JAMIOLAS 3.0: Supporting Japanese mimicry and onomatopoeia learning using sensor data

Bin Hou, Hiroaki Ogata, Masayuki Miyata, Mengmeng Li, Yuqin Liu, Yoneo Yano

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

In this article, the authors propose an improved context-aware system to support the learning of Japanese mimicry and onomatopoeia (MIO) using sensor data. In the authors' two previous studies, they proposed a context-aware language learning assistant system named JAMIOLAS (Japanese Mimicry and Onomatopoeia Learning Assistant System). The authors used wearable sensors and sensor networks, respectively, to support learning Japanese MIO. To address the disadvantages of the previous systems, the authors propose a new learning model that can support learning MIO, using sensor data and the sensor network to enable contextaware learning by either initiating the creation of context or detecting context automatically.

Original languageEnglish
Pages (from-to)40-54
Number of pages15
JournalInternational Journal of Mobile and Blended Learning
Volume2
Issue number1
DOIs
Publication statusPublished - Jan 1 2010

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Education

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