Analyzing Student Data RTI Model Student Scenario Paul

Analyzing Student Data Rti Modelstudent Scenariostudent Paulage 8gr

Analyze the provided student scenario involving Paul, an 8-year-old third-grader at Lincoln Elementary School, who has been receiving Tier 2 instruction for 10 weeks. His teacher has monitored his reading progress using the Vanderbilt University Passage Reading Fluency probe, with an 18-week goal of 55 words per minute (wpm) and an expected growth rate of 1 wpm per week. Currently, the school support team is convening to review Paul’s progress and decide which tier of instruction would best support his educational needs.

When applying the dual-discrepancy approach, team members disagree on the appropriate instructional tier for Paul. The team has obtained written permission to use data from Brown, J., Skow, K., & the IRIS Center (2009) as a reference for RTI data-based decision making.

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The response to intervention (RTI) model is a scientifically validated approach designed to identify and support students with learning needs through multiple tiers of instruction. The scenario involving Paul demonstrates a practical challenge faced by educators in utilizing RTI data to make instructional decisions, especially when there is a discrepancy between different interpretative approaches, such as the dual-discrepancy method.

To understand Paul’s situation, it is first necessary to clarify the components of the RTI framework. RTI emphasizes early detection, targeted interventions, and data-driven decision-making. In Paul’s case, he has been implementing Tier 2 interventions for 10 weeks, which is consistent with the RTI model’s emphasis on providing these supports for students who are not making adequate progress in the core curriculum but do not require intensive Tier 3 interventions.

His progress using the Vanderbilt passage reading fluency probe is tracked weekly, with an 18-week goal of 55 words per minute. His current rate of progress is 1 word per week, which implies that over 10 weeks, he has gained roughly 10 words, falling short of his target. Based on the data, the support team must analyze whether Paul’s progress warrants continuation of Tier 2 instruction or a move to more intensive tiered supports, such as Tier 3.

The dual-discrepancy approach, used by the team, involves assessing both a significant discrepancy between the student’s performance and normative expectations and between the student's rate of growth and expected growth. Disagreement among team members may stem from different interpretations of whether Paul’s current progress demonstrates sufficient responsiveness to Tier 2 instruction or indicates a need for more intensive intervention. Some team members might argue that his limited progress—only 10 words in 10 weeks—is indicative of inadequate growth, warranting additional or different Tier 3 interventions. Others might believe that maintaining Tier 2 support could still be effective if adjustments are made.

Applying the dual-discrepancy method involves examining not only current performance data but also the sufficient rate of growth. Given Paul's goal of 55 wpm over 18 weeks, he should be reading approximately 55 words per minute at the 18-week mark. At his current rate, he will reach only about 20 words per minute, which suggests a substantial discrepancy between his current performance and the goal. This discrepancy supports the notion that his current instruction might be insufficient or that other factors are impeding his progress.

Deciding whether to move Paul to a higher tier involves considering multiple factors, including the consistency of his progress, the quality of interventions, and the potential for change. RTI emphasizes a data-based decision-making process, requiring educators to analyze graphs, trend data, and growth rates objectively (Brown, Skow & the IRIS Center, 2009). If data show that intensifying or modifying instruction can yield increased growth, then a tier move might be justified. Conversely, if even with intensified interventions, Paul’s growth remains limited, this indicates the need for more specialized support, such as special education evaluation and services.

In conclusion, the scenario illustrates vital applications of the RTI model and highlights the importance of collaborative data analysis, especially when disagreements arise. Using systematic progress monitoring and evidence-based decision rules, educators can make informed choices aligned with students' needs. The dual-discrepancy approach serves as a valuable tool but requires careful interpretation of multiple data sources to determine the most appropriate tier of instruction for each student.

References

• Brown, J., Skow, K., & the IRIS Center. (2009). RTI: Data-based decision making. Retrieved from https://iris.peabody.vanderbilt.edu
• Fuchs, L. S., & Fuchs, D. (2006). A comprehensive approach to early identification and intervention for students at risk for reading failure. The Journal of Special Education, 40(3), 134–149.
• National Center on Response to Intervention. (2010). RTI in elementary schools: A guide for educators. US Department of Education.
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