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Knowledge Engineering for Intelligent Tutoring Systems: Assessing Semi-automatic Skill Encoding Methods

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Intelligent Tutoring Systems (ITS 2006)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 4053))

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Abstract

Building a mapping between items and their related knowledge components, while difficult and time consuming, is central to the task of developing affective intelligent tutoring systems. Improving performance on this task by creating a semi-automatic skill encoding system would facilitate the development of such systems. The goal of this project is to explore techniques involved in text classification to the end of improving the time required to correctly tag items with their associated skills.

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References

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Author information

Authors and Affiliations

  1. Computer Science Department, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA, USA

    Kevin Kardian & Neil T. Heffernan

Authors
  1. Kevin Kardian
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  2. Neil T. Heffernan
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Editor information

Editors and Affiliations

  1. JAIST, 1-1, Asahi-dai, Nomi, 923-1292, Ishikawa, Japan

    Mitsuru Ikeda

  2. Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA

    Kevin D. Ashley

  3. Graduate Institute of Network Learning Technology, National Central University, 300, Jhongda Rd., 32001, Jhongli City,Taoyuan County, Taiwan

    Tak-Wai Chan

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© 2006 Springer-Verlag Berlin Heidelberg

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Kardian, K., Heffernan, N.T. (2006). Knowledge Engineering for Intelligent Tutoring Systems: Assessing Semi-automatic Skill Encoding Methods. In: Ikeda, M., Ashley, K.D., Chan, TW. (eds) Intelligent Tutoring Systems. ITS 2006. Lecture Notes in Computer Science, vol 4053. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11774303_84

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  • DOI: https://doi.org/10.1007/11774303_84

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35159-7

  • Online ISBN: 978-3-540-35160-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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