Close
About
FAQ
Home
Collections
Login
USC Login
Register
0
Selected
Invert selection
Deselect all
Deselect all
Click here to refresh results
Click here to refresh results
USC
/
Digital Library
/
University of Southern California Dissertations and Theses
/
Motivational differences of high-ability high-performing (HAHP) and high-ability low-performing (HALP) high school students
(USC Thesis Other)
Motivational differences of high-ability high-performing (HAHP) and high-ability low-performing (HALP) high school students
PDF
Download
Share
Open document
Flip pages
Contact Us
Contact Us
Copy asset link
Request this asset
Transcript (if available)
Content
MOTIVATIONAL DIFFERENCES OF HIGH-ABILITY HIGH-PERFORMING
(HAHP) AND HIGH-ABILITY LOW-PERFORMING (HALP) HIGH SCHOOL
STUDENTS
by
Cynthia N. Wong
____________________________________________________________________
A Dissertation Presented to the
FACULTY OF THE ROSSIER SCHOOL OF EDUCATION
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree of
DOCTOR OF EDUCATION
August 2008
Copyright 2008 Cynthia Wong
ii
ACKNOWLEDGMENTS
Sincere thanks to my dissertation chairman, Dr. Myron Dembo, and my
dissertation committee members, Dr. Tim Stowe and Dr. Charles Espalin. Your
insights and expertise were invaluable. Thank you all for supporting my efforts in
completing this study. Thank you also to Dr. Gaia Rubera and Dr. Helena Seli for
your undivided support and attention.
iii
TABLE OF CONTENTS
ACKNOWLEDGEMENTS ii
LIST OF TABLES vi
LIST OF FIGURES vii
ABSTRACT viii
CHAPTER 1: INTRODUCTION 1
Overview 1
Importance of the Study 7
Social Factors 9
School Factors 9
Family Factors 10
Individual factors 11
Purpose of the Study 13
Research Questions 14
Definition of Terms 14
CHAPTER 2: REVIEW OF THE LITERATURE 16
Family Orientation and Academic Achievement 16
Summary of Findings on Family Orientation and
Academic Achievement 18
Goal Orientation Theory and Academic Achievement 18
Summary of Goal Orientation Theory and Academic Achievement 27
Task Value Theory and Academic Achievement 28
Summary of Task Value Theory and Academic Achievement 31
Gaps and Key Questions Unanswered by the Literature Review 31
Research Questions 31
Hypotheses 32
CHAPTER 3: METHODS 34
Participants and Setting 34
Inclusion/Exclusion Criteria 38
Instruments 39
Academic Ability 39
Performance 40
Family Orientation 40
Mastery and Performance Goal Orientation 40
Task Value 41
iv
Demographic Data 42
Reliability 42
Survey Instrument 43
Procedures 44
Data Analysis 46
CHAPTER 4: RESULTS 48
Quantitative Findings 48
Intercorrelations 48
Descriptive statistics 50
Analysis of variance 58
Research Question 1 52
Research Question 2 53
Research Question 3 55
Multiple Regression 55
Differences between HALP and HALP students in
English/language arts 57
Differences between HAHP and HALP students in math 58
Analysis of gender differences 60
Analysis of differences in ethnicity 61
Summary of Research Findings 63
CHAPTER 5: DISCUSSION 69
Overview and Intent of the Study 69
Research Questions 72
Family Orientation Findings 73
Goal Orientation Findings 75
Task Value Findings 79
Ethnicity Findings 81
HALP Student Conclusions 83
Limitations of the Study 86
Next Steps for Future Research 87
Implications for Policy and Practice: How to assist HALP students 88
REFERENCES 91
APPENDICES 95
A. Classroom Motivation Survey 95
B. Site Permission Letter 103
C. Cover Letter From Principal 104
D. Informed Consent for Non-Medical Research
(Parental Permission) 105
E. Informed Consent for Non-Medical Research
v
(For youth Ages 12-17) 109
F. Recruitment Speech 113
vi
LIST OF TABLES
Table 1: Percentages of Students Achieving at Proficient or
Advanced Levels Based on CST Scores in 2004-2005 3
Table 2: HALP/HAHP Participants by Gender, Grade Level
and Ethnicity for English/language arts and Math 37
Table 3: Means and Standard Deviations of Average Grade
for HALP/HAHP Students in English/language arts and Math 39
Table 4: Means, Standard Deviations, and Pearson Product Correlations for
Measured Variables 49
Table 5a: Beta weights, t-values and p-values of HAHP students
in English/language arts 56
Table 5b: Beta weights, t-values and p-values of HALP students
in English/language arts 56
Table 6: Summary of Statistical Significance Across Variable and Subject 67
vii
LIST OF FIGURES
Figure 1: Ability and Performance Groupings 35
Figure 2: Differences in Average Grade Between HAHP and HALP 51
Students in English/language arts and Math
Figure 3: Mean differences Between HAHP and HALP Students 58
in English/language arts
Figure 4: Mean differences Between HAHP and HALP Students in Math 60
Figure 5: Mean Differences by Gender 61
Figure 6: Mean Differences by Ethnicity 63
viii
ABSTRACT
Explaining why some high-ability students do well in school while others do
poorly remains one of the most important and controversial problems in education
(Hebert, 1998). Since students with high academic abilities are often assumed to
naturally do well in school, it seems paradoxical when high-ability students do not
perform well at school (Payne, 2006). The purpose of this study is to compare the
motivational differences of high-ability high-performing (HAHP) students and high-
ability low-performing (HALP) students in relation to family orientation, goal
orientation and task value. The primary research question for this study is “Which
combinations of motivational factors differentiate high-ability high-performing
(HAHP) and high-ability low-performing (HALP) students?”
Using a 28-item questionnaire, HALP and HAHP students in English/language
arts and math classes were surveyed using the following five subscales: family
orientation, goal orientation (mastery, performance-approach, performance-avoid), and
task value. Significant differences were found between HAHP and HALP students in
terms of family orientation, mastery goal orientations, performance-approach goal
orientation, and performance-avoid goal orientations. Task value was not found to be
statistically significant among HAHP or HALP students. In terms of ethnicity,
differences in means were found in the family orientation, mastery goal orientation, and
performance-approach goal orientation subscales. No significant differences were
found on the performance-avoid and task value subscales.
ix
______________________________________________________________________
Keywords: achievement; motivation; family orientation; mastery goal orientation;
performance goal orientation; task value; high school
1
CHAPTER 1
INTRODUCTION
Overview
In 2001, the federal government created the No Child Left Behind (NCLB) Act
as a comprehensive educational reform designed to close achievement gaps in public
schools. The four principles of NCLB include greater accountability of K-12 educators
and administrators, more flexibility and local control, expanded options for parents, and
an emphasis on teaching methods that have been proven to work. The NCLB act
redefines the federal government’s role in K-12 education with the goal of improving
the academic achievement of disadvantaged students.
Two measures of student achievement are grade point averages and
standardized test scores. Through the NCLB act, statewide assessments have been
created to measure what children learn in reading and math in grades 3-8. Student
progress and achievement are measured through the standardized tests that are
administered to every child annually. The results of the annual assessments are then
made available to the public in annual report cards on school performance and on
statewide progress. The three major components of California’s Accountability
Progress Reporting system include an Academic Performance Index (API) report,
which shows how much a school is improving from year to year, an Adequate Yearly
Progress (AYP) report, which shows how well schools and districts are meeting
common standards of academic progress, and a Program Improvement (PI) report
2
which identifies schools that fail to meet their AYP goals for two consecutive years.
These reports are aimed at increasing accountability on a school and district level.
In California, the Standardized Testing and Reporting (STAR) program assesses
students in grades 2 through 11 in various subject areas. The two primary measures
included in the STAR program are the California Standards Test (CST) and a norm-
referenced test called the California Achievement Test, Sixth Edition (CAT/6). Both
assessments provide information on how well students are doing in relation to the state
content standards. On the CST, individuals are ranked according to five performance
levels: Advanced (exceeds state standards), Proficient (meets state standards), Basic
(approaching state standards), Below Basic (below state standards) and Far Below
Basic (well below state standards). Only students who score at the Advanced or
Proficient levels are considered to meet state standards in a particular content area. On
the CAT/6, scores are reported as the percentage of students scoring at or above the 50
th
percentile (the national average). The results of these assessments are compared at
district and state levels and include performance data disaggregated according to race,
gender, and other sub-grouping.
The high school chosen for this study has consistently been recognized as high
performing school based on the standards set by NCLB. The high school has received
several distinguished awards, one of which is the title of a California Distinguished
School. It has received this prestigious honor four times, most recently in 2005. The
high school was also named a national Excellence in Education school in 1984. In
terms of standards-based test scores, the high school consistently exceeds state norms.
3
For the past several years, the high school has scored between 750 and 800 on the
Academic Performance Index (API) on a scale of 200 to 1000. In 2006, the high school
had an API score of 815. The school has also met the Adequate Yearly Progress (APY)
requirements each year since 2003. When compared to the district and state level, the
high school has a higher percentage of students who scored in the Proficient and
Advanced ranges for English/language arts. However, the high school had a lower
percentage of students who scored in the Proficient and Advanced ranges in math when
compared to the state level. Table 1 shows the percentage of students who achieved
Proficient and Advanced levels, signifying that they have met or exceeded the state
standards, on the 2004-2005 CSTs as compared to the district and state averages.
Table 1
Percentage of Students Achieving at Proficient or Advanced Levels Based on CST
Scores in 2004-2005
High School District State
Subject
2003 2004 2005
2003 2004 2005
2003 2004 2005
English-
Language
Arts
56 58 60
54 55 59
35 36 40
Math 41 33 40
50 49 52
35 34 38
Despite the overall achievement of students at the high school, one problem that
has captured the attention of teachers and administrators is low achievement rates
among students who exhibit high potential for success. This distinct group of
underachievers have been described in the literature as High-Ability-Low-Performance
(HALP) students (Payne, 2006), gifted under-achievers or academically-talented low-
achievers. One common attribute that characterizes HALP students are that they
4
typically score very high on standardized achievement tests, yet they exhibit low
performance in class by earning poor grades and/or low grade point averages or
exhibiting low performance in the classroom (Hooever-Schultz, 2005).
The first step in exploring the factors influencing underachievement of high-
ability students is to define the concepts of ability and underachievement. One
difficulty is that there is little consensus among the literature about how to best define
underachievement, particularly among academically talented students (Ford, 1997).
Few studies agree on the same definition of underachievement (Ford, 1997), and some
educators even doubt the legitimacy of high-ability underachievement as an academic
behavior (Hooever-Schultz, 2005). In a comprehensive examination of literature,
Dowdall and Colangelo (1982) cited at least 15 different definitions of
underachievement, most of which included some sort of comparison between ability
and achievement (as cited in Schultz, 2002a). Currently, there is no comprehensive
protocol to discriminate between categories or labels of achievers, over-achievers, and
underachievers (Schultz, 2002a). This lack of consistency leads to varying definitions
of ability and underachievement. For example, the criteria used to identify high-ability
students vary from state to state and district to district (Hooever-Schultz, 2005). Some
districts rely on teacher recommendations, intelligence tests, or achievement scores to
identify high-ability students (Ford, 1997). Other districts have different criteria for
classifying high-ability students, such as a specific IQ or ability test scores (Neumeister
& Hebert, 2003). The lack of consistency in the definitions and criteria often lead to
varying standards and practices regarding high-ability low-performance students.
5
The measurement of achievement and underachievement is also imperfect. For
example, schools may use a combination of achievement/aptitude test scores, grade
point averages, or drop out rates to measure underachievement (Ford, 1997). One major
drawback in measurement is that standardized tests may not directly reflect the actual
school experience, and classroom grades may be unreliable and subjective (Hooever-
Schultz, 2005). Measurement errors also decrease the reliability of standardized test
scores. Indeed, there is great variance in both the definition and measurement of high
achievement and underachievement.
Despite the general lack of agreement regarding the definitions and
measurement of these two constructs, educators generally agree that the discrepancy
between ability and performance is one of the underlying themes of underachievement
(Ford, 1997). In the most general sense, underachievement is defined as: a) a
discrepancy between potential achievement and actual achievement b) discrepancy
between predicted achievement and actual achievement c) a failure of develop or use
potential (Dowdall & Colangelo, 1982 as cited in Hoover-Schultz, 2005). For the
purposes of this study, I have chosen the following definition of gifted underachievers:
Underachievers are students who exhibit a severe discrepancy between expected
achievement (as measured by standardized achievement test scores or cognitive
or intellectual ability assessments) and actual achievement (as measured by
class grades and teacher evaluations). To be classified as an underachiever, the
discrepancy between expected and actual achievement must not be the direct
result of a diagnosed learning disability. High-ability underachievers are
6
underachievers who exhibit superior scores on measures of expected
achievement (i.e. standardized achievement test scores or cognitive or
intellectual ability measurements) (Reis & McCoach, 2000, p.157).
In summary, accountability reforms, such as the NCLB Act are designed to
decrease the achievement gaps in public education. The high school used in this study
was recognized as high performing school based on the standards set by NCLB, and it
exceeds state norms on statewide standardized tests. However, one problem that has
captured the attention of teachers and administrators at high school is low achievement
rates among students who exhibit high potential for success. Currently, there is a lack
of consistency in the definitions and measurement of giftedness and underachievement.
Nonetheless, the general consensus is that underachievement is any discrepancy
between academic potential and academic achievement.
Payne (2006) conducted one study that has compared the motivational profiles
of high-ability high-performing (HAHP) and high-ability low-performing (HALP)
students. The study used middle school students from an urban school in Southern
California. Payne (2006) focused on four constructs including: (1) goal orientation
beliefs, (2) expectancy-value beliefs, (3) attribution beliefs, and (4) teacher reports of
academic behavior. Payne (2006) used the following nine subscales: goal orientation
(mastery, performance-approach, performance avoid), expectancy-value (expectancy
for success, perceptions of competence, task value), and attribution (controllability,
stability, globality) to measure differences between the two high-ability groups. He
found that significant differences occurred between High-Ability-Low-Performing
7
(HALP) and High-Ability-High-Performing (HAHP) students in the areas of mastery
goal orientation, expectancy-for-success, perceptions-of-competence, controllability
beliefs, citizenship behaviors and work habits.
This study is an extension of Payne's (2006) study comparing high-ability high-
performing (HALP) students and high-ability low-performing (HAHP) students.
However, one key difference is that this study involves high school students rather than
middle school students. In addition, this study investigates the family orientation
variable, which was not included in Payne's (2006) study. In terms of differences in
variables, this study focuses on goal orientation and task value variables and excludes
the expectancy for success, perceptions of competence, controllability beliefs,
citizenship behaviors and work habits variables. An additional difference is that this
study analyzes ability and performance in both English/language arts and math, while
Payne's (2006) study fails to differentiate between academic subjects. A final difference
unique to this study is that this paper includes an analysis of both gender and ethnicity.
Importance of the Study
In 1995, 20-50 percent of high ability students in the U.S. were reported to
underachieve academically (Ford, Alber & Heward, 1998). Explaining why some high-
ability students do well in school while others do poorly remains one of the most
important and controversial problems in education (Hebert, 1998). With the launch of
Sputnik I in 1957, the United States focused more attention on high ability students and
increased federal funding for education (Schultz, 2002a). While early research on
underachievement among high ability students was essentially diagnostic in nature,
8
research foci were very wide and varied (Schultz, 2002a). Some of the earlier research
on underachievement of high-ability students hinted at connections in fields such as
motivation, frustration, family relations, home background, mental health and
personality differences (Schultz, 2002a), but remained somewhat mysterious and
enigmatic in nature.
Since high academic ability is a typically viewed as a strong predictor of
academic success, it seems paradoxical when high-ability students do not perform well
at school. Students with high academic abilities are often assumed to naturally do well
in school. Before standardized measures began emphasizing differences between ability
and actual achievement, gifted underachievers were basically able to function in normal
classroom routines without drawing much attention to themselves (Schultz, 2002a). As
a result, high-ability low-performing students are overlooked as a group because they
do not share the same features as low-ability low-achieving students. Although it seems
that high-achieving students are a homogenous group, there is substantial variation in
reasons for achieving. High-ability students may generally achieve at high levels, but
their reasons for achieving vary greatly (Ablard, 2002). Clearly, there are substantial
within-group differences among students who are identified as high-achievers.
The causes of underachievement among high-ability students are complex.
Some researchers have begun to identify patterns of underachievement that develop in
elementary school and continue into upper grades (Hooever-Schultz, 2005).
Researchers have identified several factors influencing underachievement, which fall
9
under the following main categories: social factors, school factors, family factors, and
personal factors. Each of these variables will be discussed in detail below:
Social factors
The main social factors that have been linked to underachievement and drop-out
rates in high-ability low-performing (HALP) students are peer group influences, career
goals and after-school employment (Neumeister & Hebert, 2003). Peer influence was
found to conflict with motivation and performance when students’ peer groups held
“anti-academic” norms (Hoekman, McCormick & Gross, 1999). In other words, high-
performing students were often torn between retaining social status with their
underachieving peer groups and performing well academically. In contrast, a network
of high-achieving friends was characteristic of high-ability high-performance students.
Another social factor influencing underachievement and drop out rates in HALP
students is their educational aspirations, career goals and post-high school plans.
Renzulli and Park (2002) found that many high-ability students left school because they
got a job or got pregnant. Dropout rates were found to be significantly related to
students’ educational aspirations and pregnancy or child rearing. Several social factors
are linked to underachievement. The most prevalent social factors related to
underachievement are peer influences and educational aspirations and career goals.
School factors
Numerous school-related factors also influence the underachievement of high
ability students. The primary school factors that have been studied are school
curriculum and environment (Neumeister & Hebert, 2003) and classroom standards and
10
practices. For example, in a study of African American high-ability achievers and
underachievers, the underachieving students reported they had less positive student-
teacher relations, b) they lacked adequate time to understand the material, c) they had a
less supportive classroom climate, and d) they reported being unmotivated or
disinterested in school (Ford, 1997). Student-teacher relations have also been found to
have an effect on HALP students. In short, school-related factors such as school climate
and practices as well as student-teacher relations were found to influence
underachievement in high-ability students.
