Title
Moving from managing enrollment to predicting student success.
Abstract
We describe the construction and assessment of a plan to foster student success in Computer Science (CS) in response to continued enrollment growth. We examined cross correlations of grades from student transcripts from the past four years to determine what patterns of grades in early classes were indicative of future success. The resulting statistics and visualizations showed that students generally did better in the first class than subsequent classes, suggesting that C grades in the first class might indicate difficulty. We also examined students enrolled in the pre-capstone software engineering course. The analysis showed that no graduating CS major had received a C in both first two programming courses. We examined the data to be sure that the proposal would not diminish the participation of members of under represented groups disproportionately. As a result, the CS faculty approved a change in prerequisite for the third course to require that student receive an A or a B in at least one of the first two courses. GPA data was also analyzed and found to be a poor predictor of success in computer science, demonstrating that our previous approach to limiting enrollment was inferior. This new approach has advantages over the previous GPA-based plan, but enrollment management plans risk making college harder for at risk students to succeed in CS. The biggest limitation of this plan is that it is expected to make only a small change in CS enrollment.
Year
Venue
Keywords
2017
Frontiers in Education Conference
enrollment management,retention,Computer Science
Field
DocType
ISSN
Medical education,Grading (education),Sociology,Knowledge management,At-risk students,First class,Enrollment management,Programming profession,Limiting
Conference
0190-5848
Citations 
PageRank 
References 
0
0.34
4
Authors
2
Name
Order
Citations
PageRank
deborah a trytten163.30
Amy McGovern231228.82