Improvement of E-learning Based via Learning Management Systems (LMS) Using Artificial Neural Networks
Khaled . M. G Noama, Ahmed Khalid, Arafat A. Muharram, Ibrahim A. Ahmed
Asian Journal of Research in Computer Science · pp. 1–9 · Published 24 Sep 2019
10.9734/ajrcos/2019/v4i130105Abstract
E-Learning nowadays is one of the learning system which uses the latest technologies in the field of innovative learning, it has been an extension of traditional education. The effectiveness of E-Learning lies in achievement of education and improving the student's performance and its reflection on the demands of students by discovering the weaknesses and strengths of the factors affecting distance learning. In this research we have used the multilayered neural networks (feedforward neural network) with an input of five neurons which represent the five criteria (virtual class presence, Discussion during semester, Solving Quiz, Mid-term examination, Assignment), hidden layer has two neurons and the output layers have one neuron. to estimate the performance of the students attending an E-Learning course, feedforward neural network was applied to real data )400 student records (80%) are used for training data and the remaining 100 records (20%) are used as test data, performance = 0.0699), to predict the performance of the students that reflect their real grades.
References (6)
- 1 Experiential Learning : Experience as the Source of Learning and Development
- 2 Neural Networks: A Comprehensive Foundation
- 3 Virtual reality for collaborative e-learning [DOI]
- 4 Question classification for E-learning by artificial neural network [DOI]
- 5 E-Learning Optimization Using Supervised Artificial Neural-Network [DOI]
- 6 Evaluating the Effectiveness of the E-learning Experience in Some Universities in Saudi Arabia from Male Students’ Perceptions
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Showing 5 of 7 known citations — external sources report more than can currently be individually listed.
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