Running Head: ACADEMICS AND EXPERIENCES OF GIFTED
MIDDLE SCHOOL GIFTED STUDENTS’ ACADEMIC ACHIEVEMENT AND
PERCEPTIONS OF COGNITIVE AND AFFECTIVE EXPERIENCES WITH PARTICIPATION
IN FULL-TIME OR PART-TIME GIFTED PROGRAM SERVICE DELIVERY MODELS
A dissertation presented to
The Faculty of the College of Education
Florida Gulf Coast University
In partial fulfillment of the requirement for the degree of
Doctor of Education
By
Patricia Clunan Zubal
2015
2
APPROVAL SHEET
This dissertation is submitted in partial fulfillment of
the requirements for the degree of
Doctor of Education
____________________________
Patricia Clunan Zubal
Approved: June 2015
____________________________
Dr. Dorothy Rea, Ph.D.
Committee Chair
____________________________
Dr. Elia Vázquez-Montilla, Ph.D.
____________________________
Dr. Lynn K. Wilder, Ed.D.
Florida Gulf Coast University
Fort Myers, Florida
The final copy of this thesis [dissertation] has been examined by the signatories, and we find that both the content and the form
meet acceptable presentation standards of scholarly work in the above mentioned discipline.
3
Abstract
In this causal comparative study the researcher looked at academic achievement scores and
student perceptions of their experiences in gifted programs. The student sample for the analysis
of the students’ academic achievement scores included all gifted students in a large school
district in Southwest Florida who had recently completed 8th grade in one of the two Service
Delivery Models (SDMs). The student sample for the survey included all students from the
academic section sample who, with parental consent, voluntarily completed the study survey.
The first four research questions asked if significant differences existed between the
mean achievement scale scores of students who participated in the study by SDM, ethnicity, or
socio-economic status (SES). The final two research questions asked if significant differences
existed between the mean student survey scores for each of the three domains of the survey by
SDM, SES, or ethnicity.
Analysis of the quantitative data for academic achievement of the students in the study
indicated that significant differences existed between the academic achievement scale scores of
students by SDM for both the mathematics and reading sections of the Florida Comprehensive
Achievement Test (FCAT 2.0). There also were significant differences found by SES group and
mathematics and reading scores for gifted students in the study. Analysis of the survey data
revealed significant differences between student survey response scores by SES in all domains
and in both SDMs. No other differences were found within or between survey variables.
Key words: Gifted, Service Delivery Model (SDM), Socio-economic Status (SES), Affective,
Cognitive
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Dedication
I dedicate this work to the important people in my life who have inspired me to be a
lifelong learner. My father, Richard Clunan, modeled a curiosity about the world and a love of
learning. Some of my earliest memories of him revolve around his desire to gain and share ideas
and information about the world around us which helped to form my perspective of what is
important in life. My three wonderful and uniquely gifted children, Jennifer, Pamela, and
Nicholas, inspired my interest in the topic of gifted education as well as my desire to better
understand the social and emotional characteristics and needs that are concomitant with
intellectual giftedness. My children taught me that love has no limits and have given me the
most joyful moments and memories to cherish. I have also been inspired by the many students I
have taught over the years. I have been fortunate to teach children and adults of all ages and
backgrounds and have learned something from all of them along the way. They have challenged
me to learn more, to understand better, and to strive for continual improvement as an educator
and a person.
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Acknowledgments
There are many people that I would like to acknowledge for their support and assistance
in completing this work. Dr. Rea has been exceedingly supportive as my professor and my
committee chair. She has always been positive and helpful, had high expectations, gone above
and beyond expectations, and modeled the qualities that I would like to attain. Dr. Vázquez-
Montilla has also modeled qualities that I admire as well as provided support and assistance
throughout my coursework and the dissertation process. Dr. Wilder has served as my advisor as
well as my internship supervisor in addition to being a member of my committee. Dr. Triscari
has given generously of his time and knowledge and provided much needed assistance with
understanding the statistical and data analysis aspects of this work. Dr. Carlos Negrón has
provided me with his strong encouragement, impressive expertise, and helpful feedback
whenever I needed it.
I would also like to acknowledge the support and assistance of Danielle Bailey, Cathy
Kane, Charles Ewell, Debbie Kirchen, and Amy Galbreath for their assistance with adapting and
field testing the survey as part of the validity process. I am also grateful to my daughter Pam for
her interest in my efforts and her skilled editing feedback on the literature review. Finally, I want
to acknowledge my partner John Zubal, who has always believed in me, given me steady
support, understanding, and encouragement especially when I was feeling frustrated or
discouraged. It has been a long and winding road.
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TABLE OF CONTENTS
CHAPTER I…………………………………………………………………………………. 14
INTRODUCTION TO THE STUDY……………………………………………………….. 14
Background………………………………………………………………………………….. 14
Statement of Problem………………………………………………………………………... 16
Statement of Purpose………………………………………………………………………… 17
Research Questions………………………………………………………………………….. 17
Hypothesis…………………………………………………………………………………… 18
Definition of Terms………………………………………………………………………….. 19
Study Overview……………………………………………………………………………… 22
Significance of the Study……………………………………………………………………. 23
CHAPTER II………………………………………………………………………………… 24
LITERATURE REVIEW……………………………………………………………………. 24
Overview…………………………………………………………………………………….. 25
Historical Background……………………………………………………………………….. 25
7
Definitions of Gifted Learners………………………………………………………………. 35
Diverse Populations of Gifted Learners……………………………………………………... 39
Academic Needs of Gifted Learners………………………………………………………… 41
Social and Emotional Needs of Gifted Learners…………………………………………….. 45
Issues Unique to Adolescent Middle School Learners………………………………………. 48
Common Expectations of Parents of Gifted Learners……………………………………. 50
Characteristics of effective Gifted Programs……………………………………………....... 51
Gifted Program Service Delivery Models…………………………………………………… 56
Summary…………………………………………………………………………………….. 58
CHAPTER III……………………………………………………………………………….. 60
RESEARCH METHOD…………………………………………………………………….. 60
Participants…………………………………………………………………………………... 60
Sample……………………………………………………………………………………….. 61
Data Source………………………………………………………………………………….. 62
Goals of Research……………………………………………………………………………. 64
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Research Questions………………………………………………………………………….. 65
Hypothesis…………………………………………………………………………………… 66
Dependent Variables………………………………………………………………………… 67
Independent Variables………………………………………………………………………. 67
RESEARCH DESIGN……………………………………………………………………… 68
Design………………………………………………………………………………………... 68
Data Analysis Procedures……………………………………………………………………. 68
Assumptions, Limitations, and Delimitations……………………………………………….. 70
Assumption…………………………………………………………………………………... 70
Limitations…………………………………………………………………………………... 71
Delimitations………………………………………………………………………………… 71
CHAPTER IV……………………………………………………………………………….. 72
RESULTS……………………………………………………………………………………. 72
Descriptives………………………………………………………………………………….. 72
Research Question 1…………………………………………………………………………. 76
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Research Question 2…………………………………………………………………………. 78
Research Question 3…………………………………………………………………………. 80
Research Question 4…………………………………………………………………………. 84
Research Question 5…………………………………………………………………………. 88
Research Question 6…………………………………………………………………………. 94
Summary…………………………………………………………………………………….. 106
CHAPTER V………………………………………………………………………………… 107
DISCUSSION……………………………………………………………………………….. 107
OVERVIEW OF RESEARCH RESULTS………………………………………………….. 107
Summary of Topics and Themes…………………………………………………………….. 112
Implications of the Research………………………………………………………………… 115
Future Research……………………………………………………………………………… 116
Conclusion…………………………………………………………………………………… 116
REFERENCES……………………………………………………………………………… 118
Appendices…………………………………………………………………………………... 129
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Appendix A………………………………………………………………………………….. 129
Appendix B………………………………………………………………………………….. 130
Appendix C………………………………………………………………………………….. 131
Appendix D………………………………………………………………………………….. 133
Appendix E………………………………………………………………………………….. 134
Appendix F…………………………………………………………………………………... 135
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LIST OF TABLES
TABLE TOPIC PAGE
TABLE 1 Total Student Sample by SDM 73
TABLE 2 Total Student Sample by Ethnicity 74
TABLE 3 Total Student Sample by SES 75
TABLE 4 Reading and Mathematics Scale Scores 76
TABLE 5 Group Statistics of Mean FCAT Reading Scale Scores 77
TABLE 6 Independent Samples t-test for Equality of Means 78
TABLE 7 Group Statistics of Mean FCAT Math Scale Scores 79
TABLE 8 Independent Samples t-test for Equality of Means 80
TABLE 9 Descriptive Statistics for FCAT Reading Scale Score by
SDM and SES
81
TABLE 10 ANOVA Comparing Means of FCAT Reading Scale Score
by SDM and SES
82
TABLE 11 Descriptives for FCAT Reading Scale Score by SDM and
Ethnicity
83
TABLE 12 ANOVA comparing means of FCAT Reading Scale Scores
by SDM and Ethnicity
84
TABLE 13 Descriptives for FCAT Mathematics Scale Scores by SDM
and SES
85
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TABLE 14 ANOVA comparing means of FCAT Mathematics Scale
Scores by SDM
86
TABLE 15 Descriptives for FCAT Mathematics scale scores by SDM
and Ethnicity
87
TABLE 16 ANOVA for FCAT Mathematics Scale Score by SDM and
Ethnicity
88
TABLE 17 Group Statistics of t-test for Domain C 89
TABLE 18 Independent Samples t-test for Equality of Means 90
TABLE 19 Group Statistics of t-test for Domain A 91
TABLE 20 Independent Samples t-test for Equality of Means 92
TABLE 21 Group Statistics of t-test for Domain P 95
TABLE 22 Independent Samples t-test for Equality of Means 94
TABLE 23 Descriptives for Domain C SDM by SES 95
TABLE 24 ANOVA for Survey Domain C SDM and SES 96
TABLE 25 Descriptives for Domain C SDM and Ethnicity 97
TABLE 26 ANOVA for Survey Domain C SDM and Ethnicity 98
TABLE 27 Descriptives for Survey Domain A SDM and SES 99
TABLE 28 ANOVA for Survey Domain A SDM and SES 100
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TABLE 29 Descriptives for Domain A SDM and Ethnicity 101
TABLE 30 ANOVA for Survey Domain A SDM and Ethnicity 102
TABLE 31 Descriptives for Domain P SDM and SES 103
TABLE 32 Anova for Survey Domain P SDM and SES 104
TABLE 33 Descriptives Survey P SDM and Ethnicity 105
TABLE 34 Anova for Survey Domain P SDM and Ethnicity 106
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CHAPTER I
INTRODUCTION TO THE STUDY
Background
Since its beginning in the 1920’s, the field of gifted education has experienced a
continuous ebb and flow of public interest and support (Jolly, 2009; Delisle, 2014). Federal aid
has followed a similar pattern, increasing and decreasing in response to national security interests
and concerns from private institutions and foundations. Despite the initial enthusiasm for
educating the nation’s brightest students that was inspired by the 1957 launching of Sputnik and
the National Defense Education Act (NDEA), the impact on gifted education would be short-
lived. Debates concerning priorities of excellence and equity have also created conflict about
gifted education. Gifted and talented students become a national priority when a critical need is
perceived and excellence is required. As urgency subsides and equity becomes the focus, gifted
students’ needs begin to be viewed as an elitist extravagance and are soon exchanged with the
priorities of students from other subgroups (Delisle, 2014; Heansly, 1999; Imbeau, 1999; Jolly,
2009; NAGC, 2008; and Roberts, 1999).
Many people are concerned that in the United States (U.S.) today our students perform
inadequately on international comparisons of academic achievement. As an example, seventh-
and eighth-grade students performed poorly on the mathematics portion of the Third
International Mathematics and Science Study (TIMSS) (Boe & Shin, 2005). Such results have
led experts to develop deep concerns about the country’s ability to sustain economic
15
competitiveness (Boe & Shin, 2005). According to a task force sponsored by the Council on
Foreign Relations (CFR) in a report on U.S. Education Reform and National Security (Klein,
Levy, & Rice, 2012), our students’ lack of preparedness presents risks on five national security
fronts: economic growth and competitiveness, physical safety, intellectual property, U.S. global
awareness, and U.S. unity and cohesion. The Task Force, including Joel Klein, formerly the
leader of the New York City Public Schools System, and former Secretary of State Condoleezza
Rice, suggest three primary educational policy proposals:
Implement educational expectations and assessments in subjects vital to protecting
national security.
Make structural changes to provide students with good educational choices.
Launch a "national security readiness audit" to hold schools and policymakers
accountable for results and to raise public awareness (Klein, Levy, & Rice, 2012).
These recommendations indicate a belief that there is a need for awareness in terms of
what our schools are doing to improve education, that student achievement in critical areas
should be monitored, and that students will perform better if they are provided with good
educational choices. Society advances from the improvement and highest development of all of
the talents and abilities of all of its citizens, no matter their strengths and weaknesses (Clark,
2002 p. 6). Van Tassel-Baska points out that, “Excellence for all, if it means the same standards,
same curriculum, same instructional emphases, becomes basically inequitable for all since it fails
to recognize individual difference” (1997, p.11). The issues of excellence and equity can best
be addressed through a balanced approach. Equal opportunity does not necessarily mean the
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same opportunity. All children, including gifted children have a right to develop their own
potential (Clark, 2002).
Statement of Problem
Research has shown that students identified as gifted have intellectual, social and
emotional needs that require special educational services and accommodations (Clark, 2002).
A large Southwest Florida school district offers two service delivery models for gifted
educational services at the elementary and middle school levels: full-time and part-time services.
The part-time model is considered to be an enrichment program. In middle school the part-time
program has students receiving enrichment services from a gifted endorsed teacher one period a
day. The full-time service model for middle school has students participate in classes taught by
gifted endorsed teachers for all of their academic classes. All of the students in these classes are
gifted. In order to provide the optimum educational experience for their gifted children, parents
need to collaborate with educators to make decisions about which service delivery model
placement will be the best fit for their individual child. To make wise choices, parents and
educators need to be aware of the current academic achievement of students participating in the
two gifted service delivery model options provided. Additionally, students, educators and
parents need to be aware of the experiences of the students currently participating in the two
gifted service delivery options. Existing research has addressed general placement options but
not the strengths and weaknesses of local service delivery models regarding academic
achievement and social/emotional well-being of specific subgroups of gifted students.
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Statement of Purpose
This quantitative research study looked at the academic achievement as well as the social
and emotional experiences of two groups of students who received gifted services in either the
part-time or full-time gifted service delivery models. The purpose of this study was to provide
useful information and insight about strengths and weaknesses of the two placement options and
their impact on academic achievement and affective experiences of students. This information
will be useful to parents, educators, and students when determining the best gifted service
delivery model choice as well as when planning future instructional strategies and curriculum to
be used in the two service delivery models.
Research Questions:
1. Are there statistically significant differences in FCAT reading mean achievement scale
scores for Southwest Florida gifted middle school students when these students
participate in a full-time gifted service delivery model or a part-time gifted service
delivery model?
2. Are there statistically significant differences in FCAT mathematics mean achievement
scale scores for Southwest Florida gifted middle school students when these students
participate in a full-time gifted service delivery model or a part-time gifted service
delivery model?
3. Are there statistically significant differences in FCAT reading mean achievement scale
scores by SES status or ethnicity for Southwest Florida gifted middle school students
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when these students participate in a full-time gifted service delivery model or a part-time
gifted service delivery model?
