Volatility in School Test Scores: Implications for Test-Based Accountability Systems

By Thomas J. Kane, Douglas O. Staiger. 2002

284 citations recorded by the source corpus.

Subfields: Education, Information Systems and Management

View Paper: https://www.semanticscholar.org/paper/f65ce9993cd74414b0a5b81877df80063788eb03

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Citations in the corpus

Different Tests, Different Answers (2011, background): “Y it ð4Þ This classroom-level error, yt, can arise for a variety of reasons, such as a disruptive student in the class on test day, a teacher who inadvertently gives the students an extra 5 minutes on a section, or, as suggested by Kane and Staiger (2002), a dog barking in the parking lot.”
Principals as Agents: Subjective Performance Measurement in Education (2005, background): “4 For examples of studies that examine accountability programs within education, see Jacob 2005, Kane and Staiger 2002, Figlio and Lucas 2004, Figlio and Winicki, forthcoming.”
Incentives and Test-Based Accountability in Education (2011, background): “There is also strong evidence of random year-to-year fluctuations in student performance even at the school level, perhaps because one year the test happens to ask more questions that were covered in the school’s curriculum or because of common environmental factors, such as whether there was an imp”
Do school accountability systems make it more difficult for low-performing schools to attract and retain high-quality teachers? (2004, background): “4 At the same time, gain scores are potentially problematic in that the possibility of large random errors means that the amount of true information may be small relative to the total variation in the gain scores ( Kane and Staiger, 2002 ).”
Error Rates in Measuring Teacher and School Performance Based on Student Test Score Gains (2010, background): “2009; Goldhaber and Hansen 2008) or small to medium-sized school grade-level teams (Kane and Staiger 2002b).”
Charter School Quality and Parental Decision Making With School Choice (2005, unknown): “As Kane and Staiger (2002) and Jacob and Lefgren (2005, 2006) point out, even in the absence of confounding influences, school quality estimates capture both random error and true effects of schools.”
The Practical Relevance of Accountability Systems for School Improvement: A Descriptive Analysis of California Schools (2007, background): “Measurement errors have been found to make reliable classifications for schools with typically small API movements and small populations uncertain ( Kane & Staiger, 2002 ).”
Valuing School Quality Using Boundary Discontinuities. CEE DP 132. (2013, background): “assigned to house postcodes are highly serially correlated and short-run changes are likely to be uninformative about school quality (Kane and Staiger 2002).”
The Distribution of Teacher Quality and Implications for Policy (2012, methodology): “Other analyses have emphasized the importance of measurement error in using test outcome data (e.g., Kane & Staiger 2002, McCaffrey et al. 2009).”
Teacher Quality and Learning Outcomes in Kindergarten (2016, methodology): “21 This is analogous to the empirical Bayes approach in Kane and Staiger (2002) and many subsequent papers, but our calculation of the variance of the sampling error explicitly accounts for the fact that the classroom effects are demeaned within each school, and that the within-school mean may also…”