Integrating Academic and Behavior Supports Within an RtI Framework, Part 1: General Overview

by Hank Bohanon, Ph.D., Steve Goodman, Ph.D., and Kent McIntosh, Ph.D.

Additional Articles

School-Wide Positive Behavior Support and Response to Intervention
Integrating Academic and Behavior Supports Within an RtI Framework, Part 2: Universal Supports
Integrating Academic and Behavior Supports Within an RtI Framework, Part 3: Secondary Supports
Integrating Academic and Behavior Supports Within an RtI Framework, Part 4: Tertiary Supports

Additional Resources

Increasingly, schools are faced with challenges stemming from the intensity and scope of student needs in their settings. With each scientifically based response to these needs come separate data systems, treatment protocols, teams, and interventions. Because of this, a major consideration for schools is to ensure that teams work smarter, not just harder.

The purpose of this article series is to provide a framework for the integration of academic and behavior supports for each tier of intervention in a Response to Intervention (RtI) model. In this first article in the series, we include a rationale for combined academic and behavior supports. The second article involves a discussion of the universal academic and behavioral reform that is needed to arrive at an integrated model. The third article provides a description of supports for groups of students who do not respond to the core curriculum based on the nature of their needs. The fourth and final article includes an overview of how to identify strategies for intervention and how to establish progress monitoring for students with the most intensive needs.

Academic and Behavior RTI Systems

Over the past few years, there has been increasing interest in integrating academic and behavior supports into one system (Hawken, Vincent, & Schumann, 2008; Stewart, Benner, Martella, & Marchand-Martella, 2007). The recent focus on RtI provides an opportunity to effectively and efficiently combine academic and behavior systems into an integrated school-wide system of supports for students. There are well-documented RtI systems for addressing both academics (Simmons et al., 2002; Vaughn & Fuchs, 2003) and behavior (e.g., school-wide positive behavior support, or SWPBS; Horner, Sugai, Todd, & Lewis-Palmer, 2005). Both types of systems are similar in their focus on universal teaching of all students, provision of a continuum of supports provided to students who do not respond, and reliance on action planning guided by a representative team. They also share an emphasis on the problem-solving process (a decision-making system for identifying and addressing challenges; Tilly, 2008) and the use of data for program development, progress monitoring, and evaluation, and both rely on evidence-based practices. Figure 1 provides a brief illustration of the essential elements of both academic and behavior supports.

Figure 1: Integrated Functions Across All Three Tiers of Support

With these similarities in mind, there are several seemingly unanswered questions regarding the integration of these systems. For instance:

What are the process and outcome components of a well-designed, integrated model of academic and behavior supports (systems, practices, and data)?
What mechanisms in both systems exist for the common activities of universal behavioral screening and identifying trajectories for student success (universal supports; also referred to as Tier 1 supports and/or core instruction)?
What are the data and decision rules for determining which students need additional supports, and what is the nature of the supports needed based on function (e.g., cannot demonstrate the skill, will not demonstrate the skill)? Also, how are the most effective treatment combinations selected, and what are the most efficient methods for progress monitoring that integrate academic and behavioral data when needed (secondary supports)?
What are the most efficient and reliable ways to integrate intensive academic assessment and remediation, complex functional behavior assessment and behavioral intervention plans (including person-centered planning), and progress monitoring (tertiary supports)?
What are the current practices and future directions for integrating these models?

In this article we address these questions by presenting research on the benefits of integrating academic and behavior RtI systems (including a discussion of their similarities and differences) and by discussing implications for universal supports. We also identify the critical components of secondary intervention and discuss the role of tertiary supports.

Emerging Research Linking Academics and Behavior

There are several reasons why integrating academic and behavior supports (particularly in the area of reading) could lead to improved student outcomes. First, there is a documented connection between low academic skills and problem behavior, which may be evident as early as kindergarten but grows over time as students move from elementary to secondary school (Fleming, Harachi, Cortes, Abbott, & Catalano, 2004; Morrison, Anthony, Storino, & Dillon, 2001; Nelson, Benner, Lane, & Smith, 2004). Because of the importance of reading skills and social competence, students facing challenges in both areas are at an exponentially higher risk for negative school outcomes (McIntosh, Flannery, Sugai, Braun, & Cochrane, 2008; McKinney, 1989).

