利用成绩单数据预测本科专业

David Lang, Alex Wang, Nathan Dalal, A. Paepcke, M. Stevens
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引用次数: 3

摘要

在本科教育中,选择一个专业是决定性的一步,然而,在学术生涯早期所修课程与最终专业选择之间的关系却很少有大规模的研究。我们分析了一所私立大学2000年至2020年间26,892名本科生的学术生涯成绩单数据。我们根据从大学入学开始的选课顺序来预测学生的最终专业。我们使用自然语言方法和向量嵌入来表示课程注册历史。我们发现,学生的第一门选修课预测其最终专业的准确度是随机猜测的30倍,比多数班级投票的准确度高出三分之一以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecasting Undergraduate Majors Using Academic Transcript Data
Committing to a major is a fateful step in an undergraduate's education, yet the relationship between courses taken early in an academic career and ultimate major choice remains little studied at scale. We analyze transcript data capturing the academic careers of 26,892 undergraduates at a private university between 2000 and 2020. We forecast students' terminal major on the basis of course-choice sequences beginning at university entry. We represent course enrollment history using natural-language methods and vector embeddings. We find that a student's very first enrolled course predicts their terminal major thirty times better than random guessing and more than a third better than majority class voting.
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