AUG Repository

PREDICTING LEARNERS PERFORMANCE USING ARTIFICIAL NEURAL NETWORKS IN LINEAR PROGRAMMING INTELLIGENT TUTORING SYSTEM

Show simple item record

dc.contributor.author Abu-Naser, Samy S.
dc.date.accessioned 3/28/2012
dc.date.accessioned 3/28/2012
dc.date.accessioned 2019-05-31T17:26:26Z
dc.date.available 3/28/2012
dc.date.available 2019-05-31T17:26:26Z
dc.date.issued 2012
dc.identifier.citation International Journal of Artificial Intelligence and Applications (IJAIA),3(2), pp. 65-73 en_US
dc.identifier.uri http://dstore.alazhar.edu.ps/xmlui/handle/123456789/431
dc.description.abstract In this paper we present a technique that employ Artificial Neural Networks and expert systems to obtain knowledge for the learner model in the Linear Programming Intelligent Tutoring System(LP-ITS) to be able to determine the academic performance level of the learners in order to offer him/her the proper difficulty level of linear programming problems to solve. LP-ITS uses Feed forward Back-propagation algorithm to be trained with a group of learners data to predict their academic performance. Furthermore, LP-ITS uses an Expert System to decide the proper difficulty level that is suitable with the predicted academic performance of the learner. Several tests have been carried out to examine adherence to real time data. The accuracy of predicting the performance of the learners is very high and thus states that the Artificial Neural Network is skilled enough to make suitable predictions. en_US
dc.language.iso en_US en_US
dc.subject Linear Programming en_US
dc.subject Intelligent Tutoring System en_US
dc.subject back-propagation neural network en_US
dc.subject Artificial Neural Networks en_US
dc.title PREDICTING LEARNERS PERFORMANCE USING ARTIFICIAL NEURAL NETWORKS IN LINEAR PROGRAMMING INTELLIGENT TUTORING SYSTEM en_US
dc.type Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account