Tier 1 Support Descriptive Essay

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Considering Tier 3 Within a Response-to-Intervention Model

by Ruth A. Ervin, Ph.D., University of British Columbia, Vancouver, BC, Canada

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Schools can be viewed as intervention systems focused on promoting outcomes (e.g., literacy, social-emotional competence, etc.) deemed important to society (Deno, 2002). This is a complex task considering the nature of learning and development and the growing diversity of problems and issues facing school-aged youth. Research on child development informs us that children learn and develop skills at different rates. Specifically, children enter the learning environment with different skill sets, and an individual child’s Response to Intervention (RTI) is unique and dependent on biology, social learning history, and context. To reach desired outcomes in school, some students may require additional or unique instructional strategies or interventions beyond those typically available. Thus, for schools to meet the needs of all students it is important to establish a comprehensive continuum of multi-layered or multi-tiered systems of prevention/intervention services. This continuum should include intervention options of varying intensity that can be linked to the specific learning needs of students who are experiencing difficulties. To ensure that prevention and intervention strategies are provided in a timely manner and to students who need them, schools should establish a clear process for a) determining which students are experiencing difficulties, b) selecting intervention strategies or supports and matching these supports to students, and c) evaluating whether the intervention strategies are helpful to students.

One common multi-layered arrangement involves three tiers of prevention or intervention supports to students. At Tier 1 (i.e., primary prevention/intervention), universal (i.e., school-wide) prevention efforts are established to promote learning for all students, anticipating that most students (e.g., 80%) will respond to these strategies and will not require additional intervention. For example, a school considering Tier 1 activities might adopt a research-based reading curriculum and screen all students for reading problems three times per year to determine which students might need supports beyond the school-wide reading curriculum. At Tier 2 (secondary prevention or strategic intervention), students who are identified as being at-risk of experiencing problems receive supplemental or small-group interventions. For example, when school-wide screening reveals that some students (e.g., 15%) in Grade 3 are at risk of developing reading problems, the school might provide supplemental reading support through a classwide peer tutoring intervention. Similarly, when school-wide data indicate that higher rates of office discipline referrals are occurring on the playground, the school improvement team might look into interventions that promote appropriate playground play (e.g., Ervin, Schaughency, Matthews, Goodman, & McGlinchey, 2007). At Tier 3 (tertiary prevention), an additional layer of intensive supports is available to address the needs of a smaller percentage of students (e.g., 2%–7%) who are experiencing problems and are at risk of developing more severe problems. At Tier 3, the goal is remediation of existing problems and prevention of more severe problems or the development of secondary concerns as a result of persistent problems. For example, at Tier 3, a student whose reading performance falls significantly below that of his or her peers, despite intervention, might receive intensive reading support from the learning assistant four times per week with close monitoring of his or her progress.

The purpose of this article is to provide a general overview of special considerations pertaining to the provision of Tier 3 prevention and intervention efforts. Specifically, this article describes a self-questioning process to guide decision making at Tier 3. For each step of the process, readers are referred to additional references and resources.

Establishing a Process to Guide Decision Making at Tier 3

As noted earlier, within a multi-tier RTI approach it is important to establish a process for a) determining which students are experiencing difficulties, b) selecting intervention strategies or supports and matching these supports to students, and c) evaluating whether the intervention strategies are helpful. At each tier along the continuum, the process may vary in its intensity, yet it will always follow a consistent series of questions or steps. Practitioners can guide their decision making by adhering to a self-questioning process wherein they ask themselves the following questions:

  1. Who is experiencing a problem and what specifically is the problem?

  2. What intervention strategies can be used to solve the problem or reduce its severity?

  3. Did the problem (or problems) go away or decline in severity as a result of the intervention(s)?

This self-questioning process is familiar to most educators and is used formally or informally by many effective teachers as they proactively work to assess the progress of students in their classrooms. For example, teachers who are responsive to the individual needs of students in their classrooms regularly assess students’ skills and responsiveness to instructional strategies, providing additional supports and remediation at a whole-class, small-group, or individual level as necessary.

In school-wide, multi-tier approaches to RTI, a similar, but often more formalized, process is applied at a whole-school, classroom, and individual student level. Across tiers, the nature of services and support provided are differentiated on the basis of the intensity of the problems and the magnitude of need. At Tier 3, efforts focus on the needs of individual students who are experiencing significant problems in academic, social, and/or behavioral domains. Thus, the process at this level is more intensive and individualized than it is at other levels. In the sections that follow, considerations during each step of a Tier 3 self-questioning process are discussed.

