Impact of Contextual Predictors on Value-Added Teacher Effectiveness Estimates

It is widely believed that the teacher is one of the most important factors influencing a student’s success at school. In many countries, teachers’ salaries and promotion prospects are determined by their students’ performance. Value-added models (VAMs) are increasingly used to measure teacher effectiveness to reward or penalize teachers. The aim of this paper is to examine the relationship between teacher effectiveness and student academic performance, controlling for other contextual factors, such as student and school characteristics. The data are based on 7543 Grade 8 students matched with 230 teachers from one province in Turkey. To test how much progress in student academic achievement can be attributed to a teacher, a series of regression analyses were run including contextual predictors at the student, school and teacher/classroom level. The results show that approximately half of the differences in students’ math test scores can be explained by their prior attainment alone (47%). Other factors, such as teacher and school characteristics explain very little the variance in students’ test scores once the prior attainment is taken into account. This suggests that teachers add little to students’ later performance. The implication, therefore, is that any intervention to improve students’ achievement should be introduced much earlier in their school life. However, this does not mean that teachers are not important. Teachers are key to schools and student learning, even if they are not differentially effective from each other in the local (or any) school system. Therefore, systems that attempt to differentiate “effective” from “ineffective” teachers may not be fair to some teachers.

“Houston, We Have a Lawsuit”: A Cautionary Tale for the Implementation of Value-Added Models for High-Stakes Employment Decisions

Until recently, legal challenges to the use of value-added models (VAMs) in evaluation and teacher employment decisions in federal court had been unsuccessful. However, in May 2017 a federal court in Texas ruled that plaintiff-teachers established a viable federal constitutional claim to challenge the use of VAMs as a means for their termination in Houston Federation of Teachers v. Houston Independent School District. Houston represents a significant departure from prior federal court rulings that upheld the constitutionality of VAMs to terminate teachers on the basis of poor performance. The Houston court found that the districts’ refusals to release the underlying data of VAM ratings used to terminate those teachers violated the teachers’ procedural due process rights. By denying access to the code, teachers could not protect against the government’s making a mistaken deprivation of their property right to continued right to employment. The authors discuss Houston and its potential impact, limitations, and significance.

Putting teachers evaluation systems on the map: An overview of state’s teacher evaluation systems post–Every Student Succeeds Act

The Every Students Succeeds Act (ESSA) loosened the federal policy grip over states’ teacher accountability systems. We present information, collected via surveys sent to state department of education personnel, about all states’ teacher evaluation systems post–ESSA, while also highlighting differences before and after ESSA. We found that states have decreased their use of growth or value-added models (VAMs) within their teacher evaluation systems. In addition, many states are offering more alternatives for measuring the relationships between student achievement and teacher effectiveness besides using test score growth. State teacher evaluation plans also contain more language supporting formative teacher feedback. States are also allowing districts to develop and implement more unique teacher evaluation systems, while acknowledging challenges with states’ being able to support varied systems, as well as incomparable data across schools and districts in effect.

Policies and practices of promise in teacher evaluation: The introduction to the special issue

This introduction to the special issue on “Policies and Practices of Promise in Teacher Evaluation,” (1) presents the background and policy context surrounding the ongoing changes in U.S. states’ teacher evaluation systems (e.g., the decreased use of value-added models (VAM)s for teacher accountability purposes); (2) summarizes the two commentaries and seven research papers that were peer-reviewed and ultimately selected for inclusion in this special issue; and (3) discussess the relevance of these pieces in terms of each paper’s contribution to the general research on this topic and potential to inform educational policy, for the better, after the federal government’s passage of the Every Student Succeeds Act (ESSA, 2016).

Moving forward while looking back: Lessons learned from teacher evaluation litigation concerning Value-Added Models (VAMs)

The Every Student Succeeds Act (ESSA) appears to offer states and districts discretion to develop teacher evaluation policies, including those that may use Value Added Models (VAMs). While scholars are discussing this flexibility, limited attention has been paid to the potential role of the law in connection with the future use of VAMs in evaluation policy. While VAMs may be declining in use, several states require or permit them, making the continued assessment relevant. Moreover, given that VAMs were at the center of numerous high-profile lawsuits, assessing litigation outcomes in the context of ESSA is a useful exercise, particularly for jurisdictions that may use (or contemplate their use) of VAMs. Toward this end, this paper applies legal research methods and a law and policy framework to review lawsuits concerning VAMs to distill key principles for state and local policymakers.

Methodological Concerns About the Education Value-Added Assessment System (EVAAS): Validity, Reliability, and Bias

The Education Value-Added Assessment System (EVAAS), the value-added model (VAM) sold by the international business analytics software company SAS Institute Inc., is advertised as offering “precise, reliable and unbiased results that go far beyond what other simplistic [value-added] models found in the market today can provide.” In this study, we investigated these claims, as well as others pertaining to the validity or truthfulness of model output, by conducting analyses on more than 1,700 teachers’ EVAAS results (i.e., actual EVAAS output to which no other external scholars have had access prior) from the Houston Independent School District (HISD). We found the EVAAS to perform, overall, in line with other VAMs in terms of validity and reliability, although it yielded possibly more biased value-added estimates than other VAMs due to differences in teacher’s EVAAS scores based on school-level student composition factors.

Estimating Private School Premium for Primary School Children in Ethiopia: Evidence from Individual-level Panel Data

This article presents the first value-added model of private school effect in Ethiopia, using the unique Young Lives longitudinal data. I found a substantial and statistically significant private school premium (about 0.5 standard deviation) in Maths, but not in Peabody Picture Vocabulary Test (PPVT). Private school premium works for both low and high ability children. The results are robust to sorting on unobserved ability, grouping on lag structures and transfer between private and public schools. Combined with available contextual data, empirical evidence suggests that the effectiveness of private primary schools may be due to more learning time and teacher’s attention enjoyed by students. I also attempted to contribute methodologically to the literature by directly testing the structural assumption underpinning value-added models.

Learning More with Every Year: School Year Productivity and International Learning Divergence

I use unique child-level panel data from Ethiopia, India, Peru, and Vietnam, four developing countries with widely differing levels of student achievement, to study the extent to which differences in the productivity of primary schooling can explain international differences in human capital. I document, using identical tests of quantitative skills across countries, that although some cross-sectional gaps in test scores between these countries are evident at preschool ages, these grow substantially in the first 2–3 years of schooling. By the age of 8 years, differences are particularly stark between Vietnam and the other three countries. Using value-added models, and a regression-discontinuity design based on enrolment guidelines, I show that the causal effect of an extra grade of schooling on test scores is substantially higher in Vietnam by 0.25–0.4 standard deviations compared to the other countries. This differential productivity of a school year accounts for most of the cross-country achievement gap at 8 years of age. Equalizing the exposure to and the productivity of schooling closes the gap with Vietnam almost entirely for Peru and India and by ∼60% for Ethiopian students enrolled.