Japanese / English

Detail of Publication

Text Language English
Authors Kohei Yamaguchi, Motoi Iwata, Andrew Vargo, and Koichi Kise
Title Mobile Vocabulometer: A Context-based Learning Mobile Application to Enhance English Vocabulary Acquisition
Journal 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)
Number of Pages 4 pages
Location UbiComp/ISWC ’20
Reviewed or not Reviewed
Presentation type Oral and Poster
Month & Year September 2020
Abstract 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.
DOI 10.1145/3410530.3414406
URL https://doi.org/10.1145/3410530.3414406
Back to list