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State Data Systems: California

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.

Does not meet goal
Suggested Citation:
National Council on Teacher Quality. (2011). State Data Systems: California results. State Teacher Policy Database. [Data set].
Retrieved from: https://www.nctq.org/yearbook/state/CA-State-Data-Systems-8

Analysis of California's policies

California does not have a data system with the capacity to provide evidence of teacher effectiveness.

The state has yet to implement any of the three necessary elements of a student- and teacher-level longitudinal data system. It is in the initial stages of implementing a student data system (CALPADS) and is still in the development stage of the unique teacher identifier system (CALTIDES). When these two systems are fully implemented, California will be able to match individual student records with teacher records. 

Citation

Recommendations for California

Develop capacity of state data system.
California should ensure that its state data system is able to assign unique student identifiers that connect student data across key databases across years, and assign unique teacher identifiers that enable it to match individual teacher records with individual student records. It should also have the capacity to match student test records from year to year to measure academic growth. 

Develop a clear definition of "teacher of record."
A definition of teacher of record is necessary in order to use the student-teacher data link for the purpose of providing value-added evidence of teacher effectiveness. California defines the teacher of record as the person who is primarily responsible for the delivery of instruction, assignment of grades and certification of attendance. However, to ensure that data provided through the state data system are actionable and reliable, California should articulate a more distinct definition of teacher of record and require its consistent use throughout the state.

State response to our analysis

California recognized the factual accuracy of this analysis. The state added that in March 2006, the California Department of Education, in cooperation with the California Commission on Teacher Credentialing (CTC), was given authorization to begin the development of a California teacher data system, identified as the California Longitudinal Teacher Integrated Data Educational System (CALTIDES), which would have provided the data described above. Unfortunately, recent state budget action has halted the development of the CALTIDES system, so there is no current or projected time frame for either agency to collect these data.

    • Best practice
    • Meets goal
    • Nearly Meets goal
    • Meets goal in part
    • Meets a small part of goal
    • Does not meet goal

  • California

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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).

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