The Need for Better TQ Data |
RESPONDING TO NO CHILD LEFT BEHIND
States have had severe difficulties in responding to and reporting on TQ indicators mandated by NCLB. NCLB’s data mandates—to track annually the percentage of classes taught by “highly qualified” teachers and provide access to high-quality professional development—would appear to have the potential to catalyze state efforts to build data systems that readily could provide common data. However, this has not been the case. A recent U.S. General Accounting Office report (GAO524, 2003, p. 12) found that “states do not have the teaching quality data infrastructures that would allow them to track teacher qualifications according to the federal criteria for each subject taught.” Rather than investing in statewide TQ data systems, most states have allowed districts to self-report NCLB TQ data. Other states simply use an old-fashioned approach such as reviewing transcripts to determine if teachers were highly qualified. That was certainly the case in Alabama, where the State Department of Education had to hand review over 48,000 filed transcripts to determine if teachers met the highly qualified definition (CTQ, forthcoming). Even if data systems were in place, the tremendous variation in the definition and means of counting highly qualified teachers makes the data virtually unusable. In a 2004 report conducted by CTQ, Alabama and Tennessee reported that approximately one third of classes were taught by highly qualified teachers, whereas Georgia and North Carolina claimed about 90%. These discrepancies may be due to variances in the individual state’s definition or to measurement of highly qualified teachers. Thus, very little valid cross-state comparisons presently can be done, even by using the recent NCLB highly qualified teacher data.
We believe, however, that despite these problems with NCLB, the increased focus on accountability for both students and teachers will soon lead states and the federal government to this set of second-generation questions about teacher accountability, including the following:
- How can states develop more comprehensive measures of "highly qualified" teachers?
- What kinds of data must be gathered, housed, and linked to examine the distribution of teachers so that all students have access to competent and qualified teachers?
- How can different state agencies, universities, and school districts merge data in order to assess the effectiveness of teacher education and professional development programs?
- How can different stakeholders and constituents jointly develop the questions that need to be asked and use the data most effectively to drive needed improvements?
- How can states develop the research capacity to answer important questions about teacher preparation effectiveness?
Fortunately, with NCLB acting as a catalyst in concert with philanthropic investments and emerging research tools, three significant developments are emerging that should push policymakers to address these data infrastructure issues.
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Last updated: February 21, 2006