{"_buckets": {"deposit": "e94bf12e-e6a2-436f-b46c-99f092747aa8"}, "_deposit": {"created_by": 16, "id": "505", "owners": [16], "pid": {"revision_id": 0, "type": "depid", "value": "505"}, "status": "published"}, "_oai": {"id": "oai:seisen-jc.repo.nii.ac.jp:00000505", "sets": ["104"]}, "author_link": ["651", "650"], "item_10002_biblio_info_7": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2019-03-15", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "37", "bibliographicPageEnd": "10", "bibliographicPageStart": "1", "bibliographic_titles": [{"bibliographic_title": "清泉女学院短期大学研究紀要"}, {"bibliographic_title": "Bulletin of Seisen Jogakuin College", "bibliographic_titleLang": "en"}]}]}, "item_10002_description_5": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "本研究では、ラーニング・アナリティクス、性格特性、教学IRデータを活用し、１年春学期末のGPAと学校生活満足度を予測するモデルを開発した。モデル開発手法として、k-means法によるクラスター分析、線形重回帰分析及びニューラルネットワークを採用した。予測精度を計算した結果、線形重回帰モデルの最大決定係数は、（GPA，学校生活満足度）=（0.279，0.305）であり、ニューラルネットワークモデルの最大決定係数は、（GPA，学校生活満足度）=（0.831，0.479）となった。", "subitem_description_type": "Abstract"}]}, "item_10002_full_name_3": {"attribute_name": "著者別名", "attribute_value_mlt": [{"nameIdentifiers": [{"nameIdentifier": "651", "nameIdentifierScheme": "WEKO"}], "names": [{"name": "Katase, Takuya"}]}]}, "item_10002_publisher_8": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "清泉女学院短期大学"}]}, "item_10002_source_id_11": {"attribute_name": "書誌レコードID", "attribute_value_mlt": [{"subitem_source_identifier": "AN00293551", "subitem_source_identifier_type": "NCID"}]}, "item_10002_source_id_9": {"attribute_name": "ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "0289-6761", "subitem_source_identifier_type": "ISSN"}]}, "item_10002_version_type_20": {"attribute_name": "著者版フラグ", "attribute_value_mlt": [{"subitem_version_resource": "http://purl.org/coar/version/c_970fb48d4fbd8a85", "subitem_version_type": "VoR"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "片瀬, 拓弥"}], "nameIdentifiers": [{"nameIdentifier": "650", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "ファイル情報", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2019-05-23"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "01_katase.pdf", "filesize": [{"value": "6.7 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_11", "mimetype": "application/pdf", "size": 6700000.0, "url": {"label": "seisen-kiyo_37-1", "url": "https://seisen-jc.repo.nii.ac.jp/record/505/files/01_katase.pdf"}, "version_id": "634e4172-fb6c-45ed-ad07-7b7d5234bc39"}]}, "item_keyword": {"attribute_name": "キーワード", "attribute_value_mlt": [{"subitem_subject": "ラーニング・アナリティクス", "subitem_subject_scheme": "Other"}, {"subitem_subject_scheme": "Other"}, {"subitem_subject": "教学IR", "subitem_subject_scheme": "Other"}, {"subitem_subject_scheme": "Other"}, {"subitem_subject": "GPA", "subitem_subject_scheme": "Other"}, {"subitem_subject_scheme": "Other"}, {"subitem_subject": "学校生活満足度", "subitem_subject_scheme": "Other"}, {"subitem_subject_scheme": "Other"}, {"subitem_subject": "予測モデル", "subitem_subject_scheme": "Other"}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "jpn"}]}, "item_resource_type": {"attribute_name": "資源タイプ", "attribute_value_mlt": [{"resourcetype": "departmental bulletin paper", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_title": "ラーニング・アナリティクス、性格特性、教学IRデータを活用したGPAと学校生活満足度の予測モデルの開発", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "ラーニング・アナリティクス、性格特性、教学IRデータを活用したGPAと学校生活満足度の予測モデルの開発"}, {"subitem_title": "Development of prediction model of GPA and school life satisfaction by Learning Analytics, personality traits and data of Institutional Research for education", "subitem_title_language": "en"}]}, "item_type_id": "10002", "owner": "16", "path": ["104"], "permalink_uri": "https://seisen-jc.repo.nii.ac.jp/records/505", "pubdate": {"attribute_name": "公開日", "attribute_value": "2019-05-23"}, "publish_date": "2019-05-23", "publish_status": "0", "recid": "505", "relation": {}, "relation_version_is_last": true, "title": ["ラーニング・アナリティクス、性格特性、教学IRデータを活用したGPAと学校生活満足度の予測モデルの開発"], "weko_shared_id": -1}