A paper co-authored by Takahiro Kanayama (second year graduate student of computer science, Shibata Laboratory) and TUT Instructors Kimihiko Ando, Chihiro Shibata, and Professor Taketoshi Inaba entitled "Using Deep Learning Methods to Automate Collaborative Learning Process Coding Based on Multi-Dimensional Coding Scheme" received the Best Paper Award at the eLmL 2018 International Conference held between March 25 - 29, 2018.

■The awarded paper:
Takahiro Kanayama, Kimihiko Ando, Chihiro Shibata, Taketoshi Inaba, "Using Deep Learning Methods to Automate Collaborative Learning Process Coding Based on Multi-Dimensional Coding Scheme."
in proceedings of eLmL 2018, The Tenth International Conference on Mobile, Hybrid, and On-line Learning, in Rome, Italy, March 25 - 29, 2018.

■Paper summary
The research team studies how to automate the evaluation of the group discussion process used in meetings or in collaborative learning with the use of AI.
As a part of this endeavor, the team developed a new method for "coding," which in this case refers to assigning meaning to each statement in the discussion, and studied its automation using AI. Kanayama presented the results at the above international conference held in Rome. This is the team's second consecutive award following last year. The research for this paper was done as a part of an on-campus project of the Department of Liberal Arts, called the "Development and Evaluation of Analysis and Visualization Methods of Educational Big Data with Deep Learning Technology."

■eLmL 2018 : Awards List
https://www.iaria.org/conferences2018/AwardseLmL18.html

■Graduate School Computer Science Program website:
/grad/cs/index.html