4. Are there statistically significant differences in FCAT mathematics mean achievement
scale scores by SES status or ethnicity for Southwest Florida gifted middle school
students when these students participate in a full-time gifted service delivery model or a
part-time gifted service delivery model?
5. Are there statistically significant differences in scores in the areas of curriculum,
affective learning, and general program experiences on the Student Survey for students
receiving full-time gifted program services or part-time gifted program services?
6. Are there statistically significant differences in scores in the areas of curriculum,
affective learning, and general program experiences on the Student Survey by SES status
or ethnicity for Southwest Florida gifted middle school students who participate in a full-
time gifted service delivery model or a part-time gifted service delivery model?
Hypotheses:
1. Differences in reading achievement scale scores for full-time gifted program students will
not be statistically significantly different compared to those of students in a part-time
gifted program.
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2. Differences in mathematics achievement scale scores for full-time gifted program
students will not be statistically significantly different compared to those of students in a
part-time gifted program.
3. Differences in reading mean achievement scale scores for full-time gifted program
students will not be statistically significantly different by SES status or ethnicity
compared to those of students in a part-time gifted program.
4. Differences in mathematics mean achievement scale scores for full-time gifted program
students will not be statistically significantly different by SES status or ethnicity
compared to those of students in a part-time gifted program.
5. Differences in Student Survey scores for full-time gifted program students will not be
statistically significantly different compared to those of students in a part-time gifted
program.
6. Differences in Student Survey scores for full-time gifted program students will not be
statistically significantly different by SES status or ethnicity compared to those of
students in a part-time gifted program.
Definition of Terms
The following definitions are from the Florida Department of Education document
Education of Gifted Students in Florida: The Florida State Plan (2014, p. 87):
Acceleration- Grade level or subject level advancement designed to meet the learner’s needs.
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This includes various means for advancing through material or grade levels ahead of normal
progress. It may include subject or grade acceleration, curriculum compacting, early graduation,
etc.
Affective Curriculum - Curriculum that focuses on personal/social awareness and adjustment,
and includes the study of values, attitudes, and self.
Asynchrony - A term used to describe disparate rates of intellectual, emotional, and physical
rates of growth or development often displayed by gifted children.
Critical Thinking - Analysis of complex problems or ideas that leads to understanding and
decision making.
Differentiation - Modifying curriculum and instruction according to content, process, product,
and learning environment to meet individual student needs. Differentiated instruction is a
philosophy a teacher uses to meet the unique needs of every learner. Even within a self-
contained gifted class there should be differentiation in the curriculum.
Differentiated Curriculum- A set of activities, a program, or a plan of instruction that is designed
to meet the unique needs of special children. For gifted children this means curriculum that
allows for acceleration, stimulation of high level thinking, divergent thinking, and convergent
thinking.
21
Enrichment Programs- Activities that go beyond the basic curriculum to incorporate more
complex, higher-level thinking, and sophistication, abstractness, depth instead of the general
curriculum (different – not more).
Overexcitability - A characteristic first described by Kazimierz Dąbrowski that involves
heightened sensitivities, awareness, and intensity in one or more of five areas: psychomotor,
sensual, intellectual, imaginational, and emotional.
Perfectionism - An intrinsic motivation that through striving for perfection leads to outstanding
accomplishments. This is healthy perfectionism. Perfectionism that tends to be disabling is
extrinsically motivated by a belief that one is worthless in the eyes of others unless one can
present oneself and one’s work perfectly.
Socio-economic status (SES) - Socioeconomic status is commonly conceptualized as the social
standing or class of an individual or group. For the purposes of this study the emphasis is on a
student’s economic status as determined by eligibility for free or reduced lunch within the school
district guidelines. Examinations of socioeconomic status often reveal inequities in access to
resources, plus issues related to privilege, power and control.
Service Delivery Model (SDM)-The format in which exceptional student education services are
delivered to a student. The district referred to in this research offers two specific delivery
models for gifted services in middle school; full-time service and part-time service.
22
Social-Emotional Needs -Gifted and talented students may have affective needs that include
heightened or unusual sensitivity to self-awareness, emotions, and expectations of themselves or
others, and a sense of justice, moral judgment, or altruism. Counselors working in this area may
address issues such as perfectionism, depression, low self-concept, bullying, or
underachievement.
Study Overview
A concern for the perceived low level of achievement of students in the United States
currently exists. A suggested solution is to provide quality program choices for all students,
including those with high academic potential, to prepare them to make positive contributions to
the national security in the areas of economic growth and competitiveness, physical safety,
intellectual property, U.S. global awareness, and U.S. unity and cohesion.
The state of Florida requires that all students that qualify for gifted services must be
offered the opportunity to receive them. Placement in part-time or full-time service delivery
models is initially determined by specific gifted program eligibility criteria. Once eligibility is
determined, the actual service delivery model placement is a choice provided to parents of the
eligible gifted students. A causal comparative design was used in this study. For the academic
achievement scale scores section of the study the FCAT scale scores for each service delivery
group were compared. The Student Survey score section of the study was made up of a
comparison of student scores on a survey consisting of questions about the curricular, affective,
23
and general program experiences of the students in each of the two service delivery model
options.
Significance of the Study
The information provided by this study provides valuable information about the academic
achievement as well as the degree of academic, emotional and social satisfaction within the two
service delivery models as perceived by the students participating in each type of placement. In
addition to its helpfulness to placement decision making, this information provides valuable
feedback to both teachers and program designers.
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CHAPTER II
LITERATURE REVIEW
"Human capital will determine power in the current century, and the failure to produce
that capital will undermine America's security" warns a Council on Foreign Relations (CFR)
sponsored independent task force on U.S. education reform and national security (Klein, Levy &
Rice, 2012, p. 4). At times when concerns about the educational system's ability to keep our
country competitive reach crisis proportions, an increased emphasis on the education of the
country’s most talented students is a logical consequence. It was this logic that birthed the field
of gifted and talented education in the 1920's. Since its inception, interest in and support for the
education of gifted and talented youth has historically been cyclical in nature. Federal aid for
gifted education has increased and decreased in response to national security interests and
economic concerns from private institutions and foundations (Delisle, 2014; Jolly, 2009; Rogers,
2010). This chapter includes a review of the literature pertaining to gifted education, the historical
beliefs and attitudes that have impacted gifted education, as well as components of effective
gifted educational programs and services.
This chapter will discuss the following concepts relevant to delivering services to gifted
students:
historical background
definitions of gifted learners
diverse populations of gifted learners,
25
academic needs of gifted learners
social/emotional needs of gifted learners,
issues unique to middle school gifted learners,
common expectations of parents of gifted learners,
characteristics of effective gifted programs, and
gifted program service delivery models.
Overview
Historical Background.
Throughout history societies have attempted to advance the abilities of their citizens in an
effort to improve or sustain their level of power and control. (Winkler & Jolly, 2011).
Historically, giftedness has been strongly associated with the idea of genius. This association
started in the early 1900’s when psychologists developed assessment instruments that purportedly
were able to measure intelligence. Low scores resulted in the examinee being labeled "retarded,"
while high end scores were thought to belong to "geniuses" (McClellan, 1985). Jolly traces the
history of gifted education back to English scientist Francis Galton, whose work using statistical
methods to study high ability levels and the elements influencing success provides a basis for
later methods of research (2005). Galton, a cousin of Charles Darwin, is credited with the earliest
significant research and writing devoted to intelligence testing. His pivotal work, Hereditary
Genius, published in 1869, indicates that intelligence is passed from one generation to another
(Davis & Rimm, 2004; National Association for Gifted Children [NAGC], 2014a). Galton
26
influenced other researchers to pursue longitudinal studies that focused on both inborn and
external factors that might influence intelligence. Alfred Binet is the first to have developed tests
designed to classify children according to intelligence (Jolly, 2005). One of Binet’s significant
contributions was the notion of mental age, the idea that children grow in intelligence and that
any child may be at the proper intellectual phase for his or her age or may instead be
demonstrably behind or ahead of same age peers (Davis & Rimm, 2004; Jolly, 2005).
America has a long tradition of identifying and grooming talented individuals (Winkler &
Jolly, 2011). Lewis Terman, recognized as the father of the gifted education movement,
influenced gifted education both in its practice and in the understanding of gifted learners
(Colangelo & Davis, 2003; Cross, 1999; Delisle, 1999; Ericson, 1985; Imbeau, 1999; Jolly,
2005). He is known for two important contributions. He supervised the modification and
Americanization of the tests designed by Binet producing the forerunner of the modern Stanford
Binet Intelligence Scale. He also published results of his longitudinal study of gifted children
entitled Genetic Studies of Genius (Jolly, 2005). Both Lewis Terman and Leta Hollingsworth
were influenced by the work of Galton and Binet. Their work considered issues such as
identification, differentiation, research interests, and the social and emotional needs of gifted
children. Hollingsworth contributed to efforts to counsel the gifted, calling this practice
“emotional education” (Davis & Rimm, 2004, p.8). These topics continue to be relevant and at
the center of the current field of gifted education (Jolly, 2005).
Winkler and Jolly (2011) discussed Lewis Terman’s longitudinal research of gifted
27
children and observed that gifted children were often more healthy and stable than their peers, but
few had achieved the level of success that Terman had expected. Terman noted that intellect and
achievement are not necessarily linked. It became evident that even highly gifted learners need
more than academics to become successful adults (NAGC, 2014a ; Winkler & Jolly, 2011)
After the Second World War, United States policy makers began to recognize the need to
provide a strong education for its most talented students, as worries about shortages in
occupations such as engineering and science began to surface (Tannenbaum, 1983). The desire
was for the United States to remain the superpower it had become, along with the Soviet
Union. Although concern was voiced about America’s public schools in this period, little action
was taken until the Russian launching of Sputnik, the first satellite into space (Robinson,
1999). This event was a point in history that many cite as one of the most influential in shaping
the American educational system (Corn, 1999; Delisle, 2014). When the Russians launched
Sputnik in 1957, it became clear that American students were far behind in both mathematics and
science, which caused a dramatic shift in perspective toward education (Coleman, 1999; Delisle,
2014).
The launching of Sputnik shook the American public's confidence in the strengths of their
country, its role as a leader, and its ability to defend itself. Many Americans became concerned
that the Russians would soon dominate the world (Cross, 1999), especially in the mathematics
and science fields. Bright and talented American students were expected to fulfill their potential
and offer their advanced abilities in service to the nation (Tannenbaum, 1979). Gifted students
28
were placed in special schools focused on math and science curriculum developed by leading
educators and scientists (Delisle, 1999; 2014).
To further strengthen the emphasis on education, congress enacted the National Defense
Education Act (NDEA) of 1958 which made federal funding available for the purpose of
developing talent, particularly in the areas of science and mathematics (Roberts, 1999). The
NDEA became law on September 2, 1958, and provided funding to U. S. education institutions at
all levels. The act was designed to fulfill two purposes: to provide the country with specific
defense oriented personnel and to provide financial assistance for college students through the
National Defense Student Loan program. This included providing federal help to foreign
language scholars and engineering students. Sputnik’s impact was a turning point in gifted
education (Coleman, 1999; Corn, 1999; Delisle, 1999; 2014; Gallagher & Weiss, 1979; McIntosh,
1982; Tannenbaum, 1983). The NDEA came about at a time when the country’s immediate
needs surpassed the conflict between excellence and equity, and it may be perceived as a positive
swing of the pendulum toward interest in gifted education (Jolly, 2009).
In 1972, the Education of the Gifted and Talented Report, better known as the Marland
Report was issued. It identified six areas of giftedness: general intellectual ability, specific
academic ability, creative or productive thinking, leadership ability, visual and performing arts,
and psychomotor ability. As a result of this report, the Office of Gifted and Talented Education
was established and an awareness of the needs of gifted and talented children began to develop
29
(Roberts, 1999).
The National Commission on Excellence in Education was formed in 1983, and released
the now famous report A Nation at Risk: The Imperative for Educational Reform. The report
contained the following highly publicized line: “the educational foundations of our society are
presently being eroded by a rising tide of mediocrity that threatens our very future as a Nation and
a people" (U.S. Department of Education, 1983, p. 5). The authors of the report cautioned that
the country was in danger and expressed ominous concern that our "once unchallenged pre-
eminence in commerce, industry, science, and technological innovation is being overtaken by
competitors throughout the world" (U.S. Department of Education, 1983, p. 5). Boe and Shin
(2005) point out that the perception of poor performance by U.S. students on international
comparisons is typically attributed to the ineffectiveness of American public
education. Educators and policy makers of widely different perspectives embraced this
conclusion because it created enormous pressure for change (Boe & Shin, 2005).
The Nation at Risk report further emphasized the idea that learning is cumulative, and that
learners are able to reach their full potential only when their individual strengths are recognized
and reinforced throughout their lives. Also noted in the report was the idea that because
economically underprivileged children often face so many barriers to success, the need for
identification and support for these students’ strengths is particularly urgent. The Nation at Risk
report officially defined gifted learners as follows:
Children and youth with outstanding talent who perform or show the potential for
performing at remarkably high levels of accomplishment when compared with others of
30
their age, experience, or environment. These children and youth exhibit high performance
capability in intellectual, creative, and/or artistic areas, possess an unusual leadership
capacity, or excel in specific academic fields. They require services or activities not
ordinarily provided by the schools. Outstanding talents are present in children and youth
from all cultural groups, all economic strata, and in all areas of human endeavor. (U.S.
Department of Education, 1983, p. 5)
The authors of the Nation at Risk report noted that gains in student achievement made in
the period after Sputnik had been wasted and that support systems which had helped make those
gains possible had been taken away. They went as far as to describe this situation as “…an act of
unthinking, unilateral educational disarmament” (U.S. Department of Education, 1983, p. 5).
In 1988, Congress passed the Javits Gifted and Talented Students Act as part of the
Elementary and Secondary Education Act. The Javits Act is the only federal program devoted
exclusively to the needs of gifted students. It provides an organized program of research,
projects, strategies, and activities that develop and improve the capacity of schools to provide for
gifted students’ unique educational needs. The Javits Act concentrates its resources on
recognizing and providing services to students who are often underrepresented in gifted
programs, especially economically disadvantaged, limited-English proficient and disabled
students. It aims to decrease achievement gaps and to foster equal educational opportunities for
all students (NAGC, 2014c).
National Excellence: A Case for Developing America’s Talent, issued in 1998, was the
next national report on the state of the country’s educational programs for gifted students. The
report focused on the fact that gifted students' learning needs continued to be inadequately
addressed. The report provided a similar definition of gifted learners as did the Nation at Risk
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report and stressed that, “Outstanding talents are present in children and youth from all cultural
groups, across all economic strata, and in all areas of human endeavor” (U.S. Department of
Education, 1993, p.5). The National Excellence report provided recommendations that states
have used in their own definitions of gifted learners and in designating the services that should be
provided (Roberts, 1999). The report states that recent studies show:
Gifted and talented elementary school students have mastered from 35 to 50 percent of the
curriculum to be offered in five basic subjects before they begin the school year.
Most regular classroom teachers make few, if any, provisions for talented students.
Most of the highest-achieving students in the nation included in Who's Who Among
American High School Students reported that they studied less than an hour a day. This
suggests they get top grades without having to work hard.
In the one national survey available, only 2 cents out of every $100 spent on K-12
education in the United States in 1990, supported special opportunities for talented
students (U.S. Department of Education, 1993, p. 4).
