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Computational Study of Learning Strategies for Un-learning and Re-learning "How to Learn in the World"

Research Project

Project/Area Number 19K12064
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 61020:Human interface and interaction-related
Research InstitutionKyushu University

Principal Investigator

Okada Masaya  九州大学, 共創学部, 准教授 (10418519)

Co-Investigator(Kenkyū-buntansha) 多田 昌裕  近畿大学, 理工学部, 准教授 (40418520)
Project Period (FY) 2019-04-01 – 2022-03-31
Project Status Completed (Fiscal Year 2021)
Budget Amount *help
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2021: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2020: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Keywordsラーニングアナリティクス / 行動情報学 / 実世界学習 / 学習方略 / 計算論 / 状況論的知能
Outline of Research at the Start

実世界に根ざした知識を得るためには,机上での学びにとどまらず,実世界の中で行動を通して学ぶ実世界学習が重要である.このとき,学習者が,自らの学習活動を省みて「学び方」を適切に自己調整できれば,知的生産性を高める行動をとれる.したがって,本研究では,このような「学び方」の内省を促すために,「実世界における学び方」を学習棄却・再学習させるための計算論的学習方略研究を実施する.

Outline of Final Research Achievements

As an alternative of desktop learning, real-world learning by behaving in the world is important to acquire knowledge derived from the real world. If a learner can properly self-regulate "how to learn" by reflecting on his/her own learning activities, he/she can take actions to increase intellectual productivity. We conducted a computational study of learning strategies, as a basis to encourage a learner to reflect on, un-learn, and re-learn his/her way of real-world learning. Our computation models can be used to estimate qualitative characteristics of learning by measuring external situation of a learner. We expect that our basic findings are used for developing next-generation learning support with artificial intelligence.

Academic Significance and Societal Importance of the Research Achievements

本研究は,学習科学,行動情報学,身体性認知科学の統合によって,実世界における状況論的知能のメカニズムについて基礎的研究成果を得た.本研究は,人工知能による次世代学習支援などの応用を行う際,その基礎的知見として活用が期待される.具体的には,行動の計測・理解からの学習効果の予測技術の発展に寄与し,実世界における学習者に効果的な行動を取るよう促す学習支援技術への応用が期待される.

Report

(4 results)
  • 2021 Annual Research Report   Final Research Report ( PDF )
  • 2020 Research-status Report
  • 2019 Research-status Report
  • Research Products

    (7 results)

All 2022 2021 2020 Other

All Journal Article (3 results) (of which Peer Reviewed: 3 results,  Open Access: 3 results) Presentation (2 results) (of which Int'l Joint Research: 1 results) Remarks (2 results)

  • [Journal Article] Behavior Semantics for Computational Understanding of Real-world Learning2021

    • Author(s)
      永田 鴻流、渡邉 七江、多田 昌裕、岡田 昌也
    • Journal Title

      情報処理学会論文誌

      Volume: 62 Issue: 12 Pages: 2090-2107

    • DOI

      10.20729/00214253

    • NAID

      170000186150

    • Year and Date
      2021-12-15
    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Multimodal Analytics to Understand Self-Regulation Process of Cognitive and Behavioral Strategies in Real-World Learning2020

    • Author(s)
      Masaya Okada, Yasutaka Kuroki, and Masahiro Tada
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: E103.D Issue: 5 Pages: 1039-1054

    • DOI

      10.1587/transinf.2018EDP7364

    • NAID

      130007839108

    • ISSN
      0916-8532, 1745-1361
    • Year and Date
      2020-05-01
    • Related Report
      2020 Research-status Report 2019 Research-status Report
    • Peer Reviewed / Open Access
  • [Journal Article] Estimating Spatiotemporal Features of Collaborative Observation to Activate Scientific Inquiry in the World2020

    • Author(s)
      岡田 昌也,黒木 康能,永田 鴻流,多田 昌裕
    • Journal Title

      情報処理学会論文誌

      Volume: 61 Issue: 4 Pages: 1006-1022

    • DOI

      10.20729/00204252

    • NAID

      170000181844

    • Year and Date
      2020-04-15
    • Related Report
      2020 Research-status Report 2019 Research-status Report
    • Peer Reviewed / Open Access
  • [Presentation] 経験学習における信念システムの計算論的理解2022

    • Author(s)
      渡邉 七江,岡田 昌也
    • Organizer
      2022年度人工知能学会全国大会(第36回)
    • Related Report
      2021 Annual Research Report
  • [Presentation] Analytics of Behavior Semantics for Understanding Constraint Conditions Hidden in Formative Process of Real-world Learning2020

    • Author(s)
      Koryu Nagata, Masahiro Tada, and Masaya Okada
    • Organizer
      ACE2020
    • Related Report
      2020 Research-status Report
    • Int'l Joint Research
  • [Remarks] 九州大学 大学院システム情報科学府/共創学部 岡田研究室

    • URL

      http://okadalab.kyushu-u.ac.jp/

    • Related Report
      2021 Annual Research Report 2020 Research-status Report
  • [Remarks] 九州大学 共創学部 岡田研究室

    • URL

      http://okadalab.kyushu-u.ac.jp/

    • Related Report
      2019 Research-status Report

URL: 

Published: 2019-04-18   Modified: 2023-01-30  

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