Logistic回归在慕课学习领域的应用性研究  

Application of Logistic Regression to MOOCs Learning

作　　者：石林[1] SHI Lin(Tianjin Acadamy of Fine Arts,Tianjin 300141,China)

机构地区：[1]天津美术学院,天津300141

出　　处：《中国轻工教育》2018年第4期79-84,共6页China Education of Light Industry

摘　　要：本文针对存在于高等教育中慕课学习者占比较低的原因展开研究。经过对已有数据分析,发现最近1-2年慕课开设数量不断提高,但是学习者数量并未同比增多,而且占在校生总数比例较低。研究通过分析与学习者自身相关的可能影响选择慕课学习的因素,应用Logistic模型对影响因素和选择慕课学习结果进行建模。依据对试验结果分析,得出对于方程中变量类型选取应根据方程整体拟合优度最佳进行确定的结论。本文运用方程已知形式对学生选择慕课学习的可能性进行分类筛选。利用该结果,教学管理部门能够有的放矢地面向慕课学习中高兴趣度人群中的未选课学生开展定向导学,以此提高慕课学习者占在校学生中的比例,充分体现慕课教学的优势。This paper focuses on the reasons for the low proportion of MOOCs learners in collages. Through analyzing theexisting data, it is found that the number of MOOCs offered in the last 1-2 years has been increasing, but the number oflearners has not increased at the same time, and the proportion of the total number of MOOCs learning students is stilllow. After selecting the factors that may affect the learner＇s choice, the Logistic model is used to find the relationshipbetween the influencing factors and user＇s choices. According to the analysis of the results, it is concluded that theselection of variable types in the equation is determined by the optimum overall goodness of fit for the equation. Theresearch results not only enables us to use the known form of equations to classify students＇ choice of MOOCs learning,but also helps the teaching management department to popularize massive online courses for certain collage students anduse MOOCs to the best.

关 键 词：慕课 LOGISTIC回归 统计学 SPSS 

分 类 号：G642.0[文化科学—高等教育学]