In both the Nation at Risk and National Excellence reports, the authors established
expanded definitions of giftedness, clarified that gifted learners come from all backgrounds, and
that educators bear the responsibility for identifying learners that exhibit higher potential
compared with same age peers. The reports' authors recommended services for gifted children
that match needs instead of one size fits all programs, and they recognized that the least restrictive
32
environment for various gifted students is quite different than for students with other
exceptionalities (Jolly & Kettler, 2008).
Piirto (2007) believes that any gains made for gifted education by the National Excellence
report were destroyed when the No Child Left Behind Act (NCLB) was passed as the
reauthorization of the Elementary and Secondary Education Act in 2001. Although this
legislation was meant to improve education for all students, it focused on proficiency and
accountability instead. Funds once assigned to gifted programs are now frequently provided to
programs focused on proficiency (Piirto, 2007).
In 2004, another national research report was issued entitled, A Nation Deceived: How
Schools Hold Back America’s Brightest Students. This report debunks the myths and
misunderstandings which have led schools, parents and teachers to be resistant to the strategy of
acceleration as a means of addressing the learning needs of gifted students despite the vast
amounts of evidence of its effectiveness. The different forms of acceleration presented include
early-entrance, grade skipping, the Advanced Placement program and early college. The success
of A Nation Deceived led to the creation of the Institute for Research and Policy on Acceleration,
which is dedicated to the study and support of educational acceleration for academically talented
students (NAGC, 2014a).
As Gallagher (1994) noted, the attitude toward gifted students at a personal and societal
level has often been one of ambivalence, in both the educational setting and society at large. “We
may love the creative products of their mental processes but still feel the sting of envy when we
33
observe some persons doing, with apparent ease, what is so difficult for others to accomplish”
(Gallagher, 1994, p. 3). The field of gifted education has remained in a constant struggle between
excellence and equity. At times society focuses on education for the brightest and most creative
students, concentrating on developing their potential, but at other times the focus is on bringing
students at the other end up to the average (Davis & Rimm, 1998; Gallagher, 1994; Jolly,
2009). Roberts (1999) believes that enthusiasm for educating gifted students is influenced by
economics and politics. At times of prosperity and peace among nations interest is low, but when
a crisis occurs, gifted students become a valuable resource to be developed to their fullest
potential (Roberts, 1999). Public understanding and support as well as federal aid have reflected
this fluctuating pattern of increasing and decreasing interest and concern. Tannenbaum noted,
“The cyclical nature of interest in the gifted is probably unique in American education. No other
special group of children has been so alternately embraced and repelled with so much rigor by
educators and laypersons alike” (1983, p. 16). Reflecting the back and forth of society’s
priorities from “critical need to its elitist luxury” (Jolly & Kettler 2008, p. 427), gifted and
talented students become a national priority when excellence is pursued and a critical need is
perceived. Conversely, as equity takes the foreground, gifted students’ needs are seen as an elitist
extravagance and the needs of other subpopulations become the priority (Jolly & Kettler,
2008). Remarkably, it was decades ago that Hollingsworth explained, “Schools cannot equalize
children, schools can only equalize opportunity” (1924 in Dai, 2010, p. 174).
Negative assessment of the concept of giftedness exists in the United States due to the
34
association of gifted programs with the practice of subtle or even blatant social stratification and
exclusivity (Dai, 2010). Even in the time period when Terman was developing intelligence
testing, his encouragement for its use in the identification of gifted students was not
unchallenged. In the 1980s, research began to focus more on a developmental view of
giftedness. In this view giftedness is seen as less of an unchanging mental quality and more as
the result of multiple factors combining fortuitously. There has been an evolution of giftedness
from initial notions of conventional intelligence to more recent acknowledgement of a multitude
of indicators and expressions of talents. This changing perspective emphasizes the role of
developmental processes as opposed to innate abilities (Dai, 2010)
Currently, the United States is involved in Science, Technology, Engineering, and
Mathematics (STEM) programs to once again counteract competition from other countries that
have increased their competence in these subjects (Jolly, 2009). The purpose of these initiatives
is to encourage students to pursue careers in STEM disciplines. These programs are not
specifically aimed at gifted and talented students as were previous programs during the era of the
NDEA. Our society and its educational system have yet to fully reconcile the concept that
education can combine excellence with equity. As a result many gifted students continue to lack
sufficient appropriate learning opportunities (Delisle, 2014; Jolly, 2009).
Definitions of Gifted Learners
A comprehensive definition of giftedness is crucial because it is the basis on which a
program for gifted students is developed (McClellan, 1985). The definition selected supplies the
35
basis for gifted programs and services. It influences important decisions such as who will be
found eligible for services, the areas of giftedness that programs will address, and when and how
the services will be provided. Scholars, scientists and educators have been attempting to find the
appropriate definition of giftedness for over one hundred years. Currently, no definition of
giftedness is universally accepted (Davis & Rimm, 2005; Delisle, 2014; NAGC, 2014b).
“Without a cohesive definition…the likelihood of inequity abounds” (Delisle, 2014, p. 115).
What was once exclusively the realm of scholars, scientists and educators has now gained
the interest of the federal government. Its interest in the identification and education of gifted
learners was sparked during World War II, when a need for technological expansion to meet the
goal of upholding military and political dominance was recognized (McClellan, 1985). By 1950,
Congress had passed the National Science Foundation Act which marked the first time the federal
government provided funds specifically for the gifted and talented, especially in the areas of
mathematics and science. Thus, the legislation led to the idea of specific intellectual ability as a
form of giftedness. Another noteworthy event in defining giftedness was the publishing of
Guilford's structural model of the components of intelligence that resulted in the creation of tests
to assess intellectual capacities excluding those measured by traditional IQ tests (McClellan,
1985).
The use of intelligence tests as the sole measure of giftedness has been increasingly
criticized because the tests are frequently biased toward white middle class students. Frustration
with a narrow viewpoint has resulted in the development of more comprehensive definitions of
36
giftedness. Many experts have come to believe that giftedness includes creativity, memory,
motivation, physical dexterity, social adeptness, and aesthetic sensitivity in addition to intellectual
ability. The emergence of creativity tests and the acceptance of the relationship between
intelligence and creativity have resulted in the inclusion of creativity in many definitions of
giftedness (McClellan, 1985). A greater comprehension of what constitutes giftedness has
evolved from an intellectual, social and emotional perspective although the field continues to
struggle to adequately identify diverse groups of students (Colangelo & Davis, 2002).
Definitions of giftedness based on theoretical conceptions include those of Gagne,
Renzulli, Gardner, and Sternberg. In Gagne’s Differentiated Model of Giftedness and Talent a
well-defined difference between talent and giftedness is expressed. He sees giftedness as having
and using naturally occurring abilities to a level that identifies a learner as within the top ten
percent of same age peers. Gagne sees talent as the exceptional mastery of carefully developed
capabilities and proficiency to a level that places a child's achievement at the upper ten percent of
same age peers. Gagne’s model provides five domains of ability: intellectual, creative, socio-
affective, sensorimotor, and others such as extrasensory perception (Gagne, 1985).
Renzulli’s concept of giftedness involves the interaction of above-average abilities, high
levels of motivation, and an advanced degree of creativity. Within this concept gifted learners are
those who possess or have the capacity to develop this combination of traits and who apply their
abilities to any area of worthwhile human accomplishment (Renzulli, 1978). Howard Gardner
(1999) suggests that people have a variety of abilities and potentials, or multiple intelligences,
37
which can be made use of individually or together. For Gardner (2011), giftedness is exhibited
with the interaction of above-average abilities, motivation and creativity. Gifted learners either
have or have the ability to develop this combination of traits and to apply them to any worthwhile
human endeavor (Gardner, 1999).
The multiple intelligences, as defined by Gardner (1999), include linguistic intelligence,
logical/mathematical intelligence, musical rhythmic intelligence, bodily/kinesthetic intelligence,
spatial intelligence, naturalist intelligence, intrapersonal intelligence, interpersonal intelligence
and existential intelligence. For Gardner, intelligence itself is the ability to generate an effective
product or provide a valued service, possession of a group of skills that allow one to solve
problems, and the capacity for identifying or developing solutions for problems, which includes
collection of new knowledge (1999).
Sternberg developed a more cognitive approach with his Triarchic Theory of Intelligence.
Intelligence for Sternberg (2005) is made up of three components; analytical intelligence, creative
intelligence and practical intelligence. It is not enough to possess the three components. One
must also know when and how to use these components in order to be effective. Sternberg (2005)
sees intelligence as the ability to reach one’s goals in life, within one’s sociocultural context.
Moving from the theoretical to the practical educational perspective, the National
Association for Gifted Children, (NAGC, 2014b) provides this definition of giftedness:
Gifted individuals are those who demonstrate outstanding levels of aptitude (defined as
an exceptional ability to reason and learn) or competence (documented performance or
achievement in top 10% or rarer) in one or more domains. Domains include any
structured area of activity with its own symbol system (e.g., mathematics, music,
language) and/or set of sensorimotor skills (e.g., painting, dance, and sports).
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Almost all states have a unique gifted or gifted and talented definition. Some definitions
are based on a comparison of the student’s ability to that of the same age peers. Other state
definitions are based on student needs beyond the regular curriculum. Florida’s definition of
gifted is derived from State Rule 6A-6.03019, FAC, Special Instructional Programs for Students
Who Are Gifted. This rule describes a gifted student as “one who has superior intellectual
development and is capable of high performance.”
The current federal definition of gifted and talented is provided in No Child Left Behind
(NCLB, 2001):
The term ‘gifted and talented,” when used with respect to students, children, or youth,
means students, children, or youth who give evidence of high achievement capability in
such areas as intellectual, creative, artistic, or leadership capacity, or in specific academic
fields, and who need services or activities not ordinarily provided by the school in order to
fully develop those capabilities.
Fischetti and Shames (1998) explain that when designing and implementing a process for
identification of gifted students in a school system, educators find it challenging to differentiate
between very bright and gifted students. They recommend a multiple component process that
provides a broader picture of the student’s characteristics and abilities. The following ideas, as
provided by McClellan (1985), may serve as a guide to assist educators in making placement and
programming decisions:
The concept of giftedness is not limited to high intellectual ability. It also comprises
creativity, ability in specific academic areas, ability in visual or performing arts, social
39
adeptness, and physical dexterity.
A program for gifted children should be based on the way in which the school system
operationally defines giftedness. A definition should be the basis of decisions regarding
the selection of identification procedures as well as the provision of educational services
for gifted children.
Definitions of giftedness are influenced by social, political, economic, and cultural
factors.
Giftedness is found among all groups, including females, minorities, handicapped persons,
persons with limited English-speaking proficiency, and migrants.
The recent emphasis on math, science, foreign languages, and computer learning found in
the federal definition emphasizes how a school systems’ definition of giftedness is frequently
grounded in the needs of society, its cultural belief systems, and socioeconomic factors
(McClellan, 1985).
Diverse Populations of Gifted Learners
Identifying giftedness in children and delivering appropriate educational services to them
is especially complex when the students belong to diverse subgroups. Students who are recent
immigrants are one such group. Factors affecting these students include; their linguistic and
cultural backgrounds, economic and attitudinal factors, sociocultural peer-group expectations,
cross-cultural stress, and intergenerational conflict (Harris, 1993). Learners who have unique
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talents or gifts hail from every linguistic and cultural background. These students have an
abundance of specific qualities that are strongly valued in their own society or culture but these
students are not always identified as gifted.
Bermudez and Rakow (1993) provide survey data indicating few programs identify and
instruct gifted limited English proficient (LEP) students in states with high Hispanic
concentration. Even those programs that do have procedures in place for identifying LEP
students as gifted report little success with these measures. A contributing factor may be a failure
to gain community input into the identification process (Bermudez and Rakow, 1993).
Assessment procedures for identifying gifted and talented students have historically been
designed to be used with middle class, native English speaking children. This situation can lead to
an underrepresentation of diverse students in gifted programs and also make it more difficult for
schools to develop the unique abilities and strengths of these students (Cohen, 1990). Research
indicates that minorities (with the exception of Asian-Americans) are underrepresented in gifted
programs (Colangelo 2002). African-American, Latinos, and Native-American students are
extremely conscious of their minority status within gifted programs and are conflicted about their
involvement in these programs. Unfortunately, some minority students associate high academic
achievement with "acting white" (Colangelo, 2002). Gifted minority students may worry about
whether they belong in gifted programs as well as how they will be perceived by their ethnic
peers if they take advantage of gifted services. While gifted students could benefit from
counselor’s support, most school counselors have very little training in dealing with gifted
students’ affective needs (Colangelo, 2002).
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Research on family influences on the achievement of low socioeconomic status (SES)
students has typically focused on variables of status that correlate directly with student
performance on assessments used to identify the gifted. Current studies indicate that gifted
students are present and nurtured within low SES families but emphasize the need to focus on the
unique expressions of giftedness within cultural contexts when making decisions about placement
and programming (Hunsacker, Frasier, King, Watts-Warren, Cramond & Krisel, 1995).
Another group of students that has become a research priority within the area of gifted
education is that of special populations, particularly students who are learning disabled or on the
autism spectrum. According to the Office of Educational Research & Improvement (National
Excellence, 1993), more research including looking at program effectiveness is needed for gifted
students with disabilities. Similarly, research is needed on the effectiveness of programs for
minority students. An emphasis on studies using diverse subgroups of students, is becoming
increasingly important given the growth of these populations (Hishinuma & Nishimura, 2000)
Districts should implement programs that will best meet the needs of their specific population of
gifted and talented students (Cohen, 1990).
Academic Needs of Gifted Learners
Clark (2002) explains that a high level of intelligence can be viewed as advanced and
accelerated brain function. It has been demonstrated that brain processes present at birth will
deteriorate if they are not provided with the environmental stimulus needed to maintain them.
The richness of the environment that we provide actually influences the rate of glial cell
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production and changes the chemical structure of nerve cells. By increasing the strength and the
speed of synaptic activity we can affect the process of learning. With changes in teaching and
learning procedures, it is possible to increase the complexity of connections in a child’s brain.
The learning environment can affect students at the cellular level (Clark, 2002).
Advanced and accelerated development of functions allow for more efficient and effective
use of the brain. Giftedness includes an interaction of all of the areas of brain function; physical
sensing, emotions, cognition, and intuition. Giftedness may be conveyed through problem
solving, creativity, academic ability, leadership, artistic expression, invention, etc. Most
importantly high level intelligence is the result of interaction between inborn and learned
characteristics (Clark, 1997).
If you believe that a child is born with a set amount of intelligence, you will not be
concerned with providing opportunities for optimal development, you will only be
interested in providing information and content. If you believe that intelligence is
dynamic and dependent on the environment interacting with what is inherited, you will be
concerned about the kind of environment you provide; you will not leave education to
chance (Clark, 2002, p. 43).
While societal expectations are for students to be competitive in a global economy, and to
excel and become productive citizens; gifted education has been criticized as having possible
negative effects on non-gifted students when funding is provided to gifted programs (Adelson,
McCoach & Gavin, 2012). Research into the effects of gifted education indicates that gifted
programming does not have negative effects on the achievement of non-gifted students and
conclude that gifted programming does not appear to have any detrimental effects on non- gifted
43
students. The research also states that there are no positive effects for gifted students and
conclude that gifted programs, as provided in American schools, do not affect gifted students’
achievement (Adelson, McCoach & Gavin, 2012; Dai, 2010). Although some gifted reading and
math programs show positive gains in student achievement, their effects are minimized by the
amount of programs that have no effect or counteracted by programs with negative results
(Adelson, McCoach & Gavin, 2012) We are not implementing effective programs and practices
consistently throughout the country to improve gifted students’ achievement overall. A need
exists for researchers to study the types of programs and curriculum that positively affect the
achievement of gifted students (Adelson, McCoach & Gavin, 2012; Dai, 2010). Delcourt,
Cornell, and Goldberg (2007) explain that the main goals of gifted programs are to boost learning
and achievement to a degree corresponding to the student’s potential as well as to improve self-
concept by providing students the opportunity to interact and learn with peers sharing similar
interests and abilities. While these ideas are widely held, empirical evidence of their validity is
lacking (Delcourt et al., 2007).
According to Davis and Rimm (2004), grouping for enrichment, whether within a general
education classroom or a gifted resource room yields significant gains in academic achievement,
creativity and thinking skills. They suggest that higher achievement of gifted students is probably
caused by a mixture of high ability, engaged instructors, and the motivation to learn when gifted
students share a classroom with other high ability, engaged learners.
In the continuing quest for excellence in academic achievement, the No Child Left
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Behind Act (NCLB), was enacted to increase the accountability of educators and the academic
achievement of all students. Gallagher (2004) believes that excellence means providing sufficient
academic opportunities and instruction to allow the most able of our students to investigate and
discover novel concepts and reach their full potential. Educational policies and legislation can
and do have unintended consequences that are of particular concern to gifted students, their
parents and teachers (Gallagher, 2004). One effect of high stakes testing is that students,
including the gifted, spend large portions of their instructional time practicing basic skills that are
likely to be assessed. This practice is actually counterproductive for gifted students who need
advanced and differentiated curriculum in order to advance their learning and achieve excellence.
When gifted student’s academic needs are appropriately met, the legitimate goals of excellence
and equity in education will be attained for them (Gallagher, 2004).
Although gifted program placement may be advantageous for most gifted students, some
may experience difficulties with the label or the placement. Because gifted curriculum includes
accelerated coursework and a greater amount of work than usually occurs in the standard
curriculum classroom, a student lacking in motivation may have difficulty handling the increased
structure and expectations resulting in academic failure. Gifted program placement could cause
an increased level of psychological distress for some gifted students (Pfeiffer, 2008). Others may
find the content irrelevant to their experiences and lose interest in learning. Minority students, in
particular, may disengage if they feel uncomfortable in an unknown educational setting (Pfeiffer,
2008). Educators have an ethical responsibility to be informed about placement decision
making and the social, emotional, and academic implications of placing students in programs
45
(Pfeiffer, 2008).
When working with gifted students, the development of the whole child should be
considered. Educators should address emotional, social, cognitive and physical factors equally.
Betts and Neihart declare, “A child is a total entity; a combination of many characteristics.
Emotions cannot be treated separately from intellectual awareness or physical development. All
intertwine and influence each other” (1988, p. 248).
Social and Emotional Needs of Gifted Learners
The stereotype of a gifted student as a physical, emotional, and social misfit has been
disproven by many studies yet it is still important to understand that unique stresses and issues are
related to giftedness (Robinson, Shore & Enersen, 2007). Despite the extensive
acknowledgement of the need for healthy affective development as a goal of gifted education
programs, few studies have looked at program effects in this realm (Delcourt, Cornell, &
Goldberg, 2007). There are many reasons why school may be difficult for gifted students. One
major cause is the practice of grouping children by age instead of ability or performance level.
The result of this practice is that school is too slow and repetitive for students of high intelligence.
The greater the level of intelligence, the more emotional adjustment becomes an essential
consideration (Ruf, 2005). Some of the effects of boredom and lack of challenge for gifted
students include learning to underachieve, having problems fitting in, discovering rewarding
friendships and becoming confused about who they are and what they can accomplish (Ruf, 2005;
Robinson et al., 2007). Some additional problems encountered by gifted students include:
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perfectionism, ridicule by peers who don’t understand their interests, worry and a sense of
helplessness about world problems, uneven development, intensity, stress and burnout (Delisle &
Lewis, 2003).
Although the affective domain has been discussed as essential to the development of
personal and social talents, as well as being an essential component of motivation and social
emotional functioning, little consideration has been given to affect regulation in the gifted
(Keiley, 2002). Affect regulation includes monitoring, enduring, and managing the
physiological, behavioral, or experiential aspects of emotional experience. Affect is controlled to
lessen unfavorable circumstances or to increase positive ones. Regulation of affect allows people
to comprehend, organize, and act on their experiences. Gifted students may be at risk for
developing internalizing disorders and may be susceptible to feelings of isolation and loneliness.
Their intensity, sensitivity, and emotionality can also contribute to anxiety, phobias and
interpersonal problems (Kaplan, 1990; Keiley, 2002)
While many issues come from within the student, some of the challenges come from
outside the student such as family, school environment, peers, or society in general. Delisle and
Galbraith (2002, p. 62-67) compiled a list of eight “gripes” about being gifted identified through
interviews with gifted and talented students:
No one explains what being gifted is all about-it’s kept a big secret.
School is too easy and boring.
Parents, teachers and friends expect us to be perfect all the time.
Friends who really understand us are few and far between.
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Kids often tease us about being smart.
We feel overwhelmed by the number of things we can do in life.
We feel different and alienated.
We worry about world problems and feel helpless to do anything about them.
Cross addressed the many commonly held beliefs about the social and emotional aspects
of giftedness and gifted education that are actually myths (2002). Parents, teachers,
administrators, and gifted students themselves fall prey to these myths:
Gifted students should be with students their own age. Actually, gifted students need
opportunities to be with their intellectual peers, no matter the age differences.
Gifted students are better off if they spend their entire school day amidst same-age,
heterogeneous classmates. Research that supports this myth is virtually nonexistent.
Students have many opportunities to interact with other children such as; church, sports,
clubs and camps.
Being perfectly well rounded should be the primary goal for gifted student development. A
more reasonable approach is to encourage and nurture other interests in the child rather
than sending them the message that they are unacceptable as they are.
Being gifted is something with which you are just born. Actually, talent is developed with
hard work and some failure.
Virtually everybody in the field of gifted education is an expert on the social and
emotional development of gifted students. In reality, children would be better served by
48
having the expertise of those who specialize in social and emotional development.
Adults (parents, teachers, and administrators) know what gifted students experience. In
fact, children live in a somewhat different context today than adults did at the same age.
Being too smart in school is a problem, especially for girls. In point of fact support must
be provided for these children as they navigate the anti-intellectual contexts in which they
spend much of their time.
All kids are gifted, and no kids are gifted. Really, a person who shows extraordinary
ability for high levels of performance when young and, if provided appropriate
opportunities, demonstrates a development of talent that exceeds normal levels of
performance, is gifted (Cross, 2002, p 44-67).
Issues Unique to Adolescent Middle School Gifted Learners
The developmental issues that all adolescents encounter also exist for gifted students, yet
they are further complicated by the special needs and characteristics of being gifted (Buescher &
Higham, 1996). Gifted adolescents frequently report a variety of difficulties as a result of their
many abilities including; perfectionism, competitiveness, unrealistic appraisal of their gifts,
rejection from peers, confusion due to mixed messages about their talents, parental and social
pressures to achieve, and problems with unchallenging school programs (Buescher & Higham,
1996). Making choices about friendships, a course of study, and, eventually, a career can also
seem overwhelming. Colangelo (2002) explains that as gifted students advance through school,
their self-concept lowers while at the same time they become increasingly isolated and anxious.
Positive self-concept is linked with challenge-seeking, motivation to take risks or do challenging
49
work, and accuracy in self-evaluation. Gifted students’ self-concepts tend to be higher in
academic areas, and lower in social realms. Adolescents see their giftedness positively as it
relates to their academic performance but negatively regarding peer relations (Colangelo, 2002).
Rakow (2005) describes inconsistencies among physical, social, emotional, and
intellectual maturity, known as asynchronous development and explains that this may be the
cause of many conflicts gifted adolescents face. Some programs designed for gifted adolescents
may develop an imbalance that overemphasizes the affective domain to the detriment of the
cognitive. Rakow recommends that equal attention be given to both the mental and the social-
emotional needs of gifted students, and that schools should provide a continuum of services to
meet the needs of all gifted students (2005).
Historically, conflict has existed between educators of the gifted and educators of standard
education middle school classes (Tomlinson, 1995). Each of these groups of educators is
concerned with both the cognitive and affective well-being of their young adolescent students.
They are aware of the inconsistencies in the academic, social, emotional, and physical
development of early middle school age students. Both groups believe that all students should
experience challenging learning experiences (Tomlinson, 1995). The conflict is that of
excellence versus equity. Heterogeneous grouping is valued in middle schools however educators
of the gifted appreciate the advantages of ability grouping for gifted learners. Educators of the
gifted are also troubled by the shortage of differentiated instruction in heterogeneous middle
school classrooms. Standard education educators are concerned with the idea of labeling students
and believe this practice unfairly benefits some and disadvantages other students. Gifted
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educators believe that identifying advanced ability is needed for proper planning and talent
development to be achieved (Tomlinson, 1995).
Common Expectations of Parents of Gifted Learners
According to Clark, “No child is born gifted — only with the potential for giftedness”
(1997, p. 8). Cognitive Learning theory supports the idea that a child’s environment is as
important as their innate gifted characteristics in shaping a child’s potential achievement (Jordan,
2011). Parents have lasting and varied effects on their children. They create the attitudes and
expectations that allow high levels of development. Parents of high-achieving students want
appropriate educational programs for their children and value schools that are considerate of their
students’ needs (Brulles & Winebrenner, 2012) Gifted students’ parents are applying pressure
to states and districts to secure services for their children whose needs are greater than the
conventional classroom can provide. Although these parents have faced challenges in the past,
their struggle has recently increased due to budget constraints and competing needs. Some
parent advocates state that the problem is even greater for low income and minority parents
who see gifted programs as a way to obtain greater challenge and opportunity for their children
(Fleming, 2013). Because most teachers do not receive training in the identification of gifted
students, parents end up with the responsibility of obtaining gifted services for their children.
Educators are not proactive enough in assisting parents, particularly low SES and minority
parents, with the identification process (Fleming, 2013). Orienting educators toward supporting
academically gifted students through process and program modifications, differentiating
instructional strategies and content, and providing increased variety in program options would be
51
beneficial to all students (Olszewski-Kubilius, 1998).
Martin, a parent of gifted children himself, states that one of the biggest problems parents
of gifted students face when arguing against inclusion is that they are often portrayed as being
antidemocratic because they want special classes for their children (2002). He argues that
students with special needs require special services and that expecting schools to address the
needs of gifted students is not antidemocratic, just quality education (Martin, 2002).
When parents initially realize that their children are gifted, they may become anxious
about how to meet the needs of the child. Parents of newly identified gifted children frequently
hope for some kind of guidance, because they are convinced that they cannot cope alone and deal
with feelings of inadequacy in accessing an appropriate education for their child (Rash, 1998).
Educators need to be able to provide research based information and resources so that parents can
make informed decisions about their child’s education (Pfeiffer, 2008). According to Robinson,
Shore, and Enersen, parents have two great needs: the support of other parents who are
experiencing the same kind of challenge and information about gifted children and the resources
that are available to them (2007). To be certain that students receive the appropriate educational
opportunities and interventions at the appropriate time and intensity level, educators must
establish active collaboration with families. These collaborations will be optimally effective
when educators are sensitive to the parental perspective (Van Tassel-Baska, 2012).
Characteristics of Effective Gifted Programs
The misconception that children are innately gifted and will flourish on their own has an
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enormous impact on public perceptions of gifted students, and the practice of educators (Clark,
1997). The concepts of equity, democratic ideals, and human rights should be stressed as they
apply to gifted students. Our country was founded on democratic principles. For true equal
opportunity, a range of learning opportunities must be offered at various levels so that all children
can be taught at their level of development. The strongest programs for gifted students and other
special needs students provide choice among a variety of services and thorough assessment of the
students’ needs for services (Clark, 1997). Appropriately matched curriculum for our most
capable students is a positive direction toward the upward mobility of a society. “What a society
provides its best learners is an indication of its commitment to excellence, to the traditions of
learning that have shaped civilizations over the centuries” (Van Tassel-Baska, 2013, p. 214).
Too often the most beneficial educational settings for gifted students are not provided
based on mistaken concerns such as:
Gifted students have a need to be with other students who have different intellectual and
socioeconomic levels in order to understand how the world works.
Gifted students do not need much in the way of special programs because they can do well
without such arrangements.
Gifted students are not entitled to privileges not afforded to other students (Van Tassel-
Baska, 2013).
Cloud states that “…our education system has little idea how to cultivate its most
promising students" (2007, p. 41). He further declares his belief that schools in the United States
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are actually holding the most intelligent students back, often resulting in isolation and academic
underachievement. Cloud wonders, “Has the drive to ensure equity over excellence gone too
far?" (2007, p. 42). He concludes that it has become more critical to a school district to identify
deficits instead of nurture gifts. Each year the U.S. spends eight billion dollars on educating
children with special needs and only ten percent of that on serving gifted students (Cloud, 2007).
In taking a look at curriculum and instruction for the gifted, it is clear that there are many
methods and programs that have been implemented and embraced without sufficient testing and
without enough thought to their overall educational value. Competition among different models
has interfered with the goal of building a strong differentiated program for the gifted that
addresses all of their intellectual needs (Van Tassel-Baska, 1986). Cloud speculates as to
whether our society actually expects students with the highest capability to achieve that potential.
“We venerate Einstein, but there is no more detested creature than the know-it-all” (Cloud, 2007,
p.42). It is time for educators, parents, and policy makers to accept that children are not all the
same and that teaching every child the same material in the same fashion will never make all
children the same (Ruf, 2005).
A problem with educating gifted students in mixed-ability classes with grade-level
academic standards is that gifted learners are less likely to have learning experiences that address
their faster rate of learning or larger capacity for complex content (Burney, 2008). Because of a
lack of challenge, they may not have to make much effort to achieve the basic standards. Instead
of advancing at their own rate, they may learn that school is easy, and when they finally do
experience challenge, they may not know how to deal with it. Children will learn from what they
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experience (Burney, 2008).
The Florida Department of Education, through the Challenge Grant Project, developed
Florida’s Framework for K-12 Gifted Learners. This document, written by Weber, McKee, and
Hairston, and revised in 2013, states that:
Students who are gifted have learning needs that go beyond what is traditionally offered in
the regular classroom. The nature of their abilities, demonstrated or latent, requires
differentiated learning experiences and opportunities for them to maximize their potential.
Experts in the field of gifted education agree that this can be accomplished by providing
students with opportunities to: be unique, to socialize and learn with peers of similar ability
levels, advance at a faster pace as their needs require, tackle more authentic and complex
academic tasks, pursue individual areas of interest frequently and in greater depth or at a greater
level of cognitive challenge, and develop a sense of self and an awareness of the possibilities that
the world has to offer (Rodgers, 2007; Weber, McKee, and Hairston, 2013).
Making use of research-based practice is an important part of conscientious education.
