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Haberman, Shelby J. – ETS Research Report Series, 2020
Best linear prediction (BLP) and penalized best linear prediction (PBLP) are techniques for combining sources of information to produce task scores, section scores, and composite test scores. The report examines issues to consider in operational implementation of BLP and PBLP in testing programs administered by ETS [Educational Testing Service].
Descriptors: Prediction, Scores, Tests, Testing Programs
Milanowski, Anthony T. – Online Submission, 2011
After decades of disinterest, evaluation of the performance of elementary and secondary teachers in the United States has become an important educational policy issue. As U.S. states and districts have tried to upgrade their evaluation processes, one of the models that has been increasingly used is the Framework for Teaching. This paper summarizes…
Descriptors: Evidence, Teacher Effectiveness, Teacher Evaluation, Observation
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Liu, Jinghua; Low, Albert C. – ETS Research Report Series, 2007
This study applied kernel equating (KE) in two scenarios: equating to a very similar population and equating to a very different population, referred to as a distant population, using SAT® data. The KE results were compared to the results obtained from analogous classical equating methods in both scenarios. The results indicate that KE results are…
Descriptors: College Entrance Examinations, Equated Scores, Comparative Analysis, Evaluation Methods
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Haberman, Shelby J.; Sinharay, Sadip; Puhan, Gautam – ETS Research Report Series, 2006
Recently, there has been an increasing level of interest in reporting subscores. This paper examines the issue of reporting subscores at an aggregate level, especially at the level of institutions that the examinees belong to. A series of statistical analyses is suggested to determine when subscores at the institutional level have any added value…
Descriptors: Scores, Statistical Analysis, Error of Measurement, Reliability