This paper reports on the development of an analysis engine for the Research Writing Tutor (RWT), an AWE program designed to provide genre and discipline-specific feedback on the functional units of research article discourse. Unlike traditional NLP-based applications that categorize complete documents, the analyzer categorizes every sentence in…

In this paper we present a system for automatic correction of errors made by learners of English. The system has two novel aspects. First, machine-learned classifiers trained on large amounts of native data and a very large language model are combined to optimize the precision of suggested corrections. Second, the user can access real-life web…

We built a natural language processing (NLP) system implementing a "virtual writing conference" for elementary-school children, with German as the target language. Currently, state-of-the-art computer support for writing tasks is restricted to multiple-choice questions or quizzes because automatic parsing of the often ambiguous and fragmentary…

A typology for analyzing grammatical errors in student-written German compositions is presented and approaches to providing helpful error messages to student users of a parser-based writing aid are discussed. (19 references) (Author/LB)

A computer grammar checker is described that evolved from a sample of errors and resulting in a taxonomy of 14 main and 93 subtypes. Using a 1,402-word stem electronic dictionary, an augmented transition network parser, and a set of disambiguating rules, the checker provides feedback for 7 types of errors. (12 references) (Author/LB)

Describes development and evaluation of an error analysis procedure for a computer-assisted language learning program using natural language processing techniques. The program can be used for learning passive voice in Japanese on any World Wide Web browser. The program enables learners to type sentences freely, detects errors, and displays…