Curriculum and instructional models that have been shown to be effective with gifted learners
exist and should be employed with consistency and rigor so that gifted learners can achieve
optimal learning (Van Tassel-Baska & Brown, 2007). Brulles and Winebrenner (2011) believe
that it is doubtful that one program model can effectively meet the needs of all gifted students,
however effective gifted programs do share some important features; intellectual peer interaction,
flexible grouping, differentiation of curriculum and instruction, continuous academic progress,
continuity of support services and teachers with specialized training in gifted education.
Effective teachers of gifted are able to provide instruction that takes into account the attributes of
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gifted learners, emphasize appropriately challenging curriculum, and encourage divergent, critical
thinking (Brulles & Winebrenner, 2011).
Teachers can promote academic gains for gifted students provided the curriculum is
created to support learning at multiple ability levels, the teachers are experienced with and
knowledgeable about the content, and the classroom environment supports collaborative learning
and challenges all students. Differentiation allows teachers to support all learners and particularly
gifted learners (Pierce, Cassady, Adams, Speirs, Neumeister & Cross, 2011). Rakow (2012)
explains that for differentiation to be effective with gifted learners teachers need to be
knowledgeable in above grade and in depth content, resources and innovative instructional
strategies.
Developers of programs for the gifted rarely evaluate the success of their programs. One
reason for this is that “success” in teaching gifted and talented students is difficult to assess
(Davis & Rimm, 2004). Results of the research indicate that there are differences in cognitive
and affective outcomes across all program types. For this reason it is strongly suggested that
educators do continuing evaluation of their programs to monitor and focus on all students’ needs
(Delcourt, Cornell, & Goldberg, 2007). According to Davis and Rimm, “There are two ways in
which evaluation information can be used: to approve or to improve” (2004).
Reis explains that research has rarely studied if and how students in gifted programs
benefit from participation and what else could be done for gifted students (2013). A continuum
of services should include a variety of approaches such as acceleration, counseling, consistent
modification and differentiation of curriculum, separate classes, as well as a pull-out model.
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Reis (2013, p. 1) states:
If we could imagine a perfect learning situation for every advanced learner, it might
include some of the following: opportunities for advancement through the regular
curriculum at an appropriately challenging rate and pace; depth and advanced content;
independent, self-directed learning challenges; independent study; and varied learning
opportunities based on interest, learning styles, product preferences and modality
preferences.
Gifted Program Service Delivery Models
Research indicates that ability grouping is beneficial for all students and is particularly
impactful for academically advanced students. Gains on standardized tests are most substantial
when programs involve acceleration of instruction. Enrichment classes provide students with a
more varied educational experience, but improve test scores more moderately (Kulik, 1993; Van
Tassel-Baska & Reis, 2004). Ability grouping has minimal effects on the self-esteem of students
(Kulik, 1993).
Acceleration and ability grouping are critical and contentious issues in gifted education
(Borland, Horton, Subotnik, Shiang-Jiun, Freeman, Goldberg, &Yu, 2002). There are many
myths and misconceptions associated with these issues that influence the thinking and decision
making of parents and educators. Special schools and full-time self-contained classes for gifted
students resemble tracking in some respects and often are assumed to carry the negative effects of
full scale school-wide tracking. Research however has shown these programs to be among the
most academically effective options for gifted learners (Borland, et al, 2002). Rogers (1993)
believes gifted students require some type of ability grouping to accomplish learning goals
expeditiously because grouping allows for differentiated pacing and a broader more extensive
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curriculum. Never the less, Rogers admits that criticisms of tracking are legitimate and must be
addressed (1993).
The part-time pull-out enrichment class is the most typical, less permanent form of ability
grouping that resembles tracking the least. According to Rogers (1993), enrichment pull-out
programs provide significant increases in achievement, critical thinking, and creative thinking for
gifted students and those gains are greatest when the pullout program content is an extension of
regular classroom curriculum. Unfortunately, many parents and educators believe that part-time
pull-out programs provide little academic advantage for gifted students. The research literature is
inconclusive but involves contentious issues such as race, social class, economic status and
inequality (Borland, et al., 2002). Although parents of gifted students appreciate gifted services,
others deem these services elitist because they are frequently seen as serving more well-to-do
white children than impoverished and minority students (Brulles &Winebrenner, 2012).
Van tassel-Baska and Reis (2004) state that the manner in which gifted students are
grouped and the curriculum and instructional options offered are what is critical. Differentiation
of instruction to meet the needs and abilities of students is the key to enhancing learning within
any grouping model. Van tassel-Baska and Reis (2004) provide results of their research on the
strengths and weaknesses of different gifted service delivery models. The strengths of the part-
time pull-out gifted model include; opportunities for peer interaction, a curricular focus on
comprehensive, complex study or new content learning. For the teacher, this model requires just
one lesson plan. Weaknesses of the part-time pull-out model include lack of connection to
general education class content and only partial differentiation of curriculum. Strengths of the
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full-time gifted grouping include; complete differentiation of curriculum, an intellectual peer
group for gifted students, and flexible grouping options for teachers. The only weakness noted
with this model is that it is sometimes viewed as more extreme than other models. One of the
part-time special class model’s strengths is the ability to accommodate a wide variety of students
with academic and artistic gifts. This model also provides options for students with asynchronous
patterns of development. Weaknesses of the part-time special class model include the
possibilities of limited subjects, insufficient differentiation of curriculum and watered down
content to meet the needs of non- gifted learners in the model (Vantassel-Baska & Reis, 2004).
There are large variances within the gifted population, and it is a fallacy to believe that
one type of program or delivery model will meet the academic and affective needs of all gifted
students. Programming considerations include; the degree of giftedness, the racial, cultural and
socioeconomic differences, gender, talent area, the student’s home life, additional exceptionalities
or learning disabilities, physical challenges, and emotional illness within the child (Robinson et
al., 2007).
Summary
Gifted students’ cognitive, affective, and motivational characteristics are connected and
interactive. They cannot be separated from the methods we employ to develop gifted behaviors
in students of high potential (Renzulli, 2012). As we review the manner in which the United
States addresses issues involving educating gifted children, we find a large variety of options;
however there are many areas of deficiency and little consistency from one state to another
(Robinson, 1999). Therefore, the purpose of this study is to look at the two models offered in the
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district where this study takes place and to investigate if a relationship exists between the chosen
model of gifted service delivery, a student’s academic achievement, and his or her perceptions
regarding social/emotional development and well- being.
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CHAPTER III
RESEARCH METHOD
Participants
This chapter describes the methods used to research the relationship between a full-time or
part-time gifted program placement on student achievement and student perception of the
cognitive and affective impact of their program placement in middle schools in one large
Southwest Florida School District. The Florida Department of Education defines a gifted student
as, “one who has superior intellectual development and is capable of high performance, including
those with demonstrated achievement and/or potential ability.” To be eligible for gifted program
services in the district where the research took place, a student must demonstrate a need for a
program, a majority of characteristics of gifted students according to a standard scale or checklist,
and superior intellectual development as measured by an intelligence quotient of two standard
deviations or more above the mean on an individually administered standardized test of
intelligence. A gifted student may also be a member of an under-represented group and meet the
criteria specified in an approved school district plan for increasing participation of under-
represented groups in gifted programs. The state of Florida requires that all students that qualify
for gifted services are offered the opportunity to receive them. Students in middle schools that
are identified as eligible for program placement may participate in either a full-time or part-time
gifted program service delivery model (SDM). In this Southwest Florida School District, middle
school students in a full-time gifted SDM participate in two to five core academic gifted classes,
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while students in a part-time gifted SDM participate in one gifted class. In both SDMs, classes are
taught by gifted endorsed teachers who are knowledgeable in appropriate strategies for dealing
with academic and affective needs of gifted students. Research was conducted to determine if
students who participated in a full-time gifted SDM had significantly higher achievement scale
scores in reading or mathematics than similar students who chose a part-time gifted SDM.
Additional research was conducted to determine if eighth grade students who participated in a
full-time gifted SDM had significantly higher scores on a student survey than eighth grade gifted
students whose SDM was part-time.
Sample
A convenience sample was used in both parts of this study. A convenience sample is a
sample of the most available subjects in the population. For the analysis of students’ achievement
scores the student sample included all gifted students in a large school district in Southwest
Florida who completed eighth grade in 2014. Middle schools in this district are schools that serve
students in grades six through eight. The school district used in the study had 17 middle schools
in academic year 2013-2014. The sample group was made up of gifted students who participated
in a full-time or part-time gifted SDM during their middle school years. All students in the study
had similar potential for high academic achievement based on their having met the eligibility
criteria for participation in the gifted program. For the analysis of students’ perceptions of their
gifted program experiences, the sample included all gifted students who completed eighth grade
in 2014 and who, with their parent’s permission, agreed to complete the survey.
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Data Source
The student’s academic achievement data for this study was collected from the school
district’s central office Information Systems Department. Archived student data was provided to
the researcher for all ninth grade gifted students who completed eighth grade in district middle
schools in 2014. The students’ gifted program SDM while in middle school was included in that
data along with the student’s reading and mathematics scaled scores, SES status (as measured by
eligibility for the free or reduced lunch program) and ethnicity.
The data collected for the survey aspect of the study was from a survey created for this
study that was based on a sample survey created by Kristie Speirs Neumeister, Ph.D., and
Virginia H. Burney, Ph.D. and included in their book, Gifted Program Evaluation: A Handbook
for Administrators & Coordinators (2012) which was co-published with the National Association
for Gifted Children. The researcher was granted permission from the survey authors to make use
of their questions in designing the survey for this study. The survey questions were adapted for
use with the specific students participating in this study and content validity was established by a
panel of experts and a field test. (See Appendix A). Reliability of the survey was established by
using SPSS to determine Cronbach's alpha reliability coefficients on the sample. The survey
consisted of three domains: Domain C, curriculum and instruction, Domain A, affective needs,
attitudes and guidance, and Domain P, program effectiveness. Domain C had 16 questions,
Domain A had 8 questions and Domain P had 3 questions for a total of 27 questions based on a
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Likert scale format in the survey.
In developing the survey instrument, the panel of five experts consisted of the researcher,
who is gifted endorsed and the teacher on assignment for the district’s gifted program, three
gifted endorsed resource teachers who provide gifted services for gifted high school students, and
the district’s coordinator for the gifted endorsement. The panel used the following criteria to
establish its framework, the survey must: 1) be at an appropriate reading level for gifted students
who have recently completed eighth grade 2) refer to individual student’s perception of the gifted
program in which the student participated. 3) focus on key aspects of gifted programs that would
be present in both service delivery models and 4) be relevant to the objectives of the study. The
survey was administered as a field test to 16 gifted students who had participated in the gifted
program while in middle school. The researcher used SPSS to compute the Cronbach’s alpha
reliability coefficient on the students’ survey data for each of the domains included in the survey.
For Domain 1, Curriculum and Instruction, the reliability coefficient was .819. For domain 2,
Affective Needs, Attitudes and Guidance, the reliability coefficient was .837. For domain 3,
Program Effectiveness, the reliability coefficient was .834.which indicates a high level of internal
consistency. According to George and Mallery (2003), the closer the Cronbach’s alpha
coefficient is to1.0 the greater the internal consistency. The following rules for interpreting the
Cronbach’s alpha are applicable: ≥ .9 = Excellent, ≥ .8 = Good, ≥ .7 = Acceptable, ≥ .6 =
Questionable, ≥ .5 = Poor and ≥ .5 = Unacceptable” (George & Mallery, 2003. p. 231). The
administration of the survey was expected to take between 10 and 15minutes. The researcher
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works in the district where the survey was administered but does not teach any of the students
who participated in the survey. Parents and students were notified by newsletter (Appendix: B),
by email (Appendix: C), and by mail (Appendix: D) about the survey and student assents
(Appendix: E) for completing the survey were obtained. The survey was administered
electronically or on paper at each of the 13 high school campuses in the district. After
administration, the researcher analyzed mean student scores for each of the survey domains. The
data was used to compare scores between the two SDMs as well as the subgroups of ethnicity and
socioeconomic status within each SDM.
Goals of Research
One of the researcher’s goals with this study was to determine if students in full-time
gifted SDM placement showed a statistically significant difference in mean proficiency level
scores on the FCAT 2.0 reading and/or mathematics assessment than the mean FCAT 2.0
proficiency level scores of gifted students placed in a part-time gifted program SDM. An
additional goal was to determine if there was a statistically significant difference in student’s
responses on a Student Survey of student perceptions of the gifted program. The researcher also
examined if there were any differences in these groups by SES status or ethnicity. The end goal
of the researcher was to provide useful information and insight about strengths and weaknesses of
the two placement options and their impact on academic achievement and affective experiences
of students.
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Research Questions and Hypotheses
Research Questions:
1. Are there statistically significant differences in FCAT reading mean achievement scale scores
for Southwest Florida gifted middle school students when these students participate in a full-time
gifted service delivery model or a part-time gifted service delivery model?
2. Are there statistically significant differences in FCAT mathematics mean achievement scale
scores for Southwest Florida gifted middle school students when these students participate in a
full-time gifted service delivery model or a part-time gifted service delivery model?
3. Are there statistically significant differences in FCAT reading mean achievement scale scores
by SES status or ethnicity for Southwest Florida gifted middle school students when these
students participate in a full-time gifted service delivery model or a part-time gifted service
delivery model?
4. Are there statistically significant differences in FCAT mathematics mean achievement scale
scores by SES status or ethnicity for Southwest Florida gifted middle school students when these
students participate in a full-time gifted service delivery model or a part-time gifted service
delivery model?
5. Are there statistically significant differences in scores in the areas of curriculum, affective
learning, and general program experiences on the Student Survey for students receiving full-time
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gifted program services or part-time gifted program services?
6. Are there statistically significant differences in scores in the areas of curriculum, affective,
learning and general program experiences on the Student Survey by SES status or ethnicity for
Southwest Florida gifted middle school students who participate in a full-time gifted service
delivery model or a part-time gifted service delivery model?
Hypotheses:
1. Differences in reading achievement scale scores for full-time gifted SDM students will not be
statistically significantly different compared to those of students in a part-time gifted SDM.
2. Differences in mathematics achievement scale scores for full-time gifted SDM students will
not be statistically significantly different compared to those of students in a part-time gifted SDM.
3. Differences in reading achievement scale scores for full-time gifted SDM students will not be
statistically significantly different by SES status or ethnicity compared to those of students in a
part-time gifted SDM.
4. Differences in mathematics achievement scale scores for full-time gifted SDM students will
not be statistically significantly different by SES status, gender or ethnicity compared to those of
students in a part-time gifted SDM.
5. Differences in Student Survey scores for full-time SDM students will not be statistically
67
significantly different compared to those of students in a part-time gifted SDM.
6. Differences in Student Survey scores for full-time gifted SDM students will not be statistically
significantly different by SES status or ethnicity compared to those of students in a part-time
gifted SDM.
Dependent Variables
In the state of Florida student achievement in reading and mathematics is measured
through the use of the Florida Comprehensive Assessment Test 2.0 (FCAT 2.0). On the FCAT
2.0, reading and mathematics scores are reported on a developmental scale, which is used to
determine a student’s proficiency level with state standards and to track annual progress from
grade to grade. Reading scale scores range from 140-302 across grades 3 through 10, while
Mathematics scale scores range from 140-298 across grades 3 through 8. Students’ scale scores
on the FCAT 2.0 Reading and Mathematics Assessments were the dependent variables used to
examine the relationship between gifted program placement and student achievement.
For the analysis of Student Survey responses in the study, the dependent variables were
the students’ total scores on the three domains addressed in the survey which were curriculum and
instruction, affective needs, attitudes, and guidance, and program effectiveness.
Independent Variables
The independent variables in this study were gifted program SDM placement, SES status
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and ethnicity. Only eighth grade gifted students who were in either a full-time gifted program
SDM or a part-time gifted program SDM were part of the study. For the Academic Achievement
aspect of the study, mean achievement scale scores in reading and mathematics were analyzed to
determine if there were statistically significant differences between program placement groups.
Survey scores for each SDM group were also analyzed to determine if there were statistically
significant differences between SDM groups.
RESEARCH DESIGN
Design
The study design was causal comparative. A causal-comparative design is one that seeks
to find relationships between independent and dependent variables by comparing two or more
groups. For this study the groups being compared were made up of gifted students in the full-time
SDM placement and gifted students in the part-time SDM.
Data Analysis Procedures
Descriptive statistics was used to describe the sample being studied to include the
frequency of groups and subgroups.
Question 1
Gifted students who were in full-time SDMs were identified along with their FCAT 2.0
reading scale scores. Gifted students who were in part-time SDMs were identified along with
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their FCAT reading scale scores. Mean reading scores for each group were examined using
Statistical Package for Social Services (SPSS). An independent samples t-test was run to analyze
the mean reading achievement scale scores for each group and determine if there was a difference
that was statistically significant between the full-time SDM group and the part-time SDM group.
A study wide alpha level of .05 was used to determine significance.
Question 2
Gifted students who were in full-time SDMs were identified along with their FCAT 2.0
math scale scores. Gifted students who were in part-time SDMs were also identified along with
their FCAT math scale scores. Mean math scores for each group were examined using Statistical
Package for Social Services (SPSS). An independent samples t-test was run to analyze the mean
math achievement scale scores for each group and determine if there was a difference that was
statistically significant between the full-time SDM group and the part-time SDM group. An alpha
level of .05 was used to determine significance.
Question 3
Full-time and part-time SDM gifted students FCAT 2.0 scale scores in reading were
analyzed using SPSS by subgroups of SES and ethnicity using 2 factorial analyses of variances
(ANOVAs). An alpha level of .05 was again used to determine if a significant difference existed
between subgroups.
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Question 4
Full-time and part-time SDM gifted students FCAT 2.0 scale scores in math were
analyzed using SPSS by subgroups of SES and ethnicity using 2 factorial analyses of variances
(ANOVAs). An alpha level of .05 was used to determine if a significant difference existed
between subgroups.
Question 5
Using SPSS students were examined by gifted SDM and student survey responses in each
domain were analyzed by means of an independent samples t-test to determine if there was a
significant statistical difference between Student Survey responses of full and part-time SDM
groups at the .05 alpha level.
Question 6
Students in each gifted SDM group were examined by SES and ethnicity using SPSS. Six
factorial ANOVAs were run to determine if there was a significant statistical difference in
Student Survey responses of full and part-time SDM groups by subgroups for each of the sub
scores at .05 alpha levels.
ASSUMPTIONS, LIMITATIONS, AND DELIMITATIONS
Assumptions
1. It is assumed that the FCAT 2.0 reading and mathematics assessments are valid and reliable
instruments for determining student’s academic achievement.
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2. It is assumed that the Student Survey is a valid and reliable instrument for determining student
perceptions of their program.
3. It is assumed that assessment instruments and criteria used to determine eligibility for gifted
program services are valid and reliable instruments for determining innate intellectual ability and
learner characteristics.
Limitations of the Study
1. The type of curriculum used in the full-time and part-time SDM is not controlled.
2. The quality of instruction in individual classrooms within the two SDMs may not be the same.
3. Level of parental support and involvement in students’ schooling may not be the same.
4. Individual student motivation toward achievement varies from student to student.
5. The size of the sample for the survey is limited to those who chose to participate.
6. The sample is not random.
Delimitations
1. The results of this study could only be generalizable to eighth grade gifted students in middle
schools with similar demographics and similar SDMs to those in the large Southwest Florida
school district in which this study will be conducted.
2. The survey instrument used a Likert scale to measure the quantitative data. Although it did
include the option of open-ended comments in each domain, very few students opted to include
comments and the researcher did not analyze the comments for this study. This may have
resulted in restricted responses.
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CHAPTER IV
RESULTS
This causal comparative research study’s primary purpose was to determine if a
relationship exists between gifted service delivery model (SDM) placement and performance on
the reading and/or mathematics subtests of the Florida Comprehensive Assessment Test 2.0
(FCAT 2.0). An additional purpose was to determine if a relationship exists between ethnicity
and socioeconomic status (SES) with regard to reading and/or mathematics academic
achievement on the FCAT 2.0. The final purpose of the study was to look at the students’
perceptions of their academic, social and emotional experiences while participating in either the
part-time or full-time gifted SDMs.
This chapter will present the quantitative findings of the research study. The study
explored the mean differences between each of the following variables: SDM, ethnicity, SES,
reading and mathematics FCAT 2.0 scores and student perceptions of their experiences within the
two service delivery models. The quantitative findings will be discussed by each of the research
questions examined in the study.
Descriptives
SPSS 22 was the statistical program used to compute the quantitative findings.
Descriptives analyses were used to gain information on the student sample, which was a
convenience sample. It was made up of all students identified as gifted who completed middle
school during school year 2013-2014 in a district in Southwest Florida. The total number of
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students in the sample for academic achievement scores was 533. The number of students in the
sample who had participated in a full-time gifted service delivery model in middle school was
285 or 53.1 percent. The number of students in the sample who had participated in a part-time
gifted service delivery model was 248 or 46.2 percent. In Table 1 a relatively balanced sampling
between the two groups of students is shown.
Table 1
Total Student Sample by SDM
n %
Full-time 285 53.1
Part-time 248 46.2
Total 533
Another important aspect of the student sample was the ethnic makeup of the students.
Because this was a convenience sample, the frequency of the different ethnicities could not be
controlled. The numbers of students in each ethnic category are shown in Table 2. While the
ethnic makeup of the student sample was not equally distributed the sample did show a diverse
population overall with meaningful representation for each ethnic group except for the Native
American group which was too small.
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Table 2
Total Student Sample by Ethnicity
Ethnicity
n %
White 363 67.6
Black 29 5.4
Hispanic 103 19.2
Asian 18 3.4
Multiracial 19 3.5
Native
American 1 .2
Total 533 99.3
The next attribute of the student sample that was relevant to the research questions was the
socioeconomic status of the students in the sample. SES status was determined by each student’s
free or reduced lunch status. The number of students who were identified as low SES and the
number of students not identified as low SES are indicated in Table 3.
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Table 3
Total Student Sample by SES status
n %
Low SES 220 41.3
Not Low
SES 313 58.7
Total 533 100.0
All students in the sample had achievement scale scores reported for the 2014 FCAT 2.0
Reading and the FCAT 2.0 Mathematics Achievement Tests. For the Reading portion of the
FCAT 2.0 test the highest scale score reported within the student sample was 296 while the
lowest score reported for the sample was 222. The sample students’ FCAT 2.0 Mathematics scale
scores ranged from a high of 298 and a low of 226. For both of these tests the scores overall were
similar. The mean scores for the reading and mathematics portions of the test as well as the
standard deviations are displayed in Table 4. The similarity of these results was to be expected as
the students in the sample had all met the criteria for gifted services which included high ability
and high achievement.
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Table 4
Reading and Mathematics Scale Scores
Scores
Minimum Maximum M SD
FCAT Reading Scale Score (n=533) 222.00 296.00 264.64 16.04
FCAT Mathematics Scale Score (n=533) 226.00 298.00 262.59 14.01
Research Question 1
For the first question of the study the researcher explored whether statistically significant
differences in FCAT reading mean achievement scale scores for Southwest Florida gifted middle
school students existed when these students participated in a full-time SDM or a part-time SDM.
Research Hypothesis: There is not a statistically significant difference in FCAT reading mean
achievement scale scores for Southwest Florida gifted middle school students when these students
participate in a full-time SDM or a part-time SDM.
Statistical Hypothesis: H0: µSDM 1 = µSDM 2
An independent samples t-test was run to compare the mean scale scores on the FCAT 2.0
Reading test of the students in the full-time and part-time SDMs. The differences in mean scores
for each group are shown in Table 5.
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Table 5
Group Mean FCAT Reading Scale Scores
Group M
Full-time SDM (n=285) 267.38
Part-Time SDM (n=248) 261.48
The differences in mean reading scores between the two SDM groups was found to be
statistically significant (t (531) = 4.30, p = .00); therefore, the null hypothesis was rejected. The
mean of the part-time SDM group was significantly lower (m = 261.48, SD = 15.85) than the
mean of the full-time SDM group (m = 267.38, SD = 15.72). The Levene’s test for equality of
variances was .99 which was greater than the established p value of .05 so equal variances were
used. A significant difference in mean reading scores between the two SDMs is shown in Table 6.
78
Table 6
Independent Samples t-test for Equality of Means
t df Sig. (2-
tailed
Mean
Difference
FCAT Reading Scale Score
Equal Variances Assumed
4.30 531 .00 5.90
Research Question 2
In addressing the next research question the researcher looked to discover if there were
statistically significant differences in FCAT mathematics mean achievement scale scores for
Southwest Florida gifted middle school students when these students participated in a full-time
SDM or a part-time SDM.
Research Hypothesis: There is not a statistically significant difference in FCAT math mean
achievement scale scores for Southwest Florida gifted middle school students when these students
participate in a full-time SDM or a part-time SDM.
Statistical Hypothesis: H0: µSDM 1 = µSDM 2
An independent samples t-test was run to compare the mean scale scores on the FCAT 2.0
Mathematics test of the students in the full-time and part-time SDMs. The differences in mean
scores for each group are shown in Table 7.
79
Table 7
Group Statistics of Mean FCAT Math Scale Scores
Group M SD
Full-time SDM (n=285) 264.34 13.92
Part Time SDM (n=248) 260.57 13.87
The mean mathematics scores between the two SDM groups was found to be statistically
significant (t (531) = 3.13, p = .002); therefore, the null hypothesis was rejected. The mean of the
part-time SDM group was significantly lower (m = 260.57, SD = 13.87) than the mean of the full-
time SDM group (m = 264.34, SD = 13.92). The Levene’s test for equality of variances was .78
which was greater than the established p value of .05 so equal variances were used. A significant
difference in mean mathematics scores between the two SDMs is shown in Table 8.
80
Table 8
Independent Samples t-test for Equality of Means
t df Sig. (2-tailed) Mean Difference
FCAT Mathematics Scale Score
Equal Variances Assumed
3.13 531 .002 3.77
Research Question 3
Looking further into the academic achievement of the same sample groups, the researcher
examined whether there were statistically significant differences in FCAT reading mean
achievement scale scores by SES status or ethnicity for Southwest Florida gifted middle school
students when these students participated in a full-time gifted SDM or a part-time gifted SDM.
Research Hypothesis: There are no statistically significant differences in FCAT reading mean
achievement scale scores by SES status or ethnicity for Southwest Florida gifted middle school
students when these students participate in a full-time SDM or a part-time SDM
Statistical Hypothesis: H0: µSDM 1 = µSDM 2
FCAT 2.0 Reading scale scores were analyzed by subgroups of SES and ethnicity using a
2x2 factorial analysis of variance (ANOVA) for SES and a 2x5 ANOVA for ethnicity. An alpha
level of .05 was again used to determine if significant differences existed between subgroups.
The descriptive data for the ANOVA comparing mean reading scores of students in the two
SDMs by SES categories is displayed in Table 9.
81
Table 9
Descriptive Statistics for FCAT Reading Scale Score by SDM and SES
SDM SES M SD n
Full-time Low SES 263.54 16.12 117
Not Low SES 270.05 14.90 168
Total 267.38 15.72 285
Part-time Low SES 259.77 15.731 103
Not Low SES 262.70 15.88 145
Total 261.48 15.85 248
Total Low SES 261.77 16.01 220
Not Low SES 266.65 15.77 313
Total 264.64 16.04 533
There was a main effect on the mean reading scale scores for both SES, F (1, 529) =
11.80, p =.00 and SDM, F (1, 529) = 16.33, p =.00. There was, however, no interaction effect
indicating the reading scores of the SES subgroups were not affected across SDM, F(1,522) =
1.69, p= .19 as shown in Table 10.
82
Table 10
ANOVA Comparing Means of FCAT Reading Scale Score by SDM and SES
Source
Type III Sum
of Squares df Mean Square F Sig.
SDM 3976.57 1 3976.57 16.33 .00
SESSTATUS 2871.98 1 2871.98 11.80 .001
SDM *
SESSTATUS 411.73 1 411.73 1.69 .19
Table 11 includes the descriptive data for the ANOVA comparing mean reading scores of
students in the two SDMs by ethnicity. The sample included students identified as White, Black,
Hispanic, Asian, Multiracial and Native American. Because a convenience sample was used for
the study, the different ethnicities were not represented equally. Although there were six separate
ethnicities represented within the complete sample, there was only one Native American in the
part time SDM and no Native Americans in the SDM group. The data for Native American
students was therefore insufficient to be included in the ANOVA comparing FCAT Reading scale
scores by SDM and Ethnicity.
83
Table 11
Descriptives for FCAT Reading Scale Score by SDM and Ethnicity
SDM Ethnicity M SD n
Full-time White 268.59 15.20 188
Black 258.94 19.34 17
Hispanic 264.77 15.87 60
Asian 270.27 12.38 15
Multiracial 273.40 21.16 5
Total 267.38 15.72 285
Part-time White 262.26 15.76 175
Black 266.08 13.24 12
Hispanic 258.72 17.45 43
Asian 257.67 19.22 3
Multiracial 257.07 13.55 14
Total 261.48 15.89 247
Total White 265.54 15.77 363
Black 261.90 17.19 29
Hispanic 262.24 16.73 103
Asian 268.17 13.90 18
Multiracial 261.37 16.93 19
Total 264.64 16.05 532
84
Although a statistically significant difference in Reading scale scores was found for the
main effect of SDM F (1, 522) = 5.46, p =.02, there was no significant difference found in student
Reading scale scores by the main effect of ethnicity, F (4, 522) = 1.21, p = .30 or by the
interaction of ethnicity with SDM, F (4, 522) = 1.75, p =.14, indicating the reading scores of the
Ethnicity subgroups were not affected across SDM. The data for the ANOVA that compared
FCAT reading scale scores by SDM and ethnicity is displayed in Table 12.
Table 12
ANOVA comparing means of FCAT Reading Scale Scores by SDM and Ethnicity
Source
Type III Sum
of Squares df
Mean
Square F Sig.
Partial Eta
Squared
SDM 1349.30 1 1349.30 5.46 .02 .01
ETHNICITY 1192.87 4 238.58 1.21 .30 .01
SDM *
ETHNICITY 1725.92 4 431.48 1.75 .14 .01
Research Question 4
With the final question on academic achievement scores the researcher considered if there
were statistically significant differences in FCAT mathematics mean achievement scale scores by
SES status or ethnicity for Southwest Florida gifted middle school students when these students
participated in a full-time gifted SDM or a part-time gifted SDM.
Research Hypothesis: There are no statistically significant differences in FCAT mathematics
85
mean achievement scale scores by SES or ethnicity for Southwest Florida gifted middle school
students when these students participate in a full-time gifted SDM or a part-time gifted SDM.
