Personalized Book Recommendation to Young Readers

Online learning platforms that aim to improve reading interests and proficiency of young readers, particularly students in elementary schools, rarely have automated personalized recommendation services. This study attempts to bridge this gap by developing and evaluating two book recommenders that are integrated into an online learning platform for young readers. A preliminary user experiment was conducted to measure the effectiveness and usability of the recommender prototypes. Results of think-aloud usability testing, post-test questionnaires, and a semi-structured interview verified the feasibility of adding these book recommenders to improve personalization of the online learning platform. Further improvements of the recommenders were also suggested. The user evaluation framework provides a reference for future studies on personalized learning material recommendation.