InClass

Intuition can be a helpful tool for decision-making, but it would be a mistake to always rely on that “gut feeling.” While intuition might spark movement in a certain direction, it’s data that allows you to analyze, verify, and quantify. 

Data is an important tool because it highlights strengths and areas for improvement. When educators use data to drive their decisions and plans, they can respond more quickly and effectively to challenges, adjust their strategies, and become more reflective practitioners.

Start the data-driven decision-making process by asking yourself these questions.

What Question(s) Are You Trying to Answer?

The first step to using data to guide decision-making is to identify what questions are going to be answered by collecting data. This allows educators to be intentional about what type of data to collect. 

Data is more than just standardized test scores. Educators can collect data on student attendance, scores on formative assessments, and even qualitative observations. Why not encourage your students to collect their own data? This will help them see value in data collection and creates greater transparency. It’s also an opportunity for them to set goals, understand where they are currently in relation to the goal, and take immediate action toward making significant gains.

What Is Good Data?

Good, or high-quality, data is data that people can use, make sense of, and leverage to make changes in their environment. It is information that is collected and stored safely. This goes back to the first point above — what question are you trying to answer? Decide what to measure and how to measure it. If the data is useless or provides extraneous information, it’s no good to the decision-maker. When collecting data, ask yourself, “Does this data provide an answer toward the overarching question?” Make it as clean and easy to understand as possible.

What Happens to the Data After It’s Collected?

Use it! Analyzing and interpreting certain data is a job unto itself. A fun activity for students may be to try displaying the data in different ways (e.g., scatter plot, pie chart, bar graph, etc.). Not only is this a way for them to practice math skills, but they also learn which figures make sense for the type of data collected (and for what audience). 

Remember that data can never prove a hypothesis (or a hunch). Rather, you can only fail to reject the hypothesis. No matter how much data you collect, chance could always interfere with your results. However, you can still use the data collected to drive your next steps. 

As you continue to practice data collection and data-driven decision-making, take time to reflect on the process itself.