Mining opinions on LMOOCs: Sentiment and content analyses of Chinese students’ comments in discussion forums

Author:

Peng Jian-EORCID,Jiang YuanlanORCID

Funder

National Office for Philosophy and Social Sciences

Publisher

Elsevier BV

Subject

Linguistics and Language,Education,Language and Linguistics

Reference56 articles.

1. Comparing the effectiveness of Massive Open Online Course (MOOC) and flipped instruction on EFL learners’ reading comprehension;Ahmed;Educational Research International,2022

2. The role of students' motivation and participation in predicting performance in a MOOC;de Barba;Journal of Computer Assisted Learning,2016

3. Introduction. Language MOOCs: An emerging field;Bárcena,2014

4. Language MOOCs: Providing learning, transcending boundaries,2014

5. Analysing student participation in foreign language MOOCs: A case study;Bárcena,2014

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1. Análisis bibliométrico del aprendizaje de lenguas con apoyo tecnológico: Tendencia de LMOOC en China;Innoeduca. International Journal of Technology and Educational Innovation;2023-12-01

2. Optimizing Learning Performance through AI-Enhanced Discussion Forums;2023 14th International Conference on Intelligent Systems: Theories and Applications (SITA);2023-11-22

3. Sentiment Analysis of Student Evaluation of Teaching Based on Bi-LSTM Algorithm;2023 IEEE 15th International Conference on Advanced Infocomm Technology (ICAIT);2023-10-13

4. What matters to LMOOC learners: content and sentiment analyses of learner course reviews;Computer Assisted Language Learning;2023-10-05

5. Mining and visualizing large-scale course reviews of LMOOCs learners through structural topic model;PLOS ONE;2023-05-03

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