Special Track 2

Learning analytics for next phase: Empowerment of learning using learning analytics

Educational/learning environments and competencies required in the global society have changed, as information technologies are advancing. Along with this change, educational technology researchers are developing various solutions based on learning theories. Learning analytics research is one of the relevant research areas, and it contributes to improving educational and learning systems using various types of high end information technologies, such as making predictions using pattern analysis. The development of new technologies always presents a great challenge for educational and information technology researchers.

However, learning analytics is transitioning to the next phase: the practical use of learning analytics. It is best to explore the following topics, which are relevant to this phase:

  • User-centered system design for learning analytics
  • Decision-making support using learning analytics
  • Organizational support for learning analytics (e.g., learning support and teaching skill development for learning analytics)
  • Instructional design based on learning analytics
  • Feedback based on learning analytics
  • Policy for learning analytics–based practice
  • New technologies for stakeholders’ “sense-making” in learning analytics
  • Data literacy development for learning analytics
  • Teaching analytics and its improvement process

The special track on “learning analytics for next phase: Empowerment of learning using learning analytics” will be discussed, but this track welcomes various learning analytics-related topics.
For example

  • Big data analytics for education and learning
  • Infrastructure learning analytics
  • Scalability of technologies for learning analytics
  • Learning analytics using IoT
  • Social interaction analysis in virtual learning environments
  • Learning analytics in real classroom and learning space
  • Learning analytics in Game-based learning
  • Prediction algorithm for learning analytics
  • Technology standards for learning analytics
  • Learning dashboard design, development, and evaluation
  • Visualization technology for learning analytics

Track Chairs

  • Atsushi Shimada, Kyushu University, Japan
  • Stephen Yang, National Central University, Taiwan
  • Hiroaki Ogata, Kyoto University, Japan
  • Yoshiko Goda, Kumamoto University, Japan
  • Hiroaki Kawashima, University of Hyogo, Japan
  • Tsubasa Minematsu, Kyushu University, Japan
  • Masanori Yamada, Kyushu University, Japan

Program Committee

  • Gökhan Akçapınar, Hacettepe University, Turkey
  • Tosti Hsu-Cheng Chiang, National Taiwan Normal University, Taiwan
  • Hironori Egi, The University of Electro-Communications, Japan
  • Brendan Flanagan, Kyoto University, Japan
  • Maiya Hori, Kyushu University, Japan
  • Anna Y.Q. Huang, National Central University, Taiwan
  • Chester S.J. Huang, National Central University, Taiwan
  • Min Lu, Kyushu University, Japan
  • Owen H.T. Lu, National Pingtung University, Taiwan
  • Rwitajit Majumdar, Kyoto University, Japan
  • Kae Nakaya, Tokyo Institute of Technology, Japan
  • Misato Oi, Kyushu University, Japan
  • Yuta Taniguchi, Kyushu University, Japan
  • Hideaki Uchiyama, Kyushu University, Japan
  • Jingyun Wang, Kyushu University, Japan
  • Takayoshi Yamashita, Chubu University, Japan
  • Wilson T.C. Yang, National Chiao Tung University, Taiwan
  • Chengjiu Yin, Kobe University, Japan

Contact

la@tale2020.org