to either domain. At Level 4 (ages 12 years and older), there
are clear indications that ability is recognized as a key component that limits the effect of
effort (Folmer, 2008). These findings would suggest that there is a clear developmental
progression for children’s effort and ability attributions (Weiner, 1985).
Students at Level 3 and 4 (ages 10 and older) need to be exposed to curriculum that
explicitly teaches them that their intelligence is malleable and can be positively impacted by
exerting effort on a variety of tasks (Folmer et al. 2008). According to the research, this
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developmental time is crucial for children who are able to make clearer distinctions between
ability and effort and may develop maladaptive attributions (Folmer et al. 2008).
Schunk and colleagues (1982) also examined the ways in which effort attribution
feedback differs from the effects of ability attribution feedback in children. As research
indicates, children begin to differentiate effort from ability around the age of eight. As
children get older, ability becomes more important, while effort as an influence for outcomes
becomes less important. In addition, studies show that when students are told that successes
are a result of ability, their self-efficacy increases (Schunk, Pintrich, & Meece, 2008).
However, effort attributions are more likely to be linked to positive outcomes when the
students are faced with academic challenges.
As Moely et al. (1995) and Hareli and Weiner (2002) also note, there are inherent
characteristics within school structures that may influence attributions. Structural changes
from elementary to secondary schools may tend to develop from an individualized into a more
normative model. For example, students may tend to be recognized for academic
improvements and citizenship in grades kindergarten through fifth or sixth grade. Upon
entering middle school, however, character education is rarely taught, and, instead the
emphasis moves toward high-stakes standardized tests and focuses on achievement. In many
school systems, grades in effort are included on report cards for elementary-aged students,
while middle and secondary report cards stress academic grades. In addition, social influences
in middle school-aged children, where competition among peers may foster more
performance-goal orientations, may become progressively stronger (Weiner, 1979; Heyman &
Dweck, 1998).
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According to Eccles et al., (1993), compared to elementary classrooms, traditional
middle school classrooms are typically characterized by emphases on discipline, teacher
control and an impersonal and less positive student/teacher relationship. Cultural stereotypes
may serve to contribute to this negative student/teacher relationship, as early adolescence is
generally viewed as an arduous and unproductive stage of life. As a result, students have a
difficult time trusting and cultivating positive relationships with middle school teachers who
hold these stereotypes (Eccles et al., 1993). In addition, students are given less opportunity
for decision-making and self- management although they are developmentally entering a stage
where they have an increasing desire for autonomy with adults and seek social acceptance
(Eccles et al., 1993). This discrepancy in the middle school structure and adolescent
developmental level, referred to as stage-environment fit, leads to negative motivational
consequences.
Furthermore, federal policies such as No Child Left Behind that mandate specific goals
for academic growth can have detrimental effects on a student’s effort attributions.
Educational policies tend to focus on academic achievement without recognizing gains made
in effort, or incremental academic growth. For some children, as a result, there is a
correlation between early adolescent years and a consequential change in school-related
behaviors, which leads to a decrease in motivation and academic failure (Eccles et al., 1993).
In summary, individuals attribute the outcomes of academic tasks to a variety of factors,
including theories of intelligence, feedback of peers, teachers, and parents, and developmental
factors associated with age. A fundamental component for attributions is the belief an
individual has about his or her intelligence. If an individual believes his or her intelligence is
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fixed, it may result in diminished learning outcomes. Attributional feedback is the most
effective when it is linked to effort and when it is credible. In addition, as noted by Schunk,
Pintrich, and Meece (2008), ability feedback for prior success enhances self-efficacy.
Developmental stage can also influence an individual’s attributions. Folmer et al. (2008)
highlighted the age-related changes that impact students’ understanding of effort and ability.
Children typically view ability and effort as equivalent constructs (Robertson, 2000) and as a
result believe that working hard at a task is an indication of higher intelligence. As children
mature, they begin to see effort and ability as having in inverse relationship. Most adults
understand that working hard on a task implies less ability for that task. Equally, adults tend
to also believe that if one has high ability, it is not necessary to work hard on a related task
(Schunk, Pintrich, and Meece, 2008).
Attribution Retraining
Purpose of Attribution Retraining Programs. Attribution research has revealed the
need for attribution change programs, which attempt to modify students’ attributions for
successes and failures, thereby increasing motivation (Schunk, Pintrich, & Meece, 2008).
Attribution retraining programs have been implemented with the purpose of altering maladaptive
attributions in order to increase student achievement by changing their beliefs about ability and
achievement (Horner & Gaither, 2004). According to Robertson (2000), attribution retraining
programs have several goals. One goal is to have students focus on the task rather than be
distracted by the fear of failure. Another goal is to encourage students to reflect on undesirable
outcomes and reflect on their strategies to come up with alternate methods for problem solving,
instead of giving up. A third goal for attribution retraining programs, according to Robertson
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(2000), is to have students attribute failures to insufficient effort rather than a deficit in aptitude
or intelligence.
There is an abundance of research that supports the assertion that attribution retraining
programs can positively affect student attributions. One of the main purposes of attribution
retraining is to replace maladaptive attributions, especially those related to failure, with more
functional attributions that would serve to improve proceeding performance (Jackson, Rowe,
Hall, & Daniels, 2009). Attribution retraining programs are typically used for discouraged
individuals who are unmotivated to achieve (Perry & Penner, 1990; Weiner & Sierad, 1975)
Ideally, with attribution retraining, an individual would manifest changes in cognitions and
emotions that would also result in changes in emotion and goal-directed behavior (Jackson, et al.,
2009). Furthermore, research has shown attribution retraining to have more of an impact on
individuals who are more likely to make maladaptive attributions (Jackson, et al., 2009).
According to Schunk, Pintrich, and Meece (2008), attribution-altering programs can
increase motivation and behavior by modifying students’ attributes for successes and failures.
When individuals are learning new content or a new skill, it is likely the student will encounter
difficulty. If the difficulty is attributed to low ability, students will tend not to exert additional
effort. On the other hand, if students believe the difficulty could be decreased by a controllable
factor such as study skills or effort towards mastery.
Design of Attribution Retraining Programs. Attribution retraining programs can
positively impact student attributions, so it is important to understand their design and how they
work. Dweck was one of the first to conduct studies on attribution retraining in 1975.
Participants of the study included children who were identified as possessing low expectancies
for success and whose achievement behaviors diminished when a task was unsuccessful. The
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purpose of Dweck’s study was to determine how a particular attribution retraining treatment
might impact children’s responses to failure in comparison to a previously utilized treatment that
did not alter attributions (Dweck, 1975). The Success Only Treatment was hypothesized to
increase children’s expectations for success, which would consequently allow the child to
maintain his or her performance despite failure. The Success Only Treatment consisted of math
problems that the children could complete relatively easily and within a time limit on every trial.
In the Attribution Retraining Treatment, twenty percent of the trials included more math
problems than the children were able to complete in the previous trial. In the attribution
retraining trials, the experimenter attributed children’s failures to lack of effort, and verbalized
these attributions to the children (Dweck, 1975). Results indicated that attribution-retraining
children (those who were told that failures were due to lack of effort) showed less decline on the
results on subsequent tests than those students who were “success only” and given tasks at or
below their ability level. Students who were part of the Attribution Retraining Treatment
sustained or enhanced their academic performance (Dweck, 1975).
Weiner (1985) initially hypothesized that future success in a task or skill was solely
determined by the stability dimension. This dimension refers to whether or not an attribution is a
consistent trait of the person rather than temporary and contextual. For example, task difficulty
and ability, or aptitude, are considered to be stable attributions because they typically do not vary
over time. However, subsequent research conducted by Grove and Pargman (1986) found that
effort attributions—dimensions showing instability and controllability—led to optimum
expectancy in both failure and success conditions. This finding might suggest that results were
more indicative of a focus of controllability (the degree to which a person has control over a
cause) rather than stability (the degree to which a cause is variable and changes over time)
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(Coffee & Rees, 2008). Controllability is an important factor that positively influences
attribution retraining programs. For example, when a student perceives a cause for an outcome to
be within his or her control, the student is more likely to feel capable of controlling the outcome
for similar events in the future. These findings can inform the design of attribution retraining
programs and ensure a likelihood of success. For example, Forsterling (1985) concludes in his
review of attribution retraining programs that the most successful programs are those that
primarily teach participants that academic failures are a result of lack of effort, which is
controllable, internal, and stable.
Additional features of effective attribution retraining programs are discussed by Fowler
and Peterson (1981) as they describe two distinct approaches to attribution retraining. The
“direct” approach involves encouraging the student to articulate attribution statements orally and
to themselves. The “indirect” approach is more traditional and involves effort attribution
feedback given to students by adults. While there is evidence to support the assertion that teacher
feedback can greatly impact student attributions, it is important to note that self-talk feedback
can also be affective in attribution retraining. This would foster a self-regulatory and autonomous
method for attribution retraining that would not be contingent on adult feedback. In addition,
findings by Schunk (1982) suggest that for successful attribution retraining, feedback should
directly correlate to the tasks attempted by the student. As noted by Schunk and his colleagues
(1982), attribution feedback is most effective when it is credible to the recipient.
Attribution Retraining Meta-Analyses: Format and Findings. Meta-analyses of
attribution retraining programs have been conducted which highlight the structures of these
programs, as well as benefits and limitations. Forsterling (1985) reviewed 15 attribution
retraining studies and Robertson (2000) conducted a comprehensive review of 20 attribution
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retraining programs. Both meta-analyses determined that attribution retraining programs have
been reliably beneficial in increasing persistence and student performance.
Of the 15 programs reviewed by Forsterling, nine of the programs used a persuasion
technique, where the experimenter stated the desired attribution to the participants. Two of the
studies reviewed employed modeling where participants viewed videos that depicted scenarios
where people exhibited desirable attributions. The remaining studies utilized operant
conditioning or gave participants attribution-related information conveyed through fabricated
interviews on videotape (Forsterling, 1985). Forsterling (1985) emphasized that an important
distinction one should make when designing attribution retraining programs is determining
which attributions are desirable and which are undesirable. Attributions classified on the
attribution dimension as internal, unstable, and controllable are typically deemed more desirable
because individuals have control over future outcomes.
Both Forsterling (1985) and Robertson (2000) highlighted some limitations with the
attribution retraining programs that were reviewed. One limitation was that very few studies
assessed participants’ changes in affect following the retraining. Fosterling indicated that one
study included a mood scale among the dependent measures, and another study included a test
anxiety scale before and after the retraining process, though ultimately no significant results were
noted (Forsterling, 1985). Another limitation was that none of the studies reviewed by
Forsterling (1985) had examined the links between affects and expectancies, and Forsterling
(1985) asserts that these links would be helpful for testing various models of behavior. In
addition, another limitation was that participants’ attributions could be influenced by the
attributions of the experimenter. For example, if the experimenter attributes participants’ failures
to lack of effort, those participants might perceive the experimenter’s attribution as an instruction
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to try harder. As a result of this perception, participants’ increased persistence following the
retraining could simply be an attempt to comply with an instruction to try harder, rather than an
attributional change. However, Forsterling cited evidence against this limitation, which included
long-term follow-ups, changes in tasks and experimenters, and finding the same results even
when subjects were not directly encouraged to try harder.
Robertson (2000) also highlighted some of the limitations of the attribution retraining
programs, including the concerns of conducting the programs in classrooms, the inverse
relationship between effort and ability, and the challenges related to researching attribution
training in classroom settings. Robertson (2000) found that in many cases attributions were not
implemented as fully in classroom settings as they would be in a laboratory, because teachers
had insufficient time. Because attribution retraining can be time-consuming, it was believed by
some participants that the programs might not be the most effective method for motivating
students to learn. With regards to the inverse relationship between ability and effort, Robertson
(2000) noted that prior to age seven, children believe that ability and effort are correlating
constructs and that intelligence is demonstrated by exerting effort. After age seven, however,
children began to think quite differently and believe, instead, that intelligence is demonstrated
when one does not have to try hard at a task. As a result, one concern with attribution retraining
programs that encourage effort is that low achieving students may infer that they have lower
ability than others if they are encouraged to try harder (Robertson, 2000). When attribution
research was conducted in classroom settings, limitations arose, as well. The validity of
attribution retraining programs conducted in a laboratory was difficult to transfer to a classroom
setting. One limitation was that teachers were unable to deliver all attribution statements to
targeted children. Also, it was rare that observers were unaware of the research objectives, so
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objectivity was limited. In addition, according to Robertson (2000), there were many variables
that could not be controlled for in a classroom environment.
Robertson (2000) has also reviewed research on the impact of attribution retraining used for
students with learning disabilities in order to determine if attribution retraining was a practical
intervention for this demographic. A comprehensive review was done so that the various
methods, which included scripts, dialogues, and procedures, could be duplicated in classrooms
(Robertson, 2000). Although the results of the 20 studies reviewed by Robertson (2000) were
mixed, it was determined that attribution retraining was a worthwhile intervention for students
with disabilities, with some conditions. When further examining the studies, it was determined
that while the attribution programs may at first appear to be based on the simple concept of
encouraging students, the process of attribution retraining is much more complex, and programs
are not always practiced in a way that aligns to the theory of attributions (Robertson, 2000).
Despite the mixed outcomes of the effectiveness and practicality of the attribution programs
reviewed, it was asserted that overall attribution retraining was beneficial in most cases.
(Robertson, 2000).
Furthermore, Schunk and his colleagues (1982) have conducted studies on attribution
retraining that have revealed its complexities and variations. One finding by Schunk (1982) was
that children demonstrated enhanced motivation, self-efficacy, and skill acquisition when they
received verbal feedback that linked prior achievements with effort (i.e. “You’ve been working
hard”) versus when those children received verbal feedback that linked effort to their future
achievements (i.e. “You need to work hard.”). One criterion for effort feedback to prove
successful is that it must be credible to the individual receiving the feedback. If, for example, a
child can recall a previous occasion when they were successful at a task after putting forth effort,
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they are more likely to respond positively and continue to exert effort when a similar task
presents itself in the future.
Developmental Factors that Influence Attribution Retraining Programs. Research
also suggests that attribution retraining programs are necessary for students as they transition
from elementary to middle and high school. As research by Folmer et al. (2008) and others
indicate, the perception of the relationship between effort and ability is correlated with age.
Folmer et al. (2008) found, based on the foundations of previous research conducted by Nicholls
(1978) that children’s understanding of effort and ability when faced with a negative outcome
varied with age. In elementary-aged children, ability and effort are found to be positively
correlated with the resulting belief that smart students exert considerable effort on a given task
(Folmer et al., 2008). Conversely, older children believe that ability and effort are reciprocally
related concepts and that smart students do not need to work hard, while students who do work
hard must do so because they lack intelligence. This discrepancy between age groups regarding
attributions indicates that there is a need for adolescent students to modify their beliefs in order
to associate effort, rather than solely ability, with achievement. One way to elicit this shift is
paradigms would be to create attribution retraining programs geared toward adolescents and
academics. However, consistency with administration may be one notable obstacle with
implementing attribution retraining programs in secondary schools. Middle and senior high
school students have multiple classrooms and a variety of teachers who teach different content.
For an optimal attribution retraining program, it may be recommended that a student receive
similar attributional reinforcement in every class, which would require intensive training and
committed instruction by the teacher. If a high school student receives attributional instruction in
one class, for example, then is praised for achievement over effort in another class, attributional
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retraining progress might be undermined. Once the success of an attribution retraining program
is established for secondary students, perhaps administrators can create policies to have these
programs implemented on a larger scale.
Additional Attributional Retraining Programs. Another form of attribution retraining
is described by Homsma, Van Dyck, De Gilder, Koopman, and Elfring (2007) as error
management training. Participants are encouraged to view task errors as a positive occurrence
and an opportunity for growth and improvement on the task. Participants were given three
different trials of a video game, and their tactical insights after errors were monitored. Error
heuristics such as, “I have made an error. Great!” are presented to facilitate emotional coping
after error occurrences, which, in turn guides individuals towards the belief that mistakes can
lead to constructive feedback. According to the study, error management training leads to more
functional task behavior such as increased requests for assistance, less frustration, and better
performance compared to error avoidant training. In addition, according to Homsma, et al.
(2007), individuals are more likely to engage in functional behavior when error occurrence is
interpreted as a circumstance from which positive aspects may come. For example, if errors are
perceived to be informative positive, a person is more likely to ask for assistance after the error
has occurred. Furthermore, the importance of identifying the cause of an error before it can be
interpreted is stressed (Homsma, et al., 2007). The results of the study showed that in general,
participants who were instructed to consider internal and unstable causes following an error were
more likely to engage in exploratory behavior (seeking a range of zero to eight specified
strategies to navigate through the video game) than those participants who were instructed to use
other causal ascriptions (Homsma, et al., 2007).
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Cognitive behavioral therapy (CBT) has also been used in attribution retraining. Resting
on the assumption that cognition is an antecedent to feelings and behavior, CBT had been shown
to change the attributions for success and failure of students with regard to learning (Toland &
Boyle, 2008). Research has shown correlations between attributions, motivation, and self-
esteem. As a result, students may become discouraged in academic settings when they are
unsuccessful. As a result, Toland and Boyle (2008) assert that students blame themselves for
academic failure and avoid practicing the very skills needed to improve. The goal of the study
was to transform the ways in which students thought of themselves and the attributions they had
for their achievement.
In the Toland and Boyle (2008) study, students with self-esteem and motivational issues
were identified by their schools. The students participated in 30-minute group sessions with an
educational psychologist who then worked with the students in reading and spelling, using
methods from CBT. Small groups, modeling, discussion, worksheets, and role play were used to
teach students the correlation between actions, thoughts, and feelings. Students then practiced
replacing negative thoughts about themselves with more positive thoughts, such as “I can” and a
belief that academic outcomes could be improved with increased effort (Toland & Boyle, 2008).
In addition, students were encouraged to monitor the positive feelings and the actions that
resulted (Toland & Boyle, 2008). Results of the study indicated that both children and parents
reported significant improvements in motivation and self-esteem.
Attribution Retraining in Non-Academic Settings. Attribution retraining has had an
impact in other areas outside of academia, and its applications in these areas can provide further
insight into its benefits. Attribution retraining methods have also been designed for non-
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academic areas such as behaviors around physical activity, career-orientation, and sports. One
study, for example, sought to eliminate the epidemic of a sedentary lifestyle in middle-aged and
elderly adults. While many theories and programs were applied to this demographic in an
attempt to increase quality of life, an attribution retraining program was shown to have positive
results (Sarkisian, Prohaska, Davis, & Weiner, 2007). The theoretical model used for this study
was Weiner’s attribution theory of achievement motivation. To reiterate, this theory is based on
the idea that individuals explain failures and successes using causal attributions that can be
classified by three dimensions: locus of causality, stability, and controllability. For the purpose
of this study, the goal was to provide participants with experiences that would foster the most
adaptive attributions—internal, unstable, and controllable (Sarkisian, Prohaska, Davis, &
Weiner, 2007).
A standardized curriculum was used in the Sarkisian, et al. study, and participants were
encouraged to both verbalize and put in writing commitments to increasing physical activities.
Focus groups were utilized to discuss issues that served as obstacles for participants, and
possible solutions were discussed. Results indicated that the participants increased their physical
activity as a result of the retraining program. In addition, the intervention increased the age
expectations of participants, and they were less likely to perceive that growing older would
inevitably cause a sedentary lifestyle. Sarkisian, et al. (2007) also found that the increased
physical activity and age expectations were positively correlated. Strategies used in the above
study, such as developing specific curricula, involving participants in the process of the program
and making them accountable, and being explicit about challenges and setbacks, serve as a viable
foundation for attribution retraining in an academic setting, as well.
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According to Zsuzsanna (2006), attribution retraining can have an impact on career
choices an individual makes. Attributional perceptions can affect the way individuals think about
their performance, the types of tasks people choose to engage in, and ultimately their career
choices. If an individual has an adaptive attributional style, for example, and perceives outcomes
to be determined by controllable factors such as effort, that individual is more likely to explore a
variety of career options. Furthermore, an abundance of research exists that supports the idea that
attributions can greatly impact performance in sports. LeFoll, Rascle, and Higgins (2008) sought
to explore the influence of functional (defined as internal, controllable, and unstable) and
dysfunctional (defined as external, uncontrollable, and stable) attributional feedback on causal
attributions, affect, perceptions about success, and short-term persistence during failure in golf.
Findings indicated that functional attributional feedback yielded improvements in causal
attributions regarding failure. Subjects were found to exhibit improved attributions, expectancies,
and persistence over time, compared to these beliefs before the feedback. Conversely,
dysfunctional attributional feedback yielded deterioration in causal attributions about failure,
and, as a result, was followed by lower success expectations, hopefulness, and persistence after
failure. The golf study found that improvement or deterioration was contingent upon the type of
feedback received (either functional or dysfunctional) more so than the initial attribution (LeFoll,
Rascle, & Higgins, 2008).
In summary, attribution retraining programs can have positive outcomes for participants
in academia, physical activity, career choices, and sports performance. There are many different
methods used to retrain attributions, including persuasion, modeling, cognitive behavioral
therapy, and error management training. Despite the variations on the design and
implementation, reviews of attribution retraining programs confirm the effectiveness of these
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programs, as well of the importance to help students foster functional attributions (Schunk,
Pintrich, & Meece, 2008).
An Attribution Retraining Curriculum in LAUSD
Dweck’s (2007) English Language Arts curriculum is an example of an attribution
retraining program that may influence attributions of 8
th
grade students. Researcher Carol Dweck
has used her research and applied them to academic settings. For example, in 2007, Carol Dweck
assisted eighth grade English teachers in the Los Angeles Unified School District to create a
curriculum that would teach students that the brain is a muscle that can become stronger when
working harder. Teachers, literacy coaches, administrators, and Local District and Central Office
staff, along with consultants Carol Dweck, Kylene Beers, Carol Jago, and Robert Probst,
compiled the English/Language Arts Instructional Units for Grade 8. Fifteen middle schools
throughout Los Angeles Unified were involved in the creation and piloting of the curriculum,
which included 28 middle school English Language Arts teachers and seventeen literacy coaches
who directly provided input and support through the development and implementation process.
In its entirety, the eighth grade curriculum consists of four units: Narrative, Exposition,
Response to Literature, and Persuasion. Unit One and Unit Two (Narrative and Exposition,
respectively) were designed, in large part, with the assistance of Carol Dweck and her research
(indicated in Table 1). For the purposes of this study, the discussion will focus on Unit One and
Unit Two of the curriculum, with additional emphasis on Unit One, as this unit, the Narrative
Unit, will be evaluated for the study.
The curriculum includes components that describe the entity and incremental views of
intelligence (referred to as “fixed” and “growth” mindsets) and how becoming self-aware of
personal factors that influence motivation could serve as catalysts to improved student
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achievement. Students were given activities throughout the curriculum that encouraged them to
reflect on their perceptions of their own intelligence, as well as use metacognition to identify and
reflect on factors that influence their motivation.
Dweck’s research, described in a synopsis in the introduction of the English Language
Arts lessons (Narrative Unit, Module 1), asks the question of whether teaching students how to
think of their intelligence as something malleable would benefit their achievement. The
introduction section of Narrative Unit Module 1 describes an early math study conducted by
Dweck and makes a connection between the findings of the study and the foundation for the
English Language Arts pilot lessons, which will be the basis of this study. Approximately 100
seventh graders who were struggling in mathematics were randomly assigned to two workshops
on study skills. One workshop specifically provided strategies for studying more effectively. The
other workshop taught students about the growth potential of the brain and its subsequent affect
on intelligence. Essentially, students in the latter workshop learned that every time something
new is learned, the brain makes new connections and, over time, this increases intelligence. The
results of Dweck’s mathematics study, and a basis for the LAUSD attribution retraining
curriculum, showed that students who received education indicating the growing potential of the
brain had significantly higher math grades than the students who did not receive this education.
The participants involved in the development and implementation of the curriculum set out to
determine if the success of the math study could be transferred to English Language Arts, as
well.
The California English Language Arts content standards for grade eight indicate that
students must learn and master skills related to narrative, expository, and persuasive texts, and be
able to respond critically to literature, as well. Each of the four genres as represented in the
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language arts curriculum consists of a number of modules (ranging from four to seven) that may
contain reading selections, visual texts, and graphic organizers to help students make meaning of
the text that they read. The overarching theme of the unit is the “Power of Language” which
looks at the way language can be used effectively in various forms, such as visual, spoken,
interactive, and written. The elements of the curriculum related to Dweck’s research, which lay
the foundation for attribution retraining, are in the introduction of the first unit, which is the
narrative unit.
Module 1 is entitled “Brainology and Growing Your Intelligence” and its main objective
is to engage students in texts, tasks, and discuss the effects of effort on the growth of
intelligence. Students examine current research on the brain while interpreting and evaluating the
effects of the power of language, via words and images, on students’ opinions of themselves and
others. After reading a synopsis of Dweck’s research with seventh graders and math
achievement, and reading a brief biography about Dweck, students view a “visual text” that
depicts a cartoon-like picture of a brain that is attempting to lift a barbell. The picture depicts the
brain with a grimacing facial expression with drops of sweat coming down its face. Students are
asked to describe what they believe is taking place in the visual text.
Students then read a short expository text that discusses how the brain works and can be
developed like a muscle. Teachers ask students a series of comprehension questions, then refer
back to the visual text of the brain and the barbell and ask students if their interpretation of the
picture has changed after reading the expository text. Students are then asked to reflect on why
they may have changed their interpretation. Students are then given another visual text to
interpret, which is a graphical representation that delineates a relatively simplified version of the
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elements of incremental and entity views of intelligence and how they manifest themselves in
attitude, behavior, and ultimately, effort and motivation.
The culminating activity of Module 1 requires students to write a “brain narrative”.
Students are asked to incorporate new learning from the texts and discussions to write a narrative
from the perspective of their brain. Students must use their brain character to make a statement
about whether or not they believe their brain can grow. After writing the brain narrative, students
are instructed to share their writing with a small group of peers and reflect on what was learned
from themselves and others. Students are given an opportunity to modify their narrative after
hearing input from other students, as well as listening to the narrative of their peers. In addition,
students are given the assignment to share their brain narratives with their family at home, and
reflect on how reading the article, writing the brain narrative, and sharing it with others has
supported their understanding of intelligence and effort.
The concept of motivation is the focus of Module 2. Students begin by completing a
graphic organizer, which is a series of boxes with letters of the alphabet heading each box.
Students are asked to think of the things that motivate them, and list those things in the
appropriate box according to the letter of the alphabet the word begins with. Students then read
an autobiographical narrative text written by Steve Brody titled, “How I Got Smart”, which
humorously depicts how the author is motivated to learn an abundance of information by
memorizing an encyclopedia with the hopes of impressing a female student. Students have the
opportunity to discuss how the narrative reflects the attitudes and beliefs of the author, and
students will ultimately compose a creative non-fiction narrative as they examine what
influences them to learn.
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In the second unit, Research/Exposition, students will reread the expository text “You
Can Grow Your Intelligence” and discuss the characteristics of the piece that classify it as
expository writing. Students are then assigned to read another expository text written by Carol S.
Dweck that further explains the “fixed” and “growth” mindsets and describes how detrimental it
can be when students are praised for achievement instead of effort. Students discuss these
concepts with their teacher and classmates, and reflect on how this can be applied to their own
learning. The goal of this process is to explicitly teach students how internal forces (beliefs about
intelligence) and external forces (feedback) can impact academic performance, and to guide
students toward mastery-oriented learning goals.
In summary, attribution retraining programs seek to transform maladaptive attributions in
order to yield more successful outcomes. In LAUSD, eighth grade English Language arts
students were exposed to an attribution retraining program based on the research of Carol
Dweck. One of the goals of the curriculum was to explicitly teach students about the growing
potential of the brain. With this information, students would further understand their cognitive
potential and their ability to control their own learning, ultimately being able to retrain their
attributions for academic outcomes. The results of the impact of this attribution retraining
curriculum on the eighth grade students will be determined, in part, by a qualitative study
discussed in chapters three through five. At this time, no data has been formally collected to
monitor the effectiveness of the LAUSD attribution retraining program.

