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“Whenever a theory appears to you as the only possible one, take this as a sign that you have neither understood the theory nor the problem which it was intended to solve.” — Karl Popper
Imagine returning from a doctor’s visit. The diagnosis? Acid reflux. Your doctor recommended exercise, a more careful diet, and—the best part—wrote you a prescription for Nexium.
After a frustrating process, your morale is high now that you’ve found a fix. Nexium’s advertising even goes as far as to call it the “Healing Purple Pill.” Plus, it’s a popular and successful drug with sales passing $6 billion per year. That kind of revenue has to be a good sign, right?
You check with Google to confirm your cause for optimism. But what you learn is downright shocking.
On top of startling side effects, you find out that Nexium only works for 1 in 25 people (Schork, 2015).
The drug was likely approved on the basis that it worked far better than placebos did. This was based on analyzing a group average. It doesn’t come anywhere close to telling you whether the specific treatment will work for you.
In other words, it doesn’t tell you the one thing you need to know.
You can ask a similar question for educational programs, like intervention. The research shows that, on average across a group, it works. Around two in three students receiving intervention get above the lower 30th percentile (Torgesen, 2000), a much better percentage than most pharmaceutical drugs.
But until the intervention is underway, it’s difficult to know which students will respond.
Remember back to the 1 in 25 chance that Nexium would fix your acid reflux? Well, there’s a push in medicine for better results.
It’s called precision medicine.
The idea behind precision medicine is logical. Identify the traits of individuals that will determine a drug’s effectiveness. Then doctors can better understand what should be prescribed.
Intervention could learn from precision medicine to better understand the individual traits that lead to better educational outcomes. It goes beyond merely knowing a student’s reading scores. You want to know about the destination—where exactly a student can get to with the intervention—before you even start.
Let’s examine the 30% of students in reading intervention who are still stuck in that lowest group—the ones who fail to respond to it. Despite receiving research-based reading interventions, one of every three students remains in the 30th percentile or lower.
Through intervention, if these students are not getting back to grade level reading, they wouldn’t be able to participate and comprehend the general education curriculum. What then? You’d want some precision diagnostics to know what they need.
That’s what the diagnostic screener called uPAR (Universal Protocol for Accommodations in Reading) gives you.
For the students who likely won’t get to grade level with intervention, uPAR shows the text level they can comprehend with a reading accommodation.
This is not the type of prediction based on an average of student outcomes. It’s a personal precision diagnostic where you and your students find out exactly the text levels they can comprehend with an accommodation.
It’s often transformative for students. Many of them learn that they can comprehend grade-level content while some students find out that they can read well above grade level by listening to text read aloud.
Gavin is one of the students who was transformed when his teacher brought in uPAR in 5th grade. Despite Gavin reading at a first-grade level, he learned that through listening to passages read aloud, he could comprehend text up to the level of a sophomore in high school.
It was exactly what he needed.
Gavin would still receive specialized reading instruction through Snap&Read, but now he had a way to read independently and handle grade-level passages while his reading skills improved.
Now extrapolate Gavin’s transformation across an entire school, district, or state. How many students could say that what they learned in one class period would change their lives?
The future of educational intervention does not lie in group averages. It starts with seeing the future.
For more information and to request a trial click here.