Poster Session 3, 1:15 PM - 2:00 PM: Campus Center Auditorium [A39]

College Success Factors

Presenter: Alivia Glynn

Group Members: Zachary Albert Kimball

Faculty Sponsor: Elena Braynova

School: Worcester State University

Research Area: Computer Science

ABSTRACT

Abstract: In this project we studied a College Placement dataset consisting of 10,000 student records focusing on the factors that determine students’ success such as academic performance, cognitive ability, experience, and placement outcomes. The dataset was analyzed using a variety of visualization, statistical analysis and Machine Learning techniques. Using R, we created histograms, boxplots, scatterplots, bar charts, and correlation heatmaps to explore patterns and relationships. Visualizations revealed a notably strong positive relationship between Previous Semester Result and CGPA. Internship experience appeared to relate to higher placement rates, while IQ and other cognitive measures showed relatively weak associations with academic outcomes. Statistical analysis supported these observations. The correlation between Previous Semester Result and CGPA was approximately 0.98, and linear regression produced an R2 value near 0.96, indicating that prior academic performance explains much of the variation in current GPA. Hypothesis testing showed no statistically significant difference in GPA based solely on internship experience. Using the WEKA tool we looked deeper into the dataset and the patterns there. Using the Decision Tree Classification methods we achieved very high accuracy in predicting Academic Performance, while regression models effectively estimated Projects Completed and Previous Semester Result. In contrast, predicting IQ resulted in higher error rates, suggesting that cognitive measures are not easily inferred from academic or experiential experiences attributes. Overall, the findings highlight the strong role of academic consistency in student outcomes and provide insight into the relative influence of experiential and cognitive factors.

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