What's Happening in Self-Contained Special Education Classrooms?
In recent years, more than 4 million handicapped students received
all or part of their education in classrooms directed by a specially
trained teacher. Conventional wisdom holds that categories used to
classify individuals as elgibile for special services represent mutually
exclusive groups of people and serve as the basis for some type of
differentiated treatment (cf. Hallahan & Kauffman, 1986; Kirk &
Gallagher, 1986). Hallahan and Kauffman (1986, p. 5) defined special
education as "specially designed instruction that meets the unique
needs of an exceptional child." Educators have reasoned that
special materials as well as special teaching techniques, equipment, or
facilities are required for special education to be effective.
Clearly, there is a need for specially designed instruction for
some exceptional students. For example, it is difficult to imagine not
providing specialized classroom interventions for individuals who are
blind or deaf; in fact, special education programs for these people are
the oldest, and maybe the best developed. Identifying the unique needs
of learning disabled, emotionally handicapped, or mentally retarded
students--or their educational treatments--is not so simply
accomplished. There are many reasons why a student does not achieve
commensurate with ability, or why abilities differ, or why a student
fails to demonstrate expected ability, achievement, or adaptive
behavior. Most of these reasons do not lead directly to specific
interventions (Ysseldyke & Algozzine, 1984).
This failure to identify categorically specific characteristics or
treatments has led some to argue for a decrease in categorization. For
example, Hallahan and Kauffman (1977) provided "logical
justification for considering children traditionally falling into three
categories of mildly handicapped--learning disabled, emotionally
disturbed, and educable mentally retarded--within a behavioral rather
than a categorical framework" (p. 139). Their argument was
supported by discussion of the confusing, imprecise definitions that are
used to develop eligibility criteria in most states, the common
historical perspective evident in studying the development of each of
the mild handicaps, and the overlap of behavioral characteristics among
these three groups of exceptional students. Similarly convincing
rhetoric has been offered by others (cf. Gardner, 1977; Hewett &
Forness, 1974; Lilly, 1979; Neisworth & Greer, 1975); in fact, as
Edgar and Hayden (1984-1985) pointed out, "the literature is
replete with statements that these three groups represent essentially
the same population . . ." (p. 533).
Despite its logical support, the noncategorical perspective does
not enjoy universal acceptance. For example, Epstein and Cullinan
(1983) stated: "It is most unfortunate that, despite the intense
and often persuasive advocacy of some of its proponents, there has been
very little scientific study of the assumptions on which
cross-categorical special education is based" (p. 306). They used
academic performance of learning disabled (LD) and behaviorally
disordered (BD) students to derive the following conclusion: "The
results do not support the idea that intervention practices should
necessarily be the same for students with LD, BD, and educable mental
retardation" (p. 305). Again, the literature is replete with
opinions and data supporting the separation of exceptional students into
categorical groups to supply appropriate special education (cf. Becker,
1978; Cullinan, Epstein, & Dembinski, 1979; Lieberman, 1980; Phipps,
1982).
The purpose of this research was to describe instruction provided
in categorical special education classrooms. Such information would be
a valuable starting point for determining the appropriatness of
categorical grouping of students.
METHOD
Subjects
Teachers of students classified as emotionally handicapped (EH),
learning disabled (LD), or educable mentally retarded (EMR) were
observed during different types of classroom instruction. Students
classified as emotionally handicapped exhibited severe behavior problems
that disrupted their own (or others') school progress; students
classified as educable mentally retarded had significantly subaverage
intellectual ability and adaptive behavior problems, and students
classified as learning disabled showed a "severe" discrepancy
between their ability and achievement. Generalizations to teachers in
special classes containing similar students are warranted.
Classroom observations were completed in 40 self-contained special
education rooms; exceptional students were assigned to these rooms for
at least 25 hours each week. Students in 16 of the classrooms were
classified as EMR, students in 13 of the classrooms were classified as
LD, and students in the remaining 11 rooms were classified as EH. This
distribution roughly approximates the overall demography for students
with high-incidence handicaps in the state in which the data were
collected (i.e., 37% 17%, and 10% are classified as LD, EMR, and EH,
respectively).