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Table 1: Outline of Curriculum Guide Table of Contents
Modules listed below that related to the attribution retraining curriculum are indicated with an
asterisk.
Unit One:
Narrative
Unit Two: Exposition Unit Three:
Response to
Literature
Unit Four:
Persuasion
Module 1:
Brainology and
Growing Your
Intelligence
* “Intelligence”
and Biography of
Carol S. Dweck
* Visual Text 1.1:
Brain
* “You Can Grow
Your Intelligence”
by Lisa Blackwell
* Visual Text 1.2:
Mindset
* ABC Word Wall
* Writing a Brain
Narrative
Module 1: Research
Exposition Unit
Introduction
* “You Can Grow Your
Intelligence” by Lisa
Blackwell
* ABC Word Wall
* “The Secret to Raising
Smart Kids” by Carol
Dweck
Guidelines for
Developing a Research
Question
Module 1: Thematic
Statement: Langston
Hughes
Access Prior
Knowledge: Thematic
Topics
Identify Topics
Access Prior
Knowledge: Dreams
Read, Write, Talk, and
Listen for Multiple
Purposes: “Dreams”
StepBack on the
Process
Read, Write, Talk, and
Listen for Multiple
Purposes: “Harlem”
Read, Write, Talk, and
Listen for Multiple
Purposes Visual Text
1.1 “Dream Deferred”
Identify Recurring
Themes
The Stylistic Lens
Revise Recurring
Themes
Reread to Explore
Recurring Themes
Craft a Thesis About
Recurring Theme
Write About a
Recurring Theme
Read, Write, Talk, and
Listen for Multiple
Purposes:
“Culminating Task
Sheet and Graphic”
Read, Write, Talk, and
Listen for Multiple
Purposes: “Student
Draft of Hughes
Academic Essay”

