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Discussion of expert systems and intelligent tutoring systems in the education field highlights an expert system that was developed to enhance the learning process in the field of grammatical constructs. Topics addressed include representing the natural language; parsing; LOGOOP (Logo in Object-Oriented Programing); and user-system interface. (11 references) (LRW)

GPARS is a generalized transition network system designed for language study by both students and researchers. The GPARS system generalizes the Augmented Transition Network formalism by allowing top-down, bottom-up, depth-first, breadth-first, deterministic, and nondeterministic parsing strategies to be freely intermixed. These various strategies have also allowed the system to be used for parsing Chinese, Russian, Japanese, and other languages. The GPARS project is supported in part by the U.S. Department of Education, Office of Postsecondary Education [G008740399], Secretary's Discretionary Fund [G008720150], and Office of Special Education and Rehabilitative Services [H180P80020].

The development of a successful, \"intelligent\" parser is essential to \"intelligent\" CALL programs. A modification of ATN makes possible the incorporation of case grammar analysis to judge meaningfully the use of prepositions, articles, tenses, and other parts of speech. This modified ATN makes possible the difficult task of constructing a parser which recognizes semantic and syntactic differences in an infinite number of possible sentences. This parser works with an internally generated copy of the text so as to not compromise the original text. The parser stores characters and compares them against internal dictionaries and other characters or words. These comparisons are made via several algorithms which make distinctions between such classes as Agent/Experiencer and Path/Location. The parser is able to skip around in a sentence through the use of pointers and stripping suffixes to find roots.