Researchers of constructivist learning suggest that students should rather learn to solve real-world problems than artificial problems. This paper proposes a smart constructivist learning environment which provides real-world problems collected from crowd-sourcing problem-solution exchange platforms. In addition, this learning environment helps students solve real-world problems by retrieving relevant information on the Internet and by generating appropriate questions automatically. This learning environment is smart from three points of view. First, the problems to be solved by students are real-world problems. Second, the learning environment extracts relevant information available on the Internet to support problem solving. Third, the environment generates questions which help students to think about the problem to be solved.


constructivist learning information extraction question generation 


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  1. 1.
    Yudelson, M., Brusilovsky, P.: NavEx: Providing Navigation Support for Adaptive Browsing of Annotated Code Examples. In: The 12th International Conference on AI in Education, pp. 710–717. IOS Press (2005)Google Scholar
  2. 2.
    Motschnig-Pitrik, R., Holzinger, A.: Student-Centered Teaching Meets New Media: Concept and Case Study. Journal of Edu. Technology & Society 5(4), 160–172 (2002)Google Scholar
  3. 3.
    Le, N.T., Menzel, W.: Using Weighted Constraints to Diagnose Errors in Logic Programming-The Case of an Ill-defined Domain. Journal of AI in Edu. 19, 381–400 (2009)Google Scholar
  4. 4.
    bRANSFORD, J.D., Sherwood, R.D., Hasselbring, T.S., Kinzer, C.K., Williams, S.M.: Anchored Instruction: Why We Need It and How Technology Can Help. In: Cognition, Education, Multimedia - Exploring Ideas in High Technology. Lawrence Erlbaum, NJ (1990)Google Scholar
  5. 5.
    Jonassen, D.H.: Designing Constructivist Learning Environments. In: Reigeluth, C.M. (ed.) Instructional Design Theories and Models: A New Paradigm of Instructional Theory, vol. 2, pp. 215–239. Lawrence Erlbaum (1999)Google Scholar
  6. 6.
    Land, S.M.: Cognitive Requirements for Learning with Open-ended Learning Environments. Educational Technology Research and Development 48(3), 61–78 (2000)CrossRefGoogle Scholar
  7. 7.
    Lyons, D., Hoffman, J., Krajcik, J., Soloway, E.: An Investigation of the Use of the World Wide Web for On-line Inquiry in a Science Classroom. Presented at The Meeting of the National Association for Research in Science Teaching (1997)Google Scholar
  8. 8.
    Mostow, J., Chen, W.: Generating Instruction Automatically for the Reading Strategy of Self-questioning. In: Proceeding of the Conference on AI in Education, pp. 465–472 (2009)Google Scholar
  9. 9.
    Soderland, S.: Learning Information Extraction Rules for Semi-structured and Free-text. Machine Learning 34(1-3), 233–272 (1999)zbMATHCrossRefGoogle Scholar
  10. 10.
    Etzioni, O., Banko, M., Soderland, S., Weld, D.S.: Open Information Extraction From the Web.  Communication ACM 51(12), 68–74 (2008)CrossRefGoogle Scholar
  11. 11.
    Graesser, A.C., Person, N.K.: Question Asking during Tutoring. American Educational Research Journal 31(1), 104–137 (1994)CrossRefGoogle Scholar
  12. 12.
    Becker, L., Nielsen, R.D., Okoye, I., Sumner, T., Ward, W.H.: What’s Next? Target Concept Identification and Sequencing. In: Proceedings of the 3rd Workshop on Question Generation, held at the Conference on Intelligent Tutoring Systems, pp. 35–44 (2010)Google Scholar
  13. 13.
    Varga, A., Le, A.H.: A Question Generation System for the QGSTEC 2010 Task B. In: Proc. of the 3rd WS. on Question Generation, held at the ITS Conf., pp. 80–83 (2010)Google Scholar
  14. 14.
    Chen, W., Aist, G., Mostow, J.: Generating Questions Automatically From Informational Text. In: Proceedings of the 2nd Workshop on Question Generation, held at the Conference on AI in Education, pp. 17–24 (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Nguyen-Thinh Le
    • 1
  • Niels Pinkwart
    • 1
  1. 1.Department of InformaticsClausthal University of TechnologyGermany

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