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Deane, Paul; Sabatini, John; Feng, Gary; Sparks, Jesse; Song, Yi; Fowles, Mary; O'Reilly, Tenaha; Jueds, Katherine; Krovetz, Robert; Foley, Colleen – ETS Research Report Series, 2015
This paper presents a framework intended to link the following assessment development concepts into a systematic framework: evidence-centered design (ECD), scenario-based assessment (SBA), and assessment of, for, and as learning. The context within which we develop this framework is the English language arts (ELA) for K-12 students, though the…
Descriptors: Language Arts, Learning Theories, Best Practices, English Instruction
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
De Felice, Rachele; Deane, Paul – ETS Research Report Series, 2012
This study proposes an approach to automatically score the "TOEIC"® Writing e-mail task. We focus on one component of the scoring rubric, which notes whether the test-takers have used particular speech acts such as requests, orders, or commitments. We developed a computational model for automated speech act identification and tested it…
Descriptors: Speech Acts, Electronic Mail, Language Tests, Second Language Learning
Deane, Paul; Gurevich, Olga – ETS Research Report Series, 2008
For many purposes, it is useful to collect a corpus of texts all produced to the same stimulus, whether to measure performance (as on a test) or to test hypotheses about population differences. This paper examines several methods for measuring similarities in phrasing and content and demonstrates that these methods can be used to identify…
Descriptors: Test Content, Computational Linguistics, Native Speakers, Writing Tests