Learning Support System for Providing Page-wise Recommendation in e-Textbooks

ID: 54533 Type: Full Paper
  1. Keita Nakayama, Masanori Yamada, Atsushi Shimada, Tsubasa Minematsu, and Rin-ichiro Taniguchi, Kyushu University, Japan

Wednesday, March 20 2:15-2:45 PM Location: Melrose 1 View on map

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Abstract: Thanks to the increase in the amount of information on the Internet and the spread of ICT-supported educational environments, much attention has been paid to learning support based on smart recommendation technologies. In this research, we support learning by recommending detailed information about each page of e-textbooks. We developed a recommender system that extracts important keywords on each page of an e-textbook and retrieves related websites to support students’ understanding of lecture contents. In this paper, we explain the details of the recommender system and report the experimental results.

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