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JAMIOLAS 3.0: Supporting Japanese Mimicry and Onomatopoeia Learning Using Sensor Data
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Author(s): 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)and Yoneo Yano (University of Tokushima, Japan)
Copyright: 2012
Pages: 15
Source title:
Refining Current Practices in Mobile and Blended Learning: New Applications
Source Author(s)/Editor(s): David Parsons (The Mind Lab by Unitec, New Zealand)
DOI: 10.4018/978-1-4666-0053-9.ch008
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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.
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