Family Factors
Contemporary researchers have confirmed that high-ability underachieving
students are different from high-achieving high-ability students in personal and family
relationships. Family-related variables associated with school performance are family
background variables such as parents’ highest level of education (Renzulli & Park,
2002; Deslandes, Royer, Turcotte & Bertrand, 1997), family structure, parental
education style and parental involvement in school. Parents’ levels of education and
socioeconomic level (Renzulli & Park, 2002) have been linked to low achievement and
drop out rates of high-ability students. Low levels of education and occupational status
of parents are significantly related to students’ decision to drop out of school (Renzulli
& Park, 2002). In addition, parents who place little value on education, who have low
expectations for their child’s success, whose family has a history of dropouts, had low
educational achievement, or had even dropped out themselves, were also related to
HALP students’ dropout behavior. While most of the above variables focus on external
11
family influences, such as socioeconomic levels (SES) and parents’ education, this
study focuses on the internal family influences of achievement with regards to
students’ sense of obligation as a function of their family orientations.
One variable that is unique to the multicultural population at the high school is
family orientation. Since a majority of the students at the high school come from Asian
or Latino family backgrounds, family orientation and family obligations play a major
role in students’ goal orientations and achievement. Urdan (2004) found that immigrant
students, most from Asian and Latin American cultures had a stronger sense of
obligation to care for family members in the future than did native-born students. Urdan
(2004) proposed that students with stronger family orientations might have family
members in mind when adopting performance goals. Furthermore, Urdan (2004)
hypothesized that the effects of performance goals on achievement and avoidance
behaviors will differ for students high and low in family orientation.
Individual Factors
In a landmark longitudinal study by Lewis Terman of 1,500 high-ability
students, Terman found that the underachieving group was characterized by a) low
levels of self-confidence, and b) inability to persevere, c) a lack of goals, and d)
feelings of inferiority (Hoover-Schultz, 2005). These internal processes center on
students’ perceptions, attitudes and practices. Low levels of self-confidence and
feelings of inferiority are categorized as feelings contributing to student’s self-concept,
while the inability to persevere and lack of goals are motivational variables.
12
In order to better understand how high-ability low-performing students differ
from high-ability high-performing students in terms of the three motivation indices
which are a) one’s choice on an achievement task, b) persistence on the task, and c) the
mental effort one expends in completing the task (Pintrinch & Schunk, 2002), it is
important to consider motivation in terms of goal orientations and task values. Goal
orientation theory is grounded in the belief that students’ achievement goal orientation
affects achievement in school. Ames (1992) defines an achievement goal as an
integrated pattern of beliefs, attributions, and affect that produces the intentions of
behavior that is represented by different ways of approaching, engaging in, and
responding to achievement-type activities. Goal orientation theory consists of two types
of achievement goals: mastery and performance goal orientations. In general, mastery-
oriented students are focused on the development of competence through task mastery
while performance-oriented students are focused on demonstrating competence in
relation to others (Elliott & McGregor, 2001). In addition, mastery learners tend to be
self-oriented while performance learners tend to be task-oriented (Payne, 2006).
Mastery and performance-oriented students also differ in the types of activities they
choose to engage in, their levels of persistence through difficult tasks, and the degree to
mental effort and energy invested into each activity.
Task value refers to the value that one places on the specific task as a means of
accomplishing one’s goals. Task values deal with how students value tasks, which
include attainment value, intrinsic value, utility value and cost. Attainment value is the
importance of doing well on a test in terms of students’ core personal values. Intrinsic
13
interest is the inherent enjoyment or pleasure that is derived from an activity. Utility
value is the value of the task in order to help a person achieve short or long-term goals.
Finally, cost is what is lost or given up as a consequence for engaging in a particular
activity (Eccles & Wigfield, 1995). All of these factors have also been shown to
influence active choice, persistence and mental effort.
In summary, high-ability high-achievers and high-ability underachievers were
found to differ in terms of social, school, family and individual factors. The most
prevalent social factors related to underachievement are peer influences and educational
aspirations and career goals. School-related factors such as school climate and practices
as well as student-teacher relations were also found to influence underachievement.
Among the various family factors that differentiate high-ability high-achievers, and
high-ability underachievers, family orientation and a sense of obligation to the family
was found to affect students from immigrant families. Finally, individual factors such
as goal orientation and task value were also linked to achievement. This paper will
discuss the interaction effects among each of these variables.
Purpose of the Study
Teachers and administrators at the high school have recognized the need to
better understand underachievement and find ways to motivate underachieving students
who have high academic abilities and the potential to succeed. The purpose of this
study is to investigate motivational factors that differentiate high-ability high-
performing (HAHP) students from high-ability low-performing (HALP) students.
Among the social, school, family, and personal factors that are related to
14
underachievement, the two variables that have been found to have a major influence on
underachievement of high-ability students are family and personal factors. However, it
is unclear what the relationship between the two variables is. Previous studies have
touched upon the relationships between the different motivational factors (Payne,
2005), personal factors (McCoach & Siegle, 2003a), family and school-related factors
(Hebert, 2001), but few studies have exclusively paired together family and personal
factors. The primary goal of this paper is to better understand the relationship between
the two motivational variables (goal orientation and expectancy value) and family
support. More specifically, which combinations of factors are most prevalent in high-
ability low-performing students?
Research Questions
In an attempt to better understand the interactions between family and
individual factors, this paper will investigate the relationships between family
orientation, goal orientations, and task values. The examination each of the motivation
variables and family support will add depth, clarity and understanding to the
motivational factors influencing high-ability underachievers. In short, the primary
research question for this study is “Which combinations of family and motivational
factors differentiate high-ability high achievers from high-ability underachievers?"
Definition of Terms
Achievement goals – reasons for engaging in achievement-oriented behaviors (Bong,
2001).
15
Goal valuation – beliefs about the importance and interest of the task (McCoach &
Siegle, 2003a).
Task-value – Interest in and perceived importance and usefulness of a task (Bong,
2001).
Underachievement:
• A discrepancy between potential achievement and actual achievement
• A discrepancy between predicted achievement and actual achievement
• A failure of develop or use potential (Hoover-Schultz, 2005).
16
CHAPTER 2
REVIEW OF THE LITERATURE
The articles used in this literature review were obtained through an online
search from the PsychInfo, PsychArticles, and ERIC computer databases. The time
parameters of the articles in this literature review range from 1995-2007, however a
few articles published before 1995 were also included in this review of literature
because they formed a foundational framework upon which prior studies were based.
The search terms used in the online search included: underachievement, gifted
education, high-ability, family factors, motivation, goal orientation, task values, and
achievement. This paper seeks to address the main question, what are the motivational
differences between high-ability high-performing (HAHP) and high-ability low-
performing (HALP) students?
This literature review is organized into the following three sections: “Family
Orientation and Academic Achievement”, “Goal Orientation Theory and Achievement”
and “Task Value Theory and Achievement”. Each section will conclude with a
summary in order to draw attention to the most salient findings that contribute to the
underachievement of high-ability students. Furthermore, this review will conclude with
a discussion on the relationships between each of the variables, and well as a series of
unanswered questions and further areas of research.
Family Orientation and Academic Achievement
Students from individualist and collectivist cultures have been found to differ in
terms of family orientation. For example, individualists tend to view themselves in
17
terms of their accomplishments, such as academic achievement, while collectivists tend
to evaluate themselves with consideration to how their individual accomplishments
reflect on their family (Urdan, 2004). Urdan (2004) focused on how students with
different family orientations would pursue performance goals for different reasons.
They found that immigrant students, mostly from Asian and Latin American cultures
tend to have stronger senses of obligation to care for their family members in
comparison to students born in the U.S. Urdan (2004) hypothesized that participants
with strong senses of family obligation would have stronger performance-avoidance
goals because they would want to do well academically in order to please their parents
and take care of their families in the future.
Urdan (2004) found that participants with a stronger sense of obligation to care
for their family reported strong pursuit of performance-approach goals, whereas those
with weaker family orientations were higher in performance-avoidance goals. The
rationale for the study of family orientations in relation to performance goals is that
students with weak family orientations may pursue performance goals for the purposes
of ego augmentation or protection, whereas, student with stronger family orientations
might have family members in mind when adopting performance goals.
The association between performance goals and academic achievement may
also differ for individuals with different levels of family orientation (Urdan, 2004). For
example, students may respond to performance-goal messages in the classroom
differently. Low family-orientated students may respond to the messages by adopting
performance-approach goals in order to feel pride and boost their self-esteem. Students
18
with high family-orientations may become more inclined to adopt performance-
avoidance goals in order to avoid shaming their families (Urdan, 2004).
Summary of Family Orientation and Academic Achievement
Family orientations, within the context of individualist and collectivist cultures,
have been found to impact students’ goals and student achievement. Urdan (2004)
found that immigrant students, mostly from Asian and Latin American cultures tend to
have stronger senses of obligation to care for their family members in comparison to
students born in the U.S. Urdan (2004) hypothesized that participants with strong
senses of family obligation would have stronger performance-avoidance goals because
they would want to do well academically in order to please their parents and take care
of their families in the future. Urdan (2004) also found that participants with a stronger
sense of obligation to care for their family reported strong pursuit of performance-
avoidance goals, whereas those with weaker family orientations were higher in
performance-approach goals. Finally, he found that the use of performance-approach
and performance-avoidance goals may differ for individuals with different levels of
family orientation (Urdan, 2004).
Goal Orientation Theory and Academic Achievement
Over the past two decades, achievement goals have become an important
framework in studying academic motivation among students (Bouffard & Couture,
2003). Goal orientation theory, also known as achievement goal theory defines goals as
cognitive representations of the different purposes students adopt for their learning in
achievement situations (Dowson & McInerney, 2003). In terms of academic
19
importance, goals reflect the fundamental reasons for which students take part in a
given learning activity (Bouffard & Couture, 2003). Not all academically gifted
students possess the same academic goals. Although it seems that most academically
talented students have achievement goals that facilitate long-term high achievement,
there is evidence that high-ability students vary substantially in their academic goals
(Ablard, 2002).
One of the underlying principles of goal orientation theory is the concept of
achievement goals. According to Ames (1992), an achievement goal is an integrated
pattern of beliefs, attributions, and affect that produces the intentions of behavior that is
represented by different ways of approaching, engaging in, and responding to
achievement-type activities. Achievement goals create a framework for how individuals
interpret and experience achievement settings (Baldwin & Coleman, 200). In the
literature on goal orientations, achievement goals are commonly categorized as either
mastery or performance goals. These types of achievement goals have been
alternatively labeled as learning and performance goals, task-involvement goals and
ego-involvement goals, and mastery and performance goals (Ames, 1992). Grant and
Dweck (2003) go even further to classify achievement goals into three different
categories: learning goals, ability-linked goals, and outcome goals. In brief, learning
goals, which are characteristic of mastery orientations, are described as goals that place
an emphasis on acquiring new skills and knowledge (Grant & Dweck, 2003; Payne,
2006). Ability-goals and outcome goals are more common among performance-
oriented students. Briefly, ability goals validate one’s ability in real-world situations
20
that are measured by exams, grades, achievement test scores etc. Outcome goals have a
narrower range that focus more specifically on obtaining good grades in school.
Because there is not a clear-cut distinction between ability and outcome goals, the more
traditional classification of achievement goals as either mastery or performance goals
will be used throughout this paper.
Under performance goals, two distinct types of goal orientations are classified
in the literature: performance-approach goals and performance-avoidance goals
(Midgley, Avi & Kaplan, 2001). Performance-approach learners are motivated by
outperforming others and appearing competent to their peers, while performance-
avoidance learners avoid the demonstration of lack of ability (Midgley et al., 2001).
Research indicates that performance-approach goals are positively related to academic
achievement and performance-avoidance goals are negatively related to achievement.
However, students use performance-approach goals for a variety of reasons which
include developing and improving their abilities or proving their abilities to others
(Middleton & Midgley, 1997). For example, performance-approach students who are
focused on proving their abilities to others may concentrate their efforts on doing well
academically in order to avoid looking stupid or receive negative judgments from
others (Middleton & Midgley, 1997). Other students who are concerned about proving
their abilities to others may take an opposite approach and engage in performance-
avoidance behaviors instead.
Some behaviors that are associated with performance-avoidance orientations are
deliberately not doing well in school, procrastinating studying until the last minute,
21
fooling around at night before a test and other “self-handicapping” strategies that are
attributed as causes of low performance rather than lack of ability (Midgley,
Arunkumar, and Urdan, 1996). In some cases, performance goals have been linked to
higher achievement. However, performance-approach and performance-avoidance
behaviors have been linked to maladaptive patterns of learning when students are more
focused on proving their abilities to others rather than on acquiring new skills or
knowledge.
Mastery and performance orientations influence the three motivational indices,
which are: 1) active choice 2) persistence and 3) mental effort (Clark & Estes, 2002).
Mastery and performance-oriented students differ in the types of activities they choose
to engage in, their levels of persistence through difficult tasks, and the degree to mental
effort and energy invested into each activity. For example, mastery-oriented students
are more likely to choose to work toward a specific goal (active choice), persist at
problem-solving while working toward their goal (persistence), and invest great
amounts of time and effort toward mastering specific material or skills (mental effort)
(Midgley, Maehr, Hruda, Anderman & Anderman, 2000 et al.). On the other hand,
performance-oriented learners may avoid specific assignments that threaten their
competence or may reluctantly participate in activities despite the urging of parents or
teachers (active choice). They are also less likely to persist at difficult tasks
(persistence), and may choose not to invest the mental effort above and beyond what is
required to accomplish a task (mental effort). In short, when it comes to the three
motivational indices of active choice, persistence, and mental effort, there are major
22
differences between mastery and performance-oriented learners. In general, mastery-
oriented students are focused on the development of competence through task mastery
while performance-oriented students are focused on demonstrating competence in
relation to others (Elliott & McGregor, 2001). Other differences between mastery and
performance-oriented students are that mastery learners tend to be self-oriented while
performance learners tend to be task-oriented (Payne, 2006).
The research on the effects of performance goal orientations on
underachievement is mixed. For example, some researchers question whether or not
learning goals affect performance at all, while others argue that performance goals
result in higher, rather than lower grades, and that they do not affect motivation (Grant
& Dweck, 2003). One reason for the discrepancies in the literature is that the positive
and negative effects of the different types of performance goals have not been
systematically explored (Grant & Dweck, 2003). Another point of argument depends on
how performance goals are classified or operationalized (Grant & Dweck, 2003). One
study that investigated the effects of different types of performance goals on motivation
is Grant and Dweck (2003). Grant and Dweck (2003) propose that performance goals
take three distinct forms. The first type is goals that are linked to validating an aspect of
self (e.g. one’s ability). The next type is goals that are explicitly normative in nature,
and the last type is goals that are simply focused on obtaining positive outcomes. The
differences between these three groups of performance goals is that the first form,
validating aspects of self, has been linked to negative effects, such as impairment, while
normative goals and those focused on positive outcomes have been linked to more
23
positive outcomes (Grant & Dweck, 2003). Currently, there is lack of agreement in the
literature regarding the positive and negative effects of different types of performance
goals on achievement. More research is needed to better define and operationalize
performance goals and to tease apart the different effects on motivation.
On the other hand, mastery learning has traditionally been looked upon
favorably in the literature. Mastery-oriented learners are more likely to employ
adaptive learning strategies, especially when they face difficult challenges (Midgley et
al., 2000). For example, students who employ a mastery goal orientation are also more
likely to invest more effort in learning. Additionally, mastery learners are more likely
to value learning, endorse deep-level cognitive processing, exhibit higher self-efficacy,
and utilize self-regulated learning strategies (Ames, 1992). For example, high-ability
students who are mastery-oriented are likely to succeed in challenging academic
environments since the acceleration and enrichment of the coursework would
contribute to the students’ understanding and knowledge (Ames, 1992). On the other
hand, high-ability students who are performance-oriented may not welcoming new
challenges, but rather avoid challenges and exhibit patterns of performance-avoidance
behavior, including learned helplessness (Elliot & Dweck, 1988). Avoidance behavior
is one of many factors that contribute to underachievement. In short, high-ability
students with strong mastery-oriented achievement goals are less susceptible to factors
leading to underachievement than high-ability students with strong performance goals.
Ablard (2002) sets the achievement goal framework for high-ability
underachieving students by classifying them into different combinations of weak and
24
strong mastery goals, as well as different combinations of weak and strong performance
goals. In a sample of 425 fifth grade students who scored at or above the 97
th
percentile
on grade-level standardized achievement tests, and were in the top 3% of their grade
level, Ablard (2002) categorized each student according to different combinations of
mastery and performance goals, ranging from very weak to very strong performance
goals and very weak to very strong learning (or mastery) goals.
According to the results of the study, Ablard (2002) found that two goals are not
systematically related. One group of students that showed some risk for under-
achievement was the students with very strong mastery goals and very weak
performance goals. These students were found to be at risk because they may pursue
their own interests and spend a great deal of energy studying topics they enjoyed
without regard to grades. In short, these students may learn a great deal of information
about their particular interests, but may do poorly in mastering the course content
(Ablard, 2002).
At the other extreme, high-ability students who strongly embraced performance
goals were also found to be more at risk of underachievement. Ablard (2002) found
that approximately 25.2% of the students could be potentially at risk for
underachievement because they tended to focus on overt accomplishments and
embraced very strong performance goals. They were more likely to avert challenges
and showed more maladaptive patterns of achievement such as performance-avoidance
behaviors (Ablard, 2002). Elliot and Dweck (1988) found that instead of welcoming
new challenges, these students are found to avoid challenges, and they exhibited
25
patterns of performance-avoidance behavior, including learned helplessness. Overall,
students who strongly endorsed performance goals were more likely than mastery-
oriented students to be more aggressive, argumentative, opinionated, confident,
determined, forceful and have a show-off attitude (Ablard, 2002). Students with strong
performance goals are more likely to focus on getting good grades and may limit
themselves by avoiding challenges, whereas mastery-oriented students would be more
likely to pursue them.
Recently, there has been a reconceptualization of goal theory that highlights the
positive effects of performance-approach goals and performance-avoidance goals
(Midgley, Kaplan, & Middleton, 2001). For example, performance goals have been
found to increase the use of rehearsal strategies that increase short-term performance
(Ablard, 2002). Another example is that performance goals enhance achievement on a
simple task. Students with performance goals are likely to feel confident on simple
tasks and may even use more rehearsal strategies to enhance their performance (Ablard,
2002). In a nutshell, performance goals have been found help high-ability students
enhance short-term performance, encourage the use of rehearsal strategies, and gain
more confidence. Currently, the research on performance goals is mixed, with some
studies arguing that performance goals are unrelated or negatively related to adaptive
patterns of learning (Midgley, Kaplan, & Middleton, 2001). Either way, performance
goals do have an impact on motivation among high-ability students.
One limitation of Ablard’s (2002) study is that it fails to clearly differentiate
between the different types of mastery and performance goals. Mastery goals are
26
defined as “focus of understanding the material, and wanting to learn even when
performance is poor,” while performance goals “focus on overt accomplishments”
(Ablard, 2002, p. 206). Since the terms are loosely defined, it is difficult to tease apart
differences in individual student motivation. For example, it is hard to say whether the
focus on overt accomplishment was due to obtaining a certain grade in order to validate
their sense of competence, or whether the goal was to perform better than others.
Another limitation is that the sample population was taken from 5
th
grade gifted
students in the North East. Therefore, the generalizability of the study is limited to that
specific population.
One reason performance-oriented students may be more susceptible to
underachievement than mastery-oriented students is due to social comparisons.
Performance learners seek to validate themselves by demonstrating their competence to
others. Because performance-oriented students are often focused on social comparisons,
the desire to be labeled as “gifted” or academically-talented may play a role in high-
ability students’ adoption of performance goals. The social labeling as a “high-
achiever” or “gifted student” has an evaluative and reinforcing impact on high-ability
students’ self-perceptions and self-beliefs, which can affect their achievement goal
orientations (Baldwin & Coleman, 2000). Labeling children as “gifted” or academically
talented represents a form of judgment of one’s intelligence which may predispose
some students to adopt performance rather than mastery goals (Baldwin & Coleman,
2000). For example, “failure” is devastating to performance learners who interpret
failure as incompetence, validating that one is “dumb” (Ames, 1992). Since
27
performance learners focus more on ability than effort, when performance learners
experience setbacks, failure indicates a lack of ability (Ames, 1992). As a result, some
high-ability students may become overly concerned with maintaining the so-called
“gifted” label through academic success like high grades or recognition, and less
concerned with seeking out challenging tasks to improve their skills (Baldwin &
Coleman, 2000). In this respect, it is possible that some high-ability students will adopt
performance goal orientations in order to seek social praise or to retain the label as an
“academically talented” or “high-ability” student.
Baldwin and Coleman (2000) have identified a variety of benefits related to
putting more emphasis on mastery-oriented learning rather than performance-focused
learning when teaching high-ability students. Baldwin and Coleman (2000) argue that
adopting task-oriented contexts with an emphasis on effort, mastery, and improvement,
can aid high-ability students with strong performance orientations to overcome personal
tendencies to adopt performance goals in order to justify or validate their high academic
abilities.
Summary of Goal Orientation Theory and Academic Achievement
There are several important differences between mastery and performance goal
orientations. In general, mastery-oriented students are focused on the development of
competence through task mastery while performance-oriented students are focused on
demonstrating competence in relation to others (Elliott & McGregor, 2001). Mastery
learning has traditionally been looked upon favorably in the literature. Nevertheless, the
effects of performance goals on academic achievement are currently under debate.
28
Ablard (2002) found that high-ability underachieving students have different
combinations of mastery and performance goals. Mastery and performance goal
orientations have been found to affect students’ performance-approach goals and
performance-avoidance goals (Midgley, Avi & Kaplan, 2001).There is some evidence
that gifted students with very strong mastery goals and very weak performance goals
are at risk of underachievement because they may choose pursue their own academic
interests without regard to grades (Ablard, 2002). Students with very strong
performance goals may also be at risk for underachievement because they are more
likely to avert challenges and display more maladaptive patterns of achievement
(Ablard, 2002).
Task Value Theory and Academic Achievement
Expectancy-value theory plays a central role in students’ motivation (Eccles &
Wigfield, 1995). The three main areas of expectancy-value theory are 1) ability beliefs,
2) expectancies for success and 3) task value. Ability beliefs are students’ beliefs about
their ability to perform a task (Pintrich & DeGroot, 1990). Expectancies include
students’ beliefs about their ability to perform a future task (Pintrich & DeGroot, 1990).
Task values involve students’ beliefs about the importance of the task or importance of
attaining a goal (Eccles & Wigfield, 1995) and their interest of the task (Pintrich &
DeGroot, 1990) Task values also include students’ incentives for engaging in academic
activities, which includes perceived importance, usefulness and interest (Wigfield &
Eccles, 1992).
29
Theorists differ in their findings about the relative importance of expectancies
and values for achievement (Berndt & Miller, 1990). Some studies have shown that
expectancy values play a critical role in initiating and sustaining students’ achievement
motivation and action (Bong, 1999). For example, Dweck and Elliott (1988)
emphasized the potentially negative impact of low or unstable expectancies on
achievement. On the other hand, Eccles (1983) argued that students’ values have a
greater long-term effect of achievement than expectancies because values affect
curriculum choices that determine students’ exposure to higher-level concepts. Since
task values are most closely related to students’ goals orientation, ability beliefs and
expectancies for success will not be addressed in this paper.
The task value theory involves students’ goals for the task and their beliefs
about the importance and interest of the task (Pintrich & DeGroot, 1990). Similar to
goal orientation theory, values represent students’ reasons for engaging in a particular
task. Rotter (1982) interjects that task value also involves the anticipated reward that an
individual will receive, which can result from the activity itself, or indirectly through
the activity’s role in acquiring other desired consequences (Eccles & Wigfield, 1995).
The four major components of task values are: 1) attainment value, 2) intrinsic value
(or interest), utility value, and cost (Eccles & Wigfield, 1995).
Attainment value is the importance of doing well on a task in terms of a
person’s self-schema and core personal values. Attainment value is further broken
down into two subcomponents: the importance of a given activity (absolute attainment
value) and the importance to other activities (relative attainment value) (Summers,
30
Schallert & Ritter, 2003). Intrinsic interest refers to the inherent enjoyment or pleasure
that a person derives from an activity. Utility value is the value of the task in order to
help a person achieve short-term or long-term goals. Cost refers to what is lost or given
up as a consequence of engaging in a particular activity (Eccles & Wigfield, 1995).
Attainment value, intrinsic value and utility value are viewed as positive or attracting
characteristics while cost is viewed as a negative characteristic affecting motivation
(Eccles & Wigfield, 1995).
Task values can differ across different tasks. In terms of task value, Eccles and
Wigfield (1995) state that individuals will find different domains such as mathematics
versus English as more or less personally interesting or valued. Thus, task values also
differ as a function of domains. Nevertheless, researchers have identified common
patterns in task theory that are directly and indirectly linked to student achievement.
Pintrich and DeGroot (1990) found that students who value academic tasks are
more likely to become more cognitively engaged, self-regulated students. The
suggested link is between intrinsic value, academic engagement, self-regulation, and
higher achievement. However, it is not clear if those factors alone are enough to
account for higher grades or test scores in school (Pintrich & DeGroot, 1990). These
findings suggest that among the three motivational indices (active choice, persistence,
and mental effort), intrinsic value is most closely related to students’ choices to become
engaged in classroom activity.
31
Summary of Task Value Theory
Theorists differ in their findings about the relative importance of expectancies
and values for achievement (Berndt & Miller, 1990). Some theorists argue that
expectancies are stronger predictors of achievement, while others make a case for
values. For this paper, only task values will be examined. The four major components
of task values are: 1) attainment value, 2) intrinsic value (or interest), utility value, and
cost (Eccles & Wigfield, 1995). In general, task values were found to differ as a
function of domains. Of the four components, intrinsic value is most closely related to
students’ choices to become engaged in classroom activity.
Gaps and Key Questions Unanswered by the Literature Review
In terms of goal orientations, the general consensus is that students with mastery
goal orientations achieve at higher levels while students who are performance-oriented
are less likely to do well in school. Since all students possess a combination of mastery
and performance oriented goals, recent studies have just begun to address the different
combinations of goals. There is some evidence that gifted students with very strong
mastery goals and very weak performance goals are at risk of underachievement and
that students with very strong performance goals may also be at risk for
underachievement. The unanswered question that this study seeks to address is how
HAHP and HALP students differ in terms of family orientations, goal orientations, and
task values.
Research Questions
1. How do HAHP and HALP students differ in terms of family orientation?
32
2. How do HAHP and HALP students differ in terms of mastery, performance-
approach, and performance-avoid goal orientation?
3. How do HAHP and HALP students differ in terms of task values?
Hypotheses
Based on the information from the literature review, the following hypotheses
were made:
1. HAHP students will exhibit higher family orientations than HALP students.
Conversely, HALP students will exhibit a lower family orientation than HAHP
students.
2. HAHP students will exhibit a higher mastery goal orientation than HALP students.
Conversely, HALP students will exhibit a lower mastery goal orientation than HAHP
students.
3. HAHP students will exhibit a higher performance-approach goal orientation than
HALP students. Conversely, HALP students will exhibit a lower performance-approach
goal orientation than HAHP students.
4. HAHP students will exhibit a lower performance-avoid goal orientation than HALP
students. Conversely, HALP students will exhibit a higher performance-avoid goal
orientation than HAHP students.
5. HAHP students will exhibit a higher task value than HAHP students for
English/language arts or math classes. Conversely, HALP students will have a lower
task value for English/language arts or math classes.
33
6. Asian and Hispanic students will exhibit a higher family orientation than Caucasian
and African American students as well as students from "Other" ethnicities.
34
CHAPTER 3
METHODS
The purpose of this study is to investigate the relationships between family
orientation, goal orientations and task values of high-ability high-performing (HAHP)
students and high-ability low-performing (HALP) students. This study compares
students’ motivation in relation to family orientation, mastery and performance
orientation and task values. The primary research question for this study is “Which
combinations of motivational factors differentiate high-ability high-performing and
high-ability low-ability students?” To better answer this question, this study utilizes a
28-item survey to analyze each of the variables.
Participants and Setting
The participants in this study were 10
th
, 11
th
and 12
th
grade students from a
middle-class suburban high school in California. A total of 452 students from 14 upper
level classes in English/language arts, math and science were selected to participate in
the study. Surveys from 181 students were collected and analyzed.
This study solely focuses on high-ability high-performing (HAHP) students and
high-ability low-performing (HALP) students. HAHP students are defined in this study
as students who scored in the Advanced or Proficient levels on the California Standards
Test (CST) in English/language arts or math and received high grades (A or B) in
English/language arts or math classes. Conversely, HALP students are identified as
those who scored in the Advanced or Proficient levels on the California but received
low grades (C, D, or F) in English/language arts or math classes. Information regarding
35
CST results for the high school was made public by the California Department of
Education through the DataQuest online database. The total percentage of students at
the high school (N = 1537) who scored in either the Advanced or Proficient levels on
the CST's for English/language arts was 59% and the total percentage of students (N =
1489) who scored in either the Advanced or Proficient levels on the CST's for
mathematics was 40.6%.
Based on their performance on the CST's as well as individual grades in
English/language arts and math, students were classified students into one of four
groups: 1) High-ability high-performing (HAHP) students, 2) high-ability low-
performing (HALP) students, 3) low-ability high-performing students, and 4) low-
ability low-performing students. Figure 1 shows ability and performance groupings in a
matrix of high-ability high performing (HAHP), high-ability low-performing (HALP),
low-ability high-performing and low-ability low-performing students.
Figure 1
Ability and Performance Groupings
Ability
High-Ability High-
Performing
(HAHP)
Low-Ability High-
Performing
Performance
High-Ability Low-
Performing
(HALP)
Low-Ability Low-
Performing
36
In terms of grouping by gender, there were more males than females in the
study. Of the 181 total high-ability students, approximately 46% were male (n = 83)
and 54% were female (n = 98). For HAHP students in English/language arts (n = 93),
there were 43 females and 50 males. For HALP students in English/language arts (n =
15), there were 5 females and 10 males. For HAHP students in math (n = 40), there
were 16 females and 24 males. For HALP students in math (n = 23), there were 6
females and 17 males.
Among the 2,171 students enrolled at the high school during the 2006-2007
academic school year, the DataQuest online database by the California Department of
Education reported student enrollment by ethnicity as the following: White (not
Hispanic) = 38%, Asian = 38.4%, Hispanic or Latino = 11.5%, African-American =
2.9%, Filipino = 3.6%, Pacific Islander = 0.8% and American Indian or Alaskan Native
= 0.3%. In this study, there were higher percentages of Asian students than Caucasian
students. Asian students comprised the largest ethnic group followed by Caucasian
students, Hispanic students, and "Other" ethnic groups. No African American students
participated in the study. In terms of grouping by ethnicity, approximately 52% of the
students were Asian (n = 90), 35% were Caucasian (n = 59), 7% were Hispanic (n =
12), approximately 6% identified with "Other" ethnicities, and 0% were African
American.
For HAHP students in English/Language (n = 93) there were 35 Caucasian
students, 44 Asian students, 8 Hispanic students, 0 African American students, and 6
students from "Other" ethnicities. For HALP students in English/language arts (n = 15),
37
there were 6 Caucasian students, 8 Asian students, 0 Hispanic students, 0 African
American students, and 1 student from "Other" ethnicities. For HAHP students in math
Arts (n = 40), there were 13 Caucasian students, 22 Asian students, 3 Hispanic
students, 0 African American students, and 2 students from "Other" ethnicities. For
HALP students in math (n = 23), there were 5 Caucasian students, 16 Asian students, 1
Hispanic student, 0 African American students, and 1 student from "Other" ethnicities.
HAHP and HALP students were broken down into two groups according to
subject, English/language arts and math. Table 2 shows the total number of participants
in this study broken down by gender, grade level and ethnicity.
Table 2
HALP/HAHP Participants by Gender, Grade Level, and Ethnicity for
English/language arts and Math
English/language arts Math
HAHP HALP HAHP HALP
(N =
93)
(N =
15)
(N =
40)
(N =
23)
Female 43 5 Female 16 6
Male 50 10 Male 24 17
Junior 43 8 Junior 17 13
Senior 50 7 Senior 23 10
Caucasian 35 6 Caucasian 13 5
Asian 44 8 Asian 22 16
Hispanic 8 0 Hispanic 3 1
African
American 0 0
African
American 0 0
Other 6 1 Other 2 1
Note: HAHP = High-Ability High-Performance students, HALP = High-Ability-
Low-Performance students.
38
Inclusion/Exclusion Criteria
Approximately 60% (N = 271) of the total students invited to participate in the
study were excluded because they either a) failed to return their parental or student
consent forms, b) their parent/guardian opted out by checking one of the "I do not
agree" boxes on the parental consent forms, c) the student opted out by checking one of
the "I do not agree" boxes on the student consent forms, or d) the student was absent on
the day the survey was administered. Data was collected from a total of N = 181
participants. However, students who did not score in the Advanced or Proficient levels
of the CST excluded from the data analysis. Based on the criteria, approximately 40%
(n = 73) of the remaining 181 participants were excluded from the data analysis for
English/language arts because they scored in the Basic, Below Basic or Far Below
Basic levels on the CST of English/language arts. For math, approximately 64% (n =
116) of the participants were excluded from the data analysis because they scored in the
Basic, Below Basic or Far Below Basic levels on the CST for math. In total, there were
(n = 108) participants in English/language arts and (n = 64) students in math. Table 3
outlines the means and standard deviations of average grades for HALP/HAHP students
in English/language arts and Math.
39
Table 3
Means and Standard Deviations of Average Grade for HALP/HAHP Students in
English/language arts and Math
English/language arts Math
HAHP HALP HAHP HALP
(n = 93) (n = 15) (n = 40) (n= 23)
M SD M SD M SD M SD
Grade 3.62 0.49 2.53 0.52 3.45 0.51 1.65 0.65
Note: HALP = High-Ability-Low-Performance, HAHP = High-Ability-High-
Performance.
Instruments
To measure students’ academic ability, the California Standards Test (CST) was
used to determine participants’ proficiency in English/language arts and mathematics.
One questionnaire consisting of a total of 28 items was created which consisted of a
combination of questions regarding students’ family orientations, goal orientations and
task values. The questions were derived from the Family Orientation Scale (Urdan,
2004), the Patterns of Adaptive Learning Strategies (P.A.L.S), Midgley et al. (2000)
and the Motivated Strategies for Learning Questionnaire (MLSQ), Pintrich, Smith,
Garcia and Mckeachie (1991).
Academic Ability - To measure students’ level of ability, California Standards
Test (CST) scores were used to determine students’ English/language arts and
Mathematics proficiency. Through the California Standardized Testing and Reporting
(STAR) Program, students in grades 2-11 are tested annually in various subject areas.
Currently, the STAR program includes California Standards Tests (CST) in
English/language arts and mathematics in grades 2-11. The five CST performance
40
levels are Advanced (exceeds state standards), Proficient (meets state standards), Basic
(approaching state standards), Below Basic (below state standards), and Far Below
Basic (approaching state standards). Students at the Proficient or Advanced level met
state content standards in that area.
Performance - Student performance was measured by students' academic grade.
The difference between CST scores and grades is that CST scores represent the aptitude
and potential to perform at or above grade level, while grades represents actual
performance in a given classes. Letter grades were converted to a numerical value
based on a typical Grade Point Average scale in which A (outstanding performance) =
4.0, B (satisfactory performance) = 3.0, C (average performance) = 2.0, D (below
average performance) = 1.0 and F (failing performance) = 0.
