ISSN 1672-9234 CN 11-5289/R
Responsible Institution:China Association for Science and Technology
Publishing:Chinese Nursing Journals Publishing House Co.,Ltd.
Sponsor:Chinese Nursing Association
Source journal for Chinese Science Citation Database
China Academic Journals Full-text Database
China Core Journal Alternative Database
Chinese Science and Technical Journal Database

Chinese Journal of Nursing Education ›› 2022, Vol. 19 ›› Issue (2): 141-146.doi: 10.3761/j.issn.1672-9234.2022.02.008

• Nursing Education • Previous Articles     Next Articles

A survey of online deep learning of nursing master students

DING Lian-di(),LI Ming-jin()   

  • Received:2021-05-06 Online:2022-02-15 Published:2022-02-18
  • Contact: Ming-jin LI E-mail:2332408762@qq.com;1374244957@qq.com

Abstract:

Objective To investigate the current status and influencing factors of online deep learning of nursing master students. Methods A convenience sampling was used to recruit 287 nursing master students from five colleges and universities in Northeast China. A package of questionnaires was used including the General information questionnaire,the Scale of Students Making Deep Learning,the Network Learning Space Scale,the Online Learning Engagement Scale and the Online Academic Emotion Scale. Results The score of online deep learning of the nursing master students was(3.47±0.49). Per capita monthly income of the family,competition awards,network learning space,online learning engagement,and negative low arousal emotion could account for 66.0% of the total variance. Conclusion The online deep learning of nursing master students is at the upper middle level. Per capita monthly income of the family,competition awards,network learning space,online learning engagement,and negative low arousal emotion are the main influences factors for nursing master students.

Key words: Education, Nursing, Graduate, Education, Distance, Questionnaires, Online deep learning, Online learning engagement, Online academic emotion, Network learning space