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Computational Argumentation for Supporting Learning Processes: Applications and Challenges

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Handbook on Intelligent Techniques in the Educational Process

Part of the book series: Learning and Analytics in Intelligent Systems ((LAIS,volume 29))

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Abstract

This book chapter analyzes different applications and challenges of computational argumentation for modeling different aspects of learning processes. Some of the topics included are argument-based recommender systems for educational purposes; argument-based shared knowledge for computer-supported collaborative learning (CSCL) and argument-based opinion mining for eliciting students’ knowledge based on information items corresponding to different topics of study. We also identify and discuss salient challenges associated with argumentation in the current state of the art. The chapter is organized to be self-contained, including an overview of the key elements in computational argumentation. Our contribution is intended to provide a reference point for researchers working on intelligent techniques for educational processes who are interested in incorporating argumentation as a metaphor for modeling intelligent decision making in Intelligent Tutoring Systems (ITS), Computer-Supported Collaborative Learning (CSCL) systems, and other related areas.

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Notes

  1. 1.

    For an in-depth treatment of DeLP and its features the reader is referred to [1].

  2. 2.

    This approach is used in some commercial platforms for assessing tweets in terms of a positive, negative or neutral value and the percentage of tweets corresponding to each value (e.g. sentiment140.com).

  3. 3.

    The full-fledged description of the algorithm can be found in [16].

  4. 4.

    CSCL stands for “Computer Supported Collaborative Learning”.

  5. 5.

    This example was originally presented in [20].

  6. 6.

    Names and values used here are fictitious. They are just considered for the sake of the example and not necessarily according to a real-world situation.

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Acknowledgements

This research was supported by Projects PICT 2014-0624 and PGI 24/N051(Universidad Nacional del Sur and ANPCyT, Argentina).

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Authors and Affiliations

  1. Departamento de Ciencias E Ingeniería de La Computación (DCIC UNS), Instituto de Ciencias E Ingeniería de La Computación (ICIC CONICET UNS), Universidad Nacional del Sur – Campus Palihue, San Andrés, 800 - 8000, Bahía Blanca, Argentina

    Carlos Chesñevar & Ana Maguitman

  2. Universidad del Cauca - Popayán, Popayán, Colombia

    César A. Collazos

Authors
  1. Carlos Chesñevar
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  2. César A. Collazos
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  3. Ana Maguitman
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Corresponding author

Correspondence to Carlos Chesñevar .

Editor information

Editors and Affiliations

  1. Faculty of Sciences, Department of Mathematics and Informatics, University of Novi Sad, Novi Sad, Serbia

    Mirjana Ivanović

  2. Faculty of Sciences, Department of Mathematics and Informatics, University of Novi Sad, Novi Sad, Serbia

    Aleksandra Klašnja-Milićević

  3. KES International, Selby, UK

    Lakhmi C. Jain

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Chesñevar, C., Collazos, C.A., Maguitman, A. (2022). Computational Argumentation for Supporting Learning Processes: Applications and Challenges. In: Ivanović, M., Klašnja-Milićević, A., Jain, L.C. (eds) Handbook on Intelligent Techniques in the Educational Process. Learning and Analytics in Intelligent Systems, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-031-04662-9_9

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  • DOI: https://doi.org/10.1007/978-3-031-04662-9_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-04661-2

  • Online ISBN: 978-3-031-04662-9

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