Larry Cuban on School Reform and Classroom Practice
Much has already been written on the U.S. obsession with standardized test scores. Add to the obsession the passionate belief that policymakers who gather, digest, and use a vast array of numbers can reshape teaching practices.
I refer to data-driven instruction–a way of making teaching less subjective, more objective, less experience-based, more scientific. Ultimately, a reform that will make teaching systematic and effective. Standardized test scores, dropout figures, percentages of non-native speakers proficient in English–are collected, disaggregated by ethnicity and school grade, and analyzed. Then with access to data warehouses, staff can obtain electronic packets of student performance data that can be used to make instructional decisions to increase academic performance. Data-driven instruction, advocates say, is scientific and consistent with how successful businesses have used data for decades in making decisions that increased their productivity.
Not a new idea. Teachers had always assessed learning informally before state- and district-designed tests…
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