Measures of Student Growth: Rhode Island
Teacher and Principal Evaluation Policy
Note
The data and analysis on this page is from 2019. View and download the most recent policy data and analysis on Measures of Student Growth in Rhode Island from the State of the States 2022: Teacher and Principal Evaluation Policies report.
Analysis of Rhode Island's policies
Impact of Student Growth: Rhode Island requires 30 percent of a teacher's overall evaluation rating to be comprised of student learning. A teacher's assignment determines which measure(s) will be used to assess impact on student learning: Student Learning Objectives (SLOs), Student Outcome Objectives (SOOs), and/or the Rhode Island Growth Model (RIGM).
State's Role in Evaluation System: Rhode Island has developed the Rhode Island Model, but districts may design their own system with state approval. However, district-developed systems must adopt the state model for SLO ratings.
Recommendations for Rhode Island
Due to Rhode Island's strong policies in this area, no recommendations are provided.
State response to our analysis
Rhode Island recognized the factual accuracy of this analysis. The state added that it has engaged in pilots of new models for measuring student learning. Starting in the fall, all districts will have the option of using new models of student learning, including an embedded practice model and student growth goals. Student learning will continue to weigh at least 30 percent in educator evaluations.
Although educators could incorporate Rhode Island Growth Model data in their SLOs or other measures of student learning, the Rhode Island Growth Model data are not a separate measure of student learning integrated into educator evaluations. A new edition of the Rhode Island Model guidebook will be posted in the summer of 2019.
Updated: June 2019
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How we graded
7A: Measures of Student Growth
- Student Growth: The state should require:
- That districts use an evaluation instrument that includes objective student growth measure
- Full credit: The state will earn full credit if it requires teacher evaluations to include objective measures of student growth.
Research rationale
Many factors should be considered in formally evaluating a teacher; however, nothing is more important than effectiveness in the classroom. Value-added models are an important tool for measuring student achievement and school effectiveness.[1] These models have the ability to measure individual students' learning gains, controlling for students' previous knowledge and background characteristics. While some research suggests value-added models are subject to bias and statistical limitations,[2] rich data and strong controls can eliminate error and bias.[3] In the area of teacher quality, examining student growth offers a fairer and potentially more meaningful way to evaluate a teacher's effectiveness than other methods schools use.
Unfortunately, districts have used many evaluation instruments, including some mandated by states, which are structured so that teachers can earn a satisfactory rating without any evidence that they are sufficiently advancing student learning in the classroom.[4] Teacher evaluation instruments should include factors that combine both human judgment and objective measures of student learning.[5]
[1] Hanushek, E. A., & Hoxby, C. M. (2005). Developing value-added measures for teachers and schools. Reforming Education in Arkansas, 99-104.; Clotfelter, C. & Ladd, H. F. (1996). Recognizing and rewarding success in public schools. In H. Ladd (Ed.), Holding schools accountable: Performance based reform in education (pp. 23-64). Washington, DC: Brookings Institution Press.; Ladd, H. F., & Walsh, R. P. (2002). Implementing value-added measures of school effectiveness: Getting the incentives right. Economics of Education Review, 21(1), 1-17.; Meyer, R. H. (1996). Value-added indicators of school performance. In E. A. Hanushek (Ed.), Improving America's schools: The role of incentives, (pp. 197-223). Washington, D.C.: National Academy Press.; Braun, H. I. (2005). Using student progress to evaluate teachers: A primer on value-added models. Educational Testing Service.
[2] Rothstein, J. (2009). Student sorting and bias in value-added estimation: Selection on observables and unobservables. Education, 4(4), 537-571.; 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.; Darling-Hammond, L., Amrein-Beardsley, A., Haertel, E., & Rothstein, J. (2012). Evaluating teacher evaluation. Phi Delta Kappan, 93(6), 8-15.; McCaffrey, D. F., Lockwood, J. R., Koretz, D. M., & Hamilton, L. S. (2003). Evaluating value-added models for teacher accountability. Monograph. Santa Monica, CA: RAND Corporation.
[3] Chetty, R., Friedman, J. N., & Rockoff, J. E. (2014). Measuring the impacts of teachers II: Teacher value-added and student outcomes in adulthood. The American Economic Review, 104(9), 2633-2679.; 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.; Chetty, R., Friedman, J. N., & Rockoff, J. E. (2014). Measuring the impacts of teachers I: Evaluating bias in teacher value-added estimates. The American Economic Review, 104(9), 2593-2632.
[4] Weisberg, D., Sexton, S., Mulhern, J., Keeling, D., Schunck, J., Palcisco, A., & Morgan, K. (2009). The widget effect: Our national failure to acknowledge and act on differences in teacher effectiveness. New Teacher Project.; Glazerman, S., Loeb, S., Goldhaber, D., Staiger, D., Raudenbush, S., & Whitehurst, G. (2010). Evaluating teachers: The important role of value-added. Washington, D.C.: Brookings Institution.
[5] Kane, T. J., Taylor, E. S., Tyler, J. H., & Wooten, A. L. (2011). Identifying effective classroom practices using student achievement data. Journal of Human Resources, 46(3), 587-613.; Taylor, E. S., & Tyler, J. H. (2012). The effect of evaluation on teacher performance. The American Economic Review, 102(7), 3628-3651.