DEVELOPING A REGRESSION MODEL TO ASSESS STUDENT ACADEMIC PERFORMANCE

Loan Trịnh Thị Anh1, Thế Anh Phạm1, , Đình Thịnh Nguyễn1, Văn Liệu Vũ2
1 Hong Duc University
2 Lớp K16 Khoa học Máy tính, Khoa Kỹ thuật, Công nghệ và Truyền thông, Trường Đại học Hồng Đức

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Abstract

In 2025, many universities in Vietnam have announced their admission plans, with several programs no longer using high school academic records for admission consideration [1]. A key reason for this trend is to improve the quality of student intake, as the management of high school academic results may not always be entirely objective and transparent [2]. In addition, the draft regulations issued by the Ministry of Education and Training specify that admission scores for different admission methods must be converted to a common scale [3].  High school academic records (Ra) and national high school graduation exam scores (Sg) are two important criteria for assessing students' academic performance. This paper applies artificial intelligence technology to analyze the correlation between these two types of scores (e.g., Ra and Sg). The correlation analysis results will serve as a foundation for developing an equivalent conversion method between them. 

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References

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