Value-added approaches for attributing student growth to teachers often use weighted estimates of building-level factors based on “typical” schools to represent a range of community, school, and other variables related to teacher and student work that are not easily measured directly. This study examines whether such estimates are likely to be accurate in “outlier” schools where building-level characteristics, such as demographics and faculty qualifications, are at the outer edges of the distribution of schools on which the “typical school” estimates are based. We examined whether building-level factors correlate with grade-level ratings in one of the most widely used approaches to value-added modeling, thus impacting interpretation of value-added ratings of teachers. Urban schools may be particularly affected by findings that reliable interpretation of a model using typical school estimates is affected by aspects of the school, even when using a weighted model. More correlations were found than would be expected by chance, many fairly large. Correlations tend to cluster around particular variables, possibly an effect of system accommodations for demographic or economic factors. A greater range and number of correlations were found for mathematics than reading. Finally, correlations and strength of relationships increase with grade level.

Amrein-Beardsley, A. (2008). Methodological concerns about the Educational Value-Added Assessment System. Educational Researcher, 37(2), 65-75.
Google Scholar | SAGE Journals
Ballou, D. (2002). Sizing up test scores. Education Next, 2(2), 10-15.
Google Scholar
Ballou, D., Sanders, W., Wright, P. (2004). Controlling for student background in value-added assessment of teachers. Journal of Educational and Behavioral Statistics, 29(1), 37-65.
Google Scholar | SAGE Journals | ISI
Bracey, G. W. (2004). Serious questions about the Tennessee value-added assessment system. Phi Delta Kappan, 85, 716-717.
Google Scholar | SAGE Journals | ISI
Bracey, G. W. (2006). Testing for growth. Principal, 85(4), 34-37.
Google Scholar
Braun, H. I. (1988). A new approach to avoiding problems of scale in interpreting trends in mental measurement data. Journal of Educational Measurement, 25(3), 171-191.
Google Scholar | Crossref
Coleman, J. S., Campbell, E. Q., Hobson, C. J., McPartland, J., Mood, A. M., Weinfeld, F. D., York, R. L. (1966). Equality of educational opportunity. Washington, DC: U.S. Government Printing Office.
Google Scholar
Darling-Hammond, L., Holtzman, D. J., Gatlin, S. J., Heilig, J. V. (2005). Does teacher preparation matter? Education Policy Analysis Archives, 13, 1-47.
Google Scholar
Dronkers, J., Robert, P. (2008). Differences in scholastic achievement of public, private government-dependent, and private independent schools: A cross-national analysis. Educational Policy, 22, 541-577.
Google Scholar | SAGE Journals
Dworkin, A.G., Haney, C.A., Dworkin, R.J., Telschow, R.L. (1990). Stress and illness behavior among urban public school teachers. Educational Administration Quarterly, Vol. 26, No. 1, pp. 60-72.
Google Scholar | SAGE Journals
Franco, S. (2006). The relationships among building-level school and non-school factors and value-added scores in Ohio (Unpublished doctoral dissertation). University of Cincinnati, Cincinnati, OH.
Google Scholar
Goddard, R. D., Sweetland, S. R., Hoy, W. K. (2000). Academic emphasis of urban elementary schools and student achievement in reading and mathematics: A multilevel analysis. Educational Administration Quarterly, 36, 683-702.
Google Scholar | SAGE Journals | ISI
Gong, B., Perie, M., Dunn, J. (2006). Using student longitudinal growth measures for school accountability under No Child Left Behind: An update to inform design decisions. Center for Assessment: 9/18/06. Available online at: http://www.nciea.org/publications/GrowthModelUpdate_BGMAPJD07.pdf
Google Scholar
Hershberg, T., Adams Simon, V., Kruger, B. L. (2004). The revelations of value-added. School Administrator. Retrieved from http://www.aasa.org/publications/saarticledetail.cfm?ItemNumber=1060
Google Scholar
Hershberg, T., Lea-Kruger, B., Adams Simon, V. (2004). The revelations of value-added: an assessment model that measures student growth in ways that NCLB fails to do. School Administrator, 61(11).
Google Scholar
Hoy, W. K., Miskel, C. W. (1996). Educational administration: Theory into practice (5th ed.). New York: McGraw-Hill.
Google Scholar
Jencks, C. (1972). Inequality: A reassessment of the effect of family and schooling in America. New York, NY: Basic Books.
Google Scholar
Kirk, R. E. (1995), Experimental Design: Procedures for the Behavioral Sciences (3rd ed.), Pacific Grove, CA: Brooks/Cole.
Google Scholar
Kupermintz, H. (2003). Teacher effects and teacher effectiveness: A validity investigation of the Tennessee value added assessment system. Educational Evaluation and Policy Analysis, 25, 287-298.
Google Scholar | SAGE Journals | ISI
Lee, J. (2006). Tracking achievement gaps and assessing the impact of NCLB on the gaps: An in-depth look into national and state reading and math outcome trends (The Civil Rights Project at Harvard University). Cambridge, MA: Harvard Education.
Google Scholar
Linn, R. L. (2004). Accountability models. In Fuhrman, S. H., Elmore, R. F. (Eds.), Redesigning accountability systems for education (pp. 73-95). New York, NY: Teacher’s College, Columbia University.
Google Scholar
Lockwood, J. R. (2002). Uncertainty in rank estimation: Implications for value-added modeling accountability systems. Journal of Educational and Behavioral Statistics, 27, 255-270.
Google Scholar | SAGE Journals | ISI
