Sage Publications, Inc.
Hammill Institute on Disabilities
The Efficacy of Function-Based Interventions for Students with Learning Disabilities Who
Exhibit Escape-Maintained Problem Behaviors: Preliminary Results from a Single-Case
Experiment
Author(s): Mack D. Burke, Shanna Hagan-Burke and George Sugai
Source: Learning Disability Quarterly, Vol. 26, No. 1 (Winter, 2003), pp. 15-25
Published by: Sage Publications, Inc.
Stable URL: http://www.jstor.org/stable/1593681
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THE
EFFICACY
OF
FUNCTION-BASED
STUDENTS
INTERVENTIONS
FOR
DISABILITIES WHO
LEARNING
WITH
EXHIBIT
ESCAPE-MAINTAINED
PROBLEM
BEHAVIORS:
PRELIMINARYRESULTS
FROM
A
SINGLE-CASE EXPERIMENT
Mack D. Burke, Shanna Hagan-Burke, and George Sugai
Abstract. This single-subject experiment explored the use of
functional behavioral assessment to develop an intervention plan
for a third-gradestudent with a learning disability, who exhibited
high rates of problem behaviors during reading instruction. A
functional analysis of the subject's behaviors revealed a relation
between his problem behaviors and the nature of the academic
tasks presented during reading instruction. The results provide
preliminary evidence to support the use of functional behavioral
assessment to influence instructional planning designed to
improve the behaviors of students who exhibit escape-maintained
problem behaviors related to academic tasks. The results are of
particular relevance as researchers continue to explore effective
interventions that support students with learning disabilities.
MACKD. BURKE,Ph.D., is assistantprofessor, Universityof Georgia.
SHANNAHAGAN-BURKE,
Ph.D., is assistant professor, Universityof Georgia.
GEORGESUGAI,Ph.D., is professor, Universityof Oregon.
The Individuals with Disabilities Education Act
(IDEA) emphasized the application of function-based
behavior support planning for all students with disabilities who display problem behaviors. Although the
benefits of functional behavioral assessment (FBA)and
function-based interventions are well documented and
quickly becoming standard practice among those who
serve students with behavioral disorders as well as more
severe disabilities, much less research has examined the
potential benefits of this technology with students
with learning disabilities (Gresham, Quinn, & Restori,
1999; Heckman, Conroy, Fox, & Chait, 2000).
Nonetheless, full compliance with IDEA requires the
use of FBA and function-based interventions with all
students with disabilities who exhibit problem behaviors, regardless of disability classification.
Much of the research substantiating the use of FBAto
guide intervention planning has been conducted with
individuals with severe disabilities and, to a lesser
extent, those who exhibit behavioral disorders
(Gresham et al., 1999; Heckman et al., 2000; Iwata,
Dorsey, Slifer, Bauman, & Richman, 1982). Many of
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these studies indicated a need to substantiate the external validity of the approach via replications with different populations and settings (Heckman et al., 2000;
Meyer, 1999; Nelson, Mathur, & Rutherford, 1999). In
particular, more research is warranted with higherfunctioning students who have complex verbal, social,
academic, and behavioral repertoires (Dunlap & Kern,
1993; Heckman et al., 2000; Nelson et al., 1999).
The purpose of this study was to examine the use of
functional behavioral assessment to develop an intervention for a third-grade student with a learning disability, who exhibited high rates of problem behaviors
during reading instruction. The authors conducted a
functional analysis to confirm the maintaining consequences of the student's problem behaviors, and then
used a single-subject design to evaluate the effects of
preteaching vocabulary concepts prior to reading
instruction. Two questions were posed: (a) Is there a
functional relation between reading task requirements
(i.e., decoding versus comprehension) and appropriate
task engagement? and (b) Is there a functional relation
between preteaching vocabulary concepts and appropriate task engagement during reading comprehension
tasks?
METHOD
Setting and Subject
This study took place in a third-grade general education classroom in a suburban elementary school (K-5) in
the Pacific Northwest. The class was part of an elementary school that served approximately 500 students.
Both the general education and special education
teachers, along with the school district's behavior intervention specialist, nominated Mario, the participant in
this study. They were in agreement that Mario exhibited
high rates of problem behaviors that ranged from mild
off-task behaviors (i.e., fidgeting with clothes and
glasses, talking to himself, and quietly refusing to work)
to disruptive behaviors that interrupted the learning of
others (i.e., singing loudly, refusing to follow directions,
and arguing with his teachers). They also suspected that
the majority of Mario's problem behaviors functioned
to escape/avoid reading tasks.
At the time of the study, Mario was in the third grade.
His native language was Spanish and he spoke English as
a second language. Like over 50% of the students in his
elementary school, he was eligible for and received free
lunch. He was diagnosed with a learning disability (LD)
at the age of seven. Mario had been evaluated to determine whether he also had an emotional/behavioral disorder, but the evaluation committee determined he did
not meet the criteria for that special education category.
Mario's most recent IEP contained goals and objectives
in mathematics, writing, reading, and social behavior.
His special education teacher explained that the primary concern during reading instruction was his
problem behavior. Mario's reading performance was
considered to be "on grade level," and he received
reading instruction with a homogeneous group of
20 students in a general education classroom. He
attended a special education resource center for
45 minutes every afternoon for supplementary assistance in mathematics and writing. The only other
time he spent in this setting was when he was
removed from his regular education classes due to disruptive problem behaviors. On Mondays and Wednesdays, the school often sent a special education aide to
Mario's reading class to assist with managing his
behavior without having to remove him from the
classroom. During these times, the aide typically sat
close to him during group work, prompted him back
to task as necessary, and when his behaviors were
problematic during independent work, she read the
task to him and facilitated discussion to help him
determine the correct answer.
Procedures
The development and subsequent implementation of
this study consisted of three parts. First, the researchers
conducted an FBAof Mario's problem behaviors during
reading class. The FBA included information from
school records, teacher interviews, curriculum-based
measures, and direct observations of Mario. Second, the
hypothesis statements (i.e., results) derived from the
FBA were tested through functional analysis procedures. Finally, an intervention was developed and its
effects were evaluated using an alternating-treatments
design (Alberto & Troutman, 2003; Barlow & Hersen,
1984; Tawney & Gast, 1984).
interviews.
behavioral assessment
Functional
Carefully trained graduate interns used an abbreviated
FBA interview protocol to interview Mario and two of
his teachers. The interns had finished all college
requirements for a teaching license in both elementary
education and special education. They had also completed three advanced courses in functional behavioral
assessment and function-based support planning as
well as two semesters of supervised internship as a
behavior specialist in elementary school settings.
The FBA interview protocols were based on the
extended FBA format provided by O'Neill, Horner,
Albin, Sprague, Storey, and Newton (1997). The three
interviews yielded descriptive information about
Mario's problem behaviors, including the places and
situations where they were more or less likely to occur.
The interviews also queried potential consequences
that maintained Mario's problem behaviors during
reading instruction. The researchers used procedures
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outlined in O'Neill et al. (1997) to examine the interview data. These data were later used along with the
results of their direct observations and academic assessments to form initial hypothesis statements concerning the conditions under which Mario's problem
behaviors occurred.
Curriculum-based measurement. The researchers
used curriculum-based measurement (CBM) as a general indicator of Mario's reading skills relative to the
other learners in his reading class. The intent was to
gather information about Mario's reading abilities that
might aid in their efforts to develop a testable hypothesis regarding the function of his problem behaviors
during reading class. First, they reviewed oral reading
fluency (ORF) data for all the students in his class.
Next, they administered a MAZEtest to the entire class
as an indicator of comprehension. Procedures outlined
by Shinn (1998) were used to administer and score
both the ORF and the MAZEmeasures.
Direct observations. Information gained from the
interviews and CBM results guided the development of
a direct observation tool. These information sources
helped the researchers establish relevant variables to
record along with various codes that could be used to
measure change via a 10-second partial interval time
sampling procedure. The tool's coding system captured
specific information on the types of problem behaviors
observed, along with the instructional context, associated antecedents and maintaining consequences, and
the behavior of a peer referent. Once the tool was complete, multiple direct observations were conducted
across a range of conditions during Mario's reading
class. The observations served to corroborate the
researchers' initial hypothesis statements and inform
their design of a functional analysis.
Functional analysis. The researchers performed a
functional analysis to determine the accuracy of the
hypothesis statement generated by the functional
behavioral assessment (i.e., interviews, academic assessments, and direct observations). Contextual conditions
were identified during the FBAprocess and targeted for
manipulation. These variables were determined a priori
and manipulated both during Mario's regular reading
class (naturalistic) and out-of-class (i.e., analogue) settings. The researchers followed the functional analysis
procedures provided in O'Neill et al. (1997), systematically manipulating contextual variables using an alternating-treatments design.
Intervention development. Applying function-based
intervention logic, the researchers and the teacher did
not develop an intervention plan until the functional
analysis was complete and they were able to carefully
study its results. The results would provide essential
information for ensuring that the intervention they
designed was technically sound. Verifying the hypothesis regarding Mario's problem behaviors prior to specifying an intervention increased their confidence that the
intervention would be relevant and effective. Specific
details of the intervention are provided following the
discussion of the results of the functional analysis.
Experimental Design
An alternating-treatments design was used to examine
the relationship between the intervention (preteaching
vocabulary concepts) and levels of task engagement. The
alternating-treatments design allowed for experimental
manipulation of the independent variable while
directly observing corresponding changes in the
dependent measure (i.e., task engagement with no
problem behavior). Mario's behaviors were measured
during the experiment using the 10-second partial
interval time sampling tool that was developed and
used during both the FBAbaseline observations and the
functional analysis.
Interobserver Agreement
Interobserver agreement (IOA) was assessed during
50% of the direct observation sessions and distributed
across all phases. Specifically, IOA was assessed during
three of the seven initial baseline observations (43%),
nine of the 11 functional analysis observations (82%),
and four of the 14 experimental observations (29%).
IOA percentages were calculated by dividing the number of agreements (i.e., instances when two independent observers coded the same thing) by the total
number of coding opportunities. The levels of overall
interobserver agreement (i.e., all variables considered
per observation) ranged from 89-99%, with a mean of
95% (standard deviation of .035). IOA was also calculated for each type of variable (i.e., instructional context, antecedent, behavior, consequence, peer referent).
Table 1 provides a summary of the average level of
agreement across each direct observation variable
coded.
Data Analysis
Consistent with established procedures for singlesubject studies, visual analysis was used to determine
whether a relationship between the independent and
dependent variables was documented. Visual analysis
procedures were chosen because they allow for (a) a
fine-grained analysis of individuals, (b) continuous collection of data, (c) data-based decisions during implementation, and (d) individualization of instruction
(Tawney & Gast, 1984). The researchers analyzed the
observation data both within and across phases. Trends
and levels were examined, and percentages of overlap
were calculated along with the mean and range for
each phase.
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RESULTS
Functional Behavioral Assessment
Although Mario'sspecialeducationteacheridentified
him as a potential participantfor this study, she concurred with his other teachers that he exhibited the
most problem behaviors and low rates of task engagement in generaleducationclassrooms.Mariospent time
in two general education settings. One was his homeroom class where he received the majority of his
instruction each day. The other was the class where he
received daily reading instruction. Mario's reading
teacherwas interviewedfirst because all of his teachers
suspectedthat the readingclasswas where he exhibited
the most problematic and off-task behaviors. Next,
Mario'shomeroom teacherwas interviewedfor possible
corroborationof summarystatementsgeneratedduring
the first interview.Finally,Mariowas interviewed.
Interview with reading teacher. Mario's reading
teacheridentified (a) insubordination,(b) failureto finish work, (c) off-task, and (d) out-of-seat as his most
problematic behaviors. Insubordination usually took
the form of saying "no"and arguingwith teachers.Offtask consisted of fiddling with objects, specificallyhis
glasses and clothing. Partnerreading with a peer was
identified as the least problematictime. Accordingto
his reading teacher, the most problematic time for
Mario was during reading circle where students
engaged in oral reading exercisesthat contained interspersed comprehension tasks. When asked what purpose Mario'sproblem behaviors during reading might
serve, the teacher said he believed that Mario misbehaved because he found the work difficult.
Interviewwith homeroomteacher. Mariospent most
of his day in a generaleducation classroomof 28 thirdgrade students. His homeroom teacher identified refus-
ing to do work and being off task as the primary problem
behaviors in her classroom. These behaviors usually took
the form of (a) playing with his pencil, (b) fiddling with
things, (c) using inappropriate language, and (d) using
self-degrading terms (e.g., "I'm stupid"). This teacher
perceived (a) spelling, (b) language arts, (c) reading,
(d) writing, and (e) music as problematic times for Mario.
She identified recess and lunch as situations that were
typically not problematic for him. She did not know
whether his special education resource classroom (where
he received support for math and writing/spelling activities) was problematic. Mario's homeroom teacher
described her previous intervention efforts, including
point sheets and assigning in-school detention. When
asked what purpose Mario's problem behaviors might
serve, his homeroom teacher indicated that although
unsure, she suspected that Mario often misbehaved to
"get out of difficult tasks."
Interview with student. During his interview, Mario
identified his problem behaviors at school as (a) not
doing work, (b) "fooling around" (e.g., dancing, laughing, singing), and (c) not listening. He explained that
these behaviors happened most often during spelling,
reading class, and math resource class. When asked
about the consequences of his misbehavior, Mario
answered that he sometimes (a) missed "Friday Fun
Club," (b) was sent to the refocus area, and (c) got his
name written on the board. When asked which academic subjects he thought were the hardest, Mario
reported that reading, resource math, and morning
work were the most difficult school activities.
Curriculum-Based Measurement
As noted, each interview identified reading class as a
time when Mario himself exhibited high rates of problem behaviors. In addition, Mario himself characterized
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reading as a difficult task. Consequently, the researchers believed a closer inspection of Mario's reading skills
was warranted. The school used curriculum-based
measurement to monitor students' reading progress
over time. Data were collected three times per year
schoolwide. First, Mario's ORF scores were examined;
that is, the number of correct words per minute that he
could orally decode using grade-level reading material.
Based on his ORFscore, Mario was within an acceptable
performance range when compared with his thirdgrade peers.
Figure 1 displays fall, winter, and spring ORF scores
for all students in Mario's reading. Scores from each
administration (i.e., fall, winter, spring) are represented
as a box plot with a solid diamond symbol indicating
the relative location of Mario's score. Although students who scored in the lower quartile were considered
at risk for reading failure, Mario's scores were within
the inter-quartile range, placing him at a non-risk status on that measure.
Focusing on the convergence of information identifying reading as the most difficult instructional situation for Mario, as well as the teachers' suspicions that
his problem behaviors functioned to escape/avoid difficult tasks, the researchers decided to administer a brief
comprehension assessment to Mario as well as his
third-grade classmates. Although oral reading fluency is
highly correlated with reading comprehension (Howell
& Nolet, 2000), and Mario's ORF score did not place
him "at risk" for reading failure, a more direct measure
of Mario's reading comprehension was deemed warranted. As a result, a MAZE test was administered to
Mario and his reading class to screen for potential comprehension deficits. Unlike his performance on the
ORF measures, Mario's performance on the comprehension measure was lower than that of the vast majority of his reading classmates. In fact, when compared to
the other students in his reading class, Mario scored at
the bottom of the lower quartile. Figure 2 displays the
results of the MAZE test as a box plot, again using a
solid diamond symbol to indicate the relative location
of Mario's score. This information, paired with Mario's
ORF performance data, proved to be very useful for
refining a hypothesis about the context in which his
problem behaviors occurred and subsequently designing a functional analysis to confirm that hypothesis.
Initial Direct Observations
Mario was observed during a variety of reading tasks
and instructional contexts in an effort to identify the
specific conditions influencing his problem behaviors.
Table 2 summarizes the reading tasks/situations where
Mario was initially observed and shows the corresponding mean percentage of intervals that Mario was on
task and not exhibiting problem behaviors. These initial
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baseline observationsyielded highly variabledata, with
a mean task engagement level of 52% and a range of
20% to 88%.
FBA Hypothesis
Initially, a variety of hypotheses regardingthe specific conditions that occasioned Mario's problem
behaviors during reading class were considered.
Examples of the variables considered included smallgroup instruction versus large-group,access to teacher
attention versus independent work, access to peer
attention versus alone, and tasks requiring oral
responses versus written. A careful review of the baseline direct observationsand interviewdata allowed the
researchersto formulatea hypothesis to be experimentally tested. The researchersconstructed the following
summary statement: Whenpresentedwith readingtasks
Mariodisplaysproblembehavthat requirecomprehension,
iors to escape those tasks. Mario's problem behaviors
were displayedwhile he was off task (failing to engage
in the academic tasks at hand) and often consisted of
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fiddling with objects, playing with his glasses, or just
staring around the room. The end result of these subtle,
but functionally effective behaviors was often a
decrease in or complete removal of work demands. In
rare instances when these behaviors did not result in
decreased work demands, Mario's behaviors would
escalate and become noncompliant or disruptive.
Functional Analysis
An experimental functional analysis of the variables
thought to occasion problem behavior was carefully
designed. The testable hypothesis appeared to depict
the task dimensions that caused problem behavior. The
percentages of intervals when Mario exhibited on-task
behaviors were examined during different conditions
using an alternating-treatments design. Two primary
conditions were examined: (a) reading tasks without
comprehension (i.e., decoding alone) and (b) reading
tasks requiring text comprehension. In addition, the
researchers examined Mario's behaviors under each
condition when he had easy access to teacher and peer
attention as well as when he did not. This allowed
them to rule out competing hypotheses about the function of Mario's problem behaviors (e.g., that his problem behaviors were maintained by teacher attention,
teacher avoidance, or peer attention).
The mean level of task engagement during the
decoding condition was 97%, with a range of 93% to
100%. Task engagement during decoding (with opportunity for peer and teacher attention) was 92%, with a
range of 87% to 95%. The comprehension task condition had a mean level of 43%, with a range of 27% to
56%. Comprehension tasks (with opportunity to access
teacher and peer attention) yielded a mean task
engagement of 49%, with a range of 40% to 58%. No
overlap was observed between decoding and comprehension conditions. Further, the presence or absence
of teacher and/or peer attention did not appear to be
associated with the mean differences during the decoding versus comprehension conditions. The direct
observation data are displayed in the second phase of
the graph in Figure 3.
Intervention Development
The results of the functional analysis clearly supported the hypothesis that Mario's problem behaviors
were triggered by reading comprehension tasks and
functioned to escape/avoid those tasks. Using the information gathered during the FBAprocess and confirmed
through the functional analysis, the researchers and
the reading teacher began designing an intervention.
Although Mario spoke English fluently, his primary
language was Spanish, which was the only language
used in his home. His reading teacher believed that he
might benefit from additional vocabulary instruction.
Preteaching vocabulary concepts was determined to be
a logical intervention. Preteaching would help ensure
that Mario had sufficient background knowledge to
complete comprehension tasks during his reading
class-the condition under which he displayed the
most problem behaviors and the lowest levels of task
engagement. The reading teacher and researchers
believed that preteaching vocabulary would be academically relevant, increase task engagement, and fit
contextually with Mario's reading program. They
believed that preteaching vocabulary would provide
Mario with cognitive and curricular access (i.e., background knowledge needed to complete the comprehension tasks) to his reading program in the general
education setting.
As the researchers collaborated with Mario's reading
teacher to finalize the details of an intervention plan,
they decided that the teacher would identify vocabulary words encountered in the reading curriculum that
Mario might find difficult. Some words were preidentified by the curriculum, but the teacher selected additional vocabulary that might be difficult for someone
who spoke English as a second language. A graduate
student intern provided 25 minutes of daily vocabulary
instruction. The vocabulary words were introduced the
day before Mario was to encounter them in his reading
class. The average number of words covered each day
was 12 (range of 8 to 16). On days when fewer new
words were introduced, some of the previous words
were interspersed to provide distributed review over
time. The intervention typically occurred in the afternoons after Mario's special education resource time.
The intern began by presenting the definition of preselected words and phrases (as provided in Mario's reading text, or from a children's dictionary if the term was
not in the glossary). Mario was allowed to ask questions
about the words/phrases and was prompted to use
them in sentences to demonstrate he understood their
meaning. When objects were available to depict a
vocabulary word or term, they were presented during
the lesson as well. The only other component of the
intervention was a set of vocabulary cards. At the end
of each lesson, Mario was provided with index cards
listing the words that were taught. The following
morning in his homeroom, he was allowed to review
his vocabulary cards for 10 minutes before going to his
reading class.
Intervention Results
An alternating-treatments design was used to evaluate the effects of preteaching vocabulary words on the
task engagement of a third-grade student during reading comprehension tasks. Results of within- and acrossphase analyses indicated high mean levels of task
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engagement during decoding tasks, initial vocabulary
instruction, and comprehension tasks. (Periodic observations during decoding tasks and preteaching vocabulary sessions were conducted as descriptive data. The
comprehension tasks, however, were the experimental
condition.) A mean task engagement of 91% (range of
79% to 100%) was observed during decoding tasks. The
percentage of intervals when Mario was on task during
observations of initial instruction of the vocabulary
terms averaged 95% (range of 89% to 100%). Most
important, the mean percentage of intervals that Mario
was on task during reading comprehension tasks when
associated vocabulary terms had been pretaught was
99% (range of 96% to 100%).
As a control condition, researchers observed Mario
during reading tasks for which he did not receive prior
vocabulary instruction. During the control condition,
he exhibited markedly lower levels of task engagement
with an observed mean of 38%. When comparing
Mario's on-task behaviors during the control condition
with his behaviors during decoding tasks, initial vocabulary instruction, and the intervention (i.e., comprehension tasks preceded by vocabulary instruction),
mean differences of 53%, 57%, and 61%, respectively,
were observed. No overlapping data points were
observed between the control condition and decoding,
initial instruction, and pretaught vocabulary conditions. The data displayed in the third phase of Figure 3
depict the functional relation between preteaching
vocabulary and on-task behaviors.
DISCUSSION
The results of this single-case experiment are encouraging and contribute to the knowledge base regarding
the use of behavioral approaches to inform the development of relevant and effective instructional interventions for students whose problem behaviors
function to escape/avoid academic tasks (Dunlap,
White, Vera, Wilson, & Panacek, 1996; Kern, Childs,
Dunlap, Clarke, & Falke, 1994; Lee, Sugai, & Horner,
1999). Some have argued that the previous research
examining escape and avoidance behaviors often
lacked instructional relevance (Gunter & Denny, 1998;
Lane, Umbreit, & Beebe-Frakenberger, 1999). The use of
preteaching as an intervention directly links the FBA
logic to antecedent interventions that are instructional
in nature. Moreover, the functional relation found
between an academic intervention and levels of task
engagement underscores the concerns of many educators regarding the need to address the relationship
between instruction and problem behavior.
Functional Analysis Procedures
Applied settings are not always conducive to arranging traditional analogue conditions to perform func-
tional analyses. Specifically, important information
about contextual and antecedent variables may be omitted, and the contrived nature of an analogue setting
may evoke reactivity in the participant. A solution is to
strike a balance that is reasonable and defensible. The
guidelines for naturalistic functional analysis followed
in this study consisted of (a) manipulating hypothesis
variables in the context of the environment in which
the ongoing behaviors were being exhibited, (b) directly
observing the ongoing interactions between target
behaviors and environmental variables, and (c) tracking
contextual changes in which behavioral interactions
were occurring. The functional analysis procedures
employed demonstrated a functional relation between
reading comprehension tasks and task engagement. The
design allowed the researchers to confirm that, unlike
comprehension tasks, the presentation of decoding tasks
was associated with high levels of task engagement.
Limitations of Study
This study has several limitations. First, the number
of observations in the control condition is limited.
Further observations are needed to establish a reliable
trend, without which caution must be exercised in
interpreting the comparisons with the control condition as well as extrapolating the pattern of data over
extended periods of time.
Another limitation is that direct measures regarding
the fidelity of implementation were not recorded.
Therefore, one cannot quantify the quality of instruction during the intervention (i.e., preteaching vocabulary and providing index cards for later review), or
document the extent to which it differed from the
control conditions. Without this information, caution
must be exercised regarding the inference that only
the independent variable and not features in the natural setting caused the observed changes in the dependent variable.
The third and perhaps greatest limitation is that
probes of academic performance over time were not
administered during the intervention. The extent to
which the student's comprehension performance
increased in the naturalistic classroom setting, therefore, is unknown. This information is needed to establish that preteaching comprehension tasks before a
student is presented with related task demands will
generate positive academic outcomes in addition to the
desired behavioral outcomes.
A fourth limitation is the interaction between low
levels of task engagement and the student's learning
disability was not investigated. Information was only
collected on observable behaviors. Future research is
needed that provides for a closer examination of (a) student characteristics on standardized measures, (b) how
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receiving instruction in a second language interacts
with task difficulty, and (c) the relationship between
problem behavior and reading comprehension for students with learning disabilities.
Finally, applied educational research is often criticized
because researchersfail to determine whether school personnel can implement an intervention with fidelity
(Nelson et al., 1999). In the present study, the researchers
did not systematically transition the delivery of the
intervention from the student intern to the regular
school staff. The researchers identified, trained, and
supervised all aspects of the intervention delivered in
this investigation. Therefore, the extent to which the
regular school personnel will continue to implement the
intervention and achieve similar results is unknown.
Implications for Research and Practice
Like the present study, much of the previous behavioral research that reported decreases in problem behaviors in academic settings did not measure the effects of
the independent variable on academic outcomes.
Educators need a knowledge base that (a) more clearly
defines the relationship between instructional variables
and problem behaviors and (b) provides evidence-based
practices to guide intervention efforts. It is imperative
that future research inquiries assess the relationship
between instructional/academic interventions and their
effects on both social behavior (e.g., on-task and/or
problem behaviors) and academic performance.
To strengthen confidence in the findings from the
present study, both direct and systematic replications
are warranted. Specifically, replications will be necessary to establish the internal validity of contextual variables and the external validity of function-based
approaches for improving academic outcomes for students with learning disabilities. Future research should
(a) identify curriculum-based measures that are sensitive
to the academic progress of the participants receiving
the intervention, (b) develop observation instruments
that add precision to the identification of subtle instructional and contextual variables that influence behavior,
and (c) improve the match between the instructional
context, the function of problem behavior, and subsequent academic performance.
Little research is available to document the effectiveness of function-based behavior support planning
for students with LD. This study contributes to the
knowledge base by (a) extending the use of FBA and
functional analysis procedures with a student with
LD, (b) designing direct observation systems based on
FBA information that measure subtle contextual variables that are academic/instructional in nature, and
(c) employing functional analysis procedures that
occurred in the natural context and addressed subtle
instructional variables. Moreover, the present singlecase experiment contributes to practice in that it integrates effective behavior and instructional support
programming by demonstrating that preteaching academic content can be an effective intervention for
students who display escape-maintained problem
behaviors during academic tasks. Given that educators and applied researchers have been asked to focus
on linking interventions generated through FBA procedures to instructionally relevant behaviors (Gunter
& Denny, 1998; Lane et al., 1999; Nelson et al., 1999),
the present study appears to be a step in the right
direction.
CONCLUSION
The purpose of applied educational research should
be to identify approaches that are trustworthy, usable,
and accessible to practitioners (Carnine, 1992). FBA
and functional analysis approaches have been criticized
in the educational literature as needing systematic
replications to verify their external validity for students
with high-incidence disabilities (Gresham et al., 1999;
Nelson et al., 1999). In addition, some have questioned
whether behavioral approaches can be linked to
instructional and academically relevant outcomes
(Steinberg & Knitzer, 1992). Consequently, the goal of
this study was to examine targeted instructional intervention approaches using FBA and functional analysis
procedures for a third-grade student with learning disabilities. The results of this single-case experiment are
encouraging as they provide preliminary evidence that
function-based support planning can be an effective and
efficient approach to identifying relevant information
for developing instructional interventions for students
who exhibit escape-maintained problem behaviors during academic tasks.
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NOTES
Preparationof this paper was supported in part by a grant from
the Office of Special Education Programs, U.S. Department of
Education (Number H324N000030). Opinions expressed herein
do not necessarily reflect the policy of the Department of
Educationand no official endorsement by the department should
be inferred.
Requests for reprints should be addressed to: Mack Burke, 552
Aderhold Hall, University of Georgia, Athens, GA 30602;
mburke@coe.uga.edu.
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