Central Office Supports for Data-Driven Talent Management Decisions

2017 ◽  
Vol 46 (1) ◽  
pp. 21-32 ◽  
Author(s):  
Jason A. Grissom ◽  
Mollie Rubin ◽  
Christine M. Neumerski ◽  
Marisa Cannata ◽  
Timothy A. Drake ◽  
...  
Keyword(s):  
Teacher Effectiveness ◽  
School Leaders ◽  
Data Use ◽  
Value Added ◽  
Talent Management ◽  
Survey Analysis ◽  
Management Decisions ◽  
Local Conditions ◽  
Central Offices ◽  
Charter Management Organizations

School districts increasingly push school leaders to utilize multiple measures of teacher effectiveness, such as observation ratings or value-added scores, in making talent management decisions, including teacher hiring, assignment, support, and retention, but we know little about the local conditions that promote or impede these processes. We investigate the barriers to principals’ use of teacher effectiveness measures in eight urban districts and charter management organizations that are investing in new systems for collecting such measures and making them available to school leaders and the supports central offices are building to help principals overcome those barriers. Interviews with more than 175 central and school leaders identify barriers in three main areas related to accessing measures, analyzing them, and taking action based on their analysis. Supports fall into four categories: professional development, connecting principals to sources of expertise, creating new structures or tools, and building a data use culture. Survey analysis suggests that indeed principals in high support systems perceive lower barriers to data use and report greater incorporation of teacher effectiveness measures into their talent management decisions.

Leadership to Support and Sustain Data Use in Data Teams

2018 ◽  
pp. 98-118 ◽  
Author(s):  
Kim Schildkamp ◽  
Cindy Louise Poortman
Keyword(s):  
School Improvement ◽  
Leadership Behaviors ◽  
School Leaders ◽  
Data Use ◽  
Intellectual Stimulation ◽  
Data Teams ◽  
Use Of Data ◽  
Data Team ◽  
Different Parts

This chapter focuses on how school leaders can support the use of data in data teams with the data team intervention, a step-by-step systematic approach to school improvement. First, the data team professional development intervention is described and an example of a data team in action is provided. Next, the authors closely examine the role of the school leader in supporting the use of data in data teams. Several leadership behaviors that are important to support data teams are described: developing a vision, norms, and goals for data use; providing individualized support; providing intellectual stimulation; creating a climate for data use; and, networking to connect different parts of the organization. Concrete examples are provided with regard to how these behaviors are demonstrated in data teams. The chapter ends with a checklist and reflection tool, which school leaders can use to reflect on their own leadership behaviors with regard to supporting data use in data teams.

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.

Teacher Effects and Teacher Effectiveness: A Validity Investigation of the Tennessee Value Added Assessment System

2003 ◽  
Vol 25 (3) ◽  
pp. 287-298 ◽  
Author(s):  
Haggai Kupermintz
Keyword(s):  
Teacher Effectiveness ◽  
Teaching Effectiveness ◽  
Value Added ◽  
Assessment System ◽  
Policy Implications ◽  
Socioeconomic Background ◽  
Background Characteristics ◽  
Definition Of ◽  
Validation Research ◽  
Value Added Measures

This article addresses the validity of teacher evaluation measures produced by the Tennessee Value Added Assessment System (TVAAS). The system analyzes student test score data and estimates the effects of individual teachers on score gains. These effects are used to construct teacher value-added measures of teaching effectiveness. We describe the process of generating teacher effectiveness estimates in TVAAS and discuss policy implications of using these estimates for accountability purposes. Specifically, the article examines the TVAAS definition of teacher effectiveness, the mechanism employed in calculating numerical estimates of teacher effectiveness, and the relationships between these estimates and student ability and socioeconomic background characteristics. Our validity analyses point to several logical and empirical weaknesses of the system, and underscore the need for a strong validation research program on TVAAS.

scholarly journals Personnel Management and School Productivity: Evidence from India

2021 ◽  
Author(s):  
Renata Lemos ◽  
Karthik Muralidharan ◽  
Daniela Scur
Keyword(s):  
Public Schools ◽  
Teacher Effectiveness ◽  
Private Schools ◽  
Private School ◽  
Effective Teachers ◽  
Teaching Practice ◽  
School Teacher ◽  
Value Added ◽  
Teacher Pay ◽  
Management Quality

This paper uses new data to study school management and productivity in India. We report four main results. First, management quality in public schools is low, and ~2σ below high-income countries with comparable data. Second, private schools have higher management quality, driven by much stronger people management. Third, people management quality is correlated with both independent measures of teaching practice, as well as school productivity measured by student value added. Fourth, private school teacher pay is positively correlated with teacher effectiveness, and better managed private schools are more likely to retain more effective teachers. Neither pattern is seen in public schools.

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.

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