2025 ASEE Annual Conference & Exposition

Graduate students in an engineering math course start with a wide variety of backgrounds. Some of the differences among the students in this class include that they are a mixture of PhD and master’s students, some are taking the class remotely, while most are taking it in person, and some of them learned most of the course content in the past few semesters, while some haven’t had a math class for years. To allow students to work at their own pace, content is delivered through video lectures, and class time is spent on weekly quizzes and time for students to work on homework and worksheets in a supported environment. For some topics, students are given access to optional online practice problems and/or additional video lectures.

The impact of students’ prior knowledge and performance in (Wright et al., 2019) and time since prerequisite courses (Wilck et al., 2016), as well as the use of additional material to help bridge any gaps (Watson et al., 2022) has been studied in courses in a number of engineering fields. However, most of work this focuses on undergraduate students rather than graduate students. This study will address the research questions: How, if at all, does graduate students’ performance on an Engineering Mathematics diagnostic assessment relate to their subsequent performance on future quizzes and in the course? To answer this question, we will use artifacts from the course, including an initial diagnostic assessment given on the first day of class and grades on homework assignments and quizzes.

Through this research, we hope to determine whether a lower level of prior knowledge puts students at a disadvantage in this course, and if it does, what content areas are most impacted by this inequity. This will give important information about how to make the learning process for this material more equitable at this and other institutions. We plan on analyzing the data at the end of the fall 2024 semester.