Automated Feedback Generation for Argument-Based Intelligent Tutoring Systems

Matej Guid, Matevž Pavlič, Martin Možina

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.

Download


Paper Citation


in Harvard Style

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


in Bibtex Style

@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},
}


in EndNote Style

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