Data: Maximize Your Mining--Sustained Student Achievement Is the Ultimate Goal of Data Mining, but Efficient Analysis Is Key to Getting There

This article looks at stages one and two of a three-stage process for success. Over the last decade, schools and districts have become increasingly sophisticated in their collection, storage, and analysis of data. And with the rise of NCLB, the focus of data analysis has been largely trained on ways...

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Bibliographic Details
Published in:Technology & learning 2005-04, Vol.25 (9)
Main Author: McIntire, Todd
Format: Magazinearticle
Language:English
Subjects:
Academic Achievement
Data Analysis
Educational Improvement
Formative Evaluation
No Child Left Behind Act 2001
Online Access:Get full text
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Summary:This article looks at stages one and two of a three-stage process for success. Over the last decade, schools and districts have become increasingly sophisticated in their collection, storage, and analysis of data. And with the rise of NCLB, the focus of data analysis has been largely trained on ways to help schools achieve Adequate Yearly Progress. The more important and greater challenge, however, remains in finding ways to harness data over the long term to raise student achievement in a consistent, sustained manner. Typically, schools move through three stages as they learn to link data to higher student achievement. Stage one consists of initial efforts to contextualize the many data sources available, stage two focuses on using data to maximize educational efficiency, and stage three represents a fundamental reorganization aimed at ensuring sustained higher levels of performance. This article describes best practices associated with stages one and two, toward the goal of helping schools and districts accelerate their progress toward stage three.
ISSN:1053-6728