Skip to main content

Automatic Distractor Generation for Domain Specific Texts

  • Conference paper
Advances in Natural Language Processing (NLP 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6233))

Included in the following conference series:

Abstract

This paper presents a system which uses Natural Language Processing techniques to generate multiple-choice questions. The system implements different methods to find distractors semantically similar to the correct answer. For this task, a corpus-based approach is applied to measure similarities. The target language is Basque and the questions are used for learners’ assessment in the science domain. In this article we present the results of an evaluation carried out with learners to measure the quality of the automatically generated distractors.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Hoshino, A., Nakagawa, H.: Assisting cloze test making with a web application. In: Proceedings of SITE (Society for Information Technology and Teacher Eduation), San Antonio, U.S., pp. 2807–2814 (2007)

    Google Scholar 

  2. Aldabe, I., Lopez de Lacalle, M., Maritxalar, M., Martinez, E., Uria, L.: ArikIturri: An Automatic Question Generator Based on Corpora and NLP Techniques. In: Ikeda, M., Ashley, K.D., Chan, T.-W. (eds.) ITS 2006. LNCS, vol. 4053, pp. 584–594. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  3. Sumita, E., Sugaya, F., Yamamota, S.: Measuring Non-native Speakers’ Proficiency of English by Using a Test with Automatically-Generated Fill-in-the-Blank Questions. In: 2nd Workshop on Building Educational Applications Using NLP (2005)

    Google Scholar 

  4. Pino, J., Heilman, M., Eskenazi, M.: A Selection Strategy to Improve Cloze Question Quality. In: Proceedings of the Workshop on Intelligent Tutoring Systems for Ill-Defined Domains (2008)

    Google Scholar 

  5. Mitkov, R., Ha, L.A., Varga, A., Rello, L.: Semantic similarity of distractors in multiple-choice tests: extrinsic evaluation. In: Proceedings of the EACL 2009 Workshop on GEMS: GEometical Models of Natural Language Semantics, pp. 49–56 (2009)

    Google Scholar 

  6. Smith, S., Kilgarriff, A., Sommers, S., Wen-liang, G., Guang-zhong, W.: Automatic Cloze Generation for English Proficiency Testing. In: Proceeding of LTTC conference, Taipei (2009)

    Google Scholar 

  7. Agirre, E., Ansa, O., Arregi, X., Arriola, J.M., Diaz de Ilarraza, A., Pociello, E., Uria, L.: Methodological issues in the building of the Basque WordNet: quantitative and qualitative analysis. In: Proceedings of the first International WordNet Conference, Mysore, India (2002)

    Google Scholar 

  8. Landauer, T.K., McNamara, D.S., Dennis, S., Kintsch, W.: Handbook of Latent Semantic Analysis. Lawrence Erlbaum Associates, Mahwah (2007)

    Google Scholar 

  9. Deerwester, S., Dumais, S., Furnas, G., Landauer, T., Harshman, R.: Indexing by Latent Semantic Analysis. Journal of the American Society for Information Science 41(6), 391–407 (1990)

    Article  Google Scholar 

  10. Gliozzo, A.M., Giuliano, C., Strapparava, C.: Domain Kernels for Word Sense Disambiguation. In: 43nd Annual Meeting of the Association for Computational Linguistics (ACL 2005). University of Michigan, Ann Arbor (2005)

    Google Scholar 

  11. Schütze, H.: Automatic word sense discrimination. In: Computational Linguistics, vol. 24(1), pp. 97–124 (1998)

    Google Scholar 

  12. Turney, P.: Mining the Web for synonyms: PMI-IR versus LSA on TOEFL. In: Flach, P.A., De Raedt, L. (eds.) ECML 2001. LNCS (LNAI), vol. 2167, pp. 491–502. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  13. Dorow, B., Widdows, D.: Discovering corpus-specific word senses. In: Proceeding of EACL, Budapest (2003)

    Google Scholar 

  14. Areta, N., Gurrutxaga, A., Leturia, I., Alegria, I., Artola, X., Diaz de Ilarraza, A., Ezeiza, N., Sologaistoa, A.: ZT Corpus: Annotation and tools for Basque corpora. In: Copus Linguistics, Birmingham, UK (2007)

    Google Scholar 

  15. Diaz de Ilarraza, A., Mayor, A., Sarasola, K.: Semiautomatic labelling of semantic features. In: 19th International Conference on Computational Linguistics (2002)

    Google Scholar 

  16. Atserias, J., Villarejo, L., Rigau, G., Agirre, E., Carroll, J., Magnini, B., Vossen, P.: The MEANING Multilingual Central Repository. In: Proceedings of the Second International WordNet Conference-GWC, Brno, Czech Republic, pp. 23–30 (2004)

    Google Scholar 

  17. Zerbitzuak, E.H. (ed.): Elhuyar Zientzia eta Teknologiaren Hiztegi Entziklopedikoa. Elhuyar Edizioak/Euskal Herriko Unibertsitatea (2009)

    Google Scholar 

  18. Agirre, E., Soroa, A.: Personalizing PageRank for Word Sense Disambiguation. In: Proceedings of EACL 2009, Athens, Greece, pp. 33–41 (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Aldabe, I., Maritxalar, M. (2010). Automatic Distractor Generation for Domain Specific Texts. In: Loftsson, H., Rögnvaldsson, E., Helgadóttir, S. (eds) Advances in Natural Language Processing. NLP 2010. Lecture Notes in Computer Science(), vol 6233. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14770-8_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-14770-8_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14769-2

  • Online ISBN: 978-3-642-14770-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics