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Chen, Jing; Zhang, Mo; Bejar, Isaac I. – ETS Research Report Series, 2017
Automated essay scoring (AES) generally computes essay scores as a function of macrofeatures derived from a set of microfeatures extracted from the text using natural language processing (NLP). In the "e-rater"® automated scoring engine, developed at "Educational Testing Service" (ETS) for the automated scoring of essays, each…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essay Tests
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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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Zechner, Klaus; Bejar, Isaac I.; Hemat, Ramin – ETS Research Report Series, 2007
The increasing availability and performance of computer-based testing has prompted more research on the automatic assessment of language and speaking proficiency. In this investigation, we evaluated the feasibility of using an off-the-shelf speech-recognition system for scoring speaking prompts from the LanguEdge field test of 2002. We first…
Descriptors: Role, Computer Assisted Testing, Language Proficiency, Oral Language
Bejar, Isaac I. – 1985
The feasibility of reducing scoring costs for the Test of Spoken English (TSE) by using one rater was investigated. Currently, two raters are used. It was found that, because of the possibility of different standards used by potential raters, it does not appear feasible to use a single rater as the sole determiner of speaking proficiency under the…
Descriptors: Analysis of Covariance, Cost Effectiveness, English (Second Language), Evaluation Criteria