Evidence for Gifted Education 125 Talent Developm

Evidence for Gifted Education
125
Talent Development & Excellence
Vol. 5, No. 1, 2013, 125–137
Questioning the Unquestionable: Reviewing the
Evidence for the Efficacy of Gifted Education
Samuel D. Mandelman
1
and Elena L. Grigorenko
1,2,3*
Abstract: Gifted education has had a long history in the US and
as a result its efficacy
is often taken for granted. In this article, the most widely used
definitions and
assessments in gifted education will be reviewed. The evidence
for the most common
educational provisions offered to the gifted – acceleration and
ability grouping – as

well as gifted education studies from the field of economics and
the long-terms
benefits of gifted education will be discussed. Finally, an
analysis of the existing
evidence and suggested future directions will be presented.
Keywords:
gifted education, efficacy, ability grouping, acceleration
Gifted education has had a relatively long history in the US, and
has existed in one form or
another for almost one hundred and fifty years. Tannenbaum
(1958) reports that formal
gifted education in the US started in the 1860s when the St.
Louis school system started
making academic accommodations for the gifted. This long
history may help to explain
why if anyone, a layperson or a professional, is asked the
fundamental question as to
whether gifted education works, you will almost certainly get an
immediate and emphatic
‘yes’. The question is on what basis is this claim made? Is there
any empirical evidence for
a claim of such great import? Or is this based on their implicit

theories and then what are
these implicit theories are based on?
Unfortunately we no longer have the luxury of relying on
implicit theories alone,
regardless of what it is they are based on, rather we must
carefully evaluate the current
practices of gifted education. With ever increasing international
competition and a global
knowledge economy, the US needs to keep pace with the world
around us. Historically it
has taken events such as the launch of Sputnik to spur US
education officials to talk about
gifted education. We are at such a point again. US school
children are falling behind, as
illustrated by international academic assessments such as
TIMSS, PISA, and PIRLS
(Provasnik, Gonzales, & Miller, 2009). The US is not the leader
in any of the subject areas
(reading, math and/or science) assessed by these international
efforts. The US ranking
continues to slip in these areas with every new administration of
these assessments. On
the PISA assessments, US 15-year olds scored lower than the
OECD average (Provasnik, et

al., 2009). Might this mean that there is a threat to the future of
the US’s edge in the
domains of intellectual pursuit? And how might these worries
impact the country’s
policies and practices toward its education for the intellectually
gifted? If the supposed
function of gifted education is to develop a country’s
intellectual and human capital
(Mandelman, Tan, Aljughaiman, & Grigorenko, 2010; Subotnik
& Rickoff, 2010), it is what is
at stake and is the impetus for this conversation.
Our objective here is to offer an overview of the most common
practices in gifted
education and review the empirical evidence of their outcomes.
Albeit briefly, we will
review the definitions/models used and identification processes
employed; we then will
1
Teachers College, Columbia University, USA
2
Yale University, USA
3
Moscow City University for Psychology and Education,

Russian Federation
*
Corresponding author: Child Study Center, Department of
Psychology, Department of
Epidemiology & Public Health, Yale University, 230 South
Frontage Road, New Haven, CT
06519-1124. Email: [email protected]
ISSN 1869-0459 (print)/ ISSN 1869-2885 (online)
2013 International Research Association for Talent
Development and Excellence
http://www.iratde.org
S. D. Mandelman & E. L. Grigorenko
126
offer a review of the most common educational provisions
offered to the gifted. We will
then turn to studies from the field of economics on gifted
education and, finally, to
ostensible long-terms benefits of gifted education. Throughout
the discourse presented

here, the concept of intellectual giftedness (IG) is defined as a
display of a high-level of
intellectual potential across multiple or within a domain(s) of
human performance, to the
extent that the level of potential differentiates a person
intellectually from his/her
reference groups.
The Status of the Field Today
Definitions
In the US, in many people’s minds in the general public and in
the field of psychology,
intellectual giftedness is synonymous/interchangeable with high
IQ (Borland, 2009;
Pfeiffer, 2011; Sternberg, Jarvin, & Grigorenko, 2011). While
this view is quite prevalent,
there are great limitations of such notions and there are those
who have proposed models
that are more complex and move beyond IQ as the sole criterion
for intellectual
giftedness. While people and cultures have had conceptions of
“smartness” (or
intelligence in modern terms) for thousands of years, only in the
last century have models

