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A fuzzy logic approach to manage uncertainty and improve the prediction accuracy in student model design

The intelligent tutoring systems (ITSs) are special classes of e-learning systems developed using artificial intelligent (AI) techniques to provide adaptive and personalized tutoring based on the individuality of each student. For an intelligent tutoring system to provide an interactive and adaptive...

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Main Authors: Muhammad Sani, Salisu, Mohd Aris, Teh Noranis, Mustapha, Norwati, Sulaiman, Md Nasir
Format: Article
Language:English
Published: Asian Research Publication Network 2015
Online Access:http://psasir.upm.edu.my/id/eprint/43497/1/abstract00.pdf
http://psasir.upm.edu.my/id/eprint/43497/
http://www.jatit.org
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spelling my.upm.eprints.434972016-06-28T08:37:41Z http://psasir.upm.edu.my/id/eprint/43497/ A fuzzy logic approach to manage uncertainty and improve the prediction accuracy in student model design Muhammad Sani, Salisu Mohd Aris, Teh Noranis Mustapha, Norwati Sulaiman, Md Nasir The intelligent tutoring systems (ITSs) are special classes of e-learning systems developed using artificial intelligent (AI) techniques to provide adaptive and personalized tutoring based on the individuality of each student. For an intelligent tutoring system to provide an interactive and adaptive assistance to students, it is important that the system knows something about the current knowledge state of each student and what learning goal he/she is trying to achieve. In other words, the ITS needs to perform two important tasks, to investigate and find out what knowledge the student has and at the same time make a plan to identify what learning objective the student intends to achieve at the end of a learning session. Both of these processes are modeling tasks that involve high level of uncertainty especially in situations where students are made to follow different reasoning paths and are not allowed to express the outcome of those reasoning in an explicit manner. The main goal of this paper is to employ the use Fuzzy logic technique as an effective and sound computational intelligence formalism to handle reasoning under uncertainty which is one major issue of great concern in student model design. Asian Research Publication Network 2015-12-31 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/43497/1/abstract00.pdf Muhammad Sani, Salisu and Mohd Aris, Teh Noranis and Mustapha, Norwati and Sulaiman, Md Nasir (2015) A fuzzy logic approach to manage uncertainty and improve the prediction accuracy in student model design. Journal of Theoretical and Applied Information Technology, 82 (3). pp. 366-377. ISSN 1992-8645; ESSN: 1817-3195 http://www.jatit.org
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description The intelligent tutoring systems (ITSs) are special classes of e-learning systems developed using artificial intelligent (AI) techniques to provide adaptive and personalized tutoring based on the individuality of each student. For an intelligent tutoring system to provide an interactive and adaptive assistance to students, it is important that the system knows something about the current knowledge state of each student and what learning goal he/she is trying to achieve. In other words, the ITS needs to perform two important tasks, to investigate and find out what knowledge the student has and at the same time make a plan to identify what learning objective the student intends to achieve at the end of a learning session. Both of these processes are modeling tasks that involve high level of uncertainty especially in situations where students are made to follow different reasoning paths and are not allowed to express the outcome of those reasoning in an explicit manner. The main goal of this paper is to employ the use Fuzzy logic technique as an effective and sound computational intelligence formalism to handle reasoning under uncertainty which is one major issue of great concern in student model design.
format Article
author Muhammad Sani, Salisu
Mohd Aris, Teh Noranis
Mustapha, Norwati
Sulaiman, Md Nasir
spellingShingle Muhammad Sani, Salisu
Mohd Aris, Teh Noranis
Mustapha, Norwati
Sulaiman, Md Nasir
A fuzzy logic approach to manage uncertainty and improve the prediction accuracy in student model design
author_facet Muhammad Sani, Salisu
Mohd Aris, Teh Noranis
Mustapha, Norwati
Sulaiman, Md Nasir
author_sort Muhammad Sani, Salisu
title A fuzzy logic approach to manage uncertainty and improve the prediction accuracy in student model design
title_short A fuzzy logic approach to manage uncertainty and improve the prediction accuracy in student model design
title_full A fuzzy logic approach to manage uncertainty and improve the prediction accuracy in student model design
title_fullStr A fuzzy logic approach to manage uncertainty and improve the prediction accuracy in student model design
title_full_unstemmed A fuzzy logic approach to manage uncertainty and improve the prediction accuracy in student model design
title_sort fuzzy logic approach to manage uncertainty and improve the prediction accuracy in student model design
publisher Asian Research Publication Network
publishDate 2015
url http://psasir.upm.edu.my/id/eprint/43497/1/abstract00.pdf
http://psasir.upm.edu.my/id/eprint/43497/
http://www.jatit.org
_version_ 1643833583230517248
score 13.211869

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