Data-Based Decision Making
Ashley A. Rosiejka
In a school setting, data-based decision making (DBDM), also known as data-driven decision making, is all about the process of collecting student data such as demographic information, academic performance and attendance statistics so that administrators, teachers and parents can accurately assess student learning (Doyle, 2009). For example, teachers may gather information about their students and use it to make decisions. One of the most common illustrations of using data-based decision making is the process of teachers reviewing grades to assess progress on academic tasks. These decisions based on data help to enhance learning conditions and better and more easily direct students towards success. Overall, many of our decisions can be made without collecting data formally however; there are instances where strategic data-based decision making processes are needed as well (Doyle, 2009).

The main advantage of using DBDM is that it helps educators and administrators to identify patterns of outcomes and design strategies to enhance student learning and success. In order to do this effectively there are three crucial elements to the process. The first is that if you are going to collect data and analyze it, it needs to be done purposefully. According to McREL (2003), when data collection and analysis are purposeful, educators are better able to identify patterns of outcomes and design strategies to enhance student learning. Secondly, necessary resources and supports need to be in place in order for DBDM to be implemented properly. For example, data structures and processes are in place including a data team, adequate time, appropriate technology and training (McREL, 2003). Lastly, there needs to be clear communication about all aspects of data collection, analysis and use on a regular and timely basis. This should also include the opportunity for stakeholders to participate in the decision making process.

We can see that Data Based Decision making is a new phenomenon in our schools today but it is often widely misunderstood and often ignored or feared (Doyle, 2009). The first main reason is because most educators view data as a burden instead of an asset. Teachers feel that their time is better served with his or her students, not with data entry and analysis. Overall, school data does not simplify life or increase a sense of professional efficacy. According to Doyle (2009), only when data becomes genuinely useful and commonplace in the classroom will teachers and administrators welcome it and only when it is useful will data quality improve. The second main problem with DBDM is that the process requires additional time and a large financial commitment, both of which are hard to fine extra of in our schools today. We need the right tools such as data collection and analysis software, access to the Internet and email, and access to practical guides and references. A technology infrastructure and professional development for users are just a few of the many necessities for effective DBDM (Holcomb, 1999).

In conclusion, DBDM is useful and desirable in our 21st century schools. With No Child Left Behind, data will have to be used, not just collected. It will help us see progress, plan and execute instructional interventions that will help our students succeed in the classroom.