Requirements Elicitation Based on Psycho-Pedagogical Theatre for Context-Sensitive Affective Educational Recommender Systems
Educational Recommender Systems (ERSs), intelligent tutoring systems that adapt their pedagogical recommendations to each student, are becoming increasingly common. Context-Sensitive Affective Educational Recommender Systems (CSAERSs) personalize the recommendations according to a learning context w...
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Format: | Article |
Language: | English |
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IEEE
2023-01-01
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Series: | IEEE Access |
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Online Access: | https://ieeexplore.ieee.org/document/10188825/ |
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author | Marcos Belver Angeles Manjarres Alejandra Barbarelli Simon Pickin |
author_facet | Marcos Belver Angeles Manjarres Alejandra Barbarelli Simon Pickin |
author_sort | Marcos Belver |
collection | DOAJ |
description | Educational Recommender Systems (ERSs), intelligent tutoring systems that adapt their pedagogical recommendations to each student, are becoming increasingly common. Context-Sensitive Affective Educational Recommender Systems (CSAERSs) personalize the recommendations according to a learning context with multiple dimensions, including the affective dimension and the personality traits of the user. To date, in the field of educational technology, there is little or no research that focuses on offering context-sensitive, personalized, psycho-pedagogical affective support to distance-learning students in real time. Nor do there seem to be any proposals for approaches to the knowledge engineering (term which encompasses knowledge acquisition and knowledge representation) of these systems, in which the relation between the user and his or her context is crucial. There is little work on a systematic approach to the requirements-elicitation phase and to the use of ontologies in the development and validation of ERSs, in general, and CSAERSs, in particular. In this article, we report on a student-centred requirements-elicitation methodology that uses psycho-pedagogical theatre in combination with student surveys. We then illustrate its application in the design and validation of an ontology, together with a semantic-similarity function, that could serve as the nucleus of a CSAERS. |
first_indexed | 2024-03-12T20:54:07Z |
format | Article |
id | doaj.art-fb70547619724a9089b08f9fad9dcb7c |
institution | Directory Open Access Journal |
issn | 2169-3536 |
language | English |
last_indexed | 2024-03-12T20:54:07Z |
publishDate | 2023-01-01 |
publisher | IEEE |
record_format | Article |
series | IEEE Access |
spelling | doaj.art-fb70547619724a9089b08f9fad9dcb7c2023-07-31T23:00:29ZengIEEEIEEE Access2169-35362023-01-0111762847629910.1109/ACCESS.2023.329750910188825Requirements Elicitation Based on Psycho-Pedagogical Theatre for Context-Sensitive Affective Educational Recommender SystemsMarcos Belver0https://orcid.org/0000-0001-9414-8361Angeles Manjarres1https://orcid.org/0000-0001-5441-3642Alejandra Barbarelli2https://orcid.org/0000-0003-1889-2599Simon Pickin3https://orcid.org/0000-0002-5506-3602Departamento de Inteligencia Artificial, Universidad Nacional de Educación a Distancia (UNED), Madrid, SpainDepartamento de Inteligencia Artificial, Universidad Nacional de Educación a Distancia (UNED), Madrid, SpainDepartamento de Inteligencia Artificial, Universidad Nacional de Educación a Distancia (UNED), Madrid, SpainDepartamento de Sistemas Informáticos y Computación, Universidad Complutense, Madrid, SpainEducational Recommender Systems (ERSs), intelligent tutoring systems that adapt their pedagogical recommendations to each student, are becoming increasingly common. Context-Sensitive Affective Educational Recommender Systems (CSAERSs) personalize the recommendations according to a learning context with multiple dimensions, including the affective dimension and the personality traits of the user. To date, in the field of educational technology, there is little or no research that focuses on offering context-sensitive, personalized, psycho-pedagogical affective support to distance-learning students in real time. Nor do there seem to be any proposals for approaches to the knowledge engineering (term which encompasses knowledge acquisition and knowledge representation) of these systems, in which the relation between the user and his or her context is crucial. There is little work on a systematic approach to the requirements-elicitation phase and to the use of ontologies in the development and validation of ERSs, in general, and CSAERSs, in particular. In this article, we report on a student-centred requirements-elicitation methodology that uses psycho-pedagogical theatre in combination with student surveys. We then illustrate its application in the design and validation of an ontology, together with a semantic-similarity function, that could serve as the nucleus of a CSAERS.https://ieeexplore.ieee.org/document/10188825/Artificial intelligenceadaptive systemseducational technologyintelligent tutoring systemsknowledge acquisitionknowledge engineering |
spellingShingle | Marcos Belver Angeles Manjarres Alejandra Barbarelli Simon Pickin Requirements Elicitation Based on Psycho-Pedagogical Theatre for Context-Sensitive Affective Educational Recommender Systems IEEE Access Artificial intelligence adaptive systems educational technology intelligent tutoring systems knowledge acquisition knowledge engineering |
title | Requirements Elicitation Based on Psycho-Pedagogical Theatre for Context-Sensitive Affective Educational Recommender Systems |
title_full | Requirements Elicitation Based on Psycho-Pedagogical Theatre for Context-Sensitive Affective Educational Recommender Systems |
title_fullStr | Requirements Elicitation Based on Psycho-Pedagogical Theatre for Context-Sensitive Affective Educational Recommender Systems |
title_full_unstemmed | Requirements Elicitation Based on Psycho-Pedagogical Theatre for Context-Sensitive Affective Educational Recommender Systems |
title_short | Requirements Elicitation Based on Psycho-Pedagogical Theatre for Context-Sensitive Affective Educational Recommender Systems |
title_sort | requirements elicitation based on psycho pedagogical theatre for context sensitive affective educational recommender systems |
topic | Artificial intelligence adaptive systems educational technology intelligent tutoring systems knowledge acquisition knowledge engineering |
url | https://ieeexplore.ieee.org/document/10188825/ |
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