A review on Recommender Systems for course selection in higher education

Author:

Lynn N D,Emanuel A W R

Abstract

Abstract Recommender systems are widely used in many fields. These systems work by recommending a personalized list of items to users based on their interests and thus helping users to overcome excessive information offered to them. For users such as students, selecting the right courses is a very challenging task while joining a new academic level. Picking the wrong courses may affect a student’s academic life as well as their future career. This paper aims at exploring the use of recommender systems to assist students in selecting courses that correspond to their abilities and interests. The results from this review showed that the Hybrid recommendation approach/system could be the best method to help students to choose the right courses in preparation for their future careers.

Publisher

IOP Publishing

Subject

General Medicine

Reference30 articles.

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Recommender System in Academic Choices of Higher Education: A Systematic Review;IEEE Access;2024

2. KNN-Based Collaborative Filtering for Fine-Grained Intelligent Grad-School Recommendation System;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2024

3. Recommender Systems for Students’ Performance in Higher Educations: A Review;2023 International Conference on Informatics, Multimedia, Cyber and Informations System (ICIMCIS);2023-11-07

4. CoBERT: A Contextual BERT model for recommending employability profiles of information technology students in unstable developing countries;Engineering Applications of Artificial Intelligence;2023-10

5. Recommender systems in education: A literature review and bibliometric analysis;Advances in Mobile Learning Educational Research;2023-09-11

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