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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/81118


    Title: 應用集群分析探究學習模式對學習成效之影響;Applying Cluster Analytics to Explore the Effect of Learning Pattern on Learning Performance
    Authors: 韓豫;Yu, Han
    Contributors: 資訊工程學系在職專班
    Keywords: 學習操作行為;滯後序列分析;叢集式分群分析;階層式分群分析;開放式教育平台
    Date: 2019-07-13
    Issue Date: 2019-09-03 15:35:10 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 由於資訊和通信技術的快速發展,行動裝置設備變得非常普遍,因此也產生了許多網路上的學習課程,這意味者獲取知識是隨手可得的。例如:國立中央大學的系統Open edX,是為了提供學生能夠即時且不因地區限制,隨時隨地的學習或做課程的複習、討論等,使學生可以透過開放式的教學平台有效提升學習成效。從教師的觀點而言,可以將學生的學習過程實質的歸納或統計成為數據,然後對此學生的學習資訊進行更有效率的分析。
    在本研究中,我們設計了一個基於Lag-sequential Analysis、K-means Clustering和Hierarchical Agglomerative Clustering的分析程序。我們的目標是透過使用Open edX系統紀錄中選定的特定班級學生操作紀錄,作為主要的分析樣本。
    應用所設計的分析程序對於萃取高學習成效和低學習成效之間的學習差異非常有效,因此教師可利用此方法協助低學習成效的學生在學習過程中的早期階段避免學習遇到的困難。
    ;Owing to the rapid development of Information and Communication Technology, mobile devices became extremely popular, and therefore, it is convenient to take a e-learning course. For example, in National Central University, the system “Open edX” is provided for students for ubiquitous learning. From a teacher’s viewpoint, he/she can digitize the learner behavior and then make analytics. In this thesis, we design a procedure of analytics based on Lag-sequential Analysis, K-means Clustering, and Hierarchical Agglomerative Clustering. We aim at clustering students who were attending courses by using Open edX. In particular, The procedure of analytics is useful for discovering the distinction between low and high performance. As a result, teachers can help the low-performance students to overcome barriers in an early stage.
    Appears in Collections:[資訊工程學系碩士在職專班 ] 博碩士論文

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