Prediction of Academic Performance of Students in Online Live Classroom Interactions-An Analysis Using Natural Language Processing and Deep Learning Methods

作     者：Yuanyi Zhen Jar-Der Luo Hui Chen 

作者机构：不详 School of Chinese Language and LiteratureBeijing Foreign Studies UniversityBeijing 100089China 

出 版 物：《Journal of Social Computing》 (社会计算（英文）)

年 卷 期：2023年第4卷第1期

页      面：12-29页

核心收录：

学科分类：0710[理学-生物学] 0502[文学-外国语言文学] 050201[文学-英语语言文学] 0401[教育学-教育学] 05[文学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：This work was supported by the Center for Social Network Research of Tsinghua University,Tsinghua’s Research Project(No.2016THZWYY03) the Project of Tencent Social Research Center(No.20162001703). 

主　　题：academic performance prediction live classroom dialogue emotional expression interactive type natural language processing deep learning 

摘      要：Prior studies have shown the importance of classroom dialogue in academic performance,through which knowledge construction and social interaction among students take place.However,most of them were based on small scale or qualitative data,and few has explored the availability and potential of big data collected from online classrooms.To address this issue,this paper analyzes dialogues in live classrooms of a large online learning platform in China based on natural language processing techniques.The features of interactive types and emotional expression are extracted from classroom dialogues.We then develop neural network models based on these features to predict high-and low-academic performing students,and employ interpretable AI(artificial intelligence)techniques to determine the most important predictors in the prediction models.In both STEM(science,technology,engineering,mathematics)and non-STEM courses,it is found that high-performing students consistently exhibit more positive emotion,cognition and off-topic dialogues in all stages of the lesson than low-performing students.However,while the metacognitive dialogue illustrates its importance in non-STEM courses,this effect cannot be found in STEM courses.While high-performing students in non-STEM courses show negative emotion in the last stage of lessons,STEM students show positive emotion.