论文标题
一个博学的模拟环境，以模拟学生参与和保留自动化的在线课程
A Learned Simulation Environment to Model Student Engagement and Retention in Automated Online Courses
论文作者
论文摘要
我们开发了一个模拟器来量化锻炼秩序对学生参与和保留的影响。我们的方法结合了用户的神经网络表示形式的构建，并使用动态矩阵分解方法进行了练习。我们进一步创建了成功和辍学预测的机器学习模型。结果，我们的系统能够根据所选的一系列练习来预测学生的参与和保留。这为多功能增强学习剂的发展打开了大门，可以替代私人辅导在考试准备中的作用。
We developed a simulator to quantify the effect of exercise ordering on both student engagement and retention. Our approach combines the construction of neural network representations for users and exercises using a dynamic matrix factorization method. We further created a machine learning models of success and dropout prediction. As a result, our system is able to predict student engagement and retention based on a given sequence of exercises selected. This opens the door to the development of versatile reinforcement learning agents which can substitute the role of private tutoring in exam preparation.
