Psychology
in
the
Schools
Volume
24,
July
1987
PSYCHOMETRIC CLASSIFICATIONS
OF
LEARNING DISABLED STUDENTS
DONALD A. LETON LEN K. MIYAMOTO DAVID
B.
RYCKMAN
University
of
Hawaii
Honowai Elementary
School
University
of
Washington
Oahu, Hawaii
The psychometric test results
of
a sample of
100
LD students with severe achieve-
ment problems were cluster analyzed. The variables included in this analysis were
the subtests
of
the WISC-R, the Bender Gestalt, the Benton Visual Retention, the
Purdue Perceptual-Motor, and the Lindamood Auditory Conceptualization tests.
Us-
ing K-means iterative clustering procedures, three clusters were obtained. The first
cluster was defined by low scores
on
attention and concentration subtests; the second
was defined by low scores
on
subtests
of
verbal-associative intelligence; the third was
defined by low scores
on
visual-spatial and motoric subtests. Limitations
of
the study,
in the scope
of
the psychometric testing and the lack
of
pediatric and neurologic
diagnoses, are discussed.
Although most professionals in the field share the assumption that LD students
represent a heterogeneous population, there has been little effort to group these students
into identifiable diagnostic patterns for special education treatments. Torgeson and Dice
(1980) failed to find any researcher who employed any system to reduce the heterogeneity
of their samples. Their observations were based on a review of about 90 LD studies
found in major education and psychology journals.
As a result of the ambiguous nature of learning disabilities, Horvath, Kass, and
Farrell (1980) claimed the classification of LD to be an example of a fuzzy set, a set
in which membership is not precisely defined. Zadeh (1965) defines a fuzzy set as:
“. . .
a class of objects with a continuum of grades of membership. Such a set is
characterized by a membership (characteristic) function which assigns to each ob-
ject a grade of membership ranging between zero and one. The notions of inclu-
sion, union, intersection, complement, relation, convexity, etc., are extended to
such sets, and various properties of these notions in the context of fuzzy sets are
established. In particular,
a
separation theorem for convex fuzzy sets is proved
without requiring that the fuzzy sets be disjoint.” (p.338)
In other words, membership in a fuzzy set is not based on an all-or-none criterion,
as in classical set theory, but may take on values in between.
A
set is fuzzy when objects
or persons can belong partially to it, rather than belonging either totally or not
at
all.
The educational classification
of
LD is a good example
of
a
set in which the criteria
of
membership are unclear. The definitions
of
the construct are vague and subject to
numerous interpretations.
In effect, the membership criteria have become too broad to be helpful in terms
of remedial instruction and research purposes. It appears that LD has become
a
con-
venient category for placing students who have a variety of educational problems. The
broad range of characteristics manifested in samples of
LD
students has been well
documented (Keogh, Major-Kingsley, Omori-Gordon,
&
Reid, 1982; Kirk
&
Elkins, 1975;
Norman
&
Zigmond, 1980). The definitional problems of LD, and thus the classifica-
tion and intervention problems, are directly attributable to the heterogeneity of students
categorized as LD.
Reprint requests should be sent to Donald A. Leton, College of Education, University of Hawaii at Manoa,
West Hall Annex 2, 1776 University Ave., Honolulu,
HI
96822.
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