“Towards Automatic Coding of Collaborative Learning Data with Deep Learning Technology,” co-authored by Chihiro Shibata, Senior Assistant Professor of the School of Computer Science, Taketoshi Inaba, Professor of the Department of Liberal Arts, and Kimihiko Ando, Assistant Professor of the Department of Katayanagi Advanced Research Laboratories, presented at The Ninth International Conference on Mobile, Hybrid, and On-line Learning held in Nice, France during March 19-23, 2017, won the Best Paper Award. The act of attaching meaning to statements in a group discussion, from the perspective of judging the quality of that discussion, is commonly called “coding.” In this research paper, the co-authors propose an automatic coding method using leading-edge artificial intelligence technology. The research was carried out cross-departmentally. First, the co-authors used a cloud-based system to determine the appropriate coding for each statement. They used conversational data from actual discussion in student-participatory exercises to identify the role of each statement. Based on that, the actual data was coded manually. Later, they used deep learning methods so that the coding can be done automatically with a calculator. As a result, the co-authors found a coding method with higher precision compared to existing automatic coding methods that had been used in past studies. The paper was prepared as part of a research led by Professor Inaba called, “Development and Evaluation of Analysis and Visualization Methods of Educational Big Data with Deep Learning Technology,” which is an on-campus project of the School of Bioscience and Biotechnology.

■Award-winning paper
Towards Automatic Coding of Collaborative Learning Data with Deep Learning Technology
■The Ninth International Conference on Mobile, Hybrid, and On-line Learning　AWARD　WEB
https://www.iaria.org/conferences2017/AwardseLmL17.html

■School of Computer Science Website:
/gakubu/cs/index.html