Presentation	2011/5/12 A Method of Extracting Diverse Spatial Characteristics from the Field of Real-World Learning MASAYA OKADA, MASAHIRO TADA,
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Abstract(in English)	Recent research on educational support acknowledges the importance of experienced-based learning in the world (i.e., real-world learning). Differently from classroom learning, real-world learning is done through interaction of a learner and the world. Thus, a real-world learning field is the key to promoting learners' diverse interaction and learning effects. We propose an analysis method to extract spatial characteristics of a real-world learning field by the technologies of ubiquitous sensing and knowledge externalization. Our analysis confirmed that real-world knowledge was ubiquitously but unevenly distributed in the world. Our method to grasp the diversity of intellectual activities is fundamental to the effective redesign of learners' interaction with the world.
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Paper #	Vol.2011-GN-80 No.11
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Conference Information
Committee	LOIS
Conference Date	2011/5/12(1days)
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Registration To	Life Intelligence and Office Information Systems (LOIS)
Language	JPN
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Title (in English)	A Method of Extracting Diverse Spatial Characteristics from the Field of Real-World Learning
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1st Author's Name	MASAYA OKADA
1st Author's Affiliation	Graduate School of Science and Technology, Shizuoka University()
2nd Author's Name	MASAHIRO TADA
2nd Author's Affiliation	ATR Intelligent Robotics and Communication Laboratories
Date	2011/5/12
Paper #	Vol.2011-GN-80 No.11
Volume (vol)	vol.111
Number (no)	50
Page	pp.pp.-
#Pages	8
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