Analysis of learner's potential factors based on Case-based and development of individualized education support system

2018 Fiscal Year Final Research Report

• Project/Area Number: 16K16326
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Educational technology
• Research Institution: Nihon University
• Principal Investigator: AZUMA Rumiko 日本大学, 商学部, 准教授 (80550102)
• Project Period (FY): 2016-04-01 – 2019-03-31
• Keywords: 学習分析 / テキストマイニング / データ分析 / 学習支援

Outline of Final Research Achievements

In Japan, it is hard for a teacher to take control of the understanding level of students and conduct personal instructing because a teacher is in charge of many students. Then, in order to respond to the wide variety of needs for education, it is necessary for teachers to get grasp student's understanding level in real time and provide individual instruction.
As a solving the problem, a reasoning system which can predict the understanding level of students with their reaction paper was proposed in this study. We analyzed some elements that are strongly related to understanding level using statistical method or machine learning algorithm from student’s writing quantified by text-mining method and tried to extrapolate their understanding level. As a result, their final exam score had stronger correlation with the content of their reaction paper than their subjective understanding level or quiz score.

Free Research Field

教育工学

Academic Significance and Societal Importance of the Research Achievements

多様化する生徒に対して、多角的な指標のもとで個々の学習問題を考慮し効率の良い教育指導を行うことは、生徒のみならず負担の多い教員にとっても必要である。またそのために、生徒の理解度を把握する教育補助システムの開発は重要である。
そのシステム開発の一助として、本研究では学生の真の理解度を推定するための要因を探り、推定精度の向上を目指した。これは先進的な教育改善策に繋がる可能性を秘めており、社会的意義は大きいと考える。