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

2022 Fiscal Year Final Research Report

Research on an automatic feedback generation method for learners to support state transition modeling learning

Research Project

  • PDF
Project/Area Number 20K03146
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 09070:Educational technology-related
Research InstitutionShinshu University

Principal Investigator

Ogata Shinpei  信州大学, 学術研究院工学系, 准教授 (10589279)

Co-Investigator(Kenkyū-buntansha) 香山 瑞恵  信州大学, 学術研究院工学系, 教授 (70233989)
岡野 浩三  信州大学, 学術研究院工学系, 教授 (70252632)
槇原 絵里奈  同志社大学, 理工学部, 助教 (90822875)
Project Period (FY) 2020-04-01 – 2023-03-31
Keywordsソフトウェア工学教育 / モデリング / 教育支援 / ステートマシン図 / 誤り検出 / 静的解析 / 動的解析 / モデル検査
Outline of Final Research Achievements

This study aims to establish a method to assist learners who fail in learning state transition modeling. (1) To automatically detect learner failures, we developed a method for analyzing model edit logs. We showed the possibility of identifying the failures of the learners with high accuracy based on the number of edits, the editing time, and the eye-tracking information. (2) To automatically identify errors in the model and requirements that the model does not satisfy, we realized a method to analyze the differences between a sample solution model, task sentences, and learner-created models by using a state transition simulator and model checking. This method includes (3) support for the automatic generation of feedback. We have shown that our method is capable of identifying errors and unmet requirements with high accuracy. These results were presented at domestic and international conferences and received a paper award.

Free Research Field

ソフトウェア工学

Academic Significance and Societal Importance of the Research Achievements

我が国の情報科目の必修化などに見られるように,社会問題を発見・解決するために情報技術は誰もが身につけるべき基礎技術となりつつある.ソフトウェアモデリングは,対象世界を抽象的かつ論理的に捉える技術の一つであり,社会的な問題を表現・整理できる技術になりうるが,未だ情報の専門領域にある技術であり,その技術を広めるには,教育人材や支援が不足している.本研究の成果は,状態遷移モデリングにおける基礎的な学習方法,これに基づく学習者の状態や答案の機械的な確認,その結果による教育支援に関する提案や知見である.これらは,学術的に例を見ず,また,将来的に教育コストを抑制する上で社会的な意義もあると期待される.

URL: 

Published: 2024-01-30  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi