MOOC Quality Characterization Using the"Theme-Emotion"Coupled Analysis on User Comments
MOOC comments contain a wealth of user opinions and emotional infor-mation,reflecting the quality demands and satisfaction from the user's perspective.This study constructs a model for the quality characterization of MOOC based on the"Theme-Emotion"coupled analysis of user comments.Specifically,it utilizes LDA to extract thematic information from comment texts,representing dimensions for as-sessing MOOC quality.Furthermore,it employs BERT for emotion classification to characterize user satisfaction and attention towards MOOC quality.The study takes"Chinese University MOOC"as an example to analyze the MOOC quality charac-terization results.The findings reveal that the quality assessment dimensions vary in MOOCs of different subject areas,user satisfaction and attention towards each dimen-sion differ for different MOOCs,and the quality assessment dimensions have varying significant impacts on MOOC quality.The proposed MOOC quality characterization model can be generalized to various online course platforms with user comments,offering a fine-grained representation of course quality.This model provides precise criteria for builders to design and improve courses and for learners to select courses,contributing to the optimization of MOOC development and user experience.
User commentsMOOC qualityquality characterization modelsenti-ment analysistheme mining
NETL
NSTL
万方数据
