学生学习成果的预测模型

Pham Cong Hiep, P. Duy
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引用次数: 0

摘要

早期发现学生表现因素对于大学制定适合个别学生的支持性学术举措至关重要。本研究考察了四个学术因素,包括12年级的平均绩点(GPA),大学课程的GPA,课程负荷,以及以前在大学的课程失败,以确定这些因素与课程表现之间的关系。对越南一所英语国际大学2021年9048名学期学生的学习记录进行了定量分析,以检验所建立的理论模型。结果发现,除当前课程负荷和学生成绩外,所有因素之间都存在显著的相关性。虽然这些数据通常存储在院校学生记录系统中,但开发的基于学术的预测系统可以为学生支持活动和决策提供价值,从而及早提高学生的表现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictive Model of Student Learning Outcomes
Early detection of student performance factors is essential for universities to develop supportive academic initiatives that suit individual students.  This study examines four academic factors, including Grade Point Average (GPA) from Grade 12, GPA of courses taken from the university, course load, and previous course failure in the university, to ascertain the relationship between these factors and course performance. Academic study records of 9048 semesterly student performance in 2021 from an English-speaking international university in Vietnam were quantitatively examined to test the developed theoretical model. The results found a significant correlation between all factors except current course load and student performance. Though such data has been commonly stored in institutional student record systems, the developed academically-based predictive system can provide value to student-support activities and decision-making to enhance student performance early.
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