基于数据挖掘与分析的学习成果定量实证研究

A Quantitative Empirical Study of Learning Effeect Based on Data Mining and Analysis

采用雨课堂数据挖掘、数据分析以及SPSS21.0统计学软件,进行了学生的作业完成分数、学习资料以及公告阅读数量对学习成果的定量实证研究。研究结果表明:不同类型的课后作业对学习成果的贡献程度不同:平时作业以无标准答案、具有一定挑战度的开放题型给出时,其开放题与学习成果基本不相关或呈弱相关;平时作业以深度学习为特点的主观题形式给出时,其主观题得分与学习成果呈强相关。学生预习多媒体课件等学习资料的阅读数量越多、阅读时间越长,学生的学习成果越显著。学生阅读公告数量的多少与学习成果呈显著正相关。

A quantitative empirical study was made of the correlation between factors such as students'homework score,learning material and the amount of announcements they read and learning effect by means of Rain Classroom's data mining and analysis technology as well as SPSS21.0.The result shows that the contribution of different types of after-school homework to learning effect is different,that is,the homework composed of challenging open problems without standard reference answers is not correlated or weakly correlated with learning effect,whereas the homework composed of subjective problems featuring deep learning shows strong correlation with learning effect.Additionally,the more materials like multimedia courseware students read and the longer they spend on them,the better their learning effect.And the number of announcements read by students is also significantly positively correlated with learning effect.