An Empirical Study On The Influencing Factors Of Online Course Credit Recognition

With the advent of the Internet + era,online courses continue to rise.In recent years,the country has successively issued "Opinions on Strengthening the Construction,Application and Management of Online Open Courses in Colleges and Universities","Education Informatization 2.0 Action Plan" and other documents,emphasizing the promotion of credit recognition for online courses in colleges and universities,and realizing the sustainability of online education resources shared.However,the credit recognition mechanism for online courses is still in its infancy,and no substantial breakthrough has been achieved.High-quality courses based on the vast MOOC platform have not been effectively recognized.Therefore,attempting to learn from previous studies,combining with the development status,and exploring the influencing factors of college online course credit recognition,so as to help us understand the needs of college educators and learners,and facilitate online courses and the steady development of course credit recognition.This article has carried out a series of research and exploration on the subject of online course credit recognition in colleges and universities.First of all,a research on the development status of online course credit recognition is carried out.taking university education managers as the research object and research perspective.This article sorts out the connotation of online course credit recognition,and analyzes the current development status of online course credit recognition;secondly,it conducts an analysis and research on the factors affecting online course credit recognition.Based on the analysis and sorting of relevant domestic and foreign documents,the article formulates the interview outline.Appropriate research objects are selected for semi-structured interviews,and the interview text is coded at three levels by using NVivo11 software based on grounded theory to extract relevant influencing factors and Preliminary theoretical model.Then,an empirical study on the influencing factors of online courses is carried out.Not only developing questionnaires based on the research model,conducting pre-tests,the research also uses SPSS software to perform a series of statistical analysis on the pre-test samples,including project analysis,reliability analysis,and exploratory factor analysis and revise the research model and questionnaires for factors affecting online course credit recognition.After that,followed by a large-scale formal questionnaire survey,with the help of statistical analysis software such as SPSS,the research processed data,drew charts of results,and verify the research hypotheses.Finally,specific policy opinions are put forward based on the research conclusions.The research shows that:(1)After the national policy’s regression analysis test on the online course credit recognition,the test result is P=0.000<0.05,and the standardized regression coefficient is 0.599.The national policy has a significant positive impact on the online course credit recognition;(2)In the online course influence dimension,both the online course learning effect and the authority of the online course have a significant positive influence on the credit recognition of the online course,but the effect of the online course quality on the credit recognition of the online course is not obvious and there is even no influence;(3)In the dimension of school education environmental impact,teachers’ willingness and school informatization level have a significant positive impact on online course credit recognition,and the incentive mechanism has a significant moderating effect on teacher’s willingness and online course credit recognition;(4)Based on the research conclusions,this article proposes relevant management strategies from the national government level,online course platform level,school level,and university learner level which provides reference for the establishment of online courses and the formulation and application of online course credit recognition mechanisms in the future.