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Title: GPA Patterns of Black Mechanical Engineering Students
In recent years, research has associated grade point average (GPA) with a variety of student outcomes during their undergraduate careers. The studies link higher GPAs to students being more likely to graduate in their major, while lower GPAs have been linked to students switching majors or leaving the institution. Further research, which focuses on how Black female and male students remain successful in different engineering degrees, is necessary to identify the underlying elements contributing to their entrance into and exit from engineering disciplines. This quantitative examination of trends among the GPAs of Black women and men is part of a larger NSF-funded mixed-methods study that includes in-depth student interviews of Black students who persisted in and switched from ME. In this quantitative paper, we examine the GPA patterns of Black students in Mechanical Engineering (ME). Students who have ever enrolled in ME have four potential, mutually exclusive, outcomes: 1) they can persist for 12 semesters without graduating; 2) they can graduate in ME within 12 semesters; 3) they can switch to another major; or 4) they can leave school. In this research, we identify the most common GPA patterns associated with graduated ME students. We hypothesize a relationship between distinct GPA patterns and whether a student persists in ME, graduates in ME, switches away from ME, or leaves the institution altogether. This quantitative investigation uses the Multiple-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD) to collect the cumulative GPA of ME students at each term. We use a functional cluster analysis approach to group similar patterns. First, a function is fit to each student record. Then a cluster analysis is conducted on the function parameters to identify natural groupings in the data. Once students are grouped according to their GPA profile, we examine the other characteristics and outcomes of the group. We present a visual quantitative analysis of the patterns in the GPAs of Black women and men who enroll in ME. Clustering analysis suggests that first-time-in-college (FTIC) Black female students in ME who graduated have a higher proportion of students in the higher GPA clusters than the proportion of FTIC Black male students who graduated in ME. A higher proportion of the male student population is clustered in the lower GPA cluster groups as compared to women in the lower GPA cluster groups. A higher proportion of students who graduated are in the higher GPA clusters than the proportion of graduated students in the lower GPA clusters.  more » « less
Award ID(s):
1734347
NSF-PAR ID:
10383435
Author(s) / Creator(s):
; ; ; ; ;
Publisher / Repository:
American Society for Engineering Education
Date Published:
Journal Name:
Proceedings of the 2022 Annual Conference of the American Society for Engineering Education. https://peer.asee.org/41089
ISSN:
2153-5965
Format(s):
Medium: X
Location:
https://peer.asee.org/41089
Sponsoring Org:
National Science Foundation
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