Using Recommender Systems for Matching Students with Suitable Specialization: An Exploratory Study at King Abdulaziz University

Authors

  • Khloud Alshaikh King Abdulaziz University
  • Naela Bahurmuz King Abdulaziz University
  • Ola Torabah King Abdulaziz University
  • Sara Alzahrani King Abdulaziz University
  • Zainab Alshingiti King Abdulaziz University
  • Maram Meccawy King Abdulaziz University

DOI:

https://doi.org/10.3991/ijet.v16i03.17829

Keywords:

Artificial Intelligence, Education, Machine learning, Recommender Systems.

Abstract


In Saudi Arabia, all high school graduates who want join local universities have to go through a preparatory year before selecting their specific specialization/major. One of the most concerning issues for those fresh undergraduate college students is the selection of their specialization. College specialization selection is critical for them, as their academic and career future will be affected by this decision. An un-suitable specialization selection will have unfortunate consequences, not only on the students' future but also on the university’s resources and budget. This paper sug-gests a solution to this problem by introducing a preliminary study of a recommend-er system (RS), which will recommend the appropriate specialization for the students based on various tests and grades during the preparatory year at King Abdulaziz University (KAU). The proposed system guides students through their specialization selection process based on their abilities. The collaborative filtering technique was used to build the RS and K-fold cross-validation was adopted to evaluate its accura-cy and performance. The results showed the prediction of a specialization for each student with good accuracy ratio. These promising initial results provide a feasible solution to assess this issue further in future studies.

Author Biographies

Khloud Alshaikh, King Abdulaziz University

Information system department

Naela Bahurmuz, King Abdulaziz University

Information system department

Ola Torabah, King Abdulaziz University

Information system department

Sara Alzahrani, King Abdulaziz University

Information system department

Zainab Alshingiti, King Abdulaziz University

Information system department

Maram Meccawy, King Abdulaziz University

Information system department

Downloads

Published

2021-02-12

How to Cite

Alshaikh, K., Bahurmuz, N., Torabah, O., Alzahrani, S., Alshingiti, Z., & Meccawy, M. (2021). Using Recommender Systems for Matching Students with Suitable Specialization: An Exploratory Study at King Abdulaziz University. International Journal of Emerging Technologies in Learning (iJET), 16(03), pp. 316–324. https://doi.org/10.3991/ijet.v16i03.17829

Issue

Section

Short Papers