Predicting new student performances and identifying important attributes of admission data using machine learning techniques with hyperparameter tuning
Chayaporn Kaensar,
Worayoot Wongnin
Abstract:Recently, many global universities have faced high student failure and early dropout rates reflecting on the quality of education. To tackle this problem, forecasting student success as early as possible with machine learning is one of the most important approaches used in modern universities. Thus, this study aims to analyze and compare models for the early prediction of student performance with six machine learning based on Thailand’s education curriculum. A large dataset was collected from the admission sco… Show more
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