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The power of data-driven instruction for reading success

You need a world of allies when making the crucial shift to instruction grounded in the Science of Reading—and data is one of them. Here’s how to make it work for you.

By èAV Staff | March 18, 2024

Cover of a book titled "The Story That Data Tells: Using Data to Chart Your Course With the Science of Reading," featuring illustrations of animals, astronauts, and educational themes, perfect for those seeking personalized instruction or dyslexia resources.

Words tell stories—and so do numbers. Even though reading can take us to magical places and spark immeasurable wonder, it’s that can best guide literacy instruction (and instructors) toward delivering reading success.

èAV’s Executive Director of Learning Science Danielle Damico, Ph.D., notes in that educators and districts can, understandably, get stuck in out-of-date beliefs. One common one is that reading is a natural process, the product of variables we can’t change in schools. But data shows the opposite—and provides immense opportunity.

Data is at the heart of what we now call the Science of Reading—a term for the decades of data now available on how kids learn to read and write, and how to best teach them. In making the shift to instruction grounded in the Science of Reading, educators can make effective use of this data to change not only literacy practices, but lives.

If you’ve been following the Science of Reading movement, you likely know the power of making that shift. But whether you’ve been following it for years or are just learning about it, there are some questions you’ll need to explore. What data do you need to make your case to your school or district? And what data will help you monitor implementation—and future success?

Using data to make your case for the Science of Reading

When making the shift to instruction grounded in the Science of Reading, you need to build buy-in among key stakeholders. Your most powerful tool in this endeavor? Data.

If your screening data shows that of your students require intervention, it’s time to make the shift. That key performance metric is sometimes all you need, but other indicators can include high error rates among students reading decodable words, fluency below grade-level, words-per-minute scores, or struggles in identifying base words with a prefix or suffix.

Your teaching materials are also a source of data. When you conduct an audit of their content and approach, do you notice—for example—a lack of direct connection between phonics lessons and texts? Emphasis on visual strategies for decoding? Few decodable texts in the first place? These clues (or even red flags) could point to materials that are not grounded in the explicit, systematic instruction recommended by the Science of Reading.

The same may be true of your shared or inherited instructional practices. Is reading typically taught through isolated topics or generic skills (like “find the main idea”) that are disconnected from knowledge domains? Those approaches to reading could contribute to low performance data—and could help you make your case as you champion a shift to data-driven instruction.

What does data-driven instruction look like—in implementation and beyond?

Science-based reading instruction reduces the need for intervention and allows students to move forward as capable, confident readers. Once you’ve begun to implement data-driven instruction, you’ll need to collect key information to make sure you get—and stay—on the right track for all of your students.

Among the eight core principles of the Science of Reading, universal screening and progress monitoring are two that are absolutely necessary to ensure that all students receive the right instruction. It’s also important that your universal screener measures phonemic awareness, phonics, fluency, vocabulary, and comprehension.

It’s important to monitor improvement in foundational literacy skills and decline in the number of students requiring literacy intervention as well. Collecting qualitative insights regarding classroom practices and tracking their alignment with Science of Reading principles forms a crucial part of the data landscape during this instructional shift.

And finally, as Danielle Damico , implementation data can help you:

  • Confirm that your program has indeed been implemented.
  • Ensure that student learning is meeting key goals.
  • Distinguish between an ineffective program and an effective program not being implemented as designed.
  • Determine opportunities for professional development and coaching.

To take a deeper dive into all the data that can help you champion, navigate, and succeed in this shift, download our ebook and explore our webinar .

 

Tags:
Literacy instruction Reading curriculum Science of Reading curriculum

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