Education Drivers

Value Added

Value-added modeling (VAM) is a statistical approach that provides quantitative performance measures for monitoring and evaluating schools and other aspects of the education system. VAM comprises a collection of complex statistical techniques that use standardized test scores to estimate the effects of individual schools or teachers on student performance. 

Value-added modeling (VAM) is a statistical approach that provides quantitative performance measures for monitoring and evaluating schools and other aspects of the education system. VAM comprises a collection of complex statistical techniques that use standardized test scores to estimate the effects of individual schools or teachers on student performance. Although the VAM approach holds promise, serious technical issues have been raised regarding VAM as a high-stakes instrument in accountability initiatives. The key question remains: Can VAM scores of standardized test scores serve as a proxy for measuring teaching quality? To date, research on the efficacy of VAM is mixed. There is a body of research that supports VAM, but there is also a body of studies suggesting that model estimates are unstable over time and subject to bias and imprecision. A second issue with VAM is the sole use of standardized tests as a measure of student performance. Despite these valid concerns, VAM has been shown to be valuable in performance improvement efforts when used cautiously in combination with other measures of student performance such as end-of-course tests, final grades, and structured classroom observations.

Data Mining

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What is the relationship between teacher working conditions and school performance?
This inquiry looks at the effect of time on the job and the quality of a teacher's skills.
Keyworth, R. (2010). What is the relationship between teacher working conditions and school performance? Retrieved from what-is-relationship-between882.
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ASA statement on using value-added models for educational assessment

Value-Added Models (VAMs) has been embraced by many states and school districts as part of educational accountability systems. Value-Added Assessment (VAA) Models attempt to estimate effects of individual teachers or schools on student achievement while accounting for differences in student background. This paper provides a summary of the American Statistical Associations analysis of the efficacy of value-added modeling in education.

American Statistical Association. (2014). ASA statement on using value-added models for educational assessment. Alexandria, VA.

Teacher Preparation and Student Achievement.

This article examined the differences in effectiveness of teacher preparation programs that supply teachers to New York City schools.  One of the important findings is that preparation directly linked to practice benefits teachers in their first year.

Boyd, D. J., Grossman, P. L., Lankford, H., Loeb, S., & Wyckoff, J. (2009). Teacher Preparation and Student Achievement. Educational Evaluation & Policy Analysis, 31(4), 416-440.

Using Student Progress to Evaluate Teachers: A Primer on Value-Added Models. Policy Information Perspective.

This report is a lay person’s guide to value added modeling as a means of evaluating teacher performace.

Braun, H. I. (2005). Using Student Progress to Evaluate Teachers: A Primer on Value-Added Models. Policy Information Perspective. Educational Testing Service. Retrieved from http://files.eric.ed.gov/fulltext/ED529977.pdf

 

The Long-Term Impacts Of Teachers: Teacher Value-Added And Student Outcomes In Adulthood

This paper examines the issue of efficacy of value-added measures in evaluating teachers. This question is important in understanding whether value-added analysis provides unbiased estimates of teachers’ impact on student achievement and whether these teachers improve long-term student outcomes.

Chetty, R., Friedman, J. N., & Rockoff, J. E. (2011). The long-term impacts of teachers: Teacher value-added and student outcomes in adulthood (No. w17699). National Bureau of Economic Research.

Selecting growth measures for school and teacher evaluations: Should proportionality matter?

In this paper we take up the question of model choice and examine three competing approaches. The first approach, (SGPs) framework, eschews all controls for student covariates and schooling environments. The second approach, value-added models (VAMs), controls for student background characteristics and under some conditions can be used to identify the causal effects of schools and teachers. The third approach, also VAM-based, fully levels the playing field so that the correlation between school- and teacher-level growth measures and student demographics is essentially zero. We argue that the third approach is the most desirable for use in educational evaluation systems.

Ehlert, M., Koedel, C., Parsons, E., & Podgursky, M. (2013). Selecting growth measures for school and teacher evaluations: Should proportionality matter?. National Center for Analysis of Longitudinal Data in Education Research, 21.

Evidence for the need to more closely examine school effects in value-added modeling and related accountability policies

This paper evaluates the reasonableness of assumptions of weighted approaches to account for building level effects when value added modeling is used to evaluate teachers.  In urban schools and ultimately teachers in those schools were negatively impacted by using weighted models to account for building level effects.