been proposed that focus on measuring traits that are believed
to comprise intelligence.
The oldest, most widely studied and still influential model of
psychometric intelligence is
that of Charles E. Spearman. Spearman (1927) suggested that
intelligence is comprised of
general and specific factors. The general factor suggested
(commonly notated as g) is a
factor that underlies all cognitive abilities. This g factor is still
widely used to describe
individual difference in cognitive ability. Cattell’s (1963) and
Horn’s (1968) and Carroll’s
(1993) theories have been merged to create the Cattell-Horn-
Carroll (CHC) three-stratum
theory of cognitive abilities, which is a modern transfiguration
of Spearman’s g. It is the
above mentioned theories of intelligence that serve as the
definition of intellectual
giftedness for those who subscribe to the g based conception.
For a more comprehensive
review of these theories see Sternberg, Jarvin, and Grigorenko
(2010).
Identification
The identification and selection processes for gifted

programming are dominated by the
use of standardized tests of cognitive ability and achievement
(Sternberg, et al., 2010). In a
comprehensive review of the literature, Mandelman, Tan,
Aljughaiman and Grigorenko
(2010) demonstrated that, as of now, in the early part of the 21
st
century, the vast majority
of the cognitive ability measures used for the purposes of the
identification of intellectual
gifts were based on the Cattell-Horn-Carroll (1993) theory of
cognitive abilities.
Educational Accommodations
Gifted education comes in many varieties. Some of the most
popular options for gifted
programming are acceleration, ability grouping, enrichment
programs, pull out programs,
curriculum compacting and summer programs. Here we do a
review of the literature on
the most widely studied empirically supported academic
accommodation practices,
which are acceleration and ability grouping. Our primary focus
while reviewing this

evidence will be on achievement and not the other variables
included in the analyses.
Each one of the meta-analyses presented will be reviewed
individually, to allow the
reader to evaluate the strengths and weakness of each effort and
to gain an understanding
as to how each study contributes to the body of evidence on the
educational provisions
covered.
Acceleration. Acceleration, the oldest form of gifted education
in the US (Tannenbaum,
1958), has been the topic of empirical investigation dating back
to at least the early1920s
(Rogers, 1991) and continuing until today. Acceleration as
defined by Pressey (1949) is
“progress through an educational program at rates faster or at
ages younger than
127
conventional” (p. 2). This definition allows for many practices
to be categorized as

acceleration. Southern and Jones (2004) in a chapter of a
comprehensive report on
acceleration titled “A nation deceived: How schools hold back
America’s brightest
students” (Colangelo, Assouline, & Gross, 2004) list and
describe 18 different types of
acceleration. These include early admission to kindergarten,
early admission to first
grade, grade skipping, continuous progress, self-paced
instruction, subject matter
acceleration/partial acceleration, combined classes, curriculum
compacting, telescoping
curriculum, mentoring, extra-curricular programs,
correspondence courses, early
graduation, concurrent/dual enrollment, advanced placement,
credit by examination,
acceleration in college, early entrance into middle school, high
school, or college.
The strongest and most widely cited evidence that gifted
education, and more specifically
that acceleration works, rely on five meta-analyses that have
been completed over the last
thirty years (Kent, 1992; J. A. Kulik, 2004; J. A. Kulik & C.-L.
C. Kulik, 1984; Rogers, 1991;

Steenbergen-Hu & Moon, 2011). Each of the meta-analyses on
acceleration conducted to
date will be briefly summarized. It is important to note, because
meta-analyses make use
of data from various studies, the details of each study are often
unavailable and therefore
do not allow for direct comparisons of the studies. For the
purposes of our discussion, it
would be important to know the identification criteria used in
each of the studies that are
included in these meta-analyses. This is particularly important
in a field that uses a wide
range of identification criteria.
Kulik and Kulik (1984) in the first published meta-analysis on
acceleration, found that
when students, who were accelerated in particular academic
subjects, were compared to
students of the same age, who were not accelerated, the students
who were accelerated
gained almost a full grade level of performance on their non-
accelerated peers, as
measured by standardized tests in the subjects in which they
were accelerated. An effect

size of .88 was found and is considered to be a large effect (the
magnitude of all of the
effect sizes reported are described based on Cohen, 1977).
Kulik and Kulik (1984) also
demonstrated that accelerated students were able to perform as
well as their older peers
in the subjects that they were accelerated in.
Rogers (1991) completed a best evidence synthesis on 314
published studies that
reported results on 12 different kinds of acceleration (early
entrance to school, grade
skipping, nongraded classrooms, curriculum compaction, grade
telescoping, concurrent
enrollment, subject acceleration, advanced placement,
mentorship, credit by examination,
early admission to college and combined accelerative options).
Significant effect sizes
> .30 were found for all but three (concurrent enrollment,
advanced placement, combined
accelerative options) of the 12 acceleration options. The
outcome measure depended on
the form of acceleration used, with teacher ratings, standardized
tests, and school records
being the most widely used outcome measure. The average

effect size for all academic
outcomes was statistically significant and substantial (.57).
Kent (1992) conducted a meta-analysis focusing on a very wide
range of social and
emotional outcomes of acceleration (see Kent, 1992, pp. 77–79
for a full listing of the
outcomes included). The author explained that the rationale for
this analysis was that the
academic benefits of acceleration had been previously
investigated and were shown to be
effective, while the social and emotional implications were not
as clear. The meta-analysis
included 23 studies and its results suggested that the overall
effects of acceleration (effect
size .13) were positive and any negative effects were minimal.
In another meta-analysis by the Kuliks (2004), 26 studies that
had previously been
included in the three preceding meta-analyses were analyzed.
As was the finding in the
previous analyses, students who were accelerated, when
compared with students of the
same age that were not accelerated, gained almost a full grade
level of performance on

achievement tests on their non-accelerated peers (median effect
size .80, which is
considered to be large). Kulik (2004) also found that
accelerated students were able to
perform as well as older peers on exams.
128
The most recent meta-analysis on acceleration was completed
by Steenbergen-Hu and
Moon (2011) and covered the literature totaling 38 studies
between 1984 and 2008.
Steenbergen-Hu and Moon’s (2011) findings were consistent
with the previously
presented meta-analyses and demonstrated that acceleration was
positive for the
accelerated students. Yet, while the overall effect was
encouraging (.18), it was not
statistically significant. The largest effect and only significant
finding (0.39) was when
accelerated students were compared to their age peers on
achievement. This study, like

the ones before it, also examined the social and emotional
impact of acceleration. The
findings were positive, although not statistically significant,
and the effects were not as
large as those on achievement.
Thus, the literature presents a generally positive landscape of
findings on acceleration as
an accommodation for the gifted. While the landscape is
positive, the overall statistical
significance indicators of these findings are mixed. Therefore,
all that can be said here is
that the results are promising, but inconclusive, and further
carefully designed and
sufficiently powered research is needed to help resolve this
inconsistency in significance
of the findings.
Grouping. The other most widely used educational
accommodation is that of ability
grouping, where students are grouped in various configurations
by ability. The practice of
ability grouping is one of the most controversial issues in
education. Tieso (2003) explains
that the great level of controversy surrounding this issue has

caused, to some degree,
research on it to be stopped. The controversy stems from the
claims that ability grouping
is racist and maintains existing social inequities (Oakes, 1985).
Other concerns about
students’ academic self-concept have been raised (for a review
on academic self concept
see Mandelman, Tan, Kornilov, Sternberg, & Grigorenko,
2010). It is important to note that
the use of terms, such as tracking and streaming, have largely
been discontinued in the
US, as have the corresponding practices. The term ‘tracking’
connotes a system in which
once students were assessed and placed, their education
placement could not be
changed (Tieso, 2003). Ability grouping, on the other hand,
allows for regular reevaluation
of students’ performance and changes in their placement to be
made accordingly. Here
we will review the major meta-analyses that serve as the
empirical basis for ability
grouping.
Kulik and Kulik (1982) conducted a meta-analysis on 51 studies
on ability grouping in