Module 1:
Persuasion as a
Social Influence
Access Prior
Knowledge:
Persuasion
Survey the Text
Visually: “The
Recursive
Continuum”
Read, Write, Talk
and Listen for
Multiple Purposes:
“The Recursive
Continuum”
Read, Write, Talk
and Listen for
Multiple Purposes:
“Culminating Task:
Persuasion”
Read, Write, Talk
and Listen for
Multiple Purposes:
“New Crush-Proof
Box” Visual Text
1.1
StepBack
Read, Write, Talk
and Listen for
Multiple Purposes:
“The Problem”
Survey the Text
Visually: “Solar
Energy is Green.
Engineered”
Read, Write, Talk
and Listen for
Multiple Purposes:
“Solar Energy is
Green. Engineered”
StepBack
Read, Write, Talk,
and Listen for
Multiple Purposes:
“Deadly
Persuasion” Visual
Text 1.2
StepBack
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Criteria Chart:
Selecting the Crisis
Homework
Module 2:
Motivation
* “How I Got
Smart” by Steve
Brody
Module 2: Secondary
Sources
“Self 2.0: Internet Users
Put a Best Face
Forward” by Yuki
Noguchi
“What Happens in a
Virtual World Has a
Real-World Impact, a
Scholar Finds” by
Andrea Foster
“Balancing Identities:
Key Findings”

Module 2: Coherent
Thesis/Introduction:
Gary Soto
Access Prior
Knowledge: Coherent
Thesis
Survey the Text
Visually: “Oranges”
Read, Write, Talk, and
Listen for Multiple
Purposes: “Oranges”
Visual Text 2.1
“Oranges”
Academic Writer’s
Craft: Identify Topics
and Create a Thematic
Statement
StepBack on the
Process
Survey the Text
Visually: “Fair Trade”
Read, Write, Talk, and
Listen for Multiple
Purposes: “Fair
Trade”
Academic Writer’s
Craft: Identify Topics
and Create a Thematic
Statement
Academic Writer’s
Craft: Writing a
Coherent Thesis
Academic Writer’s
Craft: Writing an
Introduction
Write a Recurring
Theme Using a
Gender Lens
Read, Write, Talk, and
Listen for Multiple
Purposes: “Student
Draft of Gary Soto
Academic Essay”
Academic Writer’s
Craft: Cracking Open
Your Academic Essay
StepBack on the
Process
Module 2:
Introduction and
Thesis
Access Prior
Knowledge: Energy
Crisis
Read, Write, Talk,
and Listen for
Multiple Purposes:
“Sunny Days”
Visual Text 2.1,
“Earth 2.0” Visual
Text 2.2
Survey the Text
Visually
Read, Write, Talk
and Listen for
Multiple Purposes:
“A Generational
Challenge to
Repower America”
Reflect on Content
Access Prior
Knowledge: Well-
Defined
Thesis/Introduction
Read, Write, Talk
and Listen for
Multiple Purposes:
“A Generational
Challenge to
Repower America”
Introduction
Reflect on Content
Read, Write, Talk
and Listen for
Multiple Purposes:
“Responses to A
Generational
Challenge to
Repower America”
Introduction
Write the
Introduction for
Persuasive
Composition
StepBack
Homework
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Module 3: Folio
Narratives
Shakespeare
Excerpt and
Biography
Visual Text 3:1:
Name Tags
Visual Text 3:1:
Name Tags (with
caption)
“My Name” by
Sandra Cisneros
“My Middle
Name” excerpt by
Dan Kirby
My Names
Student Draft:
Name Narrative
“Mexico Next
Right: by Sandra
Cisneros
“Ode to Pablo’s
Tennis Shoes” by
Gary Soto
Student Draft:
Place Narrative
From An
American
Childhood by
Annie Dillard
Student Draft:
Artifact Narrative
ABC Word Wall
“No Speak
English” by
Sandra Cisneros
“Roughing It” by
Mark Twain
Student Draft:
Boundaries
Narrative
Module 3: Primary
Sources
“Leveraging Identity to
Make Learning Fun” by
Joey J. Lee and
Christopher M. Hoadley
“Leveraging Identity to
Make Learning Fun”
Key Findings Excerpt
“Virtual Human
Interaction Lab:
Projects” by Jeremy
Bailensen
“Balancing Identities:
Discussion/Interpretation
of Findings”

Module 3: Text-
Based Evidence:
Robert Frost
Access Prior
Knowledge: Text-
Based Evidence
Creating and
Anticipation Guide
Survey the Text
Visually: “The Road
Not Taken”
Read, Write, Talk, and
Listen for Multiple
Purposes: “The Road
Not Taken”
Survey the Text
Visually: “Stopping
by Woods on a Snowy
Evening”
Assertion and
Evidence Charts
Academic Writer’s
Craft: Identify
Thematic Statements
Read, Write, Talk, and
Listen for Multiple
Purposes: “Stopping
By Woods on a
Snowy Evening”
Academic Writer’s
Craft: Writing Support
Paragraphs
Academic Writer’s
Craft: Write an
Academic Essay
Read, Write, Talk, and
Listen for Multiple
Purposes: “Student
Draft of Frost
Academic Essay”
Academic Writer’s
Craft: Cracking Open
Your Academic Essay
Reflect on Content
StepBack on the
Process
Module 3:
Evidence and
Rhetorical Devices
Access Prior
Knowledge:
Evidence
Read, Write, Talk
and Listen for
Multiple Purposes:
“A Generational
Challenge to
Repower America”
(Evidence and
Rhetorical Devices
Excerpt)
Reflect on Content
Access Prior
Knowledge:
Rhetorical Devices
Read, Write, Talk
and Listen for
Multiple Purposes:
PowerPoint:
Rhetorical Devices
Read, Write, Talk
and Listen for
Multiple Purposes:
“A Generational
Challenge to
Repower America”
(Evidence and
Rhetorical Devices
Excerpt)
Reflect on Content
Write Evidence and
Rhetorical Device
Section for
Persuasive
Composition
StepBack
Homework

Module 4:
Writer’s Craft
“One Million
Volumes” by
Rodolfo Anaya
Anaya’s Heritage,
Traditions,
Attitudes, and
Beliefs
Module 4: Data
Chart/Graph 1
Chart/Graph 2
Sample Avatar Study
“Balancing Identities:
Format 1”

Module 4:
Commentary: Pat
Mora
Access Prior
Knowledge:
Commentary
Survey the Text
Visually: “Legal
Alien”
Module 4:
Counterarguments
Access Prior
Knowledge:
Counterarguments
Survey the Text
Visually
Read, Write, Talk
and Listen for
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Transitional
Expressions
Similes,
Metaphors, and
Strong Verbs
Student Draft:
Culminating Task
Student Draft:
Additional Model

Read, Write, Talk and
Listen for Multiple
Purposes: “Legal
Alien”
Academic Writer’s
Craft: Excerpt from
“Legal Alien”
Academic Essay
Write a Response to
Literature
StepBack on the
Process
Multiple Purposes:
“Counterargument
from Investor’s
Business Daily”
Read, Write, Talk
and Listen for
Multiple Purposes:
“A Generational
Challenge to
Repower America”
Read, Write, Talk
and Listen for
Multiple Purposes:
“A Generational
Challenge to
Repower America”
(Counterarguments
Excerpt)
Reflect on Content
Write
Counterarguments
for Persuasive
Composition
StepBack
Homework
Module 5:Research
Report Introduction
“What Happens in a
Virtual World Has a
Real-World Impact, a
Scholar Finds” by
Andrea Foster
“Balancing Identities:
Introduction”
Evaluating a Thesis
Statement
Student Draft:
Introduction
Module 5:
Conclusion: Edwidge
Danticat
Access Prior
Knowledge:
Conclusions
Survey the Text
Visually” “White
Darkness/Black
Dreamings”
Read, Write, Talk and
Listen for Multiple
Purposes: “White
Darkness/Black
Dreamings”
Except from Krik?
Krak!
Academic Writer’s
Craft: Response to
Literature
Write a Response to
Literature
StepBack on the
Process
Module 5:
Conclusion and
Call to Action
Access Prior
Knowledge:
Conclusions
Survey the Text
Visually
Read, Write, Talk
and Listen for
Multiple Purposes:
“A Generational
Challenge to
Repower America”
(Conclusion
Excerpt)
Reflect on Content
Write Conclusions
for Persuasive
Composition
StepBack
Homework

Module 6: Methods,
Conclusion, and
Recommendation
“Leveraging Identity to
Make Learning Fun”
Methods Excerpt
Module 6: Academic
Writer’s Workshop
Access Prior
Knowledge:
Academic Writing
Preparing to Read
Module 6:
Persuasive
Writer’s Craft
Access Prior
Knowledge
Read, Write, Talk
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“Balancing Identities:
Methods”
“Leveraging Identity to
Make Learning Fun”
Conclusion Excerpt
“Balancing Identities:
Conclusion”
“Balancing Identities:
Recommendations”
Read, Write, and Talk
for Multiple Purposes:
“Grandmothers”, “Old
Man”, “One Million
Volumes”, Other
previously read texts
Academic Writer’s
Craft: Response to
Literature
Write a Response to
Literature
Evaluate and Revise
Academic Essay
StepBack on the
Process

and Listen for
Multiple Purposes:
“Child Soldiers:
Too Young to Kill,
Too Young to Die”
Reflect on Content
Read, Write, Talk
and Listen for
Multiple Purposes:
“Child Soldiers:
Too Young to Kill,
Too Young to Die”
Access Prior
Knowledge
Read, Write, Talk
and Listen for
Multiple Purposes:
“Annotated
Bibliography”
Developing the
Criteria Chart
Construct and
Combine the
Persuasive
Composition
Revise to Develop
the Final Draft
StepBack
Homework
Module 7:
Writer/Researcher’s
Craft
Balancing Identities:
Abstract
Researcher’s Craft:
Summary
Balancing Identities:
Bibliography
Balancing Identities:
Format 2
Research Tools
Search vs. Research
Strategies for Evaluating
Internet Sources
Documenting Sources
Taking Notes
Works Cited
What is Plagiarism?
Module 7:
Treatment, Scope,
and Organization
Access Prior
Knowledge:
Brochures
Read, Write, Talk
and Listen for
Multiple Purposes:
Visual Texts 7.1,
7.2, 7.3, 7.4, 7.5
Reflect on Content
Survey the Text
Visually: Sample
Brochure
Persuasive Writer’s
Craft: The Brochure
Access Prior
Knowledge: Logos
and Slogans
Creating a Slogan
StepBack
Persuasive
Presentations
Homework

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Conclusion

Attributions have been found to have a profound impact on motivation and achievement.
The three attributional dimensions (locus dimension, stability, and controllability) have
significant consequences for individuals’ expectancies for success (Schunk, Pintrich, & Meece,
2008). When the most adaptive dimensions (internal, unstable, controllable) are identified after a
success or failure, an individual is more likely to be motivated to persist on difficult tasks and to
seek help or try new methods when new material is challenging (Dweck & Elliott, 1983; Dweck
& Goetz, 1978; Homsma, et al., 2007). This increased motivation has been found to have
positive effects on achievement (Weiner, 1985).
Despite these findings, there is a limited amount of research on methods for changing
attributions and a limited amount of qualitative research examining this motivational issue;
therefore, additional research is important. While an abundance of research exists that supports
the assumption that attribution retraining programs can positively affect the attributions of
individuals, there also is a gap in the research that would provide precise documentation about
retraining programs and their consistent implementation in an academic environment.
Furthermore, it is noted that while Forsterling (1985), Robertson (2000), and Schunk
(1982) provide comprehensive reviews of attribution retraining programs, there is no substantial
information that addresses how perceptions and beliefs are influenced by the programs. Most
attribution retraining programs focused on academic achievement rather than changed
perceptions. For long-term benefits of attribution retraining, it would be important for an
individual’s perceptions about their intelligence and the impact of their effort to change, rather
than simply changing a strategy on an academic task. In addition, historically, a vast majority of
attribution retraining programs has been quantitative, and there is a need for more qualitative
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research that examines this motivational issue related to beliefs about intelligence and
attributions. Robertson (2000) posits, after a comprehensive study of 20 attribution retraining
programs designed specifically for children with learning disabilities, retraining programs are
effective, but their limitations (e.g. transfer of methodologies from laboratory settings to
classroom settings) must be acknowledged with regards to the application of attribution theory.
Attribution theory is a complex one, and many attribution retraining programs do not always
practice attribution the way the theory was intended.
Furthermore, as noted by Horner and Gaither (2004), while an abundance of research has
been conducted in relation to student thinking, behavior, and motivation, the transfer of
methodologies into real-life classrooms is challenging. Even when techniques are found to be
successful, teachers may be reluctant to use them. Therefore, there is a disconnect between
research and practical application that needs to be remedied. In addition, as noted in Robertson’s
(2000) meta-analysis of attribution retraining programs, there are limitations regarding the
transition between research and practice. Certain elements that were designed for a clinical
setting are difficult to reproduce in a classroom setting, due, in part to inconsistent teacher
implementation or limitations of time in the school day. The attribution retraining program in
LAUSD that was developed using the foundational research of Carol S. Dweck was designed
with educators with the primary goal of classroom implementation. This intentional classroom
design may be more conducive to practical application than the limitations described in
Robertson’s (2000) meta-analysis.
Several studies noted that for students to feel they can succeed at an academic task,
attribution retraining must ensure that the student has the ability to succeed at a given task before
using effort attribution (Forsterling, 1985; Robertson, 2000). If a child exerts a great deal of
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effort and is still unsuccessful, low ability attributions may be reinforced by the adult who
encourages the child to exert more effort. There is little research that offers strategies to mitigate
this relationship between low-ability, high effort situations. When implementing attribution
retraining programs such as the curriculum in this study, it is important for educators to identify
low-ability, high effort situations and be able to provide support to the student to scaffold
learning when it becomes challenging.
In summary, while this comprehensive review sheds light on the benefits and limitations
of attribution retraining programs for students with learning disabilities, there is little research
that explores the effectiveness of attribution retraining programs for students in general
education classrooms. The study of Carol Dweck’s attribution retraining curriculum for eighth
grade students will be a step toward determining the effectiveness of such programs and how
student perceptions of their academic achievement are affected.

