文献类型：会议论文

英文题名：Automatic prediction of text readability for international Chinese Language education

作者：Zhu, Shuqin[1]; Zhang, Man[2]; Guo, Dongdong[3]

第一作者：朱淑琴

机构：[1] Teacher's College, Beijing Union University, Institute of Science and Technology Education, Beijing Union University, Beijing, 100011, China; [2] College of Liberal Arts, Beijing Normal University, Beijing, 100875, China; [3] Computer School, Beijing Information Science and Technology University, Beijing, 100029, China

第一机构：北京联合大学师范学院

会议论文集：8th International Conference on Innovation in Artificial Intelligence, ICIAI 2024

会议日期：March 16, 2024 - March 18, 2024

会议地点：Tokyo, Japan

语种：英文

外文关键词：International Chinese language education; readability formula; text readability

摘要：This paper studies the text readability influencing factors and its automatic assessment issues in international Chinese language education. First, a graded text corpus was constructed based on international Chinese language textbooks, followed by an analysis of the factors influencing text readability in four dimensions: domain features, surface features, structural features, and functional features. Each feature involves three levels: character, word, and sentence. Finally, a readability formula was constructed based on a multiple linear regression model, which was then subjected to readability analysis and validation. The results show that the goodness of fit R2 of the readability formula constructed in this study is high, in which key factors such as the number of Chinese character types, the proportion of band-1 words, the average number of parts of speech (POS) in sentences, the standard deviation of the number of POS in sentences, the proportion of band-7 words, the proportion of function words, the standard deviation of the number of Chinese character strokes, and the mean of Chinese character grade bands can significantly explain the grade bands of text readability. ? 2024 ACM.