High School Scores to College Performance: Exploring the Predictive Validity of Grade 12 Standardized Test Scores for University GPA
DOI:
https://doi.org/10.23918/ijsses.v11i4p120Keywords:
High School Score, College Admission, , University GPA, Machine Learning, Linear Regression, Neural NetworkAbstract
This study examines the correlation between High School Scores (HSS) and academic achievement in the ELT Department at Tishk International University, Erbil, Iraq, aiming to assess the validity of HSS as a predictor of university GPA. The study employs traditional statistical methods and advanced AI-based algorithms to categorize and analyze a dataset comprising 225 students admitted between 2014 through 2019. As AI-based algorithms, Linear Regression model yielded a mean square error (MSE) of 0.2228 and R² of 0.1774, while Neural Network model produced an MSE of 0.2383 and R² of 0.1204. These results indicate a weak to moderate correlation between HSS and GPA, indicating that other factors significantly influence GPA. The study concludes that while HSS can serve as an initial indicator of potential academic success, it is not a definitive predictor, suggesting the need for a more comprehensive approach to evaluating student performance in the ELT program.
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