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Chapter Three: Research Methodology
Introduction

The purpose of this study was to obtain further insight regarding how middle-school
student perceptions may influence their academic achievement. The primary focus was the
perception that students have about their academic abilities, and how these perceptions may be
informed by the implementation of an attribution retraining curriculum in their English class.
How perceptions might also be influenced by theories of intelligence, feedback, and
developmental stage was also a consideration for this study. The goal of this research was to be
able to provide concrete findings about this middle school population that could be applied in a
practical way by educators to contribute to the improvement of academic outcomes of these and
other students.
This chapter presents the research questions that frame the study, as well as the specific
research methodology that was used. The research methodology section discusses the sampling
procedure used for the selection of the participating school, teacher, and students, as well as
providing a rationale for these procedures. In addition, this section includes basic demographic
information on the participants, the instrumentation, and procedures for data collection.
Research Questions
The following research questions guided this study:
1. Is there a difference between students’ beliefs about their intelligence before and after
an attribution retraining curriculum in English language arts?
2. How have middle school students’ perceptions of their academic abilities changed as
the result of an attribution retraining curriculum in English language arts?

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Research Design
While quantitative research about the effects of attribution retraining programs are
abundant, qualitative studies that delve deeper into student perceptions about attributions are
scarce. The purpose of the study was to illuminate these student perceptions, specifically, as
these perceptions relate to the effects of an attribution retraining curriculum in eighth grade
English classes. Using both qualitative and quantitative methodologies, this study sought to
examine the relationship between student perceptions about their intelligence, motivation, and
academic outcomes.
This study used three distinct methods for obtaining information from the participating
students. The first method was free-response entries in a journal prior to curriculum
implementation. The journal question was, “Thinking about your most challenging subject in
school, why do you think it is difficult?” Second, students were given a survey that consisted of
six questions to be answered on a Likert scale (Appendix A). Finally, individual interviews were
conducted with 20 students (four students randomly selected from each class) to share their
experiences with the curriculum and to discuss how their perceptions were influenced. The
following questions were asked in the interview, “How did you feel about the curriculum?”
“How have you or have you not changed the way you feel about your academic abilities?
Explain why your feelings about your academic abilities have or have not changed.” Data
collection for this research was collected over a three-week period, during which the researcher
observed lesson implementation to the 105 participating students on 17 separate occasions.
While several meta-analyses of attribution retraining programs have been published
(Forsterling, 1985; Robertson, 2000; Schunk, Pintrich, & Meece, 2008), there still remains to be
conclusive evidence as to which attribution retraining programs are most effective, and there
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fails to be consistent implementation of attribution retraining in public secondary schools. As
middle schools are typically designed in a way that emphasizes academic competition and the
normative characteristics of ability, these schools create an environment that often encourages
middle school students to exhibit perceptions of an adult (Schunk, Pintrich, & Meece, 2008).
These adult perceptions include those that suggest that ability is recognized as a factor that limits
the effects of effort (Folmer et al., 2008). Consequently, these perceptions may hinder student
persistence when academics grow more cognitively challenging. Therefore, determining the
effectiveness of attribution retraining programs for this developmental stage is crucial.
A qualitative study would give academic institutions much-needed insight to better understand
how student perceptions, particularly those of middle school students, can affect motivation and
adversely affect academic outcomes, as a result.
Participants. The 105 participants in the study were eighth grade students (mean age: 13.2
years) of Hudson Middle School located in an urban school district in Southern California.
Hudson Middle School is on a traditional academic calendar and is home to approximately 570
students. Of these students, 66% are Hispanic or Latino, 31% are African American, and 3% are
other. In addition, Hudson Middle School is comprised of 82% of students who are eligible for
free and reduced lunch, and 33% of the student population is English Language Learners.
Of the 33 teachers at Hudson Middle School, 83% are fully credentialed, compared to the
state average of 96%, and have taught for an average of 11 years, compared to a state average of
13 years. Based on voluntary teacher interest and consultation with the administrator over the
English Language Arts program, one teacher was selected to participate in the study. The
participating teacher was selected based on her teaching assignment: eighth grade English
Language Arts in a public, traditional calendar middle school in Compton Unified School
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District. The teacher who participated in the study, Janine Roberts, had been a professional in
education for 20 years, including having been a principal at a middle school in the same district
for three years. Ms. Roberts had also been a mentor for new teachers, and had obtained her
Master’s degree in Education from an accredited university eight years prior. Ms. Roberts taught
six sections of eighth grade English. For the purposes of this study, five sections of English were
selected to participate in the study, as per teacher request. Each class consisted of an average
number of students (mean class size: 21), for a total of 105 students.
Data Collection
The researcher obtained the appropriate clearance from Compton Unified School District
officials prior to data collection. After the teacher was selected to participate, consent forms for
both students and parents were distributed and collected from students subject to participate in
the study. The consent documents were available in both English and Spanish and highlighted
the purpose of the study, the methods that were used, and the confidentiality component. Consent
forms also informed the parents and participants that documentation would be collected, and
individual interviews would be conducted. It was also noted that grading of any of the work
completed during the course of the three-week attribution retraining curriculum would be
determined by teacher discretion.
After curriculum implementation, journal responses were collected by the researcher and
coded according to type of response. Students’ journal responses that indicated a positive change
in their perception of academic ability were coded positive, responses that indicated no change
were coded static, and responses that indicated a negative change were coded negative. As the
goal of this study was to determine how an attribution retraining curriculum might influence
student perceptions of their academic abilities, it was important to ascertain what those student
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perceptions were prior to participating in the retraining curriculum, and compare those
perceptions to those expressed at the end of curriculum implementation. Ultimately, the goal of
the study was to determine how the curriculum could inform other educators in the design and
implementation of their instruction to better meet the academic needs of a student population that
is at risk.
The Likert-scale survey, while a quantitative measure, served as a way to provide
baseline responses and give participants some initial language and focus for which to give their
responses. The survey was administered at the end of curriculum implementation, as well, and
these student responses were compared to those before curriculum implementation. Appendix A
shows the survey that will be distributed to participating students before and after curriculum
implementation.
Interview Protocol
Random sampling was used to select the four students per class to participate in the
individual interviews. It was determined by the researcher that four students per class, or about
20% of the average class size, would be an adequate sampling for interview responses. On small
pieces of paper, the researcher wrote numbers that corresponded to the identification numbers of
the participants. The numbers were placed in a clear plastic bag, and, in the presence of students
in each class, the researcher pulled out four numbers that would indicate those who would
participate in the interview. Individual interviews were conducted in five to ten minute sessions
during the students’ lunch and/or homeroom periods, in order to avoid interrupting time allocated
for academics. Students were seated in a quiet location with the interviewer, and responses were
transcribed on a computer by the researcher.

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Data Analysis
This study of middle school ELA students was analyzed in the context of applied
qualitative research, based on Patton’s (2002) guidelines. As Patton (2002) notes, purpose guides
analysis. The ultimate goal of the study is to be able to practically apply the beneficial
components of the attribution retraining program in other academic settings. This goal guided the
analysis of the data. In order to answer the research questions and identity a change in student
perceptions of academic abilities, data from the secondary journal responses were analyzed
holistically. After disaggregating the responses by positive, static, and negative statements, the
researcher applied deductive analysis to examine student journal responses using Weiner’s
(1980) three causal dimensions—locus dimension, stability dimension, and controllability
dimension— as a framework (Patton, 2002). With this framework laying the foundation for the
qualitative responses, the researcher was able to determine the nature of student attributions after
curriculum implementation. Responses from the randomly administered interviews were also
analyzed holistically using deductive analysis and emerging trends were noted and are discussed
in detail in Chapter 4.
In this study, 105 total responses were recorded for analysis. Ms. Roberts had 25 students
participate in her Period 2 English class, 22 students in Period 3, 26 students in Period 4, 17
students in Period 6, and 15 students in Period 7. The 105 students had the opportunity to
complete pre-journal and post-journal responses, pre-Likert-scale and post-Likert-scale surveys,
and randomly administered interviews. A qualitative analysis was done using written journal
responses and scripted interview responses. There were a total of 76 journal responses and 20
interviews for this part of the study.
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Quantitative analysis was conducted from the Likert-scale survey responses. A principle
components factor analysis (PCA) was used on the data from the Likert-scale survey, and a
paired samples dependent t-test was conducted to determine whether students’ perceptions of the
malleability of their intelligence were impacted from pretest to posttest. An inadvertent mistake
on the part of the teacher resulted in no administration of the Likert-scale survey to the students
in Period 3 and Period 4 at the beginning of the study. Consequently, those 48 students were not
included in the Likert-scale data analysis. An additional total of 14 students in Periods 2, 6, and 7
were not included in the Likert-scale data analysis because they were not present for the either
the pre-survey administration, post-survey administration, or both.
The initial research question asked if there was a difference between students’ beliefs
about their intelligence before and after an attribution retraining curriculum? In order to answer
this research question, quantitative methods of analysis were used. The quantitative data was
analyzed using SPSS Statistical software. Qualitative methods were used to answer the second
research question: How have middle school students’ perceptions of their academic abilities
changed as the result of an attribution retraining curriculum? Using deductive analysis, the
qualitative data was analyzed by assessing student narrative responses, noting patterns among the
responses, and categorizing them based on positive, negative, and static responses.
In preparation for the study, the researcher met with the selected teacher that was
recommended by the principal Hudson Middle School. These recommendations were based on
teacher willingness to participate, level of experience, and the demographic of students taught.
The researcher then provided the teacher with individualized training on the curriculum and the
teacher was given the necessary materials for the program. Finally, student participants
submitted signed consent forms for the study.
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Qualitative analysis was conducted using the pre- and post-journal responses and
randomly administered interviews. The researcher collected the qualitative data over a span of
eighteen days in February. The researcher observed five 50-minute sections of eighth grade
English (Period 2, Period 3, Period 4, Period 6, Period 7), and observed each class on three
separate occasions over the 18- day period. Students composed a written response to the journal
question on the first and last day of the program (see Appendix B). The following journal
question was posed on the first day of the curriculum implementation: Thinking about your most
challenging subject in school, why do you think it is difficult? The purpose of this question was
to identify student attributions for the difficulty of the class in order to compare these attributions
to student journal responses at the end of curriculum implementation. At the end of the
curriculum implementation, students were asked to respond to the following journal prompt:
Reread your initial journal response from two weeks ago. Do you feel the same or different?
Why or why not? The purpose of this question was the serve as a metric for the research
question: would students’ perceptions of their academic abilities change as a result of the
attribution retraining curriculum? The first journal response would establish what the student
perceived to be the cause for the difficulty in the subject at school, and the post-curriculum
journal question sought to determine if the cause of difficulty might be changed, and how the
student felt about managing that difficulty.
On the final day of the 18-day curriculum implementation, the researcher randomly
selected four students from each participating class to be interviewed. The school assigned each
student in each class a different roster number at the beginning of the semester (alphabetically by
last name), and those numbers were used for the random sampling. Absent students were also
included to support the random sampling technique. All student numbers were folded in half to
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conceal the contents and placed in a clear plastic bag. In front of the class, the researcher
randomly pulled out four numbers from the bag and wrote them on a white board in the order
selected. The researcher called each number selected and asked the corresponding student to
raise his hand to confirm the student was present. During lunch or homeroom period, the selected
students were taken one at a time to an empty classroom next door for privacy. Each student
received the two interview questions on paper, as well as heard them asked orally by the
researcher: (Q1) How did you feel about the curriculum? (Q2) How have you or have you not
changed the way you feel about your abilities? Explain why your feelings about your abilities
have or have not changed. There were a total of 20 students interviewed and the researcher
transcribed responses on a laptop computer as students were answering the questions.

