Unknown Word Estimation Based on Mobile Learners’ Reading Behavior
Language
Japanese
Type
Proceedings of Japanese Conferences
Authors
Riku Higashimura, Andrew W. Vargo, Motoi Iwata, Koichi Kise
Title
Unknown Word Estimation Based on Mobile Learners’ Reading Behavior
Journal
FIT2022
Presentation number
CK-002
Number of pages
4
Location
慶応義塾大学 矢上キャンパス
Reviewed
Not reviewed
Presentation type
Oral
Date
September 2022
Research fields
Learning Analytics
Key
Higashimura2022_FIT (id=1898)
Abstract
Vocabulary acquisition is a fundamental component of learning a new language. The widespread use of smartphones allows language learners more flexibility in their daily schedules. In order to acquire new vocabulary, words whose meanings are unknown to the individual learner (hereafter referred to as "unknown words") must be included in the language learning process in some way. A simple method for estimating unknown words in a document is to use the frequency of occurrence, which indicates the difficulty level of the word. However, this method may result in missing unknown words. In this study, we aim to improve the accuracy of unknown word estimation by using reading behavior data obtained from smartphone sensors and taking into account the reading behavior of individual learners.
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