Measuring Teacher Effectiveness in Gifted Education

2011 ◽  
Vol 22 (5) ◽  
pp. 750-770 ◽  
Author(s):  
Megan E. Welsh
Keyword(s):  
Teacher Effectiveness ◽  
Gifted Education ◽  
Evaluation System ◽  
Value Added ◽  
New Teacher ◽  
Pedagogical Content ◽  
Quality Instruction ◽  
Observation Systems ◽  
Value Added Models ◽  
New Teacher Evaluation

States and districts are under increasing pressure to evaluate the effectiveness of their teachers and to ensure that all students receive high-quality instruction. This article describes some of the challenges associated with current effectiveness approaches, including paper-and-pencil tests of pedagogical content knowledge, classroom observation systems, and value-added models. It proposes development of a new teacher evaluation system using a virtual reality environment and describes how innovations in educational measurement and technology can be used to develop an improved teacher effectiveness measure.

Rethinking Teacher Evaluation: A Conversation about Statistical Inferences and Value-Added Models

2013 ◽  
Vol 83 (2) ◽  
pp. 349-370 ◽  
Author(s):  
Kimberlee Callister Everson ◽  
Erika Feinauer ◽  
Richard Sudweeks
Keyword(s):  
Teacher Evaluation ◽  
Teacher Effectiveness ◽  
Value Added ◽  
Statistical Methodology ◽  
Current Standard ◽  
Accountability System ◽  
Statistical Inferences ◽  
Value Added Models ◽  
Value Added Modeling

In this article, the authors provide a methodological critique of the current standard of value-added modeling forwarded in educational policy contexts as a means of measuring teacher effectiveness. Conventional value-added estimates of teacher quality are attempts to determine to what degree a teacher would theoretically contribute, on average, to the test score gains of any student in the accountability population (i.e., district or state). Everson, Feinauer, and Sudweeks suggest an alternative statistical methodology, propensity score matching, which allows estimation of how well a teacher performs relative to teachers assigned comparable classes of students. This approach more closely fits the appropriate role of an accountability system: to estimate how well employees perform in the job to which they are actually assigned. It also has the benefit of requiring fewer statistical assumptions—assumptions that are frequently violated in value-added modeling. The authors conclude that this alternative method allows for more appropriate and policy-relevant inferences about the performance of teachers.

Does Student Sorting Invalidate Value-Added Models of Teacher Effectiveness? An Extended Analysis of the Rothstein Critique

2011 ◽  
Vol 6 (1) ◽  
pp. 18-42 ◽  
Author(s):  
Cory Koedel ◽  
Julian R. Betts
Keyword(s):  
Teacher Effectiveness ◽  
Value Added ◽  
Classroom Teaching ◽  
First Year ◽  
Value Added Models ◽  
Value Added Model ◽  
Extended Analysis ◽  
Research Questions ◽  
Value Added Modeling ◽  
Student Sorting

Value-added modeling continues to gain traction as a tool for measuring teacher performance. However, recent research questions the validity of the value-added approach by showing that it does not mitigate student-teacher sorting bias (its presumed primary benefit). Our study explores this critique in more detail. Although we find that estimated teacher effects from some value-added models are severely biased, we also show that a sufficiently complex value-added model that evaluates teachers over multiple years reduces the sorting bias problem to statistical insignificance. One implication of our findings is that data from the first year or two of classroom teaching for novice teachers may be insufficient to make reliable judgments about quality. Overall, our results suggest that in some cases value-added modeling will continue to provide useful information about the effectiveness of educational inputs.

scholarly journals Impact of Contextual Predictors on Value-Added Teacher Effectiveness Estimates

2020 ◽  
Vol 10 (12) ◽  
pp. 390
Author(s):  
Ismail Aslantas
Keyword(s):  
Teacher Effectiveness ◽  
Test Scores ◽  
Value Added ◽  
School Characteristics ◽  
School Life ◽  
Student Academic Performance ◽  
Value Added Models ◽  
Math Test ◽  
Math Test Scores ◽  
The Relationship

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.

Measuring Teacher Effectiveness Using Value-Added Models of High School Achievement

2016 ◽  
Vol 118 (13) ◽  
pp. 1-32
Author(s):  
Nandita G. Gawade ◽  
Robert H. Meyer
Keyword(s):  
High School ◽  
Teacher Effectiveness ◽  
School Achievement ◽  
School Context ◽  
Value Added ◽  
High School Achievement ◽  
Core Subjects ◽  
Value Added Models ◽  
Supplemental Course ◽  
Secondary Grades

This article uses empirical data to consider the consequences of particular characteristics of instruction and testing in high school for the modeling and estimation of value-added measures of school or teacher effectiveness. Unlike Mathematics and Reading for most elementary and middle school grades, there is a lack of annual testing of students in all secondary grades and subjects. The development of value-added models in high school is complicated by the resulting unavailability of direct measures of prior knowledge and readiness of the student for the relevant course. Another distinction between high school and earlier grades is the presence of greater differentiated instruction in high school caused by supplemental course requirements or by student self-selection into different courses. We show that the traditional value-added model used in NCLB grades and subjects can be generalized to the high school context. Specifically, prior-year test scores in related or core subjects can be used to control for differences in student aptitude for the course or subject being evaluated. Similarly, we can account for relevant differences in classroom characteristics—such as the average prior achievement of the students in the classroom—if they are assumed to be beyond a teacher's control.

Examining individual- and school-level predictors of principal adaptation to teacher evaluation reform in the United States: A two-year perspective

2018 ◽  
Vol 48 (2) ◽  
pp. 379-395 ◽  
Author(s):  
Alyson L Lavigne
Keyword(s):  
United States ◽  
Teacher Evaluation ◽  
Evaluation System ◽  
Online Survey ◽  
The United States ◽  
New Teacher ◽  
School Level ◽  
Achievement Data ◽  
New Teacher Evaluation ◽  
Over Time

New teacher evaluation reform efforts in the United States hold principals accountable for improving teaching and learning. Yet little is known about how effective principals are at these instructional leadership tasks or how principals experience and adapt to the demands of teacher evaluation reform over time. In the current study, principals ( n = 78) in a Race to the Top state—Illinois—completed an online survey after the first and second year of implementation of a new teacher evaluation system. Principals felt significantly more confident in how to conduct formal classroom observations, placed more value on student achievement data, and placed less value on additional artifacts over time. Individual- and school-level factors were related to some aspects of principals’ adaptations over time. Implications are discussed.

The Implications of Summer Learning Loss for Value-Added Estimates of Teacher Effectiveness

2016 ◽  
Vol 32 (1) ◽  
pp. 55-85 ◽  
Author(s):  
Seth Gershenson ◽  
Michael S. Hayes
Keyword(s):  
Teacher Effectiveness ◽  
Test Scores ◽  
Value Added ◽  
The United States ◽  
Summer Learning Loss ◽  
Learning Loss ◽  
Summer Learning ◽  
School Year ◽  
Value Added Models ◽  
Nationally Representative

School districts across the United States increasingly use value-added models (VAMs) to evaluate teachers. In practice, VAMs typically rely on lagged test scores from the previous academic year, which necessarily conflate summer with school-year learning and potentially bias estimates of teacher effectiveness. We investigate the practical implications of this problem by comparing estimates from “cross-year” VAMs with those from arguably more valid “within-year” VAMs using fall and spring test scores from the nationally representative Early Childhood Longitudinal Study–Kindergarten Cohort (ECLS-K). “Cross-year” and “within-year” VAMs frequently yield significant differences that remain even after conditioning on participation in summer activities.

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