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Chapter Four: Results
Introduction
The purpose of the study is to gain a better understanding of perceptions middle school
students have about academic abilities-viewed through the lens of the eighth grade English
Language Arts attribution retraining curriculum. Determining whether developmental and other
environmental factors or explicit attribution retraining curriculum is most influential on student
perceptions about intelligence and academic outcomes is salient to this research.
As previously stated, there is a need for analyzing how decreases in motivation may adversely
influence student achievement. Schools that fail to meet the improvements of No Child Left
Behind are subject to corrective measures, so it is important to explore viable options for such
measures.
While attribution retraining programs have been found to successfully increase self-
efficacy and academic outcomes, attribution retraining programs have not been widely used in
urban, public secondary schools. As a result, more research was needed to see how this type of
retraining curriculum might impact participant motivation and academic achievement in
adolescence, especially because the structure of traditional middle schools is not conducive to
motivation. For example, emphasis on social and academic comparison may foster a belief that
exerting effort indicates lack of intelligence; higher teacher to student ratio makes it more
difficult for students to foster personalized relationships with their teachers. Therefore, an
attribution retraining curriculum at the middle school level could be an effective tool used to
enhance motivation for middle school students.
Perceptions about intelligence, as well as developmental factors, can impact student
motivation (Schunk, Pintrich, & Meece, 2008). This study aims to present qualitative and
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quantitative data to educators that will help understand student beliefs, motivation, and ways in
which students best learn. Three metrics were used to answer the research question, how have
middle school students’ perceptions of their academic abilities changed as a result of an
attribution retraining program: pre- and post-journal responses, pre-and post-Likert scale survey
responses, and interviews conducted with randomly selected participants.
The motivational dimensions of attributions will be used to frame the qualitative
participant responses. The link between attributions and motivation can be established through
an examination of causality indicated along the following dimensions: locus dimension, stability
dimension, and causal dimension (Schunk, Pintrich, and Meece, 2008). The locus dimension
establishes whether the cause is internal or external to the individual; the stability dimension
measures stability of the cause over time; and the controllability dimension refers to how much
control an individual has over a cause These dimensions have been found to greatly impact an
individual’s expectancies for academic success (Schunk, Pintrich, and Meece, 2008). These
dimensions will be exemplified further in the qualitative results section of this chapter.
Quantitative Results
The purpose of this study was to determine the influence of an attribution retraining
curriculum on student perceptions of their intelligence. A belief in the malleability of
intelligence, which is an adaptive attribution, has been linked to increased motivation to exert
effort on academic tasks (Schunk, Pintrich, & Meece, 2008). The six survey questions assessed a
single construct, which was the belief that intelligence is something that can develop over time.
Items one through three require the participant to indicate the degree to which they agree or
disagree that an individual has a certain amount of intelligence and cannot change the amount.
Items four through six require the participant to indicate the degree to which they agree or
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disagree that intelligence can be changed no matter the circumstance. Therefore, a single scale
was used rather than examining each of the six questions separately. SPSS statistical software
was used to conduct a factor analysis and internal reliability. Second, a paired samples dependent
t-test was used to compare the mean scores from pre and post Likert scale survey results.
Factor analysis and internal reliability. A principle components factor analysis (PCA) was
conducted on the six Measuring Your Mindset questions, using orthogonal rotation (varimax).
The Kaiser-Meyer-Olkin (KMO) test was used to measure the adequacy of the sampling and
sample size. The KMO verified that the sampling and sample size of participants yielded a
dataset marginally suitable for principal component analysis (PCA) (KMO = .68; [on the upper
limit of ‘mediocre’ according to Field, 2009]). Bartlett’s test of sphericity is a test statistic used
to determine whether or not variables are correlated in the population sampled. Bartlett’s test of
sphericity (x
2
(15)
= 82.37, p < 0.001) indicated that the correlations between the six Measuring
Your Mindset items were of great enough magnitude to permit examination with PCA.
Prior to rotation, eigenvalues of the unrotated matrix were examined, yielding two factors
with an eigenvalue greater than 1. These factors, explained a total of 47.66% and 17.43% of the
observed variance, respectively. Upon closer examination, 5 of the 6 questions were grouped into
a single factor, but the remaining sixth item loaded well onto the first factor, as well (See Table
1). On its own the sixth item had an eigenvalue only marginally higher than 1 (1.05). Further
examination of a scree plot revealed inflexion (where the slope of the line on the scree plot
shows a distinct change) showing a 1- or 2-factor solution. Given that a single factor solution
performed nearly as well as the two-factor solution and that the six items appeared to tap into the
same latent construct, it was decided to include all six items in single scale. Each of the six
questions in the survey assessed a single construct—the belief the intelligence is malleable.
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Three of the items in the scale were reverse coded, so that higher scores on all six items
reflected greater belief that intelligence is malleable. A single scale comprised of the six items
was then created by summing the individual Measuring Your Mindset questions, yielding a
single variable with possible scores ranging from six to 36. Examination of Cronbach’s alpha
showed a high degree of internal consistency (α = .78), with single-item deletions making
negligible changes to the scale’s overall alpha value. This data shows that the six questions are
reliable and can be used to accurately assess student perceptions about intelligence.
Second, a paired samples dependent t-test of means was conducted to compare the
average scores of participants’ survey responses before and after participating in the curriculum.
Table 2 includes the findings from this test. Interestingly, it was found that there is a statistical
difference between the pre and post scores. For the pre-test score, the average score was 26.20,
while the post score average was 28.89. These two scores were found to be statistically
significantly different at the .01 alpha level, as indicated in Table 1. The initial research question
sought to determine if there was difference between students’ beliefs about their intelligence
before and after an attribution retraining curriculum. This data indicates that the treatment was
affective in increasing students’ perceptions of the malleability of their intelligence. Therefore, it
was established that the attribution retraining curriculum caused a change in students’ beliefs
about their intelligence.
The findings from the t-test clearly show that students’ beliefs about the malleability of
intelligence increased after students engaged in the attribution retraining curriculum. This finding
suggests that in a classroom, when a teacher explicitly teaches students about how the brain
works like a muscle and grows with exerted effort, students’ perceptions about their intelligence
can be positively impacted. When students believe that academic success lies within an internal
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locus of control, is unstable, and is controllable, they are more likely to be motivated to continue
to pursue academic success. The data supports this finding, as there was a significant statistical
difference between the pre-survey and post-survey.

Table 1

Component Loadings from Principal Component Analysis
Variable Component
Likert-Survey Questions 1 2
You have a certain amount of intelligence, and you really can't do
much to change it
.750 .268
Your intelligence is something that you can't change very much
.768 -.424
You can learn new things, but you can't really change your
intelligence
.681 -.462
No matter who you are, you can change your intelligence a lot*
.675 -.068
You can always greatly change how intelligent you are*
.702 .110
No matter how much intelligence you have, you can always change it
quite a bit*
.543 .751
* denotes reverse-scored variables

Table 2
A paired samples dependent t-test comparing pre and post responses of a Likert- scale. (p<0.01)
Mean Scores Standard
Deviation
t Sig. (2 tailed)
Pre test 26.20 6.48
Post test 28.89 4.60
Result 2.93 0.006

Qualitative Results
The reiterate, the purpose of this study was to determine if an attribution retraining
curriculum could influence students’ perceptions about their intelligence, and as a result,
potentially increase students’ academic motivation at a critical stage in development. The main
goal of the attribution retraining curriculum was to explicitly teach students about how the brain
works and to identify and understand factors that influence motivation. Qualitative methods were
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used because perceptions and beliefs are more accurately captured in a narrative form and the
study could take into account all of the nuances of student experiences. A qualitative approach
allowed for elaborated responses and also provided specific examples of student perception of
intelligence and academic ability.
Analysis of Journal Responses. Each journal response was given a code for positive,
negative, and static. The researcher read each response carefully, and underlined key phrases
such as, “I feel different” and “now I feel good” to determine if the response showed a positive
perception of academic ability after experiencing the curriculum. Responses were classified as
“static” when the respondent indicated in their post-journal or interview response that their
attitude toward their most challenging class remained the same as when the study began. Phrases
such as, “I feel the same as before” and “Algebra is still the hardest subject for me” are examples
of those given a coding for a “static” response.
Out of 76 journal responses, 47 indicated a positive change, 27 were static, indicating no
change, and one response indicated a negative change. One student response was incomplete, so
was not included in the qualitative results for this study. Responses from students who were
absent either on the first or last day of curriculum implementation and did not have both a pre-
and post-journal response were not included in the analysis of these results.
A positive response from the post-journal entry was determined if a student indicated
some expectancy of future success after having participated in the attribution retraining
curriculum. Student responses that were selected for closer analyses in this section were those
that showed a clear response to the post-journal question and students attempted to articulate a
reason for their response. The researcher selected a sample of 15 positive and 13 static journal
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responses as a representation of those types of responses. Sample post-journal responses that
were selected for analysis are included in the Appendix.
The researcher determined response trends based on the motivational dimensions of
attributions: the locus dimension, the stability dimension, and the controllability dimension
(Weiner, 1986). The locus dimension refers to whether the cause of an outcome is internal or
external to the individual. The stability dimension indicates the degree to which the cause is
stable over time. The controllability dimension indicates how much control the individual has
over the cause. To identify response trends, the researcher closely examined student responses
that were selected based on clarity of response and articulation of a reason for their response, as
stated above. Responses were highlighted that aligned to the examples provided in Schunk,
Pintrich, and Meece (2008), and the researcher noted if the statements exemplified internal or
external, stable or unstable, and controllable or uncontrollable attributions for their feelings about
the level of academic challenge of the class they selected.
The first trend that was found from a majority of positive responses was a combination
of internal, unstable, and controllable attributions for why respondents felt differently about their
most challenging class after participating in the attribution retraining curriculum. When
academic challenge is attributed to internal, unstable, and controllable causes, the individual
believes that they have the ability to improve academic outcomes in the future based on changing
a causal factor, such as applying more effort (Schunk, Pintrich, and Meece, 2008). For example,
student 3-10 responded:
“I feel different now. I understand that even if I think it is not important, if I pay attention
my intelligence will grow [internal, unstable]. I now comprehend the subject a little bit more.
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Two weeks ago I didn’t understand history a lot, but this week I took a test and scored 36/40. I
think it is because I learned about the brain and it helped me to exercise my brain [controllable].”
Student 3-11 indicated, “After all those essay research papers I think the reason history is
challenging because I don’t put many effort [internal]…So all I have to do to understand this
subject more is study to make my knowledge greater [unstable, controllable]!” Student 2-8
revealed, “I feel different because really all I had to do is just challenge my brain more [internal,
stable]. By studying reading every night. So now [sic] history is getting easier. I see a great
change in my last tests and quizzes. I really just had to unlock the inner smartness out of me
[controllable].” Student 6-15 responded: “Now that [I] went through Brainology thing I kinda
feel different…because now I know how to do the problems in algebra [unstable]. All the
reading and talking did help me out a lot [internal]. So now I can do the problems in algebra and
not only algebra but in other subjects too [controllable].” Students’ with positive responses
indicated a belief that doing better academically was something in their control such as studying
harder, concentrating more in class, or eliminating distractions. Many students attributed this
belief to the attribution retraining curriculum because it taught them that the brain is like a
muscle and the harder you work at something, the more you can learn.
Conversely, the second trend that was found was that a majority of static responses were
external, stable, and uncontrollable attributions. When academic challenge is attributed to
internal, stable, and uncontrollable causes, the individual believes that they lack the ability to
improve academic outcomes. This is the most maladaptive pattern of attributional beliefs
(Schunk, Pintrich, and Meece, 2008). For example, student 3-14 responded, “I feel the same as
before. My teacher still makes algebra a mission for me [external, stable]. She still talks and
writes too fast. Nothing has changed as to how she teaches. Her accent is still complex to
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comprehend [uncontrollable]. My feelings have not changed a bit whatsoever.” Consistent with
the fundamental attribution error, this student attributes subject difficulty to her teacher, and
therefore any expectation of future success in algebra is beyond her control. According to
Schunk, Pintrich, and Meece (2008), the fundamental attribution error can be identified when
another person’s behavior is attributed to dispositional or personal factors, while ignoring more
relevant situational factors. As the name suggests, this type of attribution is often incorrect and
can lead to subsequent biases held by the perceiver. Student 2-9 reported: “I feel the same as I
did two weeks ago because I don’t understand history [stable]. Another reason why I feel the
same as I did before is because history isn’t interesting and when you have a boring class early in
the morning, it makes you tired and sleepy [external]. But if I had an art class for first period it
would probably be much better and I would be wide awake [uncontrollable].” The student
perceives the difficulty of history to be tied to the time of day it is taught where he is likely to be
sleepy, as well as an inherent quality of being a boring subject. Both of these attributions remove
any responsibility the student might take toward making history less challenging. Student 6-1
responded: “Algebra is still the hardest subject for me. I still don’t understand algebra [stable]. I
try my best but algebra is just too hard for me. The teacher barely even explains how to do the
math problems. Maybe if the teacher explains it more I would understand algebra [external,
uncontrollable].” Since the student cannot control the teacher’s methods for explaining, the
students feel that her understanding of algebra is solely contingent on the teacher’s actions.
There were some outliers to this pattern, as some students with static responses identified
an internal locus dimension. For example, student 6-4 wrote, “Actually I feel the same about it
[stable]. My English class is the same it’s not like ‘oh my English class is hard’, or anything it’s
just my handwriting that messes me up [internal, controllable]. That is the sole reason why my
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English class is my worst class. That one aspect affects my entire grade.” Although this student
felt that English class was still difficult after the retraining curriculum, he attributes the difficulty
to his handwriting quality, a factor that is both internal and controllable. This indicates that the
student believes effort can influence academic outcomes, which is a fundamental belief
correlating to malleable intelligence. Another student with a static response wrote:
I feel the same because math is still hard to understand [stable]. After all I thought math
was numbers but now it comes up with weird signs and letters. Aside from that I know
math will never be my strongest point but I do think I should at least try [controllable].
Mainly it’s because of my goals I don’t do good in math [internal]. I want to be an author
or marine biologist and I don’t think you need to master math for it.

