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Personal Vocabulary Recommendation to Support Real Life Needs

  • 2021
  • OriginalPaper
  • Chapter
Published in:
Authors
Victoria Abou-Khalil
Brendan Flanagan
Hiroaki Ogata
Published in
Artificial Intelligence in Education
Publisher
Springer International Publishing

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Abstract

The chapter delves into the disparity between standardized vocabulary curricula and the actual needs of language learners, particularly refugees. It argues that current methods focus too heavily on native speaker usage and fail to address the specific vocabulary requirements of diverse learners. The author introduces the concept of personal vocabulary learning, which empowers learners to control their own educational goals and access vocabulary tailored to their real-life situations. A case study involving Syrian refugees in Lebanon and Germany demonstrates the inadequacy of existing vocabulary lists, such as those from Cambridge English and Duolingo. The chapter proposes a data-driven approach using learners' digital traces to create personalized vocabulary recommendations, suggesting a future where language education is more responsive to individual needs and contexts.
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previous chapter Open Learner Models for Multi-activity Educational Systems
next chapter Artificial Intelligence Ethics Guidelines for K-12 Education: A Review of the Global Landscape
Title
Personal Vocabulary Recommendation to Support Real Life Needs
Authors
Victoria Abou-Khalil
Brendan Flanagan
Hiroaki Ogata
Copyright Year
2021
Book
Artificial Intelligence in Education

Print ISBN: 978-3-030-78269-6

Electronic ISBN: 978-3-030-78270-2

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-78270-2_3
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