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：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 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 ***,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 *** address this issue,this paper analyzes dialogues in live classrooms of a large online learning platform in China based on natural language processing *** features of interactive types and emotional expression are extracted from classroom *** 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 *** 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 ***,while the metacognitive dialogue illustrates its importance in non-STEM courses,this effect cannot be found in STEM *** high-performing students in non-STEM courses show negative emotion in the last stage of lessons,STEM students show positive emotion.