secondary schools. They found the average effect size on
achievement for student
grouping was .10. In a secondary analysis considering only 14
selected studies (which
were included in the overall analyses as well) that explored the
effects of grouping in the
form of gifted programming on the gifted, Kulik found it to be
.33, more than three times
the average effect size.
Kulik and Kulik (1984) conducted another meta-analysis on
ability grouping, this time in
elementary school. This analysis included 31 separate studies.
The analysis of 28 studies
found an effect size of .19 for the general population, meaning
that grouped students on
average gained 2 months of achievement over their non-grouped
peers. In studies where
the target population was gifted students, the effect size was
.49, meaning that they gained
almost a half a grade over their non-grouped peers.
By contrast, Slavin (1987), in a best-evidence synthesis on
ability grouping in elementary
school, reviewed 14 studies in which students were assigned to

a self-contained classroom
based on ability, and found the effect size on student
achievement to be 0. For subject
grouping in math and science, Slavin (1987) could not make a
conclusive finding due to
the number and quality of studies. For the Joplin Plan
1
for grouping, there was a .45
median effect size found. For within-class grouping the effect
size for high achievers was
.41.
Slavin (1990), in yet another best-evidence synthesis on ability
grouping in secondary
schools, found that ability grouping had no effect on student
achievement. Fifteen studies
included in the analysis, that focused on ability and
achievement level, found median
129
effect sizes of +.01 for high achievers, -.08 for average
achievers, and -.02 for low

achievers. Effect sizes that are this small are so close to zero
that they are treated, in fact,
as zero.
Kulik and Kulik (1992) conducted a meta-analysis that included
the studies from their
earlier work (C.-L. C. Kulik & Kulik, 1982; C.-L. C. Kulik & J.
A. Kulik, 1984) and the work of
Slavin (1987, 1990). Their reanalysis of multi-level classes, in
which students in a given
grade were divided into separate classes based on ability, was in
line with previous
findings that multi-level grouping had zero effect on student
achievement. When studies
presented results separated by ability levels, the average effect
size for high ability
learners was .10, whereas middle and low ability groups effect
sizes were -0.02 and -0.01,
respectively on measures of achievement. In a cross-grade
Joplin Plan like grouping,
where the curriculum is adjusted to meet the needs of that
particular mixed-grade group,
the average effect size was .30. For within class grouping,
which involves curriculum

differentiation for each group, there was an average effect size
of .25. For special
programs and grouping for the gifted, the average effect size
was .41. Kulik and Kulik
(1992) concluded that grouping can be beneficial, primarily as a
result of curricular
adjustments, and it is most beneficial for high ability students.
To summarize, the evidence on grouping is conflicting. Slavin’s
(1987, 1990) overall null
findings, except for some subject specific grouping plans, and
the somewhat mixed
results of the Kuliks (although for gifted students the findings
were positive and
consistent; C.-L. C. Kulik & Kulik, 1982; C.-L. C. Kulik & J.
A. Kulik, 1984; J. A. Kulik & Kulik,
1992), certainly causes one to question really how strongly this
practice is empirically
supported. A practice that has such a long history, and that has
been so widely used,
should be able to produce far more robust results. If this mixed
evidence is the best
evidence for this practice, along with Oakes’s (1985) concerns
of inequality, it is no
wonder that there continues to be great controversy and

skepticism surrounding the
practice of grouping.
Economics
There is very little literature on the efficacy of gifted education
in general. However, there
are a number of studies that come from the field and literature
of economics that assess
the efficacy of gifted education. Although the premise and
methodology of these studies
are different from what is typically used in
effectiveness/efficacy studies in education,
these studies are informative in many ways as they pertain to
the discourse here.
Correspondingly, here we will highlight some selected research
studies from the field of
economics that considered the efficacy of gifted education.
Bui, Craig and Imberman (2011), in research that was covered
in the national media (Shea,
2011), conducted a study employing a regression discontinuity
design. In this design,
participants are assigned to groups based on a cut-off score, and
then the outcome
measures are compared to evaluate the effect that a program