Franco, M. S., & Seidel, K. (2014). Evidence for the need to more closely examine school effects in value-added modeling and related accountability policies. Education and Urban Society. Retrieved from http://journals.sagepub.com/doi/abs/10.1177/0013124511432306

Reliability and Validity of Inferences about Teachers Based on Student Scores

Policymakers and school administrators have embraced value-added models of teacher effectiveness as tools for educational improvement. Teacher value-added estimates may be viewed as complicated scores. This Paper examines the use of value-added modeling as a tool to identify effective teachers from ineffective instructors.

Haertel, E. H. (2013). Reliability and Validity of Inferences about Teachers Based on Student Scores. William H. Angoff Memorial Lecture Series. Educational Testing Service.

A Review of value-added models

This paper examines issues of value-added modeling. It describes what value-added modeling is and how it works in education.

Hibpshman, T. L. (2004). A Review of value-added models. Kentucky Education Professional Standards Board.

Estimating teacher impacts on student achievement: An experimental evaluation

This study used a random-assignment experiment in Los Angeles Unified School District to evaluate various non-experimental methods for estimating teacher effects on student test scores. Having estimated teacher effects during a pre-experimental period, the authors used these estimates to predict student achievement following random assignment of teachers to classrooms.

Kane, T. J., & Staiger, D. O. (2008). Estimating teacher impacts on student achievement: An experimental evaluation (No. w14607). National Bureau of Economic Research.

Have We Identified Effective Teachers? Validating Measures of Effective Teaching Using Random Assignment.

In this study the authors designed the Measures of Effective Teaching (MET) project to test replicable methods for identifying effective teachers. In past reports, the authors described three approaches to measuring different aspects of teaching: student surveys, classroom observations, and a teacher's track record of student achievement gains on state tests.

Kane, T. J., McCaffrey, D. F., Miller, T., & Staiger, D. O. (2013). Have We Identified Effective Teachers? Validating Measures of Effective Teaching Using Random Assignment. Research Paper. MET Project. Bill & Melinda Gates Foundation.

Identifying effective classroom practices using student achievement data

This paper combines information from classroom-based observations and measures of teachers' ability to improve student achievement as a step toward addressing these challenges. The results point to the promise of teacher evaluation systems that would use information from both classroom observations and student test scores to identify effective teachers.

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.

 

Value-added modeling: A review

This article provides a review of areas of agreement and disagreement of vaious aspects of value added modeling.

Koedel, C., Mihaly, K., & Rockoff, J. E. (2015). Value-added modeling: A review. Economics of Education Review. Retrieved from http://faculty.smu.edu/millimet/classes/eco7321/papers/koedel et al 2015.pdf

 

The politics and statistics of value-added modeling for accountability of teacher preparation programs

This paper reviews the evaluation of a value added model for evaluating teacher preparation programs in Texas.  The model produced statistically meaningful data but the results were sensitive to decisions about accountability critieria, the selection of teachers, and the selection of control variables.  Different decisions across each of these variables would impact the results of the value added modeling.

Lincove, J. A., Osborne, C., & Dillon…, A. (2014). The politics and statistics of value-added modeling for accountability of teacher preparation programs. … of Teacher Education. Retrieved from http://journals.sagepub.com/doi/abs/10.1177/0022487113504108

The promise and peril of using value-added modeling to measure teacher effectiveness

This article addresses the potential sources of bias that can be introduced into value added modeling by the decisions that are made about the  details of the model.  There is a call for a refinement of procedures used when applying value added modeling.

McCaffrey, D. F., Koretz, D., Lockwood, J. R., & Hamilton, L. S. (2004). The promise and peril of using value-added modeling to measure teacher effectiveness. rand.org. Retrieved from http://www.rand.org/pubs/research_briefs/RB9050

Evaluating Value-Added Models for Teacher Accountability. Monograph.

Value added modeling has become of interest to policymakers interested in evaluating teacher performance.  The authors argue that the models work well when the schools in the sample are homogenous but as heterogeneity of the student population  increases estimates of teacher effects are likely to confounded.

McCaffrey, D. F., Lockwood, J. R., Koretz, D. M., & Hamilton, L. S. (2003). Evaluating Value-Added Models for Teacher Accountability. Monograph. ERIC. Retrieved from http://eric.ed.gov/?id=ED529961

Models for value-added modeling of teacher effects

Value added modeling has become of interest to policymakers interested in evaluating teacher performance.  The authors argue that the models work well when the schools in the sample are homogenous but as heterogeneity of the student population  increases estimates of teacher effects are likely to confounded.

