Assessing the Potential of Using Value Added-Estimates of Teacher Job Performance for Making Tenure Decisions

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Abstract

Using individual teacher and student-level longitudinal data from North Carolina, this research brief presents selected findings from work examining the stability of value-added model estimates of teacher effectiveness, focusing on their implication for teacher tenure policies and making high stakes personnel decisions. Findings show year-to-year correlations in teacher effects are modest, but pre-tenure estimates of teacher job performance do predict estimated post-tenure performance in both math and reading, and would therefore seem to be a reasonable metric to use as a factor in making substantive teacher selection decisions.

Introduction

USING TEACHER EFFECTS ESTIMATES FOR HIGH-STAKES PERSONNEL DECISIONS

Well over a decade into the standards movement, the idea of holding schools accountable for results is now being pushed to a logical, if controversial, end point: the implementation of policies aimed at holding individual teachers (not just schools) accountable for results. Some have called for reforms such as pay for performance or changes to teacher tenure to make it easier to reward and sanction teachers based on their classroom performance. The focus on teachers is more than just a logical extension of the standards movement. It is supported by two important findings from teacher quality research: teacher quality (as measured by teacher contributions toward student gains on tests) is the most important schooling factor when it comes to improving student achievement, and teacher quality is a highly variable commodity—some teachers are simply much better than others. These findings, coupled with a large body of research suggesting that typical characteristics used to determine employment and pay (such as experience and credentials) are not strongly correlated with effective teaching, are good reasons to move the policy discussion toward a focus on individual teacher performance.

The research on teacher effects (the terms "teacher effects" and "teacher job performance" are used interchangeably here) finds considerable variation in estimated job performance, suggesting there is great potential for improving education through teacher workforce accountability policies such as teacher tenure reforms, selective retention, salary incentives, and targeted professional development.¹ However, consensus about the right way to do this has been elusive. "Value-added" models (VAMs) seek to isolate the contribution that teachers make toward student achievement gains on tests and are increasingly being considered as a potential tool for evaluating teacher performance. The use of this metric is controversial, however?—not only because of disagreement about whether student test scores ought to be used to judge teachers, but also because, even among those that support this use of student tests, there is no consensus on the right statistical approach, especially when it comes to estimating the impacts of individual teachers.² Moreover, relatively few studies have focused on the stability of estimated teacher effects, which have important implications for the formation of productive teacher policies.³ For instance, if performance turns out to be an extremely stable characteristic, then measurement and accountability might best be used to weed out poor performers, as is suggested by Gordon and colleagues (2006). Alternatively, if actual performance (or our measures of it) tends to be an unstable characteristic—over time, across student types, or educational settings—then it may be necessary to rethink this direction for teacher-based accountability.

This research brief presents selected findings from work examining the stability of value-added model estimates of teacher effectiveness and their implication for tenure policies.⁴ In related work, Steve Rivkin (2007) explores the use of value-added models for estimating true teacher productivity, and Tim Sass (2008) assesses the stability of value-added measures of teacher productivity and their implications for pay-for-performance policies.

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