Second, there is evidence that problems in one area (reading and behavior) can predict future problems in other areas. Poor academic skills early in school predict a wide range of behavior problems, because students who have difficulty with reading may find problem behavior as an effective means of escaping or avoiding reading activities (McIntosh, Horner, Chard, Dickey, & Braun, 2008). Students may engage in problem behaviors because the academic activity may be too difficult, too easy, or not relevant to student needs or interests. McIntosh, Horner, Chard, Boland, and Good (2006) found that kindergarteners with phonological awareness skills, as measured through the Dynamic Indicators of Basic Early Literacy Skills Phoneme Segmentation Fluency subtest (Good & Kaminski, 2002), that indicated low risk for reading problems (at least 35 sounds) had an 18% chance of receiving two or more office discipline referrals (ODRs) in 5^th grade. Students scoring in the some risk range (between 10 and 35 sounds) had a 25% chance of having multiple ODRs. Students with scores in the at risk range (below 10 points) had a 33% chance of multiple ODRs in 5^th grade. Moreover, a replication study indicated that students who entered school with phonological awareness deficits but responded to kindergarten reading instruction were at dramatically decreased risk for future problem behavior (McIntosh, Sadler, & Brown, 2009). Similar results have also been found for the effects of early reading challenges on depression in middle school, as students with reading challenges were at increased risk for depression in later grades (Herman, Lambert, Reinke, & Ialongo, 2008).

Fortunately, school personnel can use this interaction between academic skills and behavioral issues to prevent problems in one area by intervening in the other. For example, reducing the number of incidents of problem behavior allows quality instruction to occur more often and with fewer distractions. Lassen, Steele, and Sailor (2006) reported the effects of implementing a behavior RtI system on high stakes achievement test results. In their study, implementation of universal behavior supports in middle school led to significantly improved performance on state assessments in both math and reading. These results are likely due to research showing that improving the social behavior of students results in more minutes spent in academic instruction (Scott & Barrett, 2004). Though more time available for teaching is beneficial, it is important that instructors spend the time wisely, implementing evidence-based academic practices geared toward student need. Even by itself, high quality academic instruction can promote engagement and reduce problem behavior (Filter & Horner, 2009; Lee, Sugai, & Horner, 1999; Preciado, Horner, & Baker, 2009; Sanford, 2006).

In sum, providing behavior supports may be effective in improving academic outcomes, and providing academic supports is related to improved social behavior functioning. Given this interactive relationship between behavior and reading, an integrated system of supports may enhance students' success in both academics and behavior. Behavior supports should consider the student’s academic skills deficits as well as the quality of academic supports. Successful academic interventions may be even more effective with the addition of behavior supports to provide organized and motivating classrooms. It has been shown that integrated academic and behavior RtI models produce larger gains in both outcomes than single models (Ialongo, Poduska, Werthamer, & Kellam, 2001; Lane & Menzies, 2003; McIntosh, Chard, Boland, & Horner, 2006; Stewart et al., 2007).

Logic for an Integrated Approach

There is increasing discussion about how best to integrate academic and behavior supports in a comprehensive model. Sugai (2009b) described how SWPBS shared common elements with academic RtI systems, including the effective use of teaming, accessing universal data components, progress monitoring, utilizing effective interventions, and relying on data decision rules. Additionally, Sugai (2009b) noted that both academic RtI and SWPBS systems share a three-tier, prevention focused model based on universal, secondary, and tertiary prevention. Finally, he stated that RtI can be utilized as "a framework and logic for organizing and increasing the efficiency with which evidence-based practices are selected, organized, integrated, implemented, and adapted" (Sugai, 2009b, para. 7).

Both academic and behavior RtI systems share a common focus on the school and community contexts of implementation, such as size, location, and neighborhood protective and risk factors (Simmons et al., 2002; Stollar, Poth, Curtis, & Cohen, 2006). Key components focus on the identification of a shared approach to intervention (in reading and behavior, for example) and creating a supportive environment where these elements can be embedded into the routines of the staff, school curriculum, and school policies. Academic and behavior RtI systems both share a systems approach to promote success for students (Algozzine & Algozzine, 2009).

Process and Outcome Components of an Integrated Model (Systems, Data, and Practices)

It is our belief that academic and behavior RtI models share similar underlying principles (McIntosh, Chard, et al., 2006). However, there may be unique characteristics of each model that must be addressed somewhat differently. This section provides a brief summary from two framework documents from both academic (Simmons et al., 2002) and behavior (Horner et al., 2005) RtI perspectives. For the purposes of this article, we will solidify these principles into a parsimonious framework advanced by Sugai and Horner (2002), including three overlapping features—systems, practices, and data—all designed with the purpose of achieving valued outcomes. Both academic and behavior RtI systems inherently contain elements of these components.

Systems

Systems (e.g., teaming, visioning, empowering, communicating, institutionalizing) are considered to be "policies, staffing patterns, budgets, team structures, administrative leadership, operating routines, staff training, and action plans that affect the behavior of adults in schools" (Horner et al., 2005, p. 359-390). As Simmons and colleagues (2002) stated, "knowledge of effective, research-based practice is necessary but insufficient" (p. 537-569) in terms of changing adult behavior. Systems are needed to support implementation and the ongoing use of effective teacher practices (Kratochwill & Shernoff, 2004; Sugai & Horner, 2002).

The academic RtI process often begins with universal screening (assessment of all students) for skill deficits through the use of research-validated criteria or norms. As such, individual student data drive the implementation of interventions following this universal screening process. The behavior RtI process is more likely to start with assessment of the school-wide climate and providing universal supports, and then identification of students who do not respond to the core behavior curriculum. In some cases, it may be necessary to obtain the commitment of resources, administrative support, teams, and priorities prior to organizing data. However, a basic level of data reflection may be critical prior to establishing priorities and commitments, particularly in high school settings (Bohanon et al., 2006). Both academic and behavior RtI systems involve a) auditing current levels of implementation based on self-assessment, implementation, and student performance data, b) using these data to develop action plans addressing system strengths and weaknesses, and c) ultimately identifying the RtI system as one of the top three priorities within the building (as identified by the school).

Practices

Academic and behavior RtI approaches focus on evidence-based practices. The selection of practices (e.g., planning and implementing interventions) should be based on the following:

A short list of critical priorities identified by a school, district, or provincial/state team
A limit of only one or two major adoptions at one time
Strategies that have been proven effective in addressing the desired outcomes
The ability to monitor progress of implementation to determine need for improvement (Horner et al., 2005).

Academic RtI systems identify goals, a core academic curriculum, and organizational structures (e.g., dedicated time for instruction, grouping, and scheduling) to enhance academic instruction. Behavior RtI systems identify core behavioral expectations, a process for behavioral instruction (e.g., time for teaching behaviors, instruction within settings, scheduling), and how acknowledgement of behaviors will occur. Behavior RtI systems also involve clarifying and communicating policies that support behavior expectations (e.g., differentiating between major and minor problem behaviors). Both systems identify critical features and treatment components prior to implementation of practices.

Data

Data should be collected and compiled in an ongoing manner and reported to all stakeholders on a regular basis to guide improvement (Horner et al., 2005). Both academic and behavior RtI systems a) identify a data system for monitoring the progress of student performance, b) commit resources for analyzing and interpreting data, c) communicate results and findings, d) adjust interventions based on the review of data, e) review universal (primary) and strategic (secondary) level data monthly, and f) review intensive (tertiary) level data as often as weekly (McIntosh, Reinke, & Herman, in press). In academic RtI systems, specific goals and targets for improvement are set and effectiveness is reviewed three times per year at universal screening dates. The behavior RtI process collects school-wide data (e.g., office discipline referrals) continuously and requires the regular review and presentation of data to guide frequent adjustments in the universal behavioral curriculum. In terms of integration, it may be useful to combine the review of academic and behavior data into a regular cycle of analysis and action planning. For each, both types of data may be reviewed after the fall, winter, and spring academic assessments, or school marking periods. The use of data-based reflection supports the idea that the systems use different measures but in similar processes and with similar goals (Stollar et al., 2008).

Promoting Sustainability through Branding Initiatives

Sustainability of any school systems appears to be an elusive yet important goal (Adelman & Taylor, 2003; Vaughn, Klingner, & Hughes, 2000). New processes are at a disadvantage when presented within existing structures (Fixsen, Blase, Horner, & Sugai, 2008), so to create lasting change, every advantage is needed and potential supports need to be in place. Though consolidating multiple system efforts may seem like a threat to sustainability, integrating academic and behavior RtI systems represents a unique opportunity to enhance the sustainability of both systems.

Rather than viewing academic and behavior systems as separate entities, schools could look at their shared outcomes and combine efforts accordingly. Both academic and behavior RtI systems share a range of common outcomes, including maximizing time for instruction, enhancing student–teacher relationships, fostering school connectedness, and improving academic and social competency for all students (Walker & Shinn, 2002). Finding a balance between too few and too many systems is critical. Because academic and behavior RtI initiatives possess a shared vision (Kotter, 1995), there is an opportunity to address these outcomes together more effectively and efficiently than alone.

A key activity for integrating and sustaining systems is the braiding of initiatives. Braiding refers to building the practices of any new initiative into the fabric of existing programs and priorities within the school building and the school district (Adelman & Taylor, 2003; McLaughlin & Mitra, 2001). The process involves identifying how parallel systems, data, and practices may be combined into a coherent, unified set of daily responsibilities with a common language. Braiding (see Figure 2) will help provide a common focus for staff in improving student outcomes and in enhancing sustainability of initiatives (McIntosh, Horner, & Sugai, 2009).

Figure 2: Braiding Academic and Behavior Supports

One clear example of the opportunity for braiding involves examining the structures of school teams. Typically, each system will develop its own school teams for completing activities (e.g., grade-level teams and academic problem-solving teams for academic RtI systems; school-wide, targeted, and individual behavior problem-solving teams for behavior RtI systems). When considered individually, this approach seems to make sense. But when considering that many teams all have to function within the same school, it is easy to see how school personnel can be overloaded with too many meetings. To allow for a functioning work environment, it is our belief that school personnel should strongly consider combining academic and behavior RtI teams at each tier. In this way, school teams can take advantage of the benefits of considering both sets of data at the same time (Ervin, Schaughency, Goodman, McGlinchey, & Matthews, 2006), especially considering the research on the link between academic and behavior challenges. However, if combined, it is critical that teams consist of personnel with content knowledge in both areas, as the potential gain in efficiency may be outweighed by a potential loss in effectiveness (McIntosh et al., 2009; Stollar et al., 2006). At the very least, it is wise to identify which teams at each level can best be integrated to maximize efforts.

One suggestion for addressing the integration of teams and leadership is the use of team matrices (Sugai, 2009a). Using this process, school faculty identify current initiatives by their purpose, outcomes, intervention level, staff involvement, and connections with school improvement plans. If multiple teams serve the same function, administrators may consider combining teams. This process also allows staff to reflect on the distribution of their responsibilities and consider the amount of human capital any one person can commit. If the same people are on many teams, administrators should identify ways to distribute the leadership responsibilities across new staff members.

Establishing Priority for Integrating Systems

Kotter (1995), in his seminal work on systems change, identified a critical role for those wishing to improve school systems: establishing a sense of urgency for change through reviewing relevant data. This urgency is required on many levels. Though guiding implementation with a school-level focus is critical, district commitment and supports are essential for long-term success (Adelman & Taylor, 2003; Doolittle, 2006). In the early stages of implementation, this urgency is created through identifying shared priorities for change, from school staff to district administrators and other stakeholders (Fixsen, Naoom, Blase, Friedman, & Wallace, 2005). Both academic and behavior RtI systems begin their implementation processes with assessment of current practices and identification of changes that are likely to improve outcomes. The information presented in this article is intended to provide a clear argument for why integrating academic and behavior RtI systems could improve student outcomes. Another critical method for establishing urgency is to use local data to illustrate the subsequent effect of integration on student performance (Freeman et al., 2005). Establishing a compelling case from outcomes data may increase the probability of integrating practices for school teams. Moreover, successes, as demonstrated with academic and behavioral outcomes data, can provide the motivation to keep an integrated model in place.

References

Adelman, H. S., & Taylor, L. (2003). On sustainability of project innovations as systemic change. Journal of Educational and Psychological Consultation, 14, 1–25.

Algozzine, B., & Algozzine, K. M. (2009). Facilitating academic achievement through schoolwide positive behavior support. In W. Sailor, G. Dunlap, G. Sugai, & R. H. Horner (Eds.), Handbook of positive behavior support (pp. 521–550). New York: Springer.

Bohanon, H., Fenning, P., Carney, K., Minnis, M., Anderson-Harris, S., Moroz, K., et al. (2006). School-wide application of urban high school positive behavior support: A case study. Journal of Positive Behavior Interventions , 8, 131–145.

Doolittle, J. H. (2006). Sustainability of positive behavior supports in schools. Unpublished doctoral dissertation, University of Oregon.

Ervin, R. A., Schaughency, E., Goodman, S. D., McGlinchey, M. T., & Matthews, A. (2006). Merging research and practice agendas to address reading and behavior school-wide. School Psychology Review, 35, 198–223.

Filter, K. J., & Horner, R. H. (2009, February 1). Function-based academic interventions for problem behavior. Education and Treatment of Children, 32(1), 1–19.

Fixsen, D. L., Blase, K. A., Horner, R. H., & Sugai, G. (2008). Developing the capacity for scaling up the effective use of evidence-based programs in state departments of education. Chapel Hill, NC: State Implementation of Scaling-up Evidence-based Practices (SISEP) Center.

Fixsen, D. L., Naoom, S. F., Blase, K. A., Friedman, R. M., & Wallace, E. (2005). Implementation research: A synthesis of the literature (FMHI Publication #231). Tampa: University of South Florida, Louis de la Parte Florida Metal Health Institute, The National Implementation Research Network.

Fleming, C. B., Harachi, T. W., Cortes, R. C., Abbott, R. D., & Catalano, R. F. (2004). Level and change in reading scores and attention problems during elementary school as predictors of problem behavior in middle school. Journal of Emotional and Behavioral Disorders, 12, 130–144.

Freeman, R., Smith, C., Zarcone, J., Kimbrough, P., Tieghi-Benet, M., Wickham, D., et al. (2005). Building a statewide plan for embedding positive behavior support in human service organizations. Journal of Positive Behavior Interventions, 7, 109–119.

Good, R. H., & Kaminski, R. A. (Eds.). (2002). Dynamic Indicators of Basic Early Literacy Skills (6th ed.). Eugene, OR: Institute for the Development of Education Achievement.

Hawken, L. S., Vincent, C. G., & Schumann, J. (2008). Response to intervention for social behavior. Journal of Emotional and Behavioral Disorders, 16, 213–225.

Herman, K. C., Lambert, S. F., Reinke, W. M., & Ialongo, N. S. (2008). Low academic competence in first grade as a risk factor for depressive cognitions and symptoms in middle school. Journal of Counseling Psychology, 55, 400–410.

Horner, R. H., Sugai, G., Todd, A. W., & Lewis-Palmer, T. (2005). School-wide positive behavior support. In L. Bambara & L. Kern (Eds.), Individualized supports for students with problem behaviors: Designing positive behavior plans (pp. 359–390). New York: Guilford Press.

Ialongo, N., Poduska, J., Werthamer, L., & Kellam, S. (2001). The distal impact of two first-grade preventive interventions on conduct problems and disorder in early adolescence. Journal of Emotional and Behavioral Disorders, 9, 146.

Kotter, J. (1995). Leading change: Why transformation efforts fail. Harvard Business Review, 73, 59–67.

Kratochwill, T. R., & Shernoff, E. S. (2004). Evidence-based practice: Promoting evidence-based interventions in school psychology. School Psychology Review, 33, 34–48.

Lane, K. L., & Menzies, H. M. (2003). A school-wide intervention with primary and secondary levels of support for elementary students: Outcomes and considerations. Education and Treatment of Children, 26, 431–451.

Lassen, S. R., Steele, M. M., & Sailor, W. (2006). The relationship of school-wide positive behavior support to academic achievement in an urban middle school. Psychology in the Schools, 43, 701–712.

Lee, Y., Sugai, G., & Horner, R. H. (1999). Using an instructional intervention to reduce problem and off-task behaviors. Journal of Positive Behavior Interventions, 1, 195–204.

McIntosh, K., Chard, D. J., Boland, J. B., & Horner, R. H. (2006). Demonstration of combined efforts in school-wide academic and behavioral systems and incidence of reading and behavior challenges in early elementary grades. Journal of Positive Behavior Interventions, 8, 146–154.

McIntosh, K., Flannery, K. B., Sugai, G., Braun, D., & Cochrane, K. L. (2008). Relationships between academics and problem behavior in the transition from middle school to high school. Journal of Positive Behavior Interventions, 10, 243–255.

Mclntosh, K., Horner, R. H., Chard, D. J., Boland, J. B., & Good, R. H., III. (2006). The use of reading and behavior screening measures to predict nonresponse to school-wide positive behavior support: A longitudinal analysis. School Psychology Review, 35, 275–291.

McIntosh, K., Horner, R. H., Chard, D. J., Dickey, C. R., & Braun, D. H. (2008). Reading skills and function of problem behavior in typical school settings. Journal of Special Education, 42, 131–147.

McIntosh, K., Horner, R. H., & Sugai, G. (2009). Sustainability of systems-level evidence-based practices in schools: Current knowledge and future directions. In W. Sailor, G. Sugai, R. H. Horner, & G. Dunlap (Eds.), Handbook of positive behavior support (pp. 327–352). New York: Springer.

McIntosh, K., Reinke, W. M., & Herman, K. E. (in press). School-wide analysis of data for social behavior problems: Assessing outcomes, selecting targets for intervention, and identifying need for support. In G. G. Peacock, R. A. Ervin, E. J. Daly, & K. W. Merrell (Eds.), The practical handbook of school psychology. New York: Guilford.

McIntosh, K., Sadler, C., & Brown, J. A. (2009). Kindergarten reading skill and response to instruction as risk factors for problem behavior. Manuscript submitted for publication.

McKinney, J. D. (1989). Longitudinal research on the behavioral characteristics of children with learning disabilities. Journal of Learning Disabilities, 22, 141–150.

McLaughlin, M. W., & Mitra, D. (2001). Theory-based change and change-based theory: Going deeper, going broader. Journal of Educational Change, 2, 301–323.

Morrison, G. M., Anthony, S., Storino, M., & Dillon, C. (2001). An examination of the disciplinary histories and the individual and educational characteristics of students who participate in an in-school suspension program. Education and Treatment of Children, 24, 276–293.

Nelson, J. R., Benner, G. J., Lane, K. L., & Smith, B. W. (2004). Academic achievement of K-12 students with emotional and behavioral disorders. Exceptional Children, 71, 59–73.

Preciado, J. A., Horner, R. H., & Baker, S. K. (2009). Using a function-based approach to decrease problem behaviors and increase academic engagement for Latino English Language Learners. The Journal of Special Education, 42, 227–240.

Sanford, A. (2006). The effects of function-based literacy instruction on problem behavior and reading growth. Unpublished doctoral dissertation, University of Oregon.

Scott, T. M., & Barrett, S. B. (2004). Using staff and student time engaged in disciplinary procedures to evaluate the impact of school-wide PBS. Journal of Positive Behavior Interventions, 6, 21–27.

Simmons, D. C., Kame'enui, E. J., Good, R. H., III, Harn, B. A., Cole, C., & Braun, D. (2002). Building, implementing, and sustaining a beginning reading model: Lessons learned school by school. In M. R. Shinn, H. M. Walker, & G. Stoner (Eds.), Interventions for academic and behavioral problems II: Preventive and remedial approaches (pp. 537-569). Bethesda, MD: National Association of School Psychologists.

Stewart, R. M., Benner, G. J., Martella, R. C., & Marchand-Martella, N. E. (2007). Three-tier models of reading and behavior: A research review. Journal of Positive Interventions, 9, 239–252.

Stollar, S. A., Poth, R. L., Curtis, M. J., & Cohen, R. M. (2006). Collaborative strategic planning as illustration of the principles of systems change. School Psychology Review, 35, 181–197.

Stollar, S. A., Schaeffer, K. R., Skelton, S. M., Stine, K. C., Lateer-Huhn, A., & Poth, R. L. (2008). Best practices in professional development: An integrated three-tier model of academic and behavior supports. In A. Thomas & J. P. Grimes (Eds.), Best practices in school psychology V (pp. 875–886). Bethesda, MD: National Association of School Psychologists.

Sugai, G. (2009a). Reaching all students: RtI & SWPBS. Retrieved August 6, 2009.

Sugai, G. (2009b). School-wide positive behavior support and response to intervention. Retrieved January 31, 2009.

Sugai, G., & Horner, R. H. (2002). The evolution of discipline practices: School-wide positive behavior supports. Child and Family Behavior Therapy, 24, 23–50.

Tilly, W. D. (2008). The evolution of school psychology to science-based practice: Problem-solving and the three-tiered model. In A. Thomas & J. P. Grimes (Eds.), Best practices in school psychology V (pp. 17–36). Bethesda, MD: National Association of School Psychologists.

Vaughn, S., & Fuchs, L. S. (2003). Redefining learning disabilities as inadequate response to instruction: The promise and potential problems. Learning Disabilities Research & Practice, 18, 137–146.

Vaughn, S., Klingner, J., & Hughes, M. (2000). Sustainability of research-based practices. Exceptional Children, 66, 163–171.

Walker, H., & Shinn, M. (2002). Structuring school-based interventions to achieve integrated primary, secondary, and tertiary prevention goals for safe and effective schools. In M. R. Shinn, H. M. Walker, & G. Stoner (Eds.), Interventions for academic and behavior problems II: Preventative and remedial approaches. (pp. 1–21). Bethesda, MD: National Association of School Psychologists.

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