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Expert Systems in Academic Advising

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Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2021 (AISI 2021)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 100))

Abstract

For any college or university student, selecting the right courses in which to enrol is a critical choice that has the potential to positively or negatively affects the student’s academic performance. For this reason, universities offer academic advisors, which study the case of each student and recommend the right courses based on the student’s status. This process is expensive and time-consuming, therefore, researchers have proposed solutions to automate it. In this paper, we focus on solutions based on expert systems. To this end, we summarize and analyze six selected works that propose different expert systems to solve the problem of academic advising. The analysis aims to provide an overview about the used approaches as well as highlight areas of improvements. The goal is to help any researcher interested in the problem to take the first step towards learning about existing approaches, their advantages, and their drawbacks. Overall, existing approaches show great potential of expert systems in the problem of academic advising.

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Author information

Authors and Affiliations

  1. Computer Engineering Department, Faculty of Engineering, Cairo University, Cairo, Egypt

    Rania El-Sayed, Shahd Seddik & Lydia W. Rizkallah

Authors
  1. Rania El-Sayed
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  2. Shahd Seddik
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  3. Lydia W. Rizkallah
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Corresponding author

Correspondence to Lydia W. Rizkallah .

Editor information

Editors and Affiliations

  1. Information Technology Department, Cairo University, Faculty of Computers and Artificial Intelligence, Giza, Egypt

    Aboul Ella Hassanien

  2. Faculty of Electrical Engineering and Computer Science, VŠB-Technical University of Ostrava, Ostrava-Poruba, Moravskoslezsky, Czech Republic

    Václav Snášel

  3. Fujian University of Technology, Shulin District, New Taipei, Taiwan

    Kuo-Chi Chang

  4. Faculty of Science, Helwan University, Cairo, Egypt

    Ashraf Darwish

  5. University of Salford, Manchester, UK

    Tarek Gaber

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El-Sayed, R., Seddik, S., Rizkallah, L.W. (2022). Expert Systems in Academic Advising. In: Hassanien, A.E., Snášel, V., Chang, KC., Darwish, A., Gaber, T. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2021. AISI 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 100. Springer, Cham. https://doi.org/10.1007/978-3-030-89701-7_18

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