Family Orientation - The family orientation questions includes 4 survey items
from the Family Orientation Scale (Urdan, 2004). This scale was designed to measure
high school students’ desires please or provide for family members through academic
achievement. Sample items include, “An important reason that I try to do well in
school is to please my parents” and “I want to do well in school so that I can be better
prepared to take care of my family” (Urdan, 2004). A 5-point Likert rating scale was
used to measure each question ranging from 1 (not at all true of me) to 5 (very true of
me). Originally measured over two waves, Cronbach’s reliability coefficient is α = .72
for the first wave and α = .73 for the second wave.
Mastery and Performance Goal Orientations - The mastery and performance
orientation scales consist of a total of 15 survey items from Patterns of Adaptive
41
Learning Scales (PALS), Midgley et al. (2000). The Patterns of Adaptive Learning
Scales (PALS) instrument was used to measure participants’ goal orientation (Midgley,
et al., 2000). This instrument includes three scales that are each on a 5-point Likert
scale, which are: the Mastery Goal Orientation Scale, the Performance-Approach Goal
Orientation, and the Performance-Avoid Goal Orientation. All three scales were revised
in 2000 from the original items published in 1997. The Mastery Goal Orientation Scale
(Revised) is comprised of five items. Sample items include “It is important to me to
learn a lot of new concepts this year” and “One of my goals is to master a lot of new
skills this year”. The reliability coefficient for the Mastery Goal Orientation Scale
(Revised) is α = .85. The Performance-Approach Goal Orientation (Revised) Scale is
also comprised of five items. Sample items include “It is important to me that other
students think I am good at my class work” and “One of my goals is to show others that
the work is easy for me”. The reliability coefficient for the Performance Approach
Goal Orientation Scale (Revised) is α = .89. Finally, the Performance-Avoid Goal
Orientation Scale (Revised) also contains five items. Sample items include “It is
important to me that I don’t look stupid in class” and “One of my goals is to avoid
looking like I have trouble doing the work.” The reliability coefficient for the
Performance Avoid Goal Orientation Scale (Revised) is α = .74.
Task Value - Task value items consist of 6 survey items adapted from the
Motivated Strategies for Learning Questionnaire (MSLQ), Pintrich, Smith, Garcia and
McKeachie, (1993). The scale was designed to measure the motivational orientation
and learning strategy use. Sample items include “I think I will be able to use what I
42
learn in this course in other courses” and “I think the course material in this class is
useful for me to learn.” A 7-point Likert scale was used to measure each question
ranging from 1 (not at all true of me) to 7 (very true of me). The reliability coefficient
for the Task Value Scale is α = .90.
Demographic Data - Three demographic questions regarding students’
ethnicity, gender and grade level were also included in the survey.
Reliability - With regard to the reliability of the family orientation, mastery goal
orientation, performance-approach orientation, performance-avoid orientation and task
value subscales, an analysis of Cronbach's alpha indicated acceptable reliability on the
family orientation subscale (α = .72), performance-approach subscale, (α = .71) and
task value (α = .70). The mastery goal orientation and performance-avoid subscales
both had lower reliability rates of (α = .69), which fall under a questionable reliability
range (George & Mallery, 2003). In order to increase the reliability of the mastery goal
orientation and performance-avoid subscales, items 21 and 23 were deleted from the
survey. Item 21 measures a mastery goal orientation and reads "It's important to me that
I improve my skills this year." Item 23 measures performance-avoid goal orientation
and reads "The reason why I do my work is so others won't think I'm dumb." By
deleting these two items, the reliability increased from α = .69 to α = .76 for the
mastery orientation subscale and from α = .69 to α = .76 for the performance-avoid
subscale. With items 21 and 23 omitted, all subscales on the survey had a reliability
coefficient of at least α = .70, which are acceptable reliability ranges for this type of
study (George & Mallery, 2003).
43
Survey Instrument
In total, the questionnaire consisted of 28 questions based on a 7-point Likert
scale. The items that were originally created on a 5-point Likert scale have been
converted to a 7-point Likert scale for uniformity. A breakdown of the numbers of
items represented by each construct is as follows:
• Family orientation questions from the Family Orientation Scale, Urdan (2004) -
4 Items
• Mastery goal orientation questions from the Patterns of Adaptive Learning
Scales (PALS), Midgley et al. (2000) – 5 Items.
• Performance-approach goal orientation questions from the Patterns of Adaptive
Learning Scales (PALS), Midgley et al. (2000) – 5 Items.
• Performance-avoid goal orientation questions from the Patterns of Adaptive
Learning Scales (PALS), Midgley et al. (2000) – 5 Items.
• Task value questions from the Motivated Strategies for Learning Questionnaire
(MLSQ), Pintrich et al. (1993) – 6 Items.
• Student demographic questions to differentiate students’ gender and grade level-
3 Items.
44
Procedures
Prior to conducting research, approval for this study was obtained from the
University of Southern California. This study went through a thorough review from the
Internal Review Board (IRB) to ensure that the study followed strict ethical standards
and guidelines.
First, a packet, which included a cover letter from the school principal along
with parental consent forms, was mailed to the parents of students selected to
participate in the study. The consent forms informed parents of the purpose of the study
and outlined potential risks and benefits of participating in the study, confidentiality,
and rights of research participants. Parents were able to choose whether to have their
child's test scores, grades, and demographic information released. Contact information
of the principal investigator was listed if parents had questions regarding the study.
Parents were asked to check off the appropriate boxes and sign and date the form before
returning the forms to their child's teacher.
After approximately one week, parental consent forms were collected. Only
students whose parents checked off all the "I agree" boxes and signed, dated, and
returned the forms to school were invited to continue in the study. Students were given
student consent forms similar to parental consent forms on the day of the survey
administration.
Prior to filling out the survey, students were given an opportunity to read their
student consent forms. In addition, the principal investigator verbally informed students
of the purpose of the study and outlined potentials risks and benefits of participating in
45
the study, confidentiality, and rights of research participants. All student participants
were notified that their data were strictly confidential and their work was voluntary.
Participants were given instructions not to discuss the survey items with each other
prior to taking the survey. Participants were also given an opportunity to ask questions
about the study or regarding their rights before the survey was administered. Students
were asked to check the appropriate boxes if they chose to participate in the study, then
sign and date their consent forms.
During the survey administration, participants were asked to write their student
ID number on the actual survey. Participants were asked not to read or fill in any
bubbles ahead of time, but wait for the principal investigator to read each survey
question aloud before answering each question. The principal investigator read each
survey question aloud, pausing approximately 5-7 seconds between questions to allow
participants time to respond. More time was given if the principal investigator
perceived that any of the students needed more time to respond. After the survey was
administered, students were asked to look over and fill in the bubbles for any survey
items they may have missed. Surveys were collected from a box placed in the front of
the classroom. Students were thanked for their participation.
The process of recruiting participants, informing them of their rights, collecting
student consent forms and administering the survey took approximately 25-30 minutes
to complete. The entire process took place during a 50-minute class period during
school hours. In total, surveys were administered to 14 different classes over a three-
day period.
46
Data analysis
The purpose of the data analysis was to examine how HAHP students differed
from HALP students in terms of their family orientation, goal orientation (mastery,
performance-approach, and performance-avoid) and task values. Descriptive means and
standard deviations of each of the five variables (family orientation, mastery goal
orientation, performance-approach goal orientation, performance- avoid goal
orientation and task value) were obtained. By using the SPSS-PC computer program,
all quantitative data were coded, scored and computerized. The following statistical
analyses were conducted:
(a) Intercorrelations of family orientation, mastery goal orientations,
performance-approach goal orientation, performance-avoid goal orientation
and task values.
(b) Means and standard deviations of family orientation, goal orientations, and
task values, with raw data of ability (CST scores) and performance (grades)
in English/language arts and math.
(c) Internal consistency reliability (Cronbach’s alpha) for scores on survey
items using scales in family orientation, goal orientations and task values.
(d) Independent samples and T-tests to compare the means and standard
deviations between groups. In addition, one-way analyses of variance
(ANOVA) were used to find groups statistics and equality of means between
high-ability high-performing (HAHP) and high-ability low-performing
47
(HALP) students in relation to family orientation, goal orientations and task
values.
(e) Multiple regression analysis to determine the variance accounted for by each
of the five variables.
(f) Comparison of means (ANOVA) in relation to gender and ethnicity.
The data and findings for these types of statistical analyses can be found in
Chapter 4.
48
CHAPTER 4
RESULTS
This chapter presents the statistical outcomes for the following research
questions: 1) How do high-ability high-performing (HAHP) and high-ability low-
performing (HALP) students differ in terms of family orientation? 2) How do HAHP
and HALP students differ in terms of mastery, performance-approach, and
performance-avoid goal orientation? 3) How do HAHP and HALP students differ in
terms of task values? This chapter presents descriptive statistics of the mean grade for
students in English/language arts and math, as well as analyses of variance using one-
way ANOVAs, multiple regression, and means and standard deviations comparing
gender and ethnicity across the following five variables: family orientation, mastery
goal orientation, performance-approach goal orientation, performance-avoid goal
orientation, and task values. In essence, this study seeks to understand how HAHP and
HALP students differ in terms of motivation.
Quantitative Findings
Intercorrelations
A summary of the means, standard deviations and correlations of the family
orientation, performance-approach goal orientation, performance-avoid goal orientation
and task value are listed in Table 4.
49
Table 4
Means, Standard Deviations, and Pearson Product Correlations for
Measured Variables
Note: * p < .05
The correlational analysis revealed that family orientation had a positive
relationship with performance-avoid goal orientation (r = 0.03, p < .01). Mastery goal
orientation and performance-avoid goal orientation were also positively correlated (r =
0.01, p < .01). Another significant positive relationship was between performance-
approach goal orientations and performance-avoid goal orientations (r = 0.03, p < .01).
These findings suggest that students who were likely to be motivated to do well in
school in order to please or assist their family members were also more likely to be
motivated to avoid their teachers’ or peers' perceptions they have trouble doing their
work. In addition, students who were interested in learning and mastering academic
concepts for intrinsic purposes were also motivated to avoid their teachers’ or peers'
Variables 1 2 3 4 5
M SD
1. Family
Orientation
4.47
1
1.04
7
1.00 0.35 0.25 0.03* 0.21
2. Mastery
4.44
3
1.23
1
-- 1.00 0.28 0.01* 0.29
3.
Performance-
Approach
4.01
9
1.15
4
-- 1.00 0.03* 0.70
4.
Performance-
Avoid
3.70
3
1.07
9
-- 1.00 0.11
5. Task Value
3.92
9
1.08
1
-- 1.00
50
perceptions that they struggle in school. Finally, students who were motivated to show
others that they are good at their work or by the desire to appear "smart" in comparison
to their peers were also motivated to avoid their teachers’ or peers' perceptions they
have trouble doing their work. It appeared that a common theme among high-ability
students was to avoid appearing that they struggled in their classes or with specific
academic tasks.
Descriptive Statistics
Based on the traditional academic grade point average (GPA) scale where A =
4.0, B = 3.0, C = 2.0, D = 1.0 and F = 0, the mean grade for HAHP students in
English/language arts was 3.62 (SD =0.49). The mean grade for HALP students in
English/language arts was 2.53 (SD =0.52). In math, the mean grade for HAHP
students was 3.45 (SD =0.51). Finally, mean grade for HALP students in math was
1.65 (SD =0.65).
This data shows that there were more high-performing students in
English/language arts (n = 108) than there were in math (n = 65). While the mean
grades for HAHP students in English/language arts and math were similar (3.62 and
3.45 respectively), the mean grade was higher for HALP English/language arts students
than HALP math students (2.53 and 1.65 respectively).
These findings imply that not only were there more high-ability students in
English/language arts than math, but there were also more high-performing students as
indicated by average grade. High-performing students in English/language arts had an
average grade of 3.62, which was similar to the average grade (3.45) of high-
51
performing math students. However, the opposite finding holds true for low-performing
students. Low-performing English/language arts students had an average grade of 2.53
as compared to low-performing math students, who had an average grade of 1.65.
There appeared to be a greater disparity in grades between HAHP and HALP math
students than HAHP and HALP English/language arts students. Figure 2 shows the
differences between average grades of HAHP and HALP students in English/language
arts and math. It is interesting to note that there were higher grade averages in
English/language arts than in math, and bigger discrepancies between HAHP and
HALP students for math. The implications for these findings will be discussed in detail
in the next chapter.
Figure 2
Differences in Average Grade Between HAHP and HALP Students in English/language
arts and Math
0
0.5
1
1.5
2
2.5
3
3.5
4
HAHP HALP
A v e ra g e g ra d e
E nglish/L anguage
Arts
Math
Note: HAHP = High ability-high performing students. HALP = High-ability low-
performing students
Analysis of Variance. An analysis of variance (one-way ANOVA) and
independent sample t-tests were conducted between HAHP and HALP students in
52
English/language arts and math. For HAHP and HALP students (n = 108) in
English/language arts, statistically significant differences were found in the family
orientation, performance-approach and performance-avoid subscales. For HAHP and
HALP students in math (n = 63), significant differences were found in the family
orientation subscale and mastery goal orientation subscales. Task value was not found
to be a statistically significant factor among either group (HAHP and HALP students)
in English/language arts or math. Statistical findings for each group are represented in
detail below.
Research Question 1
How do HAHP and HALP students differ in terms of family orientation?
Between HAHP and HALP students, the one-way analysis of variance (ANOVA)
revealed statistical differences in family orientation in English/language arts (F (1, 108)
= 18.71, p = 0.002) and math (F (1, 63) = 23.66, p = 0.000). As expected, HAHP
students were more likely to be motivated to do well in school in order to please or
assist their family members than HALP students. Specifically, HAHP students scored
significantly higher on questions like, "An important reason that I try to do well in
school is to please my parents-siblings," "I want to do well in school so that I can be
better prepared to take care of my family," "The main reason I try to do well in school
is to bring honor to my family," and "It's important to me that my parents-guardians are
proud of my achievement in school." A discussion of the implications of these findings
will be discussed in detail in Chapter 5.
53
Research Question 2
How do HAHP and HALP students differ in terms of mastery, performance-
approach, and performance-avoid goal orientation? The results of the one-way ANOVA
revealed that mastery goal orientations differed between subjects. Between HAHP and
HALP students in math, the one-way analysis revealed statistical differences in mastery
goal orientation (F (1, 63) = 45.79, p = 0.001). However, for English/language arts, no
significant differences were found (F (1, 108) = 2.46, p = 0.120). This finding suggests
that HAHP students in math were interested in learning and mastering math concepts
for intrinsic purposes. Specifically, HAHP students in math were more likely to answer
positively to questions such as, "It's important to me that I learn a lot of new concepts
this year," "One of my goals in class is to learn as much as I can," "One of my goals is
to master a lot of new skills this year," and "It's important to me that I completely
understand my work." While the results were expected for HAHP students in math, the
results were contrary to expectations for English/language arts. Possible explanations
for differences between academic subjects will be discussed in Chapter 5.
The analysis of variance also revealed that with regards to performance-
approach goal orientations, HAHP and HALP students also differed between subjects.
This time, significant differences were found between HAHP and HALP students in
English/language arts, but not in math. In English/language arts, the differences
between HAHP and HALP students were significant (F (1, 108) = 8.88, p = 0.001). For
math, no significant differences between HAHP and HALP students were found in
terms of performance-approach goal orientation (F (1, 108) = 0.26, p = 0.610). While
54
the results were expected for HAHP students in English/language arts, the results were
contrary to expectations for math. The specific questions that HAHP students in
English/language arts scored higher on are "It's important to me that other students in
my class think I'm good at my class work," "One of my goals is to show others that I'm
good at my class work," "One of my goals is to show that class work is easy for me,"
"One of my goals is to look smart in comparison to other students in my class" and "It's
important to me that I look smart in comparison to other students." This finding
suggests that HAHP students were more likely to be motivated by showing others that
they are good at their work or by the desire to appear "smart" in comparison to their
peers. Again, possible explanations for differences between subjects will be discussed
in the next chapter.
Next, the one-way ANOVA showed significant differences in performance-
avoid goal orientations between HAHP and HALP students in English/language arts,
but not in math. While the results were expected for HAHP students in
English/language arts, the results were contrary to expectations for math. In
English/language arts, the differences between HAHP and HALP students were
significant (F (1, 108) = 16.62, p = 0.001). For math, no significant differences
between HAHP and HALP students were found in terms of performance-avoid goal
orientation (F (1, 108) = 0.50, p = 0.480). In English/language arts, HAHP students
were more likely to answer negatively to questions such as "It's important to me that I
don't look stupid in class," "One of my goals is to keep others from thinking I'm not
smart in class, " "It's important to me that my teacher doesn't think that I know less than
55
others in my class" and "One of my goals is to avoid looking like I have trouble doing
the work." The last finding indicates that HAHP students were less likely to be
motivated to avoid their teachers’ or peers' perceptions that they have trouble doing
their work. Implications for these findings will be discussed in detail in the next
chapter.
Research Question 3
How do HAHP and HALP students differ in terms of task values? The findings
on task value were completely contrary to expectations. The analysis of variance
revealed no significant differences between HAHP and HALP students in
English/language arts (F (1, 108) = 3.94, p = 0.050) or math (F (1, 108) = 0.37, p =
0.557). Apparently, task value was not a significant factor for HAHP and HALP
students in either subject.
Multiple Regression. The results of the multiple regression analysis revealed
that for high-ability high-performing (HAHP) students in English/language arts, the
entire model was significant (F = 5.118, df = 5, p = .000). The total variance explained
by the model was 22% (adjusted R
2
= .220). The significant independent variables
were mastery goal orientation and performance-avoid goal orientation. Performance-
approach, family orientation and task values were not significant. Table 5a shows the β,
t-test results and p-values reported for each of the variables.
