Response to Intervention
Theory Into Practice, 52:180–189, 2013
Copyright © The College of Education and Human Ecology, The Ohio State University
ISSN: 0040-5841 print/1543-0421 online
DOI: 10.1080/00405841.2013.804309
Jeremy R. Sullivan Felicia Castro-Villarreal
Special Education Policy, Response to Intervention, and the Socialization of Youth
This article discusses special education policy
with a specific focus on response to intervention
(RTI), as proponents suggest that this approach
meets the goals of both the Individuals with
Disabilities Education Improvement Act and No
Child Left Behind. Although there are legitimate
concerns about the validity and reliability of the
measures and interventions used in RTI frame-
works (in addition to other challenges), limited
research suggests positive outcomes associated
with RTI, and the benefits of the conceptual
pillars of this framework, namely high-quality in-
struction, research-based interventions, and sys-
tematic screening and progress monitoring, are
Jeremy R. Sullivan is an associate professor and
Felicia Castro-Villarreal is an assistant professor at the
University of Texas at San Antonio.
Correspondence should be addressed to Jeremy R.
Sullivan, University of Texas at San Antonio, Depart-
ment of Educational Psychology, 501 W. Cesar E.
Chavez Blvd., San Antonio, TX 78207-4415. E-mail:
jeremy.sullivan@utsa.edu.
unequivocal. In addition to reviewing the core
features of RTI, this article discusses implications
of special education eligibility processes for the
socialization of youth. The population targeted
by this article includes students in K–12 settings
who are at risk for special education placement
due to learning disabilities and/or behavioral
difficulties.
Special Education in the United States
P UBLIC LAW 94-142 (the Education for All
Handicapped Children Act), passed in 1975,
required states to provide a free and appropriate
education to children with disabilities, even those
with significant impairment caused by severe
disabilities (Jacob, Decker, & Hartshorne, 2011).
The Act was renamed the Individuals with Dis-
abilities Education Act in 1990, and the current
version of special education policy is the Indi-
viduals with Disabilities Education Improvement
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Sullivan and Castro-Villarreal Special Education Policy, RTI, and Socialization
Act of 2004 (IDEA, 2004). IDEA maintains the
spirit of inclusive education that was introduced
with Public Law 94-142, but has been revised
to reflect advances in knowledge related to the
assessment and identification of children with
disabilities.
As of 2009, over 6.5 million youth in the
United States were receiving special education
services, with almost half (49.2%) of these
students identified with some type of learning
disability (US Department of Education, Office
of Special Education Programs, Data Analysis
System, 2009). Placement in the special edu-
cation system has far-reaching and long-lasting
implications for the student, not only in terms of
instruction, but also with regard to educational
placement, participation in statewide assessment,
and expectations for transition beyond public
education. Although a major goal of special ed-
ucation services is to facilitate students’ transfer
back into regular education classrooms, it appears
as if this is a rare outcome (US Department
of Education, Office of Special Education Pro-
grams, Data Analysis System, 2010). The rela-
tive permanence of special education placement
decisions points to the need to critically examine
the methods used to determine who is placed in
special education.
Given the range of disabilities covered by
IDEA (2004), there are a variety of assessment
methods and processes used to establish eligi-
bility for special education services. Considering
the specific learning disability (SLD) category1
as an example, historically, learning disabilities
were identified using a discrepancy model. In this
approach, students are identified when there is a
significant discrepancy between a student’s abil-
ity (assessed with standardized tests of intellec-
tual ability) and their achievement (assessed with
standardized tests of academic achievement). The
discrepancy model has been widely criticized
for numerous reasons, a few of which include:
(a) variability in the size of discrepancy used for
eligibility decision making; (b) concern that by
the time a significant discrepancy is detected, the
child may already be several grade levels behind
(the discrepancy model is often referred to as
the wait to fail approach); (c) overrepresentation
of minority students in special education when
this approach is used; (d) failure to reliably dif-
ferentiate students with a learning disability from
those without; and (e) providing little information
relevant to educational planning and intervention
development (Fuchs & Vaughn, 2005; Hale et al.,
2010; Siegel, 1989). For these reasons, schools
are no longer required to use the discrepancy
model to identify students with SLD.
The Emergence of a New Model:
Response to Intervention
In 2002, a report by the President’s Commis-
sion on Excellence in Special Education (cre-
ated under President George W. Bush) made the
specific recommendation that schools discontinue
the use of ability–achievement discrepancies as
part of the diagnostic process for learning dis-
abilities due to a lack of validity evidence for
this method, and suggested the use of response
to intervention (RTI) approaches in the instruc-
tion, assessment, and intervention process. The
Commission noted that processes inherent to RTI,
namely high-quality instruction, universal screen-
ing, evidence-based interventions, and data-based
decision making could reduce the number of
students placed in special education by more
accurately distinguishing between students with
true disabilities, or nonresponders, and those bet-
ter described as instructional casualties, or those
who respond after exposure to good instruction
and additional supports and intervention.
What is RTI?
As a result of the Commission’s report, the
current version of IDEA (2004) mandates that
states develop alternative processes to traditional
discrepancy models to identify learning disabili-
ties. These alternative processes must permit the
use of the child’s response (or nonresponse) to
evidence-based interventions in determining eli-
gibility for special education (Ahearn, 2009). If
a student continues to struggle despite receiving
high-quality instruction and well-designed inter-
ventions within the general education setting, this
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Educational Policy and Youth in the 21st Century
could be evidence of a learning disability. RTI
is a three-tiered problem-solving model designed
to identify students at risk for academic failure
and/or behavioral difficulties in need of more
intensive instruction than what they experience in
the general education classroom. In the first tier
of problem solving, general education teachers
are asked to provide high-quality instruction in-
formed by universal screening data and frequent
progress monitoring with the general education
curriculum (Tier I) and may progress to increas-
ingly intensive intervention (Tiers II and III).
Because RTI is a systems-level initiative begin-
ning in the general education setting, teachers are
fundamental in the RTI process, given the empha-
sis on high-quality general education instruction,
and they are often responsible for conducting
universal screening, implementing interventions,
and collecting progress monitoring data for data-
based decision making (Werts, Lambert, & Car-
penter, 2009).
Tier I: Universal instruction. Tier I of RTI
involves the general education curriculum and
emphasizes high-quality research-based instruc-
tion, which is the foundation for a successful
and sustainable RTI system (Fuchs & Vaughn,
2005). An essential component of Tier I is the use
of psychometrically sound universal screening
tools to measure all students’ baseline academic
performance and subsequent academic progress.
These data are essential in identifying at-risk
students in need of Tier II RTI intervention.
Approximately 80% of students should have their
needs adequately met through Tier I general
education instruction (Berkeley, Bender, Peaster,
& Saunders, 2009). As an example, a teacher
who is concerned about a student’s (or several
students’) behavior may consult with the school
psychologist to develop and implement classwide
behavioral interventions to increase academic
engaged time and decrease behavioral disrup-
tions, and then collect data on students’ behavior
to demonstrate RTI. Tier I interventions occur
within the context of the regular classroom.
Tier II: Supplemental instruction. Students
who are not performing on grade level as deter-
mined by universal screening are provided with
Tier II intervention. It is estimated that approxi-
mately 15% of students will need Tier II services
(Berkeley et al., 2009); these students may work
individually with a specialist, in small groups,
or may be pulled out for support. Examples
include a student participating in the school’s
Title I reading program as a result of performing
below grade level on benchmark testing, or a
group of students identified as needing social
skills instruction via group counseling. Once in
Tier II services, the teacher, coteacher, academic
specialist, or school psychologist is responsible
for implementing the intervention with high in-
tegrity and collecting progress monitoring data to
determine students’ RTI.
Tier III: Individualized instruction. Stu-
dents who do not respond to Tier II intervention
require Tier III intervention and/or a comprehen-
sive psychoeducational evaluation. The informa-
tion obtained from Tier III progress monitoring
or comprehensive evaluation should be used to
inform the student’s future educational planning
and possible eligibility for special education. If
the student does qualify for special education,
RTI data can be used as baseline skill data, to rule
out lack of exposure to research-based instruc-
tion and intervention, and to inform instructional
planning (i.e., the student’s individual education
plan). If the student does not qualify, data can
still be used to inform instructional planning in
the general education setting. Only about 5%
of students require the intensive, individualized
services characterized by Tier III intervention
(Berkeley et al., 2009).
Deconstructing RTI:
Strengths and Limitations
Despite conceptual consistency, the manner
in which RTI is implemented across states and
districts varies widely (Ahearn, 2009). Recent
data indicate that most states have made progress
in implementing RTI (e.g., 15 states were cur-
rently implementing RTI models, 22 states were
developing RTI models, and 10 states were
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Sullivan and Castro-Villarreal Special Education Policy, RTI, and Socialization
providing guidance to districts in RTI imple-
mentation), but significant variability exists in
how RTI is being implemented (Berkeley et al.,
2009). Nonetheless, RTI’s widespread yet varied
implementation has had significant impact on the
way schools, educators, and students function.
This is especially true when one considers the
financial costs and additional training associated
with the requirements of research-based instruc-
tion, universal screening, frequent progress moni-
toring, and data-based decision making (Samuels,
2011). RTI likely means different things for
different school staff members. Generally, for
teachers it means more frequent formative assess-
ment, greater reliance on data, and required use
of evidence-based practices. To that end, most
schools require teachers to screen core academic
skills regularly, frequently monitor individual
student progress, and implement Tier II interven-
tions. The introduction of these new roles has
prompted teachers to voice concerns over what
they perceive to be inadequate preservice train-
ing, in-service training, knowledge, and skills
required to meet the standards of RTI (Castro-
Villarreal, 2012). For educational specialists, it
may mean implementing individual and small-
group interventions, collecting data, and tracking
progress. For school psychologists, it may mean
less time engaging in traditional practices at the
individual-student level and more time engaging
in consultation, problem-solving, and systems-
level activities. These role changes, however, are
considered positive due to prevention science
underpinnings, data-based decision making, and
regular progress monitoring.
On the other hand, the adoption of RTI
has complicated diagnostic decision-making. Al-
though IDEA (2004) permits the use of RTI
data in the identification of SLD, this practice
has not been without controversy. For example,
many are reluctant to conclude that RTI has
sufficient validity and reliability to be used in the
diagnosis of SLD (Reynolds & Shaywitz, 2009).
Still, using RTI as a method for identifying stu-
dents with disabilities addresses some of the con-
cerns with using discrepancy formulas for SLD
identification. Increased reliance on data reduces
referral bias, thereby potentially decreasing the
overrepresentation of minority students in special
education and advancing nondiscriminatory as-
sessment (Fuchs & Vaughn, 2005; Orosco, 2010).
Moreover, data-based decision-making and fre-
quent progress monitoring facilitates the use
of research-based instruction and evidence-based
intervention allowing decision makers to rule out
lack of exposure to high quality instruction or op-
portunity as possible explanations for academic
failure. Tier I high-quality and research-based
core instruction also allows schools to focus on
all students, not just those who are suspected of,
or identified as, having a disability.
Despite its promise, numerous limitations of
RTI have been described in the literature (see,
especially, Burns, Jacob, & Wagner, 2008; Hale
et al., 2010; McKenzie, 2009; Reynolds & Shay-
witz, 2009). One issue is that, as compared to the
discrepancy model, RTI may lead to even more
subjectivity in decisions about who should be
eligible for special education, as schools have the
freedom to select universal screening measures
and cut-off criteria, resulting in different methods
for identifying students in need of intervention
and at-risk for special education placement due to
learning disabilities and/or behavioral difficulties,
and a variety of evidence-based interventions
are implemented across the tiers. An additional
lingering criticism involves the variability and
fidelity with which RTI frameworks are imple-
mented. Relevant questions include: How does
one define evidence-based interventions? How
often does one monitor students’ progress? How
does one define lack of response to intervention
(see O’Connor & Klingner, 2010)? How does
one determine how much nonresponse warrants
referral to special education, or how long does
one give the student to respond before deciding
to formally refer? Does the dependence on failure
for students to receive more intensive services
move the referral process from wait to fail (like
in the discrepancy model) to “watch them fail”
(as suggested by Reynolds & Shaywitz, 2009,
p. 141) by prolonging the formal referral pro-
cess? What criteria should be used to determine
when to move students from one tier to another?
Even though tiered levels of support are standard
across RTI models, the varying duration and
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Educational Policy and Youth in the 21st Century
intensity of interventions will largely determine
who is deemed eligible to receive special educa-
tion services.
Another critical challenge with RTI is inter-
vention integrity, which refers to the fidelity with
which an intervention is implemented. If there
is no progress in response to an intervention,
is that lack of progress due to the severity
of the child’s difficulties, or an inappropriate
intervention, or an appropriate intervention im-
plemented haphazardly, or some combination of
these factors? The implication is that we cannot
conclude that a child has a SLD based solely
on nonresponse to intervention, as there are
multiple reasons why a child may not respond.
It also is unclear whether data generated by
RTI approaches are adequately reliable and valid
for decision-making purposes. Fundamentally, as
a preventative problem-solving model, RTI is
widely perceived as beneficial for all students but
not superior to comprehensive psychoeducational
assessment for the diagnosis of learning disabil-
ities (Machek & Nelson, 2010).
Variation in RTI Implementation
Although IDEA is a federal policy, some
freedom is granted to states with regard to how
disabilities are defined and identified (see Garda,
2006; MacFarlane & Kanaya, 2009). Thus, vari-
ability exists among states in how IDEA is
implemented, such that two states may employ
different methods for identifying disabilities, and
thus utilize RTI data in various ways. One impli-
cation of this variability is that a student could
be receiving special education services in one
state, then move to another state that uses a
different set of criteria for determining eligibility,
and find themselves no longer eligible to receive
special education services (Ahearn, 2009). Using
SLD as an example, Reschly and Hosp (2004)
found considerable variability among states in
terms of the definitions and classification crite-
ria used for identifying students with learning
disabilities, leading to commensurate variability
in prevalence rates across different states. This
variability in implementation also was noted as
a significant limitation of the discrepancy model,
and thus represents an area in which RTI has
not improved upon some of the limitations of the
older model.
The Impact of RTI on Students
Outcomes associated with RTI appear promis-
ing for reducing the number of special educa-
tion referrals, reducing the number of students
identified for special education services, and
decreasing the ratio of students tested to students
identified (Samuels, 2011). Unfortunately, there
is very little empirical data on the long-term
impact of RTI for all students, but especially for
students with disabilities (Ysseldyke et al., 2004).
Although a major ambition of RTI was to
reduce the disproportionate number of minority
students in special education, few studies docu-
ment such a reduction (McDougal, Clonan, &
Martens, 2000), and recent findings put forth
by the National Center for Learning Disabilities
cited a significant increase in the percentage
of students who qualified for SLD who were
also English language learners (ELLs; Cortiella,
2011). Some, however, have found positive out-
comes associated with RTI for ELLs based on
increased instructional effectiveness and supple-
mental and intensive small group instruction
(McIntosh, Graves, & Gersten, 2007).
RTI’s largest impact has been demonstrated
by a reduction in the overall number of stu-
dents meeting special education eligibility for
SLD (Torgesen, 2007; VanDerHeyden, Witt, &
Gilbertson, 2007) and greater precision in refer-
rals for special education testing. Additionally,
the decreased dropout rate among students with
SLD (from 40% to 22%) and the increase in the
percentage of these students who are graduating
with a regular high school diploma (from 52% to
64%) have also been attributed to the expanded
use of RTI (Cortiella, 2011). So, in spite of some
of the lingering problems of RTI, decreasing rates
of SLD suggest that it is making positive impact
when it comes to remediating students’ academic
and behavioral concerns in the general education
setting before failure, resulting in appropriate
and data-based referrals, and more accurately
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Sullivan and Castro-Villarreal Special Education Policy, RTI, and Socialization
identifying those students who are (and should
be) eligible for special education services.
With regard to RTI methods and educational
outcomes, findings show fewer students needing
Tier II supports after RTI adoption and more
students performing on grade level (Carney &
Stiefel, 2008). Additional educational gains have
been observed in an increased percentage of
students reaching benchmarks and grade level
on state testing (Bollman, Silberglitt, & Gibbons,
2007; Vaughn et al., 2010). RTI has had success
with reading evidenced by an increasing number
of studies documenting improved reading out-
comes for students (O’Connor, Harty, & Fulmer,
2005; Pearce, 2009). Moreover, initial improve-
ments in reading and behavior appear to be linked
to reductions in special education placement as
more and more studies are reporting reductions
in special education placement after the adoption
of RTI (Denton, Fletcher, Anthony, & Francis,
2006; O’Connor et al., 2005; Pearce, 2009). It is
important to note that most of the research on RTI
outcomes has been conducted at the elementary
school level and is based on reading skills, and
with much less research examining the impact of
RTI on other academic areas such as mathematics
and writing (Hughes & Dexter, 2011).
Implications of Special Education
Policy for the Socialization of Youth
This article has reviewed some of the com-
plexities associated with special education eli-
gibility decisions. As previously described, how
special education policy is implemented will de-
termine who receives special education services.
If a student who needs services is denied those
services based on a poorly implemented system,
or if a student is inappropriately or unnecessarily
placed in special education, the policy is not
working as intended, which will negatively im-
pact students’ academic and psychological devel-
opment. Within this context, RTI may contribute
to the positive socialization of students by re-
ducing inappropriate and unnecessary placements
in special education thereby minimizing stigmas
and stereotypes associated with labeling.
The RTI approach, namely increasing tiers
of support matched to student need, may be
especially important for the socialization of stu-
dents with both academic and behavioral chal-
lenges. These students may be at a significant
disadvantage due to their deviance from both
academic and behavioral norms, and therefore
are particularly at risk for poor psychosocial
outcomes. Literature suggests that academic and
behavioral problems often go hand-in-hand, as
students with learning disabilities and other aca-
demic difficulties are also at risk for aggressive
behaviors, poor social skills, difficulty with social
cognition, emotional maladjustment, feelings of
inadequacy, and diminished achievement moti-
vation due to a history of academic struggles
(Galway & Metsala, 2011; Martinez & Semrud-
Clikeman, 2004). These students also are more
likely than typically developing students to be
rejected or victimized by their peers, leading to
associated depression, anxiety, and social with-
drawal (Baumeister, Storch, & Geffken, 2008).
Further, interventions that enhance students’ aca-
demic skills also tend to result in enhanced
behavioral and psychosocial functioning (Sulli-
van & Conoley, 2004). For students with both
academic and behavioral issues, critical features
of RTI such as problem solving, increasing tiers
of support, and frequent progress monitoring can
address both areas. Moreover, the advent of RTI
problem-solving approaches nicely complements
contemporary education where 70% of students
with high incidence disabilities like SLD or
emotional disturbance will be educated in the
general education setting.
SLD and other special education classifica-
tions are often long-term diagnoses that likely
will continue to impact students’ socialization
in secondary education and beyond. Given the
long-term nature of special education eligibil-
ity and placement decisions, and the impact
on students’ socialization, it seems clear that
these decisions must be made carefully and
thoughtfully. RTI problem-solving frameworks
effectively communicate the importance of differ-
entiating instruction to match student need, data-
based decision making to reduce subjectivity, and
formative assessment to monitor student learning
185
Educational Policy and Youth in the 21st Century
and response to high quality instruction and inter-
vention.
Response to Policy:
A Balanced Approach
As described, both the discrepancy model and
RTI have their strengths and their limitations. As
noted by Kozleski and Huber (2010), if one does
not seek to understand RTI’s limitations, “RTI
can become another set of procedures that are
implemented without grasping the fundamental
precept that failure to respond resides within
complex interactions between systems, cultural
histories, and individual differences” (p. 260).
Therefore, we argue that by combining data
from RTI with data from a comprehensive psy-
choeducational assessment, one can assess these
individual differences and more readily link as-
sessment data to intervention. In many cases,
results of standardized measures of intelligence
and academic achievement offer valuable norma-
tive information. Indeed, many experts agree that
decisions regarding SLD eligibility should not
be made in the absence of data from cognitive
tests, and that failure to respond to intervention
alone is not an adequate criterion for SLD di-
agnosis (see Hale et al., 2010). At the same
time, RTI data help to rule out environmental
and instructional factors that may better explain
academic performance. Partially attributable to
the RTI movement, universal benchmark testing
is no longer unique to certain schools; these data
are being utilized for instructional modification
and informing referral for special education eval-
uation (Fuchs & Vaughn, 2005). We hope that the
dichotomized discussion of RTI models versus
cognitive assessment models that dominates the
current school psychology literature will give
way to consideration of how the strengths of
RTI and the strengths of cognitive assessment
can be combined in a way that leads to the most
informed decisions for all students.
The arguments presented in this article point
to some recommendations for improving special
education policy in a way that will positively im-
pact the socialization of the nation’s schoolchil-
dren. Simply stated, if RTI is here to stay, educa-
tors need to figure out how best to implement
it. First and foremost, much more research is
needed regarding the impact of RTI on student
outcomes (Burns et al., 2008) and should include
studies on evidence-based interventions for di-
verse groups of students across the three tiers of
RTI, evidence-based assessment approaches, and
best practices in combining RTI with compre-
hensive psychoeducational assessment. Second,
the inconsistency with which RTI is currently
being implemented suggests the need for some
sort of uniform procedures at the state or national
level. Otherwise, significant variability will likely
continue to be the norm, which makes it ex-
tremely difficult to compare outcomes and SLD
rates at the campus, district, or state level. At the
same time, it is likely that specific methods of
implementation must fit within the unique district
and campus systems in order to be sustainable
over time (Kozleski & Huber, 2010). Third,
schools need additional resources for general
education interventions. For example, if school
psychologists are going to spend more time on
RTI activities, their potential services and clients
(i.e., the whole school) significantly increase,
thereby requiring more personnel to function in
this expanded role. Similarly, if teachers are to be
expected to assume additional responsibilities for
implementing academic interventions and mea-
suring outcomes, districts need to take an active
approach to providing professional development
opportunities so that teachers can further develop
their expertise in these areas. The potential trade-
off to committing more money for additional
personnel and professional development would
be an increased number of students (both with
and without disabilities) who receive appropriate
services for their academic and behavioral chal-
lenges.
Conclusion
RTI’s focus on outcomes for all children sup-
ports the idea that students in special education
are the shared responsibility of general educa-
tion and special education (Weber, 2009). In
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Sullivan and Castro-Villarreal Special Education Policy, RTI, and Socialization
the current climate of diminishing resources and
higher need, schools must examine how general
and special education resources/services can be
combined to provide optimal educational oppor-
tunities, rather than fragmenting these services
or looking to the special education system to fix
students with disabilities. Educators must realize
that many students with disabilities (and strug-
gling learners more generally) will be in their
classrooms in need of additional supports and
differentiated instruction. Historically, struggling
learners were identified, tested, possibly placed
in special education, and pulled out for more
individualized instruction. With RTI, schools are
asking educators to play a larger role in the
identification of struggling learners, design indi-
vidualized intervention plans, monitor progress,
and collect data. Naturally, there has been re-
sistance, namely due to increased paperwork,
unclear benefit, and frustration over delays in
special education evaluation (Castro-Villarreal,
2012). However, the benefits of early identifi-
cation and prevention cannot be minimized and
the potential for RTI to enhance outcomes for
struggling learners and minority groups cannot
be dismissed. If utilized in a uniform fashion
with an agreed upon purpose and in conjunction
with more comprehensive assessment data when
necessary, RTI holds great promise for improving
outcomes for students.
Note
1. IDEA (2004) defined SLD as follows: “(i) General.
Specific learning disability means a disorder in
one or more of the basic psychological processes
involved in understanding or in using language,
spoken or written, that may manifest itself in the
imperfect ability to listen, think, speak, read, write,
spell, or to do mathematical calculations, including
conditions such as perceptual disabilities, brain
injury, minimal brain dysfunction, dyslexia, and
developmental aphasia. (ii) Disorders not included.
Specific learning disability does not include learn-
ing problems that are primarily the result of visual,
hearing, or motor disabilities, of mental retardation,
of emotional disturbance, or of environmental, cul-
tural, or economic disadvantage.”
References
Ahearn, E. M. (2009). State eligibility requirements
for specific learning disabilities. Communication
Disorders Quarterly, 30, 120–128. doi: 10.1177/15
25740108325221
Baumeister, A. L., Storch, E. A., & Geffken, G. R.
(2008). Peer victimization in children with learning
disabilities. Child & Adolescent Social Work Jour-
nal, 25, 11–23. doi: 10.1007/s10560-007-0109-6
Berkeley, S., Bender, W. N., Peaster, L. G., & Saun-
ders, L. (2009). Implementation of response to
intervention: A snapshot of progress. Journal of
Learning Disabilities, 42, 85–95. doi: 10.1177/002
2219408326214
Bollman, K. A., Silberglitt, B., & Gibbons, K. A.
(2007). The St. Croix River Education District
model: Incorporating systems-level organization
and a multi-tiered problem-solving process for in-
tervention delivery. In S. R. Jimerson, M. K. Burns,
& A. M. VanDerHeyden (Eds.), Handbook of re-
sponse to intervention: The science and practice of
assessment and intervention (pp. 319–330). Boston,
MA: Springer. doi: 10.1007/978-0-387-49053-3
Burns, M. K., Jacob, S., & Wagner, A. R. (2008).
Ethical and legal issues associated with using
response-to-intervention to assess learning disabil-
ities. Journal of School Psychology, 46, 263–279.
doi: 10.1016/j.jsp.2007.06.001
Carney, K. J., & Stiefel, G. S. (2008). Long-term re-
sults of a problem-solving approach to response to
intervention: Discussion and implications. Learn-
ing Disabilities: A Contemporary Journal, 6, 61–
75.
Castro-Villarreal, F. (2012). Memorandum received:
What one city’s teachers say about response to in-
tervention in their school. Unpublished manuscript.
Cortiella, C. (2011). The state of learning disabilities.
New York, NY: National Center for Learning Dis-
abilities.
Denton, C. A., Fletcher, J. M., Anthony, J. L., &
Francis, D. J. (2006). An evaluation of intensive
intervention for students with persistent reading
difficulties. Journal of Learning Disabilities, 39,
447–466. doi: 10.1177/00222194060390050601
Education for All Handicapped Children Act of 1975.
(Pub. L. No. 94-142), 20 U.S.C. Chapter 33.
Fuchs, L. S., & Vaughn, S. R. (2005). Response to
intervention as a framework for the identification
of learning disabilities. Trainer’s Forum: Periodical
of the Trainers of School Psychologists, 25, 12–
19.
187
Educational Policy and Youth in the 21st Century
Galway, T. M., & Metsala, J. L. (2011). Social cog-
nition and its relation to psychosocial adjustment
in children with nonverbal learning disabilities.
Journal of Learning Disabilities, 44, 33–49. doi:
10.1177/0022219410371680
Garda, R. A. (2006). Who is eligible under the Individ-
uals with Disabilities Education Improvement Act?
Journal of Law & Education, 35, 291–334.
Hale, J., Alfonso, V., Berninger, B., Bracken, B.,
Christo, C., Clark, E., : : : Yalof, J. (2010). Critical
issues in response-to-intervention, comprehensive
evaluation, and specific learning disabilities iden-
tification and intervention: An expert white paper
consensus. Learning Disability Quarterly, 33, 223–
236.
Hughes, C. A., & Dexter, D. D. (2011). Response to
intervention: A research-based summary. Theory
Into Practice, 50, 4–11. doi: 10.1080/00405841.
2011.534909
Individuals with Disabilities Education Improvement
Act of 2004 (Pub. L. No. 108-446), 20 U.S.C.
� 1400 et seq. (reauthorization of the Individuals
with Disabilities Education Act of 1990).
Jacob, S., Decker, D. M., & Hartshorne, T. S. (2011).
Ethics and law for school psychologists (6th ed.).
Hoboken, NJ: Wiley.
Kozleski, E. B., & Huber, J. J. (2010). Systemic
change for RTI: Key shifts for practice. Theory
Into Practice, 49, 258–264. doi: 10.1080/004058
41.2010.510696
MacFarlane, J. R., & Kanaya, T. (2009). What does it
mean to be Autistic? Inter-state variation in special
education criteria for Autism services. Journal of
Child and Family Studies, 18, 662–669. doi: 10.10
07/s10826-009-9268-8
Machek, G. R., & Nelson, J. M. (2010). School
psychologists’ perceptions regarding the practice
of identifying reading disabilities: Cognitive as-
sessment and response to intervention considera-
tions. Psychology in the Schools, 47, 230–245. doi:
10.1002/pits.20467
Martinez, R. S., & Semrud-Clikeman, M. (2004).
Emotional adjustment and school functioning of
young adolescents with multiple versus single
learning disabilities. Journal of Learning Disabili-
ties, 37, 411–420.
McDougal, J. L., Clonan, S. M., & Martens, B. K.
(2000). Using organizational change procedures to
promote the acceptability of prereferral interven-
tion services: The school-based intervention team
project. School Psychology Quarterly, 15, 149–171.
doi: 10.1037/h0088783
McIntosh, A. S., Graves, A., & Gersten, R. (2007).
The effects of response to intervention on literacy
development in multiple language settings. Learn-
ing Disability Quarterly, 30, 197–212. doi: 10.230
7/30035564
McKenzie, R. G. (2009). Obscuring vital distinc-
tions: The oversimplification of learning disabili-
ties within RTI. Learning Disability Quarterly, 32,
203–215.
O’Connor, R. E., Harty, K. R., & Fulmer, D. (2005).
Tiers of intervention in kindergarten through third
grade. Journal of Learning Disabilities, 38, 532–
538. doi: 10.1177/00222194050380060901
O’Connor, R. E., & Klingner, J. (2010). Poor respon-
ders in RTI. Theory Into Practice, 49, 297–304.
doi: 10.1080/00405841.2010.510758
Orosco, M. J. (2010). A sociocultural examination
of response to intervention with Latino English
language learners. Theory Into Practice, 49, 265–
272. doi: 10.1080/00405841.2010.510703
Pearce, L. R. (2009). Helping children with emotional
difficulties: A response to intervention investiga-
tion. Rural Educator, 30, 34–46.
President’s Commission on Excellence in Special Edu-
cation. (2002). A new era: Revitalizing special edu-
cation for children and their families. Washington,
DC: US Department of Education Office of Special
Education and Rehabilitative Services.
Reschly, D. J., & Hosp, J. L. (2004). State SLD identi-
fication policies and practices. Learning Disability
Quarterly, 27, 197–213. doi: 10.2307/1593673
Reynolds, C. R., & Shaywitz, S. E. (2009). Response
to intervention: Ready or not? Or, from wait-to-fail
to watch-them-fail. School Psychology Quarterly,
24, 130–145. doi: 10.1037/a0016158
Samuels, C. A. (2011, March 2). RTI: An approach on
the march. Education Week, 30(22), S2–S5.
Siegel, L. S. (1989). IQ is irrelevant to the definition
of learning disabilities. Journal of Learning Dis-
abilities, 22, 469–478.
Sullivan, J. R., & Conoley, J. C. (2004). Academic
and instructional interventions with aggressive stu-
dents. In J. C. Conoley & A. P. Goldstein (Eds.),
School violence intervention: A practical handbook
(2nd ed., pp. 235–255). New York, NY: Guil-
ford.
Torgesen, J. (2007). Using an RTI model to guide
early reading instruction: Effects on identification
rates for students with learning disabilities (Florida
Center for Reading and Research at Florida State
University Technical Report No. 7). Retrieved De-
cember 15, 2011, from http://www.fcrr.org/
188
Sullivan and Castro-Villarreal Special Education Policy, RTI, and Socialization
US Department of Education, Office of Special Ed-
ucation Programs, Data Analysis System. (2009).
Children with disabilities receiving special edu-
cation under Part B of the Individuals with Dis-
abilities Education Act, 2009 (OMB #1820-0043).
Retrieved June 6, 2011 from https://www.ideadata.
org/PartBData.asp
US Department of Education, Office of Special Ed-
ucation Programs, Data Analysis System. (2010).
Children with disabilities exiting special education
(OMB #1820-0521). Retrieved October 17, 2011
from https://www.ideadata.org
VanDerHeyden, A. M., Witt, J. C., & Gilbertson, D.
(2007). A multi-year evaluation of the effects of
a response to intervention (RTI) model on identi-
fication of children for special education. Journal
of School Psychology, 45, 225–256. doi: 10.1016/j.
jsp.2006.11.004
Vaughn, S., Cirino, P. T., Wanzek, J., Wexler, J.,
Fletcher, J. M., Denton, C. A., & Francis, D. J.
(2010). Response to intervention for middle school
students with reading difficulties: Effects of a pri-
mary and secondary intervention. School Psychol-
ogy Review, 39, 3–21.
Weber, M. C. (2009). Special education law: Chal-
lenges old and new. Phi Delta Kappan, 90, 728–
732.
Werts, M. G., Lambert, M., & Carpenter, E. (2009).
What special education directors say about RTI.
Learning Disability Quarterly, 32, 245–254.
Ysseldyke, J., Nelson, R., Christenson, S., Johnson,
D. R., Dennison, A., Triezenberg, H., Sharpe, M.,
: : : Hawes, M. (2004). What we know and need to
know about the consequences of high-stakes testing
for students with disabilities. Exceptional Children,
71, 75–95.
189
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