Study on the analysis of the learning process and the development of a learning outcome prediction model to learning support.

2023 Fiscal Year Final Research Report

• Project/Area Number: 21K20204
• Research Category: Grant-in-Aid for Research Activity Start-up
• Allocation Type: Multi-year Fund
• Review Section: :Education and related fields
• Research Institution: Akita University
• Principal Investigator: Hosokawa Shinji 秋田大学, 評価・IRセンター, 助教 (00901034)
• Project Period (FY): 2021-08-30 – 2024-03-31
• Keywords: 教学IR / Institutional Research / 教学マネジメント / 統計解析 / 機械学習 / 学修支援 / カリキュラム・マップ

Outline of Final Research Achievements

In this study, in order to realize academic support for individual students, we examined the classification of the growth process of students by type, and aimed to construct a prediction model for learning outcomes that takes factors other than academic performance, such as admissions information and extra-curricular learning (part-time jobs, club activities, etc.). As a result of this research, the method of classifying “student life,” which is considered to be related to the growth process of students, into different types was proposed. In addition, the influence of academic performance and other factors during school on learning outcomes was evaluated, and a model for predicting learning outcomes was constructed and proposed by taking these factors.

Free Research Field

教育工学

Academic Significance and Societal Importance of the Research Achievements

本研究の成果は，学生をタイプ別に分類する手法の提案や，在学中の各要因が学修成果に与える影響を評価し，これらを加味した学修成果予測モデルの構築および提案を行ったことである。これらは，高等教育の大衆化や国際化に伴い，多様化していく学生個々に寄り添った学修支援を実現するための基礎として，学生個々の特徴の捉え方や，数ある在学中の要因の中から学修成果を予測するために必要な要因の選定方法などの知見を，まとめたことに意義があると考える。