Proofreading one's own writing is difficult due to the overfamiliarity of one's writing, which has been claimed to conceal errors, even extraneous errors inserted by someone else (as in collaborative writing). In the present research, we examined whether increasing one's familiarity with text can indeed have a negative influence on error…

In the present study, we examined error detection/correction during collaborative writing. Subjects were asked to identify and correct errors in two contexts: a passage written by the subject (familiar text) and a passage written by a person other than the subject (unfamiliar text). A computer program inserted errors in function words prior to the…

This report presents work on the development of a new corpus of non-native English writing. It will be useful for the task of native language identification, as well as grammatical error detection and correction, and automatic essay scoring. In this report, the corpus is described in detail.

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…

This paper describes the first prototype of an automated tool for detecting collocation errors in texts written by non-native speakers of English. Candidate strings are extracted by pattern matching over POS-tagged text. Since learner texts often contain spelling and morphological errors, the tool attempts to automatically correct them in order to…