Data-Driven Decision Making in the Era of Accountability

May 19, 2016

In December 2015, the Every Student Succeeds Act (ESSA) was passed as a U.S. law for K-12 public education. While this law replaced the unpopular No Child Left Behind Act to modify the federal government’s involvement in elementary and secondary education, the ESSA still includes provisions of annual standardized testing.

Therefore, in this era of accountability, school data management is more important than ever. Some may be intimidated by this dependency on analytics, statistics, or data, but the truth is that data-driven decision making (DDDM) empowers teachers, administrators, and district leaders to better teach, manage, and lead schools.

What Is Data-Driven Decision Making?

“DDDM in education refers to teachers, principals, and administrators systematically collecting and analyzing various types of data, including input, process, outcome and satisfaction data, to guide a range of decisions to help improve the success of students and schools.” Rand Education

The key to successfully using data-driven decision making in schools is to consider what you want to know and why. Understanding the issues that students are facing in achieving their education goals, can enable educators to better strategize the school year and allocate their resources.

Why Do We Fear Data?

So if data-driven decision making is supposed to be helpful, why are educators wary of analytics?

Data has the capacity to uncover weaknesses and failures. Seeing multiple years of test grades, or inconsistent attendance throughout the school year is a scary reality.

But, data also has the capacity to reveal strengths and successes when you have the proper tools to manage it.

What Are The Measures Of Student Data?

Student data that gets measured and monitored will most likely improve. Without data, decisions on lesson plans, pacing, and resource allocation would only be based on opinions and hunches.

It’s important to discover patterns, practices, and relationships for the following:

  1. Standardized Test Data
  2. Formative Performance Data
  3. Demographic Data
  4. Attendance Data
  5. Student and Teacher Observation Data
  6. Perception Survey Data

Collecting this data from various perspectives and sources will enhance the strategies produced. For example, analyzing state level versus local level use of data could help guide question development.

Once the data is collected and analyzed, consider how your district can use the data to make their decisions to improve individual schools. This data can help you take actions with the greatest impact, go beyond a strategic plan, and try to close student achievement gaps.

Who Has A Role In DDDM?

Teachers can align classroom goals with district goals, analyze individual student data, collaborate with other teachers, and share the data with their students to inspire them.

Students could then create personal goals and be able to monitor their progress to make their teachers, parents, and themselves proud.

District Leaders should foster this positive climate for teaching and learning. They can model data use by being data-savvy. And by acknowledging student and school success, they can provide support to encourage administrators, teachers, and students to get on board with the era of accountability.

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