Finally, education data are democratic. They affect everybody. They are available to everybody. Not too many years ago, education data were of little consequence. School systems did not collect much data and only a few people had access to them. That began to change in the wake of federally funded education programs accompanied by government oversight and enforcement. The pace of data collection increased following states' enactment of education accountability laws, and the dam broke with No Child Left Behind Act requirements.

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Now, education data are ubiquitous. Parents who plan to relocate to a new community or state can find multiple web sites that provide student performance and other data for a specific school. Under state and federal freedom of information laws, almost all education data that do not violate individual privacy rights are available to any determined citizen, policy analyst, advocate, or reporter who requests them.

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Yet, more data do not always result in better understanding. For example, states use somewhat different criteria to calculate student academic performance and dropouts, so reports that list data for all states can be misleading. Over time, states will increasingly use common criteria for data collection, but one should always be cautious not to make snap judgments based on reported data.

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Largely because of NCLB, teachers and administrators now have more data than ever about the academic performance of their students. Because schools must disaggregate this data so they reveal the relative performance of students by ethnicity, language group, disability, and gender, educators can identify which students are on pace towards performing proficiently by 2014, and which are not. While many educators are unhappy about various requirements of NCLB, one positive result is that the law causes them to focus more intently on low-performing students in demographic sub-groups.

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Of course, teachers and administrators do not need standardized test data to determine which students are falling behind. That is obvious to even the novice educator. The greater challenge is to determine the most effective ways to help students raise their performance levels. This calls for a deep examination of student performance data of all types, including that derived from close observation of a student's behavior in class, interaction with text, and learning style.

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Teachers will have more success in responding to the learning needs of low-performing students if they partner with colleagues in collecting and analyzing student performance data and understanding its implications for their practice. This is why NSDC believes such a process should be the first step in the professional development of educator learning teams. When teachers collaborate to understand learning problems that are common to many students, they can pool their experience, knowledge, and insight to frame a more valid analysis and develop more realistic interventions.

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But an honest review of data may suggest that to address students' learning needs more effectively, teachers must first pursue new learning. This requires teacher teams to approach data analysis with great humility, ready to acknowledge that limitations of their own practice may be one factor in problems of student learning. The teacher team can then move towards consensus about what it needs to learn, create its own learning goals, and develop a plan for pursuing them.

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Engaging teacher teams in using data to chart the course of their professional development will take time and persistence. Eventually, the value of doing so will be clear to school systems as evidence mounts of rising levels of teacher and student performance.

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Hayes Mizell is NSDC's distinguished senior fellow.

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