Fletcher and Miciak (2017) claim that "there
is substantial evidence showing little difference between IQ-discrepant and low
achieving children in achievement, behavior, or cognitive skills, prognosis,
intervention outcomes, and neuroimaging markers of brain function".
IQ-DISCREPANT are children who have a discrepancy between
their IQ score and their reading/writing/ math scores. The term IQ-DISCREPANT
usually refers to children with poor reading/writing/math and (at least)
average intelligence. LOW ACHIEVING in Fletcher and Miciak's paper
refers to children who have poor reading/writing/math and lower than average IQ
scores. These children do not have a discrepancy between their
IQ and achievement scores.
Assertions like Fletcher and Miciak's were one of the reasons for abandoning the discrepancy
definition of learning disability (learning
disability as a discrepancy
between at least average IQ and poor reading/writing/math that cannot be explained by exclusionary factors) in
DSM5.
This article by Watkins, Lei &
Canivez presents a slightly different picture:
In current usage, intelligence
tests are thought to measure general reasoning skills that are predictive of
academic achievement. Indeed, concurrent IQ–achievement correlations are
substantial and, consequently, comparisons of IQ and achievement scores
constitute one of the primary methods of diagnosing learning disabilities (at least when this paper was written).
However, intelligence tests often contain items
or tasks that appear to access information
that is taught in school (i.e., vocabulary, arithmetic) and there has been considerable
debate regarding the separateness or
distinctiveness of intelligence and academic
achievement. This apparent overlap in
test coverage, among other factors, has led some to view intelligence and
achievement as identical constructs. Some researchers have suggested that the
relationship between intelligence test scores and educational achievement is
reciprocal, mutually influencing each other. According to this approach, children who read a lot
develop their cognitive abilities and intelligence. Children who do not read because of learning disabilities
have less opportunity to develop these abilities. Subsequently,
special education researchers have suggested that only achievement tests should
be used to identify children with learning disabilities (as Fletcher suggests). Other
researchers assert that intelligence is causally related to achievement.
In order to determine whether and to what extent IQ
affects achievement (or vice versa), children must be tested twice with an IQ test and twice with achievement tests over a period of a few years. If IQ affects achievement and
causes it, the correlation between the IQ
scores obtained in the first measurement (IQ 1) and the achievement scores
obtained in the second measurement
(achievement 2) should be higher than the correlation between the achievement
scores obtained in the first measurement (achievement 1) and the IQ scores obtained
in the second easurement (IQ2).
Two thousand school psychologists
were randomly selected from the National Association of School Psychologists membership
roster and invited via mail to participate in this study by providing test
scores and demographic data obtained
from recent special education triennial
reevaluations. Data were voluntarily submitted on 667 cases by 145 school psychologists
from 33 states. Of these cases, 289 contained scores for the requisite eight
WISC-III and four academic
achievement subtests.
Special education diagnosis upon
initial evaluation included 68.2% learning disability, 8.0% emotional
disability and 8.0% mental retardation. The rest of the students received other diagnoses.
The mean
age of students at first testing was 9.25 years and the mean age of students at
second testing was 12.08.
Contemporary
versions of the Woodcock–Johnson Tests of Achievement, Wechsler Individual
Achievement Test, and Kaufman Test of Educational Achievement were used in more
than 90% of the cases. In reading, all achievement tests included separate
basic word reading and reading comprehension subtests. In math, separate
calculation and reasoning subtests were available for all academic achievement
instruments
Here are some interesting correlations I found in the
second testing (which took place when the child had already spent about three years in special education):
Basic reading skills were correlated 0.56 with Information, 0.42 with
Similarities, 0.49 with Vocabulary.
Reading comprehension was correlated 0.64 with Information, 0.54 with
Similarities, 0.47 with Picture Arrangement, 0.50 with Block Design, 0.60 with
Vocabulary, 0.50 with Comprehension
subtest.
