决策树技术在移动学习性别差异研究中的应用

基于对近千名高等教育移动学习者进行大规模调查所收集到的数据,研究者使用C5.0算法分别生成男女生群体关于课件使用满意度的决策树,然后比较从中提取的不满意规则进行性别差异研究。实验结果表明:在移动学习中,女生对学习资料有更高的要求,女生对学习资料要求的个体差异高于男生,女生使用课件时更容易受外界因素干扰。

Use Decision Tree Technology to Explore Gender Differences in Mobile Learning

Data for this study are collected from large-scale surveys of nearly 1000 mobile learning users in higher education. Researchers used C5.0 algorithm to respectively generate male and female learners＇ decision tree about their satisfaction with the mobile learning eourseware. They then compared extracted dissatisfied rules to further analyze gender differences in users＇ satisfaction level and other preferences. The results show that in mobile learning, female learners have more requirements for the design of learning materials, females＇ individual differences are higher than males＇ in the requirements for the design of learning materials. And during the learning process, females are easily distracted by external factors.