I know what you are thinking, another data post? I thought you said we were going to focus on teaching strategies this month? I feel you my friends. But you can’t escape the data monster. I’m not being sneaky shoving this data post in here, it’s very intentional. We cannot talk about teaching strategies without talking about data because data is going to drive our teaching. 

This term Data-Based Instruction (or Data-Driven Instruction) is definite buzz phrase around the education world. Administrators and principals will put such high importance on the requirement for data-based instruction that honestly it freaks most teachers out. These previously confident rock-star teachers are suddenly second guess themselves. “Is what I am doing correct? Is this data based instruction? Is this what my admins want?”

Data-Based Instruction is using student data to show you where to take your instruction next.

It’s really nothing fancy or overly complicated. Data Based Instruction is using students’ current skill level (shown through their data) to plan future teaching. This means we aren’t taking data just to take data and this means each students curriculum is individualized. I’m preaching to the choir right now, right? This is what we all do on a daily basis. Data-based decision making is part of a special education teacher’s blood. It’s in our veins. So why are we all so scared we aren’t doing it right? 

The Children’s Literacy Initiative does a great job explaining data based instruction related to literacy. I love this graphic they shared. It really illustrates that data based instruction is an on-going process. You are never done. If data is truly driving your instruction, then it will be a cyclical process. 

Since Data-Based Instruction became such a buzz phrase it falls into that educator buzz word black hole – where suddenly the meaning of the word or phrase becomes insanely ambiguous and every just throws the word around to sound cool and on point. When someone uses the word data incorrectly, I’m shaking my head thinking, “oh honey, who let you use that word?” Some newbie admin pops into your room and is running her mouth about differentiated STEM project based learning that incorporates inquiry based learning that has rigor and grit but is child centered and you are all like, “Come again?? Can you speak English please?” When it comes to data based instruction, keep it simple, keep it consistent, and be confident in your methods. Your data will show that it is working. 

Streamline Your Data Based Instruction

1. Keep it simple.

Your data doesn’t need to be an in-depth formal assessment. Your data can be anything that concretely shows student achievement. Work samples, observation notes, a list of times a behavior occurred, or tracking of correct and incorrect responses all show student achievement. Don’t make it overly complicated. Use clickers, simple data sheets, and exit tickets to track student responding.

2. Set criterions – for mastery and for instructional change. 

Make a plan. And that plan should include when a skill is to be considered mastered and when it is time for an instructional change. So for mastery – you may say, this skill is considered mastered when student gets all problems correct for 3 days in a row. And for instructional change – you may say, if this student hasn’t hit mastery in 3 weeks, we will change how we are teaching this skill or go back to something easier. This will encourage you to continue taking data. And your admin wants to see data-based decision making? BOOM. Right there. I think teachers forget about setting this limits a lot. Then we are just aimlessly taking data to “see” what happens and that quickly evolves into data with no purpose which quickly evolves into stopping data collection {insert sad face emoji}.

3. Have confidence in your plan. 

It gets unnerving because our approach to data-based instruction may look different than our general education colleagues. But of course it does! Think about how different our classrooms and our students are. It makes sense that our methods for taking and utilizing data is going to be different. In special education classrooms, our data based decision making tends to be even more detailed and involved than in the gened based on our students’ need for such an individualized approach and curriculum! 


Sasha Long
Sasha Long

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