A personalized recommendation-based mobile learning approach to improving the reading performance of EFL students

In this paper, a personalized recommendation-based mobile language learning approach is proposed. A mobile learning system has been developed based on the approach by providing a reading material recommendation mechanism for guiding EFL (English as Foreign Language) students to read articles that match their preferences and knowledge levels, and a reading annotation module that enables students to take notes of English vocabulary translations for the reading content in individual or shared annotation mode. To evaluate the effectiveness of the proposed approach, an experiment was conducted on a senior high school English course by assigning three classes of students to two experimental groups and a control group. One experimental group learned with the recommendation system with the individual annotation function, the other experimental group learned with the recommendation system with the shared annotation function, while the students in the control group learned with the individual annotation function, but without the recommendation system. The experimental results show that both experimental groups outperformed the control group, but there was no difference in learning outcome between the two experimental groups in terms of learning achievements.