has. In this study, the authors
compared groups of students, whose scores were right above the
cut-off score for
admission to gifted programming, to those who were right
below the cut-off score. They
found no significant difference in achievement between the two
groups, despite the fact
that one of the groups was enrolled in a gifted program for a
year and half. In a second
analysis, comparing students, who were randomly selected to
attend a magnet school, to
their equally able peers from the same lottery pool, who were
not selected, little
difference was found except for a small difference in science
achievement among the
groups. The authors found these results surprising, as the
selected students were grouped
with students of higher ability than those who were not selected,
and there was
adjustment of the curriculum to meet their special academic
needs.
There are two other studies of interest that also use regression
discontinuity methods to
evaluate gifted programming, but these studies focus on

prestigious exam schools
(specialized schools for which entrance exams are given to be
eligible for enrollment) in
130
New York and Boston. Considering a number of academic
outcome measures (state
standardized tests, achievement tests, PSAT and SAT scores,
and AP scores),
Abdulkadiroglu, Angrist and Pathak (2011) found little to no
evidence for gains in
academic achievement for enrolled students, despite having a
more challenging
curriculum and more able peers. In another study employing the
same research methods,
and also investigating New York exam schools, Dobbie and
Fryer (2011) found that
attending an exam school had little impact on reading and
writing sections of the SAT and
a small impact on the math portion of the SAT. While
considering the findings of the three

studies presented above, it is important to understand that
because of the research design
utilized (regression discontinuity), findings presented pertain to
the groups of students
whose scores were right above or right below the cut-off for the
gifted programming.
These findings may not extend to those students whose scores
are well above or below
the cut-off.
Thus, the results from the above-mentioned studies were
consistent and somewhat
disconcerting. There was no evidence that these gifted programs
had an impact on the
students who attended them.
Long-Term Benefits
There are few studies that carefully evaluate long-term effects
of being identified and/or
educated as a gifted student (Delcourt, Cornell, & Goldberg,
2007; Subotnik, Edmiston, &
Rayhack, 2007). The scarcity of empirical evidence has been
used by some (Borland,
2005) to fundamentally question gifted education as a practice.
In the limited literature

base that does exist, the strongest of the empirical support
comes from the Study of
Mathematically Precocious Youth (SMPY; Lubinski, 2004;
Lubinski, Benbow, Webb, &
Bleske-Rechek, 2006; Lubinski, Webb, Morelock, & Benbow,
2001), which has produced
more than 30 years of longitudinal research. Lubinski and
colleagues (2001)
demonstrated that students who were identified in talent
searches using the SAT
2
attained
PhD(s) at 50 times the rate of those in the general population.
Similarly, Lubinski and
colleagues (2006) studied academic and other accomplishments,
and found that those
identified as gifted at age 13 using the SAT, were comparable to
those in top graduate
programs of their respective fields. The Study of
Mathematically Precocious Youth has
investigated various outcomes including attaining PhD(s),
getting tenure track positions at
top universities, the number of patents secured, income and life
quality, which

demonstrates how vital it is to identify and serve the gifted
(Lubinski, 2004; Lubinski, et al.,
2006; Lubinski, et al., 2001; Park, Lubinski, & Benbow, 2007).
As demonstrated by the research coming out of SMPY,
identification of great intellectual
abilities and providing for them educationally can have a
profound impact on their long-
term accomplishments. A very large percentage of the students
who were identified by
SMPY, participated in acceleration and ability grouping in its
varying form, and had very
positive feelings about being able to partake in such educational
opportunities. They
viewed these opportunities as being a vital part of their
educational experience
(Lubinski, 2004; Lubinski, et al., 2001).
Cross-Roads of Gifted Education
Here we briefly review and outline some of the primary findings
covered in the preceding
sections.
The most prevalent model of intelligence and giftedness used
in the USA is the g-

factor-based model.
The most widely used assessments for identifying gifted
students are based on the
theoretical framework of g.
The two most popular academic accommodations for the gifted
are acceleration and
grouping.
131
There are five meta-analyses on acceleration, showing positive
effects with different
effect sizes and varying levels of statistical significance (from
not significant to large
median effect sizes of .80).
There are five meta-analyses on grouping with conflicting
results (ranging from 0
effect to the largest effect of .49, which is considered a
moderate effect size, and
which was found with gifted students).
The economics literature on the efficacy of gifted programming
and exam schools
found that attending these programs and schools had little
academic impact on the

