摘要
通过典型抽样和便利抽样,以我国华东地区一所省级电大系统为个案,运用t检验、方差分析、灰关联分析等统计分析技术,对其长达11年期21个招生季节、完整的大样本数据库进行挖掘,系统分析了该地区现代远程教育辍学率的变化趋势,比较检验了多重视角下的辍学率差异,解析并揭示了辍学率序列与相关影响因子序列的关联序。研究结果显示,随着现代远程教育实践的不断深入,多视点的辍学率均呈明显下降趋势,反映了样本院校降低辍学率的能力在不断稳健提升。探讨建立的各因子序列(X)与辍学率序列(Y)的关联序,有助于识别影响辍学率的强关联因子、次强关联因子、弱关联因子,为降低辍学率、制定相应对策提供了有效地切入点和细粒度的决策参考依据。
With a case study on a provincial Radio and TV University（RTVU） in the eastern China by the Typical Sampling and Convenience Sampling,and the statistic analysis techniques such as t-test,variance analysis and Gray Relational Analysis,this paper completes mining the large sample database,which is collected from 11-year and 21-seasnonal enrollment.Then it systemically analyzes the trend of the dropout rate of distance education in this region and comparatively tests the differences of the dropout rate from multiple perspectives.It concludes with the relational sequence between the dropout rate sequence and the related influential factors sequence.The results display that with the development of modern distance education practice,the multi-view dropout rate shows a clear downward trend,which reflects the ability of the sample university to reduce the dropout rate is promoting steadily.With the Gray System Theory,this study explores and establishes relational order of the sequence of each factor（X）and the dropout rate sequence（Y）.The distance education institutions can identify the strong correlation factor,the second strongest correlation factor,and the weak correlation factor,all of which have impact on the dropout rate,to provide an effective entry point to reduce the dropout rate,and at the same time,a reference for making the countermeasures.
出处
《远程教育杂志》
CSSCI
2011年第4期18-26,共9页
Journal of Distance Education
基金
国家自然科学基金面上项目"远程开放教育辍学研究"(项目批准号:70973148)的阶段性研究成果
关键词
现代远程教育
辍学率
关联序
数据挖掘
Modern distance education
Dropout rate
Relational sequence
Data mining
