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Negotiation-Driven Learning: A New Perspective of Learning Using Negotiation

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Artificial Intelligence in Education (AIED 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9112))

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Abstract

Negotiation mechanisms used in the current implementations of Open Learner Models are mostly position-based and provide minimal support for learners to understand why their beliefs contradict with that of the system. In this paper, we propose the paradigm of Negotiation-Driven Learning with the aim to enhance the role of negotiations in open learner models with special emphasis on affect, behavior and metacognitive abilities of the learners.

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References

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Authors and Affiliations

  1. School of Knowledge Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Raja M. Suleman, Riichiro Mizoguchi & Mitsuru Ikeda

Authors
  1. Raja M. Suleman
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  2. Riichiro Mizoguchi
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  3. Mitsuru Ikeda
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Corresponding author

Correspondence to Raja M. Suleman .

Editor information

Editors and Affiliations

  1. University of British Columbia, Vancouver, British Columbia, Canada

    Cristina Conati

  2. Computer Science Department, Worcester Polytechnic Institute, Worcester, Massachusetts, USA

    Neil Heffernan

  3. Department of Computer Science and Software Engineering, University of Canterbury, Christchurch, New Zealand

    Antonija Mitrovic

  4. E.T.S.I. Informática, Universidad National de Educacion a Distancia, Madrid, Spain

    M. Felisa Verdejo

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© 2015 Springer International Publishing Switzerland

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Suleman, R.M., Mizoguchi, R., Ikeda, M. (2015). Negotiation-Driven Learning: A New Perspective of Learning Using Negotiation. In: Conati, C., Heffernan, N., Mitrovic, A., Verdejo, M. (eds) Artificial Intelligence in Education. AIED 2015. Lecture Notes in Computer Science(), vol 9112. Springer, Cham. https://doi.org/10.1007/978-3-319-19773-9_135

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  • DOI: https://doi.org/10.1007/978-3-319-19773-9_135

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19772-2

  • Online ISBN: 978-3-319-19773-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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