The RTI Data Analysis Teaming Process
Resources for this Article
For schools implementing Response-to-Intervention (RTI) approaches, team meetings are a vital part of creating curricular improvements, designing interventions, and deciding which students will benefit from additional tiered instruction.1 RTI teams should use a problem-solving process to analyze data from school-wide universal screening at the Tier 1 level to assist teachers in planning and implementing instructional strategies that will differentiate on the basis of students’ varying skill levels (Kovaleski & Pedersen, 2008). The same type of teaming process should also be used for designing instruction and placing students into higher tiers (i.e., Tier 2 and Tier 3). Data analysis teams (DATs) are convened after benchmark screenings to review universal data, select students for tiered interventions, and discuss instructional strategies.
The following guidelines for data analysis teaming are to be used in conjunction with the Data Analysis for Instructional Decision Making: Team Process script to facilitate effective RTI team meetings (Pennsylvania Training and Technical Assistance Network, 2008).2 The script, which is based on Kovaleski and Pedersen’s (2008) work on best practices in this area, is an outline of the recommended format for DAT meetings. It lists, in chronological order, the items that should be discussed, typical prompts that encourage discussion and decision making, and suggestions for record keeping at each step. Together, these guidelines and the script address in detail how to plan and conduct these meetings, including suggestions for team membership, the types of data to review, methods for analyzing student data, and how to plan interventions for students identified as needing additional support.
The script is organized into several sections. Part I is the script for the initial fall meeting, in which initial goals are set and the team plans for instruction. First, the script lists activities that should be planned and reviewed before the meetings. Then it outlines the procedures for reviewing benchmark data and planning for improved Tier 1 instruction for the entire grade level. Next, it lists procedures for considering students for Tier 2 using progress-monitoring data, followed by instructions for repeating the process for Tier 3. After Tier 3 procedures, it lists interim steps to be taken between meetings. Part II follows the same format, but for subsequent meetings (quarterly benchmark meetings). The general procedures and prompts are the same for the initial meeting and follow-up meetings, but some differences do necessitate a variant script.
Another document that should be used for DAT meetings is the Screening and Information Recording Form (SIRF; Kovaleski & Pedersen, 2008). Teams should use the SIRF or a similar document to record current student performance, goals, strategies discussed, strategies chosen, students considered for tiered services, and decisions made regarding student placement. The script lists in more detail everything that should be documented for purposes of record keeping, regardless of what document is used. It is useful for the facilitator to choose a “scribe” for the meeting to ensure that all appropriate information is recorded. An updated version of the SIRF is available here (PaTTAN, 2008).
Before the Meetings
RTI teams are often organized into grade-level DATs that include the principal, all teachers from that grade level, the individuals who provide the tiered interventions, the school psychologist, and the individual who manages benchmark and progress-monitoring data (data manager). For larger schools that have more than six teachers per grade level, more than one team per grade should be considered. The principal arranges for meeting logistics, such as scheduling, and often acts as facilitator of the meeting or appoints another team member for that role. At minimum, teams should meet shortly after each universal screening (typically three times per year). They may need to meet more frequently as needed to accommodate changes in student movement or interventions. Prior to meetings, the data should be compiled and sent to all team members ahead of time in a user-friendly format so that all team members can review the data to familiarize themselves with it before the meeting. Data shared with the team can include results of measures such as AIMSweb (Shinn & Garman, 2006), DIBELS (Good & Kaminski, 2005), or 4Sight (Slavin & Madden, 2006), using both raw data and visual displays (e.g., graphs and histograms) of individual and group data.
Tier 1 Analysis
First, the team should review whole-grade performance on the universal screening conducted for that grade level. The team should review what percentage of students is at each performance/risk level: benchmark (low risk), strategic (some risk), and intensive (high risk). Next, the team uses the percentages at each level to set measurable goals to achieve by the next review point. The goals should be stated in terms of the percentage of students making a particular amount of progress toward the identified benchmark.
After reviewing the students’ current performance and setting goals for the next universal screening, the team lists whole-class instructional strategies to consider implementing to improve student performance. Ideas should be recorded in a list that is easily viewed by everyone. The team analyzes and rates the listed strategies according to the extent to which they are evidence based, practical, and available or according to the feasibility of their creation. Finally, the team selects which strategies to implement during the next intervention period.
The team should then discuss the logistics of the strategies, such as how to locate or create necessary materials, teaching each other the strategy by using peer modeling and coaching, or identifying assistance from specialists such as the school psychologist or Title 1 staff. The team also makes plans for self-monitoring of the strategies. Then, a “to-do list” is created for strategy implementation.
Tier 2 Analysis
The team now identifies which students will be considered for Tier 2 interventions. Students meeting criteria for Tier 2 services are identified based on their risk level for academic difficulties as indicated by benchmark scores. More specifically, students whose performance is in the emerging or strategic range of the data sets are identified. All available data on these students are reviewed, such as universal screening scores and progress-monitoring data. In reviewing each student’s data, all areas of assessment should be considered to determine what kind of learning profile the student has and to ensure that the assessments validate each other. Based on all of this information, the team decides which students need Tier 2 interventions. For each of the identified students, the team sets a measurable goal in terms of specified benchmark scores for the next review point.
