The blended learning model combining online and offline teaching has been widely promoted in universities due to its greater flexibility and richer course resources. The main research content of this article is to focus on online teaching content, fully utilize fragmented time of students, and recommend reasonable online English learning and reading resources for students. Firstly, the real needs of students for English reading resources were investigated and analyzed from the perspective of students. Through interviews or questionnaires with students from different majors, genders, and learning scenarios, the needs of students were analyzed in depth. Then, a personalized online English reading resource recommendation model based on multi-source fusion was established. The model is divided into four levels: data collection module, multi-source information fusion module, information aggregation module, and application layer module. Finally, in order to verify the effectiveness of the method proposed in this article, real school students were selected as the target audience for recommendation. A model was used to obtain the demand profile of English reading resources from students, and then targeted reading resources were provided. The recommendation results met the requirements of the strategy design in this article.
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