The Authoring Assistant

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1452)


In some domains, including those requiring natural language understanding, we cannot build a system that can complete the entire task. One way to deal with such cases is to encode the result of understanding the problem description along with traces of the process used to understand that description. This places the natural language understanding portion of the system in the authoring system, as opposed to the run-time system (the one used by the student). This solution, however, puts a burden on the author, who must now verify that the problem encoding reflects the desired understanding. We describe the Authoring Assistant, a component of the pSAT system [11] for authoring problems for the PAT Algebra tutor [7] which addresses these issues.


Word Problem Problem Situation Authoring System Intelligent Tutoring System Runtime System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Andre, E., Rist, T. and Muller, J.: Life-like presentation agents: A new perspective for computer-based technical documentation. In Proceedings of the AI-ED workshop on pedagogical agents, Kobe, Japan. (1997).Google Scholar
  2. 2.
    Bobrow, D. G.: Natural language input for a computer problem-solving system. In M. Minsky (Ed.): Semantic information processing. MIT Press, Cambridge, Ma. (1968).Google Scholar
  3. 3.
    Corbett, A. T., Koedinger, K. R. and Anderson, J. R.: Intelligent Tutoring Systems. In The Handbook of Human Computer Interaction. (1996).Google Scholar
  4. 4.
    Frasson, C., Mengelle, T. and Aimeur, E.: Using pedagogical agents in a multi-strategic intelligent tutoring system. In Proceedings of the AI-ED workshop on pedagogical agents, Kobe, Japan. (1997).Google Scholar
  5. 5.
    Greer, B.: Multiplication and division as models of situations. In D. A. Grouws (Ed.). Handbook on research on mathematics teaching and learning. Macmillian, New York. (1992) 276–295.Google Scholar
  6. 6.
    Kintsch, W. and Greeno, J.: Understnading and solving word arithmetic problems. Psychological Review. 92 (1985) 109–129.CrossRefGoogle Scholar
  7. 7.
    Koedinger, K. R., Anderson, J. R.., Hadley, W. H., & Mark, M. A.: Intelligent tutoring goes to school in the big city. International Journal of Artificial Intelligence in Education. 8 (1997).Google Scholar
  8. 8.
    Murray, T.: Authoring knowledge-based tutors: Tools for content, instructional strategy, student model and interface design. The Journal of the Learning Sciences. 7 (1998).Google Scholar
  9. 9.
    Paige, J. M. and Simon, H. A.: Cognitive processes in solving algebra word problems. In B. Kleinmuntz (Ed.), Problem Solving: Research, Method and Theory. Wiley, New York.(1966).Google Scholar
  10. 10.
    Ritter, S. and Anderson, J. R.: Calculation and strategy in the equation solving tutor. In J.D. Moore & J.F. Lehman (Eds.), Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society. Erlbaum, Hillsdale, NJ: (1995) 413–418.Google Scholar
  11. 11.
    Ritter, S., Anderson, J. R., Cytrynowitz, M., & Medvedeva, O.: Authoring content in the PAT algebra tutor. Journal of Interactive Media in Education (1998).Google Scholar
  12. 12.
    Ritter, S. and Koedinger, K. R.: An architecture for plug-in tutor agents. Journal of Artificial Intelligence in Education. 7 (1996) 315–347.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  1. 1.Department of PsychologyCarnegie Mellon UniversityPittsburghUSA

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