Leveraging Children’s Behavioral Distribution and Singularities in New Interactive Environments: Study in Kindergarten Field Trips
The behavior observations on young children in new, first-in-the-life environments have significant implications. We can often uniquely observe a child’s unforeseen interaction with the environment and peer-children. It would be not only a piece of discovery but a beginning of an open quest worth exploring. Out-of-classroom activities like kindergarten’s field trips are perfect opportunities, but those are quite different from regular classroom activities where the teachers’ conventional observation methods are hardly practical. This paper proposes a novel approach to extend the teachers’ awareness on the children’s field trip behaviors by means of mobile and sensor technology. We adopt the notion of behavioral distribution and singularities. We estimate the children’s representative behavioral state in a given context, and study the effect of focusing on the behaviors which are unlikely in this context. We discuss our 14-month collaborative study and various qualitative benefits through multiple deployments on actual kindergarten field trips.
KeywordsBehavior distribution singularity children kindergarten field trip smartphone sensor
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- 5.Druin, A.: The Role of Children in the Design of New Technology. Behavior and Information Technology 21(1), 1–25 (2002)Google Scholar
- 6.EcoMote, http://www.ecomote.net/
- 8.Hayes, G.R., Gardere, L.M., Abowd, G.D., Truong, K.N.: CareLog: a Selective Archiving Tool for Behavior Management in Schools. In: CHI 2008, pp. 685–694. ACM (2008)Google Scholar
- 11.Hourcade, J.P.: Interaction Design and Children. Foundations and Trends in HCI 1(4), 277–392 (2007)Google Scholar
- 13.International Commission on Non-Ionizing Radiation Protection. Guidelines for limiting exposure to time-varying electric, magnetic, and electromagnetic fields (up to 300GHz). Health Physics 74(4), 494–522 (1998) Google Scholar
- 16.Lane, N.D., Xu, Y., Lu, H., Hu, S., Choudhury, T., Campbell, A.T., Zhao, F.: Enabling Large-scale Human Activity Inference on Smartphones using Community Similarity Networks (CSN). In: UbiComp 2011, pp. 355–364. ACM, New York (2011)Google Scholar
- 17.MacKenzie, A.A., White, R.T.: Fieldwork in Geography and Long-Term Memory Structures. American Educational Research Journal 19(4), 623–632 (1982)Google Scholar
- 22.Poole, E.S., Miller, A.D., Xu, Y., Eiriksdottir, E., Catrambone, R., Mynatt, E.D.: The Place for Ubiquitous Computing in Schools: Lessons Learned from a School-based Intervention for Youth Physical Activity. In: UbiComp 2011, pp. 395–404. ACM, New York (2011)Google Scholar
- 23.Ramsay, M.C., Reynolds, C.R., Kamphaus, R.W.: Essentials of Behavioral Assessment. John Wiley and Sons, Inc., New York (2002)Google Scholar