MTSS RTI Articles & Resources

How Meaningful Metrics Drive MTSS Success

Written by Larissa Napolitan | Nov 11, 2025 7:04:57 PM

During a parent-teacher conference, I handed a parent a printout of their child’s test scores and explained what the numbers meant. Benchmark assessments often fail to provide detailed insights into specific skills, like phonics or reading comprehension, leaving it up to educators to make this data meaningful. Helping parents understand their child’s progress is an important step in ensuring the information is actionable. Similarly, when we collect and analyze data as educators, it’s critical to approach it with clarity and purpose, so it truly informs our decisions.

This need for purposeful data is especially evident in districts implementing MTSS. When you ask educators how it’s going, a common response is, “It’s a work in progress!” A big challenge lies in having strong measures and assessments that guide day-to-day work effectively. Without reliable and actionable data, the process becomes harder to navigate.

As Dr. Andrew Shanock, a school psychologist and MTSS expert, points out, a major pain point is the quality of the data collected. “Is it good data?” he asks. Addressing this question is where the real work begins, shifting data from being a source of frustration to a tool for empowerment. When data is clear, reliable, and actionable, it becomes a powerful driver for decision-making and growth, benefiting both educators and students alike.

What Does "Meaningful Metrics" Really Mean?

Meaningful metrics aren't just about numbers on a spreadsheet; they're about clarity and the ability to take action. It is easy to get caught up in scores without understanding their meaning. Dr. Shanock points this out with universal screeners: "People say, oh, he has a 235. You're like, oh, okay… What does that mean? And nobody can explain it."

Educators are more likely to use the data they comprehend and perceive as valuable. The often missing link is a direct connection between the data and instructional practices.  Effective data metrics offer immediate, understandable feedback to teachers. It clarifies not only that a student is struggling, but also why and what concrete steps to take next.

Instead of getting lost in broad metrics, consider focusing on measures that are easy to collect and directly tied to skills. For example, Dr. Shanock recommends focusing on fluency measures, such as math fluency, writing fluency, or initial sound fluency, because they offer an easier way to assess the effectiveness of interventions for children.

These types of measures offer a few key advantages:

  • They are specific: They pinpoint precise skills like word decoding or math computation.
  • They are frequent: They can be administered quickly and regularly to track progress.
  • They are actionable: The results directly inform what skills need to be taught or retaught.

When you have this kind of information, you can move from saying a student is "struggling" to identifying that they have difficulty with CVC words, for example, which is a problem you can actively solve.

Related Resource: Using Universal Screening for Accurate, Objective Tiering in MTSS

Shifting from Benchmarks to Growth

Another challenge with data is the tendency to focus solely on benchmarks and cut scores. While these can be useful for initially identifying students who need more support, they don't tell the whole story. What happens when a student shows significant improvement but still hasn't reached the grade-level benchmark?

Dr. Shanock cautions against a black-and-white view:

He explains that a sixth grader who improves significantly but still reads below grade level is a success story. To call that student "struggling" would be “unfair to the kids' work and all that teachers' efforts."

The power of meaningful data lies in its ability to show growth over time or not. When a teacher can see a student move from reading 30 words per minute to 50, that's a tangible win. It validates the hard work of both the educator and the student, providing the motivation needed to keep going. This focus on growth helps reframe the conversation from "Why isn't this student at benchmark?" to "What is this intervention doing for this student, and is it working?"

Related Resource: How Leaders Use MTSS Data to Drive School Improvement

Building a Data-Informed Culture

For data analysis practices to be truly effective, everyone needs to be on the same page.

Consider these three steps:

  1. Select effective assessments: Choose assessments that provide meaningful, actionable data to guide instruction and support student needs.
  2. Invest in Training: Ensure all educators, from teachers to administrators, understand the "why" behind your assessments. Provide training on how to interpret the data and connect it to specific instructional strategies.
  3. Standardize Your Process: Develop clear, consistent procedures for data collection, team meetings, and decision-making. When everyone knows the process, meetings become more efficient and focused on problem-solving.
  4. Practice and Refine: Use team time to practice analyzing data from case studies in a low-stakes environment. This helps build confidence and allows your team to work out any kinks in the process before applying it to real students.

Turning MTSS Data into Student Success

Ultimately, meaningful data helps us make the MTSS process more human. It allows us to celebrate small victories, provide targeted support where it's needed most, and give every student the best possible chance to succeed. It can transform MTSS from an overwhelming mandate into a clear and supportive framework for helping all learners thrive.