How Data-Tracking Makes Classrooms Equitable

Hey there everyone! We hope 2021 has been treating you well so far… Today, we’re going to discuss a pretty difficult topic:

Educational Equity

More specifically, how data-tracking makes education more equitable.

There’s no possible way we could write about the entirety of educational equity and the racism, sexism, classism, and ableism that encompasses it. We hope this blog post can serve as a launching point for many of our teachers and we will be sure to include several resources for you throughout.

As educators we are capable of changing the world - one of the best ways we can continue doing this is by leveling the playing field for our students, so every child can be as successful as they can be. To level the playing field, we must have clarity around our students’ strengths and difficulties and we must make sure that we’re able to understand this in an equitable way.

Educational equity is absolutely crucial because it gives equal opportunities to children. Data-tracking can help set us up for educational equity, but before we can dive into the data-tracking piece, we want to make sure we understand what educational equity means.

So... what is equity? Equity is justice according to natural rights or freedoms, or the freedom of bias. Below is a fantastic (albeit simple) explanation of inequality, equality, equity, and justice by Tony Ruth. This picture demonstrates how inequality means unequal access to opportunities, equality is evenly distributed tools and assistance, equity is custom tools that identify and address inequality, and justice is fixing the system to offer equal access to both tools and opportunities.

We live in a world that is more complex than ever before.

The cultural and human diversity of the United States (and so many other places) is part of what makes it so beautiful. The merging and co-existence of that cultural diversity also can inherently bring about some biases. An implicit bias is “when we have attitudes towards people or associate stereotypes with them without our conscious knowledge” (Perception Institute). To be human is to be flawed and imperfect and to have some biases, but we should always try to be better and do better. If you are aware of your biases and truly commit yourself to anti-racism, anti-sexism, anti-classism, and anti-ableism - you are trying to better yourself. You are going to make mistakes. You will not be perfect. You might get called out. Keep trying anyway. Keep in mind that this is a rather simple explanation of implicit biases and it is absolutely crucial for you to do outside research and reading. Educating yourself about the importance of cultural diversity and equity is only going to make you a better educator.

What can this look like in the classroom?

We all create narratives constantly, whether it be about our lives or the lives of others. For example, if someone you may not particularly enjoy is late to work, you might immediately think they are lazy or inept - you attribute their lateness to internal factors. But, if you (or someone you enjoy) is late to work, you might assume they were late due to unprecedented traffic, or that something might be wrong. You attribute their lateness to external factors. This is a psychological theory called Attribution Theory which impacts our implicit biases. When we are biased toward a group of people, we are more likely to attribute their struggles to internal factors rather than external ones. The narrative we form around their ineptitude, emotional response, etc., shapes how we perceive people, as well as how we educate and review or grade people.

For example, if a child is an English Language Learner and is acting out in class, we might attribute their acting out to them refusing to learn, or maybe even saying they’re just a bad kid. We attribute their acting out to internal factors. But, once we switch the narrative to external factors, we can start to realize that they might feel overwhelmed hearing English constantly instead of their native language. When we data-track with specific measures and goals (for more on that, click here), we can begin to shift the attributions from internal to external. When we have the numbers, we can see what a child truly does or doesn’t comprehend and remove some of the biases we have. We can start to form a different and more comprehensive narrative to truly help that child.

With this, it is important to data-track consistently and accurately.

Our biases can affect the way we data-track. For example, if a child miscues when decoding a word, but then immediately pronounces it correctly, are you going to say the child got the word correct or not? If you are variable in your data-tracking, it will not be accurate because your biases will be getting in the way. Someone might be more likely to mark something incorrect if biases are present, especially with something that may not be exactly clear-cut, like a child miscueing and then saying the word correctly. Set up strict boundaries for yourself while data-tracking.

Some of these boundaries may include:

• If the child corrects themselves without any help or cueing from me, I will count it correctly.

• If I have to tell the child they did not say the word correctly, and the child then pronounces the word correctly, I will count it as incorrect.

• If the child repeats a phrase while reading, I will not count it as an error.

• If the child adds in a word to a passage, I will count that as an error.

• If it is a two-part question (ex: find the subject and the predicate), and the child gets one of them incorrect, I will mark it as incorrect.

• If there are three pronunciations to a single vowel team (ex: “ea”), and the child gets two of them correct but misses one, I will mark it as incorrect.

These are just a handful of examples that you can use to give yourself strict boundaries when data-tracking to ensure your biases are not coloring the data. Additionally, this makes sure you can look at the numbers when helping a child, not just your emotions. For example, if we return to our child who is an English Language Learner who often acts out in class, and we don’t have any data on letter review, syllable type knowledge, or phonological awareness, we will not be able to accurately assist them with next steps or targeted practice. We might let our emotions get the better of us, become extremely frustrated, and fall back on the child’s internal attributions or biases as the reason for their “failure.”

However, once we start to accurately data-track with measurable goals and strict boundaries, we might be able to see that the child can only recognize and name 1 out of every 10 letters. No wonder the child is acting out! It must be so frustrating to feel that way as a child and not be able to properly communicate it. Now, you know what you need to focus on with that child. Your data switched your narrative from an internal fault to an external one and your strict boundaries with data tracking hopefully lessened any implicit biases. You might have to go at a slower pace compared to another child, but that is okay. As we have said before, data tracking is not personal. It is not a reflection of you or your teaching.

Data is just numbers that provide you with a pathway to change the world.

For more information about effective data tracking, check out our How to Create SOR-Aligned Goals & Track Data. In this free workshop, you will learn how to use the data you already have to set appropriate goals, uncover the key to setting up your lessons to make data tracking easy and learn how to manage & organize your data. Plus, you’ll get a free data-tracking template!