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タイトル: | EXAIT: Educational eXplainable Artificial Intelligent Tools for personalized learning |
著者: | Ogata, Hiroaki Flanagan, Brendan Takami, Kyosuke Dai, Yiling Nakamoto, Ryosuke Takii, Kensuke |
著者名の別形: | 緒方, 広明 戴, 憶菱 中本, 陵介 滝井, 健介 |
キーワード: | Symbiotic learning systems Explainable AI Self-explanation Recommendation |
発行日: | 1-Jan-2024 |
出版者: | Asia-Pacific Society for Computers in Education |
誌名: | Research and Practice in Technology Enhanced Learning |
巻: | 19 |
論文番号: | 019 |
抄録: | As artificial intelligence systems increasingly make high-stakes recommendations and decisions automatically in many facets of our lives, the use of explainable artificial intelligence to inform stakeholders about the reasons behind such systems has been gaining much attention in a wide range of fields, including education. Also, in the field of education there has been a long history of research into self-explanation, where students explain the process of their answers. This has been recognized as a beneficial intervention to promote metacognitive skills, however, there is also unexplored potential to gain insight into the problems that learners experience due to inadequate prerequisite knowledge and skills that are required, or in the process of their application to the task at hand. While this aspect of self-explanation has been of interest to teachers, there is little research into the use of such information to inform educational AI systems. In this paper, we propose a system in which both students and the AI system explain to each other their reasons behind decisions that were made, such as: self-explanation of student cognition during the answering process, and explanation of recommendations based on internal mechanizes and other abstract representations of model algorithms. |
著作権等: | © The Author(s). 2023 This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. |
URI: | http://hdl.handle.net/2433/286392 |
DOI(出版社版): | 10.58459/rptel.2024.19019 |
出現コレクション: | 学術雑誌掲載論文等 |
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