Mobile Vocabulometer: A Context-based Learning Mobile Application to Enhance English Vocabulary Acquisition

言語英語
種類国際会議等の予稿
著者Kohei Yamaguchi, Motoi Iwata, Andrew Vargo, Koichi Kise
論文名Mobile Vocabulometer: A Context-based Learning Mobile Application to Enhance English Vocabulary Acquisition
論文誌名Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers (UbiComp/ISWC '20 Adjunct)
ページ数4
発表場所UbiComp/ISWC ’20
査読の有無有
発表の種類口頭ならびにポスター発表
年月2020年9月
分野リーディングライフログ
DOI10.1145/3410530.3414406
URLhttps://doi.org/10.1145/3410530.3414406
キーYamaguchi2020_ISWC (id=1755)

要約

Vocabulary acquisition is the basis of learning a language, and using flashcards applications is a popular method for learners to memorize the meaning of unknown words. Unfortunately, this method alone is not effective for learners to remember the meaning of words when they appear in sentences. To solve this, we developed the Mobile Vocabulometer which allows users to acquire new vocabulary with context-based learning. Based on the correlation between comprehension and interests, we use the learning materials that adapt to users' interests and language skills. This system harnesses the power of the original Vocabulometer, and modifies it to be effective for mobile learning. An experiment on Japanese university students showed that, overall, learners achieved better results compared to using a simple flashcard application. This result indicates that this system provides a significant advantage over context-free learning systems.

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