McCaffrey, D. F., Lockwood, J. R., Koretz, D., Louis, T. A., Hamilton, L. (2004). Models for value-added modeling of teacher effects. Journal of Educational and Behavioral Statistics, 29(1), 67-101.
Google Scholar | SAGE Journals | ISI
McNeil, K. A., Newman, I., Kelly, F., McNeil, K. (1996). Testing research hypothesis with the general linear model. Carbondale: Southern Illinois University Press.
Google Scholar
Newman, I., Newman, C. (2000). A discussion of low r-squares: Concerns and uses. Educational Research Quarterly, 24(2), 3-9.
Google Scholar
No Child Left Behind Act, 20 U. S. C. § 6301 (2001).
Google Scholar
Norton, M. S. (1998). Teacher absenteeism: A growing dilemma in education. Contemporary Education, 69(2), 95-99.
Google Scholar
Nye, B., Konstantopoulos, S., Hedges, L.V. (2004). How large are teacher effects? Educational Evaluation and Policy Analysis, Vol. 26, No. 3, pp. 237-257. URL: http://www.jstor.org/stable/3699577
Google Scholar
Patrick, J.E. (1995). Correlation between administrative style and school climate. Technical research report. ERIC, online at: http://eric.ed.gov/PDFS/ED387853.pdf
Google Scholar
Raudenbush, S. W. (2004). What are value-added models estimating and what does this imply for statistical practice? Journal of Educational and Behavioral Statistics, 29(1), 121-129.
Google Scholar | SAGE Journals | ISI
Sanders, W. L. (2006, October 16). Comparisons among various educational assessment value-added models. Paper presented at The Power of Two—National Value-Added Conference, hosted by Battelle for Kids, Columbus, OH. Retrieved from http://www.talentedteachers.com/pubs/comparisons_models_sanders.pdf
Google Scholar
Sanders, W. L. (2004, June 10-13). A summary of conclusions drawn from longitudinal analyses of student achievement data over the past 22 years (1982-2004). Presentation to Governors Education Symposium Asheville, NC. Retrieved from http://www.sas.com/resources/asset/hunt_summary.pdf
Google Scholar
Sanders, W. L. (2003). Beyond No Child Left Behind. Paper presented at the 2003 Annual Meeting AERA, Chicago, IL. Retrieved from http://www.sas.com
Google Scholar
Sanders, W. L., Saxton, A. M., Horn, S. P. (1997). The Tennessee value-added assessment system, a quantitative, outcomes-based approach to educational measurement. In Millman, J. (Ed.), Grading teachers, grading school: Is student achievement a valid evaluation measure? (pp. 137-162). Thousand Oaks, CA: Corwin.
Google Scholar
Sanders, W. L., Horn, S. P. (1998). Research findings from the Tennessee Value-Added Assessment System (TVAAS) database: Implications for educational evaluation and research. Journal of Personnel Evaluation in Education, 12, 247-256.
Google Scholar | Crossref
Sanders, W. L., Rivers, J. C. (1996). Cumulative and residual effects of teachers on future student academic achievement (Research Progress Report). Knoxville: University of Tennessee Value-Added Research and Assessment Center.
Google Scholar
Schaeffer, B. (2004). Districts pilot value-added assessment: leaders in Ohio and Pennsylvania are making better sense of their school data. School Administrator, 61(11).
Google Scholar
Stevens, J., Zvoch, K. (2006). Issues in the implementation of longitudinal growth models for student achievement. In Lissitz, R. W. (Ed.) Longitudinal and value added models of student performance (pp. 170-209). Maple Grove, MN: JAM Press.
Google Scholar
Tabachnick, B. G., Fidell, L. S. (2001). Using multivariate statistics (4th ed.). Needham Heights, MA: Allyn and Bacon.
Google Scholar
Tekwe, C. D., Carter, R. L., Ma, C.-X., Algina, J., Lucase, M. E., Roth, J., . . . Resnick, M. B. (2004). An empirical comparison of statistical models for value-added assessment of school performance. Journal of Educational and Behavioral Statistics, 29(1), 11-36.
Google Scholar | SAGE Journals | ISI
Taylor, D.L., Tashakkori, A. (1994). Predicting teachers’ sense of efficacy and job satisfaction using school climate and participatory decision making. Paper presented at the Annual Meeting of the Southwest Educational Research Association (San Antonio, TX, 1994). Retrieved from ERIC: http://eric.ed.gov/PDFS/ED368702.pdf
Google Scholar
Wenglinsky, H. (2002). How schools matter: The link between teacher classroom practices and student academic performance. Education Policy Analysis Archives, 10(12). Retrieved from http://epaa.asu.edu/epaa/v10n12
Google Scholar
Witte, R. S., Witte, J. S. (2001). Statistics (6th ed.). Orlando, FL: Harcourt College.
Google Scholar
Wright, S. P., Sanders, W. L., Rivers, J. C. (2006). Measurement of academic growth of individual students toward variable and meaningful academic standards. In Lissitz, R. (Ed.), Longitudinal and value added models of student performance (pp. 385-406). Maple Grove, MN: JAM Press.
Google Scholar
Yeagley, R. (2007). Separating growth from value added: two academic models offer different tools for different purposes–measuring individual learning and measuring what affects learning. School Administrator, 64(1).
Google Scholar
Zvoch, K., Stevens, J. J. (2006). Longitudinal effects of school context and practice on middle school mathematics achievement. Journal of Educational Research, 99, 347.
Google Scholar | Crossref | ISI
View access options

My Account

Welcome
You do not have access to this content.



Chinese Institutions / 中国用户

Click the button below for the full-text content

请点击以下获取该全文

Institutional Access

does not have access to this content.

Purchase Content

24 hours online access to download content

Your Access Options


Purchase

EUS-article-ppv for $36.00

Article available in:

Related Articles

Citing articles: 1