Step 1: Who is experiencing a problem and what, specifically, is the problem?

The first step in the process is to define the problem, and embedded within this step is noting who is experiencing the problem and what level of support (i.e., Tier 1, Tier 2, or Tier 3) is warranted. When defining a problem, it is important to clearly describe what the problem “looks like” in objective, observable terms, so that all persons involved know they are talking about the same thing. Measurement of a problem should be direct and occur within the context (e.g., classroom setting or situation) in which the problem occurs. To quantify how much of a problem exists, the problem should be described in measurement terms (e.g., frequency, rate, duration, magnitude). Furthermore, to stay focused on working toward improving problem situations, it is helpful to describe problems as discrepancies between a student’s actual or current performance (i.e., “what is”) and desired or expected performance (i.e., “what should be”). Thus, in addition to measuring a student’s actual performance, criteria regarding expected levels of performance need to be established. By quantifying problems as discrepancies, educators can use this information to determine the magnitude or severity of a problem. This information can be useful in formalizing goals (i.e., a reduction in the discrepancy) and in prioritizing problems within and across students.

To illustrate this process, consider reading as an example. One measure of “reading health” shown to be predictive of later reading fluency and comprehension is the number of words a student reads correctly per minute, or oral reading fluency (Hosp & Fuchs, 2005). The Dynamic Indicators of Basic Early Literacy Skills (DIBELS; http://www.dibels.uoregon.edu) is a research-based, standardized, norm-referenced measure of pre-reading and reading skills that includes a measure of oral reading fluency for Grades 1 to 6 (Good, Gruba, & Kaminski, 2002). The DIBELS measures were designed for use as screening and evaluation tools, and scores on the DIBELS can be used to place students in categories of reading risk. Prespecified, research-based goal rates have been established for the DIBELS and are available on the Web site just mentioned. These goal rates might be used as “expected performance” standards against which to compare actual student performance in an RTI model. Specifically, students who read at or above recommended (i.e., benchmark) rates are considered to be at low risk of reading problems. In contrast, if students perform below benchmark rates, they are considered to be either at “some risk” of developing reading problems or “at risk” of developing reading problems.

The DIBELS benchmark criteria suggest, for example, that a 3rd grade student is expected to read 77 or more words correctly per minute in the beginning (fall term) of 3rd grade, 92 or more words in the middle (winter term), and 110 or more at the end (spring term). Thus, a student who reads fewer words correctly per minute than the specified benchmark amount (i.e., 77 words in the fall of Grade 3) might be viewed as experiencing a reading problem and, depending on their scores, might be viewed as in need of strategic (Tier 2) or intensive (Tier 3) reading intervention supports. To illustrate this more clearly, consider hypothetical data taken in the fall from all 3rd grade students at one elementary school. Imagine that all of the students in Grade 3 were screened for reading difficulties using the DIBELS. As with any screening device, the DIBELS is designed to be sensitive enough to identify students who may be at risk of experiencing reading problems. Thus, to determine who might be at risk of experiencing reading difficulties, the team of 3rd grade teachers would look to see which students scored below the expected goal rate of 77 words read correctly per minute. For example, let’s assume that Ben read at a rate of 67 words correctly per minute, which means he read 10 fewer words correctly per minute than the desired rate (i.e., 77 – 67 = 10). Ella, who read 30 words correctly per minute, read 47 fewer words correctly per minute than the desired rate (i.e., 77 – 30 = 47). Both children are reading at rates less than the desired rate of 77 and may be in need of additional reading supports, but the quantified problem (i.e., discrepancy between actual and expected performance) is greater for Ella. Of course, this is not to suggest that a student should be placed in a category of Tier 2 or Tier 3 support on the basis of a single score. Instead, screening devices, like the DIBELS, which can be administered repeatedly and are time-efficient measures, are useful because they can help identify students who may be in need of additional intervention supports or further assessment to determine need for support. See Jenkins and Johnson article in section of this Web site on Universal Screening for more information. [NCLD add Link to article]

