{"created":"2025-01-19T01:31:09.354770+00:00","updated":"2025-01-19T10:54:09.579276+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00231033","sets":["6504:11436:11444"]},"path":["11444"],"owner":"44499","recid":"231033","title":["Knowledge TracingにDeep Learningと忘却モデルを組み合わせた学生モデリング手法の提案"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"5868f55b-198f-4bef-ac14-acd86e7c319d"},"_deposit":{"id":"231033","pid":{"type":"depid","value":"231033","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Knowledge TracingにDeep Learningと忘却モデルを組み合わせた学生モデリング手法の提案","author_link":["623066"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Knowledge TracingにDeep Learningと忘却モデルを組み合わせた学生モデリング手法の提案"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"コンピュータと人間社会","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2023-02-16","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"木更津高専"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/231033/files/IPSJ-Z85-5ZM-04.pdf","label":"IPSJ-Z85-5ZM-04.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-5ZM-04.pdf","filesize":[{"value":"297.2 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"e750c99e-47a8-4d1e-af1c-3ef9b8e64927","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"長谷川, 駿一"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"教育現場において，学習者のスキル状態に見合った難易度の設問を推薦することができれば，効果的な教育が可能となる．その方法として，学習履歴から学習者の潜在能力を推定して学習者の未知の設問への正答予測をするKnowledge Tracing（KT）がある．近年普及している，KTにディープラーニングを組み込むモデルは，予測精度は高いが説明可能性に乏しいため十分な性能が発揮できていない．それに対して，IRTは説明可能性が高く，このIRTに忘却を加えたモデルが存在する．本研究では，ディープラーニングを用いたKTに対して忘却モデルを組み込み，精度の向上と説明可能性の両立を目標としたモデルを提案する．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"1004","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"1003","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":231033,"links":{}}