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Peer reviewed
Direct linkChodorow, Martin; Gamon, Michael; Tetreault, Joel – Language Testing, 2010
In this paper, we describe and evaluate two state-of-the-art systems for identifying and correcting writing errors involving English articles and prepositions. Criterion[superscript SM], developed by Educational Testing Service, and "ESL Assistant", developed by Microsoft Research, both use machine learning techniques to build models of article…
Descriptors: Grammar, Feedback (Response), Form Classes (Languages), Second Language Learning
Bae, Jungok; Bachman, Lyle F. – Language Testing, 2010
This study investigated the validity of four theoretically motivated traits of writing ability across English and Korean, based on elementary school students' responses to letter- and story-writing tasks. Their responses were scored analytically and analyzed using confirmatory factor analysis. The findings include the following. A model of writing…
Descriptors: Elementary School Students, Validity, Korean, English (Second Language)
Kim, Youn-Hee – Language Testing, 2009
This study used a mixed methods research approach to examine how native English-speaking (NS) and non-native English-speaking (NNS) teachers assess students' oral English performance. The evaluation behaviors of two groups of teachers (12 Canadian NS teachers and 12 Korean NNS teachers) were compared with regard to internal consistency, severity,…
Descriptors: Methods Research, Evaluation Criteria, Oral English, English (Second Language)
