This paper describes and investigates updates to a graduate level engineering math course at a large research university in an effort to mitigate the impact of prior knowledge on student performance. This class covers the basics of ordinary differential equations, partial differential equations, and linear algebra. The class is taken by students with a wide variety of backgrounds, and this paper is part of a long-term goal to increase equity in the course.
A prior study was conducted on the relationship between performance on a diagnostic assessment given at the beginning of the semester and subsequent performance on future quizzes. We found that students’ performance on diagnostic assessment questions relevant to the partial differential equations portion of the course had a statistically significant impact on that portion of their quiz scores. The same was not found for the ordinary differential equations and linear algebra portions of the course.
Taking the results of that study into consideration, the course was restructured in Fall 2025. Key changes include an update to the order of the material, reviewing relevant material from the beginning of the semester before using it again in the later parts of the semester, creating more optional review material, and revising some lectures to improve clarity on some of the more complex subjects.
The present study aims to determine:
1. How, if at all, does graduate students’ performance on an engineering math diagnostic assessment relate to their subsequent performance on future quizzes and in the redesigned course? How do patterns of performance compare between the original and redesigned versions of the course?
2. How, if at all, do students’ learning support strategies in the redesigned course relate to their performance on the diagnostic assessment and their performance on quizzes?
Data for this project will be collected throughout the Fall 2025 semester and will include student artifacts from both Fall 2024 and Fall 2025 including scores on quizzes and homework assignments, and data on the usage of optional study material.
The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026