Feifer,
S., Nader, R. G., Flanagan, D., Fitzer, K., & Hicks, K. (2014). Identifying specific reading disability subtypes for
effective educational remediation. Learning Disabilities: A
Multidisciplinary Journal, 20(1). https://ldaamerica.org/wp-content/uploads/2013/10/LDMJ_free-article.pdf
"Overall results suggest that the
specific cognitive subtests that are predictive of Letter-Word Identification,
Reading Fluency, and Passage Comprehension vary depending on the subtype of Specific
Learning Disability".
I'm
not sure that this conclusion is the right one to derive from the data
presented in this study.
The need to prove a linkage between a
poor cognitive ability (one or more of the seven broad abilities Comprehension
Knowledge, Fluid Ability, Short Term Memory, Long Term Storage and Retrieval,
Processing Speed, Visual Processing and Auditory Processing) and poor specific
performance in reading/writing/math (for example, poor decoding, poor reading
fluency and/or poor reading comprehension) lies at the heart of Flanagan's
approach to learning disability definition.
In this study, Feifer, Flanagan and their colleagues try to demonstrate
the existence of such connections between cognition and performance in reading.
Two hundred and eighty-three students
aged 6-16, studying in grades 2-12 participated in this study. They were referred for evaluation due to
learning and/or behavior problems. Most
of them (194) were boys. They all had an
IQ score of above 75 (usually a child who meets Flanagan's definition will have
a higher IQ, since most of his cognitive abilities are supposed to be at least
average. But theoretically a child who
scores 85 on most of the cognitive abilities, and has a very low score on one
ability, will have an IQ score lower than 85).
All students were given tests from the
WJ3 battery. They were given 14 tests
out of the cognitive battery (two tests for each cognitive ability) and three
tests from the achievement battery: Letter
Word Identification, Reading Fluency and Passage Comprehension.
The students were divided into six groups
according to a theoretical conceptualization:
an Associative Learning group (which was supposed to be poor at Long Term
Storage and Retrieval); a Fluid Ability – Visual Processing group (which was
supposed to be poor at those abilities); a Comprehension Knowledge group (which
was supposed to be poor at Comprehension Knowledge); a Learning Efficiency
group (which was supposed to be poor at Processing Speed), an Executive Functions
group (which was supposed to be poor at Short Term Memory) and a control group
(with no cognitive deficits). The rational for this grouping is
not clear to me and is not explained in the paper. Perhaps it wasn't possible to group the
participants according to the seven CHC broad abilities. For instance, I see in the data that scores
in Auditory Processing tests were average in all groups. This is odd since poor
auditory processing is an indicator of poor reading.
In all groups except the control group,
children had similarly poor scores in the three reading tests. This is also odd. The main point in Flanagan's definition is
that specific poor reading skills are caused by specific poor cognitive
abilities. So we might have expected to
find different "profiles" of reading test scores in each group. For instance, it might have been expected
that in the Associative Learning group, Letter Word Identification and Reading Fluency
would be poor but Passage Comprehension would not necessarily be poor. The results were the opposite (the lowest
score in this group was in passage comprehension. The scores in the three reading tests were in
fact very similar. It is not reported if
the small differences between scores are significant).
All children had at least average scores
on most cognitive abilities.
I prepared this table out of the data:
Proportion of predicted variance
|
What was predicted
|
Tests in this group that predicted reading tests and
the broad abilities they measure
|
The broad ability that was supposed to be poor in
this group
|
Test scores in this group that were below 85 and the
broad abilities they measure.
|
Group's name
|
0.449
|
Letter-Word ID
|
Sound Blending (Ga)
Numbers Reversed) Gsm)
|
-
|
All scores were average and above
|
Control
|
0.239
|
Reading Fluency
|
Numbers Reversed) Gsm)
|
|||
0.493
|
Passage Comprehension
|
Numbers Reversed) Gsm)
Picture Recognition )Gv(
|
|||
0.187
|
Letter-Word ID
|
Visual Matching)
Gs(
Numbers Reversed) Gsm)
|
Glr
|
Visual Auditory
Learning) Glr(
Retrieval
Fluency (Glr)
|
Associative
learning
|
0.147
|
Passage Comprehension
|
Numbers Reversed) Gsm)
|
|||
0.401
|
Letter-Word ID
|
Sound Blending (Ga)
Auditory Attention (Ga)
|
Gv Gf
|
Visual Auditory
Learning) Glr(
Retrieval
Fluency (Glr)
Concept Formation)Gf(
|
Fluid/Visual
Processing
|
0.409
|
Reading Fluency
|
Visual Matching)
Gs(
|
|||
0.406
|
Passage Comprehension
|
General
Information) Gc(
Memory for Words
)Gsm(
|
|||
0.100
|
Letter-Word ID
|
Visual Matching)
Gs(
|
Gc
|
Verbal
Comprehension (Gc)
General
Information
(Gc(
Visual Auditory
Learning) Glr(
|
Crystallized
|
0.286
|
Reading Fluency
|
Visual Matching)
Gs(
Decision Speed (Gs)
|
|||
0.210
|
Passage Comprehension
|
General
Information) Gc(
|
|||
0.229
|
Reading Fluency
|
Numbers Reversed) Gsm)
|
Gs
|
Visual Matching)
Gs(
|
Learning
Efficiency
|
0.391
|
Passage Comprehension
|
Numbers Reversed) Gsm)
Memory for Words
)Gsm(
|
|||
0.323
|
Letter-Word ID
|
Verbal
Comprehension (Gc)
|
Gsm
|
Numbers Reversed
(Gsm) (the score was (
84.53
|
Executive
Subtype
|
0.142
|
Reading Fluency
|
Visual Auditory
Learning (Glr(
|
|||
0.399
|
Passage Comprehension
|
Visual Auditory
Learning (Glr(
Picture Recognition )Gv(
|
Table 1: groups, low test scores in each group and
tests predicting reading in each group
Glr long
term storage and retrieval; Gsm short term memory; Gv visual processing; Gs processing speed; Gf fluid ability; Ga auditory ability; Gc comprehension knowledge
A close look at this table reveals two
interesting things:
A.
The ability that was
supposed to be low in a specific group and the test scores that were actually
low in that group did not always fit. For
instance, in the "Fluid Ability/Visual Processing" group, Fluid Ability
and Visual Processing tests were supposed to be low, but 2 of the tests that
were actually low measured Long Term Storage and Retrieval. The third low test score did measure Fluid
Ability (but the score of the second Fluid Ability tests that was presented to
the participants was average). This
means that in this instance the group's name did not reflect the poor abilities
in this group.
B.
There were many
incongruencies between tests that predicted reading in a group, abilities that were
supposed to be poor in that group, and tests that were actually low in that
group. For example, in the "Associative
Learning" group, Long Term Storage and Retrieval was supposed to be
poor. Low test scores in this group do
indeed measure Long Term Storage and Retrieval.
But the tests that predicted reading in this group measure Processing Speed
and Short Term Memory, not Long Term Storage and Retrieval. This means that the classification of
children to the "Associative Learning" group was not relevant to the
prediction of reading. The predictors of
reading in this group were two tests in which children had average scores (Visual
Matching (89.88) and Numbers Reversed (88.51)) and that measured Processing Speed and Short Term
Memory.
I find the researchers' explanations for these
incongruencies not entirely convincing.
For instance: "nearly 19% of the variance of their reading
performance was accounted for by scores from the Visual Matching (perceiving
the visual contour and shapes of numbers quickly) and Numbers Reversed (working
memory) subtests. This finding suggests that these students may have struggled with
the orthographical representation of print, coupled with the working memory
demands inherent in print knowledge. Reading performance was likely weak for
these students because reading requires the ability to detect the symbolic
representation of letters as making up individual words (i.e., orthographic processing), and holding and
manipulating this information in the mind’s eye (i.e., working memory)".
What Feifer, Flanagan and their
colleagues are doing here is to say:
among the children who are poor at A, B explains reading
difficulties". This does not explain
why the poor performance in A in and of itself does not explain the reading
difficulties. Why the poor performance
in Associative Learning tests in this group does not predict the poor reading
scores. In associative learning tests
(like Visual Auditory Learning) the child learns to link sounds with symbols,
which is the essence of reading.
Thus it seems that this study is not able
to prove the existence of links between poor specific cognitive abilities and
poor specific reading performance. I'm
sure such links exist, but this study does not show that.
What can be learned from this study? Here are some of my conclusions (not the
researchers'):
1.
Letter and Word Identification can be predicted by these WJ3 tests: Sound Blending, Numbers Reversed, Visual ,Matching,
Verbal Comprehension.
2.
Reading Fluency can be predicted by Numbers Reversed, Visual Matching, Decision
Speed, Visual Auditory Learning. Obviously
Processing Speed predicts reading fluency.
3. Passage Comprehension can be predicted
by Numbers Reversed, Picture Identification, General Knowledge, Memory for Words
and Visual Auditory Learning. It's
interesting that tests that measure Fluid Ability do not predict reading
comprehension, and that only one test out of the two that measure Comprehension
Knowledge predict Passage Comprehension.
4.
Numbers Reversed test is a predictor of all reading skills.