Mathematical calculations were correlated 0.62 with Information, 0.55 with
Similarities, 0.52 with Picture Arrangement, 0.53 with Block Design, 0.57 with
Vocabulary and 0.55 with Comprehension.
Mathematical reasoning was correlated 0.70 with Information, 0.63 with Similarities, 0.52 with Picture Arrangement,
0.58 with Block Design, 0.67 with Vocabulary, 0.65 with Comprehension.
The relatively high correlation of Information and
Vocabulary with all achievement tests stands out.
In the first testing (before the child entered special
education) the highest correlations were
found between those same IQ subtests and achievement tests,
but correlations were generally lower. The reason for this is unclear to me and
the researchers do not explain it.
Another thing that stood out to me was that the mean of
the group of children in the Verbal Comprehension and Perceptual Organization indices
did not change between the first and the second testing.
This may be an indication of the stability of intelligence.
On the other hand, this may mean that the intervention the children may have
received in special education did not improve their
crystallized knowledge.
Even more striking is the fact that the average scores in
basic reading, reading comprehension, mathematical
calculations, and mathematical reasoning have
not changed during these two years and eight months. This
means that the children did
not make progress in their skill level relative to the
norm, but on the other hand, they also did not fall behind. Another interesting thing is that the children's average scores
in the achievement domains were average (around 85), not lower.
Oh, Glutting, Watkins, Youngstrom,
and McDermott (2004) demonstrated that both g (general intelligence) and Verbal
Comprehension contributed to the prediction of academic achievement, although g
was at least three times more important
than Verbal Comprehension.
In the present study, the average correlation between IQ1 and Achievement2 was 0.466 while the average correlation between Achievement1 and IQ2 was 0.398. This means that IQ predicts achievement, not the other way around.
IQ tests were built by Alfred Binet to measure (and
predict) the ability of students to succeed at school. This basic feature of IQ
tests has been empirically supported for more than 100 years and is also supported by this study.
The assertion that IQ predicts future achievement has
been tested with students in regular education. In this
study, it was examined with special education students and has also been
confirmed. Some researchers have suggested that correlations between reading
and IQ tests may often be an artifact of language, which affects both reading
and intelligence. By this line of thinking, reading difficulties lower
IQ scores over
time, and cause them to be weak predictors of achievement in students with
learning disabilities.
One of the most influential researchers in the field of
reading, Linda Siegel, wrote in 1998: “low scores on the IQ tests are a consequence, not a
cause, of … reading disability”. I can find some logic in this
argument, but I would mitigate it and say:
poor scores in some IQ subtests may also be caused
by learning disability.
However,
this position was not confirmed by the present results nor by those of Kline,
Graham, and Lachar (1993), who found IQ scores to have comparable external
validity for students of varying reading skill. Nor was such a
conceptualization supported by the relatively high long-term stability of
WISC-III IQ scores among more than 1000 students with disabilities.
Further, IQ has been a protective factor in several studies.
In a longitudinal analysis, Shaywitz et al.
(2003) found that two groups of impaired readers began school with similar
reading skills and socioeconomic characteristics, but those students with
higher cognitive ability became significantly better readers as young adults. A
meta-analysis of intervention research for adolescents with LD demonstrated
that IQ exercised similar protective effects (Swanson, 2001). A New Zealand 25-year longitudinal study found strong
relationships between IQ at age 7 and 8 and academic achievement at ages 18– 25
years, independent of childhood conduct problems as well as family and social
circumstances (Fergusson, Horwood, & Ridder, 2005). In sum, considerable
evidence contradicts the assertion that IQ has no predictive or seminal
relationship with academic achievement.
The
present study provides evidence that psychometric intelligence is predictive of
future achievement whereas achievement is not predictive of future psychometric
intelligence.
In conclusion, Fletcher and Miciak argue that there is no
difference between children with and without an IQ-Achievement discrepancy in
achievement, behavior,
cognitive
abilities, prognosis, intervention outcomes, and neuroimaging markers of brain function.
This study suggests that there is a difference in
prognosis between these two groups of children.
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