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In this paper we present a new spell-checking system that utilizes contextual information for automatic correction of non-word misspel-lings. The system is evaluated with a large corpus of essays written by native and non-native speakers of English to the writing prompts of high-stakes standardized tests (TOEFL ® and GRE ®). We also present comparative(More)
  • Kathleen M Sheehan, Irene Kostin, Yoko Futagi, Michael Flor, Isaac Bejar, Jana Sukkarieh
  • 2011
As part of its nonprofit mission, ETS conducts and disseminates the results of research to advance quality and equity in education and assessment for the benefit of ETS's constituents and the field. To obtain a PDF or a print copy of a report, please visit: Abstract The Common Core Standards call for students to be exposed to a much greater level of text(More)
We describe a new representation of the content vocabulary of a text we call word association profile that captures the proportions of highly associated, mildly associated , unassociated, and dis-associated pairs of words that co-exist in the given text. We illustrate the shape of the dis-tirbution and observe variation with genre and target audience. We(More)
Developments in the educational landscape have spurred greater interest in the problem of automatically scoring short answer questions. A recent shared task on this topic revealed a fundamental divide in the mod-eling approaches that have been applied to this problem, with the best-performing systems split between those that employ a knowledge engineering(More)
Many existing approaches for measuring text complexity tend to overestimate the complexity levels of informational texts while simultaneously underestimating the complexity levels of literary texts. We present a two-stage estimation technique that successfully addresses this problem. At Stage 1, each text is classified into one or another of three possible(More)