著者

近藤 伸彦 畠中 利治

出版者

教育システム情報学会

雑誌

教育システム情報学会誌 (ISSN:13414135)

巻号頁・発行日

vol.33, no.2, pp.94-103, 2016

---

Institutional Research (IR) has been receiving much attention in Japanese higher education. In order to guarantee the educational quality of university, it has been discussed how to utilize the educational big data. In this paper, it is considered to construct models of students' learning states using large-scale students' learning data collected through the baccalaureate degree program based on some machine learning methods. In this research, data in 5 years are utilized in order to investigate the generalization ability of the models, and the performances of some machine learning methods are compared. From the experimental results, it is indicated that the models of students' learning states with high generalization ability can be constructed. Its capability of application to enrollment management is also discussed from experimental results.