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Authors: Matej Guid ; Matevž Pavlič and Martin Možina

Affiliation: Faculty of Computer and Information Science, University of Ljubljana, Večna pot 113, Ljubljana and Slovenia

ISBN: 978-989-758-367-4

Keyword(s): Intelligent Tutoring Systems, Argument-based Machine Learning (ABML), ABML Knowledge Refinement Loop, Learning by Arguing, Feedback Generation, Financial Statements.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence and Decision Support Systems ; Computer-Supported Education ; Domain Applications and Case Studies ; e-Learning ; Enterprise Information Systems ; Information Technologies Supporting Learning ; Intelligent Learning and Teaching Systems ; Intelligent Tutoring Systems

Abstract: Argument-based machine learning provides the ability to develop interactive learning environments that are able to automatically select relevant examples and counter-examples to be explained by the students. However, in order to build successful argument-based intelligent tutoring systems, it is essential to provide useful feedback on students’ arguments and explanations. To this end, we propose three types of feedback for this purpose: (1) a set of relevant counter-examples, (2) a numerical evaluation of the quality of the argument, and (3) the generation of hints on how to refine the arguments. We have tested our approach in an application that allows students to learn by arguing with the aim of improving their understanding of financial statements.

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Paper citation in several formats:
Guid, M.; Pavlič, M. and Možina, M. (2019). Automated Feedback Generation for Argument-Based Intelligent Tutoring Systems.In Proceedings of the 11th International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-758-367-4, pages 70-77. DOI: 10.5220/0007717600700077

@conference{csedu19,
author={Matej Guid. and Matevž Pavlič. and Martin Možina.},
title={Automated Feedback Generation for Argument-Based Intelligent Tutoring Systems},
booktitle={Proceedings of the 11th International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2019},
pages={70-77},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007717600700077},
isbn={978-989-758-367-4},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - Automated Feedback Generation for Argument-Based Intelligent Tutoring Systems
SN - 978-989-758-367-4
AU - Guid, M.
AU - Pavlič, M.
AU - Možina, M.
PY - 2019
SP - 70
EP - 77
DO - 10.5220/0007717600700077

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