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Data-Driven Method for Assessing Skill-Opportunity Recognition in Open Procedural Problem Solving Environments

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Book cover Intelligent Tutoring Systems (ITS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 7315))

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Abstract

Our research goal is to use data-driven methods to generate the basic functionalities of intelligent tutoring systems. In open procedural problem solving environments, the tutor gives users a goal with little to no restrictions on how to reach it. Knowledge components refer to not only skill application, but also applicable skill-opportunity recognition. Syntax and logic errors further confound the results with ambiguity in error detection. In this work, we present a domain independent method of assessing skill-opportunity recognition. The results of this method can be used to provide automatic feedback to users as well as to assess users problem solving abilities.

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References

  1. Barnes, T., Stamper, J.: Toward Automatic Hint Generation for Logic Proof Tutoring Using Historical Student Data. In: Woolf, B.P., Aïmeur, E., Nkambou, R., Lajoie, S. (eds.) ITS 2008. LNCS, vol. 5091, pp. 373–382. Springer, Heidelberg (2008)

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  2. Corbett, A.T., Anderson, J.R.: Knowledge tracing: Modeling the acquisition of procedural knowledge. User Modeling and User-Adapted Interaction 4, 253–278 (1994)

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  3. Croy, M.J.: Graphic interface design and deductive proof construction. J. Comput. Math. Sci. Teach. 18, 371–385 (1999)

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Author information

Authors and Affiliations

  1. The University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC, 28213, USA

    Michael John Eagle & Tiffany Barnes

Authors
  1. Michael John Eagle
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  2. Tiffany Barnes
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Editor information

Editors and Affiliations

  1. University of Montpellier & CNRS LIRMM, 161 rue Ada, 34095, Montpellier, France

    Stefano A. Cerri

  2. NASA and Florida Institute for Human and Machine Cognition, Human Centered Computing - Intelligent Systems Division, 94035, Moffett Field, CA, USA

    William J. Clancey

  3. Department of Applied Informatics and Multimedia, Technological Educational Institute of Crete, School of Applied Technology, Stavromenos, P.O.Box 1939, 71004, Heraklion, Crete, Greece

    Giorgos Papadourakis

  4. Neoanalysis Ltd., Marni 56, 10437, Athens, Greece

    Kitty Panourgia

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© 2012 Springer-Verlag Berlin Heidelberg

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Eagle, M.J., Barnes, T. (2012). Data-Driven Method for Assessing Skill-Opportunity Recognition in Open Procedural Problem Solving Environments. In: Cerri, S.A., Clancey, W.J., Papadourakis, G., Panourgia, K. (eds) Intelligent Tutoring Systems. ITS 2012. Lecture Notes in Computer Science, vol 7315. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30950-2_88

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  • DOI: https://doi.org/10.1007/978-3-642-30950-2_88

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30949-6

  • Online ISBN: 978-3-642-30950-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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