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Multidimensional Assessment of Value Added by Teachers to Real-World Outcomes

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  • Jennifer Broatch
  • Sharon Lohr

Abstract

Measuring teacher effectiveness is challenging since no direct estimate exists; teacher effectiveness can be measured only indirectly through student responses. Traditional value-added assessment (VAA) models generally attempt to estimate the value that an individual teacher adds to students' knowledge as measured by scores on successive administrations of a standardized test. Such responses, however, do not reflect the long-term contribution of a teacher to real-world student outcomes such as graduation, and cannot be used in most university settings where standardized tests are not given. In this paper, the authors develop a multiresponse approach to VAA models that allows responses to be either continuous or categorical. This approach leads to multidimensional estimates of value added by teachers and allows the correlations among those dimensions to be explored. The authors derive sufficient conditions for maximum likelihood estimators to be consistent and asymptotically normally distributed. The authors then demonstrate how to use SAS software to calculate estimates. The models are applied to university data from 2001 to 2008 on calculus instruction and graduation in a science or engineering field.

Suggested Citation

  • Jennifer Broatch & Sharon Lohr, 2012. "Multidimensional Assessment of Value Added by Teachers to Real-World Outcomes," Journal of Educational and Behavioral Statistics, , vol. 37(2), pages 256-277, April.
    • Handle: RePEc:sae:jedbes:v:37:y:2012:i:2:p:256-277
    DOI: 10.3102/1076998610396900
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    References listed on IDEAS

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    1. Louis T. Mariano & Daniel F. McCaffrey & J. R. Lockwood, 2010. "A Model for Teacher Effects From Longitudinal Data Without Assuming Vertical Scaling," Journal of Educational and Behavioral Statistics, , vol. 35(3), pages 253-279, June.
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    3. Harvey Goldstein & Sally Thomas, 1996. "Using Examination Results as Indicators of School and College Performance," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(1), pages 149-163, January.
    4. Germán Rodríguez & Noreen Goldman, 2001. "Improved estimation procedures for multilevel models with binary response: a case‐study," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(2), pages 339-355.
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    Cited by:

    1. Karl, Andrew T. & Yang, Yan & Lohr, Sharon L., 2013. "Efficient maximum likelihood estimation of multiple membership linear mixed models, with an application to educational value-added assessments," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 13-27.

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