Efficiency or Engagement: Comparison of Book Recommendation Approaches in English Extensive Reading

Authors

  • Kensuke Takii Graduate School of Informatics, Kyoto University, Japan Author
  • Brendan Flanagan Academic Center for Computing and Media Studies, Kyoto University, Japan Author
  • Hiroaki Ogata Academic Center for Computing and Media Studies, Kyoto University, Japan Author

Abstract

Reading is one of the essential skills in mastering English as a foreign language (EFL). Extensive reading (ER), which is oriented to readers’ pleasure, has been proved to improve various skills of language learning, such as reading, writing, vocabulary, learners’ attitudes etc. Besides, many recommender systems for students have been developed, including systems which recommend English lessons the learner should take next. These systems could foster their positive attitudes to learning, but few studies have dealt with a problem, i.e., which is the better approach to improve learners’ English skills, efficiency-oriented or engagementoriented. In this paper, we focus mainly on EFL learners’ vocabulary and reading speed, and introduce two English book recommendation methods for Japanese junior-high school students, one of which utilizes knowledge map (KM) and is oriented toward efficiency of learning, and the other employs content-based filtering and aims to promote learners’ engagement. We also propose experimental methods of verifying whether each approach has a positive effect and of comparing which can improve learners’ skills better.

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Published

2020-11-23

How to Cite

Efficiency or Engagement: Comparison of Book Recommendation Approaches in English Extensive Reading. (2020). International Conference on Computers in Education. https://library.apsce.net/index.php/ICCE/article/view/4070