Using machine learning to identify the most at-risk students in physics classes

著者: Jie Yang, Seth DeVore, Dona Hewagallage, Paul Miller, Qing X. Ryan, John Stewart - Physical Review Physics Education Research 2020 被引用: 29

Demographic variables such as gender, underrepresented minority status, first-generation college student status, and low socioeconomic status are not important predictor variables in models to identify students likely to receive a D, F, or withdraw in their introductory physics course.