Participating teachers were selected by special education
administrators familiar with their experience and previous performance.
All the participants had been teaching in self-contained classrooms for
at least 3 years, and most had more than 5 years of special education
teaching experience. Ninety percent of the participating teachers were
female; all were categorically certified to teach in the areas in which
they were currently teaching, and none were teaching in classes with
temporary credentials.
Most (72%) of the observations took place during language arts,
reading, or math instruction. The average number of students in the
room during the observation was 9; over half of the data were collected
in classes containing from 6 to 12 students, and about one fourth were
collected in rooms containing less than 6 or more than 12 students.
Observation System
All observational data were collected by trained observes using the
Classroom Observation Keyed for Effectiveness Research (COKER)
observation system. The COKER consists of 389 items organized into two
sections. Specific groups of teacher behaviors (e.g., presenting,
questioning, responding) and students behaviors (e.g., compliance,
asking questions, answering questions, making voluntary comments, being
off-task) are the basis for coding interactions that occur during the
initial phase of the observations. Additionally, occurrences of 33
student behaviors that promote or disrupt learning (e.g., following
classroom routines, teasing, criticizing others) and 86 teacher behavior
related to methodlogy, grouping, classroom affect, and control are also
coded during the observation intervals. The COKER is considered a
low-inference observation instrument, and using it involves observing
and recording teacher/student behaviors as they occur during 5-minute
observation periods.
Validity, reliability, and norming information presented in the
COKER user's manual (Coker & Coker, 1982, pp. 13-19: 31-37)
indicate that the system has adequate technical characteristics for use
in this type of research. For example, construct validity was supported
when expected dimensions of classroom instruction were confirmed by a
factor analysis of data from more than 150 student teachers. When using
an observation system such as the COKER, one is concerned with
reliability of scoring keys rather than reliability of the entire
instrument. Item cluster reliability coefficients obtained during
development of the COKER ranged from .38 to .83; coefficients computed
for 22 scoring keys ranged from 0.00 to .80. As Coker and Coker (1982)
indicated. "Coefficients of zero are possible because of
unreliable measurement and/or sheer absence of the behaviors' that
comprise a key. "Generally, those scoring keys with the lower
realiabilities had fewer numbers of items" (p. 37). Median
reliabilities for 22 scoring keys ranged from .38 to .47 in four
independent studies; in each case, most (36%-77%) of the coefficients
were greater than .30. In another study, estimates of consistency
between observations gathered for the same teacher in different classes
on 12 scoring keys ranged from .47 to .85; multi-class and single-class
realiabilities for these teachers were generally moderate to high (e.g.,
58% were greater than .35). Additionally, in "studies of observer
agreement, in which the results of pairs of observers are compared, the
extent of agreement tends to be in the .80s with occasional agreement
approaching .90" (Coker & Coker, 1982, p. 31).
Observer Training
All observations were completed by university faculty members or
graduate students trained in the use of the COKER observation system by
its developers or by staff trained by them. The training sessions were
structured to provide practice using the observation forms with with
videotaped presentations of classroom interactions. All observers
completed a minimum of six training observations of at least 1 hour in
length and were considered proficient in the use of the COKER when
introbserver agreements between themselves and trained observers reached
90%.
Observation and Scoring Procedures
Each observer conducted approximately twelve 5-minute observations
in each classroom over a 2-day period of time. Teachers were informed
that the observations were for purposes of evaluating another
measurement system and that they were not being evaluated. Observers
also explained that the research was intended to help state department
personnel develop observation competencies for use in exceptional
student education. Observers are instructed to abstain from involvement
in any classroom activities, to meet the teacher early, to determine the
classroom setting, activities, and other demographic information before
entering the room and to keep a "low profile" during the
observations.
