By Craig A. Mertler
Data-driven—or data-informed—decision making in classrooms and schools has become a catchphrase concept and practice over the last several years. In fact, it has morphed into a mantra of sorts for many schools around the country. Although the idea of using the wide variety of student data that we have at our disposal as the impetus for better-informed decision making in our classrooms and schools has seemingly spread like wildfire, many educators are still unsure as to where to begin when it comes to using data to inform practice, or how to manage a potentially overwhelming collection of these data. While the process itself is not necessarily a difficult one, it is best to approach data-driven decision making in your classroom or school with a specific plan in mind. Below are five tips that can help you in developing your plan for using data to better inform your decision-making processes.
- Begin by specifying a particular problem on which you want to focus, and then pinpoint the data that will help to inform your decision-making process. Identifying a specific “problem of practice” that you want to improve or otherwise address will serve to focus your attention. Then, determine possibilities for types of data to use in helping you address your problem of practice.
- Ensure that the data you plan to use will be manageable for you. Try not to incorporate too many sources of data as this will likely become overwhelming, or perhaps simply unmanageable. Engaging in a reflective process about your problem of practice in an effort to be very specific will also help you to narrow the possibilities for data to assist you in your decision-making process.
- Avoid becoming overwhelmed at the thought of potentially including other sources of data; they can be used in future instructional cycles and associated decision making. If you are able to identify multiple sources of data that could help inform your decisions, do not discard them entirely. You may be able to use them in a future cycle of instruction and with similar problems of practice.
- Look for patterns, trends, and outliers in your data. When engaging with data, many educators simply do not know where to begin or what to look for. At a basic level, you should examine student data in order to identify patterns or trends (e.g., are there problems, items, or tasks that many students answer or perform incorrectly?) as well as outliers (e.g., are there instances where only a couple of students make mistakes, but the mistakes are the same or are similar in nature to one another?). These often help you to identify specific aspects of your instruction that you should target for changes and/or improvement.
- Treat data-driven decision making as a cyclical process. Cycles of instruction were mentioned earlier, and it is important to stress that data-driven decision making should be viewed as a cyclical process, meaning that you do not need to solve all of your problems of practice in one round of decision making. What you learn in one round or cycle can be used to inform the progress and instructional improvements you make in future cycles.
Try not to shy away from the potential contained within all of the student data that exist in abundance in our classrooms and schools. Incorporate them into the wide variety of decisions you make every day. Embrace this as an opportunity to bring a little “science of teaching” into your “art of teaching”!
Explore these ASCD resources for more information to make data meaningful.
Craig A. Mertler has been an educator for more than 30 years—18 of those in higher education and 6 as an administrator—having begun his career as a high school science teacher. He is the author of 20 books including The Data-Driven Classroom: How do I use student data to improve my instruction? Connect with Mertler at www.craigmertler.com.