43 citations · 73 across the 2 of their papers we have counts for
2 papers
physics.ed-ph2020★ 30 cited
Using Machine Learning to Identify the Most At-Risk Students in Physics Classes
Jie Yang, Seth DeVore, Dona Hewagallage +3
Machine learning algorithms have recently been used to predict students' performance in an introductory physics class. The prediction model classified students as those likely to r…
physics.ed-ph2020★ 43 cited
Exploring the Structure of Misconceptions in the Force and Motion Conceptual Evaluation with Modified Module Analysis
James Wells, Rachel Henderson, Adrienne Traxler +2
Investigating student learning and understanding of conceptual physics is a primary research area within Physics Education Research (PER). Multiple quantitative methods have been e…