{"created":"2025-01-19T01:12:06.880623+00:00","updated":"2025-01-19T17:59:05.020179+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00210916","sets":["6164:6165:6640:10580"]},"path":["10580"],"owner":"44499","recid":"210916","title":["学習効率向上に向けた脳波に基づく VR-HMD ユーザの嗜好性推定"],"pubdate":{"attribute_name":"公開日","attribute_value":"2020-06-17"},"_buckets":{"deposit":"0901b96a-fda3-43f2-8f4c-500e4f7d541a"},"_deposit":{"id":"210916","pid":{"type":"depid","value":"210916","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"学習効率向上に向けた脳波に基づく VR-HMD ユーザの嗜好性推定","author_link":["534878","534877"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"学習効率向上に向けた脳波に基づく VR-HMD ユーザの嗜好性推定"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ウェアラブルコンピューティング","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2020-06-17","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"福井大学大学院工学研究科知識社会基礎工学専攻情報工学コース"},{"subitem_text_value":"福井大学大学院工学研究科知識社会基礎工学専攻情報工学コース"}]},"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/210916/files/IPSJ-DICOMO2020203.pdf","label":"IPSJ-DICOMO2020203.pdf"},"date":[{"dateType":"Available","dateValue":"2022-06-17"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2020203.pdf","filesize":[{"value":"1.5 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"de1356b9-37e6-4eed-820c-e0a65fd957b7","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2020 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"今別府, 万大"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"長谷川, 達人"}],"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_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，アクティブ・ラーニングや反転学習という授業形態により，学習者の主体的な学習を促す取組みが見られる．しかし，これらの授業形態では学習者自身の授業への参加意欲や，教育コンテンツの良し悪しが学習効率に影響する．授業形態以外を工夫する観点として，e-Learnig 環境での自主学習環境において学習者自身のやる気を向上させるシステムを実現することで，学習効率向上の図る方法がある．このことから，学習者の好みに応じた教示者画像の生成，および生成画像をVR 空間上で教示者アバタとして投影，授業の教示者の置き換えを行うシステムの開発を目指す．そのための第一段階として，本研究では，学習者の嗜好性を脳波から推定するために実現可能性の基礎検証を行う．実験では表示される顔画像を見た際の脳波の計測を行う．その後，貪欲法を用いて特徴量選択し，機械学習で「好き」「好きでない」の2値分類で嗜好性推定を2種類の方法で行った結果，画像を相対的に比較するような形で嗜好性推定を行った方が平均推定精度の向上が見られた．また，特徴量について見てみると嗜好性の推定においてβ波やβ/αが選択される傾向が多いことが分かった．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"1421","bibliographic_titles":[{"bibliographic_title":"マルチメディア，分散協調とモバイルシンポジウム2222論文集"}],"bibliographicPageStart":"1416","bibliographicIssueDates":{"bibliographicIssueDate":"2020-06-17","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2020"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":210916,"links":{}}