Advertisement

Computer-Assisted Item Generation for Listening Cloze Tests and Dictation Practice in English

  • Shang-Ming Huang
  • Chao-Lin Liu
  • Zhao-Ming Gao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3583)

Abstract

We take advantages of abundant text resource on the Internet and information about English phonetics for assisting human teachers to prepare test items for listening and dictation in English. In this preliminary exploration, we built an environment in which teachers choose words that they want to have test items for, and teachers compose the final test items based on the test items that are algorithmically generated by our system. The output of the current system indicates that computers can play active roles in assisting the composition of test items, though we have not done a field test over the usability issues.

Keywords

Test Item Phonetic Feature English Vocabulary Tongue Position Phoneme Sequence 
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.
    Vandergrift, L.: Listen to learn or learn to listen. Annual Review of Applied Linguistics 24, 3–25 (2004)CrossRefGoogle Scholar
  2. 2.
    Mendelsohn, D.: Teaching Listening. Annual Review of Applied Linguistics 18, 81–101 (1998)CrossRefGoogle Scholar
  3. 3.
  4. 4.
    Coniam, D.: Computerized dictation for assessing listening proficiency. Computer Assisted Language Instruction Consortium Journal 13(2-3), 73–85 (1996)Google Scholar
  5. 5.
    Ross, S.: Self-assessment in second language testing: A meta-analysis and analysis of experiential factors. Language Testing 15(1), 1–20 (1998)Google Scholar
  6. 6.
    Irvine, S.H., Kyllonen, P.C. (eds.): Item Generation for Test Development. Lawrence Erlbaum Associates, Mahwah (2002)Google Scholar
  7. 7.
    Stevens, V.: Classroom concordancing: Vocabulary materials derived from relevant authentic text. English for Specific Purposes 10(1), 35–46 (1991)CrossRefGoogle Scholar
  8. 8.
    Coniam, D.: A Preliminary inquiry into using corpus word frequency data in the automatic generation of English cloze tests. Computer Assisted Language Instruction Consortium Journal 16(2-4), 15–33 (1997)Google Scholar
  9. 9.
    Wang, C.-H., Liu, C.-L., Gao, Z.-M.: Using lexical constraints for corpus-based generation of multiple-choice cloze items. In: Proc. of the Seventh IASTED Int. Conf. on Computers and Advanced Technology in Education, pp. 351–356 (2004)Google Scholar
  10. 10.
    Manning, C.D., Schütze, H.: Foundations of Statistical Natural Language Processing. MIT Press, Cambridge (1999)zbMATHGoogle Scholar
  11. 11.
    Michaud, L.N., McCoy, K.F., Stark, L.A.: Modeling the acquisition of English: An intelligent CALL approach. In: Bauer, M., Gmytrasiewicz, P.J., Vassileva, J. (eds.) UM 2001. LNCS (LNAI), vol. 2109, pp. 14–23. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  12. 12.
    Burstein, J., Chodorow, M., Leacock, C.: CriterionSM: Online essay evaluation: An application for automated evaluation of student essays. In: Proc. of the Fifteenth Annual Conf. on Innovative Applications of Artificial Intelligence, pp. 3–10 (2003)Google Scholar
  13. 13.
    Brusilovsky, P.: Adaptive and Intelligent Technologies for Web-based Education. Künstliche Intelligenz 13(4), 19–25 (1999)Google Scholar
  14. 14.
    Coniam, D.: Interactive evaluation of listening comprehension: How the context help. Computer Assisted Language Learning 11(1), 35–53 (1998)CrossRefGoogle Scholar
  15. 15.
    Oller, J.: Language Tests at School: A Pragmatic Approach. Longman, London (1979)Google Scholar
  16. 16.
  17. 17.
    AT&T Natural Voice, http://www.naturalvoices.att.com/
  18. 18.
    Jurafsky, D., Martin, J.H.: Speech and Language Processing. Prentice-Hall, Englewood Cliffs (2000)Google Scholar
  19. 19.
    Fromkin, V., Rodman, R., Hyams, N.: An Introduction to Language. Thomson Learning (2002)Google Scholar
  20. 20.
    International Phonetic Association: Handbook of the International Phonetic Association: A guide to the use of the International Phonetic Alphabet. Cambridge Univ. Press, Cambridge (1999)Google Scholar
  21. 21.
    Merriam-Webster OnLine: http://www.m-w.com/dictionary.htm
  22. 22.
    Levine, J.R., Mason, T., Brown, D.: Lex & Yacc. O’Reilly, Sebastopol (1992)Google Scholar
  23. 23.
    Porter, M.F.: An algorithm for suffix stripping. Program 14(3), 130–137 (1980)Google Scholar
  24. 24.
    Sinclair, J. (ed.): Collins CoBuild English Guides: Word Formation. HarperCollins, New York (1990)Google Scholar
  25. 25.
    Divay, M., Vitale, A.J.: Algorithms for grapheme-phoneme translation for English and French: Applications for database searches and speech synthesis. Computational Linguistics 23(4), 495–523 (1997)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Shang-Ming Huang
    • 1
  • Chao-Lin Liu
    • 1
  • Zhao-Ming Gao
    • 2
  1. 1.Dept. of Computer ScienceNational Chengchi UniversityTaipeiTaiwan
  2. 2.Dept. of Foreign Languages and LiteraturesNational Taiwan UniversityTaipeiTaiwan

Personalised recommendations