State Data Systems: Maine

Identifying Effective Teachers Policy

Look at National Findings

Goal

The state should have a data system that contributes some of the evidence needed to assess teacher effectiveness.

Meets goal in part

Suggested Citation:
National Council on Teacher Quality. (2011). State Data Systems: Maine results. State Teacher Policy Database. [Data set].
Retrieved from: https://www.nctq.org/yearbook/state/ME-State-Data-Systems-8

Analysis of Maine's policies

Maine does not have a data system that can be used to provide evidence of teacher effectiveness.

However, Maine does have two of three necessary elements that would allow for the development of a student- and teacher-level longitudinal data system. The state has assigned unique student identifiers that connect student data across key databases across years, and it has the capacity to match student test records from year to year in order to measure student academic growth.

Although Maine assigns teacher identification numbers, it cannot match individual teacher records with individual student records.

Recommendations for Maine

Develop capacity of state data system.
Maine should ensure that its state data system is able to match individual teacher records with individual student records.

Develop a clear definition of "teacher of record."
Maine has not yet established a definition of teacher of record, which is essential in order to use the student-data link for teacher evaluation and related purposes. To ensure that data provided through the state data system are actionable and reliable, Maine should articulate a definition of teacher of record and require its consistent use throughout the state.

State response to our analysis

Maine pointed out that it is the recipient of a multi-year, multi-million-dollar grant for the development of its state longitudinal data system (SLDS). The state added that its growth model has been developed, and it enables parents, schools, districts and the state to understand how individual students are progressing from year to year and provides a common measure to show how much growth is needed for each student to reach state standards. This data source is designed to enable the match of individual student records with individual teacher records.

Evaluation of Effectiveness

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Delivering Well Prepared Teachers

Expanding the Pool of Teachers

Identifying Effective Teachers

Retaining Effective Teachers

Exiting Ineffective Teachers

Research rationale

The Data Quality Campaign tracks the development of states' longitudinal data systems by reporting annually on states' inclusion of 10 elements in their data systems. Among these 10 elements are the three key elements (Elements 1, 3 and 5) that NCTQ has identified as being fundamental to the development of value-added assessment. For more information, see http://www.dataqualitycampaign.org.

For information about the use of student-growth models to report on student-achievement gains at the school level, see P. Schochet and H. Chiang, "Error Rates in Measuring Teacher and School Performance Based on Student Test Score Gains." Mathematica Policy Research. Department of Education (2010); as well as The Commission on No Child Left Behind, "Commission Staff Research Report: Growth Models, An Examination Within the Context of NCLB," Beyond NCLB, 2007.

For information about the differences between accountability models, including the differences between growth models and value-added growth models, see Pete Goldschmidt, et al., "Policymakers' Guide to Growth Models for School Accountability: How Do Accountability Models Differ?" Council of Chief State School Officers' Report, 2005 at: http://www.ccsso.org/publications/details.cfm?PublicationID=287

For information regarding the methodologies and utility of value-added analysis see, C. Koedel and J. Betts, "Does Student Sorting Invalidate Value-Added Models of Teacher Effectiveness? An Extended Analysis of the Rothstein Critique." Education Finance and Policy Vol. 6 No. 1 (2011), D. Goldhaber and M. Hansen, "Assessing the Potential of Using Value-Added Estimates of Teacher Job Performance for Making Tenure Decisions." Urban Institute (2010), and S. Glazerman et al, "Evaluating Teachers; The Important Role of Value-Added." Brookings Brown Center Task Group on Teacher Quality (2011); Glazerman, Steven et. al., Passing Muster: Evaluating Teacher Evaluation Systems, The Brookings Brown Center Task Group on Teacher Quality (2011); Harris, D.N. (2009). "Teacher value-added: Don't end the search before it starts," Journal of Policy Analysis and Management, 28(4), pp. 693-699. Hill, H.C. (2009). "Evaluating value-added models: A validity argument approach," Journal of Policy Analysis and Management, 28(4), pp. 700-709; Kane, T.J. & Staiger, D.O. (2008). Estimating teacher impacts on student achievement: An experimental evaluation. NBER Working Paper W14607. Cambridge, MA: National Bureau of Economic Research.

There is no shortage of studies using value-added methodologies by researchers including Thomas J. Kane, Eric Hanushek, Steven Rivkin, Jonah E. Rockoff and Jessie Rothstein. See also Kane, T.J. 2008. Estimating teacher impacts on student achievement: An experimental evaluation. Working Paper 14607. Cambridge, MA: National Bureau of Economic Research; Hanushek, Erik A. and Steven G. Rivkin. "Generalizations about using value-added measures of teacher quality." American Economic Review (May 2010); Rothstein, Jesse. 2010. "Teacher Quality in Educational Production: Tracking, Decay, and Student Achievement." Quarterly Journal of Economics, 25(1); Kane, Thomas J. and Douglas O. Staiger. 2008. "Estimating Teacher Impacts on Student Achievement: An Experimental Evaluation." National Bureau of Economic Research W14607, December. Rivkin, Steven G.; Eric A. Hanushek and John F. Kain. 2005. "Teachers, Schools, and Academic Achievement." Econometrica, 73(2), pp. 417-58; Hanushek, Eric A. 2010. "The Difference is Teacher Quality." In Waiting for "Superman": How We Can Save America's Failing Public Schools, Karl Weber, ed. New York: Public Affairs.

See also NCTQ's "If Wishes Were Horses" by Kate Walsh at: http://www.nctq.org/p/publications/docs/wishes_horses_20080316034426.pdf and the National Center on Performance Incentives at: www.performanceincentives.org.

For information about the limitations of value-added analysis, see Jesse Rothstein, "Do Value-Added Models Add Value? Tracking, Fixed Effects, and Casual Inference." Princeton University and NBER. (2007) as well as Dale Ballou, "Value-added Assessment: Lessons from Tennessee," Value Added Models in Education: Theory and Applications, ed. Robert W. Lissitz (Maple Grove, MN: JAM Press, 2005).See also Dale Ballou, "Sizing Up Test Scores," Education Next, Summer 2002; 2(2).

State Teacher Policy