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Deane, Paul; Lawless, René R.; Li, Chen; Sabatini, John; Bejar, Isaac I.; O'Reilly, Tenaha – ETS Research Report Series, 2014
We expect that word knowledge accumulates gradually. This article draws on earlier approaches to assessing depth, but focuses on one dimension: richness of semantic knowledge. We present results from a study in which three distinct item types were developed at three levels of depth: knowledge of common usage patterns, knowledge of broad topical…
Descriptors: Vocabulary, Test Items, Language Tests, Semantics
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Sukkarieh, Jane Z.; von Davier, Matthias; Yamamoto, Kentaro – ETS Research Report Series, 2012
This document describes a solution to a problem in the automatic content scoring of the multilingual character-by-character highlighting item type. This solution is language independent and represents a significant enhancement. This solution not only facilitates automatic scoring but plays an important role in clustering students' responses;…
Descriptors: Scoring, Multilingualism, Test Items, Role
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Sheehan, Kathleen M.; Kostin, Irene; Futagi, Yoko; Hemat, Ramin; Zuckerman, Daniel – ETS Research Report Series, 2006
This paper describes the development, implementation, and evaluation of an automated system for predicting the acceptability status of candidate reading-comprehension stimuli extracted from a database of journal and magazine articles. The system uses a combination of classification and regression techniques to predict the probability that a given…
Descriptors: Automation, Prediction, Reading Comprehension, Classification
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Higgins, Derrick; Futagi, Yoko; Deane, Paul – ETS Research Report Series, 2005
This paper reports on the process of modifying the ModelCreator item generation system to produce output in multiple languages. In particular, Japanese and Spanish are now supported in addition to English. The addition of multilingual functionality was considerably facilitated by the general formulation of our natural language generation system,…
Descriptors: Multilingualism, Computer Software, Japanese, Spanish