Dorn, Sherman
Individual repository of Sherman Dorn, Professor, Mary Lou Fulton Teachers College. In my scholarship, I trace how society defines school problems and how those definitions shape education policy. In my first major research project, I documented that dropping out became defined as a crisis in the 1960s when the proportion of teens graduating from high school had been rising for years. I have written on various topics on special education, from the fuzzy public-private divide to how the mass culture of test-prep undermines formative assessment. My book on accountability explores how we have come to distrust schoolteachers but trust test scores.
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- All Subjects: Bayesian statistical decision theory
- All Subjects: Nation-building
This paper presents a Bayesian framework for evaluative classification. Current education policy debates center on arguments about whether and how to use student test score data in school and personnel evaluation. Proponents of such use argue that refusing to use data violates both the public’s need to hold schools accountable when they use taxpayer dollars and students’ right to educational opportunities. Opponents of formulaic use of test-score data argue that most standardized test data is susceptible to fatal technical flaws, is a partial picture of student achievement, and leads to behavior that corrupts the measures.
A Bayesian perspective on summative ordinal classification is a possible framework for combining quantitative outcome data for students with the qualitative types of evaluation that critics of high-stakes testing advocate. This paper describes the key characteristics of a Bayesian perspective on classification, describes a method to translate a naïve Bayesian classifier into a point-based system for evaluation, and draws conclusions from the comparison on the construction of algorithmic (including point-based) systems that could capture the political and practical benefits of a Bayesian approach. The most important practical conclusion is that point-based systems with fixed components and weights cannot capture the dynamic and political benefits of a reciprocal relationship between professional judgment and quantitative student outcome data.
The spread of academic testing for accountability purposes in multiple countries has obscured at least two historical purposes of academic testing: community ritual and management of the social structure. Testing for accountability is very different from the purpose of academic challenges one can identify in community “examinations” in 19th century North America, or exams’ controlling access to the civil service in Imperial China. Rather than testing for ritual or access to mobility, the modern uses of testing are much closer to the state-building project of a tax census, such as the Domesday Book of medieval Britain after the Norman Invasion, the social engineering projects described in James Scott's Seeing like a State (1998), or the “mapping the world” project that David Nye described in America as Second Creation (2004). This paper will explore both the instrumental and cultural differences among testing as ritual, testing as mobility control, and testing as state-building.