| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2014: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2013: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2012: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Outline of Final Research Achievements |
This study focused on improving teaching effect by feedback students’ learning status using activity recognition. We developed a learning activity detecting system with motion smart sensors to quantify and visualize the learners’ activities. As a result, learning activities could be measured wirelessly with a 9-axis motion sensor. And 5 different activities could be classified automatically with a recognition rate of 98.5% after filtering noises, extracting feature characteristic and machine learning. Also the learning activities are associated with brain activities by electroencephalogram analysis. The results of the study show that teaching methods and teaching effects could be improved by feedback classified learning activities with smart motion sensors.
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