Improving the Personalized Analysis of Network Education based on Recommendation Algorithms

Le résumé fourni par la source

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 "guiding algorithm," "approaching algorithm," and "moving away from algorithm," to provide references for the realization of "recommendation algorithm + university network education" and promote the healthy development of university network education.

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