Personalized Book Recommendation to Young Readers: Two Online Prototypes and A Preliminary User Evaluation
Pages 413 - 416
Abstract
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.
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Index Terms
- Personalized Book Recommendation to Young Readers: Two Online Prototypes and A Preliminary User Evaluation
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Published In
August 2020
611 pages
ISBN:9781450375856
DOI:10.1145/3383583
- General Chairs:
- Ruhua Huang,
- Dan Wu,
- Gary Marchionini,
- Program Chairs:
- Daqing He,
- Sally Jo Cunningham,
- Preben Hansen
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- SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
- SIGIR: ACM Special Interest Group on Information Retrieval
- IEEE: Institute of Electrical and Electronics Engineers
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Association for Computing Machinery
New York, NY, United States
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Published: 01 August 2020
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JCDL '20: The ACM/IEEE Joint Conference on Digital Libraries in 2020
August 1 - 5, 2020
Virtual Event, China
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