One important question that schools need to consider is whether a student should receive Tier 1, 2, or 3 services. Tier 3 services are designed to address the needs of students who are experiencing significant problems and/or are unresponsive to Tier 1 and Tier 2 efforts. Schools should establish guidelines for determining how students will enter into Tier 1, 2, or 3 levels of support. Although guidelines may vary from school to school, students in need of Tier 3 services should be able to access these services in one of two ways. First, students receiving Tier 1 or Tier 2 supports who are not making adequate progress and are unresponsive to the continuum of supports available at Tier 1 or Tier 2 might be moved into Tier 3 to receive more intensive intervention supports. Second, there should be a mechanism through which students who are experiencing very severe or significant academic, behavioral, or social-emotional problems can be triaged directly into Tier 3 to receive necessary intensive and individualized intervention supports. For some students, the second option is necessary to provide needed supports in a timely fashion rather than delaying access to these supports by making students wait to go through Tier 1 and Tier 2 intervention services. Thus, in contrast to a fixed multi-gating system wherein students would only be able to receive more intensive services (i.e., Tier 3) following some time period of less intensive (i.e., Tier 1 or 2) services, the RTI approach should allow some flexibility to serve students based on their level of need in a timely and efficient manner.

As educators establish a process for determining which students at their school should receive Tier 1, 2, or 3 services, they face challenges associated with selecting criteria for tiers (for discussion, see Kovaleski, 2007). Research-based criteria of risk, like those provided by the DIBELS, are also available when looking at office discipline referrals for behavioral issues (see School Wide Information System [SWIS; http://www.swis.org]), and these criteria can be useful to schools in determining whether students should receive Tier 1, 2, or 3 services (for an example, see Ervin, Schaughency, Goodman, McGlinchey, & Matthews, 2006). Unfortunately, research-based risk criteria are not always available for other important targets, meaning that educators need to consider how they will decide to match tiered services to student needs. When research-based risk criteria for expected levels of performance are unavailable, educators must select standards for comparison (e.g., professional experience, teacher expectations, parental expectations, developmental norms, medical standards, curriculum standards, national norms, local norms, and classroom peer performance), and this is not an easy task (see Kovaleski, 2007). Furthermore, even when research-based risk criteria are available, schools serving high numbers of students at risk for reading and/or behavioral problems may not have sufficient resources to provide Tier 3 interventions to all students who fall into risk categories. In one high needs school in Michigan, for example, school-wide screening data revealed that less than 40% of the students at the school met benchmark reading goal rates according to the DIBELS, meaning 60% of the student population was at risk for developing reading problems (Ervin et al., 2006). Given such high numbers of students in need of support, coupled with limited school resources and time available to provide intensive intervention, the school-based team at this school decided to implement an early reading intervention program in kindergarten and 1st grade rather than attempt to design individualized reading plans for each student at risk for developing reading problems (see Ervin et al., 2006; Ervin, Schaughency, Goodman, McGlinchey, & Matthews, 2007). Students who continued to experience reading difficulties despite the classwide interventions were referred to grade-level teams and considered for Tier 3 intervention supports. This example illustrates that as educators develop a process for determining which students should receive Tier 3 intervention services, they need to consider how they will best use the available time and resources to provide a continuum of interventions to support the diverse learning needs of students.

Step 2: What intervention strategies can be used to reduce the magnitude or severity of the problem?

When a student has been identified as being in need of Tier 3 intervention supports, the next step in the self-questioning process is the selection and implementation of appropriate intervention supports. One option in this step is to move directly into intervention by selecting an evidence-based intervention strategy that has a standard protocol for implementation. There are many intervention strategies from which to choose. For example, several Web sites provide teacher-friendly intervention resources (e.g., http://www.interventioncentral.com; http://www.free-reading.net; http://ies.ed.gov/ncee/wwc/).

A second option at this stage is to collect more information before moving to intervention. To assist in the development and selection of an intervention for a specific problem, it may be important to conduct an analysis of the problem’s context and function. To do so, we must ask what factors are contributing to the problem and in what ways can we alter those factors to promote learning and reduce the magnitude or severity of the problem. One end goal of this stage in the process is to “diagnose the conditions under which students’ learning is enabled” (Tilly, 2002, p. 29). This goal is accomplished by gathering information (e.g., direct observation, interviews, rating scales, curriculum-based measures of academic skills, review of records) from a number of sources (e.g., the student, teacher, parent, peers, administrator) to answer questions helpful in furthering our understanding of why (i.e., under what conditions) the problem is occurring. Specifically, we want to know where, when, with whom, and during what activities the problem is likely or unlikely to occur.

