Abstract
Spontaneity, which is an attitude of voluntarily participating in activities, and sociality, which is the tendency to interact with others and to keep good relationships with others, are developed during childhood and are the fundamental attitudes in social life. To investigate the development of spontaneity and sociality, several researchers have used Learning Stories, in which on-site observers elaborately describe behaviors of each child. However, Learning Stories would need too much labor cost for monitoring and qualitatively evaluating many children. This study proposed a new method of quantitative analysis and visualization to evaluate children’s group behavior related to both spontaneity and sociality during eurhythmics, in which children move in tune with music. It used position data of children for the analysis and visualization. The results showed that children in the 6-year-old class got to work closely with other children in a short time compared to those in the 5-year-old class. Such group behavior would include the actions to spontaneously make a good relationship with others. We hope that this study will be meaningful in creating practical and useful curricula and support methods for children at nurseries.
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Notes
- 1.
We administered the questionnaire about birth dates of children to their parents. However, we could not get the information of one male and three females in class A, and one female in class B. In addition, one female in class A quit the nursery on the way. The ranges of age were therefore calculated after excluding these children.
- 2.
Software ELAN URL: https://tla.mpi.nl/tools/tla-tools/elan/.
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Acknowledgment
This study was supported by JSPS KAKENHI Grant Number 26118003.
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Ichikawa, J., Fujii, K., Nagai, T., Omori, T., Oka, N. (2018). Quantitative Analysis and Visualization of Children’s Group Behavior from the Perspective of Development of Spontaneity and Sociality. In: Rodrigues, A., Fonseca, B., Preguiça, N. (eds) Collaboration and Technology. CRIWG 2018. Lecture Notes in Computer Science(), vol 11001. Springer, Cham. https://doi.org/10.1007/978-3-319-99504-5_13
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