This respondent, while reporting feeling the same towards math after the curriculum, still
indicated an internal locus of control over setting different goals in order to improve in math.
This reveals that while the student did not directly acknowledge the curriculum, the student
identified a key element of malleable intelligence, which is the belief that effort and goal-setting
can enhance learning.
Another outlier among student responses was student 3-22 who indicated that she felt her
most difficult class became even more challenging at the end of the 18-day curriculum: “For me
science has only gotten harder. Harder because of learning about chemicals new elements and
chemical bonds. So really my feelings have changed but science is only getting harder.” This
response was coded as “negative” because the response indicated that even after having been
exposed to the curriculum, the student did not apply the principles of malleable intelligence.
The second research question sought to determine how students’ perceptions of their
academic abilities changed as the result of an attribution retraining curriculum. The researcher
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found that out of the 47 positive journal responses, 45 students attributed expectancies for future
success to factors under their control, such as: “challenge my brain more”, don’t give up and ask
for help”, “listen better and pay more attention”, and “unlock the inner smartness out of me.” Of
these 45 responses on the internal locus dimension, 18 directly (“…After reading all the articles I
learned that you can ‘grow’ your intelligence) or indirectly (“I have a different mindset than I
used to. Now I stand up to obstacles and keep trying.”) attributed this change to the curriculum.
Two students responses neither explicitly stated controllable factors nor directly referenced the
curriculum (“Now I believe I can achieve great things in science.”). These findings indicate that
62% of students’ perceptions of their academic abilities become more adaptive after exposure to
the curriculum, as they believed they had influence over future academic success.
Analysis of Interview Responses. The researcher analyzed the responses from the 20
participants and looked for patterns in the responses to Q2. The researcher found that out of the
20 respondents, 18 stated that they have changed the way they felt about their abilities and 11 of
the respondents directly or indirectly referenced one or more aspects of the attribution retraining
curriculum. For example, student 2-8 replied to Q2 and referred to one of the readings from the
curriculum: “I feel like if I put my mind to it I can achieve a lot more. Since I read that article,
‘How I Got Smart’ that really inspired me. Well, pretty much I know I am smart but I can be lazy
and I wanna change that. I feel like I have. And I ask a lot more questions now.” This student’s
response credits the autobiographical narrative, “How I Got Smart”, for his ideas about
approaching participation in school. According to the motivational dimensions of attributions,
the response also indicates internal, unstable, and controllable causes to academic outcomes,
which are more likely to encourage motivation on future tasks. The student acknowledges that
although he has confidence in his intellectual ability, he sometimes does not put forth effort. He
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also stated that he wants to change this pattern and has begun to control outcomes by asking
more questions.
Another respondent, student 7-9 stated, “Three weeks ago I didn’t think my grades could
go up that much, and now I don’t have any D’s, I have pure A’s, B’s, and C’s and now I have a
feeling I am doing better in school and also my family does, too. Yeah, the way animals, like,
how they were treated and how smart they are I started studying and reading 30 minutes per day
and now I am better.” This student referenced an experiment described in the article, “You Can
Grow Your Intelligence”. Caged animals that were placed with other animals were given toys
and showed more brain activity and development than animals kept alone in bare cages. This was
because these animals had to work to figure out how to use the toys and get along with the other
animals. This student applied the concept of brain stimulation to her own practice by reading
more each day and, as a result, noted a positive change.
In the article, “You Can Grow Your Intelligence” students learn how the brain is like a
muscle and that the more it is used, the stronger it becomes. Student 6-12 referred to this idea in
her response: “When you take in stuff, that your brain gets bigger or stronger. I have to keep
practicing and do all my work. Well, I thought that if I learned something I thought that I would
forget. Well, now I know I have to keep practicing to remember.” The student clearly indicated
that her perception about her intelligence—that she would forget something learned previously—
was positively influenced after reading the article about the malleability of intelligence. This
qualitative data reveals that the attribution retraining curriculum had a positive result on the
student and indicates that that student will adapt the way she exerts effort in academic settings in
the future.
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The variety of student journal and interview responses reveals that the attribution
retraining program yielded positive results for a majority of the respondents, as expected. The
researcher sought out to determine if the attribution retraining curriculum would affect students’
perceptions of their intelligence, which would ultimately help students increase their academic
achievement by increasing motivation. When students believe and understand that intelligence is
malleable and that effort on their part can increase academic achievement, their motivation to
persist in academic situations will also increase, as a result.
Conclusion
In summary, qualitative and quantitative methods were used to determine if an attribution
retraining curriculum would positively influence the perceptions of intelligence for 8
th
grade
English language arts students at Hudson Middle School. After three weeks of curriculum
implementation, a t-test analysis of the quantitative Likert-scale survey data indicated that the
curriculum was effective in increasing students’ perceptions about their intelligence. These
perceptions were tied to a belief of the malleability of the brain. Notable patterns emerged from
the qualitative data-- pre- and post-journal responses and student interviews—which also
revealed that the attribution retraining curriculum had a positive impact on students’ beliefs
about the malleability of the brain and beliefs about their intelligence.
The final chapter of this paper will discuss the findings, recommendations, and
implications of this study.

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Chapter Five: Discussion

In this section, discussion of the findings of the attribution retraining curriculum study
will be discussed first, followed by a discussion of the implications which address the issues
raised in this study. This section will also provide recommendations for stakeholders to further
implement attribution retraining curriculum, followed by a description of limitations and
delimitations, and culminate with concluding thoughts.
Findings
This study examined students’ attributions for subject matter difficulty both before and
after the span of the 18-day study. A survey containing Likert-scale items was used to measure
students’ perceptions about intelligence both before and after participating in the curriculum.
This Likert-scale survey garnered quantitative results that inform the results of the study. After
internal reliability was established using the Kaiser-Meyer-Olkin measure and Bartlett’s test of
sphericity, it was determined that there was a significant statistical difference between students’
pre-and post survey scores. An independent t-test of means revealed that the p-value of 0.006
was smaller than the 0.05 test value by 0.044, yielding a confidence interval of 95%. This data
indicates that the treatment was effective in increasing students’ perceptions of the malleability
of their intelligence. Students’ survey responses before curriculum implementation indicated that
some students agreed with survey statements asserting that “intelligence is something that you
can’t change very much” and disagreed that “you can learn new things, but you can’t really
change your intelligence”. Conversely, after curriculum implementation, survey responses
revealed a shift in perception about intelligence being fixed. These findings are congruent with
research that asserts that students are more likely to be academically motivated and persist when
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challenged and believe their intelligence is malleable (Peterson & Schreiber, 2006; Robertson,
2000).
Qualitative results from students’ journal responses supported this finding of a shift in the
belief of the malleability of intelligence. The completed qualitative data from 76 students was
used in this analysis, and 47 students indicated a positive change in their perception of their
intelligence after participating in the attribution retraining curriculum. A trend was established
among the 47 positive student journal responses. When responding to the post-curriculum
journal question, “Think about your most challenging subject in school. Do you feel the same or
different? Why or why not?” most responses indicated internal, unstable, and controllable causes
related to the dimensions of attributions. From the viewpoint of attributional research, these
dimensions are crucial for academic motivation (Schunk, Pintrich, and Meece, 2008).
Limitations and Delimitations

This study revealed data that can better inform educators about ways to increase
motivation, especially in adolescent-aged children, when motivation tends to wane. Nonetheless,
there are several limitations and delimitations that were revealed. Some of these are inherent due
to the study design and others revealed themselves through the course of the data collection.
As a qualitative study, which includes open-ended, narrative written responses, survey
responses, and interviews, the study was limited by the truthfulness of the student participants, as
well as the degree to which students can express themselves effectively verbally and in writing.
The study was also limited by the degree to which students interpret and understand the
questions posed in the survey, journal prompts, and interview. Another inherent limitation with
qualitative research presents itself during semi-structured interviews. There was the possibility
that the emotional state of the interviewee at the time of the interview could impact the
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responses. Furthermore, responses given by the interviewee may have been inaccurate or adapted
because of factors such as recall error, a self-serving bias, or their reaction to the interviewer
(Patton, 2002).
One delimitation was the number of participants expected to be involved in the study.
Initially, multiple classrooms from more than one school were set to participate in the study, with
the intention to conduct a comparative study using a control group. However, due to logistics and
time restraints, no control group was used, and the research was conducted by one teacher at one
school site. Therefore, due to the small sample available for the study, results may not be
generalizable beyond the specific population from which they were drawn. To further add to the
diminished sample size, one limitation was that the participating teacher inadvertently forgot to
administer the Likert survey to two of her class sections, eliminating the survey responses of
approximately 40 students from the study. In addition, since the research compared pre-journal
responses to post-journal responses, if a student was absent for either opportunity, their
responses were nullified and could not be used. This also decreased the sample size of
participants.
Another delimitation of the study was that the researcher was not present to observe all
18 days of curriculum implementation. Recommendations were made that the researcher at
minimum observes each class period at least once and to observe at least one full day. While the
researcher was able to fulfill these recommendations and also managed to observe each class on
at least three occasions, there is still no way to ascertain the fidelity with which the curriculum
was implemented on the days not observed.

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Implications and Recommendations for Practice

There are several implications from this study that inform practice. The ultimate goal of
this study was to better inform educational practitioners, especially those who work with middle
and high school students, about how to increase student effort and achievement. This
improvement could be made with an attribution retraining curriculum that emphasized the
principles of brain malleability. The hope is that the findings would be taken into consideration
when planning curriculum and professional development for school faculty. Although existing
research supports the positive impact attribution retraining curricula have on academic outcomes,
there was evidence for a need of increased awareness and implementation of such curricula,
especially in middle and high schools. Recommendations are being made to enhance secondary
school curriculum, and the presentation of these recommendations are made according those
groups who are most crucial for successful implementation: schools, teachers, students, and
teacher education programs.
Recommendations for Educational Policy Makers. First, beliefs about intelligence can
greatly influence students’ academic persistence and motivation, especially when presented with
challenging subject matter. When students are explicitly taught about the malleability of the
brain, they are more likely to view effort as a behavior within their control that can increase
academic outcomes. However, secondary school structures may impede student motivation, so it
is important to address these challenges first before making specific recommendations regarding
curriculum.
Traditional middle school structures can have an adverse effect on student motivation,
and even before introducing the attribution retraining curriculum to teachers and students,
educational policy makers must be aware of these structures in order to make positive changes.
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As previously discussed, factors such as large class sizes make it more difficult for teachers to
get to know their students as individuals and cultivate positive relationships. When teachers do
not come to know their students well, it is more difficult to teachers to grant students autonomy
and believe they are trustworthy. As a result, students have fewer opportunities for making their
own decisions and employing self-management strategies. These factors can contribute to low
self-efficacy and belief in one’s own ability (Eccles, et al., 1993). Emerging motivational
problems may also go unnoticed and continue to develop without established and sustained
teacher-student relationships. educational policy at the state level should enforce class-size
reduction so that classes are capped at a number that will reasonably allow teachers an
opportunity to get to know their students on an individual basis. Sustaining smaller class sizes
would require an increase in faculty. To the extent which it is possible, educational policy
makers would need to budget for the additional personnel.
Recommendations for Schools. It is recommended that school administration require
that during the first few weeks of school teachers are provided with suggestions and materials for
engaging students in team-building activities and icebreakers in order to build a sense of
community and to allow teachers to begin to learn about students’ interests. Understanding what
interests students and applying those interests to instruction is a key component of motivation
and will also provide a sound foundation when introducing an attribution retraining curriculum.
Middle school structures also often tend to emphasize competition and ability assessment
during a time of increased self-focus. In addition, the No Child Left Behind Act of 2001 brought
with it an emphasis on student evaluation through standardized testing. This emphasis could
further exacerbate the sometimes tenuous self-esteem of adolescents. As referenced in the
literature review, academic success of schools is often determined by achievement data. As a
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result, many students feel immense pressure to perform well and there is more at stake when a
student fails to do so. Students have become conditioned to place more value on their academic
grade then on the learning process itself. Further supporting this assertion are findings from the
study conducted by Moely et al., (1999) which indicated that students are less likely to attribute
academic achievement to effort when academic achievement is compared to that of other
students. In order to alleviate this pressure and increase student motivation, it is recommended
that school administrators make it compulsory to assess effort and growth in a course, as well as
achievement.
Also consistent with this concept were the qualitative responses from the initial journal
prompts in this study. Journal responses conveyed that many students felt negative feelings, such
as frustration and diminished self-efficacy, when describing why they felt challenged by their
most difficult class. It is recommended that school administration use a holistic evaluation
process, such as student portfolios, to measure growth in a variety of different areas. For
example, a portfolio might show a student’s writing abilities evolve from far below basic to
basic. While a ranking of basic is still below grade level, a portfolio would be a way to validate
how much improvement a student made towards mastery. When a student understands that his
effort and growth is valued as much, if not more, than achievement, he is more likely to persist
when faced with academic difficulties and welcome cognitive challenges (Mueller & Dweck,
1998).
When a school administration has established systems promoting class-size reduction and
portfolio assessments, they will begin to mitigate the traditional secondary schools structures that
might counteract the benefits of an attribution retraining curriculum. Once these systems are in
place, school administrators can then begin to communicate both the research and practical
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application of an attribution retraining curriculum. It is recommended that school administrators
first provide professional development that begins with allowing faculty to reflect on their own
beliefs about intelligence and mindsets and introduce the concepts of fixed (entity view)
mindsets and growth (incremental view) mindsets of intelligence (Dweck, 2005). These concepts
of intelligence could then be introduced as a way to provide a credible context for attribution
retraining curriculum. In addition, in cases where budget could allow, school administrators
could purchase interactive computer software that is available that teaches students about brain
malleability and teaches techniques to foster academic resiliency and persistence. It would be
essential for school administration to provide specific curriculum for continued used in the
classroom, such as the curriculum used in this study, and provide ongoing support for
implementation and follow-up.
It is also a recommendation that in order for students to better retain and apply the
concepts of the curriculum, the curriculum used in the study, as well as other similar curriculum,
should be provided in grades kindergarten through twelve, and in all content area classes. While
this study focused on a middle-school-aged demographic, it is recommended that the concepts of
malleability of intelligence and motivational dimensions be introduced as early as possible and
continued through high school. Elementary-aged children tend to exhibit more adaptive
attributions for effort, which can have a profound impact on academic success (Dweck &
Leggett, 1988; Schunk, Pintrich, & Meece, 2008). Therefore, it would be beneficial to explicitly
reinforce these attributions in elementary-aged children through effort-based feedback and grade-
level curriculum that highlights the malleability of intelligence. If elementary-aged students are
made aware of the link between effort and achievement and receive adaptive, effort-based
feedback, they will be more likely to apply this awareness in middle and high school, when
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motivational beliefs are adversely affected. It is also important for students to be made aware that
concepts of malleability transcend all content areas. For example, if a student does relatively well
in a history course, he may find it easier to adopt the understanding that effort yields improved
achievement. However, the student may find it harder to apply that same understanding to the
science or English class in which he struggles. Exposure to attribution retraining curriculum in
all content areas in grades kindergarten through grade twelve, will help students to apply the
adaptive attributions in a variety of contexts.
Recommendations for Teachers. Classroom educators are a vital part of the success of
curriculum implementation. Whether or not school administrators implement recommendations,
teachers usually have a certain degree of instructional freedom. As prescribed in this study, a
teacher should introduce the curriculum by first having students reflect on their own beliefs
about intelligence and openly discuss those beliefs. The teacher would then provide students with
grade-level appropriate text and media that introduces and explains the research behind brain
malleability and how effort exerted on academic tasks can increase achievement outcomes.
Providing students with adaptive language around attributions, encouraging the learning process
over academic outcomes, and fostering students’ internal locus of control as it relates to
academic outcomes, are key factors for successful curriculum implementation (Schunk, Pintrich,
& Meece, 2008).
Beyond the benefits of curriculum implementation, the effectiveness of the attribution
retraining curriculum could be reinforced by adaptive praise given to the student by the teacher
(Mueller & Dweck, 1998; Henderlong & Lepper, 2002; Schunk, Pintrich, & Meece, 2008). The
first recommendation regarding student praise is that praise is directed towards effort and
processes rather than outcomes. When teachers provide accurate feedback to students about
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academic failures, students are more likely to strive to make valid and precise attributions.
Furthermore, when a student’s strategy, process, or effort is criticized, students are more likely to
better deal with challenges, likely because strategy, process, and effort are conditional and can be
improved upon. Consequently, it is recommended that teachers strive to consistently praise
students for specific behaviors related to processes and navigating academic challenges. Some
examples might include, “You did a great job listening to all of the details of the story. I can tell
you concentrated very hard,” “It took hard work to solve that math problem, but you made a lot
of progress because of the effort you put in.” Strategic praise, paired with an attribution
retraining curriculum grounded in research, are recommended to increase student academic
outcomes (Kamins and Dweck, 1999).
As previously discussed, middle and high school students typical face a disconnect with
“stage-environment fit” as they are developmentally at odds with traditional secondary schools
structures (Eccles et al., 1993). It is important for students to feel as though there are sufficient
resources available to help them navigate the inevitable academic challenges they will face.
Students are often well aware of the high stakes of standardized testing, and they are also aware
of social and academic comparisons to peers. This awareness can have adverse effects on
students’ self-esteem and motivation (Eccles, et al., 1993). It is imperative the teachers are aware
of these challenges faced by their adolescent students and take strategic steps towards
overcoming these challenges. Teachers can begin to do this by providing students with accurate
and consistent academic feedback and providing students with both formative and summative
assessments to monitor academic growth. Teachers can guide students through the process of
setting academic goals and monitoring and evaluating their progress towards meeting their goals.
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This individualized feedback may help to mitigate the negative effects of academic comparison
to peers.
With teacher guidance, students may also begin to take personal accountability for their
learning by actively reading and discussing student-friendly research about the malleability of
intelligence. Teachers should give students the tools to ask questions and assimilate this
information with what they already know and make accommodations where necessary. In the
curriculum used in this study, students were required to read an article about intelligence. The
article was written at a level students could understand, and the teacher provided students with
guiding questions and other literacy strategies to make the article comprehendible. Another
useful strategy that teachers can employ is to require students to keep a metacognitive journal.
Students would use a metacognitive journal to plan, evaluate, and reflect on their learning. This
would help to steer academic outcomes towards an internal locus of control, which is more
adaptive for attributions. (Schunk, Pintrich, & Meece, 2008). Success of the attribution retraining
curriculum for students might be determined by metacognitive journal entries and academic
growth over time.
Recommendations for Teacher Education Programs. Academic institutions which
provide training for teacher education are pivotal in laying the foundation for successful
implementation of attribution retraining programs, especially in middle and high schools. It is
recommended that a course on motivational theory and practice be made a compulsory part of
the teacher education curriculum. Where this is not economically or programmatically feasible,
motivational theory and practice could be embedded in an already existing course. As noted in
the literature review, adolescent children believe that ability and effort are reciprocally related
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concepts, therefore, working hard is demonstrative of lacking intelligence because students who
are smart do not need to work hard (Folmer et al., 2008).
Similar to the structure of the attribution retraining curriculum used in this study, teacher
education programs would benefit its teachers by first giving them an opportunity to reflect and
discuss their own ideas about intelligence. Students in the program would then be given relevant
research and media support to contextualize the idea of malleability of intelligence and the need
for attribution retraining programs; this would include research regarding the developmental
factors that influence motivation and an opportunity to review attribution retraining research and
analyze and develop attribution retraining curriculum, as well. In addition, teacher education
programs should provide students with opportunities to create their own curriculum that focuses
on the malleability of intelligence. The goal of teacher education programs would be to graduate
prospective teachers with concrete and practical ways to foster adaptive attributions in students
of all ages. Therefore, it is also recommended that attribution training curriculum be adopted by
early childhood care centers and licensed child care providers who may not have attended a
teacher education program. The benefits reaped by teacher education graduates would certainly
have a profound impact on primary-aged children, as well.
Recommendations for Future Research

