2023 Fiscal Year Final Research Report
Building an Enrollment Management System Using Machine Learning in the Cloud
| Project/Area Number |
19K02868
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 09050:Tertiary education-related
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| Research Institution | Sapporo Gakuin University |
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Principal Investigator |
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| Project Period (FY) |
2019-04-01 – 2024-03-31
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| Keywords | IR / エンロールメントマネジメント / 退学予測 / 機械学習 / クラウドサービス |
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| Outline of Final Research Achievements |
We have developed a system for understanding and analyzing students' academic progress, which is indispensable for enrollment management, by developing IR analysis in universities. In particular, we used machine learning technology to construct a system for early detection and prediction of problematic situations that lead to withdrawal from the university.
The system was developed using the Python language, which has a high affinity for machine learning, and Excel. The system was able to predict the withdrawal of students whose graduation year is 2022 with an accuracy considered to be effective in practice, demonstrating the potential of the system. The system can be shared among institutions using cloud services, and practical results were obtained.
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| Free Research Field |
教育工学
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| Academic Significance and Societal Importance of the Research Achievements |
大学全入化に伴い大学（特に私立大学）の中途退学者の増加は社会的課題になっており，それを防ぐ取り組みが各大学に求められている．一方で，学生の様々な学修データや行動履歴などを一元化して，その状況を可視化するIR（Institute Research)は，まだ，分析結果の可視化のレベルに留まっており，退学者防止など実用上の対策に結びついていない．そこで，これらIRデータを単なる可視化に留めず，機械学習（AI)による退学予測システムに用いることで，大学の退学者と未然に防ぐ取り組みに用いることができるようになる．
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