The team now focuses on tiered intervention strategies. Based on students’ needs in Tier 2, the team determines which strategies apply. Pennsylvania’s RTI teams use a standard protocol approach to interventions both at Tier 2 and Tier 3 (Fuchs, 2003), selecting from among strategies that are research based, highly scripted, and targeted to particular types of instructional problems. Methods for implementing the strategy are planned by identifying instructional groups and the frequency and duration of the interventions. In addition, a plan for self-monitoring needs to be determined. One good method to determine the fidelity of the interventions is to use an intervention checklist that outlines the correct implementation of the strategy. The team then makes plans for monitoring the progress of students in Tier 2 at least twice a month.
Tier 3 Analysis
Next, the team focuses on identifying students and planning interventions for Tier 3. Students chosen for Tier 3 are typically those performing the lowest on universal screenings (i.e., those whose performance places them in the greatest risk category). Students for Tier 3 are identified by the same process described for Tier 2. Because these students need the most intensive supports, however, planning for specific interventions according to need may be more involved than Tier 2 planning. For instance, a closer look at progress-monitoring data may be necessary to make decisions for students in Tier 3. Students who continue to display deficits in level and rate of improvement after Tier 3 supports may be referred to the special education evaluation process.
Between meetings, members of the DAT should all take responsibility for monitoring the fidelity of the selected instructional strategies and interventions, monitoring student progress, and fine-tuning the strategies based on classroom performance.
Initial and Follow-up Meetings
Part I of the script is for the initial fall meeting, and Part II is for subsequent follow-up meetings. Although many items are very similar, there are some important differences to be aware of before using the script at DAT meetings. The most important difference is that the initial meeting will focus mostly on planning, whereas the follow-up meetings involve much more evaluation and fine-tuning of strategies. In follow-up meetings, previous student data are available for comparing performance over time. Previous universal screening data are helpful in determining if there is overall improvement, especially in examining specific skills via item analysis or other methods. Also, there is an increased emphasis on evaluating past decisions at follow-up meetings. In addition to selecting new strategies, the team also discusses how well the strategies they planned at the previous meeting have been working for the students. The team can decide to continue with the existing strategies or to select new ones. Finally, follow-up meetings may include more detailed discussions about tier movement. As the year progresses, students will move between the tiers, in and out of various intervention groups.
Using a systematic team approach to RTI allows teachers and staff to all be involved in planning for every student’s academic performance. By sharing responsibility as a team, more educators are accountable for student progress and aware of the diversity of needs among students. The DAT model described by the script is very explicit and detailed for the purposes of keeping teams on task and focused on the data. Although the script may seem rigid, adherence to an established systematic model helps ensure implementation fidelity and, thus, improved outcomes for students.
Fuchs, L. S. (2003). Assessing intervention responsiveness: Conceptual and technical issues. Learning Disabilities Research & Practice, 18, 172–186.
Good, R. H., & Kaminski, R. A. (2005). Dynamic indicators of basic early literacy skills (6th ed.). Longmont, CO: Sopris West.
Kovaleski, J. F., & Marco, C. M.. (2005). Screening Information Recording Form (SIRF). Unpublished manuscript.
Kovaleski, J. F., & Pedersen, J. (2008). Best practices in data analysis teaming. In A. Thomas & J. Grimes (Eds.), Best practices in school psychology V (pp. 115–130). Bethesda, MD: National Association of School Psychologists.
National Association of State Directors of Special Education. (2005). Response to intervention: Policy considerations and implementation. Alexandria, VA: Author.
Pennsylvania Training and Technical Assistance Network (PaTTAN). (2008). Data analysis team script. Harrisburg: Pennsylvania Department of Education.
Shinn, M. R., & Garman, G. (2006). AIMSweb. Eden Prairie, MN: Edformation, Inc.
Slavin, M. R., & Madden, N. A. (2006). 4Sight benchmark assessments. Baltimore: Success for All Foundation.
- 1It should be noted that the following description is based on the three-tier model for RTI used in Pennsylvania. In this model, all three tiers of support occur as part of the general education program. Special education is considered after the student has been provided with three tiers of intervention. As compared with other three-tier models (cf.,National Association of State Directors of Special Education [NASDSE], 2005), Pennsylvania’s Tiers 1 and 2 roughly correspond to NASDSE’s Tier 1, with Pennsylvania’s Tier 3 corresponding to NASDSE’s Tier 2.
- 2Contributors to the data analysis script include Joseph F. Kovaleski, Jason Pedersen, Joy Eichelberger, Edward S. Shapiro, Rosemary Nilles, Christina Marco, Caitlin Flinn, Megan Roble, and Michelle Agne.
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