Utilizing both qualitative and quantitative methods, this study begins to address the gap
in the existing research and implementation of attribution retraining programs in schools.
However, the findings in this study reveal that there is a need for additional qualitative and
quantitative research around attribution retraining curriculum and implementation. Based on the
findings in the current study, recommendations for future research are discussed below. These
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recommendations are discussed, first, as they relate to the demographics of the participants, then
as they relate to the curriculum itself.
One recommendation is to repeat the study with more participants. Increasing the sample
size would increase the generalizability of the results. This could be done by including teachers
from different grade levels. Research indicates that there are developmental factors that may
influence attributions, so it would be interesting to see if these developmental differences were
reflected in the study results. If this is found to be the case—elementary-aged students exhibit
more adaptive perceptions about intelligence than secondary students-- perhaps curriculum could
be developed for elementary-aged students that may help to sustain these adaptive perceptions.
By increasing the sample size of the study, more factors would be revealed that could better
inform the development of subsequent attribution retraining curricula.
Increasing the sample size could also be achieved by including participants from a variety
of schools. Repeating the study using teachers from other schools would allow the curriculum to
be administered by educators from a variety of professional backgrounds and with varying years
of experience. Factors such as years of experience could be analyzed to determine if they play a
role in the effectiveness of the administration of the curriculum. This data may help to inform the
type of professional development required to ensure teachers feel efficacious about curriculum
implementation and that the curriculum is successful.
Future studies should also analyze the results from students in different content area
classes, as well. Based on the responses in this study, many students identified courses such as
math and history to be their most challenging. Therefore, it may be useful to disaggregate
attributions by content areas to determine if some content areas foster more or less adaptive
attributions for academic success. If it were determined that students in mathematics classes
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expressed the most maladaptive attributions, curriculum could be developed to specifically
improve student attributions in mathematics. Mathematics practitioners may need to undergo
more intensive professional development and training to meet the needs of these students.
This study aimed to provide an in-depth look into student perceptions of intelligence and
how these perceptions may be influenced by an attribution retraining curriculum. A longitudinal
study would shed further light onto how these perceptions may change over time. Research
should follow a group of students from elementary school, when their beliefs about intelligence
tend to be more adaptive, to secondary school when beliefs about intelligence are challenged by
developmental factors and school structures, and then on to college to see how students may
have internalized these perceptions (Perry & Penner, 1990). This would provide a much-needed
perspective on the correlation between beliefs about intelligence, motivation, attributions, and
academic success and how those beliefs might change over time.
As teachers are one of the key elements for successful attribution retraining programs,
future research should also include feedback from teachers regarding their own perceptions of
intelligence and how they may change over time. Teachers may easily project their own beliefs
about intelligence on to their students, so it would be helpful to capture these perceptions and
examine how they may impact classroom instruction. For example, if a teacher believes that
students identified as gifted or having special needs have inherent aptitudes for academic
success, those beliefs can have limiting effects on those students’ academic growth. Concomitant
with this entity view of intelligence, teachers may not be unwilling to implement attribution
retraining curriculum with fidelity. Research examining teachers’ perceptions and attributions
would be beneficial for both teachers and students.
ATTRIBUTION RETRAINING CURRICULUM

96
Future research with a population of secondary students should take some
recommendations into consideration regarding curriculum. One way to analyze the effectiveness
of the attribution retraining curriculum would to be to conduct an experimental study using a
control group. This group of students would have the same qualitative and quantitative measures
such as the survey and journal prompts, but would not participate in the curriculum. Responses
would be analyzed and compared to participating student groups that engaged in the curriculum.
Utilizing a control group in future studies would help to illuminate how impactful the attribution
retraining curriculum actually was. Finally, as with all research, in order to ensure the validity
and reliability of results, future studies are needed to expand and retest these findings.
Conclusion
This study revealed several findings that are consistent with existing research. As it
pertains to intelligence, middle school students tend to perceive intelligence to be a fixed trait
(Dweck, 2005). Where these perceptions exist, an inability to persist in the face of academic
setbacks also exists. In addition, students who exhibit an entity view of intelligence often view
academic failures to be internal, stable, and uncontrollable, which makes it difficult for them to
succeed in the same or similar academic tasks in the future (Schunk, Pintrich, & Meece, 2008).
The most significant finding in this study was that an attribution retraining curriculum could
positively shape students’ perceptions about their intelligence. The curriculum explicitly taught
students about the malleability of the brain and the power that sustained effort can have on
academic outcomes. As a result, student perceptions about their intelligence became more
adaptive. A vast majority of the students who participated in this study reported that they had an
improved perspective on the class they had originally deemed most difficult, and also
ATTRIBUTION RETRAINING CURRICULUM

97
subsequently believed that they could employ specific strategies to increase their capacity in the
class.
The findings from this study support the continued need to examine current attribution
retraining studies and continue research to better inform future practice. There is very little
research on attribution retraining programs specifically geared towards middle school students,
even thought developmentally this demographic is most at risk for diminished motivation and
more instances of academic failure, as a result (Eccles et al., 1993). There is even less research
on how the positive effects of attribution retraining programs manifest themselves over time. If
traditional middle school structures encourage social and academic competition, minimize
student-teacher relationships due, in part, to large class sizes, and emphasize ability and
assessment, then traditional college settings may do the same to an even higher degree. This
would be ground to argue that attribution retraining curriculum should be available in higher
education, as well.
The qualitative analysis used in this study provided a clearer picture of students’
perceptions of their intelligence and their attributions for undesirable academic outcomes. These
perceptions could not have been captured as effectively using solely quantitative measures. As
was revealed in the findings, it was the knowledge and understanding that the brain is like a
muscle and gets stronger the more it is used, that will encourage students to take control of their
learning and lead them on a path towards academic success.

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98
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Appendix A
Likert-scale Survey

Measuring Your Mindset

Read each section below and then circle the one number that shows how much you agree with it.
There are no right or wrong answers.

1.) You have a certain amount of intelligence, and you really can’t do much to change it.
Strongly Agree 1 Agree 2 Mostly Agree 3
Mostly Disagree 4 Disagree 5 Strongly Disagree 6

2.) Your intelligence is something that you can’t change very much.
Strongly Agree 1 Agree 2 Mostly Agree 3
Mostly Disagree 4 Disagree 5 Strongly Disagree 6

3.) You can learn new things, but you can’t really change your intelligence.
Strongly Agree 1 Agree 2 Mostly Agree 3
Mostly Disagree 4 Disagree 5 Strongly Disagree 6

4.) No matter who you are, you can change your intelligence a lot.
Strongly Agree 1 Agree 2 Mostly Agree 3
Mostly Disagree 4 Disagree 5 Strongly Disagree 6

5.) You can always greatly change how intelligent you are.
Strongly Agree 1 Agree 2 Mostly Agree 3
Mostly Disagree 4 Disagree 5 Strongly Disagree 6

6.) No matter how much intelligence you have, you can always change it quite a bit.
Strongly Agree 1 Agree 2 Mostly Agree 3
Mostly Disagree 4 Disagree 5 Strongly Disagree 6

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Appendix B
Samples of positive, negative, and static student responses from the post-curriculum journal
prompt.

Post Journal Question: Re-read your initial journal response from two weeks ago. Do you
feel the same or different now? Why or why not?

Positive Responses Static (No change) Responses
• “I feel different because really all I
had to do is just challenge my brain
more. By studying reading every
night. So, [now] history is getting
easier. I see a great change in my
last test and quizzes. I really just
had to unlock that inner smartness
out of me.” (Student 2-8)
• “I don’t feel the same because now
that I’ve been going over the lesson
much slower it’s starting to its in
my brain that way I don’t get mixed
up between the lessons and I've also
went on a tutorial website call
learning upgrade which really helps
me practice and understand in a fun
way.” (Student 2-13)
• “In the beginning of the experiment
• “I feel the same as before. My
teacher still makes algebra a
mission for me. She still talks and
writes too fast. Nothing has
changed as to how she teaches. Her
accent is still complex to
comprehend. My feelings have not
changed a bit whatsoever.” (Student
3-14)
• “I feel the same as I did two weeks
ago because I don’t understand
history. Another reason why I feel
the same as I did before is because
history isn’t interesting and when
you have a boring class early in the
morning, it makes you tired and
sleepy. But if I had an art class for
first period it would probably be
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I had trouble with math. It was
either because I was just dumb or
didn’t want to do anything. Later I
found out I didn’t want to do
anything, this was only happening
in my algebra class. After reading
all the articles I learned that you can
your intelligence so I started
completing all my missing
assignments. I was really motivated
to do my work because of this girl.”
(Student 6-2)
• “Now I feel good and I feel that
studying a lot the brain help me
think I can achieve anything and I
could never stop learning new
things. I feel that learning that the
brain can never stop growing it to
me things could learn and study
new and hard words so I could spell
them.” (Student 6-3)
• “When it came to thinking about
my most challenging subject it use
much better and I would be wide
awake.” (Student 2-9)
• “Algebra is still the hardest subject
for me. I still don’t understand
algebra. I try my best but algebra is
just too hard for me. The teacher
barely even explains how to do the
math problems. Maybe if the
teacher explains it more I would
understand algebra.” (Student 6-1)
• “Actually I feel the same about it.
My English class is the same it’s
not like “oh my English class is
hard”, or anything it’s just my hand
writing that messes me up. That is
the sole reason why my English
class is my worst class. That one
aspect affects my entire grade.”
(Student 6-4)
• “I don’t feel any different because I
still think history is very confusing.
I think I will always have trouble in
history. But I think I am getting a
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to be Algebra it use to be so
difficult. Now what I feel is
different because I am
understanding more and more. Now
that everything I went through
brainology changed now I can do
Algebra problems.” (Student 6-8)
• “Now that went through the
Brainology thing I kinda feel
different. I feel different because
now I know how to do the problems
in Algebra. All the reading and
talking did help me out a lot. So
now I can do the problems in
algebra and not only algebra but in
other subjects too.” (Student 6-15)
• “I don’t really feel the way I did 2
weeks ago. I feel that I have a
different mindset than I used to.
Now I stand up to obstacles and
keep trying. I feel more confident
now.” (Student 3-5)
• “I feel a little different English is
little better in it though and I am
also trying my hardest in my history
class to get good grades.” (Student
6-9)
• “I feel the same about my response
of two weeks ago because I believe
that the most difficult or
challenging subject in school is
science because science is a really
difficult subject, it has to do with
things around us and resources, and
because science has to do with your
body and the things that have to do
with your physical or body are
really hard and that’s why I feel the
same about my response.” (Student
3-1)
• “I feel the same because math is
still hard to understand. After all I
thought math was numbers but now
it comes up with weird signs and
letter. Aside from that I know math
will never be my strongest point but
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getting easier. It’s getting easier
because I’m getting more motivated
by my parents and making myself
study. Sense I knew that if I knew if
you work hard and study your brain
will grow and you might even be
intelligent. I been doing all my
work for this class. I think its cause
the study helped me a lot for
motivation.” (Student 3-6)
• “I feel different now. I am
beginning to tell apart the steps for
solving different problems. I
believe the text “mindset” helped
me accomplish this because I
realized all I had to do to memorize
the various steps was try harder and
put a name to the different
strategies. I have not, however,
changed my feelings toward
fractions. I still have difficulty with
them.” (Student 3-8)
• “I feel different now I understand
I do think I should at least try.
Mainly it’s because of my goals I
don’t do good in math. I want to be
an author or marine biologist and I
don’t think you need to master math
for it.” (Student 3-18)
• “I feel the same as before. My
teacher still makes algebra a
mission for me. She still talks and
writes too fast. Nothing has
changed as to how she teaches. Her
accent is still complex to
comprehend. My feelings have not
changed a bit whatsoever.” (Student
3-14)
• “I still feel the same because I’m
still having trouble in algebra. I get
stuck on the question that I don’t
even know what I’m doing. It is
difficult for me; it is still
challenging. It is like an obstacle
getting in my way but I’ll get
through it. So I still do feel the
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108
that even if I think its not important,
if I pay attention my intelligence
will grow. I now comprehend the
subject a little bit more. Two weeks
I didn’t understand history a lot, but
this week I took a test and I scored
36/40. I think its because I learned
about the brain and it helped me to
exercise my brain.” (Student 3-10)
• “After all those essay research
papers I think the reason history is
challenging is because I don’t really
put many effort. So that is the
reason I think history is very hard.
So all I have to do to understand
this subject more is study to make
my knowledge greater! And yes I
feel different now that I read about
gaining knowledge!” (Student 3-11)
• “Now that I know that the brain is
like a muscle. I am sure that I can
get better at math. I do not feel the
same because I know that if I study
same today, it is a challenge for
me.” (Student 4-7)
• “Well I still think Algebra is hard
and I still don’t understand it
because in Algebra I am a very
slow learner. Well I try to practice
at home but it’s hard for me to
understand it.” (Student 4-11)
• “I feel that math is still my most
challenging subject because it’s still
the same. Math hasn’t got any
easier or harder. It’s still hard to
understand and I think it will
always be that way.” (Student 4-21)
• “Yes I still feel that math is a hard
subject for me because I am not
good at remembering the steps.
Also the class is the same it’s
moving too fast and I don’t really
get a chance to understand the
work.” (Student 4-22)
• “I still feel the same, I did
everything that I said I was going to
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109
and try harder my brain would get
bigger and I would get smarter.”
(Student 3-15)
• “I still feel math is my greatest
challenge in school. There’s still a
lot of solving and a lot of new stuff.
I know that I have a fix mind set on
math. Nut I can also work harder
and study more and become a
growth mindset. But for the
moment math is the most
challenging subject.” (Student 3-19)
• “I still believe that algebra is my
most difficult subject. But now I
have more courage to try harder.
Also by breaking down the
problem, our brain is like a muscle,
if you want to try never give up no
matter how hard the problem is. In
these two weeks that passed I
learned knowledge is power, you
have the power to learn. If you want
your brain to increase all have to do
do but I think it just the teacher. He
forgets to collect cornell notes,
homework, and more.” (Student 4-
25)
• “I feel the same because history is
still my most difficult class that I
have now. History is the most
difficult because you need to know
about what happen in the world
almost from beginning. History is
hard because I don’t like to know
what happen before.” (Student 7-
12)

