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Authors: Tina Daaboul and Hicham Hage

Affiliation: Department of Computer Science, Notre Dame University - Louaize, Zouk Mosbeh, Keserwan and Lebanon

ISBN: 978-989-758-350-6

Keyword(s): Culturally Aware Learning System, Major Adaptation, Information Extraction, Intelligent Tutoring Systems, Relation Extraction.

Related Ontology Subjects/Areas/Topics: AI and Creativity ; Applications ; Artificial Intelligence ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Natural Language Processing ; Pattern Recognition ; Soft Computing ; Symbolic Systems

Abstract: Culturally Aware Learning Systems are intelligent systems that adapt learning materials or techniques to the culture of learners having different “country, hobbies, experiences, etc.”, helping them better understand the topics being taught. In higher education, many learning sessions involve students of different majors. As observed, many instructors tend to manually modify the exercises several times, once for every major to adapt to the culture, which is tedious and impractical. Therefore, in this paper we propose an approach to making learning sessions adaptable to the major of the learner. Specifically, this work introduces an Artificial Intelligent system, “Majorly Adapted Translator (MAT)”, which aims at translating and adapting exercises from one major to another. MAT has two main phases, the first identifies the parts of an exercise that needs changing and creates an exercise template. The second translates and adapts the exercise. This work, highlights the first phase, the Fe ature Extract phase, which relies on our own relation extraction method to identify variables which extracts relations specific to named entities by using dependency relations and shallow parsing. Moreover, we report the performance of the system that was tested on a number of probability exercises. (More)

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Paper citation in several formats:
Daaboul, T. and Hage, H. (2019). “Majorly Adapted Translator”: Towards Major Adaptation in ITS.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-350-6, pages 451-457. DOI: 10.5220/0007296904510457

@conference{icaart19,
author={Tina Daaboul. and Hicham Hage.},
title={“Majorly Adapted Translator”: Towards Major Adaptation in ITS},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2019},
pages={451-457},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007296904510457},
isbn={978-989-758-350-6},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - “Majorly Adapted Translator”: Towards Major Adaptation in ITS
SN - 978-989-758-350-6
AU - Daaboul, T.
AU - Hage, H.
PY - 2019
SP - 451
EP - 457
DO - 10.5220/0007296904510457

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