56
Table 5a
Beta weights, t-values and p-values of HAHP students in English/language arts
β t p
Family
-0.111 -1.004 0.319
Mastery
0.319 2.755 0.008
Performance Approach
-0.022 -0.151 0.880
Performance Avoid
-0.36 -3.172 0.002
Task
0.296 1.907 0.061
For high-ability low-performing (HALP) students in English/language arts, the
entire model was significant (F = 5.029, df = 5, p = .001) and explained 34% of
variance in performance (adjusted R
2
= .341). Family orientation, performance-approach
and performance-avoid goal orientations emerged as significant variables. Mastery goal
orientation and task values were not significant in explaining variance in the dependent
variables. Table 5b shows the β, t-values and p-values reported for each of the
variables.
Table 5b
Beta weights, t-values and p-values of HALP students in English/language arts
β t p
Family
-0.569 -3.564 0.001
Mastery
-0.15 -1.056 0.298
Performance Approach
0.476 2.374 0.023
Performance Avoid
-0.365 -2.681 0.011
Task
0.147 0.792 0.434
The results of the multiple regression analysis demonstrated that the model was
not significant (F = 1.353, df = 5, p = .253) for high-ability high-performing (HAHP)
57
students in math. The model only explained approximately 2% (adjusted R
2
= .024) of
variance in performance. None of the independent variables were found to be
significant.
For high-ability low-performing (HALP) students in math, the whole model
accounted for approximately 2% of variance (adjusted R
2
= .019). Again, the model was
not significant (F = 1.152, df = 5, p = .353) in explaining performance in math.
Performance-avoid goal orientation emerged as the only significant factor predicting
math performance (β = 0.359, t = 2.167, p = 0.037). Family orientation, mastery goal
orientation, performance-approach and performance-avoid goal orientations were not
significant in predicting the dependent variables.
Differences between HALP and HAHP students in English/language arts. A
comparison of means showed that HAHP students scored significantly higher on the
family orientation scale (M = 4.61, SD =0.97) than HALP students in English/language
arts (M = 3.45, SD =0.98). HAHP students also scored significantly higher on the
performance-approach scale (M = 4.10, SD =1.01), than HALP students (M = 3.19, SD
=1.02). Finally, HAHP students scored significantly lower on the performance-avoid
scale (M = 3.52, SD =1.03) than HALP students (M = 4.63, SD =1.01). No significant
differences were found between HAHP and HALP students in terms of mastery goal
orientations and task values. The mean of the mastery goal orientation scale was M =
4.59 for HAHP students and M = 4.09 for HALP students. The mean of the task value
scale was M = 3.95 for HAHP students and M = 3.36 for HALP students. To reiterate,
there were differences between HAHP and HALP in terms of family orientation,
58
performance-approach and performance-avoid goal orientations, but few differences in
terms of mastery goal orientations or task values. Figure 3 shows the mean differences
between HAHP and HALP students in English/language arts.
Figure 3
Mean Differences Between HAHP and HALP Students in English/language arts
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
F amily
Mas tery
Performanc e-Approach
Performanc e Avoid
T as k Value
high ability-high
performance HAHP
high ability-low
performance HAL P
Differences between HAHP and HALP in math. A comparison of means showed
that HAHP students scored significantly higher on the family orientation scale and
mastery goal orientation scale than HALP students in math. The mean of the family
orientation scale for math was (M = 4.93, SD =0.69) for HAHP students and (M = 3.77,
SD =1.10) for HALP students. The mean of the mastery goal orientation scale was (M
=4.94, SD =0.64) for HAHP students and (M =3.12, SD =1.50) for HALP students.
Out of all of the comparisons of the means for HAHP and HALP students in both
59
English/language arts and math, the mastery goal orientation was the most significant
difference between HAHP and HALP students groups. Interestingly, HAHP and HALP
students were very similar in terms of performance-approach goal orientations,
performance-avoid goal orientations and task values. On the performance-approach
subscale, the mean for HAHP students was (M = 4.04, SD =1.09) as compared to
HALP students (M =4.20, SD =1.25). On the performance-avoid subscale, HAHP
students had a mean of (M =3.68, SD =1.09) and HALP students had a mean of (M =
3.89, SD = 1.17). Finally, on the task value scale, HAHP students had a mean of (M =
3.98, SD =1.05 and HALP students had a mean of (M = 4.14, SD =1.08). To restate,
there were significant differences in means between HAHP and HALP students in
terms of family orientation and mastery goal orientation, but few differences in terms of
performance (approach and avoid) goal orientations or task values. Figure 4 illustrates
mean differences between HAHP students and HALP students in math in terms of
family orientation, mastery goal orientation, performance-approach goal orientation,
performance-avoid goal orientation and task value.
60
Figure 4
Mean differences Between HAHP and HALP Students in Math
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
F amily
Mas tery
P eformanc e-A pproac h
P erformanc e-Avoid
T as k V alue
high ability-high
performance
high ability-low
performance
Analysis of Gender Differences. An analysis of gender did not yield any
significant results. Rather, the ANOVA analysis revealed that the means for males were
only slightly lower than females on all five scales (mastery goal orientation,
performance-approach goal orientation, performance-avoid goal orientation and task
value). On the family orientation subscale, males (M = 4.41, SD =1.14) were slightly
lower than females (M = 4.56, SD =0.90). The same holds true for males (M =4.28, SD
=1.18 and females (M = 4.66, SD =1.28) on mastery goal orientation, performance-
approach goal orientation (M = 3.81, SD =1.13 and M = 4.31, SD =1.13 respectively),
performance-avoid goal orientation (M = 3.65, SD = 1.00 and M = 3.77, SD =1.19
respectively), and task value (M = 3.78, SD =1.01 and M = 4.14, SD = 1.15
61
respectively). Figure 5 illustrates mean differences between males and females. No
significant differences were found between males and females on any of the variables.
Figure 5
Mean Differences by Gender
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
F amily Mastery Approach Avoid T ask
F emale
Male
Analysis of Differences in Ethnicity. The five major ethnic groups represented in
this study were Caucasian, Asian, Hispanic, African American and "Other".
Participants who did not identify with any ethnic backgrounds listed on the survey,
listed more than one ethnic background or chose not to disclose their ethnic
backgrounds were marked as "Other". The representation by ethnicity for all HAHP
and HALP students closely followed the school demographics, except for
representations for Asian and Caucasian students. Reporting by the California
Department of Education for 2006-2007 listed student enrollment by ethnicity as the
following: White (not Hispanic) = 38%, Asian = 38.4%, Hispanic or Latino = 11.5%,
62
African American = 2.9%, Filipino = 3.6%, Pacific Islander = 0.8% and American
Indian or Alaskan Native = 0.3%.
An analysis of means by ethnicity for HAHP and HALP students yielded
significant results. In terms of ethnicity, differences in means were found in the family
orientation, mastery goal orientation, and performance-approach goal orientation
subscales. No significant differences were found on the performance-avoid and task
value subscales. African Americans were excluded from the analysis because no
African American students participated in the study.
On the family orientation subscale Hispanic students (M = 5.06, SD =0.36)
scored higher than Caucasian students (M = 4.69, SD =1.00) and Asian students (M =
4.22, SD =1.10). On the mastery goal orientation subscale, Hispanic students (M =
4.80, SD =1.22) also scored higher than Caucasian students (M = 4.66, SD =0.93) and
Asian students (M = 4.24, SD =1.36). The most pronounced differences were on the
performance-approach goal orientation subscale with Hispanic students (M = 4.93, SD
=1.08) scoring a lot higher than Asian students (M = 3.99, SD =1.16) and Caucasian
students (M = 3.82, SD =1.12).
On the performance-avoid goal orientation and task value subscales, there were
no major differences between all three major ethnic groups. On the performance-avoid
goal orientation scale, Hispanic students (M = 3.83, SD = 0.92) were only slightly
higher than Caucasian students (M = 3.73, SD =1.25) and Asian students (M = 3.72,
SD =1.00). On the task value subscale, Asian students (M = 3.95, SD = 1.06) were only
63
slightly higher than Hispanic students (M = 3.85, SD =1.06) and Caucasian students (M
= 3.82, SD =1.16). Figure 6 shows the mean differences by ethnicity.
Figure 6
Mean Differences by Ethnicity
0.00
1.00
2.00
3.00
4.00
5.00
6.00
F amily Mastery Approach Avoid T ask
C aucasian
A sian
Hispanic
Summary of Research Findings
In summary, the purpose of this study was to examine how high-ability high-
performing (HAHP) students differed from high-ability low-performing (HALP)
students in terms of their family orientation, goal orientation (mastery, performance-
approach, and performance-avoid) and task values. The research questions for this
study were: 1) How do HAHP and HALP students differ in terms of family orientation?
2) How do HAHP and HALP students differ in terms of mastery, performance-
approach, and performance-avoid goal orientation? 3) How do HAHP and HALP
students differ in terms of task values? The following statistical analyses were
conducted for this study.
64
a) Intercorrelations of family orientation, mastery goal orientations,
performance-approach goal orientation, performance-avoid goal orientation and
task values.
b) Means and standard deviations of family orientation, goal orientations, and
task values, with raw data of ability (CST scores) and performance (grades) in
English/language arts and math.
c) Internal consistency reliability (Cronbach’s alpha) for scores on survey items
using scales in family orientation, goal orientations and task values.
d) Independent samples and T-tests to compare the means and standard
deviations between groups. In addition, one-way analyses of variance
(ANOVA) were used to find groups statistics and equality of means between
high-ability high- performing (HAHP) and high-ability low-performing (HALP)
students in relation to family orientation, goal orientations and task values.
e) Multiple regression analysis to determine the variance accounted for by each
of the five variables.
A brief summary of significant findings is presented next.
Intercorrelations. The correlational analysis revealed three significant
correlations. First, family-orientation had a positive relationship with performance-
avoid goal orientation. Next, mastery goal orientation and performance-avoid goal
orientation were positively correlated. Finally, there was a positive relationship
between performance-approach goal orientations and performance-avoid goal
65
orientations. It appears that a common theme among high-ability students was to avoid
appearing that they struggled in their classes or with specific academic tasks.
Descriptive Statistics. Not only were there more high-ability students in
English/language arts than math, but there were also more high-performing students in
English/language arts than math as indicated by average grade. In addition, there
appeared to be a greater disparity in grades between HAHP and HALP math students
than HAHP and HALP English/language arts students.
Analysis of Variance. As expected, HAHP students were more likely to be
motivated to do well in school in order to please or assist their family members than
HALP students. Between HAHP and HALP students in math, the one-way analysis
revealed statistical differences in mastery goal orientation. However, for
English/language arts, no significant differences were found. The analysis of variance
also revealed that with regards to performance-approach goal orientations, HAHP and
HALP students also differed between subjects. This time, significant differences were
found between HAHP and HALP students in English/language arts, but not in math.
Next, the one-way ANOVA showed significant differences in performance-avoid goal
orientations between HAHP and HALP students in English/language arts, but not in
math. Finally, in terms of task value, the analysis of variance revealed no significant
differences between HAHP and HALP students in English/language arts or math.
Multiple regression analysis. A multiple regression analysis revealed that for
HAHP students in English/language arts, the total variance explained by the model was
22% (R
2
= .220). The significant independent variables were mastery goal orientation
66
and performance-avoid goal orientation. For HALP students in English/language arts,
the total variance explained by the model was 34% (R
2
= .341). The significant
independent variables were family orientation, performance-approach, and
performance-avoid goal orientations. For HAHP students in math, the total variance
explained by the model was 2% (R
2
= .024) which was not significant. Furthermore,
none of the independent variables were significant. Finally, for HALP students in math,
the total variance explained by the model was 2% (R
2
= .019) (not significant). The
only significant independent variable was performance avoid.
Differences between HALP and HAHP in English/language arts. The results
from a comparison of means showed that in English/language arts, HAHP students
scored significantly higher on the family orientation scale and the performance-
approach subscale than HALP students. HAHP students also scored significantly lower
on the performance-avoid scale than HALP students. These findings suggested that
HAHP students were more likely to be motivated to do well in school in order to please
or assist their family members, more motivated to show others that they are good at
their work or to appear "smart" in comparison to their peers, and less likely to be
motivated to avoid their teachers’ or peers' perceptions they have trouble doing their
work.
Differences between HALP and HAHP in math. The comparison of means
analysis also revealed that HAHP students scored significantly higher on the family
orientation scale than HALP students in math. HAHP students also scored significantly
higher than HALP students did on the mastery goal orientation scale. These findings
67
suggested that HAHP students in math were also more likely to be motivated to do well
in school in order to please or assist their family members. They were also more
motivated to master the material for intrinsic reasons. Table 6 shows a summary of
statistically significant variables for English/language arts and Math.
Table 6
Summary of Statistical Significance Across Variable and Subject
Subject
Variable
English/language
arts Math
Family Orientation
Statistically
Significant
Statistically
Significant
Mastery-Goal Orientation X
Statistically
Significant
Performance-Approach Goal
Orientation
Statistically
Significant X
Performance-Avoid Goal
Orientation
Statistically
Significant X
Task Value X X
Note: X = Not Statistically Significant
Analysis of Gender Differences. An analysis of gender did not yield any
significant results. Rather, the ANOVA analysis revealed that the means for males were
slightly lower than females on the family orientation scale, mastery goal orientation,
performance approach-goal orientation, performance-avoid goal orientation and task
value subscales.
Analysis of Differences in Ethnicity. In terms of ethnicity, differences in means
were found in the family orientations, mastery goal orientation, and performance-
approach goal orientation subscales. No significant differences were found on the
performance-avoid and task value subscales. African Americans were excluded from
68
the analysis because no African American students participated in the study. On the
family orientation subscale Hispanic students scored higher than Caucasian students
and Asian students. On the mastery goal orientation subscale, Hispanic students also
scored higher than Caucasian students and Asian students. Finally, on the performance-
approached goal orientation subscale Hispanic students scored a lot higher than Asian
students and Caucasian students. No major differences were found across the ethnic
groups on the performance-avoid goal orientation and task value subscales. This
implies that in comparison to Caucasian and Asian students, Hispanic students were
more likely to be motivated to do well in school in order to please or assist their family
members, more likely to be intrinsically motivated to learn the material, and more
likely to be motivated to appear "smart' in comparison to their classmates or show
others that they were good at their work.
The next chapter discusses the implications of significant findings in this study.
Chapter 5 also includes a description of the limitations of this study as well as next
steps for future research with implications for policy and practice regarding how to
assist high-ability low-performing (HALP) students.
69
CHAPTER 5
DISCUSSION
This chapter begins with an overview and intent of the study followed by a brief
restatement of the three research questions. This chapter also presents a review of the
findings from each of the main variables from the current investigation, followed by a
discussion of conclusions about high-ability low-performing (HALP) students. The
chapter also includes a description of the limitations of this study as well as steps for
future research. Finally, this chapter concludes with implications for policy and practice
regarding how to assist HALP students.
Overview and Intent of the Study
This study was based on previous work by Payne (2006), which brought light to
the problems of a unique group of students with high academic potential and ability, but
low performance rates in the classroom, also known as high-ability low-performing
(HALP) students. While closing educational gaps of low-achieving students has been a
primary focus in educational research and policy, little information is known about
high-ability students who do not do well in school. As a result, high-ability low-
performing students are often overlooked as a group because they do not share the same
features as low-ability low-achieving students. Even among high-achieving students,
there are substantial within-group differences. Although it seems that high-achieving
students are a homogenous group, there are substantial variations in reasons for
achieving. High-ability students may generally achieve at high levels, but their reasons
for achieving vary greatly (Ablard, 2002). Reasons for achieving are thereby translated
70
as motivation. These observations have led to the assumption that motivation to
succeed plays a significant part in HAHP students' ability to succeed.
The purpose of this study was to investigate the motivational differences
between high-ability high-performing (HAHP) and high-ability low-performing
(HALP) students. HAHP students were defined in this study as students who scored in
the Advanced or Proficient levels on the California Standards Test (CST) in
English/language arts or math and received high grades (A or B) in English/language
arts or math classes. In addition, HALP students were identified as those who scored in
the Advanced or Proficient levels on the CST, but received low grades (C, D, or F) in
English/language arts or math.
One motivational variable that has been well researched in the literature is
achievement goals or goal orientation. Over the past two decades, achievement goals
have become an important framework in studying academic motivation among students
(Bouffard & Couture, 2003). According to Ames (1992), an achievement goal is an
integrated pattern of beliefs, attributions, and affect that produces the intentions of
behavior that is represented by different ways of approaching, engaging in, and
responding to achievement-type activities. The three different types of goal orientations
researched in this study are: (1) mastery goal orientation, (2) performance-approach
goal orientation, and (3) performance-avoid goal orientation. Mastery-oriented learners
place an emphasis on acquiring new skills and knowledge (Grant & Dweck, 2003;
Payne, 2006). Performance-approach learners are motivated by outperforming others
and appearing competent to their peers, while performance-avoidance learners avoid
71
the demonstration of lack of ability (Midgley et al., 2001). Among high-performing
students, the motivational tendencies are that high-performing students are higher on
the mastery goal orientation and performance-approach goal orientation scales than
low-performing students. In addition, high-performing students are lower on the
performance-avoidance scale than low-performing students. These findings guide the
research questions and research hypotheses for this study.
Another motivational variable that has gained attention in the literature is task
values. Task values are one aspect of the expectancy-value theory and involve students’
beliefs about their ability to perform a future task (Pintrich & DeGroot, 1990). More
specifically, task values involve students’ beliefs about the importance of the task or
importance of attaining a goal (Eccles & Wigfield, 1995) and their interest of the task
(Pintrich & DeGroot, 1990). Task values also include students’ incentives for engaging
in academic activities, which includes perceived importance, usefulness and interest
(Wigfield & Eccles, 1995). For high-performing students, one assumption is that they
perceive tasks to be more important, useful, and interesting to them than low-
performing students. This aspect of motivation lends to the notion that high-performing
students are more likely to excel because they perceive their classes to be more
valuable in terms of importance and usefulness to their future than their lower-
performing counterparts. These assumptions led to the hypothesis that high-performing
students have a higher task value for their courses than low-performing students.
