A Framework for Automated Generation of Questions Based on First-Order Logic

  • Rahul SinghalEmail author
  • Martin Henz
  • Shubham Goyal
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9112)


In this work, questions are tasks posed to students to help them understand a subject, or to help educators assess their level of competency in it. Automated question generation is important today as content providers in education try to scale their efforts. In particular, MOOCs need a continuous supply of new questions in order to offer educational content to thousands of students, and to provide a fair assessment process. In this paper we establish first-order logic as a suitable formal tool to describe question scenarios, questions and answers. We apply this approach to the domain of mechanics (physics) in high school education.


First order logic Automated deduction Pattern matching Formal domains Axiomatic approach Constraint handling rules (CHR) 


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  1. Cinderella geometry tool (January 2013).
  2. Geogebra geometry tool (January 2013).
  3. Alvin, C., Gulwani, S., Majumdar, R., Mukhopadhyay, S.: Synthesis of geometry proof problems. In: Proceedings of the 28th AAAI Conference on Artificial Intelligence, pp. 245–252 (2014)Google Scholar
  4. Frühwirth, T., Raiser, F. (eds.): Constraint Handling Rules: Compilation, Execution, and Analysis. Books On Demand (2011)Google Scholar
  5. Gao, X.-S., Lin, Q.: MMP/geometer – a software package for automated geometric reasoning. In: Winkler, F. (ed.) ADG 2002. LNCS (LNAI), vol. 2930, pp. 44–66. Springer, Heidelberg (2004) Google Scholar
  6. Melis, E., Siekmann, J.H.: ActiveMath: an intelligent tutoring system for mathematics. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds.) ICAISC 2004. LNCS (LNAI), vol. 3070, pp. 91–101. Springer, Heidelberg (2004) Google Scholar
  7. Schrijvers, T., Demoen, B.: The K. U. Leuven CHR system-implementation and application. In: First Workshop on Constraint Handling Rules-Selected Contributions, pp. 1–5 (2004)Google Scholar
  8. Singh, R., Gulwani, S., Rajamani, S.: Automatically generating algebra problems. In: Brodley, C.E., Stone, P. (eds.) Proceedings of the 26th AAAI Conference on Artificial Intelligence, pp. 1620–1627 (2012)Google Scholar
  9. Singhal, R., Henz, M., McGee, K.: Automated generation of geometry questions for high school mathematics. In: Proceeedings of the Sixth International Conference on Computer Supported Education, Barcelona, Spain (2014)Google Scholar
  10. Vanlehn, K., Lynch, C., Schulze, K., Shapiro, J.A., Shelby, R.H., Taylor, L., Treacy, D.J., Weinstein, A., Wintersgill, M.C.: The Andes physics tutoring system-five years of evaluations. In: Proceedings of the Artificial Intelligence in Education Conference, pp. 678–685 (2005)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.School of ComputingNational University of Singapore (NUS)SingaporeSingapore

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