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110
is believe that you can pass.”
(Student 3-21)
• “The information I got from the
lesson was very useful. I never
thought it would be that hard but its
better to try then not to try at all.
My grade for math went up 5% not
much but a good start for 2 weeks.”
(Student 4-10)
• “I don’t feel the same way because
no I understand my math teacher.
Now I stay with her after school
and she teaches me the things I
didn’t understand. I think that we
can communicate now. Now I have
a B+ in her class. I want to be her
best student. “ (Student 7-9)
Negative • “For me science has only gotten
harder. Harder because of learning
about chemicals new elements and
chemical bonds. So really my
feelings have changed but science is
only getting harder.” (Student 3-22)
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Appendix C
Random Sampling Interview Questions

Period 2

Student: 2-8

1. How did you feel about the curriculum?
Kinda surprised because all my years in school I was never really involved in something
like that. It was new for me to learn. Well happy to learn more of the brain and how it
works. I was happy to learn and study about that.

2. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
I feel like if I pot my mind to it I can achieve a lot more. Since I read that article “How I
Got Smart” that really inspired me. Well, pretty much I know I am smart but I can be lazy
and I wanna change that. I feel like I have. And I ask a lot more questions now.

Period 2

Student: 2-1

3. How did you feel about the curriculum?
I felt actually good because I learned new stuff that I didn’t know before and I now that I
do I am actually doing better in school. My challenge was Algebra and now I am doing
better.

4. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
I’ve started to do my missing assignments. I got motivated and I just started doing my
homework. My mom was actually the one who motivated me and my boyfriend. My
mom wants me to go to college and I am planning to go.

Period 2

Student: 2-12

5. How did you feel about the curriculum?
I don’t really know. I was just wondering what we were gonna do.

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6. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
I changed because before I would study and now when I study I put more attention so I
won’t fail. That article “How I Got Smart” showed me how I can get smarter easier.

Period 2

Student: 2-4

7. How did you feel about the curriculum?
Maybe it was a little overwhelming because it was a little hard. When we did the um…on
the brain…I thought that was hard.

8. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
I think it has. I think it helped me learn more. Study more.

Period 3

Student: 3-11

9. How did you feel about the curriculum?
Well, it made me like think that there’s no smart or dumb and if you think you don’t
know something you can gain more knowledge by studying.

10. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
Well, now I have to study more and to focus on a subject that I need help on. I didn’t
know that you could gain something if you study hard so now since I know I will plan to
do those things so I can get better grades.

Period 3

Student: 3-9

11. How did you feel about the curriculum?
Good. Um… it made me it let me learn more about how the brain functions and how does
it grow like a muscle.

12. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
ATTRIBUTION RETRAINING CURRICULUM

113
I feel like I should learn more, study harder, if I wanna achieve what I wanna be later in
the future. Cause I know if I don’t pump up my brain later on I won’t have a good future
in life.

Period 3

Student: 3-19

13. How did you feel about the curriculum?
Um, I actually really learned from this um I learned lie that we can make our brain
stronger if we study and there’s no such thing as dumb only if you choose to be dumb.
And it helped me see that I can try harder on my subjects not lack.

14. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
I think I did change because I am not a fixed mindset no more I am more of a growth
mindset. So I wanna study in a laboratory and take on challenges so I can get better and
be more of a growth mindset.

Period 3

Student: 3-3

15. How did you feel about the curriculum?
Umm… it made me wanna study more. So my brain can be stronger and like…

16. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
They’ve changed because like I know that I can do it if I try. We read “How I Got
Smart”. Even though you are not as smart as you wanna be you can still be as smart as
you can.

Period 4

Student: 4-11

17. How did you feel about the curriculum?
I felt that if you study more you can become something amazing,. Very smart, wise.. And
um that motivating. If your parents motivate you, you can become something very big,
very important.

ATTRIBUTION RETRAINING CURRICULUM

114
18. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
I think I changed a little bit. I try to read books instead of texting. Trying to be into
school instead of just playing around. I try to focus.

Period 4

Student: 4-8

19. How did you feel about the curriculum?
I felt like interested to learn about it. It was like, motivated… Like it makes me wanna
get up there like a little higher, like grades.

20. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
Umm.. I still need a little bit of help I Algebra. I feel I can do better, like, it will take me a
little time though. My future made me change the way I feel about my abilities.

Period 4

Student: 4-20

21. How did you feel about the curriculum?
I felt more motivation. Umm.. like it made be feel like better about myself.

22. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
I have changed about my abilities because I learned that you could be dumb or you could
be smart. You pick what you want to be. To have a better future…to graduate middle
school. The story, “How I Got Smart” shows that if you really want to do something you
can achieve it.

Period 4

Student: 4-21

23. How did you feel about the curriculum?
It was good information. The motivation stuff…

24. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
They haven’t changed because I think I am doing the best that I can. I have good grades.
ATTRIBUTION RETRAINING CURRICULUM

115
Period 6

Student: 6-1

25. How did you feel about the curriculum?

Umm…it was like…I didn’t know, like your brain could grow like over time. It’s… well
I think that you are smart but sometimes some people act dumb. Well I am not acting
dumb but I am not smart like the other kids.

26. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
I still can’t do good in math. I try and I try but I just can’t do good. I pay attention but it’s
just too hard. I understand the other subjects, but sometimes it’s hard. But math is the
hardest subject for me.

Period 6

Student: 6-3

27. How did you feel about the curriculum?

Well I felt good because it made me thin k about I could never stop learning. I was
sharing in my journal that English was my hardest subject and I didn’t spell really good
and was like, my brain could grow, there was no limit for my brain to grow so I could
always keep on learning new things and I could use the information that you gave me and
I could think about it and study really hard and exercise my brain and do better that the
subjects that are more challenging for me.

28. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
Like I said I changed because I was thinking about you are never too old to learn and you
can always; learn new things so I decided to give it a try and learn how to spell new
words so it madder me like more motivated to try to learn new things. It was that I didn’t
really put that much effort into it, and since we started talking about our future I started
thinking about it so I thought I should start thinking more about working hard and
changing my grades so it would be good.
Period 6

Student: 6-8

29. How did you feel about the curriculum?
Um, I felt good. That we learned about so many about intelligence. And brainology. I felt
good cause it talks about every time you study more your brain gets more stronger.

ATTRIBUTION RETRAINING CURRICULUM

116

30. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
It changed as little because before I really didn’t know nothing about it.. about what we
have talked. And now I do…I have control over school because before I didn’t feel it was
in my control. Like I used to not listen and to play around too much but now I don’t.
Before they used to tell me what to. Explain what they used to say and I didn’t know and
now I do listen and I do explain what they say.

Period 6

Student: 6-12

31. How did you feel about the curriculum?

Surprised cause um I thought it was teachers and stuff that’s why I couldn’t learn. But I
found out it was me cause I thought it was my teachers that didn’t teach you well that
went too fast but it was really me cause I didn’t have practice and I needed like to put
effort into it.

32. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
When you take in stuff, that your brain gets bigger or stronger. I have to keep practicing
and do all my work. Well I thought that if I learned something I thought that I would
forget it, well now I know I have to keep practicing to remember.

Period 7

Student: 7-12

33. How did you feel about the curriculum?
Um, good that we need to know that to be somebody in the world.

34. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
I have like Ms. Freeland my math teacher I do my work more now because I started, like,
to like more math because I think the math is the more important material that we need to
know. The brain paper showed me that you can still learn, um, like more everyday.

ATTRIBUTION RETRAINING CURRICULUM

117
Period 7

Student: 7-2

35. How did you feel about the curriculum?
Umm, I learned something new. I learned about the brain and how it works. I learned
how you get smarter. I felt good because I can know, like, how it works.

36. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
I changed because I try harder and I try my best. Cause, um, I thought about my grades
and I thought that I have to improve them. I learned how to work better, concentrate
better. I just thought about that I have to improve my grades because I thought about my
future. I just thought about it.

Period 7

Student: 7-11

37. How did you feel about the curriculum?
I learned about like how babies can learn little by little how people explaining them, like,
what to say. I felt like I never knew like how little people like babies learn how to talk
little by little and that they know what they say but they don’t know what it means.

38. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
I feel the same but I know more stuff from what the teacher taught us. I tell that teacher
like, I don’t get it, and she tells me the answer and then she helps me for the other one. So
I can get more examples. That my brain works more when I read and when you read
more it makes you smarter, like, makes you do the work.

Period 7

Student: 7-9

39. How did you feel about the curriculum?
I think it really did work because for my math class I didn’t understand the language that
my teacher was talking until she told me to stay after class and I said okay and no I kind
of understand her better. The curriculum also taught me lots valuable stuff about the brain
like how the brain grows, it’s cell and stuff and how it works for your body.

ATTRIBUTION RETRAINING CURRICULUM

118
40. How have you or have you not changed the way you feel about your abilities? Explain
why your feelings about your abilities have or have not changed.
Three weeks ago I didn’t think my grades could go up that that much, and now I don’t
have any D’s, I have pure A, B, and C’ and now I have a feeling I am doing better in
school and also my family does. Yeah the way animals like how they were treated and
how smart they are I started studying and reading 30 min per day, and now I am better.

Abstract (if available)

Abstract Qualitative and quantitative measures were used with 105 middle-school English students in an effort to better inform educators on ways to increase academic motivation at a time when motivation tends to wane. The inquiry sought to determine if the students’ perceptions about their intelligence would be positively influenced by an attribution retraining curriculum administered over the course of 18 days. Analyses of student journal responses, survey responses, and randomly administered interviews are discussed as they relate to the motivational dimensions of attributions: locus dimension, stability dimension, and causality dimension. Quantitative results support previous findings regarding the benefits of attribution retraining programs on student motivation. Qualitative data revealed that students’ beliefs about the malleability of intelligence were increased after students engaged in the attribution retraining curriculum. Following a deductive analysis, patterns that emerged from journal responses and randomly administered interviews showed that those students who indicated the most positive change from the curriculum also showed the most adaptive characteristics on the attribution dimension: internal, unstable, and controllable. Implications of the study include establishing more adaptive practices in secondary school structures regarding class-size and evaluation, attribution retraining professional development, and compulsory motivation research and application in teacher education programs.

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Asset Metadata

Creator Smith, Marini Hamilton (author)

Core Title Middle school students' perceptions of academic abilities as a result of an attribution retraining curriculum

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Publication Date 03/01/2013

Defense Date 12/22/2012

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

Tag attribution,curriculum,intelligence,Motivation,OAI-PMH Harvest,retraining

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Hirabayashi, Kimberly (committee chair), Martinez, Brandon (committee member), Seli, Helena (committee member)

Creator Email marini.hamilton@gmail.com,mghamilt@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-222703

Unique identifier UC11293924

Identifier usctheses-c3-222703 (legacy record id)

Legacy Identifier etd-SmithMarin-1454.pdf

Dmrecord 222703

Document Type Dissertation

Rights Smith, Marini Hamilton

Type texts

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

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

Repository Name University of Southern California Digital Library

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