Towards a New Learning Analytics Based on Complex Networks Sciences and Sociophysics

2017 Fiscal Year Final Research Report

• Project/Area Number: 16K12791
• Research Category: Grant-in-Aid for Challenging Exploratory Research
• Allocation Type: Multi-year Fund
• 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, 准教授 (70304764)
• Project Period (FY): 2016-04-01 – 2018-03-31
• Keywords: 学習科学 / 計算社会科学 / ネットワーク科学 / 教育工学 / 協調学習

Outline of Final Research Achievements

When we began this investigation, Learning Analytics (LA) in Japan moved into a nutshell and pursued in an old-way. The purposes of this research are as follows; (1) To introduce new scientific and mathematical approaches into Learning Analytics (LA), and (2) By these groundworks, to build a solid scientific and methodological foundation of LA as "Data Sciences". Above all else, important considerations of our research are to adopt a new approaches from the domain of Sociophysics and Complex Networks Sciences that are rapidly development areas.
The main contributions in this research are as follows; (1) When collaborate learning operates in a learning community, learners physical activities have a mathematical properties in terms of those accelerations (rhythms) distributions, and (2) Collaborate Learning Activities are affected by a community structures (the structure of multiplex networks of the community).

Free Research Field

計算社会科学