Theoretical Research on Dynamics of Learning Interaction in Multiple Networks Field

2016 Fiscal Year Final Research Report

• Project/Area Number: 25282058
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Partial Multi-year Fund
• Section: 一般
• Research Field: Educational technology
• Research Institution: Hiroshima University
• Principal Investigator: Yasutake Koichi 広島大学, 社会(科)学研究科, 准教授 (80263664)
• Co-Investigator(Kenkyū-buntansha): 中村 泰之 名古屋大学, 情報科学研究科, 准教授 (70273208) ; 多川 孝央 九州大学, 情報基盤研究開発センター, 助教 (70304764) ; 山川 修 福井県立大学, 学術教養センター, 教授 (90230325)
• Co-Investigator(Renkei-kenkyūsha): SUMIYA TAKAHIRO 広島大学, 情報メディア教育研究センター, 准教授 (90231381) ; INOUE HITOSHI 九州大学, 情報基盤研究開発センター, 准教授 (70232551)
• Project Period (FY): 2013-04-01 – 2017-03-31
• Keywords: 学習科学 / ラーニング・アナリティクス / 社会物理学 / 学習分析 / 教育工学 / 理論モデル

Outline of Final Research Achievements

In this research, we proposed the brand-new Learning Analytics approaches, which are very different from traditional ones in the areas of Learning Sciences and/or Educational Engineering. What is important and new methodologically is that our research is mathematical and computational one. Our achievements are as follows; (1) We planed and managed a lot of research seminars, forums, discussion sessions in conferences in terms of Learning Analytics (FIT2013, JSET2013, JSiSE2014, JSiSE2014, and so on). (2) We investigated relationships between "Learners Collaborative Structures" and the effects using theoretical network simulation models. (3) We expanded our research to analyze learners activities in "micro-scopic" levels. In this research, we found that the aggregated probability distribution of learners physical rhythm
(acceleration) characterize "Power Distribution" if the learning community grow positively.

Free Research Field

社会経済物理学