Why Data Management?

To Identify All Students' Needs

By Ron Benner, school psychologist, Bridgeport, Connecticut

What's all the excitement about "data management"? Why do we need to collect so much information about the students we teach? The short answer is that individual student data can show teachers when a student has mastered the material and can move on and where on a continuum of scores they should start regular and special education interventions. But we also need to collect it because federal legislation requires it.

This article will address the data we must collect for legal reasons and some ways we can become a better data collectors and managers.

Legal Requirements for Teachers to Use Data
Two pieces of legislation that directly impact the work of educators are the Elementary and Secondary Education Act (ESEA), which demands that schools make adequate yearly progress, and the reauthorized Individuals with Disabilities Education Improvement Act (IDEA) 2004, which demands that schools have reliable data to identify a student as needing special education services for a specific learning disability. 

Individual Student Data
Teachers, schools, and states must document individual student learning. The ESEA (also known as No Child Left Behind [NCLB]) says that by 2014, all students will be learning at 100 percent mastery. States have set standards and benchmarks. These goals are global in nature and set a trajectory for what a student should be learning over the years in order to reach graduation with a core of knowledge that society believes will facilitate that student's transition into a productive, responsible citizen.

Systems-Level Data
School systems must gather data using two types of systems-level assessments:

• Adequate Yearly Progress (AYP)—given once a year—measures each student's progress. This assessment shows those students who have not made adequate progress. Teachers can use this information to develop ways to teach these students individually.
  
  
• Curriculum-Based Measurements (CBM, formative testing)—given three times a year—(Universal Screening)—show the student progress in a particular subject area (e.g., reading). CBM tests use sensitive measures that give us insight into whether or not a student is likely to score in the mastery range when the summative test is given at the end of the year. 

If the student scores well, we are happy. If the student does not, we need to look at what is going on. A lack of success in the regular curriculum can become the slippery slope to special education or at least more individualized instruction in the regular education classroom. 

The most important thing is that the data offer information for educators to work with. The student data indicate whether or not the curriculum and approaches to learning are helping to move the students through the curriculum to the goal level set for the end of the year. And the data help policymakers select the most appropriate research-based instruction or program. The data also help regular education teachers and special education teachers know what interventions to use. IDEA 2004 says that students need to be taught with research-based interventions, and educators must show—with data—that a particular approach has given the desired result with a particular student.

Training Opportunities from the School System
To learn more about data management, look for professional development opportunities in your school system:

• Take a course in CBM assessment and analysis to learn how to analyze each student's data.
  
  
• Get training in differentiated instruction to help teach each student using the way that student learns.
  
  
• Use CBM assessments to help reflect on what a student or class is learning.

Ways Teachers Can Improve Data Management
Here are some ways you can improve the management of student data:

• Use a variety of evaluation tools. Use both CBM and norm-referenced tests for a balanced perspective of the systemwide and the individual perspectives of student growth. Choose CBM tools that measure a standard or benchmark. Or select CBM tools that can predict how successful the student will be when he or she has to use a particular skill to accomplish a more involved task (e.g., testing phonics skills as an indicator of the ability to sound out unknown words later on a test of reading comprehension).
  
  
• Learn the language of statistics.  The average students are made up of the middle 50 percent of all students; 25 percent of these students are below the mean of the average students.  And so on.  A nationally normed test is trying to match students' scores to the bell-shaped curve, with the greatest number of students in the middle and fewer students having high or low scores.
  
  
• Consider using an outside group that can help you analyze your data, for example, the National Center on Student Progress Monitoring, which assesses students' academic performance and evaluates the effectiveness of instruction. It can be used with individual students or an entire class.

In Summary

Data management is a very powerful tool and can be used to mold a school system into a highly developed learning mechanism. I believe the school system needs to define two key points in data management as we look at the student:

• The point where general education intervention starts
• The point where special education starts

With these two points defined, we have a basis for providing the level of instructional intervention to help students before they fail and a means for developing a continuum of services that keeps intensifying the interventions so that no student fails.

Related Links

National Center on Student Progress Monitoring - To meet the challenges of implementing effective progress monitoring, the Office of Special Education Programs (OSEP) has funded the National Center on Student Progress Monitoring Web site. 

Data-Based Decision Making: Resources for Educators - This Web site provides information for educators to use when developing a school improvement team as well as "how-to," steps, resources, and a glossary on data-based decision making.

Is It the Mantra of the Month or Does It Have Staying Power? - This article talks about data-driven decision making as a diagnostic tool that encourages teachers to tailor instruction to student needs. (The Journal, May 2003)

Scrubbing Data for D3M - This article recommends ways to make sure you have top quality data. (The Journal, October 2005)

About the Author
Ron Benner is in his sixth year as a member of the NEA IDEA Resource Cadre and he is currently working as a school psychologist in the Bridgeport Public Schools in Bridgeport, Connecticut. He taught special education for 16½ years in several Connecticut school districts.