Scores on the COKER represent occurrence-nonoccurence of items that
are being observed; combinations of these items are referred to as
"competency keys" (Coker & Coker, 1982). The use of these
keys is analogous to combining 10 items measuring computational skills
with fractions and 15 items measuring computational skills with decimals
into scores reflecting "competency" with fractions and
"competency" with decimals. Scoring the COKER is a two-step
process that involves determining the number of times an item is
observed relative to the number of times a teacher was observed and then
summing these values across keys to obtain competency scores. In this
way, individual item values summed across competencies and represented
as percentage reflect the proportion of items (0 to 100) that are
observed within a competency. The greater the competency score, the
more the behaviors indicative of effective teaching were observed (Coker
& Coker, 1982; Dickson & Wiersma, 1984). Put another way,
scores on the COKER reflect the extent to which expected behaviors
actually occurred. Because keys contain different numbers of items,
comparisons are not made across competencies when using proportionally
scores; these scores are considered appropriate for comparing
individuals within a group or when comparing groups to each other on
separate competencies.
Data Analysis
More than 50 sets of keys are available for use with the COKER.
The dimensions of competence developed for use with special education
teachers (cf. Dickson & Wiersma, 1984) were evaluated as dependent
variables in this research; descriptors for competencies within each of
these domains are presented in Figure 1. The independent variable of
interest was the type of self-contained classroom teacher being
observed.
Classroom observations were completed in 40 special classes.
Scores on effective teaching competencies were compiled, analyzed, and
compared through a series of one-way analysise of variance; a
statistical level of 0.50 was used in evaluating main effects in these
analyses.
RESULTS
Proportionality scores for 22 teaching competencies were available
for analysis. Internal consistency estimates (Cronbach's alpha)
were obtained as a measure of the reliability of these data. The
reliability estimates for the nine keys that comprise the instructional
strategies, techniques, or methods that are scored from COKER data
ranged from 0.00 to 0.68. Keys with unacceptable (i.e., less than 0.10)
reliability (i.e., those representing the extent to which teachers were
using a variety of resources or establishing varied transitions and
instructional sequences) were eliminated from subsequent analyses.
Three keys (i.e., motivates students to ask questions, uses verbal and
nonverbal skills, and uses questions that lead students to synthesize)
were eliminated within the learner communication domain for similar
reasons; the reliabilities for the remaining five keys in this domain
ranged from 0.17 to 0.58. Reliability estimates for the five keys
indicative of learner reinforcement and involvement by these teachers
ranged from 0.14 to 0.76. As in previous analyses (cf. Dickson &
Wiersma, 1984), lower reliabilities were obtained for keys comprised of
smaller numbers of items. Comparisons of the 17 keys with acceptable
internal consistency were completed to evaluate the similarities and
differences in instruction provided by teachers of self-contained
special classes for LD, EH, or EMR students.
Means and standard deviations for instructional competencies
exhibited in self-contained special classes are presented in Table 1.
Univariate analyses of variance indicated that differences in each
domain, except one were nonsignificant. The extent to which the
observed teachers modified instruction to meet learner needs was
different (F (2, 37) = 4.23, p < 0.05). Follow-up analysis indicated
that teachers of EMR students modified instruction less (M = 11.06) than
did teachers of EH students (M = 24.23) or teachers of LD students (M =
23.50). Of the instructional competencies that were similarly observed
in different types of classrooms, behaviors related to providing
experiences that facilitate transfer of learning were least likely to be
observed; and those related to structuring student time to facilitate
learning were more likely to be observed. Low occurrence of behaviors
(less than 20% rates) related to working with individuals and groups,
using convergent/divergent inquiry, and developing problem-solving
skills was observed. Moderate (30%-40%) use of a variety of
instructional strategies was evident.
Means and standard deviations for communication competencies
exhibited in self-contained special classes are presented in Table 2.
Univariate analyses of variance indicated that differences in each
domain were nonsignificant. Of those teaching behaviors that were
similarly observed in different types of classrooms, behaviors related
to accepting varied view-points were least likely to be observed, while
those related to demonstrating proper listening skills and giving clear
directions were the most common actions. Low occurrence (less than 10%
rates) of providing learner feedback was observed, and moderate (more
than 40%) rates of providing group communication were evident.
Means and standard deviations for involvement competencies
exhibited in self-contained special classes are also presented in Table
2. Univariate analyses of variance indicated differences in each domain
were nonsignificant. Behaviors using positive reinforcement were the
least likely to be observed; and those maintaining active involvement
were the most common actions. Moderate (20%-60%) rates of developing
student self-feedback, assisting in error correction, and using
effective classroom management were evident in different types of
self-contained classrooms.
Classroom observations of 40 teachers of self-contained special
education classrooms were completed. More than five hundred 5-minute
"snapshots" of teacher-pupil interaction were compiled and
analyzed. In general, it appears that instruction for EMR, LD, or EH
studens is more similar than different. It appears that teachers of EMR
students modify the instruction to meet individual learner needs, about
half as frequently as do teachers of LD or EH students.
DISCUSSION
While no comparisons of the effectiveness of categorical versus
noncategorical instruction or special versus regular education were
completed in this research, questioning the overall effectiveness of
special education cannot logically be completed without first
documenting the nature of instruction that takes place in all types of
special classes. To document the characteristics of classroom
instruction in self-contained special classes, teachers of LD, EH, or
EMR students were observed. This description of what was going on in
this one type of special class was considered a logical first step in
the continuing search for an answer to the following question:
What's special about special education?
Similar degrees of variability were evident in more than 90% of the
instructional activities observed in the classrooms of teachers working
with three different types of students. The magnitude of important
competencies of effective teachers, such as structuring student time,
providing learner feedback, and giving clear directions, were also
similar. It appears that this group of special education teachers was
performing adequately relative to effective teaching domains, but they
were not performing differently relative to the type of student in their
self-contained special classrooms.
Almost all states support the use of category-specific sligibility
criteria and report figures for placement of students in classes for the
emotionally disturbed, mildly mentally retarded, and learning disabled
(Algozzine & Korinek, 1985). Despite arguments supporting a
decrease in categorization (cf. Hallahan & Kauffman, 1977), authors
of special education introductory textbooks continue to present
categorical perspectives because they believe such books should reflect
"the general viewpoint of the special education profession, and the
prevailing approach to educating exceptional children remains
categorical" (Hallahan & Kauffman, 1986, p. xiii). It seems
that a type of professional schizophrenia permeates theory, research,
and practice in contemporary special education; and some argue that the
conceptual pathology results partly from the absence of data.
Students are placed in categorical programs despite limited
evidence that the groupings lead to differential treatment. Students of
special education learn the history, definitions, and supposed
characteristics of different types of students despite limited evidence
that this information is useful in planning programs for most
exceptional students. Teachers are certified to teach categorically
different students despite limited evidence that most of the groupings
are a source of differential treatment methods. Data from these
self-contained special classrooms support the scientific basis for
taking the noncategorical side of special education personality more
seriously. Observations of teachers in self-contained classrooms
containing LD, EH, or EMR students did not support conclusions about
differentiated instruction on the basis of category. Though this does
not mean that categorical instruction is better or worse than
noncategorical instruction or that special education is better or worse
than regular education for these students, it does seem a reasonable
beginning for continued research to determine the appropriateness of
placing and teaching students in disability groups.
REFERENCES
Algozzine, B., & Korinek, L. (1985). Where is special
education for students with high prevalence handicaps going?
Exceptional Children, 51, 388-394.
Becker, L. D. (1978). Learning characteristics of educationally
handicapped and retarded children. Exceptional Children, 44, 502-511.
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Cullinan, D., Epstein, M. H., & Dembinski, R. J. (1979).
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behaviors: ED, LD, and EMR reconsidered. The Journal of Special
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Kirk, S. A., & Gallagher, J. J. (1986). Educating exceptional
children (5th ed.). Boston: Houghton Mifflin.
Liberman, L. M. (1980). The implications of noncategorical special
education. Journal of Learning Disabilities, 13, 65-68.
Lilly, M. S. (1979). Children with exceptional needs. New York:
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Neisworth, J. T., & Greer, J. G. (1975). Functional
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special education. Boston: Houghton Mifflin.
BOB ALGOZZINE is Professor of Curriculum and Instruction,
University of North Carolina at Charlotte.
CATHERINE V. MORSINK is Professor of Special Education, University
of Florida, Gainsville. KATE M. ALGOZZINE is a Teacher of Gifted
Students.