Title: Recommender systems in education: systematic review and future outlook

Authors: Feng Wang; Yitong Liu; Zhu Zou; Ze Liu

Addresses: Kunming University of Science and Technology, No. 727 Jingming South Road, Chenggong District, Kunming, Yunnan, China ' Kunming University of Science and Technology, No. 727 Jingming South Road, Chenggong District, Kunming, Yunnan, China ' Kunming University of Science and Technology, No. 727 Jingming South Road, Chenggong District, Kunming, Yunnan, China ' Kunming University of Science and Technology, No. 727 Jingming South Road, Chenggong District, Kunming, Yunnan, China

Abstract: Against the background of increasingly diversified educational contents and learners' demands, continuous growth in the number of users and the scale of educational resources, and diversified educational environments, recommender systems in the field of education face challenges such as cold start, poor scalability, and difficulty in integrating online and offline education. The purpose of this paper is to systematically sort out recommender systems using the systematic literature review method and PRISMA to analyse its different development characteristics in the last decade in terms of the types of recommendation items, recommendation algorithm applications, feature engineering methods, evaluation metrics diversity, system types, etc. Also, this paper focuses on the latest research results in this field in the last five years. Meanwhile, the new challenges and characteristics it faces are elaborated. Finally, the critical future development directions of the field are inferred and foreseen.

Keywords: recommender systems; e-learning; online learning; online education; review; LDA.

DOI: 10.1504/IJLT.2025.151039

International Journal of Learning Technology, 2025 Vol.20 No.4, pp.421 - 449

Received: 29 Oct 2023
Accepted: 20 Mar 2024
Published online: 12 Jan 2026 *

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