Tackling Data-Driven Decision Making in Education

Learn more about data-driven decision making in education
Contributed By

Elizabeth Trach

Professional Writer and Blogger

Tackling Data-Driven Decision Making in Education

Posted in Evolving Ed | December 06, 2018

Data has been at the heart of education reform since the early days of No Child Left Behind (NCLB), and standardized tests have become routine for nearly every grade and subject. As we measure adequate yearly progress and break down test results to show what students know and what they have yet to master, we have been provided with a trove of data that, ideally, should be used to inspire effective change.

Data-driven decision making — or DDDM, for short — is, at its core, exactly what it sounds like: using factual information to make choices about what to teach and how to teach it. Instead of treating teaching like an art that relies on talent and intuition alone, DDDM provides some science as a jumping off point for trial and error to adjust strategies and devise an effective practice.

DDDM isn't just about having data. It's about using it to take action and improve instruction. This requires a system that gives teachers easy access to data and makes it meaningful. It also means providing flexibility to let teachers try new things based on their interpretations of test scores and other data points.

Why Is It Important to Base Instructional Decisions on Student Data?

At its most basic, DDDM is logical. When you use a pretest to find out what your students have learned and what they need more practice on, you can design lessons that address their needs. This will ultimately save time for both instructors and students, as precious teaching time can be focused on the standards students struggle with. Likewise, data will reveal what concepts need to be retaught or reinforced before moving on.

Data is also useful when it comes to individualizing learning. When you know who needs enrichment and who needs remediation, it's possible to provide more individualized instruction. This helps all students get what they need to succeed.

It's also important to use data to drive professional development. Student data may point to gaps in a teacher's knowledge and/or pedagogy, so this information should drive decisions about your district's investments in professional learning. This will help make staff more effective and give them the tools they need to do their best teaching — no guesswork required.

Tools for Data-Driven Decision Making in Education

One of the biggest challenges facing school districts is how to effectively use all the data they've collected. Whether you've been provided year-end state test scores or have used your own formative assessments to gather information, storing, analyzing, and making that data useful is critical. Many, if not most, of the teachers in your district probably lack the training and confidence to sort through data sets to reach conclusions, so it's also important to give them the tools they need to approach data in a meaningful way.

Here are some tools to consider when trying to implement data-driven decision making in education:

  • Textbooks: Providing professional development around data analysis is a great place to start, and educators will appreciate having a reference book. The Data Driven Classroom by Craig A. Mertler is a good jumping off point to develop individual and whole-group teaching strategies based on common educational data.
  • Continuing Education: Though not every teacher will be interested in a deep dive into data analysis, having teacher-leaders in your district can help mentor colleagues and provide savvy teacher perspectives on district-wide DDDM. Analytics for the Classroom Teacher is an EdX course specifically designed to give teachers an overview of the use of data analytics in education.
  • DIY Data Tracking: Your district IT department may be able to develop their own portals and data storage systems for making sense of all the numbers. This is labor-intensive, but it can allow for a customized solution that works for your specific needs.
  • Your LMS: Robust learning management systems have built-in data analysis functions to track attendance, test scores, and progress on various learning standards. If you already have an LMS in use, additional training about its data capability can set the stage for teachers and administrators to do more DDDM.

6 Steps to Mastering Data-Driven Decision Making At Any Level

To get started with DDDM at any level, it's helpful to follow some tried-and-true steps:

  1. Define Your Vision. What is the ultimate goal? By naming what you want to improve, you'll automatically narrow the scope of the work and help staff focus on what's important.
  2. Identify a Problem. What aspects of student learning aren't matching your stated vision? You may use test scores or other data to identify glaring issues, or you can rely on teacher's intuition to select an issue to work on.
  3. Develop Questions for Inquiry. What do educators and other personnel need to understand about the problem in order to solve it? These questions may be about student performance, teaching techniques, or other factors that influence outcomes.
  4. Gather Relevant Data. With so much high-quality data available to educators via their LMS and other systems, it's crucial to narrow the field to include only what will be helpful in answering your specific questions and solving your problem.
  5. Analyze the Data. Try using data analysis tools to help organize data into usable charts and tables. Once you can visualize the data clearly, determine what the result indicate about your problem.
  6. Develop a Solution. Often, a deeper, data-driven exploration of a problem points to a solution. If one isn't immediately clear, it's appropriate to develop a hypothesis, try new methods, then test the results — using that data to analyze its success, of course.

DDDM doesn't require a major overhaul of practices all at once. Even the smallest decisions about lesson planning and teaching methods can benefit from using data to improve. By encouraging your staff to use the tools at their disposal and follow these steps, you can create a culture of DDDM that benefits students in tangible ways.

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