@conference {10.1007/978-3-030-89701-7_18,
	title = {Expert Systems in Academic Advising},
	booktitle = {Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2021},
	year = {2022},
	note = {n/a},
	pages = {198{\textendash}207},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {<p>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{\textquoteright}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{\textquoteright}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.</p>
},
	isbn = {978-3-030-89701-7},
	author = {Rania El-Sayed and Shahd Seddik and Lydia W Rizkallah},
	editor = {Aboul Ella Hassanien and V{\'a}clav Sn{\'a}{\v s}el, and Chang, Kuo-Chi and Ashraf Darwish and Tarek Gaber}
}
