Multiple External Representations in Remediation of Math Errors

Maici Duarte Leite, Diego Marczal, Andrey Ricardo Pimentel

2013

Abstract

The proposition of error remediation is a widely used feature in Intelligent Tutoring Systems, but the use of Multiple External Representations to assist it, is a research subject. This paper presents (or discuss) the use of Multiple External Representations contribution in error remediation in Learning Objects. To perform this study, we present an architectural model, a conceptual framework for mathematical error classification and Multiple External Representations, using a cognitive remediation for errors. Following is presented the application of contextual remediation of error based on Multiple External Representations in a Learning Object. And finally, we present the performance of students during the application of an experiment consisting of the following steps: pre-test, test and post-test.

References

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Paper Citation


in Harvard Style

Duarte Leite M., Marczal D. and Ricardo Pimentel A. (2013). Multiple External Representations in Remediation of Math Errors . In Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-8565-59-4, pages 519-523. DOI: 10.5220/0004568105190523


in Bibtex Style

@conference{iceis13,
author={Maici Duarte Leite and Diego Marczal and Andrey Ricardo Pimentel},
title={Multiple External Representations in Remediation of Math Errors},
booktitle={Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2013},
pages={519-523},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004568105190523},
isbn={978-989-8565-59-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 15th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Multiple External Representations in Remediation of Math Errors
SN - 978-989-8565-59-4
AU - Duarte Leite M.
AU - Marczal D.
AU - Ricardo Pimentel A.
PY - 2013
SP - 519
EP - 523
DO - 10.5220/0004568105190523