Open Access
SHS Web Conf.
Volume 163, 2023
2023 8th International Conference on Social Sciences and Economic Development (ICSSED 2023)
Article Number 03012
Number of page(s) 5
Section Corporate Decision Making and Brand Operations Sales
Published online 28 April 2023
  1. Reform and Development Research Office of the Party and Government Office of Shanghai Jiaotong University. (1975).Daily briefing. [Google Scholar]
  2. L. Qing, W. Tao (2011) A giant open curriculum model based on connectionism. Chinese Journal of Distance Education, 03: 30–36. DOI: 10.13541/j.cnki.chinade.2012.03.012. [Google Scholar]
  3. J. Castaño-Muñoz, M. Rodrigues (2021) Open to MOOCs? Evidence of their impact on labour market outcomes. Computers & Education., 173: 51–59. [Google Scholar]
  4. D. Yan, Y. Yang, W. Rihan, Z. Ziyuan, L. Yana, et al (2021) Study on students' MOOC cognition and learning behavior. Journal of Baotou Medical College 9: 97–101+110. DOI: 10.16833/j.cnki.jbmc.2021.09.022. [Google Scholar]
  5. L. Lingyao, Johnson J., W. Aarhus, D. Shah, (2022) Key factors in MOOC pedagogy based on NLP sentiment analysis of learner reviews: What makes a hit. Computers & Education., 163: 13–19. [Google Scholar]
  6. Y. Yao (2022). Research on the quality assurance of university MOOCs in the post-epidemic period (Master's degree thesis, Three Gorges University) DOI: 10.27270/d.cnki.gsxau.2022.000006. [Google Scholar]
  7. R. Campos, R. P. dos Santos, J. Oliviera., (2022) Providing recommendations for communities of learners in MOOCs ecosystems. Expert Systems with Applications., 205: 123–126 [CrossRef] [Google Scholar]
  8. Y. Yue, X. Jingyue, Z. Chengxing, J. He (2021) Investigation of the stickiness status of medical students and the analysis of their influencing factors. China Medical Education Technology., 2:167–171 DOI: 10.13566/j.cnki.cmet.cn61-1317/g4.202102006. [Google Scholar]
  9. D. Yihua. (2019). Analysis of the influencing factors of college students' willingness to use MOOC (Master's degree thesis, Dalian University of Technology) DOI: 10.26991/d.cnki.gdllu.2019.001510. [Google Scholar]
  10. L. Karen, M. Hans, X. Ying et al. (2020) Teacher perspectives of self-efficacy and remote learning due to the emergency school closings of 2020., Educational Media International., 2: 58–61 DOI: 10.1080/9523987.2021.1930481 [Google Scholar]
  11. J. Alexander, M. Barcellona, S. McLachlan et al. (2019) Technology enhanced learning in physiotherapy education: Student satisfaction and knowledge acquisition of entry-level students in the United Kingdom., Research in Learning Technology., 27: 10–13 DOI: 10.25304/rlt.v27.2073 [CrossRef] [Google Scholar]
  12. P. M. Moreno-Marcos, P. J. Muñoz-Merino, J. Maldonado-Mahauad (2020) Temporal analysis for dropout prediction using self-regulated learning strategies in self-paced MOOCs., Computers & Education.,145:122–125 [Google Scholar]
  13. Z. Qing. (2022). Study on the influencing factors of MOOC continuous use intention among agricultural college students (Master's dissertation, Jiangxi Agricultural University) DOI: 10.27177/d.cnki.gjxnu.2022.000442. [Google Scholar]

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