JAMIOLAS 3.0: Supporting Japanese Mimicry and Onomatopoeia Learning Using Sensor Data

Bin Hou, Hiroaki Ogata, Masayuki Miyata, Mengmeng Li and Yuqin Liu
Additional contact information
Bin Hou: University of Tokushima, Japan
Hiroaki Ogata: University of Tokushima, Japan
Masayuki Miyata: University of Tokushima, Japan
Mengmeng Li: University of Tokushima, Japan
Yuqin Liu: University of Tokushima, Japan

International Journal of Mobile and Blended Learning (IJMBL), 2010, vol. 2, issue 1, 40-54

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 context-aware learning by either initiating the creation of context or detecting context automatically.

Date: 2010
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 4018/jmbl.2010010103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jmbl00:v:2:y:2010:i:1:p:40-54

Access Statistics for this article

International Journal of Mobile and Blended Learning (IJMBL) is currently edited by David Parsons

More articles in International Journal of Mobile and Blended Learning (IJMBL) from IGI Global
Bibliographic data for series maintained by Journal Editor ().