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. doi:10.3102/10769986029001067

Alternative student growth measures for teacher evaluation: Implementation experiences of early-adopting districts

This study examines implementation of alternative student growth measures in a sample of eight school districts that were early adopters of the measures. It builds on an earlier Region­ al Educational Laboratory Mid-Atlantic report that described the two types of alterna­tive student growth measures—alternative assessment–based value-added models and student learning objectives—in the early-adopting districts.

McCullough, M., English, B., Angus, M. H., & Gill, B. (2015). Alternative student growth measures for teacher evaluation: Implementation experiences of early-adopting districts (No. 8a9dfcb1bc6143608448114ea9b69d06). Mathematica Policy Research.

Where is the value in value-added modeling

This paper reviews the various issues and challenges associated with value added modeling.  It concludes with a discussion of how value added modeling  can be used in conjuction with other measures to identify teacher strengths and weaknesses.

Murphy, D. (2012). Where is the value in value-added modeling. 24–26 September 2014. Retrieved from http://educatoreffectiveness.pearsonassessments.com/downloads/viva_v1.pdf

Value-Added Assessment of Teacher Preparation: An Illustration of Emerging Technology

This paper describes one effort to use value added modeling to evaluate teacher preparation program in one state.

Noell, G. H., & Burns, J. L. (2006). Value-Added Assessment of Teacher Preparation: An Illustration of Emerging Technology. Journal of Teacher Education, 57(1), 37-50. doi:10.1177/0022487105284466

doi: 10.1177/0022487105284466

The legal and policy implications of value-added teacher assessment policies

This argument makes the case that policies that require states’ student test scores to account for 40-50% of the overall score of teacher performance in value added modeling may produce a significant number of teachers to be falsly identified as ineffective.  Using such value added models may leave school districts legally vulnerable to law suits.

Preston C. Green, Bruce D. Baker, and Joseph Oluwole, The Legal and Policy Implication of Value-Added Teacher Assessment Policies, 2012 BYU Educ. & L.J. 1 (2012).
Available at: http://digitalcommons.law.byu.edu/elj/vol2012/iss1/2

How teacher turnover harms student achievement

This study used a version of value added modeling to evaluate the impact of teacher turnover has on student achievement.

Ronfeldt, M., Lankford, H., Loeb, S., & Wyckoff, J. (2011). How Teacher Turnover Harms Student Achievement. National Bureau of Economic Research Working Paper Series, No. 17176. doi:10.3386/w17176

The Tennessee value-added assessment system (TVAAS): Mixed-model methodology in educational assessment

This paper describes the mixed method model Tennessee developed to evaluate teacher contributions to student achievement.  It desribes how they resolved some of the challenges to using value added modeling.

Sanders, W. L., & Horn, S. P. (1994). The Tennessee value-added assessment system (TVAAS): Mixed-model methodology in educational assessment. Journal of Personnel Evaluation in education. Retrieved from https://eric.ed.gov/?id=EJ498467

Cumulative and residual effects of teachers on future student academic achievement.

The Tennessee Value-Added Assessment System determines the effectiveness of school systems, schools, and teachers based on student academic growth over time. Research conducted utilizing data from the TVAAS database has shown that race, socioeconomic level, class size, and classroom heterogeneity are poor predictors of student academic growth. Rather, the effectiveness of the teacher is the major determinant of student academic progress.

Sanders, W. L., & Rivers, J. C. (1996). Cumulative and residual effects of teachers on future student academic achievement.

Measuring teaching using value-added modeling: The imperfect panacea

This paper attempts to untangle some of the competing claims about the value of value added modeling.  It concludes that it should not be used as the sole measure of teacher performance but should be part of a larger accountability system.

Scherrer, J. (2011). Measuring teaching using value-added modeling: The imperfect panacea. NASSP Bulletin. Retrieved from https://eric.ed.gov/?id=EJ938929.

Evaluating special educator effectiveness: Addressing issues inherent to value-added modeling

This paper addresses the unique challenges posed by special education when using value added modeling to evaluate teacher effectiveness.

Steinbrecher, T. D., Selig, J. P., Cosbey, J., & Thorstensen, B. I. (2014). Evaluating Special Educator Effectiveness. Exceptional Children, 80(3), 323-336. doi:10.1177/0014402914522425

 

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University of Pennsylvania: A Grand Bargain for Education Reform

This web site provides resources for educators to better under what value-added modeling is and how it works.

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