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題名 應用資料探勘於創造力學習系統
其他題名 A Study of Applying Data Mining Techniques to Creativity Learning System
作者 林俊甫
葉玉珠
貢獻者 師培中心
關鍵詞 決策樹; ; 個人化學習; ; 創造力訓練; ;
Decision tree;Personalize learning;Creativity training
日期 2012-12
上傳時間 31-Jan-2019 16:26:14 (UTC+8)
摘要 發展個人化與適性化數位學習系統,為近幾年數位學習發展的重要方向,主要是由於固定的學習風格、情境,學習路徑順序,並無法針對個人差異達到有效的學習,因此,我們發展一個代理人系統架構的創造力學習系統,並結合XML 技術建構智慧型創造力學習系統,系統可動態調整如執行時間,學習風格(語文、圖形),學習情境(高壓力、低壓力),遊戲路徑順序,建立符合目標的代理人並執行創造力學習系統所需執行的情境與任務。本研究使用決策樹演算法,收集42 位政治大學學生作為訓練樣本,由訓練後所建立決策樹模型可發現,使用決策樹演算法推薦訓練路徑,可有90%以上機率,使得學生創造力遊戲得分高於平均水準。
In recently year, the digital learning is toward to personalize and adapt for learning system. The static leaning style, scenarios and path may not be adaptive for each learner. The aim of personalize learning system is to enhance learning efficiency of individual differences. Therefore, we proposed a rule-based personalize learning system, the XML is employed in system to develop
intelligent creativity learning system. Learning style such as graphical or contextual expression, execution time, teaching procedure and learning scenarios (ex. high or low pressure). These learning materials could be dynamically controlled by system to adapt individual requirement. The agent system not only personalizes learning scenario, but also assistant learner to achieve the creativity
training task. The decision tree algorithm is one of data mining method which applied in system to personalize learning path; 42 university students were included in this study to examine the effectiveness of the system. Experiment result show that learner have 90% probability get high creativity score than average.
關聯 2012 Third International Conference on Information,Communication and Education Application(ICEA 2012) , 会议时间:2012-12-30 , 会议地点:Singapore
資料類型 conference
dc.contributor 師培中心
dc.creator (作者) 林俊甫zh-tw
dc.creator (作者) 葉玉珠zh-tw
dc.date (日期) 2012-12
dc.date.accessioned 31-Jan-2019 16:26:14 (UTC+8)-
dc.date.available 31-Jan-2019 16:26:14 (UTC+8)-
dc.date.issued (上傳時間) 31-Jan-2019 16:26:14 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/122242-
dc.description.abstract (摘要) 發展個人化與適性化數位學習系統,為近幾年數位學習發展的重要方向,主要是由於固定的學習風格、情境,學習路徑順序,並無法針對個人差異達到有效的學習,因此,我們發展一個代理人系統架構的創造力學習系統,並結合XML 技術建構智慧型創造力學習系統,系統可動態調整如執行時間,學習風格(語文、圖形),學習情境(高壓力、低壓力),遊戲路徑順序,建立符合目標的代理人並執行創造力學習系統所需執行的情境與任務。本研究使用決策樹演算法,收集42 位政治大學學生作為訓練樣本,由訓練後所建立決策樹模型可發現,使用決策樹演算法推薦訓練路徑,可有90%以上機率,使得學生創造力遊戲得分高於平均水準。zh_TW
dc.description.abstract (摘要) In recently year, the digital learning is toward to personalize and adapt for learning system. The static leaning style, scenarios and path may not be adaptive for each learner. The aim of personalize learning system is to enhance learning efficiency of individual differences. Therefore, we proposed a rule-based personalize learning system, the XML is employed in system to develop
intelligent creativity learning system. Learning style such as graphical or contextual expression, execution time, teaching procedure and learning scenarios (ex. high or low pressure). These learning materials could be dynamically controlled by system to adapt individual requirement. The agent system not only personalizes learning scenario, but also assistant learner to achieve the creativity
training task. The decision tree algorithm is one of data mining method which applied in system to personalize learning path; 42 university students were included in this study to examine the effectiveness of the system. Experiment result show that learner have 90% probability get high creativity score than average.
en_US
dc.format.extent 791248 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) 2012 Third International Conference on Information,Communication and Education Application(ICEA 2012) , 会议时间:2012-12-30 , 会议地点:Singaporezh_TW
dc.subject (關鍵詞) 決策樹; ; 個人化學習; ; 創造力訓練; ;zh_TW
dc.subject (關鍵詞) Decision tree;Personalize learning;Creativity trainingen_US
dc.title (題名) 應用資料探勘於創造力學習系統zh-TW
dc.title.alternative (其他題名) A Study of Applying Data Mining Techniques to Creativity Learning Systemen-US
dc.type (資料類型) conference