Using STM to Investigate Learner Satisfaction and Its Influencing Factors in LMOOCs
Learner satisfaction is a crucial factor for the continuous development of Language MOOCs.Traditionally,learner satisfaction has been studied using methods such as surveys and interviews.This study employs frequency analysis and structural topic model(STM)to investigate the current status of learner satisfaction and its influencing factors based on a self-built large-scale corpus of course reviews form Language MOOCs.Visual analysis techniques are utilized to explore the types of topics that learners are concerned about and their interrelationships.Additionally,the study examines the moderating effects of two external covariates,course type and teacher team size,on learner satisfaction.The results reveal that learners pay particular attention to negative topics such as exams,assessments,and technical issues.Learners'learning expectations and teachers'instructional styles are identified as the main influencing factors.Positive topics such as knowledge and academic aspects are significant and serve as key drivers for enhancing the quality of foreign language MOOCs.Moreover,there are interaction effects between course type,teacher team size,and the knowledge and academic aspects.The findings have implications for further enhancing the quality of Language MOOCs.
Language MOOCscourse reviewlearner satisfactionSTM
NETL
NSTL
万方数据
