Approaching data conversations with the right mindset can make all the difference in the outcome and the effectiveness of the meeting. Skillful data conversations can be a challenging practice for any educator—it is essential to approach these discussions with positive intent and a focus on problem-solving.
In the Webinar “The MTSS 6-Week Intervention Check-In,” Brittany Shurley and Larissa Napolitan discuss utilizing a problem-solving framework for examining data after six weeks of intervention. This framework could apply to any data discussion throughout the school year.
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One of the key components of the Multi-Tiered System of Supports framework is utilizing data as a tool for decisions and problem-solving to support students. Data frames the discussion of what is working and what isn’t. Data makes diagnosing problems more efficient, selecting strategies clearer, and can help plan and refine the curriculum. Using data as part of a problem-solving protocol creates a culture of continuous improvement.
At the 6-Week Check-in, it is vital to monitor and measure data to determine if the intervention is working - and if not, determine the root cause. Look closely at the ROI (Rate of Improvement), the needed slope line to move from the current baseline to the goal score.
At the 6-week mark after implementing interventions, there will be trends and patterns to address. When analyzing the data from a specific time frame, it is good practice to identify where the root cause of problems exists. Ask questions about the data. Does the intervention have the effect that you want it to have?
At the 6-Week Check-In, it’s time to evaluate the plan using the progressing monitoring data with norming charts.
Questions for Evaluating Plans:
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With any plan, monitoring the data as the plan progresses is critical. Suppose in week 2 or 3 it appears that the intervention is ineffective. In that case, it’s time to check on the fidelity of the intervention:
After monitoring that progress, determine if there is sufficient growth and make changes. This is when you set the next steps for the students and go back to the beginning of the problem-solving cycle. While these decision rules provide a framework for how to change, escalate, etc., interventions, it is essential to remember that data-driven decisions are made by teams and are collaborative in nature. It’s good practice to consider several possibilities for root causes before jumping to changing support levels, programs, and cadence of program delivery.
📊 Check out this worksheet: Questions for MTSS Data Analysis Worksheet
MTSS is not just about collecting data but also about using the data to continually improve our practice and ensure students have the most effective support. School leaders should use data to look for school or grade-level trends. Normed screener and progress monitoring data can assist leaders in continuing to provide a system of supports and professional development to teachers and staff around key areas of improvement.
(And get ready to take notes ✍️)
Related resources you may find helpful:
How To Use Progress Monitoring To Guide Decision-Making in MTSS |
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Best Practices of Data Analysis and Differentiation for Tier 1 in MTSS |
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