Although many questions can be asked at this stage, it is important to stay focused on identifying the factors that we can change (i.e., instructional strategies, curriculum materials) in attempting to mitigate the problem situation. For example, when a child’s classroom performance is below our expectations, we might ask whether the problem is a skill (i.e., can’t do) or a performance (i.e., won’t do) problem (for more information on this process, see Daly Chafouleas, & Skinner, 2005; Daly, Martens, Witt, & Dool, 1997; Witt, Daly, & Noell, 2000). Another important, and related, question to ask concerning learning problems is whether the alignment between the student’s skill level, the curriculum materials, and instructional strategies is appropriate (Howell & Nolet, 2000). When the problem involves performance that falls below what is expected, it is important to ask the following types of questions about whether this is because the student a) does not want to perform the task or activity, b) would rather be doing something else, c) gets something (e.g., attention, access to a preferred activity) by not doing the task, d) does not have the prerequisite skills to perform the task, e) is given work that is too difficult or presented in a manner that the student hasn’t seen before, or f) has been given insufficient time to practice the skill to fluency.

In answering the above questions, there is a direct link between our questioning and the development of a solution. For example, if the information we collect suggests that the student has the prerequisite skills needed to decode connected text but does so slowly, one hypothesis we might have is that perhaps the student has not had sufficient time to practice reading to develop fluency. An appropriate intervention for this student might focus on building reading fluency through an intervention that involves increased reading practice, such as repeated reading (see Daly et al., 2005, for a description of repeated reading). Alternatively, if we suspect that a student’s reading problem is related to not having enough assistance to acquire the skill and/or a deficit in pre-reading skills (e.g., problems with phonemic awareness), our hypothesized intervention strategy would might focus on direct skill development of prerequisite skills, with prompting and corrective feedback. In each example, the reading problem was related to a skill issue, and the solutions were linked to the type of skill problem (e.g., acquisition, fluency).

If the information we gather suggests that the reading problem is not a skill problem, but rather a performance (i.e., won’t do) issue, then the intervention should focus on addressing the function (e.g., escape task) of the behavior. Much has been written about linking assessment to intervention through functional behavioral assessment, and when problems are performance issues, interventions can address behavior function in several ways. When a student’s behavior is maintained by escape from a task, for example, the intervention might reduce the student’s motivation to escape the task by making the task less aversive (e.g., adjusting the choice of materials to increase interest), teach the student a more appropriate way to communicate that the task is aversive (requesting a brief break), or allowing escape from the task following performance of the task for a prespecified time period.

Regardless of whether educators decide to move directly to intervention or to collect more information to analyze the problem, the focus of this step in the self-questioning process is on selecting a solution (intervention strategy) that reduces the magnitude or severity of the problem (i.e., reduces the discrepancy between the student’s current and expected performance). Interventions should be selected on the basis of their functional relevance to the problem (i.e., match to why the problem is occurring), contextual fit (i.e., match to the setting and situation in which the problem occurs), and likelihood of success (i.e., demonstrated success within the research literature). Tier 3 interventions are designed to address significant problems for which students are in need of intensive interventions. As a result, Tier 3 interventions require careful planning. Specifically, an intervention plan should describe the following:

  1. What the intervention will look like (i.e., its steps or procedures)

  2. What materials and/or resources are needed and whether these are available within existing resources

  3. Roles and responsibilities with respect to intervention implementation (i.e., who will be responsible for running the intervention, preparing materials, etc.)

  4. The intervention schedule (i.e., how often, for how long, and at what times in the day?) and context (i.e., where, and with whom?)

  5. How the intervention and its outcomes will be monitored (i.e., what measures, by whom, and on what schedule?) and analyzed (i.e., compared to what criterion?).

In addition, an intervention plan should specify timelines for implementing objectives and for achieving desired goals. The end goal of this stage of the process is a clearly delineated intervention plan. (For examples of evidence-based intervention strategies, see the What Works Clearinghouse at http://www.whatworks.ed.gov, a resource developed by the Institute of Education Sciences, U.S. Department of Education.)

Step 3: Did the student’s problem get resolved as a result of the intervention?

An individual’s RTI can only be known following actual implementation of an intervention and careful (i.e., reliable and valid), repeated measurement of his or her behavior over time. Although a thorough description and analysis of the problem, why it is occurring, and what interventions are likely to be effective is important to the self-questioning process at Tier 3, the process is incomplete until practitioners ask if the student’s problem was resolved as a result of the intervention. The best way to determine whether a student is making progress toward the desired goals in RTI is to collect ongoing information regarding the integrity with which the intervention was implemented and, relative to intervention implementation, the discrepancy between desired and actual performance. The intervention process does not end until the problem (i.e., discrepancy between what is and what should be) is resolved. Thus, continuous monitoring and evaluation are essential parts of an effective RTI process. Specifically, information should be collected on targeted student outcomes (i.e., measurement of change in behavior relative to desired goals), proper implementation of the intervention (i.e., measure whether the intervention is implemented as planned), and social validity (practicality and acceptability of the intervention and outcome). When data are reviewed and analyzed, a decision should be made regarding whether the intervention plan should be revised or goals adjusted. Single-subject design methods are key to determining a student’s RTI (for further information, see Olson, Daly, Andersen, Turner, & LeClair, 2007).

