• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to project page

2022 Fiscal Year Final Research Report

Development of three party tutoring system for mastering machine learning

Research Project

  • PDF
Project/Area Number 18K11569
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 62030:Learning support system-related
Research InstitutionKyoto Institute of Technology

Principal Investigator

Araki Masahiro  京都工芸繊維大学, 情報工学・人間科学系, 准教授 (50252490)

Project Period (FY) 2018-04-01 – 2023-03-31
Keywordsチュータリングシステム / 質問応答システム / マルチモーダル対話
Outline of Final Research Achievements

This study aimed to develop a tutoring system that maintains learners' alertness while minimizing psychological stress. Initially, we created a triadic dialogue-based tutoring system prototype and validated its efficacy through a survey comparing it with a dyadic dialogue approach. Regarding question answering using knowledge graphs, we developed a method to construct knowledge graphs from textbook descriptions using predicate-argument structures and a search method incorporating various types of similarity. The question-response section was constructed using these methods, and functionality was confirmed through basic question scenarios. Furthermore, we developed a method for evaluating user responses to system questions. We confirmed the effectiveness of this evaluation method in creating knowledge graphs based on word dependency and predicate relations.

Free Research Field

対話処理

Academic Significance and Societal Importance of the Research Achievements

本研究で取り組んだ覚醒度を保ちつつ心理的負担を軽減する新しい形のチュータリングシステムは、個々の学習者がより効率的で快適な学習を体験することを目指したものである。特に、リモート学習や自己学習の機会が増加している現代社会において、この種の技術は教育のアクセシビリティと効率性を向上させる可能性がある。さらに、知識グラフを用いた質問応答や解答評価は、システムが学習者の理解度を評価し、個々の学習ニーズに対応するための有効なツールとなって、学習をより適切にガイドすることが可能になると考えられる。

URL: 

Published: 2024-01-30  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi