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2022 年度 実施状況報告書

Learning Support by Novel Modality Process Analysis of Educational Big Data

研究課題

研究課題/領域番号 21K19824
研究機関京都大学

研究代表者

Flanagan Brendan  京都大学, 国際高等教育院, 特定准教授 (00807612)

研究分担者 久富 望  京都大学, 教育学研究科, 助教 (70825992)
研究期間 (年度) 2021-07-09 – 2024-03-31
キーワードModality analysis / Learning process / Learning Analytics / Recommendation / Knowledge Map
研究実績の概要

Based on the analysis of pen strokes conducted in the first year of this project, we focused on trying to identify possible problems that students were facing by having them self-explain the knowledge and skills using in the process of answering quiz questions. Students reviewed their pen stroke answers and self-explained at appropriate intervals, which generated annotated time series data of the answering process. This data was then analyzed to using NLP methods to generate sample self-explanations that contained the required knowledge components to solve the quiz item. The results were disseminated as an international conference paper. A self-explanation feedback and recommender system has been developed and implemented with results currently under analysis.

現在までの達成度 (区分)
現在までの達成度 (区分)

2: おおむね順調に進展している

理由

The project is proceeding as planned due to reduced restricts from COVID. However, some areas of investigation into self-explanation that were not previously considered have been identified, and more in-depth research will be conducted as a result.

今後の研究の推進方策

Results of analysis from the first (pen stroke) and second (self-explanation) year are being combined to provide overall feedback interface to students, with the possibility of recommending learning tasks to overcome problems encountered in the answering process. More in-depth investigation into automatically analyzing self-explanations using state-of-the-art NLP methods should enable fine grained feedback and possible hints into problems that have been encountered. We are also currently preparing to publish the results of this project in international journals to disseminate the findings to the boarder research community.

次年度使用額が生じた理由

Due to the results of the project thus far, further investigation is needed into the analysis of self-explanations than was initially anticipated. More in-depth examination is planned to be carried out in the next fiscal year as a result.

  • 研究成果

    (11件)

すべて 2023 2022

すべて 雑誌論文 (6件) (うち国際共著 2件、 査読あり 6件) 学会発表 (5件) (うち国際学会 5件)

  • [雑誌論文] Fusion of Explainable Recommender System and Open Learner Model2023

    • 著者名/発表者名
      Dai, Y., Flanagan, B., Takami, K., & Ogata, H.
    • 雑誌名

      Proceedings of the 12th International Conference on Learning Analytics and Knowledge

      ページ: NA

    • 査読あり
  • [雑誌論文] An Automatic Self-Explanation Sample Answer Generation with knowledge components for Identifying Students’ Stuck Point in a Maths Quiz2022

    • 著者名/発表者名
      Nakamoto, R., Flanagan, B., Dai, Y., Takami, K., & Ogata, H.
    • 雑誌名

      Artificial Intelligence in Education (AIED)

      ページ: 254-258

    • 査読あり
  • [雑誌論文] A Learning Path Recommendation System for English Grammar Quiz Using Knowledge Map2022

    • 著者名/発表者名
      Tanimura, N., Takii, K., Flanagan, B., & Ogata, H.
    • 雑誌名

      30th International Conference on Computers in Education Conference Proceedings

      ページ: 581-583

    • 査読あり
  • [雑誌論文] Investigation on Practical Effects of the Explanation in a K-12 Math Recommender System2022

    • 著者名/発表者名
      Dai, Y., Takami, K., Flanagan, B., & Ogata, H.
    • 雑誌名

      30th International Conference on Computers in Education Conference Proceedings

      ページ: 7-12

    • 査読あり
  • [雑誌論文] Explainable English Material Recommendation Using an Information Retrieval Technique for EFL Learning2022

    • 著者名/発表者名
      Takii, K., Flanagan, B., Li, H., Yang, Y., & Ogata, H.
    • 雑誌名

      30th International Conference on Computers in Education Conference Proceedings

      ページ: 561-570

    • 査読あり / 国際共著
  • [雑誌論文] How Students’ Self-Assessment Behavior Affects Their Online Learning Performance2022

    • 著者名/発表者名
      Yang, A.C., Chen, I.Y., Flanagan, B., & Ogata, H.
    • 雑誌名

      Computers and Education: Artificial Intelligence

      巻: 3 ページ: 100058

    • DOI

      10.1016/j.caeai.2022.100058

    • 査読あり / 国際共著
  • [学会発表] Fusion of Explainable Recommender System and Open Learner Model2023

    • 著者名/発表者名
      Flanagan, B.
    • 学会等名
      Proceedings of the 12th International Conference on Learning Analytics and Knowledge
    • 国際学会
  • [学会発表] An Automatic Self-Explanation Sample Answer Generation with knowledge components for Identifying Students’ Stuck Point in a Maths Quiz2022

    • 著者名/発表者名
      Nakamoto, R
    • 学会等名
      Artificial Intelligence in Education (AIED)
    • 国際学会
  • [学会発表] A Learning Path Recommendation System for English Grammar Quiz Using Knowledge Map2022

    • 著者名/発表者名
      Tanimura, N.
    • 学会等名
      30th International Conference on Computers in Education Conference Proceedings
    • 国際学会
  • [学会発表] Investigation on Practical Effects of the Explanation in a K-12 Math Recommender System2022

    • 著者名/発表者名
      Dai, Y.
    • 学会等名
      30th International Conference on Computers in Education Conference Proceedings
    • 国際学会
  • [学会発表] Explainable English Material Recommendation Using an Information Retrieval Technique for EFL Learning2022

    • 著者名/発表者名
      Takii, K.
    • 学会等名
      30th International Conference on Computers in Education Conference Proceedings
    • 国際学会

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公開日: 2023-12-25  

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