REFERENCES

Daly, E. J., Chafouleas, S. M., & Skinner, C. H. (2005). Interventions for reading problems: Designing and evaluating effective strategies. New York: Guildford Press.

Daly, E. J., Witt, J. C., Martens, B. K., & Dool, E. J. (1997). A model for conducting a functional analysis of academic performance problems. School Psychology Review, 26, 554–574.

Deno, S. L. (2002). Problem-solving as “best practice.” In A Thomas and J. Grimes (Eds.) Best practices in school psychology IV, Volume 1 (pp. 37-55). Bethesda, MD: National Association of School Psychologists.

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

Ervin, R. A., Schaughency, E., Goodman, S. D., McGlinchey, M. T., & Matthews, A. (2007). Moving from a model demonstration project to a statewide initiative in Michigan: Lessons learned from merging research-practice agendas to address reading and behavior. In S. R. Jimerson, M. K. Burns, & A. M. VanDerHeyden (Eds.), The handbook of response to intervention: The science and practice of assessment and intervention (pp. 354–377). New York: Springer.

Ervin, R. A., Schaughency, E., Matthews, A., Goodman, S. D., & McGlinchey, M. T. (2007). Primary and secondary prevention of behavior difficulties: Developing a data-informed problem-solving model to guide decision making at a schoolwide level. Psychology in the Schools, 44, 7–18.

Good, R. H. III, Gruba, J., & Kaminski, R. A. (2002). Best practices in using Dynamic Indicators of Basic Early Literacy Skills (DIBELS) in an outcomes-driven model. In A Thomas and J. Grimes (Eds.) Best practices in school psychology IV, Volume 1 (pp. 699- 720). Bethesda, MD: National Association of School Psychologists.

Hosp, M. K., & Fuchs, L. S. (2005). Using CBM as an indicator of decoding, word reading, and comprehension: Do the relations change with grade? School Psychology Review, 34(1), 9-26.

Howell, K. W., & Nolet, V. (2000). Curriculum-based evaluation: Teaching and decision making (3rd ed.). Belmont, CA: Wadsworth.

Kovaleski, J. F. (2007). Potential pitfalls of response to intervention. In S. R. Jimerson, M. K. Burns, & A. M. VanDerHeyden (Eds.), The handbook of response to intervention: The science and practice of assessment and intervention (pp. 80–92). New York: Springer.

Olson, S. C., Daly, E. J., Andersen, M., Turner, A., & LeClair, C. (2007). Assessing student response to intervention. In S. R. Jimerson, M. K. Burns, & A. M. VanDerHeyden (Eds.), The handbook of response to intervention: The science and practice of assessment and intervention (pp. 117–129). New York: Springer.

Tilly, D. (2002). Best practices in school psychology as a problem-solving enterprise. In A Thomas & J. Grimes (Eds.), Best practices in school psychology IV (Vol. 1, pp. 21–36). Bethesda, MD: National Association of School Psychologists.

Witt, J. C., Daly, E. M., & Noell, G. (2000). Functional assessments: A step by step guide to solving academic and behavior problems. Longmont, CO: Sopris West.


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From 60 to 600:The Perfect Storm (APBS 08)

The presentation describes the features and procedures for moving evidence-based educational practices from demonstrations to large-scale adoptions. This includes state and district examples, lessons learned, and future steps.

Overview of a Function-Based Approach to Behavior Support within Schools

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Commentary: Establishing efficient and durable systems of school-based support

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Issues of personal dignity and social validity in school-wide systems of positive behavior support

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Coaching positive behavior support in school settings: Tactics and data-based decision-making

Systems of positive behavior support (PBS) that positively affect student performance involve consensus among stakeholders, the development of environments that facilitate student success, effective teaching of rules and procedures, and consistent consequences for behavior. Evaluation of such systems requires schools to collect data to assess performance and to use that information to make data-based decisions. However, surveys indicate that data collection and data-based decision making are among the most difficult components of PBS for school personnel to tackle. This article examines in-person coaching strategies and data use. Individual school results are analyzed in relation to the school's School-wide Evaluation Tool (SET) scores. A discussion of how coaches may more efficiently assess schools' readiness for coaching styles and content includes suggestions for how coaches might use a range of available assessment tools.

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Teacher outcomes of School-wide Positive Behavior Support

Thousands of Schools throughout the country are now implementing school-wide positive behavior support (SWPBS) as a way to improve school culture, safety, and climate. Research is needed to assess the effects of implementing SWPBS on (a) teacher stress and (b) and teacher efficacy. The present pilot study provides a preliminary study of these variables by analyzing self-report measures conducted by 20 teachers within schools of differing levels of SWPBS implementation. Results indicated a statistically significant relationship between SWPBS implementation and teacher perception of educational efficacy. Results did not indicate a significant relationship, but rather a trend in the anticipated direction between SWPBS implementation and reduced perception of teacher stress. Limitations of the study are discussed and directions for future research are recommended.

Longitudinal evaluation of behavior support intervention in a public middle school

Reports on a longitudinal evaluation of behavior support intervention in a public middle school. Study design and methods; Number of detentions recorded for the three behavior categories; Decreasing trend in the number of detentions each year for vandalism and substance use; Percentage of student attendance and earning a lottery drawing per term.

The Use of Reading and Behavior Screening Measures to Predict Nonresponse to School-Wide Positive Behavior Support: A Longitudinal Analysis

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Focus, Scope, and Practice of Behavioral Consultation to Public Schools

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We present a "practitioner's guide" to social skills assessment and intervention with students attending public schools. Important characteristics of assessment instruments are discussed, including psychometric properties and strategies applicable to school settings. We then review several social skills assessment protocols and rating scales that can be used efficiently by school psychologists, teachers, and other related professionals. The process of assessment-derived intervention planning is covered, with a description of social skills curricula/training programs and presentation of an illustrative case study. We conclude with a summary of salient issues and recommendations to facilitate the routine assessment and teaching of social skills by school practitioners.

Using office discipline referral data for decision-making about student behavior in elementary and middle schools: An empirical investigation of validity

In this evaluation we used Messick's construct validity as a conceptual framework for an empirical study assessing the validity of use, utility, and impact of office discipline referral (ODR) measures for data-based decision making about student behavior in schools. The Messick approach provided a rubric for testing the fit of our theory of use of ODR measures with empirical data on reported and actual use. It also facilitated our demonstration of Messick's principle that validation is both a developmental and an ongoing collaborative process among developers of educational and psychological measures, researchers interested in theories underlying such measures, and educators who use these measures in professional practice. We used a single-group, nonexperimental evaluation design to survey users of ODR measures from the standardized School Wide Information System in 22 elementary and 10 middle schools; respondents included school staff involved exclusively with data entry and staff actively involved in data-based decision making. Results were highly consistent across 2 independent data sources—electronic database records of actual access of summaries of ODR measures and self-report survey responses regarding frequencies and types of uses of ODR measures for decision making. Results indicated that ODR measures are regularly used for a variety of types of data-based decision making and are regarded as both efficient and effective for those purposes. We discuss implications of our SWIS ODR validity evaluation results within the context of the Messick framework.

Practical Considerations in Creating School-Wide Positive Behavior Support in Public Schools

School-wide positive behavior support (SWPBS) has been identified as an effective and efficient method to teach students prosocial skills. It requires both effective behavior support practices and systems that will support these changes, including data-based decision making among the school leadership team. There are many practical and systemic factors that school personnel should examine before they consider themselves ready for systemic school-wide changes, including those associated with the (a) leadership team, (b) staff, (c) administration, (d) coach/facilitator, and (e) district. Practical considerations in each of these areas will be identified and discussed so that practitioners can anticipate their needs as they create effective SWPBS, particularly in low performing urban schools.

Building district-level capacity for positive behavior support

As more and more schools adopt school-wide positive behavior support (SWPBS) as a model for school improvement and the success of initial demonstration sites becomes evident, districts are faced with expansion and sustainability issues. Careful planning of these implementation efforts requires district personnel to be familiar with the resources and supports needed to implement and sustain such district-wide systems change efforts and build an infrastructure to support SWPBS initiatives. The purpose of this article is to expand upon School-wide Positive Behavior Support: Implementers' Blueprint and Self-Assessment (Sugai et al., 2005) by describing the how-to of the SWPBS implementation process with specific activities and providing user-friendly tools that can assist a district in "going to scale." Obstacles to and future considerations for expanding the practice of SWPBS are also presented.

Promoting implementation success through the use of continuous systems-level assessment strategies

Successful implementation of school-wide positive behavior support requires a continuous evaluation of program data. It also requires an ongoing review of how those data relate to organizational strengths, needs, professional development concerns, and the larger community. Accomplishing these tasks can be a formidable undertaking, particularly when school staff members have limited training in data-based decision making. This article will describe how a continuous systems-level assessment process is being implemented in one urban middle school to address behavioral and academic objectives.

Response to Intervention: Examining Classroom Behavior Support in Second Grade

This article reports on 2 studies investigating a response-to-intervention (RTI) approach to behavior support in 2 second-grade classrooms. The results suggest that a slightly more intensive but efficient targeted intervention ("check in and check out") was effective in supporting the social behavior success of 4 students whose problem behaviors were unresponsive to general classroom management practices. For 4 other students whose problem behaviors continued to be unresponsive to the "check-in and check-out" intervention, more individualized and function-based interventions were indicated and proved to be effective. The results from this research suggest that RTI logic can be applied to the social behavior support of students who present interfering problem behaviors in the classroom. Implications and recommendations for research and practice are discussed.

Prevention and Intervention with Young Children's Challenging Behavior: Perspectives Regarding Current Knowledge

Challenging behavior exhibited by young children is becoming recognized as a serious impediment to social-emotional development and a harbinger of severe maladjustment in school and adult life. Consequently, professionals and advocates from many disciplines have been seeking to define, elaborate, and improve on existing knowledge related to the prevention and resolution of young children's challenging behaviors. Of particular concern for the field of behavioral disorders is the lack of correspondence between what is known about effective practices and what practices young children with challenging behavior typically receive. To increase the likelihood that children receive the best of evidence-based practices, the current analysis was conducted to provide a concise synthesis and summary of the principal evidence pertaining to the presence and impact, prevention, and intervention of challenging behaviors in young children. A consensus building process involving review and synthesis was used to produce brief summary statements encapsulating core conclusions from the existing evidence. This article presents these statements along with descriptions of the strength of the supporting evidence. The discussion addresses directions and priorities for practice and future research.

Importance of Student Social Behavior in the Mission Statements, Personnel Preparation Standards, and Innovation Efforts of State Departments of Education

We examined the extent to which state departments of education are including (a) goals for student social behavior in their mission statements; (b) criteria for individual student, classroom, and schoolwide behavior support in certification standards for general education teachers, special education teachers, and principals; and (c) state initiatives focused on improving student social behavior. Web-based information from state departments of education from all 50 states and from the District of Columbia were reviewed in the fall of 2004. Results indicated that only 16 states (31%) include a focus on student social behavior in their mission statements. Individual student behavior support practices were identified in the curriculum for general educators in 30 (59%) states and for special educators in 39 (76%) states. Classroom behavior support practices were required for general education teachers in 39 (76%) states and for special educators in 40 (78%) states. Schoolwide behavior support practices were most likely to be required for principal certification, and they were formally identified in 20 (39%) of the states surveyed. Character education was the most common state initiative cited for improving social behavior in schools.

A descriptive analysis of intervention research published in the Journal of Positive Behavior Interventions: 1999-2005

The Journal of Positive Behavior Interventions (JPBI) has been publishing reports of empirical intervention research since 1999, with a commitment to serve as a vehicle for dissemination of data and perspectives pertinent to positive behavior support (PBS). PBS is distinguished by an emphasis on certain features of interventions, such as ecological and social validity. The current analysis was undertaken as an effort to describe the characteristics of intervention research published in JPBI from 1999 through 2005 and to provide a comparison with other peer-reviewed journals that publish a large number of articles reporting intervention research with children and youth with disabilities. The data indicate that JPBI has been publishing research with comparatively high levels of ecological validity, social validity, and assessment-based interventions. The authors note other distinctive aspects of JPBI's publication record and discuss the data with respect to the current and future character of PBS research.

School-wide application of positive behavior support in an urban high school: A case study

The nuances of the application of schoolwide positive behavior supports (PBS) in an urban high school setting were investigated. Impact of implementation was measured using qualitative interviews and observations, including the School-wide Evaluation Tool (SET), Effective Behavior Support Survey, Student Climate Survey, and office disciplinary referrals. The results indicated that schoolwide PBS was implemented in an urban high school setting with some success. The overall level of implementation of PBS reached 80% as measured by the SET. Staff and teachers increased their level of perceived priority for implementing PBS in their school. A decrease in monthly discipline referrals to the office and the proportion of students who required secondary and tertiary supports was noted. These findings seem to indicate that PBS may be an important process for improving outcomes for teachers and students in urban high school settings.

Application of economic analysis to school-wide positive behavior support programs

The authors discuss how to use economic techniques to evaluate educational programs and show how to apply basic cost analysis to implementation of school-wide positive behavior support (SWPBS). A description of cost analysis concepts used for economic program evaluation is provided, emphasizing the suitability of these concepts for evaluating educational programs. The authors also describe the specific data and measurement and analytic procedures that cost analysis evaluation requires. The concepts are then applied in a case study showing a cost analysis of SWPBS. Implications are provided for extending the cost analysis case study into evaluation of cost-effectiveness and/or cost-benefit economic analyses of program success.

Assessment and Implementation of Positive Behavior Support in Preschools

There is increasing concern over the number of young children who exhibit challenging behaviors in early childhood settings. Comprehensive prevention models are needed to support teachers' management of challenging behaviors and to avert the development of such behaviors within at-risk populations. One approach utilizes a three-tier prevention model called positive behavior support (PBS). The present research first assessed one region's implementation of PBS in 15 early childhood settings and found that on average, few features of PBS (30.79%) were implemented. Next, the impact of PBS consultation on teachers' use of universal PBS practices and children's behavior was evaluated in a multiple baseline design across four classrooms. A functional relationship was established between PBS consultation and teachers' implementation of universal PBS practices, but overall low levels of problem behavior prevented assessment of the impact of these changes on child problem behavior. Implications for future applications of PBS to early childhood settings are discussed.

Effects of Behavior Support Team Composition on the Technical Adequacy and Contextual Fit of Behavior Support Plans

Benazzi, L., Horner R. H., & Good, R. H. (2006). Effects of behavior support team composition on the technical adequacy and contextual fit of behavior support plans. The Journal of Special Education, 40(3), 160-170

This study examined how the composition of a behavior support team affected use of assessment information in the design of behavior support plans. Specifically, we examined if typical teams designed behavior support plans that differed in (a) technical adequacy and/or (b) contextual fit when (1) teams did not include behavior specialists, (2) teams included behavior specialists, or (3) behavior specialists worked alone. Fifty-eight school personnel on 12 behavior support teams from typical elementary schools and 6 behavior specialists participated in the study. Vignettes describing hypothetical students with functional behavior assessment outcome information were used to develop 36 behavior support plans (12 by teams alone, 12 by specialists alone, and 12 by teams with specialists). Results were assessed by 3 expert behavior analysts for technical adequacy and by all 64 team members for contextual fit. Technical adequacy tended to be rated high if specialists alone or teams including a specialist designed the plan. Contextual fit tended to be rated high when teams alone or teams including a specialist designed the plan. Team members ranked plans developed by the team alone and plans developed by the team with a specialist as preferred for implementation over plans developed by a specialist alone. Implications for the selection of behavior support team membership are discussed.

Urban applications of school-wide positive behavior support: Critical issues and lessons learned

Researchers and educators have recognized that typical school-wide approaches to discipline and the prevention and management of problem behavior are often insufficient to address the needs of many students in inner-city schools with high base rates of problem behavior. This article outlines critical issues and lessons learned in the planning and implementation of effective and self-sustaining Positive Behavior Support (PBS) efforts in inner-city schools. Among these issues are methods for the facilitation of school-university partnerships, the incorporation of PBS into existing comprehensive school improvement efforts, the maintenance of school-wide PBS efforts, and the formalization of exit strategies and arrangements for subsequent technical assistance. The importance of service integration, family support, youth development, and community development are emphasized in ensuring the effectiveness and sustainability of school-wide PBS efforts in inner-city settings.

IDEA, Positive Behavioral Supports, and School Safety

A five-part article describes and analyzes the Individuals with Disabilities Education Act (IDEA) and a behavioral intervention technique called "positive behavioral interventions, supports, and strategies" (PBS). Suggests guidelines for applying PBS within the framework of IDEA, especially as it applies to discipline of students covered by the Act.

A not so good job with “Good Job”: A response to Kohn 2001

Comments on the article "Five Reasons to Stop Saying, 'Good Job'," by Kohn (2001). Involvement of the field of early intervention in the debate between proponents of behavioral teaching strategies and professionals against it; Argument that saying "good job" manipulates children in order to maximize adult convenience.

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