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.
Naser REF ) used knowledge extracted from learner models to determine the academic performance of a learner in order to offer him the proper difficulty level of problems to solve.
PREDICTING LEARNERS PERFORMANCE USING ARTIFICIAL NEURAL NETWORKS IN LINEAR PROGRAMMING INTELLIGENT TUTORING SYSTEM
International Journal of Artificial Intelligence & Applications
Computer Science