If you’ve looked at a MAP Growth report lately, you know what teachers and kids see: a cut score, a percentile, and a list of their “strongest” and “lowest” areas. That’s it.

  • “You’re in the 42nd percentile.”
  • “Your strongest area is vocabulary.”
  • “Your lowest area is fractions.”

It’s not that these data points are wrong—they’re just too vague to be actionable. They don’t tell a kid what to do differently tomorrow, or help a teacher emphasize the specific skills that will accelerate growth. And since the Learning Continuum report was removed, teachers are left to guess or dig through standards to figure out what those broad areas actually mean.

 

Why Broad Feedback Fails

MAP might tell a student their strongest domain is “Literary Text” and their lowest is “Informational Text.” But what does that actually mean for instruction? Does the student need more work with determining and analyzing the theme, or with connecting the main idea to the paragraph structure and text features? These are very different feedback conversations.

Imagine telling a student, “Your lowest area is fractions.” What are they supposed to do with that? Practice every fraction skill they’ve ever seen? Wait for the teacher to reteach everything? That kind of feedback doesn’t build agency—it builds overwhelm.

Or consider telling a student: “You’re in the 45th percentile in reading.” That doesn’t connect to any actual skill or strategy the student can use. It doesn’t show the teacher what to emphasize in the next lesson. It leaves both teacher and learner in the dark.

 

Linking Studies + AI = Specificity

This is where the AI-Powered PLC Framework steps in. We don’t stop at broad labels and generalized feedback—we translate MAP cut scores and linking studies into clear, teachable insights.

  • ELA Example: Instead of “Your lowest area is informational text,” the framework specifies: “You can identify the main idea with support, but you need more practice connecting paragraph structure and text features to summarize clearly.”
  • Math Example: Instead of “You’re low in fractions,” the framework specifies: “You understand halves and fourths, but not equivalence across denominators. You can add fractions with like denominators inconsistently, and this limits you when solving measurement problems.”

That’s not just feedback—it’s actionable direction. It gives kids clarity about their next step and helps teachers emphasize practice where it matters.

What This Means for Growth

When feedback is vague, practice is scattered. When feedback is specific, practice is targeted—and growth accelerates.

  • ELA Example (Feedback to Student): “You’re strong at retelling. Now let’s practice showing how the author uses paragraph structure to highlight the main idea.”
  • Math Example (Feedback to Student): “You’re fluent with multiplication facts. Next, apply that to solving word problems that involve multiplying fractions.”

These are conversations that build student agency. They turn MAP from a sorting mechanism into a growth tool.

How This Looks at Different Levels

When schools use the AI-Powered PLC Framework in professional learning, teachers see exactly what percentiles and Level I, II, and III mean in practice. Here are a few examples drawn from Grade 4, so you can see how specific the feedback becomes when compared to MAP’s current broad categories:

  • ELA, Level I (Below Standard): Student can retell story events but does not yet connect them to the theme. Next step: practice linking characters’ actions to the lesson of the story.
  • ELA, Level II (Basic): Student can identify the main idea with support, but struggles to summarize because they don’t use paragraph structure and text features. Next step: model how to highlight key sentences to build a summary.
  • ELA, Level III (Proficient): Student can summarize accurately and identify the theme(s) but needs to cite stronger evidence. Next step: emphasize quoting directly from the text.

 

  • Math, Level I (Below Standard): Student can add/subtract within 20 but not yet with regrouping. Next step: practice place value strategies with base-ten blocks.
  • Math, Level II (Basic): Student understands multiplication/division conceptually, but is inconsistent with facts. Next step: Build fluency with arrays and practice fact games.
  • Math, Level III (Proficient): Student can multiply/divide fluently but struggles to apply fractions in word problems. Next step: provide targeted practice with fraction operations in real contexts.

The Claim: From Broad Labels to Specific Feedback

Compare this to what MAP currently provides: a percentile score and a broad domain label, such as “Your lowest area is informational text” or “Your lowest area is fractions.” That’s helpful for sorting, but not for teaching.

With the AI-Powered PLC Framework, we move from broad to specific. We provide grade-level clarity—conceptual understanding, procedural fluency, application, and prerequisites. These are the kinds of specific, actionable insights teachers can deliver back to kids right away. It’s what turns MAP from a percentile into a pathway for growth.

From Motion to Action

When schools connect with us, we help make MAP data accessible and actionable. We don’t just show you cut scores—we show you what they mean. We move PLCs from broad categories to precise instructional moves.

And we go further:

  • We analyze your curriculum to highlight where to emphasize the skills that will boost MAP growth.
  • We equip teachers with feedback language they can use immediately with students.
  • We ensure your student data stays secure—we never use personally identifiable information (PPI).

Closing the Specificity Gap

MAP is still powerful, but without specificity, it leaves teachers and students with data points they can’t act on. The AI-Powered PLC Framework changes that. It connects cut scores and linking studies to actionable skills, targeted practice, and clear feedback.

Because growth doesn’t happen in broad bands, it happens when kids get specific, actionable feedback—and when teachers know exactly what to emphasize next.

And now, schools can make that clarity easy.

Join the Movement

We believe specificity is the key to accelerating growth—and schools don’t have to figure it out alone. When you partner with us, you join the Impact Teams Movement: a network of educators committed to turning data into clarity, motion into action, and assessments into real growth.

Reach out to us today to learn how your PLCs can leverage the AI-Powered PLC Framework and make MAP data truly actionable. Together, we can empower teachers and students with the specificity they deserve.