Outline the typical steps of data-based decision making in a school-wide MTSS.

• A. Define problem; collect data; implement interventions; monitor progress; revise as needed.
• B. Define problem, select measures, collect data, analyze trends, implement interventions, monitor progress, revise as needed.
• C. Implement interventions first; monitor progress; revise as needed; ignore data.
• D. Gather random data and adjust without a plan.

Answer: (B)

Data-based decision making in MTSS is an ongoing, data-driven cycle. It starts by clearly defining the problem in observable, measurable terms so you know what you’re trying to improve. Then you select reliable measures that will capture information about the problem and about progress. Collect data using those measures in a consistent, systematic way. Analyze the data to identify trends, determine who is at risk, and assess whether current supports are helping. Based on that analysis, implement targeted interventions at the appropriate MTSS tier. Continuously monitor progress with progress-monitoring data to see if students are responding. Revise the plan as needed—adjust the intervention, its intensity, or the measures you use—until progress is achieved or the problem is resolved. Other options skip essential steps such as choosing measures, analyzing data, or using data to guide actions, which undermines the data-based approach.