3 Tips for Making Data-Based Decisions like a Pro!

By: Jennifer Bessette, Director of Professional Services

RethinkEd, Together We Power Potential

Data. Some people love it. For others, it can be a real four-letter word. Whether you love it or hate it, data is here to stay! It is CRUCIAL to student success. Without data, we have no way to objectively analyze student progress. However, simply collecting data without pausing to reflect & make decisions gets us nowhere. Check out these great tips to ensure a successful data-driven school year!

1. Collect a Baseline

Prior to teaching a new goal to your students, it is a great best-practice to begin by collecting baseline data. You can think of baseline data as a pre-test: we’re simply testing the student to see what he already knows before we begin teaching. Imagine you’re planning on teaching a student to identify community helpers. Without collecting a baseline, you likely don’t know if the student knows some community helpers, all community helpers, or no community helpers at all. This would make it difficult to know where to begin. Once you collect some baseline data, you may discover that the student can already identify the police offer, the fire fighter, and the doctor, but cannot identify the postal worker, the construction worker, or the teacher. You now know where to begin your lesson!

Baseline data also documents the awesome work you’re doing teaching your students. Without baseline data, someone might wonder if you actually taught this skill to the student or if he already had this skill to begin with. If your baseline data shows the student cannot accurately and reliably perform the skill, but after you begin teaching, he now has the skill, you are showing that it is your teaching that made the difference!

2. Be Specific

Analyzing data can be quite difficult if you were not specific during data collection. Take the example of teaching your student identify objects. If the student is not mastering this skill, why not? Take a look at the following graph:

What do you know about this student by looking at this graph? You can see student has not been able to perform this skill with more than 66% accuracy. Why? Honestly, it’s difficult to know the full story looking at this graph. Let’s take this same data, and present it in a different way:

Looking at this graph, you can now see the student is able to identify the ball and the car, but is struggling to identify the block, book, and doll. Now you have a much better sense of the student’s strengths & challenges, and know where you should focus your efforts moving forward!

3. Check for Pre-Requisite Skills

Sometimes students struggle to make progress on all aspects of the goal no matter how hard you try. This can be frustrating for educators, parents, and the student. Imagine a student has been learning to tell time, and has shown very little growth on this skill.

One question you might ask at this time is: Does the student know all of her numbers? If not (or maybe she’s forgotten), telling time would be a very difficult skill for her! This would be a great time to stop & test for the pre-requisite skill of Identifying Numbers.

Clearly, you can see the student did not have this pre-requisite skill. However, after pausing to teach this skill, it looks like the student can now identify all numbers 0-12. Let’s return to the Telling Time lesson.

There! That did the trick. Now that your student can identify all numbers 0-12 and she is able to tell time to the whole hour. Success!

Learn more about data-driven decision-making and how you can use it to improve your results by requesting a demo today.

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