Abstract In order to solve the problem of teachers not assigning and evaluating student writing but not completely trusting AI raters, I created and tested a rating scheme in which an AI model would rate students’ language use based on understandable criteria and humans would quickly check the AI responses while rating content and structure. Teachers tried the scheme and improvements were made based on new data and newly available research. An online practice tool was also created for students so that they could understand how the AI would rate their language use and practice accordingly. The AI rating models were improved over the course of three semesters based on student data and the ratings of external professional raters. As a result, an increasing number of teachers used the rating scheme, the number of students that practiced writing and were evaluated increased university-wide, and reasonable levels of fairness assessment were maintained.

<标题>: 一种人机整合评分系统以提高第二语言写作：以日语学习者的通用学术英语为例 Citation Key: spring2023