Abstract Dropout remains a persistent challenge within high school education. In this paper, we present a case study on automatically detecting whether a student is at-risk of dropout within a diverse school district in Texas. We predict whether a student will drop out in a future school year from data on students’ discipline, attendance, course-taking, and grades, using a logistic regression framework. We discuss the predictive properties of the model, and the features that are predictive of dropout in this context.

中文翻译：

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预测K-12辍学

摘要辍学仍然是高中教育中持续存在的挑战。在本文中，我们提供了一个案例研究，该案例可以自动检测德克萨斯州多样化的学区内学生是否面临辍学的风险。我们使用Logistic回归框架，根据学生的纪律，出勤，课程和成绩等数据，预测学生在未来的学年是否会辍学。我们讨论了模型的预测属性，以及在这种情况下可预测辍学的特征。