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    請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/13142


    題名: 應用文字探勘於數位學習環境的形成性評量;A Text Mining Approach for Formative Assessment in e-Learning Environment
    作者: 許榮隆;Jung-Lung Hsu
    貢獻者: 資訊管理研究所
    關鍵詞: 文字探勘、形成性評量、數位學習、集體認知;Text mining;formative assessment;e-learning;collective cognition
    日期: 2008-07-09
    上傳時間: 2009-09-22 15:24:40 (UTC+8)
    出版者: 國立中央大學圖書館
    摘要: 近年來,有許多的教學者對於e-learning的方式深感興趣,並嘗試將其導入實務的教學情境中。此外,也有許多的研究學者體認到e-learning的蓬勃發展,而致力於相關研究問題的探討。本研究藉由歸納出學習績效的評估類型和學習績效的評估單位兩個構面,重新構思學習績效。本文的重點在於區分出個人認知的形成性評量和集體認知的形成性評量。此一劃分方式之所以重要的原因在於,本文認為集體認知的形成性評量不應該被簡化為個人認知的形成性評量的總和。具體而言,個人認知的形成性評量和集體認知的形成性評量,具有彼此交互糾結的本質,因此實施形成性評量時不宜偏廢任一環節。有鑑於此,本研究認為針對小組進行形成性評量時,除了針對小組成員的認知結構和認知過程進行分析,更應當注意集體認知的形成性分析。此外,實施形成性評量的主要瓶頸在於其勞力密集且耗時的本質,因此本研究嘗試借助於一項新的資訊技術:文字探勘,以便提出可行的方法並解除形成性評量所加諸於教學者身上的負擔。本研究資料的來源為修習人力資源管理課程的56位學生所進行的小組討論。在個人認知的形成性評量方面,學習者的認知層次將根據Bloom的教育目標分類分為六類:知識、理解、應用、分析、綜合和評鑑。而在集體認知的形成性評量方面,本研究將結合潛在語意索引,提出集體認知環以便描繪受測小組的集體認知層次。總結來說,本研究不僅提出集體認知的形成性評量,同時也嘗試提出一個合理的方法,幫助教學者在e-learning的環境下,進行個人認知的形成性評量和集體認知的形成性評量。 Recently, not only instructors and educators are interested in the advent of e-learning, but a number of researchers are eager to shed light on relevant issues on this field. This study conceptualizes learning performance along two dimensions: Type of assessment and unit of assessment. Accordingly, distinction of formative assessment between individual cognition and collective cognition is introduced. This is an important distinction because the attempt regarding formative assessment of collective cognition as the sum of that of individual cognitions may be misguided. More specifically, the intertwined nature of formative assessment of collective cognition and individual cognition suggests researchers draw attention to analyzing cognitive structures and cognitive processes at the individual level as well as at collective level. Furthermore, since the major bottleneck of putting formative assessment into practice lies in the nature of labor-intensive and time-consuming, this study conceives one feasible way: text mining, to relieve the burden imposed on instructors. Data will be gathered from 56 participants enrolling in a “Human Resource Management” course. In the formative assessment of individual cognition, learners’ cognition will be classified into six level, namely knowledge, comprehension, application, analysis, synthesis and evaluation, based on Bloom’s taxonomy of educational objectives. With respect to formative assessment of collective cognition, this study will make use of latent semantic indexing to outline a collective cognition circle. To sum up, the approach introduced in this study serves a well solution to consider formative assessment of both individual cognition and collective cognition.
    顯示於類別:[資訊管理研究所] 博碩士論文

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