Automatic Generation of Fill-in-the-Blank Questions From History Books for School-Level Evaluation

  • Sumeet Pannu
  • Aishwarya Krishna
  • Shiwani Kumari
  • Rakesh Patra
  • Sujan Kumar Saha
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 710)


Fill-in-the-blank questions (FIBs) play an important role in educational assessment. FIBs are effective to assess the understanding of well-defined concepts, and these are often used in school level. But manual preparation of FIBs is time-consuming and requires sufficient expertise on the content. This paper presents the proposed system for automatic generation of FIB questions that accepts school textbook as input. First, we identify the informative sentences that can act as the basis of FIBs. A parse structure-based module works on the sentences to identify the concept or knowledge embedded in the sentence. The knowledge is extracted in form of subject–predicate–object triplet or expanded triplet. Then, a hybrid algorithm chooses the most appropriate word/phrase that can be marked as a gap. Proposed system is tested using class VII-level history textbook as input. The quality of the system generated questions is then evaluated manually using three defined metrics. Experimental result shows that the proposed technique is quite promising.


Question generation Fill-in-the-blanks Educational NLP 



This work is supported by the project grant (project file no.: YSS/2015/001948) provided by the Science and Engineering Research Board (SERB), Govt. of India.


  1. 1.
    Mitkov, R., Ha, L.A., 2003. Computer-aided generation of multiple-choice tests. Proceedings of the HLT/NAACL Workshop on Building educational applications using Natural Language Processing, pp. 17–22.Google Scholar
  2. 2.
    Mitkov, R., Ha, L. A., and Karamanis, N., 2006. A computer-aided environment for generating multiple-choice test items. Natural Language Engineering, Vol. 12(2), pp. 177–194.Google Scholar
  3. 3.
    Brown, J. C., Frishkoff, G. A., and Eskenazi, M., 2005. Automatic question generation for vocabulary assessment. In Proceedings of HLT and EMNLP, pp. 819–826.Google Scholar
  4. 4.
    Aldabe, I., Lopez de Lacalle, M., Maritxalar, M., Martinez, E., Uria, L., 2006. ArikIturri: An Automatic Question Generator Based on Corpora and NLP Techniques. In ITS. LNCS 4053, pp. 584–594.Google Scholar
  5. 5.
    Aldabe, I., Maritxalar, M., 2010. Automatic Distractor Generation for Domain Specific Texts. Proceedings of IceTAL, LNAI 6233. pp. 27–38.Google Scholar
  6. 6.
    Papasalouros, A., Kanaris, K., Kotis, K,. 2008. Automatic Generation of multiple-choice questions from domain ontologies. IADIS e-Learning (2008).Google Scholar
  7. 7.
    Agarwal, M., and Mannem, P., 2011. Automatic gap-fill question generation from text books. In Proceedings of the 6th Workshop on Innovative Use of NLP for Building Educational Applications, pp. 56–64.Google Scholar
  8. 8.
    Bhatia, A. S., Kirti, M., and Saha, S. K., 2013. Automatic Generation of Multiple Choice Questions Using Wikipedia. In Proceedings of Pattern Recognition and Machine Intelligence, Springer Berlin Heidelberg, pp. 733–738.Google Scholar
  9. 9.
    Majumdar M, Saha S. K., 2014. Automatic Selection of Informative Sentences: The Sentences that can generate Multiple Choice Questions. Knowledge Management & E-Learning. Vol. 6, No. 4, pp. 377–391.Google Scholar
  10. 10.
    Narendra, A., Agarwal, M. and Shah, R., 2013. Automatic Cloze-Questions Generation. In Proceedings of Recent Advances in Natural Language Processing, Bulgaria, pp. 511–515.Google Scholar
  11. 11.
    Saha SK, Sarkar S, Mitra P. 2008. A Hybrid Feature Set based Maximum Entropy Hindi Named Entity Recognition. In proceedings of IJCNLP 2008, pp. 343–349.Google Scholar
  12. 12.
    Rusu, D., Dali, L., Fortuna, B., Grobelnik, M. and Mladenić, D. 2007. Triplet Extraction from Sentences. In Proceedings of the 10th International Multiconference “Information Society - IS 2007” Ljubljana, Slovenia, October 8–12, 2007, pp. 218–222.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Sumeet Pannu
    • 1
  • Aishwarya Krishna
    • 1
  • Shiwani Kumari
    • 1
  • Rakesh Patra
    • 1
  • Sujan Kumar Saha
    • 1
  1. 1.Department of CSEBIT MesraRanchiIndia

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