Hostname: page-component-89b8bd64d-b5k59 Total loading time: 0 Render date: 2026-05-07T21:22:40.006Z Has data issue: false hasContentIssue false
  • English
  • Français

Error diagnosis for language learning systems

Published online by Cambridge University Press:  26 August 2021

Wolfgang Menzel  and
Ingo Schröder
Wolfgang Menzel
Affiliation:
Fachbereich Informatik, Universität Hamburg
Ingo Schröder
Affiliation:
Fachbereich Informatik, Universität Hamburg
Get access Rights & Permissions [Opens in a new window]

Abstract

A diagnostic component for natural language utterances has been devised which allows one to integrate (possibly inconsistent) evidence from a wide range of knowledge sources into a unique decision procedure. It is based on a procedure for the disambiguation of dependency structures using graded constraints. Different description levels like syntax, semantics, and others are treated by separate structural representations, which are disambiguated simultaneously. Due to the complete symmetry of the system architecture the approach allows for the successful handling of a wide variety or student errors.

Information

Type
Research Article
Information
ReCALL , Volume 11 , Issue S1: Natural Language Processing In Computer-Assisted Language Learning , May 1999 , pp. 20 - 30
Copyright
Copyright © The Author(s) 1999

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

Footnotes

1

This article is an extended version of a paper presented at the NLP+IA 98 conference in Moncton, Canada.

References

Briscoe, T. (1994) “Prospects for practical parsing of unrestricted text: Robust statistical parsing techniques”. In Oostdijk, N. & de Haan, P. (eds), Corpus-based Research into Language, Amsterdam: Rodopi.Google Scholar
Hamburger, H. (1995) “Tutorial tools for language learning by two-medium dialogue”. In Holland, V. M., Kaplan, J. D. & Sams, M. R. (eds), Intelligent Language Tutors, Hillsdale, NJ: Lawrence Erlbaum Associates, 183-199.Google Scholar
Heinecke, J., Kunze, J., Menzel, W. & Schröder, I. (1998) “Eliminative parsing with graded constraints”, Proceedings 17th International Conference on Computational Linguistics, 36th Annual Meeting of the ACL, Coling-ACL ‘98, Montreal, Canada, 526-530.Google Scholar
Maruyama, H. (1990) Constraint dependency grammar. Technical Report RT0044, IBM Research, Tokyo Research Laboratory.Google Scholar
Mealing, S. & Yazdani, M. (1993) “A computerbased iconic language”. In Yazdani, M. (ed), Multilingual Multimedia: Bridging the Language Barrier with Intelligent Systems. Oxford: Intellect Books.Google Scholar
Menzel, W. & Schroder, I. (1998a) “Constraintbased diagnosis for intelligent language tutoring systems”, Proceedings IT & KNOWS, XV. IFIP World Computer Congress, Wien und Budapest.Google Scholar
Menzel, W. & Schroder, I. (1998b) “Decision procedures for dependency parsing using graded constraints”. In Kahane, S. and Polguère, A. (eds), Proceedings ColingACL Workshop on Processing of Dependency based Grammars, 15 August 1998, Montreal, Canada.Google Scholar
Menzel, W. & Schröder, I. (1998c) “Model-based diagnosis under structural uncertainty”, Proceedings 13th European Conference on Artificial Intelligence, Brighton, UK, 284-288.Google Scholar
Menzel, W. (1988) “Error diagnosing and selection in a training system for second language learning”, Proceedings 12th International Conference on Computational Linguistics, Coling ‘88, Budapest, 414-419.Google Scholar
Menzel, W. (1990) “Anticipation-free diagnosing of structural faults”, Proceedings 13th International Conference on Computational Linguistics, Coling ‘90, Helsinki, 422-424.Google Scholar
Menzel, W. (1992) “Modellbasierte Fehlerdiagnose in Sprachlehrsystemen”, Sprache und Information 24, Tubingen: Niemeyer.Google Scholar
Menzel, W. (1998) ‘Constraint satisfaction for robust parsing of natural language”, Theoretical and Experimental Artificial Intelligence 10(1), 77-89.Google Scholar
Ohlsson, S. (1994) “Constraint-based student modelling”. In Greer, J.E. and McColla, G.I. (eds), Student Modelling: The Key To Individualized Knowledge-Based Instruction, Berlin: Springer-Verlag, 167-189.CrossRefGoogle Scholar
Schneider, D. & McCoy, K.F. (1998) “Recognising Syntactic Errors in the Writing of Second Language Learners”, Proceedings 17th International Conference on Computational Linguistics, 36th Annual Meeting of the ACL, Coling-ACL ‘98, Montreal, Canada, 1198-1204.Google Scholar
Schwind, C. (1995) ‘Error analysis and explanation in knowledge based language tutoring”, Computer Assisted Language Learning 8(4), 295-324.CrossRefGoogle Scholar
Uszkoreit, H. (1991) “Strategies for adding control information to declarative grammars”, Proceedings 29th Annual Meeting of the ACL, 19-21 June 1991, Berkeley, CA, 237-245.Google Scholar
Yazdani, M. & Mealing, S. (1993) Communicating through pictures. Technical report, Department of Computer Science, University of Exeter.Google Scholar
Yazdani, M. (1986) “Intelligent tutoring systems: An overview”. Expert Systems 3(3), 154-162.CrossRefGoogle Scholar