Finally, one motivational theory that has recently emerged in the literature is
family orientation. Simply stated, family orientation involves the motivation to do well
72
in school in order to please or assist one's family members. The family dimension
differs from goal orientation and task value because it focuses on external reasons for
achieving. Nevertheless, family orientation deals with individual perceptions and a
personal sense of obligation, which then becomes an internal motivational factor. Urdan
(2004) hypothesized that immigrant students, mostly from Asian and Latin American
cultures tend to have stronger senses of obligation to care for their family members in
comparison to students born in the U.S. Based on this theory, Urdan (2004) found that
participants with a stronger sense of obligation to care for their family reported strong
pursuit of performance-approach goals, whereas those with weaker family orientations
were higher in performance-avoidance goals. These finding led to the hypothesis that
HAHP students exhibit higher family orientations than HALP students.
Research Questions
To restate, the primary research question for this study is “Which combinations
of motivational factors differentiate high-ability high-performing (HAHP) students
from high-ability low-performing (HALP) students”? To summarize, the three main
research questions are:
1. How do HAHP and HALP students differ in terms of family orientation?
2. How do HAHP and HALP students differ in terms of mastery, performance-
approach, and performance-avoid goal orientation?
3. How do HAHP and HALP students differ in terms of task values?
73
A discussion of the research findings in this study will begin with the
hypotheses generated by findings in the literature review and the conclusions based on
the findings of this study.
Family Orientation Findings
Research question 1: How do HAHP and HALP students differ in terms of family
orientation?
First, it was hypothesized that HAHP students would exhibit higher family
orientations than HALP students. Conversely, HALP students would exhibit a lower
family orientation than HAHP students. Both of these findings are true, based on the
statistical analyses in this study.
This conclusion indicates that HAHP students are more likely to be motivated to
do well in school in order to please or assist their family members than HALP students.
Some of the specific subjects within the family orientation scale are the motivation to
please one's parents or siblings, the motivation to bring honor to one's family, and the
motivation for parents' guardians to be proud of one's school achievement. Another
related topic is the motivation to be better prepared to take care of one's family in the
future, whether it be making financial contributions to the family or taking on some
family responsibilities.
One factor that may have contributed to this finding is the disproportionately
high numbers of Asian students that are represented in the sample. Reporting by the
California Department of Education for 2006-2007 listed student enrollment by
ethnicity as the following: The 2006-2007 White (not Hispanic) = 38%, Asian n =
74
38.4%, Hispanic or Latino = 11.5%, African-American n = 2.9%, Filipino = 3.6%,
Pacific Islander = 0.8% and American Indian or Alaskan Native = 0.3%. In this study,
there were higher percentages of Asian students than Caucasian students.
Approximately 52% of the students are Asian, 35% are Caucasian, 7% are Hispanic,
0% are African American and approximately 6% identify with "Other" ethnicities. It is
important to focus on ethnicity in this case because Urdan (2004) found that immigrant
students, mostly from Asian and Latin American cultures tend to have stronger senses
of obligation to care for their family members in comparison to students born in the
U.S. The fact that approximately 59% of the sample consisted of Asian and Hispanic
students may have influenced the findings regarding the family orientation subscale.
The implication for this finding is that students who have a high sense of
motivation to get good grades in order to please or assist family members seem to
perform better in classes than students who have a low sense of family orientation. This
suggests that sense of connectedness to family members as well as the desire to please
them or contribute to their future may play a role in student achievement.
Since Urdan (2004) found that immigrant students tend to have stronger senses
of obligation to care for their family members in comparison to students born in the
U.S, more studies are needed to further differentiate between first, second and 1.5
generation immigrants in relation to family orientation and achievement. In addition,
more research is needed to investigate whether the effects of family orientation on
school performance increase or decrease depending on level of acculturation of students
from collectivist cultures.
75
Goal Orientation Findings
Research question 2: How do HAHP and HALP students differ in terms of mastery,
performance-approach, and performance-avoid goal orientation?
Next, it was hypothesized that HAHP students would exhibit a higher mastery
goal orientation than HALP students. Conversely, HALP students would exhibit a
lower mastery goal orientation than HAHP students. The analysis revealed significant
differences on the mastery goal orientation scale between HAHP and HALP student in
math, but no significant differences were found in English/language arts. This finding
supports hypothesis 2 as partially true because the significance differs between
subjects.
One reason HAHP students may have exhibited a significantly higher mastery
goal orientation than HALP students in math, but not English/language arts is because
students are only required to enroll in 2 years of math as opposed to 4 years of
English/language arts classes to graduate. For example, students are required to enroll
in an English/language arts course each quarter and semester they are enrolled in
school. However, they are not required to enroll in a math class each semester. Students
are only required to enroll in 20 units of math classes, which is equivalent to 2 years, as
opposed to 40 units of English/language arts classes, which is the equivalent to 4 years.
Since they are not required to take math classes every semester, it is proposed that
students who decide to enroll in math classes beyond what is required to graduate are
doing so because 1) they are interested in learning or mastering math concepts, or 2)
they are pursuing higher level math classes in order to enhance their future or prepare
76
for post-secondary education. The mastery goal orientation theory supports the first
reason, which proposes that students choose to enroll in math classes beyond what is
required to graduate because they are interested in learning and mastering math
concepts.
In terms of performance goal orientations, it was proposed that HAHP students
would exhibit a higher performance-approach goal orientation than HALP students.
Conversely, HALP students would exhibit a lower performance-approach goal
orientation than HAHP students. This time, significant differences between HAHP and
HALP students were found in English/language arts, but not in math. This finding
supports hypothesis 3 as partially true because the significance differs between
subjects.
While the mastery goal orientation mentioned in hypothesis 2 focuses on
intrinsic motivation, the performance goal orientation focuses more on extrinsic reasons
for learning. Payne (2006) found that although the positive effects of mastery goals are
rarely questioned, performance goals tend to be more controversial with respect to
adaptive learning behaviors because performance-approach learners typically place
importance on validating the self or comparing one’s ability to others (Bouffard &
Couture, 2003; Midgley, et al., 1997; Elliot & McGregor, 2001). This finding suggests
that HAHP students were more likely to be motivated by showing others that they are
good at their work, by the desire to appear "smart" in comparison to their peers.
One possible explanation that performance-approach goals were found to be a
significant difference among HAHP students and HALP students in English/language
77
arts, but not math is due to gender differences. Earlier in the study, an analysis of
gender did not yield any significant results. Rather, the ANOVA analysis revealed that
the means for males were slightly lower than females on all 5 subscales including the
performance-approach subscale. In other words, when controlling for gender, there
were no statistical differences between HAHP and HALP males and females.
In terms of performance-goal orientations, it was hypothesized that students
would exhibit a lower performance-avoid goal orientation than HALP students.
Conversely, HALP students would exhibit a higher performance-avoid goal orientation
than HAHP students. Again, significant differences on the performance-avoid goal
orientation scale were found between HAHP and HALP student in English/language
arts, but no significant differences were found in math. Once more, this finding
supports hypothesis 4 as partially true because the significance differs between
subjects.
Among the three goal structures presented in this study, the performance-avoid
goal structure represents the most maladaptive orientation (Payne, 2006). While
performance goals for the performance-approach orientation can be conceptualized as
an active effort (e.g., aiming for the best possible grade and outperforming others), the
performance-avoid orientation can be conceptualized as a more passive effort (e.g.,
aiming to avoid failure by expending the least amount of effort necessary) (Payne,
2006). In addition, as performance-approach learners are preoccupied with appearing
competent, performance-avoid learners are preoccupied with not appearing incompetent
(Payne, 2006). The last finding indicates that HALP students were more likely to be
78
motivated to avoid their teachers’ or peers' perceptions they have trouble doing their
work. Additional maladaptive behaviors that (HALP) students may be more prone to
exhibit are task avoidance, negative affect, and decreased persistence, all leading to
diminished performance (e.g., a lower academic GPA) (Payne, 2006). The implication
for this conclusion is that lower-performing students are more prone to avoiding tasks
that would make them appear incompetent or "stupid". They may thereby avoid tasks
that would threaten to expose their weaknesses or inadequacies.
One possible reason that differences between HAHP and HALP students were
statistically significant on the performance-avoidance scale for English/language arts,
but not math is the level of difficulty of math classes. Since math is typically viewed as
a more difficult subject to master for some students, students who do not do well in
math may attribute their failure to the fact that the subject matter is challenging. On the
opposite side of the coin, if students perceive English/language arts classes as less
challenging, they may be more likely to avoid perceptions they have trouble doing their
work in order to preserve their self-concept.
Another possible reason why differences in performance-avoid orientations
were significant for English/language arts classes, but not math classes is the
motivation for second-language learners to avoid appearing that they struggle with the
language. For example, it is possible that students who do not speak English as a first
language do not want to appear that they struggle with the language. Therefore, they
may try to avoid tasks, such as reading aloud in class, which would further distinguish
79
them as being second-language speakers. More research is needed regarding second-
language learners in regards to performance-avoid orientations for English classes.
Task Value Findings
Research questions 3: How do HAHP and HALP students differ in terms of task
values?
At the beginning of this study, it was hypothesized that HAHP students would exhibit a
higher task value than HALP students for English/language arts or math classes.
Conversely, HALP students would have a lower task value for English/language arts or
math classes. However, the hypotheses were not found to be true in this study. There
were no significant differences on the task value scale between HAHP and HALP
students in either English/language arts or math. This finding fails to confirm
hypothesis 5.
The task value theory involves students’ goals for the task and their beliefs
about the importance and interest of the task (Pintrich & DeGroot, 1990). The four
major components of task values are: 1) attainment value, 2) intrinsic value (or
interest), utility value, and cost (Eccles & Wigfield, 1995). Task values differ across
different domains. For example, Eccles and Wigfield (1995) state that individuals will
find different domains such as mathematics versus English as more or less personally
interesting or valued. As a matter of personal preference, task values will vary by
student. For example, one student may choose to enroll in a challenging math class
because it will prepare them to take college-level math classes at a university. Other
80
students may prefer a certain English course based on their personal interest in the
subject.
One possible explanation why task value didn't seem to have any significant
effect on HAHP and HALP students in either subject is because there are a variety of
English/language arts and math classes to suit the needs and interests of each individual
student. Apart from elective English/language arts in speech, journalism and creative
writing, the high school offers a wide variety of English/language arts courses to suit
different tastes. For example, there are 8 unique English/language arts courses that
students can select, with course listing names like, "the literary hero," "the American
dream" and "fantasy and fiction". Since students are offered a variety of unique options
and given the freedom to enroll in whichever class they desire, most students are likely
to find a class that suits their individual interests. The same holds true for math classes.
If students were given limited choices in which to choose their classes or not if they
were not granted the freedom to choose for themselves, there would likely be lower
rates of task value because they would most likely perceive the courses to be less
interesting.
In terms of usefulness, another possible reason no significant differences were
found in task value between HAHP and HALP student in either English/language arts
or math is that high-ability students may perceive that doing well in their classes will
help them to do well in the future. This is especially true for students who are enrolled
in Honors and Advanced Placement courses in which there is a direct link to future
81
college placement. Therefore, high-ability students would have relatively high utility
value for their classes as they are linked to future success.
Ethnicity Findings
Several of the finding on ethnicity yielded unexpected results. Originally, it was
thought that Asian and Hispanic students would exhibit a higher family orientation than
Caucasian and African American students as well as students from "Other" ethnicities.
However, the most astonishing outcome was that Asian students were the least family -
oriented when compared to Hispanic and Caucasian students. It is very surprising that
Asian students scored significantly lower than the other two groups because Asian
cultures tend to be more toward the collectivist side rather than the individualistic side
of the individualist-collectivist spectrum. One possible explanation for this finding is
that there are varying degrees of acculturation that may play a role in family
orientation. Urdan’s (2004) conclusions that immigrant students, mostly from Asian
and Latin American cultures tend to have stronger senses of obligation to care for their
family members in comparison to students born in the U.S. could mean that immigrant
(first generation) Asian and Hispanic students have stronger senses of family obligation
when compared to second, third or higher generation Asian and Hispanic students.
There is little research on differences in ethnicity in terms of goal orientations.
Therefore, the research in this study contributes to some insights into possible
differences, which may exist. For example, in this study, Asian students were found to
be lower than both Caucasian and Hispanic students in term of mastery goal
orientation, and significantly lower on the performance-approach orientation scale than
82
Hispanic students. On the mastery goal orientation scale, Caucasian students were also
higher than Asian students, but lower than Hispanic students. On the performance-
approach scale, Caucasian students scored the lowest among the Hispanic and Asian
students and significantly lower than Hispanic students. On the performance-avoid and
task value scales, Asian, Caucasian and Hispanic students all had similar means.
Hispanic students tended to be higher on any other ethnic group in terms of
performance-approach goal orientations. This implies that in comparison to Caucasian
and Asian students, Hispanic students are more likely to be motivated to do well in
school in order to please or assist their family members, and more likely to be
motivated to appear "smart' in comparison to their classmates, or show others that they
are good at their work than any other ethnic group.
Overall, Hispanic students tended to stand out the most among all ethnic groups
in this study. One reason for the skewed findings on Hispanic students may be the
relatively small sample size of Hispanic students. In terms of grouping by ethnicity,
approximately 52% of the students in the study were Asian 35% were Caucasian 7%
were Hispanic. With a total on 12 students who identified themselves as Hispanic, the
relatively small sample size of Hispanic students may or not play a role in the outcomes
of this study. In an ideal study, proportionate numbers of students representing all
ethnicities would have probably yielded different results. Clearly, more research is
needed regarding the different ethnicities as well as the how different generations and
levels of acculturation affect each variable.
83
HALP Student Conclusions
Although far from a complete motivational profile, the results of this study have
pointed to several key findings. The evidence reveals that high-ability low-performing
(HALP) students lack the motivational assets that high-ability high-performing (HAHP)
students possess (Payne, 2006). First, when compared to HAHP students, HALP
students are less likely to be motivated to do well in school in order to please or assist
their family members. The motivation to do well in school in order to please or assist
one's family is a newer construct in the study of motivation. While most students aim to
please their family members to some degree, it appears that HALP students do not
connect their academic achievement to their sense of pride from their family members
as much as HAHP students do. Neither do they connect academic achievement with
their sense of obligation to assist their family members in the future. It is possible that
HALP students seek other avenues such as athletics, performing arts, or other talents on
which to base their sense of pride and accomplishment to their families.
Second, HALP students exhibit lower mastery goal orientations and lower
performance-approach goals, which suggests they are more motivated to excel
academically for extrinsic purposes rather than intrinsic purposes. With a stronger focus
on getting good grades, HAHP students may limit themselves by avoiding challenging
tasks, whereas mastery-oriented students would be more likely to pursue them. HALP
students may choose less challenging assignments that increase their chances of getting
good grades rather than engage in more challenging assignments altogether. Taken a
step further, HALP students may even base their course selection on classes that they
84
perceive to be "easier" or pick teachers who have a reputation for being more lenient on
grading.
Socially, HALP students are more preoccupied with social goals and social
comparisons. It is extremely important for HALP students to be perceived as competent
to their peers. In terms of performance-approach goals, they may make a concentrated
effort to let others know that they are good at their work in order to preserve their sense
of social competitiveness. Since they have higher academic abilities, they may be more
concerned with comparing grades on assignments, tests, and quizzes with their lower-
ability peers. In terms of performance-avoidance goals, HALP students may be less
likely to seek help or assistance from the teacher or their peers because seeking help is
a sign that they are struggling with a particular subject.
HALP students are unique in that they have the capabilities to be high
achievers, but they receive lower grades when compared to other high-ability, high-
performing students. In the same sense, HALP students have higher abilities than low-
ability students, which places them above the lower achievers. Their academic
placement then becomes somewhere in the middle between high-ability high-
performers and low-ability students. There are two possible outcomes related to the
sense of "being in the middle". First, HALP students may strive toward being identified
as high-ability high-achieving students by choosing tasks and courses that increase their
chances of getting good grades, thereby elevating their status. Secondly, they may
engage in maladaptive behaviors and try to "hide" or cover-up the fact that they are
struggling in their classes or go so far as to adopt self-handicapping measures to make it
85
appear as if they could get good grades "if they really wanted to". The self-
handicapping technique would make HALP students appear fully capable of earning
good grades, but for some reason (internal or external), they sabotage themselves by
choosing not to follow-through with tasks that would help them get good grades.
In short, HALP students generally exhibit lower levels of family orientation,
lower mastery goal orientations, lower performance-approach orientations and higher
performance-avoid goal orientations that their high-ability high-performing peers.
Although Payne (2006) conducted his research among middle school students,
the findings on mastery goal orientations in this study are consistent with Payne's
(2006) findings. That is, HALP students tend to be less mastery oriented than HAHP
students. Another consistent finding between the two studies is no differences were
found between HALP and HAHP students in terms of task values. It appears HAHP
and HALP students have similar task values. One final similarity between research
findings is that Payne (2006) found that HALP students are more performance-avoid
oriented than HAHP students. This study found the same to be true for the
performance-avoid goal orientation.
One difference between conclusions is that Payne (2006) did not find any
significant differences between HAHP and HALP students in terms of performance-
approach goal orientation. This study found that there are significant differences
between HAHP and HALP students in English/language arts, but not math.
Specifically, HALP students had lower performance-approach goal orientations than
HAHP students. While the findings on mastery goal orientations, task values and
86
performance-avoid goal orientations were consistent, more research is needed to
substantiate these findings. In addition, more research in needed in regards to
performance-approach goals.
Limitations of the Study
One limitation of the study was the criteria used to classify students as HAHP
or HALP students. The original intent of this study was to identify HAHP students as
students who only scored in the "Advanced" levels on the CST. However, after a
preliminary analysis, there were too few students (n =12) to yield any significant
results. Therefore, the criteria to identify HAHP students were expanded to also include
students who scored in the "Proficient" levels of the CST. The same holds true for the
criteria distinguishing high and low performance. The original intent was to classify
high-performing students as those who received an A or B in their classes, and low-
performing students as those who received a D or F in their classes. Again, the criteria
were altered to include more students in the low-performing group, which later resulted
in including students who received a C (average) grade in their class as a low-
performing student. Since the inclusion criteria for both high-ability and high-
performance were expanded to include as many students as possible, there may not be
as "pure" as sample as originally intended.
