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.

Highlights

  • Choosing the right specialization for a fresh college student is one of the most critical decisions in his/her future life

  • Others may select their specializations based on a friend's recommendation, or because it is currently popular among their peers

  • An unsuitable specialization for fresh students has serious consequences for students and universities, with low grades related to higher switching rates, but these specialization switches do not lead to grade improvement [3]

Read more

Summary

Introduction

Choosing the right specialization for a fresh college student is one of the most critical decisions in his/her future life. Selecting inappropriate specialization can lead to unsuitable job and low earnings [1, 4]. This research introduces a Recommender system (RS), which in this context is an artificial intelligence technological assistant tool to support and guide user decisions with relevant information. This can be a great solution for fresh college students, as it efficiently decides the best fit specialization, based on students’ preference and information [5]. It proposes KAURS to help students select the most appropriate specialization by the end of the preparatory year

Literature Review
Data Gathering
The Methodology
Similarity
Prediction
System Analysis and Design
Experiment and Results
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call