Assessing agreement on classification tasks: the kappa statistic
Computational Linguistics
An intelligent tutoring system for deaf learners of written English
Assets '00 Proceedings of the fourth international ACM conference on Assistive technologies
Supporting Intelligent Tutoring in CALL by Modeling the User's Grammar
Proceedings of the Thirteenth International Florida Artificial Intelligence Research Society Conference
Recognizing syntactic errors in the writing of second language learners
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Modeling user language proficiency in a writing tutor for deaf learners of English
ASSESSEVALNLP '99 Proceedings of a Symposium on Computer Mediated Language Assessment and Evaluation in Natural Language Processing
Empirical Derivation of a Sequence of User Stereotypes for Language Learning
User Modeling and User-Adapted Interaction
User Modeling and User-Adapted Interaction
Text simplification for reading assistance: a project note
PARAPHRASE '03 Proceedings of the second international workshop on Paraphrasing - Volume 16
Evaluating a model to disambiguate natural language parses on the basis of user language proficiency
UM'03 Proceedings of the 9th international conference on User modeling
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In this paper we discuss our approach toward establishing a model of the acquisition of English grammatical structures by users of our English language tutoring system, which has been designed for deaf users of American Sign Language. We explore the correlation between a corpus of error-tagged texts and their holistic proficiency scores assigned by experts in order to draw initial conclusions about what language errors typically occur at different levels of proficiency in this population. Since errors made at lower levels (and not at higher levels) presumably represent constructions acquired before those on which errors are found only at higher levels, this should provide insight into the order of acquisition of English grammatical forms.