A personalized task recommendation system for vocabulary learning based on readability and diversity

Haoran XIE, Minhong WANG, Di ZOU, Fu Lee WANG

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Vocabulary learning is the foundation of language acquisition for second language learners. To assist language learners’ vocabulary learning, this research investigated a personalized task recommendation system based on readability and diversity. A word learning theory, the involvement load hypothesis, has also been applied as the theoretical framework of the system to facilitate task recommendation. Ten Chinese learners of English were invited to participate in the research and used the system for vocabulary learning for around two weeks. These students were all intermediate learners. The participants’ learning experience, outcomes, motivation and attitude were measured respectively using questionnaires, pretests, posttests, and interviews. The results showed that the participants were very satisfied with the learning experience, and positive learning outcomes and attitudes were observed. Many students stated that they would love to keep using the proposed recommendation system for future language learning. It is also suggested that the wide use of this system will benefit many self-access language learners. Copyright © 2019 Springer Nature Switzerland AG.
Original languageEnglish
Title of host publicationBlended learning: Educational innovation for personalized learning: 12th International Conference, ICBL 2019, Hradec Kralove, Czech Republic, July 2-4, 2019, proceedings
EditorsSimon K. S. CHEUNG, Lap-Kei LEE, Ivana SIMONOVA, Tomas KOZEL, Lam-For KWOK
Place of PublicationCham
PublisherSpringer
Pages82-92
ISBN (Electronic)9783030215620
ISBN (Print)9783030215613
DOIs
Publication statusPublished - 2019

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vocabulary
learning
language
learning theory
language acquisition
love
experience
student
questionnaire
interview

Bibliographical note

Xie, H., Wang, M., Zou, D., & Wang, F. L. (2019). A personalized task recommendation system for vocabulary learning based on readability and diversity. In S. K. S. Cheung, L.-K. Lee, I. Simonova, T. Kozel, & L.-F. Kwok (Eds.) Blended learning: Educational innovation for personalized learning: 12th International Conference, ICBL 2019, Hradec Kralove, Czech Republic, July 2-4, 2019, proceedings (pp. 82-92). Cham: Springer.

Keywords

  • Personalized learning
  • Word learning
  • Recommendation system
  • Diversity
  • Readability