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Multimodal Method to Understand Real-world Learning Driven by Internal Strategies
Proceeding

, College of Informatics, Academic Institute, Shizuoka University, Japan ; , Faculty of Informatics, Shizuoka University, Japan ; , Faculty of Science and Engineering, Kindai University, Japan

EdMedia + Innovate Learning, in Vancouver, BC, Canada ISBN 978-1-939797-24-7 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC

Abstract

Education is traditionally designed and practiced in classrooms, but recent research has shown the importance of real-world learning for autonomously searching and obtaining knowledge in and from the world. This paper considers the characteristics of knowledge space that are self-organized inside a learner through bottom-up real-world behavior, and then models a process in which a learner's strategies activate and drive inquiry behavior to achieve knowledge in and from the world. By improving our technologies for multimodal knowledge sensing, this research proposes analytics to code and understand the time-series of learning strategies occurring through learner-environment interactions. As an initial and important step in the research, we analyze learners' possible strategies in the world to find strategies related to the production of inquiry behavior.

Citation

Okada, M., Kuroki, Y. & Tada, M. (2016). Multimodal Method to Understand Real-world Learning Driven by Internal Strategies. In Proceedings of EdMedia 2016--World Conference on Educational Media and Technology (pp. 1248-1257). Vancouver, BC, Canada: Association for the Advancement of Computing in Education (AACE). Retrieved October 17, 2019 from .

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