Automatic Question Generation for Educational Applications – The State of Art

  • Nguyen-Thinh LeEmail author
  • Tomoko Kojiri
  • Niels Pinkwart
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 282)


Recently, researchers from multiple disciplines have been showing their common interest in automatic question generation for educational purposes. In this paper, we review the state of the art of approaches to developing educational applications of question generation. We conclude that although a great variety of techniques on automatic question generation exists, just a small amount of educational systems exploiting question generation has been developed and deployed in real classroom settings. We also propose research directions for deploying the question technology in computer-supported educational systems.


automatic question generation educational technology 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Ali, H., Chali, Y., Hasan, S.A.: Automation of question generation from sentences. In: Boyer, K.E., Piwek, P. (eds.) Proceedings of the 3rd Workshop on Question Generation, held at ITS 2010, pp. 58–67 (2010)Google Scholar
  2. 2.
    Bizer, C., Lehmann, J., Kobilarov, G., Auer, S., Becker, C., Cyganiak, R., Hellmann, S.: DBpedia - A crystallization point for the Web of Data. Web Semantics: Science, Services and Agents on the World Wide Web 7(3), 154–165 (2009)CrossRefGoogle Scholar
  3. 3.
    Bollacker, K., Evans, C., Paritosh, P., Sturge, T., Taylor, J.: Freebase: a collaboratively created graph database for structuring human knowledge. In: Proceedings of the SIGMOD International Conference on Management of Data, pp. 1247–1250. ACM (2008)Google Scholar
  4. 4.
    Brown, J., Frishkoff, G., Eskenazi, M.: Automatic question generation for vocabulary assessment. In: Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (2005)Google Scholar
  5. 5.
    Chen, W., Aist, G., Mostow, J.: Generating questions automatically from Informational text. In: Craig, S.D., Dicheva, D. (eds.) Proceedings of the 2nd Workshop on Question Generation, held at AIED 2009, pp. 17–24 (2009)Google Scholar
  6. 6.
    Chi, M.T.H., Lee, N., Chiu, M.H., LaVancher, C.: Eliciting Self-Explanations Improves Understanding. Cognitive Science 18(3), 439–477 (1994)Google Scholar
  7. 7.
    Cohen, F.S.: What is a Question? The Monist 39, 350–364 (1929)CrossRefGoogle Scholar
  8. 8.
    Graesser, A.C., Person, N.K.: Question Asking during Tutoring. American Educational Research Journal 31(1), 104–137 (1994)CrossRefGoogle Scholar
  9. 9.
    Graesser, A.C., Lu, S., Jackson, G.T., Mitchell, H.H., Ventura, M., Olney, A., Louwerse, M.M.: AutoTutor: a tutor with dialogue in natural language. Behavioral Research Methods, Instruments, and Computers 36(2), 180–192 (2004)CrossRefGoogle Scholar
  10. 10.
    Graesser, A.C., Rus, V., D’Mello, S.K., Jackson, G.T.: AutoTutor: Learning through natural language dialogue that adapts to the cognitive and affective states of the learner. In: Robinson, D.H., Schraw, G. (eds.) Recent Innovations in Educational Technology that Facilitate Student Learning, pp. 95–125. Information Age Publishing (2008)Google Scholar
  11. 11.
    Heath, T., Bizer, C.: Linked Data: Evolving the Web into a Global Data Space. Morgan & Claypool Publishers (2011)Google Scholar
  12. 12.
    Heilman, M., Smith, N.A.: Question generation via over-generating transformations and ranking. Report CMU-LTI-09-013, Language Technologies Institute, School of Computer Science, Carnegie Mellon University (2009)Google Scholar
  13. 13.
    Jouault, C., Seta, K.: Building a Semantic Open Learning Space with Adaptive Question Generation Support. In: Proceedings of the 21st International Conference on Computers in Education (2013)Google Scholar
  14. 14.
    Kalady, S., Elikkottil, A., Das, R.: Natural language question generation using syntax and keywords. In: Boyer, K.E., Piwek, P. (eds.) Proceedings of the 3rd Workshop on Question Generation, held at ITS 2010, pp. 1–10 (2010)Google Scholar
  15. 15.
    Knight, K., Marcu, D.: Statistics-based summarization – step one: Sentence compression. In: Proceedings of the 17th National Conference of the American Association for AI (2000)Google Scholar
  16. 16.
