Advertisement

An intelligent language tutoring system for handling errors caused by transfer

  • Yang Wang
  • Roberto Garigliano
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 608)

Abstract

This research addresses how an Intelligent Language Tutoring System can effectively help to solve a practical problem of transfer in students' second language learning of Chinese. Our empirical data shows that the problem of transfer accounts for most of the errors observed in the linguistic output of English-speaking students in their study of Chinese. This accords with views of other experts on transfer in the field of second language learning, such as Selinker [15], Cornu [6], Sheen [16] and Cowan [7]. A technique of mixed grammar of Chinese and English is used to tackle the problem of transfer. In this paper, we describe the importance of transfer, explain the data that has been collected, present an overview of the three main models, demonstrate the technique that we use to handle errors of transfer and finally discuss how our system is going to be evaluated.

Keywords

Target Language Tutoring System Negative Transfer Prepositional Phrase Student Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    J. Barchan, B. Woodmansee, M. Yazdani: “A Prolog-Based Tool for French Grammar Analysis“, Instructional Science, 15, pp 21–48, 1986.Google Scholar
  2. [2]
    J. Barchan: Language Independent Grammatical Error Reporter, M. Phil. thesis, Dept. of Computer Science, Univ. of Exeter, Britain, 1987.Google Scholar
  3. [3]
    M. E. Catt: Intelligent Diagnosis of Ungrammaticality in Computer-Assisted Language Instruction, MSc. thesis, Dept. of Computer Science, Univ. of Toronto, Canada, 1988.Google Scholar
  4. [4]
    L. Chen, B. L. Kurtz: “XTRA-TE: Using Natural Language Processing Software to Develop an ITS for Language Learning”, Proceedings of the 4th International Conference on AI and Education, pp 54–63, Amsterdam, Netherlands, 24–26 May 1989.Google Scholar
  5. [5]
    S. P. Corder: “The significance of Learners' Errors”, in Second Language Learning: Contrastive Analysis, Error Analysis, and Related Aspects, edited by B. W. Robinett, J. Schachter, pp 163–172, The Univ. of Michigan Press, 1983.Google Scholar
  6. [6]
    M. Cornu: “La France en direct, 1er degre, au fil des leçons”, Bulletin CILA, 17, 1973.Google Scholar
  7. [7]
    J. R. Cowan: “Towards a Psychological Theory of Interference in Second Language Learning”, in Second Language Learning: Contrastive Analysis, Error Analysis, and Related Aspects, edited by B. W. Robinett, J. Schachter, pp 109–119, The Univ. of Michigan Press, 1983.Google Scholar
  8. [8]
    W. Daelemans: “Learning Heuristic Diagnostic Rules in an Intelligent Tutoring System”, Third International Symposium on Knowledge Engineering, pp 113–118, Madrid, 17–21 October 1988.Google Scholar
  9. [9]
    F. Halasz, T. P. Moran: “Analogy Considered Harmful”, in Eight Short Papers in User Psychology, edited by T. P. Moran, Cognitive and Instructional Sciences Series, CIS-17, pp 33–36, Xerox Palo Alto Research Centers, Palo Alto, CA, 1982.Google Scholar
  10. [10]
    T. Odlin: Language Transfer: Cross-Linguistic Influence in Language Learning, Cambridge Univ. Press, 1989.Google Scholar
  11. [11]
    F. Pijls, W. Daelemans, G. Kempen: “Artificial Intelligence Tools for Grammar and Spelling Instruction”, in Instructional Science, 16, pp 319–336, 1987.Google Scholar
  12. [12]
    D. E. Rumelhart, D. A. Norman: “Analogical Processes in Learning”, in Cognitive Skills and Their Acquisition, edited by J. R. Anderson, Erlbaum, Hillsdale, NJ, pp 335–360, 1981.Google Scholar
  13. [13]
    E. Schuster: “The Role of Native Grammars in Correcting Errors in Second Language Learning”, Computational Intelligence, 2, pp 93–98, 1986.Google Scholar
  14. [14]
    C. B. Schwind: “An Intelligent Language Tutoring System”, International Journal of Man-Machine Studies, 33, pp 557–579, 1990.Google Scholar
  15. [15]
    L. Selinker: “Language Transfer”, General Linguistics, 9, pp 69–92, 1969.Google Scholar
  16. [16]
    R. Sheen: “The Importance of Negative Transfer in Speech of Near-Bilinguals”, International Review of Applied Linguistics, 18(2), pp 105–119, 1980.Google Scholar
  17. [17]
    D. H. Sleeman: “Assessing Competence in Basic Algebra”, in Intelligent Tutoring Systems, edited by D. H. Sleeman, J. S. Brown, pp 185–199, Academic Press, 1982.Google Scholar
  18. [18]
    E. Wenger: Artificial Intelligence and Tutoring Systems, Los Altos: Morgan Kaufmann Publishers Inc., 1987.Google Scholar
  19. [19]
    P. H. Winston: Learning and Reasoning by Analogy: the Details, MIT Press, Cambridge, Massachusetts, AI Memo 520, 1980.Google Scholar
  20. [20]
    Y. Wang, R. Garigliano: “A Language Tutoring System for Handling Transfer Errors”, Technical Report 4/91, School of Engineering and Computer Science, University of Durham, Britain, 1991.Google Scholar
  21. [21]
    M. Yazdani et al: LINGER — A Natural Language Corrector in Prolog, software in public domain, contributed by O'Brien, M. Yazdani, Exeter Univ., Britain, 1988.Google Scholar
  22. [22]
    M. Yazdani: “A Multi-Purpose Database of Learning Materials (M-DBLM) “, Computer Assisted Learning, Proceedings of 3rd international Conference, ICCAL90, pp 29-35, Hagen, FRG, June 1990.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Yang Wang
    • 1
  • Roberto Garigliano
    • 1
  1. 1.Computer ScienceUniversity of DurhamUK

Personalised recommendations