On Mathematics Software Equipped with Adaptive Tutor System

  • Hisashi YokotaEmail author
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 170)


In this article, we describe how an educators’ knowledge structure map is utilized to assess a knowledge state of a learner in college mathematics courses such as calculus and linear algebra. We also describe how an adaptive tutoring system is implemented into our mathematics learning software JCALC using the relative distance and the knowledge score.


Adaptive tutoring system Concept map Knowledge score Knowledge state Knowledge structure map Relative distance 



This work was supported in part by Shibaura Institute of Technology, Grant-in-Aid for Scientific Research in 2011–2012.

We thank all colleagues and learners participated in this project and suggested useful ideas to refine our adaptive learning system.


  1. 1.
    Ainsworth RG (1995) Turning potential school dropouts into graduates: the case for school-based one-to-one tutoring. Research report 95–07. National Commission for Employment Policy, 35Google Scholar
  2. 2.
    Alavi M, Leidner DE (2001) Knowledge management and knowledge management systems: conceptual foundations and research issues. MIS Q Rev 25(1):107–136CrossRefGoogle Scholar
  3. 3.
    Bana P (1999) Artificial intelligence in educational software: has its time come. Br J Educ Technol 30(1):79–81CrossRefGoogle Scholar
  4. 4.
    Bloom BS (1984) Taxonomy of educational objectives. Pearson Education, BostonGoogle Scholar
  5. 5.
    Brehmer B (1980) In one word: not from experience. Acta Psychol 45:223–241CrossRefGoogle Scholar
  6. 6.
    Keyes J (1990) Where’s the ‘‘expert’’ in expert systems. AI Expert 5(3):61–64Google Scholar
  7. 7.
    Newble D, Cannon R (2000) A handbook for teachers in university and colleges: a guide to improving teaching methods. Kogan page Ltd, LondonGoogle Scholar
  8. 8.
    Rentsch J, Heffner T (1994) Group Organ Manag 19(4):450–474Google Scholar
  9. 9.
    Sembugamoorthy V, Chandresekaren B (1986) Functional representation of devices and compilation of diagnostic problem-solving systems. In: Kolodner JL, Reisbeck CK (eds) Experience, memory, and reasoning. Erlbaum, HillsdaleGoogle Scholar
  10. 10.
    Yokota H (2006) On development of e-math-learning system for short-answer type questions. Res Bull HIT, 40:319–325Google Scholar
  11. 11.
    Yokota H (2011) On a development an adaptive tutoring system utilizing educator’s knowledge structure. Lecture notes in engineering and computer science. In: proceedings of the world congress on engineering and computer science 2011, WCECS 2011, 19–21 October 2011, San Francisco, pp 260–264Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.College of EngineeringShibaura Institute of TechnologySaitamaJapan

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