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Wednesday, August 8, 2018

Is it possible to link specific cognitive deficits with specific deficits in reading skills?


  
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 Journal20(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 ReversedGsm)
-
All scores were average and above
Control
0.239
Reading Fluency
Numbers ReversedGsm)
0.493
Passage Comprehension
Numbers ReversedGsm)
Picture Recognition )Gv(
0.187
Letter-Word ID
Visual Matching) Gs(
Numbers ReversedGsm)
Glr
Visual Auditory Learning) Glr(
Retrieval Fluency (Glr)
Associative learning
0.147
Passage Comprehension
Numbers ReversedGsm)

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 InformationGc(

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 InformationGc(

0.229
Reading Fluency
Numbers ReversedGsm)
Gs
Visual Matching) Gs(
Learning Efficiency
0.391
Passage Comprehension
Numbers ReversedGsm)
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.




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