Research On The Solution And Factors Of Online Deep Learning Of Nursing Master Students

Objective: Based on the background of "Internet education" and the framework model of e-Learning deep learning analysis,this paper analyzed the present situation and influencing factors of online deep learning of nursing graduate students,so as to guide nursing educators to develop deep learning and to cultivate their high-level abilities to provide scientific basis under the online teaching mode Postgraduates.Methods: This study is a cross-sectional survey of non-experimental studies.From December 2019 to September 2020,343 students from five colleges and universities in Northeast China were selected as the subjects of investigation.General information questionnaire,network depth learning scale,network learning space scale,online learning input scale and online academic emotion scale were used to investigate.All questionnaire data were analyzed and processed using SPSS 26.0statistical software.Result:(1)There were 343 valid questionnaires,the effective rate of the questionnaire was 85.75%.Average age of nursing graduate students is(24.77±2.78)years old.324 women(94.5 %);the lower grades 180(52.5 %),163(47.5 %)in the upper grades;59(17.2%)student cadres;159 subjects(46.4%)received competition awards;Most of the subjects were rural,151(44.0 %).(2)The average score of online deep learning among nursing graduate students is divided into(3.49±0.03),which is in the upper middle level.Middle grade,age,family location,per capita monthly income of the family,whether to serve as student cadres,whether to obtain competition awards,the number of online courses,online learning time on the nursing master’s degree of online deep learning level has statistical significance(P(27)0.05).(3)The average score of online learning space for nursing graduate students was(3.57±0.51),which is in the upper middle level.Age,family location,per capita monthly income of the family,whether to be a student cadre,whether to receive competition awards,the number of online courses and the length of online study had statistical significance on the spatial application ability of online learning for nursing graduate students(P(27)0.05).(4)An average score of online learning engagement was 3.55±0.54,which is in the upper middle level.The influence of age,family location,per capita monthly income,student cadre,competition award,number of online courses,length of online number of online courses,the length of online learning,the type of online learning terminal and the type of online learning platform on the online learning input of nursing graduate students was statistically significant(P(27)0.05).(5)Pearson correlation analysis showed that there was a significant positive correlation between application ability,online learning engagement,online academic emotion and online deep learning(r(28)0.684,r(28)0.766,r(28)0.357,P(27)0.05),while negative low arousal emotion about online academic emotion was low negative correlation with online deep learning(r(28)-0.189,P(27)0.05).(6)Multiple linear regressions showed that the factors of online deep learning were: age,grade,per capita monthly income,competition reward,online learning engagement,network learning space,positive high arousal emotion,negative low arousal.The above 7 variables explained 69.6%of the variation of online deep learning(F=40.088,P(27)0.001).Conclusion:(1)The online deep learning,online learning space and online learning engagement of nursing master’s degree graduate students are all in the upper middle level,while the online academic emotion is in the general level,and the overall level needs to be further improved.Age 25～30 years old,living in the city,the higher the per capita monthly income of the family,a student cadre,senior grade,the longer the online learning time,the higher the level of online deep learning.(2)Online learning space,online learning engagement,online academic emotion were significantly positively correlated with online deep learning.The higher the application level of network learning space,the more online learning engagement,the more positive online academic emotion,the higher the level of online deep learning for nursing graduate students.(3)Grade,competition reward and family per capita monthly income,online learning space,online learning input,positive high arousal emotion positively affect the online deep learning level of nursing graduate students,while age,negative low arousal emotion negatively affects the online deep learning level of nursing master research.Among them,the per capita monthly income of the family and online learning engagement have the greater impact on the online deep learning of nursing master’s graduate students.