Another limitation of this study is the weak alpha ratings for reliability for the
family orientation, mastery goal orientation, performance-approach goal orientation,
performance-avoid goal orientation and task value subscales. Reliability ratings ranged
from α = .70 to α = .76 indicating acceptable, but not outstanding levels of reliability.
87
The questions used on is this study were derived from Family Orientation Scale (Urdan,
2004), the Patterns of Adaptive Learning Strategies (P.A.L.S), Midgley et al. (2000)
and the Motivated Strategies for Learning Questionnaire (MLSQ), Pintrich et al.
(1991). With a total of 4-5 questions for each subscale, the study may not have included
enough questions to establish higher reliability ratings. In addition, two items
(questions 21 and 23) were thrown out in order to increase reliability on the mastery
goal orientation and performance-avoid goal orientation subscales from α = .69 to α =
.76 for both scales.
Next Steps on Future Research
The field of research on high-ability low-performing students is in its early
stages. Though it is difficult to approximate, past research has estimated that
approximately 20-50 percent of high ability students in the U.S. were reported to
underachieve academically (Ford, Alber & Heward, 1998). Oftentimes, high-ability
low-performing students are overlooked as a group because they do not share the same
features as low-ability low-achieving students. Therefore, it is important to invest time
and effort into identifying, understanding, and assisting this unique group of learners.
Additional research is needed to investigate the social, cultural, school, family, and
individual factors influencing high-ability low-performing students.
Among the multiple variables examined in this study, very little is known about
the effects of family orientation on achievement of high-ability low-performing
students. From a cross-cultural perspective, one possible avenue for further research is
to examine the differences between first, second and later generations of students from
88
immigrant families to see whether or not the effects of family orientation on school
performance increase or decrease depending on level of acculturation of students.
Future research should also include students from underrepresented ethnic and cultural
backgrounds not mentioned in this study.
This study attempted to explain differences across subjects in English/language
arts and math. Suggestions for future research would include motivational profile
comparisons of HALP and HAHP students across different subjects and across different
grades like elementary, high school, and university settings. Longitudinal studies would
be beneficial to examine changes that occur during various developmental periods. By
better understanding the issues affecting high-ability low-performing students, parents,
educators, school administrators and counselors can work together to develop strategies
and programs to help high-ability low-performing students succeed.
Implications for Policy and Practice: How to assist HALP students
Looking at the big picture, helping HALP students achieve their highest
potential has several benefits. First, successful HALP students would be better prepared
for the future when they are able to achieve at levels that match their abilities. In
addition, they would be better prepared for college and higher learning opportunities.
Second, successful HALP students would be less likely to suffer from boredom or
frustration at school, which may eventually lead to fewer anti-social behaviors, such as
truancy or delinquency. Third, successful HALP students would seek to understand and
master the material for intrinsic purposes rather than being concerned about how they
are being compared to their peers. Fourth, successful HALP students would be able to
89
choose challenging tasks and classes that optimize their academic capabilities rather
than choosing less challenging tasks in order to get a good grade. Fifth, successful
HALP students would be more willing to exhibit help-seeking behaviors without the
fear of appear incompetent or "dumb". Sixth, successful HALP would be less likely to
revert to maladaptive behaviors such as task avoidance, learned helplessness and
disruption of the learning program (Payne, 2006).
Policy makers, school administrators, and educators should take the following
steps to assist HALP students in achieving their academic potential:
1) To support HALP students in choosing challenging tasks and classes that
optimize their academic capabilities rather than choosing less challenging tasks to
increase the chances of getting good grades, allow students to create and design
their own learning projects and allow them to base part of their grade on their own
self-evaluation of the amount of effort they put into the project.
2) To help HALP students to emphasize effort rather than ability in performance,
give students feedback based on specific ways that they can improve rather than
general statements regarding ability.
3) To aid HALP students with seeking to understand and master the material for
intrinsic purposes, develop curriculum that emphasizes individual mastery and
improving skills rather than basing the curriculum solely on performance measures
such as grades.
90
4) To help HALP students focus less on performance and more on individual
mastery, create learning activities that engage learners in deeper level thinking
skills and are relevant and meaningful to students (Payne, 2006).
5) To create supportive and safe environments for students to seek help from
teachers or peers, develop one-on-one tutoring partnerships where students take
turns assisting their peers in subjects in which they feel competent.
Implementing these strategies requires all participants (policy makers,
administrators, educators, parents and students) work in conjunction with one another
to help HAHP students succeed. Assisting HALP students reach their academic
potential is in the best interest of the student, family, community and overall society.
91
References
Ablard, K.E. (2002). Achievement goals and implicit theories of intelligence among
academically talented students. Journal of the Education of the Gifted, 25(3),
215-232.
Ames, C. (1992). Classroom goals, structures, and student motivation. Journal of
Educational Psychology, 84, 261-271.
Baldwin, C.A. & Coleman, C.L. (2000, April) Achievement goal orientation:
Instructional practices and teacher perceptions of gifted and/or academically
talented students. Paper presented at the Annual Meeting of the American
Educational Research Association, New Orleans, LA.
Berndt, T.J. & Miller, K. E. (1990). Expectancies, values and achievement in junior
high school. Journal of Educational Psychology, 82(2), 319-326.
Bong, M. (1999, August). Role of self-efficacy and task-value in predicting college
students’ course performance and future enrollment intentions. Paper presented
at the Annual Convention of the American Psychological Association, Boston,
MA.
Bong, M. (2001). Between-and within-domain relations of academic motivation among
middle and high school students: Self-efficacy, task value, and achievement
goals. Journal of Educational Psychology, 93(1), 23-34.
Bouffard, T., & Couture, N. (2003). Motivational profile and academic achievement
among students enrolled in different schooling tracks, Educational Studies, 29,
19-38.
Clark, R.E. & Estes, F. (2002). Turning Research into Results: A guide to selecting the
right performance solutions. Atlanta, GA: CEP Press.
Cohen, R. & Kosler, J. (1991). Gender equity in high school math: A study of female
participation and achievement. ERIC Document Reproduction Service No. ED
345935.
Deslandes, R., Royer, E. Turcotte, D. & Bertrand, R. (1997). School achievement at the
secondary level: Influence of parenting style and parent involvement in
schooling. McGill Journal of Education, 32, 191-207.
92
Dowson, M., & McInerney, D. M. (2003). What do students say about their
motivational goals?: Towards a more complex and dynamic perspective on
student motivation. Contemporary Educational Psychology 28, 91-113.
Eccles, J.S. (1983). Expectancies, values and academic behaviors. In J.T. Spence (Ed.),
Achievement and achievement motives (p. 75-146). San Francisco: Freeman.
Elliott, E. S., & McGregor, (2001). A 2 X 2 achievement goal framework. Journal of
Personality and Social Psychology, 80, 501-519.
Eccles, J.S. & Wigfield, A. (1995). In the mind of the actor: The structure of
adolescents’ achievement task values and expectancy-related beliefs.
Personality and Social Psychology Bulletin, 21(3), 215-225.
Ford, D., Alber, S.& Heward, W. (1998). Setting “motivational traps” for
underachieving gifted students. Gifted Child Today Magazine, 21(2), 28-30.
Ford, D. & Thomas, A. (1997). Underachievement among gifted minority students:
Problems and promises. ERIC Document Reproduction Service No. ED
409660.
George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and
reference. 11.0 update (4th ed.). Boston: Allyn & Bacon.
Grant, H., & Dweck, C. S. (2003). Clarifying achievement goals and their impact.
Journal of Personality and Social Psychology, 85, 541-553.
Hebert, T.P. (1998). Gifted Black males in an Urban High School: Factors that
influence achievement and underachievement. Journal of the Education of the
Gifted, 21(4), 385-414.
Hebert, T.P. (2001). “If I had a new notebook, I know things would change”: Bright
underachieving you men in urban classrooms. Gifted Child Quarterly, 45(3),
174-194.
Hoekman, K., McCormick, J, & Gross, M. (1999). The Optimal context for gifted
students: A preliminary exploration of motivation and affective considerations.
Gifted Child Quarterly, 43(4), 170- 187
Hoover-Schultz, B. (2005). Gifted underachievement: Oxymoron or educational
enigma? Gifted Child Today, 28(2), 46-50.
93
McCoach, D.B., & Siegle, D. (2003). Factors that differentiate underachieving gifted
students from high-achieving gifted students. Gifted Child Quarterly, 47(2),
144-153.
Middleton, M.J. & Midgley, C. (1997). Avoiding the demonstration of lack of ability:
An underexplored aspect of goal theory. Journal of Educational Psychology,
89(4), 710-718.
Midgley, C., Arunkumar, R. & Urdan, T.C. (1996). “If I don’t do well tomorrow,
there’s a reason”: Predictors of adolescents’ use of academic self-handicapping
strategies. Journal of Educational Psychology, 88(3), 423-434.
Midgley, C., Kaplan, A., & Middleton, M. (2001). Performance-approach goals: Good
for what, for whom, under what circumstances, and at what cost? Journal of
Educational Psychology, 93(1), 77-86.
Midgley, C., Maehr, M.L., Hruda, L.Z., Anderman, E., Anderman, L. et al. (2000).
Manual for the patterns of adaptive learning strategies. University of Michigan.
Ann Arbor: MI.
Neumeister, K.L.S. & Hebert, T. (2003). Underachievement versus selective
achievement: Delving deeper and discovering the difference. Journal for the
Education of the Gifted, 26(3), 221-238.
Payne, S. (2006). Comparing the motivational profiles of high-ability-low performing
(HALP) students and high-ability-high-performing (HAHP) students. Doctoral
dissertation, University of Southern California.
Pintrich, P.R. & DeGroot, E.V. (1990). Motivational and self-regulated learning
components of classroom academic performance. Journal of Educational
Psychology 82(1), 33-40.
Pintrich, P.R., & Schunk, D.H. (2002). Motivation in education: Theory, research, and
applications, 2
nd
Ed. Englewood Cliffs, NJ: Merrill-Prentice Hall.
Pintrich, P.R. Smith, D.A., Garcia, T. & McKeachie, W.J. (1991). A Manual for the
Use of the Motivated Strategies for Learning Questionnaire (MSLQ). National
Center for Research to Improve Postsecondary Teaching and Learning: Ann
Arbor, MI.
Pintrich, P.R., Smith, D.A., Garcia, T., & Mckeachie, W.J. (1993). Reliability and
predictive validity of the Motivated Strategies for Learning Questionnaire
(MSLQ), Educational and Psychological Measurement, 53, 801-813.
94
Reis, S.M., McCoach, D.B. (2000). The underachievement of gifted students: what do
we know and where do we go? Gifted Child Quarterly, 44(3), 152-170.
Renzulli, J.S. & Park, S. (2002). Giftedness and high school dropouts: Personal,
family, and school-related factors. Research Monograph Series. Report No.
RM02168. ERIC Document Reproduction Service, No. ED 480 177.
Rotter, J.B. (1982). Social learning theory. In N.T. Feather (Ed.), Expectancy-value
models in psychology (pp. 241-260). Hillsdale, NJ: Lawrence Erlbaum.
Schultz, R.A. (2002a). Illuminating realities: A phenomenological view from two
underachieving gifted learners. Roeper Review, (24)4, 203-212.
Summers, J.J., Schallert, D.L., & Ritter, P.M. (2003). The role of social comparison in
students’ perceptions of ability: An enriched view of academic motivation in
middle school students. Contemporary Educational Psychologist, 28, 510-523.
Urdan, T. (2004). Predictors of academic self-handicapping and achievement: Examining
achievement goals, classroom goal structures, and culture. Journal of Educational
Psychology, 96(2), 251-264.
95
APPENDIX A: Classroom Motivation Survey
Dear Student:
Your input is very valuable to this study. When responding to the following survey
items please think about your own motivation in this class. When you are finished,
please turn in your survey and signed consent form in the box provided at the back of
the room. Remember, no one from West High School will see your answers.
Write down your Student ID# (including all zeros): __ __
__ __ __ __ __
Below is a list of questions about you as a student at this school. Fill in the circle that
best describes your opinion using the following rating scale: 1 = Not at all true of me,
3 = Somewhat true of me, and 5 = Very true of me
Please use a #2 pencil to fill in the answer bubbles. Fill in one bubble for each
line.
For each answer, please fill in marks like this: not like this:
Not at
All
True
of Me
1
2
3
Some
what
True
of Me
4
5
6
Very
True
of
Me
7
1. It’s
important
to me that
I learn a
lot of new
concepts
this year.
O O O O O O O
96
Not at
All
True
of Me
1
2
3
Some
what
True
of Me
4
5
6
Very
True
of
Me
7
2. An
important
reason
that I try
to do well
in school
is to
please my
parents-
siblings.
O O O O O O O
3. It’s
important
to me that
other
students
in my
class
think I’m
good at
my class
work.
O O O O O O O
4. It’s
important
to me that
I don’t
look
stupid in
class.
O O O O O O O
5. I think
that I will
be able to
use what I
learn in
this
course in
other
courses.
O O O O O O O
97
Not at
All
True
of Me
1
2
3
Some
what
True
of Me
4
5
6
Very
True
of
Me
7
6. One of
my goals
in class is
to learn as
much as I
can.
O O O O O O O
7. I want to
do well in
school so
that I can
be better
prepared
to take
care of
my
family.
O O O O O O O
8. One of
my goals
is to show
others
that I’m
good at
my class
work.
O O O O O O O
9. One of
my goals
is to keep
others
from
thinking
I’m not
smart in
class.
O O O O O O O
98
Not at
All
True
of Me
1
2
3
Some
what
True
of Me
4
5
6
Very
True
of
Me
7
10. It is
important
for me to
learn the
course
material
in this
class.
O O O O O O O
11. One of
my goals
is to
master a
lot of new
skills this
year.
O O O O O O O
12. The main
reason I
try to do
well in
school is
to bring
honor to
my
family.
O O O O O O O
13. One of
my goals
is to show
that class
work is
easy for
me.
O O O O O O O
99
Not at
All
True
of Me
1
2
3
Some
what
True
of Me
4
5
6
Very
True
of
Me
7
14. It’s
important
to me that
my
teacher
doesn’t
think that
I know
less than
others in
my class.
O O O O O O O
15. I am very
interested
in the
content
area of
this
course.
O O O O O O O
16. It’s
important
to me that
I
completel
y
understan
d my
class
work.
O O O O O O O
17. It’s
important
to me that
my
parents-
guardians
are proud
of my
achievem
ent in
school.
O O O O O O O
100
Not at
All
True
of Me
1
2
3
Some
what
True
of Me
4
5
6
Very
True
of
Me
7
18. One of
my goals
is to look
smart in
compariso
n to other
students
in my
class.
O O O O O O O
19. One of
my goals
is to avoid
looking
like I
have
trouble
doing the
work.
O O O O O O O
20. I think
course
material
in this
class is
useful for
me to
learn.
O O O O O O O
21. It’s
important
to me that
I improve
my skills
this year.
O O O O O O O
101
Not at
All
True
of Me
1
2
3
Some
what
True
of Me
4
5
6
Very
True
of
Me
7
22. It’s
important
to me that
I look
smart in
compariso
n to other
students.
O O O O O O O
23. The
reason
why I do
my work
is so
others
won’t
think I’m
dumb.
O O O O O O O
24. I like the
subject
matter of
this
course.
O O O O O O O
25. Understan
ding the
subject
matter of
this
course is
very
important
to me.
O O O O O O O
102
26. I am:
Male
O
Female
O
27. My grade level is:
9
Freshm
an
O
10
Sopho
more
O
11
Junior
O
12
Senior
O
28. My ethnicity is:
Caucasian
O
Asian
O
Hispanic
O
African
American
O
Other
O
Thank you for your time and attention to this important survey.
Please place your completed survey and signed consent form
in the box located at the back of the room.
If you have any questions regarding the questions and/ or content of this survey, please contact
Cynthia Wong at (949) 375-2295 or Dr. Myron Dembo at (213) 740-2364.
103
APPENDIX B: Site Permission Letter
June 2, 2008
UPIRB Chair
University Park Institutional Review Board (UPIRB)
3601 Watt Way – GFS 306
Los Angeles, CA 90089-1695
RE: Dr. Myron Dembo
Cynthia Wong, M.A.
Family and Motivational Factors Differentiating High Ability High Achievers
from High-Ability Underachievers
Dear UPIRB Chair:
This letter is to convey that I have reviewed the proposed research study entitled,
“Family and Motivational Factors of High Achieving Students from West High” being
conducted by Myron H. Dembo, Ph.D. and Cynthia Wong, M.A., from the University
of Southern California. I understand that research activities as described in the proposed
research study will occur at Torrance West High School. I give permission for the
above investigator(s) to conduct their study at this site. If you have any questions
regarding this permission letter, please contact me at (310) 533-4299.
Sincerely,
Mr. Ben Egan
Principal, Torrance West High School
WEST HIGH SCHOOL
20401 Victor St., Torrance, CA 90503 (310) 533-4299
104
APPENDIX C: Cover Letter from Principal
November 13, 2007
Dear West High Parent/Guardian,
Your child has been selected to participate in a research study conducted by
researchers at USC working with the Torrance Unified School District and West High
School. Your child’s participation is voluntary.
The purpose of this study is to better understand the relationship between student
motivation and achievement. In addition, information from this study will be used to
help improve instruction and services for students. Please consider allowing your child
to participate in this unique and valuable research opportunity for West High School.
The answers your child gives will be anonymous and teachers will not have
access to the information your child provides on this survey and your child’s
answers will not influence any grades he or she receives in any course.
Your child can choose whether to be in this study or not. If your child volunteers to be
in this study, your child may withdraw at any time without consequences of any kind.
Students participating in this survey will miss approximately 30 minutes of one class
period in order to complete the survey. Your child’s teacher will be notified and this
activity will not negatively impact his/her grade.
