An Analysis of Characteristics of Learning Community Using Accelerometer Sensor Data with High Sampling Rate

ID: 52511 Type: Poster/Demo
  1. Takahiro Tagawa, Kyushu University, Japan
  2. Osamu Yamakawa, Fukui Prefectural University, Japan

Wednesday, March 28 5:45 PM-7:00 PM Location: Edison Ballroom D View on map

Presider: Rashid Khan, DCC- King Fahd University of Petroleum and Minerals, Dhahran Saudi Arabia, Saudi Arabia

Abstract: We investigate how characteristics of a group in group learning situation can be analyzed using accelerometer sensor data. Distributions of the time length of active body movements showed little variation between example cases. The distributions of the period of a cycle of body movement showed the difference between the case by whether the case includes out-of-classroom activities or not, at certain range of period. This can be regarded that we can distinguish normal classroom learning activities and extra activities with intentional body movements. On the other hand, index values (power exponents) of distribution of duration of body movements (of respective students) in a case showed a negative and weak correlation with the scores of Emotional Intelligence (EI) of students. These findings suggest that these analysis can be applied to understand the status of students and/or groups. For these analysis, the accelerometer sensor with high sampling rate was necessary and essential for collecting data of duration of active time and period of body movements with sufficient precision.


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