Improving the Personalized Analysis of Network Education based on Recommendation Algorithms
Xuefeng Hu, Haijuan Zhou, Yanhua Su
Journal of Intelligent Computing, Vol. 16, No. 2, 2025.
DOI: https://doi.org/10.6025/jic/2025/16/2/60-70
Link: https://www.dline.info/jic/fulltext/v16n2/jicv16n2_2.pdf
Abstract:
With the rapid development of science and technology, the internet and new media have entered the era of
algorithmic recommendation. This article investigates and analyzes the new characteristics of content
dissemination and discourse expression in university network education from the perspective of
recommendation algorithms. Addressing the practical dilemmas of value bias at different stages of integration,
decreased independent thinking ability of learners, and divergence of social values, this study explores the
incorporation of algorithmic recommendation techniques into university network education. It proposes
guiding strategies, such as the â€œguiding algorithm,â€ â€œapproaching algorithm,â€ and â€œmoving away from
algorithm,â€ to provide references for the realization of â€œrecommendation algorithm + university network
educationâ€ and promote the healthy development of university network education.