学生のPHANさんらが国際会議KICSS 2022においてKunifuji Awardを受賞

 学生のPHAN, Huy Thanhさん(博士前期課程2年、長谷川研究室)、人間情報学研究領域の長谷川 忍教授および谷 文助教が国際会議The 17th International Conference on Knowledge, Information and Creativity Support Systems(KICSS 2022)においてKunifuji Awardを受賞しました。

 KICSS 2022は、知識科学、情報システム、システム科学および創造性支援システムに関する分野における国際的な研究者間における技術と知識の交流を図ることを目的とした国際会議です。
 今回、KICSS 2022は令和4年11月23日から25日にかけて京都大学にて開催されました。


Implementation of Automated Feedback System for Japanese Essays in Intermediate Education

Huy Thanh PHAN, Shinobu HASEGAWA, Wen GU

Traditional Automated Essay Scoring (AES) only provides students with a holistic score, unable to provide meaningful feedback on students writing. Holistic, structure, style, word, and readability are chosen from the 6+1 writing-trait theory to create an Automated Essay Feedback (AEF) for Japanese L1 students. By combining these rule-based traits with a data-driven model, we created a hybrid system that can automatically grade and give feedback to students. The system automatically identifies parts of student writing that need improvement, then recommends corrective and suggestive feedback. Our contributions are twofold: design a 5-writing-trait AEF for Japanese L1 students and implement the holistic corrective writing-trait.

Receiving the Kunifuji Award at the KICSS 2022 Conference is a great honor for us. We would like to take this opportunity to express our gratitude to Prof. Hasegawa, for always encouraging us to pursue this research. We would also like to thank all of our colleagues, family members, friends, and loved ones who helped us receive this award. This award validates our beliefs, motivates us to work even harder, and inspires us to do better in the future. Despite the fact that problems frequently arose during our research, they were resolved one by one through consistency and persistence. We hope that our efforts will benefit educational research in the long run.