Statistical Hypothesis: H0: µSDM 1 = µSDM 2
FCAT 2.0 Mathematics scale scores were analyzed by the subgroups of SES and ethnicity
using a 2x2 ANOVA for SES and a 2x5 ANOVA for ethnicity. An alpha level of .05 was used to
determine if significant differences existed by subgroups. Descriptives for the FCAT 2.0
Mathematics Scale Scores by SDM and SES are provided in Table 13.
Table 13
Descriptives for FCAT Mathematics Scale Scores by SDM and SES
SDM SES M SD n
Full-time Low SES 262.09 13.35 117
Not Low SES 265.92 14.12 168
Total 264.34 13.92 285
Part-time Low SES 258.27 12.73 103
Not Low SES 262.21 14.44 145
Total 260.57 13.86 248
Total Low SES 260.30 13.17 220
Not Low SES 264.20 14.37 313
Total 262.59 14.01 533
A statistically significant difference in mean Mathematics scale scores was found between
the students by the main effects of SES F(1, 529 ) = 10.20, p =.001 and SDM, F(1, 529 ) = 9.58,
86
p = .002, however, there was no statistical difference identified for the interaction of SDM and
SES, F(1, 529 ) =.002, p =.966 as shown in Table 14.
Table 14
ANOVA comparing means of FCAT Mathematics Scale Scores by SDM
Source
Type III Sum
of Squares df
Mean
Square F Sig.
SDM 1819.71 1 1819.71 9.58 .002
SESSTATUS 1939.09 1 1939.09 10.20 .001
SDM *
SESSTATUS .35 1 .347 .002 .966
Table 15 includes the descriptive data for the ANOVA comparing mean Mathematics
scale scores of students in the two SDMs by ethnicity. Again the data for Native Americans was
insufficient to be included in the ANOVA comparing FCAT Mathematics scale scores by SDM
and Ethnicity.
87
Table 15
Descriptives for FCAT Mathematics scale scores by SDM and Ethnicity
SDM Ethnicity M SD n
Full-time White 265.73 13.83 188
Black 253.82 10.77 17
Hispanic 261.67 13.95 60
Asian 270.67 12.22 15
Multiracial 261.20 11.17 5
Total 264.34 13.92 285
Part-time White 260.33 13.99 175
Black 263.00 9.71 12
Hispanic 261.14 13.52 43
Asian 268.33 20.98 3
Multiracial 256.50 14.73 14
Total 260.57 13.86 248
Total White 263.13 14.15 363
Black 257.62 11.16 29
Hispanic 261.45 13.71 103
Asian 270.28 13.25 18
Multiracial 257.74 13.75 19
Total 262.59 14.01 532
88
No statistically significant difference in Mathematics scale scores was found for the main
effects of SDM, F (1, 522) = .09, p = .77 or ethnicity, F (4, 522) = 1.83, p = .12. Additionally
there was no interaction effect indicating that the Mathematics scale scores of the ethnicity
subgroups are not affected across SDM, F(4, 522) = 2.24, p =.06. The data for the ANOVA that
compared FCAT Mathematics scale scores by SDM and ethnicity is displayed in Table 16.
Table 16
ANOVA for FCAT Mathematics Scale Score by SDM and Ethnicity
Source
Type III Sum
of Squares df
Mean
Square F Sig.
Partial Eta
Squared
SDM 16.54 1 16.54 .09 .77 .00
ETHNICITY 1859.23 4 344.62 1.83 .12 .01
SDM *
ETHNICITY 1685.99 4 421.50 2.24 .06 .02
Research Question 5
After receiving the 99 completed surveys from the students in the sample whose parents
consented to their participation in the study, the researcher analyzed their responses to determine
if there were statistically significant differences in scores in the areas of curriculum, affective
needs, attitudes and guidance and general program experiences on the Student Survey for students
who received full-time gifted program services or part-time gifted program services.
Research Hypothesis: There are no statistically significant differences in scores in the areas of
89
curriculum, affective needs, attitudes and guidance and general program experiences on the
Student Survey for students who received full-time gifted program services or part-time gifted
program services.
Statistical Hypothesis: H0: µSDM 1 = µSDM 2
The sample for the student survey was determined by the number of parents who provided
consent for their child to participate as well as the students providing assent for participation.
Because this was strictly voluntary, the sample did not contain equal numbers of full and part-
time students nor were the subgroups of ethnicity and SES represented equally. Student survey
responses were analyzed by means of three independent samples t- tests to determine if there was
a significant statistical difference between student survey responses of full and part-time SDM
groups in each of three survey domains at the .05 alpha levels. The three domains included in the
survey were: Domain C (Curriculum and Instruction), Domain A (Affective Needs, Attitudes and
Guidance), and Domain P (Program Effectiveness). Group statistics and differences in mean
scores for each group for the t-test for Domain C are shown in Table 17.
Table 17
Group Statistics of t-test for Domain C
SDM M
C Total Full-time (n=58) 45.84
Part-time (n=41) 46.12
For Domain C, curriculum and instruction, the difference in mean student response score
90
totals between the two SDM groups was not found to be statistically significant (t (97) = -.14, p =
.89); therefore, the null hypothesis was accepted. The mean of the part-time SDM group was not
significantly different (m = 46.12, SD = 10.22) than the mean of the full-time SDM group (m =
45.84, SD = 8.88). The Levene’s test for equality of variances was .28 which was greater than the
established p value of .05 so equal variances were used. Although the mean response score totals
for the full-time group were slightly lower than the mean response score totals for the part-time
group, no statistically significant difference is shown in Table 18.
Table 18
Independent Samples t-test for Equality of Means
t df Sig. (2-
tailed
Mean
Difference
Domain C Score
Equal Variances Assumed
-.14 97 .89 -.28
A second independent t- test was run for student responses in Domain A. Group statistics
and differences in mean scores for each group for the independent t-test for Domain A are
provided in Table 19.
91
Table 19
Group Statistics of t-test for Domain A
SDM M
A Total Full-time (n=58) 10.02
Part-time (n=41) 9.98
For Domain A, affective needs, attitudes, and guidance, no statistically significant
difference in mean student response scores between the two SDM groups was found (t (97) =
1.24, p =.22); therefore, the null hypothesis was accepted. The mean of the part-time SDM group
was not significantly different (m = 21.89, SD = 6.33) than the mean of the full-time SDM group
(m = 23.24, SD = 4.64). The Levene’s test for equality of variances was .01 which was less than
the established p value of .05 so equal variances was not assumed. Although the mean response
scores for the full-time group were slightly higher than the mean response scores for the part-time
group, no statistically significant difference is shown in Table 20.
92
Table 20
Independent Samples t-test for Equality of Means Domain A
t df Sig. (2-
tailed
Mean
Difference
Domain A Score
Equal Variances Assumed
1.24 97 .22 1.36
A third independent t- test was run for student responses in Domain P, program
effectiveness, Group statistics and differences in mean scores for each group for the t-test for
Domain P are provided in Table 21.
93
Table 21
Group Statistics of t-test for Domain P
SDM M
P Total Full-time (n=58) 10.02
Part-time (n=41) 9.98
For Domain P, the difference in mean student response scores between the two SDM
groups was not found to be statistically significant (t (97) = .11, p = .91); therefore, the null
hypothesis was accepted. The mean of the full-time SDM group was not significantly different (m
= 10.02, SD = 1.73) than the mean of the part-time SDM group (m = 9.98, SD = 1.92). The
Levene’s test for equality of variances was .28 which was greater than the established p value of
.05 so equal variances were used. Although the mean response scores for the full-time group
were slightly higher than the mean response scores for the part-time group, no statistically
significant difference is shown in Table 22.
94
Table 22
Independent Samples T-Test for Equality of Means
t df Sig. (2-
tailed
Mean
Difference
Domain P Score
Equal Variances Assumed
.11 97 .91 .04
Research Question 6
Looking further into the students’ survey responses, the researcher wanted to determine if
there were statistically significant differences in scores in the domain areas of curriculum and
instruction, affective needs, attitudes, and guidance, and general program effectiveness on the
student survey by subgroups of SES status or ethnicity for Southwest Florida gifted middle school
students who participate in a full-time gifted SDM or a part-time gifted SDM.
Research Hypothesis: There are no statistically significant differences in mean student total
scores in the areas of curriculum, affective needs, attitudes, and guidance, and general program
experiences on the student survey by SES or ethnicity for Southwest Florida gifted middle school
students who participate in a full-time gifted SDM or a part-time gifted SDM
Statistical Hypothesis: H0: µSDM 1 = µSDM 2
Six factorial ANOVAs were run to determine if there was a significant statistical
difference in mean student survey response totals of full and part-time SDM groups by domain
for each of the subgroup scores at .05 alpha levels. The results of the ANOVAs are discussed for
each domain by the main effects and interactions of each SDM with each subgroup. Mean
95
student response totals for each domain in the survey were analyzed by subgroups of SES and
ethnicity using a 2x2 factorial analysis of variance (ANOVA) for SES and a 2x5 ANOVA for
ethnicity. Table 23 includes descriptive statistics for the Domain C ANOVA for SDM and SES.
Table 23
Descriptives for Domain C SDM by SES
SDM SES M SD n
Full-time low SES 50.44 6.03 16
not low SES 44.10 9.21 42
Total 45.84 8.88 58
Part-time low SES 50.00 8.25 14
not low SES 44.11 10.70 27
Total 46.12 10.23 41
Total low SES 50.23 7.03 30
not low SES 44.10 9.74 69
Total 45.96 9.41 99
A statistically significant difference in mean student responses for Domain C was found
by the main effect of SES F(1, 95 ) = 768.07, p =.003; however there was no statistical difference
identified for the main effect of SDM alone, F(1, 95 ) = .91, p = .917 nor the interaction of SDM
and SES, F(1, 95) =1.05, p =.910 indicating that the mean student survey scores of the ethnicity
subgroups are not affected across SDM for Domain C as shown in Table 24.
96
Table 24
ANOVA for Survey Domain C SDM and SES
Source
Type III Sum
of Squares df
Mean
Square F Sig.
Partial Eta
Squared
SDM .92 1 .91 .011 .92 .00
SES 768.07 1 768.07 9.25 .003 .09
SDM * SES 1.06 1 1.06 .013 .91 .00
For the Domain C ANOVA for SDM and ethnicity there were too few students identified
as Black or Asian in the part time SDM which resulted in no means comparisons included for
those subgroups in the descriptive statistics shown in Table 25.
97
Table 25
Descriptives for Domain C SDM and Ethnicity
No statistically significant difference in mean student responses for Domain C were found
by the main effects of SDM, F(1, 89) = 1.29, p =.26, ethnicity, F(4, 95 ) = .91, p = .92 nor the
interaction of SDM and ethnicity, F(4, 95) = 1.05, p =.91 indicating that the mean student survey
SDM Ethnicity M SD n
Full-time White 45.25 9.43 44
Black 55.50 2.12 2
Hispanic 44.40 6.69 5
Asian 47.20 7.43 5
Mixed Race 49.50 3.54 2
Total 45.84 8.88 58
Part-time White 45.35 10.82 31
Black 39.00 . 1
Hispanic 50.80 5.31 5
Asian 32.00 . 1
Mixed Race 53.33 3.51 3
Total 46.12 10.22 41
Total White 45.29 9.96 75
Black 50.00 9.64 3
Hispanic 47.60 6.62 10
Asian 44.67 9.09 6
Mixed Race 51.80 3.70 5
Total 45.96 9.41 99
98
scores of the ethnicity subgroups are not affected across SDM for Domain C of the survey as
shown in Table 26.
Table 26
ANOVA for Survey Domain C SDM and Ethnicity
Source
Type III Sum
of Squares df
Mean
Square F Sig.
Partial Eta
Squared
SDM 114.42 1 114.42 1.29 .26 .01
Ethnicity 334.89 4 83.72 .94 .44 .04
SDM *
Ethnicity 494.21 4 123.55 1.39 .24 .06
Descriptives for the ANOVA for mean student responses totals for Domain A for SDM
and SES are shown in Table 27.
99
Table 27
Descriptives for Survey Domain A SDM and SES
SDM SES M n
full-time low SES 25.25 16
Not low
SES 22.48 42
Total 23.24 58
part-time low SES 25.15 14
Not low
SES 20.19 27
Total 21.88 41
Total low SES 25.20 30
Not low
SES 21.58 69
Total 22.68 99
A statistically significant difference was found in mean student response totals for
Domain A by the main effect of SES, F(1,95) =11.60, p=.001; however there was no significant
difference found for the main effect of SDM, F(1,95) =1.12, p= .29, nor the interaction of SDM
and SES, F(1,95) = .93, p = .34 indicating that the mean student survey score totals of the SES
subgroups are not affected across SDM for Domain A as shown in Table 28.
100
Table 28
ANOVA for Survey Domain A SDM and SES
Source
Type III Sum
of Squares df
Mean
Square F Sig.
Partial Eta
Squared
SDM 29.53 1 29.53 1.12 .29 .01
SES 306.90 1 306.90 11.60 .001 .11
SDM * SES 24.49 1 24.49 .93 .34 .01
For the Domain A ANOVA for SDM and ethnicity there were too few students identified
as Black or Asian in the part-time SDM subgroup which resulted in no means comparisons
included for those subgroups in the descriptive statistics shown in Table 29.
101
Table 29
Descriptives for Domain A SDM and Ethnicity
For the ANOVA for mean student survey response totals in Domain A for SDM and
ethnicity a statistically significant difference in mean student response totals was found for the
SDM Ethnicity Mean n
Full-time White 22.84 44
Black 29.50 2
Hispanic 24.20 5
Asian 22.20 5
Mixed Race 26.00 2
Total 23.24 58
Part-time White 21.81 31
Black 17.00 1
Hispanic 22.60 5
Asian 12.00 1
Mixed Race 26.33 3
Total 21.88 41
Total White 22.41 75
Black 25.33 3
Hispanic 23.40 10
Asian 20.50 6
Mixed Race 26.20 5
Total 22.68 99
102
main effect of SDM, F(1, 89) =5.50, p = .02 however; no statistically significant differences were
found in student response totals for the main effect of ethnicity, F(4,89) =1.52 , p = .20, nor the
interaction of SDM and ethnicity, F(4,89 ) = 1.33, p = .27 indicating that the mean student survey
score totals of the ethnicity subgroups are not affected across SDM for Domain A as shown in
Table 30.
Table 30
ANOVA for Survey Domain A SDM and Ethnicity
Source
Type III Sum
of Squares df Mean Square F Sig.
Partial Eta
Squared
SDM 156.72 1 156.72 5.50 .02 .06
Ethnicity 173.54 4 43.39 1.52 .20 .06
SDM *
Ethnicity 151.00 4 37.75 1.33 .27 .06
Descriptives for the ANOVA for mean student response totals for Domain P for SDM and
SES are shown in Table 31.
103
Table 31
Descriptives for Domain P SDM and SES
SDM SES M n
Full-time low SES 10.50 16
Not low
SES 9.83 42
Total 10.02 58
Part-time low SES 10.71 14
Not low
SES 9.60 27
Total 9.98 41
Total low SES 10.60 30
Not low
SES 9.74 69
Total 10.00 99
A statistically significant difference in mean student response totals for Domain P was
found for the main effect of SES subgroup, F(1,95) = 5.18, p=.03; however no significant
difference in mean student response totals was found for the main effect of SDM, F(1,95) =
.001, p = .97, nor the interaction of SDM and SES, F(1,95) = .34, p = .56 indicating that the mean
student survey score totals of the SES subgroups are not affected across SDM for Domain P as
shown in Table 32.
