THE FACTORS INFLUENCING THE EDUCATION VALUE-ADDED MODELS

2016 ◽  
Author(s):  
Radek Krpec
Keyword(s):  
Value Added ◽  
Factors Influencing ◽  
Value Added Models ◽  
Education Value

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

SAGE Open ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 215824402092222
Author(s):  
Audrey Amrein-Beardsley ◽  
Tray Geiger
Keyword(s):  
Value Added ◽  
Assessment System ◽  
School Level ◽  
Business Analytics ◽  
Validity And Reliability ◽  
Independent School District ◽  
Value Added Models ◽  
Education Value ◽  
Composition Factors ◽  
Student Composition

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.

Methodological Concerns About the Education Value-Added Assessment System

2008 ◽  
Vol 37 (2) ◽  
pp. 65-75 ◽  
Author(s):  
Audrey Amrein-Beardsley
Keyword(s):  
Value Added ◽  
Assessment System ◽  
Regression To The Mean ◽  
Methodological Issues ◽  
User Friendliness ◽  
Paradigm Case ◽  
Student Background ◽  
Data Regression ◽  
Value Added Models ◽  
Education Value

Value-added models help to evaluate the knowledge that school districts, schools, and teachers add to student learning as students progress through school. In this article, the well-known Education Value-Added Assessment System (EVAAS) is examined. The author presents a practical investigation of the methodological issues associated with the model. Specifically, she argues that, although EVAAS is probably the most sophisticated value-added model, it has flaws that must be addressed before widespread adoption. She explores in depth the shortage of external reviews and validity studies of the model, its insufficient user-friendliness, and methodological issues about missing data, regression to the mean, and student background variables. She also examines a paradigm case in which the model was used to advance unfounded assertions.

scholarly journals Using Lagged Outcomes to Evaluate Bias in Value-Added Models

2016 ◽  
Author(s):  
Raj Chetty ◽  
John Friedman ◽  
Jonah Rockoff
Keyword(s):  
Value Added ◽  
Value Added Models

scholarly journals Smallholder Agroprocessors’ Willingness to Pay for Value-Added Solid-Waste Management Solutions

2019 ◽  
Vol 11 (6) ◽  
pp. 1759
Author(s):  
Olaoluwa Omilani ◽  
Adebayo Abass ◽  
Victor Okoruwa
Keyword(s):  
Waste Management ◽  
Willingness To Pay ◽  
Solid Waste ◽  
Management System ◽  
Solid Waste Management ◽  
Value Added ◽  
Primary Data ◽  
Management Options ◽  
Waste Management System ◽  
Factors Influencing

The paper examined the willingness of smallholder cassava processors to pay for value-added solid wastes management solutions in Nigeria. We employed a multistage sampling procedure to obtain primary data from 403 cassava processors from the forest and Guinea savannah zones of Nigeria. Contingent valuation and logistic regression were used to determine the willingness of the processors to pay for improved waste management options and the factors influencing their decision on the type of waste management system adopted and willingness to pay for a value-added solid-waste management system option. Women constituted the largest population of smallholder cassava processors, and the processors generated a lot of solid waste (605–878 kg/processor/season). Waste was usually dumped (59.6%), given to others (58.1%), or sold in wet (27.8%) or dry (35.5%) forms. The factors influencing the processors’ decision on the type of waste management system to adopt included sex of processors, membership of an association, quantity of cassava processed and ownership structure. Whereas the processors were willing to pay for new training on improved waste management technologies, they were not willing to pay more than US$3. However, US$3 may be paid for training in mushroom production. It is expected that public expenditure on training to empower processors to use solid-waste conversion technologies for generating value-added products will lead to such social benefits as lower exposure to environmental toxins from the air, rivers and underground water, among others, and additional income for the smallholder processors. The output of the study can serve as the basis for developing usable and affordable solid-waste management systems for community cassava processing units in African countries involved in cassava production.

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.

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

2019 ◽  
Vol 20 (1) ◽  
pp. 26-44
Author(s):  
Godstime Osekhebhen Eigbiremolen
Keyword(s):  
Public Schools ◽  
Private School ◽  
Primary Schools ◽  
Value Added ◽  
Primary School Children ◽  
Individual Level ◽  
Value Added Models ◽  
Value Added Model ◽  
Private And Public ◽  
Unobserved Ability

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.

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 Interpreting Tests of School VAM Validity

2016 ◽  
Vol 106 (5) ◽  
pp. 388-392 ◽  
Author(s):  
Joshua Angrist ◽  
Peter Hull ◽  
Parag Pathak ◽  
Christopher Walters
Keyword(s):  
School District ◽  
Predictive Value ◽  
Degrees Of Freedom ◽  
School Attendance ◽  
Value Added ◽  
School Effects ◽  
Test Statistic ◽  
Forecast Bias ◽  
Value Added Models

We develop over-identification tests that use admissions lotteries to assess the predictive value of regression-based value-added models (VAMs). These tests have degrees of freedom equal to the number of quasi-experiments available to estimate school effects. By contrast, previously implemented VAM validation strategies look at a single restriction only, sometimes said to measure forecast bias. Tests of forecast bias may be misleading when the test statistic is constructed from many lotteries or quasi-experiments, some of which have weak first stage effects on school attendance. The theory developed here is applied to data from the Charlotte-Mecklenberg School district analyzed by Deming (2014).

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