students.
One of the major findings of the very limited literature on the
long-term benefits show
multiple effects, for example, that those who are identified as
intellectually gifted
attain doctoral degrees at 50 times the rate of the general
population.
In evaluating the evidence presented here, it is no surprise that
the field of gifted
education has been unable to move forward as it should have.
Let us critically review the
observations presented above. The most common definition of
intellectual giftedness
used today is 85 years old, and it is so narrow that it fails to
capture the now-demonstrated
complexity of human intelligence and, correspondingly,
giftedness. The instruments that
are used to measure this narrow construct of intelligence have
changed little since the
first intelligence test that was created a century ago. These tests
consistently fail to
identify many gifted individuals, especially those of diverse
learning profiles and

minority groups (Chart, Grigorenko, & Sternberg, 2008; Ford &
Moore, 2006; Gallagher,
2005; Gordon & Bridglall, 2005). The best empirical evidence
for the educational
accommodations for gifted education is in the 10 meta-analyses
that generated mixed
findings. It is disconcerting that a field that has been around for
150 years yields such a
limited body of empirical support. The strongest findings
(among the very mixed
findings) of the studies on educational accommodations are that
accelerated students
gain at most a year on their non-accelerated peers. To what
advantage is that, at best, a
year less of school? The clearest long-term benefit of gifted
education is getting PhD(s) at
50 times the base rate; not to minimize this great
accomplishment in any way, but is this
the true objective of gifted education?
The general lack of literature on gifted education and the
quality of the existing literature
are disheartening, and trigger one to think critically. If we
believe that there is a construct

of intelligence and giftedness, and that it can be identified and
should be made for those who possess it, why is it that there is
so little empirical support
for the educational provisions made? Why has more not been
done to move the field
forward?
One possible explanation for the lack of progress in gifted
education is the enduring
disconnect between the definitions/identification methods, the
educational
accommodations, the desired outcomes of gifted education, and
the societal needs. The
definition and the desired outcome must be clearly connected
and inform each other, with
the definition guiding the true desired outcome and vice versa.
The most important
question in this process is, what is the ultimate purpose of
gifted education? If this
purpose could be made entirely clear, then definitions would
have to be updated to
clearly reflect the desired outcomes. In turn, the identification
tools would also have to be

updated to match the definition and the desired outcome. The
made for the gifted students would be clearly in line with the
desired outcome and would
thus make it possible to carefully examine the efficacy of gifted
education. If the field
were to do this, it would not only address the well-known issues
with the definition and
identification tools that draw so much criticism, it would also
be able to make educational
accommodations that can be empirically supported and
validated, gaining the field
greater credibility.
132
A Possible Step Forward
Robert J. Sternberg’s theory, while not being the only or the
definitive …
1. Has you ever taken an IQ test? After hearing your score, did
this change your mentality about tests?

2. Now it’s your
turn: http://www.freeiqtestonline.com/index.html (Links to an
external site.)
Mandelman & Grigorenko (2013) discussed how intellectually
gifted is thought of as being the same as having a high IQ. After
having taken this test, what can you identify as potential biases
related to IQ tests or other tests?
Discussion questions
1. Was there a gifted education program at your school (what
type)? Were you involved, for how long, and what was your
experience like? What was the impact academically/socially? If
you weren’t involved how did this affect you?
2. In your high school, did they implement class rankings? If
yes, how did this affect students that were close to the top?
What about students at the bottom?
3. A current problem is that schools do not have similar clearly
defined goals (if any) for their gifted education programs? What
do you believe the goal should be of gifted education?
4. Ralph and Kevin are best friends. Ralph got held back a
grade and now Kevin is a year ahead of him. How will this
affect their lives (present and future)?
5. Olive is a second grader who tested as gifted. Her teachers
want to pull her out of her classroom to do accelerated work in
a resource room. How could this be harmful or helpful to Olive
(think about social, academic, and emotional impacts)?
6. If you had to create a gifted program for an elementary
school, what would it look like? What would you do to address
some of the problems discussed? Does your definition of
“gifted” align with Mandelman & Grigorenko’s (2013)

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