NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 8 results Save | Export
Gilraine, Michael; Gu, Jiaying; McMillan, Robert – National Bureau of Economic Research, 2020
This paper proposes a new methodology for estimating teacher value-added. Rather than imposing a normality assumption on unobserved teacher quality (as in the standard empirical Bayes approach), our nonparametric estimator permits the underlying distribution to be estimated directly and in a computationally feasible way. The resulting estimates…
Descriptors: Value Added Models, Teacher Effectiveness, Nonparametric Statistics, Computation
Peer reviewed Peer reviewed
Direct linkDirect link
Gao, Niu; Semykina, Anastasia – Journal of Research on Educational Effectiveness, 2021
Inappropriate treatment of missing data may introduce bias into the value-added estimation. We consider a commonly used value-added model (VAM), which includes the past student test score as a covariate. We formulate a joint model of student achievement and missing data, in which the probability of observing a test score depends on observing the…
Descriptors: Value Added Models, Elementary School Teachers, Computation, Scores
Jinyong Hahn; John D. Singleton; Nese Yildiz – Annenberg Institute for School Reform at Brown University, 2023
Panel or grouped data are often used to allow for unobserved individual heterogeneity in econometric models via fixed effects. In this paper, we discuss identification of a panel data model in which the unobserved heterogeneity both enters additively and interacts with treatment variables. We present identification and estimation methods for…
Descriptors: Teacher Effectiveness, Models, Computation, Statistical Analysis
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Dagiene, Valentina; Stupuriene, Gabriele – Informatics in Education, 2016
As an international informatics contest, or challenge, Bebras has started the second decade of its existence. The contest attracts more and more countries every year, recently there have been over 40 participating countries. From a single contest-focused annual event Bebras developed to a multifunctional challenge and an activities-based…
Descriptors: Information Science, Computation, Competition, Models
Amrein-Beardsley, Audrey; Geiger, Tray – Phi Delta Kappan, 2017
Houston's experience with the Educational Value-Added Assessment System (R) (EVAAS) raises questions that other districts should consider before buying the software and using it for high-stakes decisions. Researchers found that teachers in Houston, all of whom were under the EVAAS gun, but who taught relatively more racial minority students,…
Descriptors: Value Added Models, School Districts, Computer Software, Educational Technology
Peer reviewed Peer reviewed
Direct linkDirect link
Tybur, Joshua M.; Lieberman, Debra; Kurzban, Robert; DeScioli, Peter – Psychological Review, 2013
Interest in and research on disgust has surged over the past few decades. The field, however, still lacks a coherent theoretical framework for understanding the evolved function or functions of disgust. Here we present such a framework, emphasizing 2 levels of analysis: that of evolved function and that of information processing. Although there is…
Descriptors: Cognitive Processes, Psychological Patterns, Motivation, Decision Making
Peer reviewed Peer reviewed
Direct linkDirect link
Via, Barbara J.; Schmidle, Deborah J. – portal: Libraries and the Academy, 2007
The library and information science field is currently confronted with difficult decisions about how best to allocate acquisition expenditures among increasingly expensive journals. This article measures the return-on-investment of serial expenditures through the use of citation analysis, which is a widely used approach to ascertaining journal…
Descriptors: Information Science Education, Libraries, Expenditures, Library Science
Peer reviewed Peer reviewed
Direct linkDirect link
Wu, Margaret – Studies in Educational Evaluation, 2005
In large-scale assessment programs such as NAEP, TIMSS and PISA, students' achievement data sets provided for secondary analysts contain so-called "plausible values." Plausible values are multiple imputations of the unobservable latent achievement for each student. In this article it has been shown how plausible values are used to: (1)…
Descriptors: Error of Measurement, Computation, Educational Research, Educational Assessment