Approach Based on Artificial Neural Network to Improve Personalization in Adaptive E-Learning Systems

  • Ibtissam AzziEmail author
  • Adil Jeghal
  • Abdelhay Radouane
  • Ali Yahyaouy
  • Hamid Tairi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1076)


Exploring the role of artificial intelligence in improving learner’s performance in E-learning systems is an important motivating research area that tries to combine E-learning and traditional tutoring opportunities. Presenting a personalized learning is one of the opportunities that is important in order to increase the effectiveness of an individual learning. In this paper, we investigate the use of soft computing technique to handle the personalization problems in E-learning systems, particularly the problem of the course design regarding the learner’s background (prerequisites). In this mind, we present an approach based on artificial neural network which is able to provide learner with the most suitable learning materials. To have information about the learner’s knowledge background, the Web data are used as the input of the neural network. The architecture of the artificial neural network is described, and the performances of our approach are illustrated by simulation test.


Adaptive E-learning systems Personalization Learning materials Knowledge background Artificial neural networks Web mining 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Ibtissam Azzi
    • 1
    Email author
  • Adil Jeghal
    • 2
  • Abdelhay Radouane
    • 3
  • Ali Yahyaouy
    • 1
  • Hamid Tairi
    • 1
  1. 1.LIIAN, Department of Informatics Faculty of Science Dhar-MahrazUniversity of Sidi Mohamed Ben AbdellahAtlas-FezMorocco
  2. 2.Groupe Sup’ManagementFezMorocco
  3. 3.Département d’informatiqueCentre Régional Des Métiers de l’éducation et de Formation, C. R. M. E. F.FezMorocco

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