Testing Mathematics Research-Based Assessment in Introductory Physics Education

• In Event: STEM Education: Assessment, Identity, and Support

Abstract

Mathematical skills play an important role in learning physics. Our work expands a mechanics cognitive diagnostic (MCD) to assess both mathematics and physics knowledge in a single assessment. We used an evidence-centered design framework to identify skills for physics learning and tested three mathematics RBAs for their ability to assess these skills. We ran a "deterministic inputs, noisy 'and' gate" (DINA) model on responses from 3,493 college students. Our results indicated the RBAs measured most skills with high classification accuracies and had good model fits. Including the three mathematics RBAs in the MCD's item bank offers a flexible tool for evaluating skills in mathematics and physics that can adapt to instructors' needs.

Authors

• Vy Le, Iowa State University

• Jayson Nissen, Montana State University

• Xiuxiu Tang, University of Notre Dame

• Yuxiao Zhang, Purdue University

• Hua-Hua Chang, Purdue University

• Jason W Morphew, Purdue University

• Ben Van Dusen, Iowa State University