Title: Wireless mobile technology in innovative teaching in universities

Authors: Min Li

Addresses: College of Marxism, Suqian University, Suqian, 223800, China

Abstract: As wireless mobile technology develops quickly, education has ushered in new development. Based on wireless mobile technology, smart classrooms are becoming more prevalent in modern schooling. Personalised learning breaks through the limitations of time, place, methods, and learning resources. At this stage, with the support of wireless mobile technology, allowing students to conduct personalised learning according to their own interests is the focus of reforming education and teaching. The existing personalised learning resources for students have certain defects in the mining of students' interests, so there are deficiencies in the recommendation of learning resources. Aiming at this problem, through the K-means clustering, a recommendation model for students' personalised learning resources is established. An experiment is conducted using the online learning course data of a university student. Experimental findings indicate that the recommendation model has an accuracy rate of 99.23%. This outperforms the K-means model and the KCF model by 6.28% and 4.06% respectively. Therefore, the improved collaborative filtering recommendation algorithm based on K-means proposed in the study has a good recommendation effect. It can effectively explore students' interests and recommend corresponding learning resources to meet their personalised development needs.

Keywords: wireless mobile technology; innovative teaching; learning resource recommendation; K-means; collaborative filtering.

DOI: 10.1504/IJCSYSE.2025.149210

International Journal of Computational Systems Engineering, 2025 Vol.9 No.2/3/4, pp.130 - 139

Received: 20 Apr 2023
Accepted: 11 Jun 2023
Published online: 20 Oct 2025 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article