Rotten Apples: An Investigation of the Prevalence and Predictors of Teacher CheatingBrian A. Jacob, Steven D. Levitt
NBER Working Paper No. 9413 We develop an algorithm for detecting teacher cheating that combines information on unexpected test score fluctuations and suspicious patterns of answers for students in a classroom. Using data from the Chicago Public Schools, we estimate that serious cases of teacher or administrator cheating on standardized tests occur in a minimum of 4-5 percent of elementary school classrooms annually. Moreover, the observed frequency of cheating appears to respond strongly to relatively minor changes in incentives. Our results highlight the fact that incentive systems, especially those with bright line rules, often induce behavioral distortions such as cheating. Statistical analysis, however, may provide a means of detecting illicit acts, despite the best attempts of perpetrators to keep them clandestine. A non-technical summary of this paper is available in the July 2003 NBER Digest.
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Machine-readable bibliographic record - MARC, RIS, BibTeX Document Object Identifier (DOI): 10.3386/w9413 Published: Jacob, Brian A. and Steven D. Levitt. "Rotten Apples: An Investigation Of The Prevalence And Predictors Of Teacher Cheating," Quarterly Journal of Economics, 2003, v118(3,Aug), 843-878. citation courtesy of Users who downloaded this paper also downloaded* these:
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