    Kunichika, H., Katayama, T., Hirashima, T., Takeuchi, A.: Automated Question Generation Methods for Intelligent English Learning Systems and its Evaluation. In: Proceedings of the International Conference on Computers in Education, pp. 1117–1124 (2001)Google Scholar
  17. 17.
    Lane, H.C., Vanlehn, K.: Teaching the tacit knowledge of programming to novices with natural language tutoring. Journal Computer Science Education 15, 183–201 (2005)CrossRefGoogle Scholar
  18. 18.
    Liu, M., Calvo, R.A., Rus, V.: G-Asks: An Intelligent Automatic Question Generation System for Academic Writing Support. Dialogue and Discourse 3(2), 101–124 (2012)CrossRefGoogle Scholar
  19. 19.
    Mannem, P., Prasady, R., Joshi, A.: Question generation from paragraphs at UPenn: QGSTEC system description. In: Boyer, K.E., Piwek, P. (eds.) Proceedings of the 3rd Workshop on Question Generation, held at ITS 2010, pp. 84–91 (2010)Google Scholar
  20. 20.
    Mitkov, R., Ha, L.A., Karamanis, N.: A computer-aided environment for generating multiple-choice test items. Journal Natural Language Engineering 12(2), 177–194 (2006)CrossRefGoogle Scholar
  21. 21.
    Mostow, J., Chen, W.: Generating instruction automatically for the reading strategy of self-questioning. In: Proceeding of the Conference on Artificial Intelligence in Education, pp. 465–472 (2009)Google Scholar
  22. 22.
    Olney, A.M., Graesser, A., Person, N.K.: Question Generation from Concept Maps. Dialogue and Discourse 3(2), 75–99 (2012)CrossRefGoogle Scholar
  23. 23.
    Pal, S., Mondal, T., Pakray, P., Das, D., Bandyopadhyay, S.: QGSTEC system description - JUQGG: A rule-based approach. In: Boyer, K.E., Piwek, P. (eds.) Proceedings of the 3rd Workshop on Question Generation, held at ITS 2010, pp. 76–79 (2010)Google Scholar
  24. 24.
    Person, N.K., Graesser, A.C.: Human or Computer? AutoTutor in a Bystander Turing Test. In: Cerri, S.A., Gouardéres, G., Paraguaçu, F. (eds.) ITS 2002. LNCS, vol. 2363, pp. 821–830. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  25. 25.
    Piwek, P., Boyer, K.E.: Varieties of Question Generation: introduction to this special issue. Dialogue & Discourse 3(2), 1–9 (2012)CrossRefGoogle Scholar
  26. 26.
    Ratinov, L., Roth, D.: Design Challenges and Misconceptions in Named Entity Recognition. In: Proceedings of the 13th Conference on Computational Natural Language Learning (2009)Google Scholar
  27. 27.
    Rus, V., Cai, Z., Graesser, A.: Question Generation: Example of A Multi-year Evaluation Campaign. In: Rus, V., Graesser, A. (eds.) Online Proceedings of 1st Question Generation Workshop, NSF, Arlington, VA (2008)Google Scholar
  28. 28.
    Sneiders, E.: Automated question answering using question templates that cover the conceptual model of the database. In: Proceedings of the 6th Int. Conference on Applications of Natural Language to IS, pp. 235–239 (2002)Google Scholar
  29. 29.
    Tenenberg, J., Murphy, L.: Knowing What I Know: An Investigation of Undergraduate Knowledge and Self-Knowledge of Data Structures. Journal Computer Science Education 15(4), 297–315 (2005)CrossRefGoogle Scholar
  30. 30.
    Varga, A., Le, A.H.: A question generation system for the QGSTEC 2010 Task B. In: Boyer, K.E., Piwek, P. (eds.) Proceedings of the 3rd Workshop on Question Generation, held at ITS 2010, pp. 80–83 (2010)Google Scholar
  31. 31.
    Wyse, B., Piwek, P.: Generating questions from OpenLearn study units. In: Craig, S.D., Dicheva, D. (eds.) Proceedings of the 2nd Workshop on Question Generation, held at AIED 2009, pp. 66–73 (2009)Google Scholar
  32. 32.
    Yu, F.-Y., Liu, Y.-H., Chan, T.-W.: A Web-Based Learning System for Question-Posing and Peer Assessment. Innovations in Education and Teaching International 42(4), 337–348 (2005)CrossRefGoogle Scholar
  33. 33.
    Vanlehn, K., Graesser, A.C., Jackson, G.T., Jordan, P., Olney, A., Rosé, C.P.: When are tutorial dialogues more effective than reading? Cognitive Science 31(1), 3–62 (2007)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Nguyen-Thinh Le
    • 1
    Email author
  • Tomoko Kojiri
    • 2
  • Niels Pinkwart
    • 1
  1. 1.Humboldt Universität zu BerlinBerlinGermany
  2. 2.Kansai UniversitySuitaJapan

Personalised recommendations