Electronic learning- virtual
H. Banadkouki; K. Abbasi; A. Rahati
Abstract
: E-learning, by eliminating the limitation of space and time to attend in classes, has found a widespread use in communication between students and teachers. On the other hand, intelligence components, such as providing feedback and hint for students will increase the quality of education. But current ...
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: E-learning, by eliminating the limitation of space and time to attend in classes, has found a widespread use in communication between students and teachers. On the other hand, intelligence components, such as providing feedback and hint for students will increase the quality of education. But current methods for implementation of intelligent have high costs. This paper introduces a new method to provide intelligent e-learning at a low cost. Intelligence emergences in two components, including knowledge assessment and selection of appropriate hint during the problem solving. In this approach, a Bayesian network utilized to assess student knowledge and an Artificial Neural network utilized to select the appropriate hint. The structure of both networks is determined by training data. The proposed method is implemented and assessed in an e-learning system. The above 90 percent accuracy in both networks and low implementation cost are of the important advantages of the proposed method. The structure of the two networks which is based on training data makes it possible to use it in a variety of systems use e-learning systems with a diverse range of knowledge.
Electronic learning- virtual
F. Zolfaghari; A. Rahati
Abstract
Designing an educational system is costly and a time consuming task, hence, providing electronic learning modules according to the characteristics of each learner in order to reduce the learning time and increase productivity of education is very important. The purpose of this study is to provide an ...
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Designing an educational system is costly and a time consuming task, hence, providing electronic learning modules according to the characteristics of each learner in order to reduce the learning time and increase productivity of education is very important. The purpose of this study is to provide an electronic module according to the learning characteristics of each student, using some of the e-Learning standards, learning theories , memetic algorithm and also assess the learning outcomes of this approach. At the stage of subject preparation to teach each concept, a set of maximum possible learning activities is provided with different materials such as slides, lectures, etc. The compatibility between the activities and characteristics of student who want to learn is produced based on the theory of Folder on learning styles and Bloom's theory for knowledge classification. Student learning styles are designed based on a questionnaire using Folder approach and testing of his/her knowledge is extracted based on Bloom's theory and learning path which is include the proper ordering of learning activities is produced based on memetic algorithm. The populations of this study were 40 girls of third-year computer science class of high school in Zahedan. They were selected randomly. They have been subdivided into two groups of 20 randomly. The proposed system is trained with 20 people and 20 people have traditionally learned their lesson. Comparison between the proposed approach and traditional method in term of quality of education were performed. The results indicate that the proposed method has good quality.
