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Web of Proceedings - Francis Academic Press
Web of Proceedings - Francis Academic Press

Design of a Personalized Learning Recommender System for English Learners

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DOI: 10.25236/ACEPMB.2019.024


Zhang Yi

Corresponding Author

Zhang Yi


Taking the platform of English listening as an example, with fully analyzation of students’ learning behavior and characteristics, the purpose of this article aims at designing a hybrid Personalized Learning Recommender System (a personalized intelligent information service in E-learning teaching platform) based on the theory of constructivism, with learners as the center of it. According to the topic and the factors of difficulty level, people can use collaborative filtering recommendation and interpersonal correlation algorithm technology to classify the system’s recommendations. The system recommends personalized learning contents based on the learners’ background, English cognition and interest, and it teaches students in accordance with their aptitude. In addition, the design of the system takes into account of the need of students’ autonomous learning, interactive learning, group activities, and it realizes the function of interactive learning, bringing instant communication between teachers and students or students within themselves into realization.


PLRS; English listening teaching; CALL; cognition and interest