104
Table 32
Anova for Survey Domain P SDM and SES
Source
Type III Sum
of Squares df
Mean
Square F Sig.
Partial Eta
Squared
SDM .004 1 .004 .001 .97 .00
SES 16.42 1 16.42 5.18 .03 .05
SDM * SES 1.06 1 1.06 .34 .56 .004
For the Domain P ANOVA for SDM and ethnicity there were too few students identified
as Black or Asian in the part time SDM which resulted in no means comparisons included for
those subgroups in the descriptive statistics shown in Table 33.
105
Table 33
Descriptives Survey P SDM and Ethnicity
SDM Ethnicity M n
Full-time White 10.05 44
Black 12.00 2
Hispanic 10.20 5
Asian 8.80 5
Mixed Race 10.00 2
Total 10.02 58
Part-time White 9.94 31
Black 10.00 1
Hispanic 10.00 5
Asian 7.00 1
Mixed Race 11.33 3
Total 9.98 41
Total White 10.00 75
Black 11.33 3
Hispanic 10.10 10
Asian 8.50 6
Mixed Race 10.80 5
Total 10.00 99
106
No statistically significant differences were found in mean student responses for Domain
P for SDM, ethnicity, or the intersection of SDM and ethnicity indicating that the mean student
survey score totals of the ethnicity subgroups are not affected across SDM for Domain P as
shown in Table 34.
Table 34
Anova for Survey Domain P SDM and Ethnicity
Source
Type III Sum
of Squares df
Mean
Square F Sig.
Partial Eta
Squared
SDM 1.93 1 1.93 .60 .44 .01
Ethnicity 19.60 4 4.90 1.51 .20 .06
SDM *
Ethnicity 7.22 4 1.81 .56 .70 .02
Summary
Analysis of the quantitative data for academic achievement of the students in the study
indicates that a relationship exists between the SDM in which the students participated during
middle school and their scores on the FCAT 2.0 assessment for both mathematics and reading.
There also was a relationship found between SES group and mathematics and reading scores for
gifted students in the study. Analysis of the survey data revealed a relationship between SES and
student responses to survey questions in all domains and both SDMs. No other relationships were
found within or between survey variables.
107
CHAPTER V
DISCUSSION
Services provided in the two different service delivery model (SDM) placements are
apparent factors in gifted students’ academic achievement as well as their perceptions of their
gifted program experiences while in middle school. Analysis of the research literature suggests
that variables such as SDM, Socio Economic Status (SES) and ethnicity may play a critical role in
students’ academic achievement as well as the level of their feelings of satisfaction with their
experiences within a gifted program.
The goal of this causal comparative study was to examine if and how the variables of
SDM, SES and ethnicity relate to gifted students’ academic achievement and their perceptions of
their experiences in the gifted program in middle school. The results presented in this research
study support previous research in the field as well as raise new questions for future research.
OVERVIEW OF RESEARCH RESULTS
This quantitative research study investigated six research questions that focused on two
separate aspects of student outcomes as a result of completing middle school while participating
in a gifted program. The first four questions of the study looked at students’ achievement scores
on the FCAT 2.0 for reading and mathematics. Student scores were analyzed statistically in SPSS
using Descriptives, independent samples t-tests and factorial ANOVAs to compare students’
mean scores for each subject area by the independent variables of SDM, SES, and ethnicity to
108
better understand how the different independent variables affect the dependent variable of student
achievement scores.
The last two research questions focused on students’ perceptions of their experiences in a
gifted program while in middle school. Student responses to a survey were analyzed using
Descriptives, independent samples t–tests and factorial ANOVAs to determine relationships
between the independent variables of SDM, SES and ethnicity with the dependent variable of
survey response scores. The survey was based on a handbook written by Neumeister and Burney
(2012) with the authors’ permission and adapted with permission from the authors for use with
this study (See Appendix A). Validity was established by a panel of experts and the survey was
field tested for reliability and analyzed using Cronbach’s alpha reliability coefficient (See
Appendix F).
The following section will be organized around topics covered in the existing literature as
well as those that emerged as a result of this study.
Excellence versus Equity
Historically, the conflict between the ideals of excellence and equity has negatively
impacted support for gifted education (Delisle, 2014; Jolly, 2009). One of the most common
myths that impact attitudes and educational policies about gifted students is that their giftedness is
innate, and therefore, they will be successful on their own. This misconception leads to opposition
toward providing appropriately differentiated learning experiences and encourages the mistaken
notion that excellence and equity are separate and opposing concepts (Clark, 1997). The academic
109
achievement findings for research questions 1-4 provide support for the idea that gifted students
do benefit from full-time gifted SDMs with increased academic achievement, disproving the myth
that they can reach their full potential on their own without special programs. Students in the
study who participated in the full-time gifted SDM had significantly higher mean scale scores on
both the Reading and Mathematics sections of the FCAT 2.0 achievement test than those students
who participated in the part-time SDM. Additionally, mean scale scores for low SES students
participating in a full-time SDM were significantly higher than scores for low SES students
participating in a part-time SDM. Further research could be done to compare mean scores of
gifted ability students who did not receive any gifted services to gifted students who participated
in the different SDMs.
Identification of Diverse Populations of Gifted Learners
Cohen (1990) explains that common processes used to identify gifted students have
traditionally been developed for use with middle class, native English speaking students which
can result in an underrepresentation of diverse students in gifted programs. This has proven to be
the case in the district where this study took place. Although steps have been taken to increase
the numbers of diverse students in gifted programs, the percentage of White students remains
significantly higher in the gifted population than in the population as a whole. Hispanic students
were represented fairly strongly in the study sample; however other ethnicities were not as well
represented. There were actually no limited English proficiency students in the convenience
sample that was used for this study. Low SES students were well represented in the sample so
110
that group was able to be included as an independent variable in the study. More research needs
to be done to determine what identification methods are effective in identifying giftedness in all
populations of students.
Gifted Program Service Delivery Models
Cognitive Learning Theory supports the concept that a student’s educational setting is
equally important as their inborn gifted qualities in the development of their potential
achievement (Jordan, 2011). For students in gifted programs SDM placement determines the
educational setting. Acceleration and ability grouping are significant and controversial matters in
the realm of gifted education (Borland, Horton, Subotnik, Shiang-Jiun, Freeman, Goldberg, &Yu,
2002). Many myths and misconceptions exist relative to these issues that continue to influence
decision making of legislators, educators and parents. Although frequently criticized as elitist and
unnecessary, part-time gifted SDMs have been found to produce significantly greater
achievement scores for gifted students than regular education programs (Feldhusen & Moon,
1992). Full-time programs for gifted students are burdened with the negative feelings associated
with school-wide tracking despite the fact that research has shown these programs to be among
the most academically effective options for gifted learners (Borland, et al., 2002). The findings
for the first four research questions of this study support the research of Borland et al. by
revealing that gifted students in full-time SDMs have significantly higher academic achievement
test scores than gifted students in part-time SDMs.
111
Academic and Social/Emotional Needs of Gifted Learners
The main objectives of gifted education are to increase achievement to a level consistent
with students’ potential and to improve their self-concept by providing opportunities to learn and
collaborate with other students of similar interests and abilities (Delcourt, Cornell, and Goldberg,
2007). Findings for the first four research questions indicate that of the SDM options available
the full-time SDM is most effective in meeting the academic aspect of this goal. Overall positive
answers to Affective Needs Attitudes and Guidance (Domain A) and Program Effectiveness
(Domain P) questions on the survey indicate that the gifted program options available in district
middle schools are providing meaningful opportunities for students to work collaboratively with
students of like abilities in the areas of affective needs, attitudes and guidance. In fact, for
Domain A, the mean total score for all students in the survey was 22.68, which when divided by
8, the total number of questions in that domain, yields a mean response of 2.84 with a score of 3
representing a response of “adequately or sufficiently” on the Likert scale. Similarly, for Domain
P, the mean total score for all students in the survey was 10.00, which when divided by 3, the
number of questions in that domain, yields a mean response of 3.3. Again a response of 3 on the
Likert scale represents a response of “adequately or sufficiently.” The results further suggest that
further research into the reasons behind student responses would provide further insight into the
programs’ relationship to positive self-concept and social/emotional development.
Characteristics of Effective Gifted Programs
Few studies have focused on how gifted students benefit from their experiences in gifted
112
programs, or what else could have been done to enhance programs for gifted students (Reis,
2013). Educators are encouraged to do continuing evaluation of their programs to monitor and
focus on all students’ needs (Delcourt, Cornell, & Goldberg, 2007). In the survey aspect of this
study, students were asked about their experiences and the findings provide insights into their
perceptions of program effectiveness. The findings suggest that further investigation into the
reasons behind the responses would provide richer understanding and suggest additional ideas for
program improvement. According to Davis and Rimm (2004), evaluation information can be
used either to approve or to improve programs. Conducting further surveys and interviews of
students on a regular basis would provide opportunities for continuous program improvement.
Needs and Expectations of Parents of Gifted Learners
Parents of gifted children frequently look for guidance in accessing an appropriate
education for their child (Rash, 1998). Educators must provide research based information to
parents to allow them to make informed decisions regarding their children’s education (Pfeiffer,
2008). Program choice is a critical decision that parents make and the findings from this study
should help parents to be better informed about the academic achievement results of the available
SDM choices as well as the students’ perceptions of their experiences in both of the district’s
SDMs.
Summary of Topics and Themes
The samples for the academic achievement aspect of the study and the survey aspect of
113
the study were very different both in size and in the makeup of the subgroups. The academic
achievement portion of the study used a convenience sample that was made up of all current ninth
grade students in the large school district in Southwest Florida who had participated in one of the
two gifted SDMs while in middle school. This sample included 533 gifted students. The survey
sample was made up of 99 of those students whose parents gave consent for them to participate.
These students also assented to participation. Both the survey sample and the academic
achievement sample had unequal representation within SDM, SES and ethnicity groups.
The academic achievement data for both reading and mathematics indicated that there
were significantly higher mean scores reported for gifted students who participated in the full-
time SDM than those students who participated in the part-time SDM. Additionally the reading
and mathematics mean scores of low SES students were lower than those who were not identified
as low SES in both the full-time SDM and the part-time SDM student groups. There were no
significant differences in mean reading or math scores for different ethnic groups for either of the
SDM groups.
The survey response data indicated that SDM had no significant relationship with student
mean response scores for survey questions in any of the three domain areas. Interestingly,
students identified as low SES had higher mean response scores in all three domains for both
part-time and full-time SDMs, indicating more positive perceptions of their experiences in all
three domains than those students not identified as low SES. No differences in mean response
scores were found by ethnic group in either SDM on any of the survey domains. It is important to
114
note that there was low representation in some ethnic groups which affected the output of
ethnicity data.
Assumptions
1. It is assumed that the FCAT 2.0 reading and mathematics assessments are valid and reliable
instruments for determining student’s academic achievement.
2. It is assumed that the Student Survey is a valid and reliable instrument for determining student
perceptions of their program.
3. It is assumed that assessment instruments and criteria used to determine eligibility for gifted
program services are valid and reliable instruments for determining innate intellectual ability and
learner characteristics.
Limitations of the Study
1. The type of curriculum used in the full-time and part-time SDM was not controlled.
2. The quality of instruction in individual classrooms within the two programs may not have been
the same.
3. Level of parental support and involvement in students’ schooling may not have been the same.
4. Individual student motivation toward achievement varies from student to student.
5. The size of the sample for the survey was limited to those who chose to participate.
115
6. The sample was not random.
Delimitations
1. The results of this study could only be generalizable to eighth grade gifted students in middle
schools with similar demographics and similar SDMs to those in the large Southwest Florida
school district in which this study will be conducted.
2. The survey instrument used a Likert scale to measure the quantitative data. Although it did
include the option of open-ended comments in each domain, very few students opted to include
comments and the researcher did not analyze the comments for this study. This may have
resulted in restricted responses.
Implications of Research
It is clear that participation in a full-time SDM results in increased achievement test scores
in both reading and math for gifted middle school students as compared to gifted students who
participated in a part-time SDM. This suggests that more information is needed about what
aspects of the full-time model had a positive effect on academic achievement scores and whether
those aspects would benefit gifted students at the elementary and high school levels as well. It is
also clear that SES is an important factor influencing academic achievement, and that neither of
the available SDM options were able to bridge the gap for low SES students.
Students of low SES do have more positive perceptions of their experiences in a full-time
gifted model than in a part-time gifted model. This was true in all three domains of the survey.
116
This suggests that more information is needed regarding the reasons why low SES students’
perceptions were more positive and whether the full-time model would have a similar effect on
the perceptions of students in other grade levels.
Future Research
While this study has provided information about the effect of SDM on students’ academic
achievement in middle school, further research is suggested regarding effective curriculum
models and instructional strategies that can provide further academic advancement at all grade
levels. As evidenced by the convenience sample used in this study, the field of gifted education
continues to struggle to adequately identify diverse groups of students (Colangelo and Davis
2002). Future research should investigate various identification methods to determine which are
most effective in identifying gifted students from diverse groups. Additionally, the findings of
this study indicate a need for further research into student perceptions of their experiences to
include qualitative research into the reasons behind students’ perceptions of their gifted program
experiences.
Conclusion
Solutions to current societal concerns for national security brought about by the perceived
low level of achievement of students in the United States are in need of discovery. One suggested
solution is to provide quality program choices for all students, including those with high academic
potential, to prepare them to make positive contributions to the national security in the areas of
117
economic growth and competitiveness, physical safety, intellectual property, global awareness,
and countrywide unity and cohesion. Improving program services for high ability gifted students
across various levels of economic status and ethnicities will contribute to the resolution of
concerns about low achievement levels of students in our country. Research based information
about the effects of available service delivery models on gifted students’ achievement and
perceptions of their educational experiences will be useful to those interested in resolving
anxieties about American students’ academic achievements and improving educational options
for students with high potential.
It is further hoped that this study will help inform stakeholders; including district and
school level administrators, policy makers, teachers, parents, and gifted students themselves to
better understand the relationships that exist between academic achievement, SDM, SES,
ethnicity, and student perceptions of their gifted program experiences. This increased
understanding should allow for better decision making and an increased ability to meet the needs
of all gifted students so that they can reach their full potential academically and affectively.
118
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APPENDICES
APPENDIX A
STUDENT SURVEY
130
APPENDIX B
NEWSLETTER
131
APPENDIX C
PARENT NOTIFICATION EMAIL (Page 1 of 2)
132
APPENDIX C
PARENT NOTIFICATION EMAIL (Page 2 of 2)
133
APPENDIX D
NOTIFICATION FOR PARENTS WITHOUT EMAIL
134
APPENDIX E
STUDENT ASSET FORM
135
APPENDIX F
CRONBACH’S ALPHA RELIABILITY COEFFICIENTS FOR STUDENT SURVEY
Reliability Statistics for Domain C
Reliability Statistics for Domain A
Cronbach's
Alpha
Cronbach's
Alpha Based
on
Standardized
Items n
.837 .855 8
Reliability Statistics for Domain P
Cronbach's
Alpha
Cronbach's
Alpha Based
on
Standardized
Items n
.834 .833 3
Cronbach's
Alpha
Cronbach's
Alpha Based
on
Standardized
Items n
.819 .827 16