If you have any questions after reading the consent form, you can contact the
researcher at the number provided on the form or the Principal’s office at 533-4299
x7680.
Sincerely,
Ben Egan
Principal
Excellence in Education Award
United States Department of Education
WEST HIGH SCHOOL
20401 Victor St., Torrance, CA 90503 (310) 533-4299
105
APPENDIX D: Informed Consent for Non-Medical Research
University of Southern California
Rossier School of Education
Waite Phillips Hall, Room 600, Suite C
University of Southern California
Los Angeles, CA 90089-4036
INFORMED CONSENT FOR NON-MEDICAL RESEARCH
(PARENTAL PERMISSION)
*********************************************************************
CONSENT TO PARTICIPATE IN RESEARCH
Family and Motivational Factors of High Achieving Students from West
High
Your child is asked to participate in a research study conducted by Dr. Myron Dembo,
Ph.D. and Cynthia Wong M.A., from the Rossier School of Education at the University
of Southern California (USC) because he or she is a student at Torrance West High
School. Graduate students from USC are working with the Torrance Unified School
District and Torrance West High School on this project. The purpose of this study is to
better understand the relationship between student motivation and achievement. The
study will involve looking at students’ grades and test scores. It will also involve filling
out a questionnaire with 28 questions on it. The results will contribute to a doctoral
dissertation. Your child was selected as a possible participant in this study because they
are enrolled in a math or English course chosen for this study. A total of 250-350
students will be selected from math and English classes to participate. Your child’s
participation is voluntary. You should read the information below, and ask questions
about anything you do not understand by contacting the investigator whose name listed
below, before deciding whether or not to allow your child to participate.
PURPOSE OF THE STUDY
The purpose of this study is to better understand the relationship between student
motivation and achievement. This will be done by having students fill out a survey
about how they feel about school.
PROCEDURES
If your child volunteers to participate in this study, we would ask you or your child to
do the following things:
106
Your child will be asked to complete a survey in class, which asks questions about how
your child approaches learning. The survey will take approximately 30 minutes to
complete in class. For example, your child will be asked to rate their opinion on survey
items using the following scale: “Not true of me at all”, “Somewhat true of me”, and
“Very true of me”.
This study will also be looking at your child’s Spring 2007 grades, demographic data
(such as, gender, ethnicity and grade standing) which are all questions on the survey,
and Spring 2007 California Standards Test (CST) scores, which require your
permission to access. This information is routinely viewed by Torrance West High
School and is used to inform program decisions at the school. However, for the purpose
of this study we must obtain your permission to access the information. Your child’s
student ID number and the information we collect will only be viewed by the people
conducting the study.
The answers your child gives will be confidential and teachers will not have access
to the information your child provides on this survey. Your child’s answers will
not influence the grade he or she receives in any course. Your child may still
participate even if you do not grant permission for their scores, demographic data, or
grades to be viewed as part of this study.
POTENTIAL RISKS AND DISCOMFORTS
This study does not pose any known risks beyond minor discomfort. Your child may be
uncomfortable due to spending time away from their studies, from their grades and test
scores being reviewed, or being concerned with the confidentiality of their answers on
the survey. If your child feels discomfort he or she may stop and drop out from the
study at any time. Confidentiality will be protected at all times during data collection,
data analysis, and presenting the written research report.
POTENTIAL BENEFITS TO PARTICIPANTS AND/OR TO SOCIETY
There will be no direct benefit to you or your child for participating in this study.
However, the information from this study will be used to help improve instruction and
services for students.
PAYMENT/COMPENSATION FOR PARTICIPATION
There is no monetary compensation for participating in this study.
CONFIDENTIALITY
Your child’s answers on the survey will be completely confidential. Any information
that is obtained in connection with this study and that can be identified with your child
will remain confidential and will be disclosed only with your permission or as required
by law.
107
Only members of the research team will have access to the data associated with this
study. The data will be stored in the investigator’s office in a locked file cabinet or a
password protected computer. The data will be stored for three years after the study has
been completed and then destroyed. When the results of the research are published or
discussed in conferences, no information will be included that would reveal you or your
child’s identity.
PARTICIPATION AND WITHDRAWAL
Your child can choose whether to be in this study or not. If your child volunteers to be
in this study, your child may withdraw at any time without consequences of any kind.
Your child may also refuse to answer any questions he or she doesn’t want to answer
and still remain in the study. The investigator may withdraw your child from this
research if certain circumstances arise.
ALTERNATIVES TO PARTICIPATION
You and/or your child’s alternative is to not participate.
RIGHTS OF RESEARCH PARTICIPANTS
You or your child may withdraw consent at any time and discontinue participation in
the study without penalty. You or your child are not waiving any legal claims, rights or
remedies because of his or her participation in this research study. If you have questions
regarding your child’s rights as a research participant, contact the University Park IRB,
Office of the Vice Provost for Research Advancement, Stonier Hall, Room 224a, Los
Angeles, CA 90089-1146, (213) 821-5272 or upirb@usc.edu.
IDENTIFICATION OF INVESTIGATORS
If you have any questions or concerns about the research, please feel free to contact the
Co- Principal Investigator, Investigator Cynthia Wong at email cynwong@usc.edu or
phone (949) 375-2295. You may also contact the Co-Principal Investigator Dr. Myron
H. Dembo via mail at WPH 600C, Los Angeles, CA 90089-4036; email at
dembo@usc.edu; or phone at (213) 740-2364.
108
SIGNATURE OF PARENT OR GUARDIAN
I have read (or someone has read to me) the information provided above. I have been
given an opportunity to ask questions and I agree to have my child participate in this
study. I have been given a copy of this form.
□ I agree to have my child’s
demographic information released (i.e.
grade level, gender etc).
□ I do not agree to have my child’s
demographic information released (i.e.
grade level, gender etc).
□ I agree to have my child’s grades
released.
□ I do not agree to have my child’s
grades released.
□ I agree to have my child’s test scores
released.
□ I do not agree to have my child’s
test scores released.
_______________________________
Student ID # (including all leading zeros, if applicable):
Name of Participant
Name of Parent
Signature of Parent Date
SIGNATURE OF INVESTIGATOR
I have explained the research to the participant and his/her parent(s), and answered all
of their questions. I believe that the parent(s) understand the information described in
this document and freely consents to participate.
Name of Investigator
Signature of Investigator Date (must be the same as
participant’s/parent’s)
109
APPENDIX E: Informed Consent for Non-Medical Research
University of Southern California
Rossier School of Education
Waite Phillips Hall, Room 600, Suite C
University of Southern California
Los Angeles, CA 90089-4036
INFORMED CONSENT FOR NON-MEDICAL RESEARCH
FOR YOUTH (AGES 12-17)
*********************************************************************
CONSENT TO PARTICIPATE IN RESEARCH
Family and Motivational Factors of High Achieving Students from West
High
You are asked to participate in a research study conducted by Dr. Myron H. Dembo,
PhD (Principal Investigator) and Cynthia Wong M.A., a doctoral candidate from the
Rossier School of Education at the University of Southern California because you are
a student. The study will involve looking at students’ grades and California Standards
Test (CST) Spring 2007 test scores. It will also involve filling out a questionnaire
with 28 questions on it. The results of this study will be contributed to a dissertation.
You were selected as a possible participant in this study because you are enrolled in a
math or English course identified for this study. A total of 250-350 students will be
selected to participate. Your participation is voluntary. Your parent’s permission has
been sought; however, the final decision is yours. Even if your parents agree to your
participation, you don’t have to participate if you don’t want to. Please take as much
time as you need to read this form and ask questions about anything you do not
understand, before deciding whether or not to participate. You may also decide to
discuss it with your family or friends. If you decide to participate, you will be asked to
sign this form. You will be given a copy of this form.
PURPOSE OF THE STUDY
The purpose of this study is to better understand the relationship between student
motivation and achievement. This will be done by having you fill out a survey about
how you feel about school.
PROCEDURES
If you volunteer to participate in this study, we will ask you to do the following things:
110
You will be asked to complete a survey in class, which asks questions about how you
approach learning. The survey will take approximately 30 minutes to complete in class.
For example, you will be asked to rate your opinion on survey items using the
following scale: “Not true of me at all”, “Somewhat true of me”, and “Very true of
me”.
This study will also be looking at your grades, your demographic data (that is, gender
and ethnicity and grade level), which will be part of your survey, and your California
Standards Test (CST) test scores, which require your permission to access. This type of
analysis is normal and is used to improve instruction at the school. However, for the
purpose of this study permission to access your student records has been asked from
both you and your parents. The information collected and your student ID number will
only be viewed by the people conducting the study.
The answers you give will be kept confidential and teachers will not have access to
the information you provide on this survey. Your answers will not influence the
grade you receive in any course. You may still participate even if you do not grant
permission to access your scores, demographic data, or grades as part of this study.
POTENTIAL RISKS AND DISCOMFORTS
This study does not pose any known risks beyond minor discomfort. You may be
uncomfortable due to spending time away from your studies, from your grades and test
scores being reviewed, or being concerned with the confidentiality of your answers on
the survey. If you feel discomfort you may stop and drop out from the study at any
time. Your confidentiality will be protected at all times during data collection, data
analysis, and presenting the written research report.
POTENTIAL BENEFITS TO PARTICIPANTS AND/OR TO SOCIETY
There will be no direct benefit to you for participating in this study. However, the
information from this study will be used to help improve instruction and services for
students.
PAYMENT/COMPENSATION FOR PARTICIPATION
There is no cash payment or compensation for participating in this study.
CONFIDENTIALITY
There will be no information published in this study that can identify you. Your name,
address, or other identifying information will not be published during this research
study. Your answers on the survey will be kept completely confidential.
Only members of the research team will have access to the data associated with this
study. The data will be stored in the investigator’s office in a locked file cabinet or a
111
password protected computer. The data will be stored for three years after the study has
been completed and then destroyed. When the results of the research are published or
discussed in conferences, no information will be included that would reveal your
identity.
PARTICIPATION AND WITHDRAWAL
You can choose whether to be in this study or not. If you volunteer to be in this study,
you may withdraw at any time without consequences of any kind. You may also refuse
to answer any questions you don’t want to answer and still remain in the study. The
investigator may withdraw your information from this research if certain circumstances
arise.
RIGHTS OF RESEARCH PARTICIPANTS
You may withdraw your consent at any time and discontinue participation without
consequence. You are not waiving any legal claims, rights or remedies because of your
participation in this research study. If you have questions regarding your rights as a
research participant, contact the University Park IRB, Office of the Vice Provost for
Research Advancement, Stonier Hall, Room 224a, Los Angeles, CA 90089-1146, (213)
821-5272 or upirb@usc.edu.
IDENTIFICATION OF INVESTIGATORS
If you have any questions or concerns about the research, please feel free to contact the
Principal Investigator, Dr. Myron H. Dembo via mail at WPH 600C, Los Angeles, CA
90089-4036; email at dembo@usc.edu; or phone at (213) 740-2364. You may also
contact the Co-Principal Investigator Cynthia Wong at cynwong@usc.edu or phone at
(949) 375-2295
112
SIGNATURE OF RESEARCH SUBJECT
I have read (or someone has read to me) the information provided above. I have been
given a chance to ask questions. My questions have been answered to my satisfaction,
and I agree to participate in this study. I have been given a copy of this form.
□ I agree to have my demographic
information released (i.e. grade level,
gender etc).
□ I do not agree to have my
demographic information released
(i.e. grade level, gender etc).
□ I agree to have my grades released. □ I do not agree to have my grades
released.
□ I agree to have my test scores released. □ I do not agree to have my test
scores released.
Name of Participant
Signature of Participant Date
SIGNATURE OF INVESTIGATOR
I have explained the research to the participant and answered all of his/her questions. I
believe that he/she understands the information described in this document and freely
consents to participate.
Name of Investigator
Signature of Investigator Date (must be the same as
participant’s)
113
APPENDIX F: Recruitment Speech
Hi, my name is Cynthia Wong and I am a doctoral student at USC. I am currently
working on a study about student learning and motivation and I have received
permission from your principal, Dr. Stowe and the Torrance School District to collect
some information about how you feel toward school. This study is very important and
will help improve the quality of education here at West High.
Your parents have been informed of my study and I sent home a permission form which
they were asked to sign to allow you to participate in this study. I am also going to have
you sign your own permission form today. This form says that the information you give
me will be totally private and will not be seen by your parents or anyone at this school.
The main thing I want you to know about you participating today is that you can choose
whether or not to take the survey, and you may quit at any time for any reason. If you
choose to take the survey, I assure you that no one will see your personal information or
responses to any of the questions on this survey. This is not a graded assignment, and
your grades will not be affected in any way. I guarantee you will remain completely
anonymous throughout the entire process.
Once you have signed a consent form (and I am passing those out right now), you will
be asked to participate in a survey. This anonymous survey takes about 25 minutes to
complete, and I will walk you through every question.
Now that you have given your consent to take the survey, let’s take a look at it together.
Read along silently as I read to you the opening bit of information:
“Dear Student:
Your input is very valuable to this study. When responding to the following survey items
please think about your own motivation in this class. When you are finished, please turn in
your survey and signed consent form in the box provided at the back of the room.”
Now look at that next line – “Provide your Student ID# (including all zeros):
Student ID #: __ __ __ __ __ __ __” So fill in your student ID number on those dashes. If you
do not know it, raise your hand and I’ll look it up for you very quickly on this list I
have.
Okay, now look at that first bubble that says, “O Please indicate if you are under 18 years of
age by filling in the bubble to the left.” So if you are under 18 fill that in, please.
Okay this next section is a little unusual. Let me read it aloud as you read it silently.
“Below is a list of questions about you as a student in this class. Please use a #2 pencil
or black ink to fill in the answer bubbles. Fill in one bubble for each line. Fill in the
circle that best describes your opinion using the following rating scale: 1 = Not at all
true of me, 3 = somewhat true of me and 5 =Very true of me.” That 1-5 ranking means
114
you can use ANY number, not just 1, 3 and 5 even though they are the only ones with
words above them. These numbers are like volume numbers on a stereo 1 is very low
and 5 is very high volume. 1 is not true of you at all and 5 is very true of you. But you
can set the volume anywhere in between depending on how you feel on each question.
Here’s a final reminder on how to bubble: “For each answer, please fill in marks like
this:
not like this:
Please use a #2 pencil only.
If you need a pencil, raise your hand and I’ll give you one.
Okay now let’s star on the survey itself – remember, since you are anonymous, I want
you to try to be as honest as possible about each response you give.
Okay, item #1 (through item #27).
Before you hand in the survey, please double check to make sure that your student ID
number is filled in at the top, and that you answered every questions completely. If you
skipped any questions, please go back and fill them in.
As soon as you have double checked that everything is filled out correctly, please turn
in BOTH the consent form and the completed survey to the box at the back of the room.
Thank you very much for your time and your honesty. I appreciate the time and effort
you have spent today to help improve the quality of education here at West High.
Abstract (if available)
Linked assets
University of Southern California Dissertations and Theses
Conceptually similar
PDF
The relationship between student perceptions of parental expectations, utility value, aptitude and English achievement among Asian American high school students
PDF
Factors influencing student achievement in advanced placement and honors
PDF
Passing CAHSEE but failing math and English: what best predicts high school classroom achievement?
PDF
Comparing the motivational profiles of high -ability-low -performing (HALP) students and high -ability -high -performing (HAHP) students
PDF
Organizational structures and systems in high-performing, high-poverty urban schools: the construct of race and teacher expectations as mediating factors in student achievement
PDF
Factors that contribute to high and low performing Vietnamese American high school students
PDF
A study of academic success with students of color: what really matters? Lessons from high-performing, high-poverty urban schools
PDF
School-wide implementation of the elements of effective classroom instruction: lessons from high-performing, high-poverty urban schools
PDF
Overcoming a legacy of low achievement: systems and structures in a high-performing, high-poverty California elementary school
PDF
School-wide implementation of the elements of effective classroom instruction: lessons from a high-performing, high-poverty urban school
PDF
Factors influencing nursing students' motivation to succeed
PDF
A case study of factors related to a high performing urban charter high school: investigating student engagement and its impact on student achievement
PDF
A case study of student engagement in a high performing urban continuation high school
PDF
Females' video game playing motivation and performance: examining gender stereotypes and competence goals
PDF
Student engagement in a high performing urban high school: a case study
PDF
School-wide implementation of the elements of effective classroom instruction: lesson from a high performing high poverty urban elementary school
PDF
A case study to determine what perceived factors, including student engagement, contribute to academic achievement in a high performing urban high school
PDF
The tracking effect: tracking and the impact on self-efficacy in middle school students
PDF
Factors including student engagement impacting student achievement in a high performing urban high school district: a case study
PDF
Doubling student performance through the use of human capital at high-performing high-poverty schools
Asset Metadata
Creator
Wong, Cynthia N.
(author)
Core Title
Motivational differences of high-ability high-performing (HAHP) and high-ability low-performing (HALP) high school students
School
Rossier School of Education
Degree
Doctor of Education
Degree Program
Education (Psychology)
Publication Date
06/10/2008
Defense Date
04/29/2008
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
achievement,family orientation,High School,mastery goal orientation,Motivation,OAI-PMH Harvest,performance goal orientation,task value
Language
English
Advisor
Dembo, Myron H. (
committee chair
), Espalin, Charles A. (
committee member
), Stowe, Timothy (
committee member
)
Creator Email
cynwong@usc.edu
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-m1262
Unique identifier
UC1248451
Identifier
etd-Wong-20080610 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-70628 (legacy record id),usctheses-m1262 (legacy record id)
Legacy Identifier
etd-Wong-20080610.pdf
Dmrecord
70628
Document Type
Dissertation
Rights
Wong, Cynthia N.
Type
texts
Source
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Repository Name
Libraries, University of Southern California
Repository Location
Los Angeles, California
Repository Email
cisadmin@lib.usc.edu
Tags
achievement
family orientation
mastery goal orientation
performance goal orientation
task value