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A Framework for Parameterized Design of Rule Systems Applied to Algebra

Part of the Lecture Notes in Computer Science book series (LNPSE,volume 9684)

Abstract

Creating a domain model (expert behavior) is a key component of every tutoring system. Whether the process is manual or semi-automatic, the construction of the rules of expert behavior requires substantial effort. Once finished, the domain model is treated as a fixed entity that does not change based on scope, sequence modifications, or student learning parameters. In this paper, we propose a framework for automatic learning and optimization of the domain model (expressed as condition-action rules) based on designer-provided learning criteria that include aspects of scope, progression sequence, efficiency of learned solutions, and working memory capacity. We present a proof-of-concept implementation based on program synthesis for the domain of linear algebra, and we evaluate this framework through preliminary illustrative scenarios of objective learning criteria.

Keywords

  • Intelligent tutoring systems
  • Program synthesis
  • Automated domain modeling
  • Artificial intelligence

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Correspondence to Eric Butler .

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© 2016 Springer International Publishing Switzerland

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Butler, E., Torlak, E., Popović, Z. (2016). A Framework for Parameterized Design of Rule Systems Applied to Algebra. In: Micarelli, A., Stamper, J., Panourgia, K. (eds) Intelligent Tutoring Systems. ITS 2016. Lecture Notes in Computer Science(), vol 9684. Springer, Cham. https://doi.org/10.1007/978-3-319-39583-8_36

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  • DOI: https://doi.org/10.1007/978-3-319-39583-8_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39582-1

  • Online ISBN: 978-3-319-39583-8

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